isolateR: an R package for generating microbial libraries from Sanger sequencing data

• Published in: Bioinformatics (Oxford, England) England), 2024-07, Vol.40 (7)
• Main Authors: Daisley, Brendan, Vancuren, Sarah J, Brettingham, Dylan J L, Wilde, Jacob, Renwick, Simone, Macpherson, Christine, Good, David A, Botschner, Alexander J, Yen, Sandi, Hill, Janet E, Sorbara, Matthew T, Allen-Vercoe, Emma
• Format: Article
• Language: English
• Subjects: Original Paper
• ISSN: 1367-4811; 1367-4803; 1367-4811
• DOI: 10.1093/bioinformatics/btae448

Sanger sequencing of taxonomic marker genes (e.g., 16S/18S/ITS/rpoB/cpn60) represents the leading method for identifying a wide range of microorganisms including bacteria, archaea, and fungi. However, the manual processing of sequence data and limitations associated with conventional BLAST searches impede the efficient generation of strain libraries essential for cataloging microbial diversity and discovering novel species. isolateR addresses these challenges by implementing a standardized and scalable three-step pipeline that includes: 1) automated batch processing of Sanger sequence files, 2) taxonomic classification via global alignment to type strain databases in accordance with the latest international nomenclature standards, and 3) straightforward creation of strain libraries and handling of clonal isolates, with the ability to set customizable sequence dereplication thresholds and combine data from multiple sequencing runs into a single library. The tool's user-friendly design also features interactive HTML outputs that simplify data exploration and analysis. Additionally, in silico benchmarking done on two comprehensive human gut genome catalogues (IMGG and Hadza hunter-gather populations) showcase the proficiency of isolateR in uncovering and cataloging the nuanced spectrum of microbial diversity, advocating for a more targeted and granular exploration within individual hosts to achieve the highest strain-level resolution possible when generating culture collections. isolateR is available at: https://github.com/bdaisley/isolateR. Supplementary data are available at Bioinformatics online.