To date, transcriptomics have been widely and successfully employed to study gene expression in different cell growth phases of bacteria. Since bifidobacteria represent a major component of the gut microbiota of a healthy human that is associated with numerous health benefits for the host, it is important to study them using transcriptomics. In this study, we applied the RNA-Seq technique to study global gene expression of B. longum at different growth phases in order to better understand the response of bifidobacterial cells to the specific conditions of the human gut. We have shown that in the lag phase, ABC transporters, whose function may be linked to active substrate utilization, are increasingly expressed due to preparation for cell division. In the exponential phase, the functions of activated genes include synthesis of amino acids (alanine and arginine), energy metabolism (glycolysis/gluconeogenesis and nitrogen metabolism), and translation, all of which promote active cell division, leading to exponential growth of the culture. In the stationary phase, we observed a decrease in the expression of genes involved in the control of the rate of cell division and an increase in the expression of genes involved in defense-related metabolic pathways. We surmise that the latter ensures cell survival in the nutrient-deprived conditions of the stationary growth phase.

Bifidobacteria are commensal microorganisms that inhabit a wide range of hosts, including insects, birds and mammals. The mechanisms responsible for the adaptation of bifidobacteria to various hosts during the evolutionary process remain poorly understood. Previously, we reported that the species-specific PFNA gene cluster is present in the genomes of various species of the Bifidobacterium genus. The cluster contains signal transduction and adhesion genes that are presumably involved in the communication between bifidobacteria and their hosts. The genes in the PFNA cluster show high sequence divergence between bifidobacterial species, which may be indicative of rapid evolution that drives species-specific adaptation to the host organism. We used the maximum likelihood approach to detect positive selection in the PFNA genes. We tested for both pervasive and episodic positive selection to identify codons that experienced adaptive evolution in all and individual branches of the Bifidobacterium phylogenetic tree, respectively. Our results provide evidence that episodic positive selection has played an important role in the divergence process and molecular evolution of sequences of the species-specific PFNA genes in most bifidobacterial species. Moreover, we found the signatures of pervasive positive selection in the molecular evolution of the tgm gene in all branches of the Bifidobacterium phylogenetic tree. These results are consistent with the suggested role of PFNA gene cluster in the process of specific adaptation of bifidobacterial species to various hosts.

The interaction between gut microbiota and the host immune system is a complex and understudied field, with cytokines like TNFα, IL-6, IL-8, and IL-10 playing pivotal roles. Commensal bacteria, including lactobacilli, respond to these cytokines through adaptive mechanisms that support their survival and function within the gut. While the influence of cytokines on pathogenic bacteria is well documented, their impact on commensal bacteria, particularly lactobacilli, remains underexplored. This study investigates the transcriptional responses of Lacticaseibacillus rhamnosus strains K32 and R19-3 to various cytokines using next-generation RNA sequencing (RNA-seq). Our findings reveal that cytokines, especially IL-8 and IL-10, significantly alter the L. rhamnosus transcriptome, affecting genes involved in carbohydrate metabolism, stress response, and transcriptional regulation. Notably, IL-8 and IL-10 induce a significant downregulation of genes related to the phosphotransferase system, suggesting a reduction in metabolic activity in response to inflammatory signals. This study unveils a previously unexplored aspect of L. rhamnosus adaptation, highlighting its intricate response to cytokine signals. By modulating gene expression, L. rhamnosus may mitigate the adverse effects of inflammation and promote gut health. These insights could inform the development of targeted probiotic therapies for inflammatory bowel disease (IBD) and other conditions with altered cytokine levels. Our results suggest that co-evolution between a host and gut microbiota enables bacteria to respond to specific cytokines through gene expression changes, revealing a unique and underexplored facet of the interaction between commensal bacteria and the host organism.

Melanoma is an aggressive malignancy with a significant risk of mortality. In recent years, treatment strategies have undergone a paradigm shift with the advent of immunotherapy, particularly immune checkpoint inhibitors (ICIs). Despite notable clinical success, a substantial proportion of patients fail to respond or eventually develop resistance to ICIs. Emerging evidence highlights the gut microbiota as a critical modulator of host immune responses and is one of the potential determinants of immunotherapy efficacy. We performed a cross-cohort analysis of gut microbiome profiles from melanoma patients treated with ICIs. The study integrated the first Russian cohort (62 patients) with six previously published international datasets, comprising a total of 490 patients across seven cohorts. In all cases, metagenomic sequencing was performed using various Illumina platforms, and raw sequencing data were processed using a unified bioinformatic pipeline. Analysis revealed 527 metagenome-assembled genomes (MAGs) significantly associated with treatment outcome: 239 with response and 288 with non-response. Notably, the species Faecalibacterium sp900539945, Phocaeicola vulgatus, Bifidobacterium adolescentis, Faecalibacterium taiwanense, and Gemmiger qucibialis were consistently associated with response, while Enterobacter ludwigii was linked to non-response. Analysis of the Russian cohort revealed both conserved and population-specific microbial signatures, highlighting the coexistence of globally shared and region-dependent microbiome features. Our results also show that species-level annotations may obscure opposing response associations within the same taxa, highlighting the need for MAGs or strain profiling. Together, this study demonstrates that cross-cohort analysis enables the identification of robust and reproducible bacterial markers of immunotherapy response, providing a foundation for microbiome-based prediction and modulation strategies in melanoma.