Pseudo-pac site sequences used by phage P22 in generalized transduction of Salmonella.

Salmonella enterica Serovar Typhimurium (Salmonella) and its bacteriophage P22 are a model system for the study of horizontal gene transfer by generalized transduction. Typically, the P22 DNA packaging machinery initiates packaging when a short sequence of DNA, known as the pac site, is recognized on the P22 genome. However, sequences similar to the pac site in the host genome, called pseudo-pac sites, lead to erroneous packaging and subsequent generalized transduction of Salmonella DNA. While the general genomic locations of the Salmonella pseudo-pac sites are known, the sequences themselves have not been determined. We used visualization of P22 sequencing reads mapped to host Salmonella genomes to define regions of generalized transduction initiation and the likely locations of pseudo-pac sites. We searched each genome region for the sequence with the highest similarity to the P22 pac site and aligned the resulting sequences. We built a regular expression (sequence match pattern) from the alignment and used it to search the genomes of two P22-susceptible Salmonella strains-LT2 and 14028S-for sequence matches. The final regular expression successfully identified pseudo-pac sites in both LT2 and 14028S that correspond with generalized transduction initiation sites in mapped read coverages. The pseudo-pac site sequences identified in this study can be used to predict locations of generalized transduction in other P22-susceptible hosts or to initiate generalized transduction at specific locations in P22-susceptible hosts with genetic engineering. Furthermore, the bioinformatics approach used to identify the Salmonella pseudo-pac sites in this study could be applied to other phage-host systems.

Standards for fecal microbiota transplant: Tools and therapeutic advances.

Fecal microbiota transplantation (FMT) has been demonstrated to be efficacious in preventing recurrent Clostridioides difficile (C. difficile) infections, and is being investigated for treatment of several other diseases including inflammatory bowel disease, cancer, obesity, liver disease, and diabetes. To speed up the translation of FMT into clinical practice as a safe and standardized therapeutic intervention, additional evidence-based technical and regulatory guidance is needed. To this end in May of 2022, the International Alliance for Biological Standardization (IABS) and the BIOASTER Microbiology Technology Institute hosted a second webinar to discuss key issues still impeding the advancement and standardization of FMT. The goal of this two-day webinar was to provide a forum for scientific experts to share and discuss data and key challenges with one another. Discussion included a focus on the evaluation of safety, efficacy, clinical trial design, reproducibility and accuracy in obtained microbiome measurements and data reporting, and the potential for standardization across these areas. It also focused on increasing the application potential and visibility of FMT beyond treating C. difficile infections.

Meta-analysis reveals the vaginal microbiome is a better predictor of earlier than later preterm birth.

BACKGROUND: High-throughput sequencing measurements of the vaginal microbiome have yielded intriguing potential relationships between the vaginal microbiome and preterm birth (PTB; live birth prior to 37 weeks of gestation). However, results across studies have been inconsistent. RESULTS: Here, we perform an integrated analysis of previously published datasets from 12 cohorts of pregnant women whose vaginal microbiomes were measured by 16S rRNA gene sequencing. Of 2039 women included in our analysis, 586 went on to deliver prematurely. Substantial variation between these datasets existed in their definition of preterm birth, characteristics of the study populations, and sequencing methodology. Nevertheless, a small group of taxa comprised a vast majority of the measured microbiome in all cohorts. We trained machine learning (ML) models to predict PTB from the composition of the vaginal microbiome, finding low to modest predictive accuracy (0.28-0.79). Predictive accuracy was typically lower when ML models trained in one dataset predicted PTB in another dataset. Earlier preterm birth (< 32 weeks, < 34 weeks) was more predictable from the vaginal microbiome than late preterm birth (34-37 weeks), both within and across datasets. Integrated differential abundance analysis revealed a highly significant negative association between L. crispatus and PTB that was consistent across almost all studies. The presence of the majority (18 out of 25) of genera was associated with a higher risk of PTB, with L. iners, Prevotella, and Gardnerella showing particularly consistent and significant associations. Some example discrepancies between studies could be attributed to specific methodological differences but not most study-to-study variations in the relationship between the vaginal microbiome and preterm birth. CONCLUSIONS: We believe future studies of the vaginal microbiome and PTB will benefit from a focus on earlier preterm births and improved reporting of specific patient metadata shown to influence the vaginal microbiome and/or birth outcomes.

Rookery through rehabilitation: Microbial community assembly in newborn harbour seals after maternal separation.

Microbial community assembly remains largely unexplored in marine mammals, despite its potential importance for conservation and management. Here, neonatal microbiota assembly was studied in harbour seals (Phoca vitulina richardii) at a rehabilitation facility soon after maternal separation, through weaning, to the time of release back to their native environment. We found that the gingival and rectal communities of rehabilitated harbour seals were distinct from the microbiotas of formula and pool water, and became increasingly diverse and dissimilar over time, ultimately resembling the gingival and rectal communities of local wild harbour seals. Harbour seal microbiota assembly was compared to that of human infants, revealing the rapid emergence of host specificity and evidence of phylosymbiosis even though these harbour seals had been raised by humans. Early life prophylactic antibiotics were associated with changes in the composition of the harbour seal gingival and rectal communities and surprisingly, with transient increases in alpha diversity, perhaps because of microbiota sharing during close cohabitation with other harbour seals. Antibiotic-associated effects dissipated over time. These results suggest that while early life maternal contact may provide seeding for microbial assembly, co-housing of conspecifics during rehabilitation may help neonatal mammals achieve a healthy host-specific microbiota with features of resilience.

Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology.

Short-read, high-throughput sequencing (HTS) methods have yielded numerous important insights into microbial ecology and function. Yet, in many instances short-read HTS techniques are suboptimal, for example, by providing insufficient phylogenetic resolution or low integrity of assembled genomes. Single-molecule and synthetic long-read (SLR) HTS methods have successfully ameliorated these limitations. In addition, nanopore sequencing has generated a number of unique analysis opportunities, such as rapid molecular diagnostics and direct RNA sequencing, and both Pacific Biosciences (PacBio) and nanopore sequencing support detection of epigenetic modifications. Although initially suffering from relatively low sequence quality, recent advances have greatly improved the accuracy of long-read sequencing technologies. In spite of great technological progress in recent years, the long-read HTS methods (PacBio and nanopore sequencing) are still relatively costly, require large amounts of high-quality starting material, and commonly need specific solutions in various analysis steps. Despite these challenges, long-read sequencing technologies offer high-quality, cutting-edge alternatives for testing hypotheses about microbiome structure and functioning as well as assembly of eukaryote genomes from complex environmental DNA samples.

High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution.

Targeted PCR amplification and high-throughput sequencing (amplicon sequencing) of 16S rRNA gene fragments is widely used to profile microbial communities. New long-read sequencing technologies can sequence the entire 16S rRNA gene, but higher error rates have limited their attractiveness when accuracy is important. Here we present a high-throughput amplicon sequencing methodology based on PacBio circular consensus sequencing and the DADA2 sample inference method that measures the full-length 16S rRNA gene with single-nucleotide resolution and a near-zero error rate. In two artificial communities of known composition, our method recovered the full complement of full-length 16S sequence variants from expected community members without residual errors. The measured abundances of intra-genomic sequence variants were in the integral ratios expected from the genuine allelic variants within a genome. The full-length 16S gene sequences recovered by our approach allowed Escherichia coli strains to be correctly classified to the O157:H7 and K12 sub-species clades. In human fecal samples, our method showed strong technical replication and was able to recover the full complement of 16S rRNA alleles in several E. coli strains. There are likely many applications beyond microbial profiling for which high-throughput amplicon sequencing of complete genes with single-nucleotide resolution will be of use.

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.

Motivation: Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results: We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation: Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/. Supplementary information: Supplementary data are available at Bioinformatics online.

Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women.

Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. Previous studies have suggested that the maternal vaginal microbiota contributes to the pathophysiology of PTB, but conflicting results in recent years have raised doubts. We conducted a study of PTB compared with term birth in two cohorts of pregnant women: one predominantly Caucasian (n = 39) at low risk for PTB, the second predominantly African American and at high-risk (n = 96). We profiled the taxonomic composition of 2,179 vaginal swabs collected prospectively and weekly during gestation using 16S rRNA gene sequencing. Previously proposed associations between PTB and lower Lactobacillus and higher Gardnerella abundances replicated in the low-risk cohort, but not in the high-risk cohort. High-resolution bioinformatics enabled taxonomic assignment to the species and subspecies levels, revealing that Lactobacillus crispatus was associated with low risk of PTB in both cohorts, while Lactobacillus iners was not, and that a subspecies clade of Gardnerella vaginalis explained the genus association with PTB. Patterns of cooccurrence between L. crispatus and Gardnerella were highly exclusive, while Gardnerella and L. iners often coexisted at high frequencies. We argue that the vaginal microbiota is better represented by the quantitative frequencies of these key taxa than by classifying communities into five community state types. Our findings extend and corroborate the association between the vaginal microbiota and PTB, demonstrate the benefits of high-resolution statistical bioinformatics in clinical microbiome studies, and suggest that previous conflicting results may reflect the different risk profile of women of black race.

