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Examining how pharyngeal taste input and internal physiological context influence feeding decisions in… LeDue, Emily Elizabeth 2016

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		EXAMINING	HOW	PHARYNGEAL	TASTE	INPUT	AND	INTERNAL	PHYSIOLOGICAL	CONTEXT	INFLUENCE	FEEDING	DECISIONS	IN	DROSOPHILA		by	Emily	Elizabeth	LeDue		B.Sc.,	Dalhousie	University,	2010	M.Sc.,	Dalhousie	University,	2012		A	THESIS	SUBMITTED	IN	PARTIAL	FULFILLMENT	OF	THE	REQUIREMENTS	FOR	THE	DEGREE	OF			DOCTOR	OF	PHILOSOPHY		in	THE	FACULTY	OF	GRADUATE	AND	POSTDOCTORAL	STUDIES	(Zoology)		THE	UNIVERSITY	OF	BRITISH	COLUMBIA	(Vancouver)			December	2016			©	Emily	Elizabeth	LeDue,	2016		 ii	ABSTRACT	To	survive	animals	must	find	and	consume	nutritive	foods.	The	chemical	composition	of	food	sources	is	evaluated	using	gustation.	Because	of	its	importance	to	survival,	feeding	behaviors	are	tightly	regulated.	Changes	in	feeding	occur	in	response	to	the	external	environment	and	the	animal’s	internal	physiological	state.	Expendable	behaviours	can	be	suppressed	during	starvation	to	prioritize	feeding.	This	thesis	examines	the	role	of	two	factors	in	feeding	decisions:	the	location	of	taste	input	and	starvation.		Pharyngeal	sense	organs	in	Drosophila	are	the	last	evaluation	point	before	food	is	ingested.	It	was	previously	unclear	whether	they	served	a	unique	function	in	feeding.	To	investigate	this,	we	focused	on	appetitive	gustatory	pharyngeal	neurons	and	showed	they	express	nine	gustatory	receptors	which	respond	to	sweet	compounds.	Mutants	lacking	peripheral	taste	have	functional	pharyngeal	sense	organs.	In	the	absence	of	peripheral	taste	cues,	the	pharyngeal	sense	organs	can	drive	the	choice	and	ingestion	of	sweet	compounds	by	sustaining	consumption.	Knocking	down	pharyngeal	neurons	in	these	mutants	allowed	us	to	examine	a	sweet-blind	fly	in	a	short	term	feeding	assay.	Putatively	sweet-blind	flies	do	not	show	a	preference	for	sweet	compounds	in	a	short-term	feeding	assay,	suggesting	that	nutrient	sensing	is	not	operating	in	this	context.		Starved	flies	have	an	increased	tolerance	for	bitter	foods,	which	is	mediated	by	sensitization	and	desensitization	of	sweet	and	bitter	taste,	respectively.	Mechanisms	that	cause	the	sensitization	of	sweet	taste	have	been	studied,	but	those	that	underlie		 iii	desensitization	of	bitter	taste	were	unknown.	We	identify	a	pair	of	octopaminergic/tyraminergic	modulatory	neurons	called	the	ventrolateral	cluster	of	octopaminergic	neurons	(OA-VLs).	Because	OA-VLs	exist	in	close	physical	proximity	to	bitter	neuron	axon	terminals	but	are	not	postsynaptic	to	them,	we	examined	their	function	as	modulators	of	bitter	neuron	output.	Tonic	firing	rate	of	OA-VLs	decreases	as	a	function	of	starvation.	Octopamine	and	tyramine	are	sufficient	to	potentiate	bitter	neuron	response	in	starved	flies,	suggesting	that	reduction	in	OA-VL	activity	during	starvation	depotentiates	bitter	neuron	output.	Silencing	OA-VLs	causes	a	reduction	in	bitter	neuron	output	and	increased	acceptance	of	bitter	compounds.	OA-VLs	may	act	directly	on	bitter	sensory	neurons	through	the	Oct-Tyr	receptor.																		 iv	PREFACE	Chapter	2	Experiments	discussed	in	this	chapter	were	part	of	a	collaborative	effort	with	Dr.	Anupama	Dahanukar’s	group	at	University	of	California	at	Riverside	in	Riverside,	California.	This	work	produced	a	manuscript	published	as	LeDue	EE,	Chen	Y-C,	Jung	AY,	Dahanukar	A,	Gordon	MD	(2015)	Pharyngeal	sense	organs	drive	robust	sugar	consumption	in	Drosophila.	Nature	Communications	doi:	10.1038/ncomms7667.	For	this	publication,	I	performed	proboscis	extension	experiments	and	the	majority	of	the	binary	feeding	assays.	Aera	Jung	performed	the	initial	binary	feeding	assays	during	the	conception	of	the	project.	Michael	Gordon	and	I	performed	experiments	to	examine	the	Gr-Gal4	expression	of	poxn	mutants	and	the	GCaMP	imaging	experiments.	Yu-Chieh	Chen	and	I	performed	temporal	consumption	assays.	Yu-Chieh	Chen	performed	the	wildtype	Gr-Gal4	expression	analysis.	Yu-Chieh	Chen,	Aera	Jung,	Anupama	Dahanukar,	Michael	Gordon	and	I	analyzed	data.	The	projected	was	conceived	and	supervised	by	Michael	Gordon	and	Anupama	Dahanukar.	Michael	Gordon	wrote	the	original	manuscript	with	input	from	Yu-Chieh	Chen,	Anupama	Dahanukar,	and	I.		Chapter	3	Work	published	in	this	chapter	produced	a	manuscript	published	as	LeDue	EE,	Mann	K,	Koch	E,	Chu	B,	Dakin	R,	Gordon	MD	(2016)	Starvation-induced	depotentiation	of	bitter	taste	in	Drosophila.	Current	Biology.	This	work	was	carried	out	exclusively	at	the	Life	Sciences	Institute	at	the	University	of	British	Columbia.	This	project	was	conceived	and	supervised	by	Michael	Gordon.	The	anatomical		 v	GRASP	screen	that	initially	identified	our	neurons	of	interest	was	carried	out	by	Ellen	Koch.	I	performed	the	anatomical	analysis	and	immunohistochemistry	screens.	Cell	attached	recordings	and	their	analyses	were	performed	by	Kevin	Mann	and	I.	All	calcium	imaging	experiments	in	the	body	of	the	manuscript	were	done	with	sparse	Gal4	lines	not	identified	in	the	original	screen	and	were	performed	by	myself.	The	original	silencing	and	calcium	imaging	of	Gal4	lines,	that	included	more	general	labeling,	were	carried	out	by	Bonnie	Chu	and	I	and	were	ultimately	included	in	the	supplemental	data	of	the	manuscript.	I	performed	all	behavioural	assays.	Statistical	analysis	of	binary	behavioural	data	was	done	by	Roslyn	Dakin.	The	original	manuscript	was	written	by	Michael	Gordon	and	I,	while	review	and	editing	was	done	by	Michael	Gordon	and	I,	with	input	from	Bonnie	Chu	and	Roslyn	Dakin.																		 vi	TABLE	OF	CONTENTS		ABSTRACT	..................................................................................................................................	ii	PREFACE	....................................................................................................................................	iv	TABLE	OF	CONTENTS	............................................................................................................	vi	LIST	OF	FIGURES	..................................................................................................................	viii	LIST	OF	ABBREVIATIONS	....................................................................................................	xii	ACKNOWLEDGEMENTS	........................................................................................................	xv	CHAPTER	1		 	INTRODUCTION	.............................................................................................	1	1.1	Mammalian	Taste	......................................................................................................................	1	1.1.1	Appetitive	Taste	in	Mammals	.........................................................................................................	2	1.1.2	Aversive	Taste	in	Mammals	.............................................................................................................	4	1.1.3	Transduction	of	Mammalian	Taste	into	the	Cortex	..............................................................	5	1.2	The	Fly	Gustatory	System	........................................................................................................	6	1.3	Peripheral	Fly	Taste	..................................................................................................................	7	1.4	Fly	Taste	Circuits	......................................................................................................................	13	1.5	Feeding	Behaviour	in	Drosophila	.......................................................................................	17	1.6	Integration	of	Hunger	and	Satiety	Signals	in	Drosophila	...........................................	18	1.7	Fly	Neurogenetics	....................................................................................................................	21	1.7.1	The	Gal4/UAS	Binary	Expression	System	..............................................................................	22	1.7.2	Using	Gal4/UAS	to	Manipulate	Neuronal	Activity	..............................................................	23	1.7.3	Using	Gal4/UAS	to	Measure	Neuronal	Activity	Through	Calcium	Imaging	.............	24	1.8	Objective	of	the	Current	Experiments	..............................................................................	25	1.8.1	Chapter	2	..............................................................................................................................................	26	1.8.2	Chapter	3	..............................................................................................................................................	26	CHAPTER	2		 	THE	ROLE	OF	PHARYNGEAL	SENSE	ORGANS	IN	FEEDING	DECISIONS	IN	DROSOPHILA	MELANOGASTER	..............................................................	28	2.1	Introduction	..............................................................................................................................	28	2.2	Materials	And	Methods	..........................................................................................................	30	2.2.1	Fly	Stocks	..............................................................................................................................................	30	2.2.2	Immunohistochemistry	..................................................................................................................	30	2.2.3	Gr	Expression	Mapping	..................................................................................................................	31	2.2.4	GCaMP	Imaging	..................................................................................................................................	31	2.2.5	Behavioural	Assays	..........................................................................................................................	32	2.3	Results	.........................................................................................................................................	34		 vii	2.3.1	Pharyngeal	GRNs	Express	Sweet	Receptors	.........................................................................	34	2.3.2	Pharyngeal	GRNs	Detect	a	Variety	of	Sugars	........................................................................	35	2.3.3	poxn	Mutants	Retain	Functional	Pharyngeal	Sense	Organs	...........................................	40	2.3.3	poxn	Mutants	Prefer	Sweet	Compounds	.................................................................................	44	2.3.3	Pharyngeal	Sweet	GRNs	Sustain	Ingestion	............................................................................	52	2.4	Discussion	..................................................................................................................................	52	CHAPTER	3	 	STARVATION-INDUCED	DEPOTENTIATION	OF	BITTER	TASTE	IN	DROSOPHILA	………………………………………………………………………………………………….57	3.1	Introduction	..............................................................................................................................	57	3.2	Materials	And	Methods	..........................................................................................................	60	3.2.1	Fly	Stocks	..............................................................................................................................................	60	3.2.2	Immunohistochemistry	..................................................................................................................	60	3.2.3	Physiology	............................................................................................................................................	61	3.2.4	Behavioural	Assays	..........................................................................................................................	64	3.2.5	Statistical	Analyses	...........................................................................................................................	64	3.3	Results	.........................................................................................................................................	65	3.3.1	OA-VL	Neurons	are	in	Close	Proximity	to	Bitter	GRNs	.....................................................	65	3.3.2	OA-VL	Neurons	are	Regulated	by	Satiety	State	...................................................................	70	3.3.3	OA-VLs	Modulate	Bitter	GRN	Output	.......................................................................................	73	3.3.1	OA	and	TA	Act	Directly	on	Bitter	Neurons	.............................................................................	79	3.4	Discussion	..................................................................................................................................	81	3.4.1	Independent	and	Reciprocal	Regulation	of	Sweet	and	Bitter	Taste	...........................	81	3.4.2	OA/TA	Regulation	of	Gustation	and	Starvation-Dependent	Behaviours	.................	82	CHAPTER	4			 	DISCUSSION	.............................................................................................	84	4.1	Discussion	..................................................................................................................................	84	4.1.1	Implications	for	the	Field	of	Drosophila	Taste	.....................................................................	84	4.1.2	Caveats	and	Future	Directions	in	our	Current	Studies	.....................................................	88	4.1.3	Implications	for	Human	Health	..................................................................................................	93	References	..............................................................................................................................	95										 viii	LIST	OF	FIGURES	Figure	1.	Schematic	showing	location	of	taste	sensilla	in	the	adult	Drosophila,	and	structure	of	individual	sensilla.	Adult	flies	have	taste	sensilla	one	the	legs,	labellum	of	the	proboscis,	wing	margin	and	within	the	pharynx	(A).	Generally,	each	taste	sensilla	contains	one	sweet	and	one	bitter	neuron	that	respond	to	sweet	and	bitter	tastes	and	cause	acceptance	or	rejection	behaviour,	respectively,	along	with	one	mechanosensory	neuron	(B).	Depending	on	the	type	of	sensilla,	other	GRNs	housed	within	taste	hairs	can	be	responsive	to	compounds	such	as	salt	or	water.	GRN	dendrites	extend	up	into	the	bristle,	coming	into	contact	with	tastants	through	an	opening	at	the	tip	of	the	bristle	called	the	pore.	GRN	axon	terminals	project	to	the	taste	center	of	the	brain,	formally	known	as	the	subesophageal	zone	(Adapted	by	Michael	D	Gordon	from	Chu,	2014).	..........................................................................................................................................	8	Figure	2.	Proboscis	Extension	Reflex	in	Drosophila	melanogaster.	When	an	appetitive	stimulus	is	presented	to	either	the	labellum	of	the	proboscis	or	the	legs	flies	will	extend	their	proboscis	in	attempt	to	feed.	This	behaviour	measures	food	acceptance	and	is	easily	quantifiable	in	the	lab	as	a	binary	response:	yes	(full	extension:	middle	panel)	or	no	(partial	extension	or	no	extension:	all	other	panels)	behaviour	(Adapted	from	Flood	et	al.,	2013).	.........	12	Figure	3.	Peripheral	gustatory	sensory	neurons	send	their	axonal	projections	to	the	taste	center	of	the	fly	brain,	called	the	subesophageal	zone	(white	box,	A).	Sweet	(B)	and	bitter	(C)	axonal	projections	are	non-overlapping	(D)	suggesting	that	taste	modality	is	segregated	in	the	fly	brain.	...........................................................	14	Figure	4.	Gustatory	receptor	neurons	detect	sweet	(blue)	and	bitter	(orange)	compounds	at	the	periphery.	When	sweet	sensory	neurons	are	activated	they	will	evoke	motor	programs	that	initiate	feeding	behaviour	(green).	When	bitter	sensory	neurons	are	activated	they	will	prevent	feeding	behaviour	through	presynaptic	GABAergic	inhibition	on	sweet	sensory	neurons	(red).	The	only	known	second	order	gustatory	neuron	is	the	sweet	gustatory	projection	neuron	(sGPN)	in	the	AMMC	(teal).	.......................................................................................................	16	Figure	5.	Pharyngeal	GRNs	express	sweet	Grs	(a)	Cartoon	showing	the	positions	of	the	LSO	and	VCSO,	with	associated	images	of	each	structure	from	a	fly	expressing	GFP	under	control	of	Gr43a-GAL4.	Dotted	white	box	indicates	area	shown	in	e-f.	(b)	Axonal	projections	of	Gr43a-GAL4	(green)	and	Gr64fLexA	(red)	to	the	SEZ.	Overlapping	regions	are	from	LSO	projections.	(c)	Gr-GAL4-driven	GFP	expression	in	LSO.	Scale	bars	are	10	μm	in	c-d.	(d)	LSO	GFP	expression	from	flies	carrying	Gr43a-GAL4	and	indicated	second	Gr-GAL4	or	Gr64fLexA.	(e)	Gr-GAL4-driven	GFP	expression	in	VCSO.	(f)	VCSO	GFP	expression	from	flies	carrying	Gr43a-GAL4	and	indicated	second	Gr-GAL4.	Scale	bars	are	5	μm	in	e-f.	Dotted	circles	indicate	the	cuticular	pore	of	sensilla.	(g)	Schematic	of	observed	sweet	Gr	expression	in	LSO	and	VCSO	GRNs.	Asterisk	indicates	that	Gr64c-	GAL4	expression	is	seen	in	only	one	neuron	per	side	of	the	VCSO.	.....................................	36		 ix	Figure	6.	Pharyngeal	GRNs	respond	to	sweet	compounds	(a)	Immunofluorescence	of	anti-GFP	(green)	and	nc82	(magenta)	in	the	SEZ	of	flies	expressing	GCaMP3	under	control	of	Gr43a-GAL4.	Dotted	line	shows	area	imaged	in	panel	(b).	(b)	Single	optical	section	of	baseline	GCaMP3	fluorescence	in	pharyngeal	GRN	axon	terminals.	Scale	bars	are	20	μm	in	a-b.	(c)	Heat	map	showing	change	in	GCaMP3	fluorescence	during	ingestion	of	1	M	fructose.	(d)	Representative	trace	of	fluorescence	change	of	GCaMP3	in	Gr43a	axon	terminals	during	ingestion	of	1	M	fructose.	Arrow	indicates	time	at	which	stimulus	is	applied	to	the	proboscis	to	initiate	feeding.	(e)	Peak	fluorescence	changes	of	GCaMP3	in	Gr43a	axon	terminals	during	ingestion	of	1	M	solutions	of	the	indicated	compounds.	Values	represent	mean	+/−	SEM.	for	n	=	5	flies	per	stimulus	(n	=	4	for	sorbitol),	with	data	collected	over	at	least	2	days.	Asterisks	indicate	significant	difference	from	water	by	one-way	ANOVA	with	Bonferroni	correction	for	multiple	comparisons:	**p	<	0.01,	***p	<	0.001,	ns	=	not	significant.	.......................................	38	Figure	7.	poxn	null	mutants	retain	functional	pharyngeal	sense	organs	(a,b)	Pharyngeal	GRNs	labeled	by	Gr43a-GAL4	driving	UAS-TdTomato	in	poxnΔM22-B5/+	heterozygotes	(a)	and	poxnΔM22-B5/poxn70	null	mutants	(b).	Arrows	point	to	GRNs	in	the	LSO	and	VCSO.	(c,d)	Labellar	GRNs	labeled	by	Gr64e-GAL4	driving	UAS-TdTomato	in	poxnΔM22-B5/+	heterozygotes	(a)	and	poxnΔM22-B5/poxn70	null	mutants	(b).	Arrows	point	to	taste	peg	GRNs	in	d.	(e-h)	Immunofluorescence	of	anti-GFP	(green)	and	nc82	(magenta)	in	the	brains	of	poxnΔM22-B5/+	heterozygotes	(e,g)	and	poxnΔM22-B5/poxn70	null	mutants	(f,h)	expressing	GCaMP3	under	control	of	Gr43a-GAL4	(e,f)	or	Gr64e-GAL4	(g,h).	Arrows	point	to	GRN	projections	originating	from	the	various	body	locations.	(i-j)	Peak	fluorescence	changes	of	GCaMP3	in	Gr43a-GAL4	pharyngeal	(i)	or	Gr64e-GAL4	taste	peg	(j)	axon	terminals	in	poxnΔM22-B5/poxn70	null	mutants	during	ingestion	of	the	indicated	compounds.	Values	represent	mean	+/−	SEM.	for	n	=	5	flies,	with	data	collected	over	at	least	2	days.	Asterisks	indicate	significant	difference	from	sorbitol	(i)	or	water	(j)	by	one	way	ANOVA	with	Bonferroni	correction	for	multiple	comparisons:	**p	<	0.01,	***p	<	0.001,	ns	=	not	significant.	Scale	bars	are	100	μm.	......................................................................................................................................	42	Figure	8.	poxn	null	mutants	lack	peripheral	taste	responses	but	prefer	sweet	compounds	(a-d)	PER	responses	of	w1118	(a,c)	and	poxnΔM22-B5/poxn70	null	mutant	(b,d)	flies	following	stimulation	of	the	tarsi	(a,b)	or	labellum	(c,d)	with	the	indicated	compounds.	Values	represent	percentage	of	stimulations	resulting	in	a	positive	response;	error	bars	show	95%	binomial	confidence	interval,	and	asterisks	indicate	significant	difference	from	ribose	stimulation:	*	p	<	0.05,	**	p	<	0.01,	***	p	<	0.001	by	Fisher's	exact	test.	n	=	17-	50	flies	for	w1118	tarsal	PER,	n	=	17-33	flies	for	poxn	tarsal	PER,	n	=	9-19	flies	for	w1118	labellar	PER,	and	n	=	9-17	flies	for	poxn	labellar	PER.	(e,f)	Preference	of	w1118	(e)	and	poxnΔM22-B5/poxn70	null	mutant	flies	(f)	for	100	mM	solutions	of	the	indicated	compounds	in	1%	agar	versus	agar	alone.	Values	represent	mean	+/−	SEM.	for	n	=	10	groups	of	10	flies	each,	with	independent	replicates	performed	over	at	least	2	days.	Asterisks	indicate	significant	difference	from	ribose	preference	by		 x	one-way	ANOVA	with	Bonferroni	correction	for	multiple	comparisons:	**p	<	0.01,	***p	<	0.001.	.........................................................................................................................	45	Figure	9.	Pharyngeal	GRNs	are	necessary	for	the	preference	of	poxn	mutants	for	sweet	compounds	(a)	Immunofluorescence	of	anti-GFP	(green)	and	nc82	(magenta),	showing	expression	of	the	Gr64e-GAL4II	and	Gr43aGAL4	drivers	used	in	the	behavioural	experiments	shown.	Gr64e-GAL4	is	shown	in	a	poxn	null	mutant	background,	while	Gr43aGAL4	is	in	a	poxn/+	heterozygous	background.	Scale	bars	are	100	μm.	(b)	Preference	of	indicated	genotypes	for	100	mM	solutions	of	the	specified	compounds	in	1%	agar	(positive)	versus	agar	alone	(negative).	(c)	Temporal	consumption	characteristics	of	the	indicated	genotypes	in	response	to	stimulation	with	50	mM	arabinose.	Values	represent	mean	+/−	SEM.	for	n	=	10	groups	of	10	flies	each	in	b	and	n	=	29-60	flies	in	c,	with	independent	replicates	performed	over	at	least	2	days.	Asterisks	indicate	significant	difference	by	one-way	ANOVA	with	Bonferroni	correction	for	multiple	comparisons:	*p	<	0.05,	**p	<	0.01,	***p	<	0.001,	ns	=	not	significant.	49	Figure	10.	OA-VL	neurons	show	specific	proximity	to	bitter	sensory	inputs.	(A-D)	VT026002-Gal4	and	VT049128-Gal4	each	drive	expression	in	a	single	OA-VL	neuron	per	side	of	the	SEZ	(magenta)	that	shows	extensive	GRASP	(green)	with	bitter	GRNs	(A,C),	but	little	to	no	GRASP	with	sweet	GRNs	(B,D).	(E)	A	single	OA-VL1	neuron	from	VT026002-Gal4	(magenta),	labeled	using	FLP-out	mosaics,	displays	prominent	GRASP	(green)	with	bitter	GRNs.	(F)	OA-VL1	presynaptic	zones	labeled	with	synaptotagmin-GFP	(green).	OA-VL	processes	labeled	with	anti-dsRed	(magenta).	................................................................................................................	66	Figure	11.	(A-B)	Full	brain	expression	of	VT026002-Gal4	(A)	and	VT049128-Gal4	(L)	driving	CD8::GFP.	Neuropil	is	labeled	with	nc82	(magenta).	(C-D)	GRASP	between	GMR38A06-Gal4	neurons	and	bitter	(C)	or	sweet	(D)	GRNs.	..................	69	Figure	12.	OA-VL1	activity	prior	to	and	following	stimulation	with	bitter	(left)	or	sweet	(right)	tastants.	Each	line	represents	a	single	OA-VL1	neuron,	and	joins	the	pre-stimulus	and	post-stimulus	values.	Bitter	stimuli	used	were:	1	M	denatonium,	20	mM	lobeline,	or	a	cocktail	of	5	mM	berberine	mixed	with	100	mM	caffeine.	Sweet	stimuli	were	1	M	sucrose	or	1	M	glucose.	.................................	71	Figure	13.	OA-VL	neuron	activity	is	regulated	by	satiety	state.	(A)	Representative	cell-attached	recordings	of	OA-VL1	in	flies	that	were	fully	fed	(top)	or	starved	for	24	h	(bottom).	(B)	Raster	plots	of	OA-VL1	activity	in	five	flies	that	were	fully	fed	(top)	or	starved	for	24	h	(bottom).	