Gut Microbiota and Depressive Symptoms at the End of CRT for Rectal Cancer: A Cross-Sectional Pilot Study

Background. The role of alterations in gut microbiota composition (termed dysbiosis) has been implicated in the pathobiology of depressive symptoms; however, evidence remains limited. This cross-sectional pilot study is aimed at exploring whether depressive symptom scores changed during neoadjuvant chemotherapy and radiation therapy to treat rectal cancer, and if gut microbial taxa abundances and predicted functional pathways correlate with depressive symptoms at the end of chemotherapy and radiation therapy. Methods. 40 newly diagnosed rectal cancer patients (ages 28-81; 23 males) were assessed for depressive symptoms using the Hamilton Rating Scale for Depression (HAM-D) and provided stool samples for 16S rRNA sequencing. Gut microbiome data were analyzed using QIIME2, and correlations and regression analyses were performed in R. Results. Participants had significantly higher depressive symptoms at the end as compared to before CRT. The relative abundances of Gemella, Bacillales Family XI, Actinomyces, Streptococcus, Lactococcus, Weissella, and Leuconostocaceae were positively correlated (Spearman’s rho = 0.42 to 0.32), while Coprobacter, Intestinibacter, Intestimonas, Lachnospiraceae, Phascolarctobacterium, Ruminiclostridium, Ruminococcaceae (UCG-005 and uncultured), Tyzzerella, and Parasutterella (Spearman’s rho = − 0.43 to − 0.31 ) were negatively correlated with HAM-D scores. Of the 14 predicted MetaCyc pathways that correlated with depressive symptom scores at the end of CRT, 11 (79%) were associated with biosynthetic pathways. Conclusions. Significant bacterial taxa and predicted functional pathways correlated with depressive symptoms at the end of chemotherapy and radiation therapy for rectal cancer which warrants further examination and replication of our findings.

Integration of Diverse Transcriptomics Datasets using Random Forest to Predict Universal Functional Pathways in Tfr Cells

Motivation T follicular regulatory (Tfr) cells are a specialized cell subset that controls humoral immunity. Despite a number of individual transcriptomic studies on these cells, core functional pathways have been difficult to uncover due to the substantial transcriptional overlap of these cells with other effector cell types, as well as transcriptional changes occurring due to disease settings. Developing a core transcriptional module for Tfr cells that integrates multiple cell type comparisons as well as diverse disease settings will allow a more accurate prediction of functional pathways. Researchers studying allergic reactions, immune responses to vaccines, autoimmunity and cancer could use this gene set to better understand the roles of Tfr cells in controlling disease progression. Additional cell types beyond Tfr cells that have similar features of transcriptomic complexity within diverse disease settings may also be studied using similar approaches. High-throughput sequencing technologies allow the generation of large datasets that require specific tools to best interpret the data. The development of a core transcriptional module for Tfr cells will allow investigators to determine if Tfr cells may have functional roles within their biological systems with little knowledge of Tfr biology. With this work, we have addressed the need of core gene modules to define specific subsets of immune cells. Results We introduce an integrated "core Tfr cell gene module" that can be incorporated into GSEA analysis using various input sizes. The integrated core Tfr gene module was built using transcriptomic studies in Tfr cells from several different tissues, disease settings, and cell type comparisons. Random forest was used to integrate the transcriptomic studies to generate the core gene module. A GSEA gene set was formulated from the integrated core Tfr gene module for incorporation into end-user friendly GSEA. The gene sets are presented along with random genes taken from the GTEX data set and are presented as GMT files. The user can upload the gene set to the GSEA website or any gene set tool which takes GMT files. We also present the full results of the model including p-values calculated by random forest. This allows the user to choose a p-value cutoff that is most appropriate for the experimental setting.

