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International Journal of Molecular... Oct 2023Non-alcoholic fatty liver disease (NAFLD) is considered the most common chronic liver disease worldwide, affecting nearly 25% of the global adult population. Increasing...
Non-alcoholic fatty liver disease (NAFLD) is considered the most common chronic liver disease worldwide, affecting nearly 25% of the global adult population. Increasing evidence suggests that functional and compositional changes in the gut microbiota may contribute to the development and promote the progression of NAFLD. 16S rRNA gene next-generation sequencing is widely used to determine specific features of the NAFLD microbiome, but a complex system such as the gut microbiota requires a comprehensive approach. We used three different approaches: MALDI-TOF-MS of bacterial cultures, qPCR, and 16S NGS sequencing, as well as a wide variety of statistical methods to assess the differences in gut microbiota composition between NAFLD patients without significant fibrosis and the control group. The listed methods showed enrichment in sp. and for the control samples and enrichment in (and in particular sp.) and in NAFLD. The families, , , and (particularly and ), were also found to be important taxa for NAFLD microbiome evaluation. Considering individual method observations, an increase in and a decrease in for NAFLD patients were detected using MALDI-TOF-MS. An increase in , , , , , and , and a decrease in in NAFLD were observed with 16S NGS, and enrichment in was shown using qPCR analysis. These findings confirm that NAFLD is associated with changes in gut microbiota composition. Further investigations are required to determine the cause-and-effect relationships and the impact of microbiota-derived compounds on the development and progression of NAFLD.
Topics: Adult; Humans; Non-alcoholic Fatty Liver Disease; Gastrointestinal Microbiome; RNA, Ribosomal, 16S; Fibrosis; Microbiota; Bacteroidetes; Liver
PubMed: 37894951
DOI: 10.3390/ijms242015272 -
Frontiers in Cellular and Infection... 2022This is the first study on gut microbiota (GM) in children affected by coronavirus disease 2019 (COVID-19). Stool samples from 88 patients with suspected severe acute...
This is the first study on gut microbiota (GM) in children affected by coronavirus disease 2019 (COVID-19). Stool samples from 88 patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and 95 healthy subjects were collected (admission: 3-7 days, discharge) to study GM profile by 16S rRNA gene sequencing and relationship to disease severity. The study group was divided in COVID-19 (68), Non-COVID-19 (16), and MIS-C (multisystem inflammatory syndrome in children) (4). Correlations among GM ecology, predicted functions, multiple machine learning (ML) models, and inflammatory response were provided for COVID-19 and Non-COVID-19 cohorts. The GM of COVID-19 cohort resulted as dysbiotic, with the lowest α-diversity compared with Non-COVID-19 and CTRLs and by a specific β-diversity. Its profile appeared enriched in , , and and reduced in , , , , , , and , compared with CTRLs ( 0.05). All GM paired-comparisons disclosed comparable results through all time points. The comparison between COVID-19 and Non-COVID-19 cohorts highlighted a reduction of in the COVID-19 cohort ( < 0.05). The GM of MIS-C cohort was characterized by an increase of , , , , and and a decrease of , , , and , compared with CTRLs. Stratifying for disease severity, the GM associated to "moderate" COVID-19 was characterized by lower α-diversity compared with "mild" and "asymptomatic" and by a GM profile deprived in , , , and and enriched in , , , , , , and The ML models identified , , , , , , , , , , , , , , , , and as microbial markers of COVID-19. The KEGG ortholog (KO)-based prediction of GM functional profile highlighted 28 and 39 KO-associated pathways to COVID-19 and CTRLs, respectively. Finally, and correlated with proinflammatory cytokines regardless disease severity. Unlike adult GM profiles, was a specific marker of pediatric COVID-19 GM. The durable modification of patients' GM profile suggested a prompt GM quenching response to SARS-CoV-2 infection since the first symptoms. and reduced fatty acid and amino acid degradation were proposed as specific COVID-19 disease traits, possibly associated to restrained severity of SARS-CoV-2-infected children. Altogether, this evidence provides a characterization of the pediatric COVID-19-related GM.