(C)	Summary	plot	of	OA-VL1	and	OA-VL2	activity	as	the	duration	of	starvation	increases.	Lines	and	error	bars	represent	mean	+/-	SEM	for	OA-VL1	and	OA-VL2	recordings	combined.	Asterisks	indicate	statistical	significance	in	a	one-way	ANOVA	with	Bonferroni	correction,	*	p	<	0.05,	***	p	<	0.001.	........................................................................................................................	72	Figure	14.	OA-VL	activity	modulates	bitter	GRN	calcium	responses.	(A)	Schematic	of	bitter	GRN	calcium	imaging	paradigm,	along	with	sample	heat	map	of	taste-	 xi	evoked	activity	in	bitter	GRNs	and	traces	showing	the	change	in	fluorescence	over	time.	..........................................................................................................................................	74	Figure	15.	Average	peak	GCaMP6f	fluorescence	change	in	Gr66a	axon	terminals	following	stimulation	with	0.07	mM	lobeline,	for	indicated	genotypes	under	fed	and	40h	starved	conditions.	Lines	represent	mean	+/-	SEM,	with	blue	lines	representing	fed	flies	and	red	lines	representing	starved	flies.	Grey	dots	indicate	values	for	individual	flies.	Asterisks	indicate	significance	by	two-way	ANOVA	with	Bonferroni	correction,	***	p	<	0.001,	ns	=	not	significant.	We	also	found	significant	interactions	between	the	fed/starved	condition	and	genotype	for	both	controls	compared	to	OA-VL-silenced	flies.	VT026002>ORK	is	short	form	for	VT026002-Gal4/UAS-ORK,	and	all	indicated	genotypes	also	had	Gr66a-LexA::VP16	and	LexAop-GCaMP6f	in	the	background.	...................................................	76	Figure	16.	OA-VL	neurons	regulate	behavioural	bitter	taste	sensitivity.	The	PER	of	flies	with	silenced	OA-VLs	is	significantly	less	inhibited	by	high	concentrations	of	the	bitter	compound	L-canavanine.	Each	panel	shows	the	percent	PER	(mean	+/-	SEM)	of	flies	starved	for	18	h.	All	genotypes	with	UAS-KIR2.1	also	have	tub-Gal80ts	for	temporal	control	of	KIR2.1	expression.	“+”	indicates	the	w1118	strain	from	VDRC	used	to	make	the	Vienna	Tile	(VT)	collection;	PBDPGal4U	is	an	enhancerless	Gal4	control	for	the	Janelia	lines.		A	colored	asterisk	indicates	that	the	genotype	shown	in	black	was	significantly	more	likely	to	exhibit	PER	than	its	red	or	blue	control	line,	after	a	false	discovery	rate	correction.	n	=	25	flies	per	genotype	at	each	L-canavanine	concentration.	.......................................................	78	Figure	17.	Oct-TyrR	mediates	the	potentiation	of	bitter	sensitivity.	(A)	The	PER	of	flies	with	Oct-TyrR	knocked	down	in	bitter	sensory	neurons	is	significantly	less	inhibited	by	high	concentrations	of	the	bitter	compound	L-canavanine.	Plot	shows	the	percent	PER	(mean	+/-	SEM)	of	flies	starved	for	18	h.	The	colored	asterisks	indicate	that	the	Gr66a>Oct-TyrRRNAi	flies	were	significantly	more	likely	to	exhibit	PER	than	the	red	or	blue	control	lines,	after	a	false	discovery	rate	correction.	(B)	Model	for	the	effect	of	OA-VLs	on	bitter	sensitivity	and	feeding	behaviour.	Green	arrows	indicate	excitation,	red	lines	indicate	inhibition.	The	dashed	line	indicates	that	most,	but	not	all,	bitter	compounds	directly	inhibit	sweet	neurons.	Synaptic	inhibition	of	sweet	GRNs	by	bitter	GRN	activity	is	based	on	previous	work	(Chu	et	al.,	2014).	..................................................	80								 xii	LIST	OF	ABBREVIATIONS	AHL	 	 adult	hemolymph-like	AKH	 	 adipokinetic	hormone	AMMC		 antennal	mechanosensory	and	motor	center	 	C	 	 Celsius		CaM	 	 calcium	binding	protein	calmodulin	ChR2	 	 Channelrhodopsin-2	cpGFP		 circularly	permuted	GFP	DA	 	 dopamine	DCSO	 	 dorsal	cibarial	sense	organs	DNA	 	 deoxyribonucleic	acid	dNPF	 	 neuropeptide	F	DopEcR	 dopamine/ecdysteroid	receptor	DTK	 	 tachykinin	dTRPA1	 Drosophila	transient	receptor	potential	channel	A1	ENaC	 	 epithelial	sodium	channel	Fdg	 	 feeding	neurons2	FLP	 	 LexAop-Flippase	GABA	 	 γ-Aminobutyric	acid	GFP	 	 green	fluorescent	protein	GPCR	 	 G-protein	coupled	receptors	GRASP		 GFP	reconstitution	across	synaptic	partners		Gr	 	 gustatory	receptor	GRN	 	 gustatory	receptor	neuron	 	 	 	h	 	 hours	I	 	 intermediate		K+	 	 potassium		 xiii	KCl	 	 potassium	chloride	KIR2.1		 inwardly	rectifying	potassium	channel	2.1	L	 	 long	 	 	LSO	 	 labral	sense	organ	M	 	 molar	 	MIP	 	 myoinhibitory	peptide		mM	 	 millimolar	ms	 	 milliseconds	Na+	 	 sodium	 	 	NaChBac	 voltage-gated	bacterial	sodium	channel	NaCl	 	 sodium	chloride		ns	 	 not	significant	NST	 	 nucleus	of	the	solitary	tract	OA	 	 octopamine	OA-VL		 ventrolateral	cluster	of	octopaminergic	neurons	OBP	 	 odourant	binding	protein	Octβ1R	 octopamine	receptor	beta	1R	Oct-TyrR	 Octopamine-Tyramine	receptor	ORK	 	 open	rectifier	potassium	channel		ORN	 	 olfactory	receptor	neuron	PER	 	 proboscis	extension	reflex	PI	 	 preference	index	PKD2L1	 polycystic-kidney-disease-like	ion	channel	PLC	 	 phospholipase	C	poxn	 	 pox-neuro	RASSL		 receptor	activated	solely	by	a	synthetic	ligand	RNAi	 	 ribonucleic	acid	(RNA)	interference		 xiv	s	 	 seconds	S	 	 short	SEM	 	 standard	error	of	the	mean	SEZ	 	 subesophageal	zone	sGPNs		 sweet	gustatory	projection	neurons	sNPF	 	 short	neuropeptide	F	sNPFR		 short	neuropeptide	F	receptor	Syt-GFP	 Synaptotagmin-GFP	TA	 	 tyramine	tdc2	 	 tyrosine	decarboxylase	2	TH-VUM	 tyrosine	hydroxylase	positive	ventral	unpaired	medial	TRC	 	 taste	receptor	cell	TRP	 	 transient	receptor	potential		TRPm5	 transient	receptor	potential	channel	m5;	UAS	 	 upstream	activating	sequence		µM	 	 micromolar	VCSO	 	 ventral	cibarial	sense	organs	vnc	 	 ventral	nerve	cord	VT	 	 Vienna	Tile									 xv	ACKNOWLEDGEMENTS		I	would	like	to	extend	my	unending	gratitude	to	Dr.	Michael	Gordon.	He	has	been	an	exceptional	supervisor.	Thanks	for	your	guidance	and	patience,	and	for	pushing	me	when	I	needed	it.	Thanks	to	my	supervisory	committee,	Dr.	Douglas	Allen,	Dr.	Douglas	Altshuler,	and	Dr.	Vanessa	Auld,	for	all	the	feedback	into	my	thesis	research.	It	was	a	pleasure	interacting	with	such	great	faculty	members.			I	would	also	like	to	thank	the	past	and	present	members	of	the	Gordon	Lab	for	their	support	and	friendship	over	the	years.	I	am	extremely	grateful	to	have	met	Bonnie	Chu	and	to	have	had	her	show	me	the	calcium	imaging	ropes.	Thanks	for	sharing	endless	cups	of	coffee	while	trying	to	fix	all	our	failures,	in	the	lab	and	in	life.	Thanks	to	Kevin	Mann	for	being	a	truly	amazing	scientist	and	friend.	The	time	he	spent	in	the	lab	was	short,	but	I	couldn’t	have	been	more	inspired	by	him.	I	am	so	glad	we	got	the	opportunity	to	work	(and	drink)	together.	Ally	Jaeger,	thank	you	for	shifting	the	spectrum	in	my	favour.	Thank	you	to	my	parents,	John	and	Rita	LeDue.	My	endless	determination	and	work	ethic	stems	from	everything	you	both	instilled	in	me	growing	up.	I	couldn’t	be	more	grateful	to	have	parents	who	showed	me	how	to	persevere	through	whatever	life	threw	at	me.	Thanks	to	my	brother	Adam	LeDue,	for	giving	me	countless	opportunities	to	learn	how	to	get	back	up	when	I’ve	fallen	(or	been	pushed)	down.	I	am	also	extremely	thankful	for	west	coast	family,	my	brother	Jeff	LeDue,	and	his	wife	Sarah	Burke.	Thanks	for	many	nights	talking	shop	over	wine,	and	for	all	the	advice	they	each	have	given	me	throughout	my	PhD.	They	are	both	remarkable	people	and	scientists.								And	of	course,	thanks	to	Philip	Kwan.	He	has	been	a	constant	source	of	understanding	and	encouragement	throughout	all	the	challenges	I	faced	in	graduate	school,	and	in	life.	Thanks	to	him	for	truly	understanding	what	motivates	me	to	work	so	hard,	but	also	for	providing	me	with	perspective.	I	am	ever	grateful	for	all	his	support	throughout	this	chapter	of	my	life	and	I	can’t	wait	to	start	the	next	one	with	him	by	my	side.			 1	CHAPTER	1		 	 INTRODUCTION	1.1	MAMMALIAN	TASTE	Across	all	species,	gustation	functions	ubiquitously	to	evaluate	food	sources	and	drive	feeding	decisions.	Animals	must	be	able	to	distinguish	potentially	toxic	food	sources,	from	those	that	can	provide	nutritional	value.	In	general,	detection	of	a	bitter	taste	will	provoke	an	animal	to	reject	that	food	source	to	avoid	harm.	On	the	other	hand,	sweetness	is	the	universal	indicator	of	caloric	value	in	a	food	source	and	sweet	taste	promotes	the	acceptance	of	a	compound	to	maintain	homeostasis	and	reverse	energy	deficits.			In	mammals,	taste	detection	is	mediated	by	specialized	epithelial	cells	called	taste	receptor	cells	(TRC).	TRCs	are	located	in	taste	buds	on	the	tongue	and	mediate	the	transduction	of	gustatory	stimuli	to	primary	sensory	neurons.	TRCs	come	into	contact	with	tastants	through	a	terminal	pore	in	the	taste	bud	tip.	When	a	tastant	contacts	a	TRC	it	causes	a	signal	transduction	cascade	that	generates	graded	depolarization	in	the	TRC.	TRC	depolarization	is	caused	by	action	of	voltage	gated	ion	channels,	such	as	sodium	(Na+)	and	potassium	(K+)	channels	(Gao	et	al.,	2009).	TRCs	then	activate	gustatory	nerves	within	different	craniofacial	nerve	fibers,	depending	on	their	location	on	the	tongue.	The	chorda	tympani	and	greater	superficial	petrosal	cranial	nerves	generally	innervate	TRCs	found	on	the	anterior	portion	of	the	tongue,	while	TRCs	found	on	the	posterior	portion	of	the	tongue	are	innervated	by	the	glossopharyngeal	nerve	(Iguchi	et	al.,	2011).	Through	the	craniofacial	nerves,	taste	fibers	first	convey	information	to	the	nucleus	of	the		 2	solitary	tract	(NST;	Yarmolinsky,	Zuker	and	Ryba,	2009).	From	the	NST,	information	then	enters	the	parvocellular	stream	of	the	thalamus.	Taste	neurons	in	the	thalamus	then	send	projections	to	the	cerebral	cortex	through	the	parabrachial	nucleus	(Spector	and	Travers,	2005).	Mammals	can	detect	five	distinct	primary	taste	modalities:	sweet,	bitter,	salt,	sour	and	umami.	Sweet	and	umami	are	appetitive	taste	modalities,	while	sour	and	bitter	are	considered	aversive	(Nelson	et	al.,	2001;	Zhao	et	al.,	2003;	Huang	et	al.,	2006;	Mueller	et	al.,	2005).	Salt	is	unique	in	that	high	concentrations	are	aversive,	while	low	concentrations	produce	appetitive	behavioural	responses	(Oka	et	al.,	2013).	The	membrane	bound	ion	channels	and	G-protein	coupled	receptors	(GPCRs)	responsible	for	detecting	these	tastants	are	located	on	the	apical	membrane	of	TRCs,	allowing	for	direct	contact.				1.1.1	Appetitive	Taste	in	Mammals			 The	mechanism	of	taste	transduction	depends	on	the	nature	of	the	taste	stimulus.	The	appetitive	modalities	include	sweet,	umami	(L-amino	acids)	and	low	concentrations	of	salt	(10	–	150mM	NaCl).	Sweet	and	umami	tastes	activate	heterodimeric	receptors	composed	of	members	of	the	T1R	family	of	GPCRs:	T1R2	and	T1R3	for	sweet,	and	T1R1	and	T1R3	for	umami	(Zhao	et	al.,	2003).	Low	concentrations	of	salt	activate	the	heterotrimeric	amiloride-sensitive	epithelial	sodium	channel	(ENaC)	(Chandrashekar	et	al.,	2010).		Appetitive	taste	modalities	innately	drive	behavioural	attraction	to	ensure	animals	eat	foods	with	nutritional	value.	Mammals	prefer	to	consume	sweet,	umami,		 3	and	mildly	salty	substances	over	substances	that	lack	these	attractive	tastes	(Steiner	et	al.,	2001;	Nelson	et	al.,	2001;	Chandrashekar	et	al.,	2010).	Evidence	linking	the	activation	of	the	receptors	responsible	for	detection	of	simple	sugars	and	L-glutamic	acid	with	behavioural	attraction	has	come	from	studies	in	which	the	combinations	of	the	T1R	receptors	(T1R2+T1R3	for	sweet	and	T1R1+T1R3	for	umami)	have	been	knocked	out	and	selectively	rescued	in	mice	(Damak	et	al.,	2003;	Zhao	et	al.,	2003).	Knocking	out	either	T1R2	or	T1R3	causes	a	severe	defect	in	the	animal’s	ability	to	physiologically	respond	to,	and	behaviourally	select,	compounds	with	sweet	taste	(Zhao	et	al.,	2003).	Similar	methods	were	used	to	show	that	abolishing	T1R1	or	T1R3	leaves	animals	unable	to	detect	the	appetitive	taste	of	umami,	indicating	that	the	two	receptors	form	a	complex	responsible	for	the	behavioural	attraction	to	umami	(Damak	et	al.,	2003;	Zhao	et	al.,	2003).	Interestingly,	when	the	modified	opioid	receptor,	RASSL,	was	misexpressed	in	sweet	cells,	mice	developed	a	preference	for	RASSL	indicating	that	the	activation	of	sweet	cells	drives	innate	attraction	(Zhao	et	al.,	2003).			Salt	drives	behavioural	attraction	at	low	concentrations	(10mM	NaCl),	especially	in	times	of	salt	deprivation,	and	remains	attractive	to	animals	up	until	concentrations	of	around	300mM	NaCl	(Oka	et	al.,	2003).	This	appetitive	to	aversive	switch	serves	to	maintain	proper	ionic	balance	without	threatening	water	homeostasis.	The	attractive	low	salt	pathway	is	unique	from	the	high	salt	pathway	in	that	it	is	activated	only	by	the	positively	charged	Na+	ion	of	the	NaCl	ionic	compound.	High	salt	receptors	are	responsive	to	other	positively	charged	ions	of	ionic	salt	compounds,	such	as	KCl	(Oka	et	al.,	2003).	In	addition,	the	low	salt		 4	responsive	ENaC	receptors	are	also	inhibited	by	the	drug	amiloride,	whereas	those	receptors	responding	to	high	salt	are	not.		A	conditional	knock-out	of	ENaC	in	mice	caused	the	inability	to	respond	to	low	concentrations	of	NaCl,	while	retaining	responsiveness	to	other	salts	(Chandrashekar	et	al.,	2010).	In	addition,	ENaC	knockout	mice	no	longer	show	any	amiloride	sensitivity	(Chandrashekar	et	al.,	2010).	Both	of	these	pieces	of	evidence	combined	support	that	ENaC	is	the	receptor	for	low	concentrations	of	sodium.		1.1.2	Aversive	Taste	in	Mammals		 Aversive	tastes	in	mammals	consist	of	bitter,	sour	and	high	concentrations	of	salt.	Bitter	chemicals	act	through	the	T2R	family	of	GPCRs	(Adler	et	al.,	2000),	and	expressing	the	murine	T2R	specifically	responsive	to	the	bitter	chemical	cyclohexamide	(mT2R5)	in	heterologous	cells	imparts	cyclohexamide	responsiveness,	as	measured	by	calcium	imaging	(Chandrashekar	et	al.,	2000).	TRCs	containing	the	polycystic-kidney-disease-like	ion	channel	(PKD2L1)	have	been	identified	as	the	candidate	cells	responsible	for	detecting	acidic	chemicals	that	evoke	the	taste	of	sour	(Huang	et	al.,	2006).	Evidence	for	the	role	of	PKD2L1	in	acid	sensing	comes	from	studies	in	which	the	PKD2L1	expressing	cells	have	been	genetically	ablated	in	TRCs.	Mice	lacking	PKD2L1	in	TRCs	show	reduced	responses	to	multiple	acids	across	varying	pH	ranges	as	measured	by	electrophysiological	recordings	of	nerves	coming	from	the	tongue	(Huang	et	al.,	2006).	Interestingly,	it	was	shown	that	high	concentrations	of	salt	do	not	activate	independent	receptors,	but	activate	both	the	bitter	and	sour	TRCs	to	mediate	behavioural	aversion	(Oka	et		 5	al.,	2013).	Calcium	imaging	of	bitter	sensing	TRCs	reveal	responses	to	500mM	KCl	and	mice	lacking	bitter	taste	and	sour	sensing	TRC	function	cannot	detect	high	salt,	suggesting	that	high	salt	recruits	both	the	sour	and	bitter	sensing	pathways	to	promote	aversion	(Oka	et	al.,	2013).		1.1.3	Transduction	of	Mammalian	Taste	into	the	Cortex		 The	sweet,	bitter	and	umami	signal	transduction	pathways	all	utilize	common	downstream	signaling	components,	including	TRPm5	and	PLC	(transient	receptor	potential	channel	m5;	phospholipase	C).	Evidence	for	their	downstream	role	came	from	studies	using	knockout	mice	in	which	TRPm5	and	PLC	expression	was	abolished.	These	animals	displayed	an	inability	to	detect	sweet,	bitter	or	umami	tastes	(Zhang	et	al.,	2003).	This	behavioural	phenotype	suggests	that	TRPm5	and	PLC	are	common	components	of	the	taste	transduction	pathway,	and	play	a	role	downstream	of	the	GPCRs	that	interact	with	the	chemical	ligands	that	activate	sweet	and	bitter	pathways.		Taste	modality	is	spatially	segregated	within	the	primary	gustatory	cortex	of	mice	(Chen	et	al.,	2011).	A	labeled	line	model	of	taste	coding	has	been	proposed	due	to	the	specificity	of	neuronal	response	dedicated	to	each	modality	at	the	periphery,	which	is	maintained	up	into	the	primary	gustatory	cortex	(Bradbury,	2004;	de	Brito	Sanchez	and	Gruifa,	2011).	Although,	taste	in	both	the	mammalian	and	fly	system	does	not	conform	truly	to	a	labelled	line	model,	as	tastes	such	as	high	salt	act	through	other	aversive	receptors	such	as	the	bitter	pathway.	However,	tastes	do	remain	separated	in	their	valence,	i.e.,	whether	they	are	appetitive	or	aversive.		 6	Overall,	many	similarities	can	be	drawn	between	the	mammalian	taste	system	and	that	of	the	fly.	Taste	cells	in	both	can	be	broadly	categorized	into	those	promoting	or	inhibiting	feeding	behaviour,	although	they	are	tuned	to	respond	to	a	multitude	of	chemical	ligands.			1.2	THE	FLY	GUSTATORY	SYSTEM			 Chemosensation	is	necessary	for	multiple	evolutionarily	relevant	behaviours	such	as	locating	food	sources,	mate	selection,	and	predator	avoidance.	Fruit	flies	(Drosophila	melanogaster)	are	highly	adept	at	detecting	chemicals	in	their	environment,	through	both	olfaction	and	gustation.	Although	many	mammals	depend	on	vision	as	their	primary	sense,	the	gustatory	system	of	the	fly	plays	a	critical	role	in	its	survival	and	propagation,	making	Drosophila	an	excellent	model	system	for	beginning	to	parse	out	the	complex	neural	circuits	that	regulate	perception	of	taste,	and	the	integration	of	taste	with	internal	physiological	cues	critical	to	making	feeding	decisions.	Another	benefit	of	using	Drosophila	is	that	it	provides	a	genetically	tractable	model	in	which	to	manipulate	specific	cell	populations.	This	will	ultimately	aide	in	the	dissection	of	circuits	in	the	gustatory	system	that	underlie	taste	perception	and	feeding	behaviour.	In	contrast	to	other	sensory	systems,	which	have	been	studied	extensively,	relatively	little	is	known	about	the	gustatory	systems	of	mammals	and	fruit	flies.	The	fruit	fly	brain	contains	roughly	150000	neurons,	of	which	about	4000	are	contained	in	the	taste	center	of	the	brain,	formally	called	the	subesophageal		 7	zone	(SEZ).	The	SEZ	receives	axonal	projections	from	the	gustatory	sensory	neurons	that	detect	taste	at	the	periphery.		The	afferent	projections	and	functions	of	gustatory	sensory	neurons	in	Drosophila	have	been	well	characterized	and	motor	neurons	controlling	the	behavioural	output	of	the	taste	circuit	have	also	been	identified	(Wang	et	al.,	2004;	Marella	et	al.,	2006;	Fischler	et	al.,	2007;	Gordon	and	Scott,	2009;	Cameron	et	al.,	2010;	Manzo	et	al.,	2012).	Research	has	begun	to	focus	on	revealing	interneurons	in	this	circuit,	but	of	those	that	have	been	described,	few	have	been	shown	to	make	synaptic	connections	with	gustatory	sensory	neurons.	Thus,	much	work	remains	in	characterizing	the	neural	circuits	underlying	taste	processing	in	the	fly	brain.	1.3	PERIPHERAL	FLY	TASTE		Adult	D.	melanogaster	have	multiple	taste	organs	that	are	broadly	distributed	over	the	body,	including	taste	sensilla	located	on	the	proboscis,	pharynx,	wing	margins,	and	legs	(Figure	1;	Nayak	and	Singh,	1983;	Lienhard	and	Stocker,	1987;	Stocker,	1994).	Each	sensillum	houses	primary	gustatory	sensory	neurons	(GRNs),	the	dendrites	of	which	come	in	contact	with	external	taste	stimuli	through	a	single	terminal	pore.	The	proboscis	is	the	primary	taste	organ	of	the	fly,	and	taste	sensilla	on	the	labellum,	which	is	the	terminal	segment	of	the	proboscis,	have	been	the	focus	of	many	studies	of	the	gustatory	system	due	to	their	function	in	feeding	(Mitchell,	Itagaki	and	Rivet,	1999).	Each	labellum	contains	about	31	sensilla	(Falk,	Bleiser-Avivi	and	Atidia,	1976;	Vosshall	and	Stocker,	2007),	which	can	be	classified	as	short	(S),	intermediate	(I)	and	long	(L)	type	depending	on	their	morphology	and	location			 8		Figure	1.	Schematic	showing	location	of	taste	sensilla	in	the	adult	Drosophila,	and	structure	of	individual	sensilla.	Adult	flies	have	taste	sensilla	on	the	legs,	labellum	of	the	proboscis,	wing	margin	and	within	the	pharynx	(A).	Generally,	each	taste	sensilla	contains	one	sweet	and	one	bitter	neuron	that	respond	to	sweet	and	bitter	tastes	and	cause	acceptance	or	rejection	behaviour,	respectively,	along	with	one	mechanosensory	neuron	(B).	Depending	on	the	type	of	sensilla,	other	GRNs	housed	within	taste	hairs	can	be	responsive	to	compounds	such	as	salt	or	water.	GRN	dendrites	extend	up	into	the	bristle,	coming	into	contact	with	tastants	through	an	opening	at	the	tip	of	the	bristle	called	the	pore.	GRN	axon	terminals	project	to	the	taste	center	of	the	brain,	formally	known	as	the	subesophageal	zone	(Adapted	by	Michael	D	Gordon	from	Chu,	2014).	 9	(Montell,	2009;	Benton	and	Dahanuker,	2011).	L-type	sensilla	house	four	GRNs,	with	each	responding	to	a	particular	stimulus:	water,	sugar,	low	salt	or	high	salt	(Hiroi,	Marion-Poll	and	Tanimura,	2002).	S-type	sensilla	also	have	four	GRNs	each,	with	neurons	tuned	to	bitter	and	high	salt,	water,	sugar,	and	pheromones	(Hiroi	et	al.,	2004;	Thistle	et	al.,	2012;	Freeman	and	Dahanukar,	2015).	I-type	sensilla	house	only	two	GRNs	each,	one	of	which	responds	to	low	salt	and	sugar,	while	the	other	responds	to	high	salt	and	bitter	compounds	(Hiroi	et	al.,	2004).	Additionally,	the	internal	surface	of	the	labellum	is	lined	with	a	distinct	class	of	taste	structures,	called	taste	pegs,	which	each	house	a	single	neuron	that	appears	to	sense	carbon	dioxide	and	polyamines	(Fischler	et	al.,	2007;	Hussain	et	al.,	2016).	GRNs	are	also	housed	within	the	pharynx	of	the	fly,	which	contains	three	internal	taste	organs:	the	labral	sense	organ	(LSO),	and	the	dorsal	and	ventral	cibarial	sense	organs	(DCSO	and	VCSO,	respectively)	(Mitchell,	Itagaki	and	Rivet,	1999).	The	roles	of	and	response	profiles	of	GRNs	in	these	taste	organs	were	not	well	defined.		GRNs	express	a	variety	of	receptors	for	taste	ligands.	The	Gustatory	Receptor	(GR)	family	of	genes	was	discovered	based	on	predicted	structural	similarities	to	seven-transmembrane,	G	protein-coupled	receptors	(Clyne,	Warr	and	Carlson,	2000).	All	68	members	of	this	receptor	family	share	a	common	motif	in	the	seventh	transmembrane	domain,	and	appear	to	be	receptors	for	either	sweet	or	bitter	compounds	(Clyne,	Warr	and	Carlson,	2000;	Scott	et	al.,	2001;	Dunipace	et	al.,	2001;	Robertson,	Warr	and	Carlson,	2003).	Another	class	of	taste	receptors	is	encoded	by	members	of	the	pickpocket	(ppk)	ion	channel	family,	which	is	a	member	of	the	Deg/ENaC	family	of	ion	channels	(Cameron	et	al.,	2010).	Water	GRNs	express	the		 10	gene	ppk28	and	are	sensitive	to	low	osmolarity.	Other	members	of	the	ppk	gene	family,	ppk23,	ppk25	and	ppk29,	act	in	GRNs	to	detect	pheromones	(Thistle	et	al.,	2012).		Recently,	members	of	the	ionotropic	receptor	(IR)	family,	made	up	of	61	genes	related	to	ionotropic	glutamate	receptors,	have	also	been	found	to	be	expressed	in	GRNs	of	the	fly	(Benton	et	al.,	2009).	A	specific	member	of	this	family,	IR76B,	was	shown	to	respond	to	and	mediate	appetitive	behaviour	towards	low	concentrations	of	salt	(Zhang,	Ni	and	Montell,	2013).	The	appetitive	effect	mediated	by	this	receptor	is	separate	from	the	pathway	that	detects	and	assesses	high	concentrations	of	salt.	Flies	mutant	for	IR76B	show	a	loss	of	attraction	for	low	salt,	but	maintain	the	ability	to	perceive	high	salt	concentrations	as	aversive.	Since	there	are	a	number	of	other	IR	family	members	expressed	in	GRNs,	it	is	likely	that	IRs	act	as	receptors	for	additional	taste	modalities.	It	is	now	well	established	that	each	sensillum	houses	a	GRN	that	responds	to	sweet	compounds.	Sweet	GRNs	expresses	members	of	a	clade	of	sugar-sensitive	GRs,	which	includes	Gr5a,	a	receptor	required	for	the	response	to	trehalose	(Dahanukar	et	al.,	2001),	and	Gr64a	–	f,	which	respond	to	a	wide	array	of	sugars.	Additionally,	many	sweet	GRNs	also	express	the	fructose	receptor	Gr43a	(Ling	et	al.,	2014).	In	general,	most	sweet	GRNs	express	Gr5a	and	Gr64f,	in	addition	to	a	number	of	other	sweet	GRs.	