Comprehensive function annotation of metagenomes and microbial genomes using a deep learning-based method
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Novel species identification and deep functional annotation of electrogenic biofilms , selectively enriched in a microbial fuel cell array
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Frontiers in Microbiology
Treatment With Multi-Species Probiotics Changes the Functions, Not the Composition of Gut Microbiota in Postmenopausal Women With Obesity: A Randomized, Double-Blind, Placebo-Controlled Study
Probiotics are known to regulate host metabolism. In randomized controlled trial we aimed to assess whether interventions with probiotic containing following strains: Bifidobacterium bifidum W23, Bifidobacterium lactis W51, Bifidobacterium lactis W52, Lactobacillus acidophilus W37, Levilactobacillus brevis W63, Lacticaseibacillus casei W56, Ligilactobacillus salivarius W24, Lactococcus lactis W19, and Lactococcus lactis W58 affect gut microbiota to promote metabolic effects. By 16S rRNA sequencing we analysed the faecal microbiota of 56 obese, postmenopausal women randomised into three groups: (1) probiotic dose 2...
Frontiers in cellular and infection microbiology
Sequence-structure-function relationships in the microbial protein universe
For the past half-century, structural biologists relied on the notion that similar protein sequences give rise to similar structures and functions. While this assumption has driven research to explore certain parts of the protein universe, it disregards spaces that don't rely on this assumption. Here we explore areas of the protein universe where similar protein functions can be achieved by different sequences and different structures...
Gut microbiome in serious mental illnesses: A systematic review and critical evaluation
Schizophrenia and bipolar disorder (BD) are associated with debilitating psychiatric and cognitive dysfunction, worse health outcomes, and shorter life expectancies. The pathophysiological understanding of and therapeutic resources for these neuropsychiatric disorders are still limited. Humans harbor over 1000 unique bacterial species in our gut, which have been linked to both physical and mental/cognitive health...
Structure-based protein function prediction using graph convolutional networks
The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, we introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures. It outperforms current leading methods and sequence-based Convolutional Neural Networks and scales to the size of current sequence repositories...
A semiparametric model for between‐subject attributes: Applications to beta‐diversity of microbiome data
The human microbiome plays an important role in our health and identifying factors associated with microbiome composition provides insights into inherent disease mechanisms. By amplifying and sequencing the marker genes in high‐throughput sequencing, with highly similar sequences binned together, we obtain operational taxonomic units (OTUs) profiles for each subject. Due to the high‐dimensionality and nonnormality features of the OTUs, the measure of diversity is introduced as a summarization at the microbial community level, including the distance‐based beta‐diversity between individuals...
Deep embeddings to comprehend and visualize microbiome protein space
Understanding the function of microbial proteins is essential to reveal the clinical potential of the microbiome. The application of high-throughput sequencing technologies allows for fast and increasingly cheaper acquisition of data from microbial communities. However, many of the inferred protein sequences are novel and not catalogued, hence the possibility of predicting their function through conventional homology-based approaches is limited...
Individuals with substance use disorders have a distinct oral microbiome pattern
Substance use disorder emerges from a complex interaction between genetic predisposition, life experiences, exposure, and subsequent adaptation of biological systems to the repeated use of drugs. Recently, investigators have proposed that the human microbiota may play a role in brain health and disease. In particular, the human oral microbiome is a distinct and diverse ecological niche with its composition influenced by external factors such as lifestyle, diet, and oral hygiene...
Brain, behavior, & immunity-health
Gut microbiome in Schizophrenia: Altered functional pathways related to immune modulation and atherosclerotic risk
Emerging evidence has linked the gut microbiome changes to schizophrenia. However, there has been limited research into the functional pathways by which the gut microbiota contributes to the phenotype of persons with chronic schizophrenia. We characterized the composition and functional potential of the gut microbiota in 48 individuals with chronic schizophrenia and 48 matched (sequencing plate, age, sex, BMI, and antibiotic use) non-psychiatric comparison subjects (NCs) using 16S rRNA sequencing...
Brain, behavior, and immunity
Differing salivary microbiome diversity, community and diurnal rhythmicity in association with affective state and peripheral inflammation in adults
Interactions between gut microbiota and the host play an important role in central nervous system function and behavior, primarily mediated through immune and neuroendocrine pathways (ie, the gut-brain axis)(Cryan and Dinan, 2012, Liang et al., 2018). Over the past decade, clinical studies and animal models have suggested that chronic distress-related conditions, such as depression and anxiety disorders, are associated with altered gut microbiome composition...
