Olga A. Zlobovskaya

The contribution of the microbiome to sporadic colorectal cancer (CRC) has traditionally been interpreted through the detection of individual tumor-enriched taxa or isolated virulence factors. However, accumulating evidence indicates that CRC-associated microorganisms often act as structured polymicrobial consortia rather than as independent agents. This review proposes an expanded ecological framework for understanding the role of oral taxa in colorectal carcinogenesis. Oral bacteria, including genera Fusobacterium , Parvimonas , Peptostreptococcus , Porphyromonas , Prevotella , Streptococcus , and related taxa, may translocate to the colorectal niche through enteral or hematogenous routes and establish tumor-associated communities that partially recapitulate the structural organization and succession patterns of oral biofilms. Within these communities, Fusobacterium nucleatum serves as the primary bridging organism, facilitating interspecies adhesion and spatial organization. Parvimonas micra , Porphyromonas gingivalis , and Candida albicans display potential bridging structural and functional properties, with their roles in cooperative pathogenicity and tumor progression supported by substantial experimental evidence. We integrate three complementary conceptual frameworks: oral microbial complexes (gut co-abundance groups), bridging organisms and the extended driver-passenger model of CRC. This synthesis supports a shift from taxonomy-centered interpretation toward a functional virulome-based view, in which the role of a taxon is defined by its ecological position, interaction network, and virulence determinants. Key oral virulence factors contribute to biofilm formation, epithelial adhesion and invasion, barrier disruption, immune evasion, inflammatory modulation, metabolic remodeling of the tumor microenvironment, and metastatic potential. Because the composition of translocated oral consortia changes gradually within the colorectal niche, successive consortium members and their associated virulence determinants may serve as indirect microbial signatures of CRC progression. Recognizing CRC-associated oral communities as structured, interactive ecosystems has important diagnostic and therapeutic implications. Simultaneous detection of pathobionts, their cooperative clusters, and functionally relevant virulence determinants may improve microbiome-based risk stratification. Moreover, targeted disruption of bridging functions, interspecies interactions, or virulence factor activity may offer a precision strategy to weaken carcinogenic consortia without broad, dysbiosis-promoting antimicrobial pressure.

Colorectal cancer remains one of the leading causes of cancer-related mortality, highlighting the importance of optimizing approaches for its early diagnosis and therapy. One promising area in this field is the investigation of the role of the gut microbiome in the initiation and progression of colorectal cancer. This review examines three principal hypotheses explaining the contribution of microbiota to carcinogenesis: the “Alpha-bug”, the “Keystone pathogen”, and the “Driver–Passenger” models. We analyze data on the mechanisms of microbiota–tumor cells interactions, including the induction of inflammation, genotoxicity, and disruption of the intestinal barrier function. Findings are also presented indicating that certain microorganisms previously considered markers of the advanced stages may possess pro-oncogenic properties, thereby refining existing carcinogenesis models. Overall, the data suggest that the microbiota and its dysbiotic alterations can be considered potential targets for colorectal cancer diagnosis and therapy.

The emergence of new data on the association between the composition of the intestinal microbiota and various human diseases has generated increasing interest in microbiome research. In this context, selection of the DNA extraction method represents a critical stage in the design of the experiment, significantly affecting the reliability and reproducibility of results. This study presents a comparative analysis of 12 DNA extraction methods, including nine commercial kits and three laboratory protocols. We evaluated the taxonomic representation, including Gram-positive (Lactobacillaceae, Coprococcus spp., Streptococcus sp., Clostridium leptum) and Gram-negative bacteria (Enterobacteriaceae, Akkermansia muciniphila, Fusobacterium nucleatum, Bacteroides fragilis). The extraction efficiency was assessed by the DNA yield, expressed in GE/μL of eluate or in GE/g of feces, as well as by the frequency of low-abundance taxa loss. Clustering of the methods according to the type of lysis was demonstrated: mechanical lysis provided stable and high DNA yields, particularly for Gram-positive bacteria, while chemical and enzymatic methods showed lower efficiency. We determined that the lysis type and pre-processing of intact fecal samples are the key factors affecting the DNA extraction efficiency and preservation of the native taxonomic profile. The best results were demonstrated by the QIAamp® PowerFecal® Pro DNA Kit (Qiagen) and the combination of AmpliTest UniProb + AmpliTest RIBO-prep kits (Center for Strategic Planning, Federal Medical–Biological Agency, Russia), both of which outperformed other methods in terms of DNA yield. The QIAamp® Fast DNA Stool Mini Kit (Qiagen) showed minimal losses of low-abundance taxa. These findings can be used for the standardization of gut microbiota DNA extraction methodologies and the development of domestic protocols.