The	majority	of	sensilla	also	contain	a	GRN	that	expresses	the	gene	Gr66a,	along	with	a	suite	of	other	GR	family	members,	and	respond	to	compounds	that	humans	would	perceive	as	bitter	(Wang	et	al.,	2004;	Thorne	et	al.,	2004).		 11	Neurons	expressing	Gr5a	mediate	appetitive	behaviours,	while	those	expressing	Gr66a	mediate	avoidance.		This	is	demonstrated	by	artificial	activation	of	Gr5a	or	Gr66a	neurons,	which	results	in	taste	acceptance	or	avoidance	behaviours,	respectively	(Marella	et	al.,	2006).	In	response	to	sweet,	palatable	substances,	flies	initiate	feeding	by	extending	their	proboscis	towards	food.	This	robust	feeding	behaviour,	known	as	proboscis	extension	reflex	(PER),	is	easily	quantifiable	and	can	be	used	to	measure	taste	acceptance	in	the	lab	(Figure	2;	Shiraiwa	and	Carlson,	2007).	Upon	stimulation	of	the	labellum	or	legs	with	a	bitter	compound,	there	is	a	retraction	of	the	proboscis	due	to	inhibition	of	the	motor	programs	coordinating	feeding	behaviour	(Rajashekhar	and	Singh,	1994).		In	Drosophila,	many	bitter	compounds	not	only	activate	bitter	GRNs	directly,	but	also	inhibit	the	firing	of	GRNs	that	are	responsive	to	appetitive	taste	stimuli	(Meunier	et	al.,	2003).	By	using	single	sensillum	recordings,	Meunier	et	al.	(2003)	showed	that	bitter	compounds	influence	the	activity	of	GRNs	responsive	to	sugar	or	both	sugar	and	water	at	a	latency	similar	to	the	response	seen	in	GRNs	directly	activated	by	bitter	compounds.	In	addition,	a	lower	threshold	was	required	to	produce	inhibition	of	the	sugar	cell	by	a	particular	bitter	chemical	than	was	necessary	to	cause	an	action	potential	in	the	bitter	responsive	GRN	(Meunier	et	al.,	2003).			More	recently,	it	has	been	shown	that	the	odorant	binding	protein	(OBP)	Obp49a	is	responsible	for	much	of	the	suppression	of	the	sugar	response	by	bitter			 12		Figure	2.	Proboscis	Extension	Reflex	in	Drosophila	melanogaster.	When	an	appetitive	stimulus	is	presented	to	either	the	labellum	of	the	proboscis	or	the	legs	flies	will	extend	their	proboscis	in	attempt	to	feed.	This	behaviour	measures	food	acceptance	and	is	easily	quantifiable	in	the	lab	as	a	binary	response:	yes	(full	extension:	middle	panel)	or	no	(partial	extension	or	no	extension:	all	other	panels)	behaviour	(Adapted	from	Flood	et	al.,	2013).												 13	chemicals	in	sweet	GRNs	(Jeong	et	al.,	2013).	In	wild-type	flies,	sugar	solutions	mixed	with	bitter	compounds	cause	a	blunted	response	in	L-type	sensilla,	which	is	dependent	on	the	amount	of	bitter	tastant	in	the	sugar	solution.	However,	recordings	from	L-type	sensilla	in	Obp49a	mutants	do	not	exhibit	this	inhibition	by	bitter	compounds.	In	addition,	this	lack	of	inhibition	occurs	even	though	Obp49a	mutants	have	normal	electrophysiological	responses	to	sugar	and	bitter	stimuli,	as	recorded	in	the	S	and	L-type	sensilla.	Importantly,	this	study	also	revealed	a	unique	bitter	stimulus,	L-canavinine,	that	drives	responses	of	bitter	neurons	in	the	fly	without	causing	inhibition	of	the	sugar	response	(Jeong	et	al.,	2013).	Use	of	L-canavanine	is	therefore	ideal	in	studies	that	aim	to	parse	out	the	response	of	sugar	and	bitter	neurons,	while	eliminating	crosstalk	between	the	two	pathways	at	the	level	of	the	receptors.	1.4	FLY	TASTE	CIRCUITS	Interestingly,	it	has	been	shown	that	taste	projections	in	Drosophila	segregate	in	the	SEZ	by	modality	(Figure	3;	Thorne	et	al.,	2004;	Wang	et	al.,	2004;	Marella	et	al.,	2006;	Zhang	et	al.,	2013).	Projections	from	sugar/low	salt	(i.e.,	those	that	elicit	acceptance	behaviour	when	activated)	GRNs	terminate	in	more	lateral	regions	of	the	SEZ,	while	projections	from	bitter/high	salt	GRNs	terminate	in	the	medial	region	of	the	SEZ.	Projections	of	GRNs	from	the	different	taste	organs	are	also	segregated	within	the	SEZ.	From	anterior	to	posterior,	we	first	see	projections	of	GRNs	from	the	internal	mouthparts,	followed	by	the	proboscis	and	finally	the	legs				 14		Figure	3.	Peripheral	gustatory	sensory	neurons	send	their	axonal	projections	to	the	taste	center	of	the	fly	brain,	called	the	subesophageal	zone	(white	box,	A).	Sweet	(B)	and	bitter	(C)	axonal	projections	are	non-overlapping	(D)	suggesting	that	taste	modality	is	segregated	in	the	fly	brain.										 15	(Wang	et	al.,	2004).	As	mentioned	previously,	primary	sensory	neurons	have	been	identified	and	well	described	in	the	fly	(Marella	et	al.,	2006;	Wang	et	al.,	2004;	Thorne	et	al.,	2004),	and	much	recent	work	has	focused	on	elucidating	higher	order	neurons	in	the	taste	circuit.		A	study	by	Flood	et	al.	(2013)	identified	a	pair	of	interneurons	that	cause	full	proboscis	extension	when	artificially	activated	using	UAS-dTRPA1.	These	feeding	(Fdg)	neurons	show	large	calcium	transients	in	response	to	sucrose	stimulation	in	starved	flies.	It	was	suggested	by	Flood	et	al.	(2013)	that	Fdg	neurons	are	command	neurons	that	control	the	feeding	motor	program,	as	laser	ablation	of	the	neurons	decreased	normal	feeding	in	response	to	sucrose.	However,	no	direct	connections	were	found	between	Fdg	neurons	and	Gr5a	sensory	neurons	(Flood	et	al.,	2013).		The	first	class	of	second-order	gustatory	neurons	in	the	sweet	pathway	was	described	by	Kain	and	Dahanukar	(2015;	Figure	4).	These	neurons,	named	the	sweet	gustatory	projection	neurons	(sGPNs)	project	their	axons	to	a	higher	brain	region	called	the	antennal	mechanosensory	and	motor	center	(AMMC),	which	was	not	known	to	participate	in	higher	order	taste	processing.	When	the	sGPNs	are	silenced,	there	is	a	reduction	in	appetitive	behaviours	that	promote	food	ingestion,	such	as	PER.	The	converse	is	also	true,	in	that	artificial	activation	of	these	neurons	promotes	PER.	The	activity	of	these	neurons	is	also	modulated	by	satiety	state.	Starvation	appears	to	increase	the	calcium	activity	in	these	neurons	in	response	to	stimulation	of	the	proboscis	with	25	and	50	mM	of	sucrose	(Kain	and	Dahanukar,	2015).	However,	is	it	still	unknown	whether	the	sGPNs	themselves	relay			 16		Figure	4.	Gustatory	receptor	neurons	detect	sweet	(blue)	and	bitter	(orange)	compounds	at	the	periphery.	When	sweet	sensory	neurons	are	activated	they	evoke	motor	programs	that	initiate	feeding	behaviour	(green).	When	bitter	sensory	neurons	are	activated	they	will	prevent	feeding	behaviour	through	presynaptic	GABAergic	inhibition	on	sweet	sensory	neurons	(red).	The	only	known	second	order	gustatory	neuron	is	the	sweet	gustatory	projection	neuron	(sGPN)	in	the	AMMC	(teal).										 17	information	to	other	unidentified	interneurons	in	the	sweet	circuit,	or	to	neurons	controlling	motor	output	of	the	proboscis.	1.5	FEEDING	BEHAVIOUR	IN	DROSOPHILA	In	the	fruit	fly,	feeding	is	a	modular	process	that	consists	of	sub-programs,	each	of	which	in	itself	is	a	distinct	behaviour	(Pool	and	Scott,	2014).	These	sub-programs	are	hierarchical,	and	the	decision	to	engage	in	any	further	sub-program	comes	from	signals	that	pertain	not	only	the	palpability	of	the	food	in	question	but	also	depend	on,	for	example,	the	fly’s	current	nutritional	state,	or	reproductive	needs,	among	other	factors.	The	sub-programs	of	fly	feeding	include:	foraging,	detection	of	food	sources	on	the	legs,	proboscis,	and	pharynx,	and	ingestion	(Pool	and	Scott,	2014).		Adult	flies,	when	nutritionally	deprived,	will	forage	for	food	in	the	environment,	using	olfaction	as	their	guiding	chemical	cue.	It	has	been	shown	that	olfactory	sensitivity	increases	during	starvation,	through	a	short	neuropeptide	F	(sNPF)-dependent	mechanism	that	improves	the	foraging	capabilities	of	the	fly	(Root	et	al.,	2011).	During	starvation,	low	levels	of	circulating	insulin	relieve	suppression	on	the	short	neuropeptide	F	receptor	(sNPFR).		More	sNPFR	is	thus	transcribed	and	integrated	into	the	membrane	of	olfactory	receptor	neurons	(ORNs).	This	increase	in	sNPFR	in	ORNs	mediates	the	starvation-induced	increase	in	odour	sensitivity	by	directly	facilitating	their	response,	and	that	of	their	downstream	projection	neurons	(PNs).			 18	As	flies	are	guided	through	their	environment	by	smell,	the	legs	are	used	to	actively	sample	the	taste	of	potential	food	sources.	Detection	of	a	favourable	food	source	on	the	legs	causes	a	cessation	of	locomotion	(Mann,	Gordon	and	Scott,	2013).	The	activation	of	appetitive	GRNs	on	the	legs	increases	the	probability	that	a	fly	will	extend	its	proboscis	and	initiate	feeding	(Dethier,	1976).	Contacting	food	with	the	proboscis	allows	for	further	evaluation	of	the	food	source	by	activating	GRNs	on	the	labellum	of	the	proboscis	(Pool	and	Scott,	2014).		If	the	food	source	is	judged	to	be	favourable	for	ingestion,	feeding	is	initiated.	The	fly’s	pharyngeal	sense	organs	contain	the	last	GRNs	to	be	activated	by	a	food	source,	and	can	monitor	quality	of	the	incoming	food	and	sustain	ingestion.	Instructions	to	terminate	ingestion	come	from	post-ingestive	signals,	such	as	physical	stretching	of	the	gut	(Pool	et	al.,	2014)	and	detection	of	circulating	levels	of	fructose	in	the	hemolymph	by	nutrient	sensors	in	the	brain	(Miyamoto	et	al.,	2012).		1.6	INTEGRATION	OF	HUNGER	AND	SATIETY	SIGNALS	IN	DROSOPHILA		Hunger	signals	and	taste	perception	must	act	together	to	guide	feeding	and	ensure	homeostasis.	In	Drosophila,	the	influence	of	internal	physiological	states	on	feeding	behaviour	has	become	an	increasingly	studied	topic.	Differential	responses	to	similar	compounds	(i.e,	acceptance	or	rejection)	can	occur	depending	on	the	fly’s	current	level	of	nutritional	deficit	(Inagaki,	Panse	and	Anderson,	2014).		This	behavioural	shift	comes	from	changes	in	sensory	neuron	sensitivity	and	from	modulation	of	sensory	neurons	by	other	neurons.	A	multitude	of	studies	have	been	published	that	describe	sets	of	neurons	that	change	their	activity	based	on	the		 19	satiety	state	of	the	fly	(Marella,	Mann	and	Scott,	2012;	Iganaki	et	al.,	2012;	Inagaki,	Panse	and	Anderson,	2014;	Kain	and	Dahanukar,	2015;	Yapici	et	al.,	2016).	These	neurons	are	therefore	poised	to	modulate	sensory	neuron	sensitivity	as	the	nutritional	requirements	of	the	fly	change.			Starvation	increases	the	fly’s	sensitivity	to	sugar,	while	simultaneously	decreasing	its	sensitivity	to	bitters.	This	system	serves	to	increase	the	fly’s	receptivity	to	sugars	while	decreasing	its	aversion	to	bitter	substances	that	it	may	normally	reject	in	the	fed	state.	Enhancement	in	sugar	sensitivity	is	caused	by	a	dopaminergic	interneuron	residing	in	the	SEZ	called	the	tyrosine	hydroxylase	positive	ventral	unpaired	medial	(TH-VUM)	neuron	(Marella,	Mann	and	Scott,	2012).	TH-VUM	activity	increases	in	starved	flies,	which	increases	the	amount	of	dopamine	released.	It	is	thought	that	TH-VUM	acts	through	the	dopamine/ecdysteroid	receptor,	DopEcR,	which	is	present	in	Gr5a	axon	terminals,	to	enhance	the	activity	of	Gr5a	neurons	under	conditions	of	starvation	(Inagaki	et	al.,	2012).	Behaviourally,	this	potentiation	of	Gr5a	activity	by	starvation	causes	increased	PER	to	lower	concentrations	of	sugar	compared	to	fed	flies	(Inagaki	et	al.,	2012).		The	one	second-order	sweet	neuron	to	be	connected	to	labellar	Gr5a	sensory	neurons	has	also	been	shown	to	increase	its	activity	in	response	to	dopamine	(Kain	and	Dahanukar,	2015).	Both	starvation	and	feeding	of	L-Dopa	increases	the	calcium	output	of	sPGNs,	mimicking	the	increase	seen	in	the	Gr5a	sensory	neurons	themselves,	perhaps	by	TH-VUM	acting	to	release	dopamine	on	both	Gr5a	and	sPGNs.	neuropeptide	F	(dNPF)	positive	neurons	can	also	increase	the	sensitivity	of		 20	sweet	sensory	neurons,	and	act	upstream	of	dopaminergic	neurons	(Inagaki,	Panse	and	Anderson,	2014).	Starvation-induced	sugar	sensitivity	caused	by	dNPF	is	abolished	in	DopEcR	mutants.	One	other	set	of	neurons,	the	ingestion	neurons	(IN1)	has	been	empirically	shown	to	be	part	of	the	sweet	taste	pathway	but	these	neurons	are	postsynaptic	to	sweet	sensory	neurons	originating	in	the	pharynx	(Yapici	et	al.,	2016).	These	neurons	also	have	altered	activity	depending	on	the	satiety	state	of	the	animal,	with	increased	activity	in	the	starved	state.	It	is	unknown	whether	the	activity	of	these	neurons	can	be	increased	by	dopamine,	or	whether	their	increased	response	is	a	product	of	the	increased	sweet	sensory	neuron	activity.									Much	less	is	known	about	the	composition	of	the	bitter	taste	circuit	in	Drosophila	and	how	it	is	regulated	in	response	to	hunger.	Peptidergic	modulators	responsible	for	the	desensitization	of	primary	bitter	sensory	neurons	have	been	identified	(Iganaki,	Panse	and	Anderson,	2015).	Flies	lacking	sNPF	do	not	show	reduced	bitter	sensitivity	when	starved,	but	retain	normal	sugar	sensitivity.	Adipokinetic	hormone	(AKH)	is	released	upon	starvation	and	silencing	AKH	neurons	or	deletion	of	the	AKH	receptor	has	been	shown	to	suppress	starvation	induced	behaviours,	such	as	increased	foraging	(Lee	and	Park,	2004).	Abolishing	AKH	cells	eliminates	the	starvation	induced	decrease	in	bitter	sensitivity.	AKH	was	shown	to	act	upstream	of	sNPF	to	achieve	this	reduction,	as	activating	AKH	cells	in	sNPF	mutant	flies	resulted	in	no	change	in	bitter	sensitivity.	However,	sNPF	does	not	act	directly	on	the	Gr66a	bitter	neurons	themselves	as	knockdown	of	sNPFR	in	these	sensory	neurons	has	no	effect	on	bitter	sensitivity.	Therefore,	sNPF	positive		 21	neurons	must	act	on	another	cell	population	upstream	of	the	Gr66a	sensory	neurons,	but	this	population	was	not	identified	(Inagaki,	Panse	and	Anderson,	2015).						 Other	neurons	have	also	been	shown	to	influence	hunger-dependent	behaviours,	but	it	is	unclear	how	these	neurons	fit	into	the	taste	circuit.	A	group	of	serotonergic	neurons	appear	to	elicit	hunger	responses	in	fed	flies.	When	these	neurons	are	artificially	activated	fed	flies	show	PER	to	lower	concentrations	of	sucrose	than	fed	controls	and	correspondingly	increase	their	consumption	(Albin	et	al.,	2015).	Another	independent	group	of	peptidergic	neurons,	those	expressing	myoinhibitory	peptide	(MIP),	regulate	body	weight	by	conveying	a	sated	signal	and	suppressing	food	intake	(Min	et	al.,	2016).	Both	of	these	subsets	of	neurons	appear	to	modulate	sucrose	sensitivity	depending	on	the	satiety	state	of	the	fly,	but	is	still	unknown	where	and	how	these	neurons	interact	with	sweet	sensory	neurons.	1.7	FLY	NEUROGENETICS	The	fruit	fly,	Drosophila	melanogaster,	has	become	a	prominent	model	organism	in	neuroscience	research	over	the	last	decade.	Drosophila	provides	us	with	the	ability	to	genetically	manipulate	distinct	cell	types	and	circuits,	which	will	ultimately	aid	in	the	dissection	of	neural	mechanisms	governing	perception	and	behaviour	(Venken,	Simpson	and	Bellen,	2011).	In	particular,	this	genetically	tractable	model	system	is	advantageous	because	it	can	be	used	in	combination	with	in	vivo	imaging	techniques	(calcium	imaging)	that	allow	for	the	observation	of	activity	in	neuron	populations	over	time.			 22	1.7.1	The	Gal4/UAS	Binary	Expression	System		 In	flies,	the	Gal4/UAS	binary	expression	system	is	a	powerful	means	of	manipulating	gene	expression.		This	technique	uses	genomic	promoters	or	enhancers	to	spatially	control	the	expression	of	transgenes	in	subpopulations	of	neurons	(Duffy,	2002).	Gal4	is	a	yeast	transcription	activator	protein	that	binds	to	an	upstream	activating	sequence	(UAS)	to	initiate	gene	transcription	of	downstream	elements	(Brand	and	Perrimon,	1993).	Transgenes	containing	genes	of	interest	can	be	inserted	downstream	of	UAS	sequences,	and	tissue-specific	expression	of	this	transgene	is	determined	by	which	enhancers	and/or	promoters	regulate	the	expression	of	a	separate	transgene	containing	Gal4.	The	spatial	and	temporal	activity	of	Gal4	can	be	further	restricted	using	Gal80,	a	protein	that	interacts	with	Gal4	by	binding	to	its	transcriptional	activation	domain,	preventing	the	binding	of	Gal4	to	UAS	regions.			Pfeiffer	et	al.	(2008)	created	a	large	collection	of	Gal4	promoter	lines	that	express	in	small	subsets	of	neurons	in	the	Drosophila	brain.	To	create	this	collection,	3-kb	DNA	fragments	flanking	genes	expressed	in	the	brain	were	cloned	upstream	of	Gal4	and	inserted	into	the	genome	using	site-specific	recombination	(Groth	et	al.,	2004).	This	process	has	now	been	used	extensively	to	create	large	collections	of	Gal4	promoter	lines,	including	Janelia	and	Vienna	Tile	(VT)	collections.	Crossing	these	promoter	lines	to	flies	that	contain	a	UAS-GFP	transgene	allows	for	visualization	of	the	subset	of	cells	where	Gal4	is	active.	Researchers	can	then		 23	visually	screen	large	collections	of	Gal4	promoter	lines	and	select	those	that	contain	neuronal	Gal4	expression	within	circuits	of	interest.	1.7.2	Using	Gal4/UAS	to	Manipulate	Neuronal	Activity		 The	Gal4/UAS	system	can	be	used	to	activate	or	silence	different	populations	of	cells	to	determine	their	effect	on	behaviour.	The	inwardly	rectifying	potassium	channel	2.1	(Kir2.1)	maintains	an	open	confirmation	at	resting	potential.	As	a	result,	potassium	exits	neurons	expressing	this	channel,	hyperpolarizing	the	membrane	and	preventing	depolarization	by	presynaptic	neurons	(Hodge,	2009).	Similarly,	expressing	Drosophila	TRPA1	(dTRPA1)	in	Gal4	lines	allows	for	inducible	activation	of	neurons	at	temperatures	around	30°C.	dTRPA1	is	a	member	of	the	highly	conserved	transient	receptor	potential	(TRP)	family	of	cation	channels.	The	channel	conductance	of	dTRPA1	varies	with	alterations	in	temperature,	and	thus	these	channels	can	be	expressed	exogenously	in	populations	of	neurons	to	cause	acute	activation	in	response	to	warming	(Hamada	et	al.,	2008).	Warming	of	flies	expressing	dTRPA1	causes	a	more	robust	depolarization	of	neurons	than	the	alternative	optogenetic	channel,	Channelrhodopsin-2	(ChR2;	Bernstein,	Garrity	and	Boyden,	2012).	In	addition,	the	voltage-gated	bacterial	sodium	channel	NaChBac	can	be	expressed	in	neurons	to	cause	increased	membrane	excitability	(Nitabach	et	al.,	2006).	NaChBac	may	be	a	good	alternative	to	dTRPA1	in	situations	where	heating	the	fly	while	performing	an	assay	is	not	feasible.				 24	1.7.3	Using	Gal4/UAS	to	Measure	Neuronal	Activity	Through	Calcium	Imaging		 The	Gal4/UAS	system	can	also	be	used	to	express	the	calcium	sensor	GCaMP	in	specific	populations	of	neurons,	allowing	measurement	of	neural	activity	via	a	change	in	fluorescence.	GCaMP	is	a	fluorescent	calcium	indicator	derived	from	circularly	permuted	GFP	(cpGFP),	the	calcium	binding	protein	calmodulin	(CaM),	and	the	CaM	binding	peptide	M13	(Crivici	and	Ikura,	1995;	Baird,	Zacharias	and	Tsien,	1999;	Nagai	et	al.,	2001).	As	calcium	enters	the	cell	during	neuronal	depolarization,	CaM	binds	calcium	through	an	E-F	hand	motif	(Mank	and	Griesbeck,	2008;	McCombs	and	Palmer,	2008;	Whitaker,	2010).	Binding	of	calcium	by	CaM	causes	a	conformational	change	as	a	result	of	its	interaction	with	M13,	which	subsequently	closes	a	pore	in	the	GFP	barrel.	This	change	causes	a	fluorescence	increase	compared	to	the	baseline	conformational	state,	thus	acting	as	a	proxy	for	neuronal	activity	and	allowing	us	to	measure	the	activity	in	many	cells	simultaneously.		In	flies,	GCaMP	offers	advantages	in	measuring	neural	activity	when	compared	to	electrophysiology.	It	provides	the	ability	to	measure	calcium	transients	in	specific	neural	populations	in	response	to	a	behaviour	or	stimulus,	without	damaging	cells.	The	small	size	of	fly	neurons	also	makes	cell	recordings	particularly	challenging.	GCaMP3	was	the	first	indicator	capable	of	detecting	single	action	potentials	in	populations	of	mammalian	neurons,	and	fluorescence	of	GCaMP3	caused	by	calcium	influx	increased	linearly	with	an	increase	in	the	number	of	action	potentials	(Tian	et	al.,	2009).	In	Drosophila	antennal	lobe	neurons,	GCaMP3		 25	provided	a	4	–	6x	increase	in	stimulus-evoked	fluorescent	responses	when	compared	to	earlier	version	of	GCaMP	(Tian	et	al.,	2009).	Yet	GCaMP3	still	did	not	surpass	the	ability	of	synthetic	calcium	indicator,	OGB-1,	in	terms	of	photostability	and	the	calcium	binding	rate.	It	also	had	lower	sensitivity	to	calcium,	a	smaller	dynamic	range,	and	slower	decay	kinetics.	However,	synthetic	OGB-1	must	be	injected	into	the	brain	making	it	difficult	to	target	specific	neurons.	So	researchers	were	forced	to	trade-off	between	specificity	in	labelling	neurons	of	interest	and	using	a	superior	indicator	of	neural	activity.	Further	versions	of	GCaMP	have	since	been	designed,	improving	on	the	structure	of	the	original	GCaMP	by	using	protein	structure	guided-mutagenesis	(Tian	et	al.,	2009;	Akerboom	et	al.,	2012).	With	the	advent	of	GCaMP6,	the	abilities	of	genetically	encoded	calcium	indicators	came	to	rival	synthetic	indicators.	GCaMP6	exceeded	the	ability	of	OGB-1	in	terms	of	sensitivity	to	calcium	and	had	an	improved	signal	to	noise	ratio.		GCaMP6	was	also	able	to	detect	single	action	potentials	in	vivo	(Chen	et	al.,	2013).										1.8	OBJECTIVE	OF	THE	CURRENT	EXPERIMENTS		One	of	the	main	objectives	in	neuroscience	research	is	to	understand	the	neural	circuits	that	govern	behaviour.	This	is	of	fundamental	importance	in	order	decipher	the	relationship	between	neural	activity	and	behaviour	in	both	healthy	and	diseased	states.	Drosophila	is	an	excellent	model	system	in	which	to	address	this	challenge.	We	can	make	use	of	the	powerful	genetic	tools	available	in	Drosophila	to	precisely	manipulate	neuronal	circuits	and	combine	these	tools	with	live	imaging	to	measure	corresponding	neural	activity.	These	techniques	provide	a	promising		 26	avenue	towards	comprehension	of	the	causal	relationships	between	the	formation	of	percepts	and	the	generation	of	appropriate	behavioural	outputs.		1.8.1	Chapter	2			 In	chapter	2,	we	sought	to	characterize	the	role	of	pharyngeal	neurons	in	taste	perception	and	feeding	behaviour	using	multiple	techniques.	We	were	interested	in	whether	pharyngeal	GRNs	could	drive	feeding	decisions	and	whether	they	had	a	function	that	was	independent	from	that	of	taste	receptors	on	the	labellum.	We	identified	subsets	of	sweet	Grs	that	reside	in	the	internal	taste	organs	of	the	pharynx	using	double	labeling.	By	using	calcium	imaging,	we	determined	that	these	Grs	are	functional	and	respond	to	sugars.	By	abolishing	all	peripheral	taste	using	a	pox-neuro	(poxn)	mutant,	we	determined	that	these	pharyngeal	GRNs	alone	can	be	used	to	discriminate	sweet	compounds.	Pharyngeal	GRNs	are	also	required	for	sustained	ingestion	of	sweet	compounds,	suggesting	that	they	have	a	unique	role	in	feeding	separate	from	that	of	GRNs	on	the	labellum.	1.8.2	Chapter	3				 In	chapter	3,	we	identified	a	small	set	of	neurons,	the	OA-VL	neurons,	that	modulate	primary	sensory	bitter	neuron	output	during	starvation.	Using	GRASP,	we	identified	that	these	octopaminergic/tyraminergic	neurons	are	in	close	physical	proximity	to	bitter	sensory	neuron	axon	terminals.	During	starvation	OA-VL	neurons	decrease	their	firing	rate,	suggesting	that	they	act	to	potentiate	bitter	neuron	output	in	the	fed	state.	We	genetically	silenced	OA-VL	neurons	and		 27	performed	both	PER	assays	and	calcium	imaging	of	bitter	axon	terminals.	When	OA-VL	neurons	are	silenced,	bitter	neuron	output	is	reduced	to	levels	observed	in	starved	flies.	Consistent	with	this	reduction,	flies	show	less	inhibition	to	sucrose	mixed	with	increasing	concentrations	of	bitter	in	a	PER	assay.	Knockdown	of	the	Oct-TyrR,	a	receptor	that	binds	both	octopamine	and	tyramine,	in	bitter	sensory	neurons	attenuated	starvation-induced	bitter	sensitivity.	We	also	applied	octopamine	or	tyramine	or	both	to	the	brain	while	measuring	the	bitter	axon	terminals	and	found	that	each	had	the	ability	to	potentiate	bitter	neuron	output	in	starved	flies.	