Quantitative Insights Into Microbial Ecology Research Articles

Adolescent gut microbiome imbalance and its association with immune response in inflammatory bowel diseases and obesity

BackgroundRecently, there has been an increase in the number of studies focusing on the association between the gut microbiome and obesity or inflammatory diseases, especially in adults. However, there is a lack of studies investigating the association between gut microbiome and gastrointestinal (GI) diseases in adolescents.MethodWe obtained 16S rRNA-seq datasets for gut microbiome analysis from 202 adolescents, comprising ulcerative colitis (UC), Crohn’s disease (CD), obesity (Ob), and healthy controls (HC). We utilized Quantitative Insights Into Microbial Ecology (QIIME) and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) to acquire Operational Taxonomic Units (OTUs). Subsequently, we analyzed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) terms and pathway enrichment for the identified OTUs.ResultsIn this study, we investigated the difference between the gut microbiomes in adolescents with GI diseases and those in healthy adolescents using 202 samples of 16S rRNA sequencing data. The distribution of the six main gut microbiota (i.e., unclassified Dorea, unclassified Lachnospiraceae, unclassified Ruminococcus, Faecalibacterium prausnitzii, Prevotella copri, unclassified Sutterella) was different based on the status of obesity and inflammatory diseases. Dysbiosis was observed within Lachnospiraceae in adolescents with inflammatory diseases (i.e., UC and CD), and in adolescents with obesity within Prevotella and Sutterella. More specifically, our results showed that the relative abundance of Faecalibacterium prausnitzii and unclassified Lachnospiraceae was more than 10% and 8% higher, respectively, in the UC group compared to the CD, Ob, and HC groups. Additionally, the Ob group had over 20% and over 3% higher levels of Prevotella copri and unclassified Sutterella, respectively, compared to the UC, CD, and HC groups. Also, inspecting associations between the six specific microbiota and KO terms, we found that the six microbiota -relating KO terms were associated with NOD-like receptor signaling. These six taxa differences may affect the immune system and inflammatory response by affecting NOD-like receptor signaling in the host during critical adolescence.ConclusionIn this study, we discovered that dysbiosis of the microbial community had varying degrees of influence on the inflammatory and immune response pathways in adolescents with inflammatory diseases and obesity.

Impact of artisanal refining activities on bacterial diversity in a Niger Delta fallow land

Hydrocarbon pollution is a major ecological problem facing oil-producing countries, especially in the Niger Delta region of Nigeria. In this study, a site that had been previously polluted by artisanal refining activity was investigated using 16S rRNA Illumina high-throughput sequencing technology and bioinformatics tools. These were used to investigate the bacterial diversity in soil with varying degrees of contamination, determined with a gas chromatography-flame ionization detector (GC-FID). Soil samples were collected from a heavily polluted (HP), mildly polluted (MP), and unpolluted (control sample, CS) portion of the study site. DNA was extracted using the Zymo Research (ZR) Fungi/Bacteria DNA MiniPrep kit, followed by PCR amplification and agarose gel electrophoresis. The microbiome was characterized based on the V3 and V4 hypervariable regions of the 16S rRNA gene. QIIME (Quantitative Insights Into Microbial Ecology) 2 software was used to analyse the sequence data. The final data set covered 20,640 demultiplexed high-quality reads and a total of 160 filtered bacterial OTUs. Proteobacteria dominated samples HP and CS, while Actinobacteria dominated sample MP. Denitratisoma, Pseudorhodoplanes, and Spirilospora were the leading genera in samples HP, CS, and MP respectively. Diversity analysis indicated that CS [with 25.98 ppm of total petroleum hydrocarbon (TPH)] is more diverse than HP (with 490,630 ppm of TPH) and MP (with 5398 ppm of TPH). A functional prediction study revealed that six functional modules dominated the dataset, with metabolism covering up to 70%, and 11 metabolic pathways. This study demonstrates that a higher hydrocarbon concentration in soil adversely impacts microbial diversity, creating a narrow bacterial diversity dominated by hydrocarbon-degrading species, in addition to the obvious land and ecosystem degradation caused by artisanal refining activities. Overall, the artisanal refining business is significantly driving ecosystem services losses in the Niger Delta, which calls for urgent intervention, with focus on bioremediation.

Oropharyngeal microbial ecosystem perturbations influence the risk for acute respiratory infections in common variable immunodeficiency.

