Differential Abundance Analysis Research Articles

Development of MetaXplore: An Interactive Tool for Targeted Metagenomic Analysis.

Over the last decades, the analysis of complex microbial communities by high-throughput sequencing of marker gene amplicons has become routine work for many research groups. However, the main challenges faced by scientists who want to make use of the generated sequencing datasets are the lack of expertise to select a suitable pipeline and the need for bioinformatics or programming skills to apply it. Here, we present MetaXplore, an interactive, user-friendly platform that enables the discovery and visualization of amplicon sequencing data. Currently, it provides a set of well-documented choices for downstream analysis, including alpha and beta diversity analysis, taxonomic composition, differential abundance analysis, identification of the core microbiome within a population, and biomarker analysis. These features are presented in a user-friendly format that facilitates easy customization and the generation of publication-quality graphics. MetaXplore is implemented entirely in the R language using the Shiny framework. It can be easily used locally on any system with R installed, including Windows, Mac OS, and most Linux distributions, or remotely via a web server without bioinformatic expertise. It can also be used as a framework for advanced users who can modify and expand the tool.

Mibianto: ultra-efficient online microbiome analysis through k-mer based metagenomics.

Quantifying microbiome species and composition from metagenomic assays is often challenging due to its time-consuming nature and computational complexity. In Bioinformatics, k-mer-based approaches were long established to expedite the analysis of large sequencing data and are now widely used to annotate metagenomic data. We make use of k-mer counting techniques for efficient and accurate compositional analysis of microbiota from whole metagenome sequencing. Mibianto solves this problem by operating directly on read files, without manual preprocessing or complete data exchange. It handles diverse sequencing platforms, including short single-end, paired-end, and long read technologies. Our sketch-based workflow significantly reduces the data volume transferred from the user to the server (up to 99.59% size reduction) to subsequently perform taxonomic profiling with enhanced efficiency and privacy. Mibianto offers functionality beyond k-mer quantification; it supports advanced community composition estimation, including diversity, ordination, and differential abundance analysis. Our tool aids in the standardization of computational workflows, thus supporting reproducibility of scientific sequencing studies. It is adaptable to small- and large-scale experimental designs and offers a user-friendly interface, thus making it an invaluable tool for both clinical and research-oriented metagenomic studies. Mibianto is freely available without the need for a login at: https://www.ccb.uni-saarland.de/mibianto.

Nitrogen functional profiles of microbiomes in diverse agricultural and forest soils and its driver at continental scale in China

Functional characteristics of microbiomes are good predictors of nitrogen (N) biogeochemistry, but soil microbial N-functional profiles under different land use practices and their dominant drivers at continental scale remain unclear. For this study, we selected soils having a broad range of edaphic factors across different land use practices and soil types in China and used metagenomic sequencing to investigate N-functional profiles of microbiomes. The N-pathway frequencies were highest in paddy soils, and the composition of N-cycling genes in paddy soils significantly diverged from upland and forest soils. Differential abundance analysis showed that genes associated with nitrogen dissimilatory pathways exhibited enrichment in paddy soils, whereas those linked to assimilatory pathways were enriched in forest soils. Aggregated boosted tree analysis revealed that the frequencies of N-pathways and relative abundances of N-cycling genes were mainly explained by soil moisture and pH. Partial Mantel and redundancy analysis consistently showed that N-functional composition correlated strongest with moisture and pH. Overall, our results demonstrated that soil moisture and pH were vital drivers of microbial N-functional profiles, providing novel evidence for soil moisture and pH’s role in driving whole nitrogen cycling. Considering the large fluctuations in moisture over time, soil pH, with minor seasonality, could be used as indicators to reflect microbial N-functional profiles at the continental scale.

Insights into the early-life chemical exposome of Nigerian infants and potential correlations with the developing gut microbiome

Early-life exposure to natural and synthetic chemicals can impact acute and chronic health conditions. Here, a suspect screening workflow anchored on high-resolution mass spectrometry was applied to elucidate xenobiotics in breast milk and matching stool samples collected from Nigerian mother-infant pairs (n = 11) at three time points. Potential correlations between xenobiotic exposure and the developing gut microbiome, as determined by 16S rRNA gene amplicon sequencing, were subsequently explored. Overall, 12,192 and 16,461 features were acquired in the breast milk and stool samples, respectively. Following quality control and suspect screening, 562 and 864 features remained, respectively, with 149 of these features present in both matrices. Taking advantage of 242 authentic reference standards measured for confirmatory purposes of food bio-actives and toxicants, 34 features in breast milk and 68 features in stool were identified and semi-quantified. Moreover, 51 and 78 features were annotated with spectral library matching, as well as 416 and 652 by in silico fragmentation tools in breast milk and stool, respectively. The analytical workflow proved its versatility to simultaneously determine a diverse panel of chemical classes including mycotoxins, endocrine-disrupting chemicals (EDCs), antibiotics, plasticizers, perfluorinated alkylated substances (PFAS), and pesticides although it was originally optimized for polyphenols. Spearman rank correlation of the identified features revealed significant correlations between chemicals of the same classification such as polyphenols. One-way ANOVA and differential abundance analysis of the data obtained from stool samples revealed that molecules of plant-based origin were elevated when complementary foods were introduced to the infants’ diets. Annotated compounds in the stool, such as tricetin, positively correlated with the genus Blautia. Moreover, vulgaxanthin negatively correlated with Escherichia-Shigella. Despite the limited sample size, this exploratory study provides high-quality exposure data of matched biospecimens obtained from mother-infant pairs in sub-Saharan Africa and shows potential correlations between the chemical exposome and the gut microbiome.

Mi-Mic: a novel multi-layer statistical test for microbiota-disease associations.

mi-Mic, a novel approach for microbiome differential abundance analysis, tackles the key challenges of such statistical tests: a large number of tests, sparsity, varying abundance scales, and taxonomic relationships. mi-Mic first converts microbial counts to a cladogram of means. It then applies a priori tests on the upper levels of the cladogram to detect overall relationships. Finally, it performs a Mann-Whitney test on paths that are consistently significant along the cladogram or on the leaves. mi-Mic has much higher true to false positives ratios than existing tests, as measured by a new real-to-shuffle positive score.

Distinct anal microbiome is correlated with anal cancer precursors in men who have sex with men living with HIV.

Anal cancer risk is elevated in men who have sex with men living with HIV (MSMLWH). Anal high-risk human papillomavirus (hr-HPV) infection is necessary but insufficient to develop high-grade squamous intraepithelial lesion (HSIL), the anal cancer precursor, suggesting additional factors. We sought to determine whether the microbiome of the anal canal is distinct by comparing it with the microbiome of stool. We also sought to determine whether changes in the anal microbiome are associated with HSIL among MSMLWH. Cross-sectional comparison of the microbiome of the anal canal with the microbiome of stool in MSMLWH and cross-sectional comparison of the anal microbiome of MSMLWH with anal HSIL with the anal microbiome of MSMLWH without anal HSIL. Sterile swabs were used to sample the anus of MSMLWH for microbiome and HPV testing, followed by high-resolution anoscopy. Stool samples were mailed from home. 16S sequencing was used for bacterial identification. Measures of alpha diversity, beta diversity and differential abundance analysis were used to compare samples. 166 anal samples and 103 matching stool samples were sequenced. Beta diversity showed clustering of stool and anal samples. Of hr-HPV-positive MSMLWH, 31 had HSIL and 13 had no SIL. Comparison of the microbiome between these revealed 28 different species. The highest-fold enrichment among MSMLWH/hr-HPV/HSIL included pro-inflammatory and carcinogenic Prevotella, Parasuterella, Hungatella, Sneathia and Fusobacterium species. The anti-inflammatory Anaerostipes caccae showed the greatest reduction among MSMLWH/hr-HPV/HSIL. The anal microbiome is distinct from stool. A pro-inflammatory and carcinogenic environment may be associated with anal HSIL.

Exploring the Predictive Value of Gut Microbiome Signatures for Therapy Intensification in Patients With Inflammatory Bowel Disease: A 10-Year Follow-up Study.

Inflammatory bowel diseases (IBDs) pose a significant challenge due to their diverse, often debilitating, and unpredictable clinical manifestations. The absence of prognostic tools to anticipate the future complications that require therapy intensification presents a substantial burden to patient private life and health. We aimed to explore whether the gut microbiome is a potential biomarker for future therapy intensification in a cohort of 90 IBD patients. We conducted whole-genome metagenomics sequencing on fecal samples from these patients, allowing us to profile the taxonomic and functional composition of their gut microbiomes. Additionally, we conducted a retrospective analysis of patients' electronic records over a period of 10 years following the sample collection and classified patients into (1) those requiring and (2) not requiring therapy intensification. Therapy intensification included medication escalation, intestinal resections, or a loss of response to a biological treatment. We applied gut microbiome diversity analysis, dissimilarity assessment, differential abundance analysis, and random forest modeling to establish associations between baseline microbiome profiles and future therapy intensification. We identified 12 microbial species (eg, Roseburia hominis and Dialister invisus) and 16 functional pathways (eg, biosynthesis of L-citrulline and L-threonine) with significant correlations to future therapy intensifications. Random forest models using microbial species and pathways achieved areas under the curve of 0.75 and 0.72 for predicting therapy intensification. The gut microbiome is a potential biomarker for therapy intensification in IBD patients and personalized management strategies. Further research should validate our findings in other cohorts to enhance the generalizability of these results.

Adolescent alcohol use is associated with differences in the diversity and composition of the oral microbiome.

Adolescence is a sensitive stage of oral microbial development that often coincides with the initiation and escalation of alcohol use. Thus,adolescents may be particularly susceptible to alcohol-induced alterations in the oral microbiome, though minimal research has been done in this area. Understanding the connection between the oral microbiome and alcohol use during adolescence is important to understand fully the biological consequences of alcohol use to mitigate potential adverse outcomes. Saliva samples were collected from adolescents aged 17-19 who used alcohol heavily (n = 21, 52.4% female) and those who did not use alcohol or any other substances (n = 18, 44.4% female). We utilized 16S rRNA sequencing to examine differences in microbial diversity and composition between the groups. Foralpha diversity, evenness was significantly lower in the drinking group than the control group as indicated by Pielou's evenness, Shannon, and Simpson indices. There were no statistically significant findings for beta diversity. Differential abundance analyses revealed higher abundances of Rothia and Corynebacterium in the alcohol-using group using both centered-log-ratio and relative abundance normalization. These genera are known for their high capacity to convert alcohol into acetaldehyde, a toxic metabolite reported to play a role in the neurobiological effects of alcohol. An unclassified Clostridia UCG-014, Streptobacillus, Comamonas, unclassified Lachnospiraceae, and Parvimonas were also identified as significantly different between groups when using only one of the normalization techniques. This is the first study designed specifically to compare the oral microbiome of adolescents who use alcohol with that of control participants. Our findings reveal distinct alcohol-related differences in microbial composition and taxon abundance, emphasizing the importance of understanding the impact onthe oral microbiome of alcohol use during adolescence. Because the oral microbiome is malleable, this study provides foundational work for future prevention and intervention studies.

16S rRNA sequencing reveals microbiota differences in orthopedic implants between aseptic loosening and prosthetic joint infection cases.