Combined,	this	data	suggests	that	OA-VLs	act	directly	on	bitter	sensory	neurons	to	potentiate	their	activity	in	the	fed	state,	and	during	starvation	depotentiation	caused	by	reduced	OA-VL	activity	allows	flies	to	consume	potentially	contaminated	foods	to	survive.																 28	CHAPTER	2		 	 THE	ROLE	OF	PHARYNGEAL	SENSE	ORGANS	IN	FEEDING	DECISIONS	IN	DROSOPHILA	MELANOGASTER	2.1	INTRODUCTION	Sweet	taste	plays	a	key	role	in	promoting	ingestion	of	nutritionally	rich	sources	of	carbohydrates.	Adult	Drosophila	express	sweet	taste	receptors	in	GRNs	located	in	the	legs,	labellum	and	a	set	of	three	pharyngeal	sense	organs	collectively	referred	to	as	the	internal	mouthparts	(Stocker,	1994).	Sweet	GRNs	in	the	legs	and	labellum	are	broadly	tuned	to	sugar	stimuli,	and	their	activation	initiates	feeding	behaviours	including	the	proboscis	extension	reflex	(Wang	et	al.,	2004;	Dahanukar	et	al.,	2007;	Freeman,	Wisotsky	and	Dahanukar,	2014;	Marella	et	al.,	2006;	Deithier,	1976).	However,	neither	the	physiology	nor	the	behavioural	roles	of	pharyngeal	GRNs	have	been	described.		The	pharyngeal	sense	organs	consist	of	the	DCSOs	and	VCSOs	and	the	more	distal	LSO	(Stocker,	1994;	Nayak	et	al.,	1983).	The	DCSO	has	two	gustatory	sensilla	on	each	side	of	the	midline,	each	housing	three	GRNs.	Each	side	of	the	VCSO	and	LSO	has	three	gustatory	sensilla	housing	a	total	of	eight	and	ten	GRNs,	respectively	(Nayak	et	al.,	1983;	Gendre,	2004).	Axons	from	pharyngeal	GRNs	project	via	the	pharyngeal	nerve	to	the	SEZ	of	the	brain,	where	they	target	an	area	that	is	distinct	from	the	projections	of	the	leg	and	labellar	GRNs	(Stocker,	1994;	Wang	et	al.,	2004).	Mapping	of	body	parts	to	different	areas	of	the	SEZ	raises	the	possibility	that	taste	detection	by	the	legs,	labellum	and	pharyngeal	sense	organs	may	each	have	distinct	ethological	functions.			 29	The	Drosophila	genome	encodes	68	members	of	the	Gr	family,	with	nine	classified	as	sweet	receptors	(Wang	et	al.,	2004;	Dahanukar	et	al.,	2007;	Freeman,	Wisotsky	and	Dahanukar,	2014;	Marella	et	al.,	2006;	Deithier,	1976;	Jiao	et	al.,	2007;	Slone	et	al.,	2007;	Scott	et	al.,	2001;	Miyamoto	et	al.,	2012).	Eight	of	these,	Gr5a,	Gr61a	and	Gr64a–64f,	are	closely	related	in	sequence	and	are	the	defining	members	of	a	clade	of	insect	sweet	taste	receptors	(Kent	and	Robertson,	2009).	Both	expression	and	functional	analyses	suggest	that	sweet	GRNs	co-express	multiple	sweet	receptors	(Dahanukar,	et	al.,	2007;	Jiao,	et	al.,	2007;	Slone	et	al.,	2007;	Miyamoto	et	al.,	2012;	Jiao	et	al.,	2008).	Furthermore,	mapping	of	Gr	promoter-GAL4	expression	patterns	to	identified	sensilla	in	the	labellum	and	tarsi	suggests	that	individual	sweet	Grs	may	be	expressed	in	overlapping	but	distinct	subsets	of	sweet	GRNs	(Nayak	et	al.,	1983;	Gendre,	2004;	Weiss	et	al.,	2011;	Ling	et	al.,	2014).	In	addition	to	the	sweet	clade,	a	highly	conserved	receptor,	Gr43a,	also	functions	as	a	sugar	receptor	(Freeman,	Wisotsky	and	Dahanukar,	2014;	Miyamoto	et	al.,	2012;	Sato,	Tanaka	and	Touhara,	2011).	Interestingly,	Gr43a,	which	is	expressed	in	a	few	neurons	in	the	protocerebrum,	appears	to	be	restricted	to	some	tarsal	and	pharyngeal	GRNs	in	the	gustatory	system	(Miyamoto	et	al.,	2012;	Weiss	et	al.,	2011;	Ling	et	al.,	2014).		In	addition	to	sweet	taste,	mounting	evidence	suggests	that	the	caloric	content	of	sugars	can	drive	feeding	preferences	in	both	insects	and	mammals	(Sclafani,	2006;	de	Araujo	et	al.,	2011;	Dus	et	al.,	2011;	Dus	et	al.,	2013;	Burke	and	Waddell,	2011;	Burke	et	al.,	2012;	Fujita	and	Tanimura,	2011;	Stafford	et	al.,	2012).	To	distinguish	between	the	nutritional	and	gustatory	effects	of	various	sugars,	it	would		 30	be	beneficial	to	examine	animals	that	completely	lack	taste	sensory	input	(de	Araujo	et	al.,	2011;	Dus	et	al.,	2011;	Dus	et	al.,	2013).	One	proposed	means	of	achieving	this	effect	in	flies	has	been	to	use	poxn	mutants,	in	which	external	taste	bristles	are	transformed	into	mechanosensory	bristles	(Dus	et	al.,	2011;	Dus	et	al.,	2013;	Nottebohm	et	al.,	1994;	Awasaki	and	Kimura,	1997).	However,	there	is	evidence	that	the	pharyngeal	sense	organs	of	poxn	mutants	retain	expression	of	at	least	some	gustatory	genes	(Galindo	and	Smith,	2001).	If	poxn	mutants	have	functional	pharyngeal	taste	sensilla,	this	could	account	for	their	observed	preference	for	caloric	sugars	(Dus	et	al.,	2011;	Dus	et	al.,	2013).	2.2	MATERIALS	AND	METHODS		2.2.1	Fly	Stocks		 Flies	were	raised	on	standard	cornmeal	fly	food	at	25	°C	and	70%	relative	humidity.	The	following	fly	lines	were	used:	Gr5a-GAL4,	Gr43a-GAL4,	Gr64a-GAL4,	Gr61a-GAL4,	Gr64c-GAL4,	Gr64d-GAL4	and	Gr64e-GAL4	(Weiss	et	al.,	2011);	Gr64fLexA	and	Gr43aGAL4	(Miyamoto	et	al.,	2012);	UAS-GCaMP3	(Tian	et	al.,	2009);	UAS-KIR2.1	(Baines	et	al.,	2001);	UAS-TdTomato	and	UAS-GFP	(Bloomington	stock	centre);	poxnΔM22-B5	(Boll,	2002);	and	poxn70	(Awasaki	and	Kimura,	1997).	2.2.2	Immunohistochemistry		 Immunohistochemistry	was	carried	out	as	previously	described	(Gordon	and	Scott,	2009).	The	primary	antibodies	used	were	rabbit	anti-GFP	(1:1000,	Invitrogen)	and	mouse	nc82	(1:50,	Developmental	Studies	Hybridoma	Bank).	The	secondary		 31	antibodies	used	were	goat	anti-rabbit	Alexa-488	and	goat	anti-mouse	Alexa-568	(Invitrogen).	Images	are	maximum	intensity	projections	of	confocal	z-stacks	acquired	using	a	Leica	SP5	II	confocal	microscope	with	25	×	water	immersion	objective	or	63	×	oil	immersion	objective.	Images	were	taken	sequentially	with	a	scanning	speed	of	200	lines	per	second,	a	line	average	of	2,	and	a	resolution	of	1024	×	1024	pixels.	2.2.3	Gr	Expression	Mapping		 Expression	of	sweet	Gr	promoter-GAL4	lines	was	mapped	in	the	three	pharyngeal	sense	organs	by	visualizing	UAS-mCD8::GFP	fluorescence	in	live	tissue.	Proboscis	tissue	was	dissected	and	mounted	in	80%	glycerol	in	1	×	PBS	before	imaging	with	a	Leica	SP5	laser	scanning	confocal	microscope.	For	double-driver	analysis,	the	UAS-mCD8::GFP	transgene	was	under	the	control	of	two	different	Gr	promoter-Gal4	transgenes	and	the	number	of	GFP-labelled	neurons	were	compared	with	those	in	flies	containing	a	single-Gal4	driver	alone.	2.2.4	GCaMP	Imaging		 Female	flies	aged	2–12	days	were	used	for	calcium	imaging.	To	prepare	flies	for	imaging,	they	were	briefly	anaesthetized	and	all	the	legs	were	removed	to	allow	unobstructed	access	to	the	proboscis.	Using	a	custom	chamber,	each	fly	was	mounted	by	inserting	the	cervix	into	individual	collars.	To	further	immobilize	the	head,	nail	polish	was	applied	in	a	thin	layer	to	seal	the	head	to	the	chamber.	Melted	wax	was	applied	using	a	modified	dental	waxer	to	adhere	the	fully	extended		 32	proboscis	to	the	chamber	rim.	The	antennae	and	associated	cuticle	covering	the	SEZ	were	removed	and	adult	hemolymph-like	(AHL)	buffer	with	ribose	(Liu	et	al.,	2012)	was	immediately	injected	into	preparation	to	cover	the	exposed	brain.	A	coverslip	was	inserted	into	the	chamber	to	keep	the	proboscis	dry	and	separated	from	the	bath	solution.		GCaMP3	fluorescence	was	viewed	with	a	Leica	SP5	II	laser	scanning	confocal	microscope	equipped	with	a	tandem	scanner	and	HyD	detector.	The	relevant	area	of	the	SEZ	was	visualized	using	the	25	×	water	objective	with	an	electronic	zoom	of	eight.	Images	were	acquired	at	a	speed	of	8000	lines	per	second	with	a	line	average	of	four,	resulting	in	collection	time	of	60	ms	per	frame	at	a	resolution	of	512	×	200	pixels.	The	pinhole	was	opened	to	2.68	AU.	Stimuli	were	applied	to	the	proboscis	using	a	pulled	glass	pipette,	and	flies	were	allowed	to	ingest	solutions	during	imaging.	The	maximum	change	in	fluorescence	(ΔF/F)	was	calculated	as	the	peak	intensity	change	divided	by	the	average	intensity	over	10	frames	before	stimulation.	2.2.5	Behavioural	Assays		2.2.5.1	Proboscis	Extension	Reflex	Assay		 For	PER,	adult	female	flies	were	aged	3–10	days	and	starved	on	1%	agar	at	room	temperature	(~22	°C)	for	24	h	before	testing.	For	tarsal	PER,	flies	were	mounted	on	glass	slides	using	nail	polish.	For	labellar	PER,	flies	were	placed	inside	a	pipette	tip	cut	to	size	so	that	only	the	head	was	exposed.	Flies	were	then	sealed	into	the	tube	with	tape,	and	then	adhered	to	a	glass	slide	with	doublesided	tape.	Flies		 33	were	allowed	1–2	h	to	recover	before	testing	began.	Flies	were	stimulated	with	water	on	their	front	tarsi	or	labella	for	tarsal	and	labellar	PER,	respectively,	and	allowed	to	drink	until	satiated.	Each	fly	was	then	stimulated	with	a	tastant	on	either	the	tarsi	or	labella,	and	responses	to	each	of	three	trials	were	recorded.	Flies	were	provided	with	water	between	each	tastant.	All	stimuli	were	delivered	with	a	1	mL	syringe	attached	to	a	20	mL	pipette	tip.	For	statistical	purposes,	each	trial	was	treated	as	an	independent	unit	of	analysis.		2.2.5.2	Binary	Choice	Assay		 Binary	choice	preference	tests	were	performed	similarly	to	previous	descriptions	(Weiss	et	al.,	2011;	Dus	et	al.,	2011;	Riberio	and	Dickson,	2010).	Female	flies	aged	3–8	days	were	sorted	into	groups	of	10	at	least	2	days	before	the	experiment,	and	starved	on	1%	agar	at	room	temperature	(~22	°C)	for	24	h	before	testing.	For	the	assay,	flies	were	transferred	into	standard	vials	containing	six	10	µL	dots	of	agar	that	alternated	in	color.	The	agar	substrates	were	1%	agar	with	or	without	the	test	stimulus	at	a	concentration	of	100	mM.	Each	choice	contained	either	0.125	mg	mL-1	blue	(Erioglaucine,	FD&C	Blue#1)	or	0.5	mg	ml-1	red	(Amaranth,	FD&C	Red#2)	dye,	and	half	the	replicates	for	each	stimulus	were	done	with	the	dyes	swapped	to	control	for	any	dye	preference.	Flies	were	allowed	to	feed	for	2	h	in	the	dark	at	25	°C	and	then	frozen	and	scored	for	abdomen	color.	PI	for	sugar	was	calculated	as	((number	of	flies	labelled	with	the	stimulus	colour)−(number	of	flies	labelled	with	the	plain	agar	colour))/(total	number	of	flies	that	fed).		 34	2.2.5.3	Temporal	Consumption	Assay		 The	temporal	consumption	assay	was	performed	on	flies	deprived	of	food	for	24	h	(Pool	et	al.,	2014).	As	described	above	for	PER,	flies	were	mounted	on	glass	slides	using	nail	polish	and	allowed	to	recover	for	1–2	h	in	a	humidified	chamber.	Water-satiated	flies	were	then	offered	50	mM	arabinose	on	their	labella.	Once	they	initiated	feeding,	the	time	between	starting	and	stopping	their	first	feeding	bout	was	recorded	(first	bout	length).	The	fly	was	then	offered	arabinose	again	and	if	they	failed	to	reinitiate	feeding	for	three	consecutive	stimulations,	the	assay	was	terminated	for	that	fly.	If	flies	began	a	new	bout	of	feeding	on	stimulation,	the	time	of	the	subsequent	bouts	was	added	to	the	first	bout	to	determine	total	consumption	time	and	the	number	of	bouts	was	recorded.		2.3	RESULTS	2.3.1	Pharyngeal	GRNs	Express	Sweet	Receptors		 Pharyngeal	GRNs	express	sweet	receptors.	Previous	studies	have	suggested	that	sweet	receptors	are	expressed	in	internal	pharyngeal	GRNs	(Dahanukar	et	al.,	2007;	Miyamoto	et	al.,	2012;	Wisotsky	et	al.,	2011).	To	assign	selected	sweet	receptors	to	identified	pharyngeal	GRNs,	we	used	seven	previously	reported	Gr	promoter-GAL4	transgenes	(Weiss	et	al.,	2011;	Ling	et	al.,	2014)	and	a	LexA	knock-in	allele	of	Gr64f	(Miyamoto	et	al.,	2012).	Mapping	was	based	on	the	examination	of	GFP	expression	in	the	LSO,	VCSO	and	DCSO	(Figure	5)	of	flies	carrying	each	Gr-GAL4	or	GrLexA	driver,	as	well	as	analysis	of	GFP	expression	in	flies	carrying	two	different		 35	drivers.	Six	of	the	seven	sweet	Gr-GAL4	drivers,	as	well	as	Gr64fLexA,	showed	expression	in	the	pharynx	and	suggest	that	the	LSO	and	VCSO	are	innervated	by	sweet	GRNs	(Figure	5).	We	did	not	detect	any	Gr5a-GAL4	expression	in	the	pharynx,	and	none	of	the	sweet	Gr-GAL4	lines	tested	showed	expression	in	the	DCSO	(not	shown).	The	map	identifies	two	candidate	sweet	GRNs	per	side	of	the	LSO,	which	co-express	Gr43a	and	Gr64e	with	other	members	of	the	sweet	clade.	The	VCSO	also	contains	two	candidate	sweet	GRNs	per	side,	both	of	which	express	Gr43a-GAL4	and	Gr64e-GAL4.	Thus,	Gr43a-GAL4	and	Gr64e-GAL4	offer	two	tools	to	explore	the	physiological	and	behavioural	roles	of	the	pharyngeal	sense	organs.	Both	are	expressed	in	all	identified	candidate	pharyngeal	sweet	neurons,	as	well	as	GRNs	in	the	legs;	however,	Gr64e-GAL4	is	also	expressed	in	the	taste	hairs	and	taste	pegs	of	the	labellum,	while	Gr43a-GAL4	lacks	labellar	expression,	but	is	expressed	in	sugar-sensing	neurons	in	the	protocerebrum	(Miyamoto	et	al.,	2012;	Weiss	et	al.,	2011;	Ling	et	al.,	2014;	Wisotsky	et	al.,	2011).	2.3.2	Pharyngeal	GRNs	Detect	a	Variety	of	Sugars		 To	examine	the	role	of	sweet	taste	detected	by	the	pharyngeal	sense	organs,	we	began	by	measuring	the	response	properties	of	pharyngeal	neurons	expressing	Gr43a.	We	expressed	GCaMP3	under	the	control	of	Gr43a-GAL4	and	used	an	in	vivo	imaging	preparation	to	measure	the	calcium	responses	of	GRN	axon	terminals	in	the	SEZ	during	consumption	of	sweet	stimuli	(Figure	6).	Pharyngeal	Gr43a+	GRNs			 36		Figure	5.	Pharyngeal	GRNs	express	sweet	Grs	(a)	Cartoon	showing	the	positions	of	the	LSO	and	VCSO,	with	associated	images	of	each	structure	from	a	fly	expressing	GFP	under	control	of	Gr43a-GAL4.	Dotted	white	box	indicates	area	shown	in	e-f.	(b)	Axonal	projections	of	Gr43a-GAL4	(green)	and	Gr64fLexA	(red)	to	the	SEZ.	Overlapping	regions	are	from	LSO	projections.	(c)	Gr-GAL4-driven	GFP	expression	in	LSO.	Scale	bars	are	10	μm	in	c-d.	(d)	LSO	GFP	expression	from	flies	carrying	Gr43a-GAL4	and	indicated	second	Gr-GAL4	or	Gr64fLexA.	(e)	Gr-GAL4-driven	GFP	expression	in	VCSO.	(f)	VCSO	GFP	expression	from	flies	carrying	Gr43a-GAL4	and	indicated	Gr43a Gr61a Gr64a Gr64e Gr64fGr43a-Gal4+GrX-Gal4 or -LexAGr64a Gr64e Gr43a/Gr64fGr61aGr43aGr61aGr64aGr64eGr64fLSOGr43aGr64c*Gr64dGr64eVCSOLSOVCSOGr43aGr64fGr43a-Gal4+GrX-Gal4Gr43a Gr64c Gr64d Gr64eGr64c Gr64d Gr64eLSOVCSOabcedfgSEZFigure-1 (gordon)	 37	second	Gr-GAL4.	Scale	bars	are	5	μm	in	e-f.	Dotted	circles	indicate	the	cuticular	pore	of	sensilla.	(g)	Schematic	of	observed	sweet	Gr	expression	in	LSO	and	VCSO	GRNs.	Asterisk	indicates	that	Gr64c-	GAL4	expression	is	seen	in	only	one	neuron	per	side	of	the	VCSO. 														 38		Figure	6.	Pharyngeal	GRNs	respond	to	sweet	compounds	(a)	Immunofluorescence	of	anti-GFP	(green)	and	nc82	(magenta)	in	the	SEZ	of	flies	expressing	GCaMP3	under	control	of	Gr43a-GAL4.	Dotted	line	shows	area	imaged	in	panel	(b).	(b)	Single	optical	section	of	baseline	GCaMP3	fluorescence	in	pharyngeal	GRN	axon	terminals.	Scale	bars	are	20	μm	in	a-b.	(c)	Heat	map	showing	change	in	GCaMP3	fluorescence	during	ingestion	of	1	M	fructose.	(d)	Representative	trace	of	fluorescence	change	of	GCaMP3	in	Gr43a	axon	terminals	during	ingestion	of	1	M	fructose.	Arrow	indicates	3500 90 180270ΔF/F (%)20%5sGr43a-GAL4 ; UAS-GCaMP3ΔF/F (%)stima b cd e020406080100************** ***nsnswatersucrosefructoseglucoseglyceroltrehalosesorbitolarabinoseL-fucosenutritive, pharyngeal GRN activitynutritive, no pharyngeal GRN activitynon-nutritive, pharyngeal GRN activityGr43a+ pharyngeal projectionsFigure-2 (gordon)	 39	time	at	which	stimulus	is	applied	to	the	proboscis	to	initiate	feeding.	(e)	Peak	fluorescence	changes	of	GCaMP3	in	Gr43a	axon	terminals	during	ingestion	of	1	M	solutions	of	the	indicated	compounds.	Values	represent	mean	+/−	SEM.	for	n	=	5	flies	per	stimulus	(n	=	4	for	sorbitol),	with	data	collected	over	at	least	2	days.	Asterisks	indicate	significant	difference	from	water	by	one-way	ANOVA	with	Bonferroni	correction	for	multiple	comparisons:	**p	<	0.01,	***p	<	0.001,	ns	=	not	significant.													 40	exhibited	broad	tuning	to	sweet	compounds,	with	responses	to	both	nutritive	(sucrose,	fructose	and	glucose)	and	non-nutritive	(arabinose	and	L-fucose)	sugars,	as	well	as	the	sweet	sugar	alcohol	glycerol	(Figure	6e).	Consistent	with	the	reported	lack	of	Gr5a	expression	in	the	pharyngeal	sense	organs,	we	did	not	observe	responses	to	the	Gr5a	ligand	trehalose	(Wang	et	al.,	2004;	Dahanukar	et	al.,	2007;	Freeman,	Wisotsky	and	Dahanukar,	2014).	We	also	saw	no	response	to	the	nutritive	sugar	alcohol	sorbitol,	which	is	generally	considered	tasteless	to	the	fly.	Taken	together,	these	data	confirm	that,	as	predicted	by	their	Gr	expression,	a	subset	of	pharyngeal	GRNs	is	activated	by	the	ingestion	of	sweet	compounds.	In	addition,	it	is	notable	that	calcium	responses	in	pharyngeal	GRNs	were	sustained	much	longer	than	those	previously	observed	from	stimulation	of	labellar	GRNs	(Marella	et	al.,	2006;	Chu	et	al.,	2014).		2.3.3	poxn	Mutants	Retain	Functional	Pharyngeal	Sense	Organs		 To	investigate	the	behavioural	role	of	internal	pharyngeal	GRNs,	we	began	by	examining	null	mutants	for	the	transcription	factor	poxn.	poxn	mutants	lack	external	taste	bristles,	which	are	instead	transformed	into	mechanosensory	bristles	(Awasaki	and	Kimura,	1997).	This	has	resulted	in	the	use	of	poxn	mutants	as	taste-blind	flies	(Dus	et	al.,	2011;	Dus	et	al.,	2013).	However,	the	pharyngeal	sense	organs	of	poxn	mutants	have	been	reported	to	express	a	reporter	for	the	apparently	gustatory-specific	odorant-	binding	protein,	OBP56b,	raising	the	possibility	that	taste	sensilla	may	be	intact	in	these	tissues	(Galindo	and	Smith,	2001).	Moreover,	many	of	the	neurons	in	the	pharyngeal	organs	of	the	adult	originate	in	the	embryo		 41	and	persist	through	the	larval	stages	and	metamorphosis,	which	contrasts	with	the	general	principle	that	adult	sensory	structures	are	born	during	metamorphosis	and	suggests	that	the	pharyngeal	organs	may	depend	on	an	entirely	distinct	developmental	program	(Gendre	et	al.,	2004).	We,	therefore,	began	by	asking	whether	poxn	mutants	have	functional	pharyngeal	taste	sensilla.		Transheterozygotes	for	two	poxn	null	alleles	(poxn70	and	poxnΔM22-B5)	showed	normal	expression	of	Gr43a-GAL4	in	GRNs	of	the	LSO	and	VCSO	(Figure	7a,b).	In	addition,	the	brains	from	poxn	null	mutants	had	morphologically	normal	projections	from	pharyngeal	GRNs,	while	they	lacked	the	leg	projections	seen	in	otherwise	wild-type	flies	(Figure	7e,f).	Examining	Gr64e-GAL4	expression	in	the	poxn	background	confirmed	these	results	and	additionally	demonstrated	that	labellar	taste	peg	GRNs	are	also	present	in	poxn	mutants	(Figure	7c,d,g,h).	To	ask	whether	the	pharyngeal	GRNs	of	poxn	mutants	are	functional,	we	expressed	GCaMP3	under	the	control	of	Gr43a-GAL4	in	the	poxn	null	mutant	background,	and	measured	calcium	responses	during	ingestion	of	sweet	compounds.	We	observed	robust	activation	of	Gr43a+	pharyngeal	GRNs	on	ingestion	of	fructose	and	glycerol	but	not	sorbitol	(Figure	7i).	Due	to	the	technical	difficulties	in	stimulating	flies	lacking	external	taste	sensation	to	ingest	sweet	tastants	during	calcium	imaging,	we	did	not	expand	our	analysis	to	a	larger	panel	of	compounds.	However,	it	is	very	likely	that	poxn	Gr43a+	pharyngeal	neurons	retain	the	same	receptive	fields	seen	in	a	wild-type	background	(Figure	6e).	By	contrast,	Gr64e+	taste	peg	GRNs	did	not	respond	to	any	of	the	sweet	compounds	tested	but	were	activated	by	carbonated	water	(Figure	7j),	as	previously	reported	for	taste	pegs	in	a	wild-type	background			 42		Figure	7.	poxn	null	mutants	retain	functional	pharyngeal	sense	organs	(a,b)	Pharyngeal	GRNs	labeled	by	Gr43a-GAL4	driving	UAS-TdTomato	in	poxnΔM22-B5/+	heterozygotes	(a)	and	poxnΔM22-B5/poxn70	null	mutants	(b).	Arrows	point	to	GRNs	in	the	LSO	and	VCSO.	(c,d)	Labellar	GRNs	labeled	by	Gr64e-GAL4	driving	UAS-TdTomato	in	poxnΔM22-B5/+	heterozygotes	(a)	and	poxnΔM22-B5/poxn70	null	mutants	(b).	Arrows	point	to	taste	peg	GRNs	in	d.	(e-h)	Immunofluorescence	of	anti-GFP	(green)	and	nc82	(magenta)	in	the	brains	of	poxnΔM22-B5/+	heterozygotes	(e,g)	and	poxnΔM22-B5/poxn70	null	mutants	(f,h)	expressing	GCaMP3	under	control	of	Gr43a-GAL4	(e,f)	or	Gr64e-GAL4	(g,h).	Arrows	point	to	GRN	projections	originating	from	the	various	body	locations.	(i-j)	Peak	fluorescence	changes	of	GCaMP3	in	Gr43a-GAL4	pharyngeal	(i)	or	Gr64e-GAL4	taste	peg	(j)	axon	terminals	in	poxnΔM22-B5/poxn70	null	mutants	during	ingestion	of	the	indicated	compounds.	Values	represent	mean	+/−	SEM.	for	n	=	5	flies,	with	data	collected	over	at	least	2	days.	Asterisks	indicate	significant	difference	from	sorbitol	(i)	or	water	(j)	by	one	way	ANOVA	with	GCaMP ΔF/F (%)poxnΔM22-B5 /+poxnΔM22-B5 /poxn70Gr43a>GCaMP3Gr43a>TdTomabcdGr64e>GCaMP3sorbitolfructoseglycerol020406080** **watersucrosefructoseglucoseglyceroltrehalosesorbitolarabinoseL-fucosecarbonated water05101520***gGr64e>TdTomGCaMP ΔF/F (%)Gr64e taste peg projections(poxn mutant)Gr43a pharyngeal GRNs(poxn mutant)ef hijpharynxpharynxpharynxpharynxlegslabellartaste hairstastepegstastepegsLSOLSOVCSOVCSOtaste pegsnsns ns nsnsns nsnsFigure-3 (gordon)	 43	Bonferroni	correction	for	multiple	comparisons:	**p	<	0.01,	***p	<	0.001,	ns	=	not	significant.	Scale	bars	are	100	μm.																	 44	(Fischler	et	al.,	2007).	Together,	these	data	demonstrate	unequivocally	that	poxn	mutants	retain	functional	pharyngeal	taste	sensilla	that	are	capable	of	responding	to	sweet	compounds.	Moreover,	while	functional	taste	peg	GRNs	also	exist	in	these	mutants,	they	do	not	respond	to	sweet	compounds,	and	thus	are	unlikely	to	affect	our	subsequent	behavioural	analyses	of	sweet	taste	preferences	driven	by	the	pharyngeal	sense	organs.		2.3.3	poxn	Mutants	Prefer	Sweet	Compounds		 Given	that	poxn	mutants	have	functional	pharyngeal	sweet	taste,	but	apparently	lack	all	peripheral	sweet	taste	sensation,	we	asked	whether	pharyngeal	taste	is	sufficient	to	direct	consumption	of	a	variety	of	sweet	compounds.	First,	we	verified	that	poxn	null	mutants	lack	peripheral	sweet	taste	responses	by	performing	PER	(Dethier,	1976;	Gordon	and	Scott,	2009;	Rajashekhar	and	Singh,	1994).	We	used	ribose	as	a	negative	control	stimulus,	as	it	evokes	no	significant	response	from	L-type	taste	sensilla	on	the	labellum	(Dahanukar	et	al.,	2007).	However,	our	observation	that	ribose	elicits	a	mean	PER	response	of	~20%	in	control	flies	suggests	that	it	may	stimulate	some	appetitive	taste	neurons	at	a	low	level	(Figure	8).	Alternatively,	these	responses	could	be	the	result	of	osmotic	differences	between	the	ribose	solution	and	water	used	to	water	satiate	the	flies	before	testing	(Cameron	et	al.,	2010;	Chen,	Wang	and	Wang,	2010).	Nevertheless,	control	flies	(w1118)	showed	robust	PER	to	all	sweet	compounds	tested,	responding	at	frequencies	significantly	higher	than	those	elicited	by	ribose	(Figure	8a,c).	By	contrast,	PER	was	entirely	abolished	in	poxn	mutants	following	stimulation	of	either	the	labellum	or	the	tarsal			 45		Figure	8.	poxn	null	mutants	lack	peripheral	taste	responses	but	prefer	sweet	compounds	(a-d)	PER	responses	of	w1118	(a,c)	and	poxnΔM22-B5/poxn70	null	mutant	PER (%)PER (%)PER (%)a bc de fPER (%)Feeding preference (PI)Binary choice feedingFeeding preference (PI)w1118 poxn70/poxnΔM22-B5ribosesucrosefructoseglucoseglyceroltrehalosearabinoseL-fucose020406080100ribosesucrosefructoseglucoseglyceroltrehalosearabinoseL-fucose020406080100ribosesucrosefructoseglucoseglyceroltrehalosearabinoseL-fucose020406080100ribosesucrosefructoseglucoseglyceroltrehalosearabinoseL-fucose020406080100Tarsal PERLabellar PERw1118 poxn70/poxnΔM22-B5w1118 poxn70/poxnΔM22-B5*** *** *** *** ********* ********** *** *** *** ****************** ********* *** *** ******** **ribosesucrosefructoseglucoseglyceroltrehalosesorbitolarabinoseL-fucose-1.0-0.50.00.51.0ribosesucrosefructoseglucoseglyceroltrehalosesorbitolarabinoseL-fucose-1.0-0.50.00.51.0sugar plus agar sugar plus agaragar alone agar alone	 46	(b,d)	flies	following	stimulation	of	the	tarsi	(a,b)	or	labellum	(c,d)	with	the	indicated	compounds.	