The respiratory tract microbiome is essential for human health and well-being and is determined by genetic, lifestyle, and environmental factors. Patients with Common Variable Immunodeficiency (CVID) suffer from respiratory and intestinal tract infections, leading to chronic diseases and increased mortality rates. While CVID patients' gut microbiota have been analyzed, data on the respiratory microbiome ecosystem are limited. This study aims to analyze the bacterial composition of the oropharynx of adults with CVID and its link with clinical and immunological features and risk for respiratory acute infections. Oropharyngeal samples from 72 CVID adults and 26 controls were collected in a 12-month prospective study. The samples were analyzed by metagenomic bacterial 16S ribosomal RNA sequencing and processed using the Quantitative Insights Into Microbial Ecology (QIME) pipeline. Differentially abundant species were identified and used to build a dysbiosis index. A machine learning model trained on microbial abundance data was used to test the power of microbiome alterations to distinguish between healthy individuals and CVID patients. Compared to controls, the oropharyngeal microbiome of CVID patients showed lower alpha- and beta-diversity, with a relatively increased abundance of the order Lactobacillales, including the family Streptococcaceae. Intra-CVID analysis identified age >45 years, COPD, lack of IgA, and low residual IgM as associated with a reduced alpha diversity. Expansion of Haemophilus and Streptococcus genera was observed in patients with undetectable IgA and COPD, independent from recent antibiotic use. Patients receiving azithromycin as antibiotic prophylaxis had a higher dysbiosis score. Expansion of Haemophilus and Anoxybacillus was associated with acute respiratory infections within six months. CVID patients showed a perturbed oropharynx microbiota enriched with potentially pathogenic bacteria and decreased protective species. Low residual levels of IgA/IgM, chronic lung damage, anti antibiotic prophylaxis contributed to respiratory dysbiosis.

Association of Estimated Daily Lactose Consumption, Lactase Persistence Genotype (rs4988235), and Gut Microbiota in Healthy Adults in the United States

BackgroundLactase persistence (LP) is a heritable trait in which lactose can be digested throughout adulthood. Lactase nonpersistent (LNP) individuals who consume lactose may experience microbial adaptations in response to undigested lactose. ObjectivesThe objective of the study was to estimate lactose from foods reported in the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) and determine the interaction between lactose consumption, LP genotype, and gut microbiome in an observational cross-sectional study of healthy adults in the United States (US). MethodsAverage daily lactose consumption was estimated for 279 healthy US adults, genotyped for the lactase gene −13910G>A polymorphism (rs4988235) by matching ASA24-reported foods to foods in the Nutrition Coordinating Center Food and Nutrient Database. Analysis of covariance was used to identify whether the A genotype (LP) influenced lactose and total dairy consumption, with total energy intake and weight as covariates. The 16S rRNA V4/V5 region, amplified from bacterial DNA extracted from each frozen stool sample, was sequenced using Illumina MiSeq (300 bp paired-end) and analyzed using Quantitative Insights Into Microbial Ecology (QIIME)2 (version 2019.10). Differential abundances of bacterial taxa were analyzed using DESeq2 likelihood ratio tests. ResultsAcross a diverse set of ethnicities, LP subjects consumed more lactose than LNP subjects. Lactobacillaceae abundance was highest in LNP subjects who consumed more than 12.46 g/d (upper tercile). Within Caucasians and Hispanics, family Lachnospiraceae was significantly enriched in the gut microbiota of LNP individuals consuming the upper tercile of lactose across both sexes. ConclusionsElevated lactose consumption in individuals with the LNP genotype is associated with increased abundance of family Lactobacillaceae and Lachnospriaceae, taxa that contain multiple genera capable of utilizing lactose.This trial was registered on clinicaltrials.gov as NCT02367287.

Effects of Lacticaseibacillus casei (Lactobacillus casei) and Saccharomyces cerevisiae mixture on growth performance, hematological parameters, immunological responses, and intestinal microbiome in weaned pigs.

This study was conducted to evaluate the effects of Lacticaseibacillus casei (Lactobacillus casei) and Saccharomyces cerevisiae mixture on growth performance, hematological parameters, immunological responses, and gut microbiome in weaned pigs. A total of 300 crossbred pigs [(Landrace × Yorkshire] × Duroc; 8.87 ± 0.34 kg of average initial body weight [BW]; 4 weeks of age) were divided into two dietary treatments (15 pigs/pen, 10 replicates/treatment) using a randomized complete block design (block = BW): control (CON) and the effective microorganism (MEM). The CON was not treated, while the MEM was treated with the mixture of L. casei (1 × 107 CFU/mL) and S. cerevisiae (1 × 107 CFU/mL) at 3 mL/pig/day for 4 weeks via the drinking water supply. Two feces and one blood sample from the randomly selected pigs in each pen were collected on D1 and D28 after weaning. Pigs were individually weighed, and pen feed intakes were recorded to evaluate pig growth performance. For the gut microbiome analysis, 16S rRNA gene hypervariable regions (V5 to V6) were sequenced using the Illumina MiSeq platform, and Quantitative Insight into Microbial Ecology (QIIME) and Microbiome Helper pipeline were used for 16S rRNA gene sequence analysis. The daily weight gain and feed efficiency of MEM were significantly higher than those of CON (p < 0.001). There were no significant differences in hematological parameters and immune responses between CON and MEM. However, MEM had significantly lower Treponema genus, whereas significantly higher Lactobacillus and Roseburia genera compared to CON. Overall, our data showed that L. casei and S. cerevisiae mixture could promote growth performance through the modulation of gut microbiota in pigs. This study will help to understand the correlation between the growth performance and the gut microbiome.

