Molecular Epidemiology and Antimicrobial Resistance of Clostridioides difficile in Hospitalized Patients From Mexico

Clostridioides difficile is a global public health problem, which is a primary cause of antibiotic-associated diarrhea in humans. The emergence of hypervirulent and antibiotic-resistant strains is associated with the increased incidence and severity of the disease. There are limited studies on genomic characterization of C. difficile in Latin America. We aimed to learn about the molecular epidemiology and antimicrobial resistance in C. difficile strains from adults and children in hospitals of México. We studied 94 C. difficile isolates from seven hospitals in Mexico City from 2014 to 2018. Whole-genome sequencing (WGS) was used to determine the genotype and examine the toxigenic profiles. Susceptibility to antibiotics was determined by E-test. Multilocus sequence typing (MLST) was used to determine allelic profiles. Results identified 20 different sequence types (ST) in the 94 isolates, mostly clade 2 and clade 1. ST1 was predominant in isolates from adult and children. Toxigenic strains comprised 87.2% of the isolates that were combinations of tcdAB and cdtAB (tcdA+/tcdB+/cdtA+/cdtB+, followed by tcdA+/tcdB+/cdtA-/cdtB-, tcdA-/tcdB+/cdtA-/ cdtB-, and tcdA-/tcdB-/cdtA+/cdtB+). Toxin profiles were more diverse in isolates from children. All 94 isolates were susceptible to metronidazole and vancomycin, whereas a considerable number of isolates were resistant to clindamycin, fluroquinolones, rifampicin, meropenem, and linezolid. Multidrug-resistant isolates (≥3 antibiotics) comprised 65% of the isolates. The correlation between resistant genotypes and phenotypes was evaluated by the kappa test. Mutations in rpoB and rpoC showed moderate concordance with resistance to rifampicin and mutations in fusA substantial concordance with fusidic acid resistance. cfrE, a gene recently described in one Mexican isolate, was present in 65% of strains linezolid resistant, all ST1 organisms. WGS is a powerful tool to genotype and characterize virulence and antibiotic susceptibility patterns.

Identification of Nitrogen Fixation Genes in Lactococcus Isolated from Maize Using Population Genomics and Machine Learning

Sierra Mixe maize is a landrace variety from Oaxaca, Mexico, that utilizes nitrogen derived from the atmosphere via an undefined nitrogen fixation mechanism. The diazotrophic microbiota associated with the plant’s mucilaginous aerial root exudate composed of complex carbohydrates was previously identified and characterized by our group where we found 23 lactococci capable of biological nitrogen fixation (BNF) without containing any of the proposed essential genes for this trait (nifHDKENB). To determine the genes in Lactococcus associated with this phenotype, we selected 70 lactococci from the dairy industry that are not known to be diazotrophic to conduct a comparative population genomic analysis. This showed that the diazotrophic lactococcal genomes were distinctly different from the dairy isolates. Examining the pangenome followed by genome-wide association study and machine learning identified genes with the functions needed for BNF in the maize isolates that were absent from the dairy isolates. Many of the putative genes received an ‘unknown’ annotation, which led to the domain analysis of the 135 homologs. This revealed genes with molecular functions needed for BNF, including mucilage carbohydrate catabolism, glycan-mediated host adhesion, iron/siderophore utilization, and oxidation/reduction control. This is the first report of this pathway in this organism to underpin BNF. Consequently, we proposed a model needed for BNF in lactococci that plausibly accounts for BNF in the absence of the nif operon in this organism.