Values	represent	percentage	of	stimulations	resulting	in	a	positive	response;	error	bars	show	95%	binomial	confidence	interval,	and	asterisks	indicate	significant	difference	from	ribose	stimulation:	*	p	<	0.05,	**	p	<	0.01,	***	p	<	0.001	by	Fisher's	exact	test.	n	=	17-	50	flies	for	w1118	tarsal	PER,	n	=	17-33	flies	for	poxn	tarsal	PER,	n	=	9-19	flies	for	w1118	labellar	PER,	and	n	=	9-17	flies	for	poxn	labellar	PER.	(e,f)	Preference	of	w1118	(e)	and	poxnΔM22-B5/poxn70	null	mutant	flies	(f)	for	100	mM	solutions	of	the	indicated	compounds	in	1%	agar	versus	agar	alone.	Values	represent	mean	+/−	SEM.	for	n	=	10	groups	of	10	flies	each,	with	independent	replicates	performed	over	at	least	2	days.	Asterisks	indicate	significant	difference	from	ribose	preference	by	one-way	ANOVA	with	Bonferroni	correction	for	multiple	comparisons:	**p	<	0.01,	***p	<	0.001.										 47	segment	of	the	legs	(Figure	8b,d).		Next,	we	subjected	poxn	mutants	and	controls	to	a	variation	of	the	binary	feeding	choice	paradigm	in	which	groups	of	food-deprived	flies	were	allowed	to	feed	for	2	h	on	drops	of	1%	agar	with	or	without	a	given	test	compound.	Again,	we	used	ribose	as	a	negative	control	because	it	has	little	to	no	taste	response	or	nutritional	value	(Dahanukar	et	al.,	2007;	Stafford	et	al.,	2012).	Control	flies	showed	a	small	preference	for	ribose	(PI	=	0.23±0.09)	over	plain	agar,	which	may	be	due	to	weak	taste	responses	or	the	osmolarity	differences	discussed	above	(Figure	8e).	This	effect	was	reduced	in	poxn	mutants	(PI	=	0.06±0.06).		As	expected,	poxn	mutants	and	controls	displayed	robust	preference	for	sucrose,	fructose,	glucose	and	glycerol	(Figure	8f).	All	of	these	compounds	are	nutritional	(Burke	and	Waddell,	2011;	Fujita	and	Tanimura,	2011;	Stafford	et	al.,	2011)	and	activate	Gr43a+	pharyngeal	GRNs	(Figure	6e).	The	potential	role	of	nutritional	content	in	guiding	feeding	decisions	is	supported	by	the	observation	that	poxn	mutants	preferred	two	compounds,	trehalose	and	sorbitol,	that	are	caloric	but	did	not	stimulate	pharyngeal	GRNs	in	our	experiments	(Figure	8f).	Importantly,	poxn	mutants	also	strongly	preferred	arabinose	and	L-fucose,	both	of	which	stimulate	sugar	taste	but	offer	no	caloric	value	(Dahanukar	et	al.,	2007;	Burke	and	Waddell,	2011;	Fujita	and	Tanimura,	2011;	Stafford	et	al.,	2012).	These	data	strongly	suggest	that	activation	of	pharyngeal	taste	neurons	is	sufficient	to	drive	consumption	behaviour,	and	that	this	activation	accounts	for	at	least	part	of	the	previously	reported	preference	of	poxn	mutants	for	caloric	sugars	(Dus	et	al.,	2011;		 48	Dus	et	al.,	2013).		To	further	examine	the	role	of	pharyngeal	taste	in	driving	the	preference	of	poxn	mutants	for	sweet	compounds,	we	silenced	Gr64e+	pharyngeal	GRNs	in	the	poxn	mutant	background	through	expression	of	the	inward	rectifying	potassium	channel	KIR2.1	(Baines	et	al.,	2001).	Importantly,	the	insertion	of	Gr64e-GAL4	used	(Gr64e-GAL4II)	lacks	expression	in	the	taste	pegs	(Figure	9a),	meaning	that	silencing	specifically	affects	pharyngeal	GRNs.	Silencing	of	Gr64e+	GRN	function	in	poxn	mutants	resulted	in	a	complete	loss	of	preference	for	arabinose	and	L-fucose	over	agar	alone,	indicating	that	Gr64e+	pharyngeal	GRNs	are	necessary	for	the	preference	for	non-caloric	sweet	sugars	in	poxn	mutants	(Figure	9b).	This	suggests	that	Gr64e-GAL4	likely	labels	the	complete	set	of	pharyngeal	sweet	GRNs,	and	that	poxn	mutants	lacking	Gr64e+	pharyngeal	GRN	function	may	be	sweet-blind.		Since	poxn,	Gr64e-silenced	flies	lack	both	peripheral	and	identified	pharyngeal	sweet	taste,	we	used	them	to	re-evaluate	the	role	of	post-ingestive	nutrient	sensing	in	driving	preference	for	a	number	of	sugars.	Silencing	of	pharyngeal	taste	caused	only	a	mild,	nonsignificant	decrease	in	the	preference	of	poxn	mutant	flies	for	sorbitol	(Figure	9b),	consistent	with	previously	reported	post-	ingestive	mechanisms	promoting	consumption	of	this	compound,	and	its	reported	tastelessness	(Miyamoto	et	al.,	2012).	However,	it	is	worth	noting	that	the	preference	for	sorbitol	in	these	experiments	was	weak,	so	it	is	difficult	to	confidently	ascribe	a	taste-independent	effect.	In	contrast	to	sorbitol,	the	preference	for	trehalose	was	significantly	reduced	following	silencing	of	Gr64e+	pharyngeal			 49		Figure	9.	Pharyngeal	GRNs	are	necessary	for	the	preference	of	poxn	mutants	for	sweet	compounds	(a)	Immunofluorescence	of	anti-GFP	(green)	and	nc82	(magenta),	showing	expression	of	the	Gr64e-GAL4II	and	Gr43aGAL4	drivers	used	in	the	behavioural	experiments	shown.	Gr64e-GAL4	is	shown	in	a	poxn	null	mutant	background,	while	Gr43aGAL4	is	in	a	poxn/+	heterozygous	background.	Scale	bars	are	100	μm.	(b)	Preference	of	indicated	genotypes	for	100	mM	solutions	of	the	specified	compounds	in	1%	agar	(positive)	versus	agar	alone	(negative).	(c)	Temporal	consumption	characteristics	of	the	indicated	genotypes	in	response	to	stimulation	arabinose-1.0-0.50.00.51.0ns******L-fucose-1.0-0.50.00.51.0ns******sorbitol-1.0-0.50.00.51.0***nstrehalose-1.0-0.50.00.51.0****nssucrose-1.0-0.50.00.51.0ns******fructose-1.0-0.50.00.51.0ns****glucose-1.0-0.50.00.51.0ns******glycerol-1.0-0.50.00.51.0*******poxn70/poxnΔM22-B5 ; UAS-KIR2.1/+poxn70/poxnΔM22-B5, Gr64e-GAL4II ; UAS-KIR2.1/+poxn70/poxnΔM22-B5, Gr64e-GAL4II ; +/+poxn70/poxnΔM22-B5, Gr43aGAL4 ; UAS-KIR2.1/+poxn70/poxnΔM22-B5, Gr43aGAL4 ; +/+ribose-1.0-0.50.00.51.0nsnsnsFeeding preference (PI)Gr43aGAL4 expressionGr64e-GAL4II expressionpoxn mutantfirst bout020406080Consumption time (s)***all bouts020406080Consumption time (s)**Feeding preference (PI)012345Number of bouts***numberof boutscontrol sweet, not nutritive not sweet (pharynx), nutritivesweet and nutritiveabcarabinose arabinose arabinoseFigure-5 (gordon)	 50	with	50	mM	arabinose.	Values	represent	mean	+/−	SEM.	for	n	=	10	groups	of	10	flies	each	in	b	and	n	=	29-60	flies	in	c,	with	independent	replicates	performed	over	at	least	2	days.	Asterisks	indicate	significant	difference	by	one-way	ANOVA	with	Bonferroni	correction	for	multiple	comparisons:	*p	<	0.05,	**p	<	0.01,	***p	<	0.001,	ns	=	not	significant.															 51	GRNs,	suggesting	that	this	sugar	may	stimulate	pharyngeal	GRNs	at	a	level	below	the	sensitivity	of	our	calcium	imaging	but	enough	to	affect	behaviour.	Strikingly,	silencing	Gr64e+	pharyngeal	GRNs	markedly	reduced	the	preference	of	poxn	flies	for	all	four	sweet	and	nutritive	compounds	tested	(Figure	9b).	These	data	suggest	that	taste	is	the	dominant	driver	of	feeding	preference	in	our	short-term	binary	choice	assay,	and,	in	contrast	to	previous	reports	(Dus	et	al.,	2011;	Dus	et	al.,	2013),	taste-independent	post-ingestive	sugar	sensing	has	little,	if	any,	effect	on	consumption	behaviour	in	this	context.		To	further	probe	the	factors	influencing	sugar	preference,	we	repeated	the	silencing	experiment	using	a	GAL4	knock-in	allele	of	Gr43a	that	is	expressed	in	the	same	complement	of	pharyngeal	GRNs	as	Gr64e-GAL4II	but	also	shows	additional	expression	in	identified	sugar-sensing	neurons	in	the	protocerebrum	and	a	population	of	neurons	in	the	proventricular	ganglion	(Miyamoto	et	al.,	2012).	Consistent	with	a	role	for	Gr43a+	brain	neurons	in	promoting	the	ingestion	of	sorbitol,	we	observed	a	complete	lack	of	sorbitol	preference	in	Gr43a-silenced	poxn	mutants	(Figure	9b).	Notably,	this	was	a	significant	reduction	compared	with	both	genetic	controls	and	Gr64e-silenced	flies.	Interestingly,	while	the	behavioural	assay	used	may	lack	the	resolution	to	tease	out	small	differences	between	Gr64e	and	Gr43a	silencing,	we	observed	a	trend	towards	increased	preference	for	sweet	and	nutritive	sugars	in	Gr43a-silenced	mutants	compared	with	Gr64e-silenced	flies.	This	trend,	which	was	nonsignificant	for	sucrose	and	fructose	but	significant	for	glycerol,	could	reflect	weaker	silencing	with	the	Gr43aGAL4	driver,	a	difference	in	genetic		 52	background,	or	the	previously	reported	role	for	Gr43a+	brain	neurons	in	promoting	feeding	termination	of	nutritive	sweet	sugars	in	some	contexts	(Miyamoto	et	al.,	2012).	Nevertheless,	overall,	our	silencing	results	strongly	support	the	conclusion	that	short-term	sugar	preferences	are	primarily	taste-mediated,	even	in	poxn	mutants	lacking	external	gustatory	sensilla.		2.3.3	Pharyngeal	Sweet	GRNs	Sustain	Ingestion		 On	the	basis	of	the	anatomical	position	of	pharyngeal	GRNs,	we	wondered	whether	they	might	affect	food	preference	by	preferentially	sustaining	the	ingestion	of	sweet	compounds.	To	test	this,	we	subjected	poxn,	Gr64e-silenced	flies	to	a	temporal	consumption	assay	(Pool	et	al.,	2014)	and	compared	their	behaviour	with	that	of	the	poxn	controls	with	intact	pharyngeal	GRN	function	(Figure	9c).	We	found	that	poxn	flies	with	silenced	pharyngeal	GRNs	displayed	a	dramatic	reduction	in	the	duration	of	consumption	during	the	first	bout	of	feeding	on	a	solution	of	sweet,	non-nutritive	arabinose	compared	with	non-silenced	controls,	as	well	as	a	reduction	in	total	feeding	time	over	multiple	bouts	and	an	elevated	number	of	feeding	bouts	before	‘satiety’	(defined	here	as	the	refusal	to	initiate	further	feeding).	These	data	support	the	notion	that	pharyngeal	GRNs	indeed	function	to	sustain	ingestion	of	sweet,	appetitive	food	sources.		2.4	DISCUSSION	Much	is	known	about	sugar	sensing	through	peripheral	sweet	taste	neurons	in	the	fly’s	legs	and	labellum,	and	there	is	growing	interest	in	mechanisms	that	sense		 53	dietary	sugars	following	ingestion	(Itskov	and	Ribeiro,	2013;	Miyamoto,	Wright	and	Amrein,	2013).	Sugar	sensing	by	the	pharyngeal	sense	organs,	however,	has	remained	virtually	unexplored	due	to	their	inaccessibility	to	electrophysiology	and	the	lack	of	genetic	tools	to	specifically	manipulate	their	function.	This	represents	an	important	gap	in	our	understanding	of	how	sugar	feeding	is	regulated,	since	the	pharyngeal	sense	organs	must	operate	following	the	initiation	of	feeding,	but	before	ingestion.	They	are,	therefore,	poised	to	provide	feedback	during	feeding,	contributing	to	the	ongoing	decision	of	whether	to	maintain	or	terminate	ingestion.		Our	calcium	imaging	data	demonstrated	that	the	receptive	fields	of	pharyngeal	sweet	GRNs	are	in	line	with	predictions	based	on	the	receptor	expression	and	specificities	(Dahanukar	et	al.,	2007;	Freeman,	Wisotsky	and	Dahanukar,	2014;	Jiao,	Moon	and	Montell,	2007;	Slone,	Daniels	and	Amrein,	2007;	Miyamoto	et	al.,	2012;	Jiao	et	al.,	2008;	Miyamoto	et	al.,	2013).	All	putative	pharyngeal	sweet	GRNs	co-express	Gr43a	and	Gr64e,	which	are	receptors	tuned	to	fructose	and	glycerol,	respectively,	and	we	observed	robust	calcium	responses	to	those	two	compounds.	Expression	of	Gr61a	in	the	LSO	likely	accounts	for	the	response	to	glucose,	since	Gr61a-dependent	glucose	responses	are	seen	in	tarsal	GRNs	lacking	Gr5a	(Miyamoto	et	al.,	2013).	Likewise,	sucrose	and	L-fucose	responses	can	be	accounted	for	by	the	expression	of	Gr64a	in	the	LSO	(Dahanukar	et	al.,	2007;	Freeman,	Wisotsky	and	Dahanukar,	2014;	Jiao,	Moon	and	Montell,	2007).	Notably,	we	did	not	observe	responses	to	trehalose,	consistent	with	the	lack	of	Gr5a	expression,	which	is	necessary	for	trehalose	responses	in	the	labellum	(Dahanukar	et	al.,	2007).	However,	our	behavioural	data	suggested	that	Gr64e+	pharyngeal	GRNs		 54	mediate	some	attraction	to	trehalose.	This	apparent	discrepancy	could	be	explained	if	trehalose	excites	sweet	pharyngeal	GRNs	at	a	level	too	low	to	observe	significant	calcium	responses	in	our	preparation,	a	possibility	supported	by	previous	reports	that	overexpression	of	Gr43a	or	Gr64e	confers	trehalose	sensitivity	to	tarsal	GRNs	or	ab1C	olfactory	receptor	neurons,	respectively	(Freeman,	Wisotsky	and	Dahanukar,	2014;	Miyamoto	et	al.,	2012).	 Using	poxn	mutants	lacking	peripheral	taste,	we	demonstrated	that	pharyngeal	sweet	GRNs	are	sufficient	to	drive	preference	for	sweet	compounds	in	binary	choice	feeding	assays.	These	results	indicate	that	appetitive	taste	is	not	absolutely	necessary	for	feeding	initiation,	and	that	flies	must	‘sample’	potential	food	sources	in	the	absence	of	sweet	taste	input	from	the	legs	and	labellum.	Moreover,	we	provide	evidence	that	activation	of	pharyngeal	sweet	GRNs	prolongs	feeding	by	providing	a	positive	feedback	signal	to	sustain	ingestion.	This	proposed	role	for	pharyngeal	GRN	function	is	also	consistent	with	their	physiology,	which	exhibits	prolonged	activation	during	consumption	of	sweet	compounds	compared	with	previously	reported	responses	in	the	labellum	(Marella	et	al.,	2006;	Chu	et	al.,	2014).	It	is	likely	that	this	prolonged	activation	functions	to	maintain	ingestion	during	feeding	bouts	lasting	up	to	several	seconds.	In	the	future,	it	will	be	interesting	to	examine	whether	pharyngeal	sweet	taste	plays	any	specific	roles	outside	of	feeding.	For	example,	pharyngeal	bitter	GRNs	appear	to	be	important	in	selection	of	egg	laying	substrates	(Joseph	and	Heberlein,	2012).		A	key	component	of	our	work	is	the	demonstration	that	poxn	mutants	have	a		 55	functional	pharyngeal	taste	system	that	is	critical	in	guiding	their	preference	for	sweet	compounds,	which	therefore	precludes	their	experimental	use	as	‘taste-blind’	flies.	The	behavioural	preference	we	observed	of	poxn	mutant	flies	for	the	non-nutritional	sweetners	L-fucose	and	arabinose	contrasts	with	the	conclusion	reached	by	Dus	et	al.	2011	who	performed	a	similar	experiment	with	the	artificial	sweetner	sucralose.	One	possible	explanation	for	this	difference	is	that	arabinose	and	L-fucose	may	activate	pharyngeal	sweet	GRNs	more	potently	than	sucralose.	Another	possible	source	of	the	discrepancy	is	that	Dus	et	al.	2011	analysed	their	feeding	data	by	plotting	the	total	proportion	of	flies	to	eat	each	option	in	the	binary	choice	assay,	while	we	analysed	relative	preference	between	the	options.	Nevertheless,	the	strong	dependence	of	poxn	mutants	on	Gr64e+	GRNs	for	preferred	consumption	of	both	nutritive	and	non-nutritive	sweeteners	demonstrates	that	the	majority	of	the	preference	of	these	mutants	for	sweet	compounds	is	mediated	by	pharyngeal	taste	sensitivity.		By	silencing	Gr64e+	GRNs	in	a	poxn	mutant	background,	we	created	for	the	first	time	a	fly	that	may	completely	lack	sweet	taste,	allowing	one	to	re-evaluate	the	taste-independent	role	for	nutrient-sensing	mechanisms	in	behaviour.	While	we	did	observe	some	evidence	for	taste-independent	selection	of	nutritive	carbohydrates,	the	observed	effect	was	much	weaker	than	previously	suggested	(Dus	et	al.,	2011;	Dus	et	al.,	2013).	Although	ample	additional	evidence	supports	the	existence	of	taste-independent	carbohydrate	sensing	(Miyamoto	et	al.,	2012;	Burke	and	Wadell,	2011;	Burke	et	al.,	2012;	Fujita	and	Tanimura,	2011;	Stafford	et	al.,	2012),	its	specific	role	in	regulating	feeding	remains	unclear.	Why	do	we	observe	such	weak		 56	preference	of	putatively	sweet-blind	flies	for	nutritive	sugars?	One	possibility	is	the	particular	behavioural	assay	used,	which	operates	over	only	2	h.	We	have	previously	reported	increasing	effects	of	caloric	content	on	feeding	preferences	over	the	course	of	a	16-h	assay	(Stafford	et	al.,	2012).	It	will	be	instructive	to	re-evaluate	the	feeding	behaviour	of	poxn,	sweet	GRN-silenced	flies	over	longer	time	periods	using	different	behavioural	paradigms.	Our	newly	established	putatively	sweet-blind	flies	also	afford	the	opportunity	to	examine	potential	nutrient-sensing	mechanisms	in	a	taste-independent	context.	For	example,	by	comparing	Gr43a-silenced	with	Gr64e-silenced	flies	in	a	poxn	mutant	background,	we	were	able	to	observe	effects	for	non-taste	Gr43a+	populations	that	are	largely	consistent	with	those	previously	reported	(Miyamoto	et	al.,	2012).	Further	evaluation	of	these	and	other	putative	nutrient-sensing	cell	populations	in	a	sweet	taste-blind	background	will	continue	to	shed	light	on	the	apparently	complex	interactions	between	the	taste-dependent	and	taste-independent	mechanisms	that	ultimately	guide	critical	feeding	decisions.											 57	CHAPTER	3	 	 STARVATION-INDUCED	DEPOTENTIATION	OF	BITTER	TASTE	IN	DROSOPHILA	3.1	INTRODUCTION		 Animals	depend	on	the	appropriate	interpretation	of	sensory	information	to	make	favorable	behavioural	decisions.	To	achieve	this,	neural	circuits	underlying	innate	behaviours,	such	as	feeding	and	mating,	must	possess	some	intrinsic	flexibility	to	reflect	changing	internal	states.	Drosophila	offers	an	extensive	genetic	toolbox	to	parse	the	mechanisms	of	how	internal	motivational	states	modify	neural	circuit	function	to	achieve	behavioural	plasticity.		 Starvation	induces	a	powerful	internal	state	that	drives	extensive	behavioural	modifications.	Notably,	starvation	promotes	food	seeking	and	consumption	at	the	expense	of	behaviours	that	satisfy	other	essential	needs	like	sleep	(Farhadian	et	al.,	2012;	Keene	et	al.,	2010;	Root	et	al.,	2011).	This	behavioural	shift	is	driven	in	part	by	changes	in	chemosensory	processing.	For	example,	starvation	potentiates	or	suppresses	sensory	neuron	output	in	specific	glomeruli	of	the	fly	olfactory	system	through	the	activity	of	two	distinct	neuropeptides	–	sNPF	and	tachykinin	(DTK),	respectively	(Root	et	al.,	2011;	Lebreton	et	al.,	2015;	Ko	et	al.,	2015).	Moreover,	dNPF	acts	as	a	gate	for	the	starvation-dependent	expression	of	appetitive	olfactory	memories	(Krashes	et	al.,	2009).	Thus,	starvation	affects	food-seeking	behaviours	through	modulation	of	both	peripheral	and	central	olfactory	neurons.		 While	olfaction	drives	long-range	food	search	behaviours,	taste	serves	as	a	final	checkpoint	for	evaluating	the	suitability	of	foods	for	consumption.	In	the	fly		 58	taste	system,	segregated	classes	of	GRNs	respond	to	particular	classes	of	tastants	(Meunier	et	al.,	2003;	Marella	et	al.,	2006).	The	two	most	well	characterized	GRN	types	are	sweet	and	bitter,	each	of	which	expresses	distinct	members	of	the	Gr	family	(Wang	et	al.,	2004;	Thorne	et	al.,	2004;	Weiss	et	al.,	2011).	Sweet	GRNs	express	combinations	of	nine	identified	sweet	Grs,	including	Gr5a	and	Gr64f,	and	activation	of	these	neurons	promotes	feeding	behaviours	such	as	PER	(Wang	et	al.,	2004;	Gordon	and	Scott,	2009;	Fujii	et	al.,	2015;	Slone,	Daniels	and	Amrein,	2007;	Jiao	et	al.,	2008).	Bitter	GRNs	express	Gr66a	along	with	combinations	of	approximately	32	additional	bitter	Grs	(Wang	et	al.,	2004;	Thorne	et	al.,	2004;	Weiss	et	al.,	2011).	Activation	of	bitter	GRNs	drives	avoidance	behaviour	and	terminates	PER,	preventing	flies	from	ingesting	toxic	food	(Meunier	et	al.,	2003;	Marella	et	al.,	2006;	Keene	and	Masek,	2012).	Both	sweet	and	bitter	GRNs	project	their	axons	into	distinct	areas	of	the	SEZ,	suggesting	that	taste	information	is	segregated	by	modality	at	the	first	synapse	in	the	fly	brain	(Wang	et	al.,	2004;	Thorne	et	al.,	2004;	Kwon	et	al.,	2014).		 Like	olfaction,	taste	sensory	input	is	modulated	by	satiety	state.	Starvation	potentiates	sweet	GRN	synaptic	output,	while	independently	suppressing	the	synaptic	output	of	bitter	GRNs.	This	reciprocal	modulation	of	sweet	and	bitter	GRNs	depends	on	the	activity	of	distinct	neuropeptides:	dNPF	for	sweet,	and	sNPF	and	AKH	for	bitter	(Inagaki,	Panse	and	Anderson,	2014).	Downstream	of	dNPF,	sweet	GRN	potentiation	is	mediated	by	dopamine	signaling	through	the	dopamine/ecdysteroid	receptor,	DopEcR	(Srivastava	et	al.,	2005;	Inagaki	et	al.,	2012).	Starvation	also	enhances	the	firing	of	a	single	modulatory	dopaminergic		 59	neuron	in	the	SEZ,	TH-VUM,	the	activation	of	which	is	sufficient	to	induce	PER	(Marella	et	al.,	2012).	Although	it	has	never	been	formally	demonstrated,	it	is	appealing	to	infer	that	TH-VUM	is	the	source	of	the	direct	dopaminergic	signal	to	sweet	GRNs,	and	possibly	the	target	of	dNPF	regulation.			 	The	direct	source	of	bitter	GRN	modulation	is	unknown.	It	has	been	suggested	that	AKH	acts	upstream	of	sNPF,	which	signals	through	a	GABAergic	intermediate	to	suppress	bitter	sensitivity	(Inagaki,	Panse	and	Anderson,	2014).	However,	neither	the	signals	that	act	on	bitter	GRNs	nor	any	starvation-regulated	neurons	in	the	bitter	circuit	have	been	identified.				 Here	we	describe	a	small	cluster	of	interneurons	that	produce	octopamine	(OA)	and	tyramine	(TA),	named	OA-VLs	(ventrolateral	cluster	of	octopaminergic	neurons	(Busch	et	al.,	2009)),	which	act	to	modulate	bitter	GRN	output	during	starvation.	OA-VL	projections	are	in	close	proximity	to	bitter	GRN	axon	terminals	in	the	SEZ	and	have	presynaptic	terminals	in	the	same	region.	Patch	clamp	recordings	show	that	OA-VL	firing	decreases	significantly	as	flies	become	starved,	suggesting	that	their	activity	may	provide	a	positive	signal	to	potentiate	bitter	GRN	output	in	the	fed	state.	Consistent	with	this	model,	genetic	silencing	of	OA-VL	activity	in	fed	flies	mimics	the	behavioural	and	physiological	effects	of	starvation	on	the	bitter	circuit	–	bitter	GRN	calcium	responses	are	suppressed,	and	flies	become	less	sensitive	to	the	inhibitory	effects	of	bitter	on	PER.	Moreover,	knockdown	of	Octopamine-Tyramine	receptor	(Oct-TyrR)	in	bitter	GRNs	also	suppresses	bitter	sensitivity,	suggesting	direct	modulation	of	bitter	sensory	neuron	output	by	OA-VLs.	Finally,	pharmacological	addition	of	OA	or	TA	to	the	brain	is	sufficient	to	potentiate		 60	bitter	GRN	output	in	starved,	but	not	fed,	flies.	Thus,	OA-VL	neurons	may	represent	the	missing	link	between	peptidergic	hunger	signals	and	bitter	modulation,	allowing	starved	flies	to	consume	suboptimal	foods.	3.2	MATERIALS	AND	METHODS		3.2.1	Fly	Stocks		 Fly	stocks	were	raised	on	standard	cornmeal	fly	food	at	25°C	and	70%	humidity.	The	following	lines	were	used:	VT026002-Gal4,	VT049128-Gal4,	VT045791-Gal4,	w1118	control	(from	the	Vienna	Tile	collection);	GMR38A06-Gal4	(from	the	Janelia	Rubin	Gal4	Collection);	UAS-Oct-TyrRRNAi	(Stock	Number	26877	VDRC);	Gr5a-LexA::VP16,	UAS-CD4::spGFP1-10,	LexAop-CD4::spGFP11	(Gordon	and	Scott,	2009);	UAS-mCD8::GFP	(Lee	and	Luo,	1999);	UAS-synaptotagmin-GFP	(Zhang,	Rodesch	and	Broadie,	2002);	hs-FLP,	MKRS	(Bloomington	stock	center);	UAS-GCaMP6f		and	LexAop-GCaMP6f	(Chen	et	al.,	2013);	UAS-ORK	(Nitabach	et	al.,	2004);	Gr66a-Gal4	(Wang	et	al.,	2004);	Gr66a-LexA::VP16	(Thistle	et	al.,	2012);	UAS-KIR2.1,	tub-Gal80ts	(Baines	et	al.,	2001);	and	PBDPGal4U,	an	enhancerless	Gal4	line	from	the	Janelia	collection	used	as	a	control	with	no	Gal4	expression	(Pfeiffer	et	al.,	2008).	3.2.2	Immunohistochemistry		 Immunohistochemistry	was	carried	out	as	described	previously	(Gordon	and	Scott,	2009).	For	GRASP,	the	primary	antibodies	used	were	mouse	anti-GFP	(1:100,	Sigma,	cat#	G6539)	and	rat	anti-CD8	(1:500,	Cedarlane,	cat#	CL168AP).	Other	primary	antibodies	used	were	rabbit	anti-GFP	(1:1000,	Invitrogen,	cat#	A11122),		 61	mouse	anti-nc82	(1:50,	Developmental	Studies	Hybridoma	Bank),	rabbit	anti-DsRed	(1:2000,	Clontech,	cat#	632496)	and	rabbit	anti-tdc2	(1:2000,	Covalab,	cat#	pab0822-P).	The	secondary	antibodies	used	were	goat	anti-mouse	Alexa-488	(Invitrogen,	cat#	A11029),	goat	anti-rabbit	Alexa-488	(Invitrogen,	cat#	A11008),	goat	anti-mouse	Alexa-568	(Invitrogen,	cat#	A11036),	and	goat	anti-rat	Alexa-568	(Invitrogen,	cat#	A11077).	Images	are	maximum	intensity	projections	of	confocal	z-stacks	acquired	using	a	Leica	SP5	II	confocal	microscope	with	the	25x	water	immersion	objective	or	63x	oil	immersion	objective.		3.2.3	Physiology		 Both	calcium	imaging	and	cell-attached	recordings	were	performed	on	female	flies	aged	2	–	12	days	were	used.	Flies	were	anaesthetized	using	CO2	and	the	legs	were	removed	using	scissors.	Flies	were	mounted	by	the	cervix	into	individual	collars	of	a	custom	chamber.	