Dataset Information

SeqDe?: A Sequence Deconvolution Tool for Genome Separation of Endosymbionts From Mixed Sequencing Samples.

ABSTRACT: In recent years, the advent of NGS technology has made genome sequencing much cheaper than in the past; the high parallelization capability and the possibility to sequence more than one organism at once have opened the door to processing whole symbiotic consortia. However, this approach needs the development of specific bioinformatics tools able to analyze these data. In this work, we describe SeqDex, a tool that starts from a preliminary assembly obtained from sequencing a mixture of DNA from different organisms, to identify the contigs coming from one organism of interest. SeqDex is a fully automated machine learning-based tool exploiting partial taxonomic affiliations and compositional analysis to predict the taxonomic affiliations of contigs in an assembly. In literature, there are few methods able to deconvolve host-symbiont datasets, and most of them heavily rely on user curation and are therefore time consuming. The problem has strong similarities with metagenomic studies, where mixed samples are sequenced and the bioinformatics challenge is trying to separate contigs on the basis of their source organism; however, in symbiotic systems, additional information can be exploited to improve the output. To assess the ability of SeqDex to deconvolve host-symbiont datasets, we compared it to state-of-the-art methods for metagenomic binning and for host-symbiont deconvolution on three study cases. The results point out the good performances of the presented tool that, in addition to the ease of use and customization potential, make SeqDex a useful tool for rapid identification of endosymbiont sequences.

SUBMITTER: Chiodi A

PROVIDER: S-EPMC6761303 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

SeqDeχ: A Sequence Deconvolution Tool for Genome Separation of Endosymbionts From Mixed Sequencing Samples.

Chiodi Alice A Comandatore Francesco F Sassera Davide D Petroni Giulio G Bandi Claudio C Brilli Matteo M

Frontiers in genetics 20190919

In recent years, the advent of NGS technology has made genome sequencing much cheaper than in the past; the high parallelization capability and the possibility to sequence more than one organism at once have opened the door to processing whole symbiotic consortia. However, this approach needs the development of specific bioinformatics tools able to analyze these data. In this work, we describe SeqDex, a tool that starts from a preliminary assembly obtained from sequencing a mixture of DNA from d ...[more]

PMID: 31608107

Similar Datasets

Project description:Separating CBRN mixed samples that contain both chemical and biological warfare agents (CB mixed sample) in liquid and solid matrices remains a very challenging issue. Parameters were set up to assess the performance of a simple filtration-based method first optimized on separate C- and B-agents, and then assessed on a model of CB mixed sample. In this model, MS2 bacteriophage, Autographa californica nuclear polyhedrosis baculovirus (AcNPV), Bacillus atrophaeus and Bacillus subtilis spores were used as biological agent simulants whereas ethyl methylphosphonic acid (EMPA) and pinacolyl methylphophonic acid (PMPA) were used as VX and soman (GD) nerve agent surrogates, respectively. Nanoseparation centrifugal devices with various pore size cut-off (30 kD up to 0.45 µm) and three RNA extraction methods (Invisorb, EZ1 and Nuclisens) were compared. RNA (MS2) and DNA (AcNPV) quantification was carried out by means of specific and sensitive quantitative real-time PCRs (qPCR). Liquid chromatography coupled to time-of-flight mass spectrometry (LC/TOFMS) methods was used for quantifying EMPA and PMPA. Culture methods and qPCR demonstrated that membranes with a 30 kD cut-off retain more than 99.99% of biological agents (MS2, AcNPV, Bacillus Atrophaeus and Bacillus subtilis spores) tested separately. A rapid and reliable separation of CB mixed sample models (MS2/PEG-400 and MS2/EMPA/PMPA) contained in simple liquid or complex matrices such as sand and soil was also successfully achieved on a 30 kD filter with more than 99.99% retention of MS2 on the filter membrane, and up to 99% of PEG-400, EMPA and PMPA recovery in the filtrate. The whole separation process turnaround-time (TAT) was less than 10 minutes. The filtration method appears to be rapid, versatile and extremely efficient. The separation method developed in this work constitutes therefore a useful model for further evaluating and comparing additional separation alternative procedures for a safe handling and preparation of CB mixed samples.

Dataset Information

SeqDe?: A Sequence Deconvolution Tool for Genome Separation of Endosymbionts From Mixed Sequencing Samples.

Publications

SeqDeχ: A Sequence Deconvolution Tool for Genome Separation of Endosymbionts From Mixed Sequencing Samples.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets