Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls

San, James Emmanuel; Baichoo, Shakuntala; Kanzi, Aquillah M.; Moosa, Yumna; Lessells, Richard; Fonseca, Vagner; Mogaka, John J O; Power, Robert A.; Oliveira, Túlio de

doi:10.3389/fmicb.2019.03119

Cited by 66 publications

(74 citation statements)

References 107 publications

(170 reference statements)

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“…To overcome typical shortcomings of SNP based association tools, we additionally used SEER as an alignment free tool. This procedure is also recommended by San et al (2019) who suggest testing for multiple forms of variations, especially when the type of variation responsible for the phenotype of interest is not known a priori .…”

Section: Resultsmentioning

confidence: 99%

Genome-Wide Association Studies for the Detection of Genetic Variants Associated With Daptomycin and Ceftaroline Resistance in Staphylococcus aureus

et al. 2021

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BackgroundAs next generation sequencing (NGS) technologies have experienced a rapid development over the last decade, the investigation of the bacterial genetic architecture reveals a high potential to dissect causal loci of antibiotic resistance phenotypes. Although genome-wide association studies (GWAS) have been successfully applied for investigating the basis of resistance traits, complex resistance phenotypes have been omitted so far. For S. aureus this especially refers to antibiotics of last resort like daptomycin and ceftaroline. Therefore, we aimed to perform GWAS for the identification of genetic variants associated with DAP and CPT resistance in clinical S. aureus isolates.Materials/methodsTo conduct microbial GWAS, we selected cases and controls according to their clonal background, date of isolation, and geographical origin. Association testing was performed with PLINK and SEER analysis. By using in silico analysis, we also searched for rare genetic variants in candidate loci that have previously been described to be involved in the development of corresponding resistance phenotypes.ResultsGWAS revealed MprF P314L and L826F to be significantly associated with DAP resistance. These mutations were found to be homogenously distributed among clonal lineages suggesting convergent evolution. Additionally, rare and yet undescribed single nucleotide polymorphisms could be identified within mprF and putative candidate genes. Finally, we could show that each DAP resistant isolate exhibited at least one amino acid substitution within the open reading frame of mprF. Due to the presence of strong population stratification, no genetic variants could be associated with CPT resistance. However, the investigation of the staphylococcal cassette chromosome mec (SCCmec) revealed various mecA SNPs to be putatively linked with CPT resistance. Additionally, some CPT resistant isolates revealed no mecA mutations, supporting the hypothesis that further and still unknown resistance determinants are crucial for the development of CPT resistance in S. aureus.ConclusionWe hereby confirmed the potential of GWAS to identify genetic variants that are associated with antibiotic resistance traits in S. aureus. However, precautions need to be taken to prevent the detection of spurious associations. In addition, the implementation of different approaches is still essential to detect multiple forms of variations and mutations that occur with a low frequency.

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Section: Resultsmentioning

confidence: 99%

Genome-Wide Association Studies for the Detection of Genetic Variants Associated With Daptomycin and Ceftaroline Resistance in Staphylococcus aureus

et al. 2021

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“…We note that the presence of SNPs with identical presence/absence patterns, which would be referred to as being in perfect linkage disequilibrium (LD) in genetics [42], is common in bacteria such as Mycobacterium tuberculosis whose evolution is primarily clonal [17].…”

Section: Resultsmentioning

confidence: 99%

“…For each drug, we only consider the isolates with a status for this drug. We group all the SNPs in perfect linkage disequilibrium (LD) [56], i.e. sharing identical presence/absence patterns in those isolates, into a single feature that we call a SNP group.…”

Section: Methodsmentioning

confidence: 99%

INGOT-DR: an interpretable classifier for predicting drug resistance in M. tuberculosis

