Microbiome Studies Research Articles

Sample collection time affects microbiome study results.

Sample collection time affects microbiome study results.

Oral specimens as a tool for accurate metagenomic analysis: A pilot study

ObjectivesAcute oral mucosal damage, as well as other inflammatory processes seem to be related to dysbiosis of the oral microbiome. The need to study changes in the oral microbiome led us to hypothesize what type of sample would provide the most representative picture of the entire human oral microbiome. Materials and methodsAn observational, and cross-sectional study was carried out. Six healthy adult participants provided 3 different sample types each, that included saliva, oral rinse and mucosal biopsy tissue. We performed 16S rRNA sequencing of the V3-V4 region of the 18 samples using Illumina MiSeq technology. ResultsParticipants were 27 ± 6,3 years old. Bacterial alpha diversity was higher in oral rinse samples compared to whole unstimulated saliva and oral mucosa tissue (p = 0,005). However, saliva specimens showed a 56 % relative abundance of identified species followed by a 30 % in oral rinse and only 1 % in tissue samples. ConclusionsThis study found differences on oral microbiome composition for each type of sample. Oral rinse should be chosen when higher alpha diversity is needed, whereas whole unstimulated saliva should be more appropriate for larger amount of bacterial DNA. Clinical relevanceThe results obtained demonstrate the importance of a correct choice of the optimal type of oral sample for microbiome studies due to the differences found in its composition.

Effects of Fermented and Fiber-Rich Foods on Maternal & Offspring Microbiome Study (FeFiFo-MOMS)

Effects of Fermented and Fiber-Rich Foods on Maternal & Offspring Microbiome Study (FeFiFo-MOMS)

Gut Microbiota as Therapeutic Targets in Diabetes Management: Opportunities and Challenges

This article delves into the complex interplay between Type 2 Diabetes Mellitus (T2DM), gut microbiota, and dietary strategies for effective diabetes management. T2DM, characterized by insulin resistance and β-cell dysfunction, is influenced by genetic and environmental factors. The gut-brain axis and alterations in incretin functioning contribute to gastrointestinal permeability in T2DM. Plant-based diets offer substantial benefits for managing T2DM by improving emotional well-being, HbA1c levels, weight, and cholesterol. High-fiber diets positively impact gut microbiota, serum metabolism, and emotional health in T2DM individuals. Probiotics, prebiotics, synbiotics, and postbiotics (PPSP) are emerging as pivotal interventions. Probiotics improve serum fructosamine, HbA1c, and cholesterol levels, while prebiotics like oligofructose-enriched inulin and synbiotics enhance glycemic control and lipid profiles. Insights from microbiome studies in diverse dietary populations provide personalized approaches for diabetes management. Integrating plant-based nutrition, PPSP interventions, and microbiome-focused strategies may offer a comprehensive and effective approach to T2DM management, addressing physiological aspects and empowering individuals in their health journey.

Guideline for designing microbiome studies in neoplastic diseases

Oncobiosis has emerged as a key contributor to the development, and modulator of the treatment efficacy of cancer. Hereby, we review the modalities through which the oncobiome can support the progression of tumors, and the emerging therapeutic opportunities they present. The review highlights the inherent challenges and limitations faced in sampling and accurately characterizing oncobiome. Additionally, the review underscores the critical need for the standardization of microbial analysis techniques and the consistent reporting of microbiome data. We provide a suggested metadata set that should accompany microbiome datasets from oncological settings so that studies remain comparable and decipherable.

Bacterial barcoding facilitates plant microbiome studies.

Bacterial barcoding facilitates plant microbiome studies.

Sequencing-based analysis of microbiomes.

Microbiomes occupy a range of niches and, in addition to having diverse compositions, they have varied functional roles that have an impact on agriculture, environmental sciences, and human health and disease. The study of microbiomes has been facilitated by recent technological and analytical advances, such as cheaper and higher-throughput DNA and RNA sequencing, improved long-read sequencing and innovative computational analysis methods. These advances are providing a deeper understanding of microbiomes at the genomic, transcriptional and translational level, generating insights into their function and composition at resolutions beyond the species level.

Cтруктура микробиоты фертильных и инфертильных пациентов с различными видами азооспермии.

