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Environmental adaptation and stress response of Salmonella enterica in peanut oil, peanuts and chia seeds Fong, Karen 2015

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ENVIRONMENTAL ADAPTATION AND STRESS RESPONSE OF SALMONELLA ENTERICA IN PEANUT OIL, PEANUTS AND CHIA SEEDS  by  Karen Fong  BSc., The University of British Columbia, 2012  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Food Science)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  August 2015  © Karen Fong, 2015 ii  Abstract In North America, outbreaks of Salmonella in recent years have been linked to low-water activity (aw) foods, such as tree nuts, peanut butter and chia seed powder. The unusual emergence in microenvironments that should otherwise limit bacterial survival highlights the need for the elucidation of mechanisms that enhance Salmonella survival in low aw foods, which are currently poorly understood.  The purpose of this study was to evaluate the response of Salmonella enterica to two stressors commonly encountered in low-aw food processing, desiccation and heat treatment.  Five strains representing different serotypes of S. enterica were inoculated onto food matrices with varying aw: peanut oil (aw 0.521 ± 0.003), peanuts (aw 0.321 ± 0.20) and chia seeds (aw 0.585 ± 0.003) to identify survival characteristics in low-aw environments.  To assess the effect of stress pre-adaptation on survival, peanut oil-desiccated cells and/or cells shocked at 45°C were subsequently subjected to 70°C.  Lastly, the relative expression levels of five stress response or virulence genes (i.e. invA, fadA, otsB, rpoE and dnaK) were assessed following heat treatment or desiccation using quantitative polymerase chain reaction (qPCR).    S. enterica exhibited long-term survival in the low-aw foods (up to 105 days) and showed a strain-specific response.  S. Hartford and S. Thompson were identified as persistent in these low-aw foods, while Typhimurium was identified as the least persistent serotype.  Furthermore, cells pre-exposed to six days of desiccation in peanut oil and/or 45°C heat for three minutes exhibited significantly (p<0.05) higher resistance to 70°C heat treatment. iii   qPCR revealed various degrees of up- and down-regulation amongst the characterized genes and across different strains under the desiccation and heat treatments. Serotypes Hartford and Thompson displayed the highest up-regulation in otsB and fadA, genes vital in desiccation response, consistent with their persistence in the survival assays.  Moreover, differential expression of dnaK, a gene important for heat-tolerance was also observed across all Salmonella strains.  The current research emphasizes the adaptable nature of S. enterica to stresses encountered in low-aw food processing.  Additionally, unique stress response characteristics among Salmonella strains highlight the need for tailored mitigation strategies regarding high-risk Salmonella strains in the food industry. iv  Preface  The author, Karen Fong, under the guidance of supervisor Dr. Siyun Wang, solely conducted the research in this study.  This work is original and has not been previously published. v  Table of Contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iv Table of Contents ...........................................................................................................................v List of Tables ..................................................................................................................................x List of Figures .............................................................................................................................. xii List of Abbreviations ................................................................................................................. xiv Acknowledgements .................................................................................................................... xvi Dedication ................................................................................................................................. xviii Chapter 1: Literature review and research purpose ..................................................................1 1.1 Literature review ................................................................................................................ 1  1.1.1 Microbial characteristics of Salmonella ........................................................................ 1  1.1.2 Classification of Salmonella ......................................................................................... 2  1.1.3 Pathogenesis of non-typhoidal Salmonella infection .................................................... 4 1.1.3.1 PAI I ..................................................................................................................... 5 1.1.3.2 PAI II ................................................................................................................... 6 1.1.3.3 PAI III .................................................................................................................. 6 1.1.3.4 PAI IV .................................................................................................................. 7 1.1.3.5 PAI V ................................................................................................................... 7  1.1.4 Non-typhoidal salmonellosis ......................................................................................... 8 1.1.4.1 Diagnosis.............................................................................................................. 8 1.1.4.2 Treatment ............................................................................................................. 8 vi   1.1.5 Low-water activity foods as a concern ......................................................................... 9 1.1.5.1 Processing & production of peanuts .................................................................. 12 1.1.5.2 Processing & production of chia seed ................................................................ 13 1.1.5.3 Salmonella contamination and persistence in foods .......................................... 14 1.1.5.3.1 Agricultural environment ............................................................................ 14 1.1.5.3.2 Processing techniques in peanut production ............................................... 15 1.1.5.3.3 Processing techniques in chia seed production ........................................... 17 1.1.5.3.4 Salmonella stress response in low-aw food ................................................. 18 1.1.5.3.5 Salmonella stress response to desiccation................................................... 18 1.1.5.3.6 Salmonella response to heat shock ............................................................. 20 1.1.5.3.7 Desiccation and heat resistance among serotypes of S. enterica ................ 21 1.1.5.3.8 Cross-protection .......................................................................................... 22 1.1.5.3.9 Equipment ................................................................................................... 24 1.1.5.3.10 Improper zoning ........................................................................................ 25 1.1.5.3.11 Personnel ................................................................................................... 26 1.1.5.3.12 Control and detection of Salmonella in food production .......................... 27 1.1.5.3.13 Analysis of Salmonella in low-aw foods in Canada .................................. 29 1.2 Research purpose, origins and maintenance .................................................................... 31 Chapter 2: Survival of Salmonella in peanut oil, peanuts and chia seeds ..............................32 2.1 Introduction ...................................................................................................................... 32 2.2 Materials and methods ..................................................................................................... 32  2.2.1 Analysis of food matrices ........................................................................................... 32  2.2.2 Inoculum preparation and recovery of Salmonella ..................................................... 33 vii  2.2.2.1 Preparation of desiccated cells ........................................................................... 33 2.2.2.2 Peanut oil inoculation and recovery of Salmonella ........................................... 34 2.2.2.3 Chia seed inoculation and recovery of Salmonella ............................................ 34 2.2.2.4 Peanut inoculation and recovery of Salmonella ................................................. 35 2.2.2.4.1 Enrichment and PCR detection of Salmonella inoculated on peanuts ........ 35 2.3 Data analysis .................................................................................................................... 36 2.4 Results and discussion ..................................................................................................... 37  2.4.1 Analysis of food matrices ........................................................................................... 37 2.4.1.1 Sterility of food matrices ................................................................................... 37 2.4.1.2 Determination of water activity ......................................................................... 38  2.4.2 Survival of Salmonella in peanut oil ........................................................................... 39 2.4.2.1 Tmax of Salmonella in peanut oil ........................................................................ 39 2.4.2.2 Nmax of Salmonella in peanut oil ........................................................................ 39 2.4.2.3 AUC of Salmonella in peanut oil ....................................................................... 40  2.4.3 Survival of Salmonella in chia seeds .......................................................................... 42 2.4.3.1 Tmax of Salmonella in chia seeds ........................................................................ 42 2.4.3.2 Nmax of Salmonella in chia seeds ....................................................................... 43 2.4.3.3 AUC of Salmonella in chia seeds ...................................................................... 44  2.4.4 Survival of Salmonella on peanuts .............................................................................. 49 2.4.4.1 Tmax of Salmonella on peanuts ........................................................................... 49 2.4.4.2 Nmax of Salmonella on peanuts .......................................................................... 49 2.4.4.3 AUC of Salmonella on peanuts .......................................................................... 50 2.4.4.3.1 Recovery of Salmonella during prolonged storage of inoculated peanuts . 55 viii  2.5 Conclusions ...................................................................................................................... 58 Chapter 3: Protective effects of desiccation and mild heat treatment on lethal heat treatment on Salmonella ..............................................................................................................60 3.1 Introduction ...................................................................................................................... 60 3.2 Materials and methods ..................................................................................................... 61  3.2.1 Preparation of desiccated Salmonella cultures ............................................................ 61  3.2.2 Preparation of control Salmonella cultures ................................................................. 62  3.2.3 Desiccation for induction of cross-protection ............................................................. 62  3.2.4 Sub-lethal heat for induction of cross-protection ........................................................ 62  3.2.5 Statistical analysis ....................................................................................................... 63 3.3 Results and discussion ..................................................................................................... 63  3.3.1 Desiccated Salmonella cells survive better than the controls at 70°C ........................ 63  3.3.2 Effect of sub-lethal heat pre-adaptation on cell survival ............................................ 65 3.4 Conclusions ...................................................................................................................... 70 Chapter 4: Gene expression profiling of S. enterica under desiccation or 45°C heat treatment .......................................................................................................................................71 4.1 Introduction ...................................................................................................................... 71 4.2 Materials and methods ..................................................................................................... 72  4.2.1 RNA stabilization of bacterial cultures ....................................................................... 72 4.2.1.1 RNA stabilization of control cultures ................................................................ 72 4.2.1.2 RNA stabilization of heat-treated cultures ......................................................... 73 4.2.1.3 RNA stabilization of desiccated cultures ........................................................... 73  4.2.2 RNA isolation and quality assessment ........................................................................ 74 ix   4.2.3 Intervening sequence detection ................................................................................... 74  4.2.4 Reverse transcription of total RNA ............................................................................. 76  4.2.5 Quantitative PCR ........................................................................................................ 76 4.2.5.1 Amplification efficiency tests ............................................................................ 78 4.2.5.2 Analysis of gene expression with qPCR ............................................................ 80  4.2.6 Data and statistical analysis ........................................................................................ 81 4.3 Results and discussion ..................................................................................................... 82  4.3.1 RNA quality assessment ............................................................................................. 82  4.3.2 IVS detection ............................................................................................................... 82  4.3.3 Transcriptional profiles of S. enterica under desiccation and heat stress ................... 85  4.3.4 Expression of invA ...................................................................................................... 85  4.3.5 Expression of fadA ...................................................................................................... 87  4.3.6 Expression of rpoE...................................................................................................... 88  4.3.7 Expression of otsB ...................................................................................................... 90  4.3.8 Expression of dnaK ..................................................................................................... 92  4.3.9 Strain-related differences in gene expression levels ................................................... 94   4.3.10   The molecular basis of cross-protection .............................................................. 96 4.4 Conclusions ...................................................................................................................... 97 Chapter 5: Conclusion and future direction .............................................................................99 5.1 Conclusion ....................................................................................................................... 99 5.2 Future direction .............................................................................................................. 101 Appendices ..................................................................................................................................122 Appendix A: RNA quality assessments .................................................................................. 122 x  List of Tables  Table 1.1 Solutes and food matrices used to simulate low-aw in laboratory settings. ................. 30 Table 1.2 Origins and strain identification of S. enterica serotypes used for this study. ............. 31 Table 2.1 Presence (+) /absence (-) testing for native microflora on consumer-grade foods used in the survival assays. .......................................................................................................... 38 Table 2.2 The water activities of food matrices used in this study. ............................................. 38 Table 2.3 AUC for S. enterica in peanut oil.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD)............................... 42 Table 2.4 AUC for S. enterica on chia seeds.  Survivors were recovered on LB agar.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD). ..................................................................................................................... 48 Table 2.5 AUC for S. enterica on chia seeds.  Survivors were recovered on XLD agar.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD). ..................................................................................................................... 48 Table 2.6 AUC of S. enterica on peanuts.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD). ................................................. 55 Table 3.1 Reductions in S. enterica populations to lethal heat temperature at 70°C following sub-lethal heat and/or desiccation treatments.  All treatments were compared to the control xi  treatment at 70°.  Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD). .......................................................................................... 68 Table 4.1 rrl genes and corresponding primer sequences used for IVS detection. ...................... 75 Table 4.2 Analyzed genes and their respective primer sequences used in qPCR assays. ............ 77 Table 4.3 Master mix assembly for qPCR assays. ....................................................................... 78 Table 4.4 qPCR reaction assembly. ............................................................................................. 79 Table 4.5 Annealing temperatures of the genes analyzed in qPCR assays. ................................. 80  xii  List of Figures   Figure 2.2 Survival of S. enterica on chia seeds stored at 20°C.  Survivors were recovered on LB agar.  Error bars indicate the standard errors of the means. ................................................ 46 Figure 2.5 Survival of S. enterica serotypes Hartford and Thompson on peanuts stored at 20°C.  Survivors were recovered on LB agar.  Error bars indicate the standard errors of the means. ............................................................................................................................................. 53 Figure 2.6 Survival of S. enterica on peanuts stored at 20°C.  Survivors were recovered on LB agar.  Error bars indicate the standard errors of the means. ................................................ 54 Figure 2.7  S. enterica survivors after 70 days of desiccation on peanuts.  Peanuts were enriched in BHI broth and streaked on XLD agar to obtain isolated Salmonella colonies.  Presumptive colonies were tested for presence of the invA gene.  PCR amplicons were electrophoresed in 1x TAE buffer on 2% agarose. Bright bands indicate presence of the invA gene. ............................................................................................................................ 57  Figure 3.1 Mean log reduction of S. enterica after heat and/or desiccation treatments.  Treatments were compared to the control treatment at 70°C (dotted bars).  One asterisk (*) indicates significance below α<0.05. Error bars indicate the standard errors of the means. ............................................................................................................................................. 69 Figure 4.1 PCR products of S. enterica following IVS detection.  Primers used were specific to the rrl gene at helices 25 and 45. Presence of a ~830 bp band indicates IVSs in the corresponding helix of the 23S rRNA molecule of the strain…………………………… 84 xiii  Figure 4.2 Log2 fold change in expression of the invA gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means……………………………………………………... 86 Figure 4.3 Log2 fold change in expression of the fadA gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means……………………………………………………... 88 Figure 4.4 Log2 fold change of expression of the rpoE gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means……………………………………………………... 90 Figure 4.5 Log2 fold change of expression of the otsB gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means…………………………………………………….. 92 Figure 4.6 Log2 fold change of expression of the dnaK gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means……………………………………………………... 94   xiv  List of Abbreviations  ANOVA Analysis of variance AUC Area under the curve aw Water activity BGS Brilliant Green Sulfa BHI Brain-Heart-Infusion bp Base pair BS Bismuth sulfite cDNA Complementary DNA CFU Colony forming units Ct Threshold cycle DNA Deoxyribonucleic acid E Efficiency FDA Food and Drug Administration GASP Growth advantage in stationary phase GMP Good Manufacturing Practice H2S Hydrogen sulfide HACCP Hazard Analysis and Critical Control Points IVS Intervening sequence kb Kilo-base LB Luria-Bertani LEE Locus of enterocyte effacement Nmax Maximum achieved concentration OD600 Optical density at 600 nm PAI Pathogenicity island PBS Phosphate buffered saline PCR Polymerase chain reaction PFGE Pulsed-field gel electrophoresis xv  PUFA Polyunsaturated fatty acid qPCR Quantitative polymerase chain reaction RIN RNA integrity number RNA Ribonucleic acid RNase III Ribonuclease III rRNA Ribosomal ribonucleic acid RT Reverse transcriptase SD Standard deviation SNP Single nucleotide polymorphism TAB Total aerobic bacteria TAE buffer Tris-Acetate with EDTA buffer TBG Tetrathionate Brilliant Green Tmax Maximum survival period tRNA Transfer RNA TTS Type III secretion TTSS Type III secretion system Tukey’s HSD Tukey’s Honest Significant Difference UV Ultraviolet WGS Whole genome sequencing WGST Whole genome single-nucleotide polymorphism typing XLD Xylose-lysine-deoxycholate    xvi  Acknowledgements  First and foremost, I extend my sincere gratitude to my supervisor, Dr. Siyun Wang for being an excellent mentor and role model throughout this project.  Your continued support, optimism and wealth of knowledge are especially appreciated.  Thank you for your guidance and faith in my abilities.  Secondly, I gratefully acknowledge my committee members, Ms. Lorraine McIntyre and Dr. David Kitts, for their innovative ideas and probing questions.  Your considerations have been ever so helpful during the progression of my project.  Thank you to the University of British Columbia for funding that made this project possible.  Technical support from Yvonne Ma, Hyun Soo Seo and Yining Mao are gratefully acknowledged.  Thank you for your assistance and fun laboratory discussions!  To all members of the Wang lab, thank you for undertaking this fun roller coaster ride of a MSc. with me, and keeping me sane.  Meeting such like-minded people has definitely made this journey exciting.   To my partner-in-crime, Remo Scheidegger, I am especially appreciative of your continued encouragement and belief in me.   xvii  And last but not least, I am so thankful for my family: my parents, Susan and Chang On Fong, and my little sister, Ashley.  I appreciate all the support and stability you have given me.  Thank you for being my biggest cheerleaders. xviii  Dedication   This thesis is dedicated to my mom –  For teaching me to strive for what I wish to become. 1  Chapter 1: Literature review and research purpose  1.1 Literature review 1.1.1 Microbial characteristics of Salmonella Salmonellae are Gram-negative, rod-shaped, non-spore-forming facultative anaerobes, which cause a wide range of clinical conditions known as salmonellosis (Jay et al., 2005).  Most Salmonellae, except for serotypes Pullorum and Gallinarum, are motile with peritrichous flagella (Kwon et al., 2000).  Almost all serotypes of Salmonella produce hydrogen sulfide (H2S) from thiosulfate and sulfite (Barrett & Clark, 1987).   H2S production is a characteristic feature exploited in the formulation of selective agars (e.g. xylose-lysine-deoxycholate (XLD)) to differentiate Salmonella from other microorganisms; most appear as black colonies on the surface of XLD agar (Zajc-Satler & Gragas, 1977).  Salmonella is generally considered to be unable to ferment lactose, however, the environment may influence its ability to ferment certain sugars, such as lactose (Blackburn & Ellis, 1973).   Salmonellae are capable of infecting a wide range of hosts, with some serotypes being better adapted to specific hosts than others.  For instance, serotypes Typhi and Paratyphi are highly adapted to humans and have no known natural hosts (i.e. asymptomatic carriers of these pathogens) (Tauxe & Pavia, 1998), while serotype Choleraesuis is particularly well-adapted to swine and causes paratyphoid in these animals (Field, 1958).  Worldwide, Typhimurium and Enteritidis are the top two serotypes causing the highest proportion of disease in humans (Mattick et al., 2000) and are known to colonize the intestines of a wide variety of animals (Field, 1958).  Enteritidis has been frequently isolated from foods of animal origin, especially 2  shelled eggs and poultry (Angulo & Swedlow, 1998), while human disease caused by S. Typhimurium has been predominantly associated with pig, poultry and bovine meat (EFSA, 2011).  1.1.2 Classification of Salmonella Salmonellae are a diverse group of bacteria, characterized by two species, six subspecies and over 2500 serotypes, or serovars (Malorny et al., 2011).  Salmonella is a genus of the family Enterobacteriaceae (Farmer, 1995) and contains only two species: Salmonella bongori and Salmonella enterica.   S. bongori is predominantly associated with cold-blooded animals and rarely causes disease in humans, while S. enterica is responsible for the majority of human foodborne illnesses associated with this pathogen (Malorny et al., 2011).  S. enterica can be further subdivided into six subspecies:  enterica, salamae, arizonae, diarizonae, houtenae and indica (Malorny et al., 2011).  Biochemical testing is the primary method to distinguish between subspecies (Farmer, 1995) and can be accomplished using a variety of methods, including API20E biochemical test strips (bioMérieux, Geneva, Switzerland).  For the classification beyond the subspecies level, the White-Kauffman-Le Minor scheme is often employed (Grimont & Weill, 2007), which categorizes serotypes according to their surface antigens.   Predominantly, the O-antigen, belonging to the cell surface lipopolysaccharide, and the H1 and H2 antigens, belonging to flagellar proteins that form phase 1 or phase 2 flagella, respectively, are assayed (Brenner et al., 2000; Chan et al., 2003). Interestingly, within S. 3  enterica ssp. enterica, O-antigen serogroups A, B, C1, C2, D and E cause 99% of Salmonella cases in humans and warm-blooded animals (Brenner et al., 2000).  For example, serotypes Typhi and Enteritidis both reside within S. enterica ssp. enterica, however, S. Typhi causes the systemic disease typhoid fever, while S. Enteritidis is the cause of self-limiting gastroenteritis, diarrhea and vomiting (Morgan, 2007).   Criticisms over serotype categorization using phenotypic serological approaches have led to the development of genomic sequencing-based technologies.  The slide agglutination test is a typing method based on antibody-antigen interactions; agglutination will occur should there exist an interaction between the antibody and the antigen of the bacteria.  However, false-positive reactions can occur due to weak, nonspecific agglutination and some particular phenotypes (rough, non-motile and mucoid isolates) may lose antigenic expression altogether (Schrader et al., 2008).  Pulsed-field gel electrophoresis (PFGE) is currently considered as the gold standard in Salmonella outbreak investigations; its high discriminatory power allows for separation of related strains, allowing public health authorities to identify sources of contamination based on sets of genetic “fingerprints” generated from the electrophoretic motilities of restriction fragments (Foley et al., 2007).   However, some critics argue that PFGE is unreliable and largely subjective due to the high number of genetic profile clusters produced on the basis of only minor differences (Bakker et al., 2014; Wattiau et al., 2011).  In a recent study, Deng et al. (2015) compared the discriminatory powers of PFGE and whole-genome single-nucleotide polymorphism typing (WGST) using 52 S. Enteritidis isolates.  Subtyping using WGST resulted in the resolution of all outbreak clusters previously produced using PFGE, providing robust accuracy in the differentiation of closely related isolates (Deng et al., 2015).    4  Whole genome sequencing (WGS) is an extraordinarily powerful tool for making genomic comparisons between bacterial isolates, down to the level of the nucleotide; virtually all genetic differences are detected when comparing across isolates.  Moreover, the cost of WGS has decreased over recent years (Didelot et al., 2012) and has become a viable option for use in public health diagnostics (Koser et al., 2012).   A particular advantage of WGS is the provision of superior genomic resolution; it is a powerful tool for discovery of single nucleotide polymorphisms (SNPs), especially important for genetically homogenous serotypes such as S. Enteritidis (Deng et al., 2015).  Diagnostically, WGS is substantially more discriminatory than PFGE (Foley et al., 2006) as slight genetic variability between strains does not affect the electrophoretic mobility of the restriction fragments in PFGE subtyping (Foley et al., 2007).    1.1.3 Pathogenesis of non-typhoidal Salmonella infection The primary virulence determinants of Salmonella are encoded on pathogenicity islands (PAIs), 10-200 kilo-base (kb) regions that carry genes responsible for causing infection.   These distinct regions within the chromosome contain multiple genes which contribute towards virulence  (Marcus et al., 2000).  It has been documented that the presence of a PAI may be sufficient to transform a benign microorganism into a pathogenic one.  For instance, virulence can be conferred to a laboratory strain of Escherichia coli through introduction of a plasmid carrying the locus of enterocyte effacement (LEE) region.  The LEE PAI encodes for a type III secretion system (TTSS), which transfers virulence effectors into the host cell (McDaniel et al., 1995).  In Salmonella, five PAIs have been discovered, but the structure, number and function of these are highly variable between different members within the genus (Marcus et al., 2000).  5  Salmonella PAIs contain a lower G-C content than that of the genome and are frequently found between transfer RNA (tRNA) genes, supporting the hypothesis they arose as a result of horizontal transfer mediated by phages or plasmids of unknown origin (Marcus et al., 2000).  1.1.3.1 PAI I PAI I is the best studied of all the PAIs present in Salmonella.  PAI I accommodates at least 29 genes, which encode a type III secretion system (Collazo & Galan, 1997).  Type III secretion (TTS) has been extensively studied in S. Typhimurium, which causes gastroenteritis in humans.  Orally administered S. Typhimurium PAI I knockout mutants demonstrated attenuated virulence in a mouse model (Jones & Falkow, 1994).  However, the same effect was not observed when the same mutants were intravenously (systemically) administered, suggesting that closely related serotypes like S. Typhi likely possess other virulence factors required to cause systemic disease (Jones & Falkow, 1994).  Upon ingestion of Salmonella, the pathogen must be able to survive the gastric acidity prior to colonization of the intestinal M cells (Marcus et al., 2000). The TTSS encodes all genes necessary to construct the “needle-like” apparatus, including most of the effector proteins (Lostroh & Lee, 2001).  This structure is ~50 nm long and acts as a conduit for the effector proteins (Burkinshaw & Strynadka, 2014).  Upon encountering the necessary environmental conditions, the apparatus is produced, which spans both the inner and outer membrane (Kubori et al., 1998), and translocates into the host cell membrane, where the effector proteins are then secreted (Burkinshaw & Strynadka, 2014).  pH upshift from acidic to alkaline appears to be the predominant environmental factor regulating TTS (Daefler, 1999), which reflects the 6  translocation from the gastric acid to the mildly alkaline pH of the small intestine.  The effector proteins can go on to interrupt host ubiquitin pathways (which facilitate processes such as protein degradation, DNA repair and cell cycle control), covalently modify host cell proteins and alter the host cytoskeleton (Burkinshaw & Strynadka, 2014).  Additionally, these effectors also regulate the uptake of the Salmonella into the host cell itself. This is remarkable because the host epithelium is not normally phagocytic (Darwin & Miller, 1999).  1.1.3.2 PAI II Upon invasion of the M cell, the host immune system will deploy macrophages to envelop the infected cell and designate it for removal.  In Salmonella, PAI II also encodes for a TTSS, however it is functionally distinct from the secretion system encoded by PAI I.  Studies have suggested that the function is not for survival in adverse conditions, but for the replication of the pathogen in macrophages (termed a Salmonella-containing vacuole) (Shea et al., 1999; Waterman & Holden, 2003), allowing persistence and further dissemination.  Moreover, mutations within the TTSS of PAI I cannot be complemented by PAI II, further suggesting that these two systems do not share functionality (Marcus et al., 2000).  Although PAI II is generally understood to facilitate the growth of Salmonella in a host (Marcus et al., 2000), the exact molecular basis for this remains to be fully elucidated.  1.1.3.3 PAI III PAI III is best described as a mosaic of sorts as the genes within the cassette bear no obvious functional relationship to one another (Marcus et al., 2000).   This suggests PAI III arose from multiple transfer events.  The proteins encoded by PAI III include those essential for Mg2+ 7  transport (Blanc-Potard et al., 1999), and some bear sequence similarity to toxins produced by enteropathogenic E. coli and Vibrio cholera – suggesting that PAI III may play a role in host specificity and chronic infection (Blanc-Potard et al., 1999).  1.1.3.4 PAI IV Containing 18 open reading frames, PAI IV is structurally similar to PAI III and also contains genes that are functionally diverse (Wong et al., 1998).   Markedly, it is postulated that this PAI may encode for cytotoxins; sequence analysis has revealed the presence of a type I secretion system (Wong et al., 1998).  Therefore, it is thought that PAI IV helps to contribute to intracellular survival through direct apoptosis of the macrophage itself (Waterman & Holden, 2003).  1.1.3.5 PAI V PAI V plays a large role in enteropathogenesis and contains six open reading frames.  A well-characterized gene, sopB (Salmonella outer protein), mediates host cell inflammation and fluid secretion (Wood et al., 1998).  Interestingly, the sip gene family is necessary for SopB translocation and is located in PAI I, therefore PAI V also appears to be regulated by PAI I (Wood et al., 1998).  Other putative genes within this PAI include pipC, which encodes for a chaperone protein to assist in SopB secretion, pipB (glycolipid biogenesis) and pipD (peptidase secretion) (Hong & Miller, 1998).  8  1.1.4 Non-typhoidal salmonellosis 1.1.4.1 Diagnosis Infection with Salmonella is difficult to diagnose without performing the proper laboratory testing due to the ambiguity of symptoms.  Often, the symptoms associated with salmonellosis are much like that of other enteric pathogens and consist of fever, diarrhea and abdominal pain (Hohmann, 2001).  To make a definitive diagnosis, fecal samples from the patient are normally tested for the presence of Salmonella using a combination of selective agars (e.g. MacConkey agar) for isolation (Hohmann, 2001).  Extensive serotyping may also be used for formal identification (Chiu et al., 2004), while it is more common to classify the O-antigens into different serogroups for identification: A, B, C1, C2, D or E (Farmer, 1995).  This method allows for rapid genus identification, but cannot be used for distinguishing enteric fever from localized gastroenteritis due to antigenic cross-reactivity; serotypes Typhi and Enteritidis, which cause enteric fever and gastroenteritis, respectively, are both members of serogroup D (Chiu et al., 2004).  Similarly, serotypes Choleraesuis and Infantis, which cause invasive infection and gastroenteritis, respectively, both belong to group C1 (Chiu et al., 2004).   1.1.4.2 Treatment Due to increasing antimicrobial resistance, the Centers for Disease Control and Prevention (CDC) recommends use of antimicrobial agents only in cases of severe illness (CDC, 2015b).  Rather, due to the self-limiting nature of most salmonellosis cases, oral rehydration is recommended for loss of fluids from vomiting and diarrhea.  In cases of severe diarrhea, intravenous rehydration may take place (CDC, 2015b).  Additionally, antibiotics may increase fecal shedding of non-typhoidal Salmonella, prolonging the infectivity of these microorganisms.  9  This is likely due to the impairment of endogenous microflora, which “protects” the intestine from harm caused by Salmonella (Gopinath et al., 2014).  In general, antimicrobial agents may be used in two cases: a) patients who are severely ill (e.g. high fever, severe diarrhea, bacteremia, etc.) and b) patients who are at a high risk for additional complications (e.g. infants, people over 65 years of age and immunocompromised individuals) (CDC, 2015b).  Antibiotics proven useful to fight Salmonella infection include doses of a single bactericidal drug: fluoroquinolones, trimethoprim-sulfamethoxazole, ampicillin, or third-generation cephalosporins (Hohmann, 2001). Azithromycin was previously proposed for treatment of both typhoidal and non-typhoidal salmonellosis (Hohmann, 2001), but increasing resistance to this antibiotic has been reported amongst S. enterica (Sjolund-Karlsson et al., 2011).  1.1.5 Low-water activity foods as a concern The general notion has been that low-aw foods are at a low risk for causing salmonellosis as they are unable to support microbial life and growth.  However, outbreaks of Salmonella from foods low in moisture suggested a re-examination of the health hazards associated with the consumption of these food products (CDC, 2015a).  Mechanisms of Salmonella survival in low water environments have not been thoroughly elucidated, although efforts in recent years have unveiled new knowledge (Deng et al., 2012; Finn, Händler, et al., 2013; Gruzdev et al., 2012).  Moreover, serotypes not previously associated with low water foods have been emerging in related outbreaks (CDC, 2015a).  10  In the food safety context, water activity (aw) is known as the amount of “free” water in a given substrate (i.e.. water not bound to a solute) (Humphrey, 2004).  Low-aw foods are either naturally low-aw, or have been processed to achieve such a property (e.g. through addition of salt or sugar).  For most bacteria, the minimum aw for growth is 0.87 (Beuchat et al., 2013), however it has been suggested that the lower limits for growth are dependent on the conditions (e.g. type of solute) used to simulate low-aw in laboratory settings (Stewart et al., 2002).  A variety of solutes and food matrices have been used to simulate low-aw (table 1.1).  The Food and Drug Administration (FDA) classifies foods with aw below 0.85 as low-aw (FDA, 2015).  Examples of foods with aw <0.85 include chocolate, powdered infant formula, pasta, peanut butter, spices, peanuts, tree nuts and seeds (Beuchat et al., 2013).  Most of these foods are ready-to-eat (i.e. does not require further cooking), which poses an additional risk due to the absence of a kill-step prior to consumption.  In Canada and the U.S., the majority of low-aw food recalls have been attributed to nuts, seeds and nut or seed-derived products (CDC, 2015a; Harris et al., 2015).        11  Table 1.1 Solutes and food matrices used to simulate a low-aw condition in laboratory settings. Solute(s) or food matrix used  Aw Reference Glucose-fructose 0.75, 0.80, 0.90 Mattick et al., 2001 Glycerol 0.86, 0.93 Mattick et al., 2000 Granulated sugar 0.50 Chen et al., 2014 NaCl 0.75, 0.90 Mattick et al., 2001 Paper disks 0.11 H. Li et al., 2012 Peanut butter 0.3, 0.45, 0.50 Aviles et al., 2013; Ma et al., 2009; Shachar & Yaron, 2006 Peanut oil 0.30 Deng et al., 2012 Plastic Petri dishes 0.40 Gruzdev et al., 2012 Powdered infant formula 0.28 Koseki et al., 2015 Stainless steel coupons 0.11 Finn, Händler et al., 2013 Sucrose 0.80, 0.90 Mattick et al., 2001 Walnuts (in-shell) 0.25 Blessington et al., 2013 Whey protein powder 0.54 Farakos et al., 2014   12  1.1.5.1 Processing & production of peanuts Peanut (Arachis hypogaea L.) crops are important commodities grown worldwide, with their origins rooted in South America (Rustom et al., 1996).  