Antimicrobial resistance (AMR) threatens global public health and modern surgical medicine. Expression of β-lactamase genes is the major mechanism by which pathogens become antibiotic resistant. Pathogens expressing extended spectrum β-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 β-lactamases inhibitors (avibactam and EDTA). The assay required the development of a novel biosensor that employed New Delhi metallo-β-lactamase-1 (NDM-1) as the sensing element. Functionally probing β-lactamase activity using substrates and inhibitors combinatorically increased the informational content that enabled the development of assays capable of simultaneous, differential identification of multiple β-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 β-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 β-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.

Currently, assays for rapid therapeutic drug monitoring (TDM) of β-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 β-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-β-lactamase-1 (NDM-1) as the biological recognition layer. NDM-1 has a broad specificity range and is capable of hydrolyzing all classes of β-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 β-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 β-lactamase inhibitors avibactam and vaborbactam, respectively. Furthermore, both free and protein-bound β-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 β-lactam antibiotics present in the blood of critically ill patients.

Accurate detection of SARS-CoV-2 neutralizing antibody (nAb) is critical for assessing the immunity levels after virus infection or vaccination. As fast, cost-effective alternatives to viral infection-based assays, competitive binding (CB) assays were developed to quantitate nAb by monitoring the ability of sera to inhibit the binding of viral spike (S) protein to the angiotensin converting enzyme 2 (ACE2) receptor. Herein, we established a bead-based flow cytometric CB assay and tested the detection performance of six combination models, i.e. immobilized ACE2 and soluble Fc-tagged S1 subunit of S protein (iACE2/S1-Fc), immobilized ACE2 and soluble Fc-tagged receptor binding domain (RBD) of S protein (iACE2/RBD-Fc), immobilized S1 and soluble Fc-tagged ACE2 (iS1/ACE2-Fc), immobilized S1 and soluble His-tagged ACE2 (iS1/ACE2-His), immobilized RBD and soluble Fc-tagged ACE2 (iRBD/ACE2-Fc), and immobilized RBD and soluble His-tagged ACE2 (iRBD/ACE2-His). Using SARS-CoV-2 monoclonal antibodies and sera of convalescent COVID-19 patients and vaccinated subjects, the combination models iACE2/RBD-Fc, iACE2/S1-Fc and iS1/ACE2-His were identified to be able to specifically detect SARS-CoV-2 nAb, among which iACE2/RBD-Fc model showed the highest sensitivity, superior to a commercial SARS-CoV-2 surrogate virus neutralization test (sVNT) ELISA kit. Further studies demonstrated that the sensitivity and specificity of CB assays were affected by the tag of ACE2, type of spike and method of measuring binding rate between ACE2 and spike. Moreover, the iACE2/RBD-Fc model showed good performance in detecting kinetic development of nAb against both the prototype SARS-CoV-2 strain and an omicron variant of SARS-CoV-2 in people immunized by an inactivated SARS-CoV-2 vaccine, and the results of iACE2/RBD-Fc model are correlated well with those of live virus-based and pseudovirus-based neutralization tests, demonstrating the potential to be developed into a highly sensitive, specific, versatile and high-throughput method for detecting SARS-CoV-2 nAb in clinical practice.