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J Mol Cell Cardiol ; 2020 Apr 17.
Artigo em Inglês | MEDLINE | ID: mdl-32305360


BACKGROUND: Cardiac troponins are the preferred biomarkers of acute myocardial infarction. Despite superior sensitivity, serial testing of Troponins to identify patients suffering acute coronary syndromes is still required in many cases to overcome limited specificity. Moreover, unstable angina pectoris relies on reported symptoms in the troponin-negative group. In this study, we investigated genome-wide miRNA levels in a prospective cohort of patients with clinically suspected ACS and determined their diagnostic value by applying an in silico neural network. METHODS: PAXgene blood and serum samples were drawn and hsTnT was measured in patients at initial presentation to our Chest-Pain Unit. After clinical and diagnostic workup, patients were adjudicated by senior cardiologists in duty to their final diagnosis: STEMI, NSTEMI, unstable angina pectoris and non-ACS patients. ACS patients and a cohort of healthy controls underwent deep transcriptome sequencing. Machine learning was implemented to construct diagnostic miRNA classifiers. RESULTS: We developed a neural network model which incorporates 34 validated ACS miRNAs, showing excellent classification results. By further developing additional machine learning models and selecting the best miRNAs, we achieved an accuracy of 0.96 (95% CI 0.96-0.97), sensitivity of 0.95, specificity of 0.96 and AUC of 0.99. The one-point hsTnT value reached an accuracy of 0.89, sensitivity of 0.82, specificity of 0.96, and AUC of 0.96. CONCLUSIONS: Here we show the concept of neural network based biomarkers for ACS. This approach also opens the possibility to include multi-modal data points to further increase precision and perform classification of other ACS differential diagnoses.

Life Sci Alliance ; 2(2)2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30967445


Conceptually similar to modifications of DNA, mRNAs undergo chemical modifications, which can affect their activity, localization, and stability. The most prevalent internal modification in mRNA is the methylation of adenosine at the N6-position (m6A). This returns mRNA to a role as a central hub of information within the cell, serving as an information carrier, modifier, and attenuator for many biological processes. Still, the precise role of internal mRNA modifications such as m6A in human and murine-dilated cardiac tissue remains unknown. Transcriptome-wide mapping of m6A in mRNA allowed us to catalog m6A targets in human and murine hearts. Increased m6A methylation was found in human cardiomyopathy. Knockdown and overexpression of the m6A writer enzyme Mettl3 affected cell size and cellular remodeling both in vitro and in vivo. Our data suggest that mRNA methylation is highly dynamic in cardiomyocytes undergoing stress and that changes in the mRNA methylome regulate translational efficiency by affecting transcript stability. Once elucidated, manipulations of methylation of specific m6A sites could be a powerful approach to prevent worsening of cardiac function.

Adenosina/química , Cardiomiopatia Dilatada/genética , Cardiomiopatia Dilatada/patologia , Crescimento Celular , Proliferação de Células/genética , Regulação da Expressão Gênica , Miócitos Cardíacos/fisiologia , RNA Mensageiro/genética , Animais , Tamanho Celular , Células Cultivadas , Estudos de Coortes , Técnicas de Silenciamento de Genes , Humanos , Masculino , Metilação , Metiltransferases/genética , Camundongos , Biossíntese de Proteínas/genética , Ratos
Microbiome ; 5(1): 11, 2017 01 25.
Artigo em Inglês | MEDLINE | ID: mdl-28122610


BACKGROUND: Microbiome sequencing projects typically collect tens of millions of short reads per sample. Depending on the goals of the project, the short reads can either be subjected to direct sequence analysis or be assembled into longer contigs. The assembly of whole genomes from metagenomic sequencing reads is a very difficult problem. However, for some questions, only specific genes of interest need to be assembled. This is then a gene-centric assembly where the goal is to assemble reads into contigs for a family of orthologous genes. METHODS: We present a new method for performing gene-centric assembly, called protein-alignment-guided assembly, and provide an implementation in our metagenome analysis tool MEGAN. Genes are assembled on the fly, based on the alignment of all reads against a protein reference database such as NCBI-nr. Specifically, the user selects a gene family based on a classification such as KEGG and all reads binned to that gene family are assembled. RESULTS: Using published synthetic community metagenome sequencing reads and a set of 41 gene families, we show that the performance of this approach compares favorably with that of full-featured assemblers and that of a recently published HMM-based gene-centric assembler, both in terms of the number of reference genes detected and of the percentage of reference sequence covered. CONCLUSIONS: Protein-alignment-guided assembly of orthologous gene families complements whole-metagenome assembly in a new and very useful way.

Biologia Computacional/métodos , Metagenômica/métodos , Microbiota , Alinhamento de Sequência , Software , Algoritmos , Sequência de Aminoácidos , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Metagenoma , Análise de Sequência de DNA/métodos
PLoS Comput Biol ; 12(6): e1004957, 2016 06.
Artigo em Inglês | MEDLINE | ID: mdl-27327495


There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here:

Genoma Bacteriano/genética , Metagenoma/genética , Microbiota/genética , Análise de Sequência de DNA/métodos , Software , Sequenciamento de Nucleotídeos em Larga Escala , Interface Usuário-Computador
PLoS One ; 11(2): e0149564, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-26919743


BACKGROUND/OBJECTIVES: Cross-sectional studies suggested that obesity is promoted by the gut microbiota. However, longitudinal data on taxonomic and functional changes in the gut microbiota of obese patients are scarce. The aim of this work is to study microbiota changes in the course of weight loss therapy and the following year in obese individuals with or without co-morbidities, and to asses a possible predictive value of the gut microbiota with regard to weight loss maintenance. SUBJECTS/METHODS: Sixteen adult patients, who followed a 52-week weight-loss program comprising low calorie diet, exercise and behavioral therapy, were selected according to their weight-loss course. Over two years, anthropometric and metabolic parameters were assessed and microbiota from stool samples was functionally and taxonomically analyzed using DNA shotgun sequencing. RESULTS: Overall the microbiota responded to the dietetic and lifestyle intervention but tended to return to the initial situation both at the taxonomical and functional level at the end of the intervention after one year, except for an increase in Akkermansia abundance which remained stable over two years (12.7x103 counts, 95%CI: 322-25100 at month 0; 141x103 counts, 95%CI: 49-233x103 at month 24; p = 0.005). The Firmicutes/Bacteroidetes ratio was higher in obese subjects with metabolic syndrome (0.64, 95%CI: 0.34-0.95) than in the "healthy obese" (0.27, 95%CI: 0.08-0.45, p = 0.04). Participants, who succeeded in losing their weight consistently over the two years, had at baseline a microbiota enriched in Alistipes, Pseudoflavonifractor and enzymes of the oxidative phosphorylation pathway compared to patients who were less successful in weight reduction. CONCLUSIONS: Successful weight reduction in the obese is accompanied with increased Akkermansia numbers in feces. Metabolic co-morbidities are associated with a higher Firmicutes/Bacteroidetes ratio. Most interestingly, microbiota differences might allow discrimination between successful and unsuccessful weight loss prior to intervention.

Microbioma Gastrointestinal/genética , Trato Gastrointestinal/microbiologia , Metagenoma/genética , Obesidade/microbiologia , Perda de Peso/fisiologia , Adulto , Bacteroidetes/isolamento & purificação , Feminino , Firmicutes/isolamento & purificação , Humanos , Resistência à Insulina , Masculino , Pessoa de Meia-Idade , Obesidade/terapia