Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome

Bioactive Food Abates Metabolic and Synaptic Alterations by Modulation of Gut Microbiota in a Mouse Model of Alzheimer's Disease

Recent investigations have demonstrated an important role of gut microbiota (GM) in the pathogenesis of Alzheimer's disease (AD). GM modulates a host's health and disease by production of several substances, including lipopolysaccharides (LPS) and short-chain fatty acids (SCFAs), among others. Diet can modify the composition and diversity of GM, and ingestion of a healthy diet has been suggested to lower the risk to develop AD. We have previously shown that bioactive food (BF) ingestion can abate neuroinflammation and oxidative stress and improve cognition in obese rats, effects associated with GM composition. Therefore, BF can impact the gut-brain axis and improved behavior. In this study, we aim to explore if inclusion of BF in the diet may impact central pathological markers of AD by modulation of the GM. Triple transgenic 3xTg-AD (TG) female mice were fed a combination of dried nopal, soy, chia oil, and turmeric for 7 months. We found that BF ingestion improved cognition and reduced Aβ aggregates and tau hyperphosphorylation. In addition, BF decreased MDA levels, astrocyte and microglial activation, PSD-95, synaptophysin, GluR1 and ARC protein levels in TG mice. Furthermore, TG mice fed BF showed increased levels of pGSK-3β. GM analysis revealed that pro-inflammatory bacteria were more abundant in TG mice compared to wild-type, while BF ingestion was able to restore the GM's composition, LPS, and propionate levels to control values. Therefore, the neuroprotective effects of BF may be mediated, in part, by modulation of GM and the release of neurotoxic substances that alter brain function.

Beneficial effects of tea water extracts on the body weight and gut microbiota in C57BL/6J mice fed with a high-fat diet

Accumulative evidence has suggested that tea consumption has benefits in reducing body fat and alleviating metabolic syndrome. We hypothesize that benefits of tea consumption can be partially mediated by modulating intestinal microbiota via inhibiting the formation of lipopolysaccharides (LPS) and promoting the production of short chain fatty acids (SCFAs). C57BL/6J mice were fed a high fat diet with the addition of 1% water extracts of green tea, oolong tea and black tea. Results showed that the dietary supplementation of three tea water extracts equally improved the glucose tolerance and reduced a high fat diet-induced gain in weight, hepatic lipids, and white adipose tissue weights. This was accompanied by a significant reduction in plasma LPS and a significant increase in the production of SCFAs. The metagenomic analyses showed that the tea extracts changed the overall composition of gut microbiota and decreased the relative abundance of family Rikenellaceae and Desulfovibrionaceae. In addition, tea water extracts could also change the abundance of key operational taxonomic units (OTUs) including OTU473 (Alistipes), OTU229 (Rikenella), OTU179 (Ruminiclostridium) and OTU264 (Acetatifactor). In conclusion, three tea extracts could improve the glucose tolerance, induce the production of SCFAs and inhibit the production of endotoxin LPS, most likely mediated by modulating gut microbiota.

Current State of and Future Opportunities for Prediction in Microbiome Research: Report from the Mid-Atlantic Microbiome Meet-up in Baltimore on 9 January 2019

Accurate predictions across multiple fields of microbiome research have far-reaching benefits to society, but there are few widely accepted quantitative tools to make accurate predictions about microbial communities and their functions. More discussion is needed about the current state of microbiome analysis and the tools required to overcome the hurdles preventing development and implementation of predictive analyses. We summarize the ideas generated by participants of the Mid-Atlantic Microbiome Meet-up in January 2019. While it was clear from the presentations that most fields have advanced beyond simple associative and descriptive analyses, most fields lack essential elements needed for the development and application of accurate microbiome predictions. Participants stressed the need for standardization, reproducibility, and accessibility of quantitative tools as key to advancing predictions in microbiome analysis. We highlight hurdles that participants identified and propose directions for future efforts that will advance the use of prediction in microbiome research.

The Microbiota-Gut-Brain Axis

The importance of the gut-brain axis in maintaining homeostasis has long been appreciated. However, the past 15 yr have seen the emergence of the microbiota (the trillions of microorganisms within and on our bodies) as one of the key regulators of gut-brain function and has led to the appreciation of the importance of a distinct microbiota-gut-brain axis. This axis is gaining ever more traction in fields investigating the biological and physiological basis of psychiatric, neurodevelopmental, age-related, and neurodegenerative disorders. The microbiota and the brain communicate with each other via various routes including the immune system, tryptophan metabolism, the vagus nerve and the enteric nervous system, involving microbial metabolites such as short-chain fatty acids, branched chain amino acids, and peptidoglycans. Many factors can influence microbiota composition in early life, including infection, mode of birth delivery, use of antibiotic medications, the nature of nutritional provision, environmental stressors, and host genetics. At the other extreme of life, microbial diversity diminishes with aging. Stress, in particular, can significantly impact the microbiota-gut-brain axis at all stages of life. Much recent work has implicated the gut microbiota in many conditions including autism, anxiety, obesity, schizophrenia, Parkinson’s disease, and Alzheimer’s disease. Animal models have been paramount in linking the regulation of fundamental neural processes, such as neurogenesis and myelination, to microbiome activation of microglia. Moreover, translational human studies are ongoing and will greatly enhance the field. Future studies will focus on understanding the mechanisms underlying the microbiota-gut-brain axis and attempt to elucidate microbial-based intervention and therapeutic strategies for neuropsychiatric disorders.

Microbiota: a novel regulator of pain

Among the various regulators of the nervous system, the gut microbiota has been recently described to have the potential to modulate neuronal cells activation. While bacteria-derived products can induce aversive responses and influence pain perception, recent work suggests that "abnormal" microbiota is associated with neurological diseases such as Alzheimer's, Parkinson's disease or autism spectrum disorder (ASD). Here we review how the gut microbiota modulates afferent sensory neurons function and pain, highlighting the role of the microbiota/gut/brain axis in the control of behaviors and neurological diseases. We outline the changes in gut microbiota, known as dysbiosis, and their influence on painful gastrointestinal disorders. Furthermore, both direct host/microbiota interaction that implicates activation of "pain-sensing" neurons by metabolites, or indirect communication via immune activation is discussed. Finally, treatment options targeting the gut microbiota, including pre- or probiotics, will be proposed. Further studies on microbiota/nervous system interaction should lead to the identification of novel microbial ligands and host receptor-targeted drugs, which could ultimately improve chronic pain management and well-being.

Pain regulation by gut microbiota: molecular mechanisms and therapeutic potential

The relationship between gut microbiota and neurological diseases, including chronic pain, has received increasing attention. The gut microbiome is a crucial modulator of visceral pain, whereas recent evidence suggests that gut microbiota may also play a critical role in many other types of chronic pain, including inflammatory pain, headache, neuropathic pain, and opioid tolerance. We present a narrative review of the current understanding on the role of gut microbiota in pain regulation and discuss the possibility of targeting gut microbiota for the management of chronic pain. Numerous signalling molecules derived from gut microbiota, such as by-products of microbiota, metabolites, neurotransmitters, and neuromodulators, act on their receptors and remarkably regulate the peripheral and central sensitisation, which in turn mediate the development of chronic pain. Gut microbiota-derived mediators serve as critical modulators for the induction of peripheral sensitisation, directly or indirectly regulating the excitability of primary nociceptive neurones. In the central nervous system, gut microbiota-derived mediators may regulate neuroinflammation, which involves the activation of cells in the blood-brain barrier, microglia, and infiltrating immune cells, to modulate induction and maintenance of central sensitisation. Thus, we propose that gut microbiota regulates pain in the peripheral and central nervous system, and targeting gut microbiota by diet and pharmabiotic intervention may represent a new therapeutic strategy for the management of chronic pain.

Is fecal calprotectin always normal in children with irritable bowel syndrome?

Background/Aims

Fecal calprotectin (FC) is a marker of intraluminal intestinal inflammation. Intestinal inflammation may contribute to the pathophysiology of irritable bowel syndrome (IBS). This study evaluated FC levels in children with IBS and differences in FC levels in children stratified by IBS subtype and healthy controls (HCs).

Methods

A total of 157 children with IBS and 56 HCs aged 4–16 years (119 boys, 94 girls, mean age of 9.48 years) were included in this prospective study. Children with IBS were diagnosed using the Rome III criteria and classified into 4 subtypes: IBS with constipation (IBS-C, n=37), IBS with diarrhea (IBS-D, n=54), IBS with alternating constipation and diarrhea (IBS-M, n=49), and IBS unsubtyped (IBS-U, n=17); postinfectious IBS (PI-IBS) was also considered. The FC concentration in stool samples was analyzed using an enzyme-linked immunosorbent assay. All participants answered a questionnaire regarding several demographic and clinical characteristics.

