Blue poo: impact of gut transit time on the gut microbiome using a novel marker

Background and aimsGut transit time is a key modulator of host–microbiome interactions, yet this is often overlooked, partly because reliable methods are typically expensive or burdensome. The aim of this single-arm, single-blinded intervention study is to assess (1) the relationship between gut transit time and the human gut microbiome, and (2) the utility of the ‘blue dye’ method as an inexpensive and scalable technique to measure transit time.MethodsWe assessed interactions between the taxonomic and functional potential profiles of the gut microbiome (profiled via shotgun metagenomic sequencing), gut transit time (measured via the blue dye method), cardiometabolic health and diet in 863 healthy individuals from the PREDICT 1 study.ResultsWe found that gut microbiome taxonomic composition can accurately discriminate between gut transit time classes (0.82 area under the receiver operating characteristic curve) and longer gut transit time is linked with specific microbial species such as Akkermansia muciniphila, Bacteroides spp and Alistipes spp (false discovery rate-adjusted p values <0.01). The blue dye measure of gut transit time had the strongest association with the gut microbiome over typical transit time proxies such as stool consistency and frequency.ConclusionsGut transit time, measured via the blue dye method, is a more informative marker of gut microbiome function than traditional measures of stool consistency and frequency. The blue dye method can be applied in large-scale epidemiological studies to advance diet-microbiome-health research. Clinical trial registry website https://clinicaltrials.gov/ct2/show/NCT03479866 and trial number NCT03479866.

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Cross-Sectional Study on the Gut Microbiome of Parkinson’s Disease Patients in Central China

Frontiers in Microbiology ◽

10.3389/fmicb.2021.728479 ◽

2021 ◽

Vol 12 ◽

Author(s):

Liangwei Mao ◽

Yu Zhang ◽

Jing Tian ◽

Ming Sang ◽

Guimin Zhang ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Gut Microbiome ◽

Clinical Symptoms ◽

Characteristic Curve ◽

Central China ◽

Metagenomic Sequencing ◽

Microbial Composition ◽

Protein Database ◽

Shotgun Metagenomics

Gastrointestinal dysfunction plays an important role in the occurrence and development of Parkinson’s disease (PD). This study investigates the composition of the gut microbiome using shotgun metagenomic sequencing in PD patients in central China. Fecal samples from 39 PD patients (PD group) and the corresponding 39 healthy spouses of the patients (SP) were collected for shotgun metagenomics sequencing. Results showed a significantly altered microbial composition in the PD patients. Bilophila wadsworthia enrichment was found in the gut microbiome of PD patients, which has not been reported in previous studies. The random forest (RF) model, which identifies differences in microbiomes, reliably discriminated patients with PD from controls; the area under the receiver operating characteristic curve was 0.803. Further analysis of the microbiome and clinical symptoms showed that Klebsiella and Parasutterella were positively correlated with the duration and severity of PD, whereas hydrogen-generating Prevotella was negatively correlated with disease severity. The Cluster of Orthologous Groups of protein database, the KEGG Orthology database, and the carbohydrate-active enzymes of gene-category analysis showed that branched-chain amino acid–related proteins were significantly increased, and GH43 was significantly reduced in the PD group. Functional analysis of the metagenome confirmed differences in microbiome metabolism in the PD group related to short-chain fatty acid precursor metabolism.

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Large-scale quality assessment of prokaryotic genomes with metashot/prok-quality

F1000Research ◽

10.12688/f1000research.54418.1 ◽

2021 ◽

Vol 10 ◽

pp. 822

Author(s):

Davide Albanese ◽

Claudio Donati

Keyword(s):

Quality Assessment ◽

Large Scale ◽

Metagenomic Sequencing ◽

Link Type ◽

Archaeal Species ◽

Prokaryotic Genomes ◽

Genomic Characterization ◽

Computational Workflow ◽

Quality Tool

Metagenomic sequencing allows large-scale identification and genomic characterization. Binning is the process of recovering genomes from complex mixtures of sequence fragments (metagenome contigs) of unknown bacteria and archaeal species. Assessing the quality of genomes recovered from metagenomes requires the use of complex pipelines involving many independent steps, often difficult to reproduce and maintain. A comprehensive, automated and easy-to-use computational workflow for the quality assessment of draft prokaryotic genomes, based on container technology, would greatly improve reproducibility and reusability of published results. We present metashot/prok-quality, a container-enabled Nextflow pipeline for quality assessment and genome dereplication. The metashot/prok-quality tool produces genome quality reports that are compliant with the Minimum Information about a Metagenome-Assembled Genome (MIMAG) standard, and can run out-of-the-box on any platform that supports Nextflow, Docker or Singularity, including computing clusters or batch infrastructures in the cloud. metashot/prok-quality is part of the metashot collection of analysis pipelines. Workflow and documentation are available under GPL3 licence on GitHub.