Approximately 33 million tons of peanuts are produced yearly on a global scale (Zhao et al., 2012).  Unlike other nuts, such as almonds, pecans or pistachios, peanuts mature underground inside pods, and each pod typically contain two to four seeds (Maness, 2005).  In the United States, Runner peanuts are the most commonly produced and are primarily used for peanut butter production (Miksch et al., 2013).  Other mass-produced peanut derived commodities include edible oil, confections, as ingredients in meat products, snack products and soups (Rustom et al., 1996).   Following harvesting of the peanuts, mechanical drying normally takes place.  This is accomplished with on-farm dryers which blow heated air (~35°C) through the peanuts, drying them to moisture levels of approximately 7-10% to minimize aflatoxin contamination, toxic metabolic byproducts of the fungal pathogens Aspergillus flavus and Aspergillus parasiticus (Woodroof, 1983).  Subsequently, sizing of in-shell or shelled nuts will take place according to sizing standards, followed by blanching and roasting steps.  Salt and flavouring may be added (Kader & Thompson, 1992).  At this point, processed peanuts may be separated into different streams according to the finished product.  In such pre-destined streams, they may be packaged for consumption, ground for confections such as peanut butter, or the oil in the kernels may be extracted (Ivarsson & Napasol, 2013).  Should further processing steps occur, packaging of the finished product will take place, which should aim to provide a moisture barrier, be oxygen-free to slow development of rancidity and exclude light to minimize colour deterioration (Kader & Thompson, 1992). 13  1.1.5.2 Processing & production of chia seed Salvia hispanica L., commonly known as chia, is native to Mexico and Guatemala.  As such, it is commonly cultivated in subtropical and tropical regions (Huxley, 1992) due to the long growing season required (Kummer & Phillips, 2012).  However, it may also be grown in greenhouses in some parts of Europe because they are relatively frost-resistant (Huxley, 1992).  In South America, chia is commonly cultivated commercially (Coates & Ayerza, 1996).  Worldwide demands for chia seeds are high, due to their high nutritive contents and association with decreased risks for cancer and heart disease (Kummer & Phillips, 2012).  Chia seeds contain the highest proportion of α-linolenic acid compared to other natural sources (Ayerza, 1995) and high levels of protein compared to traditional cereals (Coates & Ayerza, 1996).  Additionally, chia seeds and meal have high levels of polyunsaturated fatty acids (PUFAs) without the commonly associated drawbacks (e.g. undesirable “fishy” tastes, digestion problems, etc.) compared to other PUFA-containing sources (Ayerza, 1995).  The chia plant is herbaceous in nature, producing white or dark seeds, although white seed varieties are rather rare; white seeds are encoded for by a single recessive gene (Ayerza et al., 2002).  The seeds of the chia plant may be utilized and processed in a variety of ways, including production for whole seed consumption, production of sprouts, as ingredients in other products (such as nut butters) or milled to produce powder.    Harvesting of the seeds takes place mechanically with a standard combine and is delivered directly to the processor after harvest (Kummer & Phillips, 2012).  Upon arrival at the processing facility, chia seeds contain 11-14% moisture.  Seeds are soaked in water for 45 seconds for 14  germination and drained.  Following germination, seeds are left overnight in trays for drying.  Subsequently, they are dried in an oven heated to 49 to 60°C for 20 to 24 hours.  The seeds are then cooled at room temperature and may be ground for production of chia seed powder (CDC, 2014c).  1.1.5.3 Salmonella contamination and persistence in foods 1.1.5.3.1 Agricultural environment Primarily, the reservoir for Salmonella is poultry, and as such, poultry farms, by law, have adopted a wide variety of control measures to control transmission and minimize consumer risk (Keery, 2010).  However, other animals, such as swine and beef cattle, can also harbour Salmonella (Rodriguez et al., 2006) and therefore are significant vectors for transmission.   As such, fecal contamination of irrigation water and manure are regarded as two significant hazards that may contribute to transmission of Salmonella onto agricultural crops, including peanuts and chia (Franz & van Bruggen, 2008).  Furthermore, agricultural products may be contaminated by salmonellae through contact with bird feces, wild animals and mishandling by personnel during and after harvest (Mahon et al., 1997).  The risk of Salmonella transmission onto crops largely depends on the ability of this pathogen to survive and persist in soil.  General understanding of pathogen persistence in the agricultural environment has greatly increased over the past few years, with numerous reports that pathogens, like Salmonella, can persist in such environments over long periods of time (Beuchat & Mann, 2010; Danyluk et al., 2008; Uesugi et al., 2006).  Guo et al. artificially inoculated Salmonella into moist soil and demonstrated survival for at least 45 days (Guo et al., 2002).  Additionally, 15  tomatoes grown in this contaminated soil tested positive for Salmonella at the time of harvest.  Natvig et al. also demonstrated the persistence, or prolonged survival, of S. Typhimurium on root vegetables following soil enrichment with contaminated manure (Natvig et al., 2002).   Calhoun et al. reported that 22 lots of peanuts (out of 944 samples) tested positive for 12 Salmonella serotypes over three crop years in the United States (Calhoun et al., 2013).  Further, the 2014 Salmonella outbreak associated with chia seed powder brought to light the persistence of this pathogen in previously undocumented low-aw foods (CDC, 2014b).  There have also been reports of Salmonella contamination on other seeds.  For example, S. Stanley was linked to an outbreak of alfalfa sprouts grown from contaminated seeds in the United States and Finland (Mahon et al., 1997) and S. Bovismorbificans was also traced to contaminated alfalfa seeds resulting in outbreaks in Finland and Sweden (Ponka et al., 1995).  Collectively, these incidents reinforce the notion that Salmonella can successfully colonize in the agricultural environment and subsequently contaminate the resultant crop.    1.1.5.3.2 Processing techniques in peanut production One of the most effective and commonly used interventions for pathogen reduction in peanut production is thermal processing.  In peanut production, however, this step is not necessarily targeted towards pathogen elimination but rather towards achieving desirable sensory attributes, such as colour, taste and texture (Pattee et al., 1991).  Heat treatments commonly take place prior to grinding or milling the nuts for peanut butter production (Frelka & Harris, 2014).  Roasting reduces the moisture content of the nut and modifies its microstructure, which results in 16  the crunchy and crispy textures consumers often associate with peanuts (Perren & Escher, 2013).  The peanut industry commonly roasts the products until a desired surface colour is achieved according to Hunter’s L-value, which is reflective of texture and flavour.   The process can be attained using a variety of different time and temperature combinations (Pattee et al., 1991).  Thus, the ambiguity of this procedure makes process validation for removal of pathogenic microorganisms difficult, especially because roasting processes designed for pathogen removal may also adversely affect quality attributes of the peanut (Ivarsson & Napasol, 2013).  This was part of the problem at one peanut butter processing facility, where S. Typhimurium was implicated in an outbreak in the U.S. in 2008, affecting over 700 people and resulting in the deaths of nine individuals.  In the FDA inspection report for the investigation, one of the major reasons for the contamination was the failure to validate their thermal process, which was a critical control point in the facility.  Specifically, validation of the roast temperature, volume and roaster belt speed was absent (FDA, 2009b).  From a food safety perspective, a notable drawback to peanut roasting is the conditions under which heat is applied.  Typically, moisture content of the nut is low and roasting takes place in dry conditions, which further desiccates (dries) the nut.  Interestingly, Salmonella exhibits resistance to dry heat (Ivarsson & Napasol, 2013) compared to heat treatments in humid environments.   Consequences of roasting in humidity, however, include de-skinning, softening of texture and undesirable flavor notes (Perren & Escher, 2013), which may result in large economic losses to peanut processors.  17  1.1.5.3.3 Processing techniques in chia seed production One of the microbial risks associated with chia seed production is the sprouting procedure.  After harvesting, seeds are soaked in water to commence the germination process, usually in a moist, aerated environment (CDC, 2014c; Gill et al., 2003).  Jaquette et al. investigated the behaviour of S. Stanley on alfalfa seeds during sprouting.  First, they artificially inoculated the pathogen onto the surface of the alfalfa seed, followed by a 5 or 10-minute water dip to induce germination.  Increases of three, to over seven, log10 colony forming units (CFU)/g were reported after 18 hours, despite a low initial inoculum and irregular dispersion throughout the seeds. Therefore, the conclusion was that in the presence of Salmonella contamination on the raw seeds, the germination process could greatly exacerbate microbial risk due to rapid increases in cell concentration (Jaquette et al., 1996).  It is well documented that Salmonella is able to proliferate upon introduction of moisture (Beuchat et al., 2013; Mattick et al., 2000).  Jaquette et al. also treated the water dip with 5,000 ug/ml of chlorine or applied the treatment at 71°C, however, S. Stanley was not eliminated, although there was a significant decrease in the bacterial cell density.   Unfortunately, these treatments are unlikely to be used in industry due to potential decreased sensory attributes of the product (Jaquette et al., 1996).  The U.S. FDA recommends raw seeds be treated with 20,000 ppm Ca(OCl)2 during pre-germination.  However, it is unclear whether these recommendations are fully adhered to.  Moreover, the proportion of seeds produced from such suggested pre-germination treatments is unknown (Gill et al., 2003).  18  Another issue regarding the germination process is the source of the water used for dipping.  In the U.S., it is estimated that 19 million cases of disease from contaminated drinking water occur yearly (Reynolds et al., 2008).  Following the Salmonella outbreak in chia seed powder in the U.S. and Canada (CDC, 2014b), it was observed that germination water was sourced from the municipal supply (CDC, 2014c).   1.1.5.3.4 Salmonella stress response in low-aw food Throughout the food processing continuum, microorganisms encounter various sub-optimal environmental conditions which exert a stress upon the cell.   Specifically, stress may be described as any departure from optimal conditions, with the potential to decrease bacterial growth (Storz & Hengge-Aronis, 2000).  An appropriate response must be mounted to mitigate effects of any cellular damage and/or prevent further damage, and this concept is known as stress response.  In the food industry, interventions are designed to create a stress that results in the destruction of pathogenic and/or spoilage microorganisms.  These stresses may take many forms, including pH shift, disinfectants, antimicrobials, dehydration, ultraviolet (UV) radiation and temperature shift.  Specifically, processing of low-aw foods incorporate desiccation and heat treatments to facilitate reduction of Salmonella.   1.1.5.3.5 Salmonella stress response to desiccation Desiccation stress is typically encountered at various time points within low-aw food production; from the drying processes to the storage of the finished product.   Hyperosmotic stress results in a net loss of water from the cytoplasm and translocation across the phospholipid bilayer into the microenvironment (Delamarche et al., 1999; Spector & Kenyon, 2012).  Cellular damage from 19  desiccation may occur at multiple sites; including pore formation in the outer membrane (Wesche et al., 2009), membrane segregation leading to loss of solutes (Beney et al., 2004) and cessation of enzymatic and metabolic activities (Deng et al., 2012).    To counteract such cellular modifications, Salmonella has evolved several innate adaptive mechanisms.   Small, low-molecular weight biomolecules called osmoprotectants, may be synthesized de novo and/or sequestered to balance out the osmotic potential (H. Li et al., 2012).  Such osmoprotectants include proline, glycine-betaine, ectoine and trehalose, and can effectively replace water under such circumstances (Finn, Condell, et al., 2013; H. Li et al., 2012; Spector & Kenyon, 2012).  Subsequently, transporter genes proP, proU, and osmU may also be upregulated to facilitate translocation of these osmolytes into the external environment (Finn, Händler, et al., 2013).     Increased rates of degradation in certain cell components have also been observed, likely to serve as a release of nutrients and energy for synthesis of compounds against desiccation.  Through transcriptome analysis of desiccated S. Enteritidis using RNA sequencing, increased levels of ribosomal RNA degradation were observed (Deng et al., 2012).  Degradation can also occur in the membrane, where fatty acids, a cost-effective energy source, can be fed directly into the tri-carboxylic acid cycle (James et al., 1999).  It was demonstrated that following two hours of air-drying at 11% relative humidity, S. Tennessee exhibited a 95-fold upregulation in the fad gene family, responsible for fatty acid catabolism (H. Li et al., 2012).   One of the stress responses directly related to the conservation of energy is filamentation.  20  Desiccated S. enterica cells form long filaments under sub-optimal aw as a result of the inhibition of cell division proteins (Mattick et al., 2000).  It was hypothesized that the septation and cell division is an energy-expensive process and resources could be better allocated towards survival instead of growth (Finn, Condell, et al., 2013).  Other responses involving the conservation of energy include mobility limitation through cessation of flagella formation genes (H. Li et al., 2012), generalized metabolic dormancy through viable but non-culturable state (Aviles et al., 2013; Deng et al., 2012; Gruzdev et al., 2011) and attenuated expression of other genes non-essential for survival (e.g. virulence-related genes) (Gruzdev et al., 2011).  1.1.5.3.6 Salmonella response to heat shock Compared to other stress responses, the physiological response to temperature upshift is perhaps the most studied and well known.  Heat shock occurs when temperatures are elevated to an extent at which growth ceases to occur (Wesche et al., 2009).  The cell membrane is the first organelle to be particularly affected; through the creation of pores, molecules such as lipopolysaccharides, lipids, phospholipids and periplasmic enzymes may be released (Wesche et al., 2009).  Additionally, protein and enzyme damage is particularly apparent following thermal stress.  Glycosylases and endonucleases, enzymes which play a role in DNA repair, are particularly sensitive to mild temperature upshift (Pellon & Sinskey, 1984).  The denaturation of ribosomes and ribosomal RNA has been observed in S. Typhimurium upon heat shock, with severe impairments in ribosomal assembly (Genthner & Martin, 1990).    The adaptive response largely involves production of proteins to mitigate damage of other 21  proteins caused by heat shock.  The best characterized cellular response of Salmonella is the production of heat shock proteins, thought to be induced through accumulation of damaged proteins (Wesche et al., 2009).   Heat shock proteins are synthesized in an effort to bind and stabilize other essential proteins, acting as “chaperones” to prevent denaturation (Sirsat et al., 2011) but some also possess catabolic activity to degrade irreparably damaged proteins (Wesche et al., 2009).   Following the heat treatment at 55°C, S. Typhimurium was found to have increased synthesis of various heat shock proteins, including IbpA, CpxP, FkpA and HtrA (Hsu-Ming et al., 2012).  Further, expression of another heat shock protein, dnaK, amongst others, was also induced in S. Typhimurium treated at 42°C (Sirsat et al., 2011).  It should be noted that the heat shock proteins induced in response to elevated temperature are distinct from those expressed through RpoS-dependent resistance induced during stationary phase (Lianou & Koutsoumanis, 2013).  1.1.5.3.7 Desiccation and heat resistance among serotypes of S. enterica Usage of different strains or serotypes of S. enterica can inevitably lead to variability across experiments, particularly when describing their desiccation and heat responses.  Furthermore, uncommon serotypes of S. enterica have been implicated in various different low-aw foods in North America (CDC, 2015a), suggesting discrepancies between the potential of Salmonella to cause low-aw-related foodborne illnesses amongst serotypes.    Compared to other foodborne pathogens, (e.g. E. coli, Listeria monocytogenes and Staphylococcus aureus), relatively little is known regarding the serotype-specific behaviours of S. enterica (Lianou & Koutsoumanis, 2013), thereby opening up an emerging area of interest. 22  However, some research has documented variability within S. enterica.  Following air-drying at 11% relative humidity, it was observed that S. Tennessee was substantially more resistant to desiccation than S. Typhimurium.  These observations were subsequently confirmed with microarray and qPCR, where S. Tennessee exhibited significantly higher levels in expression of desiccation-tolerant genes than S. Typhimurium (H. Li et al., 2012).   S. Senftenberg has also been noted to be significantly more heat resistant in milk than other Salmonella serotypes (e.g. Anatum, Cubana, Binza, Newbrunswick, Meleagridis and Tennessee) (Read et al., 1968).   Although the exact molecular basis behind such phenomena is debated, it is hypothesized that specific mutations in genes, such as rpoS, can give rise to distinct stress response profiles within serotypes or strains of S. enterica (Humphrey, 2004; Jorgensen et al., 2000).  Additionally, attenuated expression of rpoS-dependent genes could cause such variation between strains (Jorgensen et al., 2000).   1.1.5.3.8 Cross-protection An interesting phenotype associated with low-aw food processing is the resistance of Salmonella to pasteurization following desiccation procedures.  This phenomenon, known as cross-protection or cross-resistance, can also be applied to combinations of other stressors, including bile salts, UV radiation and disinfecting agents (Gruzdev et al., 2011).  Further, habituation at lower heat temperatures can also result in an increased resistance at higher heat (Bunning et al., 1990; Mackey & Derrick, 1987); therefore industrial pasteurization equipment heat come-up times must be abrupt; exposing cells to a prolonged temperature gradient could result in sub-lethal injury and possibly induce cross-protection.  23   Peanuts are desiccated to prevent aflatoxin contamination, rendering them suitable for storage (Woodroof, 1983) directly following harvest.   Chia seeds also undergo a similar series of events; seeds are dried for moisture evaporation after the germination soak, then heated between 49 to 60°C (CDC, 2014c).  Should Salmonella survive this initial desiccation process, they may gain resistance to further thermal processing steps, ultimately promoting dissemination and persistence in the production environment.   Ma et al. previously demonstrated the thermal resistance of S. enterica in peanut butter (aw 0.45) heated to temperatures of 71, 77, 83 and 90°C (Ma et al., 2009).  Other authors have also demonstrated cross-protection in different S. enterica serotypes (Aviles et al., 2013; Gruzdev et al., 2011; Leyer & Johnson, 1993; Podolak et al., 2010). This phenotype may also explain why Salmonella possesses a lower infectious dose in contaminated low-moisture food products, since resistance to gastric acid and bile salts may occur following habituation to low aw (Aviles et al., 2013).  Normally, the infectious dose for S. enterica to cause disease is 104 CFU/g (Aviles et al., 2013), however 10-100 cells were reported to cause disease in chocolate contaminated with S. Typhimurium (Kapperud et al., 1990).  