A genome-wide association study identifies a horizontally transferred bacterial surface adhesin gene associated with antimicrobial resistant strains

Genome-Wide Association Studies (GWAS) Approaches for the Detection of Genetic Variants Associated with Antibiotic Resistance: A Systematic Review

Antibiotic resistance is a significant threat to public health worldwide. Genome-wide association studies (GWAS) have emerged as a powerful tool to identify genetic variants associated with this antibiotic resistance. By analyzing large datasets of bacterial genomes, GWAS can provide valuable insights into the resistance mechanisms and facilitate the discovery of new drug targets. The present study aimed to undertake a systematic review of different GWAS approaches used for detecting genetic variants associated with antibiotic resistance. We comprehensively searched the PubMed and Scopus databases to identify relevant studies published from 2013 to February 2023. A total of 40 studies met our inclusion criteria. These studies explored a wide range of bacterial species, antibiotics, and study designs. Notably, most of the studies were centered around human pathogens such as Mycobacterium tuberculosis, Escherichia coli, Neisseria gonorrhoeae, and Staphylococcus aureus. The review seeks to explore the several GWAS approaches utilized to investigate the genetic mechanisms associated with antibiotic resistance. Furthermore, it examines the contributions of GWAS approaches in identifying resistance-associated genetic variants through binary and continuous phenotypes. Overall, GWAS holds great potential to enhance our understanding of bacterial resistance and improve strategies to combat infectious diseases.

A genome-wide association study reveals that epistasis underlies the pathogenicity of Pectobacterium

Pectobacterium spp. are important bacterial pathogens that cause soft rot symptoms in various crops. However, their mechanism of pathogenicity requires clarity to help control their infections. Here, genome-wide association studies (GWAS) were conducted by integrating genomic data and measurements of two phenotypes (virulence and cellulase activity) for 120 various Pectobacterium strains in order to identify the genetic basis of their pathogenicity. An artificial intelligence-based software program was developed to automatically measure lesion areas on Chinese cabbage, thereby facilitating accurate and rapid data collection for virulence phenotypes for use in GWAS analysis. The analysis discovered 428 and 158 loci significantly associated with Pectobacterium virulence (lesion area) and cellulase activity, respectively. In addition, 1,229 and 586 epistasis loci pairs were identified for the virulence and cellulase activity phenotypes, respectively. Among them, the AraC transcriptional regulator exerted epistasis effects with another three nutrient transport-related genes in pairs contributing to the virulence phenotype, and their epistatic effects were experimentally confirmed for one pair with knockout mutants of each single gene and double gene. This study consequently provides valuable insights into the genetic mechanism underlying Pectobacterium spp. pathogenicity. IMPORTANCE Plant diseases and pests are responsible for the loss of up to 40% of food crops, and annual economic losses caused by plant diseases reach more than $220 billion. Fighting against plant diseases requires an understanding of the pathogenic mechanisms of pathogens. This study adopted an advanced approach using population genomics integrated with virulence-related phenotype data to investigate the genetic basis of Pectobacterium spp., which causes serious crop losses worldwide. An automated software program based on artificial intelligence was developed to measure the virulence phenotype (lesion area), which greatly facilitated this research. The analysis predicted key genomic loci that were highly associated with virulence phenotypes, exhibited epistasis effects, and were further confirmed as critical for virulence with mutant gene deletion experiments. The present study provides new insights into the genetic determinants associated with Pectobacterium pathogenicity and provides a valuable new software resource that can be adapted to improve plant infection measurements.

