Linear Discriminant Analysis Effect Size Research Articles

Bioindicator responses to extreme conditions: Insights into pH and bioavailable metals under acidic metal environments

Acid mine drainage (AMD) caused environmental risks from heavy metal pollution, requiring treatment methods such as chemical precipitation and biological treatment. Monitoring and adapting treatment processes was crucial for success, but cost-effective pollution monitoring methods were lacking. Using bioindicators measured through 16S rRNA was a promising method to assess environmental pollution. This study evaluated the effects of AMD on ecological health using the ecological risk index (RI) and the Risk Assessment Code (RAC) indices. Additionally, we also examined how acidic metal stress affected the diversity of bacteria and fungi, as well as their networks. Bioindicators were identified using linear discriminant analysis effect size (LEfSe), Partial least squares regression (PLS-R), and Spearman analyses. The study found that Cd, Cu, Pb, and As pose potential ecological risks in that order. Fungal diversity decreased by 44.88% in AMD-affected areas, more than the 33.61% decrease in bacterial diversity. Microbial diversity was positively correlated with pH (r = 0.88, p = 0.04) and negatively correlated with bioavailable metal concentrations (r = −0.59, p = 0.05). Similarly, microbial diversity was negatively correlated with bioavailable metal concentrations (bio_Cu, bio_Pb, bio_Cd) (r = 0.79, p = 0.03). Acidiferrobacter and Thermoplasmataceae were prevalent in acidic metal environments, while Puia and Chitinophagaceae were identified as biomarker species in the control area (LDA>4). Acidiferrobacter and Thermoplasmataceae were found to be pH-tolerant bioindicators with high reliability (r = 1, P < 0.05, BW > 0.1) through PLS-R and Spearman analysis. Conversely, Puia and Chitinophagaceae were pH-sensitive bioindicators, while Teratosphaeriaceae was a potential bioindicator for Cu–Zn–Cd metal pollution. This study identified bioindicator species for acid and metal pollution in AMD habitats. This study outlined the focus of biological monitoring in AMD acidic stress environments, including extreme pH, heavy metal pollutants, and indicator species. It also provided essential information for heavy metal bioremediation, such as the role of omics and the effects of organic matter on metal bioavailability.

Abstract 758: Comparative Microbiome Analysis of Paired Mucosal and Fecal Samples in Korean Colorectal Cancer Patients

Abstract Background Beyond the known risk factors such as age over 50, unhealthy diet, ethnicity, and smoking, emerging evidence suggests that gut microbial dysbiosis plays a crucial role in the early stages of colorectal cancer (CRC) by contributing to chronic inflammation and various intestinal dysfunctions. Even though various bacterial species have been studied, the gut microbiome profile as a representative biomarker in CRC patients remains largely unreported. This study presents a comparative analysis of the microbiome profiles of fecal and mucosal samples from CRC patients, followed by metagenomic profiling investigation to validate dominant bacteria in each sample type of CRC patients. Methods The study involved 12 patients receiving CRC resection at Myongji Hospital in South Korea, recruited from May 2020 to June 2021. Fecal samples were collected pre-surgery, and mucosal samples during surgery. Paired-end sequencing was performed using Illumina MiSeq (Illumina, San Diego, USA) platform. 16s rRNA gene-based microbiome profiling was analyzed using QIIME2 (V.2020.11), a plugin-based platform for microbiome analysis. Sequencing reads were filtered, denoised, and clustered into amplicon sequence variants (ASVs) using DADA2 included in QIIME2. Taxonomic classification was assigned in the QIIME2 pipeline using a pre-trained classifier based on the Silva 138.1 reference sequence. Linear discriminant analysis (LDA) effect size (LEfSe) analysis was performed with LDA score ≥3.0 and p-value of 0.05. Results The study subjects included 12 Korean patients, with an average age of 71 ± 10 years. The gender distribution included 3 men and 9 women whose body mass index was 24.6 ± 2.4 (mean ± SD). There was significant difference observed in UniFrac beta-diversity between the two groups (p=0.001). The relative taxonomic patterns of the microbiota between CRC stool and tissue showed that Bacteroides and Fusobacterium were more dominant in tissue than stool at both phylum and genus levels. Further taxonomic differences between the samples revealed that Firmicutes, Bacilli, and Lactobacillacease were over-represented in CRC patient stool, while Pseudomonadales (p&amp;lt;0.001) and Pseudomonas (p&amp;lt;0.001) were identified in the mucosal tissue. Conclusion Our findings revealed that notable distinction was observed in the beta-diversity, indicating a unique microbial composition in tissue. Specifically, higher prevalence of Bacteroides and Fusobacterium at the genus level were identified in tissue. Additionally, our analysis highlighted Pseudomonadales and Pseudomonas emerged in CRC mucosal tissues. Furthermore, by comparing with a healthy control group, we aim to further elucidate potential markers unique to CRC patients. Citation Format: Sanghun Lee. Comparative Microbiome Analysis of Paired Mucosal and Fecal Samples in Korean Colorectal Cancer Patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 758.

