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SeqSero2: Rapid and Improved Salmonella Serotype Determination Using Whole-Genome Sequencing Data.

Overview of attention for article published in Applied and Environmental Microbiology, November 2019
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Title
SeqSero2: Rapid and Improved Salmonella Serotype Determination Using Whole-Genome Sequencing Data.
Published in
Applied and Environmental Microbiology, November 2019
DOI 10.1128/aem.01746-19
Pubmed ID
Authors

Shaokang Zhang, Hendrik C den Bakker, Shaoting Li, Jessica Chen, Blake A Dinsmore, Charlotte Lane, A C Lauer, Patricia I Fields, Xiangyu Deng

Abstract

SeqSero, launched in 2015, is a software tool for Salmonella serotype determination from whole genome sequencing (WGS) data. Despite its routine use in public health and food safety laboratories in the United States and other countries, the original SeqSero pipeline is relatively slow (minutes per genome using sequencing reads), is not optimized for draft genome assemblies, and may assign multiple serotypes for a strain. Here we present SeqSero2 (github.com/denglab/SeqSero2; denglab.info/SeqSero2), an algorithmic transformation and functional update of the original SeqSero. Major improvements include: 1) additional sequence markers for identification of Salmonella species and subspecies and certain serotypes; 2) a k-mer based algorithm for rapid serotype prediction from raw reads (seconds per genome) and improved serotype prediction from assemblies; and 3) a targeted assembly approach for specific retrieval of serotype determinants from WGS for serotype prediction, new allele discovery, and prediction troubleshooting. Evaluated using 5,794 genomes representing 364 common US serotypes, including 2,280 human isolates of 117 serotypes from the National Antimicrobial Resistance Monitoring System, SeqSero2 is up to 50 times faster than the original SeqSero while maintaining equivalent accuracy for raw reads and substantially improving accuracy for assemblies. SeqSero2 further suggested that 3% of the tested genomes contained reads from multiple serotypes, indicating a use for contamination detection. In addition to short reads, SeqSero2 demonstrated potential for accurate and rapid serotype prediction directly from long nanopore reads despite base call errors. Testing of 40 nanopore-sequenced genomes of 17 serotypes yielded a single H antigen misidentification.IMPORTANCE: Serotyping is the basis of public health surveillance of Salmonella It remains a first-line subtyping method even as surveillance continues to be transformed by whole genome sequencing. SeqSero allows the integration of Salmonella serotyping into a whole genome sequencing-based laboratory workflow while maintaining continuity with the classic serotyping scheme. SeqSero2, informed by extensive testing and application of SeqSero in the United States and other countries, incorporates important improvements and updates that further strengthen its application in routine and large scale surveillance of Salmonella by whole genome sequencing.

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 129 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 16%
Student > Master 14 11%
Student > Ph. D. Student 13 10%
Other 6 5%
Student > Doctoral Student 6 5%
Other 23 18%
Unknown 47 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 16%
Agricultural and Biological Sciences 17 13%
Veterinary Science and Veterinary Medicine 9 7%
Immunology and Microbiology 8 6%
Unspecified 6 5%
Other 14 11%
Unknown 55 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 December 2019.
All research outputs
#2,718,583
of 25,385,509 outputs
Outputs from Applied and Environmental Microbiology
#1,400
of 19,165 outputs
Outputs of similar age
#55,603
of 374,997 outputs
Outputs of similar age from Applied and Environmental Microbiology
#15
of 116 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 19,165 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 374,997 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.