Systematic Mapping of Antibiotic Resistance Genes to Clinically Relevant Microorganisms Using Curated Databases and Guidelines
Dr. Safedin Sajo Beqaj, Dr. Rojeet Shrestha, Dr. Puja Neopane, David Le, Kairav Patel
June 24, 2026
Background
Antibiotic resistance genes (ARGs) are segments of bacterial DNA that confer resistance to antimicrobial agents, arising through spontaneous mutation or acquired via horizontal gene transfer [1,2]. The CDC estimates that antimicrobial-resistant infections cause more than 2.8 million infections and 35,000 deaths annually in the United States [3,4]. Traditional culture-based susceptibility testing remains the diagnostic standard but typically requires 3-5 days, can miss non-culturable or fastidious organisms, and does not reveal the underlying resistance mechanism. Genotypic detection of ARGs (PCR, next-generation sequencing, microarrays, and related molecular methods) provides results in 1–5 hours, can detect resistance genes from non-culturable or low-abundance organisms, and identifies the specific mechanism conferring resistance (e.g., gyrA/parC for fluoroquinolone resistance, mecA for methicillin resistance, blaKPC for carbapenem resistance). Molecular ARG detection alone, however, cannot determine which organism in a polymicrobial specimen carries a given gene an attribution gap that LDS®Rx is designed to close.
LDS®Rx and the ARG-Pathogen Mapping Database
Medical Database has developed LDS®Rx, an interpretation platform for syndromic infectious disease panels and antibiotic stewardship. LDS®Rx incorporates a proprietary ARG-to-pathogen mapping database that links every resistance gene identified by molecular testing to its most likely host organism(s), producing organism-specific resistance reporting for Urinary Tract Infection (UTI), Wound and skin, Gastrointestinal (GI), Respiratory, and Sexually Transmitted Infection (STI) syndromic panels. Mappings were built from the Comprehensive Antibiotic Resistance Database (CARD; ~1,600 catalogued ARGs) [5,6,7], the NCBI / National Library of Medicine Bacterial Antimicrobial Resistance Reference Gene Database (AMRFinderPlus), the EMBL-EBI Antimicrobial Resistance Portal (2020–2025 data), peer-reviewed literature (PubMed / PubMed Central) [8-23], and current CLSI [24] and IDSA (2024) [25] treatment guidelines. Each candidate gene was confirmed to encode a functional resistance mechanism, consolidated into canonical gene families, and mapped to all clinically significant pathogens reported to carry it within each specimen type.
Database Coverage
The LDS®Rx ARG Mapping Database comprises 43 canonical antibiotic resistance genes (ARGs) and gene families, consolidated from 109 reported resistance gene targets spanning 15 antimicrobial resistance mechanism classes. These genes are mapped to 94 clinically significant pathogens represented across five syndromic testing panels: Urinary Tract Infection (UTI), Wound and Skin, Gastrointestinal (GI), Respiratory, and Sexually Transmitted Infection (STI). Collectively, the database contains 1,853 curated ARG–pathogen linked.
Table 1 details each ARG, its resistance class and mechanism, the antibiotic classes affected, and the number and proportion of database pathogens to which it is mapped. To our knowledge, this remains the first database of its kind, built from peer-reviewed publications and publicly available ARG databases from governmental and private sources, and specifically designed to operate within a clinical molecular diagnostic workflow.
Table 1. Antibiotic resistance genes (ARGs) and gene families in the LDS®Rx mapping database, organized by resistance class, with associated resistance mechanisms, antibiotic classes affected, and the number and percentage of mapped pathogens (n = 94).