Results

Children with IBS had significantly higher levels of FC than the HCs (88.71 μg/g vs. 17.77 μg/g). Among the 4 IBS subtypes, the FC concentration was highest in children with IBS-D, followed by those with IBS-M, IBS-C, and IBS-U (169.94 μg/g vs. 45.04, 31.22, and 33.52 μg/g, respectively), and these differences were statistically significant. For PI-IBS, 90% of cases were in the IBS-D group.

Conclusions

The FC level was significantly higher in children with IBS than in HCs and differed depending on the IBS subtype, supporting the notion that IBS is a type of low-grade bowel inflammation.

Approach to stress endocrine response: somatization in the context of gastroenterological symptoms: a systematic review

Background

Stress can be defined as an acute threat to the homeostasis of an organism, and in order to manage stress, and maintain stability, the allostatic systems activate an adaptive response. Stress has been shown to have both short - and long-term effects on the function of the gastrointestinal tract, but long-term exposure to stress is more likely to cause endocrine disorders.

Objective

The aim of this study was to investigate the endocrine response to stress, and evaluate the relationship between somatization and gastrointestinal symptoms.

Methods

A systematic literature search was conducted on several academic databases, which included, Pubmed, EBSCO and Science Direct. The search was performed using the keywords, “endocrine response to stress”, “somatization” and “gastrointestinal symptoms”.

Results

The hypothalamic-pituitary-adrenal (HPA) axis is essential in controlling physiological stress responses. Dysfunction is related to several mental disorders, including anxiety and depression, or somatization. Symptoms associated with genetic, or other traumatic experiences of individuals under stress, can lead to a maladaptive response to stress. These stressful life events were found to be associated with digestive system-related chronic diseases. Gastrointestinal disorders significantly affect millions of people worldwide.

Conclusion

This study examined how the endocrine system responds to stress, and the effect this has in causing stress-related gastrointestinal distresses. Our findings indicate that stress-related psychological disorders are strongly associated with the severity of gastrointestinal symptoms.

A machine learning model to predict hepatocellular carcinoma response to transcatheter arterial chemoembolization

PURPOSE

Some patients with hepatocellular carcinoma (HCC) are more likely to experience disease progression despite transcatheter arterial chemoembolization (TACE) treatment, and thus would benefit from early switching to other therapeutic regimens. We sought to evaluate a fully automated machine learning algorithm that uses pre-therapeutic quantitative computed tomography (CT) image features and clinical factors to predict HCC response to TACE.

MATERIALS AND METHODS

Outcome information from 105 patients receiving first-line treatment with TACE was evaluated retrospectively. The primary clinical endpoint was time to progression (TTP) based on follow-up CT radiological criteria (mRECIST). A 14-week cutoff was used to classify patients as TACE-susceptible (TTP ≥14 weeks) or TACE-refractory (TTP <14 weeks). Response to TACE was predicted using a random forest classifier with the Barcelona Clinic Liver Cancer (BCLC) stage and quantitative image features as input as well as the BCLC stage alone as a control.

RESULTS

The model's response prediction accuracy rate was 74.2% (95% CI=64%-82%) using a combination of the BCLC stage plus quantitative image features versus 62.9% (95% CI= 52%-72%) using the BCLC stage alone. Shape image features of the tumor and background liver were the dominant features correlated to the TTP as selected by the Boruta method and were used to predict the outcome.

CONCLUSION

This preliminary study demonstrates that quantitative image features obtained prior to therapy can improve the accuracy of predicting response of HCC to TACE. This approach is likely to provide useful information for aiding HCC patient selection for TACE.

Probiotics for paediatric functional abdominal pain disorders: A rapid review

BACKGROUND

Functional abdominal pain disorders (FAPD) are prevalent in the paediatric population, however, there is currently no consensus regarding best practices for treatment. The use of probiotics is becoming popular to treat FAPD. The goal of this rapid review is to synthesize the best evidence on the use of probiotics in children with FAPD.

METHODS

Searches were conducted on five main databases. Randomized controlled trials (RCTs) of probiotic use in children (0 to 18 years) with FAPD were searched. Populations of interest were patients with functional abdominal pain (FAP), irritable bowel syndrome (IBS), and functional dyspepsia (FD), recruited based on Rome criteria. Outcomes of interest were changes in abdominal pain severity, frequency, and duration.

FINDINGS

Eleven RCTs with 829 participants with the diagnosis of FAP (n=400), IBS (n=329), FD (n=45), and mixed population (n=55) were included. Of six studies of children with FAP, two (n=103) used Lactobacillus rhamnosus GG (LGG) and reported no significant effects on pain, and four (n=281) used Lactobacillus (L) reuteri DSM 17938, of which three (n=229) reported significant positive effects on either severity or frequency of pain. Of six trials of children with IBS, four (n=219) used LGG, of which three (n=168) reported a positive effect. One (n=48) used bifidobacteria and one used VSL #3 (n=59), both demonstrating positive effects with probiotics. Two studies of FD reported no benefit. No adverse events were attributed to probiotics.

CONCLUSIONS

There is preliminary evidence for use of probiotics, particularly LGG, in reducing abdominal pain in children with IBS. There are inconsistent positive effects of other probiotics, including L. reuteri DSM 17938, in reducing pain in patients with FAP, IBS, or FD. More RCTs with rigorous methodology using single or combination probiotics are warranted.

Gut Microbial Dysbiosis in the Irritable Bowel Syndrome: A Systematic Review and Meta-Analysis of Case-Control Studies

BACKGROUND

Irritable bowel syndrome (IBS) is the most common functional digestive condition in the industrialized world. The gut microbiota plays a key role in disease pathogenesis.

OBJECTIVE

A systematic review and meta-analysis on case-control studies was conducted to determine whether there is gut microbial dysbiosis in participants with IBS in comparison with healthy controls and, if so, whether the dysbiosis pattern differs among IBS subtypes and geographic regions.

METHODS

This review was conducted and reported according to the MOOSE (Meta-Analysis of Observational Studies in Epidemiology) 2000 and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2009 guidelines. Research articles published up to May 9, 2018 were identified through MEDLINE (PubMed), Cochrane Central Register of Controlled Trials (Cochrane Library), ClinicalTrials.gov, EMBASE, and Web of Science. Study quality was assessed using the Newcastle-Ottawa Scale. Case-control studies of participants with IBS who had undergone quantitative gut microbial stool analysis were included. The primary exposure measure of interest is log₁₀ bacterial counts per gram of stool. Meta-analyses were performed to estimate the mean difference (MD) in gut microbiota between participants with IBS and healthy controls using the random-effects model with inverse variance in Revman 5.3 and R 3.5.1. Publication bias was assessed with funnel plots and Egger's test. Between-study heterogeneity was analyzed using Higgins I² statistic with 95% CIs.

RESULTS

There were 6,333 unique articles identified; 52 qualified for full-text screening. Of these, 23 studies were included for analysis (n=1,340 participants from North America, Europe, and Asia). Overall, the studies were moderate in quality. Comparing participants with IBS to healthy controls, lower fecal Lactobacillus (MD= -0.57 log₁₀ colony-forming unit [CFU]/g; P<0.01) and Bifidobacterium (MD= -1.04 log₁₀CFU/g; P<0.01), higher Escherichia coli (MD=0.60 log₁₀CFU/g; P<0.01), and marginally higher Enterobacter (MD=0.74 log₁₀CFU/g; P=0.05). No difference was found between participants with IBS and healthy controls in fecal Bacteroides and Enterococcus (P=0.18 and 0.68, respectively). Publication bias was not observed except in Bifidobacterium (P=0.015). Subgroup analyses on participants with diarrhea-predominant and constipation-predominant IBS showed consistent results with the primary results. A subgroup analysis of Chinese studies was consistent with the primary results, except for fecal Bacteroides, which was increased in participants with IBS vs healthy controls (MD=0.29; 95% CI 0.13 to 0.46; P<0.01). Although substantial heterogeneity was detected (I²>75%) in most comparisons, the direction of the effect estimates is relatively consistent across studies.

CONCLUSIONS

IBS is characterized by gut microbial dysbiosis. Prospective, large-scale studies are needed to delineate how gut microbial profiles can be used to guide targeted therapies in this challenging patient population.

