Negative binomial mixed models for analyzing microbiome count data.

BACKGROUND: Recent advances in next-generation sequencing (NGS) technology enable researchers to collect a large volume of metagenomic sequencing data. These data provide valuable resources for investigating interactions between the microbiome and host environmental/clinical factors. In addition to the well-known properties of microbiome count measurements, for example, varied total sequence reads across samples, over-dispersion and zero-inflation, microbiome studies usually collect samples with hierarchical structures, which introduce correlation among the samples and thus further complicate the analysis and interpretation of microbiome count data. RESULTS: In this article, we propose negative binomial mixed models (NBMMs) for detecting the association between the microbiome and host environmental/clinical factors for correlated microbiome count data. Although having not dealt with zero-inflation, the proposed mixed-effects models account for correlation among the samples by incorporating random effects into the commonly used fixed-effects negative binomial model, and can efficiently handle over-dispersion and varying total reads. We have developed a flexible and efficient IWLS (Iterative Weighted Least Squares) algorithm to fit the proposed NBMMs by taking advantage of the standard procedure for fitting the linear mixed models. CONCLUSIONS: We evaluate and demonstrate the proposed method via extensive simulation studies and the application to mouse gut microbiome data. The results show that the proposed method has desirable properties and outperform the previously used methods in terms of both empirical power and Type I error. The method has been incorporated into the freely available R package BhGLM ( http://www.ssg.uab.edu/bhglm/ and http://github.com/abbyyan3/BhGLM ), providing a useful tool for analyzing microbiome data.

Molecular characterization of the intestinal microbiota in patients with and without abdominal bloating.

Recent studies have demonstrated differences in the intestinal microbiota between patients with irritable bowel syndrome (IBS) and healthy controls (HC), suggesting a role for the intestinal microbiota in the pathogenesis of IBS. Alterations in the microbiota have also been implicated in the pathogenesis of abdominal bloating, a commonly reported symptom in IBS. We investigated the relationship between the intestinal microbiota, abdominal bloating, and altered bowel patterns in a cohort of patients with IBS and HC. The 16S rRNA gene from fresh fecal samples was amplified and pyrosequenced by using Roche-454 Titanium chemistry. A Core Measurable Microbiome (CMM) was generated for Operational Taxonomic Unit (OTU) detected in >75% of all samples and compositional features of CMM were compared between groups by Linear Discriminant Analysis (LDA). IBS differentiated from HC by LDA using continuous variation in the species/OTUs or the CMM genera. When subcategorized based on bloating symptoms and bowel characteristics, the same subjects were also well differentiated from one another and from HC. ANOVA analysis showed quantitative species/OTU differences between the subgroups including IBS with and without bloating, and subtypes based on bowel characteristics. The clear LDA differentiation and the significant microbial taxa differences between the groups imply a significant association of the microbiota with bloating symptoms and bowel characteristics in IBS. These changes in the microbiota may serve as a biomarker for IBS and its clinical subtypes and suggest a role for the intestinal microbiota in the pathogenesis of the main symptoms of the disorder.

Molecular characterization of host-specific biofilm formation in a vertebrate gut symbiont.

Although vertebrates harbor bacterial communities in their gastrointestinal tract whose composition is host-specific, little is known about the mechanisms by which bacterial lineages become selected. The goal of this study was to characterize the ecological processes that mediate host-specificity of the vertebrate gut symbiont Lactobacillus reuteri, and to systematically identify the bacterial factors that are involved. Experiments with monoassociated mice revealed that the ability of L. reuteri to form epithelial biofilms in the mouse forestomach is strictly dependent on the strain's host origin. To unravel the molecular basis for this host-specific biofilm formation, we applied a combination of transcriptome analysis and comparative genomics and identified eleven genes of L. reuteri 100-23 that were predicted to play a role. We then determined expression and importance of these genes during in vivo biofilm formation in monoassociated mice. This analysis revealed that six of the genes were upregulated in vivo, and that genes encoding for proteins involved in epithelial adherence, specialized protein transport, cell aggregation, environmental sensing, and cell lysis contributed to biofilm formation. Inactivation of a serine-rich surface adhesin with a devoted transport system (the SecA2-SecY2 pathway) completely abrogated biofilm formation, indicating that initial adhesion represented the most significant step in biofilm formation, likely conferring host specificity. In summary, this study established that the epithelial selection of bacterial symbionts in the vertebrate gut can be both specific and highly efficient, resulting in biofilms that are exclusively formed by the coevolved strains, and it allowed insight into the bacterial effectors of this process.

Alignment behaviors of short peptides provide a roadmap for functional profiling of metagenomic data.

BACKGROUND: Functional assignments for short-read metagenomic data pose a significant computational challenge due to perceived unpredictability of alignment behavior and the inability to infer useful functional information from translated protein-fragments/peptides. To address this problem, we have examined the predictability of short peptide alignments by systematically studying alignment behavior of large sets of short peptides generated from well-characterized proteins as well as hypothetical proteins in the KEGG database. RESULTS: Using test sets of peptides modeling the length and phylogenetic distributions of short-read metagenomic data, we observed that peptides from well-characterized proteins had indistinguishable alignments to proteins from the same orthologous family and proteins from different families. Nonetheless, the patterns contained remarkable phylogenetic and structural signals, with alignments of even very short peptides naturally restricted to their orthologous family and/or proteins having similar structural folds. In stark contrast, peptides from "hypothetical proteins" had only sparse hit patterns with low frequencies and much lower identities. By weighting the structure-driven alignments and filtering peptides with behaviors similar to those derived from "hypothetical proteins", we demonstrate that the accuracy of abundance predictions of protein families is dramatically improved. CONCLUSIONS: Evolutionary processes have dispersed protein folds across multiple protein families, precluding accurate functional assignment to short peptides, whose alignment behavior is non-random and driven by structure. Algorithms that filter sparse peptides and weight hit patterns of peptides from "known space" dramatically improve quantification of functions from diverse mixtures of peptides and should substantially improve applications of metagenomic analyses requiring accurate quantitative measures of functional families.

Microbial successions are associated with changes in chemical profiles of a model refrigerated fresh pork sausage during an 80-day shelf life study.

Fresh pork sausage is produced without a microbial kill step and therefore chilled or frozen to control microbial growth. In this report, the microbiota in a chilled fresh pork sausage model produced with or without an antimicrobial combination of sodium lactate and sodium diacetate was studied using a combination of traditional microbiological methods and deep pyrosequencing of 16S rRNA gene amplicons. In the untreated system, microbial populations rose from 10(2) to 10(6) CFU/g within 15 days of storage at 4°C, peaking at nearly 10(8) CFU/g by day 30. Pyrosequencing revealed a complex community at day 0, with taxa belonging to the Bacilli, Gammaproteobacteria, Betaproteobacteria, Actinobacteria, Bacteroidetes, and Clostridia. During storage at 4°C, the untreated system displayed a complex succession, with species of Weissella and Leuconostoc that dominate the product at day 0 being displaced by species of Pseudomonas (P. lini and P. psychrophila) within 15 days. By day 30, a second wave of taxa (Lactobacillus graminis, Carnobacterium divergens, Buttiauxella brennerae, Yersinia mollaretti, and a taxon of Serratia) dominated the population, and this succession coincided with significant chemical changes in the matrix. Treatment with lactate-diacetate altered the dynamics dramatically, yielding a monophasic growth curve of a single species of Lactobacillus (L. graminis), followed by a uniform selective die-off of the majority of species in the population. Of the six species of Lactobacillus that were routinely detected, L. graminis became the dominant member in all samples, and its origins were traced to the spice blend used in the formulation.

The evolution of host specialization in the vertebrate gut symbiont Lactobacillus reuteri.

