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Salmonella enterica Typhimurium DT104 (S. Typhimurium DT104) is an important foodborne pathogen that is associated with poultry and poultry products. Currently, there is very little information on the underlying molecular mechanisms that allow DT104 to survive and propagate in poultry meat and the poultry processing environment. The current study assessed the global gene expression of DT104 in ground chicken extract (GCE) compared to brain heart infusion (BHI) medium using RNA-Seq technology. DT104 was grown to the early stationary phase (ESP), inoculated into GCE or BHI, and then re-grown to the log phase before RNA was extracted and transcripts were quantified by RNA-Seq. Gene expression for DT104 grown in GCE was then compared to that of DT104 grown in BHI for samples grown to the ESP. Growth in GCE resulted in the up-regulated expression of genes related to translation, carnitine metabolism (23–283-fold change), and cobalamin (vitamin B12) biosynthesis (14-fold change). In particular, the presence of carnitine in chicken meat, and thus, in GCE, which lacks carbohydrates, may allow Salmonella to utilize this compound as a carbon and nitrogen source. This study demonstrates that RNA-Seq data can provide a comprehensive analysis of DT104 gene expression in a food model for poultry products. This study also provides additional evidence for the importance of metabolic adaptation in the ability of S. enterica to successfully adapt to and occupy niches outside of its host and provides potential targets that could be used to develop intervention strategies to control Salmonella in poultry.

Abstract Background Toxin-antitoxin (TA) systems are commonly found in bacteria and Archaea, and it is the most common mechanism involved in bacterial programmed cell death or apoptosis. Recently, MazF, the toxin component of the toxin-antitoxin module, has been categorized as an endoribonuclease, or it may have a function similar to that of a RNA interference enzyme. Results In this paper, with comparative data and phylogenetic analyses, we are able to identify several potential MazF-conserved motifs in limited subsets of foodborne pathogens and probiotic strains and further provide a molecular basis for the development of engineered/synthetic probiotic strains for the mitigation of foodborne illnesses. Our findings also show that some probiotic strains, as fit as many bacterial foodborne pathogens, can be genetically categorized into three major groups based on phylogenetic analysis of MazF. In each group, potential functional motifs are conserved in phylogenetically distant species, including foodborne pathogens and probiotic strains. Conclusion These data provide important knowledge for the identification and computational prediction of functional motifs related to programmed cell death. Potential implications of these findings include the use of engineered probiotic interventions in food or use of a natural probiotic cocktail with specificity for controlling targeted foodborne pathogens.

Abstract Background Salmonella is a major bacterial pathogen associated with a large number of outbreaks of foodborne diseases. Many highly virulent serovars that cause human illness belong to Salmonella serogroup C1, and Salmonella ser. Choleraesuis is a prominent cause of invasive infections in Asia. Comparative genomic analysis in our previous study showed that two homologous genes, SC0368 and SC0595 in Salmonella ser. Choleraesuis were unique to serogroup C1. In this study, two single-deletion mutants (Δ0368 and Δ0595) and one double-deletion mutant (Δ0368Δ0595) were constructed based on the genome. All these mutants and the wild-type strain were subjected to RNA-Seq analysis to reveal functional relationships of the two serogroup C1-specific genes. Results Data from RNA-Seq indicated that deletion of SC0368 resulted in defects in motility through repression of σ28 in flagellar regulation Class 3. Consistent with RNA-Seq data, results from transmission electron microcopy (TEM) showed that flagella were not present in △0368 and △0368△0595 mutants resulting in both swimming and swarming defects. Interestingly, the growth rates of two non-motile mutants △0368 and △0368△0595 were significantly greater than the wild-type, which may be associated with up-regulation of genes encoding cytochromes, enhancing bacterial proliferation. Moreover, the △0595 mutant was significantly more invasive in Caco-2 cells as shown by bacterial enumeration assays, and the expression of lipopolysaccharide (LPS) core synthesis-related genes (rfaB, rfaI, rfaQ, rfaY, rfaK, rfaZ) was down-regulated only in the △0368△0595 mutant. In addition, this study also speculated that these two genes might be contributing to serotype conversion for Salmonella C1 serogroup based on their apparent roles in biosynthesis of LPS and the flagella. Conclusion A combination of biological and transcriptomic (RNA-Seq) analyses has shown that the SC0368 and SC0595 genes are involved in biosynthesis of flagella and complete LPS, as well as in bacterial growth and virulence. Such information will aid to revealing the role of these specific genes in bacterial physiology and evolution within the serogroup C1.

