A cross-omics data analysis strategy for metabolite-microbe pair identification.

Given the pivotal roles of metabolomics and microbiomics, numerous data mining approaches aim to uncover their intricate connections. However, the complex many-to-many associations between metabolome-microbiome profiles yield numerous statistically significant but biologically unvalidated candidates. To address these challenges, we introduce BiOFI, a strategic framework for identifying metabolome-microbiome correlation pairs (Bi-Omics). BiOFI employs a comprehensive scoring system, incorporating intergroup differences, effects on feature correlation networks, and organism abundance. Meanwhile, it establishes a built-in database of metabolite-microbe-KEGG functional pathway linking relationships. Furthermore, BiOFI can rank related feature pairs by combining importance scores and correlation strength. Validation on a dataset of cesarean-section infants confirms the strategy's validity and interpretability. The BiOFI R package is freely accessible at https://github.com/chentianlu/BiOFI.

Venom-microbiomics of eight species of Neotropical spiders from the Theraphosidae family.

AIM: Tarantulas are one of the largest predatory arthropods in tropical regions. Tarantulas though not lethal to humans, their venomous bite kills small animals and insect upon which they prey. To understand the abiotic and biotic components involved in Neotropical tarantula bites, we conducted a venom-microbiomics study in eight species from Costa Rica. METHODS AND RESULTS: We determined that the toxin profiles of tarantula venom are highly diverse using shotgun proteomics; the most frequently encountered toxins were ω-Ap2 toxin, neprilysin-1, and several teraphotoxins. Through culture-independent and culture-dependent methods, we determined the microbiota present in the venom and excreta to evaluate the presence of pathogens that could contribute to primary infections in animals, including humans. The presence of opportunistic pathogens with hemolytic activity was observed, with a prominence of Stenotrophomonas in the venoms. Other bacteria found in venoms and excreta with hemolytic activity included members of the genera Serratia, Bacillus, Acinetobacter, Microbacterium, and Morganella. CONCLUSIONS: Our data shed light on the venom- and gut-microbiome associated with Neotropical tarantulas. This information may be useful for treating bites from these arthropods in both humans and farm animals, while also providing insight into the toxins and biodiversity of this little-explored microenvironment.

Microbial and metabolomic profiles of type 1 diabetes with depression: A case-control study.

BACKGROUND: Depression is the most common psychological disorder in patients with type 1 diabetes (T1D). However, the characteristics of microbiota and metabolites in these patients remain unclear. This study aimed to investigate microbial and metabolomic profiles and identify novel biomarkers for T1D with depression. METHODS: A case-control study was conducted in a total of 37 T1D patients with depression (TD+), 35 T1D patients without depression (TD-), and 29 healthy controls (HCs). 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis were conducted to investigate the characteristics of microbiota and metabolites. The association between altered microbiota and metabolites was explored by Spearman's rank correlation and visualized by a heatmap. The microbial signatures to discriminate TD+ from TD- were identified by a random forest (RF) classifying model. RESULTS: In microbiota, 15 genera enriched in TD- and 2 genera enriched in TD+, and in metabolites, 14 differential metabolites (11 upregulated and 3 downregulated) in TD+ versus TD- were identified. Additionally, 5 genera (including Phascolarctobacterium, Butyricimonas, and Alistipes from altered microbiota) demonstrated good diagnostic power (area under the curve [AUC] = 0.73; 95% CI, 0.58-0.87). In the correlation analysis, Butyricimonas was negatively correlated with glutaric acid (r = -0.28, p = 0.015) and malondialdehyde (r = -0.30, p = 0.012). Both Phascolarctobacterium (r = 0.27, p = 0.022) and Alistipes (r = 0.31, p = 0.009) were positively correlated with allopregnanolone. CONCLUSIONS: T1D patients with depression were characterized by unique profiles of gut microbiota and serum metabolites. Phascolarctobacterium, Butyricimonas, and Alistipes could predict the risk of T1D with depression. These findings provide further evidence that the microbiota-gut-brain axis is involved in T1D with depression.

Comprehensive analysis of flavor formation mechanisms in the mechanized preparation Cantonese soy sauce koji using absolute quantitative metabolomics and microbiomics approaches.

Based on the widespread application and under-research of mechanized preparation Cantonese soy sauce koji (MP), absolute quantitative approaches were utilized to systematically analyze the flavor formation mechanism in MP. The results indicated that the enzyme activities increased greatly during MP fermentation, and 4 organic acids, 15 amino acids, and 2 volatiles were identified as significantly different flavor actives. The flavor parameters of MP4 were basically identical to those of MP5. Furthermore, microorganisms were dominated by Staphylococcus, Weissella, and Aspergillus in MP, and their biomass demonstrated an increasing trend. A precise enumeration of microorganisms exposed the inaccuracy of relative quantitative data. Concurrently, Staphylococcus and Aspergillus were positively correlated with numerous enzymes and flavor compounds, and targeted strains for enhancing MP quality. The flavor formation network comprises pathways including carbohydrate metabolism, lipid metabolism and oxidation, and protein degradation and amino acid metabolism. In summary, the fermentation period of MP can be substantially shortened without compromising the product quality. These findings lay the groundwork for refining parameters in modern production processes.

Microbiome and its relevance to indigenous inflammatory bowel diseases in China.

BACKGROUND: Inflammatory Bowel Disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract with an unknown etiology. Although dysbiosis is implicated in its pathogenesis, deep sequencing and oral microbiota study in Chinese IBD patients is absent. AIM: To explore the role of oral / intestinal microbiota in patients with IBD and the potential associations therein. METHODS: Clinical data, fecal and saliva samples were harvested from 80 patients with IBD (Crohn's disease, CD, n = 69; Ulcerative colitis, UC, n = 11) and 24 normal controls. Microbiomics (16S rRNA sequencing and 16S rRNA full-length sequencing) were used to detect and analyze the difference between IBD patients and normal control. RESULTS: Compared with normal controls, a higher abundance of the intestinal Shigella spp. (Shigella flexneri and Shigella sonnei, which were positively relate to the severity of IBD), lower abundance of intestinal probiotics (Prevotella, Faecalibacterium and Roseburia), and higher abundance of oral Neisseria were present in IBD patients with microbiome. The higher inflammation-related markers, impaired hepatic and renal function, and dyslipidaemia were present in patients with IBD. A higher intake of red meat and increased abundance of Clostridium in the gut were found in CD patients, while the elevated abundance of Ruminococcus in the gut was showed in UC ones. The bacterial composition of saliva and fecal samples was completely different, yet there was some correlation in the distribution of dominant probiotics. CONCLUSION: Enteric dysbacteriosis and the infections of pathogenic bacteria (Shigella) may associate with the occurrence or development of IBD.

In-depth investigation of the therapeutic effect of Tribulus terrestris L. on type 2 diabetes based on intestinal microbiota and feces metabolomics.

ETHNOPHARMACOLOGICAL RELEVANCE: The fruit of Tribulus terrestris L. (TT) is extensively documented in the Tibetan medical literature 'Si Bu Yi Dian', has been used to treat diabetes mellitus for more than a thousand years. However, the underlying mechanisms and comprehensive effects of TT on diabetes have yet to be investigated. AIM OF THE STUDY: The aim of the study was to systemically elucidate the potential mechanisms of TT in treating diabetes mellitus, and further investigate the therapeutic effects of the water extract, small molecular components and saccharides from TT. MATERIALS AND METHODS: Fecal metabolomics was employed to draw the metabolic profile based on UHPLC-Q-TOF-MS/MS. The V3-V4 hypervariable regions of the bacteria 16S rRNA gene were amplified to explore the structural changes of the intestinal microbiome after TT intervention and to analyze the differential microbiota. The microbial metabolites SCFAs were determined by GC-MS, and the BAs and tryptophan metabolites were quantified by UPLC-TQ-MS. Spearman correlation analysis was carried out to comprehensively investigate the relationship among the endogenous metabolites profile, intestinal microbiota and their metabolites. RESULTS: TT exhibited remarkably therapeutic effect on T2DM rats, as evidenced by improved glucolipid metabolism and intestinal barrier integrity, ameliorated inflammation and remission in insulin resistance. A total of 24 endogenous biomarkers were screened through fecal metabolomics studies, which were mainly related to tryptophan metabolism, fatty acid metabolism, bile acid metabolism, steroid hormone biosynthesis and arachidonic acid metabolism. Investigations on microbiomics revealed that TT significantly modulated 18 differential bacterial genera and reversed the disordered gut microbial in diabetes rats. Moreover, TT notably altered the content of gut microbiota metabolites, both in serum and fecal samples. Significant correlation among microbial community, metabolites and T2DM-related indicators was revealed. CONCLUSIONS: The multiple components of TT regulate the metabolic homeostasis of the organism and the balance of intestinal microbiota and its metabolites, which might mediate the anti-diabetic capacity of TT.