Specific vaginal and gut microbiome and the anti-tumor effect of butyrate in cervical cancer women

ObjectiveTo investigate the vaginal and gut microbes changes during the carcinogenesis of cervical and the auxiliary diagnostic value. To investigate the effect of microbiome-specific metabolites butyric on cervical cancer cells. MethodsWe studied 416 vaginal 16S rRNA sequencing data and 116 gut sequencing data. Reads were processed using VSEARCH. We used Shannon index, Chao1 index, Simpson diversity index, β diversity index, Linear discriminant analysis Effect Size (LEfSe), co-abundance network and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to explore microbiome differences between groups. We constructed random forest models based on genus and verified its discriminant effect. Finally, we used the cell counting kit-8 (CCK-8) method to detect cell proliferation capacity and flow cytometry to detect apoptosis and induction of cell cycle progression. ResultsCompared to the non-cancerous population, patients with cervical cancer had unique microbial community characteristics in both vaginal and gut ecological niches. Our predictive model based on genus in two ecological regions achieved high accuracy in the diagnosis of cervical cancer (vaginal model AUC=91.58 %; gut model AUC=99.95 %). Butyric inhibited cervical cancer cell proliferation in a concentration-dependent manner and promoted apoptosis of cancer cells. ConclusionSignificant differences were found in vaginal and gut microbes in patients with cervical cancer compared to the non-cancerous population. The prediction models constructed at the genus level in both ecological sites have good diagnostic value. Microorganisms may be involved in cervical cancer progression in a metabolite-dependent way, and targeting butyric may provide therapeutic options for cervical cancer.

Combining fecal microbiome and metabolomics reveals diagnostic biomarkers for esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the most predominant subtypes of esophageal cancer. The characteristics of the gut microbiome and its metabolites from patients with ESCC have not been adequately studied and discussed. In this study, 40 fecal samples (20 from ESCC patients and 20 from healthy controls) were analyzed by 16S rRNA gene sequencing and untargeted metabolomics. The data sets were analyzed individually and synthesized using various bioinformatics methods. Alpha and beta diversity indicated significant differences in microbial diversity and abundance between ESCC and healthy control feces. At the genus level, the abundance of Phascolarctobacterium, Sutterella, and Streptococcus was significantly increased in ESCC. At the genus level, linear discriminant analysis effect size identified two biomarkers: Bacteroides_stercoris and Prevotella_copri. Untargeted metabolomics analysis revealed 307 differential metabolites between ESCC and healthy control feces, with indoles and derivatives, tropane alkaloids, lipids, and lipid-like molecules in higher relative abundance in ESCC feces than in healthy control feces. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that unsaturated fatty acids (FAs), ascorbate and aldarate metabolism, and hypoxia-inducible factor 1 signaling pathway were significantly associated with differential metabolite. Phenylethanolamine and despropionyl p-fluoro fentanyl could be used as reliable biomarkers to differentiate ESCC from healthy control. The correlation analysis showed that Prevotella may be involved in the synthesis of fatty acyl, carboxylic acids and derivatives, benzenes and substituted derivatives, organic oxygenates, and indoles and derivatives as metabolites. Fusicatenibacter and Lachnospira may be involved in the degradation of indoles and derivatives. Alistipes, Agathobacter, and Parabacteroides may be involved in the synthesis of indoles and derivatives with strong contributions. There is an intricate relationship between the gut microbiome and the levels of several metabolites (e.g., fatty acyls, carboxylic acids and derivatives, indoles, and derivatives). Microbial-associated metabolites can be used as diagnostic biomarkers in therapeutic exploration. Further analysis revealed that Prevotella, Alistipes, Agathobacter, and Parabacteroides might promote ESCC by regulating the synthesis of indoles and their derivatives. The results of this study provide favorable evidence for the early diagnosis of ESCC and subsequent individualized treatment and targeted interventions.IMPORTANCEWe describe for the first time the differences in fecal microbiome composition and metabolites between patients with esophageal squamous cell carcinoma (ESCC) and healthy controls by 16S rRNA gene sequencing and untargeted metabolomics. The results of this study provide a favorable basis for the early diagnosis of ESCC and subsequent targeted interventional therapy.

