Hodges Lisa M, Taboada Eduardo N, Koziol Adam, Mutschall Steven, Blais Burton W, Inglis G Douglas, Leclair Daniel, Carrillo Catherine D
Canadian Food Inspection Agency, Dartmouth, NS, Canada.
Public Health Agency of Canada, Winnipeg, MB, Canada.
Front Microbiol. 2021 Nov 16;12:776967. doi: 10.3389/fmicb.2021.776967. eCollection 2021.
The increasing prevalence of antimicrobial resistance (AMR) in spp. is a global concern. This study evaluated the use of whole-genome sequencing (WGS) to predict AMR in er and . A panel of 271 isolates recovered from Canadian poultry was used to compare AMR genotype to antimicrobial susceptibility testing (AST) results (azithromycin, ciprofloxacin, erythromycin, gentamicin, tetracycline, florfenicol, nalidixic acid, telithromycin, and clindamycin). The presence of antibiotic resistance genes (ARGs) was determined for each isolate using five computational approaches to evaluate the effect of: ARG screening software, input data (i.e., raw reads, draft genome assemblies), genome coverage and genome assembly software. Overall, concordance between the genotype and phenotype was influenced by the computational pipelines, level of genome coverage and the type of ARG but not by input data. For example, three of the pipelines showed a 99% agreement between detection of a gene and tetracycline resistance, whereas agreement between the detection of and TET resistance was 98 and 93% for two pipelines. Overall, higher levels of genome coverage were needed to reliably detect some ARGs; for example, at 15X coverage a ) gene was detected in >70% of the genomes, compared to <60% of the genomes for . No genes associated with florfenicol or gentamicin resistance were found in the set of strains included in this study, consistent with AST results. Macrolide and fluoroquinolone resistance was associated 100% with mutations in the 23S rRNA (A2075G) and gyrA (T86I) genes, respectively. A lower association between a A2075G 23S rRNA gene mutation and resistance to clindamycin and telithromycin (92.8 and 78.6%, respectively) was found. While WGS is an effective approach to predicting AMR in , this study demonstrated the impact that computational pipelines, genome coverage and the genes can have on the reliable identification of an AMR genotype.
某菌属中抗菌药物耐药性（AMR）的日益流行是一个全球关注的问题。本研究评估了使用全基因组测序（WGS）来预测某菌和另一菌中的AMR情况。从加拿大家禽中分离出的一组271株菌株用于比较AMR基因型与抗菌药物敏感性测试（AST）结果（阿奇霉素、环丙沙星、红霉素、庆大霉素、四环素、氟苯尼考、萘啶酸、泰利霉素和克林霉素）。使用五种计算方法确定每种菌株中抗生素抗性基因（ARG）的存在情况，以评估以下因素的影响：ARG筛选软件、输入数据（即原始读数、草图基因组组装）、基因组覆盖率和基因组组装软件。总体而言，基因型和表型之间的一致性受计算流程、基因组覆盖水平和ARG类型的影响，但不受输入数据的影响。例如，其中三个流程显示检测到某基因与四环素耐药性之间的一致性为99%，而对于两个流程，检测到另一基因与TET耐药性之间的一致性分别为98%和93%。总体而言，需要更高水平的基因组覆盖才能可靠地检测到一些ARG；例如，在15倍覆盖率时，在>70%的基因组中检测到某基因，而另一基因在<60%的基因组中被检测到。在本研究纳入的菌株组中未发现与氟苯尼考或庆大霉素耐药性相关的基因，这与AST结果一致。大环内酯类和氟喹诺酮类耐药性分别与23S rRNA（A2075G）和gyrA（T86I）基因的突变100%相关。发现23S rRNA基因A2075G突变与克林霉素和泰利霉素耐药性之间的关联较低（分别为92.8%和78.6%）。虽然WGS是预测某菌中AMR的有效方法，但本研究证明了计算流程、基因组覆盖和基因对可靠鉴定AMR基因型可能产生的影响。