Prospective fecal microbiomic biomarkers for chronic wasting disease.

Chronic wasting disease (CWD) is a naturally occurring prion disease in cervids that has been rapidly proliferating in the United States. Here, we investigated a potential link between CWD infection and gut microbiome by analyzing 50 fecal samples obtained from CWD-positive animals of different sexes from various regions in the USA compared to 50 CWD-negative controls using high throughput sequencing of the 16S ribosomal RNA and targeted metabolomics. Our analysis reveals promising trends in the gut microbiota that could potentially be CWD-dependent, including several bacterial taxa at each rank level, as well as taxa pairs, that can differentiate between CWD-negative and CWD-positive deer. Through machine-learning, these taxa and taxa pairs at each rank level could facilitate identification of around 70% of both the CWD-negative and the CWD-positive samples. Our results provide a potential tool for diagnostics and surveillance of CWD in the wild, as well as conceptual advances in our understanding of the disease.IMPORTANCEThis is a comprehensive study that tests the connection between the composition of the gut microbiome in deer in response to chronic wasting disease (CWD). We analyzed 50 fecal samples obtained from CWD-positive animals compared to 50 CWD-negative controls to identify CWD-dependent changes in the gut microbiome, matched with the analysis of fecal metabolites. Our results show promising trends suggesting that fecal microbial composition can directly correspond to CWD disease status. These results point to the microbial composition of the feces as a potential tool for diagnostics and surveillance of CWD in the wild, including non-invasive CWD detection in asymptomatic deer and deer habitats, and enable conceptual advances in our understanding of the disease.

Impacts of Aspergillus oryzae 3.042 on the flavor formation pathway in Cantonese soy sauce koji.

To investigate the mechanism of flavor formation during the traditional preparation Cantonese soy sauce koji (TP), the changes of microorganisms, physicochemical properties, and flavor compounds in TP were comprehensively and dynamically monitored by absolute quantitative methods. Results demonstrated that inoculating Aspergillus oryzae 3.042 in TP was crucial role in enhancing enzyme activity properties. Absolute quantification of flavor combined with multivariate statistical analysis yielded 5 organic acids, 15 amino acids, and 2 volatiles as significantly different flavors of TP. Amplicon sequencing and RT-qPCR revealed that the dominant genera were Staphylococcus, Weissella, Enterobacter, Lactic streptococci, Lactobacillus, and Aspergillus, which exhibited a increasing trend in TP. Correlation analysis exhibited that Staphylococcus and Aspergillus were the pivotal genera contributing to the enzyme activities and flavor of TP. The flavor formation network involved lipid and protein degradation, carbohydrate metabolism and other pathways. Simultaneously, TP can appropriately increase the fermentation time to improve product quality.

A novel enzyme-based functional correlation algorithm for multi-omics reveals the potential mechanisms of traditional Chinese medicines: Taking Jian-Pi-Yi-Shen formula as an example.

