A multiplex molecular assay for detection of six penA codons to predict decreased susceptibility to cephalosporins in Neisseria gonorrhoeae

Multigeographic clinical assessment of a molecular diagnostic assay for detection of key codons to predict decreased susceptibility or resistance to cephalosporins in Neisseria gonorrhoeae

Cephalosporin resistance in Neisseria gonorrhoeae has severely compromised the efficacy of World Health Organization (WHO)-recommended therapies. This study aimed to methodologically evaluate the optimized Six-CodonPlus assay, and additionally conducted a multicenter evaluation to assess its clinical application, especially for predicting antimicrobial resistance (AMR). For methodological evaluation, 397 sequence-known N. gonorrhoeae isolates were evaluated for specificity, 17 nongonococcal isolates were assessed for cross-reactivity, 159 uncultured urogenital swabs and urine samples were evaluated for sensitivity at the clinical level. For multicenter evaluation, 773 isolates with confirmed phenotypic data and 718 clinical urogenital swabs collected from four geographical cities were, respectively, utilized for the evaluation of AMR-prediction strategies and the clinical application of the assay. The assay accurately identified specific single-nucleotide polymorphisms in resistance-associated genes, the detection limits dropped to 10 copies/reaction for individual targets. The specificity reached 100% and no cross-reactivity occurred with double-target confirmation. The assay could be directly applied to clinical samples containing over 20 copies/reaction. Multicenter evaluation formulated two optimal strategies for decreased susceptibility prediction in specific scenarios, and one tactic for prediction of resistance and identification of FC428-like strains. High sensitivity of 86.84% (95% CI, 71.11-95.05) and specificity of 99.59% (95% CI, 98.71-99.89) for resistance prediction were demonstrated for ceftriaxone (CRO). Regarding N. gonorrhoeae identification among multicenter swabs, specificity reached 97.53% (95% CI, 95.49-98.69), and sensitivity reached 93.77% (95% CI, 90.04-96.22). The Six-CodonPlus assay exhibited excellent detection performance and formulated optimal AMR-related prediction strategy with regional adaptability, providing critical information for population screening and clinical treatment.

Next-generation molecular diagnostics: Leveraging digital technologies to enhance multiplexing in real-time PCR

Real-time polymerase chain reaction (qPCR) enables accurate detection and quantification of nucleic acids and has become a fundamental tool in biological sciences, bioengineering and medicine. By combining multiple primer sets in one reaction, it is possible to detect several DNA or RNA targets simultaneously, a process called multiplex PCR (mPCR) which is key to attaining optimal throughput, cost-effectiveness and efficiency in molecular diagnostics, particularly in infectious diseases. Multiple solutions have been devised to increase multiplexing in qPCR, including single-well techniques, using target-specific fluorescent oligonucleotide probes, and spatial multiplexing, where segregation of the sample enables parallel amplification of multiple targets. However, these solutions are mostly limited to three or four targets, or highly sophisticated and expensive instrumentation. There is a need for innovations that will push forward the multiplexing field in qPCR, enabling for a next generation of diagnostic tools which could accommodate high throughput in an affordable manner. To this end, the use of machine learning (ML) algorithms (data-driven solutions) has recently emerged to leverage information contained in amplification and melting curves (AC and MC, respectively) - two of the most standard bio-signals emitted during qPCR - for accurate classification of multiple nucleic acid targets in a single reaction. Therefore, this review aims to demonstrate and illustrate that data-driven solutions can be successfully coupled with state-of-the-art and common qPCR platforms using a variety of amplification chemistries to enhance multiplexing in qPCR. Further, because both ACs and MCs can be predicted from sequence data using thermodynamic databases, it has also become possible to use computer simulation to rationalize and optimize the design of mPCR assays where target detection is supported by data-driven technologies. Thus, this review also discusses recent work converging towards the development of an end-to-end framework where knowledge-based and data-driven software solutions are integrated to streamline assay design, and increase the accuracy of target detection and quantification in the multiplex setting. We envision that concerted efforts by academic and industry scientists will help advance these technologies, to a point where they become mature and robust enough to bring about major improvements in the detection of nucleic acids across many fields.

The Optimal Management of Neisseria gonorrhoeae Infections

Neisseria gonorrhoeae is one of the most frequent etiologic agents of STDs (sexually transmitted diseases). Untreated asymptomatic gonococcal infection in women can lead to spreading of the infection in the sexually active population and could lead to late consequences, such as sterility or ectopic pregnancies. One important issue about N. gonorrhoeae is its increasing resistance to antibiotics. This paper summarized the newest molecular antimicrobial resistance (AMR) detection assays for Neisseria gonorrhoeae connected with the latest therapeutic antimicrobials and gonococcal vaccine candidates. The assays used to detect AMR varied from the classical minimal inhibitory concentration (MIC) detection to whole-genome sequencing. New drugs against multi drug resistant (MDR) N. gonorrhoeae have been proposed and were evaluated in vivo and in vitro as being efficient in decreasing the N. gonorrhoeae burden. In addition, anti-N. gonorrhoeae vaccine candidates are being researched, which have been assessed by multiple techniques. With the efforts of many researchers who are studying the detection of antimicrobial resistance in this bacterium and identifying new drugs and new vaccine candidates against it, there is hope in reducing the gonorrhea burden worldwide.

Rapid Detection of Antimicrobial Resistance in Mycoplasma genitalium by High-Resolution Melting Analysis with Unlabeled Probes

With looming resistance to fluoroquinolones in Mycoplasma genitalium, public health control strategies require effective antimicrobial resistance (AMR) diagnostic methods for clinical and phenotypic AMR surveillance. We developed a novel AMR detection method, MGparC-AsyHRM, based on the combination of asymmetric high-resolution melting (HRM) technology and unlabeled probes, which simultaneously performs M. genitalium identification and genotypes eight mutations in the parC gene that are responsible for most cases of fluoroquinolone resistance. These enhancements expand the traditional HRM from the conventional detection of single-position mutations to a method capable of detecting short fragments with closely located AMR positions with a high diversity of mutations. Based on the results of clinical sample testing, this method produces an accordance of 98.7% with the Sanger sequencing method. Furthermore, the specificity for detecting S83I, S83N, S83R, and D87Y variants, the most frequently detected mutations in fluoroquinolone resistance, was 100%. This method maintained a stable and accurate performance for genomic copies at rates of ≥20 copies per reaction, demonstrating high sensitivity. Additionally, no specific cross-reactions were observed when testing eight common sexually transmitted infection (STI)-related agents. Notably, this work highlights the significant potential of our method in the field of AMR testing, with the results suggesting that our method can be applied in a range of scenarios and to additional pathogens. In summary, our method enables high throughput, provides excellent specificity and sensitivity, and is cost-effective, suggesting that this method can be used to rapidly monitor the molecular AMR status and complement current AMR surveillance. IMPORTANCE Mycoplasma genitalium was recently added to the antimicrobial-resistant (AMR) threats "watch list" of the U.S. Centers for Disease Control and Prevention because this pathogen has become extremely difficult to treat as a result of increased resistance. M. genitalium is also difficult to culture, and therefore, molecule detection is the only method available for AMR testing. In this work, we developed a novel AMR detection method, MGparC-AsyHRM, based on the combination of asymmetrical HRM technology and unlabeled probes, and it simultaneously performs M. genitalium identification and genotypes eight mutations in the parC gene that are responsible for most cases of fluoroquinolone resistance. The MGparC-AsyHRM method is a high-throughput, low-cost, simple, and culture-free procedure that can enhance public health and management of M. genitalium infections and AMR control, providing a strong complement to phenotypic AMR surveillance to address the spread of fluoroquinolone resistance.