Prosthetic joint infection (PJI) and aseptic loosening (AL) are common complications of total joint arthroplasty. An accumulation of evidence indicates the presence of microbial communities on prosthetic implants, but the overall microbial profile is unclear. In this study, we aimed to investigate the differences in the microbial composition of prosthetic implants obtained from PJI and AL patients using the 16S rRNA sequencing method. Patients who underwent revision hip, knee, or shoulder arthroplasty caused by PJI (n = 20) or AL (n = 10) were enrolled in the study. 16S rRNA sequencing targeting the V3-V4 region was performed on the microbial specimens collected from synovial fluid, periprosthetic deep-tissue, and biofilm during the revision surgery. The sequenced raw data were analysed for microbial composition and ecological and differential abundance analyses using bioinformatics tools. The AL group had relatively balanced and higher diversity, with Staphylococcus, Streptococcus, and Veillonella being prominent. In the PJI group, Staphylococcus and Pseudomonas were predominant, especially in deep-tissue samples and biofilm samples, respectively. The differential abundance analysis identified 15 and 2 distinctive taxa in the AL and PJI groups, respectively. Our findings provided preliminary insights supporting the existence of periprosthetic microbiota in orthopedic implants and explaining the differences in microbial composition between the AL and PJI groups.

Comparative Analysis of the Methanogen Microbiota Associated to Pasture and Stall Housing in Kazakh Cattle.

The microbial community of cattle rumen (archaea) are the key players in methane emissions. Methane pollutes the atmosphere and leads to the loss of feed energy. The aim of this study was to comparatively investigate the cattle microbiota, with a particular focus on archaea, in relation to the type of housing: pasture versus stall. A 16S metabarcoding analysis of the intestinal contents of cattle was carried out. Аlpha - diversity of grazing animals showed to be higher compared to animals in the stall period (p=0.002). Beta - diversity confirmed a difference in methanogens and microbiota between animals kept on pasture and those in a stall. Differential abundance analysis showed that the relative abundance of the Methanobacteriacea family in animals in the pasture period was significantly higher compared to animals in the stall period (FDR p = 0.00122). In conclusion, this study demonstrates that the concentration of methanogens in the fecal contents of animals during pasture period was higher than that in animals during the stall period. We recommend feeding grazing animals with concentrates in the evening in order to mitigate methane emissions.

Effect of aerobic exercise and particulate matter exposure duration on the diversity of gut microbiota

ABSTRACT Inhalation of ambient particulate matter (PM) can disrupt the gut microbiome, while exercise independently influences the gut microbiome by promoting beneficial bacteria. In this study, we analyzed changes in gut microbial diversity and composition in response to combined interventions of PM exposure and aerobic exercise, extending up to 12 weeks. This investigation was conducted using mice, categorized into five groups: control group (Con), exercise group (EXE), exercise group followed by 3-day exposure to PM (EXE + 3-day PM), particulate matter exposure (PM), and PM exposure with concurrent treadmill exercise (PME). Notably, the PM group exhibited markedly lower alpha diversity and richness compared to the Con group and our analysis of beta diversity revealed significant variations among the intervention groups. Members of the Lachnospiraceae family showed significant enhancement in the exercise intervention groups (EXE and PME) compared to the Con and PM groups. The biomarker Lactobacillus, Coriobacteraceae, and Anaerofustis were enriched in the EXE group, while Desulfovibrionaceae, Mucispirillum schaedleri, Lactococcus and Anaeroplasma were highly enriched in the PM group. Differential abundance analysis revealed that Paraprevotella, Bacteroides, and Blautia were less abundant in the 12-week PM exposure group than in the 3-day PM exposure group. Moreover, both the 3-day and 12-week PM exposure groups exhibited a reduced relative abundance of Bacteroides uniformis, SMB53, and Staphylococcus compared to non-PM exposure groups. These findings will help delineate the possible roles and associations of altered microbiota resulting from the studied interventions, paving the way for future mechanistic research.

Searching for new plastic-degrading enzymes from the plastisphere of alpine soils using a metagenomic mining approach.