The integrated analysis of host metabolome and intestinal microbiome is an opportunity to explore the complex therapeutic mechanisms of traditional Chinese medicines. Currently, researchers mainly employ various statistical correlation analytical methods to investigate metabolome-microbiome correlations. However, these conventional correlation techniques often focus on statistical correlations and their biological meanings are always ignored, especially the functional relevance between them. Here, we developed a novel enzyme-based functional correlation (EBFC) algorithm to further improve the interpretability and the identified scope of microbe-metabolite correlations based on the conventional Spearman's analysis. The proposed EBFC algorithm is successfully utilized to reveal the therapeutic mechanisms of Jian-Pi-Yi-Shen (JPYS) formula on the treatment of adenine-induced chronic kidney disease (CKD) rats. JPYS, a TCM formula for treating CKD, has beneficial clinical effects. We tentatively revealed the potential mechanism of JPYS for treating CKD rats from the perspective of the serum metabolome, gut microbiome, and their interactions. Specifically, 11 metabolites and 19 bacterial genera in the CKD rats were significantly regulated to approaching normal status after JPYS treatment, suggesting that JPYS could ameliorate the pathological symptoms of CKD rats by reshaping the disturbed metabolome and gut microbiota. Further correlation analysis between the significantly perturbed metabolites, microbiota, and the related enzymes provided more strong evidence for the study of host metabolism-microbiota interactions and the therapeutic mechanism of JPYS on CKD rats. In conclusion, these findings will help us to deeply understand the pathogenesis of CKD and provide new insights into the therapeutic mechanism of JPYS.

Long-term toxic effects of iron-based metal-organic framework nanopesticides on earthworm-soil microorganism interactions in the soil environment.

With the widespread use of controlled-release nanopesticides in field conditions, the interactions between these nanopesticides and biological systems are complex and highly uncertain. The toxicity of iron-based metal organic frameworks (CF@MIL-101-SL) loaded with chlorfenapyr (CF) to terrestrial invertebrate earthworms in filter paper and soil environments and the potential mechanisms of interactions in the nanopesticide-earthworm-cornfield soil microorganism system were investigated for the first time. The results showed that CF@MIL-101-SL was more poisonous to earthworms in the contact filter paper test than suspension concentrate of CF (CF-SC), and conversely, CF@MIL-101-SL was less poisonous to earthworms in the soil test. In the soil environment, the CF@MIL-101-SL treatment reduced oxidative stress and the inhibition of detoxifying enzymes, and reduced tissue and cellular substructural damage in earthworms compared to the CF-SC treatment. Long-term treatment with CF@MIL-101-SL altered the composition and abundance of microbial communities with degradative functions in the earthworm intestine and soil and affected the soil nitrogen cycle by modulating the composition and abundance of nitrifying and denitrifying bacterial communities in the earthworm intestine and soil, confirming that soil microorganisms play an important role in reducing the toxicity of CF@MIL-101-SL to earthworms. In conclusion, this study provides new insights into the ecological risks of nanopesticides to soil organisms.

Deciphering the Mechanism by Which Carbon Dioxide Extends the Shelf Life of Raw Milk: A Microbiomics- and Metabolomics-Based Approach.

Microbial community succession in raw milk determines its quality and storage period. In this study, carbon dioxide (CO2) at 2000 ppm was used to treat raw milk to investigate the mechanism of extending the shelf life of raw milk by CO2 treatment from the viewpoint of microbial colonies and metabolites. The results showed that the shelf life of CO2-treated raw milk was extended to 16 days at 4 °C, while that of the control raw milk was only 6 days. Microbiomics analysis identified 221 amplicon sequence variants (ASVs) in raw milk, and the alpha diversity of microbial communities increased (p < 0.05) with the extension of storage time. Among them, Pseudomonas, Actinobacteria and Serratia were the major microbial genera responsible for the deterioration of raw milk, with a percentage of 85.7%. A combined metagenomics and metabolomics analysis revealed that microorganisms altered the levels of metabolites, such as pyruvic acid, glutamic acid, 5'-cmp, arginine, 2-propenoic acid and phenylalanine, in the raw milk through metabolic activities, such as ABC transporters, pyrimidine metabolism, arginine and proline metabolism and phenylalanine metabolism, and reduced the shelf life of raw milk. CO2 treatment prolonged the shelf life of raw milk by inhibiting the growth of Gram-negative aerobic bacteria, such as Acinetobacter guillouiae, Pseudomonas fluorescens, Serratia liquefaciens and Pseudomonas simiae.

Mechanism of procyanidins for health functionality by improving the intestinal environment.

Procyanidins are one of the polyphenols consisting of multiple flavan-3-ols (eg epicatechin). They have a complex chemical structure, with the degree of polymerization and linked position of flavan-3-ols varying among various foods, such as apples and chocolate. Physiological functional studies of procyanidins have investigated their mechanisms in cells and animals based on their antioxidant effects. Recently, the intestinal environment, including the intestinal microflora, has played an important role in the energy metabolism and health status of the host. Regulation of the intestinal environment by dietary polyphenols is becoming a new concept in health functions, and we have begun to investigate the mechanism of apple procyanidins, focusing on the gut microbiota and metabolites in our functional research. In this minireview, we will discuss the effects of procyanidin ingestion on the gut microbiota and metabolites.

10. Role of high dimensional technology in preeclampsia (omics in preeclampsia).

Preeclampsia is a pregnancy-specific disease that has no known precise cause. Integrative biology approach based on multi-omics has been applied to identify upstream pathways and better understand the pathophysiology of preeclampsia. At DNA level, genomics and epigenomics studies have revealed numerous genetic variants associated with preeclampsia, including those involved in regulating blood pressure and immune response. Transcriptomics analyses have revealed altered expression of genes in preeclampsia, particularly those related to inflammation and angiogenesis. At protein level, proteomics studies have identified potential biomarkers for preeclampsia diagnosis and prediction in addition to revealing the main pathophysiological pathways involved in this disease. At metabolite level, metabolomics has highlighted altered lipid and amino acid metabolisms in preeclampsia. Finally, microbiomics studies have identified dysbiosis in the gut and vaginal microbiota in pregnant women with preeclampsia. Overall, omics technologies have improved our understanding of the complex molecular mechanisms underlying preeclampsia. However, further research is warranted to fully integrate and translate these omics findings into clinical practice.

Biological biomarkers of oral cancer.

The oral squamous cell carcinoma (OSCC) 5 year survival rate of 41% has marginally improved in the last few years, with less than a 1% improvement per year from 2005 to 2017, with higher survival rates when detected at early stages. Based on histopathological grading of oral dysplasia, it is estimated that severe dysplasia has a malignant transformation rate of 7%-50%. Despite these numbers, oral dysplasia grading does not reliably predict its clinical behavior. Thus, more accurate markers predicting oral dysplasia progression to cancer would enable better targeting of these lesions for closer follow-up, especially in the early stages of the disease. In this context, molecular biomarkers derived from genetics, proteins, and metabolites play key roles in clinical oncology. These molecular signatures can help predict the likelihood of OSCC development and/or progression and have the potential to detect the disease at an early stage and, support treatment decision-making and predict treatment responsiveness. Also, identifying reliable biomarkers for OSCC detection that can be obtained non-invasively would enhance management of OSCC. This review will discuss biomarkers for OSCC that have emerged from different biological areas, including genomics, transcriptomics, proteomics, metabolomics, immunomics, and microbiomics.

Attempts to Understand Oral Mucositis in Head and Neck Cancer Patients through Omics Studies: A Narrative Review.

Oral mucositis (OM) is a common and clinically impactful side effect of cytotoxic cancer treatment, particularly in patients with head and neck squamous cell carcinoma (HNSCC) who undergo radiotherapy with or without concomitant chemotherapy. The etiology and pathogenic mechanisms of OM are complex, multifaceted and elicit both direct and indirect damage to the mucosa. In this narrative review, we describe studies that use various omics methodologies (genomics, transcriptomics, microbiomics and metabolomics) in attempts to elucidate the biological pathways associated with the development or severity of OM. Integrating different omics into multi-omics approaches carries the potential to discover links among host factors (genomics), host responses (transcriptomics, metabolomics), and the local environment (microbiomics).

Triangulating nutrigenomics, metabolomics and microbiomics toward personalized nutrition and healthy living.

The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

P-coumaric acid ameliorates Aß25-35-induced brain damage in mice by modulating gut microbiota and serum metabolites.

