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The biology of deep soil microbacteria Li, Ka Chi Jarvis 2016

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THE BIOLOGY OF DEEP SOIL MICROBACTERIA   by  Ka Chi Jarvis Li  B.Sc., The University of British Columbia, 2011  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF   MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Microbiology and Immunology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   August 2016  © Ka Chi Jarvis Li, 2016 ii  Abstract The use of antibiotics to treat bacterial infections has been one of the most significant breakthroughs in modern medicine. However, drug resistance is increasingly threatening the efficacy of the current repertoire of antimicrobials. The search for novel classes of antimicrobials from microbes in varied natural environments has become a useful approach to this issue. The topic of my thesis is to study the resistome and the microbial composition of deep soil samples collected from the Vancouver campus of UBC, and to use these soils in the isolation of Actinobacteria with the potential of producing new antimicrobials. The detection of antibiotic resistance genes in these soils was carried out by a PCR approach.  I found a spatial relationship between the presence of genes aac(3), erm, vanX and tetM/otrA and the different microbial populations in various layers of soil. The bacterial community compositions of these soils were determined by metagenomic sequencing of the small subunit 16S rRNA gene. The results of these analyses prompted a search in the Actinobacteria-rich soil samples as the sources for isolation of novel antibiotic-producing bacteria. Twenty-two bacterial isolates were isolated and screened for the production of inhibitory compounds against a panel of bacterial pathogens.  The principal focus of this thesis is the study of Microbacterium strains isolated from soil.  Microbacterium is a genus of Actinobacteria first discovered in 1919 by Dr. Sigurd Orla-Jensen. To date, there have been 97 distinct species of microbacteria identified from a wide variety of natural, clinical and manmade environments. Representatives of the genus have been implicated as plant commensals and for the bioremediation of environmental contaminants. The microbacteria have not been studied for the production of antimicrobials. Microbacterium sp. D3N3, isolated from a deep soil sample, produces phenylacetic acid which displays broad-iii  spectrum antimicrobial activity and other bioactivities such as gene activation in Staphylococcus aureus as well as weak additive interactions with the antibiotics tetracycline, colistin, ampicillin and novobiocin.  Four microbacteriophages that infect two Microbacterium strains from this work were isolated from the UBC wastewater treatment plant, sea water and a soil sample from UBC Wreck beach.  iv  Preface  I conducted the majority of experiments and data analyses described in this research program. High-performance liquid chromatography and nuclear magnetic resonance studies of the Microbacterium sp. D3N3 bioactive compound were done in collaboration with Meng Wang and the electron microscopy studies of microbacteriophages was completed by Chris Deeg. The genome sequencing and assembly of M. sp. D3N3 was assisted by Hai Xu and phenotype study of bacterial strains was done by Lando Robillo. I wrote this resulting thesis.  v  Table of Contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iv Table of Contents ...........................................................................................................................v List of Tables ................................................................................................................................ ix List of Figures .................................................................................................................................x List of Abbreviations .................................................................................................................. xii Acknowledgements .................................................................................................................... xiv Dedication .....................................................................................................................................xv Chapter 1: Introduction ................................................................................................................1 1.1 Antibiotics in medical history ......................................................................................... 1 1.2 Novel antimicrobial compounds ..................................................................................... 2 1.2.1 Methods of drug discovery ......................................................................................... 3 1.3 Microbacterium, a bacterial genus of interest................................................................. 4 1.3.1 Microbacteria as opportunistic pathogens .................................................................. 6 1.4 Polyketide synthase ......................................................................................................... 7 1.4.1 Type III polyketide synthases ..................................................................................... 7 1.5 Phenylacetic acid ............................................................................................................ 8 1.6 Microbacteriophages ....................................................................................................... 8 1.7 Thesis objectives ............................................................................................................. 9   vi  Chapter 2: Materials and methods .............................................................................................11 2.1 Soil sample collection and preparation ......................................................................... 11 2.2 Extraction of total soil DNA ......................................................................................... 12 2.3 PCR detection of antibiotic-associated genes in soil DNA .......................................... 12 2.4 Denaturing gradient gel electrophoresis ....................................................................... 14 2.5 16S rRNA pyrotag sequencing of soil samples ............................................................ 14 2.6 Processing and analysis of pyrotag sequence data ........................................................ 15 2.7 Isolation of bacteria from soil ....................................................................................... 15 2.8 Antibiotic resistance profiles ........................................................................................ 16 2.9 Bacterial growth and antimicrobial production assay ................................................... 17 2.10 Salmonella typhimurium luciferase reporter assays ...................................................... 17 2.11 Bioactive compound(s) isolation and identification ..................................................... 18 2.12 Staphylococcus aureus luciferase reporter assays ........................................................ 18 2.13 Antibiotic interaction assays ......................................................................................... 19 2.14 Microbacterium sp. D3N3 genome sequencing ............................................................ 20 2.15 AntiSMASH database screen ........................................................................................ 21 2.16 CARD database screen ................................................................................................. 21 2.17 16S rRNA gene alignment and phylogeny ................................................................... 22 2.18 Phenotypic analyses of microbacteria ........................................................................... 22 2.19 Multilocus sequence typing .......................................................................................... 23 2.20 Microbacteriophage isolation........................................................................................ 23 2.21 Transmission electron microscopy of microbacteriophages ......................................... 24  vii  Chapter 3: Results........................................................................................................................25 3.1 Soil sample collection and DNA extraction.................................................................. 25 3.1.1 PCR detection of antibiotic resistance genes in soil DNA ....................................... 26 3.1.2 PCR detection of phosphoenolpyruvate mutase in soil DNA ................................... 28 3.2 Soil bacterial community analysis by DGGE ............................................................... 29 3.2.1 Bacterial community analysis by 16S rRNA pyrotag sequencing ............................ 31 3.3 Isolation of soil bacteria ................................................................................................ 34 3.3.1 Antibiotic resistance profiles of soil bacteria ............................................................ 36 3.3.2 Screening soil bacteria for production of antimicrobials .......................................... 38 3.3.3 Screening soil bacteria for products of transcription-regulation ............................... 38 3.4 Isolation of antimicrobial compound(s) from Microbacterium sp. D3N3 .................... 39 3.4.1 Mode of action of phenylacetic acid ......................................................................... 43 3.4.2 Phenylacetic acid interactions with antibiotics ......................................................... 44 3.5 Genome sequencing of Microbacterium sp. D3N3 ...................................................... 45 3.5.1 Type III polyketide synthase of Microbacterium sp. D3N3 ..................................... 46 3.5.2 PKS and NRPS in genome-sequenced microbacteria ............................................... 48 3.5.3 The resistome of Microbacterium sp. D3N3 ............................................................ 53 3.6 Microbacterial phylogeny by 16S rRNA gene alignment............................................. 55 3.6.1 Phenotypic tests of microbacteria ............................................................................. 56 3.6.2 Multilocus sequence typing ...................................................................................... 57 3.7 Isolation of microbacteriophages .................................................................................. 63 3.7.1 Transmission electron microscopy of microbacteriophages ..................................... 64  viii  Chapter 4: Discussion ..................................................................................................................66 4.1 Soil sample collection and total DNA extraction ......................................................... 67 4.1.1 Antibiotic-associated genes in soil DNA .................................................................. 68 4.2 Soil bacterial community analyses................................................................................ 70 4.3 Characteristics of PS soil bacteria ................................................................................. 72 4.4 Microbacterium sp. D3N3 and the production of phenylacetic acid ............................ 74 4.5 Biosynthetic potential of microbacteria ........................................................................ 75 4.6 Identity of Microbacterium sp. D3N3 .......................................................................... 77 4.7 Microbacteriophages ..................................................................................................... 78 References .....................................................................................................................................81  ix  List of Tables  Table 2.1       Oligonucleotides employed .................................................................................... 12 Table 2.2       Staphylococcus aureus promoter-lux reporters ...................................................... 19 Table 3.1       Bacterial isolates from PS soil ................................................................................ 35 Table 3.2       Antibiotic resistance phenotypes of PS soil isolates ............................................... 37 Table 3.3       Salmonella typhimurium luciferase reporter responses to soil isolate cultures ...... 39 Table 3.4       Results of AntiSMASH scan of genome-sequenced microbacteria ....................... 49 Table 3.5       Microbacterium sp. D3N3 draft genome CARD hits (loose algorithm) ................ 53 Table 3.6       Microbacterium sp. D3N3 draft genome CARD hits (strict algorithm) ................. 55 Table 3.7       Phenotypic tests of Microbacterium sp. D3N3 and closely related species ........... 57  x  List of Figures  Figure 2.1       Soil sampling sites ................................................................................................. 11 Figure 2.2       Schematic of 96-well plate checkerboard assay .................................................... 20 Figure 3.1       PCR amplification of 16S rRNA gene fragments from PS and SK soil DNA ...... 25 Figure 3.2       PCR amplification of antibiotic resistance gene fragments from PS and SK soil DNA ...................................................................................................................... 27 Figure 3.3       PCR amplification of antibiotic resistance gene fragments from PS and SK bacterial DNA ....................................................................................................... 27 Figure 3.4       PCR amplification of phosphoenolpyruvate mutase (PEP mutase) gene fragment    from PS and SK soil DNA .................................................................................... 28 Figure 3.5       Community 16S rRNA gene fingerprinting by denaturing gradient gel electrophoresis ...................................................................................................... 30 Figure 3.6       Assignment of operational taxonomic units in PS and SK soil samples ............... 32 Figure 3.7       Distribution of bacterial phyla in PS and SK soil communities ............................ 33 Figure 3.8       Antibacterial activity of Microbacterium sp. D3N3 culture                         extract ..................................................................................................................... 40 Figure 3.9       UV light image of thin layer chromatography of Microbacterium sp. D3N3 culture extract .................................................................................................................... 41 Figure 3.10     Proton nuclear magnetic resonance of active HPLC fraction ............................... 42 Figure 3.11     Active HPLC fraction of Microbacterium sp. D3N3 culture extract .................... 42 Figure 3.12     Staphylococcus aureus RN4220 luciferase reporter response to                          phenylacetic acid ................................................................................................... 43 xi  Figure 3.13     Disc diffusion assays testing phenylacetic acid interaction with antibiotics ......... 45 Figure 3.14     Amino acid sequence alignment of Microbacterium sp. D3N3 T3PKS ............... 46 Figure 3.15     Phylogenetic relationship between bacterial and plant T3PKS ............................. 47 Figure 3.16     Simplified 16S rRNA gene identity matrix of Microbacterium sp. D3N3                          and other Microbacterium spp. ............................................................................. 55 Figure 3.17     Phylogenetic trees of genome-sequenced Microbacterium strains                         in MLST analysis ................................................................................................... 59 Figure 3.18     Microbacteriophage isolates infect Microbacterium sp. D1S2O and D1S3 ......... 