Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 6.456
Filtrar
1.
Water Res ; 185: 116127, 2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-33086465

RESUMO

Antibiotic resistance has become a global public health concern, rendering common infections untreatable. Given the widespread occurrence, increasing attention is being turned toward environmental pathways that potentially contribute to antibiotic resistance gene (ARG) dissemination outside the clinical realm. Studies during the past decade have clearly proved the increased ARG pollution trend along with gradient of anthropogenic interference, mainly through marker-ARG detection by PCR-based approaches. However, accurate source-tracking has been always confounded by various factors in previous studies, such as autochthonous ARG level, spatiotemporal variability and environmental resistome complexity, as well as inherent method limitation. The rapidly developed metagenomics profiles ARG occurrence within the sample-wide genomic context, opening a new avenue for source tracking of environmental ARG pollution. Coupling with machine-learning classification, it has been demonstrated the potential of metagenomic ARG profiles in unambiguously assigning source contribution. Through identifying indicator ARG and recovering ARG-host genomes, metagenomics-based analysis will further increase the resolution and accuracy of source tracking. In this review, challenges and progresses in source-tracking studies on environmental ARG pollution will be discussed, with specific focus on recent metagenomics-guide approaches. We propose an integrative metagenomics-based framework, in which coordinated efforts on experimental design and metagenomic analysis will assist in realizing the ultimate goal of robust source-tracking in environmental ARG pollution.


Assuntos
Antibacterianos , Genes Bacterianos , Antibacterianos/farmacologia , Resistência Microbiana a Medicamentos/genética , Genes Bacterianos/genética , Metagenoma , Metagenômica
2.
Nat Commun ; 11(1): 5015, 2020 10 06.
Artigo em Inglês | MEDLINE | ID: mdl-33024120

RESUMO

Human gut microbiome is a promising target for managing type 2 diabetes (T2D). Measures altering gut microbiota like oral intake of probiotics or berberine (BBR), a bacteriostatic agent, merit metabolic homoeostasis. We hence conducted a randomized, double-blind, placebo-controlled trial with newly diagnosed T2D patients from 20 centres in China. Four-hundred-nine eligible participants were enroled, randomly assigned (1:1:1:1) and completed a 12-week treatment of either BBR-alone, probiotics+BBR, probiotics-alone, or placebo, after a one-week run-in of gentamycin pretreatment. The changes in glycated haemoglobin, as the primary outcome, in the probiotics+BBR (least-squares mean [95% CI], -1.04[-1.19, -0.89]%) and BBR-alone group (-0.99[-1.16, -0.83]%) were significantly greater than that in the placebo and probiotics-alone groups (-0.59[-0.75, -0.44]%, -0.53[-0.68, -0.37]%, P < 0.001). BBR treatment induced more gastrointestinal side effects. Further metagenomics and metabolomic studies found that the hypoglycaemic effect of BBR is mediated by the inhibition of DCA biotransformation by Ruminococcus bromii. Therefore, our study reports a human microbial related mechanism underlying the antidiabetic effect of BBR on T2D. (Clinicaltrial.gov Identifier: NCT02861261).


Assuntos
Berberina/farmacologia , Diabetes Mellitus Tipo 2/tratamento farmacológico , Diabetes Mellitus Tipo 2/microbiologia , Microbioma Gastrointestinal/efeitos dos fármacos , Probióticos/uso terapêutico , Berberina/uso terapêutico , Feminino , Microbioma Gastrointestinal/fisiologia , Hemoglobina A Glicada/metabolismo , Humanos , Hipoglicemiantes/farmacologia , Hipoglicemiantes/uso terapêutico , Masculino , Metagenoma/efeitos dos fármacos , Metagenoma/genética , Pessoa de Meia-Idade , Placebos , Resultado do Tratamento
3.
Nat Commun ; 11(1): 5281, 2020 10 19.
Artigo em Inglês | MEDLINE | ID: mdl-33077707

RESUMO

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.


