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ABSTRACT Bacterial infection clusters cause high mortality rates and healthcare costs due to excessive therapy and hygiene measures. The aim of this study was to develop an automated real-time PCR-based point-of-care (POC) system with a customized microfluidic chip that facilitates fast detection of bacterial cluster isolates by targeting cluster-specific single-nucleotide polymorphisms (SNPs). For cluster detection of Acinetobacter baumannii, Staphylococcus aureus, and Escherichia coli, nine TaqMan real-time PCR assays targeting cluster-specific SNPs were designed. Additionally, for DNA input control, a universal PCR amplifying the 16S rDNA was constructed. All reactions were implemented into a microfluidic chip that was analyzed by a POC prototype enabling automated sample processing, fluid handling, and signal detection. Performance of the prototype was evaluated using 45 chips loaded with defined bacterial solutions, including swab eluates. For seven PCRs, implementation into the microfluidic chip was successful, leading to correct identification of all SNPs specific for A. baumannii and E. coli cluster isolates and delineation of all non-cluster strains within 70 min. The remaining three reactions failed in the chip, which resulted in misidentification of the S. aureus cluster. Sensitivity, specificity, and accuracy of the prototype were 43%, 88%, and 55%, respectively. The detection limit was PCR dependent and ranged between 103 and 105 colony-forming units/mL. Once optimized, the microfluidic POC system for cluster detection could be applied as time-saving and easy-to-use method to complement whole-genome sequencing efforts during screening for bacterial clusters.IMPORTANCEEspecially in medical facilities, where morbid people are nursed in close distance to each other, pathogenic bacteria can accumulate and spread. To contain such infection clusters, usually time- and labor-intensive large-scale screening assays are conducted, where patients and patient-side surfaces are sampled, and PCR or whole-genome sequencing analyses are conducted to confirm or deny cluster affiliation of cultivated bacteria. Hence, fast solutions with easy application are required to complement the current state-of-the-art technology for cluster surveillance. Here, we developed a fully automated microfluidic point-of-care prototype that identified bacterial cluster isolates within 70 min from bacterial solutions, including swab eluates. The system requires only low hands-on time and can be applied apart from laboratory infrastructures near the patient, which considerably reduces the time from sampling to result. This ensures fast implementation of hygiene measures and quick containment of the infection cluster, which would enhance patients’ safety and outcome.

ABSTRACT Infection clusters of multidrug-resistant bacteria increase mortality and entail expensive infection control measures. Whereas whole-genome sequencing (WGS) is the current gold standard to confirm infection clusters, PCR-based assays targeting cluster-specific signatures, such as single nucleotide polymorphisms (SNPs) derived from WGS data, are more suitable to initially screen for cluster isolates within large sample sizes. Here, we evaluated four software tools (SeqSphere+, RUCS, Gegenees, and Find Differential Primers) regarding their efficiency to find SNPs within WGS data sets that were specific for two bacterial monospecies infection clusters but were absent from a WGS reference data set comprising several hundred diverse genotypes of the same bacterial species. Cluster-specific SNPs were subsequently used to establish a probe-based real-time PCR screening assay for in vitro differentiation between cluster and noncluster isolates. SeqSphere+ and RUCS found 2 and 24 SNPs for clusters 1 and 14 and 24 SNPs for cluster 2, respectively. However, some signatures detected by RUCS were not cluster specific. Interestingly, all SNPs identified by SeqSphere+ were also detected by RUCS. In contrast, analyses with the remaining tools either resulted in no SNPs (with Find Differential Primers) or failed (Gegenees). Design of six cluster-specific real-time PCR assays enabled reliable cluster screening in vitro. Our evaluation revealed that SeqSphere+ and RUCS identified cluster-specific SNPs that could be used for large-scale screening in surveillance samples via real-time PCR, thereby complementing WGS efforts. This faster and simplified approach for the surveillance of bacterial clusters will improve infection control measures and will enhance protection of patients and physicians. IMPORTANCE Infection clusters of multidrug-resistant bacteria threaten medical facilities worldwide and cause immense health care costs. In recent years, whole-genome sequencing (WGS) has been increasingly applied to detect and to further control bacterial clusters. However, as WGS is still expensive and time-consuming, its exclusive application for screening and confirmation of bacterial infection clusters contributes to high costs and enhanced turnaround times, which many hospitals cannot afford. Therefore, there is need for alternative methods that can enable further surveillance of bacterial clusters that are initially detected by WGS in a faster and more cost-efficient way. Here, we established a system based on real-time PCR that enables rapid large-scale sample screening for bacterial cluster isolates within 7 days after the initial detection of an infection cluster, thereby complementing WGS efforts. This faster and simplified surveillance of bacterial clusters will improve infection control measures and will enhance protection of patients and physicians.