Introduction. The study of the human microbiome has become of increasing scientific interest. A balanced and diverse microbiota of the male re- productive system is essential for optimal reproductive health. Today, there are no diagnostic tests to determine the effect of specific microorganisms on the quality of seminal fluid, however, the use of next-generation sequencing (NGS), using the 16S rRNA gene sequence as a molecular marker, provides us with the opportunity to understand the complexity of the relationship between the microbiome and its host. The aim of the study. To conduct a comparative analysis of the taxonomic structure of the microbiota between patients with obstructive and nonobstructive azoospermia and the fertility group (patients with a history of having children). Materials and methods. The study included (n=57) patients (infertile patients with obstructive azoospermia (OA), non-obstructive azoospermia (NOA) and a control group (FERT). All patients underwent percutaneous aspiration of sperm from the testicle (testicular sperm aspiration, MESA), with subsequent in vitro fertilization using ICSI technology, or cryopreservation of biological material. The amplicons of the bacterial 16S rRNA gene were analyzed using high-performance next-generation sequencing (NGS). For this research of bacterial composition of the urogenital tract and control the purity of the method, samples has been taken from the urethra of each patient who underwent testicular biopsy. The data was processed using the QUICKTIME program (version 1.9.1). Results. No significant differences were found in the comparison groups during the study of the urethral bacterial composition. The species diversity, as well as the total number of detected taxonomic units (OTE) in the NOA and OA groups are significantly lower than in the FERT group. The presentation of the phylum like Proteobacteria, Firmicutes, Bacteroidetes, Bifidobacterium adolescentis in the studied groups is different. Three microorganisms were identified with the same frequency in the urethra and testicular tissue (the exact Fisher criterion was used, adjusted for multiple comparison by the Benjamin-Hochberg method). The representation of the phylum Prevotella, Comamonadaceae, Veillonella dispa, Comamonadaceae in the studied groups differs. Conclusion. Testicular tissue is not sterile and has its own unique microbial landscape for each comparison group. Bacterial communities of testicular tissue in patients with azoospermia are characterized by a reduced diversity and a specific composition that differs from the urethral microbiota. These results may be useful in further to study the role of microbiota in the pathology of spermatogenesis and developing new approaches to the treatment and diagnosis of male infertility.

Strain-specific gut microbial signatures in type 2 diabetes identified in a cross-cohort analysis of 8,117 metagenomes.

The association of gut microbial features with type 2 diabetes (T2D) has been inconsistent due in part to the complexity of this disease and variation in study design. Even in cases in which individual microbial species have been associated with T2D, mechanisms have been unable to be attributed to these associations based on specific microbial strains. We conducted a comprehensive study of the T2D microbiome, analyzing 8,117 shotgun metagenomes from 10 cohorts of individuals with T2D, prediabetes, and normoglycemic status in the United States, Europe, Israel and China. Dysbiosis in 19 phylogenetically diverse species was associated with T2D (false discovery rate < 0.10), for example, enriched Clostridium bolteae and depleted Butyrivibrio crossotus. These microorganisms also contributed to community-level functional changes potentially underlying T2D pathogenesis, for example, perturbations in glucose metabolism. Our study identifies within-species phylogenetic diversity for strains of 27 species that explain inter-individual differences in T2D risk, such as Eubacterium rectale. In some cases, these were explained by strain-specific gene carriage, including loci involved in various mechanisms of horizontal gene transfer and novel biological processes underlying metabolic risk, for example, quorum sensing. In summary, our study provides robust cross-cohort microbial signatures in a strain-resolved manner and offers new mechanistic insights into T2D.

Unassigning bacterial species for microbiome studies.

The method of 16S rRNA marker gene sequencing has fueled microbiome research and continues to be relevant. A perceived weakness of the method is that taxonomic assignments are not possible to make at the rank of species. We show that by working to rule out bacterial or archaeal species membership, we can provide an answer that is more accurate and useful. The Unassigner software operates on 16S rRNA marker gene data and computes a rule-out probability for species membership using a beta-binomial distribution. We demonstrate that our approach is accurate based on full-genome comparisons. Our method is consistent with existing approaches and dramatically improves on them based on the percentage of reads it can associate with a species in a sample. The software is available at https://github.com/PennChopMicrobiomeProgram/unassigner.IMPORTANCEWhile existing methods do not provide reliable species-level assignments for 16S rRNA marker gene data, the Unassigner software solves this problem by ruling out species membership, allowing researchers to reason at the species level.