64 Figure 3.19     Transmission electron micrographs of microbacteriophage attachment to                          host cells................................................................................................................ 65  xii  List of Abbreviations  AIA  Actinomycete isolation agar BA  Bennett’s agar bp  base pair DGGE  denaturing gradient gel electrophoresis DNA  deoxyribonucleic acid HTA  Hickey-Tresner agar ISP4  International Streptomyces Project medium 4 LB  Luria-Bertani LBA  Luria-Bertani agar MHA  Mueller-Hinton agar MIC   minimal inhibitory concentration MSA  mannitol soy agar NRP  nonribosomal peptide NRPS  nonribosomal peptide synthetase ORF  open reading frame OTU  operational taxonomic unit PAA  phenylacetic acid PCR  polymerase chain reaction PDA  potato dextrose agar PEP mutase phosphoenolpyruvate mutase PKS  polyketide synthase xiii  PS  Pharmaceutical Sciences building (UBC) RP-HPLC reversed-phase high performance liquid chromatography SK  Sitka residence (UBC) T1PKS type I polyketide synthase T2PKS type II polyketide synthase T3PKS type III polyketide synthase TSA  tryptic soy agar UPGMA unweighted pair group method with arithmetic mean  xiv  Acknowledgements  I thank my supervisor Dr. Julian Davies for granting me the opportunity to conduct research in his laboratory. I am indebted to his abundant guidance and to the liberty he provided for me to explore my research topics.   I also deeply thank my committee members Drs. William Mohn and Steven Hallam for their kind support, suggestions and encouragements. I would like to thank Meng Wang, from Dr. Raymond Andersen’s lab, who has assisted me in the HPLC fractionation experiments and the determination of the active compound produced by Microbacterium sp. D3N3. I acknowledge Chris Deeg, from Dr. Curtis Suttle’s lab, for helping with the electron microscopy studies of microbacteriophages. I also thank Lando Robillo for completing the phenotypic tests on M. sp. D3N3 and Hai Xu for assisting in the genome sequencing and sequence data assembly of strain D3N3. I thank all of the past and present members of the Davies’ lab for their support of me and my work.  I acknowledge the funding provided by Natural Sciences and Engineering Research Council of Canada’s (NSERC) Undergraduate Student Research Award, which led me to begin my research as an undergraduate student in the Davies’ laboratory, as well as by the MITACS Accelerate program.  I acknowledge my family for their unconditional love and support through my years of studies. And to all my friends from the Davies’ and adjacent laboratories with whom I’ve shared good times during my studies.  xv  Dedication  I dedicate this thesis to my family. 1  Chapter 1: Introduction  1.1 Antibiotics in medical history Bacterial infections plagued human history prior to the discovery of antimicrobial compounds that can effectively treat them. The pre-antibiotic era saw many lives succumb to some of the most treatable infections encountered today. For example, the majority of casualties in the First World War were due to the lack of sanitation and to the untreated infections of battle wounds (Runcie, 2015). The discovery of penicillin by Alexander Fleming led to the realization that compounds with antimicrobial activities can be used as therapeutic agents. This was a revolutionary development in modern medicine which created increased efforts in the search of active compounds (Aminov, 2010). After all, Fleming himself came to the realization of the significance that his discovery spawned.  He stated: "When I woke up just after dawn on September 28, 1928, I certainly didn't plan to revolutionize all medicine by discovering the world's first antibiotic, or bacteria killer…" (Tan & Tatsumura, 2015).  The advent of antibiotics to treat infections gained much overzealous popularity in its infancy. This was clearly evident in the infamous 1940s advertisement suggesting that “Penicillin cures gonorrhea in 4 hours”. However, this false sense of success against microbial infections was short lived. Antibiotic resistance became an abundantly obvious issue and has become the most critical factor for the future of effective treatments of infectious diseases (Hermsen et al., 2012). The misuse of these drugs as the result of erroneous applications and over-prescription have severely complicated the problem by selecting for antibiotic resistant pathogens (Spellberg et al., 2008). We face the imminent danger of returning to a “pre-antibiotic era” where no effective 2  antimicrobial drugs are available to treat infections of highly drug resistant microbes (Clardy et al., 2009; Spellberg et al., 2008).  The issue is compounded by the fact that the discovery of new antibiotics has diminished in recent years (Fair & Tor, 2014). Many old antibiotics such as the polymyxins, phosphomycin, chloramphenicol, rifampicin are being repurposed to treat bacterial infections (Maviglia et al., 2009; Cassir et al., 2014).  However, these drugs are not immune to resistance. It has become a high priority that novel classes of antibiotic drugs with various modes of action are discovered or developed. The majority of compounds in the current antibiotic repertoire have been isolated from bacteria, namely the Actinomycetes (Waksman et al., 1946). They have been a rich source of antimicrobials used in the clinic and/or have served as platforms for chemical modifications to increase drug potency and specificity. This thesis focuses on aspects of antibiotic resistance and biosynthesis in Actinobacteria.   1.2 Novel antimicrobial compounds One of the most effective ways to counter antibiotic resistance is the discovery of new classes of antibiotics. One could argue that novel compounds will inevitably encounter resistance and become obsolete. But the discovery of antimicrobial compounds with new modes of action is still the best approach to offset the problem of drug resistance (Cooper, 2015). The rapid evolution of bacteria is the major factor that leads to the increasing occurrence of antibiotic resistance. However, one could imagine that bacteria may produce antimicrobial compounds with new modes of action as quickly as they develop mechanisms of drug resistance.  Many groups have turned to searching exotic environments of the world to study their characteristics of antibiotic resistance and for the discovery of novel bacteria with the potential of making novel 3  molecules that will serve clinical purposes in the future (D’Costa et al., 2011; Montano and Henderson , 2013).   1.2.1 Methods of drug discovery Classical drug discovery involves using a culture-based method to ferment bacterial cultures in growth media for extended periods of time to produce bioactive natural products (Lewis, 2013). The whole cultures or culture supernatants are then tested for inhibitory actions towards bacterial pathogens. This method remains to be the principal approach for the discovery of antimicrobial compounds. However, a limiting factor is its restriction to studies on culturable microbes, which makes up only a fraction of the total microbial diversity (Bakken et al., 1997). The latter is only made possible for studies through advances in metagenomic sequencing technologies. In addition, culture-based methods are time and labor intensive. Thousands upon thousands of microbial isolates must be screened in order to identify a few strains producing activities which are deemed worthy of further investigations (Lewis, 2013).  With the availability of more accurate and inexpensive DNA sequencing technologies at researchers’ disposal, we can more thoroughly explore the biosphere for its potential for antimicrobial drug biosynthesis (Moir et al.,1999). DNA sequencing serves many applications including sequencing of single genes to genomes, shotgun sequencing for metagenomic studies and functional genomic studies. The genomic approach of antibiotic drug discovery uses environmental DNA sequences or microbial genome sequences to look for novel biosynthetic gene clusters (Miesel et al., 2003). Scientists are able to target specific environments or bacterial 4  genomes of interest for their searches. These methods prove useful in finding cryptic biosynthetic pathways in the unculturable microbes.  The ease and accuracy of modern genome sequencing technologies, allows for the rapid searching of genes related to antimicrobial biosynthesis. This approach enhances the effectiveness of culture-base methods. One can search for biosynthetic gene clusters in thousands of genome-sequenced organisms without the need to carry out screening assays. Sequencing-based techniques also remove some of the problems inherent to culture-based drug discovery. Specific fermentation or assay conditions are required for bacterial isolates to produce the desired active compounds. With the enormous number and variety of microbes in any given screening pipeline, it is difficult to employ all the culture conditions required. Sequence-based approaches give rapid and definitive clues as to whether particular environments or microbes of interest have useful biosynthetic potential. The work in this thesis began with a culture-based approach to isolate bacteria from soils that have not been exposed to clinical concentrations of antibiotics. The strains were tested for their ability to produce inhibitory compounds against a collection of bacteria. This effort led to a focus on an active Microbacterium isolate, which was studied by genome sequencing techniques to identify genes relating to the synthesis of bioactive compounds.  1.3 Microbacterium, a bacterial genus of interest Microbacteria are high G+C content organisms belonging to the Actinobacteria (Funke et al, 1995). They are obligate aerobes that grow in an optimal temperature range of 18-37oC. They are non-sporulating bacteria have small (~0.5μm) and irregular rod/cocci morphology under the 5  microscope. The colony morphology of these bacteria can be small, round and convex shaped. They have characteristic yellow pigmentation, with colonies of various species ranging from creamy white shades to intense yellow-orange (Orla-Jensen, 1919). Microbacteria have been found in various types of soils, in freshwater and marine environments and have shown to cause systemic infections in hospital patients (Kageyama et al., 2007; Dastager et al., 2008; Park et al., 2008; Zhang et al., 2012; Gneiding et al., 2008). Microbacterium spp. have also been isolated from the clean-room environment of a spacecraft assembly facility (Osman et al., 2008). To date, ninety-seven species of Microbacterium have been identified. The majority of species have little more than a 16S rRNA gene sequences and limited phenotypic characteristics (sugar assimilation phenotypes and cell wall/cell membrane compositions) to describe them. The microbacteria are a very tightly related group of bacteria, with 16S rRNA gene sequence identities of 90% or above between species. Some of the identities exceed 98.7%. The 16S rRNA marker alone is insufficient to distinguish among microbacteria. The identification of novel isolates of Microbacterium have turned to the use of classical phenotypic tests for species delineation.  The ecological roles of microbacteria in their natural environments are yet unclear. There has been limited reports on the natural roles and human applications of these bacteria in the literature. Microbacterium testaceum, a plant endophyte, was proposed to have significant biological roles as a plant commensal due to its production of an enzyme, QsdA, which degrades N-acylhomoserine lactones from potential plant pathogens (Morohoshi et al, 2011). The type strains of M. oleivorans and M. hydrocarbonoxydans have been proposed as bioremediation agents for their activities in degrading crude oil (Schippers et al., 2005). Mixed cultures of a Microbacterium strain in conjunction with Rhodococcus degraded polychlorinated biphenyls in 6  contaminated soils (Egorova et al., 2013). The ability of microbacteria to degrade other environmental contaminations, such as antibiotics have been studied. For example, an unidentified strain of Microbacterium was highlighted for its ability to degrade sulfonamide antibiotics in agricultural waste and wastewater (Tappe et al., 2013; Ricken et al., 2015).  Microbacteria have not been studied for their biosynthetic potential in producing antimicrobial compounds. As a member of the Actinobacteria, Microbacterium likely possess biosynthetic determinants such as nonribosomal peptide synthetases (NRPS) and polyketide synthases (PKS). The products of NRPS and PKS clusters have a wide range of bioactive properties including antimicrobial, antiviral, antitumor and immunosuppressant functions (Shen, 2003; Felnagle et al., 2008; Katsuyama & Ohnishi, 2012). A major component of this thesis involved the isolation and identification of antibacterial compound(s) from a bioactive Microbacterium sp. D3N3. The genomic DNA sequence of this strain was searched for the presence of NRPS and PKS genes.  1.3.1 Microbacteria as opportunistic pathogens Microbacteria are not considered to be pathogenic to humans. Most of the species originate from the environment and fail to grow above temperatures of 35oC. However, there are exceptions, certain species thrive at temperatures upwards of 37oC. These latter that grow at elevated temperatures have been associated with systemic infections in hospital patients. They have been isolated from the blood, urine and peritoneal cavity of infected patients, as well as from surgical implants such as catheters (Funke et al., 1995; Gneiding et al., 2008). Mechanisms of virulence or the production of toxins have not been reported for Microbacterium. Clinical isolates of 7  microbacteria have been found to possess moderate levels of drug resistance to ciprofloxacin, rifampicin and cefotaxime (Gneiding et al. 2008).  1.4 Polyketide synthase 1.4.1 Type III polyketide synthases Type III polyketide synthases (T3PKS), previously known as naringenin-chalcone synthases, were originally thought to be found exclusively in plants (Katsuyama & Ohnishi, 2012; Yu et al, 2012). These synthases produce flavonoid compounds, with functions including hormone signaling, pigment production and defense mechanisms against infections. T3PKS were first recognized in bacteria, with the identification of the rppA gene homolog in Streptomyces griseus (Funa et al., 1999). Bacterial T3PKS products have an array of activities and functions such as: the production of the amino acid (S)-3,5dihydroxyphenylglycine for synthesis of balhimycin in Amycolatopsis balhimycina and the formation of phloroglucinol in Pseudomonas fluorescens. Phloroglucinol is used as an antispasmodic drug for gastrointestinal disorders, in the production of explosives, and as a printing ink coupling agent (Katsuyama & Ohnishi, 2012)  Unlike the type 1 and 2 polyketide synthases, which encode gene clusters that produce several enzymes acting in coordination to synthesize their polyketide products, the T3PKS consist of a single gene (Shen, 2003; Katsuyama & Ohnishi, 2012). The protein product of this gene spontaneously homodimerizes to form an active enzyme. The catalytic center of the T3PKS enzyme is characterized by three amino acids, cys164, his303, and asn336 (Medicago sativa numbering) (Jez et al., 2002). This active site is responsible for all of the substrate condensation, 8  elongation and release functions, thus making the T3PKS more functionally intricate than the multi-enzyme nature of T1PKS and T2PKS.  1.5 Phenylacetic acid Phenylacetic acid is produced by plants and bacteria (Sugawara et al., 2015; Kaczmarek & Coykendall, 1980). The compound possesses hormone signaling functions in plants (Sugawara et al., 2015).  It has been suggested that phenylacetic acid acts as a communication signal between plant hosts and their associated bacteria. For example, a strain of Azospirillum brasilense, a well-known plant-growth promoting bacterium, was shown to produce phenylacetic acid (Somers et al, 2005). The antimicrobial activity of phenylacetic acid has been reported, it has broad spectrum antibacterial and antifungal properties (Kim et al., 2004; Hwang et al, 2001; Somers et al., 2005). However, its mode of action remains unclear. The biosynthetic pathway to phenylacetic acid in microbacteria is also unclear. Although in the case of production by Azospirillum it is likely a product of phenylalanine metabolism (Somers et al., 2005).   