Emotional well-being and gut microbiome profiles by enterotype

Impact of the gut microbiome composition on social decision-making

There is increasing evidence for the role of the gut microbiome in the regulation of socio-affective behavior in animals and clinical conditions. However, whether and how the composition of the gut microbiome may influence social decision-making in health remains unknown. Here, we tested the causal effects of a 7-week synbiotic (vs. placebo) dietary intervention on altruistic social punishment behavior in an ultimatum game. Results showed that the intervention increased participants' willingness to forgo a monetary payoff when treated unfairly. This change in social decision-making was related to changes in fasting-state serum levels of the dopamine-precursor tyrosine proposing a potential mechanistic link along the gut-microbiota-brain-behavior axis. These results improve our understanding of the bidirectional role body-brain interactions play in social decision-making and why humans at times act "irrationally" according to standard economic theory.

Deciphering the Impact of Defecation Frequency on Gut Microbiome Composition and Diversity

This study explores the impact of defecation frequency on the gut microbiome structure by analyzing fecal samples from individuals categorized by defecation frequency: infrequent (1-3 times/week, n = 4), mid-frequent (4-6 times/week, n = 7), and frequent (daily, n = 9). Utilizing 16S rRNA gene-based sequencing and LC-MS/MS metabolome profiling, significant differences in microbial diversity and community structures among the groups were observed. The infrequent group showed higher microbial diversity, with community structures significantly varying with defecation frequency, a pattern consistent across all sampling time points. The Ruminococcus genus was predominant in the infrequent group, but decreased with more frequent defecation, while the Bacteroides genus was more common in the frequent group, decreasing as defecation frequency lessened. The infrequent group demonstrated enriched biosynthesis genes for aromatic amino acids and branched-chain amino acids (BCAAs), in contrast to the frequent group, which had a higher prevalence of genes for BCAA catabolism. Metabolome analysis revealed higher levels of metabolites derived from aromatic amino acids and BCAA metabolism in the infrequent group, and lower levels of BCAA-derived metabolites in the frequent group, consistent with their predicted metagenomic functions. These findings underscore the importance of considering stool consistency/frequency in understanding the factors influencing the gut microbiome.

Exploring the Role of Gut Microbiota in Patients with Alopecia Areata

Imbalances in gut microbiota reportedly contribute to the development of autoimmune diseases, but the association between the etiopathogenesis of alopecia areata (AA) and gut microbial dysbiosis remains unclear. This cross-sectional study was conducted to identify and compare the composition of the gut microbiome in patients affected by AA and those in a healthy control (HC) group, and to investigate possible bacterial biomarkers for the disease. Fecal samples were collected from 19 AA patients and 20 HCs to analyze the relationship with fecal bacteria. The three major genera constituting the gut microbiome of AA patients were Bacteroides, Blautia, and Faecalibacterium. The alpha diversity of the AA group was not statistically significant different from that of the HC group. However, bacterial community composition in the AA group was significantly different from that of HC group according to Jensen-Shannon dissimilarities. In patients with AA, we found an enriched presence of the genera Blautia and Eubacterium_g5 compared to the HC group (p < 0.05), whereas Bacteroides were less prevalent (p < 0.05). The gut microbiota of AA patients was distinct from those of the HC group. Our findings suggest a possible involvement of gut microbiota in in the as-yet-undefined pathogenesis of AA.

Differential network connectivity analysis for microbiome data adjusted for clinical covariates using jackknife pseudo-values

BACKGROUND

A recent breakthrough in differential network (DN) analysis of microbiome data has been realized with the advent of next-generation sequencing technologies. The DN analysis disentangles the microbial co-abundance among taxa by comparing the network properties between two or more graphs under different biological conditions. However, the existing methods to the DN analysis for microbiome data do not adjust for other clinical differences between subjects.

RESULTS

We propose a Statistical Approach via Pseudo-value Information and Estimation for Differential Network Analysis (SOHPIE-DNA) that incorporates additional covariates such as continuous age and categorical BMI. SOHPIE-DNA is a regression technique adopting jackknife pseudo-values that can be implemented readily for the analysis. We demonstrate through simulations that SOHPIE-DNA consistently reaches higher recall and F1-score, while maintaining similar precision and accuracy to existing methods (NetCoMi and MDiNE). Lastly, we apply SOHPIE-DNA on two real datasets from the American Gut Project and the Diet Exchange Study to showcase the utility. The analysis of the Diet Exchange Study is to showcase that SOHPIE-DNA can also be used to incorporate the temporal change of connectivity of taxa with the inclusion of additional covariates. As a result, our method has found taxa that are related to the prevention of intestinal inflammation and severity of fatigue in advanced metastatic cancer patients.