Characteristics of the oral and gastric microbiome in patients with early-stage intramucosal esophageal squamous cell carcinoma

BackgroundOral microbiome dysbacteriosis has been reported to be associated with the pathogenesis of advanced esophageal cancer. However, few studies investigated the potential role of oral and gastric microbiota in early-stage intramucosal esophageal squamous carcinoma (EIESC).MethodA total of 104 samples were collected from 31 patients with EIESC and 21 healthy controls. The compositions of oral and gastric microbiota were analyzed using 16 S rRNA V3-V4 amplicon sequencing. Linear discriminant analysis effect size (LEfSe) analysis was performed to assess taxonomic differences between groups. The correlation between oral microbiota and clinicopathological factors was evaluated using Spearman correlation analysis. Additionally, co-occurrence networks were established and random forest models were utilized to identify significant microbial biomarkers for distinguishing between the EIESC and control groups.ResultsA total of 292 oral genera and 223 species were identified in both EIESC and healthy controls. Six oral genera were remarkably enriched in EIESC groups, including the genera Porphyromonas, Shigella, Subdoligranulum, Leptotrichia, Paludibacter, and Odoribacter. LEfSe analysis identified genera Porphyromonas and Leptotrichia with LDA scores > 3. In the random forest model, Porphyromonas endodontalis ranked the top microbial biomarker to differentiate EIESC from controls. The elimination rate of Porphyromonas endodontalis from the oral cavity to the stomach was also dramatically decreased in the EIESC group than controls. In the microbial co-occurrence network, Porphyromonas endodontalis was positively correlated with Prevotella tannerae and Prevotella intermedia and was negatively correlated with Veillonella dispar.ConclusionOur study potentially indicates that the dysbacteriosis of both the oral and gastric microbiome was associated with EIESC. Larger scale studies and experimental animal models are urgently needed to confirm the possible role of microbial dysbacteriosis in the pathogenesis of EIESC. (Chinese Clinical Trial Registry Center, ChiCTR2200063464, Registered 07 September 2022, https://www.chictr.org.cn/showproj.html?proj=178563)

A Comparative Investigation of the Bile Microbiome in Patients with Choledocholithiasis and Cholecystolithiasis through Metagenomic Analysis.

While the precise triggers of gallstone formation remain incompletely understood, it is believed to arise from a complex interplay of genetic and environmental factors. The bile microbiome is being increasingly recognized as a possible contributor to the onset of gallstone disease. The primary objective of this study was to investigate distinctions in the microbial communities within bile specimens from patients with choledocholithiasis (common bile duct stones) and cholecystolithiasis (gallbladder stones). We employed massively parallel sequencing of the 16S rRNA gene to examine the microbial communities within bile samples obtained from 28 patients with choledocholithiasis (group DS) and cholecystolithiasis (group GS). The taxonomic composition of the bile microbial communities displayed significant disparities between the group DS and the group GS. Within the 16 prevalent genera, only Streptococcus, Ralstonia, Lactobacillus, and Enterococcus were predominantly found in the group GS. In contrast, the group DS displayed a more diverse range of genera. The alpha diversity of bile specimens was also notably lower in the group GS compared to the group DS (p = 0.041). Principal coordinate analysis unveiled distinct clustering of bile microbial communities depending on the location of the gallstone. Linear discriminant analysis effect size analysis, with a score threshold of >3 and the Kruskall-Wallis test (α < 0.05), recognized Bacilli and Lactobacillales as potential taxonomic markers for distinguishing patients with cholecystolithiasis limited to the gallbladder. Significant variations were found in the distribution and diversity of bile microbial communities between patients with choledocholithiasis and cholecystolithiasis. This observation suggests that alterations in the bile microbiome may contribute to the development of gallstones in these patients.