DADA2: High-resolution sample inference from Illumina amplicon data.

We present the open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors (https://github.com/benjjneb/dada2). DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide. In several mock communities, DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

Temporal and spatial variation of the human microbiota during pregnancy.

Despite the critical role of the human microbiota in health, our understanding of microbiota compositional dynamics during and after pregnancy is incomplete. We conducted a case-control study of 49 pregnant women, 15 of whom delivered preterm. From 40 of these women, we analyzed bacterial taxonomic composition of 3,767 specimens collected prospectively and weekly during gestation and monthly after delivery from the vagina, distal gut, saliva, and tooth/gum. Linear mixed-effects modeling, medoid-based clustering, and Markov chain modeling were used to analyze community temporal trends, community structure, and vaginal community state transitions. Microbiota community taxonomic composition and diversity remained remarkably stable at all four body sites during pregnancy (P > 0.05 for trends over time). Prevalence of a Lactobacillus-poor vaginal community state type (CST 4) was inversely correlated with gestational age at delivery (P = 0.0039). Risk for preterm birth was more pronounced for subjects with CST 4 accompanied by elevated Gardnerella or Ureaplasma abundances. This finding was validated with a set of 246 vaginal specimens from nine women (four of whom delivered preterm). Most women experienced a postdelivery disturbance in the vaginal community characterized by a decrease in Lactobacillus species and an increase in diverse anaerobes such as Peptoniphilus, Prevotella, and Anaerococcus species. This disturbance was unrelated to gestational age at delivery and persisted for up to 1 y. These findings have important implications for predicting premature labor, a major global health problem, and for understanding the potential impact of a persistent, altered postpartum microbiota on maternal health, including outcomes of pregnancies following short interpregnancy intervals.

1,2-Dichloroethane Exposure Alters the Population Structure, Metabolism, and Kinetics of a Trichloroethene-Dechlorinating Dehalococcoides mccartyi Consortium.

Bioremediation of groundwater contaminated with chlorinated aliphatic hydrocarbons such as perchloroethene and trichloroethene can result in the accumulation of the undesirable intermediate vinyl chloride. Such accumulation can either be due to the absence of specific vinyl chloride respiring Dehalococcoides mccartyi or to the inhibition of such strains by the metabolism of other microorganisms. The fitness of vinyl chloride respiring Dehalococcoides mccartyi subpopulations is particularly uncertain in the presence of chloroethene/chloroethane cocontaminant mixtures, which are commonly found in contaminated groundwater. Therefore, we investigated the structure of Dehalococcoides populations in a continuously fed reactor system under changing chloroethene/ethane influent conditions. We observed that increasing the influent ratio of 1,2-dichloroethane to trichloroethene was associated with ecological selection of a tceA-containing Dehalococcoides population relative to a vcrA-containing Dehalococcoides population. Although both vinyl chloride and 1,2-dichloroethane could be simultaneously transformed to ethene, prolonged exposure to 1,2-dichloroethane diminished the vinyl chloride transforming capacity of the culture. Kinetic tests revealed that dechlorination of 1,2-dichloroethane by the consortium was strongly inhibited by cis-dichloroethene but not vinyl chloride. Native polyacrylamide gel electrophoresis and mass spectrometry revealed that a trichloroethene reductive dehalogenase (TceA) homologue was the most consistently expressed of four detectable reductive dehalogenases during 1,2-dichloroethane exposure, suggesting that it catalyzes the reductive dihaloelimination of 1,2-dichloroethane to ethene.

Correlated evolution of nearby residues in Drosophilid proteins.