Microbiomic profiles of bile in patients with benign and malignant pancreaticobiliary disease.

The prognostic and pathophysiologic significance of the biliary microbiota in pancreaticobiliary malignancies is little understood. Our goal was to find malignancy-related microbiomic fingerprints in bile samples taken from patients with benign and malignant pancreaticobiliary diseases. Bile specimens were collected from consenting patients during routine endoscopic retrograde cholangiopancreatography. We used PowerViral RNA/DNA Isolation kit to extract DNA from bile specimens. The Illumina 16S Metagenomic Sequencing Library Preparation guide was used to amplify the bacterial 16S rRNA gene and create libraries. QIIME (Quantitative Insights Into Microbial Ecology), Bioconductor phyloseq, microbiomeSeq, and mixMC packages were used for post-sequencing analysis. Of 46 enrolled patients, 32 patients had pancreatic cancers, 6 had cholangiocarcinoma and 1 had gallbladder cancer. Rest of the patients had benign diseases including gallstones, and acute and chronic pancreatitis. We used multivariate approach in mixMC to classify Operational Taxonomic Units (OTUs). Doing this, we found a predominance of genera Dickeya (p = 0.00008), [Eubacterium] hallii group (p = 0.0004), Bacteroides (p = 0.0006), Faecalibacterium (p = 0.006), Escherichia-Shigella (p = 0.008), and Ruminococcus 1 (p = 0.008) in bile samples from pancreaticobiliary cancers as compared to benign diseases. Additionally, bile samples from patients with pancreatic cancer exhibited a predominance of genus Rothia (p = 0.008) as compared to those with cholangiocarcinoma, whereas bile samples from patients with cholangiocarcinoma exhibited a predominance of genera Akkermansia (p = 0.031) and Achromobacter (p = 0.031) as compared to those with pancreatic cancers. Both benign and malignant pancreaticobiliary diseases have distinct microbiomic fingerprints. The relative abundance of OTUs in bile samples varies between patients with benign and malignant pancreaticobiliary diseases, as well as between cholangiocarcinoma and pancreatic cancer. Our data suggest that either these OTUs play a role in carcinogenesis or that benign disease-specific microenvironmental changes differ from cancer-specific microenvironmental changes, resulting to a clear separation of OTU clusters. We need more research to confirm and expand on our findings.

Tear film microbiome in Sjogren's and non-Sjogren's aqueous deficiency dry eye.

To understand the bacterial microbiome changes associated with Sjogren's syndrome (SS) and non-Sjogren's syndrome (NSS) aqueous-deficient dry eyes compared to healthy eyes. Bacterial microbiome was generated from the deoxyribonucleic acid of tear film samples in healthy (n = 33), SS (n = 17), and NSS (n = 28) individuals. Sequencing of the V3-V4 region of the 16S rRNA gene was performed on the Illumina HiSeq2500 platform. Quantitative Insights Into Microbial Ecology (QIIME) pipeline was used to assign taxa to sequences. Statistical analysis was performed in R to assess the alpha diversity and beta diversity indices. Significant changes between the healthy, SS, and NSS cohorts were depicted by principal coordinate analysis (PCoA), differential abundance, and network analysis. Tear microbiome was generated in healthy, SS, and NSS samples. Phyla Actinobacteria, Firmicutes, and Bacteroidetes showed significant changes in SS and NSS compared to healthy. Genera Lactobacillus and Bacillus were predominantly present in all samples. PCoA and heat map analysis showed distinct clusters for SS and NSS from the healthy cohort. Genera Prevotella, Coriobacteriaceae UCG-003, Enterococcus, Streptomyces, Rhodobacter, Ezakiella, and Microbacterium significantly increased in abundance in SS and NSS compared to a healthy cohort. Bacteria-bacteria interaction in SS, NSS, and healthy cohorts was predicted by CoNet network analysis. This analysis predicted a major hub of interaction for the pro-inflammatory bacterium Prevotella in the SS and NSS cohorts. The results of the study indicate significant changes in the phyla and genera in SS and NSS compared to healthy. Both discriminative analysis and network analysis indicated a possible association of predominant pro-inflammatory bacteria with SS and NSS.