Esmolol increases the fecal abundance of Lactobacillus in a rat model of sepsis

BackgroundDisorders of the gut microbiome could be responsible for the progression of multiple organ dysfunction syndrome. In this study, we examined the effect of esmolol on the gut microbiome in a rat model of sepsis induced by cecal ligation and puncture (CLP).MethodsThe animals (n = 32) were randomly divided into 3 groups: Sham group (sham operation + normal saline treatment, n = 8), CLP group (cecal ligation and puncture + normal saline treatment, n = 12), and CLP + ESM group (cecal ligation and puncture + esmolol treatment, n = 12). After 24 h, feces in the colon were collected for 16S rRNA gene sequencing and nitric oxide analysis. In addition, colon was removed for immunohistochemical staining of inducible nitric oxide synthase (iNOS).ResultsFour rats in the CLP group and two rats in the CLP + ESM group died. The abundance of Lactobacillus in the CLP + ESM group was higher than CLP group (P = 0.048). In the linear discriminant analysis effect size analysis, Norank f Muribaculaceae, Escherichia–Shigella and Lactobacillus were the predominant bacteria in the Sham group, CLP group and CLP + ESM group, respectively. The iNOS expression in colonocytes stained by brown in the CLP group were much more than Sham group (P = 0.001). Compared to CLP group, the iNOS expression in colonocytes reduced after esmolol treatment (P = 0.013). The concentration of nitric oxide in colon feces was different in Sham group, CLP group and CLP + ESM group (1.31 ± 0.15μmmol/l vs. 1.98 ± 0.27μmmol/l vs. 1.51 ± 0.14μmmol/l, P = 0.001). In addition, the concentration of nitric oxide in CLP group was higher than Sham group (P = 0.001) or CLP + ESM group (P = 0.001).ConclusionsEsmolol increased the fecal abundance of Lactobacillus in a rat model of sepsis. Moreover, esmolol reduced the iNOS expression of colonocytes and the nitric oxide concentration of colon feces.

Exploring prognostic microbiota markers in patients with endometrial carcinoma: Intratumoral insights

Endometrial cancer, a leading gynecological malignancy, is profoundly influenced by the uterine microbiota, a key factor in disease prognosis and treatment. Our study underscores the distinct microbial compositions in endometrial cancer compared to adjacent non-cancerous tissues, revealing a dominant presence of p_Actinobacteria in cancerous tissues as opposed to p_Firmicutes in surrounding areas. Through comprehensive analysis, we identified 485 unique microorganisms in cancer tissues, 26 of which correlate with patient prognosis. Employing univariate Cox regression and LASSO regression analyses, we devised a microbial risk scoring model, effectively stratifying patients into high and low-risk categories, thereby providing predictive insights into their overall survival. We further developed a nomogram that incorporates the microbial risk score along with age, grade, and clinical stage, significantly enhancing the accuracy of our clinical prediction model for endometrial cancer. Moreover, our study delves into the differential immune landscapes of high-risk and low-risk patients. The low-risk group displayed a higher prevalence of activated B cells and increased T cell co-stimulation, indicative of a robust immune response. Conversely, high-risk patients showed elevated tumor immune dysfunction and exclusion scores, suggesting less favorable outcomes in immunotherapy. Notably, the efficacy of IPS-CTLA4 and PD1/PD-L1/PD-L2 blockers was substantially higher in the low-risk group, pointing to a more responsive immunotherapeutic approach. In summary, our research elucidates the unique microbial patterns in endometrial cancer and adjacent tissues, and establishes both a microbial risk score model and a clinical prediction nomogram. These findings highlight the potential of uterine microbiota as a biomarker for customizing treatment strategies, enabling precise interventions for high-risk patients while preventing overtreatment in low-risk cases. This study emphasizes the microbiota's role in tailoring immunotherapy, offering a novel perspective in the treatment and prognosis of endometrial cancer. Significantly, our study's expansive sample analysis from the TCGA-UCEC cohort, employing linear discriminant analysis effect size methodology, not only validates but also enhances our understanding of the microbiota's role in endometrial cancer, paving the way for novel diagnostic and therapeutic approaches in its management.

Comparative Analysis of Hindgut Microbiota Variation in Protaetia brevitarsis Larvae across Diverse Farms.

Protaetia brevitarsis larvae are farm-raised for food, are used in traditional East Asian medicine, and convert organic waste into biofertilizers. Here, the comparative analysis of the gut microbiota of third-instar larvae obtained from five different farms was investigated using 16S rRNA microbial profiling. Species richness, evenness, and diversity results using α-diversity analysis (observed species, Chao1, Shannon, Simpson) were similar between farms, except for those between the TO and KO farms. β-diversity was significantly different in distribution and relative abundance between farms (PERMANOVA, pseudo-F = 13.20, p = 0.001). At the phylum level, Bacillota, Bacteroidota, Actinomycetota, and Pseudomonadota were the most dominant, accounting for 73-88% of the hindgut microbial community. At the genus level, Tuberibacillus, Proteiniphilum, Desulfovibrio, Luoshenia, and Thermoactinomyces were the most abundant. Although oak sawdust was the main feed component, there were large variations in distribution and relative abundance across farms at the phylum and genus levels. Venn diagram and linear discriminant analysis effect size analyses revealed large variations in the hindgut microbial communities of P. brevitarsis larvae between farms. These results suggest environmental factors were more important than feed ingredients or genetic predisposition for the establishment of the intestinal microbiota of P. brevitarsis larvae. These findings serve as reference data to understand the intestinal microbiota of P. brevitarsis larvae.

