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.

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.

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.

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.

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.

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.

Evaluation of SARS-CoV-2 identification methods through surveillance of companion animals in SARS-CoV-2-positive homes in North Carolina, March to December 2020.

We collected oral and/or rectal swabs and serum from dogs and cats living in homes with SARS-CoV-2-PCR-positive persons for SARS-CoV-2 PCR and serology testing. Pre-COVID-19 serum samples from dogs and cats were used as negative controls, and samples were tested in duplicate at different timepoints. Raw ELISA results scrutinized relative to known negative samples suggested that cut-offs for IgG seropositivity may require adjustment relative to previously proposed values, while proposed cut-offs for IgM require more extensive validation. A small number of pet dogs (2/43, 4.7%) and one cat (1/21, 4.8%) were positive for SARS-CoV-2 RNA, and 28.6 and 37.5% of cats and dogs were positive for anti-SARS-CoV-2 IgG, respectively.

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.

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.

A pile of pipelines: An overview of the bioinformatics software for metabarcoding data analyses.

Environmental DNA (eDNA) metabarcoding has gained growing attention as a strategy for monitoring biodiversity in ecology. However, taxa identifications produced through metabarcoding require sophisticated processing of high-throughput sequencing data from taxonomically informative DNA barcodes. Various sets of universal and taxon-specific primers have been developed, extending the usability of metabarcoding across archaea, bacteria and eukaryotes. Accordingly, a multitude of metabarcoding data analysis tools and pipelines have also been developed. Often, several developed workflows are designed to process the same amplicon sequencing data, making it somewhat puzzling to choose one among the plethora of existing pipelines. However, each pipeline has its own specific philosophy, strengths and limitations, which should be considered depending on the aims of any specific study, as well as the bioinformatics expertise of the user. In this review, we outline the input data requirements, supported operating systems and particular attributes of thirty-two amplicon processing pipelines with the goal of helping users to select a pipeline for their metabarcoding projects.

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.

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.

Gallbladder microbiota in healthy dogs and dogs with mucocele formation.

To date studies have not investigated the culture-independent microbiome of bile from dogs, a species where aseptic collection of bile under ultrasound guidance is somewhat routine. Despite frequent collection of bile for culture-based diagnosis of bacterial cholecystitis, it is unknown whether bile from healthy dogs harbors uncultivable bacteria or a core microbiota. The answer to this question is critical to understanding the pathogenesis of biliary infection and as a baseline to exploration of other biliary diseases in dogs where uncultivable bacteria could play a pathogenic role. A pressing example of such a disease would be gallbladder mucocele formation in dogs. This prevalent and deadly condition is characterized by excessive secretion of abnormal mucus by the gallbladder epithelium that can eventually lead to rupture of the gallbladder or obstruction of bile flow. The cause of mucocele formation is unknown as is whether uncultivable, and therefore unrecognized, bacteria play any systematic role in pathogenesis. In this study we applied next-generation 16S rRNA gene sequencing to identify the culture-negative bacterial community of gallbladder bile from healthy dogs and gallbladder mucus from dogs with mucocele formation. Integral to our study was the use of 2 separate DNA isolations on each sample using different extraction methods and sequencing of negative control samples enabling recognition and curation of contaminating sequences. Microbiota findings were validated by simultaneous culture-based identification, cytological examination of bile, and fluorescence in-situ hybridization (FISH) performed on gallbladder mucosa. Using culture-dependent, cytological, FISH, and 16S rRNA sequencing approaches, results of our study do not support existence of a core microbiome in the bile of healthy dogs or gallbladder mucus from dogs with mucocele formation. Our findings further document how contaminating sequences can significantly contribute to the results of sequencing analysis when performed on samples with low bacterial biomass.

Identification of microbial taxa present in Ctenocephalides felis (cat flea) reveals widespread co-infection and associations with vector phylogeny.