Alzheimer's disease (AD) is a progressive neurodegenerative disease for which there is a lack of effective therapeutic drugs. There is great potential for natural products to be used in the development of anti-AD drugs. P-coumaric acid (PCA), a small molecule phenolic acid widely distributed in the plant kingdom, has pharmacological effects such as neuroprotection, but its anti-AD mechanism has not been fully elucidated. In the current study, we investigated the mechanism of PCA intervention in the Aß25-35-induced AD model using gut microbiomics and serum metabolomics combined with in vitro and in vivo pharmacological experiments. PCA was found to ameliorate cognitive dysfunction and neuronal cell damage in Aß25-35-injected mice as measured by behavioral, pathological and biochemical indicators. 16S rDNA sequencing and serum metabolomics showed that PCA reduced the abundance of pro-inflammatory-associated microbiota (morganella, holdemanella, fusicatenibacter and serratia) in the gut, which were closely associated with metabolites of the glucose metabolism, arachidonic acid metabolism, tyrosine metabolism and phospholipid metabolism pathways in serum. Next, in vivo and in vitro pharmacological investigations revealed that PCA regulated Aß25-35-induced disruption of glucose metabolism through activation of PI3K/AKT/Glut1 signaling. Additionally, PCA ameliorated Aß25-35-induced neuroinflammation by inhibiting nuclear translocation of NF-κB and by modulating upstream MAPK signaling. In conclusion, PCA ameliorated cognitive deficits in Aß25-35-induced AD mice by regulating glucose metabolism and neuroinflammation, and the mechanism is related not only to restoring homeostasis of gut microbiota and serum metabolites, but also to PI3K/AKT/Glut1 and MAPK/NF-κB signaling.

Omics sciences and precision medicine in sarcoma.

Background: Sarcomas are a relatively rare but diverse group of cancers that typically develop in the mesenchymal cells of bones and soft tissues. Occurring in more than 70 subtypes, sarcomas have broad histological presentations, posing significant challenges of prognosis and treatment. Modern multi-omics studies, which include genomics, proteomics, metabolomics, and micro-biomics, are vital to understand the underlying mechanisms of sarcoma development and progression, identify molecular biomarkers for early detection, develop personalized treatment plans, and discover drug resistance mechanisms in sarcomas to upsurge the survival rate. Aim: This study aims to highlight the genetic risk factors responsible for sarcoma-genesis, and to present a comprehensive review of multi-omics studies about sarcoma. Methods: Extensive literature research was undertaken using reliable and authentic medical journals, e-books, and online cancer research databases. Mendelian inheritance in man database (OMIM) was explored to study particular genes and their loci that are responsible to cause various sarcomas. Result: This in-depth research led to the finding out that omics studies provide a more comprehensive understanding of underlying molecular mechanisms of sarcomas. Through genomics, we can reveal genetic alterations that predispose to sarcoma, like mutation in TP53, NF1, and so on. Pharmacogenomics enable us to find molecular targets for specific drugs. Whereas, proteomic and metabolomic studies provide insights into the biological pathways involved in sarcoma development and progression. Conclusion: Future advancements in omics sciences for sarcoma are on the cutting-edge of defining precision treatment plans and improved resilience of sarcoma patients.

Exercise and microbiome: From big data to therapy.

Exercise is a vital component in maintaining optimal health and serves as a prospective therapeutic intervention for various diseases. The human microbiome, comprised of trillions of microorganisms, plays a crucial role in overall health. Given the advancements in microbiome research, substantial databases have been created to decipher the functionality and mechanisms of the microbiome in health and disease contexts. This review presents an initial overview of microbiomics development and related databases, followed by an in-depth description of the multi-omics technologies for microbiome. It subsequently synthesizes the research pertaining to exercise-induced modifications of the microbiome and diseases that impact the microbiome. Finally, it highlights the potential therapeutic implications of an exercise-modulated microbiome in intestinal disease, obesity and diabetes, cardiovascular disease, and immune/inflammation-related diseases.

Research Progress on Microbial Community Succession in the Postmortem Interval Estimation.

The postmortem interval (PMI) estimation is a key and difficult point in the practice of forensic medicine, and forensic scientists at home and abroad have been searching for objective, quantifiable and accurate methods of PMI estimation. With the development and combination of high-throughput sequencing technology and artificial intelligence technology, the establishment of PMI model based on the succession of the microbial community on corpses has become a research focus in the field of forensic medicine. This paper reviews the technical methods, research applications and influencing factors of microbial community in PMI estimation explored by using high-throughput sequencing technology, to provide a reference for the related research on the use of microbial community to estimate PMI.