Detection of hidden antibiotic resistance through real-time genomics
Lara UrbanEla SauerbornCarolina CorredorTim ReskaAlbert PerlasSamir Vargas da Fonseca AtumNick GoldmanNina WantiaClarissa Prazeres da CostaEbenezer Foster-Nyarko
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Foreword Metagenomics: Methods & Challenges Towards a More Complete Metagenomics Toolkit Analyzing Metagenomic Data: Inferring Microbial Community Function with MG-RAST Automatic Annotation of Microbial Genomes & Metagenomic Sequences Next-Generation & Future DNA Sequencing Technologies & Metagenomics Comparison of De Novo Short Read Assemblers on Simulated Metagenomic Data Submetagenomics: Selective Sampling of Metagenomic Subsets of Interest Dynamics of the Rumen Microbiota Detection of Functional Shifts in the Rumen Microbiota in Response to Propionate Intake in Cattle Carbohydrate Actives Enzymes Derived from Metagenomes: From Microbial Ecology to Enzymology An Evolutionary Ecology Perspective on Comparative Metagenomics Interactions of the Gut Microbiota & its Host in the Context of Gastrointestinal & Metabolic Diseases Metagenomic Analysis of Human Gut Microbiota Emerging Relevance of Metagenomics in Medicine Metagenomic Gene Discovery Emerging Techniques for Metagenome Screening Viral Metagenomics: From Fish Slime to the World Exploration of a Microbial Community for Novel Genetic Resources using Activity-Based Screening of a Metagenomic Library Microbial Communities in Crude Petroleum Oils & Metagenomics Environmental Metaproteomics: Identifying the Protein Machinery that Impact the Activities & Interactions of Microbes in Isolation or Communities Index.
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【Objective】To analyze and study the drug resistance phenotype of Klebsiella Pneumoniae and its relationship with genotypes.To detect the epidemic situation of different ESBL genotype.【Method】Detected the drug resistance of Klebsiella Pneumoniae by K-B method.Studied the relationship between its drug-resistance phenotype and its genotype by PFGE method.Analyzed the epidemic situation of ESBL genotype by PCR amplifying TEM,SHV and CTX-M gene fragments.【Results】It had a much severer drug-resistance nowadays for Klebsiella Pneumoniae and the result of ESBL-producing rate was 43.59%.117 clinical strains were dispatched into three groups by PFGE and its similar value resulted in 37.30%.No special ESBL DNA band was found.SHV detection rate resulted in 29.4%(15/51) by PCR,TEM 76.5%(39/51),CTX-M17.6%(9/51).【Conclusion】Much severer drug resistance of Klebsiella Pneumoniae was identified and most of it appeared multi-drug resistance.ESBL detecting rate was rather high.No nosocomoal infection resulted by a strain was detected through the study.Some drug resistance phenotype of Klebsiella Pneumoniae can be in accord with its genotype,while some not.The major genotype of ESBL producing Klebsiella Pneumoniae were tested to be TEM and SHV and it was very common strain carried multi-drug resistance genes.
Klebsiella
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Abstract Background DNA-stable isotope probing (DNA-SIP) links microorganisms to their in-situ function in diverse environmental samples. Combining DNA-SIP and metagenomics (metagenomic-SIP) allows us to link genomes from complex communities to their specific functions and improves the assembly and binning of these targeted genomes. However, empirical development of metagenomic-SIP methods is hindered by the complexity and cost of these studies. We developed a toolkit, ‘MetaSIPSim,’ to simulate sequencing read libraries for metagenomic-SIP experiments. MetaSIPSim is intended to generate datasets for method development and testing. To this end, we used MetaSIPSim generated data to demonstrate the advantages of metagenomic-SIP over a conventional shotgun metagenomic sequencing experiment. Results Through simulation we show that metagenomic-SIP improves the assembly and binning of isotopically labeled genomes relative to a conventional metagenomic approach. Improvements were dependent on experimental parameters and on sequencing depth. Community level G+C content impacted the assembly of labeled genomes and subsequent binning, where high community G+C generally reduced the benefits of metagenomic-SIP. Furthermore, when a high proportion of the community is isotopically labeled, the benefits of metagenomic-SIP decline. Finally, the choice of gradient fractions to sequence greatly influences method performance. Conclusions Metagenomic-SIP is a valuable method for recovering isotopically labeled genomes from complex communities. We show that metagenomic-SIP performance depends on optimization of experimental parameters. MetaSIPSim allows for simulation of metagenomic-SIP datasets which facilitates the optimization and development of metagenomic-SIP experiments and analytical approaches for dealing with these data.