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Association between metabolic status and gut microbiome in obese populations

Microbial Genomics ◽

10.1099/mgen.0.000639 ◽

2021 ◽

Vol 7 (8) ◽

Author(s):

Qiang Zeng ◽

Zhenyu Yang ◽

Fei Wang ◽

Dongfang Li ◽

Yanhong Liu ◽

...

Keyword(s):

Gut Microbiome ◽

Operating Characteristic ◽

Metabolic Diseases ◽

Characteristic Curve ◽

Significant Proportion ◽

Gene Markers ◽

Content Type ◽

Link Type ◽

Metabolically Healthy ◽

Operating Characteristic Curve

Despite that obesity is associated with many metabolic diseases, a significant proportion (10–30 %) of obese individuals is recognized as ‘metabolically healthy obeses’ (MHOs). The aim of the current study is to characterize the gut microbiome for MHOs as compared to ‘metabolically unhealthy obeses’ (MUOs). We compared the gut microbiome of 172 MHO and 138 MUO individuals from Chongqing (China) (inclined to eat red meat and food with a spicy taste), and performed validation with selected biomarkers in 40 MHOs and 33 MUOs from Quanzhou (China) (inclined to eat seafood and food with a light/bland taste). The genera Alistipes , Faecalibacterium and Odoribacter had increased abundance in both Chongqing and Quanzhou MHOs. We also observed different microbial functions in MUOs compared to MHOs, including an increased abundance of genes associated with glycan biosynthesis and metabolism. In addition, the microbial gene markers identified from the Chongqing cohort bear a moderate accuracy [AUC (area under the operating characteristic curve)=0.69] for classifying MHOs distinct from MUOs in the Quanzhou cohort. These findings indicate that gut microbiome is significantly distinct between MHOs and MUOs, implicating the potential of the gut microbiome in stratification and refined management of obesity.

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Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds

Scientific Data ◽

10.1038/s41597-021-01008-4 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Deborah O. Dele-Oni ◽

Karen E. Christianson ◽

Shawn B. Egri ◽

Alvaro Sebastian Vaca Jacome ◽

Katherine C. DeRuff ◽

...

Keyword(s):

Large Scale ◽

Cell Model ◽

Cellular Responses ◽

Proteomic Profiling ◽

Reduced Representation ◽

Link Type ◽

Original Dataset ◽

Quality Control Metrics ◽

Biological Insight ◽

Chromatin Profiling

AbstractWhile gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of “connectivity” to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https://clue.io/proteomics.

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A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning

Cancers ◽

10.3390/cancers13092111 ◽

2021 ◽

Vol 13 (9) ◽

pp. 2111

Author(s):

Bo-Wei Zhao ◽

Zhu-Hong You ◽

Lun Hu ◽

Zhen-Hao Guo ◽

Lei Wang ◽

...

Keyword(s):

Drug Target ◽

Large Scale ◽

Computational Models ◽

Structural Information ◽

Characteristic Curve ◽

Representation Learning ◽

Graph Representation ◽

Convolutional Network ◽

Novel Method

Identification of drug-target interactions (DTIs) is a significant step in the drug discovery or repositioning process. Compared with the time-consuming and labor-intensive in vivo experimental methods, the computational models can provide high-quality DTI candidates in an instant. In this study, we propose a novel method called LGDTI to predict DTIs based on large-scale graph representation learning. LGDTI can capture the local and global structural information of the graph. Specifically, the first-order neighbor information of nodes can be aggregated by the graph convolutional network (GCN); on the other hand, the high-order neighbor information of nodes can be learned by the graph embedding method called DeepWalk. Finally, the two kinds of feature are fed into the random forest classifier to train and predict potential DTIs. The results show that our method obtained area under the receiver operating characteristic curve (AUROC) of 0.9455 and area under the precision-recall curve (AUPR) of 0.9491 under 5-fold cross-validation. Moreover, we compare the presented method with some existing state-of-the-art methods. These results imply that LGDTI can efficiently and robustly capture undiscovered DTIs. Moreover, the proposed model is expected to bring new inspiration and provide novel perspectives to relevant researchers.

