Cutting Edge: identification of neutrophil PGLYRP1 as a ligand for TREM-1.

Triggering receptor expressed on myeloid cells (TREM)-1 is an orphan receptor implicated in innate immune activation. Inhibition of TREM-1 reduces sepsis in mouse models, suggesting a role for it in immune responses triggered by bacteria. However, the absence of an identified ligand has hampered a full understanding of TREM-1 function. We identified complexes between peptidoglycan recognition protein 1 (PGLYRP1) and bacterially derived peptidoglycan that constitute a potent ligand capable of binding TREM-1 and inducing known TREM-1 functions. Interestingly, multimerization of PGLYRP1 bypassed the need for peptidoglycan in TREM-1 activation, demonstrating that the PGLYRP1/TREM-1 axis can be activated in the absence of bacterial products. The role for PGLYRP1 as a TREM-1 activator provides a new mechanism by which bacteria can trigger myeloid cells, linking two known, but previously unrelated, pathways in innate immunity.

Analytical Tools to Improve Optimization Procedures for Lateral Flow Assays.

Immunochromatographic or lateral flow assays (LFAs) are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor's office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads), biological reagents (e.g., antibodies, blocking reagents and buffers) and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness.