Metagenomic analysis of microbial communities and antibiotic resistant genes in the Tijuana river, and potential sources

The Tijuana River is a transborder river that flows northwest across the border from Baja California in Mexico into Southern California before discharging into the Pacific Ocean. The river is frequently contaminated with raw sewage due to inadequate sanitary infrastructure in Tijuana. To assess the type and degree of microbial contamination, water samples were collected monthly from a near-border and an estuarine site from August 2020 until May 2021. A portion of each sample was used for epifluorescent microscopy and DNA was extracted directly from the rest for shotgun metagenomic sequencing. After sequence quality checking and processing, we used the rapid taxonomic identifier tool Kaiju to characterize the microbial diversity of the metagenomes and matched the sequences against the Comprehensive Antibiotic Resistance Database (CARD) to examine antimicrobial resistance genes (ARGs). Bacterial and viral-like particle (VLP) abundance was consistently higher in the near-border samples than in the estuarine samples, while alpha diversity (within sample biodiversity) was higher in estuarine samples. Beta-diversity analysis found clear compositional separation between samples from the two sites, and the near-border samples were more dissimilar to one another than were the estuarine sites. Near-border samples were dominated by fecal-associated bacteria and bacteria associated with sewage sludge, while estuarine sites were dominated by marine bacteria. ARGs were more abundant at the near-border site, but were also readily detectable in the estuarine samples, and the most abundant ARGs had multi-resistance to beta-lactam antibiotics. SourceTracker analysis identified human feces and sewage sludge to be the largest contributors to the near-border samples, while marine waters dominated estuarine samples except for two sewage overflow dates with high fecal contamination. Overall, our research determined human sewage microbes to be common in the Tijuana River, and the prevalence of ARGs confirms the importance of planned infrastructure treatment upgrades for environmental health.

AutoPhy: Automated phylogenetic identification of novel protein subfamilies

Phylogenetic analysis of protein sequences provides a powerful means of identifying novel protein functions and subfamilies, and for identifying and resolving annotation errors. However, automation of functional clustering based on phylogenetic trees has been challenging and most of it is done manually. Clustering phylogenetic trees usually requires the delineation of tree-based thresholds (e.g., distances), leading to an ad hoc problem. We propose a new phylogenetic clustering approach that identifies clusters without using ad hoc distances or other pre-defined values. Our workflow combines uniform manifold approximation and projection (UMAP) with Gaussian mixture models as a k-means like procedure to automatically group sequences into clusters. We then apply a "second pass" clade identification algorithm to resolve non-monophyletic groups. We tested our approach with several well-curated protein families (outer membrane porins, acyltransferase, and nuclear receptors) and showed our automated methods recapitulated known subfamilies. We also applied our methods to a broad range of different protein families from multiple databases, including Pfam, PANTHER, and UniProt, and to alignments of RNA viral genomes. Our results showed that AutoPhy rapidly generated monophyletic clusters (subfamilies) within phylogenetic trees evolving at very different rates both within and among phylogenies. The phylogenetic clusters generated by AutoPhy resolved misannotations and identified new protein functional groups and novel viral strains.

Metabolic dysregulation and gut dysbiosis linked to hyperandrogenism in female mice

INTRODUCTION

Polycystic ovary syndrome (PCOS) is a common endocrine pathology in women. In addition to infertility, women with PCOS have metabolic dysregulation which predisposes them to Type 2 diabetes, cardiovascular disease and non-alcoholic fatty liver disease. Moreover, women with PCOS have changes in their gut microbial community that may be indicative of dysbiosis. While hyperandrogenism is associated with both the development of metabolic dysfunction and gut dysbiosis in females, the mechanisms involved are not well understood.

METHODS

We used dihydrotestosterone (DHT) and ovariectomy (OVX) mouse models coupled with metabolic assessments and 16S rRNA gene sequencing to explore the contributions of hyperandrogenism and oestrogen deficiency to the development of insulin resistance and gut microbial dysbiosis in pubertal female mice.

RESULTS

We demonstrated that, while DHT treatment or OVX alone were insufficient to induce insulin resistance during the pubertal-to-adult transition, combining OVX with DHT resulted in insulin resistance similar to that observed in letrozole-treated mice with elevated testosterone and decreased oestrogen levels. In addition, our results showed that OVX and DHT in combination resulted in a distinct shift in the gut microbiome compared to DHT or OVX alone, suggesting that the substantial metabolic dysregulation occurring in the OVX + DHT model was accompanied by unique changes in the abundances of gut bacteria including S24-7, Rikenellaceae and Mucispirillum schaedleri.

CONCLUSIONS

While hyperandrogenism plays an important role in the development of metabolic dysregulation in female mice, our results indicate that investigation into additional factors influencing insulin resistance and the gut microbiome during the pubertal-to-adult transition could provide additional insight into the pathophysiology of PCOS.

Genetic hypogonadal mouse model reveals niche-specific influence of reproductive axis and sex on intestinal microbial communities

BACKGROUND

The gut microbiome has been linked to many diseases with sex bias including autoimmune, metabolic, neurological, and reproductive disorders. While numerous studies report sex differences in fecal microbial communities, the role of the reproductive axis in this differentiation is unclear and it is unknown how sex differentiation affects microbial diversity in specific regions of the small and large intestine.

METHODS

We used a genetic hypogonadal mouse model that does not produce sex steroids or go through puberty to investigate how sex and the reproductive axis impact bacterial diversity within the intestine. Using 16S rRNA gene sequencing, we analyzed alpha and beta diversity and taxonomic composition of fecal and intestinal communities from the lumen and mucosa of the duodenum, ileum, and cecum from adult female (n = 20) and male (n = 20) wild-type mice and female (n = 17) and male (n = 20) hypogonadal mice.

RESULTS

Both sex and reproductive axis inactivation altered bacterial composition in an intestinal section and niche-specific manner. Hypogonadism was significantly associated with bacteria from the Bacteroidaceae, Eggerthellaceae, Muribaculaceae, and Rikenellaceae families, which have genes for bile acid metabolism and mucin degradation. Microbial balances between males and females and between hypogonadal and wild-type mice were also intestinal section-specific. In addition, we identified 3 bacterial genera (Escherichia Shigella, Lachnoclostridium, and Eggerthellaceae genus) with higher abundance in wild-type female mice throughout the intestinal tract compared to both wild-type male and hypogonadal female mice, indicating that activation of the reproductive axis leads to female-specific differentiation of the gut microbiome. Our results also implicated factors independent of the reproductive axis (i.e., sex chromosomes) in shaping sex differences in intestinal communities. Additionally, our detailed profile of intestinal communities showed that fecal samples do not reflect bacterial diversity in the small intestine.