Additionally, Aviles et al. found increased resistance of S. Tennessee through a simulated gastrointestinal tract following pre-adaptation to peanut butter.  In this study, S. Tennessee was also found to grow by two logarithms in concentration (Aviles et al., 2013), emphasizing its highly adaptable nature. Given that peanut butter has a high fat content, it is also believed that in addition to low-aw, a high fat percentage may confer some degree of protection to Salmonella upon encountering gastric and intestinal stresses (Aviles et al., 2013; Shachar & Yaron, 2006).   The specific molecular basis underlying cross-protection remains poorly understood, although it 24  is acknowledged that several genes may have interconnected roles in protection against diverse stresses.  For instance, OmpC and OmpF, outer membrane proteins involved in desiccation resistance, have also been found to be expressed under acidic conditions in both S. Typhimurium and E. coli (Foster & Hall, 1990; Heyde & Portalier, 1987)  Additionally, alternate sigma factor RpoS (σS), in particular, is activated upon encountering an environmental stress.  Since rpoS is involved in the transcription of several genes for general stress tolerance, it is acknowledged that genes responsible for tolerance of different stresses can subsequently be activated by this system (Lianou & Koutsoumanis, 2013), affording protection for a variety of stresses.   Interestingly, it is hypothesized that mutations in rpoS could account for the diversity of stress tolerance between serotypes and strains of S. enterica (Jorgensen et al., 2000).  It was observed that susceptibility to stress was correlated with mutations in rpoS, potentially resulting in different degrees of transcription in RpoS-dependent genes directly related to stress resistance (Jorgensen et al., 2000).  1.1.5.3.9 Equipment Poorly maintained and designed machinery within low-aw processing facilities pose a significant risk for end product cross-contamination.  For instance, cracks or gouges in equipment can potentially harbor dangerous microbial pathogens because these crevices are difficult to properly sanitize.  This may lead to end-product contamination through pathogen accumulation at these sites (Hobbs & Roberts, 1993).  In a 2014 outbreak of S. Braenderup in peanut butter and almond butter, the FDA discovered that the shovels used for transfer of roasted almonds contained large gouges, which could allow for harbourage of Salmonella.  Secondly, facility floors were poorly designed, containing obvious cracks and crevices, that were difficult to clean and disinfect.  25  Lastly, plastic buckets used for storage contained huge gouges; in some instances, large pieces of plastic were missing from the interior (CDC, 2014a).  Mullane et al. monitored for persistence of Cronobacter spp. (a bacterium with a peculiar resistance to desiccation) in a powdered infant formula processing facility over the course of one year.  Results indicated that 2.5% of intermediate and final end products tested positive for Cronobacter and 31% of sites tested in the facility were positive for this pathogen.  Upon further PFGE subtyping, it was identified that 70% were clonal, indicating the presence of a single persistent isolate in the processing environment (Mullane et al., 2007).  1.1.5.3.10 Improper zoning Facilities specialized for low-aw processing must adhere to specific regulations and guidelines for low-aw food production.   Bacterial contamination may be significantly increased when moisture is introduced into a dry environment; vegetative or metabolically dormant cells will be presented with the opportunity to grow and proliferate upon introduction of moisture (Beuchat et al., 2013), resulting in increased risk for product contamination.   Additionally, filamentous Salmonella (characterized by the absence of a septum) can successfully dissociate and resume septation with the introduction of water (Mattick et al., 2000).  This can be problematic for the food industry because it could account for an underestimation in microbial counts during end product testing.  Further, it should be noted that large increases in biomass would take place, without a correlating increase in microbial counts (Mattick et al., 2000).  26  It is also important to note is that moisture may take many forms, which may or may not be particularly apparent.  These include water droplets from leaking pipes, condensate formation or high humidity in the air (Finn, Condell, et al., 2013).  Interestingly, Salmonella can not only grow in water droplets, but also proliferate on surfaces after which standing water has dried (Beuchat et al., 2013).  Since bacterial growth can only occur when sufficient water levels are present, it is imperative that low-aw facilities adopt a dry cleaning regime to minimize the use of water during routine sanitation. Such regimes commonly consist of mechanical removal of soil or residue, followed by the use of high-pressure air and/or alcohol-based compounds, which evaporate very rapidly after application.  Furthermore, wet cleaning should only be performed under controlled conditions (Finn, Condell, et al., 2013).  1.1.5.3.11 Personnel Personnel may constitute a large risk for contamination of peanuts post-harvest.  Established processing operations tend to employ large numbers of personnel, so risk for transmission and accumulation of contaminating microorganisms is likely to increase.  Additionally, personnel may acquire pathogens in the agricultural environment, leading to tracking of contamination onto the raw peanuts and/or the processing facility itself.    A 2006 study in Finland examined the tools, hands, gloves, work clothes and shoes of employees from four food production sites for total aerobic bacteria (TAB), Enterobacteriaceae and Listeria monocytogenes.  They reported high prevalence of TAB, particularly on the personnel compared to the tools used (Aarnisalo et al., 2006). These results illustrate the need for established uniform cleaning and hand washing protocols.  L. monocytogenes, a potentially fatal pathogen frequently 27  associated with ready-to-eat foods, has also been isolated from the hands or gloves of food handlers (Autio et al., 1999; Destro et al., 1996).  Wherever possible, movements of personnel and materials should be restricted, particularly between raw material and end product areas (Chen et al., 2009) to minimize risk of contamination; microbes can be spread around a processing plant through footwear and equipment wheels (Morita et al., 2006).  By convention, the “riskier”, or more microbiologically hazardous the raw material is, the greater the need for a larger physical separation from the finished product (Chen et al., 2009).  By design, food production facilities may have a “transition” area where personnel can change uniforms, shoes, gloves, etc. prior to entering other areas (e.g. finished product storage) (Chen et al., 2009).  Trained and educated personnel are vital for minimizing pathogen risks during processing operations.   A comprehensive knowledge of post-processing Good Manufacturing Practices (GMPs) is also critical in limiting post-processing contamination (Frelka & Harris, 2014).  1.1.5.3.12 Control and detection of Salmonella in food production To effectively control Salmonella in a food production facility, particularly in a facility specialized in the production of low-aw foods, control and verification measures are of utmost importance.   Control of Salmonella in low-aw foods represents a great challenge, due to its natural heat resistance and possible amplification of resistance because of tandem desiccation and heat treatments (see section 1.1.5.3.8: Cross-protection).  This problem has been further exacerbated due to debates regarding the appropriate level of control (Frelka & Harris, 2014).  28  The FDA has proposed that a 5-log reduction of Salmonella to be sufficient, however, these guidelines are not mandatory and it is unknown whether food processors strictly adhere to these recommendations (FDA, 2009a).  Besides the measures of control discussed in the previous sections (e.g. pasteurization, moisture control and appropriate segregation of classified risk areas), appropriate verification measures must be used to confirm the performance of the implemented controls.  According to Beuchat et al., verification refers to “activities that aim at obtaining evidence that control measures have been correctly implemented and that the resulting product meets predefined safety criteria” (Beuchat et al., 2013).   Examples of effective control measures include use of control charts, monitoring of non-conformances, frequent equipment calibration and internal and external audits for both the plant and suppliers (Beuchat et al., 2013).  While end-product verification is important in ensuring consumer safety, it should not be the sole verification measure.  Pathogens in low-aw foods can be sporadically distributed within the food matrix (Jongenburger et al., 2011), which can be problematic during microbiological analysis as only selected analytes of the matrix are routinely tested.  Thus, unless the product is heavily contaminated it is probable that false negatives would be reported.  Environmental monitoring is a critical surveillance tool that helps to validate implemented control measures and determine if they are effective.  If well-designed, it will allow processors to determine potential sources of Salmonella contamination before it becomes an issue in the finished products (Beuchat et al., 2013).  An environmental sampling plan can consist of routine swabbing of various areas in the processing facility, such as food contact surfaces, equipment 29  and drains.  With regular collection and review of facility data, problems can be rectified as quickly and efficiently as possible.  If any non-conformances in routine swabbing arises, corrective actions can be put into place, which may include the alteration of Hazard Analysis and Critical Control Points (HACCP) and GMP procedures, changes to sanitation regimes, and potential modifications to zoning or equipment (Finn, Condell, et al., 2013).  Further, if a pathogen is isolated in multiple sites in a production facility, further molecular subtyping, such as pulsed field gel electrophoresis, may be undertaken to determine the clonality and relatedness (Beuchat et al., 2013).  1.1.5.3.13 Analysis of Salmonella in low-aw foods in Canada In Canada, MFHPB-20 is enforced to detect Salmonella in low-aw foods (Health Canada, 2009), and is summarized in the following.  Following a non-selective enrichment step, a series of procedures selective for Salmonella takes place, involving an initial enrichment step in Tetrathionate Brilliant Green (TBG) broth.   The bile salts in TBG broth are inhibitory to lactose-fermenting Enterobacteriaceae, while brilliant green inhibits Gram-positive bacteria (MacFaddin, 1985).  Selective plating is then carried out using two of three selected agars for selective isolation of Salmonella species:  Bismuth Sulfite (BS) agar, Brilliant Green Sulfa (BGS) agar or Brilliance™ Salmonella agar.  Other agars (e.g. MacConkey agar) may also be used for isolation, but only in conjunction with the aforementioned three.  On BGS agar, Typical colonies of Salmonella appear pink to fuschia; on BS agar: black, and on Brilliance™ Salmonella agar: purple.  It should be noted that on BGS and BS agar, atypical or uncommon strains (e.g. lactose-and/or sucrose fermenters) may exhibit different colours than typical strains.  On BS agar, S. Enteritidis may appear green or brown and possesses stricter modes of 30  preparation than the BFS or Brilliance™ Salmonella agars.  At this stage, if Salmonella cannot be isolated, the analytical sample is considered to be free of Salmonellae.  If the presence of Salmonella is suspected, serological testing will be used to identify the serogroup (Health Canada, 2009).                  31  1.2 Research purpose, origins and maintenance The purpose of this study was to analyze and characterize the survival mechanisms of S. enterica strains in response to desiccation and heat stresses.  This project comprises three objectives: (i) to examine the survival of S. enterica strains in peanut oil, peanuts and chia seeds; (ii) to elucidate a cross-protective mechanism following sub-lethal desiccation and/or heat stress; and (iii) to quantify relative gene expression of the desiccation-treated or heat-treated S. enterica strains.  To accomplish these objectives, a panel of five S. enterica strains, each representing a different serotype, was used (table 1.2).  Table 1.2 Origins and strain identification of S. enterica serotypes used for this study. S. enterica serotype Origin Strain identification Hartford Peanut R8-5223 Tennessee Peanut R8-5221 Enteritidis Human S5-523 Thompson Human S5-483 Typhimurium Human S5-536  Strains were frozen in Brain-Heart-Infusion (BHI) broth (Becton, Dickinson and Co., East Rutherford, New Jersey, USA) supplemented with 20% glycerol at -80°C.  Working stocks were maintained on Luria-Bertani (LB) agar (Amresco, Solon, OH, USA) at 4°C for a maximum of four weeks.   32  Chapter 2: Survival of Salmonella in peanut oil, peanuts and chia seeds  2.1 Introduction The ability for Salmonella to survive in a food product is a vital attribute for this pathogen to cause subsequent diseases in humans. Concern about the ability of Salmonella to survive in food commodities is exacerbated given that some low-aw foods (e.g., chocolate and peanut butter) do not require a pathogen elimination step (e.g. heat treatment) before consumption (Finn, Condell, et al., 2013).  Previous studies have focused on the survival of Salmonella in dry matrices including almonds (Uesugi et al., 2006), walnuts (Blessington et al., 2013), cocoa beans (do Nascimento et al., 2013) and peanut butter (Keller et al., 2012). In the past, numerous outbreaks of Salmonella have been linked to peanut butter (CDC, 2015a), therefore peanuts and peanut-derived products may be of particular concern.  Additionally, the unprecedented 2014 outbreak of Salmonella in chia seed powder highlighted the need for study of this emerging food vehicle (CDC, 2014b).   The first research objective was to characterize the behavior and survival of five strains of S. enterica in three low-aw food matrices: peanut oil, peanuts and chia seeds. We hypothesized that S. enterica is able to survive for extended periods of time in peanut oil, peanuts and chia seeds.  Moreover, the S. enterica strains examined in the present study will exhibit differences between survival capabilities within these low-aw foods. 2.2 Materials and methods 2.2.1 Analysis of food matrices The food matrices used in the survival assays were purchased from local supermarkets. Peanut oil, chia seeds and peanuts (in-shell, unsalted and unflavoured) were chosen for use in this study 33  due to their diverse water activities.  Additionally, chia seeds were involved in a recent chia seed powder outbreak (CDC, 2014b).  The water activities of peanut oil, chia seeds and peanuts were measured at ambient temperature in triplicate using a water activity meter (Decagon Devices, Pullman, WA, USA).    To test for microbiological sterility, 100 ul of peanut oil was spread onto sterile LB agar (Amresco, Solon, OH, USA) plates in duplicate and incubated at 37°C for 24 ± 2 hours (Thermo Fisher Scientific, Waltham, MA).  Chia seeds and peanuts were subjected to a 1:10 dilution in phosphate buffered saline (PBS) (Amresco, Solon, OH, USA), after which 100 ul was spread onto LB agar for enumeration.  Plates were incubated at 37°C for 24 ± 2 hours (Thermo Fisher Scientific, Waltham, MA).    2.2.2 Inoculum preparation and recovery of Salmonella 2.2.2.1 Preparation of desiccated cells One colony of each S. enterica strain (three replicates per strain) was used to inoculate 10 ml of BHI broth (Becton, Dickinson and Co.) and incubated at 37°C and 170 rpm for 18 hours.  Subsequently, 30 ul from each culture was transferred into three ml of fresh BHI broth and incubated (37°C; 170 rpm) for an additional 1.5 hours. Broth cultures were periodically assessed for their optical densities (ODs) at 600 nm with a spectrophotometer (Shimadzu Corp., Kyoto, Japan), until a target OD600 of 0.400 ± 0.020 (mid-log phase) was attained (~108 CFU/ml as determined from previous pilot studies), and adjustments were made when necessary using sterile BHI broth.  34  2.2.2.2 Peanut oil inoculation and recovery of Salmonella A 1 ml aliquot of the overnight cultures was diluted in 9 ml of PBS. Subsequently, 100 ul of diluted culture was transferred to a 30 ml conical tube (VWR, Radnor, Pennsylvania, USA) and air-dried for 0.5 hours in a type A2 biological safety cabinet (Esco, Portland, OR, USA).   The air-dried pellet was then suspended in 9.90 ml of peanut oil (~105 CFU/ml). Samples were subsequently stored at 20°C in an incubator (Thermo Fisher, Waltham, MA, USA) for a maximum of 105 days. To obtain initial cell counts, suspensions were serially diluted with PBS, immediately spread onto LB agar in duplicate, and colonies were counted after incubation at 37°C for 24 ± 2 hours. Cell densities were assessed at day 0, 2, 4, 6, 8, 10, 12, 14, 16, 19, 22, 25, 28, 38, 48, 58, 68, 78, 90 and 105. At each sampling time, peanut oil suspensions were serially diluted in PBS. Subsequently, 50 ul of the diluted samples was spread onto LB agar in duplicate. Plates were incubated at 37°C for 24 ± 2 hours.  2.2.2.3 Chia seed inoculation and recovery of Salmonella Ten g aliquots of chia seeds were placed in sterile Whirl-Pak® bags (Nasco, Fort Atkinson, Wisconsin, USA).  OD600-adjusted inoculum was diluted 10:1 in PBS and 100 ul of the bacterial culture was inoculated onto the surface of the seeds to reach a final concentration of ~105 CFU/g. Samples were then hand-massaged for one minute to ensure even distribution and break up aggregates of seeds. The bags were left open in the biological safety cabinet and air-dried for 0.5 hours, followed by storage at 20°C for a maximum of 105 days. To obtain initial counts at time 0, suspensions were serially diluted in PBS, immediately spread onto LB agar in duplicate, and colonies were counted after incubation at 37°C for 24 ± 2 hours.  Cell populations were assessed at specific sampling times: 0, 2, 4, 6, 8, 10, 12, 14, 16, 19, 22, 25, 28, 38, 48, 58, 68, 78, 90, 105, 35  120, 135 and 150 days. At specified sampling times (above), sampling bags were opened and the samples were diluted 10:1 in PBS and subjected to vigorous mechanical shaking for one minute.  Subsequently, 100 ul was spread onto LB agar and Xylose Lysine Deoxycholate (XLD) agar (Difco, East Rutherford, New Jersey, USA) in duplicate. Plates were incubated at 37°C for 24 ± 2 hours.  2.2.2.4 Peanut inoculation and recovery of Salmonella Initially, 10 g aliquots of Runner peanuts were separated into sterile sampling bags.  OD600-adjusted inoculum (~108 CFU/ml) was diluted 10:1 in PBS and 100 ul was inoculated onto the surface of the nuts (~105 CFU/g). Sampling bags were then left open in the biological safety cabinet (Esco) and air-dried for 0.5 hours, at which point the surface of the nut was dry. Samples were stored at 20°C until no further survivors were detected.  To obtain initial counts, suspensions were serially diluted in PBS and spread onto LB agar in duplicate.  Colonies were counted after incubation at 37°C for 24 ± 2 hours.  Cell populations were assessed at specific sampling times: 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 24, 48, 72 and 96 hours. At specified sampling times (above), peanuts were diluted 10:1 in the sampling bags in PBS and pummeled in a Stomacher® (Seward, Worthing, West Sussex, UK) at 230 rpm for two minutes. Afterwards, 100 ul was spread onto LB agar and XLD agar in duplicate. Plates were incubated at 37°C for 24 ± 2 hours.  2.2.2.4.1 Enrichment and PCR detection of Salmonella inoculated on peanuts To test for the presence of Salmonella after 70 days of storage, inoculated peanuts were enriched 10:1 in BHI broth and incubated at 37°C for 24 ± 2 hours.  Following incubation, samples were pummeled in a Stomacher® at 230 rpm for two minutes.  A loopful of culture was subsequently 36  streaked onto XLD agar to obtain isolated colonies, followed by incubation at 37°C for 24 ± 2 hours.  Presumptive Salmonella colonies exhibiting characteristic black centres were subjected to colony PCR for confirmation. Suspect colonies were picked off the surface of the XLD agar and suspended in 200 ul of sterile water in a microcentrifuge tube (Eppendorf, Missisauga, ON, CA).  The tubes were placed into a microwave (Panasonic, Osaka, Japan) and heated for two minutes on high for crude lysis. Peanuts stored for 70 days that were not inoculated with S. enterica were used as the negative control. Since the negative control did not yield colonies on XLD agar, 1 ul of BHI enrichment broth following 24 hours of incubation was used as the template in the PCR set-up. For the positive control, an isolated colony from a stock culture of S. Enteritidis previously grown on LB agar was suspended in 200 ul of sterile water and lysed in a microwave as described above.  