scholarly journals Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance

2020 ◽  
Vol 11 ◽  
Author(s):  
Ashley L. Cooper ◽  
Andrew J. Low ◽  
Adam G. Koziol ◽  
Matthew C. Thomas ◽  
Daniel Leclair ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Genome Sequence ◽  
Whole Genome Sequence ◽  
Systematic Evaluation ◽  
Whole Genome ◽  
Salmonella Serotype

scholarly journals Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection

2019 ◽  
Vol 20 (S15) ◽  
Author(s):  
Jinhong Shi ◽  
Yan Yan ◽  
Matthew G. Links ◽  
Longhai Li ◽  
Jo-Anne R. Dillon ◽  
...  
Keyword(s):  
Feature Selection ◽  
Antimicrobial Resistance ◽  
Genome Sequence ◽  
Sequence Data ◽  
Bacterial Species ◽  
Clinical Diagnostics ◽  
New Drugs ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

Abstract Background Antimicrobial resistance (AMR) is a major threat to global public health because it makes standard treatments ineffective and contributes to the spread of infections. It is important to understand AMR’s biological mechanisms for the development of new drugs and more rapid and accurate clinical diagnostics. The increasing availability of whole-genome SNP (single nucleotide polymorphism) information, obtained from whole-genome sequence data, along with AMR profiles provides an opportunity to use feature selection in machine learning to find AMR-associated mutations. This work describes the use of a supervised feature selection approach using deep neural networks to detect AMR-associated genetic factors from whole-genome SNP data. Results The proposed method, DNP-AAP (deep neural pursuit – average activation potential), was tested on a Neisseria gonorrhoeae dataset with paired whole-genome sequence data and resistance profiles to five commonly used antibiotics including penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime. The results show that DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae, and also provide a list of candidate genomic features (SNPs) that might lead to the discovery of novel AMR determinants. Logistic regression classifiers were built with the identified SNPs and the prediction AUCs (area under the curve) for penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime were 0.974, 0.969, 0.949, 0.994, and 0.976, respectively. Conclusions DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae. It also provides a list of candidate genes and intergenic regions that might lead to novel AMR factor discovery. More generally, DNP-AAP can be applied to AMR analysis of any bacterial species with genomic variants and phenotype data. It can serve as a useful screening tool for microbiologists to generate genetic candidates for further lab experiments.

scholarly journals Whole genome sequence analysis of Shigella from Malawi identifies fluoroquinolone resistance

2021 ◽  
Vol 7 (5) ◽  
Author(s):  
George E. Stenhouse ◽  
Khuzwayo C. Jere ◽  
Chikondi Peno ◽  
Rebecca J. Bengtsson ◽  
End Chinyama ◽  
...  
Keyword(s):  
Sequence Analysis ◽  
Antimicrobial Resistance ◽  
Genome Sequence ◽  
Whole Genome Sequence ◽  
Fluoroquinolone Resistance ◽  
Whole Genome ◽  
Genome Sequence Analysis ◽  
Content Type ◽  
Link Type ◽  
Global Priority

Increasing antimicrobial resistance and limited alternative treatments have led to fluoroquinolone-resistant Shigella strain inclusion on the WHO global priority pathogens list. In this study we characterized multiple Shigella isolates from Malawi with whole genome sequence analysis, identifying the acquirable fluoroquinolone resistance determinant qnrS1.

scholarly journals Whole genome sequence analysis of Shigella from Malawi identifies fluoroquinolone resistance

2020 ◽  
Author(s):  
George E. Stenhouse ◽  
Khuzwayo C. Jere ◽  
Chikondi Peno ◽  
Rebecca J. Bengtsson ◽  
End Chinyama ◽  
...  
Keyword(s):  
Sequence Analysis ◽  
Antimicrobial Resistance ◽  
Genome Sequence ◽  
Resistance Determinant ◽  
Whole Genome Sequence ◽  
Fluoroquinolone Resistance ◽  
Whole Genome ◽  
Alternative Treatments ◽  
Genome Sequence Analysis ◽  
Global Priority

AbstractIncreasing antimicrobial resistance and limited alternative treatments led to fluoroquinolone resistant Shigella strain inclusion on the WHO global priority pathogens list. In this study we characterised multiple Shigella isolates from Malawi with whole genome sequence analysis, identifying the acquirable fluoroquinolone resistance determinant qnrS1.

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