Recent research has provided mechanistic insight into the important contributions of the gut microbiota to vertebrate biology, but questions remain about the evolutionary processes that have shaped this symbiosis. In the present study, we showed in experiments with gnotobiotic mice that the evolution of Lactobacillus reuteri with rodents resulted in the emergence of host specialization. To identify genomic events marking adaptations to the murine host, we compared the genome of the rodent isolate L. reuteri 100-23 with that of the human isolate L. reuteri F275, and we identified hundreds of genes that were specific to each strain. In order to differentiate true host-specific genome content from strain-level differences, comparative genome hybridizations were performed to query 57 L. reuteri strains originating from six different vertebrate hosts in combination with genome sequence comparisons of nine strains encompassing five phylogenetic lineages of the species. This approach revealed that rodent strains, although showing a high degree of genomic plasticity, possessed a specific genome inventory that was rare or absent in strains from other vertebrate hosts. The distinct genome content of L. reuteri lineages reflected the niche characteristics in the gastrointestinal tracts of their respective hosts, and inactivation of seven out of eight representative rodent-specific genes in L. reuteri 100-23 resulted in impaired ecological performance in the gut of mice. The comparative genomic analyses suggested fundamentally different trends of genome evolution in rodent and human L. reuteri populations, with the former possessing a large and adaptable pan-genome while the latter being subjected to a process of reductive evolution. In conclusion, this study provided experimental evidence and a molecular basis for the evolution of host specificity in a vertebrate gut symbiont, and it identified genomic events that have shaped this process.

Genomic co-localization of variation affecting agronomic and human gut microbiome traits in a meta-analysis of diverse sorghum.

Substantial functional metabolic diversity exists within species of cultivated grain crops that directly or indirectly provide more than half of all calories consumed by humans around the globe. While such diversity is the molecular currency used for improving agronomic traits, diversity is poorly characterized for its effects on human nutrition and utilization by gut microbes. Moreover, we know little about agronomic traits' potential trade-offs and pleiotropic effects on human nutritional traits. Here we applied a quantitative genetics approach using a meta-analysis and parallel genome-wide association studies of Sorghum bicolor traits describing changes in the composition and function of human gut microbe communities and any of 200 sorghum seed and agronomic traits across a diverse sorghum population to identify associated genetic variants. A total of fifteen multiple-effect loci (MEL) were initially found where different alleles in the sorghum genome produced changes in seed that affected the abundance of multiple bacterial taxa across two human microbiomes in automated in vitro fermentations. Next, parallel genome-wide studies conducted for seed, biochemical, and agronomic traits in the same population identified significant associations within the boundaries of 13/15 MEL for microbiome traits. In several instances, the co-localization of variation affecting gut microbiome and agronomic traits provided hypotheses for causal mechanisms through which variation could affect both agronomic traits and human gut microbes. This work demonstrates that genetic factors affecting agronomic traits in sorghum seed can also drive significant effects on human gut microbes, particularly bacterial taxa considered beneficial. Understanding these pleiotropic relationships will inform future strategies for crop improvement toward yield, sustainability, and human health.

Antibiotic-induced gut dysbiosis elicits gut-brain axis relevant multi-omic signatures and behavioral and neuroendocrine changes in a nonhuman primate model.

Emerging evidence indicates that antibiotic-induced dysbiosis can play an etiological role in the pathogenesis of neuropsychiatric disorders. However, most of this evidence comes from rodent models. The objective of this study was to evaluate if antibiotic-induced gut dysbiosis can elicit changes in gut metabolites and behavior indicative of gut-brain axis disruption in common marmosets (Callithrix jacchus) - a nonhuman primate model often used to study sociability and stress. We were able to successfully induce dysbiosis in marmosets using a custom antibiotic cocktail (vancomycin, enrofloxacin and neomycin) administered orally for 28 days. This gut dysbiosis altered gut metabolite profiles, behavior, and stress reactivity. Increase in gut Fusobacterium spp. post-antibiotic administration was a novel dysbiotic response and has not been observed in any rodent or human studies to date. There were significant changes in concentrations of several gut metabolites which are either neurotransmitters (e.g., GABA and serotonin) or have been found to be moderators of gut-brain axis communication in rodent models (e.g., short-chain fatty acids and bile acids). There was an increase in affiliative behavior and sociability in antibiotic-administered marmosets, which might be a coping mechanism in response to gut dysbiosis-induced stress. Increase in urinary cortisol levels after multiple stressors provides more definitive proof that this model of dysbiosis may cause disrupted communication between gut and brain in common marmosets. This study is a first attempt to establish common marmosets as a novel model to study the impact of severe gut dysbiosis on gut-brain axis cross-talk and behavior.

