StrainSeeker: fast identification of bacterial strains from raw sequencing reads using user-provided guide trees

PeerJ. 2017 May 18:5:e3353. doi: 10.7717/peerj.3353. eCollection 2017.

Abstract

Background: Fast, accurate and high-throughput identification of bacterial isolates is in great demand. The present work was conducted to investigate the possibility of identifying isolates from unassembled next-generation sequencing reads using custom-made guide trees.

Results: A tool named StrainSeeker was developed that constructs a list of specific k-mers for each node of any given Newick-format tree and enables the identification of bacterial isolates in 1-2 min. It uses a novel algorithm, which analyses the observed and expected fractions of node-specific k-mers to test the presence of each node in the sample. This allows StrainSeeker to determine where the isolate branches off the guide tree and assign it to a clade whereas other tools assign each read to a reference genome. Using a dataset of 100 Escherichia coli isolates, we demonstrate that StrainSeeker can predict the clades of E. coli with 92% accuracy and correct tree branch assignment with 98% accuracy. Twenty-five thousand Illumina HiSeq reads are sufficient for identification of the strain.

Conclusion: StrainSeeker is a software program that identifies bacterial isolates by assigning them to nodes or leaves of a custom-made guide tree. StrainSeeker's web interface and pre-computed guide trees are available at http://bioinfo.ut.ee/strainseeker. Source code is stored at GitHub: https://github.com/bioinfo-ut/StrainSeeker.

Keywords: Clade; Diagnostics; Species identification; Strain identification; k-mer.

Associated data

  • figshare/10.6084/m9.figshare.c.3750794.v1

Grants and funding

This work was supported by the European Union through the European Regional Development Fund through Estonian Centre of Excellence in Genomics and Translational Medicine (project No. 2014-2020.4.01.15-0012) and project ARMMD (No. 3.2.0701.11-0013), by the Estonian Ministry of Education and Research (institutional grant IUT34-11, target financing grants SF0180132s08 and KOGU-HUMB), by the Baltic Antibiotic Resistance collaborative Network (BARN), by the Estonian Research Council (grant No. IUT34-19) and by the Estonian Science Foundation (grant No. 9059). There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.