CONCLUSION

SOHPIE-DNA is the first attempt of introducing the regression framework for the DN analysis in microbiome data. This enables the prediction of characteristics of a connectivity of a network with the presence of additional covariate information in the regression. The R package with a vignette of our methodology is available through the CRAN repository ( https://CRAN.R-project.org/package=SOHPIE ), named SOHPIE (pronounced as Sofie). The source code and user manual can be found at https://github.com/sjahnn/SOHPIE-DNA .

Chronodisruption and Gut Microbiota: Triggering Glycemic Imbalance in People with Type 2 Diabetes

The desynchronization of physiological and behavioral mechanisms influences the gut microbiota and eating behavior in mammals, as shown in both rodents and humans, leading to the development of pathologies such as Type 2 diabetes (T2D), obesity, and metabolic syndrome. Recent studies propose resynchronization as a key input controlling metabolic cycles and contributing to reducing the risk of suffering some chronic diseases such as diabetes, obesity, or metabolic syndrome. In this analytical review, we present an overview of how desynchronization and its implications for the gut microbiome make people vulnerable to intestinal dysbiosis and consequent chronic diseases. In particular, we explore the eubiosis-dysbiosis phenomenon and, finally, propose some topics aimed at addressing chronotherapy as a key strategy in the prevention of chronic diseases.

Gut microbial signatures in clinically stable ulcerative colitis according to the mucosal state and associated symptoms

BACKGROUND AND AIM

The gut microbiome of patients with clinically stable ulcerative colitis (UC) differs from that of healthy individuals depending on the state of the colonic mucosa, especially with or without advanced scarring; however, the underlying mechanism is unclear. Therefore, this study examined the gut microbiome compositional signatures in patients with significant mucosal scarring and UC-related symptoms.

METHODS

Stool samples for gut microbiome analysis were prospectively collected from 57 patients with clinically stable UC between January 1 and December 31, 2022. Data from 57 individuals without inflammatory bowel disease (non-IBD) paired by age and sex were selected from our previous study as the control group. The fecal samples were subjected to 16S rRNA gene sequencing. Associations between gut microbiome profiles and clinical or colonoscopic assessments were examined using diversity and differential abundance analyses.

RESULTS

Gut microbiome compositions between the patients with clinically stable UC and non-IBD controls differed significantly. Furthermore, gut microbiome compositions varied between the preserved and altered mucosa groups identified based on mucosal changes in the UC group. Differential abundance test of patients with UC for symptomatic remission based on stool frequency from the two-item patient-reported outcome identified several overlapping taxa specified as gut microbiome signatures, including the Enterobacteriaceae unknown genera (Enterobacteriaceae_g), Klebsiella, and several Lachnospiraceae spp. both in mucosal and symptom change analyses.

CONCLUSIONS

The gut microbiome can change with mucosal changes, even in clinically stable UC, and some gut microbial signatures may explain the symptom manifestations in patients with UC showing significant mucosal changes.

Feasibility study for a fully decentralized clinical trial in participants with functional constipation symptoms

Decentralized clinical trials (DCTs) leverage digital technologies to reduce dependency on study sites and intermediaries. DCT should be balanced with accessibility and data reliability while meeting regulatory requirements. Here, we conducted a pilot study for functional constipation symptoms to investigate the feasibility of DCT. The study was an open, fully remote, randomized clinical trial in participants who had functional constipation symptoms. Electronic consent was obtained remotely, and study volunteers were screened through web-based questionnaires. Subjects were randomized to either receive Lactobacillus and vitamin C supplements or vitamin C alone in a 1:1 ratio, which were delivered directly to subjects. Subjects kept track of bowel diaries daily during the 1-week baseline and 2-week treatment period using mobile applications. Bowel symptoms and the validity of the records were descriptively evaluated. A total of 30 subjects were randomized and completed the study. A total of 26.7% of subjects resided outside of the metropolitan area. Two-week Lactobacillus treatments increased the number of defecations (+0.80 vs. +0.46 times per week) and decreased the defecation time (-3.94 h vs. -1.62 h) compared to the comparator group. Overall, 67.1% of bowel diary records were completed in accordance with the schedule whereas 32.9% were not. Implementation of DCTs can facilitate geographic accessibility but should be guaranteed for data reliability. Prompt detection of errors and response using objective metrics would be required.

Gut feelings: associations of emotions and emotion regulation with the gut microbiome in women

BACKGROUND

Accumulating evidence suggests that positive and negative emotions, as well as emotion regulation, play key roles in human health and disease. Recent work has shown the gut microbiome is important in modulating mental and physical health through the gut-brain axis. Yet, its association with emotions and emotion regulation are understudied. Here we examined whether positive and negative emotions, as well as two emotion regulation strategies (i.e. cognitive reappraisal and suppression), were associated with the gut microbiome composition and functional pathways in healthy women.

