A guide to human microbiome research: study design, sample collection, and bioinformatics analysis

Environmentally responsive changes in mucus indicators and microbiota of Chinese sturgeon Acipensersinensis

The impact of environmental factors on the health of the endangered Chinese sturgeon (Acipenser sinensis) and the potential hazards associated with sample collection for health monitoring pose urgent need to its conservation. In this study, Chinese sturgeons were selected from indoor and outdoor environments to evaluate metabolic and tissue damage indicators, along with a non-specific immune enzyme in fish mucus. Additionally, the microbiota of both water bodies and fish mucus were determined using 16S rRNA high-throughput sequencing. The correlation between the indicators and the microbiota was investigated, along with the measurement of multiple environmental factors. The results revealed significantly higher levels of two metabolic indicators, total protein (TP) and cortisol (COR) in indoor fish mucus compared to outdoor fish mucus (p < 0.05). The activities of acid phosphatase (ACP), alkaline phosphatase (ALP), creatine kinase (CK), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) were significantly higher in indoor fish, serving as indicators of tissue damage (p < 0.05). The activity of lysozyme (LZM) was significantly lower in indoor fish (p < 0.01). Biomarker analysis at the phylum and genus levels in outdoor samples revealed that microorganisms were primarily related to the catabolism of organic nutrients. In indoor environments, microorganisms displayed a broader spectrum of functions, including ecological niche establishment, host colonization, potential pathogenicity, and antagonism of pathogens. KEGG functional enrichment corroborated these findings. Dissolved oxygen (DO), electrical conductivity (EC), ammonia nitrogen (NH3-N), turbidity (TU), and chemical oxygen demand (COD) exerted effects on outdoor microbiota. Temperature (TEMP), nitrate (NO3-), total phosphorus (TP), and total nitrogen (TN) influenced indoor microbiota. Changes in mucus indicators, microbial structure, and function in both environments were highly correlated with these factors. Our study provides novel insights into the health impacts of different environments on Chinese sturgeon using a non-invasive method.

Visualizing set relationships: EVenn's comprehensive approach to Venn diagrams

Venn diagrams serve as invaluable tools for visualizing set relationships due to their ease of interpretation. Widely applied across diverse disciplines such as metabolomics, genomics, transcriptomics, and proteomics, their utility is undeniable. However, the operational complexity has been compounded by the absence of standardized data formats and the need to switch between various platforms for generating different Venn diagrams. To address these challenges, we introduce the EVenn platform, a versatile tool offering a unified interface for efficient data exploration and visualization of diverse Venn diagrams. EVenn (http://www.ehbio.com/test/venn) streamlines the data upload process with a standardized format, enhancing the capabilities for multimodule analysis. This comprehensive protocol outlines various applications of EVenn, featuring representative results of multiple Venn diagrams, data uploads in the centralized data center, and step-by-step case demonstrations. Through these functionalities, EVenn emerges as a valuable and user-friendly tool for the in-depth exploration of multiomics data.

Bioaerosols in the coastal region of Qingdao: Community diversity, impact factors and synergistic effect

Atmospheric bioaerosols are influenced by multiple factors, including physical, chemical, and biotic interactions, and pose a significant threat to the public health and the environment. The nonnegligible truth however is that the primary driver of the changes in bioaerosol community diversity remains unknown. In this study, putative biological association (PBA) was obtained by constructing an ecological network. The relationship between meteorological conditions, atmospheric pollutants, water-soluble inorganic ions, PBA and bioaerosol community diversity was analyzed using random forest regression (RFR)-An ensemble learning algorithm based on a decision tree that performs regression tasks by constructing multiple decision trees and integrating the predicted results, and the contribution of different rich species to PBA was predicted. The species richness, evenness and diversity varied significantly in different seasons, with the highest in summer, followed by autumn and spring, and was lowest in winter. The RFR suggested that the explanation rate of alpha diversity increased significantly from 73.74 % to 85.21 % after accounting for the response of the PBA to diversity. The PBA, temperature, air pollution, and marine source air masses were the most crucial factors driving community diversity. PBA, particularly putative positive association (PPA), had the highest significance in diversity. We found that under changing external conditions, abundant taxa tend to cooperate to resist external pressure, thereby promoting PPA. In contrast, rare taxa were more responsive to the putative negative association because of their sensitivity to environmental changes. The results of this research provided scientific advance in the understanding of the dynamic and temporal changes in bioaerosols, as well as support for the prevention and control of microbial contamination of the atmosphere.

The association between alpha diversity of gut microbiota, neuroimaging markers and cognitive function in cerebral small vessel disease

There is increasing recognition of gut microbial dysbiosis in cerebral small vessel disease (CSVD). The altered diversity in a single ecosystem - alpha diversity index of gut microbiota has attracted wide attention. Our study aims to determine whether the alpha diversity index differs among healthy control (HC), CSVD with and without cognitive impairment. Moreover, we investigate the correlation between the alpha diversity index, neuroimaging markers, and cognitive function. We recruited 40 HC, 43 CSVD patients without cognitive impairment (CSVD-NCI), and 35 CSVD patients with mild cognitive impairment (CSVD-MCI). Clinical and neuropsychological assessments, MRI scanning, and gut microbiota analysis were performed on all participants. The alpha diversity indexes Chao1 and Shannon were calculated to evaluate community richness and diversity in a sample, respectively. Individual neuroimaging markers of CSVD and the CSVD burden score were also evaluated. A significantly lower level of Chao 1 rather than the Shannon index was observed in the CSVD subgroups than in the HC group. The level of the Chao 1 index was negatively correlated with both CMB counts, a neuroimaging characteristic of CSVD, and CSVD burden score in patients with CSVD. Additionally, the Chao 1 index has been associated with general cognitive function, information processing speed, and language function in patients with CSVD. Remarkably, the increased CSVD burden score mediated the effects of decreased levels of Chao 1 on information processing speed and language function. Hence, the alterations in species richness may be associated with CSVD-related cognitive impairment and mediated by CSVD neuroimaging markers.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

Microbiome as a biomarker and therapeutic target in pancreatic cancer

Studying the effects of the microbiome on the development of different types of cancer has recently received increasing research attention. In this context, the microbial content of organs of the gastrointestinal tract has been proposed to play a potential role in the development of pancreatic cancer (PC). Proposed mechanisms for the pathogenesis of PC include persistent inflammation caused by microbiota leading to an impairment of antitumor immune surveillance and altered cellular processes in the tumor microenvironment. The limited available diagnostic markers that can currently be used for screening suggest the importance of microbial composition as a non-invasive biomarker that can be used in clinical settings. Samples including saliva, stool, and blood can be analyzed by 16 s rRNA sequencing to determine the relative abundance of specific bacteria. Studies have shown the potentially beneficial effects of prebiotics, probiotics, antibiotics, fecal microbial transplantation, and bacteriophage therapy in altering microbial diversity, and subsequently improving treatment outcomes. In this review, we summarize the potential impact of the microbiome in the pathogenesis of PC, and the role these microorganisms might play as biomarkers in the diagnosis and determining the prognosis of patients. We also discuss novel treatment methods being used to minimize or prevent the progression of dysbiosis by modulating the microbial composition. Emerging evidence is supportive of applying these findings to improve current therapeutic strategies employed in the treatment of PC.

