Activity fingerprinting of AMR ß-lactamase towards a fast and accurate diagnosis.

Antibiotic resistance has become a serious threat to global public health and economic development. Rapid and accurate identification of a patient status for antimicrobial resistance (AMR) are urgently needed in clinical diagnosis. Here we describe the development of an assay method for activity fingerprinting of AMR ß-lactamases using panels of 7 ß-lactam antibiotics in 35 min. New Deli Metallo ß-lactamase-1 (NDM-1) and penicillinase were demonstrated as two different classes of ß-lactamases. The panel consisted of three classes of antibiotics, including: penicillins (penicillin G, piperacillin), cephalosporins (cefepime, ceftriaxone, cefazolin) and carbapenems (meropenem and imipenem). The assay employed a scheme combines the catalytic reaction of AMR ß-lactamases on antibiotic substrates with a flow-injected thermometric biosensor that allows the direct detection of the heat generated from the enzymatic catalysis, and eliminates the need for custom substrates and multiple detection schemes. In order to differentiate classes of ß-lactamases, characterization of the enzyme activity under different catalytic condition, such as, buffer composition, ion strength and pH were investigated. This assay could provide a tool for fast diagnosis of patient AMR status which makes possible for the future accurate treatment with selected antibiotics.

Rapid Detection of Multiple Classes of ß-Lactam Antibiotics in Blood Using an NDM-1 Biosensing Assay.

Currently, assays for rapid therapeutic drug monitoring (TDM) of ß-lactam antibiotics in blood, which might be of benefit in optimizing doses for treatment of critically ill patients, remain challenging. Previously, we developed an assay for determining the penicillin-class antibiotics in blood using a thermometric penicillinase biosensor. The assay eliminates sample pretreatment, which makes it possible to perform semicontinuous penicillin determinations in blood. However, penicillinase has a narrow substrate specificity, which makes it unsuitable for detecting other classes of ß-lactam antibiotics, such as cephalosporins and carbapenems. In order to assay these classes of clinically useful antibiotics, a novel biosensor was developed using New Delhi metallo-ß-lactamase-1 (NDM-1) as the biological recognition layer. NDM-1 has a broad specificity range and is capable of hydrolyzing all classes of ß-lactam antibiotics in high efficacy with the exception of monobactams. In this study, we demonstrated that the NDM-1 biosensor was able to quantify multiple classes of ß-lactam antibiotics in blood plasma at concentrations ranging from 6.25 mg/L or 12.5 mg/L to 200 mg/L, which covered the therapeutic concentration windows of the tested antibiotics used to treat critically ill patients. The detection of ceftazidime and meropenem was not affected by the presence of the ß-lactamase inhibitors avibactam and vaborbactam, respectively. Furthermore, both free and protein-bound ß-lactams present in the antibiotic-spiked plasma samples were detected by the NDM-1 biosensor. These results indicated that the NDM-1 biosensor is a promising technique for rapid TDM of total ß-lactam antibiotics present in the blood of critically ill patients.

Rapid personalized AMR diagnostics using two-dimensional antibiotic resistance profiling strategy employing a thermometric NDM-1 biosensor.

Antimicrobial resistance (AMR) threatens global public health and modern surgical medicine. Expression of ß-lactamase genes is the major mechanism by which pathogens become antibiotic resistant. Pathogens expressing extended spectrum ß-lactamases (ESBL) and carbapenemases (CP) are especially difficult to treat and are associated with increased hospitalization and mortality rates. Despite considerable effort, identification of ESBLs and CPs in a clinically relevant timeframe remains challenging. In this study, a two-dimensional AMR profiling assay strategy was developed employing panels of antibiotics (penicillins, cephamycins, oximino-cephalosporins and carbapenems) and ß-lactamases inhibitors (avibactam and EDTA). The assay required the development of a novel biosensor that employed New Delhi metallo-ß-lactamase-1 (NDM-1) as the sensing element. Functionally probing ß-lactamase activity using substrates and inhibitors combinatorically increased the informational content that enabled the development of assays capable of simultaneous, differential identification of multiple ß-lactamases expressed in a single bacterial isolate. More specifically, the assay enabled the simultaneous identification of ESBL and CP in mock samples, as well as in an engineered construct which co-expressed these ß-lactamases. The NDM-1 biosensor assay was 16 times and 8 times more sensitive than the ESBL Nordmann/Dortet/Poirel (NDP) and Carba Nordmann/Poirel (NP) assays, respectively. In a retrospective study, NDM-1 biosensor assays were able to differentially identify ESBLs, metallo-CPs and serine-CPs ß-lactamases in 23 clinical isolates with 100% accuracy. An assay algorithm was developed which accelerated data analytics reducing turnaround to <1 h. The assay strategy integrated with AI-based data analytics has the potential to provide physicians with a comprehensive readout of patient AMR status.

A biosensing strategy for the rapid detection and classification of antibiotic resistance.