CONCLUSIONS

Our results indicate that sex differences in the gut microbiome are intestinal niche-specific and that sampling feces or the large intestine may miss significant sex effects in the small intestine. These results strongly support the need to consider both sex and reproductive status when studying the gut microbiome and while developing microbial-based therapies.

Taxonomic and functional restoration of tallgrass prairie soil microbial communities in comparison to remnant and agricultural soils

Restoring ecosystems requires the re-establishment of diverse soil microbial communities that drive critical ecosystem functions. In grasslands, restoration and management require the application of disturbances like fire and grazing. Disturbances can shape microbial taxonomic composition and potentially functional composition as well. We characterized taxonomic and functional gene composition of soil communities using whole genome shotgun metagenomic sequencing to determine how restored soil communities differed from pre-restoration agricultural soils and original remnant soils, how management affects soil microbes, and whether restoration and management affect the number of microbial genes associated with carbohydrate degradation. We found distinct differences in both taxonomic and functional diversity and composition among restored, remnant, and agricultural soils. Remnant soils had low taxonomic and functional richness and diversity, as well as distinct composition, indicating that restoration of agricultural soils does not re-create soil microbial communities that match remnants. Prescribed fire management increased functional diversity, which also was higher in more recently planted restorations. Finally, restored and post-fire soils included high abundances of genes encoding cellulose-degrading enzymes, so restorations and their ongoing management can potentially support functions important in carbon cycling.

Sex, puberty, and the gut microbiome

In brief

Sex differences in the gut microbiome may impact multiple aspects of human health and disease. In this study, we review the evidence for microbial sex differences in puberty and adulthood and discuss potential mechanisms driving differentiation of the sex-specific gut microbiome.

Abstract

In humans, the gut microbiome is strongly implicated in numerous sex-specific physiological processes and diseases. Given this, it is important to understand how sex differentiation of the gut microbiome occurs and how these differences contribute to host health and disease. While it is commonly believed that the gut microbiome stabilizes after 3 years of age, our review of the literature found considerable evidence that the gut microbiome continues to mature during and after puberty in a sex-dependent manner. We also review the intriguing, though sparse, literature on potential mechanisms by which host sex may influence the gut microbiome, and vice versa, via sex steroids, bile acids, and the immune system. We conclude that the evidence for the existence of a sex-specific gut microbiome is strong but that there is a dearth of research on how host-microbe interactions lead to this differentiation. Finally, we discuss the types of future studies needed to understand the processes driving the maturation of sex-specific microbial communities and the interplay between gut microbiota, host sex, and human health.

Metagenomic Analysis of Microbial Contamination in the U.S. Portion of the Tijuana River Watershed

The Tijuana River watershed is binational, flowing from Tijuana, Mexico into San Diego and Imperial Beach, USA. Aging sewage and stormwater infrastructure in Tijuana has not kept pace with population growth, causing overflows into this watershed during major rainfall or equipment failures. The public health consequences of this impaired watershed on the surrounding communities remain unknown. Here, we performed untargeted metagenomic sequencing to better characterize the sewage contamination in the Tijuana River, identifying potential pathogens and molecular indicators of antibiotic resistance in surface waters. In 2019-2020, water samples were collected within 48 h of major rainfall events at five transborder flow sites and at the mouth of the river in the US portion of the Tijuana River and estuary. After filtration, DNA was extracted and sequenced, and sequences were run through the Kaiju taxonomic classification program. A pathogen profile of the most abundant disease-causing microbes and viruses present in each of the samples was constructed, and specific markers of fecal contamination were identified and linked to each site. Results from diversity analysis between the sites showed clear distinction as well as similarities between sites and dates, and antibiotic-resistant genes were found at each site. This serves as a baseline characterization of microbial exposures to these local communities.

Automated high confidence compound identification of electron ionization mass spectra for nontargeted analysis

Nontargeted analysis based on mass spectrometry is a rising practice in environmental monitoring for identifying contaminants of emerging concern. Nontargeted analysis performed using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC/TOF-MS) generates large numbers of possible analytes. Moreover, the default spectral library similarity score-based search algorithm used by LECO® ChromaTOF® does not ensure that high similarity scores result in correct library matches. Therefore, an additional manual screening is necessary, but leads to human errors especially when dealing with large amounts of data. To improve the speed and accuracy of the chemical identification, we developed CINeMA.py (Classification Is Never Manual Again). This programming suite automates GC×GC/TOF-MS data interpretation by determining the confidence of a match between the observed analyte mass spectrum and the LECO® ChromaTOF® software generated library hit from the NIST Electron Ionization Mass Spectral (NIST EI-MS) library. Our script allows the user to evaluate the confidence of the match using an algorithmic method that mimics the manual curation process and two different machine learning approaches (neural networks and random forest). The script allows the user to adjust various parameters (e.g., similarity threshold) and study their effects on prediction accuracy. To test CINeMA.py, we used data from two different environmental contaminant studies: an EPA study on household dust and a study on stormwater runoff. Using a reference set based on the analysis performed by highly trained users of the ChromaTOF and GC×GC/TOF-MS systems, the random forest model had the highest prediction accuracies of 86% and 83% on the EPA and Stormwater data sets, respectively. The algorithmic approach had the second-best prediction accuracy (82% and 79%), while the neural network accuracy had the lowest (63% and 67%). All the approaches required less than 1 min to classify 986 observed analytes, whereas manual data analysis required hours or days to complete. Our methods were also able to detect high confidence matches missed during the manual review. Overall, CINeMA.py provides users with a powerful suite of tools that should significantly speed-up data analysis while reducing the possibilities of manual errors and discrepancies among users, and can be applicable to other GC/EI-MS instrument based nontargeted analysis.

Altered microbiomes in thirdhand smoke-exposed children and their home environments

INTRODUCTION

Tobacco smoke contains numerous toxic chemicals that accumulate in indoor environments creating thirdhand smoke (THS). We investigated if THS-polluted homes differed in children's human and built-environment microbiomes as compared to THS-free homes.

METHODS

Participants were n = 19 THS-exposed children and n = 10 unexposed children (≤5 years) and their caregivers. Environmental and biological samples were analyzed for THS pollutants and exposure. Swab samples were collected from the built-environment (floor, table, armrest, bed frame) and child (finger, nose, mouth, and ear canal), and 16S ribosomal RNA genes were analyzed for bacterial taxa using high-throughput DNA sequencing.

RESULTS

Phylogenetic α-diversity was significantly higher for the built-environment microbiomes in THS-polluted homes compared to THS-free homes (p < 0.014). Log2-fold comparison found differences between THS-polluted and THS-free homes for specific genera in samples from the built-environment (e.g., Acinetobacter, Bradyrhizobium, Corynebacterium, Gemella, Neisseria, Staphylococcus, Streptococcus, and Veillonella) and in samples from children (esp. Corynebacterium, Gemella, Lautropia, Neisseria, Rothia, Staphylococcus, and Veillonella).

