Metagenomic Analyses of Multiple Gut Datasets Revealed the Association of Phage Signatures in Colorectal Cancer

Abstract

The association of colorectal cancer (CRC) and the human gut microbiome dysbiosis has been the focus of several studies in the past. Many bacterial taxa have been shown to have differential abundance among CRC patients compared to healthy controls. However, the relationship between CRC and non-bacterial gut microbiome such as the gut virome is under-studied and not well understood. In this study we conducted a comprehensive analysis of the association of viral abundances with CRC using metagenomic shotgun sequencing data of 462 CRC subjects and 449 healthy controls from 7 studies performed in 8 different countries. Despite the high heterogeneity, our results showed that the virome alpha diversity was consistently higher in CRC patients than in healthy controls (p-value <0.001). This finding is in sharp contrast to previous reports of low alpha diversity of prokaryotes in CRC compared to healthy controls. In addition to the previously known association of Podoviridae, Siphoviridae and Myoviridae with CRC, we further demonstrate that Herelleviridae, a newly constructed viral family, is significantly depleted in CRC subjects. Our interkingdom association analysis reveals a less intertwined correlation between the gut virome and bacteriome in CRC compared to healthy controls. Furthermore, we show that the viral abundance profiles can be used to accurately predict CRC disease status (AUROC >0.8) in both within-study and cross-study settings. The combination of training sets resulted in rather generalized and accurate prediction models. Our study clearly shows that subjects with colorectal cancer harbor a distinct human gut virome profile which may have an important role in this disease.

Impact of HIV infection and integrase strand transfer inhibitors-based treatment on the gut virome

“…However, the importance of gut virome has been understudied. Only few studies have revealed an altered gut viral composition in different pathological conditions such as cancer 12,13 , type I diabetes 14 and inflammatory bowel disease (IBD) 15,16 . Little is known about the impact of HIV infection on gut virome (bacteriophages and eukaryotic viruses).…”

Meta-analyses of host metagenomes from colorectal cancer patients reveal strong relationship between colorectal cancer-associated species

“…These results are in line with previous articles showing the same pattern of little statistical differences in species diversity between CRC and normal conditions but high levels of differences according to cohort. 16,21,35,36,38,61 We tested for all confounders effects (especially Project) using two-sided Wilcoxon-Mann-Whitney tests, comparing the condition blocked for each confounder separately. These analyses replicated the same results observed for the univariate results based on samples conditions (Table S8, ESI †).…”

“…[13][14][15] Recent studies of metagenomic CRC datasets have demonstrated the association between particular microbial species and CRC, suggesting these taxa as signatures for early identification of CRC. [16][17][18][19][20][21][22][23][24] While most of the gut microbiota is composed of the phyla Bacteroidetes and Firmicutes, 1,13 the composition of species and strains is unique to each person. 1 Early reports based on isolated cultures indicated a possible role of some organisms based on their metabolic properties, with more recent studies reinforcing the role of some species in CRC oncogenesis, 25 including John Cunningham virus, 26 Streptococcus gallolyticus, 27 Bacteroides fragilis 28,29 and Fusobacterium nucleatum.…”

Multi-omics analysis of human gut microbiota in colorectal cancer patients

“…Metagenomic studies have most commonly used one of two main approaches to assess the composition of microbiomes: whole-genome shotgun (WGS) sequencing, and 16S ribosomal RNA amplicon sequencing.16S sequencing is the lack of taxonomic resolution; while the variable regions of the gene are particular to different organisms, finding differences within this section of a few hundred base pairs versus differences across the entire genome can often limit identification to only the genus level. In contrast, WGS allows for more accurate detection of species/ strains, and diversity within samples, as well as identification of the coding potential of the genome, which can only be indirectly inferred in the case of 16S sequencing, by extrapolation from known genomes (Ranjan et al, 2016) and provide information on the genes encoded by the strains present in the sample, thus this information can be used to reconstruct potential metabolic capcities of microbial ecosystem (Saus et al, 2019).By using knowledge of WGS many bacterial taxa have been shown to have differential abundance among CRC patients in comparison to healthy controls (Zuo et al, 2022).…”