Increased Dietary Trp, Thr, and Met Supplementation Improves Performance, Health, and Protein Metabolism of Weaned Piglets under Mixed Management and Poor Housing Conditions.

A sanitary challenge was carried out to induce suboptimal herd health while investigating the effect of amino acids supplementation on piglet responses. Weaned piglets of high sanitary status (6.33 ± 0.91 kg of BW) were distributed in a 2 × 2 factorial arrangement into two similar facilities with contrasting sanitary conditions and two different diets. Our results suggest that increased Trp, Thr, and Met dietary supplementation could support the immune systems of piglets under a sanitary challenge. In this manner, AA+ supplementation improved the performance and metabolism of piglets under mixed management and poor sanitary conditions. No major temporal microbiome changes were associated with differences in performance regardless of sanitary conditions or diets. Since piglets often become mixed in multiple-site production systems and facility hygiene is also often neglected, this study suggests that increased Trp, Thr, and Met (AA+) dietary supplementation could contribute to mitigating the side effects of these harmful risk factors in modern pig farms.

Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors.

In vertebrates, including humans, individuals harbor gut microbial communities whose species composition and relative proportions of dominant microbial groups are tremendously varied. Although external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genome-wide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.

Salmonella enterica induces biogeography-specific changes in the gut microbiome of pigs.

Swine are a major reservoir of an array of zoonotic Salmonella enterica subsp. enterica lineage I serovars including Derby, Typhimurium, and 4,[5],12:i:- (a.k.a. Monophasic Typhimurium). In this study, we assessed the gastrointestinal (GI) microbiome composition of pigs in different intestinal compartments and the feces following infection with specific zoonotic serovars of S. enterica (S. Derby, S. Monophasic, and S. Typhimurium). 16S rRNA based microbiome analysis was performed to assess for GI microbiome changes in terms of diversity (alpha and beta), community structure and volatility, and specific taxa alterations across GI biogeography (small and large intestine, feces) and days post-infection (DPI) 2, 4, and 28; these results were compared to disease phenotypes measured as histopathological changes. As previously reported, only S. Monophasic and S. Typhimurium induced morphological alterations that marked an inflammatory milieu restricted to the large intestine in this experimental model. S. Typhimurium alone induced significant changes at the alpha- (Simpson's and Shannon's indexes) and beta-diversity levels, specifically at the peak of inflammation in the large intestine and feces. Increased community dispersion and volatility in colonic apex and fecal microbiomes were also noted for S. Typhimurium. All three Salmonella serovars altered community structure as measured by co-occurrence networks; this was most prominent at DPI 2 and 4 in colonic apex samples. At the genus taxonomic level, a diverse array of putative short-chain fatty acid (SCFA) producing bacteria were altered and often decreased during the peak of inflammation at DPI 2 and 4 within colonic apex and fecal samples. Among all putative SCFA producing bacteria, Prevotella showed a broad pattern of negative correlation with disease scores at the peak of inflammation. In addition, Prevotella 9 was found to be significantly reduced in all Salmonella infected groups compared to the control at DPI 4 in the colonic apex. In conclusion, this work further elucidates that distinct swine-related zoonotic serovars of S. enterica can induce both shared (high resilience) and unique (altered resistance) alterations in gut microbiome biogeography, which helps inform future investigations of dietary modifications aimed at increasing colonization resistance against Salmonella through GI microbiome alterations.

The waxy mutation in sorghum and other cereal grains reshapes the gut microbiome by reducing levels of multiple beneficial species.

Waxy starches from cereal grains contain >90% amylopectin due to naturally occurring mutations that block amylose biosynthesis. Waxy starches have unique organoleptic characteristics (e.g. sticky rice) as well as desirable physicochemical properties for food processing. Using isogenic pairs of wild type sorghum lines and their waxy derivatives, we studied the effects of waxy starches in the whole grain context on the human gut microbiome. In vitro fermentations with human stool microbiomes show that beneficial taxonomic and metabolic signatures driven by grain from wild type parental lines are lost in fermentations of grain from the waxy derivatives and the beneficial signatures can be restored by addition of resistant starch. These undesirable effects are conserved in fermentations of waxy maize, wheat, rice and millet. We also demonstrate that humanized gnotobiotic mice fed low fiber diets supplemented with 20% grain from isogenic pairs of waxy vs. wild type parental sorghum have significant differences in microbiome composition and show increased weight gain. We conclude that the benefits of waxy starches on food functionality can have unintended tradeoff effects on the gut microbiome and host physiology that could be particularly relevant in human populations consuming large amounts of waxy grains.