Plastic materials, including microplastics, accumulate in all types of ecosystems, even in remote and cold environments such as the European Alps. This pollution poses a risk for the environment and humans and needs to be addressed. Using shotgun DNA metagenomics of soils collected in the eastern Swiss Alps at about 3,000 m a.s.l., we identified genes and their proteins that potentially can degrade plastics. We screened the metagenomes of the plastisphere and the bulk soil with a differential abundance analysis, conducted similarity-based screening with specific databases dedicated to putative plastic-degrading genes, and selected those genes with a high probability of signal peptides for extracellular export and a high confidence for functional domains. This procedure resulted in a final list of nine candidate genes. The lengths of the predicted proteins were between 425 and 845 amino acids, and the predicted genera producing these proteins belonged mainly to Caballeronia and Bradyrhizobium. We applied functional validation, using heterologous expression followed by enzymatic assays of the supernatant. Five of the nine proteins tested showed significantly increased activities when we used an esterase assay, and one of these five proteins from candidate genes, a hydrolase-type esterase, clearly had the highest activity, by more than double. We performed the fluorescence assays for plastic degradation of the plastic types BI-OPL and ecovio® only with proteins from the five candidate genes that were positively active in the esterase assay, but like the negative controls, these did not show any significantly increased activity. In contrast, the activity of the positive control, which contained a PLA-degrading gene insert known from the literature, was more than 20 times higher than that of the negative controls. These findings suggest that in silico screening followed by functional validation is suitable for finding new plastic-degrading enzymes. Although we only found one new esterase enzyme, our approach has the potential to be applied to any type of soil and to plastics in various ecosystems to search rapidly and efficiently for new plastic-degrading enzymes.

The alteration of fecal microbial and metabolic profile of gallstone patients in Taiwan: Single center study.

Gallstone disease is a common health problem worldwide. The role of the gut microbiota in gallstone pathogenesis remains obscure. Our aim was to evaluate the association and crosstalk between gut microbiota, gut metabolomic, and metabolic parameters in cholesterol gallstone (CS) patients, pigmented gallstone (PS) patients, and controls. We collected stool samples from healthy individuals and patients with gallstones in our hospital from March 2019 to February 2021. 16s rRNA sequencing was performed, followed by differential abundance analyses. Measurement of bile acids and short-chain fatty acids was conducted via targeted metabolomics. Thirty healthy individuals and 20 gallstone patients were recruited. The intergroup difference of microbial composition was significant between control and gallstone patients. The control group had more abundant Faecalibacterium , Prevotella 9 and Bacteroides plebeius DSM 17135 . The CS group had higher Desulfovibrionaceae and Bacteroides uniformis than the other two groups, while the PS group had more abundant Escherichia-Shigella . In the analysis of metabolites, only n-butyric acid had a significantly higher concentration in the controls than in the gallstone group ( p < 0.01). The level of 3α-hydroxy-12 ketolithocholic acid, deoxycholic acid, and cholic acid showed no intergroup differences, but was correlated to the serum cholesterol level and bacterial richness and evenness. Our study revealed the key taxa that can discriminate between individuals with or without gallstones. We also identified metabolites that are possibly associated with metabolic parameter and bacterial diversity. However, the correlation of the metabolites to certain clusters of bacteria should be analyzed in a larger cohort.

The effect of feeding on different hosts on the egg proteins in Haemaphysalis qinghaiensis tick.

The majority of ixodid ticks display host-specificity to varying extents. Feeding on different hosts affects their development and reproduction. Consequences can be analyzed at the level of the egg, as it is the initial stage of tick development. Tick egg proteins are abundant and diverse, providing nutrients for embryonic development. However, studies on tick egg profiles are scarce. In this study, we aimed to analyze whether feeding Haemaphysalis qinghaiensis ticks on the yaks (Bos grunniens) and domestic sheep (Ovis aries) has an impact on the variety and variability of the egg proteome. Detached engorged females were used to lay eggs, which were then collected, dewaxed, and subjected to protein extraction. The extracted egg proteins were enzymatically digested using Filter-Aided Sample Preparation (FASP), and the unique peptides were separated and detected by Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS). The MS data were searched against the previously constructed whole tick transcriptome library of H. qinghaiensis, and the UniProt database for the identification of tick-derived egg proteins. The analysis revealed 49 and 53 high-confidence proteins identified in eggs collected from B. grunniens (EggBg) and O. aries (EggOa), respectively. Of these, 46 high-confidence proteins were common to both egg types, while three were unique to EggBg and seven to EggOa. All the identified proteins mainly belonged to enzymes, enzyme inhibitors, transporters, and proteins with unknown functions. The differential abundance analysis showed that nine proteins were significantly more present in EggBg, while six were significantly more present in EggOa. Overall, enzymes were the most diverse group, while vitellogenin (Vg) was the most abundant. Blood meal uptake on different hosts has a certain effect on the egg proteome composition and the abundance of some proteins, but it may also lead to compensation of protein roles.