Nail	polish	was	applied	behind	the	head	in	a	thin	layer	to	hold	the	fly	in	place.	A	dental	waxer	was	used	to	apply	melted	wax	to	the	sides	of	the	extended	proboscis,	adhering	it	to	the	rim	of	the	chamber.		3.2.3.1	GCaMP	Imaging		 For	calcium	imaging,	the	antennae	and	cuticle	covering	access	to	the	SEZ	were	removed	using	forceps.	AHL	buffer	with	ribose	(Liu	et	al.,	2012)	was	used	to	cover	the	open	brain.	A	coverslip	was	inserted	into	a	slot	of	the	chamber,	keeping	the	proboscis	free	from	the	buffer	solution	to	allow	stimulation	of	the	labellum	with	tastants.	GCaMP6f	fluorescence	was	monitored	using	a	Leica	SP5	II	scanning	confocal	with	a	tandem	scanner	and	HyD	detector.	The	SEZ	was	viewed	with	the	25x		 62	water	objective	and	an	electronic	zoom	of	eight.	Images	were	acquired	at	a	speed	of	8,000	lines	per	second	with	a	line	average	of	four,	resulting	in	collection	time	of	60	ms	per	frame	at	a	resolution	of	512	x	200	pixels.	The	pinhole	was	opened	to	2.68	-	4	AU.	Using	a	manual	micromanipulator,	a	glass	pipette	was	used	to	briefly	apply	tastant	stimuli	to	the	proboscis	after	acquiring	5	–	10	seconds	of	baseline	fluorescence.	Octopamine	hydrochloride	and	tyramine	hydrochloride	(Sigma	Aldrich)	were	dissolved	as	0.1	mM	stocks	in	AHL	buffer	with	ribose.	Both	the	octopamine	and	tyramine	solutions	were	applied	directly	to	the	brain	preparation	and	were	used	at	a	final	concentration	of	1	μM.	The	stimulus	was	delivered	one	minute	after	drug	addition.	For	all	Gr66a	GRN	imaging,	flies	were	stimulated	with	0.07mM	lobeline.	The	change	in	fluorescence	(ΔF/F0)	was	calculated	by	the	5-frame	average	peak	intensity	minus	a	ten-frame	average	pre-stimulus	intensity	(F0),	divided	by	F0.	The	heat	map	in	Figure	10	was	created	using	Image	J.	To	generate	this	image,	10	frames	prior	to	stimulation	and	8	frames	following	stimulation	were	each	averaged,	and	then	a	threshold	was	applied	(values	<	10	=	0)	to	reduce	background	noise.	A	Gaussian	blur	with	a	pixel	radius	of	2	was	applied,	and	then	the	two	images	were	subtracted	to	give	the	change	in	fluorescence.	The	resulting	image	was	divided	by	the	prestimulus	image	to	give	ΔF/F0.	3.2.3.2	Electrophysiology		 For	cell-attached	recordings,	we	made	use	of	two	different	dissection	methods	depending	on	whether	the	fly	was	being	stimulated	with	a	tastant.	In	both	cases	the	antennae	and	cuticle	covering	the	SEZ	were	removed.	For	preparations		 63	where	taste	stimulations	were	carried	out,	the	top	head	cuticle	was	also	cut	away,	and	the	perineural	sheath	was	removed	lateral	to	the	base	of	the	antennal	lobe	using	sharp	forceps.	For	baseline	recordings	where	the	proboscis	was	not	required,	both	the	proboscis	and	surrounding	cuticle	were	removed.	The	perineural	sheath	was	then	removed	at	the	bottom	of	the	brain	in	the	area	where	the	optic	lobe	meets	the	SEZ.		 All	electrophysiological	recordings	were	performed	using	glass	electrodes	(~1.5-3	MOhm)	containing	AHL,	with	patch	resistances	from	50-500	MOhm.	OA-VL1	or	OA-VL2	neurons	were	identified	by	driving	UAS-mCD8::GFP	with	VT026002-Gal4	or	VT049128-Gal4,	respectively.	Spiking	was	recorded	in	voltage-clamp	mode	with	a	multiclamp	700B	recorder	at	20	kHz.	Recordings	were	first	passed	through	a	low-pass	filter	at	5kHz	and	then	band-pass	filtered	between	100	and	3000	Hz	with	a	Butterworth	filter.	A	custom	Python	script	was	used	for	spike	detection.	Taste	stimuli	used	were:	1	mM	denatonium,	20	mM	lobeline,	or	a	cocktail	of	5	mM	berberine	mixed	with	100	mM	caffeine	(bitter);	1	M	sucrose	or	1	M	glucose	(sweet).		All	tastants	were	delivered	to	the	proboscis	of	the	fly	using	a	glass	pipette	controlled	by	a	manual	micromanipulator.	At	contact,	a	stimulus	artifact	could	be	seen	in	the	recording.	Prestimulation	and	taste-evoked	firing	were	calculated	from	the	average	firing	rate	during	the	five	seconds	preceding	and	two	seconds	following	this	artifact,	respectively.	Tonic	firing	for	food-deprived	flies	(0,	12,	24,	40	hours)	was	calculated	by	averaging	30	–	140	seconds	of	steady	activity.				 64	3.2.4	Behavioural	Assays		 For	PER,	female	flies	were	aged	3	–	10	days.	Flies	were	shifted	to	29°C	for	48	hours	to	induce	production	of	KIR2.1	in	cells	of	interest.	Flies	were	starved	on	1%	agar	at	29°C	for	the	last	18	hours	of	this	induction	period	and	then	mounted	inside	pipette	tips	that	were	cut	to	size	so	that	only	the	head	was	exposed.	The	tubes	were	sealed	with	tape,	positioned	on	a	glass	slide	with	double-sided	tape,	and	allowed	to	recover	for	1	–	2	hours	in	a	humidified	chamber.	Before	testing	began,	flies	were	stimulated	with	water	and	allowed	to	drink	until	satiated.	Flies	were	then	stimulated	on	the	labellum	with	increasing	concentrations	of	the	bitter	tastant	L-canavanine	(25,	50,	75,	100	mM)	in	200	mM	sucrose,	using	a	20μL	pipette	attached	to	a	1mL	syringe.	Flies	were	presented	with	each	stimulus	three	times	and	PER	responses	were	recorded.	For	analysis,	each	fly’s	responses	were	treated	as	an	independent	replicate,	and	5-10	flies	of	each	genotype	were	tested	on	at	least	three	different	days.	The	order	of	genotypes	tested	on	each	day	was	random.	3.2.5	Statistical	Analyses		 We	used	the	lme4	1.1-7	package	in	R	3.2.1	(Bates	et	al.,	2015)	to	model	the	binary	PER	at	each	concentration	using	generalized	linear	mixed	models	with	a	binomial	error	distribution	and	a	random	effect	of	fly	ID	to	account	for	repeated	measures	of	individual	flies.	Twenty-five	flies	of	each	genotype	were	measured	3	times	at	each	concentration.	We	obtained	p-values	from	these	models	to	compare	each	genotype	with	the	two	controls	(40	tests	total),	and	classified	these	comparisons	as	statistically	significant	only	if	p	<	0.05	even	after	applying	the		 65	positive	false	discovery	rate	procedure	to	correct	for	multiple	tests	(Benjamini	and	Hochberg,	1995)	using	the	q-value	2.2.2	package	in	R.	This	procedure	controls	the	expected	rate	of	false	positives	(as	a	proportion	of	all	positive	results)	to	be	0.05,	and	is	thus	a	more	appropriate	way	to	maintain	statistical	power	while	performing	a	large	number	of	comparisons	than	the	Bonferroni	procedure	(Benjamini	and	Hochberg,	1995;	Nakagawa,	2004).	All	other	statistical	tests	were	performed	using	GraphPad	Prism	6	and	we	used	the	Bonferroni	correction	to	adjust	p-values	for	other	experiments	with	a	small	number	of	comparisons.	3.3	RESULTS	3.3.1	OA-VL	Neurons	are	in	Close	Proximity	to	Bitter	GRNs			 	 To	identify	novel	neurons	in	the	Drosophila	taste	circuit,	we	conducted	an	anatomical	screen	using	GRASP	(Gordon	and	Scott,	2009;	Feinberg	et	al.,	2008).	We	selected	20	lines	from	the	Vienna	Tile	(VT)	or	Janelia	Rubin	Gal4	collections	that	showed	sparse	SEZ	labeling	without	detectable	GRN	expression,	and	tested	each	for	GRASP	with	sweet	and	bitter	GRNs.	This	led	us	to	identify	two	lines	of	interest,	VT026002-Gal4	and	VT049128-Gal4,	which	both	showed	strong	GRASP	with	bitter	GRNs,	and	little	to	no	GRASP	with	sweet	GRNs	(Figure	10A-D).	Each	line	labeled	a	similar	prominent	bilateral	pair	of	neurons	in	the	SEZ;	however,	double	labeling	of	both	VT026002-Gal4	and	VT049128-Gal4	demonstrated	that	the	neurons	labeled	by	each	line	are	distinct.		 Using	antibody	markers	for	candidate	neurotransmitter	pathways,	we	determined	that	the	prominent	SEZ	neurons	in	each	line	were	positive	for	tyrosine			 66		Figure	10.	OA-VL	neurons	show	specific	proximity	to	bitter	sensory	inputs.	(A-D)	VT026002-Gal4	and	VT049128-Gal4	each	drive	expression	in	a	single	OA-VL	neuron	per	side	of	the	SEZ	(magenta)	that	shows	extensive	GRASP	(green)	with	bitter	GRNs	VT026002-Gal4 Bitter GRN GRASP VT026002-Gal4Bitter GRN GRASPVT049128-Gal4 VT049128-Gal4Sweet GRN GRASPVT026002-Gal4 cloneSweet GRN GRASPBitter GRN GRASPOA-VL1OA-VL2OA-VL1A BC DEG IH JTdc2 Tdc2 Tdc2 Tdc2VT049128VT026002VT026002-Gal4 Syt::GFPFVT045791 GMR38A06GMR38A06-Gal4 nc82VT045791-Gal4 nc82K L	 67	(A,C),	but	little	to	no	GRASP	with	sweet	GRNs	(B,D).	(E)	A	single	OA-VL1	neuron	from	VT026002-Gal4	(magenta),	labeled	using	FLP-out	mosaics,	displays	prominent	GRASP	(green)	with	bitter	GRNs.	(F)	OA-VL1	presynaptic	zones	labeled	with	synaptotagmin-GFP	(green).	OA-VL	processes	labeled	with	anti-dsRed	(magenta).	(G-J)	Anti-Tdc2	immunofluorescence	(magenta)	detects	two	OA-VL	neurons	per	side	of	the	brain.	The	four	Gal4	lines	used	to	label	OA-VLs	in	this	study	label	either	OA-VL1	(G),	OA-VL2	(H),	or	both	OA-VLs	(I,J).	(K-L)	Full	brain	and	ventral	nerve	cord	expression	of	VT045791-Gal4	(K)	and	GMR38A06-Gal4	(L)	driving	CD8::GFP.	Neuropil	is	labeled	with	nc82	(magenta).	All	scale	bars	are	50	µm.	Full	genotypes:	(A)	Gr66a-LexA::VP16/+;	lexAop-CD4::GFP11/+;	VT026002-Gal4/UAS-CD4::GFP1-10,	UAS-CD8::dsRed.	(B)	Gr5a-LexA::VP16/+;	lexAop-CD4::GFP11/+;	VT026002-Gal4/UAS-CD4::GFP1-10,	UAS-CD8::dsRed.	(C)	Gr66a-LexA::VP16/+;	lexAop-CD4::GFP11/+;	VT049128-Gal4/UAS-CD4::GFP1-10,	UAS-CD8::dsRed.	(D)	Gr5a-LexA::VP16/+;	lexAop-CD4::GFP11/+;	VT049128-Gal4/UAS-CD4::GFP1-10,	UAS-CD8::dsRed.	(E)	tub>Gal80>/+;	Gr66a-LexA::VP16/LexAop-CD4::GFP11,	UAS-CD8::dsRed;	VT026002-Gal4,	UAS-CD4::GFP1-10/MKRS,	hs-FLP.	(F)	VT026002-Gal4/+,	UAS-CD8::dsRed/UAS-syt::GFP.	(G)	UAS-CD8::GFP/+,	VT026002-Gal4/+.	(H)	UAS-CD8::GFP/+,	VT049128-Gal/+.	(I,K)	UAS-CD8::GFP/+,	VT045791-Gal4/+.	(J,L)	UAS-CD8::GFP/+,	GMR38A06-Gal4/+											 68	decarboxylase	2	(Tdc2),	a	key	enzyme	in	the	synthesis	of	TA	and	its	product	OA	(Figure	10G,H;	Cole	et	al.,	2005).	Previous	anatomical	studies	have	defined	these	two	neurons	in	each	hemisphere	as	the	OA-VL	cluster,	and	shown	they	are	immunoreactive	for	both	OA	and	TA	(Busch	et	al.,	2009).	By	comparing	the	morphology	of	each	neuron	to	the	published	images,	we	determined	that	VT026002-Gal4	labels	OA-VL1	and	VT049128-Gal4	labels	OA-VL2	(Busch	et	al.,	2009).	Importantly,	mosaic	analysis	of	VT026002-Gal4	confirmed	that	OA-VL1	exhibits	a	strong	GRASP	signal	with	bitter	GRNs	(Figure	10E).	Although	we	cannot	formally	rule	out	contributions	from	non-OA-VL	neurons	to	the	full	VT026002-Gal4	GRASP	signal,	we	did	not	find	evidence	for	other	GRASP-positive	neurons	in	our	mosaics.	To	examine	the	structure	of	OA-VLs	in	more	detail,	we	expressed	Synaptotagmin-GFP	(Syt-GFP)	under	the	control	of	VT026002-Gal4.	This	revealed	extensive	presynaptic		labeling	in	the	SEZ	(Figure	10F),	suggesting	that	OA-VLs	may	release	OA	and/or	TA	locally	to	modulate	circuit	function.		 In	addition	to	labeling	one	of	the	OA-VL	pairs,	VT026002-Gal4	and	VT049128-Gal4	each	labels	a	number	of	other	neurons	in	the	brain	(Figure	11A,B).	Therefore,	we	sought	additional	lines	for	functional	analyses.	By	visually	screening	the	VT	and	Janelia	Gal4	collections,	we	identified	VT045791-Gal4	and	GMR38A06-Gal4,	each	of	which	has	sparse	expression	patterns	that	include	both	OA-VL1	and	OA-VL2	(Figure	10I,J).	In	addition	to	the	OA-VLs,	VT045791-Gal4	has	weak	activity	in	a	group	of	neurons	in	the	ventral	SEZ	and	stronger	activity	in	a	small	cluster	of	local	or	motor	neurons	in	the	ventral	nerve	cord	(vnc)	(Figure	10K),	while	GMR38A06-Gal4	drives	expression	in	1-2	neurons	in	the	protocerebrum	and	a	few	ascending	neurons	in	the			 69		Figure	11.	(A-B)	Full	brain	expression	of	VT026002-Gal4	(A)	and	VT049128-Gal4	(L)	driving	CD8::GFP.	Neuropil	is	labeled	with	nc82	(magenta).	(C-D)	GRASP	between	GMR38A06-Gal4	neurons	and	bitter	(C)	or	sweet	(D)	GRNs.	Full	genotypes:	(A)	UAS-CD8::GFP/+,	VT026002-Gal4/+.	(B)	UAS-CD8::GFP/+,	VT049128-Gal/+.	(C)	Gr66a-LexA::VP16/+;	lexAop-CD4::GFP11/+;	GMR38A06-Gal4/UAS-CD4::GFP1-10,	UAS-CD8::dsRed.	(D)	Gr5a-LexA::VP16/+;	lexAop-CD4::GFP11/+;	GMR38A06-Gal4/UAS-CD4::GFP1-10,	UAS-CD8::dsRed.										 70	vnc	(Figure	10L).	To	further	confirm	the	robustness	of	our	GRASP	results,	we	tested	GRASP	between	the	OA-VLs	and	GRNs	using	GMR38A06-Gal4.	As	expected,	we	observed	a	strong	GRASP	signal	between	the	OA-VLs	and	bitter,	but	not	sweet,	GRNs	(Figure	11C,D).	3.3.2	OA-VL	Neurons	are	Regulated	by	Satiety	State		 To	investigate	possible	functions	of	OA-VLs	in	bitter	processing,	we	began	by	testing	whether	OA-VLs	receive	input	from	GRNs.	Using	cell-attached	electrophysiological	recordings,	we	measured	OA-VL1	spike	rates	before	and	after	stimulation	of	the	fly	labellum	with	either	sugar	or	a	cocktail	of	bitter	compounds.	Neither	sweet	nor	bitter	stimulation	evoked	a	significant	change	in	OA-VL	firing,	suggesting	that	these	neurons	do	not	receive	excitatory	or	inhibitory	input	from	sweet	or	bitter	GRNs	(Figure	12).		Our	observation	of	OA-VL	presynaptic	terminals	in	the	region	of	bitter	GRN	axon	terminals	(Figure	10F),	and	their	lack	of	bitter-evoked	activity,	suggested	an	alternative	mechanism	for	OA-VL	function	in	bitter	processing:	OA	and	TA,	released	by	OA-VLs,	could	directly	modulate	bitter	GRNs.	Given	that	satiety	state	is	known	to	affect	bitter	sensitivity,	we	tested	whether	starvation	may	affect	OA-VL	activity.	Indeed,	we	observed	a	progressive	decrement	in	OA-VL	firing	rate	following	starvation	for	up	to	40	hours	(Figure	13A-C).	These	results,	along	with	the	previous	observation	that	starvation	lowers	bitter	sensitivity	(Inagaki,	Panse	and	Anderson,	2014),	led	us	to	examine	the	hypothesis	that	OA-VL	activity	potentiates	bitter	GRN	output,	and	that	this	potentiation	is	decreased	upon	starvation.		 71		Figure	12.	OA-VL1	activity	prior	to	and	following	stimulation	with	bitter	(left)	or	sweet	(right)	tastants.	Each	line	represents	a	single	OA-VL1	neuron,	and	joins	the	pre-stimulus	and	post-stimulus	values.	Bitter	stimuli	used	were:	1	M	denatonium,	20	mM	lobeline,	or	a	cocktail	of	5	mM	berberine	mixed	with	100	mM	caffeine.	Sweet	stimuli	were	1	M	sucrose	or	1	M	glucose.											 72		Figure	13.	OA-VL	neuron	activity	is	regulated	by	satiety	state.	(A)	Representative	cell-attached	recordings	of	OA-VL1	in	flies	that	were	fully	fed	(top)	or	starved	for	24	h	(bottom).	(B)	Raster	plots	of	OA-VL1	activity	in	five	flies	that	were	fully	fed	(top)	or	starved	for	24	h	(bottom).	(C)	Summary	plot	of	OA-VL1	and	OA-VL2	activity	as	the	duration	of	starvation	increases.	Lines	and	error	bars	represent	mean	+/-	SEM	for	OA-VL1	and	OA-VL2	recordings	combined.	Asterisks	indicate	statistical	significance	in	a	one-way	ANOVA	with	Bonferroni	correction,	*	p	<	0.05,	***	p	<	0.001.				 		 73	3.3.3	OA-VLs	Modulate	Bitter	GRN	Output			 To	directly	test	whether	OA-VL	activity	potentiates	bitter	GRN	output,	we	performed	calcium	imaging	of	bitter	GRN	axon	terminals	in	the	SEZ	using	GCaMP6f	(Figure	14A).	As	reported	by	Inagaki	and	colleagues	(2014),	we	found	that	starvation	reduces	calcium	responses	in	bitter	GRNs	evoked	by	stimulation	with	a	low	concentration	of	lobeline	(Figure	14A,B).	We	then	examined	bitter-evoked	calcium	responses	in	flies	with	OA-VLs	silenced	through	expression	of	the	Drosophila	open	rectifier	potassium	channel	(ORK)	under	the	control	of	VT045791-Gal4	(Nitabach	et	al.,	2004).	Strikingly,	artificial	reduction	of	OA-VL	firing	in	fed	flies	led	to	bitter	GRN	calcium	responses	indistinguishable	to	those	seen	following	starvation	(Figure	14B).	Moreover,	no	further	reduction	in	the	bitter	response	was	observed	following	starvation	of	OA-VL-silenced	flies.	These	results	indicate	that	OA-VLs	are	necessary	for	the	potentiation	of	taste-evoked	bitter	GRN	calcium	signals	in	fed	flies.	Surprisingly,	we	observed	similar	effects	from	silencing	just	the	OA-VL1s,	suggesting	that	lowering	the	activity	of	just	this	single	pair	of	neurons	is	sufficient	to	confer	a	starvation-like	phenotype	to	bitter	GRNs	(Figure	15).		 OA-VL	neurons	were	previously	identified	as	octopaminergic	based	on	immunoreactivity	for	OA	(Busch	et	al.,	2009).	However,	they	are	also	strongly	immunoreactive	for	the	OA	precursor	TA	(Busch	et	al.,	2009),	raising	the	possibility	that	OA-VLs	co-release	these	two	neurotransmitters.	To	assess	the	roles	of	OA	and	TA	in	bitter	modulation,	we	measured	the	impact	of	each	on	the	bitter	GRN	calcium	response.	Pharmacological	addition	of	OA	or	TA	to	the	brain	of	starved	flies	caused	a	significant	elevation	in	the	taste-evoked	calcium	transients	of	bitter	GRNs,	and			 74			Figure	14.	OA-VL	activity	modulates	bitter	GRN	calcium	responses.	(A)	Schematic	of	bitter	GRN	calcium	imaging	paradigm,	along	with	sample	heat	map	of	taste-evoked	activity	in	bitter	GRNs	and	traces	showing	the	change	in	fluorescence	over	time.	(B)	Average	peak	GCaMP6f	fluorescence	change	in	Gr66a	axon	terminals	following	stimulation	with	0.07	mM	lobeline,	for	indicated	genotypes	under	fed	and	40h	starved	conditions.	Lines	represent	mean	+/-	SEM,	with	blue	lines	representing	fed	flies	and	red	lines	representing	starved	flies.	Grey	dots	indicate	values	for	individual	flies.	Asterisks	indicate	statistical	significance	in	a	two-way	ANOVA	with	Bonferroni	correction,	***	p	<	0.001,	ns	=	not	significant.	We	also	found	a	significant	interaction	between	the	fed/starved	condition	and	genotype	for	both	controls	compared	to	OA-VL-silenced	flies.	VT045791>ORK	is	short	form	for	VT045791-Gal4/UAS-ORK,	and	all	indicated	genotypes	also	had	Gr66a-LexA::VP16	and	LexAop-GCaMP6f	in	the	background.	(C)	Average	peak	bitter	GRN	responses	in	Gr66a-Gal4,	UAS-GCaMP6f	flies	following	addition	of	the	indicated	compound	to	the	brain	at	a	final		 75	concentration	of	1	μM.	Lines	represent	mean	+/-	SEM,	grey	dots	represent	values	for	individual	flies,	and	open	grey	circles	are	values	that	are	higher	than	the	y-axis	maximum.	Asterisks	indicate	a	statistically	significant	difference	from	the	vehicle	condition	by	one-way	ANOVA	with	Bonferroni	correction,	*p	<	0.05,	**p<0.01,	***	p	<	0.001,	ns	=	not	significant.										 76		Figure	15.	Average	peak	GCaMP6f	fluorescence	change	in	Gr66a	axon	terminals	following	stimulation	with	0.07	mM	lobeline,	for	indicated	genotypes	under	fed	and	40h	starved	conditions.	Lines	represent	mean	+/-	SEM,	with	blue	lines	representing	fed	flies	and	red	lines	representing	starved	flies.	Grey	dots	indicate	values	for	individual	flies.	Asterisks	indicate	significance	by	two-way	ANOVA	with	Bonferroni	correction,	***	p	<	0.001,	ns	=	not	significant.	We	also	found	significant	interactions	between	the	fed/starved	condition	and	genotype	for	both	controls	compared	to	OA-VL-silenced	flies.	VT026002>ORK	is	short	form	for	VT026002-Gal4/UAS-ORK,	and	all	indicated	genotypes	also	had	Gr66a-LexA::VP16	and	LexAop-GCaMP6f	in	the	background.			 77	addition	of	both	together	produced	a	roughly	additive	effect	(Figure	14C).	Importantly,	application	of	OA	or	TA,	or	both,	had	no	effect	on	the	bitter	GRN	responses	measured	in	fed	flies,	supporting	the	conclusion	that	reduction	of	OA	and/or	TA	signaling	underlies	the	starvation-dependent	depotentiation	of	bitter	GRN	responses.		 	To	confirm	the	behavioural	relevance	of	bitter	modulation	by	OA-VLs,	we	measured	their	role	in	PER	inhibition	by	bitter	compounds.	We	conditionally	silenced	OA-VLs	in	adult	flies	with	KIR2.1	expression	under	the	temporal	control	of	Gal80ts,	and	then	measured	PER	to	sucrose	plus	increasing	concentrations	of	the	bitter	compound	L-canavanine	(Figure	17).	L-canavanine	was	chosen	because,	unlike	lobeline	and	most	other	bitter	compounds,	it	does	not	directly	suppress	the	firing	of	sweet	GRNs,	and	therefore	should	inhibit	PER	exclusively	through	the	activation	of	bitter	GRNs	(Jeong	et	al.,	2013;	Chu	et	al.,	2014).	We	performed	PER	following	18	h	of	starvation,	which	increases	sugar	sensitivity	and	the	robustness	of	PER,	but	is	not	sufficient	to	decrease	bitter	GRN	sensitivity	(Inagaki,	Panse	and	Anderson,	2014).	Silencing	of	both	OA-VLs	with	either	VT045791-Gal4	or	GMR38A06-Gal4	led	to	a	significant	reduction	in	PER	inhibition	by	L-canavanine,	demonstrating	that	OA-VLs	are	necessary	for	the	inhibition	of	PER	by	bitter	compounds	(Figure	17).	We	infer	that	this	reduction	in	bitter	sensitivity	upon	OA-VL	silencing	is	due	to	the	reduced	bitter	GRN	output	we	observed	with	calcium	imaging.	Also	consistent	with	the	results	of	our	calcium	imaging,	silencing	of	either	the	VT026002-Gal4	or	VT049128-Gal4	population	produced	a	similar	phenotype,	suggesting	that	both	OA-VL1	and	OA-VL2	are	necessary	for	the	potentiation	of	bitter			 78		Figure	16.	OA-VL	neurons	regulate	behavioural	bitter	taste	sensitivity.	The	PER	of	flies	with	silenced	OA-VLs	is	significantly	less	inhibited	by	high	concentrations	of	the	bitter	compound	L-canavanine.	Each	panel	shows	the	percent	PER	(mean	+/-	SEM)	of	flies	starved	for	18	h.	All	genotypes	with	UAS-KIR2.1	also	have	tub-Gal80ts	for	temporal	control	of	KIR2.1	expression.	“+”	indicates	the	w1118	strain	from	VDRC	used	to	make	the	Vienna	Tile	(VT)	collection;	PBDPGal4U	is	an	enhancerless	Gal4	control	for	the	Janelia	lines.		A	colored	asterisk	indicates	that	the	genotype	shown	in	black	was	significantly	more	likely	to	exhibit	PER	than	its	red	or	blue	control	line,	after	a	false	discovery	rate	correction.	n	=	25	flies	per	genotype	at	each	L-canavanine	concentration.								020406080100[L-canavanine] (mM)+200 mM sucrose0 25 50 75 100VT045791>KIR2.1VT045791-Gal4/++/UAS-KIR2.1** **020406080100% PER0 25 50 75 100GMR38A06>KIR2.1GMR38A06-Gal4/+pBDPGal4U/UAS-KIR2.1* ** **0204060801000 25 50 75 100VT026002>KIR2.1VT026002-Gal4/++/UAS-KIR2.1** * *0204060801000 25 50 75 100VT049128>KIR2.1VT049128-Gal4/++/UAS-KIR2.1* ** **[L-canavanine] (mM)+200 mM sucrose[L-canavanine] (mM)+200 mM sucrose[L-canavanine] (mM)+200 mM sucrose	 79	sensitivity	(Figure	17).	Although	none	of	our	Gal4	lines	exclusively	label	OA-VLs,	our	expression	analyses	suggest	it	is	highly	unlikely	that	any	non-OA-VL	expression	is	shared	by	all	four	lines.	Thus,	we	are	confident	that	the	observed	phenotypes	are	produced	by	manipulation	of	the	OA-VLs.	3.3.1	OA	and	TA	Act	Directly	on	Bitter	Neurons			 Given	the	anatomical	and	functional	characteristics	of	OA-VLs,	the	most	parsimonious	model	is	that	OA	and	TA	released	by	OA-VLs	directly	modulate	bitter	GRN	sensitivity.	To	provide	additional	support	for	this	model,	we	tested	the	function	of	OA	and	TA	receptors	in	bitter	GRNs.		 There	are	seven	OA	and	TA	receptors	in	Drosophila	(El-Kholy	et	al.,	2015).	To	identify	likely	candidate	receptors	functioning	in	bitter	GRNs,	we	made	use	of	a	published	microarray	dataset	comparing	gene	expression	in	the	labella	of	control	flies	to	that	of	poxn	mutants	with	reduced	numbers	of	GRNs	(Cameron	et	al.,	2010).	Two	OA	and/or	TA	receptor	genes	showed	evidence	of	possible	enrichment	in	taste	tissue:	Octβ1R	(CG6919)	and	Oct-TyrR	(CG7485).	We	performed	PER	following	knockdown	of	each	receptor	in	bitter	GRNs,	and	found	that	Oct-TyrR	knockdown	significantly	reduced	bitter	sensitivity	in	flies	that	had	been	starved	18	hours	(Figure	17A).	This	result	suggests	that	OA	and	TA,	released	by	OA-VLs,	acts	directly	on	bitter	GRNs	to	potentiate	their	output	through	the	activity	of	Oct-TyrR	(Figure	17B).	Moreover,	the	previous	observation	that	Oct-TyrR	expressed	in	heterologous	cells	mediates	similar	calcium	responses	following	addition	of	either	OA	or	TA	(Robb	et	al.,	1994)	may	explain	why	either	ligand	is	sufficient	to	potentiate	bitter			 80		Figure	17.	Oct-TyrR	mediates	the	potentiation	of	bitter	sensitivity.	(A)	The	PER	of	flies	with	Oct-TyrR	knocked	down	in	bitter	sensory	neurons	is	significantly	less	inhibited	by	high	concentrations	of	the	bitter	compound	L-canavanine.	Plot	shows	the	percent	PER	(mean	+/-	SEM)	of	flies	starved	for	18	h.	The	colored	asterisks	indicate	that	the	Gr66a>Oct-TyrRRNAi	flies	were	significantly	more	likely	to	exhibit	PER	than	the	red	or	blue	control	lines,	after	a	false	discovery	rate	correction.	(B)	Model	for	the	effect	of	OA-VLs	on	bitter	sensitivity	and	feeding	behaviour.	