Microbial Features Research Articles

Uncovering specific taxonomic and functional alteration of gut microbiota in chronic kidney disease through 16S rRNA data.

Chronic kidney disease (CKD) is worldwide healthcare burden with growing incidence and death rate. Emerging evidence demonstrated the compositional and functional differences of gut microbiota in patients with CKD. As such, gut microbial features can be developed as diagnostic biomarkers and potential therapeutic target for CKD. To eliminate the outcome bias arising from factors such as geographical distribution, sequencing platform, and data analysis techniques, we conducted a comprehensive analysis of the microbial differences between patients with CKD and healthy individuals based on multiple samples worldwide. A total of 980 samples from six references across three nations were incorporated from the PubMed, Web of Science, and GMrepo databases. The obtained 16S rRNA microbiome data were subjected to DADA2 processing, QIIME2 and PICRUSt2 analyses. The gut microbiota of patients with CKD differs significantly from that of healthy controls (HC), with a substantial decrease in the microbial diversity among the CKD group. Moreover, a significantly reduced abundance of bacteria Faecalibacterium prausnitzii (F. prausnitzii) was detected in the CKD group through linear discriminant analysis effect size (LEfSe) analysis, which may be associated with the alleviating effects against CKD. Notably, we identified CKD-depleted F. prausnitzii demonstrated a significant negative correlation with three pathways based on predictive functional analysis, suggesting its potential role in regulating systemic acidbase disturbance and pro-oxidant metabolism. Our findings demonstrated notable alterations of gut microbiota in CKD patients. Specific gut-beneficial microbiota, especially F. prausnitzii, may be developed as a preventive and therapeutic tool for CKD clinical management.

Abundance of Prevotella copri in gut microbiota is inversely related to a healthy diet in patients with type 2 diabetes.

While the gut microbiota is known to be influenced by habitual food intake, this relationship is seldom explored in type 2 diabetes patients. This study aims to investigate the relationship between dietary patterns and gut microbial species abundance in 113 type 2 diabetes patients (mean age, 58 years; body mass index, 29.1; glycohemoglobin [HbA1c], 8.1%). We analyzed the gut microbiota using 16S amplicon sequencing, and all patients were categorized into either the Bacteroides enterotype (57.5%, n = 65) or the Prevotella enterotype (42.5%, n = 48) using the partitioning around medoids clustering algorithm, based on the most representative genera. Patients with the Bacteroides enterotype showed better glycemic control with a 2.71 odds of HbA1c ≤ 7.0% compared to the Prevotella enterotype (95% confidence interval, 1.02-7.87; P, 0.034). Dietary habits and the nutrient composition of all patients were assessed using a validated food frequency questionnaire. It was observed that the amounts of dietary fiber consumed were suboptimal, with an average intake of 16 g per day. Additionally, we extracted four dietary patterns through factor analysis: eating-out, high-sugar foods, fish-vegetable, and fermented foods patterns. Patients with the Bacteroides enterotype had higher scores for the fish-vegetable pattern compared to the Prevotella enterotype (0.17 ± 0.13 versus -0.23 ± 0.09; P, 0.010). We further investigated the relationship between the microbiota and the four dietary patterns and found that only the fish-vegetable dietary pattern scores were correlated with principal coordinate values. A lower pattern score was associated with the accumulated abundance of the 31 significant microbial features. Among these features, Prevotella copri was identified as the most significant by using a random forest model, with an area under the receiver operating characteristic of 0.93 (95% confidence interval, 0.88-0.98). To validate these results, we conducted a custom quantitative polymerase chain reaction assay. This assay confirmed the presence of P. copri (sensitivity, 0.96; specificity, 0.97) in our cohort, with a prevalence of 47.8%, and a mean relative abundance of 21.0% in subjects harboring P. copri. In summary, type 2 diabetes patients with the Prevotella enterotype demonstrated poorer glycemic control and deviations from a healthy dietary pattern. The abundance of P. copri, as a major contributing microbial feature, was associated with the severity in the deficiency in dietary fish and vegetables. Emphasis should be placed on promoting a healthy dietary pattern and understanding the microbial correlations.