Genome-Wide Association to Study the Host-Specificity Determinants of Xanthomonas perforans

Xanthomonas perforans and X. euvesicatoria are the causal agents of bacterial spot disease of tomato and pepper, endemic to the Southeastern United States. Although very closely related, the two bacterial species differ in host specificity, where X. perforans is the dominant pathogen of tomato and X. euvesicatoria that of pepper. This is in part due to the activity of avirulence proteins that are secreted by X. perforans strains and elicit effector-triggered immunity in pepper leaves, thereby restricting pathogen growth. In recent years, the emergence of several pepper-pathogenic X. perforans lineages has revealed variability within the bacterial species to multiply and cause disease in pepper, even in the absence of avirulence gene activity. Here, we investigated the basal evolutionary processes underlying the host range of this species using multiple genome-wide association analyses. Surprisingly, we identified two novel gene candidates that were significantly associated with pepper-pathogenic X. perforans and X. euvesicatoria. Both candidates were predicted to be involved in the transport/acquisition of nutrients common to the plant cell wall or apoplast and included a TonB-dependent receptor, which was disrupted through independent mutations within the X. perforans lineage. The other included a symporter of protons/glutamate, gltP, enriched with pepper-associated mutations near the promoter and start codon of the gene. Functional analysis of these candidates revealed that only the TonB-dependent receptor had a minor effect on the symptom development and growth of X. perforans in pepper leaves, indicating that pathogenicity to this host might have evolved independently within the bacterial species and is likely a complex, multigenic trait.

Genome-Wide Association Study of Listeria monocytogenes Isolates Causing Three Different Clinical Outcomes

Heterogeneity in virulence potential of L. monocytogenes subgroups have been associated with genetic elements that could provide advantages in certain environments to invade, multiply, and survive within a host. The presence of gene mutations has been found to be related to attenuated phenotypes, while the presence of groups of genes, such as pathogenicity islands (PI), has been associated with hypervirulent or stress-resistant clones. We evaluated 232 whole genome sequences from invasive listeriosis cases in human and ruminants from the US and Europe to identify genomic elements associated with strains causing three clinical outcomes: central nervous system (CNS) infections, maternal-neonatal (MN) infections, and systemic infections (SI). Phylogenetic relationships and virulence-associated genes were evaluated, and a gene-based and single nucleotide polymorphism (SNP)-based genome-wide association study (GWAS) were conducted in order to identify loci associated with the different clinical outcomes. The orthologous results indicated that genes of phage phiX174, transfer RNAs, and type I restriction-modification (RM) system genes along with SNPs in loci involved in environmental adaptation such as rpoB and a phosphotransferase system (PTS) were associated with one or more clinical outcomes. Detection of phenotype-specific candidate loci represents an approach that could narrow the group of genetic elements to be evaluated in future studies.

Population genomics of Group B Streptococcus reveals the genetics of neonatal disease onset and meningeal invasion

Group B Streptococcus (GBS), or Streptococcus agalactiae, is a pathogen that causes preterm births, stillbirths, and acute invasive neonatal disease burden and mortality. Here, we investigate bacterial genetic signatures associated with disease onset time and meningeal tissue infection in acute invasive neonatal GBS disease. We carry out a genome-wide association study (GWAS) of 1,338 GBS isolates from newborns with acute invasive disease; the isolates had been collected annually, for 30 years, through a national bacterial surveillance program in the Netherlands. After controlling for the population structure, we identify genetic variation within noncoding and coding regions, particularly the capsule biosynthesis locus, statistically associated with neonatal GBS disease onset time and meningeal invasion. Our findings highlight the impact of integrating microbial population genomics and clinical pathogen surveillance, and demonstrate the effect of GBS genetics on disease pathogenesis in neonates and infants.

Genome-wide association study of gastric cancer- and duodenal ulcer-derived Helicobacter pylori strains reveals discriminatory genetic variations and novel oncoprotein candidates

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. We conducted a small-sample GWAS (125 gastric cancer cases and 115 controls) followed by prediction of gastric cancer and control (duodenal ulcer) H. pylori strains. We identified 11 single nucleotide polymorphisms (eight amino acid changes) and three DNA motifs 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 gastric cancer pathogenesis and a basis for identifying a set of biomarkers for distinguishing these H. pylori-related diseases.