METHODS

Participants were from the Mind-Body Study (N = 206, mean age = 61), a sub-study of the Nurses' Health Study II cohort. In 2013, participants completed measures of emotion-related factors. Two pairs of stool samples were collected, 6 months apart, 3 months after emotion-related factors measures were completed. Analyses examined associations of emotion-related factors with gut microbial diversity, overall microbiome structure, and specific species/pathways and adjusted for relevant covariates.

RESULTS

Alpha diversity was negatively associated with suppression. In multivariate analysis, positive emotions were inversely associated with the relative abundance of Firmicutes bacterium CAG 94 and Ruminococcaceae bacterium D16, while negative emotions were directly correlated with the relative abundance of these same species. At the metabolic pathway level, negative emotions were inversely related to the biosynthesis of pantothenate, coenzyme A, and adenosine.

CONCLUSIONS

These findings offer human evidence supporting linkages of emotions and related regulatory processes with the gut microbiome and highlight the importance of incorporating the gut microbiome in our understanding of emotion-related factors and their associations with physical health.

On the roles of function and selection in evolving systems

Physical laws-such as the laws of motion, gravity, electromagnetism, and thermodynamics-codify the general behavior of varied macroscopic natural systems across space and time. We propose that an additional, hitherto-unarticulated law is required to characterize familiar macroscopic phenomena of our complex, evolving universe. An important feature of the classical laws of physics is the conceptual equivalence of specific characteristics shared by an extensive, seemingly diverse body of natural phenomena. Identifying potential equivalencies among disparate phenomena-for example, falling apples and orbiting moons or hot objects and compressed springs-has been instrumental in advancing the scientific understanding of our world through the articulation of laws of nature. A pervasive wonder of the natural world is the evolution of varied systems, including stars, minerals, atmospheres, and life. These evolving systems appear to be conceptually equivalent in that they display three notable attributes: 1) They form from numerous components that have the potential to adopt combinatorially vast numbers of different configurations; 2) processes exist that generate numerous different configurations; and 3) configurations are preferentially selected based on function. We identify universal concepts of selection-static persistence, dynamic persistence, and novelty generation-that underpin function and drive systems to evolve through the exchange of information between the environment and the system. Accordingly, we propose a "law of increasing functional information": The functional information of a system will increase (i.e., the system will evolve) if many different configurations of the system undergo selection for one or more functions.

Microbiome Interconnectedness throughout Environments with Major Consequences for Healthy People and a Healthy Planet

Microbiomes have highly important roles for ecosystem functioning and carry out key functions that support planetary health, including nutrient cycling, climate regulation, and water filtration. Microbiomes are also intimately associated with complex multicellular organisms such as humans, other animals, plants, and insects and perform crucial roles for the health of their hosts. Although we are starting to understand that microbiomes in different systems are interconnected, there is still a poor understanding of microbiome transfer and connectivity. In this review we show how microbiomes are connected within and transferred between different habitats and discuss the functional consequences of these connections. Microbiome transfer occurs between and within abiotic (e.g., air, soil, and water) and biotic environments, and can either be mediated through different vectors (e.g., insects or food) or direct interactions. Such transfer processes may also include the transmission of pathogens or antibiotic resistance genes. However, here, we highlight the fact that microbiome transmission can have positive effects on planetary and human health, where transmitted microorganisms potentially providing novel functions may be important for the adaptation of ecosystems.

Absence of enterotypes in the human gut microbiomes reanalyzed with non-linear dimensionality reduction methods

Enterotypes of the human gut microbiome have been proposed to be a powerful prognostic tool to evaluate the correlation between lifestyle, nutrition, and disease. However, the number of enterotypes suggested in the literature ranged from two to four. The growth of available metagenome data and the use of exact, non-linear methods of data analysis challenges the very concept of clusters in the multidimensional space of bacterial microbiomes. Using several published human gut microbiome datasets of variable 16S rRNA regions, we demonstrate the presence of a lower-dimensional structure in the microbiome space, with high-dimensional data concentrated near a low-dimensional non-linear submanifold, but the absence of distinct and stable clusters that could represent enterotypes. This observation is robust with regard to diverse combinations of dimensionality reduction techniques and clustering algorithms.