1.6 Microbacteriophages Six microbacteriophages belonging to the Siphoviridae family, have been isolated and genome sequenced (Hatfull et al, 2016). Transmission electron micrographs of some of these phage isolates indicate icosahedral capsid heads and long tail fibers.  Phage Min1 infects host Microbacterium nematophilum CBX102, and has been suggested to contribute to the virulence of the host against nematodes (Akimkina et al., 2007). Phages Zeta1847, BonaeVitae and Metamorphoo have been isolated from Mycobacterium sp. by undergraduate students at Nebraska Wesleyan University (unpublished). They infect Microbacterium paraoxydans NWU1 9  (Hatfull et al., 2016). Phages SuperFresh and Antoinette were isolated by Audrey Jonas and Gabrielle Gentile (University of Pittsburgh), from soils collected from a garden and parking lot, respectively. Both of these phages infect Microbacterium foliorum NRRL B-24224 (Hatfull et al., 2016). One objective of my thesis was to isolate microbacteriophages that infect Microbacterium isolated from deep soil.   1.7 Thesis objective Scientists have investigated in a large variety of environments for novel bacteria, the antimicrobials they produce and other genes/products of interest. The objective of my thesis is to study the resistome, biosynthetic potential and bacterial community structure within two soil columns from UBC, and to isolate antimicrobial-producing Actinobacteria. The following experiments were conducted to survey collected soils for these characteristics and to study the biology of Microbacterium isolates.  i) To examine the presence of antibiotic resistance genes and the biosynthetic gene, phosphoenolpyruvate mutase, in deep soil layers, the total soil DNA from each sample was extracted and used as template for PCR gene detection.  ii) Two experimental approaches (DGGE and 16S rRNA pyrotag sequencing) were employed to determine the bacterial community structures of the collected soils. These studies provided insights into the distribution and abundance of bacterial phyla among the different horizons of soil. The soils dominated by Actinobacteria were targeted for isolation of bacteria with the potential for the production of antimicrobial compounds. 10  iii) Isolated bacteria were tested for their potential to produce antimicrobial activity against Acinetobacter baumannii ATCC 19606, Micrococcus luteus JVC 1154, Staphylococcus aureus RN4220 and Escherichia coli MG1655. Spent culture supernatants of the isolates were tested for inhibition of the tester strains above. To test for the isolates’ ability to produce compound(s) that modulate gene expression, they were also assayed for light production using a collection of Salmonella typhimurium lux reporter strains.  iv) Microbacterium sp. D3N3 culture supernatant inhibited the growth of a Staphylococcus and a Micrococcus strain. Strain D3N3 was grown to stationary phase and extracted with ethyl acetate. The extract was further tested for antimicrobial activity, fractionated by thin layer chromatography and reversed phase high-performance liquid chromatography to purify bioactive compound(s).  v) The antimicrobial activity of phenylacetic acid (PAA) isolated from M. sp. D3N3 was tested against bacterial pathogens. Other properties of PAA such as its mode of action and its potential interaction with other inhibitors were studied.  vi) The isolation of microbacteriophages was done using host bacteria isolated from soil and from the UBC wastewater treatment pilot plant. Phage morphology and host attachment were visualized by transmission electron microscopy. 11  Chapter 2: Materials and methods  2.1 Soil sample collection and preparation  The soils samples used in this project were collected from two sites on the Vancouver campus of the University of British Columbia (Fig 2.1). The excavations of the Pharmaceutical Sciences building (PS) site in September 2010 and the adjacent Sitka Residence (SK) site in May 2011 provided opportunities to collect soils at various levels from the surface to 25 feet underground. Specifically, soils from the surface, 10 16, 18 and 19ft were collected from the PS site and 5, 10, 15, 20 and 25ft were collected from the SK site.  Care was taken to collect the undisturbed soils that were a few inches within the walls of the collection sites. These sandy/ sandy loam sediments were processed by removing large pebbles during their collection. The samples were stored in sterile 50ml tubes and stored at 4oC until use.  Figure 2.1.  Soil sampling sites. The Pharmaceutical Sciences Building (left) and Sitka Residence (right) were the sampling sites for this study. A total of 10 soil samples were collected at various depths at both sites (ground surface to 25 feet underground).  12  2.2 Extraction of total soil DNA Total soil DNA was extracted using the FastDNA spin kit for soil (MP Biomedicals, Santa Ana, CA, USA) according to manufacturer’s instructions. The FastPrep-24 tissue and cell homogenizer (MP Biomedicals, Santa Ana, CA, USA) was used to homogenize soil samples using homemade lysing matrix tubes consisting of 0.5g of 1.5mm ceramic beads and 0.5g of 0.1mm silica beads. Samples were treated for 30 seconds at the highest homogenization setting. The eluted DNA was stored at 4oC until use and at -20oC for extended storage.  2.3 PCR detection of antibiotic-associated genes in soil DNA PCR assays were used to study the distribution of selected antibiotic resistance genes in total soil DNA samples. Approximately 200-300ng of each soil DNA were used as PCR templates. The genes aac(3), bla, erm, tetM/otrA and vanX were the targets of detection. Primers for DNA amplification are listed in Table 2.1.  Genomic DNA of Streptomyces coelicolor A3(2) substrain CH999 was used as positive control for amplification of all five genes. The various PCR conditions for each primer set were previously described (D’Costa et al., 2011). The detection of the phosphoenolpyruvate mutase gene in soil DNA was carried out using the degenerate primer set CHIpepmutF1 and CHIpepmutR2 (Table 2.1).  Table 2.1. Oligonucleotides employed. Oligonucleotide                        Nucleotide sequence 5’ to 3’                              Source  16S_7F    GAGAGTTTGATCCTGGCTCAG              This study 16S_27F   AGAGTTTGATCMTGGCTCAG              (Weisburg et al., 1991) 13  Oligonucleotide                        Nucleotide sequence 5’ to 3’                              Source  16S_517F  GCCTATTACCGCGGCAGCTGGC                           This study 16S_1511R  CGGCTACCTTGTTACGACTTC                               This study aac(3)_F  CTGGAACGACGCTCCGCCGTA   (D’Costa et al., 2011) aac(3)_R  GGCGCGCCGAGGAGCAGCA    (D’Costa et al., 2011) bla_F   CCTCGCCCGGCGCGTCCAGTA    (D’Costa et al., 2011) bla_R   AGCAGGTTGGCCGCGGTGTTGTC   (D’Costa et al., 2011) erm_F   GCTCTCGCAGAACTTCCTCGC    (D’Costa et al., 2011) erm_R   AGCCGGGGGTCGATCTCGTAG   (D’Costa et al., 2011) tetM/otrA_F  CCCCGGGACACCCCGACTTC    (D’Costa et al., 2011) tetM/otrA_R  CGGCACGGTCGATCTTGTTGA    (D’Costa et al., 2011) vanX_F   CCAAGTACCCCACGTGGGACAAC   (D’Costa et al., 2011) vanX_R   CTTCGTCCGGCCGTCCTCC    (D’Costa et al., 2011)  atpD_F   GGCAAGGTCTTCAACGTGACCGGC   (Guo et al., 2008) atpD_R   ACGGCCGGGTACAGGCCCTTCG   (Guo et al., 2008) gyrB_F   GTCCTGACGGTGCTGCACGCC    (Guo et al., 2008) gyrB_R   CTCGAGCGAGATGTGCCGGACG   (Guo et al., 2008) recA_F   GCATCGCCGCGTTCATCGACGC   (Guo et al., 2008) recA_R   CCATCTTGTTCTTCACGACCTTGACGCG  (Guo et al., 2008) rpoB_F   ATGACCACGCAGGACATCGAGGCC   (Guo et al., 2008) rpoB_R   CGTCCTCGAAGTTGTGGCCTTCCC   (Guo et al., 2008) trpB_F   CGGGTCGCACAAGATCAACAACGTGC  (Guo et al., 2008) trpB_R   CTCGATCGCCGGGATGATGCCCTC   (Guo et al., 2008)  CHIpepmutF1  CGCCGGCGTCTGCNTNGARGAYAA   (Eliot et al., 2008) CHIpepmutR2  GGCGCGCATCATGTGRTTNGCVYA   (Eliot et al., 2008)  T3PKS_F  GTGGATCCGCTCACGCGTGCTCC   This study T3PKS_R  GGTGGATCCATGACCACGAGCGTCCTGT  This study  14  2.4 Denaturing gradient gel electrophoresis Prior to 16S rRNA pyrotag sequencing to study the bacterial community structures of the PS and SK site soils, denaturing gradient gel electrophoresis (DGGE) was carried out to fingerprint the 16S rRNA genes amplified from the samples. DGGE gels was prepared with a 0 to 100% gradient of denaturing agents, urea and 40% formamide solution. The 0% denaturing solution of the gel composed of 4.5ml of 40% acrylamide/bis-acrylamide (19:1), 0.6ml 50X TAE buffer and 24.9ml of deionized water, while the 100% denaturing solution has deionized water replaced with 12ml of the aforementioned formamide solution and 12.6g of urea. 4.5ml of TEMED was added to both solutions before they were loaded onto the gradient wheel apparatus (Bio-Rad Laboratories, CA, USA) to cast the gel.  The 490bp γ-region of the 16S rRNA gene was amplified from total soil DNA samples using the 16S_27F and 16S_517R primer pair (Table 2.1). The concentration of amplicons from each sample was normalized, and 300ng of each DNA was loaded per well of the DGGE gel. The loaded gel was placed in the gel tank equipped with temperature regulator and buffer agitator (Bio-Rad Laboratories, CA, USA). The gel was run at 60oC at 20V for 10min before the voltage was increased to 200V for the next 11 hrs. The finished gel was then removed from the cast, stained with a 0.1mg/ml ethidium bromide solution for 1hr and visualized with a UV transilluminator.    2.5 16S rRNA pyrotag sequencing of soil samples The bacterial community structures of each PS and SK site soil sample were investigated by metagenomic sequencing of the 16S rRNA gene. The V6-V8 hypervariable regions of the gene were amplified from the total DNA extracted from each soil sample using the primers 16S_926F 15  (5’-CCTATCCCCTGTGTGCCTTGGCAGTCTCAGAAACTYAAAKGAATTFRCGG-3’) and 16S_1392R (5′-CCATCTCATCCCTGCGTGTCTCCGACTCAG-“XXXXX”ACGGGCGTGT GTRC-3’) (Allers et al., 2013). The reverse primer has a unique 10-bp barcode sequence (shown as –“XXXXX”- above) to differentiate each of the soil samples for multiplex sequencing. Approximately 200-300ng of total soil DNA was used as PCR template. The PCR conditions were 95 °C for 3 min, 95 °C for 30s (25 cycles), 50 °C for 45s, and 68 °C for 90s and a final 68 °C extension period of 10 min. PCR amplicons were purified using the Illustra GFX PCR DNA purification kit (GE Healthcare Life Sciences, PA, USA) then quantified with the PicoGreen assay (ThermoFisher Scientific, MA, USA). The samples were submitted for 454 pyrotag sequencing (Génome Québec).  2.6 Processing and analysis of pyrotag sequence data Approximately 88,000 pyrotag sequences were obtained from the ten soil samples studied. The reads were processed with the bioinformatics program, Mothur (Schloss et al., 2009), using default parameters provided in the 454 pyrotag analysis tutorial. The 10-bp unique barcodes for each of the ten samples were removed prior to subsequent steps. Reads from each soil sample were analyzed separately. The resulting high quality sequences were assigned operational taxonomic units (OTU) for phylogenetic analysis.   2.7 Isolation of bacteria from soil The soils samples collected from the UBC Pharmaceutical Sciences were used to isolate bacteria with the potential to produce bioactive small molecules. 0.1g of each soil was mixed with 2ml of 0.15% NaCl and 0.01% TritonX100. The suspension was vortexed at full speed for 1 minute and 16  allowed for larger particulates to settle before serial dilution and spread plating. 100μl of each 10 fold diluted suspension (10-2 to 10-6) was plated onto International Streptomyces Project medium 4 (ISP4), Luria-Bertani agar (LBA), tryptic soy agar (TSA), mannitol soy agar (MSA), Bennett’s agar (BA), potato dextrose agar (PDA), Hickey-Tresner agar (HTA), and actinomycete isolation agar (AIA). All media were supplemented with cycloheximide, benomyl and nalidixic acid at final concentrations of 50μg/ml, 20μg/ml and 20μg/ml, respectively, to select against the growth of Gram negative bacteria and fungi. The isolation plates were incubated at 30oC from overnight to up to three weeks for isolated bacterial colonies to appear. Single bacterial colonies were selected at random and subcultured to purity in their respective isolation media without antibiotic supplementation. Bacterial isolates were maintained on their respective isolation media and stored at 4oC. Some isolates were preserved at -80oC in glycerol stocks prepared by mixing 500μl of stationary phase cultures with 500μl of 50% glycerol in sterile deionized water. Working cultures of the strains were grown in LB medium for the ease of propagation and assays.  2.8 Antibiotic resistance profiles Soil isolates were tested for their antibiotic resistance profiles using disc diffusion assays. The overnight cultures of the isolates were inoculated into 15ml of 0.7% soft agar and overlaid onto fresh LBA plates (with NaCl removed from the original medium recipe). Commercially available Sensi-Disc antibiotic discs (BD medical, NJ, USA) were placed on the overlays and incubated inverted overnight at 30oC. The size of inhibition zones was observed and recorded.  17  2.9 Bacterial growth and antimicrobial production assay Bacterial isolates were maintained on their respective isolation media with no antibiotic supplementation. The isolates were fermented in 3ml cultures for 5 days using Luria-Bertani (LB) medium. Small volumes of the cultures were collected at days 1, 2, 3 and 5 of the fermentation process and tested for growth inhibition against tester bacteria: Acinetobacter baumannii ATCC 19606, Micrococcus luteus JVC 1154, Staphylococcus aureus RN4220 and Escherichia coli MG1655. The tester bacteria were grown in LB overnight and 5μl of the cultures were inoculated into 15ml of 0.7% soft agar and overlaid onto fresh Mueller-Hinton agar (MHA) plates. The fermentation cultures were centrifuged for 2 minutes at maximum speed to achieve cell-free supernatants. 15μl of each supernatant was impregnated on a sterilized paper disc and placed onto the tester bacteria overlays. The plates were incubated inverted at 37oC overnight and checked for zones of inhibition.  2.10 Salmonella typhimurium luciferase reporter assays The production of bioactive small molecules from soil isolates was tested. The soil bacterial isolates were streaked onto LBA plates and incubated at 30oC until growth was visible. The plates were then overlaid with 5ml of 0.7% soft agar inoculated 5μl of each reporter strain. Five Salmonella typhimurium 14028 pCS26 promoter-lux constructs (ydcW, tsr, phoB, fadB and yrbC) were the reporter systems used (Yim et al., 2006). Rifampicin 5μg discs (BD and company, NJ, USA) were used as positive light control. The plates were incubated inverted at 37oC for 18hr before detection of light induction with a chemiluminescence camera (DNR Bio-Imaging Systems, Jerusalem, Israel). The light responses of each reporter were recorded and compared against the that of the rifampicin control. 18  2.11 Bioactive compound(s) isolation and identification The collection of bioactive compound(s) from Microbacterium sp. D3N3 was achieved by extracting the culture with ethyl acetate. The crude organic extract was evaporated to dryness using a rotary evaporator. A small amount of the dried extract was dissolved in 100μl of fresh ethyl acetate and spotted onto a silica plate for thin layer chromatography separation. A mobile phase composed of toluene, dioxane and acetic acid (90:25:4) was used. The separated bands were visualized under UV light, scraped from the glass backing of the plate and re-extracted with ethyl acetate for antimicrobial activity testing. The crude extract was also separated using reversed-phase high performance liquid chromatography with a LH-20 sephadex HPLC column (GE Healthcare Life Sciences, PA, USA). The RP-HPLC fractions were tested for antimicrobial activity. A single active fraction was subjected to proton nuclear magnetic resonance spectroscopy to identify its content(s).  2.12 Staphylococcus aureus luciferase reporter assays The mode of action of phenylacetic acid (PAA) was tested by gene regulation testing of a  Staphylococcus aureus RN4220 promoter-lux fusion reporter panel (Mesak et al., 2010). The reporter library clones are listed in Table 2.2. 0.7% soft agar overlays of each reporter was poured onto fresh LBA plates without NaCl addition. Sterile paper discs impregnated with 1mg, 0.5mg, 0.25mg, 0.125mg and 0.0625mg PAA were placed onto the reporter overlays along with the appropriate antibiotic discs as positive controls.     19  Table 2.2. Staphylococcus aureus promoter-lux reporters Reporter clones   Promoter-lux fusion   Light induction controls           A   tet-lux   novobiocin B   recA-lux   levofloxacin C   recA-lux   novobiocin D   recA-lux   ciprofloxacin E   recA-lux   mitomycin C F   recA-lux   levofloxacin G   SAOUHSC_02631-lux    ciprofloxacin H   SAOUHSC_T0008-lux    ciprofloxacin I   SAOUHSC_01895-lux    novobiocin J   SAOUHSC_00545-lux    penicillin G K   SAOUHSC_00535-lux   ciprofloxacin L   SAOUHSC_00007-lux    ciprofloxacin M   SAOUHSC_00694-lux    ciprofloxacin N   SAOUHSC_01100-lux   ciprofloxacin   2.13 Antibiotic interaction assays The interaction of PAA with antibiotics was tested using disc diffusion assays on Acinetobacter baumannii ATCC 19606. A. baumannii was inoculated into 5ml of 0.7% soft agar and overlaid onto Mueller-Hinton agar. A 1mg PAA disc along with one commercially prepared antibiotic disc (5mm distance from each other) was placed onto the overlay. The plates were incubated inverted at 37oC overnight. The shapes of the inhibition zones were compared to those of the phenylacetic acid or antibiotic controls. The PAA-antibiotic combinations that exhibited positive interactions were further tested by the checkerboard assay method in order the estimate the fractional inhibitory concentration to determine synergism. The minimal inhibitory concentration of PAA and interacting antibiotics were obtained as the baseline for A. baumannii ATCC 19606. The checkerboard assay was set up with final PAA concentration starting at 1024μg/ml and 20  diluted 2-fold across the 96 well plate from columns 1 to 12, as well as the test antibiotic at their appropriate starting concentrations being diluted 2-fold from row A to H (Fig 2.2). The A. baumannii strain was inoculated to the test plates and incubated at 37oC overnight. The fractional inhibitory concentration (FIC) is calculated using the formula: FIC = MICPAA(combined)/ MICPAA(alone) + MICantibiotic(combined)/ MICantibiotic(alone). When the FIC value between two putatively synergistic compounds is calculated to be under 0.5, they are deemed to be interacting synergistically.       High                                                                                 low                                   High                                     Low  Figure 2.2.  Schematic of 96-well plate checkerboard assay. PAA is diluted across the columns from high to low concentration; likewise, the antibiotic tested is diluted down the rows.     2.14 Microbacterium sp. D3N3 genome sequencing The genomic DNA of M. sp. D3N3 was extracted using the QIAamp DNA mini kit (Qiagen, Hilden, Germany). Genomic DNA was resuspended in the elution buffer provided and 1.15μg of DNA was sent to Shanghai Hanyu Bio-Tech in Shanghai, China, for paired-end shotgun 21  sequencing using the Illumina HiSeq2000 platform (Illumina, San Diego, USA). DNA was ultrasonicated and 180bp and 500bp fragments were selected for pre-treatment using the TruSeq DNA sample prep kit (Illumina, USA). The treated fragments of each selected size were used to generate genomic DNA libraries using the TruSeq pair-end cluster kit (Illumina, USA) and sequenced. Genome sequence assembly was completed using Velvet (version 1.2.03) (Zerbino & Birney, 2008). The generation of sequence scaffolds was completed using the SSPACE software (Boetzer et al., 2011). Gene predictions from the genome scaffolds were done using the Glimmer software (Delcher et al., 1999).  2.15 AntiSMASH database screen  The genome sequence scaffolds of M. sp. D3N3 in fasta file format were uploaded to the AntiSMASH database server to scan for biosynthetic gene clusters (Medema et al., 2011). The default settings were selected and the long runtime scan was used. The ClusterFinder algorithm was enabled and all the parameters under the “BLAST comparison to other gene clusters” and the “Additional annotations” categories were checked. Published microbacterial genome sequences were also scanned using AntiSMASH in the same manner to search for biosynthetic genes common among different species of the genus. The results of the search in the M. sp. D3N3 genome were further analyzed to verify the identity of the genes matched to the database.  2.16 CARD database screen The draft genome of M. sp. D3N3 was scanned with the Resistance Gene Identifier function of the Comprehensive Antibiotic Resistance Database (McArthur et al., 2013). The program’s three search algorithms were used. The perfect algorithm detects exact matches to gene sequences in 22  the database, the strict algorithm detects matches which allow for variations in sequence identity and the loose algorithm detects low confidence sequence matches to allow for the discovery of novel resistance genes.   2.17 16S rRNA gene alignment and phylogeny The 16S rRNA gene sequence of M. sp. D3N3 was aligned with those of 83 other microbacterial species. The ClustalW alignment algorithm was used within the MacVector software (MacVector Inc., NC, USA) along with default parameters. All sequences were manually adjusted to 5’ to 3’ orientation prior to alignment. The 16S rRNA gene of Mycobacterium iranicum CCUG 52297 was used as an outlier sequence in the alignment. A sequence identity matrix was generated from the alignment to identify the closest relatives of M. sp. D3N3.  2.18 Phenotypic analyses of microbacteria The sugar fermentation characteristics of three PS soil microbacteria, M. sp. D3N3, M. sp. D3N3, M. sp. D3N3, two UBC wastewater treatment pilot plant isolates, M. sp. JVC 1784 and M. sp. JVC 1785 and M. testaceum IFP12675 (Zinniel et al., 2008) were studied. The microbacteria were grown to exponential phase and inoculated into 3ml of phenol red broth (1% trypticase, 0.5% NaCl, 0.1% beef extract, and 0.0018% phenol red) supplemented with 1% of carbohydrates: arabinose, mannitol, galactose, sucrose, mannose, trehalose, lactose, glucose, raffinose, sorbitol, ribose, rhamnose and fructose. The phenol red indicator turns yellow indicating acid production from sugars utilized by the strains, while a red color suggests the sugar is not being utilized. Additional tests such as NO3 assimilation, gelatinase, indole-motility, 23  triple sugar iron slant, Simmon’s citrate, urease and DNase tests were also completed for these strains.  2.19 Multilocus sequence typing A multilocus sequence typing analysis was used to study microbacterial classification using the rpoB, trpB, atpD, gyrB, and recA marker genes. The sequences were collected from the M. sp. D3N3 draft genome sequence scaffolds and of thirty-nine microbacterial genomes on GenBank. The marker gene sequences were manually adjusted to a 5’ to 3’ orientation prior to sequence alignments. The Jukes-Cantor distance method was used to align the sequences of each gene using the MacVector software (MacVector Inc., NC, USA) with default parameters provided. Phylogenetic trees of the individual genes were constructed using the UPGMA method with bootstrapping at 1000 resampling repetitions. A concatenated phylogenetic tree was also created by alignment of the joint sequences of the five genes and 16S rRNA. Each of the trees were evaluated for their ability to predict phylogeny by comparison against a 16S rRNA gene tree of the same microbacterial strains.  2.20 Microbacteriophage isolation The microbacteriophages isolated originated from a sludge sample of the UBC wastewater treatment pilot plant, seawater and a soil sample from Wreck beach. All raw samples were passed through 0.22μm filters to remove any debris and microorganisms. The wastewater sludge sample was stored at 4oC and allowed to settle for large particulates to flocculate before the filtration process. Seawater was filtered without pretreatment, while the soil sample was resuspended in SM buffer (100mM sodium chloride, 10mM magnesium sulfate heptahydrate and 24  50mM Tris-HCL pH 7.5) and allowed to settle before filtration. 50ml of each filtrate was added to an equal volume of a mixture of cultures consisting of eight Microbacterium isolates grown to stationary phase. These strains include M. sp. D3N3, M. sp. D1S3,  M. sp. D1S2O (isolated from PS soil samples), M. sp. JVC 1714, M. sp. JVC 1719, M. sp. JVC 1784, M. sp. JVC 1785 (isolated from UBC wastewater treatment pilot plant sludge samples, and M. testaceum IFP12675 (Zinniel et al., 2008). The culture-filtrate mixtures were incubated at 30oC and gently shaken at 50rpm overnight. The mixtures were then filtered through 0.22μm filters to remove microbacterial cells. The phage-containing filtrates were then spotted onto LBA plates inoculated with each of the eight microbacteria mentioned above and incubated at 30oC overnight to observe for plaque formation. Individual phage plaques were extracted from the agar using the tip of a sterile Pasteur pipette and transferred to 100μl of SM buffer. Each phage stock was stored at 4oC.  2.21 Transmission electron microscopy of microbacteriophages The microbacteriophage samples used were prepared from areas of infection on LBA plates inoculated with host bacteria M. sp. D1S3, and M. sp. D1S2O. Specifically, agar plugs from the areas with host cell lysis were collected and resuspended in SM buffer. The suspension was then vortexed at maximum speed for 2 seconds to break up the agar plugs followed by overnight storage at 4oC. Uninfected controls of the host cells were collected in the same manner. 10ul of each preparation was deposited onto the carbon surface of a formvar-carbon coated 400 mesh copper grid (TedPella, CA, USA) and stored in the dark at 4oC overnight. The residual liquids were removed from the grids and stained with 1% uranylacetate for 20 seconds and imaged with a Hitachi H7600 transmission electron microscope.25  Chapter 3: Results  3.1 Soil sample collection and DNA extraction The construction excavation of the Pharmaceutical Sciences Building (PS) in 2010 and the adjacent Sitka Residence (SK) in 2011 provided opportunities of collecting deep soil samples from the Vancouver campus of the University of British Columbia. Five samples were collected from each site, with soil depths of 0, 10 16, 18 and 19ft collected from the PS site and 5, 10, 15, 20 and 25ft collected from the SK site. After processing the soil samples to remove rocks and debris, the soils were subjected to total DNA extraction. The extracted DNA samples were at concentrations below the detection limits of agarose gel electrophoresis. However, the samples were used as template DNA in the PCR amplification of a 16S rRNA fragment (using primer pair 16S_27F and 16S_517R, Table 2.1) to verify the presence of DNA suitable for PCR studies. The 16S rRNA gene fragment was amplified from all 10 soil DNA samples (Fig 3.1).                                                   ________PS_________     ________SK_________                      1kb   (-)     (+)     0’    10’   16’    18’   19’    5’     10’    15’    20’    25’        Figure 3.1. PCR amplification of 16S rRNA gene fragments from PS and SK soil DNA.  Lane 1 is the GeneRuler 1kb ladder (ThermoFisher Scientific, MA, USA) with labeled reference size bands. Lane 2 is the PCR negative control with no template DNA added. Lane 3 is the PCR positive control with 1μl of E. coli MG1655 genomic DNA as template. Lanes 4-8 (blue) represent the 0, 10 16, 18 and 19ft samples of PS site and lanes 9-13 (green) are the 5, 10, 15, 20 and 25ft samples of the SK site.  26   3.1.1 PCR detection of antibiotic resistance genes in soil DNA Total soil DNA was used for PCR amplification of resistance genes from Streptomyces: aac(3), bla, erm, tetM/otrA and vanX. The bla, and erm gene fragments were not detected in any of the PS and SK soil DNAs (data not shown). The tetM/otrA gene fragment was detected in all soil samples from both sites with the exception of the 15ft sample from the SK site (Fig 3.2 a). The aac(3) gene was only detected in the 18ft sample of the PS site and the vanX gene was detected in the 10 and 16ft samples of the PS site and 5ft sample of the SK site (Fig 3.2 b and c). Due to a limited total soil DNA, replication of the PCR experiment was not possible. As substitutes of total soil DNA, the DNA extracted from mixed bacterial cultures from each soil sample was used to screen for resistance genes using the same oligonucleotide primer sets (Table 2.1). The tetM/otrA gene was detected in all of the culture DNA samples except for the 18ft PS soil culture (Fig 3.3 a). The aac(3) was detected only in the 10ft cultures of both PS and SK soils (Fig 3.3 b). No bla, erm and vanX fragments were detected in any of the culture DNA extracts (data not shown).                                                27                                   ___________PS_________      __________SK__________                      1kb      0’      10’      16’    18’    19’       5’    10’     15’      20’     25’    (+)    (-)       Figure 3.2. PCR amplification of antibiotic resistance gene fragments from PS and SK soil DNA.  The a) 175bp tetM/otrA, b) 300bp aac(3) and c) 220bp vanX gene fragments were detected in total soil DNA using PCR amplification. Lane 1 is the GeneRuler 1kb ladder (ThermoFisher Scientific, MA, USA). Lanes 2-6 (blue) are the 0, 10 16, 18 and 19ft samples of PS site and lanes 7-11 (green) are the 5, 10, 15, 20 and 25ft samples of the SK site. Lane 12 is the PCR positive control using Streptomyces coelicolor A3(2) substrain CH999 genome DNA template. Lane 13 is the PCR negative control with no template DNA added.                                                        ______PS_____     ______SK_______       1kb  (-)   0’   10’  16’  18’    5’  10’  15’  20’  25’                                       a                  tetM/otrA                                     b                      aac(3)  Figure 3.3. PCR amplification of antibiotic resistance gene fragments from PS and SK bacterial DNA.  The a) 175 bp tetM/otrA b) 300bp aac(3) gene fragments were detected in the mass bacterial culture DNA using PCR amplification. Lane 1 is the GeneRuler 1kb ladder (ThermoFisher Scientific, MA, USA). Lane 2 is the PCR negative control with no template DNA 28  added. Lanes 3-6 (blue) are the 0, 10 16 and 18ft samples of PS site and lanes 7-11 (green) are the 5, 10, 15, 20 and 25ft samples of the SK site. Lane 12 is the PCR positive control using Streptomyces coelicolor A3(2) substrain CH999 genome DNA template. Lane 13 is the PCR negative control with no template DNA added.   3.1.2 PCR detection of phosphoenolpyruvate mutase in soil DNA Total soil DNA was used as PCR template to detect for the phosphoenolpyruvate mutase (PEP mutase) gene. The gene is involved in the production of natural products containing carbon-phosphorus bonds, such as phosphomycin.  The potential of PS and SK soil communities for production of C-P bond-containing compounds was studied. The 406bp fragment of the gene was amplified using the CHIpepmutF1 and CHIpepmutR2 primer set (Table 2.1). The gene was detected in the 5, 10 and 25ft soil DNA extracts of the SK collection site (Fig 3.4).                                                  _________PS___________     _________SK___________             100bp     0’    10’    16’     18’     19’       5’      10’     15’     20’    25’           PEP mutase   Figure 3.4. PCR amplification of phosphoenolpyruvate mutase (PEP mutase) gene fragment from PS and SK soil DNA.  