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1.
Eur J Pediatr ; 183(5): 2311-2324, 2024 May.
Article in English | MEDLINE | ID: mdl-38427038

ABSTRACT

Infantile functional gastrointestinal disorders, such as colic, constipation, diarrhea, and gastroesophageal reflux (regurgitation), often occur in early infancy and, representing one of the causes of significant parental anxiety, lead to a significant strain on the healthcare resources. In this study, we aimed to evaluate the effects of Lactobacillus reuteri drops (L. reuteri NCIMB 30351) on the symptoms of infantile colic, constipation, diarrhea, and gastroesophageal reflux, as well as on the levels of intestinal microbiota in full-term newborns during the first months of life. A randomized, placebo-controlled, single-masked (blinded), post-marketing clinical study was conducted in two clinical units-Children's City Clinical Hospital of Moscow and Medical Center "St. Andrew's Hospitals-NEBOLIT" from March 2020 to May 2022 in 90 infants aged from 1 to 4 months (mean age (± SD) 12.3 ± 5.09 weeks; 53.3% females, 46.7% males). Patients with colic, regurgitation (single symptom or combination of several symptoms), and constipation or diarrhea were randomly allocated in two parallel arms to receive either 5 drops (2 × 108 colony forming unit) of L. reuteri NCIMB 30351 (n = 60) or masked placebo (n = 30) for 25 consecutive days. Two treatment arms had equal numbers of patients with constipation and diarrhea (n = 30 each). Daily crying times and their duration, evacuations, and regurgitations were recorded in a structured diary. The levels of gut microbiota were analyzed by deep sequencing of bacterial 16S rRNA gene. Infants with colic receiving supplementary L. reuteri NCIMB 30351 for 25 days had significant reduction in the numbers of colic (change from baseline - 6.3 (7.34) vs - 3.0 (7.29) in placebo, P < 0.05) and numbers of crying cases and mean duration of crying (decrease from baseline - 144 (70.7) minutes, lower in the diarrhea subgroup than in constipation infants, compared with - 80 (58.9) in placebo, P < 0.0001), as well as regurgitation numbers (decreased by - 4.8 (2.49) with L. reuteri vs - 3 (7.74) with placebo). We also observed increased numbers of evacuations in infants with constipation (L. reuteri 2.2 (2.4) vs 0.9 (1.06) in placebo, P < 0.05). There was a remarkable reduction of evacuations in infants with diarrhea, while not statistically significant. The analysis of bacterial 16S rRNA gene in the collected samples showed that L. reuteri positively influences the proportions of prevalent species, while it negatively affects both conditionally pathogenic and commensal microbes. Additional in vitro test for formation of Clostridium colonies in the presence of the probiotic demonstrated that L. reuteri effectively inhibits the growth of pathogenic Clostridium species. No adverse events were reported in this study.   Conclusion: The uptake of L. reuteri NCIMB 30351 leads to a significant reduction in the number of regurgitations, feeding-induced constipations, and diarrhea as well as mean daily numbers of crying and crying duration in infants during the first months of life. Our results suggest that L. reuteri NCIMB 30351 represents a safe and effective treatment for colic in newborns.  Trial registration: ClinicalTrials.gov : NCT04262648. What is Known: • Infantile functional gastrointestinal disorders, such as colic, constipation, diarrhea, and gastroesophageal reflux (regurgitation), often occur in early infancy and, represent one of the causes of significant parental anxiety. • A number of studies have shown that both the composition and diversity of the intestinal microbiota play important roles in the development and function of the gastrointestinal tract. What is New: • The uptake of L. reuteri NCIMB 30351 leads to a significant reduction in the number of regurgitations, feeding-induced constipations, and diarrhea as well as mean daily numbers of crying and crying duration in infants during the first months of life. • L. reuteri positively influences the proportions of prevalent species, while it negatively affects both conditionally pathogenic and commensal microbes in gut microbiota.


Subject(s)
Gastrointestinal Diseases , Gastrointestinal Microbiome , Limosilactobacillus reuteri , Probiotics , Female , Humans , Infant , Infant, Newborn , Male , Colic/therapy , Colic/microbiology , Constipation/therapy , Constipation/microbiology , Diarrhea/microbiology , Diarrhea/therapy , Gastroesophageal Reflux/microbiology , Gastroesophageal Reflux/therapy , Gastrointestinal Diseases/microbiology , Gastrointestinal Diseases/therapy , Probiotics/therapeutic use , Probiotics/administration & dosage , Single-Blind Method , Treatment Outcome , Prospective Studies
3.
NPJ Biofilms Microbiomes ; 8(1): 77, 2022 10 08.
Article in English | MEDLINE | ID: mdl-36209276

ABSTRACT

Maintaining equilibrium of the gut microbiome is crucial for human health. Diet represents an important and generally accessible natural channel of controlling the nutrients supply to the intestinal microorganisms. Although many studies showed that dietary interventions can specifically modulate gut microbiome composition, further progress of the approach is complicated by interindividual variability of the microbial community response. The reported causes of this variability include the baseline microbiome composition features, but it is unclear whether any of them are intervention-specific. Here, we applied a unified computational framework to investigate the variability of microbiome response measured as beta diversity in eight various dietary interventions using previously published 16S rRNA sequencing datasets. We revealed a number of baseline microbiome features which determine the microbiome response in an intervention-independent manner. One of the most stable associations, reproducible for different interventions and enterotypes, was a negative dependence of the response on the average number of genes per microorganism in the community-an indicator of the community functional redundancy. Meanwhile, many revealed microbiome response determinants were enterotype-specific. In Bact1 and Rum enterotypes, the response was negatively correlated with the baseline abundance of their main drivers. Additionally, we proposed a method for preliminary assessment of the microbiome response. Our study delineats the universal features determining microbiome response to diverse interventions. The proposed approach is promising for understanding the mechanisms of gut microbiome stability and improving the efficacy of personalised microbiome-tailored interventions.


Subject(s)
Gastrointestinal Microbiome , Microbiota , Diet , Feces , Humans , RNA, Ribosomal, 16S/genetics
4.
mSystems ; 7(3): e0015522, 2022 06 28.
Article in English | MEDLINE | ID: mdl-35532211

ABSTRACT

Linking microbiome composition obtained from metagenomic or 16S rRNA sequencing to various factors poses a real challenge. The compositional approach to such data is well described: a so-called isometric log-ratio (ILR) transform provides correct treatment of relative abundances. Most existing compositional methods differ in the particular choice of the transform. Although this choice does not influence the prediction of a model, it determines the subset of balances between groups of microbial taxa subsequently used for interpreting the composition shifts. We propose a method to interpret these shifts independently of the initial choice of ILR coordinates by the nearest single-balance shift. We describe here application of the method to regression, classification, and principal balance analysis of compositional data. Analytical treatment and cross-validation show that the approach provides the least-squares estimate of a single-balance shift associated with a factor with possible adjustment for covariates. As for classification and principal balance analysis, the nearest balance method provides results comparable to other compositional tools. Its advantages are the absence of assumptions about the number of taxa included in the balance and its low computational cost. The method is implemented in the R package NearestBalance. IMPORTANCE The method proposed here extends the range of compositional methods providing interpretation of classical statistical tools applied to data converted to the ILR coordinates. It provides a strictly optimal solution in several special cases. The approach is universally applicable to compositional data of any nature, including microbiome data sets.