Diazotrophic bacteria from maize exhibit multifaceted plant growth promotion traits in multiple hosts

Sierra Mixe maize is a geographically remote landrace variety grown on nitrogen-deficient fields in Oaxaca, Mexico that meets its nutritional requirements without synthetic fertilizer by associating with free-living diazotrophs comprising the microbiota of its aerial root mucilage. We selected nearly 500 diazotrophic (N2-fixing) bacteria isolated from Sierra Mixe maize mucilage and sequenced their genomes. Comparative genomic analysis demonstrated that isolates represented diverse genera and composed three major diazotrophic groups based on nitrogen fixation gene content. In addition to nitrogen fixation, we examined deamination of 1-amino-1-cyclopropanecarboxylic acid, biosynthesis of indole-3-acetic acid, and phosphate solubilization as alternative mechanisms of direct plant growth promotion (PGP). Genome mining showed that isolates of all diazotrophic groups possessed marker genes for multiple mechanisms of direct plant growth promotion (PGP). Implementing in vitro assays corroborated isolate genotypes by measuring each isolate's potential to confer the targeted PGP traits and revealed phenotypic variation among isolates based on diazotrophic group assignment. Investigating the ability of mucilage diazotrophs to confer PGP by direct inoculation of clonally propagated potato plants in planta led to the identification of 16 bio-stimulant candidates. Conducting nitrogen-stress greenhouse experiments demonstrated that potato inoculation with a synthetic community of bio-stimulant candidates, as well as with its individual components, resulted in PGP phenotypes. We further demonstrated that one diazotrophic isolate conferred PGP to a conventional maize variety under nitrogen-stress in the greenhouse. These results indicate that, while many diazotrophic isolates from Sierra Mixe maize possessed genotypes and in vitro phenotypes for targeted PGP traits, a subset of these organisms promoted the growth of potato and conventional maize, potentially through the use of multiple promotion mechanisms.

Biological Machine Learning Combined with Campylobacter Population Genomics Reveals Virulence Gene Allelic Variants Cause Disease

Highly dimensional data generated from bacterial whole-genome sequencing is providing an unprecedented scale of information that requires an appropriate statistical analysis framework to infer biological function from populations of genomes. The application of genome-wide association study (GWAS) methods is an appropriate framework for bacterial population genome analysis that yields a list of candidate genes associated with a phenotype, but it provides an unranked measure of importance. Here, we validated a novel framework to define infection mechanism using the combination of GWAS, machine learning, and bacterial population genomics that ranked allelic variants that accurately identified disease. This approach parsed a dataset of 1.2 million single nucleotide polymorphisms (SNPs) and indels that resulted in an importance ranked list of associated alleles of porA in Campylobacter jejuni using spatiotemporal analysis over 30 years. We validated this approach using previously proven laboratory experimental alleles from an in vivo guinea pig abortion model. This framework, termed µPathML, defined intestinal and extraintestinal groups that have differential allelic porA variants that cause abortion. Divergent variants containing indels that defeated automated annotation were rescued using biological context and knowledge that resulted in defining rare, divergent variants that were maintained in the population over two continents and 30 years. This study defines the capability of machine learning coupled with GWAS and population genomics to simultaneously identify and rank alleles to define their role in infectious disease mechanisms.

Insular Microbiogeography: Three Pathogens as Exemplars

Traditional taxonomy in biology assumes that life is organized in a simple tree. Attempts to classify microorganisms in this way in the genomics era led microbiologists to look for finite sets of 'core' genes that uniquely group taxa as clades in the tree. However, the diversity revealed by large-scale whole genome sequencing is calling into question the long-held model of a hierarchical tree of life, which leads to questioning of the definition of a species. Large-scale studies of microbial genome diversity reveal that the cumulative number of new genes discovered increases with the number of genomes studied as a power law and subsequently leads to the lack of evidence for a unique core genome within closely related organisms. Sampling 'enough' new genomes leads to the discovery of a replacement or alternative to any gene. This power law behaviour points to an underlying self-organizing critical process that may be guided by mutation and niche selection. Microbes in any particular niche exist within a local web of organism interdependence known as the microbiome. The same mechanism that underpins the macro-ecological scaling first observed by MacArthur and Wilson also applies to microbial communities. Recent metagenomic studies of a food microbiome demonstrate the diverse distribution of community members, but also genotypes for a single species within a more complex community. Collectively, these results suggest that traditional taxonomic classification of bacteria could be replaced with a quasispecies model. This model is commonly accepted in virology and better describes the diversity and dynamic exchange of genes that also hold true for bacteria. This model will enable microbiologists to conduct population-scale studies to describe microbial behaviour, as opposed to a single isolate as a representative.