Gut microbiome encoded purine and amino acid pathways present prospective biomarkers for predicting metformin therapy efficacy in newly diagnosed T2D patients

Metformin is widely used for treating type 2 diabetes mellitus (T2D). However, the efficacy of metformin monotherapy is highly variable within the human population. Understanding the potential indirect or synergistic effects of metformin on gut microbiota composition and encoded functions could potentially offer new insights into predicting treatment efficacy and designing more personalized treatments in the future. We combined targeted metabolomics and metagenomic profiling of gut microbiomes in newly diagnosed T2D patients before and after metformin therapy to identify potential pre-treatment biomarkers and functional signatures for metformin efficacy and induced changes in metformin therapy responders. Our sequencing data were largely corroborated by our metabolic profiling and identified that pre-treatment enrichment of gut microbial functions encoding purine degradation and glutamate biosynthesis was associated with good therapy response. Furthermore, we identified changes in glutamine-associated amino acid (arginine, ornithine, putrescine) metabolism that characterize differences in metformin efficacy before and after the therapy. Moreover, metformin Responders' microbiota displayed a shifted balance between bacterial lipidA synthesis and degradation as well as alterations in glutamate-dependent metabolism of N-acetyl-galactosamine and its derivatives (e.g. CMP-pseudaminate) which suggest potential modulation of bacterial cell walls and human gut barrier, thus mediating changes in microbiome composition. Together, our data suggest that glutamine and associated amino acid metabolism as well as purine degradation products may potentially condition metformin activity via its multiple effects on microbiome functional composition and therefore serve as important biomarkers for predicting metformin efficacy.

Metagenomic and targeted metabolomic analyses reveal distinct phenotypes of the gut microbiota in patients with colorectal cancer and type 2 diabetes mellitus

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.

The Next Generation Fecal Microbiota Transplantation: To Transplant Bacteria or Virome

Fecal microbiota transplantation (FMT) has emerged as a promising therapeutic approach for dysbiosis-related diseases. However, the clinical practice of crude fecal transplants presents limitations in terms of acceptability and reproductivity. Consequently, two alternative solutions to FMT are developed: transplanting bacteria communities or virome. Advanced methods for transplanting bacteria mainly include washed microbiota transplantation and bacteria spores treatment. Transplanting the virome is also explored, with the development of fecal virome transplantation, which involves filtering the virome from feces. These approaches provide more palatable options for patients and healthcare providers while minimizing research heterogeneity. In general, the evolution of the next generation of FMT in global trends is fecal microbiota components transplantation which mainly focuses on transplanting bacteria or virome.

[Analysis of Salivary Microbiota Characteristics in Patients With Pulmonary Nodules: A Prospective Nonrandomized Concurrent Controlled Trial]

Objective

To uncover and identify the differences in salivary microbiota profiles and their potential roles between patients with pulmonary nodules (PN) and healthy controls, and to propose new candidate biomarkers for the early warning of PN.

Methods

16S rRNA amplicon sequencing was performed with the saliva samples of 173 PN patients, or the PN group, and 40 health controls, or the HC group, to compare the characteristics, including diversity, community composition, differential species, and functional changes of salivary microbiota in the two groups. Random forest algorithm was used to identify salivary microbial markers of PN and their predictive value for PN was assessed by area under the curve (AUC). Finally, the biological functions and potential mechanisms of differentially-expressed genes in saliva samples were preliminarily investigated on the basis of predictive functional profiling of Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2).

Results

The α diversity and β diversity of salivary microbiota in the PN group were higher than those in the HC group (P<0.05). Furthermore, there were significant differences in the community composition and the abundance of oral microorganisms between the PN and the HC groups (P<0.05). Random forest algorithm was applied to identify differential microbial species. Porphyromonas, Haemophilus, and Fusobacterium constituted the optimal marker sets (AUC=0.79, 95% confidence interval: 0.71-0.86), which can be used to effectively identify patients with PN. Bioinformatics analysis of the differentially-expressed genes revealed that patients with PN showed significant enrichment in protein/molecular functions involved in immune deficiency and redox homeostasis.

Conclusion

Changes in salivary microbiota are closely associated with PN and may induce the development of PN or malignant transformation of PN, which indicates the potential of salivary microbiota to be used as a new non-invasive humoral marker for the early diagnosis of PN.

Exploring the gut microbiota: lifestyle choices, disease associations, and personal genomics

The gut microbiota is a rich and dynamic ecosystem that actively interacts with the human body, playing a significant role in the state of health and disease of the host. Diet, exercise, mental health, and other factors have exhibited the ability to influence the gut bacterial composition, leading to changes that can prevent and improve, or favor and worsen, both intestinal and extra-intestinal conditions. Altered gut microbial states, or 'dysbiosis', associated with conditions and diseases are often characterized by shifts in bacterial abundance and diversity, including an impaired Firmicutes to Bacteroidetes ratio. By understanding the effect of lifestyle on the gut microbiota, personalized advice can be generated to suit each individual profile and foster the adoption of lifestyle changes that can both prevent and ameliorate dysbiosis. The delivery of effective and reliable advice, however, depends not only on the available research and current understanding of the topic, but also on the methods used to assess individuals and to discover the associations, which can introduce bias at multiple stages. The aim of this review is to summarize how human gut microbial variability is defined and what lifestyle choices and diseases have shown association with gut bacterial composition. Furthermore, popular methods to investigate the human gut microbiota are outlined, with a focus on the possible bias caused by the lack of use of standardized methods. Finally, an overview of the current state of personalized advice based on gut microbiota testing is presented, underlining its power and limitations.

Role of gut microbiome in cancer immunotherapy: from predictive biomarker to therapeutic target

Immunotherapy has emerged as an effective treatment for various types of cancers. Recent studies have highlighted a significant correlation between the gut microbiome and patients' response to immunotherapy. Several characteristics of the gut microbiome, such as community structures, taxonomic compositions, and molecular functions, have been identified as crucial biomarkers for predicting immunotherapy response and immune-related adverse events (irAEs). Unlike other -omics, the gut microbiome can serve as not only biomarkers but also potential targets for enhancing the efficacy of immunotherapy. Approaches for modulating the gut microbiome include probiotics/prebiotics supplementation, dietary interventions, fecal microbiota transplantation (FMT), and antibiotic administration. This review primarily focuses on elucidating the potential role of the gut microbiome in predicting the response to cancer immunotherapy and improving its efficacy. Notably, we explore reasons behind inconsistent findings observed in different studies, and highlight the underlying benefits of antibiotics in liver cancer immunotherapy.

The entero-endocrine response following a mixed-meal tolerance test with a non-nutritive pre-load in participants with pre-diabetes and type 2 diabetes: A crossover randomized controlled trial proof of concept study

INTRODUCTION

This crossover randomized controlled trial (RCT) investigated differences in short-term entero-endocrine response to a mixed-meal tolerance test preceded by nutrient sensing between participants with pre-diabetes (pre-T2D) and type 2 diabetes (T2D). Additionally, differences in gut and oral microbiome composition between participants with a high and low entero-endocrine response were investigated.

RESEARCH DESIGN AND METHODS

Ten participants with pre-T2D and ten with T2D underwent three test days with pre-loads consisting of either swallowing water (control), or rinsing with a non-nutritive sweetener solution, or swallowing the sweetener solution before a mixed-meal tolerance test. Blood glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide-1 (GLP-1), glucagon, glucose, insulin and peptide YY (PYY) were determined at t = -20, 0, 15, 30, 60, 120 and 240 minutes. The composition of the oral and gut microbiome at baseline were also determined.

RESULTS

The entero-endocrine response differed by pre-loads, e.g. a lower PYY response after swallowing the non-nutritive sweetener (-3585.2pg/mL [95% CI: -6440.6; -729.8]; p = 0.01). But it also differed by T2D status, e.g. a higher glucose, glucagon and PYY response was found in participants with T2D, compared to those with pre-T2D. Evidence for associations between the oral and gut microbiome composition and the entero-endocrine response was limited. Still, the level of entero-endocrine response was associated with several oral microbiome measures. Higher oral anterior α-diversity was associated with a lower PYY response (e.g. Inverse Simpson index -1357pg/mL [95% CI -2378; -336; 1.24]), and higher oral posterior α-diversitywith a higher GIP response (e.g. Inverse Simpson index 6773pg/mL [95% CI 132; 13414]) in models adjusted for sex, age and T2D status.

