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1.
EBioMedicine ; 80: 104039, 2022 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-35509143

RESUMO

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) has been reported to be associated with longer screen time utilization (STU) at the behavioral level. However, whether there are shared neural links between ADHD symptoms and prolonged STU is not clear and has not been explored in a single large-scale dataset. METHODS: Leveraging the genetics, neuroimaging and behavioral data of 11,000+ children aged 9-11 from the Adolescent Brain Cognitive Development cohort, this study investigates the associations between the polygenic risk and trait for ADHD, STU, and white matter microstructure through cross-sectionally and longitudinal analyses. FINDINGS: Children with higher polygenic risk scores for ADHD tend to have longer STU and more severe ADHD symptoms. Fractional anisotropy (FA) values in several white matter tracts are negatively correlated with both the ADHD polygenic risk score and STU, including the inferior frontal-striatal tract, inferior frontal-occipital fasciculus, superior longitudinal fasciculus and corpus callosum. Most of these tracts are linked to visual-related functions. Longitudinal analyses indicate a directional effect of white matter microstructure on the ADHD scale, and a bi-directional effect between the ADHD scale and STU. Furthermore, reduction of FA in several white matter tracts mediates the association between the ADHD polygenic risk score and STU. INTERPRETATION: These findings shed new light on the shared neural overlaps between ADHD symptoms and prolonged STU, and provide evidence that the polygenic risk for ADHD is related, via white matter microstructure and the ADHD trait, to STU. FUNDING: This study was mainly supported by NSFC and National Key R&D Program of China.

2.
Nat Commun ; 13(1): 2326, 2022 Apr 28.
Artigo em Inglês | MEDLINE | ID: mdl-35484115

RESUMO

Metagenomic binning is the step in building metagenome-assembled genomes (MAGs) when sequences predicted to originate from the same genome are automatically grouped together. The most widely-used methods for binning are reference-independent, operating de novo and enable the recovery of genomes from previously unsampled clades. However, they do not leverage the knowledge in existing databases. Here, we introduce SemiBin, an open source tool that uses deep siamese neural networks to implement a semi-supervised approach, i.e. SemiBin exploits the information in reference genomes, while retaining the capability of reconstructing high-quality bins that are outside the reference dataset. Using simulated and real microbiome datasets from several different habitats from GMGCv1 (Global Microbial Gene Catalog), including the human gut, non-human guts, and environmental habitats (ocean and soil), we show that SemiBin outperforms existing state-of-the-art binning methods. In particular, compared to other methods, SemiBin returns more high-quality bins with larger taxonomic diversity, including more distinct genera and species.


Assuntos
Metagenoma , Microbiota , Algoritmos , Metagenoma/genética , Metagenômica/métodos , Microbiota/genética , Redes Neurais de Computação
3.
Mol Psychiatry ; 2022 Apr 04.
Artigo em Inglês | MEDLINE | ID: mdl-35379909

RESUMO

Neurological and psychiatric disorders have overlapped phenotypic profiles, but the underlying tissue-specific functional processes remain largely unknown. In this study, we explore the shared tissue-specificity among 14 neuropsychiatric disorders through the disrupted long-range gene regulations by GWAS-identified regulatory SNPs. Through Hi-C interactions, averagely 38.0% and 17.2% of the intergenic regulatory SNPs can be linked to target protein-coding genes in brain and non-brain tissues, respectively. Interestingly, while the regulatory target genes in the brain tend to enrich in nervous system development related processes, those in the non-brain tissues are inclined to interfere with synapse and neuroinflammation related processes. Compared to psychiatric disorders, neurological disorders present more prominently the neuroinflammatory processes in both brain and non-brain tissues, indicating an intrinsic difference in mechanisms. Through tissue-specific gene regulatory networks, we then constructed disorder similarity networks in two brain and three non-brain tissues, highlighting both known disorder clusters (e.g. the neurodevelopmental disorders) and unexpected disorder clusters (e.g. Parkinson's disease is consistently grouped with psychiatric disorders). We showcase the potential pharmaceutical applications of the small bowel and its disorder clusters, illustrated by the known drug targets NR1I3 and NFACT1, and their small bowel-specific regulatory modules. In conclusion, disrupted long-range gene regulations in both brain and non-brain tissues contribute to the similarity among distinct clusters of neuropsychiatric disorders, and the tissue-specifically shared functions and regulators for disease clusters may provide insights for future therapeutic investigations.

