Intestinal microbial communities and Holdemanella isolated from HIV+/- men who have sex with men increase frequencies of lamina propria CCR5+ CD4+ T cells.

Men who have sex with men (MSM), regardless of HIV infection status, have an intestinal microbiome that is compositionally distinct from men who have sex with women (MSW) and women. We recently showed HIV-negative MSM have elevated levels of intestinal CD4+ T cells expressing CCR5, a critical co-receptor for HIV. Whether elevated expression of CCR5 is driven by the altered gut microbiome composition in MSM has not been explored. Here we used in vitro stimulation of gut Lamina Propria Mononuclear Cells (LPMCs) with whole intact microbial cells isolated from stool to demonstrate that fecal bacterial communities (FBCs) from HIV-positive/negative MSM induced higher frequencies of CCR5+ CD4+ T cells compared to FBCs from HIV-negative MSW and women. To identify potential microbial drivers, we related the frequency of CCR5+ CD4+ T cells to the abundance of individual microbial taxa in rectal biopsy of HIV-positive/negative MSM and controls, and Holdemanella biformis was strongly associated with increased frequency of CCR5+ CD4+ T cells. We used in vitro stimulation of gut LPMCs with the type strain of H. biformis, a second strain of H.biformis and an isolate of the closely related Holdemanella porci , cultured from either a HIV-positive or a HIV-negative MSM stool. H. porci elevated the frequency of both CCR5+ CD4+ T cells and the ratio of TNF-α/IL-10 Genomic comparisons of the 3 Holdemanella isolates revealed unique cell wall and capsular components, which may be responsible for their differences in immunogenicity. These findings describe a novel mechanism potentially linking intestinal dysbiosis in MSM to HIV transmission and mucosal pathogenesis.

Systems Analysis of Gut Microbiome Influence on Metabolic Disease in HIV-Positive and High-Risk Populations.

Poor metabolic health, characterized by insulin resistance and dyslipidemia, is higher in people living with HIV and has been linked with inflammation, antiretroviral therapy (ART) drugs, and ART-associated lipodystrophy (LD). Metabolic disease is associated with gut microbiome composition outside the context of HIV but has not been deeply explored in HIV infection or in high-risk men who have sex with men (HR-MSM), who have a highly altered gut microbiome composition. Furthermore, the contribution of increased bacterial translocation and associated systemic inflammation that has been described in HIV-positive and HR-MSM individuals has not been explored. We used a multiomic approach to explore relationships between impaired metabolic health, defined using fasting blood markers, gut microbes, immune phenotypes, and diet. Our cohort included ART-treated HIV-positive MSM with or without LD, untreated HIV-positive MSM, and HR-MSM. For HIV-positive MSM on ART, we further explored associations with the plasma metabolome. We found that elevated plasma lipopolysaccharide binding protein (LBP) was the most important predictor of impaired metabolic health and network analysis showed that LBP formed a hub joining correlated microbial and immune predictors of metabolic disease. Taken together, our results suggest the role of inflammatory processes linked with bacterial translocation and interaction with the gut microbiome in metabolic disease among HIV-positive and -negative MSM.IMPORTANCE The gut microbiome in people living with HIV (PLWH) is of interest since chronic infection often results in long-term comorbidities. Metabolic disease is prevalent in PLWH even in well-controlled infection and has been linked with the gut microbiome in previous studies, but little attention has been given to PLWH. Furthermore, integrated analyses that consider gut microbiome, together with diet, systemic immune activation, metabolites, and demographics, have been lacking. In a systems-level analysis of predictors of metabolic disease in PLWH and men who are at high risk of acquiring HIV, we found that increased lipopolysaccharide-binding protein, an inflammatory marker indicative of compromised intestinal barrier function, was associated with worse metabolic health. We also found impaired metabolic health associated with specific dietary components, gut microbes, and host and microbial metabolites. This study lays the framework for mechanistic studies aimed at targeting the microbiome to prevent or treat metabolic endotoxemia in HIV-infected individuals.

The Gut Microbiome in Autism: Study-Site Effects and Longitudinal Analysis of Behavior Change.

Research relating gut microbiome composition to autism spectrum disorders (ASD) has produced inconsistent results, indicative of the disorder's complexity and the need for more sophisticated experimental designs. We address this need by (i) comparing gut microbiome composition between individuals with ASD and neurotypical controls in Arizona and Colorado using standardized DNA extraction and sequencing methods at both locations and (ii) longitudinally evaluating the gut microbiome's relationship to autism behavioral severity, diet, and gastrointestinal symptoms. Gut microbiome composition differed between individuals in Arizona and individuals in Colorado, and gastrointestinal symptoms were significantly higher in ASD individuals than in neurotypical individuals in Arizona but not in Colorado. Gut microbiome composition was significantly associated with ASD while controlling for study-site location but not when controlling for gastrointestinal symptoms. This suggests that non-ASD-related study site differences in gut microbiome composition and different degrees of gastrointestinal symptoms involvement with ASD between sites may contribute to inconsistent results in the literature regarding the association between gut microbiome composition and ASD. In the longitudinal analysis, we found that difference in levels of lethargy/social withdrawal measured in individuals at different time points correlated with the degree of change in gut microbiome composition and that a worsening of inappropriate speech between time points was associated with decreased gut microbiome diversity. This relationship between changes in the gut microbiome composition within individuals and ASD behavioral severity metrics indicates that longitudinal study designs may be useful for exploring microbial drivers of ASD severity when substantial variability exists in baseline microbiome compositions across individuals and geographical regions.IMPORTANCE Autism spectrum disorder (ASD) is a brain developmental disorder with varying behavioral symptom severity both across individuals and within individuals over time. There have been promising but also inconsistent literature results regarding how the gut microbiota (microbiome) may be involved. We found that the gut microbiome in individuals with ASD is affected by study-site location as well as gastrointestinal symptom severity. When we sampled some individuals with ASD at several different time points, we found that some behaviors, such as lethargy/social withdrawal and inappropriate speech, changed along with changes in the gut microbiota composition. This is the first study to relate severity of behavior symptoms to gut microbiome composition within individuals over time and suggests a dynamic relationship between ASD-associated symptoms and gut microbes. Longitudinal study designs as well as collaborative efforts across multiple centers are needed to fully characterize the relationship between ASD and gut microbes.

Applying citizen science to gene, drug and disease relationship extraction from biomedical abstracts.

MOTIVATION: Biomedical literature is growing at a rate that outpaces our ability to harness the knowledge contained therein. To mine valuable inferences from the large volume of literature, many researchers use information extraction algorithms to harvest information in biomedical texts. Information extraction is usually accomplished via a combination of manual expert curation and computational methods. Advances in computational methods usually depend on the time-consuming generation of gold standards by a limited number of expert curators. Citizen science is public participation in scientific research. We previously found that citizen scientists are willing and capable of performing named entity recognition of disease mentions in biomedical abstracts, but did not know if this was true with relationship extraction (RE). RESULTS: In this article, we introduce the Relationship Extraction Module of the web-based application Mark2Cure (M2C) and demonstrate that citizen scientists can perform RE. We confirm the importance of accurate named entity recognition on user performance of RE and identify design issues that impacted data quality. We find that the data generated by citizen scientists can be used to identify relationship types not currently available in the M2C Relationship Extraction Module. We compare the citizen science-generated data with algorithm-mined data and identify ways in which the two approaches may complement one another. We also discuss opportunities for future improvement of this system, as well as the potential synergies between citizen science, manual biocuration and natural language processing. AVAILABILITY AND IMPLEMENTATION: Mark2Cure platform: https://mark2cure.org; Mark2Cure source code: https://github.com/sulab/mark2cure; and data and analysis code for this article: https://github.com/gtsueng/M2C_rel_nb. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

Geography and Location Are the Primary Drivers of Office Microbiome Composition.