BACKGROUND: Ctenocephalides felis, the cat flea, is the most common ectoparasite of cats and dogs worldwide. As a cause of flea allergy dermatitis and a vector for two genera of zoonotic pathogens (Bartonella and Rickettsia spp.), the effect of the C. felis microbiome on pathogen transmission and vector survival is of substantial medical importance to both human and veterinary medicine. The aim of this study was to assay the pathogenic and commensal eubacterial microbial communities of individual C. felis from multiple geographic locations and analyze these findings by location, qPCR pathogen prevalence, and flea genetic diversity. METHODS: 16S Next Generation Sequencing (NGS) was utilized to sequence the microbiome of fleas collected from free-roaming cats, and the cox1 gene was used for flea phylogenetic analysis. NGS data were analyzed for 168 individual fleas from seven locations within the US and UK. Given inconsistency in the genera historically reported to constitute the C. felis microbiome, we utilized the decontam prevalence method followed by literature review to separate contaminants from true microbiome members. RESULTS: NGS identified a single dominant and cosmopolitan amplicon sequence variant (ASV) from Rickettsia and Wolbachia while identifying one dominant Bartonella clarridgeiae and one dominant Bartonella henselae/Bartonella koehlerae ASV. Multiple less common ASVs from these genera were detected within restricted geographical ranges. Co-detection of two or more genera (Bartonella, Rickettsia, and/or Wolbachia) or multiple ASVs from a single genus in a single flea was common. Achromobacter, Peptoniphilus, and Rhodococcus were identified as additional candidate members of the C. felis microbiome on the basis of decontam analysis and literature review. Ctenocephalides felis phylogenetic diversity as assessed by the cox1 gene fell within currently characterized clades while identifying seven novel haplotypes. NGS sensitivity and specificity for Bartonella and Rickettsia spp. DNA detection were compared to targeted qPCR. CONCLUSIONS: Our findings confirm the widespread coinfection of fleas with multiple bacterial genera and strains, proposing three additional microbiome members. The presence of minor Bartonella, Rickettsia, and Wolbachia ASVs was found to vary by location and flea haplotype. These findings have important implications for flea-borne pathogen transmission and control.

Phylogeny-guided microbiome OTU-specific association test (POST).

BACKGROUND: The relationship between host conditions and microbiome profiles, typically characterized by operational taxonomic units (OTUs), contains important information about the microbial role in human health. Traditional association testing frameworks are challenged by the high dimensionality and sparsity of typical microbiome profiles. Phylogenetic information is often incorporated to address these challenges with the assumption that evolutionarily similar taxa tend to behave similarly. However, this assumption may not always be valid due to the complex effects of microbes, and phylogenetic information should be incorporated in a data-supervised fashion. RESULTS: In this work, we propose a local collapsing test called phylogeny-guided microbiome OTU-specific association test (POST). In POST, whether or not to borrow information and how much information to borrow from the neighboring OTUs in the phylogenetic tree are supervised by phylogenetic distance and the outcome-OTU association. POST is constructed under the kernel machine framework to accommodate complex OTU effects and extends kernel machine microbiome tests from community level to OTU level. Using simulation studies, we show that when the phylogenetic tree is informative, POST has better performance than existing OTU-level association tests. When the phylogenetic tree is not informative, POST achieves similar performance as existing methods. Finally, in real data applications on bacterial vaginosis and on preterm birth, we find that POST can identify similar or more outcome-associated OTUs that are of biological relevance compared to existing methods. CONCLUSIONS: Using POST, we show that adaptively leveraging the phylogenetic information can enhance the selection performance of associated microbiome features by improving the overall true-positive and false-positive detection. We developed a user friendly R package POSTm which is freely available on CRAN ( https://CRAN.R-project.org/package=POSTm ). Video Abstract.

Ultra-accurate microbial amplicon sequencing with synthetic long reads.

BACKGROUND: Out of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge. METHODS: Here, we describe and analytically validate LoopSeq, a commercially available synthetic long-read (SLR) sequencing technology that generates highly accurate long reads from standard short reads. RESULTS: LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq perfectly recovered the full diversity of 16S rRNA genes from known strains in a synthetic microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kb in length. LoopSeq full-length 16S rRNA reads could accurately classify organisms down to the species level in rinsate from retail meat samples, and could differentiate strains within species identified by the CDC as potential foodborne pathogens. CONCLUSIONS: The order-of-magnitude improvement in length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex- to low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics. Video abstract.