Assuntos
Bactérias/genética , Bactérias/metabolismo , Microbiota , Águas Residuárias/microbiologia , Bactérias/classificação , Bactérias/isolamento & purificação , Reatores Biológicos/microbiologia , Ecossistema , Metabolômica , Metagenoma , Metagenômica , Proteômica , Fatores de Tempo
4.
BMC Bioinformatics ; 21(1): 488, 2020 Oct 30.
Artigo em Inglês | MEDLINE | ID: mdl-33126862

RESUMO

BACKGROUND: Microbiome/metagenomic data have specific characteristics, including varying total sequence reads, over-dispersion, and zero-inflation, which require tailored analytic tools. Many microbiome/metagenomic studies follow a longitudinal design to collect samples, which further complicates the analysis methods needed. A flexible and efficient R package is needed for analyzing processed multilevel or longitudinal microbiome/metagenomic data. RESULTS: NBZIMM is a freely available R package that provides functions for setting up and fitting negative binomial mixed models, zero-inflated negative binomial mixed models, and zero-inflated Gaussian mixed models. It also provides functions to summarize the results from fitted models, both numerically and graphically. The main functions are built on top of the commonly used R packages nlme and MASS, allowing us to incorporate the well-developed analytic procedures into the framework for analyzing over-dispersed and zero-inflated count or proportion data with multilevel structures (e.g., longitudinal studies). The statistical methods and their implementations in NBZIMM particularly address the data characteristics and the complex designs in microbiome/metagenomic studies. The package is freely available from the public GitHub repository https://github.com/nyiuab/NBZIMM . CONCLUSION: The NBZIMM package provides useful tools for complex microbiome/metagenomics data analysis.


Assuntos
Análise de Dados , Metagenômica , Microbiota/genética , Modelos Estatísticos , Algoritmos , Humanos , Metagenoma , Análise Multinível
5.
PLoS One ; 15(10): e0237207, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33125392

RESUMO

In this work we propose an index to estimate the gut microbiota biodiversity using a modeling approach with the aim of describing its relationship with health and aging. The gut microbiota, a complex ecosystem that links nutrition and metabolism, has a pervasive effect on all body organs and systems, undergoes profound changes with age and life-style, and substantially contributes to the pathogenesis of age-related diseases. For these reasons, the gut microbiota is a suitable candidate for assessing and quantifying healthy aging, i.e. the capability of individuals to reach an advanced age, avoiding or postponing major age-related diseases. The importance of the gut microbiota in health and aging has been proven to be related not only to its taxonomic composition, but also to its ecological properties, namely its biodiversity. Following an ecological approach, here we intended to characterize the relationship between the gut microbiota biodiversity and healthy aging through the development a parsimonious model of gut microbiota from which biodiversity can be estimated. We analysed publicly available metagenomic data relative to subjects of different ages, countries, nutritional habits and health status and we showed that a hybrid niche-neutral model well describes the observed patterns of bacterial relative abundance. Moreover, starting from such ecological modeling, we derived an estimate of the gut microbiota biodiversity that is consistent with classical indices, while having a higher statistical power. This allowed us to unveil an increase of the gut microbiota biodiversity during aging and to provide a good predictor of health status in old age, dependent on life-style and aging disorders.


Assuntos
Envelhecimento , Microbioma Gastrointestinal , Modelos Biológicos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Envelhecimento/genética , Envelhecimento/fisiologia , Biodiversidade , Criança , Pré-Escolar , Bases de Dados de Ácidos Nucleicos , Feminino , Microbioma Gastrointestinal/genética , Microbioma Gastrointestinal/fisiologia , Nível de Saúde , Envelhecimento Saudável/genética , Envelhecimento Saudável/fisiologia , Humanos , Lactente , Recém-Nascido , Masculino , Metagenoma , Pessoa de Meia-Idade , RNA Ribossômico 16S/genética , Adulto Jovem
6.
PLoS One ; 15(10): e0239741, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33022000