CONCLUSIONS

Non-nutritive pre-loads influence the entero-endocrine response to a mixed-meal, and this effect varies based on (pre-)T2D status. The entero-endocrine response is likely not associated with the gut microbiome, and there is limited evidence for association with the α-diversity of the oral microbiome composition.

TRIAL REGISTRATION

Trial register: Netherlands Trial Register NTR7212, accessible through International Clinical Trials Registry Platform: ICTRP Search Portal (who.int).

Probiotic supplementation during antibiotic treatment is unjustified in maintaining the gut microbiome diversity: a systematic review and meta-analysis

BACKGROUND

Probiotics are often used to prevent antibiotic-induced low-diversity dysbiosis, however their effect is not yet sufficiently summarized in this regard. We aimed to investigate the effects of concurrent probiotic supplementation on gut microbiome composition during antibiotic therapy.

METHODS

We performed a systematic review and meta-analysis of randomized controlled trials reporting the differences in gut microbiome diversity between patients on antibiotic therapy with and without concomitant probiotic supplementation. The systematic search was performed in three databases (MEDLINE (via PubMed), Embase, and Cochrane Central Register of Controlled Trials (CENTRAL)) without filters on 15 October 2021. A random-effects model was used to estimate pooled mean differences (MD) with 95% confidence intervals (CI). This review was registered on PROSPERO (CRD42021282983).

RESULTS

Of 11,769 identified articles, 15 were eligible in the systematic review and 5 in the meta-analyses. Quantitative data synthesis for Shannon (MD = 0.23, 95% CI: [(-)0.06-0.51]), Chao1 (MD = 11.59 [(-)18.42-41.60]) and observed OTUs (operational taxonomic unit) (MD = 17.15 [(-)9.43-43.73]) diversity indices revealed no significant difference between probiotic supplemented and control groups. Lacking data prevented meta-analyzing other diversity indices; however, most of the included studies reported no difference in the other reported α- and ß-diversity indices between the groups. Changes in the taxonomic composition varied across the eligible studies but tended to be similar in both groups. However, they showed a potential tendency to restore baseline levels in both groups after 3-8 weeks. This is the first meta-analysis and the most comprehensive review of the topic to date using high quality methods. The limited number of studies and low sample sizes are the main limitations of our study. Moreover, there was high variability across the studies regarding the indication of antibiotic therapy and the type, dose, and duration of antimicrobials and probiotics.

CONCLUSIONS

Our results showed that probiotic supplementation during antibiotic therapy was not found to be influential on gut microbiome diversity indices. Defining appropriate microbiome diversity indices, their standard ranges, and their clinical relevance would be crucial.

Aerobic exercise training and gut microbiome-associated metabolic shifts in women with overweight: a multi-omic study

Physical activity is essential in weight management, improves overall health, and mitigates obesity-related risk markers. Besides inducing changes in systemic metabolism, habitual exercise may improve gut's microbial diversity and increase the abundance of beneficial taxa in a correlated fashion. Since there is a lack of integrative omics studies on exercise and overweight populations, we studied the metabolomes and gut microbiota associated with programmed exercise in obese individuals. We measured the serum and fecal metabolites of 17 adult women with overweight during a 6-week endurance exercise program. Further, we integrated the exercise-responsive metabolites with variations in the gut microbiome and cardiorespiratory parameters. We found clear correlation with several serum and fecal metabolites, and metabolic pathways, during the exercise period in comparison to the control period, indicating increased lipid oxidation and oxidative stress. Especially, exercise caused co-occurring increase in levels of serum lyso-phosphatidylcholine moieties and fecal glycerophosphocholine. This signature was associated with several microbial metagenome pathways and the abundance of Akkermansia. The study demonstrates that, in the absence of body composition changes, aerobic exercise can induce metabolic shifts that provide substrates for beneficial gut microbiota in overweight individuals.

Probiotics, prebiotics, and synbiotics in nonalcoholic fatty liver disease and alcohol-associated liver disease

The use of probiotics, prebiotics, and synbiotics has become an important therapy in numerous gastrointestinal diseases in recent years. Modifying the gut microbiota, this therapeutic approach helps to restore a healthy microbiome. Nonalcoholic fatty liver disease and alcohol-associated liver disease are among the leading causes of chronic liver disease worldwide. A disrupted intestinal barrier, microbial translocation, and an altered gut microbiome metabolism, or metabolome, are crucial in the pathogenesis of these chronic liver diseases. As pro-, pre-, and synbiotics modulate these targets, they were identified as possible new treatment options for liver disease. In this review, we highlight the current findings on clinical and mechanistic effects of this therapeutic approach in nonalcoholic fatty liver disease and alcohol-associated liver disease.

Bacillus amyloliquefaciens alleviates the pathological injuries in mice infected with Schistosoma japonicum by modulating intestinal microbiome

Schistosoma japonicum causes serious pathological organ damage and alteration of the intestinal microbiome in the mammalian host, threatening the health of millions of people in China. Bacillus amyloliquefaciens has been reported to be able to alleviate the damage to the gut and liver and maintain the homeostasis of the intestinal microenvironment. However, it was unclear whether B. amyloliquefaciens could alleviate the hepatic and intestinal symptoms caused by S. japonicum. In this study, the intragastric administration of B. amyloliquefaciens was performed to treat S. japonicum-infected mice during the acute phase. Histopathological analysis and 16S rRNA gene sequencing were used to evaluate the pathological damage and changes in the intestinal microbiome. The results of the study showed that B. amyloliquefaciens treatment significantly reduced the degree of granuloma and fibrosis in infected mice. Additionally, recovery of diversity in the intestinal microbiome, decrease in the relative abundance of potential pathogenic bacteria such as Escherichia-Shigella, and reshaping of the interactive network between genera in the intestine were also observed after treatment with B. amyloliquefaciens. Our findings indicated that treatment with B. amyloliquefaciens effectively alleviated the pathological injuries of the liver and intestine in mice infected with S. japonicum by modulating the intestinal microbiome, implying that this probiotic can function as an effective therapeutic agent against schistosomiasis. We hope our study will provide auxiliary strategies and methods for the early prevention of schistosomiasis japonica.

Metatranscriptomic analysis of the gut microbiome of black soldier fly larvae reared on lignocellulose-rich fiber diets unveils key lignocellulolytic enzymes

Recently, interest in the black soldier fly larvae (BSFL) gut microbiome has received increased attention primarily due to their role in waste bioconversion. However, there is a lack of information on the positive effect on the activities of the gut microbiomes and enzymes (CAZyme families) acting on lignocellulose. In this study, BSFL were subjected to lignocellulose-rich diets: chicken feed (CF), chicken manure (CM), brewers' spent grain (BSG), and water hyacinth (WH). The mRNA libraries were prepared, and RNA-Sequencing was conducted using the PCR-cDNA approach through the MinION sequencing platform. Our results demonstrated that BSFL reared on BSG and WH had the highest abundance of Bacteroides and Dysgonomonas. The presence of GH51 and GH43_16 enzyme families in the gut of BSFL with both α-L-arabinofuranosidases and exo-alpha-L-arabinofuranosidase 2 were common in the BSFL reared on the highly lignocellulosic WH and BSG diets. Gene clusters that encode hemicellulolytic arabinofuranosidases in the CAZy family GH51 were also identified. These findings provide novel insight into the shift of gut microbiomes and the potential role of BSFL in the bioconversion of various highly lignocellulosic diets to fermentable sugars for subsequent value-added products (bioethanol). Further research on the role of these enzymes to improve existing technologies and their biotechnological applications is crucial.

