Harvesting and amplifying gene cassettes confers cross-resistance to critically important antibiotics.

Amikacin and piperacillin/tazobactam are frequent antibiotic choices to treat bloodstream infection, which is commonly fatal and most often caused by bacteria from the family Enterobacterales. Here we show that two gene cassettes located side-by-side in and ancestral integron similar to In37 have been "harvested" by insertion sequence IS26 as a transposon that is widely disseminated among the Enterobacterales. This transposon encodes the enzymes AAC(6')-Ib-cr and OXA-1, reported, respectively, as amikacin and piperacillin/tazobactam resistance mechanisms. However, by studying bloodstream infection isolates from 769 patients from three hospitals serving a population of 1.2 million people in South West England, we show that increased enzyme production due to mutation in an IS26/In37-derived hybrid promoter or, more commonly, increased transposon copy number is required to simultaneously remove these two key therapeutic options; in many cases leaving only the last-resort antibiotic, meropenem. These findings may help improve the accuracy of predicting piperacillin/tazobactam treatment failure, allowing stratification of patients to receive meropenem or piperacillin/tazobactam, which may improve outcome and slow the emergence of meropenem resistance.

Improving nitrofurantoin resistance prediction in Escherichia coli from whole-genome sequence by integrating NfsA/B enzyme assays.

Nitrofurantoin resistance in Escherichia coli is primarily caused by mutations damaging two enzymes, NfsA and NfsB. Studies based on small isolate collections with defined nitrofurantoin MICs have found significant random genetic drift in nfsA and nfsB, making it extremely difficult to predict nitrofurantoin resistance from whole-genome sequence (WGS) where both genes are not obviously disrupted by nonsense or frameshift mutations or insertional inactivation. Here, we report a WGS survey of 200 oqxAB-negative E. coli from community urine samples, of which 34 were nitrofurantoin resistant. We characterized individual non-synonymous mutations seen in nfsA and nfsB among this collection using complementation cloning and NfsA/B enzyme assays in cell extracts. We definitively identified R203C, H11Y, W212R, A112E, and A112T in NfsA and R121C, Q142H, F84S, P163H, W46R, K57E, and V191G in NfsB as amino acid substitutions that reduce enzyme activity sufficiently to cause resistance. In contrast, E58D, I117T, K141E, L157F, A172S, G187D, and A188V in NfsA and G66D, M75I, V93A, and A174E in NfsB are functionally silent in this context. We identified that 9/166 (5.4%) nitrofurantoin-susceptible isolates were "pre-resistant," defined as having loss of function mutations in nfsA or nfsB. Finally, using NfsA/B enzyme assays and proteomics, we demonstrated that 9/34 (26.5%) ribE wild-type nitrofurantoin-resistant isolates also carried functionally wild-type nfsB or nfsB/nfsA. In these cases, NfsA/B activity was reduced through downregulated gene expression. Our biological understanding of nitrofurantoin resistance is greatly improved by this analysis but is still insufficient to allow its reliable prediction from WGS data.

Trade-Offs between Antibacterial Resistance and Fitness Cost in the Production of Metallo-ß-Lactamases by Enteric Bacteria Manifest as Sporadic Emergence of Carbapenem Resistance in a Clinical Setting.

Meropenem is a clinically important antibacterial reserved for treatment of multiresistant infections. In meropenem-resistant bacteria of the family Enterobacterales, NDM-1 is considerably more common than IMP-1, despite both metallo-ß-lactamases (MBLs) hydrolyzing meropenem with almost identical kinetics. We show that blaNDM-1 consistently confers meropenem resistance in wild-type Enterobacterales, but blaIMP-1 does not. The reason is higher blaNDM-1 expression because of its stronger promoter. However, the cost of meropenem resistance is reduced fitness of blaNDM-1-positive Enterobacterales. In parallel, from a clinical case, we identified multiple Enterobacter spp. isolates carrying a plasmid-encoded blaNDM-1 having a modified promoter region. This modification lowered MBL production to a level associated with zero fitness cost, but, consequently, the isolates were not meropenem resistant. However, we identified a Klebsiella pneumoniae isolate from this same clinical case carrying the same blaNDM-1 plasmid. This isolate was meropenem resistant despite low-level NDM-1 production because of a ramR mutation reducing envelope permeability. Overall, therefore, we show how the resistance/fitness trade-off for MBL carriage can be resolved. The result is sporadic emergence of meropenem resistance in a clinical setting.