The 406bp PEP mutase gene fragment was detected in 5, 10 and 25ft soil DNA samples of the SK site. Lane 1 is the GeneRuler 100bp ladder (ThermoFisher Scientific, MA, USA). Lanes 2-6 (blue) are the 0, 10 16, 18 and 19ft samples of PS site and lanes 7-11(green) are the 5, 10, 15, 20 and 25ft samples of the SK site.    29  3.2 Soil bacterial community analysis by DGGE The bacterial communities within the various soil layers were studied using denaturing gradient gel electrophoresis (DGGE). This analysis provides a visual representation of the potential similarities and differences of the bacterial populations in soil columns which are close in proximity. The 490bp γ-region of the 16S rRNA gene was successfully amplified from each of the 10 soil DNA samples. The amplicons were run on a DGGE gel for fingerprinting analysis (Fig 3.5). The positive control lane contains the 16S rRNA gene fragments amplified from eight SK soil isolates. At least eight clear bands appear in this control lane, suggesting the differentiation of amplicons of distinct phylogeny. The amplicon banding profiles of the 0, 10, 16 and 18ft samples of PS site are highly similar; however, the 19ft sample from the site is starkly different. The band profiles for the 5, 10, 15, 20 and 25ft samples for SK appear much fainter in this gel, despite the normalization of DNA amounts loaded to each well. There is clear variation between each of these samples.  The results suggest that PS soils have less diverse bacterial populations than those of the SK soil column. There are also some similarities in banding pattern between the 19ft PS sample and the 15ft SK sample.         30                                        __________PS________      __________SK_________                              (+)     0’     10’    16’    18’   19’      5’     10’    15’     20’    25’                    Figure 3.5. Community 16S rRNA gene fingerprinting by denaturing gradient gel electrophoresis.  A 0-100% denaturing gradient gel was produced with urea and formamide as the denaturing agents. 300ng of each amplified DNA sample was loaded per lane. Lane 1 is the positive control consisting of 16S rRNA gene amplicons from 8 laboratory strains combined. Lanes 2-6 (blue) are the 0, 10 16, 18 and 19ft samples of PS site and lanes 7-11 (green) are the 5, 10, 15, 20 and 25ft samples of the SK site     31  3.2.1 Bacterial community analysis by 16S rRNA pyrotag sequencing The bacterial communities of the soil samples were studied using 454 pyrotag sequencing of the 16S rRNA gene. The 466bp V6-V8 hypervariable region of the 16S rDNA was the target sequence for this study. A minimum of 30ng of 16S rDNA amplicon from each sample was obtained after amplification with the barcoded primer pairs, and submitted for pyrosequencing. The resulting raw data from the sequencer were processed with the Mothur software (Schloss et al., 2009). A total of 88,680 sequence reads were obtained for all ten soil samples. The reads were not equally distributed among the samples. The sequences from each sample were analyzed independently, using identical software parameters across all samples. After the removal of sequence barcodes, chimeric and low quality sequences, the resulting 51,482 high quality reads were analyzed yielding 5021 unique operational taxonomic units (OTU) which are not equally distributed among the 10 samples (Fig 3.6). The OTUs of each soil sample were then assigned phylogenies at the phylum level (Fig 3.7).  In the PS soil populations, 55% to 78% of the sequences belonged to the Actinobacteria group. Interestingly, the deepest level collected from this site (19ft) showed a dominance of Proteobacteria. The most prevalent bacterial phylum in the SK dataset is the Proteobacteria, representing 28% to 47% of sequences. At the 20 feet sample of this site, there is an abrupt change to Actinobacterial predominance. The SK communities also exhibit richer diversity of OTU than those of the PS soils. Due to the high abundance of Actinobacteria in the PS samples, they were chosen as the source for isolation of bacteria to test for production of antimicrobials and bioactive compounds.  32                                           0’        10’      16’      18’       19’       5’        10’      15’      20’       25’                               ___________________________    ___________________________                    PS                                                    SK  Figure 3.6. Assignment of operational taxonomic units in PS and SK soil samples.         33                                                    0’             10’           16’           18’            19’             5’           10’            15’           20’           25’                 _____________________________________           ______________________________________                   PS                                                                                SK Figure 3.7. Distribution of bacterial phyla in PS and SK soil communities. Phyla assignments based on 16S rRNA gene pyrotag sequencing.  34   3.3 Isolation of soil bacteria PS and SK soil suspensions were plated on a variety of isolation media to identify bacterial strains for assays in production of bioactive small molecules. Many of the isolation plates were continuously incubated for up to three weeks before any bacterial growth was observed. Numerous types of bacterial colonies appeared on most of the culture media used. However, many of the plates were overcrowded with colonies. Only a small number of fast-growing single colonies were chosen for purification and maintained for further studies. Twenty-two strains were isolated from the PS soils. The majority of the isolates were identified by 16S rRNA gene sequencing. Morphologies of the isolates were observed with a compound light microscope. The Gram reaction of the isolates are listed in Table 3.1.             35  Table 3.1. Bacterial isolates from PS soil.    PS soil   Isolates Sequence Blast identification Isolation media Gram stain reaction microscopic morphology                   S1        uncultured bacterium ISP4 (+) filaments matrix of filaments     S2        Staphylococcus epidermidis ISP4 (+) cocci motile cocci, mostly paired 0ft   S3        Micrococcus luteus TSA (+) cocci motile cocci, mostly paired     S6        Staphylococcus caprae TSA (+) cocci fast motile cocci, singles     S7        Micrococcus luteus TSA (+) cocci fast motile cocci, singles     D11        ND* ISP4 ND cocci, clusters     D12        Bacillus sp. TSA (+) filaments ND     D1S1        uncultured bacterium TSA (+/-) filaments filamentous 10ft   D1S2Y        Staphylococcus lugdunensis ISP4 (+) cocci motile cocci, singles     D1S2O        Microbacterium oxydans ISP4 (+) short rods ND     D1S3        Microbacterium oxydans ISP4 (+) cocci motile cocci     D1S4        ND ISP4 (+) cocci/short rods motile cocci/rods in chains     D211Y        Micrococcus luteus TSA (+) cocci motile cocci, singles 16ft   D211W        Micrococcus sp. TSA (+) cocci motile cocci, singles     D213        ND ISP4 (-) cocci large cocci     D221        Staphylococcus sp. TSA (+) branching filaments ND     D3N1        uncultured bacterium TSA (+) cocci large cocci 18ft   D3N3        Microbacterium sp. HTA (+) cocci motile cocci/small rods, singles/chains     D3N5        Pseudomonas cuatrocienegasensis HTA (-) rods fast motile rods, unidirectional     D3N6        uncultured bacterium HTA (+) cocci motile cocci, singles/clusters 19ft   D4SW1        ND TSA (+) cocci motile cocci, singles/pairs     D4SW1O        ND TSA (+) cocci motile cocci, pairs  ND*= No Data 36    3.3.1 Antibiotic resistance profiles of soil bacteria The soil isolates were tested for antibiotic resistance phenotypes. The individual strains were swabbed onto fresh MHA plates before commercial antibiotic discs were placed onto the inoculated agar surface for incubation. Thirteen out of the twenty-two isolates (S1, D1S1, D1S2O, D1S2Y, D1S3, D1S4, D211W, D213, D221, D3N3, D3N5, D4SW1 and D4SW1O) were resistant to three or more of the twenty antibiotics tested. Strains S3, S6 and S7 are susceptible to all antibiotics tested except for methicillin at 5μg. D11 is resistant to methicillin at 5μg and nalidixic acid at 30μg. D211Y is only resistant to nalidixic acid at 30μg. D12 and D3N6 are both resistant to phosphomycin at 20μg, while D3N6 is also resistant to sulfadiazine at 250μg. S2 and D3N1 are the only isolates that are susceptible to all antibiotics tested. These results suggest that deep soil bacteria inherently possess genes relating to antibiotic resistance.           37  Table 3.2. Antibiotic resistance phenotypes of PS soil isolates. Zones of inhibition (mm) for 20 antibiotics tested against the PS soil isolates.  R= resistant, WH= weak inhibition halo, L= inhibition zone larger than 50mm and - = no date  Antibiotic discs                                     Isolates Van30 Meth5 Colis 10 Bac10 Nal30 Oxa1 Phos20  Dap30 Imp10 Trim5 Sulf 0.25 Poly300 Spec100 Strep100 Ery5 Kan30 Novo5 Tetra30 Amp10 Rif5                                           S1 30 R 20 25 R R R R 35 R 50 23 32 32 35 40 22 34 R 17 S2 30 18 15 22 25 34 33 28 L 27 33 21 24 18 33 33 34 40 25 45 S3 35 R 23 40 17 15 29 28 L 25 43 22 36 37 41 36 L L L L S6 33 R 21 38 15 15 28 29 L 28 40 24 22 24 22 24 28 24 28 L S7 33 R 21 39 12 12 30 29 L 27 37 22 24 24 26 20 28 32 23.5 L D11 23 R 15 29 R 10 18 22 42 18 24 18 28 31 31 30 37 40 42 45 D12 35 30 21 21 39 25 R 30 L 44 29 28 37 40 25 L 31 L L 38 D1S1 45 R 25 47 R R R 44 L R R 29 R 38 R 40 22 L L 38 D1S2Y 25 R 9 7 R R R 7 28 25 30 15 25 13 19 17.5 23 26 15 25 D1S2O 26 R 10 7 WH R R 8 29 23 40 15 25 10 18 22 22 22 18 32 D1S3 27 R 10 WH WH R R 10 30 R 44 15 24 13 19 17 19 25 16.5 24 D1S4 L R 34 L R R R L R R R 48 20 L 34 L R L L 23 D211Y 40 15 23 47 R 14 27 34 34 33 50 24 27 21 35 20 40 24 25 34 D211W 32 R R R 15 R R 10 27 30 27 17 15 17 20 16.5 22 24 25 30 D213 33 R R 37 R R R 40 R R R 17 35 32 26 26 16 - - 16 D221 25 R R R R R R 7 28 25 25 15 21 34 20 29 28 32.5 25 32 D3N1 22 15 15 32 17 17 34 30 L 20 25 15 33 26 34 25 40 46 46 44 D3N3 42 23 14 35 R R R 10 L 27 R 21 32 32 45 24 L L L 43 D3N5 R R 20 R 40 R 24 R 47 20 34 20 36 24 33 32 21 43 9 20 D3N6 30 17 15 11 18 33 R 23 L 25 R 19 24 32 35 40 32 40 40 50 D4SW1 35 24 18 R 15 36 R 28 L 35 R 22 27 35 36 40 35 L L L D4SW1O L 13 19 L R R R L L R 32 29 35 29 L L L L L L 38   3.3.2 Screening soil bacteria for production of antimicrobials The day 1, 2, 3 and 5 fermentation culture supernatants of all soil isolates were collected and tested against Acinetobacter baumannii ATCC 19606, Micrococcus luteus JVC 1154, Staphylococcus aureus RN4220 and Escherichia coli MG1655. The results of these tests showed that D12, D211Y and D4SW1 culture supernatants were weak inhibitors of M. luteus JVC 1154. The zones of inhibition were only marginally larger than the 7mm paper discs holding the supernatant samples. Isolate D3N3 inhibited both M. luteus JVC 1154 and S. aureus RN4220. Microbacterium sp. D3N3 was chosen for further studies.   3.3.3 Screening soil bacteria for products of transcription-regulation  The twenty-two soil isolates were tested for production of diffusible small molecules that regulate transcription of promoter-lux fusion cassettes in S. typhimurium 14028. The light responses of each reporter tested against the soil isolates are summarized in Table 3.3. The soil isolates from the upper levels of the PS soil column induced light production in the S. typhimurium reporters that were comparable in intensity relative to the control. The yrbC reporter was an exception, which showed high light induction levels from both the shallow sample isolates and the deep sample isolates.      39  Table 3.3. Salmonella typhimurium luciferase reporter responses to soil isolate cultures.  Blanks specify the lack of light induction data. (-) specifies no light induction, while (+), (++), (+++) and (++++) represent increasing light intensities, where (+++) represents the level of intensity of rifampicin control.    Isolates                          luciferase reporter systems                         ydcW fadB phoB tsr yrbC                       S1     ++++ ++++ +++ ++++ +   S2     - - - - ++++   S3     +++ +++ +++ +++ +   S6     ++++ +++ +++ +++ +++   S7     + - - - ++++   D11           - +       D12     +++ ++ ++++ - ++++   D1S1     ++ - +++ + -   D1S2Y     ++ - ++ - +   D1S2O     ++ - ++ - +   D1S3                     ++ - ++ - +   D1S4     +++ - - -     D211Y     + - - - +   D211W     + - - - +++   D213     + + - -     D221     + - - + +   D3N1     + ++ - - +++   D3N3     + ++ - - +++   D3N5     + ++ - - +++   D3N6     - - - - ++++   D4SW1     - - - - ++++   D4SW1O     - - - - ++++                          3.4 Isolation of antimicrobial compound(s) from Microbacterium sp. D3N3 Microbacterium sp. D3N3 became the focus for the isolation of antimicrobial compounds following the observation of its culture supernatant’s inhibitory action against M. luteus JVC 40  1154 and S. aureus RN4220. M. sp. D3N3 was cultured on solid LBA medium for one week and extracted with ethyl acetate. The dried extract was tested for antimicrobial activity against 8 tester bacteria. The crude extract has inhibitory activity on all of the eight strains tested (Fig 3.8).    a                 b                 c                  d                 e                 f                    g                   h    Figure 3.8. Antibacterial activity of Microbacterium sp. D3N3 culture extract. 1mg of M. sp. D3N3 ethyl acetate extract inhibits the growth of a) Acinetobacter baumannii 17978, b) Escherichia coli O157:H7, c) Enterococcus faecalis 29212, d) Enterococcus faecium 35667, e) Staphylococcus aureus MRSA USA400, f) Staphylococcus aureus 29213, g) Klebsiella pneumoniae 700721 and h) Pseudomonas aeruginosa PAO1    The active crude extract was fractionated using thin layer chromatography (TLC) in order to identify the fraction(s) responsible for the inhibitory activity. The developed TLC plate had multiple faint yellow-colored bands and one pink-colored band. Under UV light, the bands appear clear and separate from each other. Each of the separated bands were removed from the TLC plate and tested for antibacterial activity. One single TLC band retained antibacterial activity (Fig 3.9). This active TLC fraction was the pink-colored band observed on the plate.     41            Figure 3.9. UV light image of thin layer chromatography of Microbacterium sp. D3N3 culture extract. TLC separation of the crude extract resulted in several distinct fractions. The band indicated by the arrow was the only fraction that showed antimicrobial activity.   The crude culture extract was also fractionated by RP-HPLC. Seven fractions were obtained and each was tested for antibacterial activity against Acinetobacter baumannii ATCC 19606. Similar to the TLC fractionation results, the HPLC fractionation resolved one active fraction. Proton nuclear magnetic resonance was performed on the active fraction to identify the active compound(s). The results predicted the presence of one pure compound, phenylacetic acid (PAA), in the fraction (Fig 3.10). The activity of the active HPLC fraction was compared to that of pure PAA. 1mg of active HPLC fraction produced an identical inhibitory effect on A. baumannii ATCC 19606 as 1mg of commercially available PAA (Fig 3.11).  42            Figure 3.10. Proton nuclear magnetic resonance of active HPLC fraction.          Figure 3.11. Active HPLC fraction of Microbacterium sp. D3N3 culture extract. The HPLC fractions of M. sp. D3N3 were tested on Acinetobacter baumannii ATCC 19606. Paper discs with a) an inactive HPLC fraction, b) the active HPLC fraction, c) Rifampicin 5μg control, d) blank disk control and e) 1mg of phenylacetic acid are shown.   43  3.4.1 Mode of action of phenylacetic acid The mode of action of phenylacetic acid was tested on a library of Staphylococcus aureus RN4220 promoter-lux fusion reporters. Of the fourteen reporter clones tested, five showed light responses to PAA (Fig 3.12). Clones A, H, I, L and M carry the tet, SAOUHSC_T0008 (trnaN), SAOUHSC_01895 (hypothetical protein gene, FlgJ), SAOUHSC_00007 (yjeF) and SAOUHSC_00694 (mgrA) gene promoter fusions respectively.    Clone A                                  Clone H                               Clone I       Clone L                                  Clone M                         Relative luminescence High        Low   Figure 3.12. Staphylococcus aureus RN4220 luciferase reporter response to phenylacetic acid. Varying light response intensities of five reporter clones. The amounts of PAA assayed are a) 1mg, b) 0.5mg, c) 0.25mg, d) 0.125mg and e) 0.0625mg. The antibiotics used as positive control for light induction is (f).   44  The tet and trnaN promoters were strongly induced by 1mg of PAA at intensities comparable to the positive control antibiotics (Table 2.2). 