Highly heterogenous humoral immune response in Lyme disease patients revealed by broad machine learning-assisted antibody binding profiling with random peptide arrays.

Introduction: Lyme disease (LD), a rapidly growing public health problem in the US, represents a formidable challenge due to the lack of detailed understanding about how the human immune system responds to its pathogen, the Methods: This study was designed to perform a broad profiling of the entire repertoire of circulating antibodies in human sera at the single-individual level using planar arrays of short linear peptides with random sequences. The peptides sample sparsely, but uniformly the entire combinatorial sequence space of the same length peptides for profiling the humoral immune response to a Results: The study revealed substantial variability in antibody binding profiles between individual LD patients even to the same antigen (VlsE protein) and strong similarity between individuals diagnosed with Lyme disease and healthy controls from the areas endemic to LD suggesting a high prevalence of seropositivity in endemic healthy control. Discussion: This work demonstrates the utility of the approach as a valuable analytical tool for agnostic profiling of humoral immune response to a pathogen.