The menopause-related gut microbiome: associations with metabolomics, inflammatory protein markers, and cardiometabolic health in women with HIV.

This study aimed to identify menopause-related gut microbial features, as well as their related metabolites and inflammatory protein markers, and link with cardiometabolic risk factors in women with and without HIV. In the Women's Interagency HIV Study, we performed shotgun metagenomic sequencing on 696 stool samples from 446 participants (67% women with HIV), and quantified plasma metabolomics and serum proteomics in a subset (~86%). We examined the associations of menopause (postmenopausal vs premenopausal) with gut microbial features in a cross-sectional repeated-measures design and further evaluated those features in relation to metabolites, proteins, and cardiometabolic risk factors. Different overall gut microbial composition was observed by menopausal status in women with HIV only. We identified a range of gut microbial features that differed between postmenopausal and premenopausal women with HIV (but none in women without HIV), including abundance of 32 species and functional potentials involving 24 enzymatic reactions and lower β-glucuronidase bacterial gene ortholog. Specifically, highly abundant species Faecalibacterium prausnitzii , Bacteroides species CAG:98 , and Bifidobacterium adolescentis were depleted in postmenopausal versus premenopausal women with HIV. Menopause-depleted species (mainly Clostridia ) in women with HIV were positively associated with several glycerophospholipids, while negatively associated with imidazolepropionic acid and fibroblast growth factor 21. Mediation analysis suggested that menopause may decrease plasma phosphatidylcholine plasmalogen C36:1 and C36:2 levels via reducing abundance of species F. prausnitzii and Acetanaerobacterium elongatum in women with HIV. Furthermore, waist-to-hip ratio was associated with menopause-related microbes, metabolites, and fibroblast growth factor 21 in women with HIV. Menopause was associated with a differential gut microbiome in women with HIV, related to metabolite and protein profiles that potentially contribute to elevated cardiometabolic risk.

Biogenicity of amorphous organic matter and bacteriomorph acritarchs preserved in wrinkle structures from the Ediacaran Cíjara Formation, Spain

AbstractEstablishing the biogenicity of sedimentary surface textures with unresolved microbial origin is critical to any environmental and geobiological interpretation of clastic settings. Here, some Ediacaran wrinkle structures and associated carbonaceous greywacke samples containing mat fragments rich in ‘bacteriomorph acritarchs’ are investigated. Their biogenicity was evaluated with transmitted light and scanning electron microscopy, epifluorescence and Raman spectroscopy, and confirmed by the presence of distinct cyanobacterial biomarkers. The comparison of results yielded by these techniques validates the use of Raman spectroscopy on Neoproterozoic kerogen (organic‐walled microfossils and amorphous organic material) under low metamorphic conditions. Raman spectrographs also allowed recognition of associated rare‐earth element‐rich phosphate (monazite) and subsidiary metal sulphide concentrations, and interpreted as a result of biosorption and/or mat trapping under normal oxic conditions. These microbial mat features represent cyanobacterial bloom‐forming Bavlinella acritarchs, which characterise eutrophic episodes in a semi‐enclosed retroarc basin sandwiched between an active Cadomian arc and West Gondwana.

Unveiling microbial biomarkers of ruminant methane emission through machine learning.

Enteric methane from cow burps, which results from microbial fermentation of high-fiber feed in the rumen, is a significant contributor to greenhouse gas emissions. A promising strategy to address this problem is microbiome-based precision feed, which involves identifying key microorganisms for methane production. While machine learning algorithms have shown success in associating human gut microbiome with various human diseases, there have been limited efforts to employ these algorithms to establish microbial biomarkers for methane emissions in ruminants. In this study, we aim to identify potential methane biomarkers for methane emission from ruminants by employing regression algorithms commonly used in human microbiome studies, coupled with different feature selection methods. To achieve this, we analyzed the microbiome compositions and identified possible confounding metadata variables in two large public datasets of Holstein cows. Using both the microbiome features and identified metadata variables, we trained different regressors to predict methane emission. With the optimized models, permutation tests were used to determine feature importance to find informative microbial features. Among the regression algorithms tested, random forest regression outperformed others and allowed the identification of several crucial microbial taxa for methane emission as members of the native rumen microbiome, including the genera Piromyces, Succinivibrionaceae UCG-002, and Acetobacter. Additionally, our results revealed that certain herd locations and feed composition markers, such as the lipid intake and neutral-detergent fiber intake, are also predictive features for methane emissions. We demonstrated that machine learning, particularly regression algorithms, can effectively predict cow methane emissions and identify relevant rumen microorganisms. Our findings offer valuable insights for the development of microbiome-based precision feed strategies aiming at reducing methane emissions.

