Amplysis: an R package for microbial composition and diversity analysis using 16S rRNA amplicon data

BackgroundWith the rapid progress of high-throughput sequencing technology, characterization of schizophrenia (SZ) with underlying probing of the gut microbiome can explore pathogenic mechanisms, estimate disease risk, and allow customization of therapeutic and prophylactic modalities. In this study, we compared the differences in gut microbial diversity and composition between 50 SZ subjects and 50 healthy matched subjects in Zhejiang, China via targeted next-generation sequencing (16S rRNA amplicon).ResultsAccordingly, the alpha diversity indices (observed species index, Shannon index, and Simpson index) of the gut microbiome in the healthy control group were higher than those in the SZ group. Additionally, principal coordinate analysis and non-metric multidimensional scaling of beta diversity revealed that patients with SZ clustered more tightly than healthy controls. At the phylum level, we found that the abundance of Bacteroidetes and Proteobacteria in the SZ group was significantly increased. At the genus level, the relative abundances of Prevotella, Parabacteroides, and Sutterella were significantly higher, whereas the abundances of Faecalibacterium, Blautia, Lachnospira, Clostridium, Ruminococcus, and Coprococcus were lower than those in the healthy control group. Further analyses revealed that Succinivibrio, Megasphaera, and Nesterenkonia may serve as potential biomarkers for distinguishing patients with SZ from those in the control cohort.ConclusionsThis study profiled differences in gut microbiome diversity, taxonomic composition, and function between SZ and healthy cohorts, and the insights from this research could be used to develop targeted next-generation sequencing-based diagnoses for SZ.

Colorectal cancer (CRC) has a high mortality rate worldwide. Oral and intestinal microbiota members may have an effect on gastrointestinal tumors’ pathogenesis, particularly in CRC. Designed as a pilot study, this study’s aim was to investigate the relationship between CRC and oral microbiota and to identify potential biomarkers for CRC diagnosis. Saliva samples were collected from recently diagnosed CRC patients (n = 14) and healthy controls (n = 14) between March 2023 and December 2023. Microbiota (16S rRNA) analyses were conducted on these saliva samples using a next-generation sequencing method. Phylogenetic analyses, including alpha diversity, principal component analysis (PCA), principal coordinate analysis (PCoA), beta diversity, biomarker, and phenotype analyses, were conducted using the Qiime2 (Quantitative Insights Into Microbial Ecology) platform. Alpha diversity indices (Shannon: p = 0.78, Cho1: p = 0.28, Simpson: p = 0.81) showed no significant difference between CRC and control groups. Beta diversity analysis using Bray–Curtis PCoA indicated significant differences in the microbial community between the two groups (p = 0.003). Examination of OTU distributions revealed that the Mycoplasmatota phylum was undetectable in the oral microbiota of healthy controls but was significantly elevated in CRC patients (CRC: 0.13 ± 0.30, Control: 0.00 ± 0.00, p < 0.05). Additionally, Metamycoplasma salivarium, Bacteroides intestinalis, and Pseudoprevotella muciniphila were undetectable in healthy controls but significantly more prevalent in CRC patients (p < 0.05 for all three species). LEfSe analysis identified eight species with an LDA score > 2, Granulicatella adiacens, Streptococcus thermophilus, Streptococcus gwangjuense, Capnocytophaga sp. FDAARGOS_737, Capnocytophaga gingivalis, Granulicatella elegans, Bacteroides intestinalis, and Pseudoprevotella muciniphila, as potential biomarkers. The results of this study contribute critical evidence of the role of oral microbiota in the pathogenesis of colorectal cancer. Alterations in the microbiota suggest potential biomarkers in understanding the biological mechanisms underlying CRC and developing diagnostic and therapeutic strategies.

Endophthalmitis is a serious eye infection that can occur after intravitreal injections. Topical antibiotics are frequently used as a preventative measure, but their impact on the conjunctival microbiome is not fully understood. Conjunctival swabs were collected from 33 eyes of 33 patients undergoing intravitreal injections, both before and after a 3-day course of prophylactic topical levofloxacin 0.5%. Conjunctival microbiome analysis was conducted using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics processing identified unique amplicon sequence variants (ASVs) to evaluate microbial diversity and community composition. Alpha and beta diversity indices were analyzed. Topical levofloxacin treatment resulted in no significant change in alpha diversity indices, including Shannon index, Chao1, Shannon, PD whole tree, and observed ASVs, indicating stable microbial richness and evenness. In contrast, beta diversity analysis, assessed through Bray-Curtis dissimilarity, revealed significant differences in microbial composition between pre- and post-treatment samples. These changes included a decrease in the abundance of Staphylococcus and Bacillus species and an increase in the abundance of Streptococcus, Haemophilus, and Neisseria. Although prophylactic topical levofloxacin was found to alter the conjunctival microbiome and showed inconsistent effects on the abundance of pathogenic bacteria, its clinical effectiveness as a preventative measure against endophthalmitis remains inconclusive. Further studies are needed to clarify its role in infection prevention.