Bacterial genome-wide association study of hyper-virulent pneumococcal serotype 1 identifies genetic variation associated with neurotropism

Hyper-virulent Streptococcus pneumoniae serotype 1 strains are endemic in Sub-Saharan Africa and frequently cause lethal meningitis outbreaks. It remains unknown whether genetic variation in serotype 1 strains modulates tropism into cerebrospinal fluid to cause central nervous system (CNS) infections, particularly meningitis. Here, we address this question through a large-scale linear mixed model genome-wide association study of 909 African pneumococcal serotype 1 isolates collected from CNS and non-CNS human samples. By controlling for host age, geography, and strain population structure, we identify genome-wide statistically significant genotype-phenotype associations in surface-exposed choline-binding (P = 5.00 × 10-08) and helicase proteins (P = 1.32 × 10-06) important for invasion, immune evasion and pneumococcal tropism to CNS. The small effect sizes and negligible heritability indicated that causation of CNS infection requires multiple genetic and other factors reflecting a complex and polygenic aetiology. Our findings suggest that certain pathogen genetic variation modulate pneumococcal survival and tropism to CNS tissue, and therefore, virulence for meningitis.

GeneMates: an R package for detecting horizontal gene co-transfer between bacteria using gene-gene associations controlled for population structure

Background

Horizontal gene transfer contributes to bacterial evolution through mobilising genes across various taxonomical boundaries. It is frequently mediated by mobile genetic elements (MGEs), which may capture, maintain, and rearrange mobile genes and co-mobilise them between bacteria, causing horizontal gene co-transfer (HGcoT). This physical linkage between mobile genes poses a great threat to public health as it facilitates dissemination and co-selection of clinically important genes amongst bacteria. Although rapid accumulation of bacterial whole-genome sequencing data since the 2000s enables study of HGcoT at the population level, results based on genetic co-occurrence counts and simple association tests are usually confounded by bacterial population structure when sampled bacteria belong to the same species, leading to spurious conclusions.

Results

We have developed a network approach to explore WGS data for evidence of intraspecies HGcoT and have implemented it in R package GeneMates (github.com/wanyuac/GeneMates). The package takes as input an allelic presence-absence matrix of interested genes and a matrix of core-genome single-nucleotide polymorphisms, performs association tests with linear mixed models controlled for population structure, produces a network of significantly associated alleles, and identifies clusters within the network as plausible co-transferred alleles. GeneMates users may choose to score consistency of allelic physical distances measured in genome assemblies using a novel approach we have developed and overlay scores to the network for further evidence of HGcoT. Validation studies of GeneMates on known acquired antimicrobial resistance genes in Escherichia coli and Salmonella Typhimurium show advantages of our network approach over simple association analysis: (1) distinguishing between allelic co-occurrence driven by HGcoT and that driven by clonal reproduction, (2) evaluating effects of population structure on allelic co-occurrence, and (3) direct links between allele clusters in the network and MGEs when physical distances are incorporated.

Conclusion

GeneMates offers an effective approach to detection of intraspecies HGcoT using WGS data.

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

Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes, such as drug resistance, virulence, host specificity and prognosis. Several computational tools and methods have been developed or adapted from human GWAS to facilitate the discovery of novel mutations and structural variations that are associated with the phenotypes of interest. However, no comprehensive, end-to-end, user-friendly tool is currently available. The development of a broadly applicable pipeline presents a real opportunity among computational biologists. Here, (i) we review the prominent and promising tools, (ii) discuss analytical pitfalls and bottlenecks in mGWAS, (iii) provide insights into the selection of appropriate tools, (iv) highlight the gaps that still need to be filled and how users and developers can work together to overcome these bottlenecks. Use of mGWAS research can inform drug repositioning decisions as well as accelerate the discovery and development of more effective vaccines and antimicrobials for pressing infectious diseases of global health significance, such as HIV, TB, influenza, and malaria.

