A comprehensive review for gut microbes: technologies, interventions, metabolites and diseases

Microbial diversity characterizations, associated pathogenesis and antimicrobial resistance profiling of Najafgarh drain

The Najafgarh drain plays a significant role in the pollution of the Yamuna River, accounting for 40% of the total pollution. Therefore, it is crucial to investigate and analyze the microbial diversity, metabolic functional capacity, and antibiotic resistance genes (ARGs) present in the Najafgarh drain. Additionally, studying the water quality and its relationship with the proliferation of microorganisms in the drain is of utmost importance. Results obtained confirmed the deteriorated water quality as physico-chemical parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), and total suspended solids (TSS) in the range of 125-140, 400-460, 0-0.2, 25-140.4 mg/l respectively violated the standard permissible national and global standards. In addition, the next generation sequencing (NGS) analysis confirm the presence of genus such as Thauera, Arcobacter, Pseudomonas, Geobacter, Dechloromonas, Tolumonas, Sulfurospirullum, Desulfovibrio, Aeromonas, Bacteroides, Prevotella, Cloacibacterium, Bifidobacterium, Clostridium etc. along with 864 ARGs in the wastewater obtained from the Najafgarh drain. Findings confirm that the pathogenic species reported from this dataset possess severe detrimental impact on faunal and human health. Further, Pearson's r correlation analysis indicated that environmental variables, mainly total dissolved solids (TDS) and chemical oxygen demand (COD), play a pivotal role in driving microbial community structure of this heavily polluted drain. Thus, the poor water quality, presence of a microbial nexus, pathogenic markers, and ARGs throughout this drain confirmed that it would be one potential contributor to the dissemination of disease-causing agents (pathogens) to the household and drinking water supplies in the near future.

Lactic acid bacteria-derived exopolysaccharide: Formation, immunomodulatory ability, health effects, and structure-function relationship

Exopolysaccharides (EPSs) synthesized by lactic acid bacteria (LAB) have implications for host health and act as food ingredients. Due to the variability of LAB-EPS (lactic acid bacteria-derived exopolysaccharide) gene clusters, especially the glycosyltransferase genes that determine monosaccharide composition, the structure of EPS is very rich. EPSs are synthesized by LAB through the extracellular synthesis pathway and the Wzx/Wzy-dependent pathway. LAB-EPS has a strong immunomodulatory ability. The EPSs produced by different genera of LAB, especially Lactobacillus, Leuconostoc, and Streptococcus, have different immunomodulatory abilities because of their specific structures. LAB-EPS possesses other health effects, including antitumor, antioxidant, intestinal barrier repair, antimicrobial, antiviral, and cholesterol-lowering activities. The bioactivities of LAB-EPS are tightly related to their structures such us monosaccharide composition, glycosidic bonds, and molecular weight (MW). For the excellent physicochemical property, LAB-EPS acts as product improvers in dairy, bakery food, and meat in terms of stability, emulsification, thickening, and gelling. We systematically summarize the detailed process of EPS from synthesis to application, with emphasis on physiological mechanisms of EPS, and specific structure-function relationship, which provides theoretical support for the potential commercial value in the pharmaceutical, chemical, food, and cosmetic industries.

The Microbiome and Mental Health Across the Lifespan

INTRODUCTION

The combined genetic material of the microorganisms in the human body, known as the microbiome, is being increasingly recognized as a major determinant of human health and disease. Although located predominantly on mucosal surfaces, these microorganisms have profound effects on brain functioning through the gut-brain axis.

METHOD

The content of the chapter is based on a study group session at the annual meeting of the American College of Neuropsychopharmacology (ACNP). The objective was to discuss the emerging relationship between the human microbiome and mental health as relevant to ACNP's interests in developing and evaluating novel neuropsychiatric treatment strategies. The focus is on specific brain disorders, such as schizophrenia, substance use, and Alzheimer's disease, as well as on broader clinical issues such as suicidality, loneliness and wisdom in old age, and longevity.

RESULTS

Studies of schizophrenia indicate that the microbiome of individuals with this disorder differs from that of non-psychiatric comparison groups in terms of diversity and composition. Differences are also found in microbial metabolic pathways. An early study in substance use disorders found that individuals with this disorder have lower levels of beta diversity in their oral microbiome than a comparison group. This measure, along with others, was used to distinguish individuals with substance use disorders from controls. In terms of suicidality, there is preliminary evidence that persons who have made a suicide attempt differ from psychiatric and non-psychiatric comparison groups in measures of beta diversity. Exploratory studies in Alzheimer's disease indicate that gut microbes may contribute to disease pathogenesis by regulating innate immunity and neuroinflammation and thus influencing brain function. In another study looking at the microbiome in older adults, positive associations were found between wisdom and alpha diversity and negative associations with subjective loneliness. In other studies of older adults, here with a focus on longevity, individuals with healthy aging and unusually long lives had an abundance of specific microorganisms which distinguished them from other individuals.