Disentangling the age-related manner in the associations between gut microbiome and women’s health: a multi-cohort microbiome study

ABSTRACT Women’s health encompasses life-course healthcare, and mounting evidence emphasizes the pivotal contribution of gut microbiota. Therefore, understanding the temporal dynamics of gut microbiota and how age influences disease-gut microbiota associations is essential for improving women’s health. By analyzing metagenomic data from 3625 healthy women, we revealed significant effects of age on gut microbiota and age-dependent patterns in microbial features, such as relative abundance, Shannon index, and microbial network properties. Additionally, declining trends in the predictive accuracy of gut microbiota for age groups were shown using iterative sub-sampling based random forest (ISSRF) model. Age-specific species markers were also identified, many of which were shared across age groups. To investigate the influence of age on disease-gut microbiota associations, metagenomic data from 681 women with various disease conditions and 491 matched healthy controls were collected. A substantial proportion of species markers for inflammatory bowel disease (IBD), type 2 diabetes (T2D), atherosclerotic cardiovascular disease (ACVD), and impaired glucose tolerance (IGT) differed in relative abundance across age groups, and were also age-specific species markers. Besides, the microbiota-based probabilities of IBD and ACVD were positively correlated with age. Furthermore, the age specificity of disease-gut microbiota associations was explored using the ISSRF model. Associations between IBD and gut microbiota were age-specific, with reduced stability of disease species markers in childhood and adolescence, possibly due to decrease in the effect size between patients and controls. Our findings provided valuable insights into promoting healthy aging and developing personalized healthcare strategies for women.

Sutterella and its metabolic pathways positively correlate with vaccine-elicited antibody responses in infant rhesus macaques.

It is becoming clearer that the microbiota helps drive responses to vaccines; however, little is known about the underlying mechanism. In this study, we aimed to identify microbial features that are associated with vaccine immunogenicity in infant rhesus macaques. We analyzed 16S rRNA gene sequencing data of 215 fecal samples collected at multiple timepoints from 64 nursery-reared infant macaques that received various HIV vaccine regimens. PERMANOVA tests were performed to determine factors affecting composition of the gut microbiota throughout the first eight months of life in these monkeys. We used DESeq2 to identify differentially abundant bacterial taxa, PICRUSt2 to impute metagenomic information, and mass spectrophotometry to determine levels of fecal short-chain fatty acids and bile acids. Composition of the early-life gut microbial communities in nursery-reared rhesus macaques from the same animal care facility was driven by age, birth year, and vaccination status. We identified a Sutterella and a Rodentibacter species that positively correlated with vaccine-elicited antibody responses, with the Sutterella species exhibiting more robust findings. Analysis of Sutterella-related metagenomic data revealed five metabolic pathways that significantly correlated with improved antibody responses following HIV vaccination. Given these pathways have been associated with short-chain fatty acids and bile acids, we quantified the fecal concentration of these metabolites and found several that correlated with higher levels of HIV immunogen-elicited plasma IgG. Our findings highlight an intricate bidirectional relationship between the microbiota and vaccines, where multiple aspects of the vaccination regimen modulate the microbiota and specific microbial features facilitate vaccine responses. An improved understanding of this microbiota-vaccine interplay will help develop more effective vaccines, particularly those that are tailored for early life.