Listeria monocytogenes is a foodborne pathogen and the causative agent of listeriosis, a disease associated with high fatality (20-30%) and hospitalization rates (>95%). ATP-Binding Cassette (ABC) transporters have been demonstrated to be involved in the general stress response. In previous studies, in-frame deletion mutants of the ABC transporter genes, LMOf2365_1875 and LMOf2365_1877, were constructed and analyzed; however, additional work is needed to investigate the virulence potential of these deletion mutants. In this study, two in vitro methods and one in vivo model were used to investigate the virulence potential of in-frame deletion mutants of ABC transporter genes. First, the invasion efficiency in host cells was measured using the HT-29 human cell line. Second, cell-to-cell spread activity was measured using a plaque forming assay. Lastly, virulence potential of the mutants was tested in the Galleria mellonella wax moth model. Our results demonstrated that the deletion mutant, ⊿LMOf2365_1875, displayed decreased invasion and cell-to-cell spread efficiency in comparison to the wild-type, LMOf2365, indicating that LMOf2365_1875 may be required for virulence. Furthermore, the reduced virulence of these mutants was confirmed using the Galleria mellonella wax moth model. In addition, the expression levels of 15 virulence and stress-related genes were analyzed by RT-PCR assays using stationary phase cells. Our results showed that virulence-related gene expression levels from the deletion mutants were elevated (15/15 genes from ⊿LMOf2365_1877 and 7/15 genes from ⊿LMOf2365_1875) compared to the wild type LMOf2365, suggesting that ABC transporters may negatively regulate virulence gene expression under specific conditions. The expression level of the stress-related gene, clpE, also was increased in both deletion mutants, indicating the involvement of ABC transporters in the stress response. Taken together, our findings suggest that ABC transporters may be used as potential targets to develop new therapeutic strategies to control L. monocytogenes.

The gold standard method for serotyping Escherichia coli has relied on antisera-based typing of the O- and H-antigens, which is labor intensive and often unreliable. In the post-genomic era, sequence-based assays are potentially faster to provide results, could combine O-serogrouping and H-typing in a single test, and could simultaneously screen for the presence of other genetic markers of interest such as virulence factors. Whole genome sequencing is one approach; however, this method has limited multiplexing capabilities, and only a small fraction of the sequence is informative for subtyping or identifying virulence potential. A targeted, sequence-based assay and accompanying software for data analysis would be a great improvement over the currently available methods for serotyping. The purpose of this study was to develop a high-throughput, molecular method for serotyping E. coli by sequencing the genes that are required for production of O- and H-antigens, as well as to develop software for data analysis and serotype identification. To expand the utility of the assay, targets for the virulence factors, Shiga toxins (stx1, and stx2) and intimin (eae) were included. To validate the assay, genomic DNA was extracted from O-serogroup and H-type standard strains and from Shiga toxin-producing E. coli, the targeted regions were amplified, and then sequencing libraries were prepared from the amplified products followed by sequencing of the libraries on the Ion S5™ sequencer. The resulting sequence files were analyzed via the SeroType Caller™ software for identification of O-serogroup, H-type, and presence of stx1, stx2, and eae. We successfully identified 169 O-serogroups and 41 H-types. The assay also routinely detected the presence of stx1a,c,d (3 of 3 strains), stx2c−e,g (8 of 8 strains), stx2f (1 strain), and eae (6 of 6 strains). Taken together, the high-throughput, sequence-based method presented here is a reliable alternative to antisera-based serotyping methods for E. coli.

Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a student model that can both evaluate learning as well inform relevant feedback. Building such a model for interactive simulations is especially challenging because the exploratory nature of the interaction makes it hard to know a priori which behaviors are conducive to learning. To address this problem, in this paper we leverage the student modeling framework proposed in (Kardan and Conati, 2011) to specifically address the challenge of modeling students in interactive simulations. The framework has already been successfully applied to build a student model and to give adaptive interventions for an interactive simulation for constraint satisfaction. We seek to investigate the generality of the framework by building student models for a more complex simulation on electric circuits called Circuit Construction Kit (CCK). We evaluate alternative representations of logged interaction data with CCK, capturing different amounts of granularity and feature engineering. We then apply the student modeling framework proposed in (Kardan and Conati, 2011) to group students based on their interaction behaviors, map these behaviors into learning outcomes and leverage the resulting clusters to classify new learners. Data collected from 100 college students working with the CCK simulation indicates that the proposed framework is able to successfully classify students in groups of high and low learners and identify patterns of productive behaviors that are common across representations that can inform real-time feedback. In addition to presenting these results, we discuss trade-offs between levels of granularity and feature engineering in the tested interaction representations in terms of their ability to evaluate learning, classify students, and inform feedback.