DISCUSSION

Future studies would benefit from standardizing methods of sample collection, processing, and analysis. There is also a need for the standardized collection of relevant demographic and clinical data, including diet, medications, cigarette smoking, and other potentially confounding factors. While still in its infancy, research to date indicates a role for the microbiome in mental health disorders and conditions. Interventions are available which can modulate the microbiome and lead to clinical improvements. These include microbiome-altering medications as well as probiotic microorganisms capable of modulating the inflammation in the brain through the gut-brain axis. This research holds great promise in terms of developing new methods for the prevention and treatment of a range of human brain disorders.

The effect of FMT and vitamin C on immunity-related genes in antibiotic-induced dysbiosis in mice

Antibiotics are double-edged swords. Although antibiotics are used to inhibit pathogenic bacteria, they also run the risk of destroying some of the healthy bacteria in our bodies. We examined the effect of penicillin on the organism through a microarray dataset, after which 12 genes related to immuno-inflammatory pathways were selected by reading the literature and validated using neomycin and ampicillin. The expression of genes was measured using qRT-PCR. Several genes were significantly overexpressed in antibiotic-treated mice, including CD74 and SAA2 in intestinal tissues that remained extremely expressed after natural recovery. Moreover, transplantation of fecal microbiota from healthy mice to antibiotic-treated mice was made, where GZMB, CD3G, H2-AA, PSMB9, CD74, and SAA1 were greatly expressed; however, SAA2 was downregulated and normal expression was restored, and in liver tissue, SAA1, SAA2, SAA3 were extremely expressed. After the addition of vitamin C, which has positive effects in several aspects, to the fecal microbiota transplantation, in the intestinal tissues, the genes that were highly expressed after the fecal microbiota transplantation effectively reduced their expression, and the unaffected genes remained normally expressed, but the CD74 gene remained highly expressed. In liver tissues, normally expressed genes were not affected, but the expression of SAA1 was reduced and the expression of SAA3 was increased. In other words, fecal microbiota transplantation did not necessarily bring about a positive effect of gene expression restoration, but the addition of vitamin C effectively reduced the effects of fecal microbiota transplantation and regulated the balance of the immune system.

Can habitual tea drinking be an effective approach against age-related neurodegenerative cognitive disorders: A systematic review and meta-analysis of epidemiological evidence

Our present knowledge about the efficacy of tea consumption in improving age-related cognitive disorders is incomplete since previous epidemiological studies provide inconsistent evidence. This unified systematic review and meta-analysis based on updated epidemiological cohort studies and randomized controlled trials (RCTs) evidence aimed to overcome the limitations of previous reviews by examining the efficacy of distinct types of tea consumption. PubMed, Embase, and MEDLINE were searched up to May 20, 2022, and 23 cohorts and 12 cross-sectional studies were included. Random-effects meta-analyses were conducted to obtain pooled RRs or mean differences with 95% CIs. The pooled RRs of the highest versus lowest tea consumption categories were 0.81 (95% CIs: 0.75-0.88) and 0.69 (95% CIs: 0.61-0.77), respectively. The pooled mean difference of four included RCTs revealed a beneficial effect of tea on cognitive dysfunction (MMSE ES: 1.03; 95% CI, 0.14-1.92). Subgroup analyses further demonstrated that green and black tea intake was associated with a lower risk of cognitive disorders in eastern countries, especially in women. The evidence quality was generally low to moderate. The present review provides insight into whether habitual tea consumption can be an effective approach against age-related neurodegenerative cognitive disorders and summarizes potential mechanisms based on currently published literature.

gutMDisorder v2.0: a comprehensive database for dysbiosis of gut microbiota in phenotypes and interventions

Gut microbiota plays a significant role in maintaining host health, and conversely, disorders potentially lead to dysbiosis, an imbalance in the composition of the gut microbial community. Intervention approaches, such as medications, diets, and several others, also alter the gut microbiota in either a beneficial or harmful direction. In 2020, the gutMDisorder was developed to facilitate researchers in the investigation of dysbiosis of gut microbes as occurs in various disorders as well as with therapeutic interventions. The database has been updated this year, following revision of previous publications and newly published reports to manually integrate confirmed associations under multitudinous conditions. Additionally, the microbial contents of downloaded gut microbial raw sequencing data were annotated, the metadata of the corresponding hosts were manually curated, and the interactive charts were developed to enhance visualization. The improvements have assembled into gutMDisorder v2.0, a more advanced search engine and an upgraded web interface, which can be freely accessed via http://bio-annotation.cn/gutMDisorder/.