Alzheimer’s disease‐driven microbiome dysbiosis is a strong predictor of cognitive performance in humans

AbstractBackgroundThe association between Alzheimer’s Disease (AD) and dysbiosis of the gastrointestinal (GI) microbiome has been demonstrated in several studies. Here, we aimed to expand on our previous findings that in nursing home residents the microbiome and clinical variables are predictive of AD compared to no dementia (ND) by expanding our study population to include those residing in the general community. We sought to identity microbiota characteristics that stratify AD from ND individuals across environments. Further, in our community residing population, we assessed the longitudinal microbiome’s ability to predict cognitive performance (ADAS‐Cog‐13).MethodOlder individuals residing in Massachusetts nursing homes (n = 79) or in the general community (n = 71) were enrolled in our study. At each visit, fecal samples and clinical variables were collected. For those residing in the community, ADAS‐Cog‐13 testing was done. Metagenomic profiling was performed on longitudinal fecal samples. Random forest classification models were used to identify associations between residency, AD diagnosis and microbial features and metabolic pathways. Mixed‐effect random forest regression models were created to identify metagenome features informative of cognitive performance.ResultAmong AD and ND individuals residing in both the NH and community, microbial abundance and basic clinical variables were informative of AD status (F1‐score = 0.827±0.03), with Clostrida, Blautia and Neglecta species associating with AD diagnosis. In specifically the community residing individuals, increase in Bacteroidetes (F1‐score = 0.906 ± 0.03) and pathways (F1‐score = 0.885±0.03) involved in amino acid catabolism and nucleotide synthesis was informative of AD diagnosis. Additionally, mixed‐effect random forest machine learning models determined that variability in the abundance of these bacteria and pathways accurately predicts the cognitive performance (ADAS‐Cog‐13) in community residing individuals.ConclusionTaken together our study describes that the AD microbiome from both nursing home and community‐dwelling older adults is depleted in health‐associated Clostridia and that the abundance of these bacteria and their metabolites not only optimally discriminates older human according to disease status, but it also accurately reflects their cognitive ability.

OBMeta: a comprehensive web server to analyze and validate gut microbial features and biomarkers for obesity-associated metabolic diseases.

Gut dysbiosis is closely associated with obesity and related metabolic diseases including type 2 diabetes (T2D) and nonalcoholic fatty liver disease (NAFLD). The gut microbial features and biomarkers have been increasingly investigated in many studies, which require further validation due to the limited sample size and various confounding factors that may affect microbial compositions in a single study. So far, it lacks a comprehensive bioinformatics pipeline providing automated statistical analysis and integrating multiple independent studies for cross-validation simultaneously. OBMeta aims to streamline the standard metagenomics data analysis from diversity analysis, comparative analysis, and functional analysis to co-abundance network analysis. In addition, a curated database has been established with a total of 90 public research projects, covering three different phenotypes (Obesity, T2D, and NAFLD) and more than five different intervention strategies (exercise, diet, probiotics, medication, and surgery). With OBMeta, users can not only analyze their research projects but also search and match public datasets for cross-validation. Moreover, OBMeta provides cross-phenotype and cross-intervention-based advanced validation that maximally supports preliminary findings from an individual study. To summarize, OBMeta is a comprehensive web server to analyze and validate gut microbial features and biomarkers for obesity-associated metabolic diseases. OBMeta is freely available at: http://obmeta.met-bioinformatics.cn/.

Dynamics of the sedimentary bacterial communities in a plain river network: similar coalescence patterns with bacterioplankton communities driven by distinct assembly processes.

Microorganisms play important roles in driving the biogeochemical cycles within river ecosystems. It has been suggested that hydrologic conditions could influence microbial communities in rivers, but their specific effects on the behaviours of microbial coalescence have not been thoroughly investigated. In this study, the dynamics of sedimentary bacterial communities within a plain river network were analyzed by amplicon sequencing followed by several ecological models to uncover the underlying assembly processes. Additionally, a comparative analysis between bacterioplankton communities and sedimentary bacterial communities was performed to unveil their coalescence patterns. The results suggested that similar coalescence patterns between sedimentary bacterial and bacterioplankton communities were driven by distinct assembly processes under dynamic hydrological conditions. These findings enhanced our understanding of microbial diversity features within river ecosystems.