0.5mg of PAA also induces the expression of these promoters, although not as strongly. The lower amounts of PAA tested did not induce light production in either of the two reporter clones. The FlgJ, yjeF, and mgrA promoters were induced at low levels with 1mg of PAA. Small amounts of PAA induced no light production on these three reporter clones. Clones B, C, D, E, F, G, J, K and N were not responsive to any of the PAA amount tested (data not shown). The identities of these clones are summarized in Table 2.2. The light induction profile of PAA does not match those of thirteen antibiotics previously tested on the reporter panel (Mesak et al., 2010). Therefore, the mode of action of PAA likely do not coincide with those antibiotics.  3.4.2 Phenylacetic acid interactions with antibiotics Drug interactions of phenylacetic acid with other antibiotics were tested on Acinetobacter baumannii ATCC 19606 using disc diffusion assays. Antibiotic discs were placed 5mm from paper discs containing 1mg PAA, on A. baumannii overlay plates. The shape and size of inhibition zones were compared to those of the antibiotics or 1mg PAA discs alone. Four antibiotics (tetracycline, colistin, ampicillin and novobiocin) showed changes in their inhibition zone shapes and sizes when placed adjacent to a PAA disc (Fig 3.13). These changes were most apparent with tetracycline and novobiocin. Pear-shaped zones of inhibition have developed as a result of the interaction between these antibiotics and PAA. Colistin and ampicillin have less dramatic changes to their inhibition zone characteristics, however both antibiotic inhibition zones are expanded slightly beyond boundaries of the zones in antibiotic controls. This results suggests weak interaction of PAA with colistin and with ampicillin. Nine other antibiotics (ciprofloxacin, 45  erythromycin, penicillin G, imipenem, kanamycin, sulfamethoxazole/trimethoprim, neomycin, rifampicin and azithromycin) had no indication of additive effects with PAA.                  a                        b                        c                       d      Figure 3.13. Disc diffusion assays testing phenylacetic acid interaction with antibiotics. Interaction of PAA with a) tetracycline, b) colistin, c) ampicillin and d) novobiocin. The top discs are the antibiotic discs while the bottom discs are 1mg PAA discs. The red circles represent the shape of inhibition zones for each antibiotic and PAA individual controls.   These potential PAA-antibiotic synergies were further tested using the standard method of checkerboard assay.  The calculated FIC values for PAA-tetracycline, PAA-colistin, PAA-ampicillin and PAA-novobiocin synergy tests were 0.75, 2, 1.5 and 1.25, respectively. The checkerboard assays suggested no synergy between PAA and the four antibiotics.   3.5 Genomic sequencing of Microbacterium sp. D3N3 The genome of Microbacterium sp. D3N3 was sequenced with the objective of identifying biosynthetic and antibiotic resistance genes. The raw sequence data derived from the Illumina HiSeq2000 platform was analyzed with Velvet software for the sequence assembly followed by 46  the generation of sequence scaffolds using SSPACE. A total of thirty-six scaffolds, with a combined size of 3,238,703bp, were obtained. The minimum scaffold length is 500bp and the largest is 559,273bp, with an N50 value of 208,346bp. The G+C content of the genome is 70.75%. The scaffolds were used in open reading frame predictions (ORF) and gene annotations using Glimmer. A total of 3020 ORFs were predicted. tRNAscan-SE found 46 tRNA genes and RNAmmer predicted 8 rRNA gene sequences from the genome scaffolds.  3.5.1 Type III polyketide synthase of Microbacterium sp. D3N3 The thirty-six sequence scaffolds of the M. sp. D3N3 genome were scanned for biosynthetic gene clusters using AntiSMASH software. The sequences were uploaded onto the online server of the software for processing. The results suggested only one hit. The 1122bp ORF_155 on scaffold number 1 of M. sp. D3N3 was putatively matched to a type III polyketide synthase (T3PKS). The DNA sequence of ORF_155 was translated to its amino acid sequence and aligned with known bacterial and plant T3PKS sequences (Fig 3.14).                                                                Cys164                                                     His303                                                       Asn336                                                                   *                                                             *                                                                 *                        …    Figure 3.14. Amino acid sequence alignment of Microbacterium sp. D3N3 T3PKS. The three amino acid residues that are essential for T3PKS catalytic activity are marked by the asterisks (*)   47  The three catalytic residues of the T3PKS protein, Cys164, His303 and Asn336 (Medicago sativa numbering), were conserved in the ORF_155 protein sequence. The putative T3PKS homolog was further confirmed in M. sp. D3N3 through PCR amplification using the T3PKS_F and T3PKS_R primer set (Table 2.1).                                                                                                                                    Other bacteria                                                                                                             Microbacterium spp.                                                                                                                                                                  Plants    Figure 3.15. Phylogenetic relationship between bacterial and plant T3PKS. T3PKS protein sequence alignment.     48  T3PKS is widely distributed among the bacterial and plant phyla. The T3PKS products from these organisms have a wide range of biological functions involved in, but not limited to; hormone signaling, pigment production and the biosynthesis of antimicrobials. T3PKS is apparently common among species of Microbacterium (Fig 3.15). The identity and functions of T3PKS products from the microbacteria have not been studied. The M. sp. D3N3 ORF_155 protein clustered with the T3PKS homologs identified in other microbacteria, but not those of other bacteria.    3.5.2 PKS and NRPS in genome-sequenced microbacteria As indicated, the only AntiSMASH hit from the Microbacterium sp. D3N3 genome was a T3PKS homolog. To examine biosynthetic potential in other microbacteria, the complete or draft genomes of thirty-one microbacteria were scanned using AntiSMASH. The results are summarized in Table 3.4. This analysis revealed that nineteen of the genomes contained T3PKS homologs. Only three of the genomes contained NRPS genes. Many of the strains also encode terpene production-related gene homologs.         49  Table 3.4. Results of AntiSMASH scan of genome-sequenced microbacteria. Species Strain     Gene cluster type Genomic location       D3N3              M. sp. t3pks ORF_0155 (1 - 1122 nt.)                                            M. testaceum StLB037     t3pks NC_015125 (2771979 - 2813067 nt.)             other NC_015125 (2927514 - 2971452 nt.)              terpene NC_015125 (3392102 - 3412971 nt.)                      M. paraoxydans DH1b     t3pks NZ_AYME01000010 (176193 - 217350 nt.)             terpene NZ_AYME01000010 (19025 - 39933 nt.)                       7MFTsu3.2     t3pks NZ_AQYI01000006 (341572 - 382693 nt.)                     M. laevaniformans OR221     other NZ_AJGR01000124 (94471 - 138400 nt.)             other NZ_AJGR01000124 (135248 - 175715 nt.)             terpene NZ_AJGR01000432 (1425 - 22279 nt.)                     M. xylanilyticum JCM 13591     No clusters detected                       M. maritypicum MF109     t3pks NZ_ATAO01000146 (20451 - 61611 nt.)             terpene NZ_ATAO01000188 (135730 - 158001 nt.)                     M. luticocti DSM 19459     bacteriocin NZ_AULS01000002 (96471 - 107262 nt.)             M. indicum DSM 19969     terpene NZ-KE383821 (102162 - 123031 nt.)                     M. gubbeenense DSM 15944     nrps NZ_AUGQ01000001 (332052 - 390610 nt.)     50  Species Strain     Gene cluster type Genomic location              terpene NZ_AUGQ01000013 (9982 - 30848 nt.)                     M. oleivorans RIT293     terpene NZ_JFYO01000001 (614101 - 624599 nt.)             t3pks NZ_JFYO01000002 (1 - 32458 nt.)                       NBRC 103075     other NZ_BCRG01000004 (219574 - 264188 nt.)             t3pks NZ_BCRG01000008 (137096 - 161690 nt.)             terpene NZ_BCRG01000010 (103089 - 130566 nt.)                     M. hydrocarbonoxydans SA35     other NZ_JYJB01000005 (223548 - 267471 nt.)             terpene-bacteriocin NZ_JYJB01000008 (366557 - 389679 nt.)              siderophore NZ_JYJB01000009 (317516 - 329294 nt.)                       NBRC 103074     terpene NZ_BCRF01000008 (46110 - 72450 nt.)             t3pks NZ_BCRF01000025 (17249 - 48550 nt.)                     M. resistens NBRC 103078     t3pks BCRA01000020 (1 - 31699 nt.)           terpene BCRA01000066 (955 - 21819 nt.)                 M. barkeri 2001-R4     terpene AKVP01000002 (29360 - 50418 nt.)           t3pks AKVP01000028 (1 - 40607 nt.)  M. yannicii   PS01     terpene    NZ_CAJF01000007 (27611 - 48459 nt.)           t3pks NZ_CAJF01000011 (28817 - 69980 nt.)          nrps NZ_CAJF01000018 (5664 - 49800 nt.)          other NZ_CAJF01000028 (34885 - 57296 nt.)                 51  Species Strain     Gene cluster type Genomic location       M. profundi Shh49     ectoine  NZ_JPSY01000001 (1493129 - 1503521 nt.)           terpene NZ_JPSY01000001 (1612953 - 1633834 nt.)          other NZ_JPSY01000001 (1992295 - 2034946 nt.)          other NZ_JPSY01000001 (2090968 - 2134897 nt.)         t3pks NZ_JPSY01000004 (98769 - 139917 nt.)                M. enclense NIO-1002     ladderane NZ_KQ758467 (587359 - 629761 nt.)            terpene NZ_KQ758468 (128782 - 149651 nt.)          other NZ_KQ758471 (20598 - 64548 nt.)          t3pks NZ_KQ758471 (146116 - 187210 nt.)                  M. chocolatum SIT 101     t3pks NZ_KQ440285 (88395 - 129540 nt.)           terpene NZ_KQ440290 (182473 - 203330 nt.)                  M. ketosireducens DSM 12510     siderophore NZ_JYIZ01000030 (28010 - 49860 nt.)           terpene NZ_JYIZ01000036 (1 - 16281 nt.)          terpene NZ_JYIZ01000036 (55764 - 72044 nt.)          other NZ_JYIZ01000042 (39743 - 83687 nt.)          t3pks NZ_JYIZ01000046 (23611 - 64729 nt.)          resorcinol NZ_JYIZ01000054 (68736 - 109899 nt.)                 M. gensengisoli DSM 18659     terpene  NZ_JYIY01000067 (43053 - 67526 nt.)                     M. azadirachtae ARN176     other NZ_JYIX01000030 (11302 - 55390 nt.)            t3pks NZ_JYIX01000036 (69390 - 110529 nt.)                    DSM 23848     other NZ_JYIT01000050 (1 - 23554 nt.)    52  Species Strain     Gene cluster type Genomic location               bacteriocin NZ_JYIT01000073 (14949 - 25749 nt.)          terpene NZ_JYIT01000077 (55284 - 76177 nt.)          linaridin NZ_JYIT01000083 (19986 - 42465 nt.)                  M. trichothecenolyticum DSM 8608     terpene NZ_JYJA01000024 (22931 - 43812 nt.)            resorcinol NZ_JYJA01000030 (123501 - 154948 nt.)          other NZ_JYJA01000032 (35744 - 79688 nt.)         t3pks NZ_JYJA01000035 (45579 - 86736 nt.)          other NZ_JYJA01000036 (132563 - 175208 nt.)                  M. mangrovi MUSC 115     terpene NZ_JTDK01000006 (722230 - 743144 nt.)            t3pks NZ_JTDK01000014 (141421 - 182545 nt.)          other NZ_JTDK01000015 (58059 - 101985 nt.)                  M. foliorum DSM 12966     terpene NZ_JYIU01000018 (1 - 22807 nt.)            t3pks NZ_JYIU01000038 (1 - 39534 nt.)          other NZ_JYIU01000045 (40156 - 84073 nt.)                  M. hominis TPW29     other NZ_JWSZ01000001 (211749 - 255678 nt.)            terpene NZ_JWSZ01000011 (100765 - 121619 nt.)                 M. oxydans BEL163     terpene NZ_JYIV01000023 (50970 - 71878 nt.)                      BEL4b     other NZ_JYIW01000024 (81329 - 125252 nt.)            terpene NZ_JYIW01000025 (126663 - 147571 nt.)                   NS234     terpene NZ_LDRQ01000011 (54575 - 68709 nt.)           nrps NZ_LDRQ01000023 (71980 - 124608 nt.)         t3pks NZ_LDRQ01000073 (Location: 1 - 5606 nt.)        53   3.5.3 The resistome of Microbacterium sp. D3N3 The genome scaffolds of M. sp. D3N3 were scanned using the comprehensive antibiotic resistance database (CARD) to scan for genes related to antibiotic resistance. The loose, strict and perfect search algorithms were all applied in the scan. The results returned 458 hits. 437 of which were derived from the loose search algorithm, suggesting low confidence matches. The purpose of the loose search is to allow for the possibility of discovering novel genes that are distantly related to resistance genes in the database. These loose search hits and their categories are summarized in Table 3.5. The gene sequences and the functional properties of these loose search hits have not been further studied; however, the phosphomycin, sulfonamide and beta-lactam resistance gene hits correlate with the resistance phenotype of M. sp. D3N3. These resistance gene hits are the following: a 49% match to a portion of the murA gene in Chlamydia trachomatis related to phosphomycin resistance, a 31% sequence match to the sul3 gene related to sulfonamide resistance and varying 26-34% sequence matches to the pbp2x, pbp1a, evgA, mecB, golS, ramA and PEDO-2 genes relating to β-lactam resistance.  Table 3.5. Microbacterium sp. D3N3 draft genome CARD hits (loose algorithm).  Type of resistance gene hits Number of hits    pyrazinamide resistance gene 1 phosphomycin resistance gene 1 gene altering cell wall charge conferring antibiotic resistance 5 polymyxin resistance gene 5 gene modulating permeability to antibiotic 1 sulfonamide resistance gene 1 gene involved in antibiotic sequestration 1 pleuromutilin resistance gene 2 rifampin resistance gene 8 fusidic acid resistance gene 1 54  Type of resistance gene hits Number of hits  streptogramin resistance gene 4 phenicol resistance gene 2 antibiotic target modifying enzyme 6 linezolid resistance gene 1 beta-lactam resistance gene 10 lipopeptide antibiotic resistance gene 3 antibiotic inactivation enzyme 12 chloramphenicol resistance gene 12 gene modulating antibiotic efflux 33 aminoglycoside resistance gene 7 trimethoprim resistance gene 10 antibiotic target replacement protein 6 antibiotic resistance gene cluster, cassette, or operon 13 gene conferring antibiotic resistance via molecular bypass 14 glycopeptide resistance gene 13 tetracycline resistance gene 19 macrolide resistance gene 42 mupirocin resistance gene 2 antibiotic target protection protein 6 isoniazid resistance gene 1 fluoroquinolone resistance gene 24 elfamycin resistance gene 2 antibiotic resistant gene variant or mutant 7 gene involved in self resistance to antibiotic 5 aminocoumarin resistance gene 7 lincosamide resistance gene 4 efflux pump conferring antibiotic resistance 126       Nineteen CARD hits were derived from the strict search algorithm. These hits represent higher confidence matches to the database resistance genes and are summarized in Table 3.6. Many of the hits represent more than one category of resistance gene recorded in the CARD. No hits resulted from the perfect sequence match search algorithm.     55  Table 3.6. Microbacterium sp. D3N3 draft genome CARD hits (strict algorithm).  Type of resistance gene hits Gene hits    mupirocin resistance gene ileS antibiotic target protection protein mfd isoniazid resistance gene katG fluoroquinolone resistance gene qepA, mfd and gyrB elfamycin resistance gene EF-Tu antibiotic resistant gene variant or mutant katG, gyrB, parY, EF-Tu gene involved in self resistance to antibiotic desR aminocoumarin resistance gene novA, alaS, parY lincosamide resistance gene lmrB efflux pump conferring antibiotic resistance novA, lmrB, qepA       3.6 Microbacterial phylogeny by 16S rRNA gene alignment The 16S rRNA gene sequence of M. sp. D3N3 was aligned with those of eighty-three species of Microbacterium in order to identify its closest relatives. A simplified version of the alignment matrix is shown in Fig 3.16.       