Subject(s)
Microbiota , RNA, Ribosomal, 16S/genetics , Microbiota/genetics , Metagenomics/methods , Metagenome , Social Group
5.
J Pers Med ; 11(11)2021 Oct 29.
Article in English | MEDLINE | ID: mdl-34834465

ABSTRACT

Cardiac surgery remains a field of medicine with a high percentage of postoperative complications, including infectious ones. Modern data indicate a close relationship of infectious disorders with pathological changes in the composition of the gut microbiome; however, the extent of such changes in cardiac surgery patients is not fully clarified. In this prospective, observational, single center, pilot study, 72 patients were included, 12 among them with the infectious complications. We analyzed the features of the fecal microbiota before and in the early postoperative period, as one of the markers for predicting the occurrence of bacterial infection. We also discovered the significant change in microbial composition in the group of patients with infectious complications compared to the non-infectious group before and after cardiac surgery, despite the intra-individual variation in composition of gut microbiome. Our study demonstrated that the group of patients that had a bacterial infection in the early postoperative period already had an altered microbial composition even before the surgery. Further studies will evaluate the clinical significance of the identified proportions of individual taxa of the intestinal microbiota and consider the microbiota as a novel target for reducing the risk of infectious complications.

6.
Food Microbiol ; 94: 103658, 2021 Apr.
Article in English | MEDLINE | ID: mdl-33279083

ABSTRACT

The production of experimental beer and cider products has increased, worldwide. The complex microbiomes found in these beverages affect their organoleptic qualities and chemical compositions and can have diverse impacts on human health. The total diversity of a microbiome can be elucidated through the use of high-throughput sequencing and comprehensive data analysis tools. We analysed the bacterial and yeast microbiomes found in mixed and spontaneously fermented beers (n = 14) and unpasteurised apple ciders (n = 6), using high-throughput 16S rRNA and internal transcribed spacer (ITS) sequencing. The ratio of bacteria to yeast was measured using quantitative polymerase chain reaction (qPCR), and short-chain organic acids were analysed using high-performance liquid chromatography (HPLC). An upgraded version of the Knomics-Biota system was used to analyse the data. The microbiomes included both starter microorganisms and those that originate from the production environment and the raw materials. In addition to the common Saccharomyces and Brettanomyces, the yeast diversity included many non-conventional species. The bacterial community in beer was dominated by Lactobacillus species, whereas these communities were more diverse in cider. Lactobacillus acetotolerans was prevalent in wild ales, whereas Candida ethanolica was prevalent in cask-matured beverages. We observed complex patterns of subspecies-level yeast diversity across beer styles, breweries, and countries. Our study represents an exploratory analysis of non-conventional beer and cider microbiomes and metabolomes, which contributes information necessary to develop improved quality control processes and may drive innovative product development in experimental and artisanal brewing.


Subject(s)
Alcoholic Beverages/microbiology , Bacteria/isolation & purification , Alcoholic Beverages/analysis , Bacteria/classification , Bacteria/genetics , Bacteria/metabolism , Beer/analysis , Beer/microbiology , Fermentation , Food Microbiology , Malus/microbiology , Microbiota , Yeasts/classification , Yeasts/genetics , Yeasts/isolation & purification , Yeasts/metabolism
7.
Orphanet J Rare Dis ; 15(1): 327, 2020 11 20.
Article in English | MEDLINE | ID: mdl-33218345

ABSTRACT

BACKGROUND: Viliuisk encephalomyelitis (VE) is a rare endemic neurodegenerative disease occurring in the Yakut population of Northeastern Siberia. The main clinical features of VE are spasticity, dysarthria, dementia, central paresis and paralysis, and cortical atrophy observed via MRI. Many hypotheses have been proposed regarding its etiology, including infectious agents, genetics, environmental factors, and immunopathology. Each of these hypotheses has been supported to some extent by epidemiological and experimental data. Nevertheless, none of them has been decisively proven. Gut microbiome is one of the factors that might be involved in VE pathogenesis. RESULTS: Here we performed a pilot survey of the stool microbiomes of Yakut subjects with VE (n = 6) and without VE (n = 11). 16S rRNA sequencing showed that in comparison with the control group, the Yakuts with VE had increased proportions of Methanobrevibacter and Christensenella, which are reported to be linked to body mass index, metabolism, dietary habits and potentially to neurodegenerative disorders. The identified associations suggest that the microbiome may be involved in VE. Overall, the Yakut microbiome was quite specific in comparison with other populations, such as metropolitan Russians and native inhabitants of the Canadian Arctic. CONCLUSIONS: Describing the gut microbiome of indigenous human populations will help to elucidate the impact of dietary and environmental factors on microbial community structure and identify risks linked to the lifestyles of such groups as well as endemic diseases.