Mechanisms Underlying the Interaction Between Chronic Neurological Disorders and Microbial Metabolites via Tea Polyphenols Therapeutics

The number of hydroxyl groups and existence of characteristic structural groups in tea polyphenols (TP) make them have antioxidant activity, which gives TP anti-inflammatory effects, toward protecting the intestinal flora and brain neurons. Host-associated microbial metabolites are emerging as dominant modifiers of the central nervous system. As yet, the investigations on host-microbiota crosstalking remain challenging, studies focusing on metabolites such as serotonin, short-chain fatty acids, and others have pinpointed multiple actionable signaling pathways relevant to host health. However, there are still complexities and apparent limitations inherent in transforming complex human diseases to corresponding animal models. Here, we choose to discuss several intestinal metabolites with research value, as crucial areas for assessing TP-mediated chronic brain diseases interactions with microbial.

Effect of Different Dietary Regimes on the Gut Microbiota and Fecal Metabolites of Père David’s Deer

Simple Summary

Père David’s deer is native to the middle and lower reaches of the Yangtze River and the Yellow River in China. However, the wild population became extinct in China around 1900. In 1986, 39 Père David’s deer were reintroduced into Dafeng. Up until now, its wild population has reached 2658, with a total of 6119 in 2021. At present, due to the continuous increase in the population, the repeated grazing on the same plants by the Père David’s deer has affected the re-growth of plants, which has led to insufficient natural food. Therefore, feeding supplement with silage is necessary. As a key nutritional factor, diet is the most important for the gut microbiota and metabolites of wild animals. In order to determine the effect of different dietary patterns on the nutrition and health of Père David’s deer in Dafeng Reserve in spring, we conducted a comprehensive analysis of Père David’s deer feces by UPLC-MS/MS and 16S rRNA gene sequencing to reveal its intestinal chemical environment and the differences in the fecal microbiome. Altogether, our data explored the significant changes in the gut microbiota and metabolic pathways during the transition from full silage to a combination diet with silage and plant in spring. These data provided important information to make more reasonable measures for Père David’s deer’s protection.

Abstract

A deep understanding of the effect of seasonal dietary changes on the nutrition and health of Père David’s deer in Dafeng Reserve will contribute greatly to Père David’s deer’s protection. In this reserve, there were three seasonal dietary regimes: feeding on naturally occurring plants (PLANT diet), silage (SILAGE diet), and a combination of natural plants and silage (COMB diet). To some extent, the COMB diet reflects the seasonal transition from silage to the all-natural plant diet, especially in early spring. However, little is known regarding the gut microbiota changes and metabolic consequences under the COMB diet. Based on 16S rRNA sequencing and ultra-high performance liquid chromatography combined with tandem mass spectrometry, the gut microbiota and fecal metabolites of Père David’s deer under these three diets were compared. Results showed the alpha diversity of the gut microbiota was significantly lower under the COMB diet compared to either the SILAGE or PLANT diets. Although no significant changes were observed in the core phyla, Firmicutes and Bacteroidetes, among the three dietary regimes, a significant lower abundance of several other phyla (Spirochaetes, Melainabacteria, Proteobacteria, and Verrucobacteria) was observed in the COMB diet compared to the SILAGE diet. A greater number of fecal metabolite differences was identified between the COMB and SILAGE or COMB and PLANT diets than between the SILAGE and PLANT diets, suggesting that the COMB diet had more of an effect on the metabolism of Père David’s deer. The integrated pathway analysis showed that several metabolic pathways were significantly affected by the different dietary regimes, such as tryptophan metabolism, vitamin metabolism, and the platelet activation pathways. These metabolic changes reflect the responses and adaptations of Père David’s deer to different diets. Taken overall, our data reveal the difference in the gut microbiota and metabolic pathways of Père David’s deer under three dietary regimes in Dafeng Reserve, which provides important information for Père David’s deer conservation.