Green	arrows	indicate	excitation,	red	lines	indicate	inhibition.	The	dashed	line	indicates	that	most,	but	not	all,	bitter	compounds	directly	inhibit	sweet	neurons.	Synaptic	inhibition	of	sweet	GRNs	by	bitter	GRN	activity	is	based	on	previous	work	(Chu	et	al.,	2014).			sensoryneurons(GRNs)higher-orderneuronsbitter sweet feedingavoidancesugarsbittercompoundsOA-VLstarvationBAGr66a>Oct-TyrRRNAiGr66a>Octβ1RRNAiGr66a-Gal4/+UAS-Oct-TyrRRNAi/+ *  * *  *0204060801000 25 50 75 100[L-canavanine] (mM)+200 mM sucrose% PER	 81	GRNs	(Figure	14C).	3.4	DISCUSSION		 Fly	chemosensation	has	emerged	as	a	leading	model	for	understanding	the	neuromodulatory	effects	of	starvation	on	sensory	processing	(Su	and	Wang,	2014).	In	the	gustatory	system,	sweet	and	bitter	taste	show	orthogonal	responses	to	starvation	–	sweet	taste	is	potentiated,	while	bitter	taste	is	suppressed	(Inagaki,	Panse	and	Anderson,	2014).	While	sweet	GRNs	are	known	to	be	directly	modulated	by	dopamine,	the	signal	that	suppresses	bitter	sensitivity	was	unknown.	Here,	we	identify	a	novel	class	of	starvation-regulated	octopaminergic/tyraminergic	neurons	that	directly	modulate	bitter	GRN	output,	demonstrating	a	key	link	in	the	mechanism	of	bitter	taste	regulation	(Figure	17).	3.4.1	Independent	and	Reciprocal	Regulation	of	Sweet	and	Bitter	Taste			 Inagaki	and	colleagues	(2014)	demonstrated	that	sweet	and	bitter	taste	sensitivities	were	independently	modulated	by	starvation	through	the	activity	of	dNPF	and	sNPF,	respectively.	This	raised	the	question	of	how	these	two	related	peptide	systems,	both	of	which	are	thought	to	increase	following	starvation,	could	affect	opposite	physiological	responses	in	two	distinct	taste	neuron	classes.	Our	results	explain	this	phenomenon:	sweet	and	bitter	GRNs	are	both	potentiated	by	their	respective	neuromodulators	(DA	for	sweet,	OA/TA	for	bitter),	but	the	neurons	releasing	these	signals	are	regulated	in	opposite	directions.	While	the	starvation-induced	increase	in	TH-VUM	activity	potentiates	sweet	taste	(Marella,	Mann	and	Scott,	2012),	the	concomitant	decrease	in	OA-VL	activity	depotentiates	bitter	taste.		 82	We	expect	that	the	inhibition	of	OA-VL	activity	may	be	from	the	activity	of	a	GABAergic	intermediate	suggested	previously	(Inagaki,	Panse	and	Anderson,	2014).		 One	intriguing	aspect	to	our	results	is	that	silencing	of	a	single	OA-VL	pair	(OA-VL1)	was	sufficient	to	confer	starved-like	bitter	sensitivity.	We	believe	the	most	likely	explanation	for	this	observation	is	that	silencing	one	OA-VL	reduces	OA/TA	levels	below	a	specific	threshold	that	signals	starvation.	It	is	worth	noting	that	24	hours	of	starvation,	which	has	been	shown	to	produce	near	minimal	levels	of	bitter	sensitivity	(Inagaki,	Panse	and	Anderson,	2014),	resulted	in	only	an	approximate	50%	reduction	in	OA-VL	firing.	Thus,	it	is	conceivable	that	genetic	silencing	of	one	OA-VL	neuron	pair,	which	is	likely	a	more	potent	inhibitor	of	firing	than	starvation,	reduces	the	total	OA-VL	output	enough	to	confer	the	starved	state.	Another	possibility	is	that	the	OA-VLs	could	be	synaptically	coupled	to	provide	coordinated	regulation,	and	expression	of	KIR2.1	or	ORK	in	one	of	them	leads	to	decreased	activity	in	both.	3.4.2	OA/TA	Regulation	of	Gustation	and	Starvation-Dependent	Behaviours			 Functional	roles	for	TA	have	been	rather	obscure,	with	the	exception	of	its	recent	implication	in	courtship	drive	(Huang	et	al.,	2016)	and	evidence	for	differential	roles	of	OA	and	TA	in	larval	locomotion	(Saraswati	et	al.,	2004).	However,	OA	is	known	to	modulate	numerous	fly	behaviors,	including	sleep,	visual	guidance,	and	social	behaviors	such	as	aggression	and	courtship	(Wasserman,	Salomon	and	Frye,	2013;	van	Breugel,	Suver	and	Dickinson,	2014;	Nall	and	Sehgal,	2014;	Zhou,	Rao	and	Rao,	2008;	Certel	et	al.,	2010;	Andrews	et	al.,	2014).	Of		 83	particular	relevance	to	our	work	is	a	report	that	bitter	GRNs	–	which	detect	some	male	pheromones	in	addition	to	canonical	bitter	compounds	–	provide	input	to	a	cluster	of	OA	neurons	in	the	SEZ	that	regulates	male	aggression	and	courtship	behaviours	(Andrews	et	al.,	2014).	TBh	mutant	males,	unable	to	synthesize	octopamine,	showed	reduced	aggression	towards	other	males	and	elevated	male-male	courtship,	and	this	was	phenocopied	by	ablation	of	bitter	GRNs.	Additionally,	GRASP	and	calcium	imaging	suggested	functional	excitatory	connections	between	bitter	GRNs	and	SEZ	OA	neurons	(Andrews	et	al.,	2014).	While	the	specific	OA	neurons	receiving	this	input	were	not	identified,	the	cluster	examined	with	calcium	imaging	did	not	include	OA-VLs.	Thus,	it	appears	that	OA	may	modulate	some	gustatory	behaviours	in	multiple	ways,	including	presynaptic	control	of	GRN	output	and	modulation	of	downstream	circuitry.	It	would	be	interesting	to	examine	whether	OA-VLs	are	regulated	by	any	starvation-independent	motivational	states,	including	those	that	may	have	more	salience	in	social	behaviours.		 A	role	for	OA	in	starvation-induced	hyperactivity	has	also	been	recently	demonstrated	(Yang	et	al.,	2015).	In	this	case,	however,	mutants	lacking	OA	displayed	activity	levels	comparable	with	the	fed	state,	suggesting	that	OA	promotes	hyperactivity	in	starved	flies.	Thus,	there	may	exist	a	subset	of	OA	neurons	that	is	positively	regulated	by	starvation,	in	contrast	to	the	starvation-induced	reduction	OA-VL	activity	shown	here.	Further	characterization	of	OA/TA	populations	and	their	relationship	to	identified	nutrient	sensors	and	other	starvation-regulated	neural	circuits	will	greatly	enhance	our	understanding	of	how	internal	states	modify	perception	and	behavior.		 84	CHAPTER	4			 	 DISCUSSION	4.1	DISCUSSION	4.1.1	Implications	for	the	Field	of	Drosophila	Taste			 How	animals	are	able	to	sense	the	nutritional	value	of	food	independently	of	taste	is	becoming	an	increasingly	popular	area	of	research	interest	(de	Araujo,	2011).	Specifically,	there	appears	to	be	a	mechanism	by	which	animals	have	the	ability	to	detect	the	caloric	value	of	food	without	sweetness.	This	mechanism	is	also	separate	from	other	satiety	signals	that	reinforce	the	cessation	of	ingestion,	such	as	gut	stretching	and	release	of	insulin.	The	seminal	papers	on	this	topic	in	the	field	of	Drosophila	gustation	made	use	of	what	were	thought	to	be	taste-blind	flies	to	tease	apart	taste	from	nutrient	sensing	(Dus	et	al.,	2011;	Dus	et	al.,	2013).	These	flies	were	either	mutants	for	the	developmental	gene	poxn,	which	had	all	external	taste	sensilla	transformed	into	mechanosensory	neurons,	or	flies	that	were	double-mutants	for	the	sugar	receptors	Gr5a	and	Gr64a	and	were	reported	to	not	detect	sweet	tastes.	These	studies	used	the	putatively	taste-blind	flies	to	determine	whether	flies	could	sense	the	caloric	value	of	food	when	it	was	uncoupled	from	its	appetitive	taste.	Researchers	were	interested	in	whether	flies	could	use	this	caloric	information	alone	to	make	appropriate	feeding	choices,	and	if	so,	what	the	underlying	mechanisms	were.		However,	these	early	studies	that	purported	to	lay	the	foundation	of	our	understanding	of	this	phenomenon	were	confounded.	First,	the	double	mutants	used	in	these	experiments	are	not	sugar	blind,	only	limited	in	their	perception	of		 85	certain	sugars	(Miyamoto	et	al.,	2012).	Loss	of	Gr5a	results	in	the	inability	to	detect	trehalose,	whereas	loss	of	Gr64a	compromises	detection	of	sucrose,	maltose	and	glucose.	Secondly,	although	at	the	time	no	one	had	formally	shown	that	the	pharyngeal	neurons	played	a	role	in	detecting	appetitive	tastes,	it	was	well	established	that	the	pharynx	did	indeed	contain	taste	sensilla	that	were	anatomically	similar	to	those	on	other	parts	of	the	body	(Nayak	and	Singh,	1983;	Stocker,	1994).	The	study	presented	as	chapter	2	of	this	thesis	examines	the	role	of	these	sorely	overlooked	taste	receptors	in	evaluating	food	sources	and	controlling	feeding	behaviour.	The	initial	nutrient	sensing	studies	do	not	acknowledge	that	the	internal	pharyngeal	sense	organs	may	play	a	role	in	feeding,	in	the	absence	of	peripheral	taste.	Therefore,	the	work	in	chapter	2	serves	to	address	a	fundamental	gap	in	the	literature	by	concretely	showing	that	even	without	functional	peripheral	taste	receptors,	the	pharyngeal	taste	receptors	alone	are	enough	to	drive	consumption	of	sweet	compounds	over	tasteless	ones.	Moreover,	my	work	shows	that	much,	if	not	all,	the	preference	for	sweet	compounds	that	was	originally	attributed	to	post-ingestive	nutrient	sensing,	is	likely	to	be	a	function	of	pharyngeal	sweet	taste.	Thus,	this	study	provides	a	new	framework	in	which	to	interpret	past	results.	In	addition,	with	the	identification	of	the	receptors	in	the	taste	sensilla	of	pharyngeal	sense	organs,	we	provide	a	method	to	create	a	more	realistic	sweet-blind	fly,	which	could	aide	in	future	studies	wishing	to	implicate	mechanisms	in	taste-independent	nutrient	sensing.	Animal	survival	depends	on	the	neural	circuitry	underlying	taste	perception	and	feeding.	Drosophila	feeding	operates	as	series	of	hierarchical	subprograms,	with		 86	taste	receptors	on	different	body	organs	playing	a	role	at	discrete	stages.	Detecting	sugar	is	the	first	step	in	feeding	and	the	sweet	receptors	contained	in	taste	hairs	of	the	legs	provide	the	first	signal	that	a	potential	food	has	nutritional	value.	The	detection	of	sugar	on	the	legs	plays	a	key	role	in	commencing	feeding:	it	terminates	locomotion	thereby	allowing	the	fly	to	extend	its	proboscis.	The	legs	contain	two	distinct	groups	of	taste	neurons.	One	set	projects	to	the	thoracic	ganglion,	called	segmental	tarsal	GRNs	(stGRNs)	and	another	set	projects	into	the	SEZ,	called	the	ascending	tarsal	GRNs	(atGRNs;	Thoma	et	al.,	2016).	Interestingly,	each	group	serves	a	distinct	behavioural	function.	The	stGRNs	are	required	for	the	cessation	of	locomotion	when	the	fly	encounters	sugar,	and	silencing	these	neurons	prolongs	locomotion	of	starved	flies	on	foods	with	high	concentration	of	sucrose	(Thoma	et	al.,	2016).	The	atGRNs	detect	sweet	compounds	that	initiate	feeding	via	extension	of	the	proboscis.	Once	the	proboscis	contacts	a	sweet	compound,	the	labellar	GRNs	can	further	examine	the	quality	of	the	food	source	and	may	play	a	role	in	opening	of	the	labial	palps	to	allow	food	to	enter	the	mouth	parts	(Thoma	et	al.,	2016).	Once	food	enters	the	pharynx	it	is	further	monitored	by	the	pharyngeal	GRNs.	This	is	the	last	point	of	evaluation	for	a	food	source	before	entering	the	gut.	Our	study	empirically	shows	that	pharyngeal	GRNs	are	required	for	sustaining	consumption	bouts	of	appetitive	compounds	in	hungry	flies,	which	confers	them	a	unique	function	in	feeding.				 Chapter	3	details	a	number	of	experiments	that	led	to	the	identification	of	the	first	higher-order	components	of	the	bitter	circuit	in	Drosophila.	As	discussed	in	the	introduction,	a	number	of	independent	studies	have	been	published	that	describe		 87	higher-order	taste	neurons.	In	particular,	there	are	several	reports	of	sweet-responsive	neurons,	or	putative	sweet	circuit	neurons,	in	the	fly	brain	(Flood	et	al.,	2013;	Miyazaki	et	al.,	2015;	Kain	and	Dahanukar,	2015,	Yapici	et	al.,	2016),	and	neuron	populations	that	affect	starvation-dependent	behaviors	(Marella,	Mann	and	Scott,	2006;	Inagaki	et	al.,	2012;	Inagaki	et	al.,	2015;	Min	et	al.,	2016).	These	studies	have	become	numerous	in	our	field,	and	although	they	provide	valuable	information	on	which	future	researchers	will	build,	without	identifying	how	each	fits	with	each	other	or	with	known	inputs	and	outputs	of	taste	circuits,	we	remain	far	from	understanding	how	taste	information	is	processed	in	the	fly	brain.	Therefore,	we	must	work	towards	integrating	the	current	studies	in	our	field	to	place	these	neurons	in	their	appropriate	hierarchy	in	taste	circuits,	and	further	build	on	our	understanding	of	these	neurons	to	determine	how	they	function	in	a	network.		The	study	described	in	chapter	3	describes	a	bilateral	pair	of	neurons	that	modulate	the	primary	sensory	bitter	neuron	at	their	first	synapse	in	the	taste	center	of	the	fly	brain.	The	discovery	of	these	neurons	answered	a	long-standing	question	in	the	field	of	how	the	sensitivity	of	bitter	neurons	was	altered	in	a	state-dependent	manner.	With	the	identification	of	these	neurons,	we	now	know	how	sweet	and	bitter	neurons	become	reciprocally	sensitized	and	desensitized,	respectively,	when	the	fly	is	starved.	This	adds	a	valuable	piece	of	information	to	the	overall	body	of	literature	on	the	much	less	well	studied	and	understood	bitter	circuit,	and	to	our	comprehensive	understanding	of	mechanisms	by	which	taste	perception	is	altered	in	response	to	changes	in	energy	deficits	that	threaten	homeostasis.			 88	4.1.2	Caveats	and	Future	Directions	in	our	Current	Studies			4.1.2.1	Chapter	2			 In	chapter	2,	we	showed	that	in	the	absence	of	both	peripheral	and	pharyngeal	sweet	taste,	flies	showed	little	preference	for	either	caloric	or	non-caloric	sweet	foods.	It	is	possible	that	we	were	unable	to	discern	the	effects	of	post-ingestive	nutrient	sensing	due	to	the	short	time	frame	of	our	binary	feeding	assay.	It	would	be	of	interest	to	evaluate	the	protein,	named	Cupcake,	that	Dus	et	al.	(2013)	identified	to	be	responsible	for	taste-independent	nutrient	sensing	in	our	sweet-blind	flies.	Because	post-ingestive	mechanisms	are	likely	to	operate	over	a	longer	time	scale	than	can	be	detected	by	the	original	assay	we	used	in	chapter	2,	it	would	have	been	ideal	for	us	to	use	a	long-term	quantitative	feeding	assay.	The	most	appropriate	assay	for	this	purpose	would	be	the	capillary	feeding	(CAFE)	assay,	which	is	a	quantitative	assay	that	can	measure	feeding	over	multiple	days	(Ja	et	al.,	2007).	Unfortunately,	it	was	not	possible	to	use	this	assay	in	conjunction	with	poxn	mutant	flies.	The	CAFE	assay	requires	that	flies	feed	in	an	inverted	position	at	the	tip	of	a	capillary.	This	assay	is	incompatible	with	poxn	mutants	because	they	show	a	motor	defect	that	hinders	their	ability	to	climb	onto	the	capillary	and	maintain	the	inverted	position	necessary	to	feed	from	these	tubes.	Although	this	motor	defect	associated	with	the	poxn	mutant	gene	is	not	well	described,	it	could	stem	from	a	documented	defect	in	the	segmentation	of	the	tarsi	(Awasaki	and	Kimura,	2001).	This	may	explain	their	difficulties	in	walking	on	the	glass	capillaries	and	maintaining	the	position	necessary	to	feed	in	the	CAFE	assay.	Even	with	the	arrival	of	new		 89	apparatuses	designed	to	better	measure	feeding	dynamics,	such	as	Expresso	or	the	FlyPad,	none	have	yet	been	designed	that	would	provide	both	easy	access	to	food	for	flies	that	have	a	poxn	mutant	background	and	could	measure	feeding	choices	over	multiple	days	(Yapici	et	al.,	2016;	Itskov	et	al.,	2014).			Another	possible	alternative	is	that	post-ingestive	effects	may	require	sweet	taste	to	guide	feeding,	and	this	is	why	we	see	no	preference	for	caloric	sweet	foods	in	our	experiment.	It	may	be	that	sweet	taste	acts	a	permissive	signal	for	taste-independent	function,	perhaps	by	allowing	flies	to	form	memories	associating	sweet	taste	with	the	caloric	value	of	a	food	compound,	and	without	this	initial	signal,	i.e.,	the	sweet	taste,	taste-independent	functions	like	post-ingestive	sensing	have	no	impact.	This	may	be	because	sweet	taste	is	the	guiding	indicator	of	caloric	value	in	a	food,	and	nutrient	value	contributes	to	the	reinforcement	of	appetitive	memories,	while	non-caloric	sugars	do	not	produce	strong	appetitive	memories.	Sorbitol,	a	tasteless	but	nutritive	sugar	alcohol,	does	not	impart	an	appetitive	memory	unless	mixed	with	a	sweet	tastant	(Burke	and	Waddell,	2011).	In	addition,	flies	do	not	form	long-term	appetitive	memories	to	sweet	but	not	nutritive	sugars	like	arabinose	and	xylose	(Burke	and	Waddell,	2011).	In	the	case	of	sorbitol,	the	lack	of	appetitive	memory	is	thought	to	be	due	to	insufficient	ingestion	of	the	taste-less	sugar	alcohol,	while	no	long-term	appetitive	memory	is	formed	with	arabinose	due	to	its	lack	of	calories.	However,	it	may	be	the	case	that	both	the	sweet	taste	and	caloric	value	are	needed.	The	sweet	taste	might	be	necessary	as	a	reinforcing	component	that	underlies	post-ingestive	effects.	It	could	be	that	in	the	absence	of	sweet	taste	in	our		 90	poxn	mutant	flies	with	silenced	pharyngeal	neurons,	there	is	no	signal	for	nutrient	sensing	to	reinforce,	thus	the	preference	for	these	sugars	is	lost.					4.1.2.2	Chapter	3		 One	of	the	issues	we	attempted	to	address	in	this	study,	but	could	not	fully	resolve	was	the	use	of	a	GAL4	driver	line	that	was	completely	selective	for	OA-VL	neurons.	It	would	be	ideal	to	have	GAL4	lines	that	label	the	both	of	OA-VL	pairs	and	each	individual	pair	of	neurons,	OA-VL1	and	OA-VL2.	This	would	allow	us	to	determine	conclusively	that	the	OA-VL	neurons	are	responsible	for	depotentation	of	bitter	neurons	in	the	starved	state,	and	would	be	beneficial	moving	forward	with	further	experiments	to	address	how	OA-VL	neurons	themselves	are	being	regulated,	whether	it	be	through	a	peptidergic	mechanism	as	suggested	by	Iganaki	et	al.	(2014)	or	GABA	inhibition,	or	some	combination	of	both.	One	possible	way	to	address	this	would	be	to	use	a	mosaic	analysis	(Gordon	and	Scott,	2009),	but	this	was	not	feasible	in	our	case.	Most	importantly	mosaic	analysis	creates	a	random	expression	pattern	that	varies	from	fly	to	fly	and	thus	requires	a	large	number	of	replicates.	With	our	behavioural	experiments,	this	may	have	been	feasible	but	the	phenotype	of	each	fly	would	still	vary	depending	on	the	random	expression	pattern	created.	There	would	undoubtedly	be	a	large	overlap	between	populations	of	neurons	labelled	and	the	corresponding	behavioural	phenotype,	making	it	difficult	to	examine	only	the	effect	caused	by	OA-VLs.		Iganaki	et	al.	(2014)	showed	compelling	evidence	that	implicates	sNPF	acts	through	GABA	to	decrease	bitter	sensitivity	during	starvation,	independently	of	the		 91	increase	in	sugar	sensitivity.		Both	24	and	48	hour	starved	sNPF	homozygous	mutant	flies	showed	an	increased	sensitivity	to	bitter	compounds	compared	to	wild-type	controls.	Because	there	are	roughly	4000	sNPF	positive	neurons	in	the	fly	brain	Iganaki	et	al	(2014)	tested	11	individual	sNPF-GAL4	lines	that	labeled	smaller	subsets	of	the	overall	sNPF	population.	They	drove	expression	of	KIR2.1	in	these	lines	in	an	attempt	to	identify	a	smaller	subset	of	sNPF	positive	neurons	that	were	responsible	for	regulating	bitter	sensitivity.	Lines	in	which	a	defect	in	bitter	sensitivity	was	seen	after	starvation	had	one	subset	of	sNPF	neurons	in	common:	a	set	of	11	–	12	neurons	called	the	lateral	neurosecretory	cells	(LNCs).	The	cell	bodies	of	the	LNCs	reside	in	the	central	brain,	but	these	neurons	send	their	axonal	projections	the	SEZ	and	are	thus	poised	to	modulate	bitter	sensory	neurons.		Iganaki	et	al	(2014)	also	examined	whether	sNPF	acted	directly	on	bitter	GRNs	through	the	one	sNPF	receptor	in	Drosophila.	To	do	this	they	knocked	down	sNPFR	in	bitter	neurons	using	Gr66a-GAL4	and	then	performed	calcium	imaging	in	bitter	GRNs.	If	sNPF	were	acting	directly	on	bitter	GRNs	through	the	sNPFR	it	would	reduce	bitter	sensitivity	in	the	fed	state.	However,	this	experiment	resulted	in	no	defect	in	the	modulation	of	the	sensitivity	of	bitter	neurons	during	starvation,	showing	that	sNPF	does	not	directly	act	on	bitter	GRNs	through	sNPFR.	Iganaki	et	al	(2014)	then	postulated	that	sNPF	could	be	acting	through	GABAergic	interneurons	to	decrease	the	sensitivity	of	bitter	neurons	during	starvation.	To	test	this	hypothesis,	they	knocked	down	sNPFR	in	GABAergic	neurons	using	the	dvGAT-GAL4	driver.	When	sNPF	was	unable	to	act	through	GABAergic	neurons,	starvation-dependent	modulation	of	bitter	sensitivity	was	abolished.	The	evidence	provided	by		 92	these	experiments	show	that	sNPF	acts	through	GABAergic	interneurons	to	induce	a	change	in	bitter	sensitivity	when	flies	are	starved.				Therefore,	we	believe	that	OA-VL	neurons	may	be	receiving	GABAergic	inhibition	from	local	interneurons	in	the	SEZ	that	are	in	turn	being	acted	upon	by	the	sNPF	positive	LNCs.	Our	own	experiments	show	that	double	labeling	of	GFP	under	the	control	of	GABABR2-GAL4	and	anti-tdc2	reveals	overlap	with	both	OA-VL	neurons	and	GABABR2	expression.	However,	the	expression	pattern	of	GABABR2-GAL4	is	extremely	broad	and	therefore	does	not	provide	sufficient	evidence	that	this	double	labeling	reflects	the	endogenous	expression	of	GABABR2	in	OA-VL	neurons.	It	would	be	of	interest	to	test	the	role	GABA	may	have	in	setting	the	inhibitory	tone	in	OA-VL	neurons	during	starvation	in	a	number	of	ways.	First,	GABABR2	RNAi	could	be	expressed	in	OA-VL	neurons	using	the	sparse	GAL4	lines	we	identified	that	label	each	OA-VL	neuron	pair	separately,	with	little	expression	elsewhere.	With	this	fly,	in	which	GABABR2	has	been	knocked	down	specifically	in	OA-VL	neurons,	we	could	do	both	behavioural	and	physiological	experiments	to	test	whether	this	receptor	is	acting	in	OA-VL	neurons	and	controlling	their	reduced	response	in	the	starved	state.	For	example,	if	GABABR2	were	knocked	down	in	OA-VL	neurons,	we	would	expect	the	frequency	of	firing	in	OA-VL	neurons	to	resemble	that	seen	in	the	fed	state,	which	allows	for	high	bitter	sensory	neuron	output.	In	this	case,	we	would	expect	starved	flies	to	continue	to	show	aversion	to	bitter	compounds,	as	assessed	by	PER,	similar	to	that	seen	in	the	fed	state.	We	could	also	measure	the	tonic	firing	rate	of	OA-VL	neurons	in	OA-VL	>	GABABR2	knockdown	flies.	We	would	expect	that	OA-VL	neurons	in	starved	flies	without	GABA	inhibition	would	show	a	comparable	tonic		 93	firing	rate	to	that	measured	in	fed	flies.	The	decrement	seen	when	measuring	the	firing	over	a	starvation	time	course	would	be	lost.	We	could	also	perform	an	experiment	where	we	add	sNPF	directly	to	the	brain	while	recording	from	OA-VL	neurons.	If	sNPF	acts	on	GABAergic	interneurons,	which	in	turn	act	on	OA-VL	neurons,	the	addition	of	sNPF	to	the	brain	could	cause	a	decrease	in	their	firing	rate,	and	depotentiate	bitter	sensory	neurons	mimicking	the	starved	state,	and	this	reduction	would	be	blocked	with	pharmacological	inhibitors	of	GABA	receptors.	4.1.3	Implications	for	Human	Health			 Drosophila	provides	an	excellent	model	for	understanding	the	elaborate	neural	circuits	underlying	taste	perception	and	feeding.	Compared	to	mammals,	the	fruit	fly	has	a	complex,	yet	manageably	sized,	nervous	system	and	the	genetic	tools	available	to	dissect	circuits	offer	an	advantage	over	mammalian	models.	Elucidation	of	feeding	circuits	in	Drosophila	could	provide	valuable	information	that	helps	uncover	how	similar	mechanisms	regulate	food	intake	in	mammalian	models,	and	eventually	humans.	Human	obesity	has	become	an	increasingly	impactful	health	issue	over	the	last	few	decades,	and	obesity	is	linked	to	many	serious	diseases,	including	type	2	diabetes,	heart	disease	and	even	cancer.		The	rampant	increase	in	human	obesity	has	also	lead	to	widespread	consumption	of	artificial	sweeteners.	Artificial	sweeteners	impart	sweet	taste	without	providing	any	nutrition	and	were	originally	directed	for	use	in	people	who	were	required	to	limit	their	sugar	intake,	such	as	diabetics.	Now	these	sweeteners	have	become	increasingly	common	within	foods	marketed	to	the	general	population.		 94	However,	we	know	little	about	how	they	affect	the	human	body	and	there	is	intense	debate	within	the	literature	as	to	their	safety	as	an	effective	way	to	reduce	sugar	intake	and	eliminate	weight	gain	(Tandel,	2011).	