Multi-kingdom gut microbiota analysis identifies bacterial-viral association in multiple myeloma.

INTRODUCTION

Alterations in the gut microbiome are closely associated with the progression of multiple myeloma (MM). Previous research has predominantly focused on the bacterial components of the microbiota; however, the virome, a significant component of the microbiota, also plays a critical role, with bacteriophages influencing bacterial community composition and evolution.

METHODS

This study utilized shotgun metagenomic sequencing of fecal samples to explore the interaction between the gut microbiota and MM development. Fecal samples from 28 MM patients and 20 healthy controls were analyzed to evaluate microbial diversity. Taxonomic profiling of both bacterial and viral communities was performed using the Kraken2 classifier.

RESULTS

Our analysis confirmed microbial dysbiosis in MM patients and revealed concomitant changes in both bacterial and viral communities. At the phylum level, this study identified a significant increase in the relative abundance of Pseudomonadota (from 1.63 to 8.88%, p < 0.001) and a decrease in Bacillota in MM patients compared to controls. Furthermore, several viral taxa were notably enriched in the MM cohort, including the phylum Heunggongvirae (linear discriminant analysis [LDA] = 4.74, p = 0.00003), phylum Uroviricota, and genus Punavirus (specifically Punavirus RCS47). Functional analysis demonstrated shifts in microbial metabolic pathways associated with MM, including a reduced capacity for amino acid and secondary bile acid biosynthesis and an enrichment of pathways associated with biofilm formation and cationic antimicrobial peptide (CAMP) resistance.

DISCUSSION: This multi-kingdom metagenomic analysis reveals distinct bacterial and viral signatures associated with MM, enhancing our understanding of gut microbial dysbiosis in the disease. These findings lay the groundwork for future mechanistic investigations and highlight the importance of validating these results in larger, independent cohorts.