• SCFA
• body mass index
• developmental programming
• fecal
• gut
• maternal
• microbiome
• preterm infant
• preterm neonate
• short chain fatty acids

• Humans
• Female
• Feces/microbiology
• Pregnancy
• Body Mass Index
• Infant, Premature
• Infant, Newborn
• Gastrointestinal Microbiome
• Adult
• Fermentation
• Cohort Studies
• Fatty Acids, Volatile/analysis
• Fatty Acids, Volatile/metabolism
• Obesity/microbiology
• Male
• Overweight/microbiology

• RDC ETSU

• childhood obesity
• epigenetics
• fetal programming
• gestational diabetes
• gut microbiota
• maternal diet
• maternal lifestyle
• obesogenes

• GA 101080219 European Union

• Actinobacteria
• Bacteroidetes
• Firmicutes
• Gut microbiota
• Metabolic disorder
• Real-time qPCR
• Type 2 diabetes

• Bacterial community
• Bile acids
• Intestine-hepatopancreas axis
• Penaeus vannamei

• Animals
• Penaeidae/metabolism
• Penaeidae/microbiology
• Hepatopancreas/metabolism
• Bile Acids and Salts/metabolism
• Gastrointestinal Microbiome/physiology
• Intestines/microbiology
• Bacteria/metabolism

• early disorder markers
• infant
• maternal
• microbiome
• obesity
• offspring

• obesity

• Humans
• Female
• Pregnancy
• Pregnancy in Obesity
• Dysbiosis
• Obesity/therapy
• Microbiota
• Cardiovascular Diseases

• Gut-microbiota
• bacteriology.
• diabetes
• intestine
• microbiology
• obesity
• treatment

• Humans
• Diabetes Mellitus
• Diet
• Gastrointestinal Microbiome/physiology
• Obesity/metabolism

• gut metagenome
• metabolic syndrome
• obesity
• school-age population
• type-2 diabetes mellitus

• diabetes
• metabolism
• obesity

• Humans
• Gastrointestinal Microbiome
• Dysbiosis/metabolism
• Dysbiosis/microbiology
• Bacteria
• Gastrointestinal Tract/metabolism
• Bacteroidetes/metabolism

• NAFLD
• absorption and utilization
• gut microbiota
• metabolites
• phenolic acids

• Humans
• Non-alcoholic Fatty Liver Disease
• Gastrointestinal Microbiome/physiology
• Diet
• Dysbiosis

• BMI Z score
• CHILD Cohort Study
• childhood weight gain
• early life
• gut fungi
• infant growth
• microbiome
• mycobiome
• obesity

• Humans
• Infant
• Child
• Body Mass Index
• Mycobiome
• Cohort Studies
• Pediatric Obesity
• Gastrointestinal Microbiome
• Canada

• glaucoma
• gut microbiome
• inflammation
• intraocular pressure
• ocular disorders
• overweight
• probiotics
• resident brain–ocular microbiome
• therapies

• Humans
• Dysbiosis/pathology
• Neuroinflammatory Diseases
• Ecosystem
• Glaucoma/pathology
• Retina/pathology
• Obesity/pathology
• Gastrointestinal Microbiome/physiology

• Child
• Humans
• Adolescent
• Gastrointestinal Microbiome
• Pediatric Obesity/complications
• Pediatric Obesity/therapy
• Prebiotics
• Probiotics/therapeutic use
• Synbiotics

• dysbiosis
• gut microbiome
• gut–liver axis
• non-alcoholic fatty liver disease
• obesity

• 16S rRNA sequencing
• Amphipod
• Gut microbiota
• Hadal trench

• Amphipoda/genetics
• Animals
• Gastrointestinal Microbiome
• Microbiota
• Pacific Ocean
• RNA, Ribosomal, 16S/genetics