Overall, 1 ul of the cell lysates were used to detect for the invA gene (for primer sequence, see table 4.2).   PCR was performed in a C1000 Touch™ thermal cycler (Bio-Rad Laboratories, Hercules, CA, USA).  PCR cycling conditions were as follows: initial denaturation (three minutes; 94°C), three-step cycling: denaturation (30 seconds, 94°C), annealing (30 seconds; 55°C) and extension (1 minute; 72°C), followed by a final extension (ten minutes, 72°C).  The sizes of the PCR products were confirmed using electrophoresis (Bio-Rad Laboratories, Hercules, CA, USA) in 1x Tris-Acetate with EDTA (TAE) buffer (Invitrogen, Waltham, MA, USA) on 2% agarose (Amresco, Solon, OH, USA) at 90 volts.  A 100-base pair (bp) DNA ladder (Invitrogen, Waltham, MA, USA) was used for standardization.  PCR products were visualized with the ChemiDoc™ MP System (Bio-Rad Laboratories, Hercules, CA, USA).  2.3 Data analysis Three parameters were used to assess survival of the S. enterica strains: (i) survival period 37  (Tmax); (ii) the maximum achieved concentration (Nmax); and (iii) the area under the curve (AUC). For each S. enterica strain and food matrix tested, the AUC was calculated according to the Trapezoidal Rule (Haggerty, 1999):    AUC = (t2 - t1) ƒ(t1) + ƒ(t2) 2                   (2.1)  where t is equal to the amount of time survived (hours or days). The differences between serotype survival in each food matrix were analyzed by a one-way analysis of variance (ANOVA).  To compare all possible pairs of means, Tukey’s Honest Significant Difference (HSD) was used.  A P value of <0.05 was considered statistically significant.  Statistical analyses were performed using JMP version 11.1.1 (SAS Institute, Inc., Cary, NC, USA).  2.4 Results and discussion 2.4.1 Analysis of food matrices 2.4.1.1 Sterility of food matrices No colonies were recovered from peanut oil and peanuts on LB agar (table 2.1). Both replicates of chia seeds showed colonies on LB agar, indicating the presence of native microorganisms on chia seeds. XLD agar, selective for Salmonella, was also used in the analysis of chia seeds. The 38  recovered colonies were atypical for Salmonella as they did not exhibit black-centered colonies characteristic of H2S production.   Table 2.1 Presence (+) /absence (-) testing for native microflora on consumer-grade foods used in the survival assays.   Replicate Peanut oil Chia seeds Peanuts 1 - + - 2 - + -   2.4.1.2 Determination of water activity Water activity measurements were taken in triplicate.  Results are presented as mean ± standard deviation (SD) (table 2.2).     Table 2.2 The water activities of food matrices used in this study. Food matrix Water Activity (Mean ± SD) Peanut oil 0.521 ± 0.003 Chia seeds 0.585 ± 0.003 In-shell peanuts 0.321 ± 0.200   39  2.4.2 Survival of Salmonella in peanut oil 2.4.2.1 Tmax of Salmonella in peanut oil Of the five strains examined, serotypes Hartford and Thompson demonstrated the highest Tmax of 105 days in peanut oil (figure 2.1).  S. Enteritidis, S. Tennessee and S. Typhimurium had a Tmax of 90 days in peanut oil.  All serotypes of S. enterica displayed long-term resistance to the desiccation conditions encountered in peanut oil (aw 0.521 ± 0.003), suggesting peanut oil could potentially harbor these pathogens for long periods of time.  While no long-term survival studies  in peanut oil have been reported, survival of S. enterica in other low-aw foods has been described in literature.  For example, this pathogen was capable of surviving for eight weeks in skim milk powder (Licari & Potter, 1970).  2.4.2.2 Nmax of Salmonella in peanut oil S. Enteritidis and S. Tennessee demonstrated similar high Nmax values (7.09 and 7.31 log CFU/ml, respectively) in peanut oil until day 60, after which cell densities began to notably decrease (figure 2.1).  S. Typhimurium, S. Hartford and S. Thompson all displayed an Nmax of ~6 log CFU/ml. However, S. Typhimurium displayed a period of stability at this Nmax compared to S. Hartford and S. Thompson, which demonstrated periods of fluctuation throughout the sampling period.  Growth of the S. enterica strains in peanut oil was not expected due to the previously-defined aw requirement of >0.94 for growth (Bell & Kyriakides, 2009).  Nevertheless, Deng et al. (2012) observed a similar growth pattern with S. Enteritidis in peanut oil, where increases in cell density were detected after 216 hours.  Further, it is thought that fluctuations in cell concentrations are exacerbated by a phenomenon known as growth advantage in stationary phase (GASP) (Finkel & Kolter, 1999; Lewis, 2007; Martinez-Garcia et al., 2003).  This takes 40  place when genetic mutants more adaptable to the microenvironment will continue to re-emerge and replace less adapted cells, causing these fluctuations to occur.  However, further studies should be conducted to fully understand the relationship between this phenotype the diversity of S. enterica strains under desiccation stress.  2.4.2.3 AUC of Salmonella in peanut oil The AUCs calculated from the survival assay in peanut oil indicate the various survival capabilities of the S. enterica strains.  S. Enteritidis and S. Tennessee significantly (p<0.05) demonstrated the highest AUCs (table 2.3) compared to the other evaluated strains.  S. Hartford and S. Thompson displayed lower AUCs and S. Typhimurium demonstrated the lowest AUC value (table 2.3).  S. Enteritidis and S. Tennessee appear better adapted to survival in peanut oil than S. Typhimurium.  However, although S. Hartford and S. Thompson did not demonstrate the highest AUCs, they should also be regarded as particularly resistant to the conditions in peanut oil. 41    Figure 2.1 Survival of S. enterica in peanut oil.  Survivors were enumerated on LB agar. Error bars indicate the standard errors of the means. 0.001.002.003.004.005.006.007.008.000 20 40 60 80 100Bacterial population (log CFU/mL) Day TennesseeHartfordThompsonEnteritidisTyphimurium42   Table 2.3 AUC for S. enterica in peanut oil.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD).   2.4.3 Survival of Salmonella in chia seeds Following the multi-strain outbreak of S. Newport, S. Oranienburg, S. Saintpaul and S. Hartford in chia seed powder in 2014 (CDC, 2014b), which affected 63 individuals across multiple Canadian provinces (British Columbia, Ontario and Quebec), we felt it pertinent to examine survival of our strains in this matrix (aw 0.585 ± 0.003).  To our knowledge, this is the first survival study in this particular food matrix.  2.4.3.1 Tmax of Salmonella in chia seeds S. Hartford was most resistant to the stress conditions encountered in the chia seed matrix (Tmax = 150 days) (figure 2.2).  This was followed by S. Tennessee (135 days), S. Enteritidis and S. Thompson (68 days) and lastly, S. Typhimurium (48 days) – highlighting the diversity of strain-Serotype AUC(𝑑𝑎𝑦𝑠 𝑙𝑜𝑔𝐶𝐹𝑈𝑚𝑙) (Mean ± SD) Enteritidis 496.53 ± 0.97 A Tennessee 493.63 ± 0.73 A Hartford 415.76 ± 0.72 A Thompson 380.15 ± 0.83 B Typhimurium 267.97 ± 0.97 C 43  specific responses to stresses in chia seeds.   Additionally, survivors recovered on XLD agar (figure 3) demonstrated a notable reduction in Tmax values compared to cells recovered on LB agar.  Recovery on selective agars represents a challenge in the food industry; injured cells may not be recoverable on selective agars because of the presence of selective agents, potentially leading to an underestimation in viable cell counts.   S. Hartford, persisting for the longest period of time (150 days) in the present study (figure 2.3), was also one of the serotypes implicated in the 2014 Canadian chia seed powder outbreak (CDC, 2014b).   The desiccation resistance of this serotype has not been extensively studied, and the current findings have highlighted the potential risk of this particular strain to food industry.  The second-most persistent strain, S. Tennessee, has also been reported in literature to be capable of surviving long-term desiccation stress.  Farakos et al. (2014) observed its unique capability for persistence for six months in whey protein powder (aw 0.54), compared to weaker survivors S. Agona, S. Montevideo and S. Typhimurium.  Other serotypes (S. Enteritidis, S. Thompson and S. Typhimurium) were also able to survive for over one month in chia seeds, necessitating the importance of controlling these pathogens in the food industry.  Moreover, as chia seeds are particularly shelf-stable, long periods of persistence emphasize the degree of risks associated with consumption of the contaminated product.    2.4.3.2 Nmax of Salmonella in chia seeds In addition to possessing the highest Tmax (150 days) in chia seeds, S. Hartford also had the highest Nmax value (4.17 log CFU/g) and was able to maintain a cell density of ~log 3.5 CFU/g for 80 days (figure 2.2).  The other serotypes (Tennessee, Thompson, Enteritidis and 44  Typhimurium) demonstrated a lower Nmax of ~log 3.5 CFU/g.  Notably, S. Thompson, S. Enteritidis and S. Typhimurium were not able to maintain >log 3.5 CFU/g for extended periods of time, suggesting that these strains are less adapted to survival in chia seeds compared to S. Hartford.  Moreover, the ability to persist at higher concentrations may exacerbate the risks associated with consumption of contaminated chia seeds, although high concentrations are not necessarily needed to cause disease in low-aw foods (Aviles et al., 2013).  The Nmax value of the same strain was much lower when recovered on XLD agar compared to that recovered on LB agar (figure 2.3), indicating that sub-lethally injured (i.e. causing minor cellular damage) cells are difficult to recover using selective agars.  For example, S. Hartford had an Nmax of 3.52 log CFU/g when using XLD agar for recovery, a 0.6 log CFU/g decline in Nmax compared to recovery on LB agar.    2.4.3.3 AUC of Salmonella in chia seeds Compared to serotypes Enteritidis, Tennessee, Thompson and Typhimurium, S. Hartford exhibited the highest AUCs on chia seeds using LB or XLD agar for recovery.  These values were significantly higher (p<0.05) than those of the other strains.  S. Tennessee exhibited the second highest AUC using LB agar for recovery, followed by S. Thompson, S. Enteritidis and S. Typhimurium (table 2.4).  These AUC values were proportionally reduced when XLD agar was used for recovery (table 2.5), possibly due to the presence of injured cells.  It is evident that S. Hartford is particularly well-adapted to the chia seed environment, which may provide an explanation for its persistence in the chia seed powder outbreak (CDC, 2014c).  S. Tennessee also exhibited a particularly strong resistance, consistent with its phenotype in peanut oil.  S. Tennessee is also known to be capable of surviving long-term desiccation stress.  Farakos et al. 45  (2014) observed persistence for 6 months in whey protein powder (aw 0.54), considerably longer than weaker survivors S. Agona, S. Montevideo and S. Typhimurium.  S. Enteritidis and S. Thompson were also persistent, but were not as resistant as S. Tennessee or S. Hartford.  S. Typhimurium was identified as the least resistant serotype, also consistent with its weak response in peanut oil.  S. Typhimurium was the least resistant serotype after inoculation into whey protein powder (aw 0.54) (Farakos et al.) and also survived at lower concentrations at 11% relative humidity on a paper disk, compared to S. Tennessee (H. Li et al., 2012).46   Figure 2.2 Survival of S. enterica on chia seeds stored at 20°C.  Bacterial cells were recovered on LB agar.  Error bars indicate the standard errors of the means. 0.001.002.003.004.005.000 20 40 60 80 100 120 140 160Bacterial population (log CFU/g) Storage time (day) EnteritidisTennesseeHartfordThompsonTyphimurium47    Figure 2.3 Survival of S. enterica on chia seeds stored at 20°C.  Bacterial cells were recovered on XLD agar.  Error bars indicate the standard errors of the means. 0.001.002.003.004.005.000 10 20 30 40 50 60 70Bacterial population (log CFU/g)  Storage time (day) EnteritidisTennesseeHartfordThompsonTyphimurium48  Table 2.4 AUC for S. enterica on chia seeds.  Survivors were recovered on LB agar.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD). Serotype AUC(𝑑𝑎𝑦𝑠 𝑙𝑜𝑔𝐶𝐹𝑈𝑚𝑙) (Mean ± SD) Enteritidis 142.70 ± 0.82 C Tennessee 284.68 ± 0.94 B Hartford 410.03 ± 0.60 A Thompson 164.75 ± 0.40 C Typhimurium 62.02 ± 1.05 D   Table 2.5 AUC for S. enterica on chia seeds.  Survivors were recovered on XLD agar.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD). Serotype AUC(𝑑𝑎𝑦𝑠 𝑙𝑜𝑔𝐶𝐹𝑈𝑚𝑙) (Mean ± SD) Enteritidis 19.18 ± 1.11 B Tennessee 22.01 ± 1.35 B Hartford 76.77 ± 1.02 A Thompson 25.63 ± 0.69 B Typhimurium 17.09 ± 1.38 BC   49  2.4.4 Survival of Salmonella on peanuts 2.4.4.1 Tmax of Salmonella on peanuts The strains of S. enterica inoculated onto peanuts exhibited a diversity of Tmax values.  S. Hartford and S. Thompson, in particular, exhibited very high Tmax values of 96 hours (figure 2.5), while, S. Tennessee, S. Typhimurium and S. Enteritidis exhibited lower Tmax values of 10, 4.5 and 4 hours, respectively (figure 2.4).  Overall, the Tmax of the S. enterica strains were much lower in peanuts (figure 2.6) compared to the Tmax in peanut oil or chia seeds.  This observation suggests that these strains are the least adapted for survival in very dry environments; whole peanuts had the lowest aw among the three food matrices used in the current study (aw 0.321 ± 0.200).  Blessington et al. (2013) artificially inoculated S. Enteritidis onto the surface of in-shell walnuts (aw 0.42) and observed enhanced periods of survivability (>1 year), however larger concentrations (8 log CFU/g) of bacterium were used in that study, which may have contributed to the prolonged survival time.  Additionally, Brar et al. (2015) inoculated S. enterica onto peanut kernels and observed long-term persistence (>1 year), which is not in agreement with our results.  However, the present study focuses on shell inoculation, which is likely to have a limited nutrient composition compared to kernels.  For instance, the kernel is likely to have a higher lipid content, which has been documented to provide significant protection to cells undergoing desiccation stress (Aviles et al., 2013; Shachar et al., 2006).  2.4.4.2 Nmax of Salmonella on peanuts S. Thompson achieved the highest Nmax (4.32 log CFU/g), after inoculation, however, this value is not particularly relevant because it was not able to maintain this cell density at two hours following inoculation (figure 2.5).  Rather, S. Thompson was able to maintain a cell density of 50  >3 log CFU/g for up to 48 days.  S. Hartford achieved similar, although slightly lower, cell densities for the duration of the sampling period.  S. Tennessee also demonstrated a short period of stability as the cell density did not rapidly decline (figure 2.4), however its relative persistence was short-lived as the survival was only 10 hours.  S. Enteritidis and S. Typhimurium both displayed almost linear decreases in cell density following inoculation.  As a whole, all S. enterica strains underwent large declines in cell density almost immediately following inoculation (figure 2.6), although the extent of the decline differed between strains.  Moreover, none of the strains showed an increase in cell density from the original inoculated concentration of ~log 5 CFU/g, as was seen in peanut oil, which indicate that the conditions encountered on the surface of peanuts are particularly adverse to survival.  However, high cell densities are not essential for causing disease in low-aw foods; as few as 10-100 cells of S. enterica were found in samples of chocolate responsible for one outbreak (Kapperud et al., 1990).  2.4.4.3 AUC of Salmonella on peanuts S. Hartford and S. Thompson both demonstrated similarly high AUC on peanuts, emphasizing the desiccation resistance of these strains (table 2.6).  S. Thompson was implicated in a peanut outbreak in the U.S. in 2006, which affected 100 people (Calhoun et al., 2013).  Moreover, S. Hartford was one of only 12 Salmonella serotypes recovered from Virginia and Runner type peanuts, which make up 98% of all peanut-based products in the U.S.  S. Hartford was recovered at the second highest concentration: 0.036 Most Probable Number/g.  Although this appears to be of little consequence, Kirk et al. (2004) previously reported prevalence of Salmonella in raw in-shell peanuts of 0.03 – 2 cells/g, following a peanut outbreak in Australia.   51  The AUCs obtained for S. Thompson and S. Hartford were significantly greater (p<0.05) compared to the AUC of S. Enteritidis, S. Tennessee and S. Typhimurium, indicating the weak resistance to desiccation on peanuts.  While S. Enteritidis and S. Tennessee have previously been shown to survive better in peanut oil compared to the other strains analyzed in the current study, it is apparent that they are not well-adapted to survival on the peanut, especially since peanuts are the lowest aw food matrix used in this study (aw 0.321 ± 0.020).  Moreover, the weak relative persistence of S. Typhimurium on peanuts is not surprising; this serotype has consistently been one of the least resistant to a range of food matrices.               52   Figure 2.4 Survival of S. enterica serotypes Tennessee, Typhimurium and Enteritidis on peanuts stored at 20°C.  Bacterial cells were recovered on LB agar.  Error bars indicate the standard errors of the means. 0.001.002.003.004.005.000 2 4 6 8 10Bacterial population (log CFU/g) Storage time (hours) TennesseeTyphimuriumEnteritidis53   Figure 2.5 Survival of S. enterica serotypes Hartford and Thompson on peanuts stored at 20°C.  Bacterial cells were recovered on LB agar.  Error bars indicate the standard errors of the means. 0.001.002.003.004.005.006.000 20 40 60 80 100Bacterial population (log CFU/g) Storage time (hours) HartfordThompson54    Figure 2.6 Survival of S. enterica on peanuts stored at 20°C.  Bacterial cells were recovered on LB agar.  Error bars indicate the standard errors of the means. 0.001.002.003.004.005.006.000 20 40 60 80 100Bacterial population (log CFU/g) Storage time (hours) TennesseeTyphimuriumEnteritidisHartfordThompson55   Table 2.6 AUC of S. enterica on peanuts.  Results are summarized by mean ± standard deviation for the bacterial strains tested in triplicate. Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD). Serotype AUC(ℎ𝑟𝑠 𝑙𝑜𝑔𝐶𝐹𝑈𝑚𝑙) (Mean ± SD) Enteritidis 6.97 ± 1.23 CD Tennessee 30.48 ± 0.70 B Hartford 226.95 ± 0.94 A Thompson 241.04 ± 0.80 A Typhimurium 11.37 ± 0.76 C   2.4.4.3.1 Recovery of Salmonella during prolonged storage of inoculated peanuts Following 70 days of desiccation on whole peanuts, serotypes Enteritidis, Tennessee, Hartford and Thompson were recovered on XLD agar and presumptive colonies were confirmed using primers targeting invA (figure 2.7).   The absence of recoverable S. Typhimurium on XLD agar after 70 days correlates with the previous findings in peanuts, peanut oil, chia seeds, where it was identified to be the least persistent serotype as determined from the AUC.  Poor survival of S. Typhimurium in low-aw foods is not widely documented in literature. Differences in survival could be due to the different molecular mechanisms of Salmonella strains in response to stress conditions.   56  Collectively, the results indicate that certain strains of S. enterica are indeed capable of long-term survival on peanuts, a food product characterized by severely low-aw, and also the precursor to many peanut-based products (e.g. peanut oil, peanut butter, etc.).  Although only recoverable following 24 ± 2 hours of enrichment in BHI broth, the presence of S. enterica indicates that some resistant cells are particularly well-adapted to the adverse conditions encountered and may still possess pathogenic potential.  Presence of these well-adapted cells, even at low cell densities, still pose a significant risk; a high cell density is not necessary to cause disease in humans, especially in low-aw foods (Aviles et al., 2013).  It has been reported that as few as 10-100 cells are capable of causing salmonellosis in low-aw foods, such as chocolate and peanut butter (Kapperud et al., 1990), possibly due to acid tolerance following desiccation.   It is therefore imperative that low-aw foods be monitored carefully to reduce survival of Salmonella.             57     Figure 2.7 S. enterica survivors after 70 days of desiccation on peanuts.  Peanuts were enriched in BHI broth and streaked on XLD agar to obtain isolated Salmonella colonies.  Presumptive colonies were tested for presence of the invA gene.  PCR amplicons were electrophoresed in 1x TAE buffer on 2% agarose. Bright bands indicate the presence of the invA gene.    