Nalidixic Acid

The second dataset, published by Holt et al. [24 (link)], consists of 130 globally distributed genomes of Shigella sonnei (Table S2), a Gram-negative bacterium that is a causative agent of dysentery. It enabled a comparison of ARIBA, SRST2, and KmerResistance with the manual method employed in the study of Holt et al. [24 (link)], confirming the accuracy of ARIBA for identifying known resistance SNPs as well as the presence or absence of genes of interest.
The phenotypic resistance profile for a number of antimicrobials is known for each isolate, and is attributable to both acquired resistance genes and SNPs. The three tools were run on all 130 samples using the reference database from CARD, version 1.1.2. To ensure our results were comparable with those originally reported in Table S1 of Holt et al. [24 (link)], we manually added those AMR genes listed on page 4 of their supplementary text not already included in the database (Table S3). The AMR determinants originally reported in the study of Holt et al. [24 (link)] were identified from mapping data, and reported as the proportion of bases in the gene sequence that were covered by reads from each isolate. From these originally reported data, we used a cut-off of >90 % to indicate that a gene was present by their method.
In order to interpret the output of each tool as an AMR call, the following rules were used, where all relevant genes are listed in Table S4. A gene was counted as present by ARIBA if ariba summary reported yes or yes_nonunique; present by KmerResistance if it appeared in its output file; and present by SRST2 if it was reported without a ‘?’.
The focus for the genes of interest for each AMR call were those originally identified and reported in Holt et al. [24 (link)]. Given that the discovery and classification of AMR gene variants is an ongoing process, an AMR gene was called as present if it was either the originally identified gene in Holt et al. [24 (link)], or in the same CD-HIT cluster. Genes conferring resistance to antimicrobials not examined in the original paper were excluded, as were genes conferring resistance to the antimicrobials examined in the paper but falling in different CD-HIT clusters from the originally identified genes. For each antimicrobial examined, an AMR call for a resistant genotype was identified using the following rules. Ampicillin (Amp): the presence of any gene from a set of blaTEM, blaCTX-M and blaOXA genes. Chloramphenicol (Cmp): the presence of any gene from a set of cat genes. Nalidixic acid (Nal): the gyrA gene present, together with one of the SNPs S83L, D87G, or D87Y. Streptomycin (Str): both of the strA and strB genes, or one of the aadA genes. Sulfonamides (Sul): any gene from the set of sul1 and sul2 genes. Tetracycline (Tet): both of tetA +tetR, or all of tetA, C, D, R, where each of the two sets of tetA and tetR genes are disjoint. Trimethoprim (Tmp): any one of a set of dfrA or dhfr genes.