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Flavonoid-Modifying Capabilities of the Human Gut Microbiome—An In Silico Study

Nutrients ◽

10.3390/nu13082688 ◽

2021 ◽

Vol 13 (8) ◽

pp. 2688

Author(s):

Tobias Goris ◽

Rafael R. C. Cuadrat ◽

Annett Braune

Keyword(s):

Gut Microbiome ◽

Large Scale ◽

Health Impact ◽

Gut Bacteria ◽

Human Gut ◽

Positive Health ◽

Human Gut Microbiome ◽

Nutritional Recommendations ◽

Genes Encoding ◽

A Minor

Flavonoids are a major group of dietary plant polyphenols and have a positive health impact, but their modification and degradation in the human gut is still widely unknown. Due to the rise of metagenome data of the human gut microbiome and the assembly of hundreds of thousands of bacterial metagenome-assembled genomes (MAGs), large-scale screening for potential flavonoid-modifying enzymes of human gut bacteria is now feasible. With sequences of characterized flavonoid-transforming enzymes as queries, the Unified Human Gastrointestinal Protein catalog was analyzed and genes encoding putative flavonoid-modifying enzymes were quantified. The results revealed that flavonoid-modifying enzymes are often encoded in gut bacteria hitherto not considered to modify flavonoids. The enzymes for the physiologically important daidzein-to-equol conversion, well studied in Slackiaisoflavoniconvertens, were encoded only to a minor extent in Slackia MAGs, but were more abundant in Adlercreutzia equolifaciens and an uncharacterized Eggerthellaceae species. In addition, enzymes with a sequence identity of about 35% were encoded in highly abundant MAGs of uncultivated Collinsella species, which suggests a hitherto uncharacterized daidzein-to-equol potential in these bacteria. Of all potential flavonoid modification steps, O-deglycosylation (including derhamnosylation) was by far the most abundant in this analysis. In contrast, enzymes putatively involved in C-deglycosylation were detected less often in human gut bacteria and mainly found in Agathobacter faecis (formerly Roseburia faecis). Homologs to phloretin hydrolase, flavanonol/flavanone-cleaving reductase and flavone reductase were of intermediate abundance (several hundred MAGs) and mainly prevalent in Flavonifractor plautii. This first comprehensive insight into the black box of flavonoid modification in the human gut highlights many hitherto overlooked and uncultured bacterial genera and species as potential key organisms in flavonoid modification. This could lead to a significant contribution to future biochemical-microbiological investigations on gut bacterial flavonoid transformation. In addition, our results are important for individual nutritional recommendations and for biotechnological applications that rely on novel enzymes catalyzing potentially useful flavonoid modification reactions.

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673 Precision microbiome mapping identifies a microbiome signature predictive of Immune checkpoint inhibitor response across multiple research study cohorts

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0673 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A711-A711

Author(s):

Matthew Robinson ◽

Kevin Vervier ◽

Simon Harris ◽

David Adams ◽

Doreen Milne ◽

...

Keyword(s):

