Incorporation of Data From Multiple Hypervariable Regions when Analyzing Bacterial 16S rRNA Gene Sequencing Data

Current progresses and challenges for microbiome research in human health: a perspective

It is becoming increasingly clear that the human microbiota, also known as "the hidden organ", possesses a pivotal role in numerous processes involved in maintaining the physiological functions of the host, such as nutrient extraction, biosynthesis of bioactive molecules, interplay with the immune, endocrine, and nervous systems, as well as resistance to the colonization of potential invading pathogens. In the last decade, the development of metagenomic approaches based on the sequencing of the bacterial 16s rRNA gene via Next Generation Sequencing, followed by whole genome sequencing via third generation sequencing technologies, has been one of the great advances in molecular biology, allowing a better profiling of the human microbiota composition and, hence, a deeper understanding of the importance of microbiota in the etiopathogenesis of different pathologies. In this scenario, it is of the utmost importance to comprehensively characterize the human microbiota in relation to disease pathogenesis, in order to develop novel potential treatment or preventive strategies by manipulating the microbiota. Therefore, this perspective will focus on the progress, challenges, and promises of the current and future technological approaches for microbiome profiling and analysis.

Temporal profiling of sediment microbial communities in the Three Gorges Reservoir Area discovered time-dissimilarity patterns and multiple stable states

Microbial communities play vital roles in cycling nutrients and maintaining water quality in aquatic ecosystems. To better understand the dynamics of microbial communities and to pave way to effective ecological remediation, it's essential to reveal the temporal patterns of the communities and to identify their states. However, research exploring the dynamic changes of microbial communities needs a large amount of time-series data, which could be an extravagant requirement for a single study. In this research, we overcame this challenge by conducting a meta-analysis of years of accumulations of 16S rRNA high-throughput sequencing data from the Three Gorges Reservoir Area (TGRA), an ecological and environmental hotspot. For better understanding the microbial communities time-dissimilarity dynamics, three microbial communities time-dissimilarity patterns were hypothesized, and the linear pattern in the TGRA was validated. In addition, to explore the stability of microbial communities in the TGRA, two alternative stable states were revealed, and their differences in community richness, alpha diversity indices, community composition, ecological network topological properties, and metabolic functions were demonstrated. In short, two states of microbial communities showed distinct richness and alpha diversity indices, and the communities in one state were more dominated by Halomonas and Nitrosopumilaceae genera, facilitating nitrogen cycling metabolic processes; whilst the main genera of the other state were Bathyarchaeia and Methanosaeta, which favored methane-related metabolism. Moreover, different studies and environmental differences between mainstream and tributaries were attributed as the potential inducing factors of the state division. Our study provides a comprehensive insight into the dynamics and stability of microbial communities in the TGRA, and a reference for future studies on microbial community dynamics.

The potential role of the microbiota in prostate cancer pathogenesis and treatment

The human body hosts a complex and dynamic population of trillions of microorganisms - the microbiota - which influences the body in homeostasis and disease, including cancer. Several epidemiological studies have associated specific urinary and gut microbial species with increased risk of prostate cancer; however, causal mechanistic data remain elusive. Studies have associated bacterial generation of genotoxins with the occurrence of TMPRSS2-ERG gene fusions, a common, early oncogenic event during prostate carcinogenesis. A subsequent study demonstrated the role of the gut microbiota in prostate cancer endocrine resistance, which occurs, at least partially, through the generation of androgenic steroids fuelling oncogenic signalling via the androgen receptor. These studies present mechanistic evidence of how the host microbiota might be implicated in prostate carcinogenesis and tumour progression. Importantly, these findings also reveal potential avenues for the detection and treatment of prostate cancer through the profiling and modulation of the host microbiota. The latter could involve approaches such as the use of faecal microbiota transplantation, prebiotics, probiotics, postbiotics or antibiotics, which can be used independently or combined with existing treatments to reverse therapeutic resistance and improve clinical outcomes in patients with prostate cancer.

Potential role of intratumor bacteria outside the gastrointestinal tract: More than passengers

INTRODUCTION

Tumor-associated bacteria and gut microbiota have gained significant attention in recent years due to their potential role in cancer development and therapeutic response. This review aims to discuss the contributions of intratumor bacteria outside the gastrointestinal tract, in addition to exploring the mechanisms, functions, and implications of these bacteria in cancer therapy.

METHODS

We reviewed current literature on intratumor bacteria and their impact on tumorigenesis, progression, metastasis, drug resistance, and anti-tumor immune modulation. Additionally, we examined techniques used to detect intratumor bacteria, precautions necessary when handling low microbial biomass tumor samples, and the recent progress in bacterial manipulation for tumor treatment.

RESULTS

Research indicates that each type of cancer uniquely interacts with its microbiome, and bacteria can be detected even in non-gastrointestinal tumors with low bacterial abundance. Intracellular bacteria have the potential to regulate tumor cells' biological behavior and contribute to critical aspects of tumor development. Furthermore, bacterial-based anti-tumor therapies have shown promising results in cancer treatment.

CONCLUSIONS

Understanding the complex interactions between intratumor bacteria and tumor cells could lead to the development of more precise cancer treatment strategies. Further research into non-gastrointestinal tumor-associated bacteria is needed to identify new therapeutic approaches and expand our knowledge of the microbiota's role in cancer biology.

Could the tumor-associated microbiota be the new multi-faceted player in the tumor microenvironment?

Microorganisms have been identified in tumor specimens for over a century. It is only in recent years that tumor-associated microbiota has become a rapidly expanding field. Assessment techniques encompass methods at the frontiers of molecular biology, microbiology, and histology, requiring a transdisciplinary process to carefully decipher this new component of the tumor microenvironment. Due to the low biomass, the study of tumor-associated microbiota poses technical, analytical, biological, and clinical challenges and must be approached as a whole. To date, several studies have begun to shed light on the composition, functions, and clinical relevance of the tumor-associated microbiota. This new piece of the tumor microenvironment puzzle could potentially change the way we think about and treat patients with cancer.

Multi-amplicon microbiome data analysis pipelines for mixed orientation sequences using QIIME2: Assessing reference database, variable region and pre-processing bias in classification of mock bacterial community samples

Microbiome research relies on next-generation sequencing and on downstream data analysis workflows. Several manufacturers have introduced multi-amplicon kits for microbiome characterization, improving speciation, but present unique challenges for analysis. The goal of this methodology study was to develop two analysis pipelines specific to mixed-orientation reads from multi-hypervariable (V) region amplicons. A secondary aim was to assess agreement with expected abundance, considering database and variable region. Mock community sequence data (n = 41) generated using the Ion16S™ Metagenomics Kit and Ion Torrent Sequencing Platform were analyzed using two workflows. Amplicons from V2, V3, V4, V6-7, V8 and V9 were deconvoluted using a specialized plugin based on CutPrimers. A separate workflow using Cutadapt is also presented. Three reference databases (Ribosomal Database Project, Greengenes and Silva) were used for taxonomic assignment. Bray-Curtis, Euclidean and Jensen-Shannon distance measures were used to evaluate overall annotation consistency, and specific taxon agreement was determined by calculating the ratio of observed to expected relative abundance. Reads that mapped to regions V2-V9 varied for both CutPrimers and Cutadapt-based methods. Within the CutPrimers-based pipeline, V3 amplicons had the best agreement with the expected distribution, tested using global distance measures, while V9 amplicons had the worst agreement. Accurate taxonomic annotation varied by genus-level taxon and V region analyzed. For the first time, we present a microbiome analysis pipeline that employs a specialized plugin to allow microbiome researchers to separate multi-amplicon data from the Ion16S Metagenomics Kit into V-specific reads. We also present an additional analysis workflow, modified for Ion Torrent mixed orientation reads. Overall, the global agreement of amplicons with the expected mock community abundances differed across V regions and reference databases. Benchmarking data should be referenced when planning a microbiome study to consider these biases related to sequencing and data analysis for multi-amplicon sequencing kits.

Analysis of correlations between gut microbiota, stool short chain fatty acids, calprotectin and cardiometabolic risk factors in postmenopausal women with obesity: a cross-sectional study

BACKGROUND

Microbiota and its metabolites are known to regulate host metabolism. In cross-sectional study conducted in postmenopausal women we aimed to assess whether the microbiota, its metabolites and gut barrier integrity marker are correlated with cardiometabolic risk factors and if microbiota is different between obese and non-obese subjects.

METHODS

We analysed the faecal microbiota of 56 obese, postmenopausal women by means of 16S rRNA analysis. Stool short chain fatty acids, calprotectin and anthropometric, physiological and biochemical parameters were correlates to microbiome analyses.

RESULTS

Alpha-diversity was inversely correlated with lipopolysaccharide (Rho = - 0.43, FDR P (Q) = 0.004). Bray-Curtis distance based RDA revealed that visceral fat and waist circumference had a significant impact on metabolic potential (P = 0.003). Plasma glucose was positively correlated with the Coriobacteriaceae (Rho = 0.48, Q = 0.004) and its higher taxonomic ranks, up to phylum (Actinobacteria, Rho = 0.46, Q = 0.004). At the metabolic level, the strongest correlation was observed for the visceral fat (Q < 0.15), especially with the DENOVOPURINE2-PWY, PWY-841 and PWY0-162 pathways. Bacterial abundance was correlated with SCFAs, thus some microbiota-glucose relationships may be mediated by propionate, as indicated by the significant average causal mediation effect (ACME): Lachnospiraceae (ACME 1.25, 95%CI (0.10, 2.97), Firmicutes (ACME 1.28, 95%CI (0.23, 3.83)) and Tenericutes (ACME - 0.39, 95%CI (- 0.87, - 0.03)). There were significant differences in the distribution of phyla between this study and Qiita database (P < 0.0001).

CONCLUSIONS

Microbiota composition and metabolic potential are associated with some CMRF and fecal SCFAs concentration in obese postmenopausal women. There is no unequivocal relationship between fecal SCFAs and the marker of intestinal barrier integrity and CMRF. Further studies with appropriately matched control groups are warranted to look for causality between SCFAs and CMRF.

Composition of gastrointestinal microbiota in association with treatment response in individuals with metastatic castrate resistant prostate cancer progressing on enzalutamide and initiating treatment with anti-PD-1 (pembrolizumab)

Recent studies in cancer patients and animal models demonstrate that intestinal microbiota influence the therapeutic efficacy of cancer treatments, including immune checkpoint inhibition. However, no studies to-date have investigated relationships between gastrointestinal microbiota composition and response to checkpoint inhibition in advanced metastatic castrate resistant prostate cancer (mCRPC). We performed 16S rRNA gene sequencing of fecal DNA from 23 individuals with mCRPC progressing on enzalutamide and just prior to treatment with anti-PD-1 (pembrolizumab) to determine whether certain features of the microbiome are associated with treatment response (defined as serum PSA decrease >50% at any time on treatment or radiographic response per RECIST V.1.1). Global bacterial composition was similar between responders and non-responders, as assessed by multiple alpha and beta diversity metrics. However, certain bacterial taxa identified by sequencing across multiple 16S rRNA hypervariable regions were consistently associated with response, including the archetypal oral bacterium Streptococcus salivarius. Quantitative PCR (qPCR) of DNA extracts from fecal samples confirmed increased Streptococcus salivarius fecal levels in responders, whereas qPCR of oral swish DNA extracts showed no relationship between oral Streptococcus salivarius levels and response status. Contrary to previous reports in other cancer types, Akkermansia muciniphila levels were reduced in responder samples as assessed by both 16S rRNA sequencing and qPCR. We further analyzed our data in the context of a previously published “integrated index” describing bacteria associated with response and non-response to checkpoint inhibition. We found that the index was not reflective of response status in our cohort. Lastly, we demonstrate little change in the microbiome over time, and with pembrolizumab treatment. Our results suggest that the association between fecal microbiota and treatment response to immunotherapy may be unique to cancer type and/or previous treatment history.

A Multi-Functional Anti-Aging Moisturizer Maintains a Diverse and Balanced Facial Skin Microbiome

AIMS

To assess the effect of a 28-day skincare regimen in healthy female subjects on the facial skin microbiome composition and to determine if the skincare regimen including a gentle cleansing lotion, a multi-functional anti-aging moisturizer formulated with prebiotics and postbiotics at skin neutral pH, and bland sunscreen pushed the microbiome to a healthier state and improved skin aging measured by self-assessment and clinical photography.

METHODS AND RESULTS

The study protocol was in accordance with the EU Scientific Committee on Consumer Safety (SCCS) guidance and met all international standards. Twenty-five female subjects between 35 to 65 years old with Fitzpatrick skin type I - VI, moderate crow's feet wrinkles and global face photodamage were enrolled. After 28 days the skincare regimen improved microbial facial diversity and shifted the microbiota composition when compared to baseline.

CONCLUSIONS

After 28-days, the skincare regimen treatment shifted the distribution of the facial skin microbiome, positively influencing the skin microbiome diversity and balance, to promote long term skin health and protect from further skin aging.

SIGNIFICANCE AND IMPACT OF STUDY

These results suggest that incorporating prebiotics and postbiotics into a skincare regimen may have a positive impact on the facial skin microbiome in healthy women.