Background: Movile Cave (SE Romania) is a chemoautotrophically-based ecosystem fed by hydrogen sulfide-rich groundwater serving as a primary energy source analogous to the deep-sea hydrothermal ecosystems. Our current understanding of Movile Cave microbiology has been confined to the sulfidic water and its proximity, as most studies focused on the water-floating microbial mat and planktonic accumulations likely acting as the primary production powerhouse of this unique subterranean ecosystem. By employing comprehensive genomic-resolved metagenomics, we questioned the spatial variation, chemoautotrophic abilities, ecological interactions and trophic roles of Movile Cave’s microbiome thriving beyond the sulfidic-rich water.Results: A customized bioinformatics pipeline led to the recovery of 106 high-quality metagenome-assembled genomes from 7 cave sediment metagenomes. Assemblies’ taxonomy spanned 19 bacterial and three archaeal phyla withAcidobacteriota,Chloroflexota,Proteobacteria,Planctomycetota,Ca.Patescibacteria,Thermoproteota,Methylomirabilota,andCa.Zixibacteria as prevalent phyla. Functional gene analyses predicted the presence of CO₂fixation, methanotrophy, sulfur and ammonia oxidation in the explored sediments. Species Metabolic Coupling Analysis of metagenome-scale metabolic models revealed the highest competition-cooperation interactions in the sediments collected away from the water. Simulated metabolic interactions indicated autotrophs and methanotrophs as major donors of metabolites in the sediment communities. Cross-feeding dependencies were assumed only towards 'currency' molecules and inorganic compounds (O₂, PO₄³⁻, H⁺, Fe²⁺, Cu²⁺) in the water proximity sediment, whereas hydrogen sulfide and methanol were assumedly traded exclusively among distant gallery communities.Conclusions: These findings suggest that the primary production potential of Movile Cave expands way beyond its hydrothermal waters, enhancing our understanding of the functioning and ecological interactions within chemolithoautotrophically-based subterranean ecosystems.

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS). Its first clinical presentation (clinically isolated syndrome, CIS) is often followed by the development of relapsing–remitting MS (RRMS). The periphery-to-CNS transmission of inflammatory molecules is a major pathophysiological pathway in MS. This could include signalling via extracellular vesicle (EV) microRNAs (miRNAs). In this study, we investigated the serum EV miRNome in CIS and RRMS patients and matched controls, with the aims to identify MS stage-specific differentially expressed miRNAs and investigate their biomarker potential and pathophysiological relevance. miRNA sequencing was conducted on serum EVs from CIS-remission, RRMS-relapse, and viral inflammatory CNS disorder patients, as well as from healthy and hospitalized controls. Differential expression analysis was conducted, followed by predictive power and target-pathway analysis. A moderate number of dysregulated serum EV miRNAs were identified in CIS-remission and RRMS-relapse patients, especially relative to healthy controls. Some of these miRNAs were also differentially expressed between the two MS stages and had biomarker potential for patient-control and CIS–RRMS separations. For the mRNA targets of the RRMS-relapse-specific EV miRNAs, biological processes inherent to MS pathophysiology were identified using in silico analysis. Study findings demonstrate that specific serum EV miRNAs have MS stage-specific biomarker potential and contribute to the identification of potential targets for novel, efficacious therapies.

The interaction between the microbial communities in the human body and the onset and progression of cancer has not been investigated until recently. The vast majority of the metagenomics research in this area has concentrated on the composition of microbiomes, attempting to link the overabundance or depletion of certain microorganisms to cancer proliferation, metastatic behaviour, and its resistance to therapies. However, studies elucidating the functional implications of the microbiome activity in cancer patients are still scarce; in particular, there is an overwhelming lack of studies assessing such implications directly, through analysis of the transcriptome of the bacterial community. This review summarises the contributions of metagenomics and metatranscriptomics to the knowledge of the microbial environment associated with several cancers; most importantly, it highlights all the advantages that metatranscriptomics has over metagenomics and suggests how such an approach can be leveraged to advance the knowledge of the cancer bacterial environment.

Immune-inflammatory activation impacts extracellular vesicles (EVs), including their miRNA cargo. There is evidence for changes in the EV miRNome in inflammation-associated neuropsychiatric disorders. This mouse study investigated: (1) effects of systemic lipopolysaccharide (LPS) and chronic social stress (CSS) on plasma EV miRNome; and (2) physiological, transcriptional, and behavioural effects of peripheral or central delivered LPS-activated EVs in recipient mice. LPS or CSS effects on the plasma EV miRNome were assessed by using microRNA sequencing. Recipient mice received plasma EVs isolated from LPS-treated or SAL-treated donor mice or vehicle only, either intravenously or into the nucleus accumbens (NAc), on three consecutive days. Bodyweight, spleen or NAc transcriptome and reward (sucrose) motivation were assessed. LPS and CSS increased the expression of 122 and decreased expression of 20 plasma EV miRNAs, respectively. Peripheral LPS-EVs reduced bodyweight, and both LPS-EVs and SAL-EVs increased spleen expression of immune-relevant genes. NAc-infused LPS-EVs increased the expression of 10 immune-inflammatory genes. Whereas motivation increased similarly across test days in all groups, the effect of test days was more pronounced in mice that received peripheral or central LPS-EVs compared with other groups. This study provides causal evidence that increased EV levels impact physiological and behavioural processes and are of potential relevance to neuropsychiatric disorders.

Metatranscriptomics has not yet been applied to the study of the endodontic microbiome. Therefore, this study investigated the microbial composition and patterns of gene expression in teeth with asymptomatic apical periodontitis. We performed next-generation, microbiomewide RNA-sequencing in eight root canal samples, including five primary and three secondary endodontic infections. Proteobacteria, Bacteroidetes, Firmicutes and Actinobacteria represented the dominant phyla, whereas Fusobacteria, Spirochaetes and Synergistetes were among the non-dominant phyla. At species level, the microbiome was dominated by Gram-negative and Gram-positive anaerobes. In particular, Prevotella spp. and Olsenella uli were more abundant in primary than in secondary infections. Transcripts encoding moonlighting proteins were abundant, including glycolytic proteins, translational elongation factors, chaperonin, and heat shock proteins. Fusobacterium was highly active in primary infections, showing upregulation of genes involved in protein synthesis, responses to oxidative stress and resistance to antibiotics, especially tetracycline. In addition, other members of the community expressed high numbers of antimicrobial resistance genes. Overall, metatranscriptomics revealed the expression of putative virulence factors and the activity of potential endodontic pathogens, represented mainly by obligate anaerobes. In particular, the functional role of Fusobacterium in primary infections was highlighted. Furthermore, antimicrobial resistance, especially to tetracycline, was a common feature in endodontic samples.