Lactobacillus acidophilus alleviates type 2 diabetes by regulating hepatic glucose, lipid metabolism and gut microbiota in mice

Diabetes, an endocrine and metabolic disorder, has become the third most non-infectious chronic disease that threatens human health. Type 2 diabetes (T2D) accounts for more than 90% of diabetic patients, mainly caused by environmental factors. Lactic acid bacteria (LAB) exhibit several health benefits to the host including regulating glucose and lipid metabolism and improving oxidative stress and inflammatory response. However, the anti-diabetic mechanism of probiotics has not been elucidated clearly. In this study, the anti-diabetic effects of Lactobacillus acidophilus KLDS1.1003 and KLDS1.0901 on T2D mice were assessed. Oral administration of L. acidophilus KLDS1.1003 and KLDS1.0901 for 6 weeks significantly improved the epithelial barrier function, which in turn lowered inflammation cytokines, including IL-8, TNF-α and IL-1β in liver and colon tissue, and prevented liver and colon tissue injuries to some extent. Additionally, L. acidophilus treatment regulated the expression genes that are related to glucose and lipid metabolism. The two tested strains down-regulated the expression of glycogen synthase kinase 3β (GSK-3β), fatty acid synthase (FAS) and sterol regulatory element-binding transcription factor 1c (SREBP-1c), and up-regulated the expression of protein kinase B (Akt). However, L. acidophilus KLDS1.0901 is better for improving T2D than L. acidophilus KLDS1.1003. Further research showed that L. acidophilus KLDS1.0901 supplementation could reshape gut microbiota, increasing short chain fatty acid-producing bacteria (Blautia, Roseburia and Anaerotruncus) and the level of SCFAs and decreasing the relative abundance of Gram-negative bacteria such as Desulfovibrio, Alistipes and Bacteroides. Notably, L. acidophilus KLDS1.0901 treatment restored the structure of gut microbiota similar to the control group. These findings suggested that L. acidophilus KLDS1.0901 might be used as a new type of antidiabetic drug candidate.

On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications

Advances in sequencing and computational biology have drastically increased our capability to explore the taxonomic and functional compositions of microbial communities that play crucial roles in industrial processes. Correspondingly, commercial interest has risen for applications where microbial communities make important contributions. These include food production, probiotics, cosmetics, and enzyme discovery. Other commercial applications include software that takes the user's gut microbiome data as one of its inputs and outputs evidence-based, automated, and personalized diet recommendations for balanced blood sugar levels. These applications pose several bioinformatic and data science challenges that range from requiring strain-level resolution in community profiles to the integration of large datasets for predictive machine learning purposes. In this perspective, we provide our insights on such challenges by touching upon several industrial areas, and briefly discuss advances and future directions of bioinformatics and data science in microbiome research.

Konjaku flour reduces obesity in mice by modulating the composition of the gut microbiota

BACKGROUND

Changes in the intestinal flora composition is referred to as dysbiosis, which is related to obesity development, thus supporting the potential roles of nutrients acting on intestinal flora to exert salutary effects on energetic metabolism of host. Dietary fiber has been known to affect the composition of intestinal flora. The aim of the present study was to investigate the functional effects of konjac flour (KF) on obesity control in respect to improving inflammation, metabolism, and intestinal barrier function, and the possible association of the effects with intestinal flora composition changes.

METHODS

Mice (n = 30) were randomly divided into control group (n = 10), high-fat-diet (HFD) group (n = 10), and KF intervention group (n = 10), followed by feeding for 12 weeks and with adding a KF daily supplementation for the treatment group. Body weight, fat accumulation, inflammation, and energetic metabolism markers in multiple tissues and the gut microbiota of the mice were examined at the end of the experiment.

RESULTS

The KF supplementation significantly reduced the gains in weight, fat mass, as well as adipocyte size of HFD mice and lowered the serum TC, leptin (LEP), thiobarbituric acid-reacting substance (TBARS), IL-6, and lipopolysaccharide (LPS) levels in HFD mice. KF also upregulated the expression of intestinal mucosa protein gene Intection and tight junction ZO-1 in HFD mice, as well as upregulate the expression of energy metabolism genes PPARα and CPT-1 as well as the fat metabolism gene HLS in livers and fat tissues, and downregulate that of fat synthesis gene PPARγ (p < 0.05). The KF treatment increases the α-diversity and change the β-diversity of the intestinal microflora in HFD mice and boosted the abundances of some obesity-related beneficial microorganisms (such as Megasphaera elsdenii) in the intestinal microflora of HFD mice, while reduced those of harmful microorganisms (such as Alistipes, Alloprevotella, Bacteroides acidifaciens, and Parabacteroides goldsteinii). The abundance of Alistipes was positively correlated with weight, fat mass, serum TC, TG, LEP, IL-6, and LPS contents as well as PPARγ gene expression; while notably and negatively related to the expression of CPT-1 and HLS genes (p < 0.01). KF remarkably increased the abundance of Aerococcaceae, while reduced that of Alistipes finegoldii (p < 0.01).

CONCLUSIONS

Supplementation with KF achieves favorable effects on treating obesity, improving inflammatory response, metabolism, and intestinal barrier function, by regulating intestinal microfloral structure in HFD-fed mice.

Association Between Gut Microbiota and Autism Spectrum Disorder: A Systematic Review and Meta-Analysis

Autism spectrum disorder (ASD) is characterized by stereotyped behavior and deficits in communication and social interactions. Gastrointestinal (GI) dysfunction is an ASD-associated comorbidity, implying a potential role of the gut microbiota in ASD GI pathophysiology. Several recent studies found that autistic individuals harbor an altered bacterial gut microbiota. In some cases, remodeling the gut microbiota by antibiotic administration and microbiota transfer therapy reportedly alleviated the symptoms of ASD. However, there is little consensus on specific bacterial species that are similarly altered across individual studies. The aim of this study is to summarize previously published data and analyze the alteration of the relative abundance of bacterial genera in the gut microbiota in controls and individuals with ASD using meta-analysis. We analyzed nine studies, including 254 patients with ASD, and found that children with ASD had lower percentages of Akkermansia, Bacteroides, Bifidobacterium, and Parabacteroides and a higher percentage of Faecalibacterium in the total detected microflora compared to controls. In contrast, children with ASD had lower abundance of Enterococcus, Escherichia coli, Bacteroides, and Bifidobacterium and higher abundance of Lactobacillus. This meta-analysis suggests an association between ASD and alteration of microbiota composition and warrants additional prospective cohort studies to evaluate the association of bacterial changes with ASD symptoms, which would provide further evidence for the precise microbiological treatment of ASD.

Establishment and evaluation of prediction model for multiple disease classification based on gut microbial data

Diseases prediction has been performed by machine learning approaches with various biological data. One of the representative data is the gut microbial community, which interacts with the host's immune system. The abundance of a few microorganisms has been used as markers to predict diverse diseases. In this study, we hypothesized that multi-classification using machine learning approach could distinguish the gut microbiome from following six diseases: multiple sclerosis, juvenile idiopathic arthritis, myalgic encephalomyelitis/chronic fatigue syndrome, acquired immune deficiency syndrome, stroke and colorectal cancer. We used the abundance of microorganisms at five taxonomy levels as features in 696 samples collected from different studies to establish the best prediction model. We built classification models based on four multi-class classifiers and two feature selection methods including a forward selection and a backward elimination. As a result, we found that the performance of classification is improved as we use the lower taxonomy levels of features; the highest performance was observed at the genus level. Among four classifiers, LogitBoost-based prediction model outperformed other classifiers. Also, we suggested the optimal feature subsets at the genus-level obtained by backward elimination. We believe the selected feature subsets could be used as markers to distinguish various diseases simultaneously. The finding in this study suggests the potential use of selected features for the diagnosis of several diseases.

TADA: phylogenetic augmentation of microbiome samples enhances phenotype classification

MOTIVATION

Learning associations of traits with the microbial composition of a set of samples is a fundamental goal in microbiome studies. Recently, machine learning methods have been explored for this goal, with some promise. However, in comparison to other fields, microbiome data are high-dimensional and not abundant; leading to a high-dimensional low-sample-size under-determined system. Moreover, microbiome data are often unbalanced and biased. Given such training data, machine learning methods often fail to perform a classification task with sufficient accuracy. Lack of signal is especially problematic when classes are represented in an unbalanced way in the training data; with some classes under-represented. The presence of inter-correlations among subsets of observations further compounds these issues. As a result, machine learning methods have had only limited success in predicting many traits from microbiome. Data augmentation consists of building synthetic samples and adding them to the training data and is a technique that has proved helpful for many machine learning tasks.

RESULTS

In this paper, we propose a new data augmentation technique for classifying phenotypes based on the microbiome. Our algorithm, called TADA, uses available data and a statistical generative model to create new samples augmenting existing ones, addressing issues of low-sample-size. In generating new samples, TADA takes into account phylogenetic relationships between microbial species. On two real datasets, we show that adding these synthetic samples to the training set improves the accuracy of downstream classification, especially when the training data have an unbalanced representation of classes.