DNA ladder  Blank  Negative control  Positive control  S. Enteritidis  S. Tennessee  S. Hartford  S. Thompson   58  2.5 Conclusions In the first objective, the survival of five S. enterica strains, representing different serotypes was determined in peanut oil, peanuts and chia seeds.  Interestingly, some strains exhibited unique characteristic behaviours, which demonstrated consistency across the matrices analyzed.  S. Tennessee was identified as particularly persistent due to its high AUCs, although these values sometimes varied between food matrices as demonstrated by a low AUC on peanuts compared to peanut oil and chia seeds. Similarly, S. Thompson had a high AUC in peanut oil and in-shell peanuts, but a low AUC in chia seeds, compared to other serotypes.   However, the strong resistance to desiccation in peanuts emphasizes the hardiness of this particular strain to very low-aw conditions. Differing observations between food matrices suggest a matrix-dependent response; when examining a specific parameter (in this case, low-aw) in food, other factors (e.g. fat and protein content) attributed to the nature of the food itself are difficult to control.  S. Hartford was notably resistant and had consistently high AUC across all food matrices, indicating the ability to readily adapt to a variety of different microenvironments.  Survival of S. Enteritidis and S. Typhimurium was largely dependent on the food matrix; high AUC were exhibited in peanut oil but comparatively low AUCs were documented on chia seeds and peanuts.  S. Typhimurium exhibited consistently lower AUC values compared to other strains across all matrices tested, and could not be recovered after 70 days on peanuts. Strain-specific differences observed in the survival assays could be due to differences in the expression of genes required for regulation of osmotic pressure.  Specifically, it has been documented that different mutations in rpoS, the general stress response regulator, could influence differences in gene regulatory networks responsible for desiccation response (Jongenburger et al., 2011).  This could 59  therefore give rise to the array of strain-specific behaviours observed in the survival studies.  Overall, the strains were able to survive in all food matrices for long periods of time.  Although recovery of S. enterica was severely reduced upon desiccation on in-shell peanuts, presence of survivors at day 70 indicates that the risk to consumers is still present. These results are of particular importance because peanut oil, peanuts and chia seeds are relatively shelf-stable and as such, could harbor contaminating Salmonella for extended periods of time.  Moreover, lipid-containing foods (e.g. peanut oil and chia seeds) may protect Salmonella and enhance its survivability (Aviles et al., 2013; Shachar & Yaron, 2006) by preserving the membrane integrity of bacterial cells.  Water droplets within lipid-dense foods, where nutrients are more readily available, could also promote perseverance (Torlak et al., 2013).    The ability for Salmonella to adapt to its microenvironment should not only be acknowledged, but be considered in assessments of risks in low-aw foods.  This is particularly important given that low-aw foods are often ready-to-eat and shelf-stable.  Additionally, it is important to design appropriate control strategies in the processing industry; a finished product low in moisture cannot be considered an effective hurdle strategy as previously assumed.      60  Chapter 3: Protective effects of desiccation and mild heat treatment on lethal heat treatment on Salmonella  3.1 Introduction In the processing of low-aw food products, many stresses are applied with the aim to eliminate pathogenic microorganisms and spoilage microorganisms.  These stresses, also known as “hurdles” may include: (i) the use of antimicrobial agents (e.g. spices, organic acids, and disinfectants); and (ii) the use of food processing technologies (e.g. freezing, dehydration and pasteurization).  Although these interventions are geared towards eliminating pathogenic microbes, the pathogens may continue to survive and persist through subsequent treatments, particularly if the initial intervention causes minor injury to the cell (known as sub-lethal injury).   Upon the introduction of a stressor, the bacterial cells can adapt their cellular machinery to facilitate their survival.  These networks play interconnected roles in cellular stress response, which may produce a phenomenon known as cross-protection or cross-resistance, where an initial sub-lethal injury incurred by a stress can enhance the resistance to a different stress incurred subsequently (Gruzdev et al., 2011).  This anomaly is of particular concern in the low-aw food industry, where commodities undergo a series of interventions in tandem to reduce the microbial load.  In particular, drying (desiccation) treatments often take place prior to pasteurization (heat) (Finn, Condell, et al., 2013; Woodroof, 1983).  The cross-protection mechanism is of major concern because it may facilitate the survival of bacterial pathogens during food processing, in the food product, and also upon consumption.  Previous studies have suggested that cross-protection accounts for the lower infectious dose of Salmonella in low-aw 61  food commodities, since they may be better able to survive gastric acids and bile salts prior to colonization of the small intestine (Aviles et al., 2013; Gruzdev et al., 2011; Stackhouse et al., 2012).  In this work, the cross-protective effects following (i) pre-adaptation to desiccation in peanut oil (aw 0.521 ± 0.003) for six days; (ii) pre-adaptation to a mild, sub-lethal heat shock of 45°C for three minutes; and (iii) pre-adaptation to both six days of desiccation in peanut oil and 45°C heat shock on the heat resistance of Salmonella at 70°C were evaluated.  3.2 Materials and methods 3.2.1 Preparation of desiccated Salmonella cultures A single colony of each of the five S. enterica strains (three replicates per strain) was inoculated into 10 ml BHI broth and the cultures were incubated at 37°C with aeration (170 rpm) for 18 hours.  Subsequently, 30 ul from each culture were transferred into 3 ml of fresh BHI broth and incubated at 37°C and 170 rpm for an additional 1.5 hours. The cultures were periodically assessed for their optical densities (ODs) at 600 nm with a spectrophotometer (Shimadzu Corp.), until a target OD600 of 0.400 ± 0.020 (mid-log phase) was attained; adjustments were made accordingly with sterile BHI broth.   Afterwards, 100 ul of inoculum was transferred to a 30 ml disposable conical tube and air-dried for 0.5 hours in a type A2 biological safety cabinet at 20°C.  Subsequently, the air-dried culture was suspended in 9.90 ml of peanut oil (~107 CFU/ml).  To obtain initial counts at time 0, the peanut oil suspensions were serially diluted with PBS, immediately spread-plated onto LB agar (Amresco) in duplicate, and colonies were counted at 37°C after 24 ± 2 hours.  Peanut oil suspensions were stored at 20°C for six days to reach stationary phase, after which thermal resistance assays were carried out. 62  3.2.2 Preparation of control Salmonella cultures A single colony of each of the five S. enterica strains (three replicates per strain) was inoculated into 10 ml BHI broth and the cultures were incubated at 37°C with aeration (170 rpm) for 18 hours to reach a final concentration of ~109 CFU/ml.    3.2.3 Desiccation for induction of cross-protection Non-desiccated S. enterica cells (controls) and desiccated S. enterica cells (107 – 108 CFU/ml) were serially diluted in PBS and 50 ul was spread on LB agar at 37°C for 24 ± 2 hours to obtain initial bacterial populations.  Subsequently, 50 ul volumes of bacterial culture were added .;to microcentrifuge tubes and incubated at 70°C for one minute in a C1000 Touch™ thermal cycler (Bio-Rad Laboratories).  The temperature, 70°C, was selected based on pasteurization guidelines for peanut-based products (Shachar & Yaron, 2006).  Serial dilutions in BHI broth were prepared and spread onto LB agar in duplicate.  Colonies were counted after incubation at 37°C for 24 ± 2 hours.  3.2.4 Sub-lethal heat for induction of cross-protection Overnight S. enterica cultures (controls) were serially diluted with sterile PBS, and 50 ul were spread on LB agar and incubated at 37°C for 24 ± 2 hours to obtain initial bacterial counts.  Subsequently, 50 ul volumes of both bacterial cultures were added into sterile microcentrifuge tubes and incubated at 45°C for three minutes, followed by incubation at 70°C for one minute in a C1000 Touch™ thermal cycler (Bio-Rad Laboratories).  The temperature of 45°C was chosen as the sub-lethal challenge temperature as it is the upper limit at which Salmonella can replicate (Montville & Matthews, 2005).  After heat treatment, the cultures were immediately diluted in 63  sterile BHI broth and spread onto LB agar in duplicate. Colonies were counted after incubation at 37°C for 24 ± 2 hours.  3.2.5 Statistical analysis The effects of the single treatments (e.g. desiccation or sub-lethal heat shock) on different strains were analyzed by a one-way ANOVA.  The interaction between two treatments (e.g. desiccation and sub-lethal heat shock) on different strains was analyzed by a two-way ANOVA.  The Student’s t-test was used to compare the effect of the desiccation and/or mild heat (45°C) treatments to the control at 70°C (figure 3.1).  To compare all possible pairs of means, Tukey’s HSD was performed (table 3.1). Statistical analyses were performed using JMP version 11.1.1.  A P value of < 0.05 was considered statistically significant.  3.3 Results and discussion 3.3.1 Desiccated Salmonella cells survive better than the controls at 70°C S. enterica cells desiccated for six days in peanut oil (aw 0.521 ± 0.003) exhibited significantly (p<0.05) higher resistance to heat treatment at 70°C across all serotypes (figure 3.1 and table 3.1). This is important because peanut production involves roasting at temperatures between 70-75°C (Shachar & Yaron, 2006).  These findings highlight the importance of pathogen control in low-aw foods, where production schemes typically involve a series of drying (desiccation) and pasteurization (heat) treatments (Finn, Condell, et al., 2013).  Mattick et al. (2000) also observed the protective effect of low-aw on temperatures above 70°C.  This cross-protection has also been reported in other studies (Bucher et al., 2008; Gruzdev et al., 2011; Sperber et al., 2007). Nevertheless, the methods used to reduce aw as well as the food matrices used, varied in these 64  studies (table 1.1).  It is likely that cross-protection occurred due to the overlapping roles that some genes play in stress response.  For example, the habituation of Salmonella to a low-aw environment was found to induce the expression of heat shock proteins DnaK, GroEL and IbpA, chaperones that stabilize other proteins and prevent their denaturation during the exposure to stresses (Gruzdev et al., 2012).  Because these proteins are also induced upon heat stress (Sirsat et al., 2011), increased heat resistance following low-aw habituation was observed (Gruzdev et al., 2012).  Still, other researchers propose that low concentrations of water in the bacterial cell can inhibit protein denaturation caused by heat shock.  Because high temperatures cause the breakage of S-S and hydrogen bonds of proteins through the vibration of water molecules, protein denaturation can be substantially limited if intracellular water is also limited (Hiramatsu et al., 2005; Peña-Meléndez et al., 2014).  Many previous studies investigating cross-protection were focused on S. Enteritidis and S. Typhimurium, while other serotypes of importance in low-aw foods and foodborne illness were also included in the current study.  Shachar et al. (2006) performed kinetics-based modeling on serotypes Enteritidis, Agona and Typhimurium at varying temperatures (70, 80 or 90°C) after pre-adaptation to peanut butter (aw 0.500) and found heat tolerance was significantly (p<0.05) increased compared to control cells suspended in saline.  After five minutes challenge at 70°C, increased death rates were observed, followed by lower rates of death.  In this study, Salmonella cells were only challenged at 70°C for one minute, however, it is possible that cells would show decreased rates of death in the current model had the challenge time been extended.  65  Although all desiccated strains showed significantly (p<0.05) higher tolerance to heat, a particularly interesting observation was S. Tennessee, which was the most susceptible to heat challenge at 70°C, but also had the greatest heat tolerance following six days of desiccation.   This emphasizes the highly adaptable nature of this particular strain to hurdles encountered in peanut production; S. Tennessee was implicated in a US multi-state peanut outbreak in 2007 (CDC, 2015a).  The high heat resistance of desiccated S. Tennessee was also observed by Van Cauwenberge et al. (1981). The authors investigated the use of dry heat to inactivate eight S. enterica serotypes in corn flour (moisture between 10-15%).  They observed the lowest log reductions in S. Tennessee and, interestingly, S. Thompson, the serotype displaying the second-greatest heat tolerance in the current study.  3.3.2 Effect of sub-lethal heat pre-adaptation on cell survival All serotypes challenged with a sub-lethal heat treatment at 45°C showed significantly (p<0.05) enhanced resistance to heat treatment at 70°C (figure 3.1 & table 3.1).  This result suggested a cross-protective effect following very limited (three minutes) sub-lethal heat shock.  To our knowledge, few studies have examined the heat resistance of Salmonella following pre-adaptation at a lower, sub-lethal temperature.  However, this bears high relevance to the food industry where it may take extra time to reach the desired pasteurization temperature, exposing cells to sub-lethal temperatures for an extended period of time.  Moreover, the exposure of foods to a warm environment prior to cooking can also give rise to sub-lethal injury.  Bunning et al. exposed S. Typhimurium and L. monocytogenes to sub-lethal heat shocks at varying temperatures (35, 42, 48 or 52°C) for 30 minutes and assessed their susceptibility to a further 66  challenge temperature of 57.8°C.  Compared to non-pre-adapted S. Typhimurium, the D-value of pre-adapted S. Typhimurium showed a significant (p<0.05) increase by one to two minutes, indicating the adaptable nature of this pathogen.  Conversely, the thermotolerance of L. monocytogenes did not increase following pre-adaptation, suggesting the unique innate ability of S. Typhimurium to adapt to thermal challenges (Bunning et al., 1990).  Similarly, heat tolerance of S. Typhimurium to a lethal temperature of 56°C also increased upon pre-adaptation to temperatures between 30 - 50°C (Humphrey et al., 1993).    Upon the elevation of temperature, heat shock proteins are produced to provide stability to other proteins and prevent denaturation (Sirsat et al., 2011).  While the role of heat shock proteins in cross-protection is not fully understood, pre-exposing cells to sub-lethal temperatures could prolong the period where heat shock proteins are produced in response to the increase in temperature, thereby facilitating survival at higher temperatures.  Despite potential significance to the food industry, the amount of literature documenting Salmonella adaptive heat tolerance from lower temperatures is very limited.  This begs the need for further addition of knowledge to this research focus.  Collectively, these results suggest that it is important to monitor the temperature change during the pasteurization process and other food processing procedures to ensure that pre-adaptation to sub-lethal heat temperatures will not occur, especially since it could enhance the thermotolerance of Salmonellae.  3.1.1 Effect of combined desiccation and heat pre-adaptation on cell survival The combination of six-day desiccation and 45°C treatment did not afford greater protection to 70°C heat shock than desiccation or 45°C heat shock alone.  However, multiple treatments did 67  induce a significant (p<0.05) increase in heat tolerance of all strains when compared to the controls.  Although the integration of both treatments provided protection against heat at 70°C, additional exposure to sub-lethal stresses did not necessarily result in an increasingly resistant pathogen.  It is probable that the combination of multiple treatments proved too stressful, resulting in the deaths of the bacterial cells.    Although extremely limited research has addressed the effect of multiple treatments on cross-protection, Shachar et al. (2006) previously reported a lower lethality against serotypes Enteritidis, Agona and Typhimurium following pre-adaptation in peanut butter at 80°C.  In their study, the cells were incubated in pre-heated peanut butter (aw 0.50) at 80°C for 30 minutes, then at room temperature peanut butter for 24 hours.  Following this, cells were challenged at 70, 80 or 90°C.  Cells survived ~2 log CFU better at 70 and 80°C and ~1 log CFU better at 90°C.  These observations are in direct accordance with the present findings; observed was a mean 1.97 log difference in cell populations following combined desiccation and sub-lethal heat treatment, compared to controls.  Similarly, Lathrop et al. inoculated a five-strain cocktail of S. enterica into peanut butter cookie dough and monitored cell populations during baking of the cookies for 15 minutes.   During baking, the aw of the cookies decreased from 0.82 to 0.51, and temperatures of the cookies increased from 21 to 109°C.  The results indicated that heat resistance of S. enterica increased following pre-adaptation to the aw and temperature gradients (Lathrop et al., 2014).     68     Table 3.1 Reductions in S. enterica populations to lethal heat temperature at 70°C following sub-lethal heat and/or desiccation treatments.  All treatments were compared to the control treatment at 70°.  Means with the same letter are not statistically different from each other (overall α=0.05, Tukey’s HSD).  Serotype                         Mean log reduction (log CFU/ml) ± SD 70°C 45°C & 70°C 70°C & Desiccation 45°C, 70°C & Desiccation Enteritidis 4.85 ± 0.18 A 3.53 ± 0.34 B 3.82 ± 0.54 B 3.95 ± 0.61 B Typhimurium 4.65 ± 0.22 A 3.58 ± 0.13 BC 2.91 ± 0.57 C 3.78 ± 0.60 B Tennessee 5.73 ± 0.64 A 4.03 ± 1.07 B 1.89 ± 0.63 C 2.03 ± 0.43 C Hartford 4.53 ± 0.11 A 2.92 ± 0.25 B 2.57 ± 0.34 B 2.55 ± 0.18 B Thompson 4.39 ± 0.66 A 3.13 ± 0.10 B   2.41 ± 0.70 BC 2.00 ± 0.15 C 69   Figure 3.1 Mean log reductions in S. enterica populations to lethal heat temperature at 70°C following heat and/or desiccation treatments.  Treatments were compared to the control treatment at 70°C (dotted bars).  One asterisk (*) indicates significance below α<0.05. Error bars indicate the standard errors of the means.* *        * * * *        *       * *   *   *        * * *     * 0.001.002.003.004.005.006.007.00Enteritidis Tennessee Hartford Thompson TyphimuriumLog reduction (log CFU/ml) S. enterica serotype 70°C70°C & Desiccation45°C & 70°C45°C, Desiccation & 70°C70  3.4 Conclusions Desiccation in peanut oil and heat treatment at 45°C, both of a sub-lethal nature, exerted a significant (p<0.05) protective effect on S. enterica challenged at a lethal temperature of 70°C.  Increases in surviving cell populations were observed upon pre-adaptation under either of these stresses, compared to controls subjected to only a heat challenge at 70°C.  These experiments were designed to simulate real-world scenarios, where desiccation is commonly used as a hurdle prior to pasteurization, and where sub-lethal heat of various temperatures may occur prior to lethal temperature upshifts.    Upon pre-exposure of cells to combined desiccation and mild heat treatment, a significant (p<0.05) decrease in log reduction after 70°C challenge was also observed, evidencing the presence of cross-protection.  However, because the combined treatments did not afford greater degrees of protection than desiccation or mild heat shock alone, we cannot conclude that dual pre-adaptive treatments could enhance the resistance of Salmonella.    The data presented in chapter 2 emphasizes the adaptability of S. enterica to survive in environments where sub-lethal stresses may occur.  It is evident that sub-lethal stresses can induce elaborate stress response networks, which then provide the bacterial cells with greater protection to subsequent, and sometimes unrelated, stressors.  Low-aw foods are of particular risk due to the nature of processing, which may support the survival or even proliferation of Salmonella.  Therefore, these data call into concern the importance of validating intervention processes; exposing Salmonella to unnecessarily low magnitudes of stress can ultimately promote the dissemination of this pathogen along the food supply chain.   71  Chapter 4: Gene expression profiling of S. enterica under desiccation or 45°C heat treatment  4.1 Introduction The majority of scientific literature available on Salmonella survival in low-aw environments is largely observational; that is to say, little research has focused on the molecular basis behind observed phenomena.  