Discovery of bioactive microbial gene products in inflammatory bowel disease.

Microbial communities and their associated bioactive compounds1-3 are often disrupted in conditions such as the inflammatory bowel diseases (IBD)4. However, even in well-characterized environments (for example, the human gastrointestinal tract), more than one-third of microbial proteins are uncharacterized and often expected to be bioactive5-7. Here we systematically identified more than 340,000 protein families as potentially bioactive with respect to gut inflammation during IBD, about half of which have not to our knowledge been functionally characterized previously on the basis of homology or experiment. To validate prioritized microbial proteins, we used a combination of metagenomics, metatranscriptomics and metaproteomics to provide evidence of bioactivity for a subset of proteins that are involved in host and microbial cell-cell communication in the microbiome; for example, proteins associated with adherence or invasion processes, and extracellular von Willebrand-like factors. Predictions from high-throughput data were validated using targeted experiments that revealed the differential immunogenicity of prioritized Enterobacteriaceae pilins and the contribution of homologues of von Willebrand factors to the formation of Bacteroides biofilms in a manner dependent on mucin levels. This methodology, which we term MetaWIBELE (workflow to identify novel bioactive elements in the microbiome), is generalizable to other environmental communities and human phenotypes. The prioritized results provide thousands of candidate microbial proteins that are likely to interact with the host immune system in IBD, thus expanding our understanding of potentially bioactive gene products in chronic disease states and offering a rational compendium of possible therapeutic compounds and targets.

Simulants: Synthetic Clinical Trial Data via Subject-Level Privacy-Preserving Synthesis.

Clinical trials capture high-quality data for millions of patients each year, yet these data are largely unavailable for research beyond the scope of any individual trial due to a combination of regulatory, intellectual property, and patient privacy barriers. Synthetic clinical trial data that captures the analytical properties of the source data, could provide significant value for research and drug development by making insights widely available while protecting the privacy of the participants. We present a method "Simulants" for generating research-grade synthetic clinical trial data from a real data source. We compared the fidelity and privacy preservation performance of Simulants to the state-of-the-art deep learning synthesizers and found that Simulants had superior performance when applied to clinical trial data as assessed both by established metrics and when considering critical clinical features. We also demonstrate how Simulants' privacy settings may be configured to conform to specific privacy policies governing data sharing.

Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes.

BACKGROUND: Heterogeneity in the definition and measurement of complex diseases in Genome-Wide Association Studies (GWAS) may lead to misdiagnoses and misclassification errors that can significantly impact discovery of disease loci. While well appreciated, almost all analyses of GWAS data consider reported disease phenotype values as is without accounting for potential misclassification. RESULTS: Here, we introduce Phenotype Latent variable Extraction of disease misdiagnosis (PheLEx), a GWAS analysis framework that learns and corrects misclassified phenotypes using structured genotype associations within a dataset. PheLEx consists of a hierarchical Bayesian latent variable model, where inference of differential misclassification is accomplished using filtered genotypes while implementing a full mixed model to account for population structure and genetic relatedness in study populations. Through simulations, we show that the PheLEx framework dramatically improves recovery of the correct disease state when considering realistic allele effect sizes compared to existing methodologies designed for Bayesian recovery of disease phenotypes. We also demonstrate the potential of PheLEx for extracting new potential loci from existing GWAS data by analyzing bipolar disorder and epilepsy phenotypes available from the UK Biobank. From the PheLEx analysis of these data, we identified new candidate disease loci not previously reported for these datasets that have value for supplemental hypothesis generation. CONCLUSION: PheLEx shows promise in reanalyzing GWAS datasets to provide supplemental candidate loci that are ignored by traditional GWAS analysis methodologies.

Role of KRAS in regulating normal human airway basal cell differentiation.