Subject(s)
Encephalomyelitis , Gastrointestinal Microbiome , Neurodegenerative Diseases , Canada , Feeding Behavior , Humans , RNA, Ribosomal, 16S , Siberia
8.
Bioinformatics ; 35(19): 3803-3811, 2019 10 01.
Article in English | MEDLINE | ID: mdl-30825306

ABSTRACT

MOTIVATION: The resistance of bacterial pathogens to antibiotics is one of the most important issues of modern health care. The human microbiota can accumulate resistance determinants and transfer them to pathogenic microbiota by means of horizontal gene transfer. Thus, it is important to develop methods of prediction and monitoring of antibiotics resistance in human populations. RESULTS: We present the agent-based VERA model, which allows simulation of the spread of pathogens, including the possible horizontal transfer of resistance determinants from a commensal microbiota community. The model considers the opportunity of residents to stay in the town or in a medical institution, have incorrect self-treatment, treatment with several antibiotics types and transfer and accumulation of resistance determinants from commensal microorganism to a pathogen. In this model, we have also created an assessment of optimum observation frequency of infection spread among the population. Investigating model behavior, we show a number of non-linear dependencies, including the exponential nature of the dependence of the total number of those infected on the average resistance of a pathogen. As the model infection, we chose infection with Shigella spp., though it could be applied to a wide range of other pathogens. AVAILABILITY AND IMPLEMENTATION: Source code and binaries VERA and VERA.viewer are freely available for download at github.com/lpenguin/microbiota-resistome. The code is written in Java, JavaScript and R for Linux platform. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Subject(s)
Gastrointestinal Microbiome , Anti-Bacterial Agents , Drug Resistance, Microbial , Gene Transfer, Horizontal , Humans , Systems Analysis
9.
BioData Min ; 11: 25, 2018.
Article in English | MEDLINE | ID: mdl-30450127

ABSTRACT

BACKGROUND: Metagenomic surveys of human microbiota are becoming increasingly widespread in academic research as well as in food and pharmaceutical industries and clinical context. Intuitive tools for investigating experimental data are of high interest to researchers. RESULTS: Knomics-Biota is a web-based resource for exploratory analysis of human gut metagenomes. Users can generate and share analytical reports corresponding to common experimental schemes (like case-control study or paired comparison). Interactive visualizations and statistical analysis are provided in association with the external factors and in the context of thousands of publicly available datasets arranged into thematic collections. The web-service is available at https://biota.knomics.ru. CONCLUSIONS: Knomics-Biota web service is a comprehensive tool for interactive metagenomic data analysis.