Changes in fecal microbiota during estrous cycle in healthy thoroughbred mares

Gut microbiota plays a crucial role in various physiological processes, including the regulation of the reproductive system and steroid sex hormones. Throughout the normal estrous cycle of healthy mares, the levels of estradiol-17β (E2) and progesterone (P4) in the blood exhibit periodic changes. To investigate the relationship between cyclic changes in steroid sex hormones and the gut microbiome of mares, we analyzed the fecal microbiota composition in healthy mares during the typical estrous cycle. Blood and fecal samples from five healthy mares were collected, E2 and P4 levels in serum were analyzed using radioimmunoassay (RIA), and the gut microbiome was analyzed by 16S rRNA sequencing. The overall richness and composition of the gut microbiota remained relatively stable during the normal estrous cycle in mares. The Linear Discriminant Analysis Effect Size analysis of the microbial composition during the follicular and luteal phases identified the Rhodococcus genus as differentially abundant. These findings indicate that the mare's gut microbiota's significant composition remains consistent throughout the estrous cycle. At the same time, specific low-abundance pathogenic bacteria exhibit changes that align with sexual hormonal fluctuations.

Comparative profiling of the skin and gut microbiota during metamorphosis in Chinese spiny frogs (Quasipaa spinosa) highlights microbial communities involved in disease pathogenesis

The symbiotic microbiota inhabiting the skin and gut of amphibians exerts roles in maintaining host health, especially during the critical stage of complete metamorphosis where failure to remodel the microbiota can result in various diseases. However, the composition and alterations in the amphibian microbiota in diverse diseased populations, as well as the exact mechanisms underlying disruptions in skin and gut microbial communities leading to diseases, are not yet well established. Herein, skin and gut microbiota were sampled from healthy Chinese spiny frogs (CTL group) as well as individuals with ascites disease (AD group), cataract disease (CD group), and rotten-skin disease (RD group) for Illumina high-throughput sequencing analysis to comprehensively explore potential associations between microbiota composition and the health status of the host. Venn diagrams and UpSet analysis revealed that the CTL group exhibited the highest number of unique amplicon sequence variants (ASVs) in their skin, while the CD group displayed the lowest abundance of ASVs in their gut. Compared to the CTL group, the alpha-diversity of skin microbiota was dramatically depressed in diseased groups, and notable variations in the beta-diversity of both skin and gut microbiota were observed. Further compositional analysis identified Firmicutes, Proteobacteria, and Bacteroidota as the dominant bacterial phyla in both skin and gut microbiota, although their relative abundances varied widely among groups. The linear discriminant analysis effect size (LEfSe) analysis identified various bacteria species with substantial differences between skin and gut microbiota groups including beneficial populations as well as opportunistic ones. Functional predictions indicated significant differences between CTL and diseased groups mainly enriched in metabolism-relevant pathways. Furthermore, in vitro culture experiments confirmed the presence of a total of 19 strains of bacteria from the skin microbiota of RD group, including opportunistic bacteria population Acinetobacter closely associated with spiny frog rotten-skin disease. Taken together, this work provides insights into the composition dynamics of skin and gut microbiota under different health conditions in spiny frogs, highlighting potential applications for symbiotic microbiota modification in promoting healthy amphibian culture practices as well as preventing diseases.

Skin ulcers and microbiota in Rana dybowskii: Uncovering the role of the gut-skin axis in amphibian health

Amphibians' gut and skin microbiota are vital for host health. Ulcers may affect the skin microbiota, with unknown impacts on the gut microbiota. Skin diseases could influence both, but research on their interrelationships is limited. The cutaneous and gut microbiota of healthy and ulcerated Rana dybowskii were analyzed with Illumina sequencing. The result showed healthy frogs showed greater alpha diversity in skin microbiota than ulcerated ones, with no gut microbiota difference. Bray-Curtis and unweighted UniFrac distances revealed distinct skin microbiotas in healthy versus ulcerated groups and significant gut microbiota differences only in Bray-Curtis. Linear discriminant analysis of effect size (LEfSe) showed that ulcerated skin groups were enriched in Proteobacteria and healthy in Actinobacteria. A variety of analyses revealed that diseased frogs, unlike healthy ones, exhibit similar skin and gut microbiota, suggesting disease impacts microbiota relationships and composition. Using the indicator method, identify key bacterial species indicating healthy or diseased status in the frog's skin and gut microbiota. There were significant differences in skin and gut microbiota functions between diseased and healthy frogs, with disease impacting bacterial community structure and physiological functions. Research on R. dybowskii indicated disease aligns the skin and gut microbiota, affecting composition and function, with distinct bacterial indicators for health and disease status. This research underscores the complex interplay between skin and gut microbiota in amphibian health, highlighting implications for disease understanding and conservation strategies.