AVAILABILITY AND IMPLEMENTATION

TADA is available at https://github.com/tada-alg/TADA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition

Microbial communities are ubiquitous and often influence macroscopic properties of the ecosystems they inhabit. However, deciphering the functional relationship between specific microbes and ecosystem properties is an ongoing challenge owing to the complexity of the communities. This challenge can be addressed, in part, by integrating the advances in DNA sequencing technology with computational approaches like machine learning. Although machine learning techniques have been applied to microbiome data, use of these techniques remains rare, and user-friendly platforms to implement such techniques are not widely available. We developed a tool that implements neural network and random forest models to perform regression and feature selection tasks on microbiome data. In this study, we applied the tool to analyze soil microbiome (16S rRNA gene profiles) and dissolved organic carbon (DOC) data from a 44-day plant litter decomposition experiment. The microbiome data includes 1709 total bacterial operational taxonomic units (OTU) from 300+ microcosms. Regression analysis of predicted and actual DOC for a held-out test set of 51 samples yield Pearson's correlation coefficients of.636 and.676 for neural network and random forest approaches, respectively. Important taxa identified by the machine learning techniques are compared to results from a standard tool (indicator species analysis) widely used by microbial ecologists. Of 1709 bacterial taxa, indicator species analysis identified 285 taxa as significant determinants of DOC concentration. Of the top 285 ranked features determined by machine learning methods, a subset of 86 taxa are common to all feature selection techniques. Using this subset of features, prediction results for random permutations of the data set are at least equally accurate compared to predictions determined using the entire feature set. Our results suggest that integration of multiple methods can aid identification of a robust subset of taxa within complex communities that may drive specific functional outcomes of interest.

Gut Microbiota in Patients With Irritable Bowel Syndrome-A Systematic Review

BACKGROUND & AIMS

Irritable bowel syndrome (IBS) is common but difficult to treat. Altering the gut microbiota has been proposed as a strategy for treatment of IBS, but the association between the gut microbiome and IBS symptoms has not been well established. We performed a systematic review to explore evidence for this association.

METHODS

We searched databases, including MEDLINE, EMBASE, Cochrane CDSR, and CENTRAL, through April 2, 2018 for case-control studies comparing the fecal or colon microbiomes of adult or pediatric patients with IBS with microbiomes of healthy individuals (controls). The primary outcome was differences in specific gut microbes between patients with IBS and controls.

RESULTS

The search identified 2631 citations; 24 studies from 22 articles were included. Most studies evaluated adults presenting with various IBS subtypes. Family Enterobacteriaceae (phylum Proteobacteria), family Lactobacillaceae, and genus Bacteroides were increased in patients with IBS compared with controls, whereas uncultured Clostridiales I, genus Faecalibacterium (including Faecalibacterium prausnitzii), and genus Bifidobacterium were decreased in patients with IBS. The diversity of the microbiota was either decreased or not different in IBS patients compared with controls. More than 40% of included studies did not state whether cases and controls were comparable (did not describe sex and/or age characteristics).

CONCLUSIONS

In a systematic review, we identified specific bacteria associated with microbiomes of patients with IBS vs controls. Studies are needed to determine whether these microbes are a product or cause of IBS.

Different duck products protein on rat physiology and gut microbiota

We report the effects of protein from different duck products on the intestinal flora and physiology of rats. After 30 days of feeding, rats fed water-boiled salted duck protein had the lowest gut microbial diversity and richness. Allobaculum, Lactobacillus, Coprococcus and Eubacterium increased in rats fed wine-cured duck protein, while rats fed water-boiled salted and wine-cured duck protein showed increased serum urea (UREA) concentrations and serum cholesterol (CHOL) to HDL-cholesterol (HDLC) ratios, but decreased retroperitoneal white adipose tissue (rWAT) and perirenal white adipose tissue (pWAT) to body weight ratios. The changes in gut bacteria were mainly associated with the fat-mass index (weight of rWAT or pWAT to body weight ratio), accompanied by the opposite correlation with UREA content. SIGNIFICANCE: It showed that protein from different duck products impacted the intestinal flora and caused physiological changes in rats. Different sources of processed protein vary in their digestibility and digestive kinetics, all of which can affect the intestinal microbiota and physiology. We report the effects is an effort to map the complex interactions of "host physiology-nutrition-microbiota" in order to provide some insights into that food processing can be improved to promote beneficial gut microbes and enhance human health.

A Prospective Study of the Urinary and Gastrointestinal Microbiome in Prepubertal Males

OBJECTIVE

To determine if urinary microbial communities similar to those described in adults exist in children and to profile the urinary and gastrointestinal microbiome in children presenting to urology for both routine and complex urologic procedures.

METHODS

Prepubertal boys (n = 20, ages 3 months-8 years; median age 15 months) who required elective urologic procedures were eligible. Urine samples were collected via sterile catheterization and fecal samples were obtained by rectal swabs. DNA was extracted from urine pellet and fecal samples and subjected to bacterial profiling via 16S rDNA Illumina sequencing and 16S rDNA quantitative polymerase chain reaction. We assessed within and between sample diversity and differential species abundance between samples.

RESULTS

Urine samples had low bacterial biomass that reflected the presence of bacterial populations. The most abundant genera detected in urine samples are not common to skin microbiota and several of the genera have been previously identified in the urinary microbiome of adults. We report presumably atypical compositional differences in both the urinary and gastrointestinal microbiome in children with prior antibiotic exposure and highlight an important case of a child who had undergone lifelong antibiotic treatment as prophylaxis for congenital abnormalities.

CONCLUSION

This study provides one of the first characterizations of the urinary microbiome in prepubertal males. Defining the baseline healthy microbiome in children may lay the foundation for understanding the long-term impact of factors such as antibiotic use in the development of a healthy microbiome as well as the development of future urologic and gastrointestinal diseases.

A Pilot Study on Anti-Obesity Mechanisms of Kappaphycus Alvarezii: The Role of Native κ-Carrageenan and the Leftover Sans-Carrageenan Fraction

Kappaphycus is a commercially important edible red alga widely cultivated for carrageenan production. Here, we aimed to investigate the anti-obesity mechanism of Kappaphycus alvarezii by comparing the effects of whole seaweed (T), extracted native κ-carrageenan (CGN), and the leftover fraction sans-carrageenan (SCGN) supplementations (5%, w/w) on diet-induced obese C57BL/6J mice. A high-fat diet induced both a raised body fat percentage and serum cholesterol level, increased adipocytes size, abnormal levels of adipocytokines, and promoted gut dysbiosis. Our results showed that, overall, both CGN and SCGN were more effective in reversing obesity and related metabolic syndromes to normal levels than T. Furthermore, these findings suggested that CGN- and SCGN-modulated gut dysbiosis induced by a high-fat diet, which may play an influencing role in adiponectin dysregulation. Our data also showed some evidence that CGN and SCGN have distinct effects on selected genes involved in lipid metabolism. In conclusion, both κ-carrageenan and SCGN have novel anti-obesity potential with possible different mechanisms of action.

Metaproteomic investigation to assess gut microbiota shaping in newborn mice: A combined taxonomic, functional and quantitative approach

Breastfeeding is nowadays known to be one of the most critical factors contributing to the development of an efficient immune system. In the last decade, a consistent number of pieces of evidence demonstrated the relationship between a healthy organism and its gut microbiota. However, this link is still not fully understood and requires further investigation. We recently adopted a murine model to describe the impact of either maternal milk or parental genetic background, on the composition of the gut microbial population in the first weeks of life. A metaproteomic approach to such complex environments is a big challenge that requires a strong effort in both data production and analysis, including the set-up of dedicated multitasking bioinformatics pipelines. Herein we present an LC-MS/MS based investigation to monitor mouse gut microbiota in the early life, aiming at characterizing its functions and metabolic activities together with a taxonomic description in terms of operational taxonomic units. We provided a quantitative evaluation of bacterial metaproteins, taking into account differential expression results in relation to the functional and taxonomic classification, particularly with proteins from orthologues groups. This allowed the reduction of the bias arising from the presence of a high number of shared peptides, and proteins, among different bacterial species. We also focused on host mucosal proteome and its modulation, according to different microbiota composition. SIGNIFICANCE: This paper would represent a reference work for investigations on gut microbiota in early life, from both a microbiological and a functional proteomic point of view. We focused on the shaping of the mouse gut microbiota in dependence on the feeding modality, defining a reliable taxonomic description, highlighting some functional characteristics of the microbial community, and performing a first quantitative evaluation by data independent analysis in metaproteomics.