Evidence for a Causal Role for Escherichia coli Strains Identified as Adherent-Invasive (AIEC) in Intestinal Inflammation.

Enrichment of adherent-invasive Escherichia coli (AIEC) has been consistently detected in subsets of inflammatory bowel disease (IBD) patients. Although some AIEC strains cause colitis in animal models, these studies did not systematically compare AIEC with non-AIEC strains, and causal links between AIEC and disease are still disputed. Specifically, it remains unclear whether AIEC shows enhanced pathogenicity compared to that of commensal E. coli found in the same ecological microhabitat and if the in vitro phenotypes used to classify strains as AIEC are pathologically relevant. Here, we utilized in vitro phenotyping and a murine model of intestinal inflammation to systematically compare strains identified as AIEC with those identified as non-AIEC and relate AIEC phenotypes to pathogenicity. Strains identified as AIEC caused, on average, more severe intestinal inflammation. Intracellular survival/replication phenotypes routinely used to classify AIEC positively correlated with disease, while adherence to epithelial cells and tumor necrosis factor alpha production by macrophages did not. This knowledge was then applied to design and test a strategy to prevent inflammation by selecting E. coli strains that adhered to epithelial cells but poorly survived/replicated intracellularly. Two E. coli strains that ameliorated AIEC-mediated disease were subsequently identified. In summary, our results show a relationship between intracellular survival/replication in E. coli and pathology in murine colitis, suggesting that strains possessing these phenotypes might not only become enriched in human IBD but also contribute to disease. We provide new evidence that specific AIEC phenotypes are pathologically relevant and proof of principle that such mechanistic information can be therapeutically exploited to alleviate intestinal inflammation. IMPORTANCE Inflammatory bowel disease (IBD) is associated with an altered gut microbiota composition, including expansion of Proteobacteria. Many species in this phylum are thought to contribute to disease under certain conditions, including adherent-invasive Escherichia coli (AIEC) strains, which are enriched in some patients. However, whether this bloom contributes to disease or is just a response to IBD-associated physiological changes is unknown. Although assigning causality is challenging, appropriate animal models can test the hypothesis that AIEC strains have an enhanced ability to cause colitis in comparison to other gut commensal E. coli strains and to identify bacterial traits contributing to virulence. We observed that AIEC strains are generally more pathogenic than commensal E. coli and that bacterial intracellular survival/replication phenotypes contributed to disease. We also found that E. coli strains lacking primary virulence traits can prevent inflammation. Our findings provide critical information on E. coli pathogenicity that may inform development of IBD diagnostic tools and therapies.

Dietary selenium affects host selenoproteome expression by influencing the gut microbiota.

Colonization of the gastrointestinal tract and composition of the microbiota may be influenced by components of the diet, including trace elements. To understand how selenium regulates the intestinal microflora, we used high-throughput sequencing to examine the composition of gut microbiota of mice maintained on selenium-deficient, selenium-sufficient, and selenium-enriched diets. The microbiota diversity increased as a result of selenium in the diet. Specific phylotypes showed differential effects of selenium, even within a genus, implying that selenium had unique effects across microbial taxa. Conventionalized germ-free mice subjected to selenium diets gave similar results and showed an increased diversity of the bacterial population in animals fed with higher levels of selenium. Germ-free mice fed selenium diets modified their selenoproteome expression similar to control mice but showed higher levels and activity of glutathione peroxidase 1 and methionine-R-sulfoxide reductase 1 in the liver, suggesting partial sequestration of selenium by the gut microorganisms, limiting its availability for the host. These changes in the selenium status were independent of the levels of other trace elements. The data show that dietary selenium affects both composition of the intestinal microflora and colonization of the gastrointestinal tract, which, in turn, influence the host selenium status and selenoproteome expression.