Topics: Adult; Bacteroides; Bifidobacterium; COVID-19; Child; Clostridium; Feces; Gastrointestinal Microbiome; Humans; RNA, Ribosomal, 16S; SARS-CoV-2; Systemic Inflammatory Response Syndrome
PubMed: 35873161
DOI: 10.3389/fcimb.2022.908492 -
International Journal of Molecular... Jul 2023Despite the recent breakthroughs in targeted and immunotherapy for melanoma, the overall survival rate remains low. In recent years, considerable attention has been paid...
Despite the recent breakthroughs in targeted and immunotherapy for melanoma, the overall survival rate remains low. In recent years, considerable attention has been paid to the gut microbiota and other modifiable patient factors (e.g., diet and body composition), though their role in influencing therapeutic responses has yet to be defined. Here, we characterized a cohort of 31 patients with unresectable IIIC-IV-stage cutaneous melanoma prior to initiation of targeted or first-line immunotherapy via the following methods: (i) fecal microbiome and metabolome via 16S rRNA amplicon sequencing and gas chromatography/mass spectrometry, respectively, and (ii) anthropometry, body composition, nutritional status, physical activity, biochemical parameters, and immunoprofiling. According to our data, patients subsequently classified as responders were obese (i.e., with high body mass index and high levels of total, visceral, subcutaneous, and intramuscular adipose tissue), non-sarcopenic, and enriched in certain fecal taxa (e.g., ) and metabolites (e.g., anethole), which were potentially endowed with immunostimulatory and oncoprotective activities. On the other hand, non-response was associated with increased proportions of , , , , , higher neutrophil levels (and a higher neutrophil-to-lymphocyte ratio), and higher fecal levels of butyric acid and its esters, which also correlated with decreased survival. This exploratory study provides an integrated list of potential early prognostic biomarkers that could improve the clinical management of patients with advanced melanoma, in particular by guiding the design of adjuvant therapeutic strategies to improve treatment response and support long-term health improvement.
Topics: Humans; Gastrointestinal Microbiome; Melanoma; RNA, Ribosomal, 16S; Skin Neoplasms; Metabolome; Feces; Body Composition
PubMed: 37511376
DOI: 10.3390/ijms241411611 -
Clinical Nutrition (Edinburgh, Scotland) Aug 2022The response to weight loss depends on the interindividual variability of determinants such as gut microbiota and genetics. The aim of this investigation was to develop... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND & AIMS
The response to weight loss depends on the interindividual variability of determinants such as gut microbiota and genetics. The aim of this investigation was to develop an integrative model using microbiota and genetic information to prescribe the most suitable diet for a successful weight loss in individuals with excess of body weight.
METHODS
A total of 190 Spanish overweight and obese participants were randomly assigned to two hypocaloric diets for 4 months: 61 women and 29 men followed a moderately high protein (MHP) diet, and 72 women and 28 men followed a low fat (LF) diet. Baseline fecal DNA was sequenced and used for the construction of four microbiota subscores associated with the percentage of BMI loss for each diet (MHP and LF) and for each sex. Bootstrapping techniques and multiple linear regression models were used for the selection of families, genera and species included in the subscores. Finally, two total microbiota scores were generated for each sex. Two genetic subscores previously reported to weight loss were used to generate a total genetic score. In an attempt to personalize the weight loss prescription, several linear mixed models that included interaction with diet between microbiota scores and genetic scores for both, men and women, were studied.
RESULTS
The microbiota subscore for the women who followed the MHP-diet included Coprococcus, Dorea, Flavonifractor, Ruminococcus albus and Clostridium bolteaea. For LF-diet women, Cytophagaceae, Catabacteriaceae, Flammeovirgaceae, Rhodobacteriaceae, Clostridium-x1vb, Bacteriodes nordiiay, Alistipes senegalensis, Blautia wexlerae and Psedoflavonifractor phocaeensis. For MHP-diet men, Cytophagaceae, Acidaminococcaceae, Marinilabiliaceae, Bacteroidaceae, Fusicatenibacter, Odoribacter and Ruminococcus faecis; and for LF-men, Porphyromanadaceae, Intestinimonas, Bacteroides finegoldii and Clostridium bartlettii. The mixed models with microbiota scores facilitated the selection of diet in 72% of women and in 84% of men. The model including genetic information allows to select the type of diet in 84% and 73%, respectively.