Brain, Behavior, and Immunity
Microbiome analyses of blood and tissues suggest cancer diagnostic approach
Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas 11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia–IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent …...
IL-4Rα blockade by dupilumab decreases Staphylococcus aureus colonization and increases microbial diversity in atopic dermatitis
Dupilumab is a fully human antibody to interleukin-4 receptor α that improves the signs and symptoms of moderate to severe atopic dermatitis (AD). To determine the effects of dupilumab on Staphylococcus aureus colonization and microbial diversity on the skin, bacterial DNA was analyzed from swabs collected from lesional and nonlesional skin in a double-blind, placebo-controlled study of 54 patients with moderate to severe AD randomized (1:1) and treated with either dupilumab (200 mg weekly) or placebo for 16 weeks. Microbial diversity and relative abundance of Staphylococcus were assessed by DNA sequencing of 16S ribosomal RNA, and absolute S...
Journal of Investigative Dermatology
QIIME 2 enables comprehensive end‐to‐end analysis of diverse microbiome data and comparative studies with publicly available data
QIIME 2 is a completely re‐engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open‐source web‐based platform, to re‐use available data for meta‐analysis...
Current protocols in bioinformatics
The microbiome and its potential for pharmacology
The human microbiota (the microscopic organisms that inhabit us) and microbiome (their genes) hold considerable potential for improving pharmacological practice. Recent advances in multi-“omics” techniques have dramatically improved our understanding of the constituents of the microbiome and their functions. The implications of this research for human health, including microbiome links to obesity, drug metabolism, neurological diseases, cancer, and many other health conditions, have sparked considerable interest in exploiting the microbiome for targeted therapeutics...
Concepts and Principles of Pharmacology
The impact of skin care products on skin chemistry and microbiome dynamics
Use of skin personal care products on a regular basis is nearly ubiquitous, but their effects on molecular and microbial diversity of the skin are unknown. We evaluated the impact of four beauty products (a facial lotion, a moisturizer, a foot powder, and a deodorant) on 11 volunteers over 9 weeks. Mass spectrometry and 16S rRNA inventories of the skin revealed decreases in chemical as well as in bacterial and archaeal diversity on halting deodorant use...
Differences in gut microbiome composition between persons with chronic schizophrenia and healthy comparison subjects
Intestinal microbiome and gut-brain axis have been receiving increasing attention for their role in the regulation of brain/behavior and possible biological basis of psychiatric disorders. Several recent clinical studies have linked the microbiome with neuropsychiatric conditions, although the literature on schizophrenia is quite limited. This study investigated gut microbiome composition in 50 individuals, including 25 persons with chronic schizophrenia and 25 demographically-matched non-psychiatric comparison subjects (NCs)...
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
To the Editor—Rapid advances in DNA-sequencing and bioinformatics technologies in the past two decades have substantially improved understanding of the microbial world. This growing understanding relates to the vast diversity of microorganisms; how microbiota and microbiomes affect disease 1 and medical treatment 2; how microorganisms affect the health of the planet 3; and the nascent exploration of the medical 4, forensic 5, environmental 6 and agricultural 7 applications of microbiome biotechnology. Much of this work has been driven by marker-gene surveys (for example, bacterial/archaeal 16S rRNA genes, fungal internal-transcribed-spacer regions and eukaryotic 18S rRNA genes), which profile microbiota with varying degrees of taxonomic specificity and phylogenetic information...
Phylogenomics of 10,575 genomes reveals evolutionary proximity between domains Bacteria and Archaea
Rapid growth of genome data provides opportunities for updating microbial evolutionary relationships, but this is challenged by the discordant evolution of individual genes. Here we build a reference phylogeny of 10,575 evenly-sampled bacterial and archaeal genomes, based on a comprehensive set of 381 markers, using multiple strategies. Our trees indicate remarkably closer evolutionary proximity between Archaea and Bacteria than previous estimates that were limited to fewer “core” genes, such as the ribosomal proteins...
Best practices for analysing microbiomes
Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets...
Nature Reviews Microbiology
Overview and systematic review of studies of microbiome in schizophrenia and bipolar disorder
Schizophrenia and bipolar disorder are among the leading causes of disability, morbidity, and mortality worldwide. In addition to being serious mental illnesses, these disorders are associated with considerable systemic physiological dysfunction, including chronic inflammation and elevated oxidative stress. The advent of sophisticated sequencing techniques has led to a growing interest in the potential role of gut microbiota in human health and disease...