To date, an increasing body of evidence supports the potential role of activated platelets in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). This is likely due to their ability to secrete biologically active substances that regulate liver regeneration processes, ensure hemostasis, and participate in the immune response. Additionally, several studies have demonstrated the efficacy of antiplatelet agents in reducing inflammation, the severity of liver fibrosis, and the progression of fibrosis in non-alcoholic steatohepatitis (NASH). Since NAFLD is not an independent indication for antiplatelet therapy, the primary evidence regarding their efficacy in NAFLD has been derived from studies using animal models of NAFLD or in patients with concomitant cardiovascular diseases. This narrative review will discuss the main functions of platelets, their unique interactions with liver cells, and the outcomes of these interactions, as well as the results of studies evaluating the efficacy and safety of antiplatelet therapy in patients with NAFLD.

Objective An increasing number of international researchers are focusing on the taxonomic composition of fecal microbiota and its correlation with disorders. Thousands of researchers compare conditionally healthy cohorts to those with specific diseases to identify potential markers. However, clinical application requires assessing the feasibility of synthesizing these findings and establishing reference intervals for normal gut flora, at least at higher taxonomic levels. Design This study involves a systematic review and meta-analysis of human gut microbiota research based on 16S rRNA gene next-generation sequencing (NGS). Relevant research was sourced following the PRISMA guidelines. Descriptive statistics, linear regression analysis by weighted least squares method, Mann-Whitney test, and Benjamini-Hochberg procedure adjustments were employed. The study has been registered with PROSPERO (CRD42023431467). Results Of the 4,346 studies initially identified, 86 publications involving 20,748 unique participants met the quality criteria and were included in the analysis of the impact of fecal sample preparation on taxonomic composition. The phylotype composition, in relation to preprocessing methods and cohort locations, are presented as relative abundances (%): Bacillota (median 49.5–59.6%), Bacteroidota (28.0–33.4%), Pseudomonadota (3.4–5.9%), Actinomycetota (2.3–3.7%), Verrucomicrobiota (0.5–1.0%), Fusobacteriota (maximum 4.6%), and Euryarchaeota (maximum 2.11%). The content of 27 key family-level representatives was also evaluated. The well-known hypothesis regarding the influence of the homogenization stage on taxonomic composition was examined using generalized results. Conclusion While supported by a strong theoretical basis and evidence from individual practical cases, none of the phyla showed a statistically significant association and consistent relationship with sample preparation or cohort location when generalizing across studies after the two exceptionally large cohorts exclusion, both originating from a single research group. These findings underscore the need for strict methodological standardization in microbiome studies. Key features of the 16S NGS process accounting for these results are outlined, along with proposed optimizations for microbiome research.

Colorectal cancer (CRC) is one of the most prevalent malignant neoplasms that occupies the leading position in terms of cancer mortality. The main problem of CRC is that the disease is diagnosed at the advanced stages (about 50% of cases identified are stage III and IV CRC), which results in high mortality. Dysbiotic gut microbiota alterations represent one of the key risk factors of CRC. Three hypotheses of CRC emergence were formulated in order to explain the relationship between dysbiosis and carcinogenesis: “alpha-bug”, keystone pathogen, and driver–passenger hypotheses. The driver–passenger model is the most promising, it divides bacteria into “drivers” of cancer triggering inflammation and cell damage and the passenger bacteria modeling tumor microenvironment, accelerating tumor growth, and exacerbating dysbiosis. Drivers and passengers can be markers of various carcinogenesis stages. Colonoscopy involving examination of the surface of the rectum and colon is the most effective method to detect CRC, including the early stage disease. However, the wide use of this procedure is limited by the fact that it is associated with discomfort for patients and the risk of possible sequelae. Non-invasive microbiota assessment based on the driver–passenger model can become a safe and affordable alternative to the invasive diagnostics during preventive screening, since it makes it possible to improve survival rate due to involvement of a larger number of patients.

Recently, considerable commercialization of services for quantification of gut microbiota aimed to diagnose dysbiosis, the microbial imbalance, is observed. In the context of growing interest to the personalized approaches in medicine and preventive therapy, the diagnosis of dysbiosis is becoming increasingly important. The results of such screening are used to adjust guidelines on correction of the diet, lifestyle modification, or, where necessary, drug therapy prescription. Such assessment requires a reliable and accurate method for evaluation of microbiota, since validity of further recommendations and therapeutic interventions depends on the quality of the data obtained. The paper reports the main aspects of the two approaches used for microbiota quantification: 16S rRNA next-generation sequencing (16S NGS) and real-time PCR (qPCR). The strengths (from our perspective) and weaknesses of the approaches are also provided.