Association between microbiome and the development of adverse posttraumatic neuropsychiatric sequelae after traumatic stress exposure

Patients exposed to trauma often experience high rates of adverse post-traumatic neuropsychiatric sequelae (APNS). The biological mechanisms promoting APNS are currently unknown, but the microbiota-gut-brain axis offers an avenue to understanding mechanisms as well as possibilities for intervention. Microbiome composition after trauma exposure has been poorly examined regarding neuropsychiatric outcomes. We aimed to determine whether the gut microbiomes of trauma-exposed emergency department patients who develop APNS have dysfunctional gut microbiome profiles and discover potential associated mechanisms. We performed metagenomic analysis on stool samples (n = 51) from a subset of adults enrolled in the Advancing Understanding of RecOvery afteR traumA (AURORA) study. Two-, eight- and twelve-week post-trauma outcomes for post-traumatic stress disorder (PTSD) (PTSD checklist for DSM-5), normalized depression scores (PROMIS Depression Short Form 8b) and somatic symptom counts were collected. Generalized linear models were created for each outcome using microbial abundances and relevant demographics. Mixed-effect random forest machine learning models were used to identify associations between APNS outcomes and microbial features and encoded metabolic pathways from stool metagenomics. Microbial species, including Flavonifractor plautii, Ruminococcus gnavus and, Bifidobacterium species, which are prevalent commensal gut microbes, were found to be important in predicting worse APNS outcomes from microbial abundance data. Notably, through APNS outcome modeling using microbial metabolic pathways, worse APNS outcomes were highly predicted by decreased L-arginine related pathway genes and increased citrulline and ornithine pathways. Common commensal microbial species are enriched in individuals who develop APNS. More notably, we identified a biological mechanism through which the gut microbiome reduces global arginine bioavailability, a metabolic change that has also been demonstrated in the plasma of patients with PTSD.

Association of cigarette smoking with oral bacterial microbiota and cardiometabolic health in Chinese adults

The interplay among cigarette smoking status, oral microbiota, and cardiometabolic health is poorly understood. We aimed to examine the association of cigarette smoking status with oral microbiota and to assess the association of the identified microbial features with cardiometabolic risk factors in a Chinese population. This study included 587 participants within the Central China Cohort, including 111 smokers and 476 non-smokers, and their oral microbiota was profiled by 16S rRNA sequencing. Both oral microbial alpha- and beta-diversity were distinct between smokers and non-smokers (p < 0.05). With adjustment for sociodemographics, alcohol and tea drinking, tooth brushing frequency, and body mass index, the relative abundance of nine genera and 26 pathways, including the genus Megasphaera and two pathways involved in inositol degradation which have potentially adverse effects on cardiometabolic health, was significantly different between two groups (FDR q < 0.20). Multiple microbial features related to cigarette smoking were found to partly mediate the associations of cigarette smoking with serum triglycerides and C-reactive protein levels (p-mediation < 0.05). In conclusion, cigarette smoking status may have impacts on the oral microbial features, which may partially mediate the associations of cigarette smoking and cardiometabolic health.

Role of Gut Microbiota in Statin-Associated New-Onset Diabetes-A Cross-Sectional and Prospective Analysis of the FINRISK 2002 Cohort.

Dyslipidemia is treated effectively with statins, but treatment has the potential to induce new-onset type-2 diabetes. Gut microbiota may contribute to this outcome variability. We assessed the associations of gut microbiota diversity and composition with statins. Bacterial associations with statin-associated new-onset type-2 diabetes (T2D) risk were also prospectively evaluated. We examined shallow-shotgun-sequenced fecal samples from 5755 individuals in the FINRISK-2002 population cohort with a 17+-year-long register-based follow-up. Alpha-diversity was quantified using Shannon index and beta-diversity with Aitchison distance. Species-specific differential abundances were analyzed using general multivariate regression. Prospective associations were assessed with Cox regression. Applicable results were validated using gradient boosting. Statin use associated with differing taxonomic composition (R2, 0.02%; q=0.02) and 13 differentially abundant species in fully adjusted models (MaAsLin; q<0.05). The strongest positive association was with Clostridium sartagoforme (β=0.37; SE=0.13; q=0.02) and the strongest negative association with Bacteroides cellulosilyticus (β=-0.31; SE=0.11; q=0.02). Twenty-five microbial features had significant associations with incident T2D in statin users, of which only Bacteroides vulgatus (HR, 1.286 [1.136-1.457]; q=0.03) was consistent regardless of model adjustment. Finally, higher statin-associated T2D risk was seen with [Ruminococcus] torques (ΔHRstatins, +0.11; q=0.03), Blautia obeum (ΔHRstatins, +0.06; q=0.01), Blautia sp. KLE 1732 (ΔHRstatins, +0.05; q=0.01), and beta-diversity principal component 1 (ΔHRstatin, +0.07; q=0.03) but only when adjusting for demographic covariates. Statin users have compositionally differing microbiotas from nonusers. The human gut microbiota is associated with incident T2D risk in statin users and possibly has additive effects on statin-associated new-onset T2D risk.

Short-term effects of etifoxine on human gut microbiome in healthy men

BackgroundNeurosteroids have recently gained in interest as a treatment strategy for affective disorders. Etifoxine is known for its dual mode of action, one of which is to stimulate endogenous neurosteroid synthesis. The gut microbiome has been studied in affective disorders, but it has not been investigated in the context of human etifoxine or neurosteroid interventions.MethodsWe performed a crossover study with 36 healthy male volunteers who received etifoxine versus alprazolam and placebo in a balanced Williams design. Participants were randomized into six sequences and went through three 5-day treatments followed by wash-out phases of 9 days. Bacterial compositions in stool samples were determined by high-throughput 16S rRNA amplicon sequencing.ResultsGut microbiome analyses revealed no relevant effects between treatments with respect to alpha and beta diversity. Differential abundance analyses yielded etifoxine treatment as the only effect related to changes in microbial features with reductions of Faecalibacterium duncaniae, Roseburia hominis and Lactobacillus rogosae (i.e., Bacteroides galacturonicus).ConclusionHere we report on the first human investigation of the gut microbiome with short-term etifoxine intervention. Differences in diversity and compositional structure of the microbiome were more likely due to between- subject effects rather than medication. However, five-day treatment with etifoxine reduced the abundance of a few bacterial species. These species are currently seen as beneficial components of a healthy intestinal microbiome. This reduction in abundances may be related to elevated endogenous neurosteroids.

Microborings reveal alternating agitation, resting and sleeping stages of modern marine ooids

ABSTRACTOoids are abundant carbonate grains throughout much of Earth's history, but their formation is not well understood. Here, an in‐depth study of microbial bioerosion features of Holocene ooids from the Schooner Cays ooid shoals (Great Bahama Bank, Eleuthera, Bahamas) and the Shalil al Ud ooid shoals in the Arabian/Persian Gulf (Abu Dhabi, United Arab Emirates) is presented. No obvious differences were found in ooid size distribution, cortex layer thickness, the composition of nuclei or euendolithic community when comparing ooids from both locations. Microendolithic borings are present in most studied ooid surfaces, but the intensity of (micro‐)bioerosion varies significantly. Applying an epoxy vacuum cast‐embedding technique allowed the identification of ichnotaxa and their inferred producers (various genera of diatoms, cyanobacteria, coccolithophores and unspecified bacteria). Euendolithic taxa have specific low‐light tolerances and light optima. This implies that information about the relative bathymetry (seafloor versus burial within an ooid shoal) and ecology for ooid cortex formation can be obtained via the presence or absence of their respective ichnotaxa. The history of a statistically significant number of ooid cortices can be translated into dune dynamics and the temporal variations thereof by allocating the inferred index producer to a defined burial or light penetration zone. In this context, ooid formation can be divided into four stages: (i) an agitation stage in the water column, characterized by the colonization of grains by photoautotrophs; (ii) a resting stage, characterized by temporary burial of the ooid, leading to immobilization and a shift towards heterotrophs; (iii) a sleeping stage, characterized by prolonged burial and colonization by organotrophs; and (iv) a reactivation stage, characterized by a resurfacing of the ooid and a subsequent shift towards photoautotrophs. The sleeping stage is presumably a stage of ooid degradation where bioerosion, mainly by heterotrophic fungi and bacteria is particularly active.