Leveraging Human Microbiome Features to Diagnose and Stratify Children with Irritable Bowel Syndrome

Accurate diagnosis and stratification of children with irritable bowel syndrome (IBS) remain challenging. Given the central role of recurrent abdominal pain in IBS, we evaluated the relationships of pediatric IBS and abdominal pain with intestinal microbes and fecal metabolites using a comprehensive clinical characterization and multiomics strategy. Using rigorous clinical phenotyping, we identified preadolescent children (aged 7 to 12 years) with Rome III IBS (n = 23) and healthy controls (n = 22) and characterized their fecal microbial communities using whole-genome shotgun metagenomics and global unbiased fecal metabolomic profiling. Correlation-based approaches and machine learning algorithms identified associations between microbes, metabolites, and abdominal pain. IBS cases differed from controls with respect to key bacterial taxa (eg, Flavonifractor plautii and Lachnospiraceae bacterium 7_1_58FAA), metagenomic functions (eg, carbohydrate metabolism and amino acid metabolism), and higher-order metabolites (eg, secondary bile acids, sterols, and steroid-like compounds). Significant associations between abdominal pain frequency and severity and intestinal microbial features were identified. A random forest classifier built on metagenomic and metabolic markers successfully distinguished IBS cases from controls (area under the curve, 0.93). Leveraging multiple lines of evidence, intestinal microbes, genes/pathways, and metabolites were associated with IBS, and these features were capable of distinguishing children with IBS from healthy children. These multi-omics features, and their links to childhood IBS coupled with nutritional interventions, may lead to new microbiome-guided diagnostic and therapeutic strategies.

Effects of single and combined toxic exposures on the gut microbiome: Current knowledge and future directions

Human populations are chronically exposed to mixtures of toxic chemicals. Predicting the health effects of these mixtures require a large amount of information on the mode of action of their components. Xenobiotic metabolism by bacteria inhabiting the gastrointestinal tract has a major influence on human health. Our review aims to explore the literature for studies looking to characterize the different modes of action and outcomes of major chemical pollutants, and some components of cosmetics and food additives, on gut microbial communities in order to facilitate an estimation of their potential mixture effects. We identified good evidence that exposure to heavy metals, pesticides, nanoparticles, polycyclic aromatic hydrocarbons, dioxins, furans, polychlorinated biphenyls, and non-caloric artificial sweeteners affect the gut microbiome and which is associated with the development of metabolic, malignant, inflammatory, or immune diseases. Answering the question 'Who is there?' is not sufficient to define the mode of action of a toxicant in predictive modeling of mixture effects. Therefore, we recommend that new studies focus to simulate real-life exposure to diverse chemicals (toxicants, cosmetic/food additives), including as mixtures, and which combine metagenomics, metatranscriptomics and metabolomic analytical methods achieving in that way a comprehensive evaluation of effects on human health.

Precision Nutrition and the Microbiome, Part I: Current State of the Science

The gut microbiota is a highly complex community which evolves and adapts to its host over a lifetime. It has been described as a virtual organ owing to the myriad of functions it performs, including the production of bioactive metabolites, regulation of immunity, energy homeostasis and protection against pathogens. These activities are dependent on the quantity and quality of the microbiota alongside its metabolic potential, which are dictated by a number of factors, including diet and host genetics. In this regard, the gut microbiome is malleable and varies significantly from host to host. These two features render the gut microbiome a candidate ‘organ’ for the possibility of precision microbiomics—the use of the gut microbiome as a biomarker to predict responsiveness to specific dietary constituents to generate precision diets and interventions for optimal health. With this in mind, this two-part review investigates the current state of the science in terms of the influence of diet and specific dietary components on the gut microbiota and subsequent consequences for health status, along with opportunities to modulate the microbiota for improved health and the potential of the microbiome as a biomarker to predict responsiveness to dietary components. In particular, in Part I, we examine the development of the microbiota from birth and its role in health. We investigate the consequences of poor-quality diet in relation to infection and inflammation and discuss diet-derived microbial metabolites which negatively impact health. We look at the role of diet in shaping the microbiome and the influence of specific dietary components, namely protein, fat and carbohydrates, on gut microbiota composition.

Investigation of gut microbiome association with inflammatory bowel disease and depression: a machine learning approach

Background: Inflammatory bowel disease (IBD) is a group of chronic diseases related to inflammatory processes in the digestive tract generally associated with an immune response to an altered gut microbiome in genetically predisposed subjects. For years, both researchers and clinicians have been reporting increased rates of anxiety and depression disorders in IBD, and these disorders have also been linked to an altered microbiome. However, the underlying pathophysiological mechanisms of comorbidity are poorly understood at the gut microbiome level. Methods: Metagenomic and metatranscriptomic data were retrieved from the Inflammatory Bowel Disease Multi-Omics Database. Samples from 70 individuals that had answered to a self-reported depression and anxiety questionnaire were selected and classified by their IBD diagnosis and their questionnaire results, creating six different groups. The cross-validation random forest algorithm was used in 90% of the individuals (training set) to retain the most important species involved in discriminating the samples without losing predictive power. The validation set that represented the remaining 10% of the samples equally distributed across the six groups was used to train a random forest using only the species selected in order to evaluate their predictive power. Results: A total of 24 species were identified as the most informative in discriminating the 6 groups. Several of these species were frequently described in dysbiosis cases, such as species from the genus Bacteroides and Faecalibacterium prausnitzii. Despite the different compositions among the groups, no common patterns were found between samples classified as depressed. However, distinct taxonomic profiles within patients of IBD depending on their depression status were detected. Conclusions: The machine learning approach is a promising approach for investigating the role of microbiome in IBD and depression. Abundance and functional changes in these species suggest that depression should be considered as a factor in future research on IBD.

Elimination of Fermentable Carbohydrates to Reduce Gastrointestinal Symptoms in Pediatric Patients With Irritable Bowel Syndrome: A Narrative Review

Irritable bowel syndrome (IBS) is classified as a functional gastrointestinal (GI) disorder characterized by abdominal pain, bloating, and changes in bowel function. Although the pathophysiology of IBS is incompletely understood, fermentable carbohydrates are implicated as a potential cause of symptoms. An elimination diet, such as a low-FODMAP (fermentable oligosaccharides, disaccharides, monosaccharides, and polyols) diet, represents a potential intervention for reducing GI symptoms in patients with IBS. The role of fermentable carbohydrates in symptom onset is well studied in adult patients with IBS; however, less research exists in the pediatric population. This review sought to explore evidence for the role of dietary fermentable carbohydrate elimination to reduce GI symptoms (abdominal pain, stool changes, abdominal bloating) in children and adolescents (4-19 years of age) diagnosed with IBS based on Rome III or IV criteria. Five studies of neutral to positive quality rating were identified and analyzed using the Academy of Nutrition and Dietetics Evidence Analysis Process. These studies demonstrate that dietary elimination of fermentable carbohydrates, such as through a low-FODMAP diet, reduces the severity of 1 or more GI symptoms in about one-quarter to one-half of pediatric patients with IBS. Patients without improvement are considered "nonresponders" and may require an alternative intervention. More research is needed to establish the best way to identify patients who would respond to elimination diets vs other IBS treatment strategies.

The power of small changes: Comprehensive analyses of microbial dysbiosis in breast cancer

Disparate occurrence of breast cancer remains an intriguing question since only a subset of women with known risk factors develop cancer. Recent studies suggest an active role of local and distant microbiota in breast cancer initiation, progression, and overall prognosis. A dysbiotic microbiota predisposes the body to develop cancer by inducing genetic instability, initiating DNA damage and proliferation of the damaged progeny, eliciting favorable immune response, metabolic dysregulation and altered response to therapy. In this review, we present our analyses of the existing datasets and discuss the local dysbiosis observed in breast cancer patients and different aspects of breast carcinogenesis that can be potentially influenced by local breast microbiota. Striking differences between microbial community compositions in breast of cancer patients compared to healthy individuals were noted. Differences in microbiome were also apparent between benign and malignant disease and between nipple aspirate fluid of healthy individuals and breast survivors. We also discuss the identification of distinct bacterial, fungal, viral as well as parasite signatures for breast cancer. These microbes are capable of producing numerous secondary metabolites that can act as signaling mediators effecting breast cancer progression. We review how microbes potentially alter response to therapy affecting drug metabolism, pharmacokinetics, anti-tumor effects and toxicity. In conclusion, breast harbors a community of microbes that can communicate with the host cells inducing downstream signaling pathways and modulating various aspects of breast cancer growth and metastatic progression and an improved understanding of microbial dysbiosis can potentially reduce breast cancer risk and improve outcomes of breast cancer patients. The human microbiome, now referred to as, the "forgotten organ" contains a metagenome that is 100-fold more diverse compared to the human genome, thereby, is critically associated with human health [1,2]. With the revelations of the human microbiome project and advent of deep sequencing techniques, a plethora of information has been acquired in recent years. Body sites like stomach, bladder and lungs, once thought to be sterile, are now known to harbor millions of indigenous microbial species. Approximately 80% of the healthy microbiome consists of Firmicutes and Bacteroidetes accompanied by Verrucomicrobia, Actinobacteria, Proteobacteria, Tenericutes and Cyanobacteria [2-7]. The role of microbiome in diabetes, obesity and even neurodegenerative diseases was greatly appreciated in the last decade [1,7-14] and now it has been established that microbiome significantly contributes to many organ specific cancers [1,15,16].

