Biology subjects

Blekhman, R.

Publications and source records attributed to Blekhman, R..

9 recordsLinked to original sources

bioRxiv2018

A comprehensive analysis of the usability and archival stability of omics computational tools and resources

Developing new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through URLs published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed \"easy to install,\" and 28% of the tools failed to be installed at all due to problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software.

bioinformatics↗

bioRxiv2018

Megaphage infect Prevotella and variants are widespread in gut microbiomes

Bacteriophage (phage) dramatically shape microbial community composition, redistribute nutrients via host lysis, and drive evolution through horizontal gene transfer. Despite their importance, much remains to be learned about phage in the human microbiome. We investigated gut microbiomes of humans from Bangladesh and Tanzania, two African baboon social groups, and Danish pigs, and report that many contain phage belonging to a clade with genomes >540 kb in length, the largest yet reported in the human microbiome and close to the maximum size ever reported for phage. We refer to these as Lak phage. CRISPR spacer targeting indicates that the Lak phage infect bacteria of the genus Prevotella. We manually curated to completion 15 distinct Lak phage genomes recovered from metagenomes. The genomes display several interesting features, including use of an alternative genetic code, large intergenic regions that are highly expressed, and up to 35 putative tRNAs, some of which contain enigmatic introns. Different individuals have distinct phage genotypes, and shifts in variant frequencies over consecutive sampling days reflect changes in relative abundance of phage sub-populations. Recent homologous recombination has resulted in extensive genome admixture of nine baboon Lak phage populations. We infer that Lak phage are widespread in gut communities that contain Prevotella species, especially in individuals in the developing world, and conclude that megaphage, with fascinating and underexplored biology, may be common but largely overlooked components of human and animal gut microbiomes.

microbiology↗

bioRxiv2018

Distinct Microbes, Metabolites, and Ecologies Define the Microbiome in Deficient and Proficient Mismatch Repair Colorectal Cancers

Background\n\nThe link between colorectal cancer (CRC) and the gut microbiome has been established, but the specific microbial species and their role in carcinogenesis remain controversial. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology.\n\nMethods\n\nWe collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject sample correlation, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks.\n\nResults\n\nWe demonstrate distinct roles for microbes in dMMR and pMMR CRC. Sulfidogenic Fusobacterium nucleatum and hydrogen sulfide production were significantly enriched in dMMR CRC, but not pMMR CRC. We also surveyed the butyrate-producing microbial species, but did not find a significant difference in predicted or actual butyrate production between dMMR and pMMR microbial communities. Finally, we observed that dMMR microbial communities were predicted to be less stable than pMMR microbial communities. Community stability may play an important role in CRC development, progression, or immune activation within the respective MMR subtypes.\n\nConclusions\n\nIntegrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers.

cancer biology↗

bioRxiv2018

Gut Microbiota Diversity across Ethnicities in the United States

Composed of hundreds of microbial species, the composition of the human gut microbiota can vary with chronic diseases underlying health disparities that disproportionally affect ethnic minorities. However, the influence of ethnicity on the gut microbiota remains largely unexplored and lacks reproducible generalizations across studies. By distilling associations between ethnicity and differences in two United States based 16S gut microbiota datasets including 1,673 individuals, we report 12 microbial genera and families that reproducibly vary by ethnicity. Interestingly, a majority of these microbial taxa, including the most heritable bacterial family, Christensenellaceae, overlap with genetically-associated taxa and form co-occurring clusters linked by similar fermentative and methanogenic metabolic processes. These results demonstrate recurrent associations between specific taxa in the gut microbiota and ethnicity, providing hypotheses for examining specific members of the gut microbiota as mediators of health disparities.

microbiology↗

bioRxiv2017

Variation in gut microbiota composition impacts host gene expression

Variation in gut microbiome is associated with wellness and disease in humans, yet the molecular mechanisms by which this variation affects the host are not well understood. A likely mechanism is through changing gene regulation in interfacing host epithelial cells. Here, we treated colonic epithelial cells with live microbiota from five healthy individuals and quantified induced changes in transcriptional regulation and chromatin accessibility in host cells. We identified over 5,000 host genes that change expression, including 588 distinct associations between specific taxa and host genes. The taxa with the strongest influence on gene expression alter the response of genes associated with complex traits. Using ATAC-seq, we show that a subset of these changes in gene expression are likely the result of changes in host chromatin accessibility and transcription factor binding induced by exposure to gut microbiota. We then created a manipulated microbial community with titrated doses of Collinsella, demonstrating that both natural and controlled microbiome composition leads to distinct, and predictable, gene expression profiles in host cells. Together, our results suggest that specific microbes play an important role in regulating expression of individual host genes involved in human complex traits. The ability to fine tune the expression of host genes by manipulating the microbiome suggests future therapeutic routes.

genomics↗

bioRxiv2017

Interaction Between Host MicroRNAs and the Gut Microbiota in Colorectal Cancer

BackgroundAlthough variation in gut microbiome composition has been linked with colorectal cancer (CRC), the factors that mediate the interactions between CRC tumors and the microbiome are poorly understood. MicroRNAs (miRNAs) are known to regulate CRC progression and patient survival outcomes. In addition, recent studies suggested that host miRNAs can also regulate bacterial growth and influence the composition of the gut microbiome. Here, we investigated the association between miRNAs expression in human CRC tumor and normal tissues and the microbiome composition associated with these same tissues.\n\nMethodWe sequenced the small RNAs from patient-matched tumor and normal tissue samples collected from 44 human CRC patients performed an integrated analysis with microbiome taxonomic composition data from these same samples. We then interrogated the functions of the bacteria correlated with miRNAs that were differentially expressed (DE) between tumor and matched normal tissues, as well as the functions of miRNAs correlated with bacterial taxa that have been previously associated with CRC, including Fusobacterium, Providencia, Bacteroides, Akkermansia, Roseburia, Porphyromonas, and Peptostreptococcus.\n\nResultsWe identified 76 miRNAs as DE between CRC and normal tissue, including known oncogenic miRNAs miR-182, miR-503, and miR-17[~]92. These DE miRNAs were correlated with the relative abundance of several bacterial taxa, including Firmicutes, Bacteroidetes, and Proteobacteria. Bacteria correlated with DE miRNAs were enriched with distinct predicted metabolic categories. Additionally, we found that miRNAs correlated with CRC-associated bacteria are predicted to regulate targets that are relevant for host-microbiome interactions, and highlight a possible role for miRNA-driven glycan production in the recruitment of pathogenic microbial taxa.\n\nConclusionsOur work characterized a global relationship between microbial community composition and miRNA expression in human CRC tissues. Our results support a role for miRNAs in mediating a bi-directional host-microbiome interaction in CRC. In addition, we highlight sets of potentially interacting microbes and host miRNAs, suggesting several pathways that can be targeted via future therapies.

systems biology↗

bioRxiv2017

BugBase Predicts Organism Level Microbiome Phenotypes

Shotgun metagenomics and marker gene amplicon sequencing can be used to directly measure or predict the functional repertoire of the microbiota en masse, but current methods do not readily estimate the functional capability of individual microorganisms. Here we present BugBase, an algorithm that predicts organism-level coverage of functional pathways as well as biologically interpretable phenotypes such as oxygen tolerance, Gram staining and pathogenic potential, within complex microbiomes using either whole-genome shotgun or marker gene sequencing data. We find BugBases organism-level pathway coverage predictions to be statistically higher powered than current bag-of-genes approaches for discerning functional changes in both host-associated and environmental microbiomes.

bioinformatics↗

bioRxiv2016

Discrete mutations in colorectal cancer correlate with defined microbial communities in the tumor microenvironment

Variation in the gut microbiome has been linked to colorectal cancer (CRC), as well as to host genetic variation. However, we do not know whether, in addition to baseline host genetics, somatic mutational profiles in CRC tumors interact with the surrounding tumor microbiome, and if so, whether these changes can be used to understand microbe-host interactions with potential functional biological relevance. Here, we characterized the association between CRC microbial communities and tumor mutations using microbiome profiling and whole-exome sequencing in 44 pairs of tumors and matched normal tissues. We found statistically significant associations between loss-of-function mutations in tumor genes and shifts in the abundances of specific sets of bacterial taxa, suggestive of potential functional interaction. This correlation allows us to statistically predict interactions between loss-of-function tumor mutations in cancer-related genes and pathways, including MAPK and Wnt signaling, solely based on the composition of the microbiome. These results can serve as a starting point for fine-grained exploration of the functional interactions between discrete alterations in tumor DNA and proximal microbial communities in CRC. In addition, these findings can lead to the development of improved microbiome-based CRC screening methods, as well as individualized microbiota-targeting therapies.\n\nAuthor summaryAlthough the gut microbiome - the collection of microorganisms that inhabit our gastrointestinal tract - has been implicated in colorectal cancer, colorectal tumors are caused by genetic mutations in host DNA. Here, we explored whether various mutations in colorectal tumors are correlated with specific changes in the bacterial communities that live in and on these tumors. We find that the genes and biological pathways that are mutated in tumors are correlated with variation in the composition of the microbiome. In fact, these changes in the microbiome are consistent enough that we can use them to statistically predict tumor mutations solely based on the microbiome. Our results may be used to understand the roles of specific microbes in CRC biology, and could also be the starting point of microbiome-based diagnostics for not only detection of CRC, but characterization of tumor mutational profiles.

cancer biology↗

bioRxiv2016

HOMINID: A framework for identifying associations between host genetic variation and microbiome composition

Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome composition data, identifies host SNPs that are correlated with microbial taxa abundances. Using simulated data we show that HOMINID has accuracy in identifying associated SNPs, and performs better compared to existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition, and can facilitate discovery of mechanisms controlling host-microbiome interactions.\n\nAvailability and implementationSoftware, code, tutorial, installation and setup details, and synthetic data are available in the project homepage: https://github.com/blekhmanlab/hominid.\n\nReal dataset used here is from Blekhman et al. (Blekhman et al. 2015); 16S rRNA gene sequence data and OTU tables are available on the HMP DACC website (www.hmpdacc.org), and host genetic data are deposited in dbGaP under project number phs000228.

genomics↗