In the United States, humans spend the majority of their time indoors, where they are exposed to the microbiome of the built environment (BE) they inhabit. Despite the ubiquity of microbes in BEs and their potential impacts on health and building materials, basic questions about the microbiology of these environments remain unanswered. We present a study on the impacts of geography, material type, human interaction, location in a room, seasonal variation, and indoor and microenvironmental parameters on bacterial communities in offices. Our data elucidate several important features of microbial communities in BEs. First, under normal office environmental conditions, bacterial communities do not differ on the basis of surface material (e.g., ceiling tile or carpet) but do differ on the basis of the location in a room (e.g., ceiling or floor), two features that are often conflated but that we are able to separate here. We suspect that previous work showing differences in bacterial composition with surface material was likely detecting differences based on different usage patterns. Next, we find that offices have city-specific bacterial communities, such that we can accurately predict which city an office microbiome sample is derived from, but office-specific bacterial communities are less apparent. This differs from previous work, which has suggested office-specific compositions of bacterial communities. We again suspect that the difference from prior work arises from different usage patterns. As has been previously shown, we observe that human skin contributes heavily to the composition of BE surfaces. IMPORTANCE Our study highlights several points that should impact the design of future studies of the microbiology of BEs. First, projects tracking changes in BE bacterial communities should focus sampling efforts on surveying different locations in offices and in different cities but not necessarily different materials or different offices in the same city. Next, disturbance due to repeated sampling, though detectable, is small compared to that due to other variables, opening up a range of longitudinal study designs in the BE. Next, studies requiring more samples than can be sequenced on a single sequencing run (which is increasingly common) must control for run effects by including some of the same samples in all of the sequencing runs as technical replicates. Finally, detailed tracking of indoor and material environment covariates is likely not essential for BE microbiome studies, as the normal range of indoor environmental conditions is likely not large enough to impact bacterial 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 .

Citizen Science for Mining the Biomedical Literature.

Biomedical literature represents one of the largest and fastest growing collections of unstructured biomedical knowledge. Finding critical information buried in the literature can be challenging. To extract information from free-flowing text, researchers need to: 1. identify the entities in the text (named entity recognition), 2. apply a standardized vocabulary to these entities (normalization), and 3. identify how entities in the text are related to one another (relationship extraction). Researchers have primarily approached these information extraction tasks through manual expert curation and computational methods. We have previously demonstrated that named entity recognition (NER) tasks can be crowdsourced to a group of non-experts via the paid microtask platform, Amazon Mechanical Turk (AMT), and can dramatically reduce the cost and increase the throughput of biocuration efforts. However, given the size of the biomedical literature, even information extraction via paid microtask platforms is not scalable. With our web-based application Mark2Cure (http://mark2cure.org), we demonstrate that NER tasks also can be performed by volunteer citizen scientists with high accuracy. We apply metrics from the Zooniverse Matrices of Citizen Science Success and provide the results here to serve as a basis of comparison for other citizen science projects. Further, we discuss design considerations, issues, and the application of analytics for successfully moving a crowdsourcing workflow from a paid microtask platform to a citizen science platform. To our knowledge, this study is the first application of citizen science to a natural language processing task.

Ecological succession and viability of human-associated microbiota on restroom surfaces.

Human-associated bacteria dominate the built environment (BE). Following decontamination of floors, toilet seats, and soap dispensers in four public restrooms, in situ bacterial communities were characterized hourly, daily, and weekly to determine their successional ecology. The viability of cultivable bacteria, following the removal of dispersal agents (humans), was also assessed hourly. A late-successional community developed within 5 to 8 h on restroom floors and showed remarkable stability over weeks to months. Despite late-successional dominance by skin- and outdoor-associated bacteria, the most ubiquitous organisms were predominantly gut-associated taxa, which persisted following exclusion of humans. Staphylococcus represented the majority of the cultivable community, even after several hours of human exclusion. Methicillin-resistant Staphylococcus aureus (MRSA)-associated virulence genes were found on floors but were not present in assembled Staphylococcus pan-genomes. Viral abundances, which were predominantly enterophages, human papilloma virus, and herpesviruses, were significantly correlated with bacterial abundances and showed an unexpectedly low virus-to-bacterium ratio in surface-associated samples, suggesting that bacterial hosts are mostly dormant on BE surfaces.