Alterations of the Gut Microbiota in Patients With Severe Chronic Heart Failure

Chronic heart failure (CHF) is the final outcome of almost all forms of cardiovascular diseases, remaining the main cause of mortality worldwide. Accumulating evidence is focused on the roles of gut microbial community in cardiovascular disease, but few studies have unveiled the alterations and further directions of gut microbiota in severe CHF patients. Aimed to investigate this deficiency, fecal samples from 29 CHF patients diagnosed with NYHA Class III-IV and 30 healthy controls were collected and then analyzed using bacterial 16S rRNA gene sequencing. As a result, there were many significant differences between the two groups. Firstly, the phylum Firmicutes was found to be remarkably decreased in severe CHF patients, and the phylum Proteobacteria was the second most abundant phyla in severe CHF patients instead of phylum Bacteroides strangely. Secondly, the α diversity indices such as chao1, PD-whole-tree and Shannon indices were significantly decreased in the severe CHF versus the control group, as well as the notable difference in β-diversity between the two groups. Thirdly, our result revealed a remarkable decrease in the abundance of the short-chain fatty acids (SCFA)-producing bacteria including genera Ruminococcaceae UCG-004, Ruminococcaceae UCG-002, Lachnospiraceae FCS020 group, Dialister and the increased abundance of the genera in Enterococcus and Enterococcaceae with an increased production of lactic acid. Finally, the alternation of the gut microbiota was presumably associated with the function including Cell cycle control, cell division, chromosome partitioning, Amino acid transport and metabolism and Carbohydrate transport and metabolism through SCFA pathway. Our findings provide the direction and theoretical knowledge for the regulation of gut flora in the treatment of severe CHF.

gutMGene: a comprehensive database for target genes of gut microbes and microbial metabolites

gutMGene (http://bio-annotation.cn/gutmgene), a manually curated database, aims at providing a comprehensive resource of target genes of gut microbes and microbial metabolites in humans and mice. Metagenomic sequencing of fecal samples has identified 3.3 × 10⁶ non-redundant microbial genes from up to 1500 different species. One of the contributions of gut microbiota to host biology is the circulating pool of bacterially derived small-molecule metabolites. It has been estimated that 10% of metabolites found in mammalian blood are derived from the gut microbiota, where they can produce systemic effects on the host through activating or inhibiting gene expression. The current version of gutMGene documents 1331 curated relationships between 332 gut microbes, 207 microbial metabolites and 223 genes in humans, and 2349 curated relationships between 209 gut microbes, 149 microbial metabolites and 544 genes in mice. Each entry in the gutMGene contains detailed information on a relationship between gut microbe, microbial metabolite and target gene, a brief description of the relationship, experiment technology and platform, literature reference and so on. gutMGene provides a user-friendly interface to browse and retrieve each entry using gut microbes, disorders and intervention measures. It also offers the option to download all the entries and submit new experimentally validated associations.

Deep-4mCW2V: A sequence-based predictor to identify N4-methylcytosine sites in Escherichia coli

N4-methylcytosine (4mC) is a type of DNA modification which could regulate several biological progressions such as transcription regulation, replication and gene expressions. Precisely recognizing 4mC sites in genomic sequences can provide specific knowledge about their genetic roles. This study aimed to develop a deep learning-based model to predict 4mC sites in the Escherichia coli. In the model, DNA sequences were encoded by word embedding technique 'word2vec'. The obtained features were inputted into 1-D convolutional neural network (CNN) to discriminate 4mC sites from non-4mC sites in Escherichia coli genome. The examination on independent dataset showed that our model could yield the overall accuracy of 0.861, which was about 4.3% higher than the existing model. To provide convenience to scholars, we provided the data and source code of the model which can be freely download from https://github.com/linDing-groups/Deep-4mCW2V.

Prioritizing Disease-Related Microbes Based on the Topological Properties of a Comprehensive Network

Many microbes are parasitic within the human body, engaging in various physiological processes and playing an important role in human diseases. The discovery of new microbe-disease associations aids our understanding of disease pathogenesis. Computational methods can be applied in such investigations, thereby avoiding the time-consuming and laborious nature of experimental methods. In this study, we constructed a comprehensive microbe-disease network by integrating known microbe-disease associations from three large-scale databases (Peryton, Disbiome, and gutMDisorder), and extended the random walk with restart to the network for prioritizing unknown microbe-disease associations. The area under the curve values of the leave-one-out cross-validation and the fivefold cross-validation exceeded 0.9370 and 0.9366, respectively, indicating the high performance of this method. Despite being widely studied diseases, in case studies of inflammatory bowel disease, asthma, and obesity, some prioritized disease-related microbes were validated by recent literature. This suggested that our method is effective at prioritizing novel disease-related microbes and may offer further insight into disease pathogenesis.

Identification of Causal Genes of COVID-19 Using the SMR Method

Since the first report of COVID-19 in December 2019, more than 100 million people have been infected with SARS-CoV-2. Despite ongoing research, there is still limited knowledge about the genetic causes of COVID-19. To resolve this problem, we applied the SMR method to analyze the genes involved in COVID-19 pathogenesis by the integration of multiple omics data. Here, we assessed the SNPs associated with COVID-19 risk from the GWAS data of Spanish and Italian patients and lung eQTL data from the GTEx project. Then, GWAS and eQTL data were integrated by summary-data-based (SMR) methods using SNPs as instrumental variables (IVs). As a result, six protein-coding and five non-protein-coding genes regulated by nine SNPs were identified as significant risk factors for COVID-19. Functional analysis of these genes showed that UQCRH participates in cardiac muscle contraction, PPA2 is closely related to sudden cardiac failure (SCD), and OGT, as the interacting gene partner of PANO1, is associated with neurological disease. Observational studies show that myocardial damage, SCD, and neurological disease often occur in COVID-19 patients. Thus, our findings provide a potential molecular mechanism for understanding the complications of COVID-19.

Dysbiosis of Gut Microbiota in Patients With Acute Myocardial Infarction

Acute myocardial infarction (AMI) continues as the main cause of morbidity and mortality worldwide. Interestingly, emerging evidence highlights the role of gut microbiota in regulating the pathogenesis of coronary heart disease, but few studies have systematically assessed the alterations and influence of gut microbiota in AMI patients. As one approach to address this deficiency, in this study the composition of fecal microflora was determined from Chinese AMI patients and links between gut microflora and clinical features and functional pathways of AMI were assessed. Fecal samples from 30 AMI patients and 30 healthy controls were collected to identify the gut microbiota composition and the alterations using bacterial 16S rRNA gene sequencing. We found that gut microflora in AMI patients contained a lower abundance of the phylum Firmicutes and a slightly higher abundance of the phylum Bacteroidetes compared to the healthy controls. Chao1 (P = 0.0472) and PD-whole-tree (P = 0.0426) indices were significantly lower in the AMI versus control group. The AMI group was characterized by higher levels of the genera Megasphaera, Butyricimonas, Acidaminococcus, and Desulfovibrio, and lower levels of Tyzzerella 3, Dialister, [Eubacterium] ventriosum group, Pseudobutyrivibrio, and Lachnospiraceae ND3007 group as compared to that in the healthy controls (P < 0.05). The common metabolites of these genera are mostly short-chain fatty acids, which reveals that the gut flora is most likely to affect the occurrence and development of AMI through the short-chain fatty acid pathway. In addition, our results provide the first evidence revealing remarkable differences in fecal microflora among subgroups of AMI patients, including the STEMI vs. NSTEMI, IRA-LAD vs. IRA-Non-LAD and Multiple (≥2 coronary stenosis) vs. Single coronary stenosis groups. Several gut microflora were also correlated with clinically significant characteristics of AMI patients, including LVEDD, LVEF, serum TnI and NT-proBNP, Syntax score, counts of leukocytes, neutrophils and monocytes, and fasting serum glucose levels. Taken together, the data generated enables the prediction of several functional pathways as based on the fecal microfloral composition of AMI patients. Such information may enhance our comprehension of AMI pathogenesis.

RFhy-m2G: Identification of RNA N2-methylguanosine modification sites based on random forest and hybrid features

N2-methylguanosine is a post-transcriptional modification of RNA that is found in eukaryotes and archaea. The biological function of m2G modification discovered so far is to control and stabilize the three-dimensional structure of tRNA and the dynamic barrier of reverse transcription. To discover additional biological functions of m2G, it is necessary to develop time-saving and labor-saving calculation tools to identify m2G. In this paper, based on hybrid features and a random forest, a novel predictor, RFhy-m2G, was developed to identify the m2G modification sites for three species. The hybrid feature used by the predictor is used to fuse the three features of ENAC, PseDNC, and NPPS. These three features include primary sequence derivation properties, physicochemical properties, and position-specific properties. Since there are redundant features in hybrid features, MRMD2.0 is used for optimal feature selection. Through feature analysis, it is found that the optimal hybrid features obtained still contain three kinds of properties, and the hybrid features can more accurately identify m2G modification sites and improve prediction performance. Based on five-fold cross-validation and independent testing to evaluate the prediction model, the accuracies obtained were 0.9982 and 0.9417, respectively. The robustness of the predictor is demonstrated by comparisons with other predictors.