CONCLUSION

When exposed to THS, indoor and children microbiomes are altered in an environment-specific manner. Changes are similar to those reported in previous studies for smokers and secondhand smoke-exposed persons. THS-induced changes in child and built-environmental microbiomes may play a role in clinical outcomes in children.

IMPACT

Despite smoking bans, children can be exposed to tobacco smoke residue (i.e., thirdhand smoke) that lingers on surfaces and in settled house dust. Thirdhand smoke exposure is associated with changes in the microbiomes of the home environment and of the children living in these homes. Thirdhand smoke is associated with increased phylogenetic diversity of the home environment and changes in the abundances of several genera of the child microbiome known to be affected by active smoking and secondhand smoke (e.g., Corynebacterium, Staphylococcus, Streptococcus). Thirdhand smoke exposure by itself may induce alterations in the microbiome that play a role in childhood pathologies.

Compositional Data Analysis of Periodontal Disease Microbial Communities

Periodontal disease (PD) is a chronic, progressive polymicrobial disease that induces a strong host immune response. Culture-independent methods, such as next-generation sequencing (NGS) of bacteria 16S amplicon and shotgun metagenomic libraries, have greatly expanded our understanding of PD biodiversity, identified novel PD microbial associations, and shown that PD biodiversity increases with pocket depth. NGS studies have also found PD communities to be highly host-specific in terms of both biodiversity and the response of microbial communities to periodontal treatment. As with most microbiome work, the majority of PD microbiome studies use standard data normalization procedures that do not account for the compositional nature of NGS microbiome data. Here, we apply recently developed compositional data analysis (CoDA) approaches and software tools to reanalyze multiomics (16S, metagenomics, and metabolomics) data generated from previously published periodontal disease studies. CoDA methods, such as centered log-ratio (clr) transformation, compensate for the compositional nature of these data, which can not only remove spurious correlations but also allows for the identification of novel associations between microbial features and disease conditions. We validated many of the studies’ original findings, but also identified new features associated with periodontal disease, including the genera Schwartzia and Aerococcus and the cytokine C-reactive protein (CRP). Furthermore, our network analysis revealed a lower connectivity among taxa in deeper periodontal pockets, potentially indicative of a more “random” microbiome. Our findings illustrate the utility of CoDA techniques in multiomics compositional data analysis of the oral microbiome.

Building a Diverse Workforce and Thinkforce to Reduce Health Disparities

The Research Centers in Minority Institutions (RCMI) Program was congressionally mandated in 1985 to build research capacity at institutions that currently and historically recruit, train, and award doctorate degrees in the health professions and health-related sciences, primarily to individuals from underrepresented and minority populations. RCMI grantees share similar infrastructure needs and institutional goals. Of particular importance is the professional development of multidisciplinary teams of academic and community scholars (the "workforce") and the harnessing of the heterogeneity of thought (the "thinkforce") to reduce health disparities. The purpose of this report is to summarize the presentations and discussion at the RCMI Investigator Development Core (IDC) Workshop, held in conjunction with the RCMI Program National Conference in Bethesda, Maryland, in December 2019. The RCMI IDC Directors provided information about their professional development activities and Pilot Projects Programs and discussed barriers identified by new and early-stage investigators that limit effective career development, as well as potential solutions to overcome such obstacles. This report also proposes potential alignments of professional development activities, targeted goals and common metrics to track productivity and success.

Quantitative profiling of built environment bacterial and fungal communities reveals dynamic material dependent growth patterns and microbial interactions

Indoor microbial communities vary in composition and diversity depending on material type, moisture levels, and occupancy. In this study, we integrated bacterial cell counting, fungal biomass estimation, and fluorescence-assisted cell sorting (FACS) with amplicon sequencing of bacterial (16S rRNA) and fungal (ITS) communities to investigate the influence of wetting on medium density fiberboard (MDF) and gypsum wallboard. Surface samples were collected longitudinally from wetted materials maintained at high relative humidity (~95%). Bacterial and fungal growth patterns were strongly time-dependent and material-specific. Fungal growth phenotypes differed between materials: spores dominated MDF surfaces while fungi transitioned from spores to hyphae on gypsum. FACS confirmed that most of the bacterial cells were intact (viable) on both materials over the course of the study. Integrated cell count and biomass data (quantitative profiling) revealed that small changes in relative abundance often resulted from large changes in absolute abundance, while negative correlations in relative abundances were explained by rapid growth of only one group of bacteria or fungi. Comparisons of bacterial-bacterial and fungal-bacterial networks suggested a top-down control of fungi on bacterial growth, possibly via antibiotic production. In conclusion, quantitative profiling provides novel insights into microbial growth dynamics on building materials with potential implications for human health.

Alterations in Gut Microbiota Do Not Play a Causal Role in Diet-independent Weight Gain Caused by Ovariectomy

Acute estrogen deficiency in women can occur due to many conditions including hyperprolactinemia, chemotherapy, GnRH agonist treatment, and removal of hormone replacement therapy. Ovariectomized (OVX) rodent models, often combined with a high-fat diet (HFD), have been used to investigate the effects of decreased estrogen production on metabolism. Since evidence suggests that gut microbes may facilitate the protective effect of estrogen on metabolic dysregulation in an OVX + HFD model, we investigated whether the gut microbiome plays a role in the diet-independent weight gain that occurs after OVX in adult female mice. 16S rRNA gene sequence analysis demonstrated that OVX was not associated with changes in overall gut bacterial biodiversity but was correlated with a shift in beta diversity. Using differential abundance analysis, we observed a difference in the relative abundance of a few bacterial taxa, such as Turicibacter, 3 to 5 weeks after OVX, which was subsequent to the weight gain that occurred 2 weeks postsurgery. A cohousing study was performed to determine whether exposure to a healthy gut microbiome was protective against the development of the metabolic phenotype associated with OVX. Unlike mouse models of obesity, HFD maternal-induced metabolic dysregulation, or polycystic ovary syndrome, cohousing OVX mice with healthy mice did not improve the metabolic phenotype of OVX mice. Altogether, these results indicate that changes in the gut microbiome are unlikely to play a causal role in diet-independent, OVX-induced weight gain (since they occurred after the weight gain) and cohousing with healthy mice did not have a protective effect.

