Microbiome maps: Hilbert curve visualizations of metagenomic profiles.

Abundance profiles from metagenomic sequencing data synthesize information from billions of sequenced reads coming from thousands of microbial genomes. Analyzing and understanding these profiles can be a challenge since the data they represent are complex. Particularly challenging is their visualization, as existing techniques are inadequate when the taxa number is in the thousands.

Diet Quality and Liver Health in People Living with HIV in the MASH Cohort: A Multi-Omic Analysis of the Fecal Microbiome and Metabolome.

The gut-liver axis has been recognized as a potential pathway in which dietary factors may contribute to liver disease in people living with HIV (PLWH). The objective of this study was to explore associations between dietary quality, the fecal microbiome, the metabolome, and liver health in PLWH from the Miami Adult Studies on HIV (MASH) cohort. We performed a cross-sectional analysis of 50 PLWH from the MASH cohort and utilized the USDA Healthy Eating Index (HEI)-2015 to measure diet quality.

A novel approach for combining the metagenome, metaresistome, metareplicome and causal inference to determine the microbes and their antibiotic resistance gene repertoire that contribute to dysbiosis.

The use of whole metagenomic data to infer the relative abundance of all its microbes is well established. The same data can be used to determine the replication rate of all eubacterial taxa with circular chromosomes. Despite their availability, the replication rate profiles (metareplicome) have not been fully exploited in microbiome analyses.

Multiomic analysis reveals microbiome-related relationships between cocaine use and metabolites.

Objective: Over 19 million individuals globally have a cocaine use disorder, a significant public health crisis. Cocaine has also been associated with a pro-inflammatory state and recently with imbalances in the intestinal microbiota as compared to nonuse. The objective of this pilot study was to characterize the gut microbiota and plasma metabolites in people with HIV (PWH) who use cocaine compared with those who do not.

Potential Autoimmunity Resulting from Molecular Mimicry between SARS-CoV-2 Spike and Human Proteins.

Molecular mimicry between viral antigens and host proteins can produce cross-reacting antibodies leading to autoimmunity. The coronavirus SARS-CoV-2 causes COVID-19, a disease curiously resulting in varied symptoms and outcomes, ranging from asymptomatic to fatal. Autoimmunity due to cross-reacting antibodies resulting from molecular mimicry between viral antigens and host proteins may provide an explanation.

Prior exposure to microcystin alters host gut resistome and is associated with dysregulated immune homeostasis in translatable mouse models.

A strong association between exposure to the common harmful algal bloom toxin microcystin and the altered host gut microbiome has been shown. We tested the hypothesis that prior exposure to the cyanotoxin microcystin-LR may alter the host resistome. We show that the mice exposed to microcystin-LR had an altered microbiome signature that harbored antibiotic resistance genes.

Mutation-induced changes in the receptor-binding interface of the SARS-CoV-2 Delta variant B.1.617.2 and implications for immune evasion.

Following the initial surges of the Alpha (B.1.1.

Effect of metronidazole on vaginal microbiota associated with asymptomatic bacterial vaginosis.

Vaginal dysbiosis-induced by an overgrowth of anaerobic bacteria is referred to as bacterial vaginosis (BV). The dysbiosis is associated with an increased risk for acquisition of sexually transmitted infections. Women with symptomatic BV are treated with oral metronidazole (MET), but its effectiveness remains to be elucidated.

Causal effects in microbiomes using interventional calculus.

Causal inference in biomedical research allows us to shift the paradigm from investigating associational relationships to causal ones. Inferring causal relationships can help in understanding the inner workings of biological processes. Association patterns can be coincidental and may lead to wrong conclusions about causality in complex systems.

Large scale microbiome profiling in the cloud.

Motivation: Bacterial metagenomics profiling for metagenomic whole sequencing (mWGS) usually starts by aligning sequencing reads to a collection of reference genomes. Current profiling tools are designed to work against a small representative collection of genomes, and do not scale very well to larger reference genome collections. However, large reference genome collections are capable of providing a more complete and accurate profile of the bacterial population in a metagenomics dataset.