10.
Microbiome ; 5(1): 141, 2017 10 17.
Article in English | MEDLINE | ID: mdl-29041989

ABSTRACT

BACKGROUND: Alcohol abuse has deleterious effects on human health by disrupting the functions of many organs and systems. Gut microbiota has been implicated in the pathogenesis of alcohol-related liver diseases, with its composition manifesting expressed dysbiosis in patients suffering from alcoholic dependence. Due to its inherent plasticity, gut microbiota is an important target for prevention and treatment of these diseases. Identification of the impact of alcohol abuse with associated psychiatric symptoms on the gut community structure is confounded by the liver dysfunction. In order to differentiate the effects of these two factors, we conducted a comparative "shotgun" metagenomic survey of 99 patients with the alcohol dependence syndrome represented by two cohorts-with and without liver cirrhosis. The taxonomic and functional composition of the gut microbiota was subjected to a multifactor analysis including comparison with the external control group. RESULTS: Alcoholic dependence and liver cirrhosis were associated with profound shifts in gut community structures and metabolic potential across the patients. The specific effects on species-level community composition were remarkably different between cohorts with and without liver cirrhosis. In both cases, the commensal microbiota was found to be depleted. Alcoholic dependence was inversely associated with the levels of butyrate-producing species from the Clostridiales order, while the cirrhosis-with multiple members of the Bacteroidales order. The opportunist pathogens linked to alcoholic dependence included pro-inflammatory Enterobacteriaceae, while the hallmarks of cirrhosis included an increase of oral microbes in the gut and more frequent occurrence of abnormal community structures. Interestingly, each of the two factors was associated with the expressed enrichment in many Bifidobacterium and Lactobacillus-but the exact set of the species was different between alcoholic dependence and liver cirrhosis. At the level of functional potential, the patients showed different patterns of increase in functions related to alcohol metabolism and virulence factors, as well as pathways related to inflammation. CONCLUSIONS: Multiple shifts in the community structure and metabolic potential suggest strong negative influence of alcohol dependence and associated liver dysfunction on gut microbiota. The identified differences in patterns of impact between these two factors are important for planning of personalized treatment and prevention of these pathologies via microbiota modulation. Particularly, the expansion of Bifidobacterium and Lactobacillus suggests that probiotic interventions for patients with alcohol-related disorders using representatives of the same taxa should be considered with caution. Taxonomic and functional analysis shows an increased propensity of the gut microbiota to synthesis of the toxic acetaldehyde, suggesting higher risk of colorectal cancer and other pathologies in alcoholics.


Subject(s)
Alcoholism/microbiology , Liver Cirrhosis/microbiology , Liver Diseases, Alcoholic/microbiology , Adult , Alcoholism/physiopathology , Bifidobacterium/isolation & purification , Bifidobacterium/pathogenicity , Bifidobacterium/physiology , Dysbiosis , Enterobacteriaceae/isolation & purification , Enterobacteriaceae/physiology , Ethanol/adverse effects , Ethanol/metabolism , Feces/microbiology , Female , Gastrointestinal Microbiome/genetics , Gastrointestinal Microbiome/physiology , Humans , Inflammation , Lactobacillus/isolation & purification , Lactobacillus/pathogenicity , Lactobacillus/physiology , Liver/physiopathology , Liver Cirrhosis/physiopathology , Liver Diseases, Alcoholic/physiopathology , Liver Diseases, Alcoholic/therapy , Male , Metagenomics/methods , Middle Aged , Probiotics/therapeutic use , Symbiosis , Virulence Factors , Young Adult
11.
Curr Issues Mol Biol ; 24: 17-36, 2017.
Article in English | MEDLINE | ID: mdl-28686566

ABSTRACT

Metagenomics, the application of high-throughput DNA sequencing for surveys of environmental samples, has revolutionized our view on the taxonomic and genetic composition of complex microbial communities. An enormous richness of microbiota keeps unfolding in the context of various fields ranging from biomedicine and food industry to geology. Primary analysis of metagenomic reads allows to infer semi-quantitative data describing the community structure. However, such compositional data possess statistical specific properties that are important to be considered during preprocessing, hypothesis testing and interpreting the results of statistical tests. Failure to account for these specifics may lead to essentially wrong conclusions as a result of the survey. Here we present a researcher introduced to the field of metagenomics with the basic properties of microbial compositional data including statistical power and proposed distribution models, perform a review of the publicly available software tools developed specifically for such data and outline the recommendations for the application of the methods.


Subject(s)
Computational Biology/methods , Guidelines as Topic , High-Throughput Nucleotide Sequencing/methods , Metagenomics/methods , Microbiota , Software , Algorithms , Data Interpretation, Statistical , Humans
12.
Data Brief ; 11: 98-102, 2017 Apr.
Article in English | MEDLINE | ID: mdl-28138508

ABSTRACT

Alcoholism is associated with significant changes in gut microbiota composition. Metagenomic sequencing allows to assess the altered abundance levels of bacterial taxa and genes in a culture-independent way. We collected 99 stool samples from the patients with alcoholic dependence syndrome (n=72) and alcoholic liver cirrhosis (n=27). Each of the samples was surveyed using "shotgun" (whole-genome) sequencing on SOLiD platform. The reads are deposited in the ENA (project ID: PRJEB18041).

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