Systems-Based Approach for Optimization of Assembly-Free Bacterial MLST Mapping.

Epidemiological surveillance of bacterial pathogens requires real-time data analysis with a fast turnaround, while aiming at generating two main outcomes: (1) species-level identification and (2) variant mapping at different levels of genotypic resolution for population-based tracking and surveillance, in addition to predicting traits such as antimicrobial resistance (AMR). Multi-locus sequence typing (MLST) aids this process by identifying sequence types (ST) based on seven ubiquitous genome-scattered loci. In this paper, we selected one assembly-dependent and one assembly-free method for ST mapping and applied them with the default settings and ST schemes they are distributed with, and systematically assessed their accuracy and scalability across a wide array of phylogenetically divergent Public Health-relevant bacterial pathogens with available MLST databases. Our data show that the optimal k-mer length for stringMLST is species-specific and that genome-intrinsic and -extrinsic features can affect the performance and accuracy of the program. Although suitable parameters could be identified for most organisms, there were instances where this program may not be directly deployable in its current format. Next, we integrated stringMLST into our freely available and scalable hierarchical-based population genomics platform, ProkEvo, and further demonstrated how the implementation facilitates automated, reproducible bacterial population analysis.

The Unique Seed Protein Composition of Quality Protein Popcorn Promotes Growth of Beneficial Bacteria From the Human Gut Microbiome.

The effects of fiber, complex carbohydrates, lipids, and small molecules from food matrices on the human gut microbiome have been increasingly studied. Much less is known about how dietary protein can influence the composition and function of the gut microbial community. Here, we used near-isogenic maize lines of conventional popcorn and quality-protein popcorn (QPP) to study the effects of the opaque-2 mutation and associated quality-protein modifiers on the human gut microbiome. Opaque-2 blocks the synthesis of major maize seed proteins (α-zeins), resulting in a compensatory synthesis of new seed proteins that are nutritionally beneficial with substantially higher levels of the essential amino acids lysine and tryptophan. We show that QPP lines stimulate greater amounts of butyrate production by human gut microbiomes in in vitro fermentation of popped and digested corn from parental and QPP hybrids. In human gut microbiomes derived from diverse individuals, bacterial taxa belonging to the butyrate-producing family Lachnospiraceae, including the genera Coprococcus and Roseburia were consistently increased when fermenting QPP vs. parental popcorn lines. We conducted molecular complementation to further demonstrate that lysine-enriched seed protein can stimulate growth and butyrate production by microbes through distinct pathways. Our data show that organisms such as Coprococcus can utilize lysine and that other gut microbes, such as Roseburia spp., instead, utilize fructoselysine produced during thermal processing (popping) of popcorn. Thus, the combination of seed composition in QPP and interaction of protein adducts with carbohydrates during thermal processing can stimulate the growth of health-promoting, butyrate-producing organisms in the human gut microbiome through multiple pathways.

Genetic analysis of seed traits in Sorghum bicolor that affect the human gut microbiome.

Prebiotic fibers, polyphenols and other molecular components of food crops significantly affect the composition and function of the human gut microbiome and human health. The abundance of these, frequently uncharacterized, microbiome-active components vary within individual crop species. Here, we employ high throughput in vitro fermentations of pre-digested grain using a human microbiome to identify segregating genetic loci in a food crop, sorghum, that alter the composition and function of human gut microbes. Evaluating grain produced by 294 sorghum recombinant inbreds identifies 10 loci in the sorghum genome associated with variation in the abundance of microbial taxa and/or microbial metabolites. Two loci co-localize with sorghum genes regulating the biosynthesis of condensed tannins. We validate that condensed tannins stimulate the growth of microbes associated with these two loci. Our work illustrates the potential for genetic analysis to systematically discover and characterize molecular components of food crops that influence the human gut microbiome.

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations.