Analysis of 16s rRNA Gene Sequencing in Feces: The Impact of Bariatric Surgery on the Gut Microbiota in Patients with Obesity.

Obesity is a risk factor for many chronic diseases. This study aimed to investigate the effect of bariatric surgery on the gut microbiota from patients with obesity. The microbiota composition from stool samples before and after bariatric surgery were identified using bacterial 16S rRNA gene sequencing. Based on the speed of weight loss, patients were classified as the slow-loss group and fast-loss group. The ɑ- and β-diversity analysis was done to compare the species richness, evenness, and overall structure of the microbiota between different groups. Next, linear discriminant analysis effect size (LEfSe) and receiver operating characteristic (ROC) analysis were implemented to identify high-dimensional biomarkers and significantly different species of microbial taxa between different groups. Finally, the pathway analysis was inferred using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) to predict the functional profiling of microbial communities. β-diversity analysis suggested that species diversity of preoperative samples of slow-loss group was significantly higher than the fast-loss group. High levels of Oscillospira and Abiotrophia in the preoperative gut microbiota may lead to poor postoperative weight loss. For patients with poor postoperative weight loss due to changes in gut microbiota, the gut microbiota is mainly composed of Lactobacillus. For patients with good postoperative results, the gut microbiota is mainly composed of Escherichia, Robinsonella, and Dialister. In addition, multiple metabolic-related pathways were significantly different between the four groups. This comparative study revealed biomarker species based on microfloral composition in patients with obesity before and after bariatric surgery.

Gut Microbiota Alterations in Adolescent Idiopathic Scoliosis Are Associated with Aberrant Bone Homeostasis.

Low bone mineral density is the major prognostic factor for adolescent idiopathic scoliosis (AIS), but the underlying mechanisms remain unclear. Accumulating evidence suggests that gut microbiota (GM) have the potential to affect bone development, and the GM signatures are altered in AIS patients. However, the effect of GM alterations on aberrant bone homeostasis in AIS remains unclear. This study aims to investigate the GM profile in AIS patients with different bone mineral density (BMD) and explore the association between GM, osteopenia, and aberrant bone turnover. A total of 126 patients with AIS who received surgical treatment were retrospectively included in this study. We analyzed the composition of the GM by 16S rRNA sequencing and BMD by dual X-ray absorptiometry. Based on the BMD of the femur neck, the patients were divided into the osteopenia group (OPN) if the Z score < -1, and the normal (NOR) group if the Z score ≥ -1 SD compared to the healthy control. For the 16S rRNA sequencing, the raw reads were filtered to remove low-quality reads, and operational taxonomic units were identified with the Uparse program. Weighted UniFrac distance matrix for the beta-diversity metrics and principal coordinate analysis (PCoA) was performed, and the statistical comparisons were made with permutational multivariate analysis of variance (PERMANOVA) and analysis of similarity (ANONISM). Linear discriminant analysis effect size (LEfSe) was used to identify the enriched species in two groups. The "Random forest" was applied to determine the optimal biomarker for OPN according to the mean decrease in Gini value. The metabolic function was predicted by the Tax4Fun analysis. The Pearson correlation coefficient was used to evaluate the associations between GM species, bone turnover markers, and BMD. The serum β-CTX was increased in the OPN group (n = 67) compared to the NOR group (n = 59). Patients in OPN groups showed significantly decreased α diversity indicated by the Shannon index. Principal coordinate analysis (PCoA) analysis showed significant clustering of GM between OPN and NOR groups. At genus level, the Escherichia-Shigella and Faecalibacterium were significantly enriched in the OPN group compared to that in the NOR group (p < 0.05), whereas the abundance of Prevotella was significantly decreased (p = 0.0012). The relative abundance of Megamonas and Prevotella was positively correlated with the femur BMD. The abundance of Escherichia-Shigella was negatively correlated with femur BMD and positively correlated with serum β-CTX levels. Functional analysis revealed significant differences in starch and sucrose metabolism, pyruvate and cysteine, and methionine metabolism between NOR and OPN groups. The alterations of GM in AIS patients are correlated with osteopenia. The association between enriched species, BMD, and bone turnover markers provides novel diagnostic and therapeutic targets for the clinical management of AIS.

