Proteome Analysis for Inflammation Related to Acute and Convalescent Infection

Abstract

Infectious diseases are a significant burden in global healthcare. Pathogens engage with different host defense mechanisms. However, it is currently unknown if there are disease-specific immune signatures and/or if different pathogens elicit common immune-associated molecular entities to common therapeutic interventions. We studied patients enrolled through the Human Immunology Project Consortium (HIPC), which focuses on immune responses to various infections. Blood samples were collected and analyzed from patients during infection and follow-up time points at the convalescent stage. The study included samples from patients with Lyme disease (LD), tuberculosis (TB), malaria (MLA), dengue virus (DENV), and West Nile virus (WNV), as well as kidney transplant patients with cytomegalovirus (CMV) and polyomavirus (BKV) infections. Using an antibody-based assay, we quantified ~ 350 cell surface markers, cytokines, and chemokines involved in inflammation and immunity. Unique protein signatures were identified specific to the acute phase of infection irrespective of the pathogen type, with significant changes during convalescence. In addition, tumor necrosis factor receptor superfamily member 6 (TNR6), C-C Motif Chemokine Receptor 7 (CCR7), and C-C motif chemokine ligand-1 (CCL1) were increased in the acute and convalescent phases across all viral, bacterial, and protozoan compared to blood from healthy donors. Furthermore, despite the differences between pathogens, proteins were enriched in common biological pathways such as cell surface receptor signaling pathway and response to external stimulus. In conclusion, we demonstrated that irrespective of the pathogen type, there are common immunoregulatory and proinflammatory signals.

Keywords: BK virus; CMV; Dengue; Lyme disease; Malaria; Pathogens; Proteomics; Tuberculosis; West Nile virus.

Fig. 1

Scheme illustrating specimen collection per infection and protein expression analysis platform. a Barplot demonstrating the dispersion of sample-collection timepoints, gender, and disease state across seven distinct diseases (BKV, cytomegalovirus, dengue, Lyme disease, malaria, tuberculosis, and West Nile virus) and healthy controls. b Overview of the infections studied, specimens collected, and platform used for the data acquisition. scioCD antibody microarray platform profiled the expression of 345 proteins at any given time in plasma or serum isolated from blood.

Fig. 2

Analysis to identify significantly increased and decreased proteins and most enriched pathways in the acute infection phase compared to the healthy controls. a The heatmap shows the expression pattern of significant proteins in infection caused by each infectious agents (virus, bacteria, protozoan) with a fold change ≥ 1.4 compared to the healthy controls. b For each category, we identified several uniquely expressed proteins, with which we performed gene set enrichment analysis and identified the significantly affected biological processes at the time of infection.

Fig. 3

Analysis to identify differentially expressed proteins and most enriched pathways in the convalescent state or recovery phase of infection compared to the healthy controls. a The heatmap shows the expression pattern of top four significantly changed proteins in the convalescent or recovery phase of the infection per infectious agents (virus, bacteria, protozoan) with a fold change ≥ 0.5 compared to the healthy controls. b For each infectious agent, we identified several uniquely expressed proteins, with which we performed gene set enrichment analysis and identified the significantly affected biological processes at the time of recovery.

Fig. 4

Significantly increased and decreased blood proteins in each infection type were identified by comparing the acute infection phase to the convalescent phase. The bubble plot shows their names and the degree of their perturbation during acute infection time points.

Fig. 5

The boxplots display the most differentially changed proteins across the time points of each infection. Non-significant (ns): p < = 1.00e + 00; *1.00e − 02 < p < = 5.00e − 02; **1.00e − 03 < p < = 1.00e − 02; ***1.00e − 04 < p < = 1.00e − 03; ****p < = 1.00e − 04.