Short chain fatty acids (SCFAs) are important metabolites of the gut microbiota. It has been shown that the microbiota and its metabolic activity in children are highly influenced by the type of diet and age. Our aim was to analyse the concentration of fecal SCFAs over two years of life and to evaluate the influence of feeding method on the content of these compounds in feces. We searched PubMed/MEDLINE/Embase/Ebsco/Cinahl/Web of Science from the database inception to 02/23/2021 without language restriction for observational studies that included an analysis of the concentration of fecal SCFAs in healthy children up to 3 years of age. The primary outcome measures-mean concentrations-were calculated. We performed a random-effects meta-analysis of outcomes for which ≥2 studies provided data. A subgroup analysis was related to the type of feeding (breast milk vs. formula vs. mixed feeding) and the time of analysis (time after birth). The initial search yielded 536 hits. We reviewed 79 full-text articles and finally included 41 studies (n = 2,457 SCFA analyses) in the meta-analysis. We found that concentrations of propionate and butyrate differed significantly in breastfed infants with respect to time after birth. In infants artificially fed up to 1 month of age, the concentration of propionic acid, butyric acid, and all other SCFAs is higher, and acetic acid is lower. At 1–3 months of age, a higher concentration of only propionic acid was observed. At the age of 3–6 months, artificial feeding leads to a higher concentration of butyric acid and the sum of SCFAs. We concluded that the type of feeding influences the content of SCFAs in feces in the first months of life. However, there is a need for long-term evaluation of the impact of the observed differences on health later in life and for standardization of analytical methods and procedures for the study of SCFAs in young children. These data will be of great help to other researchers in analyzing the relationships between fecal SCFAs and various physiologic and pathologic conditions in early life and possibly their impact on health in adulthood.

• Aspergillus luchuensis mut. kawachii
• barley-koji
• microbiota
• prebiotics

Recent research suggests that gut microbiota plays an important role in the occurrence and development of excessive weight and obesity, and the early-life gut microbiota may be correlated with weight gain and later growth. However, the association between neonatal gut microbiota, particularly in preterm infants, and excessive weight and obesity remains unclear. To evaluate the relationship between gut microbiota and body mass index (BMI) growth trajectories in preterm infants, we examined microbial composition by performing 16S rDNA gene sequencing on the fecal samples from 75 preterm infants within 3 months after birth who were hospitalized in the neonatal intensive care unit of Hunan Children’s Hospital from August 1, 2018 to October 31, 2019. Then, we collected their physical growth information during 0–10 months. Latent growth mixture models were used to estimate growth trajectories of infantile BMI, and the relationship between the gut microbiota and the BMI growth trajectories was analyzed. The results demonstrated that there were 63,305 and 61 operational taxonomic units in the higher BMI group (n = 18), the lower BMI group (n = 51), and the BMI catch-up group (n = 6), respectively. There were significant differences in the abundance of the gut microbiota, but no significant differences in the diversity of it between the lower and the higher BMI group. The BMI growth trajectories could not be clearly distinguished because principal component analysis showed that gut microbiota composition among these three groups was similar. The three groups were dominated by Firmicutes and Proteobacteria in gut microbiota composition, and the abundance of Lactobacillus in the higher BMI group was significantly different from the lower BMI group. Further intervention experiments and dynamic monitoring are needed to determine the causal relationship between gut microbiota differences and the BMI change.

• 16S rDNA gene sequencing
• BMI growth trajectory
• gut microbiota
• obesity
• preterm infants

Worldwide, obesity prevalence is rising, severely impairing the health of those affected by increasing their risk for developing non-communicable diseases. The pathophysiology of obesity is complex and caused by a variety of genetic and environmental factors. Recent findings suggest that obesity is partly caused by dysbiosis, an imbalanced gut microbiome. In the context of pregnancy, maternal dysbiosis increases the child’s obesity risk, causing an intergenerational cycle of obesity. Accordingly, interventions modulating the gut microbiome have the potential to interrupt this cycle. This review discusses the potential of pre- and probiotic interventions in modulating maternal obesity associated dysbiosis to limit the child’s obesity risk. The literature search resulted in four animal studies using prebiotics as well as one animal study and six human studies using probiotics. Altogether, prebiotic supplementation in animals successfully decreased the offspring’s obesity risk, while probiotic supplementation in humans failed to show positive impacts in the offspring. However, comparability between studies is limited and considering the complexity of the topic, more studies in this field are required.

Diverticular disease (DD) is a common gastrointestinal condition. Patients with DD experience a huge variety of chronic nonspecific symptoms, including abdominal pain, bloating, and altered bowel habits. They are also at risk of complications such as acute diverticulitis, abscess formation, hemorrhage, and perforation. Intestinal dysbiosis and chronic inflammation have recently been recognized as potential key factors contributing to disease progression. Probiotics, due to their ability to modify colonic microbiota balance and to their immunomodulatory effects, could present a promising treatment option for patients with DD. Lactobacillus paracasei CNCM I 1572 (LCDG) is a probiotic strain with the capacity to rebalance gut microbiota and to decrease intestinal inflammation. This review summarizes the available clinical data on the use of LCDG in subjects with colonic DD.