Role of microbiota and microbiota-derived short-chain fatty acids in PDAC

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive lethal diseases among other cancer types. Gut microbiome and its metabolic regulation play a crucial role in PDAC. Metabolic regulation in the gut is a complex process that involves microbiome and microbiome-derived short-chain fatty acids (SCFAs). SCFAs regulate inflammation, as well as lipid and glucose metabolism, through different pathways. This review aims to summarize recent developments in PDAC in the context of gut and oral microbiota and their associations with short-chain fatty acid (SCFA). In addition to this, we discuss possible therapeutic applications using microbiota in PDAC.

Lower gut dysbiosis and mortality in acute critical illness: a systematic review and meta-analysis

BACKGROUND

The human gastrointestinal tract harbours a complex multi-kingdom community known as the microbiome. Dysbiosis refers to its disruption and is reportedly extreme in acute critical illness yet its clinical implications are unresolved. The review systematically evaluates the association between gut dysbiosis and clinical outcomes of patients early in critical illness.

METHODS

Following PRISMA guidelines, a prospectively registered search was undertaken of MEDLINE and Cochrane databases for observational studies undertaking metagenomic sequencing of the lower gastrointestinal tract of critically ill adults and children within 72 h of admission. Eligible studies reported an alpha diversity metric and one or more of the primary outcome, in-hospital mortality, or secondary clinical outcomes. After aggregate data were requested, meta-analysis was performed for four studies with in-hospital mortality stratified to high or low Shannon index.

RESULTS

The search identified 26 studies for systematic review and 4 had suitable data for meta-analysis. No effect of alpha diversity was seen on in-hospital mortality after binary transformation of Shannon index (odds ratio 0.52, CI 0.12-4.98, I² = 0.64) however certainty of evidence is low. Pathogen dominance and commensal depletion were each more frequently associated with in-hospital mortality, adverse clinical and ecological sequelae, particularly overabundance of Enterococcus.

CONCLUSIONS

There is a paucity of large, rigorous observational studies in this population. Globally, alpha diversity was dynamically reduced in early ICU admission in adults and children and was not associated with in-hospital mortality. The abundance of taxa such as Enterococcus spp. appears to offer greater predictive capacity for important clinical and ecological outcomes.

EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research

It is difficult for beginners to learn and use amplicon analysis software because there are so many software tools to choose from, and all of them need multiple steps of operation. Herein, we provide a cross-platform, open-source, and community-supported analysis pipeline EasyAmplicon. EasyAmplicon has most of the modules needed for an amplicon analysis, including data quality control, merging of paired-end reads, dereplication, clustering or denoising, chimera detection, generation of feature tables, taxonomic diversity analysis, compositional analysis, biomarker discovery, and publication-quality visualization. EasyAmplicon includes more than 30 cross-platform modules and R packages commonly used in the field. All steps of the pipeline are integrated into RStudio, which reduces learning costs, keeps the flexibility of the analysis process, and facilitates personalized analysis. The pipeline is maintained and updated by the authors and editors of WeChat official account "Meta-genome." Our team will regularly release the latest tutorials both in Chinese and English, read the feedback from users, and provide help to them in the WeChat account and GitHub. The pipeline can be deployed on various platforms, and the installation time is less than half an hour. On an ordinary laptop, the whole analysis process for dozens of samples can be completed within 3 h. The pipeline is available at GitHub (https://github.com/YongxinLiu/EasyAmplicon) and Gitee (https://gitee.com/YongxinLiu/EasyAmplicon).

OmicStudio: A composable bioinformatics cloud platform with real-time feedback that can generate high-quality graphs for publication

OmicStudio focuses on speed, quality together with flexibility. Generally, OmicStudio can not only meet the users' demand of ordinary bioinformatics data analysis, statistics, and visualization, but also provides them freedom of data mining beyond developer's framework. Additionally, unlimited to developer's aesthetics, users can get more elegant graphs through customizing. Available online https://www.omicstudio.cn.

The Role of Intratumor Microbiomes in Cervical Cancer Metastasis

BACKGROUND

Intratumor microbiomes can influence tumorigenesis and progression. The relationship between intratumor microbiomes and cervical cancer metastasis, however, remains unclear.

METHODS

We examined 294 cervical cancer samples together with information on microbial expression, identified metastasis-associated microbiomes, and used machine learning methods to validate their predictive ability on tumor metastasis. The tumors were subsequently typed based on differences in microbial expression. Differentially expressed genes in different tumor types were combined to construct a tumor-prognostic risk score model and a multiparameter nomogram model. In addition, we performed a functional enrichment analysis of differentially expressed genes to infer the mechanism of action between microbiomes and tumor cells.

RESULTS

Based on the 15 differentially expressed microbiomes, machine learning models were able to correctly predict the risk of cervical cancer metastasis. In addition, both the risk score and the nomogram model accurately predicted tumor prognosis. Differences in the expression of endogenous genes in tumors can influence the distribution of the intracellular microbiomes.

CONCLUSIONS

Intratumoral microbiomes in cervical cancer are associated with tumor metastasis and influence disease prognosis. A change in gene expression within tumor cells is responsible for differences in the microbial populations within the tumor.

GutAlive® enables DNA-based microbiome analysis without disrupting the original composition and diversity

Introduction

A precise fecal microbiome analysis requires normalized methods for microbiome sampling, transport and manipulation in order to obtain a representative snapshot of the microbial community. GutAlive^® is the unique stool collection kit that generates an anaerobic atmosphere enabling oxygen sensitive bacteria to survive, maintaining the original microbiome composition and diversity.

Methods

Five stool samples from different donors were collected using two different sampling devices, GutAlive^® and Zymo DNA/RNA Shield^®, and processed at four different time points. Shotgun metagenomics was used to evaluate the influence of the device and the processing timing on the microbial populations to unravel the potential fluctuations on the composition and diversity of the fecal microbiome and the metabolic pathways profiling. Additionally, RT-qPCR was used to quantify bacterial cell viability for downstream applications of microbiota samples beyond metagenomics.

Results

Our results show that GutAlive^® enables bacterial cell viability overtime preserving DNA integrity, obtaining high-quantity and high-quality DNA to perform microbiome analysis using shotgun metagenomics. Based on the taxonomic profiling, metabolic pathways analysis, phylogeny and metagenome-assembled genomes, GutAlive^® displayed greater performance without significant variability over time, showcasing the stabilization of the microbiome preserving the original composition and diversity. Indeed, this DNA stabilization is enabled with the preservation of bacterial viability on an anaerobic environment inside of the sampling device, without the addition of any reagents that interact directly with sample.

Conclusion

All the above makes GutAlive^® an user-friendly kit for self-collection of biological samples, suitable for microbiome analysis, diagnostics, fecal microbiota transplant and bacterial isolation, maintaining the stability and bacterial viability over time, preserving the original composition and diversity of the microbiome.