Vaginal microbiomes of breast cancer survivors treated with aromatase inhibitors with and without vulvovaginal symptoms

Genitourinary syndrome of menopause (GSM) is the leading cause of vaginal symptoms in breast cancer survivors treated with aromatase inhibitors. However, there are currently no effective treatment options available for women with a history of breast cancer. Recent research has established that changes in the vaginal microbiome may be linked to GSM. Most studies have assessed the microbiome without accounting for the estrogen status. It remains unknown whether the vaginal microbiome differ among patients with a low estrogenic state with and without vulvovaginal symptoms. To address such research questions, our study compares the vaginal microbiomes among breast cancer survivors treated with aromatase inhibitors with and without vulvovaginal symptoms. A total of 50 breast cancer survivors treated with aromatase inhibitors were recruited, among whom 25 had vulvovaginal symptoms and 25 had no vulvovaginal symptoms. Vaginal swabs were collected. DNA extraction, followed by sequencing of the V3–V4 regions of the 16S ribosomal RNA gene, were performed. Differential abundance analysis was conducted by linear discriminant analysis effect size. Taxonomy assignment, alpha diversity and beta diversity were examined. The relative abundance of genus Sneathia and genus Gardnerella was significantly increased in vulvovaginal symptoms group with no differences in bacterial diversity and richness.

MbDecoda: a debiased approach to compositional data analysis for microbiome surveys.

Potentially pathogenic or probiotic microbes can be identified by comparing their abundance levels between healthy and diseased populations, or more broadly, by linking microbiome composition with clinical phenotypes or environmental factors. However, in microbiome studies, feature tables provide relative rather than absolute abundance of each feature in each sample, as the microbial loads of the samples and the ratios of sequencing depth to microbial load are both unknown and subject to considerable variation. Moreover, microbiome abundance data are count-valued, often over-dispersed and contain a substantial proportion of zeros. To carry out differential abundance analysis while addressing these challenges, we introduce mbDecoda, a model-based approach for debiased analysis of sparse compositions of microbiomes. mbDecoda employs a zero-inflated negative binomial model, linking mean abundance to the variable of interest through a log link function, and it accommodates the adjustment for confounding factors. To efficiently obtain maximum likelihood estimates of model parameters, an Expectation Maximization algorithm is developed. A minimum coverage interval approach is then proposed to rectify compositional bias, enabling accurate and reliable absolute abundance analysis. Through extensive simulation studies and analysis of real-world microbiome datasets, we demonstrate that mbDecoda compares favorably with state-of-the-art methods in terms of effectiveness, robustness and reproducibility.

Constituents of stable commensal microbiota imply diverse colonic epithelial cell reactivity in patients with ulcerative colitis