4.
Chin J Traumatol ; 25(3): 156-160, 2022 May.
Artigo em Inglês | MEDLINE | ID: mdl-35042629

RESUMO

PURPOSE: Auditory nerve injury is one of the most common nerve injury complications of skull base fractures. However, there is currently a lack of auxiliary examination methods for its direct diagnosis. The purpose of this study was to find a more efficient and accurate means of diagnosis for auditory nerve injury. METHODS: Through retrospectively analyzing the results of brainstem auditory evoked potential (BAEP) and high-resolution CT (HRCT) in 37 patients with hearing impairment following trauma from January 1, 2018 to July 31, 2020, the role of the two inspection methods in the diagnosis of auditory nerve injury was studied. Inclusion criteria were patient had a clear history of trauma and unilateral hearing impairment after trauma; while exclusion criteria were: (1) severe patient with a Glasgow coma scale score ≤5 because these patients were classified as severe head injury and admitted to the intensive care unit, (2) patient in the subacute stage admitted 72 h after trauma, and (3) patient with prior hearing impairment before trauma. According to Goodman's classification of hearing impairment, the patients were divided into low/medium/severe injury groups. In addition, patients were divided into HRCT-positive and negative groups for further investigation with their BAEP results. The positive rates of BEAP for each group were observed, and the results were analyzed by Chi-square test (p < 0.05, regarded as statistical difference). RESULTS: A total of 37 patients were included, including 21 males and 16 females. All of them were hospitalized patients with GCS score of 6-15 at the time of admission. The BAEP positive rate in the medium and severe injury group was 100%, which was significantly higher than that in the low injury group (27.27%) (p < 0.01). The rate of BEAP positivity was significantly higher in the HRCT-positive group (20/30, 66.7%) than in the HRCT-negative group (1/7, 14.3%) (p < 0.05). Twenty patients (54.05%) were both positive for BEAP and HRCT test, and considered to have auditory nerve damage. Six patients (16.22%) were both negative for BEAP and HRCT test, and 10 patients (27.03%) were BAEP-negative but HRCT-positive: all the 16 patients were considered as non-neurological injury. The rest 1 case (2.70%) was BAEP-positive but HRCT-negative, which we speculate may have auditory nerve concussion. CONCLUSION: By way of BAEP combining with skull base HRCT, we may improve the accuracy of the diagnosis of auditory nerve injury. Such a diagnostic strategy may be beneficial to guiding treatment plans and evaluating prognosis.


Assuntos
Potenciais Evocados Auditivos do Tronco Encefálico , Perda Auditiva , Nervo Coclear , Potenciais Evocados Auditivos do Tronco Encefálico/fisiologia , Feminino , Humanos , Masculino , Estudos Retrospectivos , Base do Crânio/diagnóstico por imagem , Tomografia Computadorizada por Raios X
6.
Nucleic Acids Res ; 50(D1): D808-D816, 2022 01 07.
Artigo em Inglês | MEDLINE | ID: mdl-34718713

RESUMO

mBodyMap is a curated database for microbes across the human body and their associations with health and diseases. Its primary aim is to promote the reusability of human-associated metagenomic data and assist with the identification of disease-associated microbes by consistently annotating the microbial contents of collected samples using state-of-the-art toolsets and manually curating the meta-data of corresponding human hosts. mBodyMap organizes collected samples based on their association with human diseases and body sites to enable cross-dataset integration and comparison. To help users find microbes of interest and visualize and compare their distributions and abundances/prevalence within different body sites and various diseases, the mBodyMap database is equipped with an intuitive interface and extensive graphical representations of the collected data. So far, it contains a total of 63 148 runs, including 14 401 metagenomes and 48 747 amplicons related to health and 56 human diseases, from within 22 human body sites across 136 projects. Also available in the database are pre-computed abundances and prevalence of 6247 species (belonging to 1645 genera) stratified by body sites and diseases. mBodyMap can be accessed at: https://mbodymap.microbiome.cloud.


