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BioRxiv : the Preprint Server For... Aug 2023The vaginal microbiome (VMB) has been classified into several discrete community state types, some of which have been associated with adverse human health conditions....
BACKGROUND
The vaginal microbiome (VMB) has been classified into several discrete community state types, some of which have been associated with adverse human health conditions. However, the roles of the many vaginal bacteria in modulating the VMB and health remain unclear.
METHODS
The associations among the vaginal taxa and other vaginal taxa, the vaginal pH, and the host gene expression responses were determined by calculating the correlation among the relative abundance of the vaginal taxa, the association between the vaginal pH and the predominant taxon in the VMB, and the correlation between the relative abundance of the vaginal taxa and human gene expression at the transcriptional level, respectively. Using these associations, an alternative more informative method, the biological vagitype (BVT), is proposed to classify community state types of the VMB.
FINDINGS
Most spp., with the exception of , show significant correlations with host gene expression profiles and negative associations with dysbiosis-associated vaginal taxa. Many non- spp. exhibit varied correlations with spp., the vaginal pH, and host gene expression. Compared to other dysbiotic taxa, including Lachnocurva vaginae, has a stronger positive correlation with vaginal pH and a stronger negative correlation with spp. Most dysbiosis-associated taxa are associated with stress responses of the host at the transcriptional level, but the genus has a uniquely strong positive correlation with host immune responses. The association between BVTs of the VMBs and host characteristics, e.g., race/ethnicity, microbial infection, smoking, antibiotics, high blood pressure, economic state, diet, and others, was examined. The BVT classification method improved overall performance in associating specific vaginal microbial populations with host characteristics and phenotypes.
INTERPRETATION
This study sheds light on the biological characteristics of the vaginal microbiota, including some less abundant or still unculturable taxa. Since the BVT method was established based on these biological characteristics, the classification outcome of the VMB may have more clinical relevance. Because the BVT method performs better in associating specific vaginal community types with diseases, e.g., bacterial vaginosis and gonorrhea, it could be beneficial for the predictive modeling of adverse health.
FUNDING
This work was supported by grants [UH3AI083263, U54HD080784, and R01HD092415] from the National Institutes of Health; and support from the [GAPPS BMGF PPB] grant from the Global Alliance to Prevent Prematurity and Stillbirth. We would also like to thank the Office of Research on Women's Health at NIH for their generous support.
RESEARCH IN CONTEXT
The vaginal microbiome (VMB) refers to the community of microorganisms in the female lower reproductive tract. The VMB is often a simple ecosystem dominated by a single species. The most predominant bacteria in the VMB include several species and two non- species, i.e., Lachnocurva vaginae and species produce lactic acid to lower the vaginal pH and inhibit the growth of disease-associated bacteria. Thus, the predominance of protective Lactobacilli, i.e., , and , in the VMB is associated with overall vaginal health. However, the role of in promoting a healthy vaginal ecosystem is less clear. Actually, the biological and health relevance of many bacteria in the female lower reproductive tract is largely unknown. Some bacteria have low relative abundances, e.g., and spp.; and others are not yet culturable, e.g., Lachnocurva vaginae and BVAB TM7. When abundance of a taxon is low, its association with a host characteristic is a challenge. Previous methods to classify the VMB were based simply on their microbial compositions, and the biological characteristics of the vaginal bacteria were largely ignored. Thus, classification of these VMBs into biologically relevant community types, as described herein, should be helpful in determining their relevance to women's reproductive health. This study examines three biological characteristics of bacteria in the VMB, i.e., the associations among different bacterial taxa, the vaginal pH, and the host response. Based on these three characteristics, the influence of these bacteria, particularly low abundant and unculturable bacteria, on vaginal health is evaluated. seems to be neutral in maintaining overall vaginal health. is apparently more easily inhibited by spp. than Lachnocurva vaginae because of its stronger positive correlation with vaginal pH and negative correlation with . The genus of has a unique positive correlation with local immune responses, implying a role for in promoting inflammation. Compared with previous methods to classify the VMB, a new method, considering the above three biological characteristics of bacteria in the VMB, has been established. The new method performs better in associating specific vaginal communities with host characteristics and phenotypes; e.g., bacterial vaginosis and gonorrhea. Accurate biological classification of the VMB is fundamental for assessing its impact on women's health. Our classification scheme represents a step further toward that correct classification, eventually leading to new strategies for clinical assessment of the potential use of the VMB to diagnose or predict women's reproductive health.
PubMed: 37645743
DOI: 10.1101/2023.08.16.553525 -
MSystems Jan 2024Drug addiction can seriously damage human physical and mental health, while detoxification is a long and difficult process. Although studies have reported changes in the...
Drug addiction can seriously damage human physical and mental health, while detoxification is a long and difficult process. Although studies have reported changes in the oral microbiome of methamphetamine (METH) users, the role that the microbiome plays in the process of drug addiction is still unknown. This study aims to explore the function of the microbiome based on analysis of the variations in the oral microbiome and metabolome of METH users. We performed the 16S rRNA sequencing analysis based on the oral saliva samples collected from 278 METH users and 105 healthy controls (CTL). In addition, the untargeted metabolomic profiling was conducted based on 220 samples. Compared to the CTL group, alpha diversity was reduced in the group of METH users and the relative abundances of and were significantly increased, while the relative abundances of and were significantly decreased. Variations were also detected in oral metabolic pathways, including enhanced tryptophan metabolism, lysine biosynthesis, purine metabolism, and steroid biosynthesis. Conversely, the metabolic pathways of porphyrin metabolism, glutathione metabolism, and pentose phosphate were significantly reduced. It was speculated that four key microbial taxa, i.e., , , , and , could be involved in the toxicity and addiction mechanisms of METH by affecting the above metabolic pathways. It was found that with the increase of drug use years, the content of tryptamine associated with neuropsychiatric disorders was gradually increased. Our study provides novel insights into exploring the toxic damage and addiction mechanisms underlying the METH addiction.IMPORTANCEIt was found that with the increase of drug use years, the content of tryptamine associated with neuropsychiatric disorders gradually increased. The prediction models based on oral microbiome and metabolome could effectively predict the methamphetamine (METH) smoking. Our study provides novel insights into the exploration of the molecular mechanisms regulating the toxic damage and addiction of METH as well as new ideas for early prevention and treatment strategies of METH addiction.
Topics: Humans; Methamphetamine; RNA, Ribosomal, 16S; Amphetamine-Related Disorders; Metabolome; Microbiota; Tryptamines
PubMed: 38112416
DOI: 10.1128/msystems.00991-23 -
BMC Microbiology Apr 2024Oral microbiota imbalance is associated with the progression of various lung diseases, including lung cancer. Pulmonary nodules (PNs) are often considered a critical...
BACKGROUND
Oral microbiota imbalance is associated with the progression of various lung diseases, including lung cancer. Pulmonary nodules (PNs) are often considered a critical stage for the early detection of lung cancer; however, the relationship between oral microbiota and PNs remains unknown.
METHODS
We conducted a 'Microbiome with pulmonary nodule series study 1' (MCEPN-1) where we compared PN patients and healthy controls (HCs), aiming to identify differences in oral microbiota characteristics and discover potential microbiota biomarkers for non-invasive, radiation-free PNs diagnosis and warning in the future. We performed 16 S rRNA amplicon sequencing on saliva samples from 173 PN patients and 40 HCs to compare the characteristics and functional changes in oral microbiota between the two groups. The random forest algorithm was used to identify PN salivary microbial markers. Biological functions and potential mechanisms of differential genes in saliva samples were preliminarily explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cluster of Orthologous Groups (COG) analyses.
RESULTS
The diversity of salivary microorganisms was higher in the PN group than in the HC group. Significant differences were noted in community composition and abundance of oral microorganisms between the two groups. Neisseria, Prevotella, Haemophilus and Actinomyces, Porphyromonas, Fusobacterium, 7M7x, Granulicatella and Selenomonas were the main differential genera between the PN and HC groups. Fusobacterium, Porphyromonas, Parvimonas, Peptostreptococcus and Haemophilus constituted the optimal marker sets (area under curve, AUC = 0.80), which can distinguish between patients with PNs and HCs. Further, the salivary microbiota composition was significantly correlated with age, sex, and smoking history (P < 0.001), but not with personal history of cancer (P > 0.05). Bioinformatics analysis of differential genes showed that patients with PN showed significant enrichment in protein/molecular functions related to immune deficiency and energy metabolisms, such as the cytoskeleton protein RodZ, nicotinamide adenine dinucleotide phosphate dehydrogenase (NADPH) dehydrogenase, major facilitator superfamily transporters and AraC family transcription regulators.
CONCLUSIONS
Our study provides the first evidence that the salivary microbiota can serve as potential biomarkers for identifying PN. We observed a significant association between changes in the oral microbiota and PNs, indicating the potential of salivary microbiota as a new non-invasive biomarker for PNs.
TRIAL REGISTRATION
Clinical trial registration number: ChiCTR2200062140; Date of registration: 07/25/2022.
Topics: Humans; Saliva; RNA, Ribosomal, 16S; Microbiota; Biomarkers; Lung Neoplasms; Oxidoreductases
PubMed: 38643115
DOI: 10.1186/s12866-024-03280-x -
Nature Communications Mar 2024Multi-omic studies of the human gut microbiome are crucial for understanding its role in disease across multiple functional layers. Nevertheless, integrating and...
Multi-omic studies of the human gut microbiome are crucial for understanding its role in disease across multiple functional layers. Nevertheless, integrating and analyzing such complex datasets poses significant challenges. Most notably, current analysis methods often yield extensive lists of disease-associated features (e.g., species, pathways, or metabolites), without capturing the multi-layered structure of the data. Here, we address this challenge by introducing "MintTea", an intermediate integration-based approach combining canonical correlation analysis extensions, consensus analysis, and an evaluation protocol. MintTea identifies "disease-associated multi-omic modules", comprising features from multiple omics that shift in concord and that collectively associate with the disease. Applied to diverse cohorts, MintTea captures modules with high predictive power, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome study, MintTea identifies a module with serum glutamate- and TCA cycle-related metabolites, along with bacterial species linked to insulin resistance. In another dataset, MintTea identifies a module associated with late-stage colorectal cancer, including Peptostreptococcus and Gemella species and fecal amino acids, in line with these species' metabolic activity and their coordinated gradual increase with cancer development. This work demonstrates the potential of advanced integration methods in generating systems-level, multifaceted hypotheses underlying microbiome-disease interactions.
Topics: Humans; Multiomics; Microbiota; Bacteria; Gastrointestinal Microbiome
PubMed: 38521774
DOI: 10.1038/s41467-024-46888-3 -
Synthetic and Systems Biotechnology Dec 2023is an anaerobic bacterium, which has been found selectively en-riched in the fecal and mucosal microbiota of colorectal cancer (CRC) patients. Emerging evidence suggest...
is an anaerobic bacterium, which has been found selectively en-riched in the fecal and mucosal microbiota of colorectal cancer (CRC) patients. Emerging evidence suggest may contribute to the development of CRC in human. In this study, we designed a multi-epitope chimeric vaccine against PCWBR2, a recently identified adhesin that interacts directly with colon cell lines by binding α2/β1 integrin frequently overexpressed in human CRC tumors and cell lines. Immunoinformatics tools predicted six cytotoxic T lymphocyte epitopes, five helper T lymphocyte epitopes, and six linear B lymphocyte epitopes. The predicted epitopes were joined with AAY or GPGPG linkers and a previously reported TLR4 agonist was added to the vaccine construct's N terminal as an adjuvant using EAAAK linkers and the order of epitopes was optimized. Further analysis revealed that the vaccine construct possesses satisfactory antigenicity, allergenicity, solubility, physicochemical properties, adjuvant-TLR4 molecular docking, and immune profile characteristics. Our study provided a promising design for vaccines against .
PubMed: 38099061
DOI: 10.1016/j.synbio.2023.11.004 -
Nature Medicine May 2024Despite substantial progress in cancer microbiome research, recognized confounders and advances in absolute microbiome quantification remain underused; this raises...