Association between butyrate-producing gut bacteria and the risk of infectious disease hospitalisation: results from two observational, population-based microbiome studies

Microbiota alterations are common in patients hospitalised for severe infections, and preclinical models have shown that anaerobic butyrate-producing gut bacteria protect against systemic infections. However, the relationship between microbiota disruptions and increased susceptibility to severe infections in humans remains unclear. We investigated the relationship between gut microbiota and the risk of future infection-related hospitalisation in two large population-based cohorts. In this observational microbiome study, gut microbiota were characterised using 16S rRNA gene sequencing in independent population-based cohorts from the Netherlands (HELIUS study; derivation cohort) and Finland (FINRISK 2002 study; validation cohort). HELIUS was conducted in Amsterdam, Netherlands, and included adults (aged 18-70 years at inclusion) who were randomly sampled from the municipality register of Amsterdam. FINRISK 2002 was conducted in six regions in Finland and is a population survey that included a random sample of adults (aged 25-74 years). In both cohorts, participants completed questionnaires, underwent a physical examination, and provided a faecal sample at inclusion (Jan 3, 2013, to Nov 27, 2015, for HELIUS participants and Jan 21 to April 19, 2002, for FINRISK participants. For inclusion in our study, a faecal sample needed to be provided and successfully sequenced, and national registry data needed to be available. Primary predictor variables were microbiota composition, diversity, and relative abundance of butyrate-producing bacteria. Our primary outcome was hospitalisation or mortality due to any infectious disease during 5-7-year follow-up after faecal sample collection, based on national registry data. We examined associations between microbiota and infection risk using microbial ecology and Cox proportional hazards. We profiled gut microbiota from 10 699 participants (4248 [39·7%] from the derivation cohort and 6451[60·3%] from the validation cohort). 602 (5·6%) participants (152 [3·6%] from the derivation cohort; 450 [7·0%] from the validation cohort) were hospitalised or died due to infections during follow-up. Gut microbiota composition of these participants differed from those without hospitalisation for infections (derivation p=0·041; validation p=0·0002). Specifically, higher relative abundance of butyrate-producing bacteria was associated with a reduced risk of hospitalisation for infections (derivation cohort cause-specific hazard ratio 0·75 [95% CI 0·60-0·94] per 10% increase in butyrate producers, p=0·013; validation cohort 0·86 [0·77-0·96] per 10% increase, p=0·0077). These associations remained unchanged following adjustment for demographics, lifestyle, antibiotic exposure, and comorbidities. Gut microbiota composition, specifically colonisation with butyrate-producing bacteria, was associated with protection against hospitalisation for infectious diseases in the general population across two independent European cohorts. Further studies should investigate whether modulation of the microbiome can reduce the risk of severe infections. Amsterdam UMC, Porticus, National Institutes of Health, Netherlands Organisation for Health Research and Development (ZonMw), and Leducq Foundation.

ANTIMICROBIAL EFFECT OF TOOTHPASTES CONTAINING BIRCH EXTRACT AND NANO-HYDROXYAPATITES

The study investigates the antimicrobial efficacy of toothpaste formulations incorporating nano-hydroxyapatite (nHAP) and birch extract. Toothpastes were evaluated for their ability to inhibit bacterial growth, with observations revealing varied sensitivities among bacterial species to different formulations. Notably, toothpastes containing both nHAP and zinc exhibited heightened antimicrobial activity, while the addition of birch extract introduced variability in inhibition reactions across species. Further analysis delineated differences in effectiveness between nHAP-only and nHAP-birch extract formulations, suggesting the role of secondary metabolites in enhancing antibacterial properties. The study highlights toothpaste P11 as the most effective inhibitor of bacterial growth, offering a balanced combination of remineralization and antibacterial properties, except for S. mutans strain. Future research directions include time-course tests to assess long-term efficacy and oral microbiome studies to understand broader effects on oral microflora, informing the development of more targeted oral care products.

The microbiome in pregnancy and early life-Highlights from the 11th Maria Delivoria-Papadopoulos Perinatal Symposium.

This review was based on a symposium that examined novel aspects of the microbiome during pregnancy and early life and explored papers published by the lecturers. For example, it showed that bacterial extracellular vesicles derived from the microbiome harboured in various maternal niches, carried bacterial deoxyribonucleic acid, were isolated from the placenta and may have confounded placental microbiome studies. Maternal diet was responsible for the composition and diversity of breast milk microbiota, and may have shaped the offspring's microbiome and influenced their immune components. Probiotics and antibiotics administered perinatally may have had beneficial but also long-lasting adverse effects on offspring.

