Antimicrobial resistance in enteric or urinary Escherichia coli is a risk factor for invasive E. coli infections. Due to widespread trimethoprim resistance amongst urinary E. coli and increased bacteraemia incidence, a national recommendation to prescribe nitrofurantoin for uncomplicated urinary tract infection was made in 2014. Nitrofurantoin resistance is reported in <6% urinary E. coli isolates in the UK, however, mechanisms underpinning nitrofurantoin resistance in these isolates remain unknown. This study aimed to identify the genetic basis of nitrofurantoin resistance in urinary E. coli isolates collected from north west London and then elucidate resistance-associated genetic alterations in available UK E. coli genomes. As a result, an algorithm was developed to predict nitrofurantoin susceptibility. Deleterious mutations and gene-inactivating insertion sequences in chromosomal nitroreductase genes nfsA and/or nfsB were identified in genomes of nine confirmed nitrofurantoin-resistant urinary E. coli isolates and additional 11 E. coli isolates that were highlighted by the prediction algorithm and subsequently validated to be nitrofurantoin-resistant. Eight categories of allelic changes in nfsA, nfsB, and the associated gene ribE were detected in 12412 E. coli genomes from the UK. Evolutionary analysis of these three genes revealed homoplasic mutations and explained the previously reported order of stepwise mutations. The mobile gene complex oqxAB, which is associated with reduced nitrofurantoin susceptibility, was identified in only one of the 12412 genomes. In conclusion, mutations and insertion sequences in nfsA and nfsB were leading causes of nitrofurantoin resistance in UK E. coli . As nitrofurantoin exposure increases in human populations, the prevalence of nitrofurantoin resistance in carriage E. coli isolates and those from urinary and bloodstream infections should be monitored.

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Background Emergency admissions for infection often lack initial diagnostic certainty. COVID-19 has highlighted a need for novel diagnostic approaches to indicate likelihood of viral infection in a pandemic setting. We aimed to derive and validate a blood transcriptional signature to detect viral infections, including COVID-19, among adults with suspected infection who presented to the emergency department. Methods Individuals (aged ≥18 years) presenting with suspected infection to an emergency department at a major teaching hospital in the UK were prospectively recruited as part of the Bioresource in Adult Infectious Diseases (BioAID) discovery cohort. Whole-blood RNA sequencing was done on samples from participants with subsequently confirmed viral, bacterial, or no infection diagnoses. Differentially expressed host genes that met additional filtering criteria were subjected to feature selection to derive the most parsimonious discriminating signature. We validated the signature via RT-qPCR in a prospective validation cohort of participants who presented to an emergency department with undifferentiated fever, and a second case-control validation cohort of emergency department participants with PCR-positive COVID-19 or bacterial infection. We assessed signature performance by calculating the area under receiver operating characteristic curves (AUROCs), sensitivities, and specificities. Findings A three-gene transcript signature, comprising HERC6, IGF1R , and NAGK , was derived from the discovery cohort of 56 participants with bacterial infections and 27 with viral infections. In the validation cohort of 200 participants, the signature differentiated bacterial from viral infections with an AUROC of 0·976 (95% CI 0·919−1·000), sensitivity of 97·3% (85·8−99·9), and specificity of 100% (63·1−100). The AUROC for C-reactive protein (CRP) was 0·833 (0·694−0·944) and for leukocyte count was 0·938 (0·840−0·986). The signature achieved higher net benefit in decision curve analysis than either CRP or leukocyte count for discriminating viral infections from all other infections. In the second validation analysis, which included SARS-CoV-2-positive participants, the signature discriminated 35 bacterial infections from 34 SARS-CoV-2-positive COVID-19 infections with AUROC of 0·953 (0·893−0·992), sensitivity 88·6%, and specificity of 94·1%. Interpretation This novel three-gene signature discriminates viral infections, including COVID-19, from other emergency infection presentations in adults, outperforming both leukocyte count and CRP, thus potentially providing substantial clinical utility in managing acute presentations with infection. Funding National Institute for Health Research, Medical Research Council, Wellcome Trust, and EU-FP7.

Background There is a critical need for rapid viral infection diagnostics to enable prompt case identification in pandemic settings and support targeted antimicrobial prescribing. Methods Using untargeted high-resolution liquid chromatography coupled with mass spectrometry, we compared the admission serum metabolome of emergency department patients with viral infections including COVID-19, bacterial infections, inflammatory conditions, and healthy controls. Sera from an independent cohort of emergency department patients admitted with viral or bacterial infections underwent profiling to validate findings. Associations between whole-blood gene expression and the identified metabolite of interest were examined. Findings. 3'-Deoxy-3',4'-didehydro-cytidine (ddhC), a free base of the only known human antiviral small molecule ddhC-triphosphate (ddhCTP), was detected for the first time in serum. When comparing 60 viral to 101 non-viral cases in the discovery cohort, ddhC was the most differentially abundant metabolite, generating an area under the receiver operating characteristic curve (AUC) of 0.954 (95% CI: 0.923-0.986). In the validation cohort, ddhC was again the most significantly differentially abundant metabolite when comparing 40 viral to 40 bacterial cases, generating an AUC of 0.81 (95% CI 0.708-0.915). Transcripts of viperin and CMPK2 , enzymes responsible for ddhCTP synthesis, were amongst the five genes most highly correlated to ddhC abundance. Conclusions The antiviral precursor molecule ddhC is detectable in serum and an accurate marker for acute viral infection. Interferon-inducible genes viperin and CMPK2 are implicated in ddhC production in vivo . These findings highlight a future diagnostic role for ddhC in viral diagnosis, pandemic preparedness, and acute infection management.