Despite substantial progress in cancer microbiome research, recognized confounders and advances in absolute microbiome quantification remain underused; this raises concerns regarding potential spurious associations. Here we study the fecal microbiota of 589 patients at different colorectal cancer (CRC) stages and compare observations with up to 15 published studies (4,439 patients and controls total). Using quantitative microbiome profiling based on 16S ribosomal RNA amplicon sequencing, combined with rigorous confounder control, we identified transit time, fecal calprotectin (intestinal inflammation) and body mass index as primary microbial covariates, superseding variance explained by CRC diagnostic groups. Well-established microbiome CRC targets, such as Fusobacterium nucleatum, did not significantly associate with CRC diagnostic groups (healthy, adenoma and carcinoma) when controlling for these covariates. In contrast, the associations of Anaerococcus vaginalis, Dialister pneumosintes, Parvimonas micra, Peptostreptococcus anaerobius, Porphyromonas asaccharolytica and Prevotella intermedia remained robust, highlighting their future target potential. Finally, control individuals (age 22-80 years, mean 57.7 years, standard deviation 11.3) meeting criteria for colonoscopy (for example, through a positive fecal immunochemical test) but without colonic lesions are enriched for the dysbiotic Bacteroides2 enterotype, emphasizing uncertainties in defining healthy controls in cancer microbiome research. Together, these results indicate the importance of quantitative microbiome profiling and covariate control for biomarker identification in CRC microbiome studies.
Topics: Humans; Colorectal Neoplasms; Middle Aged; Feces; Female; Aged; Male; RNA, Ribosomal, 16S; Adult; Gastrointestinal Microbiome; Aged, 80 and over; Young Adult; Microbiota; Leukocyte L1 Antigen Complex
PubMed: 38689063
DOI: 10.1038/s41591-024-02963-2 -
ACS Infectious Diseases Sep 2023Changes in the oral microbiome are associated with oral squamous cell carcinoma (OSCC). Oral microbe-derived signatures have been utilized as markers of OSCC. However,...
Changes in the oral microbiome are associated with oral squamous cell carcinoma (OSCC). Oral microbe-derived signatures have been utilized as markers of OSCC. However, the structure of the oral microbiome during OSCC recurrence and biomarkers for the prediction of OSCC recurrence remains unknown. To identify OSCC recurrence-associated microbial biomarkers for the prediction of OSCC recurrence, we performed 16S rRNA amplicon sequencing on 54 oral swab samples from OSCC patients. Differences in bacterial compositions were observed in patients with vs without recurrence. We found that , , , , , , , , and were enriched in OSCC recurrence. Functional analysis of the oral microbiome showed altered functions associated with OSCC recurrence compared with nonrecurrence. A random forest prediction model was constructed with five microbial signatures including , , , , and to discriminate OSCC recurrence from original OSCC (accuracy = 0.963). Moreover, we validated the prediction model in another independent cohort (46 OSCC patients), achieving an accuracy of 0.761. We compared the accuracy of the prediction of OSCC recurrence between the five microbial signatures and two clinicopathological parameters, including resection margin and lymph node counts. The results predicted by the model with five microbial signatures showed a higher accuracy than those based on the clinical outcomes from the two clinicopathological parameters. This study demonstrated the validity of using recurrence-related microbial biomarkers, a noninvasive and effective method for the prediction of OSCC recurrence. Our findings may contribute to the prognosis and treatment of OSCC recurrence.
Topics: Humans; Mouth Neoplasms; Carcinoma, Squamous Cell; Squamous Cell Carcinoma of Head and Neck; RNA, Ribosomal, 16S; Biomarkers; Head and Neck Neoplasms
PubMed: 37565768
DOI: 10.1021/acsinfecdis.3c00269 -
Chinese Medical Journal Dec 2023Type 2 diabetes mellitus (T2DM) is an independent risk factor for colorectal cancer (CRC), and the patients with CRC and T2DM have worse survival. The human gut...
BACKGROUND
Type 2 diabetes mellitus (T2DM) is an independent risk factor for colorectal cancer (CRC), and the patients with CRC and T2DM have worse survival. The human gut microbiota (GM) is linked to the development of CRC and T2DM, respectively. However, the GM characteristics in patients with CRC and T2DM remain unclear.
METHODS
We performed fecal metagenomic and targeted metabolomics studies on 36 samples from CRC patients with T2DM (DCRC group, n = 12), CRC patients without diabetes (CRC group, n = 12), and healthy controls (Health group, n = 12). We analyzed the fecal microbiomes, characterized the composition and function based on the metagenomics of DCRC patients, and detected the short-chain fatty acids (SCFAs) and bile acids (BAs) levels in all fecal samples. Finally, we performed a correlation analysis of the differential bacteria and metabolites between different groups.