• Lactobacillus paracasei CNCM I 1572
• acute diverticulitis
• diverticular disease
• probiotics
• symptomatic uncomplicated diverticular disease

• children
• gut microbiota
• metabolites
• obesity
• overweight

• Adolescent
• Amines
• Amino Acids
• Bile Acids and Salts
• Child
• Fatty Acids, Volatile
• Gastrointestinal Microbiome
• Humans
• Overweight
• Pediatric Obesity/epidemiology

• Shanghai Rising-Star Program

• 1-HNMR
• butyrate
• childhood obesity
• metabolomics
• weight outcomes at 2-years

• Capsaicin
• Gut bacteria
• Gut mucus
• Obesity
• TRPV1

• BARLEYmax
• Cocoa polyphenol
• Colonic microbiota
• Short-chain fatty acid
• n-butyrate

Immunotherapy has revolutionized the clinical outcomes of intractable cancer patients. Little is known about the intestinal nonpathogenic bacterial composition of hepatocellular carcinoma (HCC) patients treated by immunotherapy.

To determine whether there is a correlation between gut bacterial composition and prognosis in HCC patients.

From September 2019 to March 2020, we prospectively collected fecal samples and examined the gut microbiome of 8 advanced HCC patients treated with nivolumab as a second- or third-line systemic treatment. Fecal samples were collected before the start of immunotherapy. Fecal samples of patients with progression during treatment were collected at the time of progression, and fecal samples of patients who showed good response to nivolumab were collected after 5-7 mo as follow-up. Metagenomic data from 16S ribosomal RNA sequencing were analyzed using CLC Genomics Workbench. Microbiome data were analyzed according to therapeutic response.

All 8 patients were male, of which 6 had underlying chronic hepatitis B. A higher Shannon index was found in the responders than in the non-responders after nivolumab therapy (P = 0.036). The unweighted beta diversity analysis also showed that the overall bacterial community structure and phylogenetic diversity were clearly distinguished according to therapeutic response. There was no significant difference in the diversity or composition of the patient gut microbiome according to the immunotherapy used. Several taxa specific to therapeutic response were designated as follows: Dialister pneumosintes, Escherichia coli, Lactobacillus reteri, Streptococcus mutans, Enterococcus faecium, Streptococcus gordonii, Veillonella atypica, Granulicatella sp., and Trchuris trichiura for the non-responders; Citrobacter freundii, Azospirillum sp. and Enterococcus durans for the responders. Of note, a skewed Firmicutes/Bacteroidetes ratio and a low Prevotella/Bacteroides ratio can serve as predictive markers of non-response, whereas the presence of Akkermansia species predicts a good response.

The current presumptive study suggests a potential role for the gut microbiome as a prognostic marker for the response to nivolumab in treatment of HCC patients.

• Microbiome
• Nivolumab
• Firmicutes/Bacteroidetes ratio
• Prevotella/Bacteroides ratio
• Hepatocellular carcinoma
• Prognosis

• Carcinoma, Hepatocellular/drug therapy
• Feces
• Gastrointestinal Microbiome
• Humans
• Liver Neoplasms/drug therapy
• Male
• Nivolumab/therapeutic use
• Phylogeny
• RNA, Ribosomal, 16S/genetics

• Diet
• Malnutrition
• Microbiome
• Nutrition
• Obesity

• colon
• gut microbiome
• intramuscular fat
• pig breeds
• short chain fatty acids

• children
• gut microbiota
• metabolomics
• obesity
• short-chain fatty acid

• adiposity
• adolescence
• childhood
• gut microbiota

• Adiposity
• Adolescent
• Aged
• Animals
• Diet
• Gastrointestinal Microbiome
• Humans
• Infant
• Microbiota
• Obesity

• R01 HL147931 NHLBI NIH HHS
• R01HL147931 NHLBI NIH HHS

Eosinophils are key components of our host defense and potent effectors in allergic and inflammatory diseases. Once recruited to the inflammatory site, eosinophils release their cytotoxic granule proteins as well as cytokines and lipid mediators, contributing to parasite clearance but also to exacerbation of inflammation and tissue damage. However, eosinophils have recently been shown to play an important homeostatic role in different tissues under steady state. Despite the tremendous progress in the treatment of eosinophilic disorders with the implementation of biologics, there is an unmet need for novel therapies that specifically target the cytotoxic effector functions of eosinophils without completely depleting this multifunctional immune cell type. Recent studies have uncovered several endogenous molecules that decrease eosinophil migration and activation. These include short chain fatty acids (SCFAs) such as butyrate, which are produced in large quantities in the gastrointestinal tract by commensal bacteria and enter the systemic circulation. In addition, high-density lipoprotein-associated anti-inflammatory apolipoproteins have recently been shown to attenuate eosinophil migration and activation. Here, we focus on the anti-pathogenic properties of SCFAs and apolipoproteins on eosinophil effector function and provide insights into the potential use of SCFAs and apolipoproteins (and their mimetics) as effective agents to combat eosinophilic inflammation.

• HDL
• apolipoproteins
• eosinophilic disorders
• eosinophils
• lipids
• short chain fatty acids

Probiotics may have beneficial effects on patients with type 2 diabetes mellitus (T2DM). We separated 4 lactobacillus and 1 saccharomycetes from traditional fermented cheese whey (TFCW) and prepared composite probiotics from camel milk (CPCM) and investigated their effects on glucose and lipid metabolism, liver and renal function and gut microbiota in db/db mice.

CPCM was prepared in the laboratory and 40 db/db mice were randomly divided into 4 groups as metformin, low-dose and high-dose group and model group, and treated for 6 weeks. In addition, 10 C57BL/Ks mice as normal control group were used for comparison. Fasting blood glucose (FBG), body weight (BW), oral glucose tolerance test (OGTT), glycated hemoglobin (HbAlc), C-peptide (CP), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), 24 h urinary microalbumin (24 h malb), urine ketone, urine sugar, pancreas and liver tissue and intestinal flora were tested.

Compared to diabetic group, high dose CPCM significantly decreased FBG, OGTT, HbAlc and IRI, plasma TC, TG, LDL-C, 24 h malb, urine ketone and urine sugar, increased CP, HDL-C levels, improved the liver and kidney function, protected the function of islets, also increased intestinal tract lactic acid bacteria and Bifidobacterium, decreased Escherichia in db/db mice.

CPCM decreased FBG, OGTT and HbAlc, increased CP, modulated lipid metabolism and improved liver and kidney protected injury in db/db mice, which may be related to various probiotics acting through protecting the function of islets and regulating intestinal flora disturbance.

The online version contains supplementary material available at 10.1186/s12906-021-03303-4.

• Composite probiotics camel milk
• Gut microbiota
• TFCW
• TG
• db/db mice

Characterization of metabolites and microbiota composition from human stool provides powerful insight into the molecular phenotypic difference between subjects with normal weight and those with overweight/obesity. The aim of this study was to identify potential metabolic and bacterial signatures from stool that distinguish the overweight/obesity state in children/adolescents. Using ¹H NMR spectral analysis and 16S rRNA gene profiling, the fecal metabolic profile and bacterial composition from 52 children aged 7 to 16 was evaluated. The children were classified into three groups (16 with normal-weight, 17 with overweight, 19 with obesity). The metabolomic analysis identified four metabolites that were significantly different (p < 0.05) among the study groups based on one-way ANOVA testing: arabinose, butyrate, galactose, and trimethylamine. Significantly different (p < 0.01) genus-level taxa based on edgeR differential abundance tests were genus Escherichia and Tyzzerella subgroup 3. No significant difference in alpha-diversity was detected among the three study groups, and no significant correlations were found between the significant taxa and metabolites. The findings support the hypothesis of increased energy harvest in obesity by human gut bacteria through the growing observation of increased fecal butyrate in children with overweight/obesity, as well as an increase of certain monosaccharides in the stool. Also supported is the increase of trimethylamine as an indicator of an unhealthy state.

• antibiotics
• dysbiosis
• gut microbiome
• prebiotics
• probiotics

• disease
• gut
• gut–kidney axis
• health
• kidney
• microbiome

Hydrogen cross-feeding microbes form a functionally important subset of the human colonic microbiota. The three major hydrogenotrophic functional groups of the colon: sulphate-reducing bacteria (SRB), methanogens and reductive acetogens, have been linked to wide ranging impacts on host physiology, health and wellbeing.

An existing mathematical model for microbial community growth and metabolism was combined with models for each of the three hydrogenotrophic functional groups. The model was further developed for application to the colonic environment via inclusion of responsive pH, host metabolite absorption and the inclusion of host mucins. Predictions of the model, using two existing metabolic parameter sets, were compared to experimental faecal culture datasets. Model accuracy varied between experiments and measured variables and was most successful in predicting the growth of high relative abundance functional groups, such as the Bacteroides, and short chain fatty acid (SCFA) production. Two versions of the colonic model were developed: one representing the colon with sequential compartments and one utilising a continuous spatial representation. When applied to the colonic environment, the model predicted pH dynamics within the ranges measured in vivo and SCFA ratios comparable to those in the literature. The continuous version of the model simulated relative abundances of microbial functional groups comparable to measured values, but predictions were sensitive to the metabolic parameter values used for each functional group. Sulphate availability was found to strongly influence hydrogenotroph activity in the continuous version of the model, correlating positively with SRB and sulphide concentration and negatively with methanogen concentration, but had no effect in the compartmentalised model version.