BACKGROUND: KRAS is a GTPase that activates pathways involved in cell growth, differentiation and survival. In normal cells, KRAS-activity is tightly controlled, but with specific mutations, the KRAS protein is persistently activated, giving cells a growth advantage resulting in cancer. While a great deal of attention has been focused on the role of mutated KRAS as a common driver mutation for lung adenocarcinoma, little is known about the role of KRAS in regulating normal human airway differentiation. METHODS: To assess the role of KRAS signaling in regulating differentiation of the human airway epithelium, primary human airway basal stem/progenitor cells (BC) from nonsmokers were cultured on air-liquid interface (ALI) cultures to mimic the airway epithelium in vitro. Modulation of KRAS signaling was achieved using siRNA-mediated knockdown of KRAS or lentivirus-mediated over-expression of wild-type KRAS or the constitutively active G12 V mutant. The impact on differentiation was quantified using TaqMan quantitative PCR, immunofluorescent and immunohistochemical staining analysis for cell type specific markers. Finally, the impact of cigarette smoke exposure on KRAS and RAS protein family activity in the airway epithelium was assessed in vitro and in vivo. RESULTS: siRNA-mediated knockdown of KRAS decreased differentiation of BC into secretory and ciliated cells with a corresponding shift toward squamous cell differentiation. Conversely, activation of KRAS signaling via lentivirus mediated over-expression of the constitutively active G12 V KRAS mutant had the opposite effect, resulting in increased secretory and ciliated cell differentiation and decreased squamous cell differentiation. Exposure of BC to cigarette smoke extract increased KRAS and RAS protein family activation in vitro. Consistent with these observations, airway epithelium brushed from healthy smokers had elevated RAS activation compared to nonsmokers. CONCLUSIONS: Together, these data suggest that KRAS-dependent signaling plays an important role in regulating the balance of secretory, ciliated and squamous cell differentiation of the human airway epithelium and that cigarette smoking-induced airway epithelial remodeling is mediated in part by abnormal activation of KRAS-dependent signaling mechanisms.

XX Disorder of Sex Development is associated with an insertion on chromosome 9 and downregulation of RSPO1 in dogs (Canis lupus familiaris).

Remarkable progress has been achieved in understanding the mechanisms controlling sex determination, yet the cause for many Disorders of Sex Development (DSD) remains unknown. Of particular interest is a rare XX DSD subtype in which individuals are negative for SRY, the testis determining factor on the Y chromosome, yet develop testes or ovotestes, and both of these phenotypes occur in the same family. This is a naturally occurring disorder in humans (Homo sapiens) and dogs (C. familiaris). Phenotypes in the canine XX DSD model are strikingly similar to those of the human XX DSD subtype. The purposes of this study were to identify 1) a variant associated with XX DSD in the canine model and 2) gene expression alterations in canine embryonic gonads that could be informative to causation. Using a genome wide association study (GWAS) and whole genome sequencing (WGS), we identified a variant on C. familiaris autosome 9 (CFA9) that is associated with XX DSD in the canine model and in affected purebred dogs. This is the first marker identified for inherited canine XX DSD. It lies upstream of SOX9 within the canine ortholog for the human disorder, which resides on 17q24. Inheritance of this variant indicates that XX DSD is a complex trait in which breed genetic background affects penetrance. Furthermore, the homozygous variant genotype is associated with embryonic lethality in at least one breed. Our analysis of gene expression studies (RNA-seq and PRO-seq) in embryonic gonads at risk of XX DSD from the canine model identified significant RSPO1 downregulation in comparison to XX controls, without significant upregulation of SOX9 or other known testis pathway genes. Based on these data, a novel mechanism is proposed in which molecular lesions acting upstream of RSPO1 induce epigenomic gonadal mosaicism.

Urban Transit System Microbial Communities Differ by Surface Type and Interaction with Humans and the Environment.

Public transit systems are ideal for studying the urban microbiome and interindividual community transfer. In this study, we used 16S amplicon and shotgun metagenomic sequencing to profile microbial communities on multiple transit surfaces across train lines and stations in the Boston metropolitan transit system. The greatest determinant of microbial community structure was the transit surface type. In contrast, little variation was observed between geographically distinct train lines and stations serving different demographics. All surfaces were dominated by human skin and oral commensals such as Propionibacterium, Corynebacterium, Staphylococcus, and Streptococcus. The detected taxa not associated with humans included generalists from alphaproteobacteria, which were especially abundant on outdoor touchscreens. Shotgun metagenomics further identified viral and eukaryotic microbes, including Propionibacterium phage and Malassezia globosa. Functional profiling showed that Propionibacterium acnes pathways such as propionate production and porphyrin synthesis were enriched on train holding surfaces (holds), while electron transport chain components for aerobic respiration were enriched on touchscreens and seats. Lastly, the transit environment was not found to be a reservoir of antimicrobial resistance and virulence genes. Our results suggest that microbial communities on transit surfaces are maintained from a metapopulation of human skin commensals and environmental generalists, with enrichments corresponding to local interactions with the human body and environmental exposures. IMPORTANCE Mass transit environments, specifically, urban subways, are distinct microbial environments with high occupant densities, diversities, and turnovers, and they are thus especially relevant to public health. Despite this, only three culture-independent subway studies have been performed, all since 2013 and all with widely differing designs and conclusions. In this study, we profiled the Boston subway system, which provides 238 million trips per year overseen by the Massachusetts Bay Transportation Authority (MBTA). This yielded the first high-precision microbial survey of a variety of surfaces, ridership environments, and microbiological functions (including tests for potential pathogenicity) in a mass transit environment. Characterizing microbial profiles for multiple transit systems will become increasingly important for biosurveillance of antibiotic resistance genes or pathogens, which can be early indicators for outbreak or sanitation events. Understanding how human contact, materials, and the environment affect microbial profiles may eventually allow us to rationally design public spaces to sustain our health in the presence of microbial reservoirs. Author Video: An author video summary of this article is available.

