Development of point-of-care sensors for diagnosis of bacterial-associated infections

Bacteria-associated infections are prevalent in our society, which can cause high mortality rates and pose a significant threat to public health. The conservative treatment of such infections using antibiotics often results in antibiotic resistance that further exacerbates the existing bacteria-associated public health problem. Additionally, bacteria associated with infections often grow as inherently resistant biofilms, e.g., on implant surfaces, that can only be treated if detected as early as possible. However, limited accessibility of reliable diagnostic tools remains challenging, particularly in low-income settings. Classical methods used for pathogen detection are time-consuming costly, and require specialized technical facilities as well as expert personnel to handle the samples. Over the next decade, we expect antimicrobial resistance cases and biofilm-associated infections to increase, thus multiplying the number of public health issues.

It is of paramount importance to develop novel, reliable point-of-care diagnostic setups to detect and identify pathogenic bacteria to find the right course of treatment and adapt to the development of the disease. Specifically, there is a need for devices that embody the recommended WHO guidelines in the development of diagnostic tools according to the ASSURED criteria (A- affordable, S- sensitive, S- specific, U- user-friendly, R- rapid and robust, E- equipment-free or simple, D- deliverable to end users). Thus, this Research Topic aims to cover existing and emerging sensor technologies, including in vitro and in vivo models, for their evaluation that could aid in the rapid detection and diagnosis of bacterial-associated infections.

We encourage submissions with a focus on the development and implementation of techniques and detection tools for bacterial-based infections. This includes methods and protocols for sample collection, purification, and isolation (microfluidics, lateral flow, paper-based), their comparison to conventional methods, development and testing of methods (photonics, electrochemical, biochemical, molecular and synthetic biology-based), as well as design and development of whole devices in the form of compact platforms (e.g. lab-on-a-chip). Research on software development for data acquisition and analysis will also be highly interesting. Investigations on in vitro and in vivo models to study infection-related scenarios are also welcome.

In summary, we invite submissions that cover aspects of method development, hardware and software tools, or combinations thereof, enabling engineering technologies to be applied to bacteria detection. These submissions may also include the use of additive manufacturing or other diagnostic chip technologies, which may be combined into “systems” using smartphones, wireless technology, IoT, and artificial intelligence for enabling diagnostics decision support.