Gut Microbiota Alterations and Their Functional Differences in Depression According to Enterotypes in Asian Individuals

This study aimed to investigate alterations in the gut microbiota of patients with depression compared to those in the gut microbiota of healthy individuals based on enterotypes as a classification framework. Fecal bacteria FASTA/Q samples from 333 Chinese participants, including 107 healthy individuals (Healthy group) and 226 individuals suffering from depression (DP group), were analyzed. The participants were classified into three enterotypes: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Prevotellaceae (ET-P). An α-diversity analysis revealed no significant differences in microbial diversity between the Healthy and DP groups across all enterotypes. However, there were substantial differences in the gut microbial composition for β-diversity, particularly within ET-L and ET-B. The DP group within ET-B exhibited a higher abundance of Proteobacteria, while a linear discriminant analysis (LDA) of the DP group showed an increased relative abundance of specific genera, such as Mediterraneibacter, Blautia, Bifidobacterium, and Clostridium. Within ET-L, Bifidobacterium, Blautia, Clostridium, Collinsella, and Corynebacterium were significantly higher in the DP group in the LDA and ANOVA-like differential expression-2 (ALDEx2) analyses. At the species level of ET-L, Blautia luti, Blautia provencensis, Blautia glucerasea, Clostridium innocuum, Clostridium porci, and Clostridium leptum were the primary bacteria in the DP group identified using the machine learning approach. A network analysis revealed a more tightly interconnected microbial community within ET-L than within ET-B. This suggests a potentially stronger functional relationship among the gut microbiota in ET-L. The metabolic pathways related to glucose metabolism, tryptophan and tyrosine metabolism, neurotransmitter metabolism, and immune-related functions showed strong negative associations with depression, particularly within ET-L. These findings provide insights into the gut-brain axis and its role in the pathogenesis of depression, thus contributing to our understanding of the underlying mechanisms in Asian individuals. Further research is warranted to explain the mechanistic links between gut microbiota and depression and to explore their potential for use in precision medicine interventions.

Metabolic pathway prediction of core microbiome based on enterotype and orotype

Introduction

Identification of key microbiome components has been suggested to help address the maintenance of oral and intestinal health in humans. The core microbiome is similar in all individuals, whereas the diverse microbiome varies across individuals, based on their unique lifestyles and phenotypic and genotypic determinants. In this study, we aimed to predict the metabolism of core microorganisms in the gut and oral environment based on enterotyping and orotyping.

Materials and methods

Gut and oral samples were collected from 83 Korean women aged 50 years or older. The extracted DNA was subjected to next-generation sequencing analysis of 16S rRNA hypervariable regions V3-V4.

Results

Gut bacteria were clustered into three enterotypes, while oral bacteria were clustered into three orotypes. Sixty-three of the core microbiome between the gut and oral population were correlated, and different metabolic pathways were predicted for each type. Eubacterium_g11, Actinomyces, Atopobium, and Enterococcus were significantly positively correlated between the gut and oral abundance. The four bacteria were classified as type 3 in orotype and type 2 in enterotype.

Conclusion

Overall, the study suggested that collapsing the human body's multidimensional microbiome into a few categories may help characterize the microbiomes better and address health issues more deeply.

Gut Microbiome-Brain Alliance: A Landscape View into Mental and Gastrointestinal Health and Disorders

Gut microbiota includes a vast collection of microorganisms residing within the gastrointestinal tract. It is broadly recognized that the gut and brain are in constant bidirectional communication, of which gut microbiota and its metabolic production are a major component, and form the so-called gut microbiome-brain axis. Disturbances of microbiota homeostasis caused by imbalance in their functional composition and metabolic activities, known as dysbiosis, cause dysregulation of these pathways and trigger changes in the blood-brain barrier permeability, thereby causing pathological malfunctions, including neurological and functional gastrointestinal disorders. In turn, the brain can affect the structure and function of gut microbiota through the autonomic nervous system by regulating gut motility, intestinal transit and secretion, and gut permeability. Here, we examine data from the CAS Content Collection, the largest collection of published scientific information, and analyze the publication landscape of recent research. We review the advances in knowledge related to the human gut microbiome, its complexity and functionality, its communication with the central nervous system, and the effect of the gut microbiome-brain axis on mental and gut health. We discuss correlations between gut microbiota composition and various diseases, specifically gastrointestinal and mental disorders. We also explore gut microbiota metabolites with regard to their impact on the brain and gut function and associated diseases. Finally, we assess clinical applications of gut-microbiota-related substances and metabolites with their development pipelines. We hope this review can serve as a useful resource in understanding the current knowledge on this emerging field in an effort to further solving of the remaining challenges and fulfilling its potential.

Impact of the mother's gut microbiota on infant microbiome and brain development

The link between the gut microbiome and health has recently garnered considerable interest in its employment for medicinal purposes. Since the early microbiota exhibits more flexibility compared to that of adults, there is a considerable possibility that altering it will have significant consequences on human development. Like genetics, the human microbiota can be passed from mother to child. This provides information on early microbiota acquisition, future development, and prospective chances for intervention. The succession and acquisition of early-life microbiota, modifications of the maternal microbiota during pregnancy, delivery, and infancy, and new efforts to understand maternal-infant microbiota transmission are discussed in this article. We also examine the shaping of mother-to-infant microbial transmission, and we then explore possible paths for future research to advance our knowledge in this area.