CONCLUSIONS
Decision algorithm models can help to select the most adequate type of weight loss diet according to microbiota and genetic information.
CLINICAL TRIAL REGISTRY NUMBER
This trial was registered at www.
CLINICALTRIALS
gov as NCT02737267 (https://clinicaltrials.gov/ct2/show/NCT02737267?term=NCT02737267&cond=obekit&draw=2&rank=1).
Topics: Diet, Reducing; Female; Gastrointestinal Microbiome; Humans; Male; Obesity; Overweight; Weight Loss
PubMed: 35777110
DOI: 10.1016/j.clnu.2022.06.008 -
Translational Psychiatry Jan 2024The causal effects of gut microbiome and the development of posttraumatic stress disorder (PTSD) are still unknown. This study aimed to clarify their potential causal...
BACKGROUND
The causal effects of gut microbiome and the development of posttraumatic stress disorder (PTSD) are still unknown. This study aimed to clarify their potential causal association using mendelian randomization (MR).
METHODS
The summary-level statistics for gut microbiome were retrieved from a genome-wide association study (GWAS) of the MiBioGen consortium. As to PTSD, the Freeze 2 datasets were originated from the Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group (PGC-PTSD), and the replicated datasets were obtained from FinnGen consortium. Single nucleotide polymorphisms meeting MR assumptions were selected as instrumental variables. The inverse variance weighting (IVW) method was employed as the main approach, supplemented by sensitivity analyses to evaluate potential pleiotropy and heterogeneity and ensure the robustness of the MR results. We also performed reverse MR analyses to explore PTSD's causal effects on the relative abundances of specific features of the gut microbiome.
RESULTS
In Freeze 2 datasets from PGC-PTSD, eight bacterial traits revealed a potential causal association between gut microbiome and PTSD (IVW, all P < 0.05). In addition, Genus.Dorea and genus.Sellimonas were replicated in FinnGen datasets, in which eight bacterial traits revealed a potential causal association between gut microbiome and the occurrence of PTSD. The heterogeneity and pleiotropy analyses further supported the robustness of the IVW findings, providing additional evidence for their reliability.
CONCLUSION
Our study provides the potential causal impact of gut microbiomes on the development of PTSD, shedding new light on the understanding of the dysfunctional gut-brain axis in this disorder. Our findings present novel evidence and call for investigations to confirm the association between their links, as well as to illuminate the underlying mechanisms.
Topics: Humans; Gastrointestinal Microbiome; Stress Disorders, Post-Traumatic; Genome-Wide Association Study; Reproducibility of Results; Dietary Supplements
PubMed: 38296956
DOI: 10.1038/s41398-024-02765-7 -
Gut Pathogens Dec 2022Emerging evidence suggests that gut microbiota plays a predominant role in Crohn's disease (CD). However, the microbiome alterations in the early stage of CD patients...
BACKGROUND
Emerging evidence suggests that gut microbiota plays a predominant role in Crohn's disease (CD). However, the microbiome alterations in the early stage of CD patients still remain unclear. The present study aimed to identify dysbacteriosis in patients with early CD and explore specific gut bacteria related to the progression of CD.
METHODS
This study was nested within a longitudinal prospective Chinese CD cohort, and it included 18 early CD patients, 22 advanced CD patients and 30 healthy controls. The microbiota communities were investigated using high-throughput Illumina HiSeq sequencing targeting the V3-V4 region of 16S ribosomal DNA (rDNA) gene. The relationship between the gut microbiota and clinical characteristics of CD was analyzed.
RESULTS
Differential microbiota compositions were observed in CD samples (including early and advanced CD samples) and healthy controls samples. Notably, Lachnospiracea_incertae_sedis and Parabacteroides were enriched in the early CD patients, Escherichia/Shigella, Enterococcus and Proteus were enriched in the advanced CD patients, and Roseburia, Gemmiger, Coprococcus, Ruminococcus 2, Butyricicoccus, Dorea, Fusicatenibacter, Anaerostipes, Clostridium IV were enriched in the healthy controls [LDA score (log10) > 2]. Furthermore, Kruskal-Wallis Rank sum test results showed that Blautia, Clostridium IV, Coprococcus, Dorea, Fusicatenibacter continued to significantly decrease in early and advanced CD patients, and Escherichia/Shigella and Proteus continued to significantly increase compared with healthy controls (P < 0.05). The PICRUSt analysis identified 16 remarkably different metabolic pathways [LDA score (log10) > 2]. Some genera were significantly correlated with various clinical parameters, such as fecal calprotectin, erythrocyte sedimentation rate, C-reactive protein, gland reduce, goblet cells decreased, clinical symptoms (P < 0.05).
CONCLUSIONS
Dysbacteriosis occurs in the early stage of CD and is associated with the progression of CD. This data provides a foundation that furthers the understanding of the role of gut microbiota in CD's pathogenesis.
PubMed: 36517872
DOI: 10.1186/s13099-022-00521-0 -
Journal of Mammary Gland Biology and... May 2023Many studies on bovine mammary glands focus on one stage of development. Often missing in those studies are repeated measures of development from the same animals. As...
Many studies on bovine mammary glands focus on one stage of development. Often missing in those studies are repeated measures of development from the same animals. As milk production is directly affected by amount of parenchymal tissue within the udder, understanding mammary gland growth along with visualization of its structures during development is essential. Therefore, analysis of ultrasound and histology data from the same animals would result in better understanding of mammary development over time. Thus, this research aimed to describe mammary gland development using non-invasive and invasive tools to delineate growth rate of glandular tissue responsible for potential future milk production. Mammary gland ultrasound images, biopsy samples, and blood samples were collected from 36 heifer dairy calves beginning at 10 weeks of age, and evaluated at 26, 39, and 52 weeks. Parenchyma was quantified at 10 weeks of age using ultrasound imaging and histological evaluation, and average echogenicity was utilized to quantify parenchyma at later stages of development. A significant negative correlation was detected between average echogenicity of parenchyma at 10 weeks and total adipose as a percent of histological whole tissue at 52 weeks. Additionally, a negative correlation between average daily gain at 10 and 26 weeks and maximum echogenicity at 52 weeks was present. These results suggest average daily gain and mammary gland development prior to 39 weeks of age is associated with development of the mammary gland after 39 weeks. These findings could be predictors of future milk production, however this must be further explored.
Topics: Cattle; Animals; Female; Diet; Obesity; Mammary Glands, Animal; Parenchymal Tissue; Milk
PubMed: 37249685
DOI: 10.1007/s10911-023-09534-0 -
EBioMedicine May 2021The relationship between tuberculosis (TB), one of the leading infectious causes of death worldwide, and the microbiome, which is critical for health, is poorly...
BACKGROUND
The relationship between tuberculosis (TB), one of the leading infectious causes of death worldwide, and the microbiome, which is critical for health, is poorly understood.
METHODS
To identify potential microbiome-host interactions, profiling of the oral, sputum and stool microbiota [n = 58 cases, n = 47 culture-negative symptomatic controls (SCs)] and whole blood transcriptome were done in pre-treatment presumptive pulmonary TB patients. This was a cross-sectional study. Microbiota were also characterised in close contacts of cases (CCCs, n = 73) and close contacts of SCs (CCSCs, n = 82) without active TB.
FINDINGS
Cases and SCs each had similar α- and β-diversities in oral washes and sputum, however, β-diversity differed in stool (PERMANOVA p = 0•035). Cases were enriched with anaerobes in oral washes, sputum (Paludibacter, Lautropia in both) and stool (Erysipelotrichaceae, Blautia, Anaerostipes) and their stools enriched in microbial genes annotated as amino acid and carbohydrate metabolic pathways. In pairwise comparisons with their CCCs, cases had Megasphaera-enriched oral and sputum microbiota and Bifidobacterium-, Roseburia-, and Dorea-depleted stools. Compared to their CCSCs, SCs had reduced α-diversities and many differential taxa per specimen type. Cases differed transcriptionally from SCs in peripheral blood (PERMANOVA p = 0•001). A co-occurrence network analysis showed stool taxa, Erysipelotrichaceae and Blautia, to negatively co-correlate with enriched "death receptor" and "EIF2 signalling" pathways whereas Anaerostipes positively correlated with enriched "interferon signalling", "Nur77 signalling" and "inflammasome" pathways; all of which are host pathways associated with disease severity. In contrast, none of the taxa enriched in SCs correlated with host pathways.