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OBJECTIVE To investigate the distribution and drug resistance status of extended-spectrum β-lactamases producing(ESBLs) Klebsiella pneumoniae and to provide the basis for clinic anti-infective treatment.METHODS To use ATB-expression analyzer to identify the microbe.The drug susceptibility was tested with the K-B method and the ESBLs producing strains detected by diffusion confirmed test.RESULTS Among 137 strains of identified K.pneumoniae,34.3% of them(47 strains)produced ESBLs,and most had been shown in geriatrics ward.The drug resistance rate of ESBLs producing K.pneumoniae was higher than that in non-producing ESBLs one.So imipenem should be considered to be a preferred antibiotic when used on K.pneumoniae seriously infected cases.CONCLUSIONS The drug resistance of K.pneumoniae is a serious problem,we should pay attention on the status of ESBLs distribution,based on the susceptibility to choose the reasonable antibacterial to avoid the producing ESBLs bacteria spread out.
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Abstract Background While genome-resolved metagenomics has revolutionized our understanding of microbial and genetic diversity in environmental samples, assemblies of short-reads often result in incomplete and/or highly fragmented metagenome-assembled genomes (MAGs), hampering in-depth genomics. Although Nanopore sequencing has increasingly been used in microbial metagenomics as long reads greatly improve the assembly quality of MAGs, the recommended DNA quantity usually exceeds the recoverable amount of DNA of environmental samples. Here, we evaluated lower-than-recommended DNA quantities for Nanopore library preparation by determining sequencing quality, community composition, assembly quality and recovery of MAGs. Results We generated 27 Nanopore metagenomes using the commercially available ZYMO mock community and varied the amount of input DNA from 1000 ng (the recommended minimum) down to 1 ng in eight steps. The quality of the generated reads remained stable across all input levels. The read mapping accuracy, which reflects how well the reads match a known reference genome, was consistently high across all libraries. The relative abundance of the species in the metagenomes was stable down to input levels of 50 ng. High-quality MAGs (> 95% completeness, ≤ 5% contamination) could be recovered from metagenomes down to 35 ng of input material. When combined with publicly available Illumina reads for the mock community, Nanopore reads from input quantities as low as 1 ng improved the quality of hybrid assemblies. Conclusion Our results show that the recommended DNA amount for Nanopore library preparation can be substantially reduced without any adverse effects to genome recovery and still bolster hybrid assemblies when combined with short-read data. We posit that the results presented herein will enable studies to improve genome recovery from low-biomass environments, enhancing microbiome understanding.
Nanopore
Sequence assembly
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Since metagenomics targets at DNA extracted from the environment directly and analyzes the sequence of DNA based on different purposes,it can succeed in escaping from cultivation procedures and open another door for the study of uncultured microorganisms.Metatranscriptomics emerges as a complement of metagenomics,and has become an important approach for studying functional genomics.Integrated metatranscriptomic and metagenomic analysis will help to understand microbial gene composition and expression in the complex environment,and get some new discoveries.In this paper,the concepts,advantages and research strategies of metagenomics and metatranscriptomics and their prospects in environmental microorganism were reviewed.