The Relationship Between Osteoporosis and Intestinal Microbes in the Henan Province of China

Osteoporosis (OP) is a chronic disease in the elderly, and China is entering an aging demographic trend. In recent years, increasing evidence has demonstrated that probiotics can treat osteoporosis. This study aimed to explore the relevant mechanisms and to validate the beneficial effect on osteoporosis by high-throughput metagenome-wide gene sequencing in humans. In this study, compared with controls, several species had altered abundances, and specific functional pathways were found in the OP group. At the species level, the species that had increased in OP individuals were positively correlated to bone resorption markers and negatively correlated to 25-OH-D3 and bone formation markers, with Streptococcus sanguinis showing the strongest relevance, followed by Streptococcus gordonii, Actinomyces odontolyticus, and Olsenella unclassified. Additionally, Actinomyces graevenitzii, enriched in the OP group, was positively correlated to inflammation indicators that included white blood cell (WBC), neutrophil count (NEC), and the neutrophil-to-lymphocyte ratio (NLR) (p < 0.05). Conversely, the levels of Akkermansia muciniphila, Bacteroides eggerthii, Bacteroides fragilis, Bacteroides uniformis, and Butyricimonas synergistic were increased in the control group, which had a negative correlation with bone resorption markers and positive correlation with bone formation markers and 25-OH-D3. Additionally, Bacteroides fragilis had a negative correlation with inflammation indicators (WBC, NEC, and NLR) and the above pathways (p < 0.05). Functional prediction revealed that 106 metabolic pathways, enriched in the OP group, were significantly higher than in the control group (p < 0.05). In particular, pathways related to LPS biosynthesis, phytate degradation, lactate acid, and ethanol fermentation were more abundant in the OP group than in the control and were positively related to WBC and NEC. Taken together, several species with altered abundances and specific functional pathways were found in OP individuals. The role of phytases in OP provides novel epidemiological evidence to elucidate the underlying microbiota-relevant mechanisms in bone mineralization and should be explored further.

Whole-Blood Methylation Analysis Reveals Respiratory Environmental Functional Pathways Involved in Severity Following SARS-CoV-2 Infection

SARS-CoV-2 causes a severe inflammatory syndrome called COVID-19 that primarily affects the lungs leading, in many cases, to bilateral pneumonia, severe dyspnea and in ~5% of the cases, death. The mechanisms through which this occurs are still being elucidated. A strong relationship between COVID-19 progression and autoimmune disorder pathogenesis has been identified as an exacerbated interferon immune response or an inflammatory condition mediated by an increase of pro-inflammatory cytokine production, among other. DNA methylation is known to regulate immune response processes, thus COVID-19 progression might be also conditioned by DNA methylation changes not studied in depth, yet. Thus, here an epigenome-wide DNA methylation analysis combined with DNA genotyping for 101 and 473 SARS-CoV-2 negative and positive lab tested individuals, respectively, from two different clinical centers is presented in order to evaluate the implications of the epigenetic regulation in the course of COVID-19 disease. The results reveal the existence of an epigenome regulation of functional pathways associated with the COVID-19 progression, such as innate interferon responses, hyperactivation of B and T lymphocytes, phagocytosis and innate C-type lectin DC-SIGN. These DNA methylation changes were found to be regulated by genetic loci associated with COVID-19 susceptibility and autoimmune disease. In mild COVID-19 patients hypomethylation of CpGs regulating genes within the AKT signaling pathway, and the hypermethylation of a group of CpGs related to environmental traits regulating IL-6 expression via the transcription factor CEBP, discriminate these individuals from those who develop the most critical outcomes of the disease. Thus, the analysis points out to an environmental contribution that mediated by DNA methylation changes in SARS-CoV-2 positive patients, might be playing a role in triggering the cytokine storm described in the most severe cases. In addition, important differences were found in terms of epigenetic regulation between severe and mild cases when compared with systemic autoimmune diseases.

Screening of key biomarkers of tendinopathy based on bioinformatics and machine learning algorithms