Glutamatergic Signaling Along The Microbiota-Gut-Brain Axis

A complex bidirectional communication system exists between the gastrointestinal tract and the brain. Initially termed the “gut-brain axis” it is now renamed the “microbiota-gut-brain axis” considering the pivotal role of gut microbiota in maintaining local and systemic homeostasis. Different cellular and molecular pathways act along this axis and strong attention is paid to neuroactive molecules (neurotransmitters, i.e., noradrenaline, dopamine, serotonin, gamma aminobutyric acid and glutamate and metabolites, i.e., tryptophan metabolites), sustaining a possible interkingdom communication system between eukaryota and prokaryota. This review provides a description of the most up-to-date evidence on glutamate as a neurotransmitter/neuromodulator in this bidirectional communication axis. Modulation of glutamatergic receptor activity along the microbiota-gut-brain axis may influence gut (i.e., taste, visceral sensitivity and motility) and brain functions (stress response, mood and behavior) and alterations of glutamatergic transmission may participate to the pathogenesis of local and brain disorders. In this latter context, we will focus on two major gut disorders, such as irritable bowel syndrome and inflammatory bowel disease, both characterized by psychiatric co-morbidity. Research in this area opens the possibility to target glutamatergic neurotransmission, either pharmacologically or by the use of probiotics producing neuroactive molecules, as a therapeutic approach for the treatment of gastrointestinal and related psychiatric disorders.

Evaluation of variable selection methods for random forests and omics data sets

Machine learning methods and in particular random forests are promising approaches for prediction based on high dimensional omics data sets. They provide variable importance measures to rank predictors according to their predictive power. If building a prediction model is the main goal of a study, often a minimal set of variables with good prediction performance is selected. However, if the objective is the identification of involved variables to find active networks and pathways, approaches that aim to select all relevant variables should be preferred. We evaluated several variable selection procedures based on simulated data as well as publicly available experimental methylation and gene expression data. Our comparison included the Boruta algorithm, the Vita method, recurrent relative variable importance, a permutation approach and its parametric variant (Altmann) as well as recursive feature elimination (RFE).  In our simulation studies, Boruta was the most powerful approach, followed closely by the Vita method. Both approaches demonstrated similar stability in variable selection, while Vita was the most robust approach under a pure null model without any predictor variables related to the outcome. In the analysis of the different experimental data sets, Vita demonstrated slightly better stability in variable selection and was less computationally intensive than Boruta. In conclusion, we recommend the Boruta and Vita approaches for the analysis of high-dimensional data sets. Vita is considerably faster than Boruta and thus more suitable for large data sets, but only Boruta can also be applied in low-dimensional settings.

Circadian disruption and divergent microbiota acquisition under extended photoperiod regimens in chicken

The gut microbiota is crucial for metabolic homeostasis, immunity, growth and overall health, and it is recognized that early-life microbiota acquisition is a pivotal event for later-life health. Recent studies show that gut microbiota diversity and functional activity are synchronized with the host circadian rhythms in healthy individuals, and circadian disruption elicits dysbiosis in mammalian models. However, no studies have determined the associations between circadian disruption in early life, microbiota colonization, and the consequences for microbiota structure in birds. Chickens, as a major source of protein around the world, are one of the most important agricultural species, and their gut and metabolic health are significant concerns. The poultry industry routinely employs extended photoperiods (>18 h light) as a management tool, and their impacts on the chicken circadian, its role in gut microbiota acquisition in early life (first 3 weeks of life), and consequences for later life microbiota structure remain unknown. In this study, the objectives were to (a) characterize circadian activity under two different light regimes in layer chicken (12/12 h′ Light/Dark (LD) and 23/1 h LD), (b) characterize gut microbiota acquisition and composition in the first 4 weeks of life, (c) determine if gut microbiota oscillate in synchrony with the host circadian rhythm, and (d) to determine if fecal microbiota is representative of cecal microbiota in early life. Expression of clock genes (clock, bmal1, and per2) was assayed, and fecal and cecal microbiotas were characterized using 16S rRNA gene amplicon analyses from birds raised under two photoperiod treatments. Chickens raised under 12/12 LD photoperiods exhibited rhythmic clock gene activity, which was absent in birds raised under the extended (23/1 LD) photoperiod. There was differential microbiota acquisition under different photoperiod regimes in newly hatched chicks. Gut microbiota members showed a similar oscillating pattern as the host, but this association was not as strong as found in mammals. Finally, the fecal microbiota was found to be not representative of cecal microbiota membership and structure in young birds. This is one of the first studies to demonstrate the use of photoperiods to modulate microbiota acquisition in newly hatched chicks, and show their potential as a tool to promote the colonization of beneficial microorganisms.

Nonceliac Wheat Sensitivity: An Immune-Mediated Condition with Systemic Manifestations

Non-celiac wheat sensitivity (NCWS) is characterized by gastrointestinal and extra-intestinal symptoms following the ingestion of gluten-containing cereals in subjects without celiac disease or wheat allergy. The identity of the molecular triggers in these cereals responsible for the symptoms of NCWS remains to be delineated. Recent research has identified a biological basis for the condition, with the observation of systemic immune activation in response to microbial translocation that appears to be linked to intestinal barrier defects. Ongoing research efforts are aimed at further characterizing the etiology, mechanism, and biomarkers of the condition.

Man and the Microbiome: A New Theory of Everything?

The gut microbiome is implicated in the pathophysiology of a wide range of psychological disorders. Preclinical studies have provided us with key insights into the mechanisms by which the microbiome influences bidirectional gut-brain communication. There are many signaling pathways involved, including the hypothalamic-pituitary-adrenal axis, immune modulation, tryptophan and serotonin metabolism, bile acid transformation, microbial production of neuroactive compounds, and regulation of the endocannabinoid system. The complex and widespread influence of the microbiome on many physiological and psychological processes has generated a keen interest in its therapeutic potential for depression, anxiety, autism, and other psychiatric disorders. It has been shown that the microbiome composition of people suffering with such conditions differs significantly from that of healthy controls, and although the area is in its infancy, interventional studies that alter a person's microbiome through the use of probiotics, prebiotics, or dietary change can alleviate psychopathological symptoms.

Current Understanding of Gut Microbiota in Mood Disorders: An Update of Human Studies

Gut microbiota plays an important role in the bidirectional communication between the gut and the central nervous system. Mounting evidence suggests that gut microbiota can influence the brain function via neuroimmune and neuroendocrine pathways as well as the nervous system. Advances in gene sequencing techniques further facilitate investigating the underlying relationship between gut microbiota and psychiatric disorders. In recent years, researchers have preliminarily explored the gut microbiota in patients with mood disorders. The current review aims to summarize the published human studies of gut microbiota in mood disorders. The findings showed that microbial diversity and taxonomic compositions were significantly changed compared with healthy individuals. Most of these findings revealed that short-chain fatty acids-producing bacterial genera were decreased, while pro-inflammatory genera and those involved in lipid metabolism were increased in patients with depressive episodes. Interestingly, the abundance of Actinobacteria, Enterobacteriaceae was increased and Faecalibacterium was decreased consistently in patients with either bipolar disorder or major depressive disorder. Some studies further indicated that specific bacteria were associated with clinical characteristics, inflammatory profiles, metabolic markers, and pharmacological treatment. These studies present preliminary evidence of the important role of gut microbiota in mood disorders, through the brain-gut-microbiota axis, which emerges as a promising target for disease diagnosis and therapeutic interventions in the future.