Environmental DNA
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Metagenome assembly is a core yet methodologically challenging step for taxonomic classification and functional annotation of a microbiome. This study aims to generate the high-resolution human gut metagenome using both Illumina and Nanopore platforms. Assembly was achieved using four assemblers, including Flye (Nanopore), metaSPAdes (Illumina), hybridSPAdes (Illumina and Nanopore), and OPERA-MS (Illumina and Nanopore). Hybrid metagenome assembly was shown to generate contigs with almost same sizes comparable to those produced using Illumina reads alone, but was more contiguous, informative, and longer compared with those assembled with Illumina reads only. In addition, hybrid metagenome assembly enables us to obtain complete plasmid sequences and much more AMR gene-encoding contigs than the Illumina method. Most importantly, using our workflow, 58 novel high-quality metagenome bins were obtained from four assembly algorithms, particularly hybrid assembly (47/58), although metaSPAdes could provide 11 high-quality bins independently. Among them, 29 bins were currently uncultured bacterial metagenome-assembled genomes. These findings were highly consistent and supported by mock community data tested. In the analysis of biosynthetic gene clusters (BGCs), the number of BGCs in the contigs from hybridSPAdes (241) is higher than that of contigs from metaSPAdes (233). In conclusion, hybrid metagenome assembly could significantly enhance the efficiency of contig assembly, taxonomic binning, and genome construction compared with procedures using Illumina short-read data alone, indicating that nanopore long reads are highly useful in metagenomic applications. This technique could be used to create high-resolution references for future human metagenome studies.
Illumina dye sequencing
Sequence assembly
Nanopore
Minion
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DNA-stable isotope probing (DNA-SIP) links microorganisms to their in-situ function in diverse environmental samples. Combining DNA-SIP and metagenomics (metagenomic-SIP) allows us to link genomes from complex communities to their specific functions and improves the assembly and binning of these targeted genomes. However, empirical development of metagenomic-SIP methods is hindered by the complexity and cost of these studies. We developed a toolkit, 'MetaSIPSim,' to simulate sequencing read libraries for metagenomic-SIP experiments. MetaSIPSim is intended to generate datasets for method development and testing. To this end, we used MetaSIPSim generated data to demonstrate the advantages of metagenomic-SIP over a conventional shotgun metagenomic sequencing experiment.Through simulation we show that metagenomic-SIP improves the assembly and binning of isotopically labeled genomes relative to a conventional metagenomic approach. Improvements were dependent on experimental parameters and on sequencing depth. Community level G + C content impacted the assembly of labeled genomes and subsequent binning, where high community G + C generally reduced the benefits of metagenomic-SIP. Furthermore, when a high proportion of the community is isotopically labeled, the benefits of metagenomic-SIP decline. Finally, the choice of gradient fractions to sequence greatly influences method performance.Metagenomic-SIP is a valuable method for recovering isotopically labeled genomes from complex communities. We show that metagenomic-SIP performance depends on optimization of experimental parameters. MetaSIPSim allows for simulation of metagenomic-SIP datasets which facilitates the optimization and development of metagenomic-SIP experiments and analytical approaches for dealing with these data.
Stable-isotope probing
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ABSTRACT Background Read binning is a key step in proper and accurate analysis of metagenomics data. Typically, this is performed by comparing metagenomics reads to known microbial sequences. However, microbial communities usually contain mixtures of hundreds to thousands of unknown bacteria. This restricts the accuracy and completeness of alignment-based approaches. The possibility of reference-free deconvolution of environmental sequencing data could benefit the field of metagenomics, contributing to the estimation of metagenome complexity, improving the metagenome assembly, and enabling the investigation of new bacterial species that are not visible using standard laboratory or alignment-based bioinformatics techniques. Results Here, we apply an alignment-free method that leverages on k-mer frequencies to classify reads within a single long read metagenomic dataset. In addition to a series of simulated metagenomic datasets, we generated sequencing data from a bioreactor microbiome using the PacBio RSII single-molecule real-time sequencing platform. We show that distances obtained after the comparison of k-mer profiles can reveal relationships between reads within a single metagenome, leading to a clustering per species. Conclusions In this study, we demonstrated the possibility to detect substructures within a single metagenome operating only with the information derived from the sequencing reads. The obtained results are highly important as they establish a principle that might potentially expand the toolkit for the detection and investigation of previously unknow microorganisms.
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Metagenomics is a segment of conventional microbial genomics dedicated to the sequencing and analysis of combined genomic DNA of entire environmental samples. The most critical step of the metagenomic data analysis is the reconstruction of individual genes and genomes of the microorganisms in the communities using metagenomic assemblers – computational programs that put together small fragments of sequenced DNA generated by sequencing instruments. Here, we describe the challenges of metagenomic assembly, a wide spectrum of applications in which metagenomic assemblies were used to better understand the ecology and evolution of microbial ecosystems, and present one of the most efficient microbial assemblers, SPAdes that was upgraded to become applicable for metagenomics.
Environmental DNA
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