RESULTS
Compared with the CRC group, LefSe analysis showed that there is a specific GM community in DCRC group, including an increased abundance of Eggerthella , Hungatella , Peptostreptococcus , and Parvimonas , and decreased Butyricicoccus , Lactobacillus , and Paraprevotella . The metabolomics analysis results revealed that the butyric acid level was lower but the deoxycholic acid and 12-keto-lithocholic acid levels were higher in the DCRC group than other groups ( P < 0.05). The correlation analysis showed that the dominant bacterial abundance in the DCRC group ( Parvimonas , Desulfurispora , Sebaldella , and Veillonellales , among others) was negatively correlated with butyric acid, hyodeoxycholic acid, ursodeoxycholic acid, glycochenodeoxycholic acid, chenodeoxycholic acid, cholic acid and glycocholate. However, the abundance of mostly inferior bacteria was positively correlated with these metabolic acid levels, including Faecalibacterium , Thermococci , and Cellulophaga .
CONCLUSIONS
Unique fecal microbiome signatures exist in CRC patients with T2DM compared to those with non-diabetic CRC. Alterations in GM composition and SCFAs and secondary BAs levels may promote CRC development.
Topics: Humans; Gastrointestinal Microbiome; Diabetes Mellitus, Type 2; Microbiota; Bacteria; Fatty Acids, Volatile; Colorectal Neoplasms; Butyrates; Feces
PubMed: 36959686
DOI: 10.1097/CM9.0000000000002421 -
Microorganisms Oct 2023The effectiveness of fecal microbiota transplantation (FMT) in ulcerative colitis (UC) remains unclear. This study aimed to investigate the feasibility and effectiveness...
The effectiveness of fecal microbiota transplantation (FMT) in ulcerative colitis (UC) remains unclear. This study aimed to investigate the feasibility and effectiveness of serial fecal infusions via colonoscopy in patients with active UC. Subjects with mild-to-moderate UC received three consecutive fecal infusions via colonoscopy. A control population with the same baseline features receiving Infliximab treatment was enrolled. Adverse events and clinical, endoscopic, and microbial outcomes were investigated. Nineteen patients with mildly-to-moderately active UC were enrolled. Clinical response was obtained in six patients at week 2, in eight at week 6, and in nine at week 12. Clinical response was maintained in eight patients at week 24. Endoscopic remission at week 12 was reached in six patients. In the control population, 13/19 patients achieved clinical response at week 6, and 10/19 patients maintained clinical response after 6 months. Microbiota richness was higher in responders compared with the non-responders. , , and were higher in non-responders, while , , , and were higher in responders at all timepoints. Serial FMT infusions appear to be feasible, safe, and effective in UC patients, with a potential role in inducing and maintaining clinical response. Specific bacteria predict the response to FMT.
PubMed: 37894194
DOI: 10.3390/microorganisms11102536 -
Molecular Oncology May 2024Oral and intestinal samples from a cohort of 93 colorectal cancer (CRC) patients and 30 healthy controls (non-CRC) were collected for microbiome analysis. Saliva (28...
Oral and intestinal samples from a cohort of 93 colorectal cancer (CRC) patients and 30 healthy controls (non-CRC) were collected for microbiome analysis. Saliva (28 non-CRC and 94 CRC), feces (30 non-CRC and 97 CRC), subgingival fluid (20 CRC), and tumor tissue samples (20 CRC) were used for 16S metabarcoding and/or RNA sequencing (RNAseq) approaches. A differential analysis of the abundance, performed with the ANCOM-BC package, adjusting the P-values by the Holm-Bonferroni method, revealed that Parvimonas was significantly over-represented in feces from CRC patients (P-value < 0.001) compared to healthy controls. A total of 11 Parvimonas micra isolates were obtained from the oral cavity and adenocarcinoma of CRC patients. Genome analysis identified a pair of isolates from the same patient that shared 99.2% identity, demonstrating that P. micra can translocate from the subgingival cavity to the gut. The data suggest that P. micra could migrate in a synergistic consortium with other periodontal bacteria. Metatranscriptomics confirmed that oral bacteria were more active in tumor than in non-neoplastic tissues. We suggest that P. micra could be considered as a CRC biomarker detected in non-invasive samples such as feces.
Topics: Humans; Colorectal Neoplasms; Male; Female; Adenocarcinoma; Middle Aged; Aged; Mouth; Feces; RNA, Ribosomal, 16S; Gingiva; Saliva; Peptostreptococcus; Firmicutes
PubMed: 37558206
DOI: 10.1002/1878-0261.13506