Assuntos
Bactérias/genética , Bases de Dados Factuais , Metagenoma , Microbiota/genética , Software , Asma/microbiologia , Asma/patologia , Bactérias/classificação , Bactérias/metabolismo , Índice de Massa Corporal , Doença de Crohn/microbiologia , Doença de Crohn/patologia , Fibrose Cística/microbiologia , Fibrose Cística/patologia , DNA Bacteriano/genética , Neoplasias do Endométrio/microbiologia , Neoplasias do Endométrio/patologia , Enterocolite Necrosante/microbiologia , Enterocolite Necrosante/patologia , Feminino , Sequenciamento de Nucleotídeos em Larga Escala , Corpo Humano , Humanos , Internet , Metadados , Filogenia , Doença Pulmonar Obstrutiva Crônica/microbiologia , Doença Pulmonar Obstrutiva Crônica/patologia , Infecções Respiratórias/microbiologia , Infecções Respiratórias/patologia , Vaginose Bacteriana/microbiologia , Vaginose Bacteriana/patologia
7.
Nucleic Acids Res ; 50(D1): D777-D784, 2022 01 07.
Artigo em Inglês | MEDLINE | ID: mdl-34788838

RESUMO

GMrepo (data repository for Gut Microbiota) is a database of curated and consistently annotated human gut metagenomes. Its main purposes are to increase the reusability and accessibility of human gut metagenomic data, and enable cross-project and phenotype comparisons. To achieve these goals, we performed manual curation on the meta-data and organized the datasets in a phenotype-centric manner. GMrepo v2 contains 353 projects and 71,642 runs/samples, which are significantly increased from the previous version. Among these runs/samples, 45,111 and 26,531 were obtained by 16S rRNA amplicon and whole-genome metagenomics sequencing, respectively. We also increased the number of phenotypes from 92 to 133. In addition, we introduced disease-marker identification and cross-project/phenotype comparison. We first identified disease markers between two phenotypes (e.g. health versus diseases) on a per-project basis for selected projects. We then compared the identified markers for each phenotype pair across datasets to facilitate the identification of consistent microbial markers across datasets. Finally, we provided a marker-centric view to allow users to check if a marker has different trends in different diseases. So far, GMrepo includes 592 marker taxa (350 species and 242 genera) for 47 phenotype pairs, identified from 83 selected projects. GMrepo v2 is freely available at: https://gmrepo.humangut.info.


Assuntos
Bases de Dados Genéticas , Neoplasias Intestinais/microbiologia , Metagenoma , Microbiota , Biomarcadores/sangue , Conjuntos de Dados como Assunto , Microbioma Gastrointestinal/genética , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Internet , Neoplasias Intestinais/sangue , Neoplasias Intestinais/genética , Neoplasias Intestinais/patologia , Anotação de Sequência Molecular , Fenótipo , RNA Ribossômico 16S , Software
8.
Asian J Androl ; 24(2): 154-160, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34380864