This study aimed to determine the impact of age on the fecal microbiota in the genetic nucleus of cattle, with a focus on microbial richness, composition, functional diversity, and correlations with blood parameters. Fecal and blood samples from 21 cattle were analyzed using 16S rRNA gene sequencing. Older cattle exhibited greater bacterial diversity and abundance, with significant changes in alpha diversity indices (p < 0.05). Beta diversity analysis revealed significant variations in microbial composition between age groups and the interaction of age and sex (p < 0.05). Correlations between alpha diversity, community composition, and hematological values highlighted the influence of microbiota on bovine health. Beneficial butyrate-producing bacteria, such as Ruminococcaceae, were more abundant in older cattle, suggesting a role in gut health. Functional diversity analysis indicated that younger cattle had significantly more abundant metabolic pathways in fermentation and anaerobic chemoheterotrophy. These findings suggest management strategies including tailored probiotic therapies, dietary adjustments, and targeted health monitoring to enhance livestock health and performance. Further research should include comprehensive metabolic analyses to better correlate microbiota changes with age-related variations, enhancing understanding of the complex interactions between microbiota, age, and reproductive status.

Putting Things in Order: The Ups and Downs of Detrended Correspondence Analysis

Study question Does the microbial composition along the female reproductive tract (vagina, cervix and uterus) differ between women with and without endometriosis? Summary answer Slight differences in the microbial composition along the female reproductive tract suggest that at genus level the microbes do not seem to associate with endometriosis. What is known already Endometriosis is a chronic inflammatory disease affecting 200 million women worldwide, characterized by the painful growth of endometrial tissue outside the uterus, significantly impacting quality of life in women affected. Patients often present comorbidity with other inflammatory diseases and experience high infertility rates. Although its etiology remains unknown, imbalances in the vaginal and endometrial microbiota have been linked to its development. Study design, size, duration This study included 34 women (mean age ± SD = 34.21 ± 3.55 years; BMI ± SD = 24.29 ± 3.84), 16 women with active endometriosis and 18 controls. Participants were recruited at the Reproduction Unit of the Virgen de las Nieves University Hospital between 2019 and 2021. Each participant provided vaginal and cervical swab samples, and endometrial sample with TaoBrush device. Participants/materials, setting, methods Each participant underwent an LH test to determine the menstrual cycle day, and samples were collected 7–9 days after the LH peak, during the implantation window. Vaginal, cervical, and uterine microbiomes were analyzed using 16S rRNA (V4) sequencing. Contamination control in uterine samples included negative controls and in silico decontamination (MicroDecon). Microbial diversity and composition analyses were adjusted for age, BMI and antimicrobial use (antibiotics, antivirals or antifungals) as confounders. Main results and the role of chance A total of 102 samples from different body sites were analyzed for microbial composition. Within-sample diversity (i.e., alpha-diversity) was estimated by Shannon diversity index and observed genera (Richness). Between-sample dissimilarity (beta-diversity) was visualized using Principal Coordinates Analysis (PCoA). 22 bacterial genera were differentially abundant along the female reproductive tract between women with endometriosis and control women. Specifically, 7 bacteria in the endometrium, 3 in the cervix and 5 in the vagina were more prevalent, while 6 in the endometrium and 1 in the vagina were less prevalent in the endometriosis group. However, these differences were not statistically significant after false discovery rate (FDR) correction. In the endometriosis group, the most prevalent genera were Streptococcus, Prevotella, Pseudomonas, Enterococcus, Acinetobacter and Escherichia, among others. Limitations, reasons for caution These first pilot study results require confirmation in larger sample sizes. Assessing microbial composition using 16S rRNA gene V4 region sequencing enabled microbial identification on genus level. Future studies should analyse microbial species and microbiome functionality to unravel the microbial involvement in endometriosis. Wider implications of the findings Endometriosis affects 10% of reproductive-age women. Identifying factors that could trigger or influence its development are essential for earlier detection of the disease and for developing possible treatment solutions. Trial registration number No

Shifts in the microbial community in rhizosphere and non-rhizosphere soils during the growth of Agrostis stolonifera

microeco: an R package for data mining in microbial community ecology.