Figure 3.16. Simplified 16S rRNA gene identity matrix of Microbacterium sp. D3N3 and other Microbacterium spp. The matrix specifies the percentage sequence identity of the 16S rRNA genes of the microbacteria shown. The colors of the heat map highlight the range of sequence identity values. Mycobacterium iranicum is used as an outlier.  56  Out of the eighty-three species of Microbacterium in the multiple sequence alignment, seven species were highly closely related to M. sp. D3N3. The seven closely related species had higher than 98% 16S rRNA gene sequence identities with each other, as well as with M. sp. D3N3. These related species are M. aoyamense, M. lacus, M. pumilum, M. schleiferi, M. terregens, M. pygmaeum and M. deminutum. Some other species of microbacteria (not shown in Fig 3.16) also appeared to form close relationships based on 16S rDNA identities above 98%. One such example is illustrated by the 99.3% matching of 16S rDNA between the distinct species; M. oxydans and M. paraoxydans (Fig 3.16). Due to the extremely close relationships of microbacterial species based on the 16S rRNA gene phylogeny, a species identification for M. sp. D3N3 cannot be determined. Additional methods of species delineation such as phenotypic tests and multilocus sequence typing are used.  3.6.1 Phenotypic tests of microbacteria It is generally recognized that 16S rRNA sequence alone is insufficient to determine microbacterial phylogeny. Novel Microbacterium sp. have been delineated from known species by the use of classical phenotypic tests. A range of sugar assimilation tests and measurements of other growth parameters for M. sp. D3N3 was completed. M. sp. D3N3 fermented mannitol, galactose, sucrose, arabinose, mannose, lactose, glucose and rhamnose, but not trehalose, raffinose or fructose. The strain assimilated nitrate. The methyl red and Vogues-Proskauer tests, urease and catalase activities were negative. Strain D3N3 is motile and does not grow at temperatures above 35oC. These results were compared with seven related microbacteria (Table 3.7) (Kageyama et al, 2006; Kageyama et al, 2007; Kageyama et al., 2007).  These authors relied on the comparison of these phenotypic parameters to assign species identifications.  Each of the 57  seven strains have multiple phenotypic differences from M. sp. D3N3. The results of these phenotype tests suggest that M. sp. D3N3 is distinct from closely related microbacteria.   Table 3.7. Phenotypic tests of Microbacterium sp. D3N3 and closely related species. The cells highlighted orange represent differences to the test results of M. sp. D3N3.           ND= no data was available from the literature   3.6.2 Multilocus sequence typing Multilocus sequence typing (MLST) is another means of microbial differentiation. Five marker genes (rpoB, trpB, gyrB, atpD, and recA) were chosen for a MLST study of Microbacterium spp.. The sequence data for these genes were collected from genome-sequenced Microbacterium species available on GenBank. A phylogenetic tree for each marker as well as for the concatenated sequences of the five markers and 16S rRNA were constructed and compared to that of 16S rRNA gene phylogeny alone (Fig 3.17). All the MLST gene markers appear to retain 58  similar clustering patterns compared to 16S rRNA. An exception may be noted for gyrB, which shows increased branching of the group containing M. hominis and M. laevaniformans species and of the group containing M. oxydans, M. paraoxydans and M. hydrocarbonoxydans species. Interestingly, there is splitting in the clustering of several strains that belong to the same species in the 16S rRNA gene tree. Specifically, the strains M. hominis LCDC 84-0209, M. hominis NBRC 15708 and M. testaceum NS 220 which did not group with their proposed closest relatives. The phylogenies based on concatenated sequences show fewer distinct groups of microbacteria when compared to the 16s rRNA tree. The concatenated data would provide more accurate predictions for the phylogenetic relationship between M. sp. D3N3 and its close relatives.              59  16S rRNA         trpB                60  rpoB                                        recA                61   gryB                       atpD               62  Six-gene concatenation              Figure 3.17. Phylogenetic trees of 33 genome-sequenced Microbacterium strains in MLST analysis. The phylogenetic trees for 16S rRNA, trpB, rpoB, recA, gyrB, atpD genes and the concatenated sequence of these six genes are shown. The major clusters of strains are highlighted with the colored boxes.63  3.7 Isolation of microbacteriophages Four potentially distinct microbacterial phages have been isolated from the UBC wastewater treatment pilot plant, sea water from UBC Wreck Beach and a soil sample from the trail leading to Wreck Beach. The phage isolates demonstrate specificity to Microbacterium. Phages WW1, WW2, SEA1 and SOIL1 infect hosts M. sp. D1S2O and D1S3 (this study), both of which are identified as M. oxydans (Fig 3.18). Phages WW1, SEA1 and SOIL1 produce similar plaques. They are small (~1mm), opaque and round plaques. The plaques of phage WW2 are about 1mm in diameter and round in appearance, but they are clear. These phages do not infect other bacteria such as Staphylococcus aureus, Micrococcus luteus, Bacillus subtilis, and Pseudomonas aeruginosa (data not shown). Moreover, the phages are species-specific as they failed to infect M. sp. D3N3 and M. testaceum. This demonstrates the potential of using microbacteria-specific phages as tools to distinguish between different species. These phage isolates infect M. oxydans, an opportunistic pathogen. The discovery of bacteriophages that infect pathogenic microbacteria may be a useful adjunct for therapy of opportunistic microbacterial infections.          64         Figure 3.18. Microbacteriophage isolates infect Microbacterium sp. D1S2O and D1S3. LBA agar plates of showing the infection of M. sp. D1S2O (left plate) and D1S3 (right plate) by phage isolates WW1, WW2, SEA1 and SOIL1.     3.7.1 Transmission electron microscopy of microbacteriophages Transmission electron microscopy of these phages were completed to observe their morphology and attachment to host cells (Fig 3.19). The phage capsule morphology and host attachment are highly similar for phages WW1, SEA1 and SOIL1. These three phage isolates appear to have heads containing icosahedral capsids, and no observable tail fibers when unattached to host cells. The phage heads are approximately 100nm in diameter.  Short, stalky tails are observed when phages WW1, SEA1 and SOIL1 are attached to their hosts. M. sp. D1S2O infected with phage WW2 appears to have membrane budding formations. The membrane buds are approximately 100nm in diameter and emerge as membrane-bound vesicles in the infected culture medium when they are released from the host cell. The budding behavior and membrane-bound morphology of phage WW2 are not consistent with the typical microbacteriophages. Phage 65  WW2 may be a new family of phage that infect Microbacterium, as they do not resemble the morphology of typical microbacterial Siphoviruses.                   Figure 3.19. Transmission electron micrographs of microbacteriophage attachment to host cells. Phage WW1 (top left), WW2 (top right), SEA1 (bottom left) and SOIL1 (bottom right).  66  Chapter 4: Discussion The search for novel secondary metabolites from microbes that reside in various unexplored environments have become the norm in drug discovery. Scientists are routinely surveying such environments for biosynthetic potential through the means of metagenomic sequencing (Miesel et al., 2003; Woodhouse et al., 2013). This method allows for rapid screening of different environments for gene sequences that are not only related to antimicrobial production, but other sequences of interest such as antibiotic resistance and metabolic genes.   This thesis focuses on the traditional method of drug discovery; by the isolation of soil Actinobacteria to study their biosynthetic potential. Soil samples were collected from the Vancouver campus of The University of British Columbia. The distribution of antibiotic resistance and a biosynthetic gene relating to Streptomyces were explored in these samples. The bacterial communities within these soils were surveyed and ultimately led to the identification of the samples that were rich in Actinobacteria, the targeted phylum of study. The focus of this thesis shifted to the in-depth study of a Microbacterium strain isolated from a layer of deep soil. Microbacteria are ubiquitous in the environment, but little is known about their potential for the production of antimicrobials and their roles in nature. The isolate, Microbacterium sp. D3N3, is potentially a new species of Microbacterium based on results of 16S rRNA gene and phenotypic comparisons against the most closely related microbacteria. M. sp. D3N3 produces phenylacetic acid, a compound with weak but broad-spectrum antimicrobial activities. Further studies of phenylacetic acid suggest that it also has the ability to induce transcription of several Staphylococcus aureus genes. The compound’s mode of action remains unknown. There is also preliminary evidence of the additive interactions that phenylacetic acid has with some 67  antibiotics. The increased level of inhibitory activity of these drug combinations may be useful for effective treatment of microbial infections.  The draft genome sequence of M. sp. D3N3 revealed a scarcity of genes related to biosynthesis of antimicrobials; however, a type III polyketide synthase homolog was identified. The resistome of strain D3N3 was also examined with the CARD database. Lastly, the isolation of microbacteriophages from the environment was explored. Four phages that infect M. sp. D1S3 and M. sp. D1S2O (isolates from this study) were discovered. The phylogeny of the phage have yet to be elucidated. Transmission electron microscopy has been completed to observe the morphology of the phage isolates.   4.1 Soil sample collection and total DNA extraction The construction site excavations of the UBC Pharmaceutical Science building and Sitka Residence provided fortunate opportunities for collecting soils that have not been studied for the dynamics of antibiotic resistance and production in their bacterial populations. A soil column was collected from each site from the surface down to 25ft in depth. Due to the differences in foundation depths and types of the two excavation sites, soil collection from equal depths at both sites was not possible. The total DNA from each of the soil samples were extracted for studies of bacterial community structure and the distribution of genes relating to antibiotic resistance and production. The FastDNA soil DNA extraction kit proved to be the most effective method of obtaining appropriate amounts of DNA. However, the concentrations of DNA extracted from each sample was still below the detection limit of agarose gel electrophoresis. This problem may 68  be attributed to the low organic matter content in the soil samples collected. Most of the samples were sandy or sandy loam types of sediment. To ensure that the extracts contained enough high quality DNA required for further studies, a fragment of the 16S rRNA gene was amplified from each DNA extract. The results suggested that all ten DNA extract samples indeed had appropriate amounts of template soil DNA for downstream PCR experiments.  4.1.1 Antibiotic-associated genes in soil DNA One of the initial research questions explored in this thesis was whether there is a pattern in the distribution of antibiotic resistance among the different horizons in soil columns. The presence and distribution of five antibiotic resistance genes (aac(3), bla, erm, tetM/otrA and vanX) were tested in the soil layers collected. These genes were previously used to detect antibiotic resistance in ancient permafrost sediments (D’Costa et al., 2011). The TME-1 ß-lactamase encoded by the bla gene and the ribosome methyltransferase encoded by the erm gene were undetected in the soils despite successful PCR amplification from the Streptomyces coelicolor A3(2) genomic DNA control. The tetM/otrA gene encoding a tetracycline resistance protein was detected in all soil samples except for the 15ft SK soil sample, while the aminoglycoside acetyltransferase, aac(3), was only found in the 18ft PS soil. The D-Ala-D-Ala dipeptide hydrolase, vanX, was amplified from the 10 and 16ft levels of PS soil and from the 5ft sample of SK soil. Due to the need to conserve soil material and soil DNA extracts for other studies, the DNA extracts from mass liquid bacterial cultures of each soil sample were used as PCR template for the detection of the five resistance genes in study. These bacterial cultures consisted of fast growing bacteria which are most likely to participate in the expression and/or dissemination of antibiotic resistance genes. PCR amplification of bla, erm and vanX genes in the culture DNAs 69  were negative. Consistent with the widespread detection of the tetM/otrA gene in soil DNA, this gene was detected among most of the mixed culture DNAs. However, its detection was not found for the 18ft PS soil culture. The aac(3) gene was detected only in the 10ft samples of both the PS and SK sites. The aac(3) primers produced a significant amount of non-specific amplification from the mass culture DNA. Therefore, it is difficult to assess if the detection of this gene in the culture DNAs is true. The apparently random patterns of gene detection did not yield meaningful data in the determination of resistance gene distribution throughout the soil columns. Metagenomic analyses of the soil DNA will provide a more robust detection of antibiotic resistance genes. This approach also avoids the limitations of using oligonucleotide primers to detect only known resistance genes. The metagenomic sequence data would also allow for further functional validation of the identified genes using a gene cloning and expression approach.   The same approach used in the detection for antibiotic resistance genes in PS and SK soil DNA was applied to detect the phosphoenolpyruvate mutase (PEP mutase) gene. The PEP mutase is involved in isomerization of its substrate phosphoenolpyruvate into the structural isomer, 3-phosphonopyruvate. The phosphate group of the former molecule is transferred onto the third carbon of the latter molecule. PEP mutase is not abundant in the environment (Seto & Kuzuyama, 1999). However, it is an essential enzyme found in those Streptomyces species which are producers of the antibiotic phosphomycin. The carbon-phosphorus bond within phosphomycin is formed through the action of PEP mutase (Hidaka et al., 1992). The presence of the PEP mutase gene was tested in the PS and SK soil DNA extracts. The detection of this gene in the soil layers would indicate the presence of biosynthetic potential specifically relating to the 70  production of compounds containing C-P bonds. The gene was detected only in the SK soils, specifically the 5, 10 and 25ft samples. It may be concluded that the SK soils may be a fruitful source of microbes that produce C-P bond containing compounds, such as phosphomycin.   4.2 Soil bacterial community analyses The traditional method of studying differences in environmental microbial communities involves fingerprinting techniques such as denaturing gradient gel electrophoresis (DGGE). This method is able to separate different species of PCR amplified marker gene products down to a single nucleotide base pair resolution. As the amplicons travel through the gel during the electrophoresis process they encounter an increasing gradient of DNA denaturing agents (usually urea and formamide). The denatured DNA amplicons will travel through the gel at different rates, hence forming distinct bands indicating individual base pair differences.  A DGGE analysis was done to compare the bacterial communities of PS and SK soils. The results suggest that the surface to 18ft PS soils had highly similar bacterial communities based on the similarities of their fingerprints. The tightly grouped banding pattern may also suggest a relatively low diversity of 16S rRNA species present. The 19ft PS soil community however was very different from the rest of its soil column, as it appears to have greater spacing between bandings suggesting higher bacterial diversity. This difference may be due to the physical property of high moisture content of the 19ft soil from the base of the excavation.  