| No. | Resistance Class | Gene / ARG (consolidated) | Resistance Mechanism | Antibiotic Class(es) Affected | Pathogens Mapped (n) | % of Database Pathogens (94) |
|---|---|---|---|---|---|---|
| 1 | Aminoglycoside Resistance | AAC(3)-IV | Aminoglycoside-modifying enzyme (acetyltransferase) | Gentamicin, tobramycin | 53 | 56.4% |
| 2 | aac(6')-Ib-cr | Bifunctional aminoglycoside/fluoroquinolone-modifying enzyme | Amikacin, tobramycin; reduced fluoroquinolone susceptibility | 53 | 56.4% | |
| 3 | AAC(6')-Ie/APH(2") | Bifunctional aminoglycoside-modifying enzyme | Gentamicin, tobramycin, amikacin | 57 | 60.6% | |
| 4 | aadA | Aminoglycoside nucleotidyltransferase | Streptomycin, spectinomycin | 53 | 56.4% | |
| 5 | ANT(2") | Aminoglycoside nucleotidyltransferase | Gentamicin, tobramycin, kanamycin | 53 | 56.4% | |
| 6 | ANT(1) | Aminoglycoside nucleotidyltransferase | Streptomycin, spectinomycin | 53 | 56.4% | |
| 7 | APH(3') | Aminoglycoside phosphotransferase | Kanamycin, neomycin | 53 | 56.4% | |
| 8 | APH(2") | Aminoglycoside phosphotransferase | Gentamicin, tobramycin | 53 | 56.4% | |
| 9 | Beta-Lactamase / ESBL / AmpC | AmpC (ACC/ampC) | AmpC cephalosporinase | Cephalosporins, cephamycins | 41 | 43.6% |
| 10 | CTX-M (ESBL) | Extended-spectrum beta-lactamase (ESBL) | Penicillins, cephalosporins, monobactams | 47 | 50.0% | |
| 11 | SHV (ESBL) | Extended-spectrum beta-lactamase (ESBL) | Penicillins, cephalosporins | 43 | 45.7% | |
| 12 | TEM (ESBL) | Extended-spectrum beta-lactamase (ESBL) | Penicillins, cephalosporins | 46 | 48.9% | |
| 13 | VEB | Extended-spectrum beta-lactamase (ESBL) | Penicillins, cephalosporins, aztreonam | 42 | 44.7% | |
| 14 | ACT/DHA (AmpC) | Plasmid-mediated AmpC beta-lactamase | Cephalosporins, cephamycins | 42 | 44.7% | |
| 15 | FOX (AmpC) | Plasmid-mediated AmpC beta-lactamase | Cefoxitin, cephamycins | 42 | 44.7% | |
| 16 | Carbapenemase | KPC | Carbapenemase (Class A) | Carbapenems, penicillins, cephalosporins | 42 | 44.7% |
| 17 | NDM | Carbapenemase (metallo-beta-lactamase, Class B) | Carbapenems, penicillins, cephalosporins | 42 | 44.7% | |
| 18 | VIM | Carbapenemase (metallo-beta-lactamase, Class B) | Carbapenems, penicillins, cephalosporins | 42 | 44.7% | |
| 19 | IMP | Carbapenemase (metallo-beta-lactamase, Class B) | Carbapenems, penicillins, cephalosporins | 42 | 44.7% | |
| 20 | OXA-48-like (carbapenemase) | Carbapenemase (Class D, oxacillinase) | Carbapenems, penicillins | 43 | 45.7% | |
| 21 | GES | Carbapenemase / ESBL (Class A) | Carbapenems, penicillins, cephalosporins | 42 | 44.7% | |
| 22 | Fluoroquinolone Resistance | gyrA | DNA gyrase target-site mutation | Fluoroquinolones | 71 | 75.5% |
| 23 | parC | Topoisomerase IV target-site mutation | Fluoroquinolones | 62 | 66.0% | |
| 24 | qnr | Plasmid-mediated quinolone target protection | Fluoroquinolones | 52 | 55.3% | |
| 25 | oqxAB | RND-family multidrug efflux pump | Fluoroquinolones, tigecycline, nitrofurantoin | 36 | 38.3% | |
| 26 | Colistin Resistance | mcr-1 | Phosphoethanolamine transferase (plasmid-mediated) | Colistin / polymyxins | 41 | 43.6% |
| 27 | Sulfonamide Resistance | sul (sul1/sul2) | Dihydropteroate synthase (drug-insensitive) | Sulfonamides | 55 | 58.5% |
| 28 | Trimethoprim Resistance | dfr (dfrA1/dfrA1/dfrA5) | Dihydrofolate reductase (drug-insensitive) | Trimethoprim | 55 | 58.5% |
| 29 | Nitrofurantoin Resistance | nfsA | Nitroreductase loss-of-function | Nitrofurantoin | 51 | 54.3% |