Discovery of fecal microbial signatures in patients with ankylosing spondylitis.

This study aimed to investigate the characteristics of the gut microbiota in Chinese patients with ankylosing spondylitis (AS) and healthy controls in Quanzhou aiming to explore the correlation between microbiome changes and AS activities. In this study, high-throughput sequencing of the gene of 16S ribosomal RNA (16S rRNA) in fecal samples from 40 AS patients and 40 healthy controls, for a total of 80 participants (70 males, 10 females; mean age 33.7±10.7 years; range, 15 to 58 years), was conducted between January 2018 and January 2019. Alpha and beta diversity were analyzed using the QIIME (Quantitative Insights Into Microbial Ecology) software, and differences were analyzed using Student's t-test, linear discriminant analysis coupled with effect size and Metastats. Finally, a correlation network was constructed using Pearson's analysis. The alpha index values of the AS group were not significantly different from those of the control group. At the genus level, eight genera, Ruminiclostridium_9, Fusicatenibacter, Adlercreutzia, CAG-56, Intestinimonas, Lachnospira, Bacteroides, and Pseudoflavonifractor, were significantly enriched in patients with AS, whereas the abundance of uncultured_bacterium_f_Saccharimonadaceae, Prevotella_7, uncultured_bacterium_f_ Enterobacteriaceae, Cronobacter, Prevotellaceae_NK3B31_group, and Weissella were significantly decreased in patients with AS. In addition, diseaserelated gut microbial communities were detected in patients with AS. We found differences in the gut microbiome between the patients with AS and controls and identified potential disease activity-related bacterial communities.

Cardiac vagal activity is associated with gut-microbiome patterns in women-An exploratory pilot study.

IntroductionA functional reciprocity between the gut microbiome and vagal nerve activity has been suggested, however, human studies addressing this phenomenon are limited.MethodsTwenty-four-hour cardiac vagal activity (CVA) was assessed from 73 female participants (aged 24.5 ± 4.3 years). Additionally, stool samples were subjected to 16SrRNA gene analysis (V1–V2). Quantitative Insights Into Microbial Ecology (QIIME) was used to analyse microbiome data. Additionally, inflammatory parameters (such as CRP and IL-6) were derived from serum samples.ResultsDaytime CVA correlated significantly with gut microbiota diversity (rsp = 0.254, p = 0.030), CRP (rsp = −0.348, p = 0.003), and IL-6 (rsp = −0.320, p = 0.006). When the group was divided at the median of 24 h CVA (Mdn = 1.322), the following features were more abundant in the high CVA group: Clostridia (Linear discriminant analysis effect size (LDA) = 4.195, p = 0.029), Clostridiales (LDA = 4.195, p = 0.029), Lachnospira (LDA = 3.489, p = 0.004), Ruminococcaceae (LDA = 4.073, p = 0.010), Faecalibacterium (LDA = 3.982, p = 0.042), Lactobacillales (LDA = 3.317, p = 0.029), Bacilli (LDA = 3.294, p = 0.0350), Streptococcaceae (LDA = 3.353, p = 0.006), Streptococcus (LDA = 3.332, p = 0.011). Based on Dirichlet multinomial mixtures two enterotypes could be detected, which differed significantly in CVA, age, BMI, CRP, IL-6, and diversity.ConclusionsAs an indicator of gut-brain communication, gut microbiome analysis could be extended by measurements of CVA to enhance our understanding of signalling via microbiota-gut-brain-axis and its alterations through psychobiotics.

Skin bacterial richness and diversity in intensive care unit patients with severe pneumonia

ObjectivesPatients with severe pneumonia admitted to the intensive care unit (ICU) have a high risk of mortality, and the microbiome is likely to affect the outcome of such patients. However, the composition of the skin microbiota of ICU patients with severe pneumonia remains unclear. In this study, on the basis of 16S ribosomal ribonucleic acid sequencing, we explored the difference in skin bacterial richness and diversity between the ICU patient group (PG) with severe pneumonia and the healthy control group (CG). MethodsThe diversity index and taxonomic distribution of skin bacteria were analyzed using the Quantitative Insights Into Microbial Ecology (QIIME) bioinformatics pipeline. Blood, endotracheal aspirate, and bronchoalveolar lavage fluid samples were collected from the same PG subjects for culture. ResultsCompared with the CG, the diversity of skin bacteria in the PG decreased significantly. Staphylococcus, Acinetobacter, Stenotrophomonas, Enterococcus, Halomonas, and Brevibacillus were differentially abundant in the PG, and most of these bacteria were also identified in the cultures of upper respiratory tract samples of the same PG. ConclusionWe provide evidence that healthcare-associated infection in ICU patients with severe pneumonia is strongly associated with skin microbiota, which necessitates the prevention and control of skin bacterial pathogens for these patients.