Nitrogen fixation in a landrace of maize is supported by a mucilage-associated diazotrophic microbiota

Plants are associated with a complex microbiota that contributes to nutrient acquisition, plant growth, and plant defense. Nitrogen-fixing microbial associations are efficient and well characterized in legumes but are limited in cereals, including maize. We studied an indigenous landrace of maize grown in nitrogen-depleted soils in the Sierra Mixe region of Oaxaca, Mexico. This landrace is characterized by the extensive development of aerial roots that secrete a carbohydrate-rich mucilage. Analysis of the mucilage microbiota indicated that it was enriched in taxa for which many known species are diazotrophic, was enriched for homologs of genes encoding nitrogenase subunits, and harbored active nitrogenase activity as assessed by acetylene reduction and ¹⁵N₂ incorporation assays. Field experiments in Sierra Mixe using ¹⁵N natural abundance or ¹⁵N-enrichment assessments over 5 years indicated that atmospheric nitrogen fixation contributed 29%–82% of the nitrogen nutrition of Sierra Mixe maize.

Nitrogen is an essential nutrient for plants, and for many nonlegume crops, the requirement for nitrogen is primarily met by the use of inorganic fertilizers. These fertilizers are produced from fossil fuel by energy-intensive processes that are estimated to use 1% to 2% of the total global energy supply and produce an equivalent share of greenhouse gases. Because maize (Zea mays L.) is a significant recipient of nitrogen fertilization, a research goal for decades has been to identify or engineer mechanisms for biological fixation of atmospheric nitrogen in association with this crop. We hypothesized that isolated indigenous landraces of maize grown using traditional practices with little or no fertilizer might have evolved strategies to improve plant performance under low-nitrogen nutrient conditions. Here, we show that for one such maize landrace grown in nitrogen-depleted fields near Oaxaca, Mexico, 29%–82% of the plant nitrogen is derived from atmospheric nitrogen. High levels of nitrogen fixation are supported, at least in part, by the abundant production of a sugar-rich mucilage associated with aerial roots that provides a home to a complex nitrogen-fixing microbiome.

Whole Cell Cross-Linking to Discover Host-Microbe Protein Cognate Receptor/Ligand Pairs

Bacterial surface ligands mediate interactions with the host cell during association that determines the specific outcome for the host–microbe association. The association begins with receptors on the host cell binding ligands on the microbial cell to form a partnership that initiates responses in both cells. Methods to determine the specific cognate partnerships are lacking. Determining these molecular interactions between the host and microbial surfaces are difficult, yet crucial in defining biologically important events that are triggered during association of the microbiome, and critical in defining the initiating signal from the host membrane that results in pathology or commensal association. In this study, we designed an approach to discover cognate host–microbe receptor/ligand pairs using a covalent cross-linking strategy with whole cells. Protein/protein cross-linking occurred when the interacting molecules were within 9–12 Å, allowing for identification of specific pairs of proteins from the host and microbe that define the molecular interaction during association. To validate the method three different bacteria with three previously known protein/protein partnerships were examined. The exact interactions were confirmed and led to discovery of additional partnerships that were not recognized as cognate partners, but were previously reported to be involved in bacterial interactions. Additionally, three unknown receptor/ligand partners were discovered and validated with in vitro infection assays by blocking the putative host receptor and deleting the bacterial ligand. Subsequently, Salmonella enterica sv. Typhimurium was cross-linked to differentiated colonic epithelial cells (caco-2) to discover four previously unknown host receptors bound to three previously undefined host ligands for Salmonella. This approach resulted in a priori discovery of previously unknown and biologically important molecules for host/microbe association that were casually reported to mediate bacterial invasion. The whole cell cross-linking approach promises to enable discovery of possible targets to modulate interaction of the microbiome with the host that are important in infection and commensalism, both of with initiate a host response.