| 30 | Fosfomycin Resistance | fosA | Fosfomycin-modifying enzyme (glutathione transferase) | Fosfomycin | 42 | 44.7% |
| 31 | Tetracycline Resistance | tetB | Tetracycline efflux pump | Tetracyclines | 56 | 59.6% |
| 32 | tetM | Ribosomal protection protein | Tetracyclines | 78 | 83.0% | |
| 33 | tetO | Ribosomal protection protein | Tetracyclines | 67 | 71.3% | |
| 34 | tetS | Ribosomal protection protein | Tetracyclines | 55 | 58.5% | |
| 35 | tet (general) | Tetracycline efflux / ribosomal protection (unspecified) | Tetracyclines | 75 | 79.8% | |
| 36 | Macrolide / Lincosamide / Oxazolidinone (MLSB) | erm (ermA/B/C) | Ribosomal target methylase (rRNA methyltransferase) | Macrolides, lincosamides, streptogramin B (MLSB) | 26 | 27.7% |
| 37 | mefA | Macrolide efflux pump | Macrolides (14-, 15-membered) | 6 | 6.4% | |
| 38 | cfr | 23S rRNA methyltransferase (PhLOPSA phenotype) | Phenicols, lincosamides, oxazolidinones (linezolid), pleuromutilins, streptogramin A | 18 | 19.1% | |
| 39 | Methicillin Resistance | mecA/mecC | Altered penicillin-binding protein (PBP2a) | Beta-lactams (methicillin/oxacillin) – confers MRSA | 6 | 6.4% |
| 40 | femA | Accessory factor for peptidoglycan cross-linking (mecA-associated) | Beta-lactams (methicillin) – modulates MRSA expression | 6 | 6.4% | |
| 41 | Vancomycin Resistance | vanA/B/C/M | Altered cell-wall precursor (D-Ala-D-Lac/Ser ligase) | Vancomycin, teicoplanin (glycopeptides) | 7 | 7.4% |
| 42 | Other / H. pylori-specific | 23S rRNA mutation (clarithromycin) | 23S rRNA target-site mutation | Clarithromycin (H. pylori) | 3 | 3.2% |
| 43 | Virulence Marker (co- reported) | PVL (virulence marker) | Pore-forming cytotoxin (virulence factor, not resistance) | Not applicable – virulence marker, often co-reported with mecA | 1 | 1.1% |
| Total | 43 canonical ARGs (109 raw gene targets) | — | — | 1853 | — |
Table 2 summarizes ARG and pathogen coverage by syndromic panels. The Wound panel covers the largest pathogen set (51 pathogens, 1,281 associations), followed by GI (44 pathogens, 1,280 associations), UTI (41 pathogens, 1,231 associations), Respiratory (30 pathogens, 630 associations), and STI (20 pathogens, 102 associations). All 43 ARGs are represented in the UTI, Wound, and GI panels; 39 ARGs in the Respiratory panel; and 37 ARGs in the STI panel. Of the 94 total pathogens in the database, 90 (96%) are linked to at least one syndromic panel, and common Enterobacteriaceae such as Escherichia coli carry mappings to 35 of the 43 ARGs (81%), reflecting their broad intrinsic and acquired resistance repertoire.
Table 2. Summary statistics of ARG-pathogen mapping by syndromic diagnostic panel in the LDS®Rx database (94 pathogens, 43 ARGs, 1,853 total associations).
| Syndromic Panel | Pathogens Covered (n) | % of Database Pathogens (94) | ARGs Mapped (n) | % of Database ARGs (43) | ARG-Pathogen Associations (n) | % of Total Associations |
|---|---|---|---|---|---|---|
| UTI | 41 | 43.6% | 43 | 100.0% | 1231 | 66.4% |
| Wound | 51 | 54.3% | 43 | 100.0% | 1281 | 69.1% |
| GI | 44 | 46.8% | 39 | 90.7% | 1280 | 69.1% |
| Respiratory | 30 | 31.9% | 43 | 100.0% | 630 | 34.0% |
| STI | 20 | 21.3% | 37 | 86.0% | 102 | 5.5% |
| Total / Unique | 94 | 100% | 43 | 100% | 1853 | 100% |
The coverage of genes and drug classes to number of pathogens per syndromic panel is shown in the table 3.
Table 3. ARG-by-syndromic-panel coverage matrix, indicating which of the 43 mapped ARGs are represented (✓) within each panel’s pathogen set, with the total number of panels covered for each gene.