This study investigates the role of gut microbiota in cardiovascular diseases, with an additional focus on pro-atherogenic metabolites. We use advanced network analysis and machine learning techniques to identify key microbial features linked to coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF). This cross-sectional study included 189 participants divided into three groups: coronary artery disease (n = 93), heart failure with reduced ejection fraction (n = 43), and controls (n = 53). Assessments included physical exams, echocardiography, dietary surveys, blood analysis, and fecal analysis. Gut microbiota composition was analyzed using next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR). Statistical analysis methods for testing hypotheses and correlations, alpha and beta-diversity analyses, co-occurrence networks, and machine learning were conducted using Python libraries or R packages with multiple comparisons corrected using the Benjamini–Hochberg procedure. Significant gut microbiota alterations were observed, with higher Bacillota/Bacteroidota ratios in CAD and HFrEF groups compared to controls (p < 0.001). Significant differences were observed in α-diversity indices (Pielou, Chao1, Faith) between disease groups and controls (p < 0.001). β-diversity analyses also revealed distinct microbial profiles (p = 0.0015). Interestingly, trimethylamine N-oxide (TMAO) levels were lower in CAD and HFrEF groups compared to controls (p < 0.05), while indoxyl sulfate (IS) levels were comparable between the study groups. Co-occurrence network analysis and machine learning identified key microbial features linked to these conditions, highlighting complex interactions within the gut microbiota associated with cardiovascular disease.

Aim. To study the relationship of gut microbiota (GM) composition with clinical and paraclinical characteristics of patients with coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF). Material and methods . The study included 64 patients (men, 71,9%) with CAD, 33 (men, 87,9%) with HFrEF and 38 (men, 63,2%) with various cardiovascular risk factors (control group). GM composition was assessed using real-time polymerase chain reaction and next- generation sequencing. To identify correlations of GM composition with clinical and paraclinical characteristics, the Spearman rank correlation coefficient (ρ) was calculated. Generalized linear models (QuasiPoisson, overdispersion) with covariates (age, body mass index) were used to compare groups by phylotype. Results. The relative abundance of Bacillota phylotypes is significantly higher in patients with CAD and HFrEF compared to controls (pConclusion. Patients with CAD and HFrEF differ significantly from the control group in GM composition at the phylotype level. In the study groups, Bacillota/Bacteroidota dysbiosis ratio was also significantly higher than in the control group. The relative abundance of the archaea Methanomassiliicoccaceae and Methanomethylophilaceae is associated with episodes of ventricular tachycardia/ventricular fibrillation.

Non-alcoholic fatty liver disease (NAFLD) is considered the most common chronic liver disease worldwide, affecting nearly 25% of the global adult population. Increasing evidence suggests that functional and compositional changes in the gut microbiota may contribute to the development and promote the progression of NAFLD. 16S rRNA gene next-generation sequencing is widely used to determine specific features of the NAFLD microbiome, but a complex system such as the gut microbiota requires a comprehensive approach. We used three different approaches: MALDI-TOF-MS of bacterial cultures, qPCR, and 16S NGS sequencing, as well as a wide variety of statistical methods to assess the differences in gut microbiota composition between NAFLD patients without significant fibrosis and the control group. The listed methods showed enrichment in Collinsella sp. and Oscillospiraceae for the control samples and enrichment in Lachnospiraceae (and in particular Dorea sp.) and Veillonellaceae in NAFLD. The families, Bifidobacteriaceae, Lactobacillaceae, and Enterococcaceae (particularly Enterococcus faecium and Enterococcus faecalis), were also found to be important taxa for NAFLD microbiome evaluation. Considering individual method observations, an increase in Candida krusei and a decrease in Bacteroides uniformis for NAFLD patients were detected using MALDI-TOF-MS. An increase in Gracilibacteraceae, Chitinophagaceae, Pirellulaceae, Erysipelatoclostridiaceae, Muribaculaceae, and Comamonadaceae, and a decrease in Acidaminococcaceae in NAFLD were observed with 16S NGS, and enrichment in Fusobacterium nucleatum was shown using qPCR analysis. These findings confirm that NAFLD is associated with changes in gut microbiota composition. Further investigations are required to determine the cause-and-effect relationships and the impact of microbiota-derived compounds on the development and progression of NAFLD.