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.2021 Oct;2(10):e545-e554.
doi: 10.1016/s2666-5247(21)00118-x. Epub 2021 Jul 23.

Identification of antibiotic pairs that evade concurrent resistance via a retrospective analysis of antimicrobial susceptibility test results

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Identification of antibiotic pairs that evade concurrent resistance via a retrospective analysis of antimicrobial susceptibility test results

Andrew M Beckley et al. Lancet Microbe.2021 Oct.

Abstract

Background: Some antibiotic pairs display a property known as collateral sensitivity in which the evolution of resistance to one antibiotic increases sensitivity to the other. Alternating between collaterally sensitive antibiotics has been proposed as a sustainable solution to the problem of antibiotic resistance. We aimed to identify antibiotic pairs that could be considered for treatment strategies based on alternating antibiotics.

Methods: We did a retrospective analysis of 448 563 antimicrobial susceptibility test results acquired over a 4-year period (Jan 1, 2015, to Dec 31, 2018) from 23 hospitals in the University of Pittsburgh Medical Center (Pittsburgh, PA, USA) hospital system. We used a score based on mutual information to identify pairs of antibiotics displaying disjoint resistance, wherein resistance to one antibiotic is commonly associated with susceptibility to the other and vice versa. We applied this approach to the six most frequently isolated bacterial pathogens (Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Enterococcus faecalis, Pseudomonas aeruginosa, andProteus mirabilis) and subpopulations of each created by conditioning on resistance to individual antibiotics. To identify higher-order antibiotic interactions, we predicted rates of multidrug resistance for triplets of antibiotics using Markov random fields and compared these to the observed rates.

Findings: We identified 69 antibiotic pairs displaying varying degrees of disjoint resistance for subpopulations of the six bacterial species. However, disjoint resistance was rarely conserved at the species level, with only 6 (0·7%) of 875 antibiotic pairs showing evidence of disjoint resistance. Instead, more than half of antibiotic pairs (465 [53·1%] of 875) exhibited signatures of concurrent resistance, whereby resistance to one antibiotic is associated with resistance to another. We found concurrent resistance to extend to more than two antibiotics, with observed rates of resistance to three antibiotics being higher than predicted from pairwise information alone.

Interpretation: The high frequency of concurrent resistance shows that bacteria have means of counteracting multiple antibiotics at a time. The almost complete absence of disjoint resistance at the species level implies that treatment strategies based on alternating between antibiotics might require subspecies level pathogen identification and be limited to a few antibiotic pairings.

Funding: US National Institutes of Health.

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Conflict of interest statement

Declaration of interests We declare no competing interests. Data sharing Individual participant data is not sharable due to University of Pittsburgh institutional review board restrictions. Aggregated resistance data for the pairs and triplets of antibiotics analysed in this study are provided in appendix 2.