We conducted a systematic review of published literature between 1990 and 2018 following the PRISMA guidelines (Additional file 1: Table S1) [22 (link)]. The protocol was registered with the international prospective register of systematic reviews (CRD42018029432). The search strategy was devised by an academic librarian (EH). MEDLINE, Ovid Embase, Global Health, Cochrane Library, Scopus, Web of Science-Core Collection and LILACS were searched using a syntax that combined Medical Subject Headings (MeSH) and free text terms for the pathogens of interest (e.g. S. Typhi, S. Paratyphi A, enteric fever) with terms for antimicrobial resistance (e.g. resistan*, suscept*, surveil*) (Additional file 1: Table S2). The extended search was conducted in October 2017 and updated in March 2019. The search was limited to publications from 1990 onwards; no restrictions on language or filters (e.g. humans) were implemented.
Included studies were required to report quantifiable in vitro antimicrobial susceptibility data for S. Typhi and/or S. Paratyphi A isolated from blood culture, examining at least 10 representative organisms and indicating the study location. Reports from travellers being diagnosed in high-income countries were excluded. Studies with pooled S. Typhi and S. Paratyphi A susceptibility data, studies reporting on isolates from stool culture and duplicate isolates were also excluded.
Prospective and retrospective hospital-, laboratory- and community-based studies were included, if they met the specified inclusion criteria. Review articles were scanned for relevant references. Studies were screened at title, abstract and full-text stage by one author (CD) and reviewed by a second author (AB). Data were extracted into a predefined database by AB and reviewed by BKH and JL. Additionally, 20% of the extracted studies were checked by a third reviewer (CD). Disagreements were resolved by discussion. Susceptibility data for antimicrobials recommended for the treatment of enteric fever by WHO, i.e. ampicillin/amoxicillin, chloramphenicol, trimethoprim-sulphamethoxazole (co-trimoxazole), fluoroquinolones (e.g. ciprofloxacin and ofloxacin), third-generation cephalosporins (e.g. ceftriaxone and cefixime) and azithromycin, were extracted [11 ]. Furthermore, multidrug resistance (MDR; defined as resistance to ampicillin/amoxicillin, chloramphenicol and co-trimoxazole) and nalidixic acid resistance, as a proxy marker for reduced ciprofloxacin susceptibility, were recorded [18 (link)].
Variables extracted included the study start and end dates, patients’ characteristics (age range, mean age, percentage of males, inpatients or outpatients), study design, number of patients screened, number of patients with positive blood culture, antimicrobial susceptibility testing (AST) method and the number (or percentage) of resistant, intermediate and susceptible isolates out of the total number of isolates tested against each antimicrobial. We also recorded case fatalities and clinical outcomes when available. Additionally, the testing standard (e.g. Clinical and Laboratory Standards Institute (CLSI)) and interpretive criteria (including version or year) used to determine resistance, use of internal quality controls and participation in external quality assessments schemes were recorded. The study setting, precise study location, country and GBD study region were recorded for each study. Data were disaggregated by serovar and study location.
We aimed to control for bias and allow for comparison across studies by adhering to the predefined inclusion and exclusion criteria. We expected that there would be differences in the quality of the AST and interpretation of results, reflecting the reality in many LMICs. We adapted a descriptive tool for quality assessment used by Arndt, based on sample size and microbiological testing methodology [23 (link)]. We reviewed the complete description of susceptibility testing methods, which included testing standard, version and/or year (i.e. breakpoints), internal quality controls and external quality assessment. No study was excluded based on this assessment, due to the lack of standardised reporting guidelines for microbiological studies.

In this study, we used two urogenital clinical isolates of N. gonorrhoeae from female patients, named, respectively, T9 (a serotype 9 strain), and T2 (a serotype 2 strain; Martin et al., 1986 (link)). These strains were grown, from frozen stocks (−80°C), on GC agar base (OXOID) supplemented with 1% (v/v) Polyvitox (OXOID) at 37°C in a 5% CO₂ incubator. The liquid medium used for growth was GC broth whose composition (per liter) is as follows: 15 g proteose peptone, 0.5 g corn starch, 4 g K₂HPO₄, 1 g KH₂PO₄, 5 g NaCl, 1% (v/v) Polyvitox (OXOID).
Thiostrepton (MIC 0.9 μg/mL; MBC 3.75 μg/mL), ampicillin (MIC 0.6 μg/mL; MBC 1.25 μg/mL), gentamicin (MIC 3.75 μg/mL; MBC 7.5 μg/mL), nalidixic acid (MIC 1.875 μg/mL; MBC 3.35 μg/mL), rifampicin (MIC 0.23 μg/mL; MBC 0.9 μg/mL), tetracycline (MIC 0.05 μg/mL; MBC 0.8 μg/mL), and DL-serine hydroxamate (MIC 1 mg/mL; MBC 4 mg/mL; all provided by Sigma-Aldrich) were used at the required concentration (values in brackets) in GC broth. Liquid cultures in GC broth were incubated at 37°C on rotary shaker at 200 rpm.

Phenotypic AST of C. jejuni isolates was performed using the microdilution method in cation-adjusted Mueller–Hinton broth with 5  % lysed horse blood, and minimum inhibitory concentrations (MICs) for erythromycin, ciprofloxacin, tetracycline, gentamicin, nalidixic acid and streptomycin (Sensititre, EUCAMP2; TREK Diagnostic Systems) were determined according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST; version 12.0; www.eucast.org). Strain C. jejuni ATCC 33560 was used as a quality control, according to the manufacturer’s instructions.