Although the model predictions compared well to only some experimental measurements, the important features of the colon environment included make it a novel and useful contribution to modelling the colonic microbiota.

• Community modelling
• Hydrogen sulphide
• Methane
• Microbiome
• microPop

• Gut microbiota
• metabolic syndrome
• microbial metabolites
• microbiome
• pediatric subjects
• school-age children

• Bacteria/classification
• Bacteria/metabolism
• Child
• Diabetes Mellitus, Type 2/pathology
• Dysbiosis
• Feeding Behavior
• Gastrointestinal Microbiome/physiology
• Humans
• Metabolic Syndrome/microbiology
• Pediatric Obesity/microbiology

Obesity is a major risk factor for developing gallstone disease (GSD). Previous studies have shown that obesity is associated with an elevated Firmicutes/Bacteroidetes ratio in the gut microbiota. These findings suggest that the development of GSD may be related to gut dysbiosis. This review presents and summarizes the recent findings of studies on the gut microbiota in patients with GSD. Most of the studies on the gut microbiota in patients with GSD have shown a significant increase in the phyla Firmicutes (Lactobacillaceae family, genera Clostridium, Ruminococcus, Veillonella, Blautia, Dorea, Anaerostipes, and Oscillospira), Actinobacteria (Bifidobacterium genus), Proteobacteria, Bacteroidetes (genera Bacteroides, Prevotella, and Fusobacterium) and a significant decrease in the phyla Bacteroidetes (family Muribaculaceae, and genera Bacteroides, Prevotella, Alistipes, Paludibacter, Barnesiella), Firmicutes (genera Faecalibacterium, Eubacterium, Lachnospira, and Roseburia), Actinobacteria (Bifidobacterium genus), and Proteobacteria (Desulfovibrio genus). The influence of GSD on microbial diversity is not clear. Some studies report that GSD reduces microbial diversity in the bile, whereas others suggest the increase in microbial diversity in the bile of patients with GSD. The phyla Proteobacteria (especially family Enterobacteriaceae) and Firmicutes (Enterococcus genus) are most commonly detected in the bile of patients with GSD. On the other hand, the composition of bile microbiota in patients with GSD shows considerable inter-individual variability. The impact of GSD on the Firmicutes/Bacteroidetes ratio is unclear and reports are contradictory. For this reason, it should be stated that the results of reviewed studies do not allow for drawing unequivocal conclusions regarding the relationship between GSD and the Firmicutes/Bacteroidetes ratio in the microbiota.

• Bacteroidetes
• Firmicutes
• bilemicrobiota
• gallstone patients
• gutmicrobiota

• delivery mode
• gut microbiota
• health outcomes
• infant
• medication
• mother
• nutrition
• urbanization

• bacterial families
• children
• metabolic markers
• microbiota
• obesity

• Firmicutes
• IL-4
• Lactobacillus species
• TiO2 nanoparticles
• gastrointestinal tract
• mucin-2
• segmented filamentous bacteria
• weight gain

The relationship between diet and the diversity and function of the intestinal microbiome and its importance for human health is currently the subject of many studies. The type and proportion of microorganisms found in the intestines can determine the energy balance of the host. Intestinal microorganisms perform many important functions, one of which is participation in metabolic processes, e.g., in the production of short-chain fatty acids—SCFAs (also called volatile fatty acids). These acids represent the main carbon flow from the diet to the host microbiome. Maintaining intestinal balance is necessary to maintain the host’s normal health and prevent many diseases. The results of many studies confirm the beneficial effect of probiotic microorganisms on the balance of the intestinal microbiome and produced metabolites, including SCFAs. The aim of this review is to summarize what is known on the effects of probiotics on the production of short-chain fatty acids by gut microbes. In addition, the mechanism of formation and properties of these metabolites is discussed and verified test results confirming the effectiveness of probiotics in human nutrition by modulating SCFAs production by intestinal microbiome is presented.

• SCFA
• human health
• intestinal microbiome
• metabolites of bacteria
• probiotics

• Bifidobacterium/metabolism
• Carbon/metabolism
• Chronic Disease/prevention & control
• Diet
• Fatty Acids, Volatile/metabolism
• Gastrointestinal Microbiome/physiology
• Host Microbial Interactions/drug effects
• Host Microbial Interactions/physiology
• Humans
• Lactic Acid/metabolism
• Lactobacillus/metabolism
• Nutritional Physiological Phenomena/physiology
• Probiotics/pharmacology