RESUMO

Corticosteroid switching can reverse abiraterone resistance in some patients with metastatic castration-resistant prostate cancer (mCRPC). Here, we investigated the potential biomarkers for predicting the efficacy of corticosteroid switching during treatment with abiraterone acetate (AA). We retrospectively analyzed 101 mCRPC patients receiving corticosteroid switching from West China Hospital and Sun Yat-Sen University Cancer Center between January 2016 and December 2018. All cases received AA plus prednisone as first-line therapy during mCRPC. Primary end points were biochemical progression-free survival (bPFS) and overall survival (OS). The risk groups were defined based on multivariate analysis. A total of 42 (41.6%) and 25 (24.8%) patients achieved 30% and 50% decline in prostate-specific antigen (PSA), respectively, after corticosteroid switching. The median bPFS and median OS on AA plus dexamethasone were 4.9 (95% confidence interval [CI]: 3.7-6.0) months and 18.8 (95% CI: 16.2-30.2) months, respectively. Aldo-keto reductase family 1 member C3 (AKR1C3) expression (hazard ratio [HR]: 2.15, 95% Cl: 1.22-3.80, P = 0.008) and baseline serum alkaline phosphatase (ALP; HR: 4.95, 95% Cl: 2.40-10.19, P < 0.001) were independent predictors of efficacy before corticosteroid switching in the multivariate analysis of bPFS. Only baseline serum ALP >160 IU l-1 (HR: 3.41, 95% Cl: 1.57-7.38, P = 0.002) together with PSA level at switch ≥50 ng ml-1 (HR: 2.59, 95% Cl: 1.22-5.47, P = 0.013) independently predicted poorer OS. Based on the predictive factors in multivariate analysis, we developed two risk stratification tools to select candidates for corticosteroid switching. Detection of serum ALP level, PSA level, and tissue AKR1C3 expression in mCRPC patients could help make clinical decisions for corticosteroid switching.


Assuntos
Neoplasias de Próstata Resistentes à Castração , Acetato de Abiraterona/uso terapêutico , Corticosteroides/uso terapêutico , Androstenos , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Dexametasona/uso terapêutico , Intervalo Livre de Doença , Humanos , Masculino , Prednisona/uso terapêutico , Antígeno Prostático Específico , Neoplasias de Próstata Resistentes à Castração/patologia , Estudos Retrospectivos , Resultado do Tratamento
9.
Nature ; 601(7892): 252-256, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34912116

RESUMO

Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.


Assuntos
Metagenoma , Metagenômica , Antibacterianos/farmacologia , Resistência Microbiana a Medicamentos , Ecossistema , Humanos , Metagenoma/genética
10.
Brief Bioinform ; 23(1)2022 01 17.
Artigo em Inglês | MEDLINE | ID: mdl-34953465

RESUMO

Alzheimer's disease (AD) has a strong genetic predisposition. However, its risk genes remain incompletely identified. We developed an Alzheimer's brain gene network-based approach to predict AD-associated genes by leveraging the functional pattern of known AD-associated genes. Our constructed network outperformed existing networks in predicting AD genes. We then systematically validated the predictions using independent genetic, transcriptomic, proteomic data, neuropathological and clinical data. First, top-ranked genes were enriched in AD-associated pathways. Second, using external gene expression data from the Mount Sinai Brain Bank study, we found that the top-ranked genes were significantly associated with neuropathological and clinical traits, including the Consortium to Establish a Registry for Alzheimer's Disease score, Braak stage score and clinical dementia rating. The analysis of Alzheimer's brain single-cell RNA-seq data revealed cell-type-specific association of predicted genes with early pathology of AD. Third, by interrogating proteomic data in the Religious Orders Study and Memory and Aging Project and Baltimore Longitudinal Study of Aging studies, we observed a significant association of protein expression level with cognitive function and AD clinical severity. The network, method and predictions could become a valuable resource to advance the identification of risk genes for AD.


Assuntos
Doença de Alzheimer/genética , Doença de Alzheimer/metabolismo , Encéfalo/metabolismo , Redes Reguladoras de Genes , Predisposição Genética para Doença , Envelhecimento/genética , Perfilação da Expressão Gênica , Humanos , Estudos Longitudinais , Memória , Proteômica , RNA-Seq , Transcriptoma
11.
Artigo em Inglês | MEDLINE | ID: mdl-34880917