Effects of alcohol on the composition and metabolism of the intestinal microbiota among people with HIV: A cross-sectional study

ObjectivesAlcohol consumption is not uncommon among people with HIV (PWH) and may exacerbate HIV-induced intestinal damage, and further lead to dysbiosis and increased intestinal permeability. This study aimed to determine the changes in the fecal microbiota and its association with alcohol consumption in HIV-infected patients. MethodsA cross-sectional survey was conducted between November 2021 and May 2022, and 93 participants were recruited. To investigate the alterations of alcohol misuse on fecal microbiology in HIV-infected individuals, we performed 16s rDNA gene sequencing on fecal samples from the low-to-moderate drinking (n = 21) and non-drinking (n = 72) groups. ResultsComparison between groups using alpha and beta diversity showed that the diversity of stool microbiota in the low-to-moderate drinking group did not differ from that of the non-drinking group (all p > 0.05). The Linear discriminant Analysis effect size (LEfSe) algorithm was used to determine the bacterial taxa associated with alcohol consumption, and the results showed altered fecal bacterial composition in HIV-infected patients who consumed alcohol; Coprobacillus, Pseudobutyrivibrio, and Peptostreptococcaceae were enriched, and Pasteurellaceae and Xanthomonadaceae were depleted. In addition, by using the Kyoto Encyclopedia of Genes and Genomes (KEGG), functional microbiome features were also found to be altered in the low-to-moderate drinking group compared to the control group, showing a reduction in metabolic pathways (p = 0.036) and cardiovascular disease pathways (p = 0.006). ConclusionLow-to-moderate drinking will change the composition, metabolism, and cardiovascular disease pathways of the gut microbiota of HIV-infected patients.

A comparative analysis of soil physicochemical properties and microbial community structure among four shelterbelt species in the northeast China plain.

The focal point of this study lies in the implementation of a controlled experiment conducted under field conditions. In this experiment, we deliberately selected four shelterbelts within the same field, characterized by identical planting density, and planting year. This deliberate selection effectively mitigated the potential impact of extraneous factors on the three microbiomes, thereby enhancing the reliability and validity of our findings.

The Effect of Artificial Substrate and Carbon Source Addition on Bacterial Diversity and Community Composition in Water in a Pond Polyculture System

The use of artificial substrates and biofloc technology can favor fish culture and improve water quality. The aim of this study was to evaluate whether artificial substrates and carbon source additions modify the microbial activity of water bodies. The diversity and structure of microflora in the water after adding artificial substrates and carbon sources to the ponds were analyzed using high-throughput sequencing based on the V3-V4 region of 16S rRNA genes. The results showed that there was no difference in the richness and diversity of intestinal microflora between the control and experimental groups. Principal coordinate analysis (PCoA) and nonmetric multidimensional scaling (NMDS) showed that artificial substrate and carbon source addition changed the structure of the microflora. The results of a linear discriminant analysis (LDA) effect size (LefSe) indicated 11 biomarkers in the EGˍst group. Spearman correlation heatmap analysis showed that environmental factors affected the bacterial communities, and the results of a redundancy analysis indicated that chemical oxygen demand was a critical factor in controlling the bacterial communities in the water. These results provide an understanding of the effect of artificial substrate and carbon source addition on bacterial diversity and community composition in water.

Predicting the role of the human gut microbiome in type 1 diabetes using machine-learning methods.

Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still unclear which gut microbiota are the key factors affecting T1D and their influence on the development and progression of the disease. To fill these knowledge gaps, we constructed a model to find biomarker from gut microbiota in patients with T1D. We first identified microbial markers using Linear discriminant analysis Effect Size (LEfSe) and random forest (RF) methods. Furthermore, by constructing co-occurrence networks for gut microbes in T1D, we aimed to reveal all gut microbial interactions as well as major beneficial and pathogenic bacteria in healthy populations and type 1 diabetic patients. Finally, PICRUST2 was used to predict Kyoto Encyclopedia of Genes and Genomes (KEGG) functional pathways and KO gene levels of microbial markers to investigate the biological role. Our study revealed that 21 identified microbial genera are important biomarker for T1D. Their AUC values are 0.962 and 0.745 on discovery set and validation set. Functional analysis showed that 10 microbial genera were significantly positively associated with D-arginine and D-ornithine metabolism, spliceosome in transcription, steroid hormone biosynthesis and glycosaminoglycan degradation. These genera were significantly negatively correlated with steroid biosynthesis, cyanoamino acid metabolism and drug metabolism. The other 11 genera displayed an inverse correlation. In summary, our research identified a comprehensive set of T1D gut biomarkers with universal applicability and have revealed the biological consequences of alterations in gut microbiota and their interplay. These findings offer significant prospects for individualized management and treatment of T1D.