INTERPRETATION
TB-specific microbial relationships were identified in oral washes, induced sputum, and stool from cases before the confounding effects of antibiotics. Specific anaerobes in cases' stool predict upregulation of pro-inflammatory immunological pathways, supporting the gut microbiota's role in TB.
FUNDING
European & Developing Countries Clinical Trials Partnership, South African-Medical Research Council, National Institute of Allergy and Infectious Diseases.
Topics: Adult; Bacteria, Anaerobic; Female; Gastrointestinal Microbiome; Humans; Inflammasomes; Interferons; Male; Signal Transduction; Transcriptome; Tuberculosis, Pulmonary; Up-Regulation
PubMed: 33975252
DOI: 10.1016/j.ebiom.2021.103374 -
Frontiers in Veterinary Science 2020Computer Vision, Digital Image Processing, and Digital Image Analysis can be viewed as an amalgam of terms that very often are used to describe similar processes. Most... (Review)
Review
Computer Vision, Digital Image Processing, and Digital Image Analysis can be viewed as an amalgam of terms that very often are used to describe similar processes. Most of this confusion arises because these are interconnected fields that emerged with the development of digital image acquisition. Thus, there is a need to understand the connection between these fields, how a digital image is formed, and the differences regarding the many sensors available, each best suited for different applications. From the advent of the charge-coupled devices demarking the birth of digital imaging, the field has advanced quite fast. Sensors have evolved from grayscale to color with increasingly higher resolution and better performance. Also, many other sensors have appeared, such as infrared cameras, stereo imaging, time of flight sensors, satellite, and hyperspectral imaging. There are also images generated by other signals, such as sound (ultrasound scanners and sonars) and radiation (standard x-ray and computed tomography), which are widely used to produce medical images. In animal and veterinary sciences, these sensors have been used in many applications, mostly under experimental conditions and with just some applications yet developed on commercial farms. Such applications can range from the assessment of beef cuts composition to live animal identification, tracking, behavior monitoring, and measurement of phenotypes of interest, such as body weight, condition score, and gait. Computer vision systems (CVS) have the potential to be used in precision livestock farming and high-throughput phenotyping applications. We believe that the constant measurement of traits through CVS can reduce management costs and optimize decision-making in livestock operations, in addition to opening new possibilities in selective breeding. Applications of CSV are currently a growing research area and there are already commercial products available. However, there are still challenges that demand research for the successful development of autonomous solutions capable of delivering critical information. This review intends to present significant developments that have been made in CVS applications in animal and veterinary sciences and to highlight areas in which further research is still needed before full deployment of CVS in breeding programs and commercial farms.
PubMed: 33195522
DOI: 10.3389/fvets.2020.551269 -
Microorganisms Sep 2023Depression is a leading cause of disease worldwide. The association between gut microbiota and depression has barely been investigated in the Japanese population. We...
Depression is a leading cause of disease worldwide. The association between gut microbiota and depression has barely been investigated in the Japanese population. We analyzed Iwaki health check-up data collected from 2017 to 2019 and constructed generalized linear mixed models. The independent variable was the relative abundance of each of the 37 gut microbiota genera that were reported to be associated with depression. The dependent variable was the presence of depression assessed by the Center for Epidemiologic Studies Depression Scale. Potential confounders, including grip strength, gender, height, weight, smoking, and drinking habits, were adjusted in the regression models. Nine genera's regression coefficients (, , , , , , , , and ) showed statistical significance after multiple comparisons adjustment. Among these nine gut bacteria genera, , , , , , and were reported to be associated with butyrate production in the intestine. Our results indicate that gut microbiotas may influence the depression condition of the host via the butyrate-producing process.
PubMed: 37764129
DOI: 10.3390/microorganisms11092286