RESUMO

Visceral hypersensitivity (VH) is the predominant pathogenesis of functional dyspepsia (FD). Duodenal hypersensitivity along with nausea further reduces the comfort level in gastric balloon dilatation and inhibits gastric receptive relaxation. The potential mechanism behind electroacupuncture- (EA-) mediated alleviation of VH has not been elucidated. In an FD rat model with tail clamping stress, iodine acetamide (IA) induced VH. The rats were treated with EA with or without PAR2 antagonist FSLLRY-NH2, and the body weight, gastric sensitivity, compliance, and gastrointestinal motility were determined. Mast cells and activated degranulation were stained with toluidine blue (TB) staining and visualized under a transmission electron microscope (TEM). Immunofluorescence was used to detect the expression of PAR2, PKC, and TRPV1 in the duodenum and dorsal root ganglion (DRG) and that of CGRP, SP in DRG, and c-fos in the spinal cord. EA alone and EA + antagonist enhanced the gastrointestinal motility but diminished the expression of TRPV1, CGRP, SP, and c-fos-downstream of PAR2/PKC pathway and alleviated VH in FD rats. However, there was no obvious superposition effect between the antagonists and EA + antagonists. The effect of EA alone was better than that of antagonists and EA + antagonists 2 alone. EA-induced amelioration of VH in FD rats was mediated by TRPV1 regulation through PAR2/PKC pathway. This protective mechanism involved several pathways and included several targets.

12.
Diagnostics (Basel) ; 11(12)2021 Dec 13.
Artigo em Inglês | MEDLINE | ID: mdl-34943586

RESUMO

The aggravation of left ventricular diastolic dysfunction (LVDD) could lead to ventricular remodeling, wall stiffness, reduced compliance, and progression to heart failure with a preserved ejection fraction. A non-invasive method based on convolutional neural networks (CNN) and heart sounds (HS) is presented for the early diagnosis of LVDD in this paper. A deep convolutional generative adversarial networks (DCGAN) model-based data augmentation (DA) method was proposed to expand a HS database of LVDD for model training. Firstly, the preprocessing of HS signals was performed using the improved wavelet denoising method. Secondly, the logistic regression based hidden semi-Markov model was utilized to segment HS signals, which were subsequently converted into spectrograms for DA using the short-time Fourier transform (STFT). Finally, the proposed method was compared with VGG-16, VGG-19, ResNet-18, ResNet-50, DenseNet-121, and AlexNet in terms of performance for LVDD diagnosis. The result shows that the proposed method has a reasonable performance with an accuracy of 0.987, a sensitivity of 0.986, and a specificity of 0.988, which proves the effectiveness of HS analysis for the early diagnosis of LVDD and demonstrates that the DCGAN-based DA method could effectively augment HS data.

13.
Annu Rev Biomed Data Sci ; 4: 43-56, 2021 07 20.
Artigo em Inglês | MEDLINE | ID: mdl-34465176

RESUMO

The accumulation of vast amounts of multimodal data for the human brain, in both normal and disease conditions, has provided unprecedented opportunities for understanding why and how brain disorders arise. Compared with traditional analyses of single datasets, the integration of multimodal datasets covering different types of data (i.e., genomics, transcriptomics, imaging, etc.) has shed light on the mechanisms underlying brain disorders in greater detail across both the microscopic and macroscopic levels. In this review, we first briefly introduce the popular large datasets for the brain. Then, we discuss in detail how integration of multimodal human brain datasets can reveal the genetic predispositions and the abnormal molecular pathways of brain disorders. Finally, we present an outlook on how future data integration efforts may advance the diagnosis and treatment of brain disorders.


Assuntos
Encefalopatias , Encéfalo , Encéfalo/diagnóstico por imagem , Encefalopatias/diagnóstico , Genômica , Humanos , Transcriptoma
14.
Bioinformatics ; 2021 Jul 28.
Artigo em Inglês | MEDLINE | ID: mdl-34320631