Characteristics of bacterial community in eyelashes of patients with Demodex blepharitis

BackgroundDemodex blepharitis (DB) is a common disease of the ocular surface. The characteristics of the bacterial community in eyelash roots after Demodex infestation are still unknown. Knowledge of the characteristics of the bacterial community of eyelash follicles in patients with DB can provide valuable insights for guiding the diagnosis and treatment of DB.MethodsTwenty-five patients with DB (DB group) and 21 non-DB volunteers (control group) were enrolled in the study. Eyelashes from the upper eyelid of the right eye were sampled, and 16S ribosomal DNA (rDNA) sequencing was performed to determine the V3-V4 regions of the microbial 16S rDNA gene within 1 month of infestation. The sequencing data of the two groups were analyzed and compared. The effect of the bacterium Burkholderia on the survival of Demodex mites was evaluated using Demodex obtained from 12 patients with DB other that the patients in the DB group.ResultsA total of 31 phyla and 862 genera were identified in the DB and control groups. The five most abundant phyla in the two groups were Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes and Cyanobacteria. The abundance of Actinomycetes was significantly higher in the DB group than in the control group. At the genus level, the five most abundant genera in the two groups were Pseudomonas, Burkholderia-Caballeronia-Paraburkholderia, Rolstonia and Acinetobacter; Clostridium sensu stricto 1 was abundant in the control group and Corynebacterium_1 was abundant in the DB group. Compared with the control group, the abundance of Burkholderia-Caballeronia-Paraburkholderia was 2.36-fold lower in the DB group. Linear discriminant analysis Effect Size (LEfSe) analysis revealed Burkholderia-Caballeronia-Paraburkholderia, SC_I_84_unclassified, Nonmyxobacteria and Succinvibrio to be the major biomarkers in the control group and Catenibacterium and Lachnospiraceae NK4A136 group to be the major biomarkers in the DB group. To explore the performance of these optimal marker models, receiver operational characteristic curve analysis was performed, and the average area under the curve value of Burkholderia-Caballeronia-Paraburkholderia was 0.7448. Burkholderia cepacia isolated from normal human eyelashes was fermented, and the Demodex mites isolated from patient eyelashes were cultured together with its fermented supernatant. The results showed that the fermentation supernatant could significantly reduce the survival time of the Demodex mites, suggesting the potential therapeutic value of this bacterium against Demodex.ConclusionsThe composition of the bacterial community in the eyelashes of DB patients differed from that in eyelashes of healthy volunteers, revealing a decrease in bacterial diversity in infested eyelashes. This decrease may be related to the occurrence and development of DB. The supernatant of Burkholderia cepacia culture medium was found to inhibit the growth of Demodex in eyelash hair follicles, providing a new insight with potential applications for the clinical treatment of Demodex infestation.Graphical

Gut microbiota was highly related to the immune status in chronic obstructive pulmonary disease patients.

This study aimed to explore the profile of gut microbiota and immunological state in COPD patients. 80 fecal and blood samples were collected from 40 COPD patients and 40 healthy controls (HC) and analyzed with 16s-rRNA gene sequencing and immunofactor omics analysis to investigate the profile of gut microbiota and immunologic factors (IFs). The linear discriminant analysis (LDA) effect size (LefSe) was used to determine the biomarker's taxa. The random forest and LASSO regression analysis were executed to screen IFs and develop an IFscore model. The correlation between gut microbiota and IFs, along with the IFscore and the diversity of gut microbiota, was evaluated with the Spearman analysis. The α and β diversity showed that the composition and distribution of gut microbiota in the COPD group differed from that of the HC group. 7 differential taxa at the phylum level and 17 differential taxa at the genus level were found. LefSe analysis screened out 5 biomarker's taxa. 32 differential IFs (up-regulated 27 IFs and down-regulated 5 IFs) were identified between two groups, and 5 IFs (CCL3, CXCL9, CCL7, IL2, IL4) were used to construct an IFscore model. The Spearman analysis revealed that 29 IFs were highly related to 5 biomarker's taxa and enriched in 16 pathways. Furthermore, the relationship between the IFscore and gut microbiota diversity was very close. The gut microbiota and IFs profile in COPD patients differed from that in healthy individuals. Gut microbiota was highly related to the immune status in COPD patients.