BackgroundDespite extensive research on microbiome alterations in ulcerative colitis (UC), the role of the constituent stable microbiota remains unclear.ResultsThis study, employing 16S rRNA-gene sequencing, uncovers a persistent microbial imbalance in both active and quiescent UC patients compared to healthy controls. Using co-occurrence and differential abundance analysis, the study highlights microbial constituents, featuring Phocaeicola, Collinsella, Roseburia, Holdemanella, and Bacteroides, that are not affected during the course of UC. Co-cultivation experiments, utilizing commensal Escherichia coli and Phocaeicola vulgatus, were conducted with intestinal epithelial organoids derived from active UC patients and controls. These experiments reveal a tendency for a differential response in tight junction formation and maintenance in colonic epithelial cells, without inducing pathogen recognition and stress responses, offering further insights into the roles of these microorganisms in UC pathogenesis. These experiments also uncover high variation in patients’ response to the same bacteria, which indicate the need for more comprehensive, stratified analyses with an expanded sample size.ConclusionThis study reveals that a substantial part of the gut microbiota remains stable throughout progression of UC. Functional experiments suggest that members of core microbiota – Escherichia coli and Phocaeicola vulgatus – potentially differentially regulate the expression of tight junction gene in the colonic epithelium of UC patients and healthy individuals.

A universal plasma metabolites-derived signature predicts cardiovascular disease risk in MAFLD

BackgroundMetabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high risk of disease progression. Fatty liver is a driver for extrahepatic complications, particularly cardiovascular diseases (CVD). Although the risk of CVD in MAFLD could be predicted by carotid ultrasound test, a very early stage prediction method before the formation of pathological damage is still lacking. MethodsStool microbiomes and plasma metabolites were compared across 196 well-characterized participants encompassing normal controls, simple MAFLD patients, MAFLD patients with carotid artery pathological changes, and MAFLD patients with diagnosed coronary artery disease (CAD). 16S rDNA sequencing data and untargeted metabolomic profiles were interrogatively analyzed using differential abundance analysis and random forest (RF) machine learning algorithm to identify discriminatory gut microbiomes and metabolomic. ResultsCharacteristic microbial changes in MAFLD patients with CVD risk were represented by the increase of Clostridia and Firmicutes-to-Bacteroidetes ratios. Faecalibacterium was negatively correlated with mean-intima-media thickness (IMT), TC, and TG. Megamonas, Bacteroides, Parabacteroides, and Escherichia were positively correlated with the exacerbation of pathological indexes. MAFLD patients with CVD risk were characterized by the decrease of lithocholic acid taurine conjugate, and the increase of ethylvanillin propylene glycol acetal, both of which had close relationship with Ruminococcus and Gemmiger. Biotin l-sulfoxide had positive correlation with mean-IMT, TG, and weight. The general auxin pesticide beta-naphthoxyacetic acid and the food additive glucosyl steviol were both positively correlated with the increase of mean-IMT. The model combining the metabolite signatures with 9 clinical parameters accurately distinguished MAFLD with CVD risk in the proband and validation cohort. It was found that citral was the most important discriminative metabolite marker, which was validated by both in vitro and in vivo experiments. ConclusionsSimple MAFLD patients and MAFLD patients with CVD risk had divergent gut microbes and plasma metabolites. The predictive model based on metabolites and 9 clinical parameters could effectively discriminate MAFLD patients with CVD risk at a very early stage.

Abstract 751: Gut microbiome and breast cancer: Report from a case-control study in Vietnam