Gut microbiome dynamics and predictive value in hospitalized COVID-19 patients: a comparative analysis of shallow and deep shotgun sequencing.

The COVID-19 pandemic caused by SARS-CoV-2 has led to a wide range of clinical presentations, with respiratory symptoms being common. However, emerging evidence suggests that the gastrointestinal (GI) tract is also affected, with angiotensin-converting enzyme 2, a key receptor for SARS-CoV-2, abundantly expressed in the ileum and colon. The virus has been detected in GI tissues and fecal samples, even in cases with negative results of the reverse transcription polymerase chain reaction in the respiratory tract. GI symptoms have been associated with an increased risk of ICU admission and mortality. The gut microbiome, a complex ecosystem of around 40 trillion bacteria, plays a crucial role in immunological and metabolic pathways. Dysbiosis of the gut microbiota, characterized by a loss of beneficial microbes and decreased microbial diversity, has been observed in COVID-19 patients, potentially contributing to disease severity. We conducted a comprehensive gut microbiome study in 204 hospitalized COVID-19 patients using both shallow and deep shotgun sequencing methods. We aimed to track microbiota composition changes induced by hospitalization, link these alterations to clinical procedures (antibiotics administration) and outcomes (ICU referral, survival), and assess the predictive potential of the gut microbiome for COVID-19 prognosis. Shallow shotgun sequencing was evaluated as a cost-effective diagnostic alternative for clinical settings. Our study demonstrated the diverse effects of various combinations of clinical parameters, microbiome profiles, and patient metadata on the precision of outcome prognostication in patients. It indicates that microbiological data possesses greater reliability in forecasting patient outcomes when contrasted with clinical data or metadata. Furthermore, we established that shallow shotgun sequencing presents a viable and cost-effective diagnostic alternative to deep sequencing within clinical environments.

Caenorhabditis elegans as a Convenient Animal Model for Microbiome Studies.

Microbes constitute the most prevalent life form on Earth, yet their remarkable diversity remains mostly unrecognized. Microbial diversity in vertebrate models presents a significant challenge for investigating host-microbiome interactions. The model organism Caenorhabditis elegans has many advantages for delineating the effects of host genetics on microbial composition. In the wild, the C. elegans gut contains various microbial species, while in the laboratory it is usually a host for a single bacterial species. There is a potential host-microbe interaction between microbial metabolites, drugs, and C. elegans phenotypes. This mini-review aims to summarize the current understanding regarding the microbiome in C. elegans. Examples using C. elegans to study host-microbe-metabolite interactions are discussed.

Fast and space-efficient taxonomic classification of long reads with hierarchical interleaved XOR filters.

Metagenomic long-read sequencing is gaining popularity for various applications, including pathogen detection and microbiome studies. To analyze the large data created in those studies, software tools need to taxonomically classify the sequenced molecules and estimate the relative abundances of organisms in the sequenced sample. Because of the exponential growth of reference genome databases, the current taxonomic classification methods have large computational requirements. This issue motivated us to develop a new data structure for fast and memory-efficient querying of long reads. Here, we present Taxor as a new tool for long-read metagenomic classification using a hierarchical interleaved XOR filter data structure for indexing and querying large reference genome sets. Taxor implements several k-mer-based approaches, such as syncmers, for pseudoalignment to classify reads and an expectation-maximization algorithm for metagenomic profiling. Our results show that Taxor outperforms state-of-the-art tools regarding precision while having a similar recall for long-read taxonomic classification. Most notably, Taxor reduces the memory requirements and index size by >50% and is among the fastest tools regarding query times. This enables real-time metagenomics analysis with large reference databases on a small laptop in the field.

Implementing ITS1 metabarcoding for the analysis of soil microeukariotic diversity in the Mountain Cloud Forest