An application of compositional data analysis to multiomic time-series data

Compositional data analysis (CoDA) methods have increased in popularity as a new framework for analyzing next-generation sequencing (NGS) data. CoDA methods, such as the centered log-ratio (clr) transformation, adjust for the compositional nature of NGS counts, which is not addressed by traditional normalization methods. CoDA has only been sparsely applied to NGS data generated from microbial communities or to multiple ‘omics’ datasets. In this study, we applied CoDA methods to analyze NGS and untargeted metabolomic datasets obtained from bacterial and fungal communities. Specifically, we used clr transformation to reanalyze NGS amplicon and metabolomics data from a study investigating the effects of building material type, moisture and time on microbial and metabolomic diversity. Compared to analysis of untransformed data, analysis of clr-transformed data revealed novel relationships and stronger associations between sample conditions and microbial and metabolic community profiles.

Chemical composition of material extractives influences microbial growth and dynamics on wetted wood materials

The impact of material chemical composition on microbial growth on building materials remains relatively poorly understood. We investigate the influence of the chemical composition of material extractives on microbial growth and community dynamics on 30 different wood species that were naturally inoculated, wetted, and held at high humidity for several weeks. Microbial growth was assessed by visual assessment and molecular sequencing. Unwetted material powders and microbial swab samples were analyzed using reverse phase liquid chromatography with tandem mass spectrometry. Different wood species demonstrated varying susceptibility to microbial growth after 3 weeks and visible coverage and fungal qPCR concentrations were correlated (R2 = 0.55). Aspergillaceae was most abundant across all samples; Meruliaceae was more prevalent on 8 materials with the highest visible microbial growth. A larger and more diverse set of compounds was detected from the wood shavings compared to the microbial swabs, indicating a complex and heterogeneous chemical composition within wood types. Several individual compounds putatively identified in wood samples showed statistically significant, near-monotonic associations with microbial growth, including C11H16O4, C18H34O4, and C6H15NO. A pilot experiment confirmed the inhibitory effects of dosing a sample of wood materials with varying concentrations of liquid C6H15NO (assuming it presented as Diethylethanolamine).

Temporal variations in bacterial community diversity and composition throughout intensive care unit renovations

BACKGROUND

Inanimate surfaces within a hospital serve as a reservoir of microbial life that may colonize patients and ultimately result in healthcare associated infections (HAIs). Critically ill patients in intensive care units (ICUs) are particularly vulnerable to HAIs. Little is known about how the microbiome of the ICU is established or what factors influence its evolution over time. A unique opportunity to bridge the knowledge gap into how the ICU microbiome evolves emerged in our health system, where we were able to characterize microbial communities in an established hospital ICU prior to closing for renovations, during renovations, and then after re-opening.

RESULTS

We collected swab specimens from ICU bedrails, computer keyboards, and sinks longitudinally at each renovation stage, and analyzed the bacterial compositions on these surfaces by 16S rRNA gene sequencing. Specimens collected before ICU closure had the greatest alpha diversity, while specimens collected after the ICU had been closed for over 300 days had the least. We sampled the ICU during the 45 days after re-opening; however, within that time frame, the alpha diversity never reached pre-closure levels. There were clear and significant differences in microbiota compositions at each renovation stage, which was driven by environmental bacteria after closure and human-associated bacteria after re-opening and before closure.

CONCLUSIONS

Overall, we identified significant differences in microbiota diversity and community composition at each renovation stage. These data help to decipher the evolution of the microbiome in the most critical part of the hospital and demonstrate the significant impacts that microbiota from patients and staff have on the evolution of ICU surfaces. Video Abstract.

Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics

Background

Microbial source tracking methods are used to determine the origin of contaminating bacteria and other microorganisms, particularly in contaminated water systems. The Bayesian SourceTracker approach uses deep-sequencing marker gene libraries (16S ribosomal RNA) to determine the proportional contributions of bacteria from many potential source environments to a given sink environment simultaneously. Since its development, SourceTracker has been applied to an extensive diversity of studies, from beach contamination to human behavior.

Methods

Here, we demonstrate a novel application of SourceTracker to work with metagenomic datasets and tested this approach using sink samples from a study of coastal marine environments. Source environment metagenomes were obtained from metagenomics studies of gut, freshwater, marine, sand and soil environments. As part of this effort, we implemented features for determining the stability of source proportion estimates, including precision visualizations for performance optimization, and performed domain-specific source-tracking analyses (i.e., Bacteria, Archaea, Eukaryota and viruses). We also applied SourceTracker to metagenomic libraries generated from samples collected from the International Space Station (ISS).

Results

SourceTracker proved highly effective at predicting the composition of known sources using shotgun metagenomic libraries. In addition, we showed that different taxonomic domains sometimes presented highly divergent pictures of environmental source origins for both the coastal marine and ISS samples. These findings indicated that applying SourceTracker to separate domains may provide a deeper understanding of the microbial origins of complex, mixed-source environments, and further suggested that certain domains may be preferable for tracking specific sources of contamination.

Viruses in the Built Environment (VIBE) meeting report

BACKGROUND

During a period of rapid growth in our understanding of the microbiology of the built environment in recent years, the majority of research has focused on bacteria and fungi. Viruses, while probably as numerous, have received less attention. In response, the Alfred P. Sloan Foundation supported a workshop entitled "Viruses in the Built Environment (VIBE)," at which experts in environmental engineering, environmental microbiology, epidemiology, infection prevention, fluid dynamics, occupational health, metagenomics, and virology convened to synthesize recent advances and identify key research questions and knowledge gaps regarding viruses in the built environment.

RESULTS

Four primary research areas and funding priorities were identified. First, a better understanding of viral communities in the built environment is needed, specifically which viruses are present and their sources, spatial and temporal dynamics, and interactions with bacteria. Second, more information is needed about viruses and health, including viral transmission in the built environment, the relationship between virus detection and exposure, and the definition of a healthy virome. The third research priority is to identify and evaluate interventions for controlling viruses and the virome in the built environment. This encompasses interactions among viruses, buildings, and occupants. Finally, to overcome the challenge of working with viruses, workshop participants emphasized that improved sampling methods, laboratory techniques, and bioinformatics approaches are needed to advance understanding of viruses in the built environment.

CONCLUSIONS

We hope that identifying these key questions and knowledge gaps will engage other investigators and funding agencies to spur future research on the highly interdisciplinary topic of viruses in the built environment. There are numerous opportunities to advance knowledge, as many topics remain underexplored compared to our understanding of bacteria and fungi. Video abstract.