Altered gut microbiota in individuals with episodic and chronic migraine

Emerging evidence reveals a close association between gut microbiota and human neurological disorders. The present study aimed to assess whether the composition of gut microbiota in participants with episodic migraine (EM) and chronic migraine (CM) was altered in comparison to that of the controls. This study was a cross-sectional, case-control study. The gut microbiota were evaluated by the partial, targeted sequencing of the 16S rRNA V3-V4 region. This study enrolled 42 and 45 participants with EM and CM, respectively, and 43 controls. Alpha and beta diversities revealed no significant difference among the three groups; however, the microbiota composition at the class, order, family, and genus levels differed significantly between EM and the control, CM and the control, and the EM and CM groups. Moreover, higher composition of PAC000195_g was significantly associated with a lower headache frequency among the five genera that exhibited significantly different microbiota composition in EM and CM. Agathobacter revealed a significant negative association with severe headache intensity. The findings of the present study provide evidence of altered gut microbiota in EM and CM. These findings will help in understanding the course and treatment of migraine.

Evaluating the Genetic Effects of Gut Microbiota on the Development of Neuroticism and General Happiness: A Polygenic Score Analysis and Interaction Study Using UK Biobank Data

Limited efforts have been invested in exploring the interaction effects between genetic factors and gut microbiota on neuroticism and general happiness. The polygenic risk scores (PRS) of gut microbiota were calculated from individual-level genotype data of the UK Biobank cohort. Linear regression models were then used to assess the associations between individual PRS of gut microbiota and mental traits and interaction analysis was performed by PLINK2.0. KOBAS-i was used to conduct gene ontology (GO) enrichment analysis of the identified genes. We observed suggestive significant associations between neuroticism and PRS for the genus Bifidobacterium (rank-normal transformation, RNT) (beta = -1.10, P = 4.16 × 10-3) and the genus Desulfovibrio (RNT) (beta = 0.54, P = 7.46 × 10-3). PRS for the genus Bifidobacterium (hurdle binary, HB) (beta = 1.99, P = 5.24 × 10-3) and the genus Clostridium (RNT) (beta = 1.26, P = 9.27 × 10-3) were found to be suggestive positively associated with general happiness. Interaction analysis identified several significant genes that interacted with gut microbiota, such as RORA (rs575949009, beta = -45.00, P = 1.82 × 10-9) for neuroticism and ASTN2 (rs36005728, beta = 19.15, P = 3.37 × 10-8) for general happiness. Our study results support the genetic effects of gut microbiota on the development of neuroticism and general happiness.

Understanding the bacterial compositional network associations between oral and gut microbiome within healthy Koreans

Oral microbial ecosystem could influence intestinal diseases, but there have been insufficient studies demonstrating the association of microbial composition between the oral cavity and the intestinal system. Thus, we aimed to investigate the compositional network within the oral microbiome related to gut enterotype from saliva and stool samples collected from 112 healthy Korean subjects. Here, we performed bacterial 16S amplicon sequencing from clinical samples. Then, we determined oral microbiome type related to individual's gut enterotype for healthy Korean. The co-occurrence analysis was performed to interactivity prediction of microbiome within saliva samples. As a result, it could be classified into two Korean oral microbiome types (KO) and four oral-gut-associated microbiome types (KOGA) according to distribution and significant differences of oral microflora. The co-occurrence analysis showed various bacterial compositional networks linked around Streptococcus and Haemophilus within healthy subjects. The present study was first approach in healthy Koreans to identify the oral microbiome types related to the gut microbiome and investigate their characteristics. Hence, we suggest that our results could be potential healthy control data for identifying differences in microbial composition between healthy people and oral disease patients and studying microbial association with the gut microbial environment (oral-gut microbiome axis).

Examining the Influence of the Human Gut Microbiota on Cognition and Stress: A Systematic Review of the Literature

The gut microbiota is seen as an emerging biotechnology that can be manipulated to enhance or preserve cognition and physiological outputs of anxiety and depression in clinical conditions. However, the existence of such interactions in healthy young individuals in both non-stressful and stressful environments is unclear. The aim of this systematic review was to examine the relationship between the human gut microbiota, including modulators of the microbiota on cognition, brain function and/or stress, anxiety and depression. A total of n = 25 eligible research articles from a possible 3853 published between October 2018 and August 2021 were identified and included. Two study design methods for synthesis were identified: cross-sectional or pre/post intervention. Few cross-sectional design studies that linked microbiota to cognition, brain activity/structure or mental wellbeing endpoints existed (n = 6); however, correlations between microbiota diversity and composition and areas of the brain related to cognitive functions (memory and visual processing) were observed. Intervention studies targeting the gut microbiota to improve cognition, brain structure/function or emotional well-being (n = 19) generally resulted in improved brain activity and/or cognition (6/8), and improvements in depression and anxiety scores (5/8). Despite inherit limitations in studies reviewed, available evidence suggests that gut microbiota is linked to brain connectivity and cognitive performance and that modulation of gut microbiota could be a promising strategy for enhancing cognition and emotional well-being in stressed and non-stressed situations.