RESUMO

MOTIVATION: Phosphorylation is one of the most studied post-translational modifications, which plays a pivotal role in various cellular processes. Recently, deep learning methods have achieved great success in prediction of phosphorylation sites, but most of them are based on convolutional neural network that may not capture enough information about long-range dependencies between residues in a protein sequence. In addition, existing deep learning methods only make use of sequence information for predicting phosphorylation sites, and it is highly desirable to develop a deep learning architecture that can combine heterogeneous sequence and protein-protein interaction (PPI) information for more accurate phosphorylation site prediction. RESULTS: We present a novel integrated deep neural network named PhosIDN, for phosphorylation site prediction by extracting and combining sequence and PPI information. In PhosIDN, a sequence feature encoding sub-network is proposed to capture not only local patterns but also long-range dependencies from protein sequences. Meanwhile, useful PPI features are also extracted in PhosIDN by a PPI feature encoding sub-network adopting a multi-layer deep neural network. Moreover, to effectively combine sequence and PPI information, a heterogeneous feature combination sub-network is introduced to fully exploit the complex associations between sequence and PPI features, and their combined features are used for final prediction. Comprehensive experiment results demonstrate that the proposed PhosIDN significantly improves the prediction performance of phosphorylation sites and compares favorably with existing general and kinase-specific phosphorylation site prediction methods. AVAILABILITY: PhosIDN is freely available at https://github.com/ustchangyuanyang/PhosIDN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

15.
Genome Med ; 13(1): 110, 2021 07 05.
Artigo em Inglês | MEDLINE | ID: mdl-34225788

RESUMO

BACKGROUND: Multimorbidities greatly increase the global health burdens, but the landscapes of their genetic risks have not been systematically investigated. METHODS: We used the hospital inpatient data of 385,335 patients in the UK Biobank to investigate the multimorbid relations among 439 common diseases. Post-GWAS analyses were performed to identify multimorbidity shared genetic risks at the genomic loci, network, as well as overall genetic architecture levels. We conducted network decomposition for the networks of genetically interpretable multimorbidities to detect the hub diseases and the involved molecules and functions in each module. RESULTS: In total, 11,285 multimorbidities among 439 common diseases were identified, and 46% of them were genetically interpretable at the loci, network, or overall genetic architecture levels. Multimorbidities affecting the same and different physiological systems displayed different patterns of the shared genetic components, with the former more likely to share loci-level genetic components while the latter more likely to share network-level genetic components. Moreover, both the loci- and network-level genetic components shared by multimorbidities converged on cell immunity, protein metabolism, and gene silencing. Furthermore, we found that the genetically interpretable multimorbidities tend to form network modules, mediated by hub diseases and featuring physiological categories. Finally, we showcased how hub diseases mediating the multimorbidity modules could help provide useful insights for the genetic contributors of multimorbidities. CONCLUSIONS: Our results provide a systematic resource for understanding the genetic predispositions of multimorbidities and indicate that hub diseases and converged molecules and functions may be the key for treating multimorbidities. We have created an online database that facilitates researchers and physicians to browse, search, or download these multimorbidities ( https://multimorbidity.comp-sysbio.org ).


Assuntos
Bancos de Espécimes Biológicos , Predisposição Genética para Doença , Genética Populacional , Multimorbidade , Adulto , Idoso , Algoritmos , Bases de Dados Factuais , Feminino , Estudos de Associação Genética , Variação Genética , Saúde Global , Humanos , Masculino , Pessoa de Meia-Idade , Modelos Teóricos , Polimorfismo de Nucleotídeo Único , Vigilância da População , Fatores de Risco , Reino Unido/epidemiologia
16.
Artigo em Inglês | MEDLINE | ID: mdl-34118462

RESUMO

Fecal microbiota transplantation (FMT) of human fecal samples into germ-free (GF) mice is useful for establishing causal relationships between the gut microbiota and human phenotypes. However, due to the intrinsic differences between human and mouse intestines and the different diets of the two organisms, it may not be possible to replicate human phenotypes in mice through FMT; similarly, treatments that are effective in mouse models may not be effective in humans. In this study, we aimed to identify human gut microbes that undergo significant and consistent changes (i.e., in relative abundances) after transplantation into GF mice in multiple experimental settings. We collected 16S rDNA-seq data from four published studies and analyzed the gut microbiota profiles from 1713 human-mouse pairs. Strikingly, on average, we found that only 47% of the human gut microbes could be re-established in mice at the species level, among which more than 1/3 underwent significant changes (referred to as "variable taxa"). Most of the human gut microbes that underwent significant changes were consistent across multiple human-mouse pairs and experimental settings. Consequently, about 1/3 of human samples changed their enterotypes, i.e., significant changes in their leading species after FMT. Mice fed with a controlled diet showed a lower enterotype change rate (23.5%) than those fed with a noncontrolled diet (49.0%), suggesting a possible solution for rescue. Most of the variable taxa have been reported to be implicated in human diseases, with some recognized as the causative species. Our results highlight the challenges of using a mouse model to replicate human gut microbiota-associated phenotypes, provide useful information for researchers using mice in gut microbiota studies, and call for additional validations after FMT. An online database named FMT-DB is publicly available at http://fmt2mice.humangut.info/#/.