Computational analysis of microbial community using amplicon sequencing of 16S rRNA gene

The microbial community has various essential applications in multiple sections such as pharmaceuticals, enzyme production, food industry and waste management. Microbes produce metabolites (crucial products for the industrial process) and utilize substrate which plays a vital role in solid waste degradation. The computational metagenomic approach is considered as a solution for these problems. Microbial species are widely used for the bioremediation of solid waste materials. In this study, the solid waste contains wheat straw and human faeces occupied in a semi-continuous bio-converter condition for 105 days. The metagenomic data of six samples of solid waste were retrieved in FASTQ format from the ENA database. The sequence reads are analyzed using the QIIME (Quantitative Insights into Microbial Ecology) pipeline. This study includes demultiplexing, quality checking, OTU (Operational Taxonomic Unit) clustering, taxonomic assignment, phylogenetic analysis, biodiversity analysis and visualizations of solid waste samples. Results showed that solid waste metagenome is characterized by phyla Firmicutes, Bacteroidetes and Proteobacteria and genera Faecalibacterium, Roseburia, Pseudomonas and Bacillus are abundant in all samples. These microbial communities have potential application in the degradation of lignocellulosic waste. Hence, these microorganisms may be used to treat several solid waste materials and are considered an effective bioremediating agent for several pollutants.

Analysis of Conjunctival Sac Microbiome in Dry Eye Patients With and Without Sjögren's Syndrome

PurposeTo analyze the conjunctival sac microbial communities in patients with Sjögren's syndrome-associated dry eyes (SSDE) and non-Sjögren's syndrome-associated dry eyes (NSSDE), compared with normal controls (NC).MethodsConjunctival sac swab samples from 23 eyes of SSDE, 36 eyes of NSSDE, and 39 eyes of NC were collected. The V3–V4 region of the 16S ribosomal RNA (rRNA) gene high-throughput sequencing was performed on an Illumina MiSeq platform and analyzed using Quantitative Insights Into Microbial Ecology (QIIME). Alpha diversity was employed to analyze microbiome diversity through Chao1 and Shannon indexes. Beta diversity was demonstrated by the principal coordinates analysis (PCoA) and Partial Least Squares Discrimination Analysis (PLS-DA). The relative abundance was bioinformatically analyzed at the phylum and genus levels.ResultsThe alpha diversity was lower in patients with dry eye disease (Shannon index: NC vs. SSDE: P = 0.020, NC vs. NSSDE: P = 0.029). The beta diversity showed divergent microbiome composition in different groups (NC vs. SSDE: P = 0.001, NC vs. NSSDE: P = 0.001, NSSDE vs. SSDE: P = 0.005). The top 5 abundant phyla were Firmicutes, Proteobacteria, Actinobacteriota, Bacteroidota, and Cyanobacteria in all three groups. The top five abundant genera included Acinetobacter, Staphylococcus, Bacillus, Corynebacterium, and Clostridium_sensu_stricto_1. The relative microbiome abundance was different between groups. The Firmicutes/Bacteroidetes (F/B) ratio was 6.42, 7.31, and 9.71 in the NC, NSSDE, and SSDE groups, respectively (NC vs. SSDE: P = 0.038, NC vs. NSSDE: P = 0.991, SSDE vs. NSSDE: P = 0.048).ConclusionThe diversity of conjunctival sac microbiome in patients with NSSDE and SSDE was diminished compared with NC. The main microbiome at the phylum and genus level were similar between groups, but the relative abundance had variations. The Firmicutes/Bacteroidetes ratio was higher in the SSDE group.

Tree-Based Analysis of Dietary Diversity Captures Associations Between Fiber Intake and Gut Microbiota Composition in a Healthy US Adult Cohort

BackgroundDiet patterns are a significant and modifiable contributing factor to the composition of the human gut microbiota. ObjectivesWe set out to identify reproducible relationships between diet and gut microbial community composition in a diverse, healthy US adult cohort. MethodsWe collected 2 to 3 automated self-administered 24-hour dietary recalls over 10–14 days, together with a single stool sample, from 343 healthy adults in a cross-sectional phenotyping study. This study examined a multi-ethnic cohort balanced for age (18–65 years), sex, and BMI (18.5–45 kg/m2). Dietary data were edited to a tree format according to published methods. The tree structure was annotated with the average total grams of dry weight, fat, protein, carbohydrate, or fiber from each food item reported. The alpha and beta diversity measurements, calculated using the tree structure, were analyzed relative to the microbial community diversity, determined by a Quantitative Insights Into Microbial Ecology (QIIME) 2 analysis of the bacterial 16S ribosomal RNA V4 region, sequenced from stool samples. K-means clustering was used to form groups of individuals consuming similar diets, and gut microbial communities were compared among groups using differential expression analysis for sequence count data. ResultsThe alpha diversity of diet dry weight was significantly correlated with the gut microbial community alpha diversity (r = 0.171). The correlation improved when diet was characterized using grams of carbohydrates (r = 0.186) or fiber (r = 0.213). Bifidobacterium was enriched with diets containing higher levels of total carbohydrate from cooked grains. Lachnospira, was enriched with diet patterns containing high consumption of fiber from fruits excluding berries. ConclusionsThe tree structure, annotated with grams of carbohydrate, is a robust analysis method for comparing self-reported diet to the gut microbial community composition. This method identified consumption of fiber from fruit robustly associated with an abundance of pectinolytic bacterial genus, Lachnospira, in the guts of healthy adults. This trial was registered at https://clinicaltrials.gov/ clinicaltrials.gov as NCT02367287.

Salivary microbial dysbiosis may predict lung adenocarcinoma: A pilot study.

Adenocarcinoma is a more common type of Non-small cell lung cancer (NSCLC). Lung cancer showed a statistically significant increment in the Kamrup Urban district of Assam, Tripura, Sikkim, and Manipur of India. The goal of our pilot study is to identify non-invasive microbial biomarkers to detect lung adenocarcinoma (LAC). DNA extraction from saliva samples of five LAC patients and five healthy controls was performed by Qiagen DNeasy blood and tissue kit using Lysozyme (3mg/ml) treatment. 16S rRNA genes of distinct regions (V3-V4) were amplified from saliva DNA by PCR. Paired-end sequencing targeting the V3-V4 region of the 16S rRNA gene has been performed on the Illumina MiSeq platform. Raw sequences were analyzed using the QIIME(Quantitative Insights Into Microbial Ecology) software package. Our preliminary results showed that Rothia mucilaginosa, Veillonella dispar, Prevotella melaninogenica, Prevotella pallens, Prevotella copri, Haemophilus parainfluenzae, Neisseria bacilliformis and Aggregatibacter segnis were significantly elevated in saliva of LAC which may serve as potential non-invasive biomarkers for LAC detection. Functional prediction analysis showed that bacterial genes involved in glycosyltransferase, peptidases, amino sugar, and nucleotide sugar metabolism, starch and sucrose metabolism were significantly enriched in LAC. These salivary bacteria may contribute to the development of LAC by increasing expression of glycosyltransferase and peptidases. However to understand their role in pathobiology, studies are required to perform in large cohort.

Microbiome differences in periodontal, peri-implant, and healthy sites: a cross-sectional pilot study.

To explore microbial communities associated with health and disease status around teeth and dental implants. A total of 10 healthy, 24 periodontitis, and 24 peri-implant sites from 24 patients were sequenced by next-generation sequencing. Microbial DNA was extracted and 16S rRNA gene was amplified. Bioinformatic analyses were performed using quantitative insights into microbial ecology (QIIME), linear discriminant analysis effect size (LEfSE), and STAMP. Differences in microbial diversity across three types of sites were not statistically significant. Several genera and species were more prevalent in healthy compared with diseased sites, including Lautropia, Rothia and Capnocytophaga and Kingella. Among diseased sites, Peptostreptococcaceae, Dialister, Mongibacterium, Atopobium, and Filifactor were over-represented in peri-implantitis sites, while Bacteroidales was more abundant in periodontitis sites. Diseased periodontal and peri-implant sites and corresponding healthy sites have distinct microbiological profiles. These findings suggest that microbial analyses could identify biomarkers for periodontal health and disease and lead to the development of new strategies to improve periodontal health and treat peri-implant and periodontal diseases. The study contributes to improving our understanding of healthy, periodontally affected, and peri-implantitis sites which can improve our ability to diagnose, monitor, and manage these oral conditions.

Vertical Transmission of Diverse Cultivation-Recalcitrant Endophytic Bacteria Elucidated Using Watermelon Seed Embryos.