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

Letrozole treatment of pubertal female mice results in activational effects on reproduction, metabolism and the gut microbiome

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in reproductive-aged women that is comprised of two out of the following three features: hyperandrogenism, oligo- or amenorrhea, or polycystic ovaries. In addition to infertility, many women with PCOS have metabolic dysregulation that increases the risk of developing type 2 diabetes, hypertension, and non-alcoholic fatty liver disease. Changes in the gut microbiome are associated with PCOS and gut microbes may be involved in the pathology of this disorder. Since PCOS often manifests in the early reproductive years, puberty is considered to be a critical time period for the development of PCOS. Exposure to sex steroid hormones during development results in permanent, organizational effects, while activational effects are transient and require the continued presence of the hormone. Androgens exert organizational effects during prenatal or early post-natal development, but it is unclear whether androgen excess results in organizational or activational effects during puberty. We recently developed a letrozole-induced PCOS mouse model that recapitulates both reproductive and metabolic phenotypes of PCOS. In this study, we investigated whether letrozole treatment of pubertal female mice exerts organizational or activational effects on host physiology and the gut microbiome. Two months after letrozole removal, we observed recovery of reproductive and metabolic parameters, as well as diversity and composition of the gut microbiome, indicating that letrozole treatment of female mice during puberty resulted in predominantly activational effects. These results suggest that if exposure to excess androgens during puberty leads to the development of PCOS, reduction of androgen levels during this time may improve reproductive and metabolic phenotypes in women with PCOS. These results also imply that continuous letrozole exposure is required to model PCOS in pubertal female mice since letrozole exerts activational rather than organizational effects during puberty.

Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Age- and Sex-Dependent Patterns of Gut Microbial Diversity in Human Adults

Gut microbial diversity changes throughout the human life span and is known to be associated with host sex. We investigated the association of age, sex, and gut bacterial alpha diversity in three large cohorts of adults from four geographical regions: subjects from the United States and United Kingdom in the American Gut Project (AGP) citizen-science initiative and two independent cohorts of Colombians and Chinese. In three of the four cohorts, we observed a strong positive association between age and alpha diversity in young adults that plateaued after age 40 years. We also found sex-dependent differences that were more pronounced in younger adults than in middle-aged adults, with women having higher alpha diversity than men. In contrast to the other three cohorts, no association of alpha diversity with age or sex was observed in the Chinese cohort. The association of alpha diversity with age and sex remained after adjusting for cardiometabolic parameters in the Colombian cohort and antibiotic usage in the AGP cohort. We further attempted to predict the microbiota age in individuals using a machine-learning approach for the men and women in each cohort. Consistent with our alpha-diversity-based findings, U.S. and U.K. women had a significantly higher predicted microbiota age than men, with a reduced difference being seen above age 40 years. This difference was not observed in the Colombian cohort and was observed only in middle-aged Chinese adults. Together, our results provide new insights into the influence of age and sex on the biodiversity of the human gut microbiota during adulthood while highlighting similarities and differences across diverse cohorts. IMPORTANCE Microorganisms in the human gut play a role in health and disease, and in adults higher gut biodiversity has been linked to better health. Since gut microorganisms may be pivotal in the development of microbial therapies, understanding the factors that shape gut biodiversity is of utmost interest. We performed large-scale analyses of the relationship of age and sex to gut bacterial diversity in adult cohorts from four geographic regions: the United States, the United Kingdom, Colombia, and China. In the U.S., U.K., and Colombian cohorts, bacterial biodiversity correlated positively with age in young adults but plateaued at about age 40 years, with no positive association being found in middle-aged adults. Young, but not middle-aged, adult women had higher gut bacterial diversity than men, a pattern confirmed via supervised machine learning. Interestingly, in the Chinese cohort, minimal associations were observed between gut biodiversity and age or sex. Our results highlight the patterns of adult gut biodiversity and provide a framework for future research.

Effects of moderate, voluntary ethanol consumption on the rat and human gut microbiome

Many alcohol-induced health complications are directly attributable to the toxicity of alcohol or its metabolites, but another potential health impact of alcohol may be on the microbial communities of the human gut. Clear distinctions between healthy and diseased-state gut microbiota have been observed in subjects with metabolic diseases, and recent studies suggest that chronic alcoholism is linked to gut microbiome dysbiosis. Here, we investigated the effects of moderate levels of alcohol consumption on the gut microbiome in both rats and humans. The gut microbiota of rats voluntarily consuming a 20 percent ethanol solution, on alternate days, were compared with a non-exposed control group to identify differential taxonomic and functional profiles. Gut microbial diversity profiles were determined using culture-independent amplification, next-generation sequencing and bioinformatic analysis of bacterial 16S ribosomal RNA gene sequence libraries. Our results showed that, compared with controls, ethanol-consuming rats experienced a significant decline in the biodiversity of their gut microbiomes, a state generally associated with dysbiosis. We also observed significant shifts in the overall diversity of the gut microbial communities and a dramatic change in the relative abundance of particular microbes, such as the Lactobacilli. We also compared our results to human fecal microbiome data collected as part of the citizen science American Gut Project. In contrast to the rat data, human drinkers had significantly higher gut microbial biodiversity than non-drinkers. However, we also observed that microbes that differed among the human subjects displayed similar trends in the rat model, including bacteria implicated in metabolic disease.

Exposure to a Healthy Gut Microbiome Protects Against Reproductive and Metabolic Dysregulation in a PCOS Mouse Model

Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting ∼10% to 15% of reproductive-aged women worldwide. Diagnosis requires two of the following: hyperandrogenism, oligo-ovulation or anovulation, and polycystic ovaries. In addition to reproductive dysfunction, many women with PCOS display metabolic abnormalities associated with hyperandrogenism. Recent studies have reported that the gut microbiome is altered in women with PCOS and rodent models of the disorder. However, it is unknown whether the gut microbiome plays a causal role in the development and pathology of PCOS. Given its potential role, we hypothesized that exposure to a healthy gut microbiome would protect against development of PCOS. A cohousing study was performed using a letrozole-induced PCOS mouse model that recapitulates many reproductive and metabolic characteristics of PCOS. Because mice are coprophagic, cohousing results in repeated, noninvasive inoculation of gut microbes in cohoused mice via the fecal-oral route. In contrast to letrozole-treated mice housed together, letrozole mice cohoused with placebo mice showed significant improvement in both reproductive and metabolic PCOS phenotypes. Using 16S rRNA gene sequencing, we also observed that the overall composition of the gut microbiome and the relative abundance of Coprobacillus and Lactobacillus differed in letrozole-treated mice cohoused with placebo mice compared with letrozole mice housed together. These results suggest that dysbiosis of the gut microbiome may play a causal role in PCOS and that modulation of the gut microbiome may be a potential treatment option for PCOS.

Seasonal dynamics of DNA and RNA viral bioaerosol communities in a daycare center

BACKGROUND

Viruses play an important role in ecosystems, including the built environment (BE). While numerous studies have characterized bacterial and fungal microbiomes in the BE, few have focused on the viral microbiome (virome). Longitudinal microbiome studies provide insight into the stability and dynamics of microbial communities; however, few such studies exist for the microbiome of the BE, and most have focused on bacteria. Here, we present a longitudinal, metagenomic-based analysis of the airborne DNA and RNA virome of a children's daycare center. Specifically, we investigate how the airborne virome varies as a function of season and human occupancy, and we identify possible sources of the viruses and their hosts, mainly humans, animals, plants, and insects.