Studies	have	shown	a	connection	between	these	artificial	sweeteners	and	human	metabolic	dysregulation,	but	the	mechanisms	underlying	these	changes	are	not	well	understood	(Dhringa	et	al.,	2007).	A	recent	study	by	Wang	et	al.	(2016)	revealed	the	mechanism	through	which	sucralose	affects	the	metabolism	of	the	fruit	fly.	Flies	that	were	fed	a	sucralose	and	yeast	diet	showed	a	number	of	effects	that	are	paralleled	in	human	studies,	the	main	similarities	being	an	increased	overall	consumption	and	an	increased	tolerance	to	glucose.	This	study	shows	the	value	in	using	the	simple	fruit	fly	model	to	identify	mechanisms	underlying	general	phenomena	observed	across	species.	The	findings	of	these	studies	can	then	allow	researchers	to	fine	tune	their	experimental	approach	in	mammalian	models,	thus	increasing	the	efficiency	of	these	studies.														 95	REFERENCES		Adler	E,	Hoon	MA,	Mueller	KL,	Chandrashekar	J,	Ryba	NJ,	Zucker	CS	(2000)	A	novel	family	of	mammalian	taste	receptors.	Cell	100:	693	–	702.		Akerboom	J,	Chen	TW,	Wardill	TJ,	Tian	L,	Marvin	JS,	Mutlu	S,	Calderon	NC,	Esposti	F,	Borghuis	BG,	Sun	XR,	Gordus	A,	Orger	MB,	Portugues	R,	Engert	F,	Macklin	JJ,	Filosa	A,	Aggarwal	A,	Kerr	RA,	Takagi	R,	Kracun	S,	Shigetomi	E,	Khakh	BS,	Baier	H,	Lagnado	L,	Wang	SS,	Bargmann	CI,	Kimmel	BE,	Jayaraman	V,	Svoboda	K,	Kim	DS,	Schreiter	ER,	Looger	LL	(2012)	Optimization	of	a	GCaMP	calcium	indicator	for	neural	activity	imaging.	Journal	of	Neuroscience	32:	13819	–	13840.		Albin	SD,	Kaun	KR,	Knapp	JM,	Chung	P,	Heberlein	U,	Simpson	JH	(2015)	A	subset	of	serotonergic	neurons	evokes	hunger	in	adult	Drosophila.	Current	Biology	25:	2435	–	2440.		Andrews	JC,	Fernández	MP,	Yu	Q,	Leary	GP,	Leung	AKW,	Kavanaugh	MP,	Kravitz	EA,	Certel	SJ	(2014)	Octopamine	neuromodulation	regulates	Gr32a-linked	aggression	and	courtship	pathways	in	Drosophila	males.	PLoS	Genetics	10	e1004356.	Awasaki	T,	Kimura	K	(1997)	pox-neuro	is	required	for	development	of	chemosensory	bristles	in	Drosophila.	Journal	of	Neurobiology	32:	707	–	721.		Baines	RA,	Uhler	JP,	Thompson	A,	Sweeney	ST,	Bate	M	(2001)	Altered	electrical	properties	in	Drosophila	neurons	developing	without	synaptic	transmission.	Journal	of	Neuroscience	21:	1523	–	1531.		 96	Baird	GS,	Zacharias	DA,	Tsien	RY	(1999)	Circular	permutation	and	receptor	insertion	within	green	fluorescent	proteins.	Proceedings	of	the	National	Academy	of	Sciences	96:	11241	–	11246.		Bates	D,	Maechler	M,	Bolker	BM,	Walker	SC	(2015)	Fitting	Linear	Mixed-Effects	Models	Using	lme4.	Journal	of	Statistical	Software	67:	1	–	48.	Benton	R,	Dahanukar	A	(2011)	Electrophysiological	recording	from	Drosophila	taste	sensilla.	Cold	Spring	Harbor	Protocols	2011	(7):	839	–	850.			Benton	R,	Vannice	KS,	Gomez-Diaz	C,	Vosshall	LB	(2009)	Variant	ionotropic	glutamate	receptors	chemosensory	receptors	in	Drosophila.	Cell	136:	149	–	162.		Bernstein	JG,	Garrity	PA,	Boyden	ES	(2012)	Optogenetics	and	thermogenetics:	technologies	for	controlling	the	activity	of	targeted	cells	within	intact	neural	circuits.	Current	Opinions	in	Neurobiology	22:	61	–	71.		Bradbury	J	(2004)	Taste	perception:	cracking	the	code.	PLoS	Biology	2(3):	e64.	doi:10.1371/journal.pbio.0020064.		Brand	AH,	Perrimon	N	(1993)	Targeted	gene	expression	as	a	means	of	altering	cell	fates	and	generating	dominant	phenotypes.	Development	118:	401	–	415.		van	Breugel	F,	Suver	MP,	Dickinson	MH	(2014)	Octopaminergic	modulation	of	the	visual	flight	speed	regulator	of	Drosophila.	Journal	of	Experimental	Biology	217:	1737	–	1744.		 97	de	Brito	Sanchez	G,	Giurfa	M	(2011)	A	comparative	analysis	of	neural	taste	processing	in	animals.	Philosophical	Transactions	of	the	Royal	Society	366:	2171	–	2180.		Burke	CJ,	Waddell	S	(2011)	Remembering	nutrient	quality	of	sugar	in	Drosophila.	Current	Biology	21:	746	–	750.		Burke	CJ,	Huetteroth	W,	Owald	D,	Perisse	E,	Krashes	MJ,	Das	G,	Gohl	D,	Silies	M,	Certel	S,	Waddell	S	(2012)	Layered	reward	signaling	through	octopamine	and	dopamine	in	Drosophila.	Nature	492:	433	–	437.		Busch	S,	Selcho	M,	Ito	K,	Tanimoto	H	(2009)	A	map	of	octopaminergic	neurons	in	the	Drosophila	brain.	Journal	of	Comparative	Neurology	513:	643	–	667.		Cameron	P,	Hiroi	M,	Ngai	J,	Scott	K	(2010)	The	molecular	basis	for	water	taste	in	Drosophila.	Nature	465:	91	–	95.		Certel	SJ,	Leung	A,	Lin	C-Y,	Perez	P,	Chiang	A-S,	Kravitz	EA	(2010)	Octopamine	Neuromodulatory	Effects	on	a	Social	Behaviour	Decision-Making	Network	in	Drosophila	Males.	PLoS	ONE	5	e13248.	Chandrashekar	J,	Kuhn	C,	Oka	Y,	Yarmolinsky	DA,	Hummler	E,	Ryba	NJP,	Zuker	CS	(2010)	The	cells	and	peripheral	representation	of	sodium	taste	in	mice.	Nature:	297	–	301.			Chen	T,	Wardill	TJ,	Sun	Y,	Pulver	SR,	Renninger	SL,	Baohan	A,	Schreiter	ER,	Kerr	RA,	Orger	MB,	Jayaraman	V,	Looger	LL,	Svoboda	K,	Kim	DS	(2013)	Ultra-sensitive	fluorescent	proteins	for	imaging	neuronal	activity.	Nature	499:	295	–	300.			 98	Chen	X,	Gabito	M,	Peng	Y,	Ryba	NJP,	Zuker	CS	(2011)	A	gustotopic	map	of	taste	qualities	in	the	mammalian	brain.	Science	333(6047):	1262	–	1266.		Chu	B,	Chui	V,	Mann	K,	Gordon	MD	(2014)	Presynaptic	gain	control	drives	sweet	and	bitter	taste	integration	in	Drosophila.	Current	Biology	24:	1978	–	1984.		Chu,	B	(2014)	The	role	of	GABA	in	modulating	taste	neuron	output	in	Drosophila.	(Master’s	Thesis)	Retrieved	from	UBC	Electronic	Theses	and	Dissertation	Database	cIRcle	doi:	10.14288/1.0165955.			Clyne	PJ,	Warr	CG,	Carlson	JR	(2000)	Candidate	taste	receptors	in	Drosophila.	Science,	287:1830	–	1834.		Cole	S,	Carney	G,	McClung	C,	Willard	S,	Taylor	B,	Hirsh	J	(2005)	Two	functional	but	noncomplementing	Drosophila	tyrosine	decarboxylase	genes:	distinct	roles	for	neural	tyramine	and	octopamine	in	female	fertility.	Journal	of	Biological	Chemistry	280:	14948	–	14955.		Crivici	A,	Ikura	M	(1995)	Molecular	and	structural	basis	of	target	recognition	by	calmodulin.	Annual	Review	of	Biophysics	and	Biomolecular	Structure	24:	85	–	116.		Dahanukar	A,	Foster	K,	van	der	Goes	van	Naters	WM,	Carlson	JR	(2001)	A	Gr	receptor	is	required	for	response	to	the	sugar	trehalose	in	taste	neurons	of	Drosophila.	Nature	Neuroscience	4:	1182	–	1186.		Dahanukar	A,	Lei	Y,	Kwon	J,	Carlson	J	(2007)	Two	Gr	genes	underlie	sugar	reception	in	Drosophila.	Neuron	56:	503	–	516.		 99	Damak	S,	Rong	M,	Yasumatsu	K,	Kokrashvili	Z,	Varadarajan	V,	Zou	S,	Jiang	P,	Ninomiya	Y,	Margolskee	RF	(2003)	Taste	in	the	absence	of	taste	receptor	T1r3.	Science	301:	850	–	853.		Dethier	VG	(1976)	The	hungry	fly.	(Cambridge:	Harvard	University	Press).		Duffy	JB	(2002)	GAL4	system	in	Drosophila:	a	fly	geneticist’s	Swiss	army	knife.	Genesis	34:	1	–	15.		Dunipace	L,	Meister	S,	McNealy	C,	Amrein	H	(2001)	Spatially	restricted	expression	of	candidate	taste	receptors	in	Drosophila	gustatory	system.	Current	Biology	11:	822	–	835.		Dus	M,	Min	S,	Keene	AC,	Lee	GY,	Suh	GSB	(2011)	Taste-independent	detection	of	caloric	content	of	sugar	in	Drosophila.	Proceedings	of	the	National	Academy	of	Sciences	108:	11644	–	11649.		Dus	M,	Ai	M,	Suh	GSB	(2013)	Taste-independent	nutrient	selection	is	mediated	by	a	brain-specific	Na+/solute	cotransporter	in	Drosophila.	Nature	Neuroscience	16:	526	–	528.		El-Kholy	S,	Stephano	F,	Li	Y,	Bhandari	A,	Fink	C,	Roeder	T	(2015)	Expression	analysis	of	octopamine	and	tyramine	receptors	in	Drosophila.	Cell	Tissue	Research	361:	669	–	684.		Falk	R,	Bleiser-Avivi	N,	Atidia	J	(1976)	Labellar	taste	organs	of	Drosophila	melanogaster.	Journal	of	Morphology	150:	327	–	342.			 100	Farhadian	SF,	Suárez-Fariñas	M,	Cho	CE,	Pellegrino	M,	Vosshall,	LB	(2012)	Post-fasting	olfactory,	transcriptional,	and	feeding	responses	in	Drosophila.	Physiology	&	Behaviour	105:	544	–	553.		Feinberg	E,	Vanhoven	M,	Bendesky	A,	Wang	G,	Fetter	R,	Shen	K,	Bargmann	C	(2008)	GFP	Reconstitution	Across	Synaptic	Partners	(GRASP)	defines	cell	contacts	and	synapses	in	living	nervous	systems.	Neuron	57:	353	–	363.		Fischler	W,	Kong	P,	Marella	S,	Scott	K	(2007)	The	detection	of	carbonation	by	the	Drosophila	gustatory	system.	Nature	448:	1054	–	1057.		Flood	TF,	Iguchi	S,	Gorczyca	M,	White	B,	Ito	K,	Yoshihara	M	(2013)	A	single	pair	of	interneurons	commands	the	Drosophila	feeding	motor	program.	Nature	499:	83	–	87.		Freeman	EG,	Dahanukar	A	(2015)	Molecular	neurobiology	of	Drosophila	taste.	Current	Opinion	in	Neurobiology	34:	140	–	148.		Freeman	EG,	Wisotsky	Z,	Dahanukar	A	(2014)	Detection	of	sweet	tastants	by	a	conserved	group	of	insect	gustatory	receptors.	Proceedings	of	the	National	Academy	of	Sciences	111:	1598	–	1603.		Fujii	S,	Yavuz	A,	Slone	J,	Jagge	C,	Song	X,	Amrein	H	(2015)	Drosophila	Sugar	Receptors	in	Sweet	Taste	Perception,	Olfaction,	and	Internal	Nutrient	Sensing.	Current	Biology	25:	1	–	8.	Fujita	M,	Tanimura	T	(2011)	Drosophila	evaluates	and	learns	the	nutritional	value	of	sugars.	Current	Biology	21:	751	–	755.			 101	Galindo	K,	Smith	DP	(2001)	A	large	family	of	divergent	Drosophila	odorant-binding	proteins	expressed	in	gustatory	and	olfactory	sensilla.	Genetics	159:	1059	–	1072.		Gao	N,	Lu	M,	Echeverri	F,	Laita	B,	Kalabat	D,	Williams	ME,	Hevezi	P,	Zlotnik	A,	Moyer	BD	(2009)	Voltage-gated	sodium	channels	in	taste	bud	cells.	BMC	Neuroscience	10:	20.		Gendre	N,	Lüer	K,	Friche	S,	Grillenzoni	N,	Ramaekers	A,	Technau	GM,	Stocker	RF	(2004)	Integration	of	complex	larval	chemosensory	organs	into	the	adult	nervous	system	of	Drosophila.	Development	131:	83	–	92.		Gordon	MD,	Scott	K	(2009)	Motor	control	in	a	Drosophila	taste	circuit.	Neuron	61:	373	–	384.		Groth	AC,	Fish	M,	Nusse	R,	Calos	MP	(2004)	Construction	of	transgenic	Drosophila	by	using	the	site-specific	integrase	from	phage	phiC31.	Genetics	166:	1775	–	1782.		Hamada	FN,	Rosenzweig	M,	Kang	K,	Pulver	SR,	Ghezzi	A,	Jegla	TJ,	Garrity	PA	(2008)	An	internal	thermal	sensor	controlling	temperature	preference	in	Drosophila.	Nature	454:	217	–	220.		Hiroi	M,	Marion-Poll	F,	Tanimura	T	(2002)	Differential	response	to	sugars	among	labellar	chemosensilla	in	Drosophila.	Zoological	Science	19:	1009	–	1018.		Hiroi	M,	Meunier	N,	Marion-Poll	F,	Tanimura	T	(2004)	Two	antagonistic	gustatory		receptor	neurons	responding	to	sweet-salty	and	bitter	taste	in	Drosophila.	Journal	of	Neurobiology	61(3):	333	–	342.			 102		Hodge	JJ	(2009)	Ion	channels	to	inactivate	neurons	in	Drosophila.	Frontiers	in	Molecular	Neuroscience	2:	1	–	10.		Huang	AJ,	Chen	X,	Hoon	MA,	Chandrashekar	J,	Guo	W,	Trankner	D,	Ryba	NJP,	Zuker	CS	(2006)	The	cells	and	logic	for	mammalian	sour	taste	detection.	Nature	442:	934	–	938.		Huang	J,	Liu	W,	Qi	Y-X,	Luo	J,	Montell,	C.	(2016)	Neuromodulation	of	Courtship	Drive	through	Tyramine-Responsive	Neurons	in	the	Drosophila	Brain.	Current	Biology	Hussain	A,	Zhang	M,	Ucpunar	HK,	Svensson	T,	Quillery	E,	Gompel	N,	Ignell	R,	Grunwald	Kadow	IC	(2016)	Ionotropic	chemosensory	receptors	mediate	the	taste	and	smell	of	polyamines.	PLoS	Biology	14(5):	e1002454.	doi:10.1371/journal.pbio.1002454	Iguchi	N,	Ohkuri	T,	Slack	JP,	Zhong	P,	Huang	L	(2011)	Sarco/endoplasmic	reticulum	Ca2+ATPases	(SERCA)	contribute	to	GPCR-mediated	taste	perception.	PLoS	One	6(8):	e23165.	doi:10.1371/journal.pone.0023165.		Inagaki	HK,	Ben-Tabou	de-Leon	S,	Wong	AM,	Jagadish	S,	Ishimoto	H,	Barnea	G,	Kitamoto	T,	Axel	R,	Anderson	DJ	(2012)	Visualizing	neuromodulation	in	vivo:	TANGO-mapping	of	dopamine	signaling	reveals	appetite	control	of	sugar	sensing.	Cell	148:	583	–	595.			 103	Inagaki	HK,	Panse	KM,	Anderson	DJ	(2014)	Independent,	reciprocal	neuromodulatory	control	of	sweet	and	bitter	taste	sensitivity	during	starvation	in	Drosophila.	Neuron	84:	806	–	820.		Itskov	PM,	Ribeiro	C	(2013)	The	dilemmas	of	the	gourmet	fly:	the	molecular	and	neuronal	mechanisms	of	feeding	and	nutrient	decision	making	in	Drosophila.	Frontiers	in	Neuroscience	7:	12.		Jeong	YT,	Shim	J,	Oh	SR,	Yoon	HI,	Kim	CH,	Moon	SJ,	Montell	C	(2013)	An	odorant-binding	protein	required	for	suppression	of	sweet	taste	by	bitter	chemicals.	Neuron	79:	725	–	737.		Jiao	Y,	Moon	SJ,	Montell	C	(2007)	A	Drosophila	gustatory	receptor	required	for	the	responses	to	sucrose,	glucose,	and	maltose	identified	by	mRNA	tagging.	Proceedings	of	the	National	Academy	of	Sciences	104:	14110	–	14115.		Jiao	Y,	Moon	SJ,	Wang	X,	Ren	Q,	Montell	C	(2008)	Gr64f	Is	Required	in	Combination	with	Other	Gustatory	Receptors	for	Sugar	Detection	in	Drosophila.	Current	Biology	18:	1797	–	1801.		Joseph	RM,	Heberlein	U	(2012)	Tissue-specific	activation	of	a	single	gustatory	receptor	produces	opposing	behavioral	responses	in	Drosophila.	Genetics	192:	521	–	532.		Kain	P,	Dahanukar	A	(2015)	Secondary	taste	neurons	that	convey	sweet	taste	and	starvation	in	the	Drosophila	brain.	Neuron	85:	819	–	832.			 104	Keene	AC,	Duboué	ER,	McDonald	DM,	Dus	M,	Suh	GSB,	Waddell	S,	Blau	J	(2010)	Clock	and	cycle	limit	starvation-induced	sleep	loss	in	Drosophila.	Current	Biology	20:	1209	–	1215.		Keene	AC,	Masek	P	(2012)	Optogenetic	induction	of	aversive	taste	memory.	Neuroscience	222:	173	–	180.		Ko	KI,	Root	CM,	Lindsay	SA,	Zaninovich	OA,	Shepherd	AK,	Wasserman	SA,	Kim	SM,	Wang	JW	(2015)	Starvation	promotes	concerted	modulation	of	appetitive	olfactory	behavior	via	parallel	neuromodulatory	circuits.	eLife	4,	221.		Krashes	MJ,	Dasgupta	S,	Vreede	A,	White	B,	Armstrong	JD,	Waddell	S	(2009)	A	neural	circuit	mechanism	integrating	motivational	state	with	memory	expression	in	Drosophila.	Cell	139:	416	–	427.		Kwon	JY,	Dahanukar	A,	Weiss	LA,	Carlson	JR	(2014)	A	map	of	taste	neuron	projections	in	the	Drosophila	CNS.	Journal	of	Biosciences	39:	565	–	574.		Lebreton	S,	Trona	F,	Borrero-Echeverry	F,	Bilz	F,	Grabe	V,	Becher	PG,	Carlsson	MA,	Nässel	DR,	Hansson	BS,	Sachse	S,	et	al	(2015)	Feeding	regulates	sex	pheromone	attraction	and	courtship	in	Drosophila	females.	Science	Reports	5:	13132	Lee	G,	Park	JH	(2004)	Hemolymph	sugar	homeostasis	and	starvation-induced	hyperactivity	affected	by	genetic	manipulations	of	the	adipokinetic	hormone-encoding	gene	in	Drosophila	melanogaster.	Genetics	167:	311	–	323.		Lee	T,	Luo	L	(1999)	Mosaic	analysis	with	a	repressible	cell	marker	for	studies	of	gene	function	in	neuronal	morphogenesis.	Neuron	22:	451	–	461.			 105	Lienhard	MC,	Stocker	RF	(1987)	Sensory	projection	patterns	of	supernumerary	legs	and	aristae	in	D.	melanogaster.	Journal	of	Experimental	Zoology	244:	187	–	201.		Ling	F,	Dahanukar	A,	Weiss	LA,	Kwon	JY,	Carlson	JR	(2014)	The	molecular	and	cellular	basis	of	taste	coding	in	the	legs	of	Drosophila.	The	Journal	of	Neuroscience	34(21):	7148	–	7164.		Liu	C,	Placais	PY,	Yamagata	N,	Pfeiffer	BD,	Aso	Y,	Friedrich	AB,	Siwanowicz	I,	Rubin	GM,	Preat	T,	Tanimoto	H	(2012)	A	subset	of	dopamine	neurons	signals	reward	for	odour	memory	in	Drosophila	488:	512	–	516.		Mank	M,	Griesbeck	O	(2008)	Genetically	encoded	calcium	indicators.	Chemical	Reviews	108:	1550	–	1564.		Mann	K,	Gordon	MD,	Scott	K	(2013)	A	pair	of	interneurons	influences	the	choice	between	feeding	and	locomotion	in	Drosophila.	Neuron	79:	754	–	765.		Manzo	A,	Silies	M,	Gohl	DM,	Scott	K	(2012)	Motor	neurons	controlling	fluid	ingestion	in	Drosophila.	Proceedings	of	the	National	Academy	of	Sciences	109:	6307	–	6312.		Marella	S,	Fischler	W,	Kong	P,	Asgarian	S,	Rueckert	E,	Scott	K	(2006)	Imaging	taste	responses	in	the	fly	brain	reveals	a	function	map	of	taste	category	and	behaviour.	Neuron	49:	285	–	295.		Marella	S,	Mann	K,	Scott	K	(2012)	Dopaminergic	modulation	of	sucrose	acceptance	behaviour	in	Drosophila.	Neuron	73:	941	–	950.			 106	McCombs	JE,	Palmer	AE	(2008)	Measuring	calcium	dynamics	in	living	cells	with	genetically	encodable	calcium	indicators.	Methods	46:	152	–	159.		Meunier	N,	Marion-Poll	F,	Rospars	JP,	Tanimura	T	(2003)	Peripheral	coding	of	bitter	taste	in	Drosophila.	Journal	of	Neurobiology	56:	139	–	152.		Min	S,	Chae	HS,	Jang	YH,	Choi	S,	Lee	S,	Jeong	YT,	Jones	WD,	Moon	SJ,	Kim	YJ,	Chung	J	(2016)	Identification	of	a	peptidergic	pathway	critical	to	satiety	responses	in	Drosophila.	Current	Biology	26:	1	–	7.		Mitchell	BK,	Itagaki	H,	Rivet	MP	(1999)	Peripheral	and	central	structures	involved	in	insect	gustation.	Microscopy	Research	and	Technique	47:	401	–	415.		Miyamoto	T,	Slone	J,	Song	X,	Amrein	H	(2012)	A	fructose	receptor	functions	as	a	nutrient	sensor	in	Drosophila	brain.	Cell	151(5):	1113	–	1125.		Miyamoto	T,	Wright	G,	Amrein	H	(2013)	Nutrient	sensors.	Current	Biology	23:	R369	–	R373.		Montell	C	(2009)	A	taste	of	the	Drosophila	gustatory	receptors.	Current	Opinions	in	Neurobiology	19:	345	–	353.		Mueller	KL,	Hoon	MA,	Erlenbach	I,	Chandrashekar	J,	Zuker	CS,	Ryba	NJP	(2005)	The	receptors	and	coding	logic	for	bitter	taste.	Nature	434:	225	–	229.		Nagai	T,	Sawano	A,	Park	ES,	Miyawaki	A	(2001)	Circularly	permuted	green	fluorescent	proteins	engineered	to	sense	Ca2+.	Proceedings	of	the	National	Academy	of	Sciences	98:	3197	–	3202.			 107	Nakagawa	S	(2004)	A	farewell	to	Bonferroni:	the	problems	of	low	statistical	power	and	publication	bias.	Behavioural	Ecology	15:	1044	–	1045.	Nall	A,	Sehgal	A	(2014)	Monoamines	and	sleep	in	Drosophila.	Behavioural	Neuroscience	128:	264	–	272.	Nayak	SV,	Singh	RN	(1983)	Sensilla	on	the	tarsal	segments	and	the	mouthparts	of	adult	Drosophila	melanogaster.	International	Journal	of	Insect	Morphology	and	Embryology	12:	273	–	291.		Nelson	G,	Hoon	MA,	Chandrashekar	J,	Zhang	Y,	Ryba	NJP,	Zuker	CS	(2001)	Mammalian	sweet	taste	receptors.	Cell	106:	381	–	390.	Nitabach	MN,	Wu	Y	Sheeba	V,	Lemon	WC,	Strumbos	J,	Zelensky	PK,	White	BH,	Holmes	TC	(2006)	Electrical	hyperexcitation	of	lateral	ventral	pacemaker	neurons	desynchronizes	downstream	circadian	oscillators	in	the	fly	circadian	circuit	and	induces	multiple	behavioural	periods.	Journal	of	Neuroscience	26:	479	–	489.		Oka	Y,	Butnaru	M,	von	Buchholtz	L,	Ryba	NJP,	Zuker	CS	(2013)	High	salt	recruits	aversive	taste	pathways.	Nature	494:	472	–	476.		Pfeiffer	BD,	Jenett	A,	Hammonds	AS,	Ngo	TB,	Misra	S,	Murphy	C,	Scully	A,	Carlson	JW,	Wan	KH,	Laverty	TR,	Mungall	C,	Svirskas	R,	Kadonaga	JT,	Doe	CQ,	Eisen	MB,	Celniker	S,	Rubin	GM	(2008)	Tools	for	neuroanatomy	and	neurogenetics	in	Drosophila.	Proceedings	of	the	National	Academy	of	Sciences	28:	9715	–	9720.			 108	Pool	AH,	Kvello	P,	Mann	K,	Cheung	SK,	Gordon	MD,	Wang	L,	Scott	K	(2014)	Four	GABAergic	interneurons	impose	feeding	restraint	in	Drosophila.	Neuron	83:	164	–	177.			Pool	AH,	Scott	K	(2014)	Feeding	regulation	in	Drosophila.	Current	Opinion	in	Neurobiology	0:	57	–	63.		Rajashekhar	KP,	Singh	RN	(1994)	Neuroarchitecture	of	the	tritocerebrum	of	Drosophila	melanogaster.	Journal	of	Comparative	Neurology	349:	633	–	645.	Ribeiro	C,	Dickson	BJ	(2010)	Sex	peptide	receptor	and	neuronal	TOR/S6K	signaling	modulate	nutrient	balancing	in	Drosophila.	Current	Biology	20:	1000	–	1005.			Robb	S,	Cheek	TR,	Hannan	FL,	Hall	LM,	Midgley	JM,	Evans	PD	(1994)	Agonist-specific	coupling	of	a	cloned	Drosophila	octopamine/tyramine	receptor	to	multiple	second	messenger	systems.	EMBO	Journal	13:	1325	–	1330.		Roberston	HM,	Warr	CG,	Carlson	JR	(2003)	Molecular	evolution	of	the	insect	chemoreceptor	gene	superfamily	in	Drosophila	melanogaster.	Proceedings	of	the	National	Academy	of	Sciences	100:	14537	–	14542.		Root	CM,	Ko	KI,	Jafari	A,	Wang	JW	(2011)	Presynaptic	facilitation	by	neuropeptide	signaling	mediates	odor-driven	food	search.	Cell	145(1):	133	–	144.		Scott	K,	Brady	R	Jr,	Cravchik	A,	Morozov	P,	Rzhetsky	A,	Zuker	C,	Axel	R	(2001)	A	chemosensory	gene	family	encoding	candidate	gustatory	and	olfactory	receptors	in	Drosophila.	Cell	104:	661	–	673.			 109	Shiraiwa	T,	Carlson	JR	(2009)	Proboscis	extension	response	(PER)	assay	in	Drosophila.	Journal	of	Visualized	Experiments	3:	193.		Slone	J,	Daniels	J,	Amrein	H	(2007)	Sugar	receptors	in	Drosophila.	Current	Biology	17:	1809	–	1816.		Spector	AC,	Travers	SP	(2005)	The	representation	of	taste	quality	in	the	mammalian	nervous	system.	Behavioural	and	Cognitive	Neuroscience	Reviews	4:	143	–	191.		Srivastava	DP,	Yu	EJ,	Kennedy	K,	Chatwin	H,	Reale	V,	Hamon	M,	Smith	T,	Evans	PD	(2005)	Rapid,	nongenomic	responses	to	ecdysteroids	and	catecholamines	mediated	by	a	novel	Drosophila	G-protein-coupled	receptor.	Journal	of	Neuroscience	25:	6145	–	6155.	Stafford	JW,	Lynd	KM,	Jung	AY,	Gordon	MD	(2012)	Integration	of	taste	and	calorie	sensing	in	Drosophila.	The	Journal	of	Neuroscience	32:	14767	–	14774.		Steiner	JE,	Glaser	D,	Hawilo	ME,	Berridge	KC	(2001)	Comparative	expression	of	hedonic	impact:	affective	reactions	to	taste	by	human	infants	and	other	primates.	Neuroscience	&	Biobehavioural	Reviews	25:	53	–	74.		Stocker	RF	(1994)	The	organization	of	the	chemosensory	system	in	Drosophila	melanogaster:	a	review.	Cell	and	Tissue	Research	275:	3	–	26.		Storey	JD	(2002)	A	direct	approach	to	false	discovery	rates.	Journal	of	the	Royal	Statistical	Society:	Series	B	(Statistical	Methodology)	64:	479	–	498.		 110	Su	C-Y,	Wang	JW	(2014)	Modulation	of	neural	circuits:	how	stimulus	context	shapes	innate	behaviour	in	Drosophila.	Current	Opinion	in	Neurobiology	29:	9	–	16.	Thistle	R,	Cameron	P,	Ghorayshi	A,	Dennison	L,	Scott	K	(2012)	Male-male	repulsion	and	male-female	attraction	during	Drosophila	Courtship.	Cell	149:	1140	–	1151.		Thorne	N,	Chromey	C,	Bray	S,	Amrein	H	(2004)	Taste	perception	and	coding	in	Drosophila.	Current	Biology	14:	1065	–	1079.		Tian	L,	Hires	SA,	Mao	T,	Huber	D,	Chiappe	ME,	Chalasani	SH,	Petreanu	L,	Akerboom	J,	McKinney	SA,	Schreiter	ER,	Bargmann	CI,	Jayaraman	V,	Svoboda	K,	Looger	LL	(2009)	Imaging	neural	activity	in	worms,	flies	and	mice	with	improved	GCaMP	calcium	indicators.	Nature	Methods	6(12):	875	–	881.		Venken	KJT,	Simpson	JH,	Bellen	HJ	(2011)	Genetic	manipulation	of	genes	and	cells	in	the	nervous	system	of	the	fruit	fly.	Neuron	72:	202	–	230.		Vosshall	LB,	Stocker	RF	(2007)	Molecular	architecture	of	smell	and	taste	in	Drosophila.	Annual	Review	of	Neuroscience	30:	505	–	533.		Wang	Z,	Singhvi	A,	Kong	P,	Scott	K	(2004)	Taste	representations	in	the	Drosophila	brain.	Cell	117:	981	–	991.		Wasserman	S,	Salomon	A,	Frye	MA	(2013)	Drosophila	Tracks	Carbon	Dioxide	in	Flight.	Current	Biology	23:	301	–	306.	Weiss	LA,	Dahanukar	A,	Kwon	JY,	Banerjee	D,	Carlson	JR	(2011)	The	Molecular	and	Cellular	Basis	of	Bitter	Taste	in	Drosophila.	Neuron	69:	258	–	272.			 111	Whitaker	M	(2010)	Genetically	encoded	probes	for	measurement	of	intracellular	calcium.	Methods	in	Cell	Biology	99:	153	–	182.		Wisotsky	Z,	Medina	A,	Freeman	E,	Dahanukar	A	(2011)	Evolutionary	differences	in	food	preference	rely	on	Gr64e,	a	receptor	for	glycerol.	Nature	Neuroscience	1534	–	1541.		Yang	Z,	Yu	Y,	Zhang	V,	Tian	Y,	Qi	W,	Wang	L	(2015)	Octopamine	mediates	starvation-induced	hyperactivity	in	adult	Drosophila.	Proceedings	of	the	National	Academy	of	Sciences	USA	112:	5219	–	5224.	Yapici	N,	Cohn	R,	Schusterreiter,	Ruta	V,	Vosshall	LB	(2016)	A	taste	circuit	that	regulates	ingestion	by	integrating	food	and	hunger	signals.	Cell	165:	1	–	15.		Yarmolinsky	DA,	Zuker	CS,	Ryba	NJP	(2009)	Common	sense	about	taste:	from	mammals	to	insects.	Cell	139:	234	–	244.		Zhang	Y,	Hoon	MA,	Chandrashekar	J,	Mueller	KL,	Cook	B,	Wu	D,	Zuker	CS,	Ryba	NJ	(2003).	Coding	of	sweet,	bitter	and	umami	tastes:	different	receptor	cells	sharing	similar	signaling	pathways.	Cell	112:	293	–	301.		Zhang	YV,	Ni	J,	Montell	C	(2013)	The	molecular	basis	for	attractive	salt	taste	coding	in	Drosophila.	Science	340:	1334	–	1338.		Zhang	YQ,	Rodesch	CK,	Broadie	K	(2002)	Living	synaptic	vesicle	marker:	Synaptotagmin-GFP.	Genesis	34:	142	–	145.		 112	Zhao	GQ,	Zhang	Y,	Hoon	MA,	Chandrashekar	J,	Erlenbach	I,	Ryba	NJP,	Zuker	CS	(2003)	The	receptors	for	mammalian	sweet	and	umami	taste.	Cell	115:	255	–	266.		Zhou	C,	Rao	Y,	Rao	Y	(2008)	A	subset	of	octopaminergic	neurons	are	important	for	Drosophila	aggression.	Nature	Neuroscience	11:	1059	–	1067.								

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