Optimization of DNA extraction and sampling methods for successful forensic microbiome analyses of the skin and saliva

Microbiome studies have contributed to many fields, such as healthcare and medicine; however, these studies are relatively limited in forensics. Microbiome analyses can provide information, such as geolocation and ancestry information, when short tandem repeat (STR) profiling fails. In this study, methods for DNA extraction and sampling from the skin and saliva were optimized for the construction of a Korean Forensic Microbiome Database (KFMD). DNA yields were estimated using four DNA extraction kits, including two automated kits (Maxwell® FSC DNA IQ™ Casework Kit and PrepFiler™ Forensic DNA Extraction Kit, updated) and two manual kits (QIAamp DNA Mini Kit and QIAamp DNA Micro Kit) commonly used in forensic DNA profiling laboratories. Next-generation sequencing of the 16S rRNA V4 region was performed to analyze microbial communities in samples. The Bacterial Transport Swab with Liquid Media (NobleBio), two cotton swabs (PoongSung and Puritan), and nylon-flocked swabs (NobleBio and COPAN) were tested for DNA recovery. The PrepFiler and Maxwell kits showed the highest yields of 3.884 ng/μL and 23.767 ng/μL from the scalp and saliva, respectively. With respect to DNA recovery, nylon-flocked swabs performed better than cotton swabs. The relative abundances of taxa sorted by DNA extraction kits were similar contributions; however, with significant differences in community composition between scalp and saliva samples. Lawsonella and Veillonella were the most abundant genera in the two sample types. Thus, the Maxwell® FSC DNA IQ™ Casework Kit and nylon-flocked swab (NobleBio) were optimal for DNA extraction and collection in microbiome analyses.

Gastrointestinal symptoms, gut microbiome, probiotics and prebiotics in anorexia nervosa: A review of mechanistic rationale and clinical evidence

Recent research has revealed the pivotal role that the gut microbiota might play in psychiatric disorders. In anorexia nervosa (AN), the gut microbiota may be involved in pathophysiology as well as in the gastrointestinal (GI) symptoms commonly experienced. This review collates evidence for the potential role of gut microbiota in AN, including modulation of the immune system, the gut-brain axis and GI function. We examined studies comparing gut microbiota in AN with healthy controls as well as those looking at modifications in gut microbiota with nutritional treatment. Changes in energy intake and nutritional composition influence gut microbiota and may play a role in the evolution of the gut microbial picture in AN. Additionally, some evidence indicates that pre-morbid gut microbiota may influence risk of developing AN. There appear to be similarities in gut microbial composition, mechanisms of interaction and GI symptoms experienced in AN and other GI disorders such as inflammatory bowel disease and functional GI disorders. Probiotics and prebiotics have been studied in these disorders showing therapeutic effects of probiotics in some cases. Additionally, some evidence exists for the therapeutic benefits of probiotics in depression and anxiety, commonly seen as co-morbidities in AN. Moreover, preliminary evidence for the use of probiotics in AN has shown positive effects on immune modulation. Based on these findings, we discuss the potential therapeutic role for probiotics in ameliorating symptoms in AN.

Probiotic supplementation for neonates with congenital gastrointestinal surgical conditions: guidelines for future research

Our pilot RCT found that probiotic supplementation with the three-strain bifidobacterial product (B. breve M-16V, B. longum subsp. infantis M-63 and B. longum subsp. longum BB536) attenuates gut dysbiosis, increases stool short-chain fatty acid (SCFA) levels and improves the growth of head circumference in neonates with congenital gastrointestinal surgical conditions (CGISC). In this article, we have provided guidelines for designing future multicentre RCTs based on the experience gained from our pilot RCT. The recommendations include advice about sample size, potential confounders, outcomes of interest, probiotic strain selection, storage, dose, duration and microbial quality assurance, collection of stool samples, storage and analysis and reporting. Following these guidelines will increase the validity of future RCTs in this area and hence confidence in their results. IMPACT: Probiotic supplementation attenuates gut dysbiosis, increases stool short-chain fatty acid (SCFA) levels and improves the growth of head circumference in neonates with congenital gastrointestinal surgical conditions. The current review provides evidence-based guidelines to conduct adequately powered RCTs in this field.

Food Peptides, Gut Microbiota Modulation, and Antihypertensive Effects

The gut microbiota is increasingly important in the overall human health and as such, it is a target in the search of novel strategies for the management of metabolic disorders including blood pressure, and cardiovascular diseases. The link between microbiota and hypertension is complex and this review is intended to provide an overview of the mechanism including the production of postbiotics, mitigation of inflammation, and the integration of food biological molecules within this complex system. The focus is on hydrolyzed food proteins and peptides which are less commonly investigated for prebiotic properties. The analysis of available data showed that food peptides are multifunctional and can prevent gut dysbiosis by positively affecting the production of postbiotics or gut metabolites (short-chain fatty acids, polysaccharides, biogenic amines, bile acids). Peptides and the postbiotics then displayed antihypertensive effects via the renin-angiotensin system, the gut barrier, the endothelium, and reduction in inflammation and oxidative stress. Despite the promising antihypertensive effect of the food peptides via the modulation of the gut, there is a lack of human studies as most of the works have been conducted in animal models.

MetaTrass: A high-quality metagenome assembler of the human gut microbiome by cobarcoding sequencing reads

Metagenomic evidence of great genetic diversity within the nonconserved regions of the human gut microbial genomes appeals for new methods to elucidate the species-level variability at high resolution. However, current approaches cannot satisfy this methodologically challenge. In this study, we proposed an efficient binning-first-and-assembly-later strategy, named MetaTrass, to recover high-quality species-resolved genomes based on public reference genomes and the single-tube long fragment read (stLFR) technology, which enables cobarcoding. MetaTrass can generate genomes with longer contiguity, higher completeness, and lower contamination than those produced by conventional assembly-first-and-binning-later strategies. From a simulation study on a mock microbial community, MetaTrass showed the potential to improve the contiguity of assembly from kb to Mb without accuracy loss, as compared to other methods based on the next-generation sequencing technology. From four human fecal samples, MetaTrass successfully retrieved 178 high-quality genomes, whereas only 58 ones were provided by the optimal performance of other conventional strategies. Most importantly, these high-quality genomes confirmed the high level of genetic diversity among different samples and unveiled much more. MetaTrass was designed to work with metagenomic reads sequenced by stLFR technology, but is also applicable to other types of cobarcoding libraries. With the high capability of assembling high-quality genomes of metagenomic data sets, MetaTrass seeks to facilitate the study of spatial characters and dynamics of complex microbial communities at enhanced resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass.

Influence of organic rice production mode on weed composition in the soil seed bank of paddy fields

INTRODUCTION

It is of great significance to determine the composition of the soil weed seed bank under different organic rice production modes to provide decision making support for rational integrated weed management in organic rice production.

METHODS

The soil weed seed bank of the four dominant organic production modes, namely, rice-green manure rotation (RG), rice monoculture (RM), rice-crayfish coculture (RC) and rice-duck coculture (RD), with different numbers of consecutive planting years (3 to 10 years) in different sites in Jiangsu Province were investigated to determine the influence of organic rice production mode on weed composition.

RESULTS AND DISCUSSION

There were significant differences in the weed composition in the soil seed bank among the four organic rice production modes. The most dominant weed group was broadleaf weeds in the soil seed bank under the RG and RM modes; however, under the RM mode, the most dominant weed species were sedge and grass weeds. Sedge and grass weeds dominated the soil seed bank of the RC and RD modes, respectively. Therefore, specific weed management strategies could be formulated based on the differences in weed composition under different organic rice production modes. The application of organic fertilizer and irrigation were identified as primary factors associated with the differences in weed composition in the soil seed banks, which had higher effects on the weed composition than hand weeding. Consequently, fertilization and irrigation strategies that alter weed composition could be used as improved weed management program components in organic rice production systems. Long-term organic rice planting is beneficial for increasing weed diversity in paddy fields. Our results indicated that weed species diversity increased and weed community evenness and dominance decreased with the increase in the number of consecutive planting years under all four organic rice production modes.

Early-life chemical exposome and gut microbiome development: African research perspectives within a global environmental health context

The gut microbiome of neonates, infants, and toddlers (NITs) is very dynamic, and only begins to stabilize towards the third year of life. Within this period, exposure to xenobiotics may perturb the gut environment, thereby driving or contributing to microbial dysbiosis, which may negatively impact health into adulthood. Despite exposure of NITs globally, but especially in Africa, to copious amounts and types of xenobiotics - such as mycotoxins, pesticide residues, and heavy metals - little is known about their influence on the early-life microbiome or their effects on acute or long-term health. Within the African context, the influence of fermented foods, herbal mixtures, and the delivery environment on the early-life microbiome are often neglected, despite being potentially important factors that influence the microbiome. Consequently, data on in-depth understanding of the microbiome-exposome interactions is lacking in African cohorts. Collecting and evaluating such data is important because exposome-induced gut dysbiosis could potentially favor disease progression.

One-year supplementation with Lactobacillus reuteri ATCC PTA 6475 counteracts a degradation of gut microbiota in older women with low bone mineral density

Recent studies have shown that probiotic supplementation has beneficial effects on bone metabolism. In a randomized controlled trial (RCT) we demonstrated that supplementation of Lactobacillus reuteri ATCC PTA 6475 reduced bone loss in older women with low bone mineral density. To investigate the mechanisms underlying the effect of L. reuteri ATCC PTA 6475 on bone metabolism, 20 women with the highest changes (good responders) and the lowest changes (poor responders) in tibia total volumetric BMD after one-year supplementation were selected from our previous RCT. In the current study we characterized the gut microbiome composition and function as well as serum metabolome in good responders and poor responders to the probiotic treatment as a secondary analysis. Although there were no significant differences in the microbial composition at high taxonomic levels, gene richness of the gut microbiota was significantly higher (P < 0.01 by the Wilcoxon rank-sum test) and inflammatory state was improved (P < 0.05 by the Wilcoxon signed-rank test) in the good responders at the end of the 12-month daily supplementation. Moreover, detrimental changes including the enrichment of E. coli (adjusted P < 0.05 by DESeq2) and its biofilm formation (P < 0.05 by GSA) observed in the poor responders were alleviated in the good responders by the treatment. Our results indicate that L. reuteri ATCC PTA 6475 supplementation has the potential to prevent a deterioration of the gut microbiota and inflammatory status in elderly women with low bone mineral density, which might have beneficial effects on bone metabolism.

Bringing pharmacomicrobiomics to the clinic through well-designed studies

Pharmacomicrobiomic studies investigate drug-microbiome interactions, such as the effect of microbial variation on drug response and disposition. Studying and understanding the interactions between the gut microbiome and drugs is becoming increasingly relevant to clinical practice due to its potential for avoiding adverse drug reactions or predicting variability in drug response. The highly variable nature of the human microbiome presents significant challenges to assessing microbes' influence. Studies aiming to explore drug-microbiome interactions should be well-designed to account for variation in the microbiome over time and collect data on confounders such as diet, disease, concomitant drugs, and other environmental factors. Here, we assemble a set of important considerations and recommendations for the methodological features required for performing a pharmacomicrobiomic study in humans with a focus on the gut microbiome. Consideration of these factors enable discovery, reproducibility, and more accurate characterization of the relationships between a given drug and the microbiome. Furthermore, appropriate interpretation and dissemination of results from well-designed studies will push the field closer to clinical relevance and implementation.

Vaginal microbiota and personal risk factors associated with HPV status conversion—A new approach to reduce the risk of cervical cancer?

Vaginal microbiota (VMB) is associated with changes in Human papilloma virus (HPV) status, which consequently influences the risk of cervical cancer. This association was often confounded by personal risk factors. This pilot research aimed to explore the relationship between vaginal microbiota, personal risk factors and their interactions with HPV status conversion to identify the vaginal microbiota that was associated with HPV clearance under heterogeneous personal risk factors. A total of 38 women participated by self-collecting a cervicovaginal mucus (CVM) sample that was sent for metagenomics sequencing. Most of the participants also filled in personal risk factors questionnaire through an eHealth platform and authorized the use of their previous HPV genotyping results stored in this eHealth platform. Based on the two HPV results, the participants were grouped into three cohorts, namely HPV negative, HPV persistent infection, and HPV status conversion. The relative abundance of VMB and personal factors were compared among these three cohorts. A correlation investigation was performed between VMB and the significant personal factors to characterize a robustness of the panel for HPV status change using R programming. At baseline, 12 participants were HPV-negative, and 22 were HPV-positive. Within one year, 18 women remained HPV-positive, 12 were HPV-negative and 4 participants showed HPV clearance. The factors in the eHealth questionnaire were systematically evaluated which identified several factors significantly associated with persistent HPV infection, including age, salary, history of reproductive tract infection, and the total number of sexual partners. Concurrent vaginal microbiome samples suggest that a candidate biomarker panel consisting of Lactobacillus gasseri, Streptococcus agalactiae, and Timona prevotella bacteria, which may be associated with HPV clearance. This pilot study indicates a stable HPV status-related vaginal microbe environment. To establish a robust biomarker panel for clinical use, larger cohorts will be recruited into follow-up studies.

Alteration in Gut Microbiota Associated with Zinc Deficiency in School-Age Children

Zinc deficiency could lead to a dynamic variation in gut microbial composition and function in animals. However, how zinc deficiency affects the gut microbiome in school-age children remains unclear. The purpose of this study was to profile the dynamic shifts in the gut microbiome of school-age children with zinc deficiency, and to determine whether such shifts are associated with dietary intake. A dietary survey, anthropometric measurements, and serum tests were performed on 177 school-age children, and 67 children were selected to explore the gut microbial community using amplicon sequencing. School-age children suffered from poor dietary diversity and insufficient food and nutrient intake, and 32% of them were zinc deficient. The inflammatory cytokines significantly increased in the zinc deficiency (ZD) group compared to that in the control (CK) group (p < 0.05). There was no difference in beta diversity, while the Shannon index was much higher in the ZD group (p < 0.05). At the genus level, Coprobacter, Acetivibrio, Paraprevotella, and Clostridium_XI were more abundant in the ZD group (p < 0.05). A functional predictive analysis showed that the metabolism of xenobiotics by cytochrome P450 was significantly depleted in the ZD group (p < 0.05). In conclusion, gut microbial diversity was affected by zinc deficiency with some specific bacteria highlighted in the ZD group, which may be used as biomarkers for further clinical diagnosis of zinc deficiency.

Scoping Review of the Relationship Between Gestational Diabetes Mellitus and the Neonatal and Infant Gut Microbiome

OBJECTIVE

To conduct a scoping review to examine the relationship between a diagnosis of gestational diabetes mellitus (GDM) and the neonatal and infant gut microbiome from 0 to 1 year of age.

DATA SOURCES

We searched PubMed, Scopus, Embase, and CINAHL for articles with key terms "microbiome" and "gestational diabetes mellitus."

STUDY SELECTION

We included articles published in English in peer-reviewed journals between 2012 and 2021 that were reports of original research studies in which researchers used next-generation sequencing for analysis of the fecal microbiome and collected meconium or transitional stool from neonates and infants.

DATA EXTRACTION

We identified nine studies with a combined sample size of 1,279 neonates and infants. We extracted data, including title, authors, sample size, study design, methods, findings, significance, and limitations. We extracted and charted confounding variables such as treatment of GDM, body mass index, gestational age at birth, antibiotic use, mode of birth, and feeding method.

DATA SYNTHESIS

Gestational diabetes mellitus may alter the neonatal and infant gut microbiome because neonates and infants of women with GDM had altered composition and diversity compared to neonates and infants of women without GDM.

CONCLUSION

Mechanisms by which the neonatal and infant microbiome changes in response to GDM are poorly understood and need to be evaluated in future research. Further study of how GDM plays a role in the initial seeding of the microbiome, how the maternal microbiome may affect fetal metabolic programming, and how the neonatal microbiome leads to the future development of obesity and glucose intolerance is critical. Future studies should include larger sample sizes, appropriate collection of potential confounding variables, assessment of maternal interventions for GDM, and longitudinal designs to further understand potential associations with long-term detrimental outcomes such as obesity and impaired glucose tolerance.