All soil horizons of the SK soil column appear to have high 16S rRNA gene diversity. Much of the gene amplicons are distributed throughout the entire gel, thus creating the effect of fainter banding patterns. A major caveat of this technique surrounds its inability to provide any comparison 71  between communities beyond a fingerprint image. The advent of next-generation multiplex sequencing has solved this issue and has become the standard method of studying the composition of microbial communities.  The PS and SK soil bacterial populations were also compared by metagenomic sequencing of their community 16S rRNA genes. Multiplex sequencing has allowed for the rapid sequencing of multiple amplicon samples in parallel, based on the use of a unique identifier barcode sequence on the reverse primers for each sample. The V6-V8 hypervariable region of the 16S rRNA gene was amplified from each of the ten soil DNA samples and submitted for sequencing using the Illumina HiSeq2000 sequencer. The sequence data were processed and analyzed as described in the methods and materials section. The results of these analyses revealed that the surface to 18ft PS soils were predominated by Actinobacteria and display an abrupt change to Proteobacteria predominance in the 19ft soil. This finding may be correlated with the fingerprinting patterns seen on the DGGE gel analysis of the PS soil communities. The SK soil communities were dominated by Proteobacteria, with the exception of the 20ft sample, which had a majority of Actinobacteria. OTU analysis of the sequence data also suggested much greater community diversity for the SK soils, which is in agreement with the DGGE results. The richness of Actinobacteria in the PS soils prompted their use as sources for the isolation of antibiotic-producing bacteria.    72  4.3 Characteristics of PS soil bacteria Twenty-two bacterial isolates were cultured from the PS soil samples. As mentioned previously, many more bacterial colonies grew on the isolation plates. Due to overcrowding of overlapping colonies, the fast growing single colonies on the plates were picked and stored for further studies. The resulting isolates are summarized in Table 3.1. Most of the strains were identified as species of Staphylococcus and Micrococcus, with one being a Bacillus species. The identities of strains S1, D1S1, D3N1 and D3N6 are unclear as their closest BLAST match were listed as uncultured bacteria. Strains D1S2O, D1S3 and D3N3 matched species of Microbacterium.   Assuming that the PS soils have not been exposed to clinical concentrations of antibiotics, the bacteria that reside in these communities should not display extensive multidrug-resistant phenotypes. However, increasing numbers of studies have shown the existence of antibiotic resistance genes in pristine environments. These findings led to the conclusion that the wide distribution of the so-called “antibiotic resistance genes” may not be the result of selection by antibiotic drugs, but are in fact genes that have alternative natural functions in their host organisms.  The antibiotic resistance profiles of the twenty-two soil isolates were studied using standard disc diffusion assays (Table 3.2). Indeed, the results showed that antibiotic resistant phenotypes were evident in most of the isolates. Thirteen of the isolates exhibited resistance to three or more antibiotics tested, while only two isolates, strains S2 and D3N1, were completely susceptible to antibiotics. The resistant strains were largely resistant to cell wall synthesis inhibitors. For example, fourteen strains were resistant to methicillin and twelve were resistant to oxacillin. 73  Fourteen were resistant to phosphomycin. Resistance phenotypes to other antibiotics tested were not at high levels. This confirms that bacteria may possess antibiotic resistant genes and phenotypes even when they have not been exposed to any significant drug selection.   The culture supernatants of four soil isolates, strains D12, D211Y, D3N3 and D4SW1, indicated weak antimicrobial activity against tester bacteria. The antibacterial compounds in the culture supernatants of strains D12, D211Y and D4SW1 were not studied further.  However, the identity of strain D3N3, a Microbacterium, rendered it an immediately interesting bacterium for further studies of antibiotic production. Microbacteria have not been studied for their production of antimicrobials.  In addition to examining the antibacterial properties of the soil isolates, they were also tested for the production of compounds that induce gene expression in Salmonella luciferase reporter systems. The reporter strains in this study were chosen based on the observation made previously in our laboratory that they produce strong light responses to rifampicin control. The identities of the reporters used are as follows: the fatty acid degradation protein gene (fadB), the phosphate regulon 2-component system response regulator gene (phoB), the methyl-accepting chemotaxis protein gene (tsr), the putative transport protein gene (yrbC), and the γ-aminobutyraldehyde dehydrogenase gene (ydcW).  The light induction results for the ydcW, fadB, phoB and tsr promoters showed clear patterns. They showed heightened induction by the soil isolates that were from the shallow soil samples. The isolates from below the 10ft in the soil column induced less light in these four Salmonella reporters. Interestingly, the Salmonella yrbC reporter was 74  strongly induced by soil isolates from the 18 and 19ft soils. These results show that the soil isolates induce gene transcription in other bacteria and may indicate novel antimicrobials. The observed light induction patterns are difficult to explain without in-depth studies of the bioactive molecules that trigger these responses.    4.4 Microbacterium sp. D3N3 and the production of phenylacetic acid Microbacterium sp. D3N3, isolated from the 18ft PS soil, became the focus of study in this thesis. As previously mentioned, microbacteria have not been thoroughly studied for their production of antimicrobials. The fact that strain D3N3 culture supernatant was inhibitory against M. luteus JVC 1154 and S. aureus RN4220 warranted further investigation. The Microbacterium strain was swabbed onto LBA plates (without NaCl) and left to grow into the stationary phase for one week. The agar cultures were extracted with ethyl acetate to produce a crude organic extract. This crude extract exhibited broad-spectrum inhibitory activity to bacterial pathogens. To test whether one or multiple compounds were responsible for the activity, the extract was separated using thin layer chromatography. The separated bands on the TLC plate were collected individually and extracted with ethyl acetate. The results suggested that one of the separated bands retained the full strength of inhibitory activity as the initial crude extract. The extract was also fractionated with RP-HPLC, to produce seven extract fractions. Again, only one fraction retained the inhibitory effects. The active HPLC fraction was predicted to contain one pure compound: phenylacetic acid. The antimicrobial activity of phenylacetic acid has been reported in the literature (Burkhead et al., 1998; Kim et al., 2004). The requirement of high PAA 75  concentrations for antibacterial activity, combined with federal regulations renders it difficult for use as an antimicrobial in the clinic.   A panel of fourteen Staphylococcus aureus RN4220 promoter-lux fusion reporters was used to aid in predicting the mode of action of PAA. The panel is used as a tool to provide fingerprint patterns of light induction when exposed to known antibiotics. As outlined in the results, PAA produced a specific light response fingerprint which did not match those of thirteen antibiotics tested. Therefore, the PAA mode of action remains unclear. However, it can be concluded from these data that PAA likely do not act as a DNA-damaging agent. The recA-lux clones are known to respond to compounds that have DNA-damaging characteristics, and none were induced by PAA at the concentrations tested.    The potential of interactions between PAA and antibiotics were examined. Disc diffusion assays suggest the possibility of weak additive interactions of PAA with tetracycline, colistin, ampicillin and novobiocin. The combinations of these antibiotics with PAA were further studied using the standard checkerboard method. The results of these assays did not produce fractional inhibitory concentration values below 0.5; therefore, the observed interactions are not synergistic.    4.5 Biosynthetic potential of microbacteria Besides the discovery of phenylacetic acid production by Microbacterium sp. D3N3, the search for biosynthetic genes in the strain was made possible from its genome sequence data. The thirty-six sequence scaffolds of M. sp. D3N3 were scanned against the AntiSMASH database in search 76  of matches to known biosynthetic gene clusters. A type III polyketide synthase gene homolog was found within the draft genome of strain D3N3. The sequence of the gene was translated to protein sequence for comparison with known T3PKS from bacteria and plants. The three key catalytic residues (Cys164, His303 and Asn336 (Medicago sativa numbering)) of the protein were conserved in the D3N3 homolog. The presence of a T3PKS gene was further proven by PCR amplification. T3PKS is found in both plants and bacteria. The products of T3PKS have an array of activities and functions as described in the introduction. The functions or products of T3PKS in M. sp. D3N3 remain unknown. The relationship between the possession of T3PKS and the production of PAA in strain D3N3 is unclear.  To explore the biosynthetic potential of other microbacteria, the genome sequences of various Microbacterium species deposited in GenBank were scanned with the AntiSMASH database. The results are summarized in Tables 3.4. A large proportion of the genomes contained T3PKS homologs. A multiple sequence alignment of several microbacterial T3PKS proteins suggested that they are closely clustered and distinct from those of other bacteria (Fig 3.15). Future studies, such as the heterologous expression of microbacterial T3PKS and identification of the polyketide products of these enzymes are necessary to understand the functions of T3PKS in this genus.   Three of the Microbacterium genomes possess putative nonribosomal peptide synthetase genes. The presence and functions of NRPS in microbacteria have not been reported in the literature. The discovery of these genes merits further investigation as with the T3PKS discussed previously. Several of the genomes also encoded genes related to terpene biosynthesis. The functions of these genes in microbacteria are unclear. However, as in the case of Staphylococcus 77  aureus, they may be involved in the production of terpenoid compounds, such as carotenoids, involved in cell pigmentation (Wieland et al., 1994). This may explain the yellow pigmentation in Microbacterium species.   4.6 Identity of Microbacterium sp. D3N3 The 16S rRNA gene is the standard marker gene used for phylogenetic classification of bacteria. The nearly complete 16S rRNA gene sequence of M. sp. D3N3 was compared with those of eighty-three species of Microbacterium through multiple sequence alignments. Results show that the many species of microbacteria are highly related based on the 16S rRNA gene sequence identities that extend beyond 97%, the standard cutoff for species differentiation. Studies of novel Microbacterium spp. have necessitated the use of phenotypic variation between isolates to aid in species identification. M. sp. D3N3 was closely matched with seven species of microbacteria based on the 16S rRNA gene comparisons (Fig 3.16). Following the methods that were used to distinguish these seven closely related microbacteria, sugar assimilation phenotypes as well as growth characteristics of strain D3N3 were compared data available for the related microbacteria (Kageyama et al, 2006; Kageyama et al, 2007; Kageyama et al., 2007). Not only are the phenotypes of the seven related microbacteria different, the results for strain D3N3 suggest that it distinct from the others. The seven related microbacteria were also compared by cell membrane fatty acid composition and cell wall peptidoglycan types of the strains. These comparative tests have not been done for strain D3N3.  78  A multilocus sequence typing analysis was completed to differentiate Microbacterium species. The phylogenies of the marker genes used largely reproduced those seen for the 16S rRNA gene alignments. However, there are some discrepancies in strain grouping for the gyrB phylogenetic tree. Many of the strains that clustered within groups in the trees of the other marker genes, were not members of such groups in the gyrB alignment. The 16S rRNA gene tree also displayed unreliability in the taxonomic assignments of certain species. As mentioned in the results, several strains did not group together with other members of the same species. These data indicate that none of the six genes (16S rRNA, recA, atpD, trpB, gyrB and rpoB) were definitive in distinguishing between Microbacterium species.  However, phylogeny based on concatenated sequences of these genes show improved grouping of strains of the same species. There is also a lower number of branching clusters seen in the concatenated gene tree. This suggests that the sequence data generated by gene concatenation were more robust in distinguishing between Microbacterium species.    4.7 Microbacteriophages Another aspect of microbacterial biology studied was the isolation of bacteriophages from the environment that infect Microbacterium. To date, six microbacteriophages have been isolated and have sequenced genomes. Three distinct environments were searched for the presence of microbacteriophages. They include wastewater from the UBC treatment plant, sea water and soil from UBC Wreck beach. Sea water and soil environments were chosen based on the fact that phages are ubiquitous in these locations, especially in the former. The individual environmental samples were processed and combined into mixed cultures of several Microbacterium strains for 79  enrichment. The enriched infection cultures were removed of bacterial cells and tested for infectivity of eight microbacterial strains. Phages WW1 and WW2 were isolated from a wastewater sample, while phage SEA1 was derived from sea water and phage SOIL1 was from a soil sample. The phage isolates are microbacteria-specific and infect only M. sp. D1S2O and M. sp. D1S3, both of which are M. oxydans strains. M. oxydans is an opportunistic human pathogen. Although the prevalence of microbacterial infections in humans is low, cases of infection are linked with other medical conditions which lead to increased complications (Gneiding et al., 2008). The treatment of microbacterial infections with antibiotics is largely effective, although in a study by Gneiding and colleagues, up to 10% of clinical isolates of microbacteria were resistant to rifampicin and cefotaxime. 22% of the strains in their study were resistance to ciprofloxacin. The isolation of phage specific for pathogenic strains of microbacteria may prove useful in the context of treating microbacterial infections.  The phylogeny of the phage isolates has not been completed, nor have they been delineated from each other. Extraction of the viral genomic material followed by restriction digest profiling will determine if the four isolates are distinct. The phage morphologies were observed using transmission electron microscopy with negative staining. The images suggested that phages WW1, SEA1 and SOIL1 were highly similar. They all have icosahedral capsid heads of approximately 100nm in diameter with very short tail fibers that are only seen during attachment to their host cells. Microbacteriophages isolated by other groups belong in the Siphoviridae family. The electron micrographs of these phages have icosahedral capsids with very long tail fibers. The TEM images of phage WW2 was very unusual. 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