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.

Feсal microbiota transplantation in the format of complex therapy in obesive siblings: clinical case

Obesity and associated metabolic diseases are often accompanied by changes in the gut microbiota leading to metagenome gene diversity decrease. Fecal microbiota transplantation (FMT) is one of the most effective methods for correcting the  intestinal microflora. FMT obtained from healthy donors has been proven to be an effective treatment of infections caused by Clostridium difficile. The use of FMT for correction of metabolic disorders is promising, however, data on its application is limited and has contradictory results. In our work, two patients (siblings) presented with obesity grade II and various types of diabetes mellitus (DM): the older brother (44 years old) with diabetes mellitus type 2 (DM 2), a younger brother (39 years old) with diabetes mellitus type 1 (DM 1). Both patients underwent FMT as part of complex antidiabetic therapy. During the course of treatment, a decrease in body weight was noted in both patients (4–5 kg for the first month of observation, then -1–2 kg per month). One year after FMT, a patient with type 2 diabetes showed a decrease in the severity of insulin resistance (IR), measured by the hyperinsulinemic euglycemic clamp test (initial M-index 2.42 mg/kg*min, after 1 year — 3.83 mg/kg* min) as well as the maintenance of satisfactory carbohydrate metabolism compensation against the diminishing the hypoglycemic therapy. In a patient with DM 1, no significant dynamics of carbohydrate exchange indices, including detected glycated hemoglobin (HbA1c), insulin dose and IR were during the observation period. Metagenomic sequencing of stool samples (n = 20) collected from both patients before and within 1 year after FMT showed no significant changes in the taxonomic profile of the microbiota at the level of microbial families. Metabolomic analysis of the composition of feces showed no directed changes in the composition of metabolites after the FMT procedure, the nature of changes within the samples from each patient during the entire study period was random. Thus, FMT had no effect on the course of DM1, but served as a starting point for weight loss and improvement glucose profile in DM2. However, convincing data confirming a causal correlation between FMT and improvement in the course of T2DM have not been obtained.

[Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis]

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]

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.