PurposeIn threatened diversity hotspots, such as mountain cloud forests, microbiome studies have focused essentially on bacteria. Unlike prokaryotic microbiomes, the study of the microeukaryotes has largely been restricted to the visual identification of specific groups. Herein, microeukaryotic edaphic diversity from a pristine mountain cloud forest (MCF) of Mexico was analyzed via the metabarcoding of the ITS1 region of ribosomal DNA.Materials and methodsAn exploratory triangular sampling was conducted in the mountain cloud forest located in El Relámpago Mount, Santiago Comaltepec, Oaxaca, Mexico. Each vertex was located adjacent to a dominant plant species in the ecosystem (Oreomunnea mexicana and Alsophila salvinii). After DNA extraction the ITS1 region (rDNA) was amplified. Microeukaryotic sequences were filtered by computational subtraction against the ITS2 Database. Next, alpha and beta diversity indexes were calculated, and the relationship between abiotic variables and diversity patterns were inferred by means of a Canonical Correspondence Analysis.ResultsOverall, 138 inferred sequence variants were identified, including 87 protists, 35 animals (microfauna), and 16 algae. Within the animals, the nematodes were the dominant group, chlorophytes dominated algae, and in Protista, no dominance patterns were observed given the high diversity and equitability of this group. Soil available carbon, carbon degrading enzymes and the pH play a key role in modeling the community structure. Remarkably, high beta diversity levels were obtained, evidencing a strong spatial heterogeneity at the small scale.ConclusionsThe ITS metabarcoding proved to be a useful tool to conduct multi-taxa diversity assessments for microeukaryotes, allowing the identification of alpha and beta diversity patterns and overcoming limitations of sampling and the direct observation of individuals. The results presented in this work evidenced high microeukaryotic diversity levels in the soil of MCF and encourage future studies aiming to explore the taxonomic diversity of individual taxa.

Medium-chain carboxylates production from plant waste: kinetic study and effect of an enriched microbiome

BackgroundThe need for addition of external electron donors such as ethanol or lactate impairs the economic viability of chain elongation (CE) processes for the production of medium-chain carboxylates (MCC). However, using feedstocks with inherent electron donors such as silages of waste biomass can improve the economics. Moreover, the use of an appropriate inoculum is critical to the overall efficiency of the CE process, as the production of a desired MCC can significantly be influenced by the presence or absence of specific microorganisms and their metabolic interactions. Beyond, it is necessary to generate data that can be used for reactor design, simulation and optimization of a given CE process. Such data can be obtained using appropriate mathematical models to predict the dynamics of the CE process.ResultsIn batch experiments using silages of sugar beet leaves, cassava leaves, and Elodea/wheat straw as substrates, caproate was the only MCC produced with maximum yields of 1.97, 3.48, and 0.88 g/kgVS, respectively. The MCC concentrations were accurately predicted with the modified Gompertz model. In a semi-continuous fermentation with ensiled sugar beet leaves as substrate and digestate from a biogas reactor as the sole inoculum, a prolonged lag phase of 7 days was observed for the production of MCC (C6–C8). The lag phase was significantly shortened by at least 4 days when an enriched inoculum was added to the system. With the enriched inoculum, an MCC yield of 93.67 g/kgVS and a productivity of 2.05 gMCC/L/d were achieved. Without the enriched inoculum, MCC yield and productivity were 43.30 g/kgVS and 0.95 gMCC/L/d, respectively. The higher MCC production was accompanied by higher relative abundances of Lachnospiraceae and Eubacteriaceae.ConclusionsEnsiled waste biomass is a suitable substrate for MCC production using CE. For an enhanced production of MCC from ensiled sugar beet leaves, the use of an enriched inoculum is recommended for a fast process start and high production performance.

Clinical studies of the human microbiome. Strategies for applying methods and translating results into clinical practice: A review

Clinical studies of the human microbiome. Strategies for applying methods and translating results into clinical practice: A review

A systematic comparison of natural product potential, with an emphasis on RiPPs, by mining of bacteria of three large ecosystems

The implementation of several global microbiome studies has yielded extensive insights into the biosynthetic potential of natural microbial communities. However, studies on the distribution of several classes of ribosomally synthesized and post-translationally modified peptides (RiPPs), non-ribosomal peptides (NRPs) and polyketides (PKs) in different large microbial ecosystems have been very limited. Here, we collected a large set of metagenome-assembled bacterial genomes from marine, freshwater and terrestrial ecosystems to investigate the biosynthetic potential of these bacteria. We demonstrate the utility of public dataset collections for revealing the different secondary metabolite biosynthetic potentials among these different living environments. We show that there is a higher occurrence of RiPPs in terrestrial systems, while in marine systems, we found relatively more terpene-, NRP-, and PK encoding gene clusters. Among the many new biosynthetic gene clusters (BGCs) identified, we analyzed various Nif-11-like and nitrile hydratase leader peptide (NHLP) containing gene clusters that would merit further study, including promising products, such as mersacidin-, LAP- and proteusin analogs. This research highlights the significance of public datasets in elucidating the biosynthetic potential of microbes in different living environments and underscores the wide bioengineering opportunities within the RiPP family.