Differences in Alpha Diversity of Gut Microbiota in Neurological Diseases

Background

Neurological diseases are difficult to diagnose in time, and there is currently a lack of effective predictive methods. Previous studies have indicated that a variety of neurological diseases cause changes in the gut microbiota. Alpha diversity is a major indicator to describe the diversity of the gut microbiota. At present, the relationship between neurological diseases and the alpha diversity of the gut microbiota remains unclear.

Methods

We performed a systematic literature search of Pubmed and Bioproject databases up to January 2021. Six indices were used to measure alpha diversity, including community richness (observed species, Chao1 and ACE), community diversity (Shannon, Simpson), and phylogenetic diversity (PD). Random-effects meta-analyses on the standardized mean difference (SMD) were carried out on the alpha diversity indices. Subgroup analyses were performed to explore the sources of interstudy heterogeneity. Meta-analysis was performed on articles by matching the age, sex, and body mass index (BMI) of the disease group with the control group. Meanwhile, subgroup analysis was performed to control the variability of the sequencing region, platform, geographical region, instrument, and diseases. The area under the curve (AUC) value of the receiver operating characteristic (ROC) curve was calculated to assess the prediction effectiveness of the microbial alpha diversity indices.

Results

We conducted a meta-analysis of 24 published studies on 16S rRNA gene amplified sequencing of the gut microbiota and neurological diseases from the Pubmed and Bioproject database (patients, n = 1,469; controls, n = 1,289). The pooled estimate demonstrated that there was no significant difference in the alpha diversity between patients and controls (P < 0.05). Alpha diversity decreased only in Parkinson's disease patients, while it increased in anorexia nervosa patients compared to controls. After adjusting for age, sex, BMI, and geographical region, none of the alpha diversity was associated with neurological diseases. In terms of Illumina HiSeq 2000 and the V3-V5 sequencing region, the results showed that alpha diversity increased significantly in comparison with the controls, while decreased in Illumina HiSeq 2500. ROC curves suggested that alpha diversity could be used as a biomarker to predict the AD (Simpson, AUC= 0.769, P = 0.0001), MS (observed species, AUC= 0.737, P = 0.001), schizophrenia (Chao1, AUC = 0.739, P = 0.002).

Conclusions

Our review summarized the relationship between alpha diversity of the gut microbiota and neurological diseases. The alpha diversity of gut microbiota could be a promising predictor for AD, schizophrenia, and MS, but not for all neurological diseases.

Pragmatic Expectancy on Microbiota and Non-Small Cell Lung Cancer: A Narrative Review

It is well known that lung cancer relies on a number of genes aberrantly expressed because of somatic lesions. Indeed, the lungs, based on their anatomical features, are organs at a high risk of development of extremely heterogeneous tumors due to the exposure to several environmental toxic agents. In this context, the microbiome identifies the whole assemblage of microorganisms present in the lungs, as well as in distant organs, together with their structural elements and metabolites, which actively interact with normal and transformed cells. A relevant amount of data suggest that the microbiota plays a role not only in cancer disease predisposition and risk but also in its initiation and progression, with an impact on patients’ prognosis. Here, we discuss the mechanistic insights of the complex interaction between lung cancer and microbiota as a relevant component of the microenvironment, mainly focusing on novel diagnostic and therapeutic objectives.

Stressful events induce long-term gut microbiota dysbiosis and associated post-traumatic stress symptoms in healthcare workers fighting against COVID-19

OBJECTIVE

The microbiota-gut-brain axis is a key pathway perturbed by prolonged stressors to produce brain and behavioral disorders. Frontline healthcare workers (FHWs) fighting against COVID-19 typically experience stressful event sequences and manifest some mental symptoms; however, the role of gut microbiota in such stress-induced mental problems remains unclear. We investigated the association between the psychological stress of FHW and gut microbiota.

METHODS

We used full-length 16S rRNA gene sequencing to characterize the longitudinal changes in gut microbiota and investigated the impact of microbial changes on FHWs' mental status.

RESULTS

Stressful events induced significant depression, anxiety, and stress in FHWs and disrupted the gut microbiome; gut dysbiosis persisted for at least half a year. Different microbes followed discrete trajectories during the half-year of follow-up. Microbes associated with mental health were mainly Faecalibacterium spp. and [Eubacterium] eligens group spp. with anti-inflammatory effects. Of note, the prediction model indicated that low abundance of [Eubacterium] hallii group uncultured bacterium and high abundance of Bacteroides eggerthii at Day 0 (immediately after the two-month frontline work) were significant determinants of the reappearance of post-traumatic stress symptoms in FHWs.

LIMITATIONS

The lack of metabolomic evidence and animal experiments result in the unclear mechanism of gut dysbiosis-related stress symptoms.

CONCLUSION

The stressful event sequences of fighting against COVID-19 induce characteristic longitudinal changes in gut microbiota, which underlies dynamic mental state changes.

Oral microbiome research - A Beginner's glossary

Oral microbiome plays a key role in the etiology of oral diseases and is linked to many diseases in other parts of the body as well. This makes the oral microbiome an area of interest for researchers globally. A meticulous planning of the research project is the first and most crucial step while conducting an oral microbiome study. For beginners in this field, it is essential to be familiar with the terminologies used in oral microbiome research for a better understanding. The purpose of this article is to familiarize new researchers to the frequently used terms for the field of oral microbiome research.

Gut microbiota and migraine

Migraine is a leading cause of disability among the adult population and is a significant burden on the economies of the world. Studies into the underlying causes of migraine have spanned centuries but its underlying mechanisms are still not fully understood. In recent years, accumulating evidence implicates that microbiota-mediated gut-brain crosstalk may contribute to the pathogenesis of migraine. This review provides a brief account of the history of migraine theories and summarizes the recent studies showing how gut microbiota is involved in the pathophysiology of migraine. Future research perspectives for better understanding the role of the gut microbiota in migraine are also discussed.

Centennial Review: Factors affecting the chicken gastrointestinal microbial composition and their association with gut health and productive performance

Maintenance of "gut health" is considered a priority in commercial chicken farms, although a precise definition of what constitutes gut health and how to evaluate it is still lacking. In research settings, monitoring of gut microbiota has gained great attention as shifts in microbial community composition have been associated with gut health and productive performance. However, microbial signatures associated with productivity remain elusive because of the high variability of the microbiota of individual birds resulting in multiple and sometimes contradictory profiles associated with poor or high performance. The high costs associated with the testing and the need for the terminal sampling of a large number of birds for the collection of gut contents also make this tool of limited use in commercial settings. This review highlights the existing literature on the chicken digestive system and associated microbiota; factors affecting the gut microbiota and emergence of the major chicken enteric diseases coccidiosis and necrotic enteritis; methods to evaluate gut health and their association with performance; main issues in investigating chicken microbial populations; and the relationship of microbial profiles and production outcomes. Emphasis is given to emerging noninvasive and easy-to-collect sampling methods that could be used to monitor gut health and microbiological changes in commercial flocks.

Variability of Classification Results in Data with High Dimensionality and Small Sample Size

The study focuses on the analysis of biological data containing information on the number of genome sequences of intestinal microbiome bacteria before and after antibiotic use. The data have high dimensionality (bacterial taxa) and a small number of records, which is typical of bioinformatics data. Classification models induced on data sets like this usually are not stable and the accuracy metrics have high variance. The aim of the study is to create a preprocessing workflow and a classification model that can perform the most accurate classification of the microbiome into groups before and after the use of antibiotics and lessen the variability of accuracy measures of the classifier. To evaluate the accuracy of the model, measures of the area under the ROC curve and the overall accuracy of the classifier were used. In the experiments, the authors examined how classification results were affected by feature selection and increased size of the data set.

Evaluation of Effects of Laboratory Disinfectants on Mouse Gut Microbiota

Disturbances in the gut microbiota are known to be associated with numerous human diseases. Mice have proven to be an invaluable tool for investigating the role of the gut microbiota in disease processes. Nonexperimental factors related to maintaining mice in the laboratory environment are increasingly being shown to have inadvertent effects on the gut microbiotaand may function as confounding variables. Microisolation technique is a term used to describe the common biosecuritypractice of spraying gloved hands with disinfectant before handling research mice. This practice prevents contamination with pathogenic microorganisms. To investigate if exposure to disinfectants can affect the mouse gut microbiota, C57BL/6 micewere exposed daily for 27 consecutive days to commonly used laboratory disinfectants through microisolation technique.The effects of 70% ethanol and disinfectant products containing chlorine dioxide, hydrogen peroxide, or potassium peroxymonosulfate were each evaluated. Fecal pellets were collected after 7, 14, 21, and 28 d of disinfectant exposure, and cecal contents were collected at day 28. DNA extractions were performed on all cecal and fecal samples, and microbial community structure was characterized using 16S ribosomal RNA amplicon sequencing. Alpha and β diversity metrics and taxon-level analyses were used to evaluate differences in microbial communities. Disinfectant had a small but significant effect on fecal microbial communities compared with sham-exposed controls, and effects varied by disinfectant type. In general, longerexposure times resulted in greater changes in the fecal microbiota. Effects on the cecal microbiota were less pronounced and only seen with the hydrogen peroxide and potassium peroxymonosulfate disinfectants. These results indicate that laboratory disinfectant use should be considered as a potential factor that can affect the mouse gut microbiota.

Impact of Concurrent Training on Body Composition and Gut Microbiota in Postmenopausal Women with Overweight or Obesity

PURPOSE

Menopause tends to be associated with an increased risk of obesity and abdominal fat mass (FM) and is associated with lower intestinal species diversity. The aim of this study was to determine the effects of a high-intensity interval training and resistance training (HIIT + RT) program on body composition and intestinal microbiota composition in overweight or obese postmenopausal women.

METHODS

Participants (n = 17) were randomized in two groups: HIIT + RT group (3 × / week, 12 weeks) and control group without any training. Dual-energy X-ray absorptiometry was used to measure whole-body and abdominal/visceral FM and fat-free mass. Intestinal microbiota composition was determined by 16S rRNA gene sequencing at baseline and at the study end, and the diet controlled.

RESULTS

Compared with sedentary controls, physical fitness (Maximal Oxygen Consumption, Peak Power Output) increased, total abdominal and visceral FM decreased, and segmental muscle mass increased in the training group. Although the HIIT + RT protocol did not modify α-diversity and taxonomy, it significantly influenced microbiota composition. Moreover, various intestinal microbiota members were correlated with HIIT + RT-induced body composition changes, and baseline microbiota composition predicted the response to the HIIT + RT program.

CONCLUSIONS

HIIT + RT is an effective modality to reduce abdominal/visceral FM and improve physical capacity in non-dieting overweight or obese postmenopausal women. Training modified intestinal microbiota composition and the response to training seems to depend on the initial microbiota profile. More studies are needed to determine whether microbiota composition could predict the individual training response.

The ultra-structural, metabolomic and metagenomic characterisation of the sudanese smokeless tobacco 'Toombak'

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Toombak, a form of moist smokeless tobacco from Sudan is placed as a dip in the oral cavity most commonly used by males.

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The microbiome of Toombak predominantly consists of the phyla, Firmicutes and Actinobacteria while abundant species include Corynebacterium casei, Atopostipes suicloacalis and Oceanobacillus chironomi.

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High concentrations of iron, volatile aldehydes and tobacco specific nitrosamines were found in Toombak and can lead to toxicity.

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Toombak has a non-homogenous abrasive surface with a high sodium level in the ready to buy form that can damage the oral mucosa.

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New measures must be taken in Sudan to limit harmful compounds in Toombak.

Toombak is a smokeless tobacco produced from the Nicotiana rustica tobacco plant from Sudan. Pre-prepared and ready to buy Toombak samples were analysed using mass spectrometry (heavy metals), gas and liquid chromatography (metabolomics), 16S rRNA metagenomic sequencing (microbiome) and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX) and pH analysis.

Chromium, cobalt, and copper were high in the pre-prepared form of Toombak while iron, tobacco specific nitrosamines (TSNAs), formaldehyde and acetaldehyde were high in both types. Firmicutes and Actinobacteria dominated Toombak. Samples of ready to buy Toombak showed inter-variational differences depending on place of purchase. We found Virgibacillus were increased in the pre-prepared form while Corynebacterium casei, Atopococus tabaci, Atopostipes suicloacalis, Oceanobacillus chironomi and Staphylococcus gallinarum were the most abundant species in the ready to buy forms. PICRUSt analysis highlighted increased activity of metal transport systems in the ready to buy samples as well as an antibiotic transport system. SEM-EDX highlighted large non-homogenous, irregular particles with increased sodium, while pH of samples was in the alkaline range.

The final composition of Toombak is affected by its method of preparation and the end product has the potential to impart many negative consequences on the health of its users. TSNA levels observed in Toombak were some of the highest in the world while the micro-environment of Toombak supports a distinct microbiota profile.

Differences in the individual curative effect of acupuncture for obese women with polycystic ovary syndrome based on metagenomic analysis: study protocol for a randomized controlled trial

BACKGROUND

Polycystic ovary syndrome is a common cause of infertility and shows a high incidence in women of reproductive age. Acupuncture is an appropriate adjunctive treatment for PCOS. However, the add-on effect of acupuncture as an adjunctive treatment for obese women with PCOS has not been studied, and previous studies indicate that there are individual differences in the curative effect of acupuncture, while deeper research on the mechanism of differences in the individual curative effect of acupuncture for obese women with PCOS is still lacking. This trial aims to assess the add-on treatment efficacy of acupuncture for obese women with PCOS and to explore the role of the gut microbiome on the differences in the individual curative effect of acupuncture based on metagenomic analysis.

METHODS/DESIGN

This is an open-label, randomized, controlled trial. A total of 86 obese women with PCOS will be recruited. Subjects will be randomly assigned to a study group and a control group in a 1:1 ratio, with 43 subjects in each group (10 patients from each group who meet the study criteria will participate in the metagenomic analysis). An additional 10 subjects who meet the study criteria will be recruited to a healthy control group. The study group will receive acupuncture and clomiphene citrate treatment; the control group will only receive clomiphene citrate. Acupuncture treatment will be conducted three times a week from the fifth day of menstruation or withdrawal bleeding until the start of the next menstruation, for up to three menstrual cycles. The primary outcome will be LH/FSH. The secondary outcomes will comprise biometric features, hormone biomarkers, metabolic biomarkers, inflammatory biomarkers, Self-Rating Anxiety Scale, Self-Rating Depression Scale, and metagenomic analysis. The outcomes will be measured at baseline and post-intervention. Data will be analyzed using SPSS 19.0, and the gut microbiome will be analyzed using metagenomic analysis.

DISCUSSION

In this study, we are evaluating the add-on effects of acupuncture and exploring the mechanism of the differences in the individual curative effect of acupuncture based on the gut microbiome, which may provide evidence to explain the different outcomes of different trials on acupuncture for PCOS and hopefully to provide a new aspect to study the mechanism of acupuncture's treatment effect.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2000029882 . Registered on 16 February 2020.