Influenza A virus subtype H9N2 infection disrupts the composition of intestinal microbiota of chickens

The impact of low pathogenic influenza viruses such as subtype H9N2, which infect the respiratory and the gastrointestinal tracts of chickens, on microbial composition are not known. Twenty-day-old specific pathogen-free chickens were assigned to two treatment groups, control (uninfected) and H9N2-infected (challenged via the oral-nasal route). Fecal genomic DNA was extracted, and the V3-V4 regions of the 16S rRNA gene were sequenced using the Illumina Miseq® platform. Sequences were curated using Mothur as described in the MiSeq SOP. Infection of chickens with H9N2 resulted in an increase in phylum Proteobacteria, and differential enrichment with the genera Vampirovibrio, Pseudoflavonifractor, Ruminococcus, Clostridium cluster XIVb and Isobaculum while control chickens were differentially enriched with genera Novosphingobium, Sphingomonas, Bradyrhizobium and Bifidobacterium. Analysis of pre- and post-H9N2 infection of the same chickens showed that, before infection, the fecal microbiota was characterized by Lachnospiracea and Ruminococcaceae family and the genera Clostridium sensu stricto, Roseburia and Lachnospiraceae incertae sedis. However, post-H9N2 infection, class Deltaproteobacteria, orders Clostridiales and Bacteroidiales and the genus Alistipes were differentially enriched. Findings from the current study show that influenza virus infection in chickens results in the shift of the gut microbiota, and the disruption of the host-microbial homeostasis in the gut might be one of the mechanisms by which influenza virus infection is established in chickens.

Daily Consumption of Orange Juice from Citrus sinensis L. Osbeck cv. Cara Cara and cv. Bahia Differently Affects Gut Microbiota Profiling as Unveiled by an Integrated Meta-Omics Approach

We have investigated the effect of intake of two different orange juices from Citrus sinensis cv. "Cara Cara" and cv. "Bahia" on faecal microbiota and metabolome using an integrated meta-omics approach. Following a randomized crossover design, healthy subjects daily consumed 500 mL of orange juice from Cara Cara or Bahia juices or an isocaloric control drink. Stools were collected at baseline (T0) and after a week (T7) of intervention. Operational taxonomic units (OTUs) were pyrosequenced targeting 16S rRNA, and faecal metabolites were analyzed by an untargeted metabolomics approach based on ¹H NMR spectroscopy. The major shift observed in microbiota composition after orange juice intake was the increased abundance of a network of Clostridia OTUs from Mogibacteriaceae, Tissierellaceae, Veillonellaceae, Odoribacteraceae, and Ruminococcaceae families, whose members were differently affected by Cara Cara or Bahia juice consumption. A core of six metabolites such as inositol, choline, lysine, arginine, urocanic acid, and formate significantly increased in Cara Cara compared to the Bahia group.

Effects of Atypical Antipsychotic Treatment and Resistant Starch Supplementation on Gut Microbiome Composition in a Cohort of Patients with Bipolar Disorder or Schizophrenia

STUDY OBJECTIVE

Previous studies identified shifts in gut microbiota associated with atypical antipsychotic (AAP) treatment that may link AAPs to metabolic burden. Dietary prebiotics such as resistant starch may be beneficial in obesity and glucose regulation, but little is known mechanistically about their ability to modify gut microbiota in AAP-treated individuals. This investigation was undertaken to delineate mechanistically the effects of AAP treatment and resistant starch supplementation on gut microbiota in a psychiatric population.

DESIGN

Cross-sectional cohort study.

SETTING

The study was performed in an outpatient setting.

PATIENTS

A total of 37 adults with a diagnosis of bipolar disorder or schizophrenia who were treated with an AAP (clozapine, olanzapine, risperidone, quetiapine, or ziprasidone [21 patients]) or lithium and/or lamotrigine (16 patients) for at least 6 months.

INTERVENTION

Patients in the AAP group received raw unmodified potato starch (resistant starch) daily for 14 days.

MEASUREMENTS AND MAIN RESULTS

Of the 37 patients, the mean ± SD age was 52.2 ± 12.5 years, and 57% were male. The primary outcome was gut microbiome DNA composition. Microbiome DNA obtained from stool samples from all patients was subject to 16S ribosomal RNA (rRNA) gene sequencing before and during resistant starch supplementation. Inter- and intragroup microbial diversity measures were performed by permutational multivariate analysis of variance and the Inverse Simpson Diversity Index, respectively. Differentially abundant organisms were detected by using linear discriminant analysis effect size. Although no significant difference in overall microbiota composition was detected at baseline between AAP users and nonusers, non-AAP users showed increased fractional representation of Alistipes. AAP-treated women exhibited decreased diversity compared with non-AAP-treated women. Although the microbiome of AAP-treated patients varied with resistant starch administration, an increased abundance of the Actinobacteria phylum was observed.

CONCLUSION

These data suggest that AAP treatment is associated with measurable differences in gut microbiota, particularly in female AAP-treated patients in whom reduced species richness was observed. Additionally, variable microbiome responses to resistant starch supplementation were seen, with a significant increase in starch degraders.

Intestinal Microbiota in Early Life and Its Implications on Childhood Health

Trillions of microbes reside in the human body and participate in multiple physiological and pathophysiological processes that affect host health throughout the life cycle. The microbiome is hallmarked by distinctive compositional and functional features across different life periods. Accumulating evidence has shown that microbes residing in the human body may play fundamental roles in infant development and the maturation of the immune system. Gut microbes are thought to be essential for the facilitation of infantile and childhood development and immunity by assisting in breaking down food substances to liberate nutrients, protecting against pathogens, stimulating or modulating the immune system, and exerting control over the hypothalamic-pituitary-adrenal axis. This review aims to summarize the current understanding of the colonization and development of the gut microbiota in early life, highlighting the recent findings regarding the role of intestinal microbes in pediatric diseases. Furthermore, we also discuss the microbiota-mediated therapeutics that can reconfigure bacterial communities to treat dysbiosis.

Key role of gut microbiota in anhedonia-like phenotype in rodents with neuropathic pain

Patients with chronic neuropathic pain frequently suffer from symptoms of anhedonia, which is a core symptom of depression. Accumulating studies suggest that gut microbiota may play a role in depression via gut-microbiota-brain axis. However, it is unknown whether gut microbiota plays a role in neuropathic pain-associated anhedonia. Here, we used a rat model of spared nerve injury (SNI). Hierarchical cluster analysis of sucrose preference test (SPT) results was used to classify the SNI rats with or without anhedonia-like phenotype. The 16S ribosomal RNA sequencing analysis showed abnormal composition of gut microbiota in the anhedonia susceptible compared to sham-operated rats and resilient rats. Furthermore, antibiotics-treated mice showed pain as well as depression-like and anhedonia-like phenotypes, suggesting a role of gut microbiota in these abnormal behaviors. Transplantation of fecal microbiota from anhedonia susceptible rats into antibiotics-treated pseudo-germ-free mice significantly exaggerated pain and depression-like phenotypes, including anhedonia. In contrast, transplantation of fecal microbiota from resilient rats into antibiotics-treated pseudo-germ-free mice significantly improved pain and depression-like phenotypes, including anhedonia. In conclusion, this study suggests that abnormal composition of gut microbiota may contribute to anhedonia susceptibility post SNI surgery, and that gut microbiota also plays a role in the pain as well as depression-like phenotypes. Interestingly, fecal microbiota transplantation from SNI rats with or without anhedonia can alter pain, depression-like and anhedonia-like phenotypes in the pseudo-germ-free mice. Therefore, it is likely that gut microbiota plays a key role in the pain as well as depression-like phenotypes including anhedonia in rodents with neuropathic pain.

Dietary Habits and Abdominal Pain-related Functional Gastrointestinal Disorders: A School-based, Cross-sectional Analysis in Greek Children and Adolescents

Background/Aims

The abdominal pain-related functional gastrointestinal disorders (AP-FGIDs) affect a significant proportion of the pediatric population and consist 1 of the most frequent causes for seeking medical advice. In this study, we aimed to assess the relation of dietary habits with the likelihood of AP-FGIDs.

Methods

This was a school-based, cross-sectional study approved by the Greek Government authorities, after obtaining informed consent by the legal representatives of the children. Diagnoses of AP-FGIDs were based on the Greek official translation of the Rome III questionnaire. Demographic, socioeconomic and dietary data were collected through self-reporting or parent-reporting questionnaires. Associations between the probability of AP-FGIDs and dietary practices were assessed after adjusting for known confounders through a multiple logistic regression analysis.

Results

A total of 1365 children (147 AP-FGIDs and 1218 controls, 52.4% females, mean age: 12.8 ± 2.8 years) were included. Multiple regression analysis identified the following statistically significant confounders: victimization, the presence of a person with a severe health problem at home, female sex, engaging in limited physical exercise, and living in a single adult family. Subsequently, logistic regression, adjusted for the abovementioned confounders, showed that reduced fish and increased junk food consumption were related to a higher likelihood of AP-FGIDs.

Conclusions

Children with AP-FGIDs report excessive junk-food and reduced fish intake compared to controls. Further studies are needed in order to clarify the nature of this observation.