Here we investigate the correlations between coding sequence substitutions as a function of their separation along the protein sequence. We consider both substitutions between the reference genomes of several Drosophilids as well as polymorphisms in a population sample of Zimbabwean Drosophila melanogaster. We find that amino acid substitutions are "clustered" along the protein sequence, that is, the frequency of additional substitutions is strongly enhanced within ≈10 residues of a first such substitution. No such clustering is observed for synonymous substitutions, supporting a "correlation length" associated with selection on proteins as the causative mechanism. Clustering is stronger between substitutions that arose in the same lineage than it is between substitutions that arose in different lineages. We consider several possible origins of clustering, concluding that epistasis (interactions between amino acids within a protein that affect function) and positional heterogeneity in the strength of purifying selection are primarily responsible. The role of epistasis is directly supported by the tendency of nearby substitutions that arose on the same lineage to preserve the total charge of the residues within the correlation length and by the preferential cosegregation of neighboring derived alleles in our population sample. We interpret the observed length scale of clustering as a statistical reflection of the functional locality (or modularity) of proteins: amino acids that are near each other on the protein backbone are more likely to contribute to, and collaborate toward, a common subfunction.

Heterozygote advantage as a natural consequence of adaptation in diploids.

Molecular adaptation is typically assumed to proceed by sequential fixation of beneficial mutations. In diploids, this picture presupposes that for most adaptive mutations, the homozygotes have a higher fitness than the heterozygotes. Here, we show that contrary to this expectation, a substantial proportion of adaptive mutations should display heterozygote advantage. This feature of adaptation in diploids emerges naturally from the primary importance of the fitness of heterozygotes for the invasion of new adaptive mutations. We formalize this result in the framework of Fisher's influential geometric model of adaptation. We find that in diploids, adaptation should often proceed through a succession of short-lived balanced states that maintain substantially higher levels of phenotypic and fitness variation in the population compared with classic adaptive walks. In fast-changing environments, this variation produces a diversity advantage that allows diploids to remain better adapted compared with haploids despite the disadvantage associated with the presence of unfit homozygotes. The short-lived balanced states arising during adaptive walks should be mostly invisible to current scans for long-term balancing selection. Instead, they should leave signatures of incomplete selective sweeps, which do appear to be common in many species. Our results also raise the possibility that balancing selection, as a natural consequence of frequent adaptation, might play a more prominent role among the forces maintaining genetic variation than is commonly recognized.

Serovar-level identification of bacterial foodborne pathogens from full-length 16S rRNA gene sequencing.

The resolution of variation within species is critical for interpreting and acting on many microbial measurements. In the key foodborne pathogens Salmonella and Escherichia coli, the primary subspecies classification scheme used is serotyping: differentiating variants within these species by surface antigen profiles. Serotype prediction from whole-genome sequencing (WGS) of isolates is now seen as comparable or preferable to traditional laboratory methods where WGS is available. However, laboratory and WGS methods depend on an isolation step that is time-consuming and incompletely represents the sample when multiple strains are present. Community sequencing approaches that skip the isolation step are, therefore, of interest for pathogen surveillance. Here, we evaluated the viability of amplicon sequencing of the full-length 16S rRNA gene for serotyping Salmonella enterica and E. coli. We developed a novel algorithm for serotype prediction, implemented as an R package (Seroplacer), which takes as input full-length 16S rRNA gene sequences and outputs serovar predictions after phylogenetic placement into a reference phylogeny. We achieved over 89% accuracy in predicting Salmonella serotypes on in silico test data and identified key pathogenic serovars of Salmonella and E. coli in isolate and environmental test samples. Although serotype prediction from 16S rRNA gene sequences is not as accurate as serotype prediction from WGS of isolates, the potential to identify dangerous serovars directly from amplicon sequencing of environmental samples is intriguing for pathogen surveillance. The capabilities developed here are also broadly relevant to other applications where intraspecies variation and direct sequencing from environmental samples could be valuable.IMPORTANCEIn order to prevent and stop outbreaks of foodborne pathogens, it is important that we can detect when pathogenic bacteria are present in a food or food-associated site and identify connections between specific pathogenic bacteria present in different samples. In this work, we develop a new computational technology that allows the important foodborne pathogens Escherichia coli and Salmonella enterica to be serotyped (a subspecies level classification) from sequencing of a single-marker gene, and the 16S rRNA gene often used to surveil bacterial communities. Our results suggest current limitations to serotyping from 16S rRNA gene sequencing alone but set the stage for further progress that we consider likely given the rapid advance in the long-read sequencing technologies and genomic databases our work leverages. If this research direction succeeds, it could enable better detection of foodborne pathogens before they reach the public and speed the resolution of foodborne pathogen outbreaks.

Impact of florfenicol dosing regimen on the phenotypic and genotypic resistance of enteric bacteria in steers.