Early life environment affects behavior, welfare, gut microbiome composition, and diversity in broiler chickens

This study aimed to identify whether early-life conditions in broiler chickens could affect their behavior and welfare, and whether or not this was associated with an altered gut microbiome composition or diversity. Broilers were tested in a 2 x 2 factorial design with hatching conditions [home pen (OH) or at the hatchery (HH)] and enrichment (dark brooder (EE) or no brooder (NE) until 14 days of age) as factors (N = 6 per treatment combination). Microbiota composition was measured in the jejunum on days (d) 7, 14, and 35 and in pooled fecal samples on day 14. A novel environment test (NET) was performed on days 1 and 11, and the behavior was observed on days 6, 13, and 33. On day 35, composite asymmetry was determined and footpad dermatitis and hock burn were scored. In their home pen, HH showed more locomotion than OH (P = 0.05), and NE were sitting more and showed more comfort behavior than EE at all ages (P <0.001 and P = 0.001, respectively). On days 6 and 13 NE showed more eating and litter pecking while sitting, but on day 33 the opposite was found (age^*enrichment: P = 0.05 and P <0.01, respectively). On days 1 and 11, HH showed more social reinstatement in the NET than OH, and EE showed more social reinstatement than NE (P <0.05). Composite asymmetry scores were lower for EE than NE (P <0.05). EE also had less footpad dermatitis and hock burn than NE (P <0.001). Within OH, NE had a more diverse fecal and jejunal microbiome compared to EE on day 14 (feces: observed richness: P = 0.052; jejunum: observed richness and Shannon: P <0.05); the principal component analysis (PCA) showed differences between NE and EE within both HH and OH in fecal samples on day 14, as well as significant differences in bacterial genera such as Lactobacillus and Lachnospiraceae (P <0.05). On day 35, PCA in jejunal samples only showed a trend (P = 0.068) for differences between NE vs. EE within the OH. In conclusion, these results suggest that especially the dark brooder affected the behavior and had a positive effect on welfare as well as affected the composition and diversity of the microbiome. Whether or not the behavior was modulated by the microbiome or vice versa remains to be investigated.

Cronos: A Machine Learning Pipeline for Description and Predictive Modeling of Microbial Communities Over Time

Microbial time-series analysis, typically, examines the abundances of individual taxa over time and attempts to assign etiology to observed patterns. This approach assumes homogeneous groups in terms of profiles and response to external effectors. These assumptions are not always fulfilled, especially in complex natural systems, like the microbiome of the human gut. It is actually established that humans with otherwise the same demographic or dietary backgrounds can have distinct microbial profiles. We suggest an alternative approach to the analysis of microbial time-series, based on the following premises: 1) microbial communities are organized in distinct clusters of similar composition at any time point, 2) these intrinsic subsets of communities could have different responses to the same external effects, and 3) the fate of the communities is largely deterministic given the same external conditions. Therefore, tracking the transition of communities, rather than individual taxa, across these states, can enhance our understanding of the ecological processes and allow the prediction of future states, by incorporating applied effects. We implement these ideas into Cronos, an analytical pipeline written in R. Cronos’ inputs are a microbial composition table (e.g., OTU table), their phylogenetic relations as a tree, and the associated metadata. Cronos detects the intrinsic microbial profile clusters on all time points, describes them in terms of composition, and records the transitions between them. Cluster assignments, combined with the provided metadata, are used to model the transitions and predict samples’ fate under various effects. We applied Cronos to available data from growing infants’ gut microbiomes, and we observe two distinct trajectories corresponding to breastfed and formula-fed infants that eventually converge to profiles resembling those of mature individuals. Cronos is freely available at https://github.com/Lagkouvardos/Cronos.

The human physiology of well-being: A systematic review on the association between neurotransmitters, hormones, inflammatory markers, the microbiome and well-being

To understand the pathways through which well-being contributes to health, we performed a systematic review according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines on the association between well-being and physiological markers in four categories, neurotransmitters, hormones, inflammatory markers, and microbiome. We identified 91 studies. Neurotransmitter studies (k_{number of studies}=9) reported only a possible positive association between serotonin and well-being. For the hormone studies (k = 48), a lower momentary cortisol level was related to higher well-being (meta-analytic r = -0.06), and a steeper diurnal slope of cortisol levels. Inflammatory marker studies (k = 36) reported negative or non-significant relations with well-being, with meta-analytic estimates of respectively r = -0.07 and r = -0.05 for C-reactive protein and interleukin-6. Microbiome studies (k = 4) reported inconsistent associations between different bacteria abundance and well-being. The results indicate possible but small roles of serotonin, cortisol, and inflammatory markers in explaining differences in well-being. The inconsistent and limited results for other markers and microbiome require further research. Future directions for a complete picture of the physiological factors underlying well-being are proposed.