Contextual risk factors impacting the colonization and development of the intestinal microbiota: Implications for children in low- and middle-income countries

Early adversities, such as poverty, maternal stress, and malnutrition, can affect the structure and functioning of the developing brain with implications for biological systems such as the intestinal microbiota. To date, most studies examining the impact of these risk factors on the development and functioning of the intestinal microbiota have primarily been conducted in high-income countries. However, arguably, children in low- and middle-income countries may be at increased risk given cumulative biological and psychosocial adversities during their development. Accumulating evidence in low- and middle-income countries has linked dysbiosis of the intestinal microbiota to child health outcomes such as stunting, malnutrition, and diarrheal diseases characterized by reduced microbial diversity and elevated pathogenic bacteria, which has implications for psychosocial outcomes. This review summarizes empirical findings that highlight the association between risk factors prevalent in low- and middle-income countries and the intestinal microbiota of children. Additionally, we briefly survey the current evidence regarding the effect of nutritional interventions on the microbial composition of children in low- and middle-income countries. We conclude that these empirical studies have the capacity to inform future research investigating the influence of preventive interventions on biological systems by targeting the predominant risk factors faced by children in low- and middle-income countries.

Interactions between Host PPARs and Gut Microbiota in Health and Disease

The human gastrointestinal tract is inhabited by many types of microbiota, including bacteria, viruses, and fungi. Dysregulations of their microenvironment are associated with various health problems, not only limited to gastrointestinal disorders, such as inflammatory bowel disease, but to impacts beyond the intestine. For example, intestinal microbiota can affect the liver in non-alcoholic fatty liver disease, visceral adipose tissue during adipogenesis, and the heart in atherosclerosis. The factors contributing to these pathogeneses involve the gut microbiota and the effector organs of the host, and everything in between. The nuclear receptor peroxisome proliferator-activated receptors (PPARs) are pivotal for the modulation of many of the pathogeneses mentioned above. It is, therefore, conceivable that, in the process of host-microbiota interactions, PPARs play important roles. In this review, we focus on the interactions between host PPARs in different organs and gut microbiota and their impacts on maintaining health and various diseases.

The microbiota-gut-brain axis: A promising avenue to foster healthy developmental outcomes

Fostering healthy developmental growth in the first years of life is associated with numerous favorable cognitive, social, and economic outcomes. Funding and promoting research aimed at identifying potential targets for early intervention should be a top priority for lawmakers and funders. One promising avenue of research and potential early intervention is the microbiota–gut–brain axis. In this report, we briefly examine the role of the gut microbiota in human life, focusing on links with health, cognition, and behavior. We then discuss the development of the gut microbiota and the critical early window in which colonization occurs. Then, we review current nonnutritive means of influencing the gut microbiota in early life. Finally, we discuss the implications this work has for early intervention in low‐income communities and end with recommendations regarding further research and research funding priorities.

The Initial Oral Microbiota of Neonates Among Subjects With Gestational Diabetes Mellitus

Objective: The objective was to investigate the potential effect of gestational diabetes mellitus on the initial neonatal oral microbiome community structure. Methods: Oral samples were collected from 20 full-term, vaginally delivered newborns with sterile swabs. Nine of them had mothers diagnosed with gestational diabetes mellitus (GDM group), while 11 had non-diabetic mothers (NDM group). The oral microbiota was analyzed using multi-barcode 16S rRNA sequencing on Illumina MiSeq system. Results: The results showed that the birth weight, gestational age and gestational weight gain were significantly higher in NDM group. There was a significant correlation between gestational age and birth weight. Neonatal oral microbiome was composed of five dominant phyla from Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Tenericutes. Compared to NDM group, a higher alpha diversity and reduction of phylum Firmicutes were observed in GDM group. Genus Lactobacillus dominated in NDM group, while Alistipes, Streptococcus, and Faecalibacterium were overabundant in GDM group. Additionally, carbohydrate metabolism increased in NDM group, whereas amino acid metabolism, vitamin metabolism and lipopolysaccharide biosynthesis were more abundant in GDM group. Conclusions: This study showed a distinct oral microbiota profile in neonates born to mothers with GDM, which indicated that maternal diabetes status played an important role in neonatal initial oral microbiota.

Evidence of increased fecal granins in children with irritable bowel syndrome and correlates with symptoms

BACKGROUND

Granins have been implicated in the pathophysiology of irritable bowel syndrome (IBS) in adults. We sought to determine whether fecal granins are altered in children with IBS and associated with symptoms.

METHODS

Children (7-12 years of age) with IBS and healthy controls (HC) kept daily pain and stool diaries for 2 weeks. Stool samples were analyzed for chromogranins A and B (CgA, CgB) and secretogranins II and III (SgII, SgIII). Children also completed psychological measures to assess anxiety, depression, somatization, and internalizing symptoms.

KEY RESULTS

Fecal CgB and SgIII concentrations were higher in all the boys (IBS plus HC, n = 48) than in all the girls (IBS plus HC, n = 75) (P = 0.02 and P = 0.046, respectively). CgA and SgIII were greater in children with IBS (n = 52) vs HC (n = 69) (P = 0.01, P = 0.017, respectively). CgB and SgII did not differ between groups. In children with IBS, the number of pain episodes per week and mean daily pain rating correlated positively with all four granins. The number of stools per day correlated positively with CgB and SgII, and the percent of diarrheal stools (6 or 7 on the Bristol Scale) correlated inversely with all four granins in boys but not in girls. Fecal granins did not correlate with psychological measures.

CONCLUSIONS AND INFERENCES

As measured by fecal granins, there is evidence of neuroimmune activation in children with IBS. Granins are related to abdominal pain symptoms, stooling frequency, and stool form in children with IBS. Sex influences the fecal concentration of CgB and SgIII.

A Metagenomics Study on Hirschsprung's Disease Associated Enterocolitis: Biodiversity and Gut Microbial Homeostasis Depend on Resection Length and Patient's Clinical History

Objectives: Since 2010, several researches demonstrated that microbiota dynamics correlate and can even predispose to Hirschsprung (HSCR) associated enterocolitis (HAEC). This study aims at assessing the structure of the microbiota of HSCR patients in relation to extent of aganglionosis and HAEC status. Methods: All consecutive HSCR patients admitted to Gaslini Institute (Genova, Italy) between May 2012 and November 2014 were enrolled. Institutional review board (IRB) approval was obtained. Stools were sampled and 16S rDNA V3-V4 regions were sequenced using the Illumina-MiSeq. Taxonomy assignments were performed using QIIME RDP. Alpha diversity indexes were analyzed by Shannon and Simpson Indexes, and Phylogenetic Diversity. Results: We enrolled 20 patients. Male to female ratio was 4:1. Six patients suffered from Total Colonic Aganglionosis (TCSA). Considering sample site (i.e., extent of aganglionosis), we confirmed the known relationship between sample site and both biodiversity and composition of intestinal microbiota. Patients with TCSA showed lower biodiversity and increased Proteobacteria/Bacteroidetes relative abundance ratio. When addressing biodiversity, composition and dynamics of TCSA patients we could not find any significant relationship with regard to HAEC occurrences. Conclusions: The composition of HAEC predisposing microbiota is specific to each patient. We could confirm that total colon resections can change the composition of intestinal microbiota and to dramatically reduce microbial diversity. The subsequent reduction of system robustness could expose TCSA patients to environmental microbes that might not be part of the normal microbiota. Future long-term studies should investigate both patients and their family environment, as well as their disease history.

The Gut Microbiome in Adult and Pediatric Functional Gastrointestinal Disorders

The importance of gut microbiota in gastrointestinal (GI) physiology was well described, but our ability to study gut microbial ecosystems in their entirety was limited by culture-based methods prior to the sequencing revolution. The advent of high-throughput sequencing opened new avenues, allowing us to study gut microbial communities as an aggregate, independent of our ability to culture individual microbes. Early studies focused on association of changes in gut microbiota with different disease states, which was necessary to identify a potential role for microbes and generate novel hypotheses. Over the past few years the field has moved beyond associations to better understand the mechanistic implications of the microbiome in the pathophysiology of complex diseases. This movement also has resulted in a shift in our focus toward therapeutic strategies, which rely on better understanding the mediators of gut microbiota-host cross-talk. It is not surprising the gut microbiome has been implicated in the pathogenesis of functional gastrointestinal disorders given its role in modulating physiological processes such as immune development, GI motility and secretion, epithelial barrier integrity, and brain-gut communication. In this review, we focus on the current state of knowledge and future directions in microbiome research as it pertains to functional gastrointestinal disorders. We summarize the factors that help shape the gut microbiome in human beings. We discuss data from animal models and human studies to highlight existing paradigms regarding the mechanisms underlying microbiota-mediated alterations in physiological processes and their relevance in human interventions. While translation of microbiome science is still in its infancy, the outlook is optimistic and we are advancing in the right direction toward precise mechanism-based microbiota therapies.