A reproducible approach to high-throughput biological data acquisition and integration.

Modern biological research requires rapid, complex, and reproducible integration of multiple experimental results generated both internally and externally (e.g., from public repositories). Although large systematic meta-analyses are among the most effective approaches both for clinical biomarker discovery and for computational inference of biomolecular mechanisms, identifying, acquiring, and integrating relevant experimental results from multiple sources for a given study can be time-consuming and error-prone. To enable efficient and reproducible integration of diverse experimental results, we developed a novel approach for standardized acquisition and analysis of high-throughput and heterogeneous biological data. This allowed, first, novel biomolecular network reconstruction in human prostate cancer, which correctly recovered and extended the NFκB signaling pathway. Next, we investigated host-microbiome interactions. In less than an hour of analysis time, the system retrieved data and integrated six germ-free murine intestinal gene expression datasets to identify the genes most influenced by the gut microbiota, which comprised a set of immune-response and carbohydrate metabolism processes. Finally, we constructed integrated functional interaction networks to compare connectivity of peptide secretion pathways in the model organisms Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa.

Sequencing and beyond: integrating molecular 'omics' for microbial community profiling.

High-throughput DNA sequencing has proven invaluable for investigating diverse environmental and host-associated microbial communities. In this Review, we discuss emerging strategies for microbial community analysis that complement and expand traditional metagenomic profiling. These include novel DNA sequencing strategies for identifying strain-level microbial variation and community temporal dynamics; measuring multiple 'omic' data types that better capture community functional activity, such as transcriptomics, proteomics and metabolomics; and combining multiple forms of omic data in an integrated framework. We highlight studies in which the 'multi-omics' approach has led to improved mechanistic models of microbial community structure and function.

Determining microbial products and identifying molecular targets in the human microbiome.

Human-associated microbes are the source of many bioactive microbial products (proteins and metabolites) that play key functions both in human host pathways and in microbe-microbe interactions. Culture-independent studies now provide an accelerated means of exploring novel bioactives in the human microbiome; however, intriguingly, a substantial fraction of the microbial metagenome cannot be mapped to annotated genes or isolate genomes and is thus of unknown function. Meta'omic approaches, including metagenomic sequencing, metatranscriptomics, metabolomics, and integration of multiple assay types, represent an opportunity to efficiently explore this large pool of potential therapeutics. In combination with appropriate follow-up validation, high-throughput culture-independent assays can be combined with computational approaches to identify and characterize novel and biologically interesting microbial products. Here we briefly review the state of microbial product identification and characterization and discuss possible next steps to catalog and leverage the large uncharted fraction of the microbial metagenome.

Functional and phylogenetic assembly of microbial communities in the human microbiome.

Microbial communities associated with the human body, that is, the human microbiome, are complex ecologies critical for normal development and health. The taxonomic and phylogenetic composition of these communities tends to significantly differ among individuals, precluding the definition of a simple, shared set of 'core' microbes. Here, we review recent evidence and ecological theory supporting the assembly of host-associated microbial communities in terms of functional traits rather than specific organisms. That is, distinct microbial species may be responsible for specific host-associated functions and phenotypes in distinct hosts. We discuss how ecological processes (selective and stochastic forces) governing the assembly of metazoan communities can be adapted to describe microbial ecologies in host-associated environments, resulting in both niche-specific and 'core' metabolic and other pathways maintained throughout the human microbiome. The extent to which phylogeny and functional traits are linked in host-associated microbes, as opposed to unlinked by mechanisms, such as lateral transfer, remains to be determined. However, the definition of these functional assembly rules within microbial communities using controlled model systems and integrative 'omics' represents a fruitful opportunity for molecular systems ecology.