Gut Microbiome-Wide Search for Bacterial Azoreductases Reveals Potentially Uncharacterized Azoreductases Encoded in the Human Gut Microbiome

The human gut is home to trillions of microorganisms that are responsible for the modification of many orally administered drugs, leading to a wide range of therapeutic outcomes. Prodrugs bearing an azo bond are designed to treat inflammatory bowel disease and colorectal cancer via microbial azo reduction, allowing for topical application of therapeutic moieties to the diseased tissue in the intestines. Despite the inextricable link between microbial azo reduction and the efficacy of azo prodrugs, the prevalence, abundance, and distribution of azoreductases have not been systematically examined across the gut microbiome. Here, we curated and clustered amino acid sequences of experimentally confirmed bacterial azoreductases and conducted a hidden Markov model-driven homolog search for these enzymes across 4644 genome sequences present in the representative Unified Human Gastrointestinal Genomes collection. We identified 1958 putative azo-reducing species, corroborating previous findings that azo reduction appears to be a ubiquitous function of the gut microbiome. However, through a systematic comparison of predicted and confirmed azo-reducing strains, we hypothesize the presence of uncharacterized azoreductases in 25 prominent strains of the human gut microbiome. Finally, we confirmed the azo reduction of Acid Orange 7 by multiple strains of Fusobacterium nucleatum, Bacteroides fragilis, and Clostridium clostridioforme Together, these results suggest the presence and activity of many uncharacterized azoreductases in the human gut microbiome and motivate future studies aimed at characterizing azoreductase genes in prominent members of the human gut microbiome. SIGNIFICANCE STATEMENT: This work systematically examined the prevalence, abundance, and distribution of azoreductases across the healthy and inflammatory bowel disease human gut microbiome, revealing potentially uncharacterized azoreductase genes. It also confirmed the reduction of Acid Orange 7 by strains of Fusobacterium nucleatum, Bacteroides fragilis, and Clostridium clostridioforme.

The Capacity to Produce Hydrogen Sulfide (H2S) via Cysteine Degradation Is Ubiquitous in the Human Gut Microbiome

As one of the three mammalian gasotransmitters, hydrogen sulfide (H₂S) plays a major role in maintaining physiological homeostasis. Endogenously produced H₂S plays numerous beneficial roles including mediating vasodilation and conferring neuroprotection. Due to its high membrane permeability, exogenously produced H₂S originating from the gut microbiota can also influence human physiology and is implicated in reducing intestinal mucosal integrity and potentiating genotoxicity and is therefore a potential target for therapeutic interventions. Gut microbial H₂S production is often attributed to dissimilatory sulfate reducers such as Desulfovibrio and Bilophila species. However, an alternative source for H₂S production, cysteine degradation, is present in some gut microbes, but the genes responsible for cysteine degradation have not been systematically annotated in all known gut microbes. We classify mechanisms of cysteine degradation into primary, secondary, and erroneous levels of H₂S production and perform a comprehensive search for primary, secondary, and erroneous cysteine-degrading enzymes in 4,644 non-redundant bacterial genomes from the Unified Human Gastrointestinal Genome (UHGG) catalog. Of the 4,644 genomes we have putatively identified 2,046 primary, 1,951 secondary, and 5 erroneous cysteine-degrading species. We identified the presence of at least one putative cysteine-degrading bacteria in metagenomic data of 100% of 6,623 healthy subjects and the expression of cysteine-degrading genes in metatranscriptomic data of 100% of 736 samples taken from 318 individuals. Additionally, putative cysteine-degrading bacteria are more abundant than sulfate-reducing bacteria across healthy controls, IBD patients and CRC patients (p < 2.2e-16, Wilcoxon rank sum test). Although we have linked many taxa with the potential for cysteine degradation, experimental validation is required to establish the H₂S production potential of the gut microbiome. Overall, this study improves our understanding of the capacity for H₂S production by the human gut microbiome and may help to inform interventions to therapeutically modulate gut microbial H₂S production.

The Capacity to Produce Hydrogen Sulfide (H2S) via Cysteine Degradation Is Ubiquitous in the Human Gut Microbiome

As one of the three mammalian gasotransmitters, hydrogen sulfide (H₂S) plays a major role in maintaining physiological homeostasis. Endogenously produced H₂S plays numerous beneficial roles including mediating vasodilation and conferring neuroprotection. Due to its high membrane permeability, exogenously produced H₂S originating from the gut microbiota can also influence human physiology and is implicated in reducing intestinal mucosal integrity and potentiating genotoxicity and is therefore a potential target for therapeutic interventions. Gut microbial H₂S production is often attributed to dissimilatory sulfate reducers such as Desulfovibrio and Bilophila species. However, an alternative source for H₂S production, cysteine degradation, is present in some gut microbes, but the genes responsible for cysteine degradation have not been systematically annotated in all known gut microbes. We classify mechanisms of cysteine degradation into primary, secondary, and erroneous levels of H₂S production and perform a comprehensive search for primary, secondary, and erroneous cysteine-degrading enzymes in 4,644 non-redundant bacterial genomes from the Unified Human Gastrointestinal Genome (UHGG) catalog. Of the 4,644 genomes we have putatively identified 2,046 primary, 1,951 secondary, and 5 erroneous cysteine-degrading species. We identified the presence of at least one putative cysteine-degrading bacteria in metagenomic data of 100% of 6,623 healthy subjects and the expression of cysteine-degrading genes in metatranscriptomic data of 100% of 736 samples taken from 318 individuals. Additionally, putative cysteine-degrading bacteria are more abundant than sulfate-reducing bacteria across healthy controls, IBD patients and CRC patients (p < 2.2e-16, Wilcoxon rank sum test). Although we have linked many taxa with the potential for cysteine degradation, experimental validation is required to establish the H₂S production potential of the gut microbiome. Overall, this study improves our understanding of the capacity for H₂S production by the human gut microbiome and may help to inform interventions to therapeutically modulate gut microbial H₂S production.

A framework for assessing 16S rRNA marker-gene survey data analysis methods using mixtures

BACKGROUND

There are a variety of bioinformatic pipelines and downstream analysis methods for analyzing 16S rRNA marker-gene surveys. However, appropriate assessment datasets and metrics are needed as there is limited guidance to decide between available analysis methods. Mixtures of environmental samples are useful for assessing analysis methods as one can evaluate methods based on calculated expected values using unmixed sample measurements and the mixture design. Previous studies have used mixtures of environmental samples to assess other sequencing methods such as RNAseq. But no studies have used mixtures of environmental to assess 16S rRNA sequencing.

RESULTS

We developed a framework for assessing 16S rRNA sequencing analysis methods which utilizes a novel two-sample titration mixture dataset and metrics to evaluate qualitative and quantitative characteristics of count tables. Our qualitative assessment evaluates feature presence/absence exploiting features only present in unmixed samples or titrations by testing if random sampling can account for their observed relative abundance. Our quantitative assessment evaluates feature relative and differential abundance by comparing observed and expected values. We demonstrated the framework by evaluating count tables generated with three commonly used bioinformatic pipelines: (i) DADA2 a sequence inference method, (ii) Mothur a de novo clustering method, and (iii) QIIME an open-reference clustering method. The qualitative assessment results indicated that the majority of Mothur and QIIME features only present in unmixed samples or titrations were accounted for by random sampling alone, but this was not the case for DADA2 features. Combined with count table sparsity (proportion of zero-valued cells in a count table), these results indicate DADA2 has a higher false-negative rate whereas Mothur and QIIME have higher false-positive rates. The quantitative assessment results indicated the observed relative abundance and differential abundance values were consistent with expected values for all three pipelines.

CONCLUSIONS

We developed a novel framework for assessing 16S rRNA marker-gene survey methods and demonstrated the framework by evaluating count tables generated with three bioinformatic pipelines. This framework is a valuable community resource for assessing 16S rRNA marker-gene survey bioinformatic methods and will help scientists identify appropriate analysis methods for their marker-gene surveys.