A Next-Generation Sequencing-Based Approach to Identify Genetic Determinants of Antibiotic Resistance in Cambodian Helicobacter pylori Clinical Isolates

We evaluated the primary resistance of Helicobacter pylori (H. pylori) to routinely used antibiotics in Cambodia, an unexplored topic in the country, and assessed next-generation sequencing’s (NGS) potential to discover genetic resistance determinants. Fifty-five H. pylori strains were successfully cultured and screened for antibiotic susceptibility using agar dilution. Genotypic analysis was performed using NGS data with a CLC genomic workbench. PlasmidSeeker was used to detect plasmids. The correlation between resistant genotypes and phenotypes was evaluated statistically. Resistances to metronidazole (MTZ), levofloxacin (LVX), clarithromycin (CLR), and amoxicillin (AMX) were 96.4%, 67.3%, 25.5%, and 9.1%, respectively. No resistance to tetracycline (TET) was observed. Multi-drug resistance affected 76.4% of strains. No plasmids were found, but genetic determinants of resistance to CLR, LVX, and AMX were 23S rRNA (A2146G and A2147G), GyrA (N87K and D91Y/N/G), and pbp1 (P473L), respectively. No determinants were genetically linked to MTZ or TET resistance. There was high concordance between resistant genotypes and phenotypes for AMX, LVX, and CLR. We observed high antibiotic resistance rates of CLR, MTZ, and LVX, emphasizing the need for periodic evaluation and alternative therapies in Cambodia. NGS showed high capability for detecting genetic resistance determinants and potential for implementation in local treatment policies.

Whole-genome sequencing of bloodstream Staphylococcus aureus isolates does not distinguish bacteraemia from endocarditis

Most Staphylococcus aureus isolates can cause invasive disease given the right circumstances, but it is unknown if some isolates are more likely to cause severe infections than others. S. aureus bloodstream isolates from 120 patients with definite infective endocarditis and 121 with S. aureus bacteraemia without infective endocarditis underwent whole-genome sequencing. Genome-wide association analysis was performed using a variety of bioinformatics approaches including SNP analysis, accessory genome analysis and k-mer based analysis. Core and accessory genome analyses found no association with either of the two clinical groups. In this study, the genome sequences of S. aureus bloodstream isolates did not discriminate between bacteraemia and infective endocarditis. Based on our study and the current literature, it is not convincing that a specific S. aureus genotype is clearly associated to infective endocarditis in patients with S. aureus bacteraemia.

Insights from genome-wide approaches to identify variants associated to phenotypes at pan-genome scale: Application to L. monocytogenes' ability to grow in cold conditions

Intraspecific variability of the behavior of most foodborne pathogens is well described and taken into account in Quantitative Microbial Risk Assessment (QMRA), but factors (strain origin, serotype, …) explaining these differences are scarce or contradictory between studies. Nowadays, Whole Genome Sequencing (WGS) offers new opportunities to explain intraspecific variability of food pathogens, based on various recently published bioinformatics tools. The objective of this study is to get a better insight into different existing bioinformatics approaches to associate bacterial phenotype(s) and genotype(s). Therefore, a dataset of 51 L. monocytogenes strains, isolated from multiple sources (i.e. different food matrices and environments) and belonging to 17 clonal complexes (CC), were selected to represent large population diversity. Furthermore, the phenotypic variability of growth at low temperature was determined (i.e. qualitative phenotype), and the whole genomes of selected strains were sequenced. The almost exhaustive gene content, as well as the core genome SNPs based phylogenetic reconstruction, were derived from the whole sequenced genomes. A Bayesian inference method was applied to identify the branches on which the phenotype distribution evolves within sub-lineages. Two different Genome Wide Association Studies (i.e. gene- and SNP-based GWAS) were independently performed in order to link genetic mutations to the phenotype of interest. The genomic analyses presented in this study were successfully applied on the selected dataset. The Bayesian phylogenetic approach emphasized an association with "slow" growth ability at 2 °C of the lineage I, as well as CC9 of the lineage II. Moreover, both gene- and SNP-GWAS approaches displayed significant statistical associations with the tested phenotype. A list of 114 significantly associated genes, including genes already known to be involved in the cold adaption mechanism of L. monocytogenes and genes associated to mobile genetic elements (MGE), resulted from the gene-GWAS. On the other hand, a group of 184 highly associated SNPs were highlighted by SNP-GWAS, including SNPs detected in genes which were already likely involved in cold adaption; hypothetical proteins; and intergenic regions where for example promotors and regulators can be located. The successful application of combined bioinformatics approaches associating WGS-genotypes and specific phenotypes, could contribute to improve prediction of microbial behaviors in food. The implementation of this information in hazard identification and exposure assessment processes will open new possibilities to feed QMRA-models.