Abstract The importance of gut microbiome on human health is being increasingly recognized. The gut microbiota may play a critical role in breast cancer etiology, likely through the roles of the gut microbiota in estrogen and nutrient metabolism as well as in immune regulation. However, evidence on associations between breast cancer and gut microbiota is limited and inconsistent. Using resources from the Vietnamese Breast Cancer Case-Control Study (VBCS), we evaluated differences in gut microbiome profiles between women with breast cancer and healthy women. Pre-treatment tool samples of 162 incident breast cancer cases (age: 50.0±9.5) and stool samples of 370 age-matched controls (age: 49.7±9.0) were included in the study. The gut microbiome was measured using shotgun metagenomic sequencing. Differences in gut microbiome α-diversity and β-diversity between breast cancer patients and healthy controls were evaluated via linear regression models and PERMANOVA testing, respectively. Case-control differences in gut microbial taxa abundance were assessed through the differential abundance analysis with adjustment for potential confounders, including age, income levels, residence, menopausal status, reproductive factors, body mass index, comorbidity, dietary intake, and physical activity. An association with a false discovery rate (FDR) &amp;lt;0.1 was considered statistically significant. No significant difference between breast cancer patients and healthy controls was observed for α- and β-diversities. A total of 2,905 gut microbial taxa were evaluated. Among them, significant case-control differences were found in the abundance of one phylum, two classes, four orders, three families, four gena, and 67 species (all p&amp;lt;0.05 and FDR &amp;lt;0.1). Compared to healthy controls, breast cancer patients had a decreased abundance of species Pauljensenia keddieii, Bifidobacterium bifidum (phylum Actinobacteriota), Clostridium Q symbiosum, Faecalicatena fissicatena, Massilioclostridium methylpentosum, Parvimonas micra (phylum Firmicutes A), Leptotrichia wadei (phylum Fusobacteriota), Enterococcus D gallinarum, Lactobacillus H fermentum, Gemella haemolysans B, genus Streptococcus and its 24 species such as S. anginosus C, S. constellatus, S. equinus, S. infantis I, S. mitis, S. oralis, S. pseudopneumoniae O (phylum Firmicutes) (all p&amp;lt;0.05 and FDR &amp;lt;0.1). The species Clostridium Q symbiosum showed the strongest association, with a log2 fold-change (SE) of -2.02 (0.45), p=7.35 × 10−6; FDR=0.006. Additionally, breast cancer patients had an increased abundance of three species belonging to the phylum Firmicutes A including MGYG-HGUT-03165, MGYG-HGUT-04111, and MGYG-HGUT-00903, compared to healthy controls (p&amp;lt;0.05 and FDR &amp;lt;0.1). These results suggest that the gut microbiome of breast cancer differs from that of control women. Additional analyses are ongoing to reveal the biological underpinning of the observed associations. Citation Format: Sang Minh Nguyen, Huong T. Tran, Jirong Long, Martha J. Shrubsole, Hui Cai, Yaohua Yang, Thuan V. Tran, Wei Zheng, Xiao-Ou Shu. Gut microbiome and breast cancer: Report from a case-control study in Vietnam [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 751.

Aerobic digestibility of waste aerobic granular sludge (AGS) assessed by respirometry, physical-chemical analyses, modeling and 16S rRNA gene sequencing

Research has evolved on aerobic granular sludge (AGS) process, but still there are very few studies on the treatment of excess AGS sludge, with almost none considering its aerobic digestion. Here therefore, the aerobic digestibility of typical AGS sludge was assessed. Granules were produced from acetate-based synthetic wastewater (WW) and were subjected to aerobic digestion for 64 d. The stabilization process was monitored over time through physical-chemical parameters, oxygen uptake rates (OUR) and 16S rRNA gene sequencing. The microbial analyses revealed that the cultivated granules were dominated by slow-growing bacteria, mainly ordinary heterotrophic organisms with potential for polyhydroxyalkanoates (PHA) aerobic storage (PHA-OHOs), polyphosphate and glycogen accumulating organisms (PAOs and GAOs), fermentative anaerobes and nitrifiers (AOB and NOB). Differential abundance analysis of the bacterial data (before versus after digestion) discriminated between the most vulnerable microbiome genera and those most resistant to aerobic digestion. Furthermore, modeling of the stabilization process determined that the endogenous decay rate constant (bH) for the heterotrophs present in the granules was notably low; bH = 0.05 d−1 (average), four times less than for common activated sludge (AS), which is rated at 0.2 d−1. For first time, the research reveals another important feature of AGS sludge, i.e. the slow-decaying character of its bacteria (along with their known slow-growing character). This results in slower stabilization, need of bigger digesters and reconsideration of the specific OUR limits in biosolids regulations (SOUR limit of 1.5 mg/gTSS.h), for waste AGS compared to conventional waste AS. The study suggests that aerobic digestion of waste AGS (fully-granulated) could differ from that of conventional AS. Future work is needed on aerobic digestibility of real AGS sludges from municipal and industrial WWs, compared to synthetic WWs.