RESUMO

The progress of next-generation sequencing has lead to the availability of massive data sets used by a wide range of applications in biology and medicine. This has sparked significant interest in using modern Big Data technologies to process this large amount of information in distributed memory clusters of commodity hardware. Several approaches based on solutions such as Apache Hadoop or Apache Spark, have been proposed. These solutions allow developers to focus on the problem while the need to deal with low level details, such as data distribution schemes or communication patterns among processing nodes, can be ignored. However, performance and scalability are also of high importance when dealing with increasing problems sizes, making in this way the usage of High Performance Computing (HPC) technologies such as the message passing interface (MPI) a promising alternative. Recently, MetaCacheSpark, an Apache Spark based software for detection and quantification of species composition in food samples has been proposed. This tool can be used to analyze high throughput sequencing data sets of metagenomic DNA and allows for dealing with large-scale collections of complex eukaryotic and bacterial reference genome. In this work, we propose MetaCache-MPI, a fast and memory efficient solution for computing clusters which is based on MPI instead of Apache Spark. In order to evaluate its performance a comparison is performed between the original single CPU version of MetaCache, the Spark version and the MPI version we are introducing. Results show that for 32 processes, MetaCache-MPI is 1.65× faster while consuming 48.12% of the RAM memory used by Spark for building a metagenomics database. For querying this database, also with 32 processes, the MPI version is 3.11× faster, while using 55.56% of the memory used by Spark. We conclude that the new MetaCache-MPI version is faster in both building and querying the database and uses less RAM memory, when compared with MetaCacheSpark, while keeping the accuracy of the original implementation.


Assuntos
Big Data , Genoma Bacteriano/genética , Metagenoma/genética , Metagenômica , Algoritmos , Metodologias Computacionais , DNA/genética , Software
7.
BMC Bioinformatics ; 21(1): 459, 2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-33059593

RESUMO

BACKGROUND: High-throughput sequencing can establish the functional capacity of a microbial community by cataloging the protein-coding sequences (CDS) present in the metagenome of the community. The relative performance of different computational methods for identifying CDS from whole-genome shotgun sequencing is not fully established. RESULTS: Here we present an automated benchmarking workflow, using synthetic shotgun sequencing reads for which we know the true CDS content of the underlying communities, to determine the relative performance (sensitivity, positive predictive value or PPV, and computational efficiency) of different metagenome analysis tools for extracting the CDS content of a microbial community. Assembly-based methods are limited by coverage depth, with poor sensitivity for CDS at < 5X depth of sequencing, but have excellent PPV. Mapping-based techniques are more sensitive at low coverage depths, but can struggle with PPV. We additionally describe an expectation maximization based iterative algorithmic approach which we show to successfully improve the PPV of a mapping based technique while retaining improved sensitivity and computational efficiency. CONCLUSION: Our benchmarking approach reveals the trade-offs of assembly versus alignment-based approaches and the relative performance of specific implementations when one wishes to extract the protein coding capacity of microbial communities.


Assuntos
Benchmarking , Simulação por Computador , Metagenoma , Fases de Leitura Aberta/genética , Algoritmos , Humanos , Metagenômica , Microbiota/genética , Valor Preditivo dos Testes
8.
Gigascience ; 9(10)2020 10 15.
Artigo em Inglês | MEDLINE | ID: mdl-33057676

RESUMO

BACKGROUND: Metagenomic next-generation sequencing (mNGS) has enabled the rapid, unbiased detection and identification of microbes without pathogen-specific reagents, culturing, or a priori knowledge of the microbial landscape. mNGS data analysis requires a series of computationally intensive processing steps to accurately determine the microbial composition of a sample. Existing mNGS data analysis tools typically require bioinformatics expertise and access to local server-class hardware resources. For many research laboratories, this presents an obstacle, especially in resource-limited environments. FINDINGS: We present IDseq, an open source cloud-based metagenomics pipeline and service for global pathogen detection and monitoring (https://idseq.net). The IDseq Portal accepts raw mNGS data, performs host and quality filtration steps, then executes an assembly-based alignment pipeline, which results in the assignment of reads and contigs to taxonomic categories. The taxonomic relative abundances are reported and visualized in an easy-to-use web application to facilitate data interpretation and hypothesis generation. Furthermore, IDseq supports environmental background model generation and automatic internal spike-in control recognition, providing statistics that are critical for data interpretation. IDseq was designed with the specific intent of detecting novel pathogens. Here, we benchmark novel virus detection capability using both synthetically evolved viral sequences and real-world samples, including IDseq analysis of a nasopharyngeal swab sample acquired and processed locally in Cambodia from a tourist from Wuhan, China, infected with the recently emergent SARS-CoV-2. CONCLUSION: The IDseq Portal reduces the barrier to entry for mNGS data analysis and enables bench scientists, clinicians, and bioinformaticians to gain insight from mNGS datasets for both known and novel pathogens.


Assuntos
Betacoronavirus/genética , Computação em Nuvem , Infecções por Coronavirus/virologia , Metagenoma , Metagenômica/métodos , Pneumonia Viral/virologia , Betacoronavirus/patogenicidade , Infecções por Coronavirus/diagnóstico , Bases de Dados Genéticas , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Pandemias , Pneumonia Viral/diagnóstico , Software
10.
Arch Virol ; 165(12): 2847-2856, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33034764

RESUMO

Here, we investigated the fecal, oral, blood, and skin virome of 10 laboratory rabbits using a viral metagenomic method. In the oral samples, we detected a novel polyomavirus (RabPyV), and phylogenetic analysis based on the large T antigen, VP1 and VP2 regions indicated that the novel strain might have undergone a recombination event. Recombination analysis based on related genomes confirmed that RabPyV is a multiple recombinant between rodent-like and avian-like polyomaviruses. In fecal samples, three partial or complete genome sequences of viruses belonging to the families Picobirnaviridae, Parvoviridae, Microviridae and Coronaviridae were characterized, and phylogenetic trees were constructed based on the predicted amino acid sequences of viral proteins. This study increases the amount of genetic information on viruses present in laboratory rabbits.


Assuntos
Metagenoma , Polyomavirus/isolamento & purificação , Coelhos/virologia , Proteínas Virais/genética , Vírus/classificação , Animais , Animais de Laboratório/virologia , Sangue/virologia , Fezes/virologia , Genoma Viral , Boca/virologia , Filogenia , Pele/virologia , Vírus/isolamento & purificação , Sequenciamento Completo do Genoma
11.
Nat Commun ; 11(1): 5104, 2020 10 09.
Artigo em Inglês | MEDLINE | ID: mdl-33037214

RESUMO

Many intestinal pathogens, including Clostridioides difficile, use mucus-derived sugars as crucial nutrients in the gut. Commensals that compete with pathogens for such nutrients are therefore ecological gatekeepers in healthy guts, and are attractive candidates for therapeutic interventions. Nevertheless, there is a poor understanding of which commensals use mucin-derived sugars in situ as well as their potential to impede pathogen colonization. Here, we identify mouse gut commensals that utilize mucus-derived monosaccharides within complex communities using single-cell stable isotope probing, Raman-activated cell sorting and mini-metagenomics. Sequencing of cell-sorted fractions reveals members of the underexplored family Muribaculaceae as major mucin monosaccharide foragers, followed by members of Lachnospiraceae, Rikenellaceae, and Bacteroidaceae families. Using this information, we assembled a five-member consortium of sialic acid and N-acetylglucosamine utilizers that impedes C. difficile's access to these mucosal sugars and impairs pathogen colonization in antibiotic-treated mice. Our findings underscore the value of targeted approaches to identify organisms utilizing key nutrients and to rationally design effective probiotic mixtures.


Assuntos
Clostridium difficile/patogenicidade , Microbioma Gastrointestinal/fisiologia , Monossacarídeos/metabolismo , Acetilglucosamina/metabolismo , Animais , Antibacterianos , Proteínas de Bactérias/metabolismo , Toxinas Bacterianas/metabolismo , Separação Celular/métodos , Infecções por Clostridium/microbiologia , Clostridium difficile/genética , Clostridium difficile/crescimento & desenvolvimento , Deutério , Feminino , Mucinas Gástricas/química , Mucinas Gástricas/metabolismo , Mucosa Intestinal/efeitos dos fármacos , Mucosa Intestinal/microbiologia , Metagenoma , Camundongos Endogâmicos C57BL , Ácido N-Acetilneuramínico/metabolismo , Polissacarídeos/química , Polissacarídeos/metabolismo , Análise Espectral Raman
12.
Viruses ; 12(9)2020 08 29.
Artigo em Inglês | MEDLINE | ID: mdl-32872469

RESUMO

The ongoing coronavirus disease 2019 (COVID-19) pandemic emphasizes the need to actively study the virome of unexplained respiratory diseases. We performed viral metagenomic next-generation sequencing (mNGS) analysis of 91 nasal-throat swabs from individuals working with animals and with acute respiratory diseases. Fifteen virus RT-PCR-positive samples were included as controls, while the other 76 samples were RT-PCR negative for a wide panel of respiratory pathogens. Eukaryotic viruses detected by mNGS were then screened by PCR (using primers based on mNGS-derived contigs) in all samples to compare viral detection by mNGS versus PCR and assess the utility of mNGS in routine diagnostics. mNGS identified expected human rhinoviruses, enteroviruses, influenza A virus, coronavirus OC43, and respiratory syncytial virus (RSV) A in 13 of 15 (86.7%) positive control samples. Additionally, rotavirus, torque teno virus, human papillomavirus, human betaherpesvirus 7, cyclovirus, vientovirus, gemycircularvirus, and statovirus were identified through mNGS. Notably, complete genomes of novel cyclovirus, gemycircularvirus, and statovirus were genetically characterized. Using PCR screening, the novel cyclovirus was additionally detected in 5 and the novel gemycircularvirus in 12 of the remaining samples included for mNGS analysis. Our studies therefore provide pioneering data of the virome of acute-respiratory diseases from individuals at risk of zoonotic infections. The mNGS protocol/pipeline applied here is sensitive for the detection of a variety of viruses, including novel ones. More frequent detections of the novel viruses by PCR than by mNGS on the same samples suggests that PCR remains the most sensitive diagnostic test for viruses whose genomes are known. The detection of novel viruses expands our understanding of the respiratory virome of animal-exposed humans and warrant further studies.


Assuntos
Infecções Respiratórias/virologia , Viroses/virologia , Zoonoses/virologia , Animais , Coronavirus/genética , Coronavirus/isolamento & purificação , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/virologia , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Metagenoma , Metagenômica/métodos , Pandemias , Filogenia , Pneumonia Viral/diagnóstico , Pneumonia Viral/virologia , Infecções Respiratórias/diagnóstico , Viroses/diagnóstico , Zoonoses/diagnóstico
13.
Water Res ; 186: 116318, 2020 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-32871290

RESUMO

The presence of antibiotics can exert significant selection pressure on the emergence and spread of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB). However, co-selection effects for ARGs, the mobility of ARGs and the identification of ARG hosts under high antibiotic selection pressures are poorly understood. Here, metagenomic assembly and binning approaches were used to comprehensively decipher the prevalence of ARGs and their potential mobility and hosts in activated sludge reactors treating antibiotic production wastewater. We found the abundance of different ARG types in antibiotic treatments varied greatly and certain antibiotic pressure promoted the co-selection for the non-corresponding types of ARGs. Antibiotic selection pressures significantly increased the abundance and proportions of ARGs mediated by plasmids (57.9%), which were more prevalent than those encoded in chromosomes (19.2%). The results indicated that plasmids and chromosomes had a tendency to carry different types of ARGs. Moreover, higher co-occurrence frequency of ARGs and MGEs revealed that antibiotics enhanced the mobility potential of ARGs mediated by both plasmids and integrative and conjugative elements. Among the 689 metagenome-assembled genomes (MAGs) with high estimated quality, 119 MAGs assigning to nine bacterial phyla were identified as the ARG hosts and 33 MAGs exhibited possible multi-resistance to antibiotics. Some ARG types tended to be carried by certain bacteria (e.g. bacitracin resistance genes carried by the family Burkholderiaceae) and thus showed a pronounced host-specific pattern. This study enhances the understanding of the mobility and hosts of ARGs and provides important insights into the risk assessment and management of antibiotic resistance.