Genome-Wide Association Analyses in the Model Rhizobium Ensifer meliloti

Genome-wide association studies (GWAS) can identify genetic variants responsible for naturally occurring and quantitative phenotypic variation. Association studies therefore provide a powerful complement to approaches that rely on de novo mutations for characterizing gene function. Although bacteria should be amenable to GWAS, few GWAS have been conducted on bacteria, and the extent to which nonindependence among genomic variants (e.g., linkage disequilibrium [LD]) and the genetic architecture of phenotypic traits will affect GWAS performance is unclear. We apply association analyses to identify candidate genes underlying variation in 20 biochemical, growth, and symbiotic phenotypes among 153 strains of Ensifer meliloti For 11 traits, we find genotype-phenotype associations that are stronger than expected by chance, with the candidates in relatively small linkage groups, indicating that LD does not preclude resolving association candidates to relatively small genomic regions. The significant candidates show an enrichment for nucleotide polymorphisms (SNPs) over gene presence-absence variation (PAV), and for five traits, candidates are enriched in large linkage groups, a possible signature of epistasis. Many of the variants most strongly associated with symbiosis phenotypes were in genes previously identified as being involved in nitrogen fixation or nodulation. For other traits, apparently strong associations were not stronger than the range of associations detected in permuted data. In sum, our data show that GWAS in bacteria may be a powerful tool for characterizing genetic architecture and identifying genes responsible for phenotypic variation. However, careful evaluation of candidates is necessary to avoid false signals of association.IMPORTANCE Genome-wide association analyses are a powerful approach for identifying gene function. These analyses are becoming commonplace in studies of humans, domesticated animals, and crop plants but have rarely been conducted in bacteria. We applied association analyses to 20 traits measured in Ensifer meliloti, an agriculturally and ecologically important bacterium because it fixes nitrogen when in symbiosis with leguminous plants. We identified candidate alleles and gene presence-absence variants underlying variation in symbiosis traits, antibiotic resistance, and use of various carbon sources; some of these candidates are in genes previously known to affect these traits whereas others were in genes that have not been well characterized. Our results point to the potential power of association analyses in bacteria, but also to the need to carefully evaluate the potential for false associations.

A GWAS on Helicobacter pylori strains points to genetic variants associated with gastric cancer risk

Background

Helicobacter pylori are stomach-dwelling bacteria that are present in about 50% of the global population. Infection is asymptomatic in most cases, but it has been associated with gastritis, gastric ulcers and gastric cancer. Epidemiological evidence shows that progression to cancer depends upon the host and pathogen factors, but questions remain about why cancer phenotypes develop in a minority of infected people. Here, we use comparative genomics approaches to understand how genetic variation amongst bacterial strains influences disease progression.

Results

We performed a genome-wide association study (GWAS) on 173 H. pylori isolates from the European population (hpEurope) with known disease aetiology, including 49 from individuals with gastric cancer. We identified SNPs and genes that differed in frequency between isolates from patients with gastric cancer and those with gastritis. The gastric cancer phenotype was associated with the presence of babA and genes in the cag pathogenicity island, one of the major virulence determinants of H. pylori, as well as non-synonymous variations in several less well-studied genes. We devised a simple risk score based on the risk level of associated elements present, which has the potential to identify strains that are likely to cause cancer but will require refinement and validation.