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.

Evaluation of fecal Lactobacillus populations in dogs with idiopathic epilepsy: a pilot study.

BACKGROUND: Idiopathic epilepsy is a common neurological disorder of dogs characterized by recurrent seizures for which no underlying basis is identified other than a presumed genetic predisposition. The pathogenesis of the disorder remains poorly understood, but environmental factors are presumed to influence the course of disease. Within the growing body of research into the microbiota-gut-brain axis, considerable attention has focused on the protective role of Lactobacilli in the development and progression of neurological disease. Investigations into the association between the gut microbiome and epilepsy are in their infancy, but some preliminary findings support a role for Lactobacilli in drug resistant epilepsy. To date, there are no published studies evaluating the gut microbiome in dogs with epilepsy. This pilot study was undertaken to evaluate fecal Lactobacillus populations in dogs with idiopathic epilepsy compared to healthy dogs. RESULTS: Fecal samples were obtained from 13 pairs of dogs, consisting of a drug-naïve epileptic dog and a healthy dog from the same household and maintained on the same diet. Evaluation of large-scale microbial patterns based on 16S rRNA gene amplicon sequencing identified a household effect in the study population. Differential prevalence testing at the 16S rRNA gene sequence variant and genus levels did not identify any statistically significant differences between epileptic and control dogs. Quantitative PCR of Lactobacillus species isolated through culture revealed no statistically significant difference between the epileptic and control dogs (median concentration, 3.8 log10 CFU/g feces and 4.6 log10 CFU/g feces, respectively). Lactobacillus in culture was not killed by exposure to phenobarbital, potassium bromide, zonisamide, or levetiracetam. CONCLUSIONS: This pilot study did not identify any difference in large-scale microbial patterns or relative or absolute abundance of Lactobacillus species in drug-naïve epileptic dogs compared to healthy dogs. Further studies are warranted to evaluate the role of the gut microbiome in disease progression and treatment response in dogs with epilepsy. Lactobacilli in culture were not killed or inhibited from growing when exposed to phenobarbital, potassium bromide, zonisamide or levetiracetam, suggesting that antiepileptic drug administration is less likely to be a confounding factor in future studies evaluating the role of Lactobacillus in epilepsy.

The role of the microbiome in host evolution.

In the last decade, we have witnessed a major paradigm shift in the life sciences: the recognition that the microbiome, i.e. the set of microorganisms associated with healthy animals (including humans) and plants, plays a crucial role in the sustained health and fitness of its host. Enabled by rapid advances in sequencing technologies and analytical methods, substantial advances have been achieved in both identifying the microbial taxa and understanding the relationship between microbiome composition and host phenotype. These breakthroughs are leading to novel strategies for improved human and animal health, enhanced crop yield and nutritional quality, and the control of various pests and disease agents. This article is part of the theme issue 'The role of the microbiome in host evolution'.

Pathogen resistance may be the principal evolutionary advantage provided by the microbiome.

To survive, plants and animals must continually defend against pathogenic microbes that would invade and disrupt their tissues. Yet they do not attempt to extirpate all microbes. Instead, they tolerate and even encourage the growth of commensal microbes, which compete with pathogens for resources and via direct inhibition. We argue that hosts have evolved to cooperate with commensals in order to enhance the pathogen resistance this competition provides. We briefly describe competition between commensals and pathogens within the host, consider how natural selection might favour hosts that tilt this competition in favour of commensals, and describe examples of extant host traits that may serve this purpose. Finally, we consider ways that this cooperative immunity may have facilitated the adaptive evolution of non-pathogen-related host traits. On the basis of these observations, we argue that pathogen resistance vies with other commensal-provided benefits for being the principal evolutionary advantage provided by the microbiome to host lineages across the tree of life. This article is part of the theme issue 'The role of the microbiome in host evolution'.