Proposal of a health gut microbiome index based on a meta-analysis of Korean and global population datasets

The disruption of the human gut microbiota has been linked to host health conditions, including various diseases. However, no reliable index for measuring and predicting a healthy microbiome is currently available. Here, the sequencing data of 1,663 Koreans were obtained from three independent studies. Furthermore, we pooled 3,490 samples from public databases and analyzed a total of 5,153 fecal samples. First, we analyzed Korean gut microbiome covariates to determine the influence of lifestyle on variation in the gut microbiota. Next, patterns of microbiota variations across geographical locations and disease statuses were confirmed using a global cohort and di-sease data. Based on comprehensive comparative analysis, we were able to define three enterotypes among Korean cohorts, namely, Prevotella type, Bacteroides type, and outlier type. By a thorough categorization of dysbiosis and the evaluation of microbial characteristics using multiple datasets, we identified a wide spectrum of accuracy levels in classifying health and disease states. Using the observed microbiome patterns, we devised an index named the gut microbiome index (GMI) that could consistently predict health conditions from human gut microbiome data. Compared to ecological metrics, the microbial marker index, and machine learning approaches, GMI distinguished between healthy and non-healthy individuals with a higher accuracy across various datasets. Thus, this study proposes a potential index to measure health status of gut microbiome that is verified from multiethnic data of various diseases, and we expect this model to facilitate further clinical application of gut microbiota data in future.

Engineering microbial technologies for environmental sustainability: choices to make

Microbial technologies have provided solutions to key challenges in our daily lives for over a century. In the debate about the ongoing climate change and the need for planetary sustainability, microbial ecology and microbial technologies are rarely considered. Nonetheless, they can bring forward vital solutions to decrease and even prevent long-term effects of climate change. The key to the success of microbial technologies is an effective, target-oriented microbiome management. Here, we highlight how microbial technologies can play a key role in both natural, i.e. soils and aquatic ecosystems, and semi-natural or even entirely human-made, engineered ecosystems, e.g. (waste) water treatment and bodily systems. First, we set forward fundamental guidelines for effective soil microbial resource management, especially with respect to nutrient loss and greenhouse gas abatement. Next, we focus on closing the water circle, integrating resource recovery. We also address the essential interaction of the human and animal host with their respective microbiomes. Finally, we set forward some key future potentials, such as microbial protein and the need to overcome microphobia for microbial products and services. Overall, we conclude that by relying on the wisdom of the past, we can tackle the challenges of our current era through microbial technologies.

Altered Fecal Microbiota Correlated With Systemic Inflammation in Male Subjects With Methamphetamine Use Disorder

Methamphetamine use disorder (MUD) is a major public health problem worldwide with limited effective treatment options. Previous studies have reported methamphetamine-associated alterations in gut microbiota. A potential role of gut microbiota in regulating methamphetamine-induced brain dysfunction through interactions with the host immune system has been proposed, but evidence for this hypothesis is limited. The present study aimed to investigate the alterations in the fecal microbiota and explore its relationship with systemic inflammation in MUD. Fecal samples were obtained from 26 male subjects with MUD and 17 sex- and age- matched healthy controls. Fecal microbial profiles were analyzed by 16S rRNA sequencing. Plasma inflammatory markers were measured using enzyme-linked immunosorbent assay. Associations between fecal microbiota, systemic inflammatory markers and clinical characteristics were examined by Spearman partial correlation analysis while controlling for possible confounders. Compared with healthy controls, individuals with MUD showed no difference in fecal microbial diversity, but exhibited differences in the relative abundance of several microbial taxa. At the genus level, a higher abundance of Collinsella, Odoribacter and Megasphaera and lower levels of Faecalibacterium, Blautia, Dorea and Streptococcus were detected in subjects with MUD. More importantly, altered fecal microbiota was found to be correlated with plasma levels of CRP, IL-2, IL-6 and IL-10. The order Lactobacillales, exhibiting lower abundance in participants with MUD, was positively related to the duration of methamphetamine abstinence and the plasma level of anti-inflammatory cytokine IL-10. This study is the first to provide evidence for a link between altered fecal microbiota and systemic inflammation in MUD. Further elucidation of interactions between gut microbiota and the host immune system may be beneficial for the development of novel therapeutic approaches for MUD.