The gut microbiome in bullous pemphigoid: implications of the gut-skin axis for disease susceptibility.

Bullous pemphigoid (BP) is an autoimmune blistering disease that primarily affects the elderly. An altered skin microbiota in BP was recently revealed. Accumulating evidence points toward a link between the gut microbiota and skin diseases; however, the gut microbiota composition of BP patients remains largely underexplored, with only one pilot study to date, with a very limited sample size and no functional profiling of gut microbiota. To thoroughly investigate the composition and function of the gut microbiota in BP patients, and explore possible links between skin conditions and gut microbiota, we here investigated the gut microbiota of 66 patients (81.8% firstly diagnosed) suffering from BP and 66 age-, sex-, and study center-matched controls (CL) with non-inflammatory skin diseases (132 total participants), using 16S rRNA gene and shotgun sequencing data. Decreased alpha-diversity and an overall altered gut microbial community is observed in BP patients. Similar trends are observed in subclassifications of BP patients, including first diagnoses and relapsed cases. Furthermore, we observe a set of BP disease-associated gut microbial features, including reduced Faecalibacterium prausnitzii and greater abundance of pathways related to gamma-aminobutyric acid (GABA) metabolism in BP patients. Interestingly, F. prausnitzii is a well-known microbiomarker of inflammatory diseases, which has been reported to be reduced in the gut microbiome of atopic dermatitis and psoriasis patients. Moreover, GABA plays multiple roles in maintaining skin health, including the inhibition of itching by acting as a neurotransmitter, attenuating skin lesions by balancing Th1 and Th2 levels, and maintaining skin elasticity by increasing the expression of type I collagen. These findings thus suggest that gut microbiota alterations present in BP may play a role in the disease, and certain key microbes and functions may contribute to the link between gut dysbiosis and BP disease activity. Further studies to investigate the underlying mechanisms of the gut-skin interaction are thus clearly warranted, which could aid in the development of potential therapeutic interventions.

Analysis of gut microbiome, host genetics, and plasma metabolites reveals gut microbiome-host interactions in the Japanese population

Interaction between the gut microbiome and host plays a key role in human health. Here, we perform a metagenome shotgun-sequencing-based analysis of Japanese participants to reveal associations between the gut microbiome, host genetics, and plasma metabolome. A genome-wide association study (GWAS) for microbial species (n= 524) identifies associations between the PDE1C gene locus and Bacteroides intestinalis and between TGIF2 and TGIF2-RAB5IF gene loci and Bacteroides acidifiaciens. In a microbial gene ortholog GWAS, agaE and agaS, which are related to the metabolism of carbohydrates forming the blood group A antigen, are associated with blood group A in a manner depending on the secretor status determined by the East Asian-specific FUT2 variant. A microbiome-metabolome association analysis (n= 261) identifies associations between bile acids and microbial features such as bile acid metabolism gene orthologs including bai and 7β-hydroxysteroid dehydrogenase. Our publicly available data will be a useful resource for understanding gut microbiome-host interactions in an underrepresented population.

VTwins: inferring causative microbial features from metagenomic data of limited samples

It is difficult to infer causality from high-dimension metagenomic data due to interference from numerous confounders. By imitating the twin studies in genetic research, we develop a straightforward method—virtual twins (VTwins)—to eliminate the confounder effects by transforming the original cohort into a paired cohort of “Twin” samples with distinct phenotypes but matched taxonomic profiles. The results show that VTwins outperforms the conventional approach in the sensitivity of identifying causative features and only requires a 10-fold reduced sample size for recalling disease-associated microbes or pathways, as tested by simulated and empirical data. Benchmark test with other 16 kinds of software further validates the power and applicability of VTwins for handling high-dimension compositional datasets and mining causalities in metagenomic research. In conclusion, VTwins is straightforward and effective in handling high-diversity, high-dimension compositional data, promising applications in mining causalities for metagenomic and potentially other omics data. VTwins is open access and available at https://github.com/mengqingren/VTwins.