However, recent findings on the behaviour of Salmonella in low-aw environments have propelled the development of novel and innovative technologies to ensure the eradication of this pathogen.  Therefore, high value is placed upon understanding its persistence at a molecular level.  A study by Deng et al. (2012) assessed the global transcriptome of S. Enteritidis under desiccation stress in low-aw peanut oil.  This provided an in-depth view of desiccation occurring in a food matrix and marked an emergence of transcriptional profiling of one S. enterica strain in a low-aw food product.   The aim of objective III was to characterize the expression of five genes related to stress-response and virulence (e.g. fadA, otsB, rpoE, dnaK and invA) in the five experimental S. enterica strains:  Based on data obtained from the prior objectives, the transcriptional profiles of these genes were also evaluated in an attempt to correlate molecular phenomena with the observed serotype-specific and cross-protective effects.  72  4.2 Materials and methods 4.2.1 RNA stabilization of bacterial cultures A single colony of the S. enterica strains (three replicates per strain) was inoculated into 10 ml BHI broth and incubated at 37°C and 170 rpm for 18 hours.  Subsequently, 30 ul of each culture was transferred into 3 ml of fresh BHI medium at 37°C and 170 rpm and incubated for an additional 1.5 hours.   Cultures were periodically assessed for their ODs at 600 nm with a spectrophotometer (Shimadzu Corp.) until a target OD600 of 0.400 ± 0.020 (mid-log phase) was attained (~108 CFU/ml); adjustments were made with sterile BHI broth when necessary.  OD600-adjusted inocula were then subjected to three treatments in preparation for RNA stabilization.  4.2.1.1 RNA stabilization of control cultures To confirm the starting concentration of cells, OD600-adjusted inoculum was serially diluted in PBS and 100 ul was spread on LB agar which was incubated at 37°C for 24 ± 2 hours.  Subsequently, cessation of transcriptomic activity was carried out: 500 ul of OD600-adjusted inoculum was added to 1 ml of RNAprotect Bacteria Reagent (Qiagen, Valencia, CA, USA) in triplicate.  Bacterial suspensions were vigorously mixed for five seconds, followed by incubation at room temperature for five minutes.  Afterwards, the suspensions were spun for ten minutes at 5000 x g (Model 5424R, Thermo Fisher, Waltham, MA, USA) and the supernatant was subsequently decanted. Pellets were immediately stored at -80°C (Thermo Fisher) until further analysis.  73  4.2.1.2 RNA stabilization of heat-treated cultures OD600-adjusted inoculum was subjected to a 45°C heat treatment for three minutes in a water bath (Thermo Fisher, Waltham, MA, USA) with continuous circulation.  Initial cell concentrations were confirmed through serial dilutions of the inoculum in PBS and plating 100 ul on LB agar. Colonies were counted after incubation at 37°C for 24 ± 2 hours.  Subsequently, cessation of transcriptomic activity was carried out: 500 ul of heat-treated culture was added to 1 ml of RNAprotect Bacteria Reagent in triplicate.  Bacterial suspensions were vigorously mixed for five seconds, followed by incubation at room temperature for five minutes.  Afterwards, the suspensions were spun for ten minutes at 5000 x g (Model 5424R, Thermo Fisher) and the supernatant was subsequently decanted. Pellets were immediately stored at -80°C freezer until further analysis.  4.2.1.3 RNA stabilization of desiccated cultures To confirm the starting concentration of bacterial cells, OD600-adjusted inoculum was serially diluted in PBS and 100 ul was spread on LB agar.  Colonies were counted after incubation at 37°C for 24 ± 2 hours.  Subsequently, 500 ul of OD600-adjusted inoculum was allowed to air-dry for 30 minutes in a biological safety cabinet, after which 4.5 ml of peanut oil was added (aw 0.521 ± 0.003).  These suspensions (107-8 CFU/ml) were stored in a 20°C incubator for six days to reach stationary phase.  After six days of desiccation, cessation of transcriptomic activity was carried out: 1 ml of culture was added to 2 ml of RNAprotect Bacteria Reagent in triplicate.  Bacterial suspensions were vigorously mixed for five seconds, followed by incubation at room temperature for five minutes.  Afterwards, the suspensions were spun for ten minutes at 5000 x g 74  (Model 5424R, Thermo Fisher) and the supernatant was subsequently decanted. Pellets were immediately stored at -80°C freezer until further analysis.  4.2.2 RNA isolation and quality assessment Total RNA isolation was performed using the RNeasy Mini Kit (Qiagen, Valencia, CA, USA) and carried out according to the manufacturer’s instructions.  Contaminating genomic DNA was removed using the RNase-Free DNase Set (Qiagen, Valencia, CA, USA).   RNA quality was assessed using a Nanodrop spectrophotometer (Thermo Fisher Scientific, Waltham, Massachusetts, USA) and the BioAnalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA).    4.2.3 Intervening sequence detection Intervening sequences (IVSs) are short, ~90 bp sequences that occur at helices 25 and 45 in the 23S ribosomal molecule of some Salmonellae.  Immediately after transcription, RNase III (ribonuclease III) excises out the IVSs, however, the 23S rRNA gene may not be re-ligated, interrupting its linearity (Bhagwat et al., 2013; Mattatall & Sanderson, 1998; Pabbaraju et al., 2000).  Salmonella contains seven ribosomal RNA synthesis genes (rrl) per chromosome and the number of IVSs present in each rrl gene may be variable in number.  Therefore, analyzing Salmonella 23S/16S ratios, a well-known practice for RNA quality assessment, may not be a reliable method for interpreting RNA quality in the current study, as it will generate incongruencies.  This is especially apparent when using the microfluidic platforms such as the Bioanalyzer, as it compares experimental samples to a limited database of RNA samples (Bhagwat et al., 2013).  75  PCR detection for IVSs in the S. enterica strains was performed using the following primers specific to the rrl gene at helices 25 and 45 (table 4.1):   Table 4.1 rrl genes and corresponding primer sequences used for IVS detection. Gene Direction Primer Sequence (5’ Æ 3’) Reference rrl (helix-25) Forward GCGCCGGTAAGCTGATATG Pabbaraju et al., 2000 Reverse GCTATCTCCCGGTTTGATTG rrl (helix-45) Forward CCGATGCAAACTGCGAATAC Reverse TTCTCTACCTGACCACCTG   Cultures of S. Enteritidis, S. Tennessee, S. Hartford, S. Thompson, S. Typhimurium and E.coli 0157:H7 were grown by inoculating a single colony into 10 ml BHI broth, followed by incubation at 37°C at 170 rpm for 18 hours.  E. coli 0157:H7 was used as a positive control, as IVSs have not been previously reported in this organism (Pabbaraju et al., 2000).  Subsequently, 1 ul from the overnight cultures were used as template DNA in the PCR assay.  PCR was performed in a C1000 Touch™ thermal cycler (Bio-Rad Laboratories).  PCR cycling conditions were as follows: initial denaturation (three minutes; 94°C), three-step cycling: denaturation (30 seconds, 94°C), annealing (30 seconds; 52°C) and extension (one minute; 72°C), followed by a final extension (ten minutes, 72°C).  PCR amplicons were electrophoresed (Bio-Rad Laboratories) in 1x TAE buffer and 2% agarose at 90 volts.  The visualization of the PCR products was carried out using the ChemiDoc™ MP System (Bio-Rad Laboratories).  76  4.2.4 Reverse transcription of total RNA Synthesis of complementary DNA (cDNA) from RNA was completed using the Quantitect Reverse Transcription Kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions.  All reactions were completed in a type A2 biological safety cabinet.  cDNA concentrations were normalized to a final concentration of 1000 ng.  “No-RT” controls, where nuclease-free water (Amresco, Solon, OH, USA) was used in place of the reverse transcriptase (RT), were also carried out to detect for presence of contaminating genomic DNA.  cDNA was stored at -20°C for subsequent qPCR.   4.2.5 Quantitative PCR qPCR was used to determine relative gene expression in S. enterica in response to six days of desiccation in peanut oil and mild heat shock of 45°C for three minutes.  Five genes were chosen for expression assessments and their respective primer sets are listed in table 4.2.  Of the genes chosen, two were crucial for survival under desiccation stress (fadA and otsB); one was crucial for heat shock survival (dnaK), one was a universal stress response regulator (rpoE) and one was a gene involved in virulence (invA).  16S rRNA was used as the reference gene for the duration of the qPCR experiments because its expression did not change between the control and treatment groups.   77  Table 4.2 Analyzed genes and their respective primer sequences used in qPCR assays. Gene Direction Primer Sequence (5’ Æ 3’) Reference fadA Forward ATCTCTCCGCCCACTTAATGCGTA H. Li et al., 2012 Reverse AGCCTTGCTCCAGCGTTTGTTGTA otsB Forward ACCTTGATGGCACATTGGCAGA H. Li et al., 2012 Reverse ACGCCCTGAAATCAATGCCA rpoE Forward GTCTACAACATGACAAACAAAAACAAATGC Humphreys et al., 1999 Reverse CCTTTTCCACTATCCCGCTATCGTCAACGC invA Forward TCATGGCACCGTCAAAGGAACC Q. Li et al., 2012 Reverse GTGAAATTATCGCCACGTTCGGGCAA dnaK Forward CGATTATGGATGGAACGCAGG Kjeldgaard et al., 2011 Reverse GGCTGACCAACCAGAGTT 16S rRNA Forward CGATCCCTAGCTGGTCTGAG Castelijn et al., 2012 Reverse GTGCAATATTCCCCACTGCT 78  4.2.5.1 Amplification efficiency tests The purpose of amplification efficiency testing was to determine the relative efficiencies for each primer set in amplifying the target sequences (Pfaffl, 2001).  Three biological replicates of untreated, control cultures of S. Enteritidis were used for all primer efficiency testing and performed in duplicated wells.   The following cDNA dilutions (initial [cDNA] = 1000 ng) were prepared with nuclease-free water in microcentrifuge tubes: 100 (no dilution), 10-1, 10-2, 10-3 and 10-4 and kept on ice. The master mix was prepared using iTaq Universal SYBR Green Supermix (Bio-Rad Laboratories, Hercules, CA, USA) (table 4.3) and volumes were scaled appropriately for each assay.    Table 4.3 Master mix assembly for qPCR assays. Reagent: Volume/reaction (+10%): Final concentration: iTaq Supermix 11 ul 1x Primer (forward) 1.1 ul 0.5 uM Primer (reverse) 1.1 ul 0.5 uM Nuclease-free H2O 6.6 ul -- Total 19.8 ul --   Into each well of a 96-well plate (Bio-Rad Laboratories, Hercules, CA, USA), 18 ul of master mix was dispensed as needed.  Subsequently, 2 ul of the appropriate cDNA dilution was added to the corresponding well in duplicate and the pipette was pumped to homogenize the reagents in each well.   As a “No-cDNA” control, 2 ul of nuclease-free water was added instead, in 79  duplicate, to detect for presence of contaminating cDNA.  Each well contained the components shown in table 4.4.  The plate was covered with optical seal (Bio-Rad Laboratories, Hercules, CA, USA) and spun briefly to collect reagents at the bottom.  Subsequently, the plate was placed into a CFX-96™ thermal cycler (Bio-Rad Laboratories, Hercules, CA, USA) for data collection.  qPCR cycling conditions were as follows for 45 cycles: initial denaturation (25 seconds; 95°C) and two-step cycling: denaturation (30 seconds, 94°C), annealing and extension (25 seconds; variable temperatures (table 4.5).  Melt curve analysis was carried out to detect the presence of non-specific binding of the primers by increasing the temperature of the CFX- 96™ thermal cycler from 65- 90°C in 0.5°C increments, with three seconds per increment increase.  Melt curve analysis was carried out following amplification to detect for presence of non-specific primer binding.  Table 4.4 qPCR reaction assembly. Reagent: Volume/reaction Final concentration: iTaq mix 10 ul 1x Primer (forward) 1 ul 0.5 uM Primer (reverse) 1 ul 0.5 uM Nuclease-free H2O 6 ul -- cDNA (or nuclease-free water) 2 ul 5 ng/ul or 100 ng total Total 20 ul --    80  Table 4.5 Annealing temperatures of the genes analyzed in qPCR assays. Gene Annealing temperature fadA 56°C otsB 55°C rpoE 55°C invA 56°C dnaK 54°C 16S rRNA 54°C   Primer efficiency (E) was calculated according to the equation (Rasmussen, 2001):    E = 10[-1/slope]                                                                                               (3.1)  Only primers optimized to 93 - 110% amplification efficiency were used in gene expression analyses.  4.2.5.2 Analysis of gene expression with qPCR cDNA was diluted 1:4 with nuclease-free water prior to beginning the experimental set-up and held on ice.  The master mix was prepared using iTaq Universal SYBR Green Supermix (table 4.3) and volumes were scaled appropriately for each assay.  Subsequently, 18 ul of master mix was dispensed into each well of a 96-well plate as needed.  Then, 2 ul of the appropriate cDNA dilution was added to the corresponding well in duplicate and the pipette was pumped to 81  homogenize the reagents in each well.  As a “No-cDNA” control, 2 ul of nuclease-free water was added instead, in duplicate.  The “No-RT” controls were used to detect genomic DNA contamination.  For all strains, three biological replicates and two technical replicates were analyzed per treatment.     Each well contained the components as shown in table 4.4.  The plate was secured with an optical seal and spun briefly to collect reagents at the bottom.  Subsequently, the plate was placed into a CFX-96™ thermal cycler (Bio-Rad Laboratories) for data collection.  qPCR cycling conditions were identical to the conditions described in amplification efficiency testing (section 4.2.5.1). Melt curve analysis was carried out to detect presence of non-specific primer binding.  4.2.6 Data and statistical analysis Fold changes were calculated according to the Pfaffl equation (Pfaffl, 2001):  ratio=( Etarget)ΔCttarget (control-sample)( Eref)ΔCtref (control-sample)     (3.2)                                             where Etarget and Eref refer to the primer efficiencies of the assessed genes and the reference 16S rRNA, respectively.  ΔCttarget and ΔCtref refer to the deviation in the threshold cycle (Ct) values between the treated and control groups for the target genes and the reference 16S rRNA gene, respectively. The Pfaffl equation was chosen for fold change calculation on the basis of primer efficiency consideration and the Ct deviation of the investigated transcripts. For the standardization of raw data, the method presented by Willems et al. (2008) was used, which is a 82  standardization procedure based on log transformation, mean centering and autoscaling.  The means of the treatment and control groups were assessed for significance (α=0.05) using the Student’s t-test (JMP, v.11.1.1).  4.3 Results and discussion 4.3.1 RNA quality assessment Agilent recommends a minimum RNA Integrity Number (RIN) of 7 or above for downstream qPCR experiments. Some S. enterica strains did not produce consistent RINs across treatments (table A.1).  The BioAnalyzer microfluidic platform analyzes RNA profiles using a limited set of biological samples and has bias towards eukaryotic RNA (Bhagwat et al., 2013).  Consequently, interpretations about quality when non-traditional banding patterns occur may be misconstrued, resulting in a low RIN.  IVSs have been reported in some serotypes of Salmonella, which are not manifested when using microfluidic platforms such as the BioAnalyzer (Bhagwat et al., 2013), thereby resulting in low RINs or absence of a RIN.  4.3.2 IVS detection PCR using primers targeting rrl helices 25 and 45 was carried out to detect for presence of IVSs.  Figure 4.1 shows the bands detected by gel electrophoresis of PCR products. The bands at ~730 bp were produced in the positive control E. coli 0157:H7 and in serotype Enteritidis, which do not harbor IVSs in the 23S molecule.   Bands at ~833 bp were produced in serotypes Tennessee, Hartford, Thompson and Enteritidis, due to the presence of the IVSs.  Presence of a band in helix 25 and/or helix 45 (~830 bp) indicates presence of one or more IVSs (~90 bp) in that particular locus, leading to the erroneous judgment of degraded RNA. 83   Figure 4.1 confirms the previous observations of low (<7) or absence of RINs for serotypes Tennessee, Hartford, Thompson and Typhimurium.  The replicates of these strains were, however, selected following qPCR experiments due to acceptable A260/280 ratios of ~2.0 as tested by the Nanodrop 2000 spectrophotometer (ThermoFisher Scientific, Waltham, MA, USA) (table A.1).  Notably, Enteritidis did not contain IVSs, consistent with the acceptable RINs of ≥7.  IVSs in some serotypes of Salmonella have also been previously documented (Bhagwat et al., 2013; Mattatall & Sanderson, 1998; Pabbaraju et al., 2000), however, only a limited set of Salmonella strains are known to harbor IVSs in their 23S rRNA.  Interestingly, Mattatall & Sanderson (1998) created RNAse-III knockout mutants of S. Typhimurium and observed no deficiencies in ribosomal integrity, suggesting that IVSs are selectively neutral.   84       Figure 4.1 PCR products of S. enterica following IVS detection.  Primers used were specific to the rrl gene at helices (H) 25 or 45. Presence of a ~830 bp band indicates IVSs in the corresponding helix of the 23S rRNA molecule of the strain. DNA ladder  Blank  E.coli H-25 E. coli H-45 S. Enteritidis H-25 S. Enteritidis H-45  S. Hartford H-25  S. Hartford H-45 S. Tennessee H-25 S. Tennessee H-45 S. Thompson H-25 S. Thompson H-45 S. Typhimurium H-25 S. Typhimurium H-25 DNA ladder       85  4.3.3 Transcriptional profiles of S. enterica under desiccation and heat stress 4.3.4 Expression of invA invA has an essential role in invasion and pathogenicity of Salmonella. S. Typhimurium possessing a mutated invA gene was incapable of invading epithelial cells (Galan et al., 1992).   Salmonella has the unique ability to initiate its own uptake into eukaryotic cells, after which type III secretion may take place, a process whereby virulence effectors are directly transported into host cells (Lostroh & Lee, 2001).    Differential gene expression of invA was demonstrated following heat stress at 45°C for three minutes (figure 4.2).  All strains showed significant (p<0.05) downregulation of invA following the mild heat treatment at 45°C.  These observations have also been documented in literature; Sirsat et al. (2011) documented 5 to 11-fold suppression of a variety of virulence genes in S. Typhimurium after 42°C heat stress, including invA, which was downregulated for 5.05-fold.   invA was significantly (p<0.05) downregulated in all strains following a six-day passage in peanut oil (Figure 4.2).  In a study analyzing the global transcriptome of S. Enteritidis desiccated in peanut oil (aw 0.3), no transcripts of invA or any virulence-related genes were detected after 528 hours desiccation (Deng et al., 2012).  Similarly, a study conducted by Lesne et al. (2000) revealed significant decreases in S. Typhimurium virulence after three weeks drying in a sealed desiccator, although infectivity was observed using animal models instead of molecular-based methods.    86  Since invasion is not essential for survival, it is probable that S. enterica diverts resources away from pathogenicity and into survival in times of heat and desiccation stress (Finn, Condell, et al., 2013).  Moreover, Deng et al. (2012) observed a generalized metabolic dormancy in S. Enteritidis subjected to desiccation in peanut oil, with only a few critical genes maintaining active transcription.  In this manner, S. enterica could therefore conserve energy by halting production of unnecessary genetic factors and increase production of factors essential for surviving heat and osmotic stress (Deng et al., 2012).      Figure 4.2 Log 2 fold change in expression of the invA gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means.   * * * * * * * * * * -14.00-12.00-10.00-8.00-6.00-4.00-2.000.00Enteritidis Tennessee Hartford Thompson TyphimuriumLog 2  fold change S. enterica serotype HeatDesiccation87  4.3.5 Expression of fadA During exposure to desiccation stress, energy requirements are greater due to an increased need for production of stress-response proteins.  fadA encodes for 3-ketoacyl-coA thiolase, which catabolizes long-chain fatty acids into acetyl-coA that can be used immediately in the tricarboxylic acid cycle for production of ATP (H. Li et al., 2012).  Under heat stress, structural integrity is compromised, especially that of proteins and the cellular envelope (Busta, 1976), therefore proteins responsible for structural repair would be of particular importance (Busta, 1976; Hsu-Ming, 2012).  Specifically, the liv gene cluster, which plays a role in amino acid and subsequent protein production, was upregulated in S. Typhimurium after heat injury and a subsequent 60-minute recovery time (Hsu-Ming, 2012).  