Conclusion

There are a number of challenges to applying GWAS to bacterial infections, including the difficulty of obtaining matched controls, multiple strain colonization and the possibility that causative strains may not be present when disease is detected. Our results demonstrate that bacterial factors have a sufficiently strong influence on disease progression that even a small-scale GWAS can identify them. Therefore, H. pylori GWAS can elucidate mechanistic pathways to disease and guide clinical treatment options, including for asymptomatic carriers.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0550-3) contains supplementary material, which is available to authorized users.

Identification of genetic variants of Brucella spp. through genome-wide association studies

Brucellosis is an important zoonotic disease caused by Brucella spp. We present a phylogeny of 552 strains based on genome-wide single nucleotide polymorphisms (SNPs) determined by an alignment-free k-mer approach. A total of 138,029 SNPs were identified from 552 Brucella genomes. Of these, 31,152 and 106,877 were core and non-core SNPs, respectively. Based on pan-genome analysis 11,937 and 972 genes were identified as pan and core genome, respectively. The pan-genome-wide analysis studies (Pan-GWAS) could not identify the group-specific variants in Brucella spp. Therefore, we focused on SNP based genome-wide association studies (SNP-GWAS) to identify the species-specific genetic determinants in Brucella spp. Phylogenetic tree representing eleven recognized Brucella spp. showed 16 major lineages. We identified 143 species-specific SNPs in Brucella abortus that are conserved in 311 B. abortus genomes. Of these, 141 species-specific SNPs were confined in the positively significant SNPs of B. abortus using SNP-GWAS. Since conserved in all the B. abortus genomes studied, these SNPs might have originated very early during the evolution of B. abortus and might be responsible for the evolution of B. abortus with cattle as the preferred host. Similarly, we identified 383 species-specific SNPs conserved in 132 Brucella melitensis genomes. Of these 379 species-specific SNPs were identified as positively associated using GWAS. Interestingly, >98% of the SNPs that are significantly, positively associated with the traits showed 100% sensitivity and 100% specificity. These identified species-specific core-SNPs identified in Brucella genomes could be responsible for the speciation and their respective host adaptation.

Emergence of Resistance Mutations in Salmonella enterica Serovar Typhi Against Fluoroquinolones

Background

Little is known about the evolutionary process and emergence time of resistance mutations to fluoroquinolone in Salmonella enterica serovar Typhi.

Methods

We analyzed S. Typhi isolates collected from returned travelers between 2001 and 2016. Based on ciprofloxacin susceptibility, isolates were categorized as highly resistant (minimum inhibitory concentration [MIC] ≥ 4 μg/mL [CIP^HR]), resistant (MIC = 1–2 μg/mL [CIP^R]), intermediate susceptible (MIC = 0.12–0.5 μg/mL [CIP^I]), and susceptible (MIC ≤ 0.06 μg/mL [CIP^S]).

Results

A total of 107 isolates (33 CIP^HR, 14 CIP^R, 30 CIP^I, and 30 CIP^S) were analyzed by whole-genome sequencing; 2461 single nucleotide polymorphisms (SNPs) were identified. CIP^S had no mutations in the gyrA or parC genes, while each CIP^I had 1 of 3 single mutations in gyrA (encoding Ser83Phe [63.3%], Ser83Tyr [33.3%], or Asp87Asn [3.3%]). CIP^HR had the same 3 mutations: 2 SNPs in gyrA (encoding Ser83Phe and Asp87Asn) and a third in parC (encoding Ser80Ile). CIP^HR shared a common ancestor with CIP^R and CIP^I isolates harboring a single mutation in gyrA encoding Ser83Phe, suggesting that CIP^HR emerged 16 to 23 years ago.

Conclusions

Three SNPs—2 in gyrA and 1 in parC—are present in S. Typhi strains highly resistant to fluoroquinolone, which were found to have evolved in 1993–2000, approximately 10 years after the beginning of the ciprofloxacin era. Highly resistant strains with survival advantages arose from strains harboring a single mutation in gyrA encoding Ser83Phe. Judicious use of fluoroquinolones is warranted to prevent acceleration of such resistance mechanisms in the future.