The food animal sector's use of antimicrobials is heavily critiqued for its role in allowing resistance to develop against critically important antimicrobials in human health. The WHO recommends using lower tier antimicrobials such as florfenicol for disease treatment. The primary objective of this study was to assess the differences in resistance profiles of enteric microbes following administration of florfenicol to steers using both FDA-approved dosing regimens and two different detection methods. Our hypothesis was that we would identify an increased prevalence of resistance in the steers administered the repeated, lower dose of florfenicol; additionally, we hypothesized resistance profiles would be similar between both detection methods. Twelve steers were administered either two intramuscular (20 mg/kg q 48 h; n = 6) or a single subcutaneous dose (40 mg/kg, n = 6). Fecal samples were collected for 38 days, and E. coli and Enterococcus were isolated and tested for resistance. Fecal samples were submitted for metagenomic sequencing analysis. Metagenomics revealed genes conferring resistance to aminoglycosides as the most abundant drug class. Most multidrug resistance genes contained phenicols. The genotypic and phenotypic patterns of resistance were not similar between drug classes. Observed increases in resistant isolates and relative abundance of resistance genes peaked after drug administration and returned to baseline by the end of the sampling period. The use of a "lower tier" antimicrobial, such as florfenicol, may cause an increased amount of resistance to critically important antimicrobials for a brief period, but these changes largely resolve by the end of the drug withdrawal period.

Gardnerella diversity and ecology in pregnancy and preterm birth.

The vaginal microbiome has been linked to negative health outcomes including preterm birth. Specific taxa, including Gardnerella spp., have been identified as risk factors for these conditions. Historically, microbiome analysis methods have treated all Gardnerella spp. as one species, but the broad diversity of Gardnerella has become more apparent. We explore the diversity of Gardnerella clades and genomic species in the vaginal microbiome of pregnant women and their associations with microbiome composition and preterm birth. Relative abundance of Gardnerella clades and genomic species and other taxa was quantified in shotgun metagenomic sequencing data from three distinct cohorts of pregnant women. We also assessed the diversity and abundance of Gardnerella variants in 16S rRNA gene amplicon sequencing data from seven previously conducted studies in differing populations. Individual microbiomes often contained multiple Gardnerella variants, and the number of clades was associated with increased microbial load, or the ratio of non-human reads to human reads. Taxon co-occurrence patterns were largely consistent across Gardnerella clades and among cohorts. Some variants previously described as rare were prevalent in other cohorts, highlighting the importance of surveying a diverse set of populations to fully capture the diversity of Gardnerella. The diversity of Gardnerella both across populations and within individual vaginal microbiomes has long been unappreciated, as has been the intra-species diversity of many other members of the vaginal microbiome. The broad genomic diversity of Gardnerella has led to its reclassification as multiple species; here we demonstrate the diversity of Gardnerella found within and between vaginal microbiomes.IMPORTANCEThe present study shows that single microbiomes can contain all currently known species of Gardnerella and that multiple similar species can exist within the same environment. Furthermore, surveys of demographically distinct populations suggest that some species appear more commonly in certain populations. Further studies in broad and diverse populations will be necessary to fully understand the ecological roles of each Gardnerella sp., how they can co-exist, and their distinct impacts on microbial communities, preterm birth, and other health outcomes.

The development of non-destructive sampling methods of parchment skins for genetic species identification.

Parchment, the skins of animals prepared for use as writing surfaces, offers a valuable source of genetic information. Many have clearly defined provenance, allowing for the genetic findings to be evaluated in temporal and spatial context. While these documents can yield evidence of the animal sources, the DNA contained within these aged skins is often damaged and fragmented. Previously, genetic studies targeting parchment have used destructive sampling techniques and so the development and validation of non-destructive sampling methods would expand opportunities and facilitate testing of more precious documents, especially those with historical significance. Here we present genetic data obtained by non-destructive sampling of eight parchments spanning the 15th century to the modern day. We define a workflow for enriching the mitochondrial genome (mtGenome), generating next-generation sequencing reads to permit species identification, and providing interpretation guidance. Using sample replication, comparisons to destructively sampled controls, and by establishing authentication criteria, we were able to confidently assign full/near full mtGenome sequences to 56.3% of non-destructively sampled parchments, each with greater than 90% of the mtGenome reference covered. Six of eight parchments passed all four established thresholds with at least one non-destructive sample, highlighting promise for future studies.

Serovar-level Identification of Bacterial Foodborne Pathogens From Full-length 16S rRNA Gene Sequencing.