RESULTS

Season strongly influenced the airborne viral community composition, and a single sample collected when the daycare center was unoccupied suggested that occupancy also influenced the community. The pattern of influence differed between DNA and RNA viromes. Human-associated viruses were much more diverse and dominant in the winter, while the summertime virome contained a high relative proportion and diversity of plant-associated viruses.

CONCLUSIONS

This airborne microbiome in this building exhibited seasonality in its viral community but not its bacterial community. Human occupancy influenced both types of communities. By adding new data about the viral microbiome to complement burgeoning information about the bacterial and fungal microbiomes, this study contributes to a more complete understanding of the airborne microbiome.

Letrozole treatment of adult female mice results in a similar reproductive phenotype but distinct changes in metabolism and the gut microbiome compared to pubertal mice

BACKGROUND

A majority of women with polycystic ovary syndrome (PCOS) have metabolic dysfunction that results in an increased risk of type 2 diabetes. We previously developed a pubertal mouse model using the aromatase inhibitor, letrozole, which recapitulates many of the reproductive and metabolic features of PCOS. To further our understanding of the effects of androgen excess, we compared the effects of letrozole treatment initiated in puberty versus adulthood on reproductive and metabolic phenotypes as well as on the gut microbiome.

RESULTS

Letrozole treatment of both pubertal and adult female mice resulted in reproductive hallmarks of PCOS, including hyperandrogenemia, anovulation and polycystic ovaries. However, unlike pubertal mice, treatment of adult female mice resulted in modest weight gain and abdominal adiposity, minimal elevation in fasting blood glucose and insulin levels, and no detectable insulin resistance. In addition, letrozole treatment of adult mice was associated with a distinct shift in gut microbial diversity compared to letrozole treatment of pubertal mice.

CONCLUSIONS

Our results indicate that dysregulation of metabolism and the gut microbiome in PCOS may be influenced by the timing of androgen exposure. In addition, the minimal weight gain and lack of insulin resistance in adult female mice after letrozole treatment indicates that this model may be useful for investigating the effects of hyperandrogenemia on the hypothalamic-pituitary-gonadal axis and the periphery without the influence of substantial metabolic dysregulation.

Discovery of a Novel Periodontal Disease-Associated Bacterium

One of the world's most common infectious disease, periodontitis (PD), derives from largely uncharacterized communities of oral bacteria growing as biofilms (a.k.a. plaque) on teeth and gum surfaces in periodontal pockets. Bacteria associated with periodontal disease trigger inflammatory responses in immune cells, which in later stages of the disease cause loss of both soft and hard tissue structures supporting teeth. Thus far, only a handful of bacteria have been characterized as infectious agents of PD. Although deep sequencing technologies, such as whole community shotgun sequencing have the potential to capture a detailed picture of highly complex bacterial communities in any given environment, we still lack major reference genomes for the oral microbiome associated with PD and other diseases. In recent work, by using a combination of supervised machine learning and genome assembly, we identified a genome from a novel member of the Bacteroidetes phylum in periodontal samples. Here, by applying a comparative metagenomics read-classification approach, including 272 metagenomes from various human body sites, and our previously assembled draft genome of the uncultivated Candidatus Bacteroides periocalifornicus (CBP) bacterium, we show CBP's ubiquitous distribution in dental plaque, as well as its strong association with the well-known pathogenic "red complex" that resides in deep periodontal pockets.

Gut Microbial Diversity in Women With Polycystic Ovary Syndrome Correlates With Hyperandrogenism

CONTEXT

A majority of women with polycystic ovary syndrome (PCOS) have metabolic abnormalities that result in an increased risk of developing type 2 diabetes and heart disease. Correlative studies have shown an association between changes in the gut microbiome and metabolic disorders. Two recent studies reported a decrease in α diversity of the gut microbiome in women with PCOS compared with healthy women.

OBJECTIVE

We investigated whether changes in the gut microbiome correlated with specific clinical parameters in women with PCOS compared with healthy women. We also investigated whether there were changes in the gut microbiome in women with polycystic ovarian morphology (PCOM) who lacked the other diagnostic criteria of PCOS.

PARTICIPANTS

Subjects were recruited at the Poznan University of Medical Sciences. Fecal microbial diversity profiles of healthy women (n = 48), women with PCOM (n = 42), and women diagnosed with PCOS using the Rotterdam criteria (n = 73) were analyzed using 16S ribosomal RNA gene sequencing.

RESULTS

Lower α diversity was observed in women with PCOS compared with healthy women. Women with PCOM had a change in α diversity that was intermediate between that of the other two groups. Regression analyses showed that hyperandrogenism, total testosterone, and hirsutism were negatively correlated with α diversity. Permutational multivariate analysis of variance in UniFrac distances showed that hyperandrogenism was also correlated with β diversity. A random forest identified bacteria that discriminated between healthy women and women with PCOS.

CONCLUSION

These results suggest that hyperandrogenism may play a critical role in altering the gut microbiome in women with PCOS.

Periodontal disease and its connection to systemic biomarkers of cardiovascular disease in young American Indian/Alaskan natives

BACKGROUND

Periodontal disease has been shown to be associated with cardiovascular disease (CVD). No known studies evaluate the relationship between periodontal disease status and biomarkers of CVD risk in the American Indian/Alaskan Native (AI/AN) population despite their disproportionately high rates of poor oral health and cardiovascular disease-related outcomes. This study compared levels of interleukin (IL)-6 and C-reactive protein (CRP) across increasing severity of periodontal disease status among younger adults between the ages of 21 and 43 years.

METHODS

Plasma levels of IL-6 and CRP were measured in adult participants (ages 21 to 43 years) as part of a study of periodontal disease and CVD risk among an AI/AN population in southern California (n = 59). Periodontal evaluations were performed and disease status was classified into three categories based on highest probing depth (none/mild: < 3 mm; moderate: 4 to 5 mm; severe: ≥6 mm). Participants with known systemic disease or active infection were excluded.

RESULTS

Severe periodontitis was significantly associated with increased levels of IL-6 compared with those with none or mild periodontitis before controlling for other variables (P = 0.02), but lacked significance after controlling for sex, BMI, smoking status, and high-density lipoprotein (P = 0.09). Moderate periodontal disease was positively associated with IL-6 levels after controlling for potential confounders (P = 0.01). Periodontal status was not associated with CRP, before or after adjusting for covariates.