Assuntos
Antibacterianos , Metagenoma , Antagonistas de Receptores de Angiotensina , Inibidores da Enzima Conversora de Angiotensina , Antibacterianos/farmacologia , Bactérias/genética , Resistência Microbiana a Medicamentos/genética , Genes Bacterianos
14.
Chemosphere ; 258: 127392, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32947654

RESUMO

Discharge of urban stormwater containing organic matter, heavy metals and sometime human feces, to the natural aquatic reservoirs without any treatment is not only an environmental problem. It can lead to prevalence of antibiotic resistant bacteria in stormwater systems and transmission of antibiotic resistance genes to the environment. We performed antibiotic resistome identification and virus detection in stormwater samples from Stockholm, using publicly available metagenomic sequencing MinION data. A MinION platform offers low-cost, precise environmental metagenomics analysis. 37 groups of antibiotic resistant bacteria (ARB), 11 resistance types with 26 resistance mechanisms - antibiotic resistance genes (ARGs) giving tolerance to the aminoglycoside, beta-lactams, fosmidomycin, MLS, multidrug and vancomycin were identified using ARGpore pipeline. The majority of the identified bacteria species were related to the natural environment such as soil and were not dangerous to human. Alarmingly, human pathogenic bacteria carrying resistance to antibiotics currently used against them (Bordetella resistant to macrolides and multidrug resistant Propionibacterium avidum) were also found in the samples. Most abundant viruses identified belonged to Caudovirales and Herpesvirales and they were not carrying ARGs. Unlike the virome, resistome and ARB were not unique for stormwater sampling points. This results underline the need for extensive monitoring of the microbial community structure in the urban stormwater systems to assess antimicrobial resistance spread.


Assuntos
Farmacorresistência Bacteriana/genética , Metagenoma , Bactérias/efeitos dos fármacos , Monitoramento Ambiental , Fezes/microbiologia , Genes Bacterianos/efeitos dos fármacos , Humanos , Macrolídeos , Metagenômica/métodos , Microbiota/efeitos dos fármacos , Águas Residuárias/microbiologia , beta-Lactamas
15.
Nat Commun ; 11(1): 4658, 2020 09 16.
Artigo em Inglês | MEDLINE | ID: mdl-32938931

RESUMO

Dimethylsulfoniopropionate (DMSP) is an important marine osmolyte. Aphotic environments are only recently being considered as potential contributors to global DMSP production. Here, our Mariana Trench study reveals a typical seawater DMSP/dimethylsulfide (DMS) profile, with highest concentrations in the euphotic zone and decreased but consistent levels below. The genetic potential for bacterial DMSP synthesis via the dsyB gene and its transcription is greater in the deep ocean, and is highest in the sediment.s DMSP catabolic potential is present throughout the trench waters, but is less prominent below 8000 m, perhaps indicating a preference to store DMSP in the deep for stress protection. Deep ocean bacterial isolates show enhanced DMSP production under increased hydrostatic pressure. Furthermore, bacterial dsyB mutants are less tolerant of deep ocean pressures than wild-type strains. Thus, we propose a physiological function for DMSP in hydrostatic pressure protection, and that bacteria are key DMSP producers in deep seawater and sediment.