17.
Bioinformatics ; 2021 May 10.
Artigo em Inglês | MEDLINE | ID: mdl-33974010

RESUMO

MOTIVATION: Aligning single-cell transcriptomes is important for the joint analysis of multiple single-cell RNA sequencing datasets, which in turn is vital to establishing a holistic cellular landscape of certain biological processes. Although numbers of approaches have been proposed for this problem, most of which only consider mutual neighbors when aligning the cells without taking into account known cell type annotations. RESULTS: In this work, we present MAT2 that aligns cells in the manifold space with a deep neural network employing contrastive learning strategy. Compared with other manifold-based approaches, MAT2 has two-fold advantages. Firstly, with cell triplets defined based on known cell type annotations, the consensus manifold yielded by the alignment procedure is more robust especially for datasets with limited common cell types. Secondly, the batch-effect-free gene expression reconstructed by MAT2 can better help annotate cell types. Benchmarking results on real scRNA-seq datasets demonstrate that MAT2 outperforms existing popular methods. Moreover, with MAT2, the hematopoietic stem cells are found to differentiate at different paces between human and mouse. AVAILABILITY AND IMPLEMENTATION: MAT2 is publicly available at https://github.com/Zhang-Jinglong/MAT2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

19.
mSystems ; 6(3)2021 May 04.
Artigo em Inglês | MEDLINE | ID: mdl-33947803

RESUMO

Common intestinal diseases such as Crohn's disease (CD), ulcerative colitis (UC), and colorectal cancer (CRC) share clinical symptoms and altered gut microbes, necessitating cross-disease comparisons and the use of multidisease models. Here, we performed meta-analyses on 13 fecal metagenome data sets of the three diseases. We identified 87 species and 65 pathway markers that were consistently changed in multiple data sets of the same diseases. According to their overall trends, we grouped the disease-enriched marker species into disease-specific and disease-common clusters and revealed their distinct phylogenetic relationships; species in the CD-specific cluster were phylogenetically related, while those in the CRC-specific cluster were more distant. Strikingly, UC-specific species were phylogenetically closer to CRC, likely because UC patients have higher risk of CRC. Consistent with their phylogenetic relationships, marker species had similar within-cluster and different between-cluster metabolic preferences. A portion of marker species and pathways correlated with an indicator of leaky gut, suggesting a link between gut dysbiosis and human-derived contents. Marker species showed more coordinated changes and tighter inner-connections in cases than the controls, suggesting that the diseased gut may represent a stressed environment and pose stronger selection on gut microbes. With the marker species and pathways, we constructed four high-performance (including multidisease) models with an area under the receiver operating characteristic curve (AUROC) of 0.87 and true-positive rates up to 90%, and explained their putative clinical applications. We identified consistent microbial alterations in common intestinal diseases, revealed metabolic capacities and the relationships among marker bacteria in distinct states, and supported the feasibility of metagenome-derived multidisease diagnosis.IMPORTANCE Gut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis, and Crohn's disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar clinical symptoms. Our meta-analysis and cross-disease comparisons identified consistent microbial alterations in each enteropathy, revealed microbial ecosystems among marker bacteria in distinct states, and demonstrated the necessity and feasibility of metagenome-based multidisease classifications. To the best of our knowledge, this is the first study to construct multiclass models for these common intestinal diseases.

20.
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