CONCLUSIONS

In this otherwise healthy AI/AN adult sample, moderate periodontal disease compared with none or mild periodontal disease was associated with increased levels of IL-6. High levels of CRP found in this population warrant further research.

Sampling, Extraction, and High-Throughput Sequencing Methods for Environmental Microbial and Viral Communities

The emergence of high-throughput sequencing technologies has deepened our understanding of complex microbial communities and greatly facilitated the study of as-yet uncultured microbes and viruses. Studies of complex microbial communities require high-quality data to generate valid results. Here, we detail current methods of microbial and viral community sample acquisition, DNA extraction, sample preparation, and sequencing on Illumina high-throughput platforms. While using appropriate analytical tools is important, it must not overshadow the need for establishing a proper experimental design and obtaining sufficient numbers of samples for statistical purposes. Researchers must also take care to sample biologically relevant sites and control for potential confounding factors (e.g., contamination).

Endosymbiont interference and microbial diversity of the Pacific coast tick, Dermacentor occidentalis, in San Diego County, California

The Pacific coast tick, Dermacentor occidentalis Marx, is found throughout California and can harbor agents that cause human diseases such as anaplasmosis, ehrlichiosis, tularemia, Rocky Mountain spotted fever and rickettsiosis 364D. Previous studies have demonstrated that nonpathogenic endosymbiotic bacteria can interfere with Rickettsia co-infections in other tick species. We hypothesized that within D. occidentalis ticks, interference may exist between different nonpathogenic endosymbiotic or nonendosymbiotic bacteria and Spotted Fever group Rickettsia (SFGR). Using PCR amplification and sequencing of the rompA gene and intergenic region we identified a cohort of SFGR-infected and non-infected D. occidentalis ticks collected from San Diego County. We then amplified a partial segment of the 16S rRNA gene and used next-generation sequencing to elucidate the microbiomes and levels of co-infection in the ticks. The SFGR R. philipii str. 364D and R. rhipicephali were detected in 2.3% and 8.2% of the ticks, respectively, via rompA sequencing. Interestingly, next generation sequencing revealed an inverse relationship between the number of Francisella-like endosymbiont (FLE) 16S rRNA sequences and Rickettsia 16S rRNA sequences within individual ticks that is consistent with partial interference between FLE and SFGR infecting ticks. After excluding the Rickettsia and FLE endosymbionts from the analysis, there was a small but significant difference in microbial community diversity and a pattern of geographic isolation by distance between collection locales. In addition, male ticks had a greater diversity of bacteria than female ticks and ticks that weren’t infected with SFGR had similar microbiomes to canine skin microbiomes. Although experimental studies are required for confirmation, our findings are consistent with the hypothesis that FLEs and, to a lesser extent, other bacteria, interfere with the ability of D. occidentalis to be infected with certain SFGR. The results also raise interesting possibilities about the effects of putative vertebrate hosts on the tick microbiome.

Rapid assemblage of diverse environmental fungal communities on public restroom floors

An increasing proportion of humanity lives in urban environments where they spend most of their lives indoors. Recent molecular studies have shown that bacterial assemblages in built environments (BEs) are extremely diverse, but BE fungal diversity remains poorly understood. We applied culture-independent methods based on next-generation sequencing (NGS) of the fungal internal transcribed spacer to investigate the diversity and temporal dynamics of fungi in restrooms. Swab samples were collected weekly from three different surfaces in two public restrooms (male and female) in San Diego, CA, USA, over an 8-week period. DNA amplification and culturing methods both found that the floor samples had significantly higher fungal loads than other surfaces. NGS sequencing of floor fungal assemblages identified a total of 2550 unique phylotypes (~800 per sample), less than half of which were identifiable. Of the known fungi, the majority came from environmental sources and we found little evidence of known human skin fungi. Fungal assemblages reformed rapidly in a highly consistent manner, and the variance in the species diversity among samples was low. Overall, our study contributes to a better understanding of public restroom floor fungal communities.

Ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses

BACKGROUND

Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a "foundation" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, "extension" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new "extension tree" child.

RESULTS

We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes.

CONCLUSIONS

The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees.

AVAILABILITY

ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree .

The Gut Microbiome Is Altered in a Letrozole-Induced Mouse Model of Polycystic Ovary Syndrome

Women with polycystic ovary syndrome (PCOS) have reproductive and metabolic abnormalities that result in an increased risk of infertility, diabetes and cardiovascular disease. The large intestine contains a complex community of microorganisms (the gut microbiome) that is dysregulated in humans with obesity and type 2 diabetes. Using a letrozole-induced PCOS mouse model, we demonstrated significant diet-independent changes in the gut microbial community, suggesting that gut microbiome dysbiosis may also occur in PCOS women. Letrozole treatment was associated with a time-dependent shift in the gut microbiome and a substantial reduction in overall species and phylogenetic richness. Letrozole treatment also correlated with significant changes in the abundance of specific Bacteroidetes and Firmicutes previously implicated in other mouse models of metabolic disease in a time-dependent manner. Our results suggest that the hyperandrogenemia observed in PCOS may significantly alter the gut microbiome independently of diet.

Characterization of the salivary microbiome in patients with pancreatic cancer

Clinical manifestations of pancreatic cancer often do not occur until the cancer has undergone metastasis, resulting in a very low survival rate. In this study, we investigated whether salivary bacterial profiles might provide useful biomarkers for early detection of pancreatic cancer. Using high-throughput sequencing of bacterial small subunit ribosomal RNA (16S rRNA) gene, we characterized the salivary microbiota of patients with pancreatic cancer and compared them to healthy patients and patients with other diseases, including pancreatic disease, non-pancreatic digestive disease/cancer and non-digestive disease/cancer. A total of 146 patients were enrolled at the UCSD Moores Cancer Center where saliva and demographic data were collected from each patient. Of these, we analyzed the salivary microbiome of 108 patients: 8 had been diagnosed with pancreatic cancer, 78 with other diseases and 22 were classified as non-diseased (healthy) controls. Bacterial 16S rRNA sequences were amplified directly from salivary DNA extractions and subjected to high-throughput sequencing (HTS). Several bacterial genera differed in abundance in patients with pancreatic cancer. We found a significantly higher ratio of Leptotrichia to Porphyromonas in the saliva of patients with pancreatic cancer than in the saliva of healthy patients or those with other disease (Kruskal–Wallis Test; P < 0.001). Leptotrichia abundances were confirmed using real-time qPCR with Leptotrichia specific primers. Similar to previous studies, we found lower relative abundances of Neisseria and Aggregatibacter in the saliva of pancreatic cancer patients, though these results were not significant at the P < 0.05 level (K–W Test; P = 0.07 and P = 0.09 respectively). However, the relative abundances of other previously identified bacterial biomarkers, e.g., Streptococcus mitis and Granulicatella adiacens, were not significantly different in the saliva of pancreatic cancer patients. Overall, this study supports the hypothesis that bacteria abundance profiles in saliva are useful biomarkers for pancreatic cancer though much larger patient studies are needed to verify their predictive utility.

Changes in microbial communities along redox gradients in polygonized Arctic wet tundra soils

This study investigated how microbial community structure and diversity varied with depth and topography in ice wedge polygons of wet tundra of the Arctic Coastal Plain in northern Alaska and what soil variables explain these patterns. We observed strong changes in community structure and diversity with depth, and more subtle changes between areas of high and low topography, with the largest differences apparent near the soil surface. These patterns are most strongly correlated with redox gradients (measured using the ratio of reduced Fe to total Fe in acid extracts as a proxy): conditions grew more reducing with depth and were most oxidized in shallow regions of polygon rims. Organic matter and pH also changed with depth and topography but were less effective predictors of the microbial community structure and relative abundance of specific taxa. Of all other measured variables, lactic acid concentration was the best, in combination with redox, for describing the microbial community. We conclude that redox conditions are the dominant force in shaping microbial communities in this landscape. Oxygen and other electron acceptors allowed for the greatest diversity of microbes: at depth the community was reduced to a simpler core of anaerobes, dominated by fermenters (Bacteroidetes and Firmicutes).

Advancing the microbiome research community

The human microbiome has become a recognized factor in promoting and maintaining health. We outline opportunities in interdisciplinary research, analytical rigor, standardization, and policy development for this relatively new and rapidly developing field. Advances in these aspects of the research community may in turn advance our understanding of human microbiome biology.

Biodiversity hot spot on a hot spot: novel extremophile diversity in Hawaiian fumaroles

Fumaroles (steam vents) are the most common, yet least understood, microbial habitat in terrestrial geothermal settings. Long believed too extreme for life, recent advances in sample collection and DNA extraction methods have found that fumarole deposits and subsurface waters harbor a considerable diversity of viable microbes. In this study, we applied culture-independent molecular methods to explore fumarole deposit microbial assemblages in 15 different fumaroles in four geographic locations on the Big Island of Hawai'i. Just over half of the vents yielded sufficient high-quality DNA for the construction of 16S ribosomal RNA gene sequence clone libraries. The bacterial clone libraries contained sequences belonging to 11 recognized bacterial divisions and seven other division-level phylogenetic groups. Archaeal sequences were less numerous, but similarly diverse. The taxonomic composition among fumarole deposits was highly heterogeneous. Phylogenetic analysis found cloned fumarole sequences were related to microbes identified from a broad array of globally distributed ecotypes, including hot springs, terrestrial soils, and industrial waste sites. Our results suggest that fumarole deposits function as an “extremophile collector” and may be a hot spot of novel extremophile biodiversity.

The personal human oral microbiome obscures the effects of treatment on periodontal disease

Periodontitis is a progressive disease of the periodontium with a complex, polymicrobial etiology. Recent Next-Generation Sequencing (NGS) studies of the microbial diversity associated with periodontitis have revealed strong, community-level differences in bacterial assemblages associated with healthy or diseased periodontal sites. In this study, we used NGS approaches to characterize changes in periodontal pocket bacterial diversity after standard periodontal treatment. Despite consistent changes in the abundance of certain taxa in individuals whose condition improved with treatment, post-treatment samples retained the highest similarity to pre-treatment samples from the same individual. Deeper phylogenetic analysis of periodontal pathogen-containing genera Prevotella and Fusobacterium found both unexpected diversity and differential treatment response among species. Our results highlight how understanding interpersonal variability among microbiomes is necessary for determining how polymicrobial diseases respond to treatment and disturbance.

Research on neonatal microbiomes: what neonatologists need to know

The aim of this article is to educate neonatal caregivers about metagenomics. This scientific field uses novel and ever changing molecular methods to identify how infants become colonized with microbes after birth. Publications using metagenomics appear infrequently in the neonatal literature because clinicians are unaccustomed to the analytical techniques, data interpretation, and illustration of the results. This review covers those areas. After a brief introduction of neonatal citations forthcoming from metagenomic studies, the following topics are covered: (1) the history of metagenomics, (2) a description of current and emerging instruments used to define microbial populations in human organs, and (3) how extensive databases generated by genome analyzers are examined and presented to readers. Clinicians may feel like they are learning a new language; however, they will appreciate this task is essential to understanding and practicing neonatal medicine in the future.

The Hospital Microbiome Project: Meeting Report for the 1st Hospital Microbiome Project Workshop on sampling design and building science measurements, Chicago, USA, June 7th-8th 2012

This report details the outcome of the 1st Hospital Microbiome Project workshop held on June 7th-8th, 2012 at the University of Chicago, USA. The workshop was arranged to determine the most appropriate sampling strategy and approach to building science measurement to characterize the development of a microbial community within a new hospital pavilion being built at the University of Chicago Medical Center. The workshop made several recommendations and led to the development of a full proposal to the Alfred P. Sloan Foundation as well as to the creation of the Hospital Microbiome Consortium.

Studying the microbiology of the indoor environment

The majority of people in the developed world spend more than 90% of their lives indoors. Here, we examine our understanding of the bacteria that co-inhabit our artificial world and how they might influence human health.

Metabolic reconstruction for metagenomic data and its application to the human microbiome

Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.

Ancestral state reconstruction for Dendroctonus bark beetles: evolution of a tree killer

While most bark beetles attack only dead or weakened trees, many species in the genus Dendroctonus have the ability to kill healthy conifers through mass attack of the host tree, and can exhibit devastating outbreaks. Other species in this group are able to successfully colonize trees in small numbers without killing the host. We reconstruct the evolution of these ecological and life history traits, first classifying the extant Dendroctonus species by attack type (mass or few), outbreaks (yes or no), host genus (Pinus and others), location of attacks on the tree (bole, base, etc.), whether the host is killed (yes or no), and if the larvae are gregarious or have individual galleries (yes or no). We then estimated a molecular phylogeny for a data set of cytochrome oxidase I sequences sampled from nearly all Dendroctonus species, and used this phylogeny to reconstruct the ancestral state at various nodes on the tree, employing maximum parsimony, maximum likelihood, and Bayesian methods. Our reconstructions suggest that extant Dendroctonus species likely evolved from an ancestor that killed host pines through mass attack of the bole, had individual larvae, and exhibited outbreaks. The ability to colonize a host tree in small numbers (as well as gregarious larvae and attacks at the tree base) apparently evolved later, possibly as two separate events in different clades. It is likely that tree mortality and outbreaks have been continuing features of the interaction between conifers and Dendroctonus bark beetles.