Assuntos
Bactérias/genética , Bactérias/metabolismo , Água do Mar/química , Água do Mar/microbiologia , Compostos de Sulfônio/metabolismo , Bactérias/isolamento & purificação , Clorofila A/análise , Clorofila A/metabolismo , Genes Bacterianos , Sedimentos Geológicos/química , Pressão Hidrostática , Marinobacter/genética , Marinobacter/isolamento & purificação , Marinobacter/metabolismo , Metagenoma , Mutação , Oceanos e Mares , Prochlorococcus/genética , Prochlorococcus/isolamento & purificação , Prochlorococcus/metabolismo , RNA Ribossômico 16S , Sulfetos/análise , Sulfetos/metabolismo , Compostos de Sulfônio/análise , Synechococcus/genética , Synechococcus/isolamento & purificação , Synechococcus/metabolismo
16.
Nat Commun ; 11(1): 4897, 2020 09 29.
Artigo em Inglês | MEDLINE | ID: mdl-32994415

RESUMO

Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. However, its feedbacks to climate warming and underlying microbial mechanisms are still poorly understood. Here we show that the temperature sensitivity of soil microbial respiration (Q10) in a temperate grassland ecosystem persistently decreases by 12.0 ± 3.7% across 7 years of warming. Also, the shifts of microbial communities play critical roles in regulating thermal adaptation of soil respiration. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improves the modeling performance of soil microbial respiration by 5-19%, and reduces model parametric uncertainty by 55-71%. In addition, modeling analyses show that the microbial thermal adaptation can lead to considerably less heterotrophic respiration (11.6 ± 7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted.


Assuntos
Carbono/análise , Metagenoma/genética , Microbiota/fisiologia , Microbiologia do Solo , Solo/química , Aclimatação/genética , Archaea/genética , Archaea/isolamento & purificação , Archaea/metabolismo , Bactérias/genética , Bactérias/isolamento & purificação , Bactérias/metabolismo , Carbono/metabolismo , Ciclo do Carbono , Celulose/metabolismo , DNA Ambiental/genética , DNA Ambiental/isolamento & purificação , Fungos/genética , Fungos/isolamento & purificação , Fungos/metabolismo , Aquecimento Global , Pradaria , Temperatura Alta/efeitos adversos , Metagenômica , Modelos Genéticos , Raízes de Plantas/química , Poaceae/química
17.
BMC Infect Dis ; 20(1): 691, 2020 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-32957922

RESUMO

BACKGROUNDS: The incidence of angiostrongyliasis is increasing in recent decades due to the expanding endemic areas all over the world. Clinicians face tremendous challenge of diagnosing angiostrongyliasis because of the lack of awareness of the disease and less effective definitive laboratory tests. CASE PRESENTATION: A 27-year-old man initially manifested skin itching, emesis, myalgia and quadriparesis. With progressive weakness of four limbs and elevated protein in the cerebrospinal fluid (CSF), he was diagnosed as Guillain-Barré syndrome and treated with intravenous methylprednisolone and immunoglobulin. However, the patient deteriorated with hyperpyrexia, headache and then persistent coma. The routine tests for Angiostrongylus cantonensis (A. cantonensis) with both the CSF and the serum were all negative. In contrast, the metagenomic next-generation sequencing (mNGS) was applied with the serum sample and the CSF sample in the middle phase. The central nervous system (CNS) angiostrongyliasis was diagnosed by mNGS with the mid-phase CSF, but not the mid-phase serum. At the same time, the CSF analysis revealed eosinophils ratio up to 67%. The discovery of A. cantonensis was confirmed by PCR with CSF later. Unfortunately, the patient died of severe angiostrongyliasis. During his hospitalization, mNGS was carried out repeatedly after definitive diagnosis and targeted treatment. The DNA strictly map reads number of A. cantonensis detected by mNGS was positively correlated with the CSF opening pressure and clinical manifestations. CONCLUSIONS: The case of A. cantonensis infection highlights the benefit of mNGS as a target-free identification in disclosing the rare CNS angiostrongyliasis in the unusual season, while solid evidence from routine clinical testing was absent. The appropriate sample of mNGS should be chosen according to the life cycle of A. cantonensis. Besides, given the fact that the DNA reads number of A. cantonensis fluctuated with CSF opening pressure and clinical manifestations, whether mNGS could be applied as a marker of effectiveness of treatment is worth further exploration.