Gut Microbiome ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitor ◽

Checkpoint Inhibitor ◽

Advanced Melanoma ◽

List Type ◽

Metagenomic Sequencing ◽

Genome Database ◽

Sequencing Platform ◽

Melanoma Patients

BackgroundThe gut microbiome of cancer patients appears to be associated with response to Immune Checkpoint Inhibitor (ICIs) treatment.1–4 However, the bacteria linked to response differ between published studies.MethodsLongitudinal stool samples were collected from 69 patients with advanced melanoma receiving approved ICIs in the Cambridge (UK) MELRESIST study. Pretreatment samples were analysed by Microbiotica, using shotgun metagenomic sequencing. Microbiotica’s sequencing platform comprises the world’s leading Reference Genome Database and advanced Microbiome Bioinformatics to give the most comprehensive and precise mapping of the gut microbiome. This has enabled us to identify gut bacteria associated with ICI response missed using public reference genomes. Published microbiome studies in advanced melanoma,1–3renal cell carcinoma (RCC) and non-small cell lung cancer (NSCLC)4 were reanalysed with the same platform.ResultsAnalysis of the MELRESIST samples showed an overall change in the microbiome composition between advanced melanoma patients and a panel of healthy donor samples, but not between patients who subsequently responded or did not respond to ICIs. However, we did identify a discrete microbiome signature which correlated with response. This signature predicted response with an accuracy of 93% in the MELRESIST cohort, but was less predictive in the published melanoma cohorts.1–3 Therefore, we developed a bioinformatic analytical model, incorporating an interactive random forest model and the MELRESIST dataset, to identify a microbiome signature which was consistent across all published melanoma studies. This model was validated three times by accurately predicting the outcome of an independent cohort. A final microbiome signature was defined using the validated model on MELRESIST and the three published melanoma cohorts. This was very accurate at predicting response in all four studies combined (91%), or individually (82–100%). This signature was also predictive of response in a NSCLC study and to a lesser extent in RCC. The core of this signature is nine bacteria significantly increased in abundance in responders.ConclusionsAnalysis of the MELRESIST study samples, precision microbiome profiling by the Microbiotica Platform and a validated bioinformatic analysis, have enabled us to identify a unique microbiome signature predictive of response to ICI therapy in four independent melanoma studies. This removes the challenge to the field of different bacteria apparently being associated with response in different studies, and could represent a new microbiome biomarker with clinical application. Nine core bacteria may be driving response and hold potential for co-therapy with ICIs.Ethics ApprovalThe study was approved by Newcastle & North Tyneside 2 Research Ethics Committee, approval number 11/NE/0312.ReferencesMatson V, Fessler J, Bao R, et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 2018;359(6371):104–108.Gopalakrishnan V, Spencer CN, Nezi L, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 2018;359(6371):97–103.Frankel AE, Coughlin LA, Kim J, et al. Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients. Neoplasia 2017;19(10):848–855.Routy B, Le Chatelier E, Derosa L, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018;359(6371):91–97.

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Efficacy of acupuncture for sciatica: study protocol for a randomized controlled pilot trial

Trials ◽

10.1186/s13063-020-04961-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Fang-Ting Yu ◽

Guang-Xia Ni ◽

Guo-Wei Cai ◽

Wen-Jun Wan ◽

Xiao-Qing Zhou ◽

...

Keyword(s):

Pain Intensity ◽

Lumbar Disc ◽

Pilot Trial ◽

Sham Acupuncture ◽

Leg Pain ◽

Power Calculation ◽

Clinical Trial Registry ◽

Randomized Controlled ◽

Link Type

Abstract Background Acupuncture is widely used for pain diseases while evidence of its efficacy for sciatica is insufficient. We aim to explore the feasibility and efficacy of acupuncture with different acupoint selecting strategies for sciatica induced by lumbar disc herniation. Methods This is a multicenter, three-arm, patient-assessor-blinded randomized controlled pilot trial. Ninety patients will be assigned randomly into 3 groups including disease-affected meridians (DAM) group, non-affected meridians (NAM) group, and sham acupuncture (SA) group in a 1:1:1 ratio. The trial involves a 4-week treatment along with follow-up for 22 weeks. The primary outcome is the change of leg pain intensity measured by the visual analogue scale (VAS) from baseline to week 4 after randomization. Secondary outcomes include functional status, back pain intensity, and quality of life. Adverse events will also be recorded. Discussion The results will inspire the optimal acupuncture strategy for sciatica and help establish a better design as well as power calculation for a full-scale study. Trial registration ChiCTR2000030680 (Chinese Clinical Trial Registry, http://www.chictr.org.cn, registered on 9 March 2020).

