Algorithm and Software to Type Stx Operons Accurately from Assembled Genomic Sequence

Shiga toxins in Shiga toxin-producing Escherichia coli (STEC) infections are responsible for bloody diarrhea and serious complications such as hemolytic uremic syndrome. Two types of toxins have been identified: Shiga toxin type 1 (Stx1) and the immunologically distinct Shiga toxin type 2 (Stx2). Numerous STEC that express toxin variants within those two major groups have been characterized, some of which confer unique biological properties. These variants are grouped within the Stx1 or Stx2 types and are often assigned subtypes to indicate they are not identical in sequence or phenotype. Because serious outcomes of infection are associated with certain Stx subtypes, there is a need to assign Stx sequences to the proper subtype. Here, we report a comprehensive analysis of known Stx subtypes and describe a scheme and algorithm to classify the Stx toxins and Stx operon sequences by phylogenetic sequence-based relatedness of the holotoxin conforming to historical type designations. We used this analysis to develop the free and open-source StxTyper software and database that implements this typing algorithm; StxTyper is also integrated into = AMRFinderPlus 4.0 at the National Center for Biotechnology Information (NCBI). We validated and compared the results to PCR assays on a set of isolates and current state of the art surveillance methods used in the Danish public health system, and we summarize StxTyper results for over 111,000 publicly available E. coli genomes. We further propose a procedure to coordinate naming and identification for newly discovered and characterized Stx subtypes.

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Publication Details

Journal
Microorganisms
Published
2026-07-23
DOI
https://doi.org/10.3390/microorganisms14081607
Primary Topic
Escherichia coli research studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Algorithm and Software to Type Stx Operons Accurately from Assembled Genomic Sequence

Curtis J. Kapsak, Vyacheslav Brover, Michael Feldgarden, Valeria Michelacci et al.
Microorganisms
Escherichia coli research studies
article

Algorithm and Software to Type Stx Operons Accurately from Assembled Genomic Sequence

Curtis J. Kapsak, Vyacheslav Brover, Michael Feldgarden, Valeria Michelacci, Susanne Schjørring, Flemming Scheutz, Katrine Joensen, Rebecca L. Lindsey, Linlin Li, Stephanie Abromaitis, William Klimke, Arjun Balmiki Prasad
article en

Abstract

Shiga toxins in Shiga toxin-producing Escherichia coli (STEC) infections are responsible for bloody diarrhea and serious complications such as hemolytic uremic syndrome. Two types of toxins have been identified: Shiga toxin type 1 (Stx1) and the immunologically distinct Shiga toxin type 2 (Stx2). Numerous STEC that express toxin variants within those two major groups have been characterized, some of which confer unique biological properties. These variants are grouped within the Stx1 or Stx2 types and are often assigned subtypes to indicate they are not identical in sequence or phenotype. Because serious outcomes of infection are associated with certain Stx subtypes, there is a need to assign Stx sequences to the proper subtype. Here, we report a comprehensive analysis of known Stx subtypes and describe a scheme and algorithm to classify the Stx toxins and Stx operon sequences by phylogenetic sequence-based relatedness of the holotoxin conforming to historical type designations. We used this analysis to develop the free and open-source StxTyper software and database that implements this typing algorithm; StxTyper is also integrated into = AMRFinderPlus 4.0 at the National Center for Biotechnology Information (NCBI). We validated and compared the results to PCR assays on a set of isolates and current state of the art surveillance methods used in the Danish public health system, and we summarize StxTyper results for over 111,000 publicly available E. coli genomes. We further propose a procedure to coordinate naming and identification for newly discovered and characterized Stx subtypes.

MicroorganismsVol. 14(8)
Statens Serum Institut (DK), Centers for Disease Control and Prevention (US), National Institutes of Health (US), California Department of Public Health (US), Istituto Superiore di Sanità (IT), National Center for Biotechnology Information (US)
Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases
Good health and well-being
Openalex Percentile: Top 10%
Escherichia coli research studies
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