The aim of this study was to investigate the effects of storage temperature and preservation time on the microbial diversity and community composition of rumen fluid. Rumen fluid samples were collected from six Hu sheep fed on a high-forage diet and stored at −80 °C and −20 °C for intervals of 0, 7, 14, 30, 60, 120, and 240 days. DNA was extracted at each time point for 16S rRNA gene sequencing to evaluate the rumen microbial diversity and community composition. The results showed that storage temperature affected only the relative abundance of Proteobacteria, with no substantial impact on alpha-diversity or other microbial groups (p &gt; 0.05), and no significant interaction effects were observed between storage temperature and preservation time (p &gt; 0.05). Alpha-diversity indices such as Chao1, observed species, and PD whole tree showed dynamic changes after 7 days of storage, while the relative abundances of Verrucomicrobiota and Christensenellaceae R-7 group, as well as the energy metabolism metabolic pathway, exhibited significant alterations after 14 days of storage (p &lt; 0.05). Notably, Patescibacteria, Rikenellaceae RC9 gut group, and Veillonellaceae UCG-001 abundances demonstrated significant changes after 240 days of storage (p &lt; 0.05). Both principal coordinates analysis (PCoA) and non-metric multidimensional scaling (NMDS) showed distinct overlaps. This study suggests that storing rumen fluid at −80 °C and −20 °C does not influence rumen microbial diversity and community composition, whereas the storage time significantly impacts these factors, with most differences emerging after 14 days of preservation. Consequently, it is advised that the analysis of microbial diversity and community composition in rumen fluid samples be conducted within 14 days post-collection.

PurposeChronic liver disease (CLD) and complications of cirrhosis are responsible for the deaths of approximately two million people per year worldwide. Abnormal intestinal permeability in the intestinal-liver axis and development of intestinal dysbiosis increase disease progression contributing to chronic systemic inflammation in CLD patients. The intestinal microbiota acts as a bioreactor for autonomous metabolic and immunological functions in regulating the host’s response to external stimuli in the intestinal microbiota. The study aimed to analyze the gut microbiota profile from colonic mucosal biopsy materials in CLD patients using a metagenomic application.Materials and methodsCLD and control groups were formed based on predefined inclusion and exclusion criteria from the study. In the metagenomic study, colonic mucosal biopsy material was studied from a total of 40 individuals, 20 with CLD and 20 healthy controls. We analyzed gut microbiota by 16 S rRNA metagenomic next-generation sequencing (NGS) method from colonic mucosal biopsy samples in CLD and healthy individuals. Metagenomic results were analyzed by Principal Component Analysis (PCA).ResultsSignificant differences were observed between the CLD and control groups across multiple taxonomic levels. At the phylum level, Proteobacteria were significantly enriched in CLD patients, while Firmicutes predominated in controls. Class-level analysis showed increased Gammaproteobacteria in CLD, the former associated with inflammatory pathways. At the order level, Enterobacterales were significantly higher in CLD (OR: 1.89, p = 0.04), whereas Clostridiales were more abundant in controls. Family-level comparisons revealed elevated Enterobacteriaceae in CLD, while Ruminococcaceae and Veillonellaceae were relatively preserved in controls. At the genus level, Prevotella and Streptococcus were increased in controls. Alpha diversity indices (Shannon, Chao1) were significantly lower in the CLD group (p < 0.001), indicating reduced microbial richness. Beta diversity analysis (PCoA, Bray-Curtis) showed distinct clustering between groups, supporting compositional divergence. Integration of metagenomic findings with biochemical markers (e.g., GGT: OR 0.79, p = 0.03) further underscored group-specific microbial signatures.ConclusionWe observed a significant compositional shift in the gut microbiota of patients with CLD. Notably, pro-inflammatory taxa were increased and a decrease in beneficial bacterial groups involved in maintaining microbial homeostasis. Diversity analyses indicated a reduction in microbial richness in the CLD group. These findings may aid in identifying CLD-specific microbial signatures. Furthermore, integrating metagenomic data with biochemical parameters may contribute to improved diagnostic strategies.

Biofiltration processes help to remove trace organic chemicals (TOrCs) both in wastewater and drinking water treatment systems. However, the detailed TOrCs biotransformation mechanisms as well as the underlying drivers behind the variability of site specific transformation processes remain elusive. In this study, we used laboratory batch incubations to investigate the biotransformation of 51 TOrCs in eight bioactive filter materials of different origins treating a range of waters, from wastewater effluents to drinking water. Microscopy, 16S rRNA amplicon and whole metagenome sequencing for assessing associations between the biotransformation rate constants, microbial composition and genetic potential complemented chemical analysis. We observed strong differences in the mean global removal of TOrCs between the individual sand filters (−1.4–58%), which were mirrored in overall biomass, microbial community composition, and enzyme encoding genes. From the six investigated biomass markers, ATP turned out to be a major predictor of the mean global biotransformation rate, while compound specific biotransformations were correlated with the microbial community composition. High biomass ecosystems were indicated in our systems by a dominance of Nitrospirae, but individual TOrC biotransformation showed a correlation with rare taxa (&amp;lt;2%) such as Hydrogenophaga, or individual functions such as the enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase encoding genes. In general, this study provides new insights into so far rarely addressed variability of TOrCs biotransformation. We propose potential novel biological indicators for the removal performance of TOrCs in biofiltration systems, highlighting the role of living biomass in predicting and normalizing the global transformation, and the role of the microbial community for the individual transformation of TOrCs in engineered and natural systems.

As part of Genetic Analysis Workshop 17 (GAW17), our group considered the application of novel and standard approaches to the analysis of genotype-phenotype association in next-generation sequencing data. Our group identified a major issue in the analysis of the GAW17 next-generation sequencing data: type I error and false-positive report probability rates higher than those expected based on empirical type I error levels (as high as 90%). Two main causes emerged: population stratification and long-range correlation (gametic phase disequilibrium) between rare variants. Population stratification was expected because of the diverse sample. Correlation between rare variants was attributable to both random causes (e.g., nearly 10,000 of 25,000 markers were private variants, and the sample size was small [n = 697]) and nonrandom causes (more correlation was observed than was expected by random chance). Principal components analysis was used to control for population structure and helped to minimize type I errors, but this was at the expense of identifying fewer causal variants. A novel multiple regression approach showed promise to handle correlation between markers. Further work is needed, first, to identify best practices for the control of type I errors in the analysis of sequencing data and then to explore and compare the many promising new aggregating approaches for identifying markers associated with disease phenotypes.

BackgroundMedical film dressings have been used to obtain skin microbiota for skin microbiome studies, although their adhesive force may be so strong that the skin could be injured when applied to those who have fragile skin, such as older people. Several products with less adhesive force are available, although their applicability for skin microbiome studies remains unknown. This study aimed to test whether the dressings with less adhesive force could be used for amplicon-based skin microbiome studies. A set of three different film dressings, with acrylic, urethane, or silicone adhesive, was applied to the back skin of nine healthy young participants. The copy number of the 16S ribosomal RNA (rRNA) gene, microbial compositions, and alpha and beta diversity indices were analyzed by amplicon analysis of the 16S rRNA gene using next-generation sequencing and were compared among the three film dressings.ResultsThe dressing with acrylic adhesive yielded the highest copy number of 16S rRNA genes, followed by that with urethane adhesive. The silicone-adhesive dressing yielded a significantly lower copy number of the 16S rRNA gene. The microbial composition of skin microbiota was similar among the three film dressings, although significant differences in the relative abundance of Pseudomonas species and alpha diversity indices were found in the silicone-adhesive dressing. The Bray–Curtis dissimilarity was significantly higher between the acrylic- and silicone-adhesive dressings than between the acrylic- and urethane-adhesive dressings. No adverse effects related to tape stripping were observed for any of the film dressings.ConclusionWe recommend dressings with acrylic or urethane adhesive for amplicon-based skin microbiome studies. An acrylic adhesive has an advantage in the yield of skin microbiota, and a urethane adhesive should be chosen when applied to fragile skin. The adhesive force of the dressing with silicone adhesive was too weak to be used for collecting skin microbiota.

The abundance and taxonomic composition of ammonia‐oxidizing archaea (AOA) were assessed in paddy soils that had received more than 50 years of fertilization with and without inorganic N. The inorganic N fertilized treatments were: NPK and NPK + CO (nitrogen (N), phosphorus (P), potassium (K) and compost (CO)). The treatments without inorganic N were: CO, PK and control (unfertilized soils). Quantitative PCR (qPCR) analysis of the archaeal amoA gene showed no significant changes in AOA abundance following the long‐term application of inorganic N fertilizers. However, subsequent analysis of amoA gene sequencing data showed that inorganic N application significantly changed the AOA community composition and alpha diversity indices. Edge principal components analysis (PCA) showed varying contributions of distinct AOA lineages in separating samples according to the fertilization treatment. Addition of inorganic N favoured an increase in the abundance of AOA lineages belonging to Nitrososphaera, and the treatments without inorganic N additions formed a separate cluster dominated by Nitrosotalea lineage. The distinct response of the two AOA lineages points towards different community organization of soil AOA and strongly supports the concept of habitat partitioning in paddy soil ecosystems.Highlights Lineages of AOA responded differently to different N management practices. Long‐term N fertilization selectively enriched AOA lineages, with C:N ratio a factor associated with such changes Inorganic N favoured Nitrososphaera lineage abundance Regardless of fertilizer status, Nitrosotalea lineage was dominant in the absence of inorganic N fertilization.

Changes in extracellular enzyme activity and microbial community structure with soil depth at the Luquillo Critical Zone Observatory