Journal of spsychiatric research
American gut: an open platform for citizen science microbiome research
Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool …...
Qiita: rapid, web-enabled microbiome meta-analysis
Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers...
Docent: transforming personal intuitions to scientific hypotheses through content learning and process training
People's lived experiences provide intuitions about health. Can they transform these personal intuitions into testable hypotheses that could inform both science and their lives? This paper introduces an online learning architecture and provides system principles for people to brainstorm causal scientific theories. We describe the Learn-Train-Ask workflow that guides participants through learning domain-specific content, process training to frame their intuitions as hypotheses, and collaborating with anonymous peers to brainstorm related questions...
Proceedings of the Fifth Annual ACM Conference on Learning at Scale
Predictions of backbone dynamics in intrinsically disordered proteins using de novo fragment-based protein structure predictions
Intrinsically disordaered proteins (IDPs) are a prevalent phenomenon with over 30% of human proteins estimated to have long disordered regions. Computational methods are widely used to study IDPs, however, nearly all treat disorder in a binary fashion, not accounting for the structural heterogeneity present in disordered regions. Here, we present a new de novo method, FRAGFOLD-IDP, which addresses this problem...
A communal catalogue reveals Earth’s multiscale microbial diversity
Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project...
Computational Investigations of Backbone Dynamics in Intrinsically Disordered Proteins
Intrinsically disordered proteins (IDPs), due to their dynamic nature, play important roles in molecular recognition, signalling, regulation, or binding of nucleic acids. IDPs have been extensively studied computationally in terms of binary disorder/order classification. This approach has proven to be fruitful and enabled researchers to estimate the amount of disorder in prokaryotic and eukaryotic genomes...
UCL (University College London)
Integrating citizen science with online learning to ask better questions
Online learners spend millions of hours per year testing their new skills on assignments with known answers. This paper explores whether framing research questions as assignments with unknown answers helps learners generate novel, useful, and difficult-to-find knowledge while increasing their motivation by contributing to a larger goal. Collaborating with the American Gut Project, the world's largest crowdfunded citizen science project, we deploy Gut Instinct to allow novices to generate hypotheses about the constitution of the human gut microbiome...
Accurate contact predictions using covariation techniques and machine learning
Here we present the results of residue–residue contact predictions achieved in CASP11 by the CONSIP2 server, which is based around our MetaPSICOV contact prediction method. On a set of 40 target domains with a median family size of around 40 effective sequences, our server achieved an average top‐L/5 long‐range contact precision of 27%. MetaPSICOV method bases on a combination of classical contact prediction features, enhanced with three distinct covariation methods embedded in a two‐stage neural network predictor...
Proteins: Structure, Function, and Bioinformatics
MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins
Motivation: Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage...
De novo structure prediction of globular proteins aided by sequence variation-derived contacts
The advent of high accuracy residue-residue intra-protein contact prediction methods enabled a significant boost in the quality of de novo structure predictions. Here, we investigate the potential benefits of combining a well-established fragment-based folding algorithm – FRAGFOLD, with PSICOV, a contact prediction method which uses sparse inverse covariance estimation to identify co-varying sites in multiple sequence alignments. Using a comprehensive set of 150 diverse globular target proteins, up to 266 amino acids in length, we are able to address the effectiveness and some limitations of such approaches to globular proteins in practice...
Impact of template choice on homology model efficiency in virtual screening
Homology modeling is a reliable method of predicting the three-dimensional structures of proteins that lack NMR or X-ray crystallographic data. It employs the assumption that a structural resemblance exists between closely related proteins. Despite the availability of many crystal structures of possible templates, only the closest ones are chosen for homology modeling purposes...
Journal of chemical information and modeling
Opportunities and limitations in applying coevolution-derived contacts to protein structure prediction
The prospect of identifying contacts in protein structures purely from aligned protein sequences has lured researchers for a long time, but progress has been modest until recently. Here, we reviewed the most successful methods for identifying structural contacts from sequence and how these methods differ and made an initial assessment of the overlap of predicted contacts by alternative approaches. We then discussed the limitations of these methods and possibilities for future development and highlighted the recent applications of contacts in tertiary structure prediction, identifying the residues at the interfaces of protein-protein interactions, and the use of these methods in disentangling alternative conformational states...
Bio-Algorithms and Med.-Systems