Aging is a well-recognized risk factor for the development of cancer. The incidence of new cancer diagnoses has increased globally given the rising senior population. Many hypotheses for this increased risk have been postulated over decades, including increased genetic and epigenetic mutations and the concept of immunosenescence. The optimal treatment strategies for this population with cancer are unclear. Older cancer patients are traditionally under-represented in clinical trials developed to set the standard of care, leading to undertreatment or increased toxicity. With this background, it is crucial to investigate new opportunities that belong to the most recent findings of an anti-cancer agent, such as immune-checkpoint inhibitors, to manage these daily clinical issues and eventually combine them with alternative administration strategies of antiblastic drugs such as metronomic chemotherapy.

Shiga toxins 1 and 2 (Stx1 and Stx2) from Shiga toxin-producing E. coli (STEC) bacteria were simultaneously detected with a newly developed, high-throughput antibody microarray platform. The proteinaceous toxins were immobilized and sandwiched between biorecognition elements (monoclonal antibodies) and pooled horseradish peroxidase (HRP)-conjugated monoclonal antibodies. Following the reaction of HRP with the precipitating chromogenic substrate (metal enhanced 3,3-diaminobenzidine tetrahydrochloride or DAB), the formation of a colored product was quantitatively measured with an inexpensive flatbed page scanner. The colorimetric ELISA microarray was demonstrated to detect Stx1 and Stx2 at levels as low as ~4.5 ng/mL within ~2 h of total assay time with a narrow linear dynamic range of ~1–2 orders of magnitude and saturation levels well above background. Stx1 and/or Stx2 produced by various strains of STEC were also detected following the treatment of cultured cells with mitomycin C (a toxin-inducing antibiotic) and/or B-PER (a cell-disrupting, protein extraction reagent). Semi-quantitative detection of Shiga toxins was demonstrated to be sporadic among various STEC strains following incubation with mitomycin C; however, further reaction with B-PER generally resulted in the detection of or increased detection of Stx1, relative to Stx2, produced by STECs inoculated into either axenic broth culture or culture broth containing ground beef.

Many rapid methods have been developed for screening foods for the presence of pathogenic microorganisms. Rapid methods that have the additional ability to identify microorganisms via multiplexed immunological recognition have the potential for classification or typing of microbial contaminants thus facilitating epidemiological investigations that aim to identify outbreaks and trace back the contamination to its source. This manuscript introduces a novel, high throughput typing platform that employs microarrayed multiwell plate substrates and laser-induced fluorescence of the nucleic acid intercalating dye/stain SYBR Gold for detection of antibody-captured bacteria. The aim of this study was to use this platform for comparison of different sets of antibodies raised against the same pathogens as well as demonstrate its potential effectiveness for serotyping. To that end, two sets of antibodies raised against each of the “Big Six” non-O157 Shiga toxin-producing E. coli (STEC) as well as E. coli O157:H7 were array-printed into microtiter plates, and serial dilutions of the bacteria were added and subsequently detected. Though antibody specificity was not sufficient for the development of an STEC serotyping method, the STEC antibody sets performed reasonably well exhibiting that specificity increased at lower capture antibody concentrations or, conversely, at lower bacterial target concentrations. The favorable results indicated that with sufficiently selective and ideally concentrated sets of biorecognition elements (e.g., antibodies or aptamers), this high-throughput platform can be used to rapidly type microbial isolates derived from food samples within ca. 80 min of total assay time. It can also potentially be used to detect the pathogens from food enrichments and at least serve as a platform for testing antibodies.

The population dynamics of Escherichia coli (E. coli) introduced at various levels on wounded apple tissue, in apple juice and in apple cider was investigated. The study seeks to clarify if human illness is caused by eating fruits with a sufficient amount of enterohemorrhagic E. coli or if the risk of human illness increases when low initial levels of the bacterium deposited on the fruit begin to reproduce. The ability of fruit flies to transmit E. coli on wounded apples was also studied.

Shiga toxin-producing Escherichia coli isolates from two 2006 outbreaks are compared to other O157:H7 isolates for their virulence genotype, biofilm formation and stress responses. The studies have also demonstrated a cooperative biofilm formation involving an Escherichia coli O157:H7 strain and a non-O157:H7 strain.