Antibiotic resistance (AR) poses an ever growing threat to global public health. Methods are urgently needed that simplify and accelerate the clinical detection and classification of AR. Here we describe a function-based antibiotic resistance assay (FARA) biosensing strategy. The scheme comprises three key components: i) FARA directly measures the thermal signal generated from the catalytic break-down of antibiotics by AR enzymes, ii) a sample specific AR profile is created by analyzing a panel of antibiotics which enhances informational content and iii) meta-analysis of the AR profile database to correlate profiles with diagnosis, treatments and outcomes. In order to test the ability of the scheme to identify and classify AR, two well-studied antibiotic resistance enzymes, penicillinase and metallo-beta-lactamase (MBL), were profiled using a panel of 5 antibiotics: penicillin G, penicillin V, ampicillin, oxacillin and imipenem. The results show that the profiles of the two enzymes could easily detect AR and differentially classified these enzymes. More importantly, both enzymes showed a significant and distinct secondary catalytic profile, which dramatically increases informational content. FARA profiles can be generated and analyzed in 1h. FARA is a fast, simple, cost effective alternative for detecting and classifying AR. FARA will speed up AR detection and classification will allow more accurate individualized treatment. This will reduce the spread of resistance and personalized treatments will improve patient outcomes. Other potential applications of FARA technology are discussed, including the possibility of developing an in vitro blood model for studying AR.

A novel thermometric biosensor for fast surveillance of ß-lactamase activity in milk.

Regulatory restrictions on antibiotic residues in dairy products have resulted in the illegal addition of ß-lactamase to lower antibiotic levels in milk in China. Here we demonstrate a fast, sensitive and convenient method based on enzyme thermistor (ET) for the surveillance of ß-lactamase in milk. A fixed amount of penicillin G, which is a specific substrate of ß-lactamase, was incubated with the milk sample, and an aliquot of the mixture was directly injected into the ET system to give a temperature change corresponding to the remained penicillin G. The amount of ß-lactamase present in sample was deduced by the penicillin G consumed during incubation. This method was successfully applied to quantify ß-lactamase in milk with the linear range of 1.1-20 UmL(-1) and the detection limit of 1.1 UmL(-1). The recoveries ranged from 93% to 105%, with relative standard deviations (RSDs) below 8%. The stability of the column equipped in ET was also studied, and only 5% decrease of activity was observed after 60 days of use. Compared with the conventional culture-based assay, the advantages of high throughput, timesaving and accurate quantification have made this method an ideal alternative for routine use.

Dual-signal analysis eliminates requirement for milk sample pretreatment.

Detection of analytes in complex biological samples, such as milk and blood, normally requires sample pretreatment. These pretreatment regimes reduce assay throughput and increase testing costs. Technologies that make it possible to eliminate sample pretreatment are of great industrial interest. Here we report the development of a dual-signal flow injected analysis device which eliminates the need for sample pretreatment. The device employs thermal traducers to measure the signal from an enzyme and a reference column. This makes it possible to independently monitor and correct for non-specifically generated heat, thereby eliminating the need for sample pretreatment. The ability of the dual-signal device to determine urea and lactate in milk samples without any prior treatment was evaluated. The spiked milk samples, the urea assay had a linear range from 0.1 to 50mM (R=0.996), and the lactate assay had a linear range from 0.025 to 5.0mM (R=0.9998). The linear regression values for urea and lactate for 0.5%, 1.5% and 3.0% fat milk were at least 0.990. The dual-signal design improves assay reproducibility, accuracy and sensitivity. Addition benefits are shorter assay times and lowers costs, as well as reducing equipment and training requirements. The potential application of the technology for multi-analyte analysis in point of care and decentralized diagnostic testing in healthcare, agriculture and environmental areas is discussed.

Electrochemical study of the XNA on Gold microarray.

A novel electrode array was developed based on the XNA on Gold trade mark microarray platform. The platform combines self-assembling monolayers, thick film patterning and streptavidin based immobilization to provide a robust, versatile platform capable of analysing virtually any biomolecule including nucleic acids, proteins, carbohydrates and lipids. Electrochemical analysis of the self-assembling monolayer/streptavidin (SAMS) XNA on Gold coating revealed that the ferrocene redox current for the SAMS modified electrode was greater than that with a bare Gold electrode. The electrochemical reaction of K4Fe(CN)6 was inhibited by the SAMS coating, but was reactivated upon addition of ferrocene. These results indicate that ferrocene is involved as a mediator in the electron transfer of K4Fe(CN)6 to the SAMS modified electrode. Addition of DNA to the SAMS resulted in only a minor change in the electrochemical signal, indicating that XNA on Gold can be used for electrochemical based bioanalysis. After cycling a SAMS electrode 50 times, no signs of deterioration were detected showing that coating has excellent stability. In addition to the biosensing applications, the scheme provides a non-invasive method for accessing the quality of the SAMS coatings which is of industrial interest. These studies show that the XNA on Gold microarray platform can be used for electrochemical studies, thus providing an additional alternative for developing multianalyte biosensors as well as expanding the range of detection methods available for microarray analysis.