The resolution of variation within species is critical for interpreting and acting on many microbial measurements. In the key foodborne pathogens Escherichia coli and Salmonella, the primary sub-species classification scheme used is serotyping: differentiating variants within these species by surface antigen profiles. Serotype prediction from whole-genome sequencing (WGS) of isolates is now seen as comparable or preferable to traditional laboratory methods where WGS is available. However, laboratory and WGS methods depend on an isolation step that is time-consuming and incompletely represents the sample when multiple strains are present. Community sequencing approaches that skip the isolation step are therefore of interest for pathogen surveillance. Here we evaluated the viability of amplicon sequencing of the full-length 16S rRNA gene for serotyping S. enterica and E. coli. We developed a novel algorithm for serotype prediction, implemented as an R package (Seroplacer), which takes as input full-length 16S rRNA gene sequences and outputs serovar predictions after phylogenetic placement into a reference phylogeny. We achieved over 89% accuracy in predicting Salmonella serotypes on in silico test data, and identified key pathogenic serovars of Salmonella and E. coli in isolate and environmental test samples. Although serotype prediction from 16S sequences is not as accurate as serotype prediction from WGS of isolates, the potential to identify dangerous serovars directly from amplicon sequencing of environmental samples is intriguing for pathogen surveillance. The capabilities developed here are also broadly relevant to other applications where intra-species variation and direct sequencing from environmental samples could be valuable.

Longitudinal Analysis of Canine Oral Microbiome Using Whole Genome Sequencing in Aging Companion Dogs.

Aged companion dogs have a high prevalence of periodontal disease and canine cognitive dysfunction syndrome (CCDS) and the two disorders are correlated. Similarly, periodontal disease and Alzheimer's Disease are correlated in people. However, little is known about the oral microbiota of aging dogs. The goal of this project was to characterize the longitudinal changes in oral microbiota in aged dogs. Oral swabs were taken from ten senior client-owned dogs on 2-3 occasions spanning 24 months and they underwent whole genome shotgun (WGS) sequencing. Cognitive status was established at each sampling time. A statistically significant increase in alpha diversity for bacterial and fungal species was observed between the first and last study visits. Bacteroidetes and proteobacteria were the most abundant bacterial phyla. Porphyromonas gulae was the most abundant bacterial species (11.6% of total reads). The species Lactobacillus gasseri had a statistically significant increase in relative abundance with age whereas Leptotrichia sp. oral taxon 212 had a statistically significant positive longitudinal association with cognition score. There is an increased fungal and bacterial alpha diversity in aging dogs over time and nearly universal oral dysbiosis. The role of the oral microbiota, particularly Leptotrichia and P. gulae and P. gingivalis, in aging and CCDS warrants further investigation.

Microbiome analysis of bile from apparently healthy cats and cats with suspected hepatobiliary disease.

BACKGROUND: Bacterial infection of bile is a common cause of hepatobiliary disease in cats. Whether bile harbors a core microbiota in health or in cases of suspected hepatobiliary disease in cats is unknown. OBJECTIVES: Establish if gallbladder bile in apparently healthy cats harbors a core microbiota composed of bacterial taxa common to many individuals. Compare results of bile cytology, bile culture, and 16S rRNA gene amplicon sequencing in apparently healthy cats and cats with suspected hepatobiliary disease. ANIMALS: Forty-three client-owned cats with suspected hepatobiliary disease and 17 control cats. METHODS: Bile was collected by ultrasound guided cholecystocentesis (cats with suspected hepatobiliary disease) or laparotomy after euthanasia (controls). Bile samples underwent cytologic examination, aerobic and anaerobic culture, and DNA was extracted for 16S rRNA gene amplification and sequencing. RESULTS: Microbiome sequencing did not identify a core microbiota in control cats or cats having bile sampled because of clinical suspicion for hepatobiliary disease. Microbiome profiles from control cats were indistinguishable from profiles obtained from sampling instruments and reagents that were not exposed to bile (technical controls). Bacterial taxa that could not be explained by contamination or off-target amplification were identified only in samples from cats with bactibilia and positive bile culture results for Escherichia coli. In several E. coli positive samples, microbiome sequencing also identified a small number of potentially co-infecting bacterial genera not identified by culture. CONCLUSIONS AND CLINICAL IMPORTANCE: Cat bile does not harbor a core microbiota. Uncultured bacteria may contribute to pathogenesis of hepatobiliary disease in cats with bile E. coli infection.