Tendinopathy is a complex multifaceted tendinopathy often associated with overuse and with its high prevalence resulting in significant health care costs. At present, the pathogenesis and effective treatment of tendinopathy are still not sufficiently elucidated. The purpose of this research is to intensely explore the genes, functional pathways, and immune infiltration characteristics of the occurrence and development of tendinopathy. The gene expression profile of GSE106292, GSE26051 and GSE167226 are downloaded from GEO (NCBI comprehensive gene expression database) and analyzed by WGCNA software bag using R software, GSE26051, GSE167226 data set is combined to screen the differential gene analysis. We subsequently performed gene enrichment analysis of Gene Ontology (GO) and "Kyoto Encyclopedia of Genes and Genomes" (KEGG), and immune cell infiltration analysis. By constructing the LASSO regression model, Support vector machine (SVM-REF) and Gaussian mixture model (GMMs) algorithms are used to screen, to identify early diagnostic genes. We have obtained a total of 171 DEGs through WGCNA analysis and differentially expressed genes (DEGs) screening. By GO and KEGG enrichment analysis, it is found that these dysregulated genes were related to mTOR, HIF-1, MAPK, NF-κB and VEGF signaling pathways. Immune infiltration analysis showed that M1 macrophages, activated mast cells and activated NK cells had infiltration significance. After analysis of THE LASSO SVM-REF and GMMs algorithms, we found that the gene MACROD1 may be a gene for early diagnosis. We identified the potential of tendon disease early diagnosis way and immune gene regulation MACROD1 key infiltration characteristics based on comprehensive bioinformatics analysis. These hub genes and functional pathways may as early biomarkers of tendon injuries and molecular therapy level target is used to guide drug and basic research.

Comprehensive profiles and diagnostic value of menopausal-specific gut microbiota in premenopausal breast cancer

In Western countries, breast cancer tends to occur in older postmenopausal women. However, in Asian countries, the proportion of younger premenopausal breast cancer patients is increasing. Increasing evidence suggests that the gut microbiota plays a critical role in breast cancer. However, studies on the gut microbiota in the context of breast cancer have mainly focused on postmenopausal breast cancer. Little is known about the gut microbiota in the context of premenopausal breast cancer. This study aimed to comprehensively explore the gut microbial profiles, diagnostic value, and functional pathways in premenopausal breast cancer patients. Here, we analyzed 267 breast cancer patients with different menopausal statuses and age-matched female controls. The α-diversity was significantly reduced in premenopausal breast cancer patients, and the β-diversity differed significantly between breast cancer patients and controls. By performing multiple analyses and classification, 14 microbial markers were identified in the different menopausal statuses of breast cancer. Bacteroides fragilis was specifically found in young women of premenopausal statuses and Klebsiella pneumoniae in older women of postmenopausal statuses. In addition, menopausal-specific microbial markers could exhibit excellent discriminatory ability in distinguishing breast cancer patients from controls. Finally, the functional pathways differed between breast cancer patients and controls. Our findings provide the first evidence that the gut microbiota in premenopausal breast cancer patients differs from that in postmenopausal breast cancer patients and shed light on menopausal-specific microbial markers for diagnosis and investigation, ultimately providing a noninvasive approach for breast cancer detection and a novel strategy for preventing premenopausal breast cancer.

The effects of removing dead bacteria by propidium monoazide on the profile of salivary microbiome

Background Oral microbiome played an important role in maintaining healthy state and might exhibit certain changes under circumstances of diseases. However, current microbiological research using sequencing techniques did not regard dead bacteria as a separate part, causing findings based on subsequent analyses on dynamic equilibrium and functional pathways of microbes somewhat questionable. Since treatment by propidium monoazide (PMA) was able to remove dead bacteria effectively, it would be worth studying how the sequencing results after PMA treatment differed from those focusing on the whole microbiota. Methods Unstimulated whole saliva samples were obtained from 18 healthy people from 3 age groups (children, adults, and the elderly). After removal of dead bacteria by propidium monoazide (PMA), changes in the profile of salivary microbiome were detected using 16S rRNA sequencing technology, and differences among age groups were compared subsequently. Results Dead bacteria accounted for nearly a half of the whole bacteria flora in saliva, while freezing had little effect on the proportion of deaths. After treatment with PMA, the numbers of OTUs reduced by 4.4–14.2%, while the Shannon diversity indices decreased significantly (P < 0.01). Only 35.2% of positive and 6.1% of negative correlations were found to be shared by the whole microbiota and that with dead bacteria removed. Differences in significantly changed OTUs and functional pathways among different age groups were also observed between the group of PMA and the control. Conclusions It was necessary to take the influence of living state of bacteria into account in analytic studies of salivary microbiome.