Zabeti

Dexter

Safari

et al. 2020

Preprint

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15Motivation: The prediction of drug resistance and the identification of its mechanisms in bacteria 16 such as Mycobacterium tuberculosis, the etiological agent of tuberculosis, is a challenging problem. 17 Modern methods based on testing against a catalogue of previously identified mutations often yield 18 poor predictive performance. On the other hand, machine learning techniques have demonstrated 19 high predictive accuracy, but lack interpretability to aid in identifying specific mutations which lead 20 to resistance. We propose a novel technique, inspired by the group testing problem and Boolean 21 compressed sensing, which yields highly accurate predictions and interpretable results at the same 22 time. 23Results: We develop a modified version of the Boolean compressed sensing problem for identifying 24 drug resistance, and implement its formulation as an integer linear program. This allows us to 25 characterize the predictive accuracy of the technique and select an appropriate metric to optimize. 26 A simple adaptation of the problem also allows us to quantify the sensitivity-specificity trade-off of 27 our model under different regimes. We test the predictive accuracy of our approach on a variety 28 of commonly used antibiotics in treating tuberculosis and find that it has accuracy comparable to 29 that of standard machine learning models and points to several genes with previously identified 30 association to drug resistance. 31 Availability: https://github.com/WGS-TB/DrugResistance/tree/RB_learning 32 Contact: hooman_zabeti@sfu.ca 33 34 2012 ACM Subject Classification Applied computing -Life and medical sciences -Computational 35 biology -Molecular sequence analysis 36 1 Introduction 43 Drug resistance is the phenomenon by which an infectious organism (also known as pathogen) 44 develops resistance to one or more drugs that are commonly used in treatment [36]. In 45 this paper we focus our attention on Mycobacterium tuberculosis, the etiological agent of 46 tuberculosis, which is the largest infectious killer in the world today, responsible for over 10 47 million new cases and 2 million deaths every year [37]. 48 The development of resistance to common drugs used in treatment is a serious public health 49 threat, not only in low and middle-income countries, but also in high-income countries where 50 it is particularly problematic in hospital settings [39]. It is estimated that, without the urgent 51 development of novel antimicrobial drugs, the total mortality due to drug resistance will 52 exceed 10 million people a year by 2050, a number exceeding the annual mortality due to 53 cancer today [35]. 54 Existing models for predicting drug resistance from whole-genome sequence (WGS) data 55 broadly fall into two classes. The first, which we refer to as "catalogue methods," involves 56 testing the WGS data of an isolate for the presence of point mutations (typically single-57 nucleotide polymorphisms, or SNPs) associated with known drug resistance. If one or 58more such mutations is identified,...

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“…The dataset is peerless in that is covers more than 100 strains from GC patients, as well as those from DU patients, which enabled the unprecedented GWAS. However, we should keep in mind that the sample size is still smaller than that of GWASs in other bacterial species that utilized thousands of genome sequences (Chewapreecha, et al 2014; Earle, et al 2016b; San, et al 2019). Accordingly, the statistical power was insufficient to judge whether each discriminatory SNP indeed has a significant effect.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide association study of gastric cancer- and duodenal ulcer-derivedHelicobacter pyloristrains reveals discriminatory amino acid differences and novel oncoprotein candidates

Tuan

Yahara

Dung

et al. 2021

Preprint

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Genome-wide association studies (GWASs) can reveal genetic variations associated with a phenotype in the absence of any hypothesis of candidate genes. The problem of false-positive sites linked with the responsible site might be bypassed in bacteria with a high homologous recombination rate, such as Helicobacter pylori, which causes gastric cancer (GC). We conducted a GWAS followed by regression-based prediction of GC and duodenal ulcer H. pylori strains. We identified 14 single nucleotide polymorphisms (11 amino acid changes) that, combined, allowed effective disease discrimination. They were often informative of the underlying molecular mechanisms, such as electric charge alteration at the ligand-binding pocket, alteration in subunit interaction, and mode-switching of DNA methylation. We also identified three novel virulence factors/oncoprotein candidates. These results provide both defined targets for further informatic and experimental analyses to gain insights into GC pathogenesis and a basis for identifying a set of biomarkers for application in clinical settings.

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Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls

Cited by 66 publications

References 107 publications

Genome-Wide Association Studies for the Detection of Genetic Variants Associated With Daptomycin and Ceftaroline Resistance in Staphylococcus aureus

Genome-Wide Association Studies for the Detection of Genetic Variants Associated With Daptomycin and Ceftaroline Resistance in Staphylococcus aureus

INGOT-DR: an interpretable classifier for predicting drug resistance in M. tuberculosis

Genome-wide association study of gastric cancer- and duodenal ulcer-derivedHelicobacter pyloristrains reveals discriminatory amino acid differences and novel oncoprotein candidates

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