Routine and systematic use of bacterial whole-genome sequencing (WGS) is enhancing the accuracy and resolution of epidemiological investigations carried out by Public Health laboratories and regulatory agencies. Large volumes of publicly available WGS data can be used to study pathogenic populations at a large scale. Recently, a freely available computational platform called ProkEvo was published to enable reproducible, automated, and scalable hierarchical-based population genomic analyses using bacterial WGS data. This implementation of ProkEvo demonstrated the importance of combining standard genotypic mapping of populations with mining of accessory genomic content for ecological inference. In particular, the work highlighted here used ProkEvo-derived outputs for population-scaled hierarchical analyses using the R programming language. The main objective was to provide a practical guide for microbiologists, ecologists, and epidemiologists by showing how to: i) use a phylogeny-guided mapping of hierarchical genotypes; ii) assess frequency distributions of genotypes as a proxy for ecological fitness; iii) determine kinship relationships and genetic diversity using specific genotypic classifications; and iv) map lineage differentiating accessory loci. To enhance reproducibility and portability, R markdown files were used to demonstrate the entire analytical approach. The example dataset contained genomic data from 2,365 isolates of the zoonotic foodborne pathogen Salmonella Newport. Phylogeny-anchored mapping of hierarchical genotypes (Serovar -> BAPS1 -> ST -> cgMLST) revealed the population genetic structure, highlighting sequence types (STs) as the keystone differentiating genotype. Across the three most dominant lineages, ST5 and ST118 shared a common ancestor more recently than with the highly clonal ST45 phylotype. ST-based differences were further highlighted by the distribution of accessory antimicrobial resistance (AMR) loci. Lastly, a phylogeny-anchored visualization was used to combine hierarchical genotypes and AMR content to reveal the kinship structure and lineage-specific genomic signatures. Combined, this analytical approach provides some guidelines for conducting heuristic bacterial population genomic analyses using pan-genomic information.

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses.

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

Captive Common Marmosets (Callithrix jacchus) Are Colonized throughout Their Lives by a Community of Bifidobacterium Species with Species-Specific Genomic Content That Can Support Adaptation to Distinct Metabolic Niches.

The common marmoset (Callithrix jacchus) is an omnivorous New World primate whose diet in the wild includes large amounts of fruit, seeds, flowers, and a variety of lizards and invertebrates. Marmosets also feed heavily on tree gums and exudates, and they have evolved unique morphological and anatomical characteristics to facilitate gum feeding (gummivory). In this study, we characterized the fecal microbiomes of adult and infant animals from a captive population of common marmosets at the Callitrichid Research Center at the University of Nebraska at Omaha under their normal dietary and environmental conditions. The microbiomes of adult animals were dominated by species of Bifidobacterium, Bacteroides, Prevotella, Phascolarctobacterium, Megamonas, and Megasphaera. Culturing and genomic analysis of the Bifidobacterium populations from adult animals identified four known marmoset-associated species (B. reuteri, B. aesculapii, B. myosotis, and B. hapali) and three unclassified taxa of Bifidobacterium that are phylogenetically distinct. Species-specific quantitative PCR (qPCR) confirmed that these same species of Bifidobacterium are abundant members of the microbiome throughout the lives of the animals. Genomic loci in each Bifidobacterium species encode enzymes to support growth and major marmoset milk oligosaccharides during breastfeeding; however, metabolic islands that can support growth on complex polysaccharide substrates in the diets of captive adults (pectin, xyloglucan, and xylan), including loci in B. aesculapii that can support its unique ability to grow on arabinogalactan-rich tree gums, were species-specific. IMPORTANCEBifidobacterium species are recognized as important, beneficial microbes in the human gut microbiome, and their ability colonize individuals at different stages of life is influenced by host, dietary, environmental, and ecological factors, which is poorly understood. The common marmoset is an emerging nonhuman primate model with a short maturation period, making this model amenable to study the microbiome throughout a life history. Features of the microbiome in captive marmosets are also shared with human gut microbiomes, including abundant populations of Bifidobacterium species. Our studies show that several species of Bifidobacterium are dominant members of the captive marmoset microbiome throughout their life history. Metabolic capacities in genomes of the marmoset Bifidobacterium species suggest species-specific adaptations to different components of the captive marmoset diet, including the unique capacity in B. aesculapii for degradation of gum arabic, suggesting that regular dietary exposure in captivity may be important for preserving gum-degrading species in the microbiome.