Analyzing Type 2 Diabetes Associations with the Gut Microbiome in Individuals from Two Ethnic Backgrounds Living in the Same Geographic Area

It is currently unknown whether associations between gut microbiota composition and type 2 diabetes (T2D) differ according to the ethnic background of individuals. Thus, we studied these associations in participants from two ethnicities characterized by a high T2D prevalence and living in the same geographical area, using the Healthy Life In Urban Settings (HELIUS) study. We included 111 and 128 T2D participants on metformin (Met-T2D), 78 and 49 treatment-naïve T2D (TN-T2D) participants, as well as a 1:1 matched group of healthy controls from, respectively, African Surinamese and South-Asian Surinamese descent. Fecal microbiome profiles were obtained through 16S rRNA gene sequencing. Univariate and machine learning analyses were used to explore the associations between T2D and the composition and function of the gut microbiome in both ethnicities, comparing Met-T2D and TN-T2D participants to their respective healthy control. We found a lower α-diversity for South-Asian Surinamese TN-T2D participants but no significant associations between TN-T2D status and the abundance of bacterial taxa or functional pathways. In African Surinamese participants, we did not find any association between TN-T2D status and the gut microbiome. With respect to Met-T2D participants, we identified several bacterial taxa and functional pathways with a significantly altered abundance in both ethnicities. More alterations were observed in South-Asian Surinamese. Some altered taxa and pathways observed in both ethnicities were previously related to metformin use. This included a strong negative association between the abundance of Romboutsia and Met-T2D status. Other bacterial taxa were consistent with previous observations in T2D, including reduced butyrate producers such as Anaerostipes hadrus. Hence, our results highlighted both shared and unique gut microbial biomarkers of Met-T2D in individuals from different ethnicities but living in the same geographical area. Future research using higher-resolution shotgun sequencing is needed to clarify the role of ethnicity in the association between T2D and gut microbiota composition.

Integrative Analysis of m6A Regulator-Mediated RNA Methylation Modification Patterns and Immune Characteristics in Lupus Nephritis

BackgroundThere is growing evidence to demonstrate that the epigenetic regulation of immune characteristics, especially for N6-methyladenosine (m6A) RNA methylation. However, how m6A methylation is involved in lupus nephritis (LN) is still unclear. This study aimed to determine the role of m6A RNA methylation and their association with the immune microenvironment in LN.MethodsIn total, 87 glomeruli (73 LN, 14 living healthy donors), 110 tubulointerstitium (95 LN, 15 living healthy donors), and 21 kidney whole tissue samples (14 LN, 7 controls) were included in our research to evaluate the expression levels of m6A regulators. CIBERSORT was used to assess the abundance of infiltrating immunocytes. The m6A regulator gene signature for LN was identified using LASSO-logistic regression and verified with external data. Consensus clustering algorithms were used for the unsupervised cluster analysis of m6A modification patterns in LN. Single-sample gene-set enrichment analysis and gene set variation analysis algorithms were employed to assess the activity of immune responses and other functional pathways. Weighted gene co-expression network analysis and protein-protein interaction networks were used to identify m6A methylation markers. Lastly, the Nephroseq V5 tool was used to analyze the correlation between m6A markers and renal function.ResultsWe found that the expression of m6A regulators was more significantly different in the glomeruli in LN compared with tubulointerstitium and whole kidney tissue. We established an m6A regulator signature, comprised of METTL3, WTAP, YTHDC2, YTHDF1, FMR1, and FTO, that can easily distinguish LN and healthy individuals. Two distinct m6A modification patterns based on 18 m6A regulators were determined, with significant differences in m6A regulator expression, immune microenvironment, biological functional pathways, and clinical characteristics. Activated NK cells, most immune responses, and HLA genes had strong correlations with m6A regulators. Seven m6A markers were identified and demonstrated a meaningful correlation with GFR, indicating that they are potential prognostic biomarkers.ConclusionThis study emphasized that m6A RNA methylation and the immune microenvironment are closely linked in LN. A better understanding of m6A modification patterns provide a basis for the development of novel therapeutic options for LN.