Comparative analysis of Campylobacter isolates from wild birds and chickens using MALDI-TOF MS, biochemical testing, and DNA sequencing

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was compared to conventional biochemical testing methods and nucleic acid analyses (16S rDNA sequencing, hippurate hydrolysis gene testing, whole genome sequencing [WGS]) for species identification of Campylobacter isolates obtained from chickens ( Gallus gallus domesticus, n = 8), American crows ( Corvus brachyrhynchos, n = 17), a mallard duck ( Anas platyrhynchos, n = 1), and a western scrub-jay ( Aphelocoma californica, n = 1). The test results for all 27 isolates were in 100% agreement between MALDI-TOF MS, the combined results of 16S rDNA sequencing, and the hippurate hydrolysis gene PCR ( p = 0.0027, kappa = 1). Likewise, the identifications derived from WGS from a subset of 14 isolates were in 100% agreement with the MALDI-TOF MS identification. In contrast, biochemical testing misclassified 5 isolates of C. jejuni as C. coli, and 16S rDNA sequencing alone was not able to differentiate between C. coli and C. jejuni for 11 sequences ( p = 0.1573, kappa = 0.0857) when compared to MALDI-TOF MS and WGS. No agreement was observed between MALDI-TOF MS dendrograms and the phylogenetic relationships revealed by rDNA sequencing or WGS. Our results confirm that MALDI-TOF MS is a fast and reliable method for identifying Campylobacter isolates to the species level from wild birds and chickens, but not for elucidating phylogenetic relationships among Campylobacter isolates.

Exhaled breath condensate methods adapted from human studies using longitudinal metabolomics for predicting early health alterations in dolphins

Monitoring health conditions is essential to detect early asymptomatic stages of a disease. To achieve this, blood, urine and breath samples are commonly used as a routine clinical diagnostic. These samples offer the opportunity to detect specific metabolites related to diseases and provide a better understanding of their development. Although blood samples are commonly used routinely to monitor health, the implementation of a relatively noninvasive technique, such as exhaled breath condensate (EBC) analysis, may further benefit the well-being of both humans and other animals. EBC analysis can be used to track possible physical or biochemical alterations caused by common diseases of the bottlenose dolphin (Tursiops truncatus), such as infections or inflammatory-mediated processes. We have used an untargeted metabolomic method with liquid chromatography-mass spectrometry analysis of EBC samples to determine biomarkers related to disease development. In this study, five dolphins under human care were followed up for 1 year. We collected paired blood, physical examination information, and EBC samples. We then statistically correlated this information to predict specific health alterations. Three dolphins provided promising case study information about biomarkers related to cutaneous infections, respiratory infections, dental disease, or hormonal changes (pregnancy). The use of complementary liquid chromatography platforms, with hydrophilic interaction chromatography and reverse-phased columns, allowed us to detect a wide spectrum of EBC biomarker compounds that could be related to these health alterations. Moreover, these two analytical techniques not only provided complementary metabolite information but in both cases they also provided promising diagnostic information for these health conditions. Graphical abstract Collection of the exhaled condensed breath from a bottlenose dolphin from U.S. Navy Marine Mammal Program (MMP).

SigTree: A Microbial Community Analysis Tool to Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree

Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree, a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.

Analytical methodologies for broad metabolite coverage of exhaled breath condensate

Breath analysis has been gaining popularity as a non-invasive technique that is amenable to a broad range of medical uses. One of the persistent problems hampering the wide application of the breath analysis method is measurement variability of metabolite abundances stemming from differences in both sampling and analysis methodologies used in various studies. Mass spectrometry has been a method of choice for comprehensive metabolomic analysis. For the first time in the present study, we juxtapose the most commonly employed mass spectrometry-based analysis methodologies and directly compare the resultant coverages of detected compounds in exhaled breath condensate in order to guide methodology choices for exhaled breath condensate analysis studies. Four methods were explored to broaden the range of measured compounds across both the volatile and non-volatile domain. Liquid phase sampling with polyacrylate Solid-Phase MicroExtraction fiber, liquid phase extraction with a polydimethylsiloxane patch, and headspace sampling using Carboxen/Polydimethylsiloxane Solid-Phase MicroExtraction (SPME) followed by gas chromatography mass spectrometry were tested for the analysis of volatile fraction. Hydrophilic interaction liquid chromatography and reversed-phase chromatography high performance liquid chromatography mass spectrometry were used for analysis of non-volatile fraction. We found that liquid phase breath condensate extraction was notably superior compared to headspace extraction and differences in employed sorbents manifested altered metabolite coverages. The most pronounced effect was substantially enhanced metabolite capture for larger, higher-boiling compounds using polyacrylate SPME liquid phase sampling. The analysis of the non-volatile fraction of breath condensate by hydrophilic and reverse phase high performance liquid chromatography mass spectrometry indicated orthogonal metabolite coverage by these chromatography modes. We found that the metabolite coverage could be enhanced significantly with the use of organic solvent as a device rinse after breath sampling to collect the non-aqueous fraction as opposed to neat breath condensate sample. Here, we show the detected ranges of compounds in each case and provide a practical guide for methodology selection for optimal detection of specific compounds.

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

Automation of PacBio SMRTbell NGS library preparation for bacterial genome sequencing

Background

The PacBio RS II provides for single molecule, real-time DNA technology to sequence genomes and detect DNA modifications. The starting point for high-quality sequence production is high molecular weight genomic DNA. To automate the library preparation process, there must be high-throughput methods in place to assess the genomic DNA, to ensure the size and amounts of the sheared DNA fragments and final library.

Findings

The library construction automation was accomplished using the Agilent NGS workstation with Bravo accessories for heating, shaking, cooling, and magnetic bead manipulations for template purification.

The quality control methods from gDNA input to final library using the Agilent Bioanalyzer System and Agilent TapeStation System were evaluated.

Conclusions

Automated protocols of PacBio 10 kb library preparation produced libraries with similar technical performance to those generated manually. The TapeStation System proved to be a reliable method that could be used in a 96-well plate format to QC the DNA equivalent to the standard Bioanalyzer System results. The DNA Integrity Number that is calculated in the TapeStation System software upon analysis of genomic DNA is quite helpful to assure that the starting genomic DNA is not degraded. In this respect, the gDNA assay on the TapeStation System is preferable to the DNA 12000 assay on the Bioanalyzer System, which cannot run genomic DNA, nor can the Bioanalyzer work directly from the 96-well plates.

Fallacy of the Unique Genome: Sequence Diversity within Single Helicobacter pylori Strains

Many bacterial genomes are highly variable but nonetheless are typically published as a single assembled genome. Experiments tracking bacterial genome evolution have not looked at the variation present at a given point in time. Here, we analyzed the mouse-passaged Helicobacter pylori strain SS1 and its parent PMSS1 to assess intra- and intergenomic variability. Using high sequence coverage depth and experimental validation, we detected extensive genome plasticity within these H. pylori isolates, including movement of the transposable element IS607, large and small inversions, multiple single nucleotide polymorphisms, and variation in cagA copy number. The cagA gene was found as 1 to 4 tandem copies located off the cag island in both SS1 and PMSS1; this copy number variation correlated with protein expression. To gain insight into the changes that occurred during mouse adaptation, we also compared SS1 and PMSS1 and observed 46 differences that were distinct from the within-genome variation. The most substantial was an insertion in cagY, which encodes a protein required for a type IV secretion system function. We detected modifications in genes coding for two proteins known to affect mouse colonization, the HpaA neuraminyllactose-binding protein and the FutB α-1,3 lipopolysaccharide (LPS) fucosyltransferase, as well as genes predicted to modulate diverse properties. In sum, our work suggests that data from consensus genome assemblies from single colonies may be misleading by failing to represent the variability present. Furthermore, we show that high-depth genomic sequencing data of a population can be analyzed to gain insight into the normal variation within bacterial strains.IMPORTANCE Although it is well known that many bacterial genomes are highly variable, it is nonetheless traditional to refer to, analyze, and publish "the genome" of a bacterial strain. Variability is usually reduced ("only sequence from a single colony"), ignored ("just publish the consensus"), or placed in the "too-hard" basket ("analysis of raw read data is more robust"). Now that whole-genome sequences are regularly used to assess virulence and track outbreaks, a better understanding of the baseline genomic variation present within single strains is needed. Here, we describe the variability seen in typical working stocks and colonies of pathogen Helicobacter pylori model strains SS1 and PMSS1 as revealed by use of high-coverage mate pair next-generation sequencing (NGS) and confirmed by traditional laboratory techniques. This work demonstrates that reliance on a consensus assembly as "the genome" of a bacterial strain may be misleading.

Human breath metabolomics using an optimized non-invasive exhaled breath condensate sampler

Exhaled breath condensate (EBC) analysis is a developing field with tremendous promise to advance personalized, non-invasive health diagnostics as new analytical instrumentation platforms and detection methods are developed. Multiple commercially-available and researcher-built experimental samplers are reported in the literature. However, there is very limited information available to determine an effective breath sampling approach, especially regarding the dependence of breath sample metabolomic content on the collection device design and sampling methodology. This lack of an optimal standard procedure results in a range of reported results that are sometimes contradictory. Here, we present a design of a portable human EBC sampler optimized for collection and preservation of the rich metabolomic content of breath. The performance of the engineered device is compared to two commercially available breath collection devices: the RTube^™ and TurboDECCS. A number of design and performance parameters are considered, including: condenser temperature stability during sampling, collection efficiency, condenser material choice, and saliva contamination in the collected breath samples. The significance of the biological content of breath samples, collected with each device, is evaluated with a set of mass spectrometry methods and was the primary factor for evaluating device performance. The design includes an adjustable mass-size threshold for aerodynamic filtering of saliva droplets from the breath flow. Engineering an inexpensive device that allows efficient collection of metalomic-rich breath samples is intended to aid further advancement in the field of breath analysis for non-invasive health diagnostic. EBC sampling from human volunteers was performed under UC Davis IRB protocol 63701-3 (09/30/2014-07/07/2017).

Salmonella Typhimurium Enzymatically Landscapes the Host Intestinal Epithelial Cell (IEC) Surface Glycome to Increase Invasion

Although gut host-pathogen interactions are glycan-mediated processes, few details are known about the participating structures. Here we employ high-resolution mass spectrometric profiling to comprehensively identify and quantitatively measure the exact modifications of native intestinal epithelial cell surface N-glycans induced by S. typhimurium infection. Sixty minutes postinfection, select sialylated structures showed decreases in terms of total number and abundances. To assess the effect of cell surface mannosylation, we selectively rerouted glycan expression on the host using the alpha-mannosidase inhibitor, kifunensine, toward overexpression of high mannose. Under these conditions, internalization of S. typhimurium significantly increased, demonstrating that bacteria show preference for particular structures. Finally, we developed a novel assay to measure membrane glycoprotein turnover rates, which revealed that glycan modifications occur by bacterial enzyme activity rather than by host-derived restructuring strategies. This study is the first to provide precise structural information on how host N-glycans are altered to support S. typhimurium invasion.

Enhanced non-invasive respiratory sampling from bottlenose dolphins for breath metabolomics measurements

Chemical analysis of exhaled breath metabolites is an emerging alternative to traditional clinical testing for many physiological conditions. The main advantage of breath analysis is its inherent non-invasive nature and ease of sample collection. Therefore, there exists a great interest in further development of this method for both humans and animals. The physiology of cetaceans is exceptionally well suited for breath analysis due to their explosive breathing behavior and respiratory tract morphology. At the present time, breath analysis in cetaceans has very limited practical applications, in large part due to lack of widely adopted sampling device(s) and methodologies that are well-standardized. Here, we present an optimized design and the operating principles of a portable apparatus for reproducible collection of exhaled breath condensate from small cetaceans, such as bottlenose dolphins (Tursiops truncatus). The device design is optimized to meet two criteria: standardized collection and preservation of information-rich metabolomic content of the biological sample, and animal comfort and ease of breath sample collection. The intent is to furnish a fully-benchmarked technology that can be widely adopted by researchers and conservationists to spur further developments of breath analysis applications for marine mammal health assessments.

Gut microbiota-produced succinate promotes C. difficile infection after antibiotic treatment or motility disturbance

Clostridium difficile is a leading cause of antibiotic-associated diarrhea. The mechanisms underlying C. difficile expansion after microbiota disturbance are just emerging. We assessed the gene expression profile of C. difficile within the intestine of gnotobiotic mice to identify genes regulated in response to either dietary or microbiota compositional changes. In the presence of the gut symbiont Bacteroides thetaiotaomicron, C. difficile induces a pathway that metabolizes the microbiota fermentation end-product succinate to butyrate. The low concentration of succinate present in the microbiota of conventional mice is transiently elevated upon antibiotic treatment or chemically induced intestinal motility disturbance, and C. difficile exploits this succinate spike to expand in the perturbed intestine. A C. difficile mutant compromised in succinate utilization is at a competitive disadvantage during these perturbations. Understanding the metabolic mechanisms involved in microbiota-C. difficile interactions may help to identify approaches for the treatment and prevention of C. difficile-associated diseases.

Genomic epidemiology of Salmonella enterica serotype Enteritidis based on population structure of prevalent lineages

Major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s.

Salmonella enterica serotype Enteritidis is one of the most commonly reported causes of human salmonellosis. Its low genetic diversity, measured by fingerprinting methods, has made subtyping a challenge. We used whole-genome sequencing to characterize 125 S. enterica Enteritidis and 3 S. enterica serotype Nitra strains. Single-nucleotide polymorphisms were filtered to identify 4,887 reliable loci that distinguished all isolates from each other. Our whole-genome single-nucleotide polymorphism typing approach was robust for S. enterica Enteritidis subtyping with combined data for different strains from 2 different sequencing platforms. Five major genetic lineages were recognized, which revealed possible patterns of geographic and epidemiologic distribution. Analyses on the population dynamics and evolutionary history estimated that major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s.

Complete Genome Sequences of a Clinical Isolate and an Environmental Isolate of Vibrio parahaemolyticus

Vibrio parahaemolyticus is the leading cause of seafood-borne infections in the United States. We report complete genome sequences for two V. parahaemolyticus strains isolated in 2007, CDC_K4557 and FDA_R31 of clinical and oyster origin, respectively. These two sequences might assist in the investigation of differential virulence of this organism.

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction

Background

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism’s genome as a database restricts metabolite identification to only those compounds that the organism can produce.

Results

To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment’s MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis.

Conclusions

Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

Gastrointestinal microbes interact with canine adipose-derived mesenchymal stem cells in vitro and enhance immunomodulatory functions

Mesenchymal stem cells (MSCs) are somatic, multipotent stromal cells with potent immunomodulatory and regenerative properties. Although MSCs have pattern recognition receptors and are modulated by Toll-like receptor ligands, MSC-microbial interactions are poorly defined. The objectives of this study were to determine the effect of bacterial association on MSC function. We hypothesized that gastrointestinal bacteria associate with MSCs and alter their immunomodulatory properties. The effect of MSC-microbial interactions on MSC morphology, viability, proliferation, migration, and immunomodulatory functions was investigated. MSCs associated with a remarkable array of enteric pathogens and commensal bacteria. MSC interactions with two model organisms, the pathogen Salmonella typhimurium and the probiotic Lactobacillus acidophilus, were further investigated. While ST readily invaded MSCs, LB adhered to the MSC plasma membrane. Neither microbe induced MSC death, degeneration, or diminished proliferation. Microbial association did not upregulate MHC-II, CD80/86, or CD1 expression. MSC-microbial interaction significantly increased transcription of key immunomodulatory genes, including COX2, IL6, and IL8, coupled with significantly increased prostaglandin E2 (PGE2), interleukin (IL)6, and IL8 secretion. MSC-ST coincubation resulted in increased MSC expression of CD54, and significant augmentation of MSC inhibition of mitogen-induced T-cell proliferation. T-cell proliferation was partially restored when PGE2 secretion was blocked from ST-primed MSCs. MSC-microbe interactions have a profound effect on MSC function and may be pivotal in a variety of clinical settings where MSCs are being explored as potential therapeutics in the context of microbial communities, such as Crohn's disease, chronic nonhealing wounds, and sepsis.

Exploring bacterial epigenomics in the next-generation sequencing era: a new approach for an emerging frontier

Epigenetics has an important role for the success of foodborne pathogen persistence in diverse host niches. Substantial challenges exist in determining DNA methylation to situation-specific phenotypic traits. DNA modification, mediated by restriction-modification systems, functions as an immune response against antagonistic external DNA, and bacteriophage-acquired methyltransferases (MTase) and orphan MTases - those lacking the cognate restriction endonuclease - facilitate evolution of new phenotypes via gene expression modulation via DNA and RNA modifications, including methylation and phosphorothioation. Recent establishment of large-scale genome sequencing projects will result in a significant increase in genome availability that will lead to new demands for data analysis including new predictive bioinformatics approaches that can be verified with traditional scientific rigor. Sequencing technologies that detect modification coupled with mass spectrometry to discover new adducts is a powerful tactic to study bacterial epigenetics, which is poised to make novel and far-reaching discoveries that link biological significance and the bacterial epigenome.

Cross-talk between E. coli strains and a human colorectal adenocarcinoma-derived cell line

Although there is great interest in the specific mechanisms of how gut microbiota modulate the biological processes of the human host, the extent of host-microbe interactions and the bacteria-specific metabolic activities for survival in the co-evolved gastrointestinal environment remain unclear. Here, we demonstrate a comprehensive comparison of the host epithelial response induced by either a pathogenic or commensal strain of Escherichia coli using a multi-omics approach. We show that Caco-2 cells incubated with E. coli display an activation of defense response genes associated with oxidative stress. Indeed, in the bacteria co-culture system, the host cells experience an altered environment compared with the germ-free system that includes reduced pH, depletion of major energy substrates, and accumulation of fermentation by-products. Measurement of intracellular Caco-2 cell metabolites revealed a significantly increased lactate concentration, as well as changes in TCA cycle intermediates. Our results will lead to a deeper understanding of acute microbial-host interactions.

Insulin receptor substrate signaling suppresses neonatal autophagy in the heart

The induction of autophagy in the mammalian heart during the perinatal period is an essential adaptation required to survive early neonatal starvation; however, the mechanisms that mediate autophagy suppression once feeding is established are not known. Insulin signaling in the heart is transduced via insulin and IGF-1 receptors (IGF-1Rs). We disrupted insulin and IGF-1R signaling by generating mice with combined cardiomyocyte-specific deletion of Irs1 and Irs2. Here we show that loss of IRS signaling prevented the physiological suppression of autophagy that normally parallels the postnatal increase in circulating insulin. This resulted in unrestrained autophagy in cardiomyocytes, which contributed to myocyte loss, heart failure, and premature death. This process was ameliorated either by activation of mTOR with aa supplementation or by genetic suppression of autophagic activation. Loss of IRS1 and IRS2 signaling also increased apoptosis and precipitated mitochondrial dysfunction, which were not reduced when autophagic flux was normalized. Together, these data indicate that in addition to prosurvival signaling, insulin action in early life mediates the physiological postnatal suppression of autophagy, thereby linking nutrient sensing to postnatal cardiac development.