Figures

Figure 1:
Figure 1:. Characteristics of the antimicrobial susceptibility test dataset
(A) Species composition of isolates in the dataset (2015–18; total n=448 563). (B) Isolation sources by species. (C) Frequency of testing of different antibiotics (grouped by antibiotic class) by species, in the two 2-year time periods (n=216 095 in 2015–16; n=232 468 in 2017–18). Testing frequency for each species is shown in the top row for 2015–16 and in the bottom row for the 2017–18 dataset. Numbers of isolates of each species in each time period are shown to the right.E cloacae=Enterobacter cloacae. E coli=Escherichia coli. E faecalis=Enterococcus faecalis. K aerogenes=Klebsiella aerogenes. K oxytoca=Klebsiella oxytoca. K pneumoniae=Klebsiella pneumoniae. P aeruginosa=Pseudomonas aeruginosa. P mirabilis=Proteus mirabilis. S agalactiae=Streptococcus agalactiae. S aureus=Staphylococcus aureus. S epidermidis=Staphylococcus epidermidis. S marcescens=Serratia marcescens. AMC=amoxicillin-clavulanic acid. AMK=amikacin. AMP=ampicillin. ATM=aztreonam. CAZ=ceftazidime. CEF=cefalotin. CFZ=cefazolin. CIP=ciprofloxacin. CLI=clindamycin. CPT=ceftaroline. CRO=ceftriaxone. CTX=cefotaxime. CXM=cefuroxime. DAP=daptomycin. DOR=doripenem. DOX=doxycycline. ERY=erythromycin. ETP=ertapenem. FEP=cefepime. FOX=cefoxitin. GEN=gentamicin. IPM=imipenem. LVX=levofloxacin. LZD=linezolid. MEM=meropenem. MXF=moxifloxacin. NIT=nitrofurantoin. NOR=norfloxacin. OX=oxacillin. PEN=penicillin. PIP=piperacillin. Q-D=quinupristin–dalfopristin. RIF=rifampicin. SAM=ampicillin-sulbactam. SXT=sulfamethoxazole–trimethoprim. TET=tetracycline. TGC=tigecycline. TIM=ticarcillin-clavulanic acid. TOB=tobramycin. TZP=piperacillin–tazobactam. VAN=vancomycin.
Figure 2:
Figure 2:. Rarely observed antibiotic resistances by species
Rates of resistance (<1%) are shown for antibiotics tested at least 1000 times per first patient isolate during a 4-year period (2015–18). Data above each bar are n/N (ie, number of resistant isolates divided by the total number of isolates tested). AMC=amoxicillin–clavulanic acid. AMK=amikacin. AMP=ampicillin. CPT=ceftaroline. CRO=ceftriaxone. CTX=cefotaxime. DAP=daptomycin. DOX=doxycycline. ETP=ertapenem. FEP=cefepime. GEN=gentamicin. IPM=imipenem. LVX=levofloxacin. LZD=linezolid. MEM=meropenem. NIT=nitrofurantoin. pEN=Penicillin. Q-D=quinupristin–dalfopristin. SXT=sulfamethoxazole–trimethoprim. TGC=tigecycline. TOB=tobramycin. TZP=piperacillin–tazobactam. VAN=vancomycin.
Figure 3:
Figure 3:. Heatmaps for six species showing the MISs for pairs of antibiotics in 2015–16 and 2017–18
2015–16 is shown in the upper right of each heatmap and 2017–18 in the lower left; the numbers along each side denote the total number of times a drug was tested. Negative MISs (blue) correspond to disjoint resistance, positive MISs (red) correspond to concurrent resistance, and MISs near zero (white) imply independence. Only three cases of statistically significant negative MISs were observed. Antibiotic classes often displayed intra-class concurrent resistance, although many positive MISs were observed between antibiotics belonging to different classes. Gray boxes designate pairs that were tested together less than 100 times, and dots signify no statistical significance (Fisher Exact test, Bonferroni corrected p≥0.01). MIS=mutual information score. AMC=amoxicillin–clavulanic acid. AMK=amikacin. AMP=ampicillin. ATM=aztreonam. CAZ=ceftazidime. CFZ=cefazolin. CIP=ciprofloxacin. CLI=clindamycin. CRO=ceftriaxone. CXM=cefuroxime. ERY=erythromycin. FEP=cefepime. GEN=gentamicin. IPM=imipenem. LVX=levofloxacin. MEM=meropenem. NIT=nitrofurantoin. OX=oxacillin. RIF=rifampicin. SAM=ampicillin–sulbactam. SXT=sulfamethoxazole-trimethoprim. TET=tetracycline. TOB=tobramycin. TZP=piperacillin-tazobactam. VAN=vancomycin.
Figure 4:
Figure 4:. Network display of antibiotic pairs with negative MISs identified in the subset of isolates from each species that were resistant to a given antibiotic
Antibiotic pairs are denoted by connected nodes and negative MISs are denoted by edges (ie, connecting lines). Conditioning on resistance to an antibiotic (titles) revealed disjoint resistances that were undiscovered in the analysis of the entire species (figure 3). Antibiotic pairs are shown with MISs of less than −0.05 in both 2015–16 and 2017–18, with dotted lines indicating statistical significance in only one of the 2-year periods and solid lines indicating statistical significance in both of the 2-year periods (Fisher’s Exact test, Bonferroni corrected p<0.01). Nodes are coloured by antibiotic class. MIS=mutual information score. AMC=amoxicillin–clavulanic acid. ATM=aztreonam. CFZ=cefazolin. FEP=cefepime. CAZ=ceftazidime. CIP=ciprofloxacin. CLI=clindamycin. CRO=ceftriaxone. CXM=cefuroxime. ETP=ertapenem. GEN=gentamicin. IPM=imipenem. LVX=levofloxacin. MEM=meropenem. NIT=nitrofurantoin. OX=oxacillin. SAM=ampicillin–sulbactam. SXT=sulfamethoxazole–trimethoprim. TET=tetracycline. TOB=tobramycin. TZP=piperacillin–tazobactam.
Figure 5:
Figure 5:. Predicted resistance rates for triplets of antibiotics inEscherichia coli
A Markov random field was used to predict resistance rates for triplets of antibiotics based on knowledge of the pairs alone. Each point represents one of eight possible susceptibility results (0–3 resistances) for three antibiotics (n=556 triplet combinations), with smaller points denoting no statistical significance (one-sided binomial test, Bonferroni corrected p≥0.01) and larger points denoting statistical significance (p<0.01). Points above the diagonal line indicate overpredicted resistance rates, points below the line indicate underpredicted rates. Data for four other pathogens are shown in appendix 1 (p 7). All results are shown for 2015–16.
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