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A Positive Association of Overactivated Immunity with Metabolic Syndrome Risk and Mitigation of Its Association by a Plant-Based Diet and Physical Activity in a Large Cohort Study

Nutrients ◽

10.3390/nu13072308 ◽

2021 ◽

Vol 13 (7) ◽

pp. 2308

Author(s):

Sunmin Park ◽

Ting Zhang

Keyword(s):

Physical Activity ◽

Metabolic Syndrome ◽

Cohort Study ◽

Large Scale ◽

Smoking Status ◽

Characteristic Curve ◽

Daily Intake ◽

Positive Association ◽

Cell Counts ◽

High Hba1c

The association between immunity and metabolic syndrome (MetS) has been studied, but its interaction with lifestyles remains unclear. We studied their association and interactions with lifestyles in 40,768 adults aged over 40 years from a large-scale, hospital-based cohort study collected during 2010–2013. White blood cell counts (WBC) and serum C-reactive protein concentrations (CRP) were used as indexes of immune status. The participants were categorized into four groups by the cutoff points of 6.2 × 109/L WBC(L-WBC) and <0.5 mg/dL CRP(L-CRP): L-WBC+L-CRP(n = 25,604), H-WBC+L-CRP(n = 13,880), L-WBC+H-CRP(n = 464), and H-WBC+H-CRP(n = 820). The participants in the H-WBC+L-CRP were younger and had higher numbers of males than the L-WBC+L-CRP. MetS risk was higher by 1.75- and 1.86-fold in the H-WBC+L-CRP and H-WBC+H-CRP, respectively, than the L-WBC+L-CRP. MetS components, including plasma glucose and triglyceride concentrations, and SBP were elevated in H-WBC+L-CRP and H-WBC+H-CRP compared with L-WBC+L-CR+P. The risk of hyperglycemia and high HbA1c was the highest in the H-WBC+H-CRP among all groups. Areas of WBC counts and serum CRP concentrations were 0.637 and 0.672, respectively, in the receiver operating characteristic curve. Daily intake of energy, carbohydrate, protein, and fat was not significantly different in the groups based on WBC counts and CRP. However, a plant-based diet (PBD), physical activity, and non-smoking were related to lowering WBC counts and CRP, but a Western-style diet was linked to elevating CRP. A high PBD intake and smoking status interacted with immunity to influence MetS risk: a low PBD and current smoking were associated with a higher MetS risk in the H-WBC+H-CRP. In conclusion, overactivated immunity determined by CRP and WBC was associated with MetS risk. Behavior modification with PBD and physical activity might be related to immunity regulation.

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Pilot Clinical Trial of Time-Restricted Eating in Patients with Metabolic Syndrome

Nutrients ◽

10.3390/nu13020346 ◽

2021 ◽

Vol 13 (2) ◽

pp. 346

Author(s):

Iwona Świątkiewicz ◽

Celestyna Mila-Kierzenkowska ◽

Alina Woźniak ◽

Karolina Szewczyk-Golec ◽

Jarosław Nuszkiewicz ◽

...

Keyword(s):

Oxidative Stress ◽

Metabolic Syndrome ◽

Clinical Trial ◽

Dietary Intake ◽

Large Scale ◽

Controlled Trial ◽

European Population ◽

Cardiac Biomarkers ◽

Cardiometabolic Health ◽

And Behavior

Metabolic syndrome (MetS) and erratic eating patterns are associated with circadian rhythm disruption which contributes to an increased cardiometabolic risks. Restricting eating period (time-restricted eating, TRE) can restore robust circadian rhythms and improve cardiometabolic health. We describe a protocol of the Time-Restricted Eating on Metabolic and Neuroendocrine homeostasis, Inflammation, and Oxidative Stress (TREMNIOS) pilot clinical trial in Polish adult patients with MetS and eating period of ≥14 h/day. The study aims to test the feasibility of TRE intervention and methodology for evaluating its efficacy for improving metabolic, neuroendocrine, inflammatory, oxidative stress and cardiac biomarkers, and daily rhythms of behavior for such population. Participants will apply 10-h TRE over a 12-week monitored intervention followed by a 12-week self-directed intervention. Changes in eating window, body weight and composition, biomarkers, and rhythms of behavior will be evaluated. Dietary intake, sleep, activity and wellbeing will be monitored with the myCircadianClock application and questionnaires. Adherence to TRE defined as the proportion of days recorded with app during the monitored intervention in which participants satisfied 10-h TRE is the primary outcome. TREMNIOS will also provide an exploratory framework to depict post-TRE changes in cardiometabolic outcomes and behavior rhythms. This protocol extends previous TRE-related protocols by targeting European population with diagnosed MetS and including long-term intervention, validated tools for monitoring dietary intake and adherence, and comprehensive range of biomarkers. TREMNIOS trial will lay the groundwork for a large-scale randomized controlled trial to determine TRE efficacy for improving cardiometabolic health in MetS population.

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