Limited phylogenetic overlap between fluoroquinolone-resistant Escherichia coli isolated on dairy farms and those causing bacteriuria in humans living in the same geographical region.

BACKGROUND: Our primary aim was to test whether cattle-associated fluoroquinolone-resistant (FQ-R) Escherichia coli found on dairy farms are closely phylogenetically related to those causing bacteriuria in humans living in the same 50 × 50 km geographical region suggestive of farm-human sharing. Another aim was to identify risk factors for the presence of FQ-R E. coli on dairy farms. METHODS: FQ-R E. coli were isolated during 2017-18 from 42 dairy farms and from community urine samples. Forty-two cattle and 489 human urinary isolates were subjected to WGS, allowing phylogenetic comparisons. Risk factors were identified using a Bayesian regularization approach. RESULTS: Of 489 FQ-R human isolates, 255 were also third-generation-cephalosporin-resistant, with strong genetic linkage between aac(6')Ib-cr and blaCTX-M-15. We identified possible farm-human sharing for pairs of ST744 and ST162 isolates, but minimal core genome SNP distances were larger between farm-human pairs of ST744 and ST162 isolates (71 and 63 SNPs, respectively) than between pairs of isolates from different farms (7 and 3 SNPs, respectively). Total farm fluoroquinolone use showed a positive association with the odds of isolating FQ-R E. coli, while total dry cow therapy use showed a negative association. CONCLUSIONS: This work suggests that FQ-R E. coli found on dairy farms have a limited impact on community bacteriuria within the local human population. Reducing fluoroquinolone use may reduce the on-farm prevalence of FQ-R E. coli and this reduction may be greater when dry cow therapy is targeted to the ecology of resistant E. coli on the farm.

A Bayesian Model Based on Local Phenotypic Resistance Data to Inform Empiric Antibiotic Escalation Decisions.

INTRODUCTION: Clinicians commonly escalate empiric antibiotic therapy due to poor clinical progress without microbiology guidance. When escalating, they should take account of how resistance to an initial antibiotic affects the probability of resistance to subsequent options. The term "escalation antibiogram" (EA) has been coined to describe this concept. One difficulty when applying the EA concept to clinical practice is understanding the uncertainty in results and how this changes for specific patient subgroups. METHODS: A Bayesian model was developed to estimate antibiotic resistance rates in Gram-negative bloodstream infections based on phenotypic resistance data. The model generates a series of "credible" curves to fit the resistance data, each with the same probability of representing the true rate given the inherent uncertainty. To avoid overfitting, an integrated penalisation term adaptively smooths the curves given the level of evidence. RESULTS: Rates of resistance to empiric first-choice and potential escalation antibiotics were calculated for the whole hospitalised population based on 10,486 individual bloodstream infections, and for a range of specific patient groups, including ICU (intensive care unit), haematolo-oncology, and paediatric patients. The model generated an expected value (posterior mean) with 95% credible interval to illustrate uncertainty, based on the size of the patient subgroup. For example, the posterior means of piperacillin/tazobactam resistance rates in Gram-negative bloodstream infection are different between patients on ICU and the general hospital population: 27.3% (95% CI 18.1-37.2 vs. 13.4% 95% CI 11.0-16.1) respectively. The model can also estimate the probability of inferiority between two antibiotics for a specific patient population. Differences in optimal escalation antibiotic options between specific patient groups were noted. CONCLUSIONS: EA analysis informed by our Bayesian model is a useful tool to support empiric antibiotic switches, providing an estimate of local resistance rates, and a comparison of antibiotic options with a measure of the uncertainty in the data. We demonstrate that EAs calculated for the whole hospital population cannot be assumed to apply to specific patient group.