Therefore, because fadA is involved in membrane fatty acid degradation, the qPCR analysis was not expected to demonstrate high fadA expression in heat-stressed Salmonella, which correlates with the present results (figure 4.3).  However, some strains of heat-shocked Salmonella showed significant (p<0.05) upregulation of fadA, a gene involved in degradation of fatty acids, although the extent to upregulation was drastically decreased compared to that involved in the desiccation response.     The expression of fadA was considerably induced following desiccation in peanut oil for six days (figure 4.3).  This is consistent with observations by H. Li et al. (2012), who also observed high fold changes of fadA in S. Tennessee and S. Typhimurium, after air-drying for 2 hours.  In fact, upregulation of a variety of genes from the fad locus has been reported following desiccation and starvation stress (Spector & Kenyon, 2011).     88   Figure 4.3 Log 2 fold change in expression of the fadA gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means.  4.3.6 Expression of rpoE rpoE is an alternate sigma factor responsible for the expression of genes involved in response to various stresses, including heat, desiccation and oxidative stress (McMeechan et al., 2007; Raivio & Sylhavy, 2001).   Consistent with this knowledge, Gruzdev et al. (2012) created rpoE knock-out mutants of S. Typhimurium and demonstrated significantly (p<0.05) decreased survival in cells undergoing desiccation compared to wild-type cells.  *       * * * *  *  *  *  *  -1.000.001.002.003.004.005.006.007.008.009.0010.00Enteritidis Tennessee Hartford Thompson TyphimuriumLog 2  fold change S. enterica serotype HeatDesiccation89  However, conflicting results were obtained in the current study; downregulation of rpoE was observed in some strains of S. enterica after heat treatment and in all strains after desiccation (figure 4.4).  Following the heat treatment (45°C), upregulation was observed in all serotypes except for S. Typhimurium and S. Thompson.  Following the six-day incubation in peanut oil, significant (p<0.05) levels of rpoE downregulation was observed in all strains, although there was no significant difference in the degree of downregulation across different strains (p>0.05).  There are of previous reports of upregulation of this gene upon introduction of desiccation (Deng et al., 2012; Gruzdev et al., 2012; Hsu-Ming et al., 2012). Several factors could account for the discrepancies observed in this study. One hypothesis is that genes not under transcriptomic control of rpoE are predominantly responsible for desiccation tolerance, and might be upregulated to such an extent that rpoE could be considered an unnecessary transcript to divert valuable resources to.  It has also been proposed that rpoE may show an aw-dependent effect; various water activities could induce different degrees of transcriptional activity of rpoE (Podolak et al., 2010).  Further, different methods of desiccation could impact degrees of up- or down-regulation. Deng et al. (2012) previously reported increases in rpoE transcription using peanut oil with aw 0.3 which was lower than the peanut oil used in the present study (aw 0.521 ± 0.003).   Additionally, Gruzdev et al., 2012 air-dried S. Typhimurium at 40% relative humidity for 22 hours and observed an upregulation with a fold change of 2.53.  Therefore, different water activities in combination with the various methods that researchers may use to induce a desiccation response, may have impacted the expression of rpoE.   90   Figure 4.4 Log 2 fold change of expression of the rpoE gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means.  4.3.7 Expression of otsB Osmoprotectants are small, molecular weight compounds that maintain osmoregulation when cells undergo osmotic shock.  In doing so, they can be transported in and out of the cell in times of stress to maintain appropriate osmotic gradient potential (Finn, Condell, et al., 2013).  In times of desiccation, or hyperosmotic stress, solute concentrations are higher outside of the cell due to the lack of available water.  Bacteria can adjust to this stress through de novo synthesis of compatible solutes, import of solutes from outside the cell, or both (Shiroda et al., 2014). * * * * *             * * -8.00-7.00-6.00-5.00-4.00-3.00-2.00-1.000.001.002.00Enteritidis Tennessee Hartford Thompson TyphimuriumLog 2 fold change S. enterica serotype HeatDesiccation91  otsB encodes for trehalose-6-phosphate phosphatase, the last enzyme in the trehalose biosynthesis pathway.  Trehalose is an osmoprotectant synthesized by S. enterica under desiccation; upregulation has been previously reported following desiccation of Salmonella on filter disks and following salt shock (Balaji et al., 2005; H. Li et al., 2012). This is consistent with the results in the present study, where otsB was upregulated to varying extents in all serotypes following desiccation (figure 4.5).  Other research has also documented otsB upregulation in S. enterica using various models for desiccation (Finn, Händler, et al., 2013; Gruzdev et al., 2012).   In the current study, upregulation of otsB was also observed in both heat-stressed S. enterica after 45°C for three minutes, although the response was much less pronounced than in desiccation-stressed cells (figure 4.5).  otsB expression following temperature shock has not been studied in detail.  However, otsB is dependent on rpoS for regulation (Finn, Condell, et al., 2013), an alternate sigma factor induced under a variety of stress conditions, including heat. Although the expression of rpoS was not evaluated in this study, it was likely involved in the induction of this gene under heat shock.    The protective effect of desiccation to lethal heat temperatures was demonstrated in this study (figure 3.1), but the effect of heat pre-adaptation on desiccation tolerance was not evaluated.  Although speculative, the detectable transcripts of otsB under heat shock in figure 4.5 suggest that heat-treated Salmonellae could demonstrate greater tolerance to subsequent desiccation.   Previously, heat-treated E.coli 0157:H7 and S. Typhimurium survived for extended times in 92  compost piles during the summer.  An analysis of the data revealed that heat conferred subsequent tolerance to desiccation on compost surfaces (Shepherd et al., 2010).     Figure 4.5 Log 2 fold change of expression of the otsB gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means.  4.3.8 Expression of dnaK dnaK encodes for Hsp70, a chaperone protein that binds to, and helps stabilize other proteins during heat shock (Gruzdev et al., 2012).  Consistent with the previous findings, upregulation of dnaK under mild heat shock was observed in all serotypes (figure 4.6).  These observations are also consistent with previous findings (Berk et al., 2005; Gruzdev et al., 2012; Sirsat et al, 2011).  * * * *  *  *  * * 0.001.002.003.004.005.006.007.008.009.00Enteritidis Tennessee Hartford Thompson TyphimuriumLog 2 fold change S. enterica serotype HeatDesiccation93  Heat tolerance at 45°C can be gained by increased production of Hsp70 transcripts.    Conversely, dnaK was significantly (p<0.05) downregulated after six days of desiccation in peanut oil.  Limited work has been directed at the examination of expression of this gene after dehydration, however, a recent study by Gruzdev et al. (2012), saw a 6.6-fold upregulation of dnaK in S. Typhimurium subjected to desiccation stress.  It should be noted that the authors did not use a food model but subjected cells to air-drying as the mode of dehydration, which induces additional challenges because of greater restrictions on water activity.  In contrast, Deng et al. (2012) performed transcriptome sequencing of S. Enteritidis after desiccation in peanut oil (aw 0.3) and did not detect any transcripts of dnaK.  Therefore, it is likely that different methods used to desiccate, as well as different water activities, may induce different degrees of dnaK expression.  94   Figure 4.6 Log 2 fold change of expression of the dnaK gene under heat and desiccation stress in S. enterica.  Asterisks (*) indicate significance below α=0.05 (Student’s t-test).  Error bars indicate standard error of the means.  4.3.9 Strain-related differences in gene expression levels Differences in gene regulation were observed among the S. enterica serotypes used in this study, as well as between the two treatments.  Specifically, fadA and otsB, genes involved in desiccation response exhibited higher degrees of upregulation in the desiccated cells compared to heat-treated cells.  dnaK, best known for its protective role following temperature upshift, was upregulated in the heat-treated group and downregulated in desiccated cells.  invA, an invasion gene, showed similar degrees of downregulation in both treatment groups and rpoE, and *         * * *, * * * * * -6.00-4.00-2.000.002.004.006.008.00Enteritidis Tennessee Hartford Thompson TyphimuriumLog 2 fold change S. enterica serotype HeatDesiccation95  interestingly, showed higher degrees of downregulation in desiccated cells.    In heat-treated Salmonella, S. Hartford exhibited lower differential gene expression compared to the other serotypes, particularly for dnaK.   However, the smallest log reduction at 70°C following 45°C pre-adaptation was seen with this serotype (table 3.1), suggesting that it employs different metabolic processes to tolerate temperature than other serotypes with a stronger expression of dnaK.   For example, other genes encoding for chaperone proteins have been documented in a previous heat challenge study (Gruzdev et al., 2012).  Notably, S. Hartford and S. Tennessee exhibited very little downregulation of invA compared to other serotypes, suggesting they may retain more virulence following mild heat treatment.   Weakly persistent S. Typhimurium, as evidenced from the previous survival assays also underwent the greatest downregulation of invA.  Additionally, rpoE was downregulated to a greater extent, which was not evident in other strains.  However, the reason for this remains to be elucidated since S. Typhimurium did not demonstrate any significant deficiencies compared to other serotypes in its heat tolerance.  Following six days of oil desiccation, the five strains demonstrated different transcriptional profiles.  Genes essential for desiccation tolerance, fadA and otsB, were significantly (p<0.05) upregulated in all strains, although to different extents.  S. Typhimurium and S. Enteritidis exhibited the lowest amount of fadA and otsB upregulation, which corresponds with lower resistance to low-aw foods.  Li et al. (2012) also documented S. Typhimurium had a less extensive transcriptional profile compared to that of S. Tennessee under desiccation stress.  Moreover, Deng et al. (2012) performed transcriptome sequencing on S. Enteritidis following peanut oil desiccation and discovered that only 1.36% - 4.42% of the genome was transcribed 96  following desiccation and starvation stress in peanut oil at 216 hours and 518 hours – indicating that S. Enteritidis undergoes metabolic dormancy to tolerate low-aw.     S. Hartford and S. Thompson demonstrated similarly high degrees of fadA and otsB upregulation, which correlates with the previous findings of high persistence in low-aw environments.  These findings are important because studies on Salmonella are not typically focused on these serotypes, which were shown to have high resistance to low-aw in the current study.  Moreover, S. Hartford was recently implicated in an outbreak in chia seed powder (CDC, 2014b), emphasizing the significance of the findings regarding high expression of genes responsible for survival in low-aw foods.  Although S. Tennessee also exhibited persistence in peanut oil, it exhibited lower expressional levels of fadA and otsB compared to Hartford and Typhimurium.  These results suggest that upregulation of other genes may be responsible for desiccation tolerance of S. Tennessee.  For example, H. Li et al. (2012) observed that genes from the opu gene family, also responsible for osmotic resistance, were also upregulated at levels significantly higher than otsB following desiccation on paper disks.    4.3.10 The molecular basis of cross-protection As demonstrated previously, pre-adaptation to desiccation and/or mild heat shock resulted in increased resistance to a lethal heat treatment of 70°C (table 3.1).  It was hypothesized that an upregulation of heat-tolerant genes under pre-adaptive desiccation stress would confer resistance to lethal heat treatments.  However, this was not observed in the current study; dnaK did not 97  show upregulation following six days of desiccation in peanut oil, and this factor does not explain the observed discrepancy.  This is likely due to the limited number of heat-tolerant genes assessed in the study; a multitude of other heat shock proteins were upregulated following desiccation stress in Salmonella (Gruzdev et al., 2012).  Additionally, the different methods used to induce low-aw could have an impact on the expression of different genes (Gruzdev et al., 2012; Mattick et al., 2001).    Pre-adaptation to a mild heat treatment of 45°C also resulted in increased tolerance to a 70°C stress, but, there was no evidence of molecular changes underlying this phenomenon in the present study.  Additionally, pre-adaptation to both desiccation and sub-lethal heat in tandem resulted in increased tolerance at 70°C, but the mechanism also remains unclear.  This may be due to the limitations of the study; if expression of a wider array of genes had been examined a clearer explanation of the cross-protective mechanism could possibly be established.   4.4 Conclusions The research on pathogen survival in low-aw foods is relatively new and emerging.  The current results provided new information to this field by including the S. enterica serotypes that are understudied.   From the qPCR data, it is evident that different stress conditions act as stimuli to induce differential regulation of genes.  The stress conditions presented in this study mimic the environments Salmonella encounters in low-aw food processing: particularly heat and desiccation.   While these interventions are usually effective at eradication of this pathogen, 98  recent outbreaks have proven otherwise.  Therefore, current methodologies should be reconsidered and revised, especially because it is known that Salmonella is able to readily adapt to the environmental stresses encountered during food production.  Although the molecular basis behind cross-protection was not fully elucidated in the current study, conclusive evidence was gained regarding strain-specific responses to heat and desiccation stresses.  These results should encourage a shift from the traditional practice of extrapolating anticipated behaviours based on observations derived from experimentation with  one serotype or strain to S. enterica as a whole, which may additionally lead to bias in public health diagnostics.  Moreover, analyzing the molecular mechanisms underlying Salmonella survival in low-aw environments is of high value to food industry because it allows for greater understanding of the regulatory networks behind tolerance in low-aw foods.   Through the acquisition of new knowledge, limitations and knowledge gaps in the understanding of pathogen persistence can be identified and remedied.  This knowledge will aid in future development of detection and intervention strategies in food industry.          99  Chapter 5: Conclusion and future direction  5.1 Conclusion In the present study, the survival and transcriptional responses of S. enterica serotypes Enteritidis, Tennessee, Hartford, Thompson and Typhimurium in low-aw food products were characterized.  In objective I, all five strains were assessed for survival in three low-aw foods of various aw: in-shell peanuts, peanut oil and chia seeds.  All strains were capable of long-term survival and exhibited marked persistence in each low-aw food matrix.  S. Hartford was shown to be the most resistant to desiccation stress, while S. Typhimurium was the most susceptible to desiccation.  These findings illustrate the need to include multiple serotypes in research meant to simulate worst-case contamination scenarios in the food production and processing environment.  In objective II, Salmonellae were pre-exposed to six days of desiccation in peanut oil and/or to a 45°C heat treatment prior to exposure to lethal heat treatment at 70°C.  There was a significant (p<0.05) increase in the thermotolerance of all Salmonella serotypes following pre-adaptation to desiccation, 45°C heat shock, or both.  These findings clearly showed that adaptive resistance resulted from pre-exposure to desiccation and sub-lethal heat stresses.    In objective III, qPCR was used to assess the transcriptional profiles of S. enterica after exposure to six days of desiccation in peanut oil or 45°C shock.  A set of five genes involved in S. enterica stress response was analyzed: these related to desiccation-tolerance (fadA and otsB), heat-tolerance (dnaK), general stress response (rpoE) and virulence (invA).  fadA and otsB showed the highest degrees of upregulation in serotypes which were treated under desiccation conditions.  100  dnaK was differentially upregulated under 45°C heat shock.  Alternate sigma factor rpoE, is known to be involved in general stress response.  rpoE regulates the expression of many other genes involved in stress and is usually transcribed under most sub-optimal conditions.  Interestingly, rpoE was not upregulated under either condition in the present study, which suggests that it may be activated in an aw-dependent manner (Spector & Kenyon, 2012).  The qPCR assays also revealed comparatively higher expression levels of fadA and otsB in serotypes Hartford and Thompson, an observation in line with the previous findings that these serotypes were more persistent in the low-aw food matrices (objective I).   However, the molecular basis behind the observed cross-protection was not explained by an examination of transcriptional events in the sub-set of genes selected for the present study. Additional insight into cross-protection would undoubtedly be gained by the inclusion of a wider array of stress-associated genes.  In conclusion, the stress response of five S. enterica serotypes in low-aw foods were examined in this work.  Survival behaviours were subsequently correlated using transcriptional gene analysis to characterize five genes crucial for survival in low-aw environments and/or virulence potential.  The findings emphasize the adaptable nature of this pathogen and highlight the importance in Salmonella control not only in low-aw food production, but also throughout the low-aw food chain continuum.        101  5.2 Future direction In this study, the molecular mechanism behind the cross-protective effects of desiccation and/or mild heat shock were not identified, probably due to the limited number of genes that were assessed.  A wider array of genes should be examined in future studies to gain better insight into this poorly-understood phenomenon.  Doing so would undoubtedly promote the development of innovative strategies to mitigate the implied risk in the food industry.  Further, peanut oil (aw 0.521 ± 0.003) was the only model used for gene expression profiling.  A recommendation for future studies would be to compare the survival of Salmonella in different food matrices to establish the effects of (i) desiccation pre-adaptation prior to different heat treatments and (ii) the global transcriptional profiles of different strains.  There is presently little information about the behaviour of Salmonella in the range of low-aw foods in the market.  Lastly, five serotypes of S. enterica were used in this study, and their relative abilities to survive desiccation and heat stresses were compared.  It would also be beneficial to evaluate strains within serotypes to gain a better understanding of strain-associated differences to more fully characterize the diversity of responses within S. enterica.   102  References  Asakura, H., Makino, S., Takagi, T., Kuri, A., Kurazono, T., Watarai, M., & Shirahata, T. (2002). 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Serotype Treatment Biological replicate A260/280 RIN Enteritidis Control 1 2.11 7.7 2 2.12 7.9 3 2.06 8.1 Heat 1 2.09 7.5 2 2.14 7.8 3 2.08 7.9 Desiccation 1 2.08 7.2 2 2.09 7.2 3 2.10 7.0 Tennessee Control  1 2.11 7.4 2 2.08 7.5 3 2.08 7.5 Heat  1 2.12 7.2 2 2.12 7.2 3 2.09 7.4 Desiccation 1 2.07 6.2 2 2.06 5.7 3 2.06 6.1 Hartford Control 1 2.11 N/A 2 2.12 N/A 3 2.11 N/A Heat 1 2.07 7.3 2 2.09 7.3 3 2.04 7.3 Desiccation 1 2.05 6.2 2 2.07 6.2 3 2.08 6.3 123   Serotype Treatment Biological replicate A260/280 RIN   Thompson       Control 1 2.14 6.7 2 2.12 6.8 3 2.11 6.9 Heat 1 2.10 6.7 2 2.12 6.8 3 2.13 6.9 Desiccation 1 2.09 6.1 2 2.08 N/A 3 2.08 7.1 Typhimurium Control 1 2.14 5.5 2 2.13 N/A 3 2.09 N/A Heat 1 2.15 N/A 2 2.06 N/A 3 2.09 N/A Desiccation 1 2.10 N/A 2 2.11 5.3 3 2.12 N/A    

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