An improved and extended dual-index multiplexed 16S rRNA sequencing for the Illumina HiSeq and MiSeq platform.

BACKGROUND: Recent advancements in next-generation sequencing (NGS) technology have ushered in significant improvements in sequencing speed and data throughput, thereby enabling the simultaneous analysis of a greater number of samples within a single sequencing run. This technology has proven particularly valuable in the context of microbial community profiling, offering a powerful tool for characterizing the microbial composition at the species level within a given sample. This profiling process typically involves the sequencing of 16S ribosomal RNA (rRNA) gene fragments. By scaling up the analysis to accommodate a substantial number of samples, sometimes as many as 2,000, it becomes possible to achieve cost-efficiency and minimize the introduction of potential batch effects. Our study was designed with the primary objective of devising an approach capable of facilitating the comprehensive analysis of 1,711 samples sourced from diverse origins, including oropharyngeal swabs, mouth cavity swabs, dental swabs, and human fecal samples. This analysis was based on data obtained from 16S rRNA metagenomic sequencing conducted on the Illumina MiSeq and HiSeq sequencing platforms. RESULTS: We have designed a custom set of 10-base pair indices specifically tailored for the preparation of libraries from amplicons derived from the V3-V4 region of the 16S rRNA gene. These indices are instrumental in the analysis of the microbial composition in clinical samples through sequencing on the Illumina MiSeq and HiSeq platforms. The utilization of our custom index set enables the consolidation of a significant number of libraries, enabling the efficient sequencing of these libraries in a single run. CONCLUSIONS: The unique array of 10-base pair indices that we have developed, in conjunction with our sequencing methodology, will prove highly valuable to laboratories engaged in sequencing on Illumina platforms or utilizing Illumina-compatible kits.

[Composition of oropharyngeal microbiota in patients with COVID-19 of different pneumonia severity].

AIM: To identify features of the taxonomic composition of the oropharyngeal microbiota of COVID-19 patients with different disease severity. MATERIALS AND METHODS: The study group included 156 patients hospitalized with confirmed diagnosis of COVID-19 in the clinical medical center of Yevdokimov Moscow State University of Medicine and Dentistry between April and June 2021. There were 77 patients with mild pneumonia according to CT (CT1) and 79 patients with moderate to severe pneumonia (CT2 and CT3). Oropharyngeal swabs were taken when the patient was admitted to the hospital. Total DNA was isolated from the samples, then V3V4 regions of the 16s rRNA gene were amplified, followed by sequencing using Illumina HiSeq 2500 platform. DADA2 algorithm was used to obtain amplicon sequence variants (ASV). RESULTS: When comparing the microbial composition of the oropharynx of the patients with different forms of pneumonia, we have identified ASVs associated with the development of both mild and severe pneumonia outside hospital treatment. Based on the results obtained, ASVs associated with a lower degree of lung damage belong predominantly to the class of Gram-negative Firmicutes (Negativicutes), to various classes of Proteobacteria, as well as to the order Fusobacteria. In turn, ASVs associated with a greater degree of lung damage belong predominantly to Gram-positive classes of Firmicutes Bacilli and Clostridia. While being hospitalized, patients with severe pneumonia demonstrated negative disease dynamics during treatment significantly more often. CONCLUSION: We have observed differences in the taxonomic composition of the oropharyngeal microbiota in patients with different forms of pneumonia developed outside hospital treatment against COVID-19. Such differences might be due to the presumed barrier function of the oropharyngeal microbiota, which reduces the risk of virus titer increase.

[Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis]. / Mikrobiom kishechnika kak prediktor uspekha anti-PD1 terapii: analiz metagenomnykh dannykh.

Anti-PD-1 immunotherapy has a large impact on cancer treatment but the rate of positive treatment outcomes is 40-45% and depends on many factors. One of the factors affecting the outcome of immunotherapy is the gut microbiota composition. This effect has been demonstrated both in model objects and in clinical patients groups. However, in order to identify clear causal relationships between microbiota and anti-PD1 immunotherapy response, it is necessary to expand the number of patients and experimental samples. This work presents an analysis of metagenomic data obtained using whole-genome sequencing of stool samples from melanoma patients (n=45) with different responses to anti-PD1 therapy. The analysis of the differential representation of microbial species has shown a difference in the composition of the microbiota between the experimental groups. Results of this study indicate existence of a strong link between the composition of the gut microbiota and the outcome of anti-PD1 therapy. Expansion of similar research may help develop additional predictive tools for the outcome of anti-PD1 cancer immunotherapy, as well as increase its effectiveness.

[Intestinal microbiom modulates the response to antitumor immunotherapy]. / Vliianie mikrobioma kishechnika na éffektivnost' protivoopukholevoi immunoterapii.

Numerous studies confirm the high degree of involvement of the intestinal microbiota in most processes in the human body. There is evidence for the effect of intestinal microbiota on the success of chemo and immunotherapy of oncological diseases. It is assumed that the intestinal microbiota exhibits an indirect effect on the antitumor therapy through such mechanisms as general immunomodulation, an increase in cells that specifically respond to antigens of both microbial and tumor origin, metabolism, degradation (utilization) of drug compounds. The intestinal microbiota is currently considered as an additional, but important target for studying the effective use of antitumor therapy and reducing its toxicity, as well as a predictor of the success of immunotherapy. In this review, we highlight the results of studies published to date that confirm the relationship between gut microbiome and antitumor efficacy of immune checkpoint inhibitors. Despite the promising and theoretically substantiated conclusions, there are still some discrepancies among the existing data that will have to be addressed in order to facilitate the further development of this direction.