Migration effects on the intestinal microbiota of Tibetans

BACKGROUND

Diet, environment, and genomic context have a significant impact on humans' intestinal microbiota. Moreover, migration may be accompanied by changes in human eating habits and living environment, which could, in turn, affect the intestinal microbiota. Located in southwestern China, Tibet has an average altitude of 4,000 meters and is known as the world's roof. Xianyang is situated in the plains of central China, with an average altitude of about 400 meters.

METHODS

To understand the association between intestinal microbiota and population migration, we collected the fecal samples from 30 Tibetan women on the first day (as TI1st), six months (as TI2nd), and ten months (as TI3rd) following migration from Tibet to Xianyang. Fecal samples were collected from 29 individuals (belonging to the Han women) as a control. The dietary information of the Tibetan women and the Han women was gathered. We performed a 16S rRNA gene survey of the collected fecal samples using Illumina MiSeq sequencing.

RESULTS

Following the migration, the alpha and beta diversity of Tibetan women's intestinal microbiota appeared unaffected. Linear discriminant analysis effect size (LEfSe) analysis showed that Klebsiella, Blautia, and Veillonella are potential biomarkers at TI1st, while Proteobacteria and Enterobacteriaceae were common in TI3rd. Finally, functional prediction by phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) found no significant up-regulation or down-regulation gene pathway in the intestinal microbiota of Tibetan women after migration. The present study reveals that the higher stability in Tibetan women's intestinal microbiota was less affected by the environment and diet, indicating that Tibetan women's intestinal microbiota is relatively stable. The main limitations of the study were the small sample size and all volunteers were women.

The Use of Fecal Microbiome Transplant in Treating Human Diseases: Too Early for Poop?

Fecal microbiome transplant (FMT) has gained popularity over the past few years, given its success in treating several gastrointestinal diseases. At the same time, microbial populations in the gut have been shown to have more physiological effects than we expected as "habitants" of the gut. The imbalance in the gut microbiome or dysbiosis, particularly when there are excessive harmful pathogens, can trigger not just infections but can also result in the development of common diseases, such as cancer and cardiometabolic diseases. By using FMT technology, the dysbiosis of the gut microbiome in patients can be resolved by administering fecal materials from a healthy donor. The current review summarizes the history and current uses of FMT before suggesting potential ideas for its high-quality application in clinical settings.

Association of Loneliness and Wisdom With Gut Microbial Diversity and Composition: An Exploratory Study

Loneliness and wisdom have opposite effects on health and well-being. Loneliness is a serious public health problem associated with increased morbidity and mortality. Wisdom is associated with better health and well-being. We have consistently found a strong negative correlation between loneliness and wisdom. The present study aimed to investigate the association of loneliness and wisdom with the gut microbiome. One hundred eighty-four community-dwelling adults (28-97 years) completed validated self-report-based measures of loneliness, wisdom, compassion, social support, and social engagement. Fecal samples were collected and profiled using 16S rRNA sequencing. Linear regression analyses, controlling for age and body mass index, revealed that lower levels of loneliness and higher levels of wisdom, compassion, social support, and social engagement were associated with greater phylogenetic richness and diversity of the gut microbiome. Partial least squares (PLS) analysis to investigate multivariate relationships extracted two composite variables. Linear regression model predicting alpha-diversity with PLS components revealed that a linear combination of all psychosocial predictors (with negative loading for loneliness and positive loadings for all others, including wisdom, compassion, social support, and social engagement) was significantly associated with alpha-diversity. For beta-diversity, compassion and wisdom accounted for a significant proportion of variance in overall microbial community composition. Findings may have implications for interventions to reduce loneliness and possibly its health-related adverse consequences. Future research should explore whether increasing compassion and wisdom may improve loneliness and overall well-being as well as microbial diversity.

Effects of Microbiota Imbalance in Anxiety and Eating Disorders: Probiotics as Novel Therapeutic Approaches

Anxiety and eating disorders produce a physiological imbalance that triggers alterations in the abundance and composition of gut microbiota. Moreover, the gut–brain axis can be altered by several factors such as diet, lifestyle, infections, and antibiotic treatment. Diet alterations generate gut dysbiosis, which affects immune system responses, inflammation mechanisms, the intestinal permeability, as well as the production of short chain fatty acids and neurotransmitters by gut microbiota, which are essential to the correct function of neurological processes. Recent studies indicated that patients with generalized anxiety or eating disorders (anorexia nervosa, bulimia nervosa, and binge-eating disorders) show a specific profile of gut microbiota, and this imbalance can be partially restored after a single or multi-strain probiotic supplementation. Following the PRISMA methodology, the current review addresses the main microbial signatures observed in patients with generalized anxiety and/or eating disorders as well as the importance of probiotics as a preventive or a therapeutic tool in these pathologies.