| Resistance Class | Gene / ARG | UTI | Wound | GI | Respiratory | STI | # Panels Covered |
|---|---|---|---|---|---|---|---|
| Aminoglycoside Resistance | AAC(3)-IV | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| aac(6')-Ib-cr | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| AAC(6')-Ie/APH(2") | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| aadA | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| ANT(2") | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| ANT(1) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| APH(3') | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| APH(2") | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| Beta-Lactamase / ESBL / AmpC | AmpC (ACC/ampC) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| CTX-M (ESBL) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| SHV (ESBL) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| TEM (ESBL) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| VEB | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| ACT/DHA (AmpC) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| FOX (AmpC) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| Carbapenemase | KPC | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| NDM | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| VIM | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| IMP | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| OXA-48-like (carbapenemase) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| GES | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| Fluoroquinolone Resistance | gyrA | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| parC | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| qnr | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| oqxAB | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| Colistin Resistance | mcr-1 | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| Sulfonamide Resistance | sul (sul1/sul2) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| Trimethoprim Resistance | dfr (dfrA1/dfrA1/dfrA5) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| Nitrofurantoin Resistance | nfsA | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| Fosfomycin Resistance | fosA | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| Tetracycline Resistance | tetB | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| tetM | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| tetO | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| tetS | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| tet (general) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| Macrolide / Lincosamide / Oxazolidinone (MLSB) | erm (ermA/B/C) | ✓ | ✓ | ✓ | ✓ | ✓ | 5 |
| mefA | ✓ | ✓ | - | ✓ | - | 3 | |
| cfr | ✓ | ✓ | ✓ | ✓ | ✓ | 5 | |
| Methicillin Resistance | mecA/mecC | ✓ | ✓ | - | ✓ | - | 3 |
| femA | ✓ | ✓ | - | ✓ | - | 3 | |
| Vancomycin Resistance | vanA/B/C/M | ✓ | ✓ | ✓ | ✓ | - | 4 |
| Other / H. pylori-specific | 23S rRNA mutation (clarithromycin) | ✓ | ✓ | ✓ | ✓ | - | 4 |
| Virulence Marker (co-reported) | PVL (virulence marker) | ✓ | ✓ | - | ✓ | - | 3 |
Clinical Significance
Polymicrobial infections are common in clinical practice for example, 10-15% of polymicrobial infections occurs in outpatient UTI cases and is substantially more frequent in catheter-associated UTIs, diabetic patients, and long-term care residents [26,27] making accurate ARG-to-organism attribution essential for appropriate therapy selection. Similarly, wound infections are frequently polymicrobial, and high polymicrobial bacterial loads can delay wound closure and accelerate the emergence of antibiotic-resistant strains [28,29]. Multidrug resistance (MDR) rates among common uropathogens are substantial (E. coli ~74%, K. pneumoniae ~49%, overall uropathogens ~71%) [30], underscoring the clinical stakes of resistance reporting. LDS®Rx applies a “no ARG without a confirmed pathogen” policy, reporting a resistance gene only when a corresponding pathogen is detected in the same specimen, reducing the risk of misattributed resistance signals. A 2025 systematic review found that combining antimicrobial stewardship programs with rapid molecular diagnostics reduced time-to-appropriate-therapy, length of stay, and mortality compared with stewardship or rapid diagnostics alone [31,32,33].
These findings align with the global surveillance picture: the WHO’s 2025 Global Antimicrobial Resistance and Use Surveillance System (GLASS) report documented over 23 million resistant infection episodes across 104 countries, with roughly 1 in 6 laboratory-confirmed bacterial infections showing resistance to commonly used antibiotics. In the U.S., CDC’s Antibiotic Resistance Laboratory Network (ARLN) and the National Healthcare Safety Network (NHSN) increasingly require resistance-gene surveillance reporting [4,34]. Within this landscape, LDS®Rx occupies a distinct niche relative to large research repositories such as CARD (~1,600 catalogued ARGs) [35,36]: rather than serving as a general reference catalog, LDS®Rx operationalizes ARG-pathogen mapping directly into clinical syndromic panel workflows, functioning as a genotypic equivalent of a phenotypic antibiogram with a turnaround measured in hours rather than the 48–72 hours required for culture-based susceptibility testing [37].
Limitations and Future Directions
The current mapping reflects literature and database curation through 2025 and will require periodic updates as new resistance mechanisms and gene variants are described. Source databases are weighted toward data from high-income countries, which may limit applicability to regions with different resistance epidemiology. Because ARG mapping is genotypic, discordance between detected genes and observed phenotypic susceptibility can occur (e.g., silent or nonexpressed genes) [38,39]; LDS®Rx reporting should be interpreted alongside clinical context and, where available, phenotypic susceptibility results. Future development will incorporate machine-learning-based genotype-to-phenotype prediction and extend mapping to additional specimen types, including blood, bronchoalveolar lavage (BAL), and cerebrospinal fluid (CSF).
Conclusion
The expanded LDS®Rx ARG-to-pathogen mapping database now covering 43 canonical resistance genes across 94 pathogens and 1,853 documented associations spanning 15 resistance mechanism classes represents a significant advance in translating molecular resistance data into actionable, organism-specific clinical guidance. By linking genotypic resistance findings directly to syndromic panel results, LDS®Rx supports a new standard of precision in antibiotic stewardship and infection management for the laboratories and clinicians it serves.
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