Seed transmission of endophytic microorganisms is a growing research area in plant biology and microbiology. We employed cultivation versus cultivation-independent approaches on excised embryos from watermelon seeds (6–12 months in storage) and on embryo-derived in vitro seedlings (EIVS) to assess the vertical transmission of endophytic bacteria. Surface-disinfected watermelon seeds bore abundant residual bacteria in the testa and perisperm tissues, predominantly Bacillus spp. propounding the essentiality of excluding all non-embryonic tissues for vertical transmission studies. Tissue homogenates from re-disinfected seed embryos displayed no cultivable bacteria during the 1-week monitoring. Bright-field live microscopy revealed abundant bacteria in tissue homogenates and in embryo sections as intracellular motile particles. Confocal imaging on embryo sections after SYTO-9 staining and eubacterial fluorescent in situ hybridization (FISH) endorsed enormous bacterial colonization. Quantitative Insights Into Microbial Ecology (QIIME)-based 16S rRNA V3–V4 taxonomic profiling excluding the preponderant chloroplast and mitochondrial sequences revealed a high bacterial diversity in watermelon seed embryos mainly Firmicutes barring spore formers followed by Proteobacteria, Bacteroidetes, and Actinobacteria, and other minor phyla. Embryo-base (comprising the radicle plus plumule parts) and embryo-cotyledon parts differed in bacterial profiles with the abundance of Firmicutes in the former and Proteobacteria dominance in the latter. EIVS displayed a higher bacterial diversity over seed embryos indicating the activation from the dormant stage of more organisms in seedlings or their better amenability to DNA techniques. It also indicated embryo-to-seedling bacterial transmission, varying taxonomic abundances for seed embryos and seedlings, and differing phylogenic profiles for root, hypocotyl, and cotyledon/shoot-tip tissues. Investigations on different watermelon cultivars confirmed the embryo transmission of diverse cultivation recalcitrant endophytic bacteria. Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes formed the core phyla across different cultivars with 80–90% similarity at genus to phylum levels. Conversely, freshly harvested seeds displayed a dominance of Proteobacteria. The findings revealed that dicot seeds such as in different watermelon cultivars come packaged with abundant and diverse vertical and seedling-transmissible cultivation recalcitrant endophytic bacteria with significant implications for plant biology.

Vegetarian diet duration\u2019s influence on women\u2019s gut environment

BackgroundNutrient composition of vegetarian diets is greatly different from that of omnivore diets, which may fundamentally influence the gut microbiota and fecal metabolites. The interactions between diet pattern and gut environment need further illustration. This study aims to compare the difference in the gut microbiota and fecal metabolites between vegetarian and omnivore female adults and explore associations between dietary choices/duration and gut environment changes.MethodsIn this study, investigations on the fecal metabolome together with the gut microbiome were performed to describe potential interactions with quantitative functional annotation. In order to eliminate the differences brought by factors of gender and living environment, 80 female adults aged 20 to 48 were recruited in the universities in Beijing, China. Quantitative Insights Into Microbial Ecology (QIIME) analysis and Ingenuity Pathway Analysis (IPA) were applied to screen differential data between groups from gut microbiota and fecal metabolites. Furthermore, weighted gene correlation network analysis (WGCNA) was employed as the bioinformatics analysis tool for describing the correlations between gut microbiota and fecal metabolites. Moreover, participants were further subdivided by the vegetarian diet duration for analysis.ResultsGPCR-mediated integration of enteroendocrine signaling was predicted to be one of the regulatory mechanisms of the vegetarian diet. Intriguingly, changes in the gut environment which occurred along with the vegetarian diet showed attenuated trend as the duration increased. A similar trend of returning to “baseline” after a 10-year vegetarian diet was detected in both gut microbiota and fecal metabolome.ConclusionsThe vegetarian diet is beneficial more than harmful to women. Gut microbiota play roles in the ability of the human body to adapt to external changes.

Mucosa-associated specific bacterial species disrupt the intestinal epithelial barrier in the autism phenome

Gut-Brain Axis provides a bidirectional communicational route, an imbalance of which can have pathophysiological consequences. Differential gut microbiome studies have become a frontier in autism research, affecting 85% of autistic children. The present study aims to understand how gut microbiota of autism subjects differ from their neurotypical counterparts. This study would help to identify the abundance of bacterial signature species in autism and their associated metabolites.16S rRNA metagenomic sequence datasets of 30 out of 206 autism subjects were selected from the American Gut Project Archive. First, the taxonomic assignment was inferred by similarity-based methods using the Quantitative Insights into Microbial Ecology (QIIME) toolkit. Next, species abundance was characterized, and a co-occurrence network was built to infer species interaction using measures of diversity. Thirdly, statistical parameters were incorporated to validate the findings. Finally, the identification of metabolites associated with these bacterial signature species connects with biological processes in the host through pathway analysis.Gut microbiome data revealed Akkermansia sp. and Faecalibacterium prausnitzii to be statistically lower in abundance in autistic children than their neurotypical peers with a five and two-fold decrease, respectively. While Prevotella sp. and Sutterella sp. showed a five and a two-fold increase in cases, respectively. The constructed pathway revealed succinate and butyrate as the significant metabolites for the bacterial signature species identified.The present study throws light on the role of mucosa-associated bacterial species: Veillonella sp., Prevotella sp., Akkermansia sp., Sutterella sp., Faecalibacterium prausnitzii, Lactobacillus sp., which can act as diagnostic criteria for detection of gut dysbiosis in autism.

Dysbiosis of gut microbiota and its correlation with dysregulation of cytokines in psoriasis patients

BackgroundPsoriasis is an inflammatory skin disease associated with multiple comorbidities and substantially diminishes patients’ quality of life. The gut microbiome has become a hot topic in psoriasis as it has been shown to affect both allergy and autoimmunity diseases in recent studies. Our objective was to identify differences in the fecal microbial composition of patients with psoriasis compared with healthy individuals to unravel the microbiota profiling in this autoimmune disease.ResultsWe collected fecal samples from 30 psoriasis patients and 30 healthy controls, sequenced them by 16S rRNA high-throughput sequencing, and identified the gut microbial composition using bioinformatic analyses including Quantitative Insights into Microbial Ecology (QIIME) and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). Our results showed that different relative abundance of certain bacterial taxa between psoriasis patients and healthy individuals, including Faecalibacterium and Megamonas, were increased in patients with psoriasis. It’s also implicated that many cytokines act as main effect molecules in the pathology of psoriasis. We selected the inflammation-related indicators that were abnormal in psoriasis patients and found the microbiome variations were associated with the level of them, especially interleukin-2 receptor showed a positive relationship with Phascolarctobacterium and a negative relationship with the Dialister. The relative abundance of Phascolarctobacterium and Dialister can be regard as predictors of psoriasis activity. The correlation analysis based on microbiota and Inflammation-related indicators showed that microbiota dysbiosis might induce an abnormal immune response in psoriasis.ConclusionsWe concluded that the gut microbiome composition in psoriasis patients has been altered markedly and provides evidence to understand the relationship between gut microbiota and psoriasis. More mechanistic experiments are needed to determine whether the differences observed in gut microbiota are the cause or consequences of psoriasis and whether the relationship between gut microbiota and cytokines was involved.

Microbiomic profiles of bile in patients with benign and malignant pancreaticobiliary disease.

417 Background: In pancreaticobiliary (PB) cancers, there is a paucity of data on predictive and pathophysiologic role of the biliary microbiome. We analyzed bile collected from patients with benign and malignant PB diseases to identify microbiomic signatures associated with malignancy. Methods: We collected bile samples from consenting patients during routine endoscopic retrograde cholangiopancreatography at the Cleveland Clinic, approved by the Institutional Review Board. DNA was extracted from bile specimens using PowerViral RNA/DNA Isolation kit. Bacterial 16S rRNA gene amplification and library construction were performed according to the 16S Metagenomic Sequencing Library Preparation guide from Illumina. Post-sequencing analysis was done using QIIME (Quantitative Insights Into Microbial Ecology), Bioconductor phyloseq, microbiomeSeq and mixMC packages. Results: Of 46 enrolled patients, 32 had PB cancers including pancreatic (N = 25), cholangiocarcinoma (N = 6), and gallbladder (N = 1). The rest (N = 14) had benign PB diseases including acute and chronic pancreatitis, and gallstones. Using multivariate approach in mixMC to classify Operational Taxonomic Units (OTUs), we found a predominance of genera Dicekeya (p = 0.0002), [ Eubacterium] hallii group (p = 0.0007) , Bacteroides (p = 0.00099) , Faecalibacterium (p = 0.007) , Facklamia (p = 0.013) , Peptococcus (p = 0.013) , Bergeyella (p = 0.0024) , Lachnospira (p = 0.026) , and Lactobacillus (p = 0.025) in bile samples from PB cancers as compared to benign PB diseases. Furthermore, bile samples from patients with pancreatic cancer showed an increased abundance of genera Enterobacter, Parabacteroides, Atopobium, Alloprevotella, Prevotella 7, Acinetobacter, Bergeyella, Clostridium sensu stricto, Lactobacillus, and Rothia; and a decreased abundance of genera Tannerella, Peptococcus, Colinsella, Capnocytophaga, Achromobacter, Ruminococcus 2, Bacteroides, Alistipes, Barnesiella,, Lachnoclostridium, Lautropia, Akkermansia, and Christensenellaceae R-7 group as compared to bile samples from patients with cholangiocarcinoma. Conclusions: Distinct microbiome signatures are associated with benign and malignant PB diseases. There is a difference in the relative abundance of OTUs in bile samples between patients with benign PB diseases vs PB cancers, and between pancreatic cancer vs cholangiocarcinoma. Our findings raise the possibility that either these OTUs have a role in carcinogenesis, or that changes in the microenvironment of benign PB diseases differ from PB cancers leading to distinct separation of the OTU clusters. Further studies to explore and validate our findings are needed.