Assuntos
Angiostrongylus cantonensis/genética , Helmintíase do Sistema Nervoso Central/parasitologia , Sequenciamento de Nucleotídeos em Larga Escala , Infecções por Strongylida/parasitologia , Adulto , Albendazol/uso terapêutico , Animais , Anti-Helmínticos/uso terapêutico , Helmintíase do Sistema Nervoso Central/tratamento farmacológico , Helmintíase do Sistema Nervoso Central/etiologia , Líquido Cefalorraquidiano/parasitologia , Humanos , Masculino , Metagenoma , Metilprednisolona/uso terapêutico , Reação em Cadeia da Polimerase , Infecções por Strongylida/tratamento farmacológico , Infecções por Strongylida/etiologia
18.
BMC Bioinformatics ; 21(1): 412, 2020 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-32957925

RESUMO

BACKGROUND: It is a computational challenge for current metagenomic classifiers to keep up with the pace of training data generated from genome sequencing projects, such as the exponentially-growing NCBI RefSeq bacterial genome database. When new reference sequences are added to training data, statically trained classifiers must be rerun on all data, resulting in a highly inefficient process. The rich literature of "incremental learning" addresses the need to update an existing classifier to accommodate new data without sacrificing much accuracy compared to retraining the classifier with all data. RESULTS: We demonstrate how classification improves over time by incrementally training a classifier on progressive RefSeq snapshots and testing it on: (a) all known current genomes (as a ground truth set) and (b) a real experimental metagenomic gut sample. We demonstrate that as a classifier model's knowledge of genomes grows, classification accuracy increases. The proof-of-concept naïve Bayes implementation, when updated yearly, now runs in 1/4th of the non-incremental time with no accuracy loss. CONCLUSIONS: It is evident that classification improves by having the most current knowledge at its disposal. Therefore, it is of utmost importance to make classifiers computationally tractable to keep up with the data deluge. The incremental learning classifier can be efficiently updated without the cost of reprocessing nor the access to the existing database and therefore save storage as well as computation resources.


Assuntos
Microbioma Gastrointestinal/genética , Genoma Bacteriano , Aprendizado de Máquina , Metagenômica/métodos , Algoritmos , Bactérias/genética , Teorema de Bayes , Humanos , Metagenoma , Análise de Sequência de DNA/métodos
19.
Artigo em Inglês | MEDLINE | ID: mdl-32910916

RESUMO

Although bacteriophages are highly abundant in the gut microbiome, little is known about their potential effects on gut bacteria. In this issue of Cell Host & Microbe, Hryckowian et al. (2020) and Fujimoto et al. (2020) combined metagenomic analysis and experiments to study phage-bacteria associations in order to develop future research tools and therapies.


Assuntos
Bacteriófagos , Terapia por Fagos , Bactérias , Metagenoma
20.
Nat Commun ; 11(1): 4635, 2020 09 15.
Artigo em Inglês | MEDLINE | ID: mdl-32934239

RESUMO

Providing insight into one's health status from a gut microbiome sample is an important clinical goal in current human microbiome research. Herein, we introduce the Gut Microbiome Health Index (GMHI), a biologically-interpretable mathematical formula for predicting the likelihood of disease independent of the clinical diagnosis. GMHI is formulated upon 50 microbial species associated with healthy gut ecosystems. These species are identified through a multi-study, integrative analysis on 4347 human stool metagenomes from 34 published studies across healthy and 12 different nonhealthy conditions, i.e., disease or abnormal bodyweight. When demonstrated on our population-scale meta-dataset, GMHI is the most robust and consistent predictor of disease presence (or absence) compared to α-diversity indices. Validation on 679 samples from 9 additional studies results in a balanced accuracy of 73.7% in distinguishing healthy from non-healthy groups. Our findings suggest that gut taxonomic signatures can predict health status, and highlight how data sharing efforts can provide broadly applicable discoveries.


Assuntos
Bactérias/isolamento & purificação , Microbioma Gastrointestinal , Nível de Saúde , Bactérias/classificação , Bactérias/genética , Fezes/microbiologia , Humanos , Metagenoma , Microbiota
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA