Biolayer interferometry (BLI) is a well-established laboratory technique for studying biomolecular interactions important for applications such as drug development. Currently, there are interesting opportunities for expanding the use of BLI in other fields, including the development of rapid diagnostic tools. To date, there are no detailed frameworks for implementing BLI in target-recognition studies that are pivotal for developing point-of-need biosensors. Here, we attempt to bridge these domains by providing a framework that connects output(s) of molecular interaction studies with key performance indicators used in the development of point-of-need biosensors. First, we briefly review the governing theory for protein-ligand interactions, and we then summarize the approach for real-time kinetic quantification using various techniques. The 2020 PRISMA guideline was used for all governing theory reviews and meta-analyses. Using the information from the meta-analysis, we introduce an experimental framework for connecting outcomes from BLI experiments (K_D, k_on, k_off) with electrochemical (capacitive) biosensor design. As a first step in the development of a larger framework, we specifically focus on mapping BLI outcomes to five biosensor key performance indicators (sensitivity, selectivity, response time, hysteresis, operating range). The applicability of our framework was demonstrated in a study of case based on published literature related to SARS-CoV-2 spike protein to show the development of a capacitive biosensor based on truncated angiotensin-converting enzyme 2 (ACE2) as the receptor. The case study focuses on non-specific binding and selectivity as research goals. The proposed framework proved to be an important first step toward modeling/simulation efforts that map molecular interactions to sensor design.

Filamentous plant pathogens, including fungi and oomycetes, pose significant threats to cultivated crops, impacting agricultural productivity, quality and sustainability. Traditionally, disease control heavily relied on fungicides, but concerns about their negative impacts motivated stakeholders and government agencies to seek alternative solutions. Biocontrol agents (BCAs) have been developed as promising alternatives to minimize fungicide use. However, BCAs often exhibit inconsistent performances, undermining their efficacy as plant protection alternatives. The eukaryotic cell wall of plants and filamentous pathogens contributes significantly to their interaction with the environment and competitors. This highly adaptable and modular carbohydrate armor serves as the primary interface for communication, and the intricate interplay within this compartment is often mediated by carbohydrate-active enzymes (CAZymes) responsible for cell wall degradation and remodeling. These processes play a crucial role in the pathogenesis of plant diseases and contribute significantly to establishing both beneficial and detrimental microbiota. This review explores the interplay between cell wall dynamics and glycan interactions in the phytobiome scenario, providing holistic insights for efficiently exploiting microbial traits potentially involved in plant disease mitigation. Within this framework, the incorporation of glycobiology-related functional traits into the resident phytobiome can significantly enhance the plant's resilience to biotic stresses. Therefore, in the rational engineering of future beneficial consortia, it is imperative to recognize and leverage the understanding of cell wall interactions and the role of the glycome as an essential tool for the effective management of plant diseases.