Characterization of the gut DNA and RNA Viromes in a Cohort of Chinese Residents and Visiting Pakistanis

Abstract

Trillions of viruses inhabit the gastrointestinal tract. Some of them have been well-studied on their roles in infection and human health, but the majority remain unsurveyed. It has been established that the composition of the gut virome is highly variable based on the changes of diet, physical state, and environmental factors. However, the effect of host genetic factors, e.g. ethnic origin, on the gut virome is rarely investigated. Here, we characterized and compared the gut virome in a cohort of local Chinese residents and visiting Pakistani individuals, each group containing 24 healthy adults and 6 children. Using metagenomic shotgun sequencing and assembly of fecal samples, a huge number of viral operational taxonomic units (vOTUs) were identified for profiling the DNA and RNA viromes. National background contributed a primary variation to individuals’ gut virome. Compared with the Chinese adults, the Pakistan adults showed higher macrodiversity and different compositional and functional structures in their DNA virome and lower diversity and altered composition in their RNA virome. The virome variations of Pakistan children were inherited from the that of the adults but also tended to share similar characteristics with the Chinese cohort. We also analyzed and compared the bacterial microbiome between two cohorts and further revealed numerous connections between viruses and bacterial host. Statistically, the gut DNA and RNA viromes were covariant to some extent (p < 0.001), and they both correlated the holistic bacterial composition and vice versa. This study provides an overview of the gut viral community in Chinese and visiting Pakistanis and proposes a considerable role of ethnic origin in shaping the virome.

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“…The vOTUs were annotated with the latest NCBI virus database using the blastp function of DIAMOND with options –query-cover 70 and –id 30. If more than one-third of the annotated proteins of a vOTU belonged to the same family, the vOTU would be assigned to that viral family ( 79 ). The average abundance of vOTUs was calculated by the CoverM-contig pipeline ( https://github.com/wwood/CoverM ) with the following parameter settings: –min-read-percent-identity 0.95, –min-read-aligned-percent 0.5, –proper-pairs-only, and –exclude-supplementary.…”

“…Kruskal-Wallis test, Wilcoxon test, and t test were used to evaluate differences in various variables between groups; P values were corrected for multiple testing using the Benjamini-Hochberg procedure. The method of effect size analysis was performed according to Yan et al ( 79 ). The centered log-ratio (clr) abundance transformation was performed using the R package microbiome.…”

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“…The gut microbiota has been shown to affect the host physiological processes, and, in some cases, it even drives the development of disease (such as inflammatory bowel disease, asthma, anxiety, obesity, and CVD) through absorption of gut microbe-originated bioactive metabolites into the cardiovascular system ( 22 , 23 ). The gut-heart axis is a recently established concept in the field of CVD research, and the bidirectional interactions between the two body locations may open innovative and promising diagnostic and treatment options for CAD ( 1 , 3 ).…”

“…P values were corrected for multiple testing using the Benjamini-Hochberg procedure. The effect size analysis was performed according to Yan et al ( 22 ). Briefly, a set of nonredundant covariates (species versus clinical indicators, metabolites, or immune parameters) were selected from the omics and clinical parameter data sets, and then the accumulated effect size was calculated by Adonis analysis in each case.…”

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“…Prodigal GenBank coordinates were used as input for each sample for vConTACT2 and it was run with pc-inflation and vc-inflation set to 1.5, pcs-mode set to MCL, and vcs-mode set to ClusterONE. 31 Databases used for the analysis were TrEMBL and ProkaryoticViralRefSeq94-Merged.…”