Cervical-vaginal dysbiosis: Clinical query of infections in selected private medical laboratories in Abakaliki Ebonyi State Nigeria

Cervical-Vaginal Dysbiosis refers to an imbalance or disruption in the microbial communities inhabiting the cervix and vaginal tract, leading to an altered composition of microorganisms, often accompanied by a decline in overall vaginal health. This phenomenon contrasts with the notion of a balanced and stable vaginal microbiome, which is characterized by the predominance of Lactobacillus species, known for their protective properties against infections and maintenance of a low pH environment This study evaluates the potential of cervical-vaginal dysbiosis among patients with clinical presentation of cervical vaginal infection in Private Medical Laboratories with limited diagnostics resources and specialization. It addresses the need for cytological investigation in addition to microbiological techniques. Clinical queries of cervical-vaginal infections of patients in twelve selected private medical laboratories in Abakaliki Ebonyi state Nigeria was studied. A total number of 38 patients who met the eligibility criteria were recruited into this study. Cervical- vaginal smear was collected from each subject, samples were fixed, and stained using Papanicolaou and Diff-Quick staining method. Out of these 38 smear samples, 17 (44.7%) had normal cytological features with no microbial features observed. Out of the remaining 21 smear samples, Trichomonas vaginalis occurred 9 times(42.9%), followed by fungi occurring 6 times (28.5%), Human papillomavirus occurring 4 times (19.1%) and Actinomyces occurring 2 times(9.5%). Notable cytological features were revealed, these included squamous intraepithelial lesions characterized by parabasal cells showing perinuclear halo, hyperchromatic nuclei, and slight nuclei polymorphism. Inflammatory lesions were also observed, characterized by the conspicuous number of superficial cells, inflammatory background, red blood cells, and infiltrating polymorphs. This study has highlighted the need to adopt a more proactive approach by evaluating the microbial profile of the cervical smear, which can be a risk factor for cervical malignancy; it has also buttressed the need to retrain and incorporate cytology services in private laboratories.

The influence of tide-brought nutrients on microbial carbon metabolic profiles of mangrove sediments

Mangrove ecosystems in the intertidal zone are continually affected by tidal inundation, but the impact of tidal-driven nutrient inputs upon bacterial communities and carbon metabolic features in mangrove surface sediments remains underexplored, and the differences in such impacts across backgrounds are not known. Here, two mangrove habitats with contrasting nutrient backgrounds in Shenzhen Bay and Daya Bay in Shenzhen City, China, respectively, were studied to investigate the effects of varying tidal nutrient inputs (especially dissolved inorganic nitrogen and PO43−-P) on bacterial community composition and functioning in sediment via field sampling, 16S rDNA amplicon sequencing, and the quantitative potential of microbial element cycling. Results showed that tidal input increased Shenzhen Bay mangrove's eutrophication level whereas it maintained the Daya Bay mangrove's relatively oligotrophic status. Dissolved inorganic nitrogen and PO43−-P levels in Shenzhen Bay were respectively 12.6–39.6 and 7.3–29.1 times higher than those in Daya Bay (p < 0.05). In terms of microbial features, Desulfobacteraceae was the dominant family in Shenzhen Bay, while the Anaerolineaceae family dominated in Daya Bay. Co-occurrence network analysis revealed more interconnected and complex microbial networks in Shenzhen Bay. The quantitative gene-chip analysis uncovered more carbon-related functional genes (including carbon degradation and fixation) enriched in Shenzhen Bay's sediment microbial communities than Daya Bay's. Partial least squares path modeling indicated that tidal behavior directly affected mangrove sediments' physicochemical characteristics, with cascading effects shaping microbial diversity and C-cycling function. Altogether, these findings demonstrate that how tides influence the microbial carbon cycle in mangrove sediments is co-correlated with the concentration of nutrient inputs and background status of sediment. This work offers an insightful lens for better understanding bacterial community structure and carbon metabolic features in mangrove sediments under their tidal influences. It provides a theoretical basis to better evaluate and protect mangroves in the context of global change.