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Human infectious diseases are contributed equally by the host immune system's efficiency and any pathogens' infectivity. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the coronavirus strain causing the respiratory pandemic coronavirus disease 2019 (COVID-19). To understand the pathobiology of SARS-CoV-2, one needs to unravel the intricacies of host immune response to the virus, the viral pathogen's mode of transmission, and alterations in specific biological pathways in the host allowing viral survival. This review critically analyzes recent research using high-throughput "omics" technologies (including proteomics and metabolomics) on various biospecimens that allow an increased understanding of the pathobiology of SARS-CoV-2 in humans. The altered biomolecule profile facilitates an understanding of altered biological pathways. Further, we have performed a meta-analysis of significantly altered biomolecular profiles in COVID-19 patients using bioinformatics tools. Our analysis deciphered alterations in the immune response, fatty acid, and amino acid metabolism and other pathways that cumulatively result in COVID-19 disease, including symptoms such as hyperglycemic and hypoxic sequelae.

Antimicrobial peptides (AMPs) are intensively studied in terms of alternative drugs. Sub5 is a synthetic 12-mer AMP with substitutions of five amino acids of bactenecin 2A (Bac2A), a linear-ized bactenecin variant of bovine. Sub5 is highly effective against fungi with an ability to trans-locate cell membrane, but its targets are unknown. Systematic analysis of Sub5 targets will facil-itate our understanding on its mechanism of action. In this study, we used high-throughput Saccharomyces cerevisiae proteome microarrays to explore the potential protein targets of Sub5. The screening results showed 128 potential protein targets of Sub5. Bioinformatics analysis of protein targets of Sub5 revealed significant gene ontology (GO) enrichment in actin related pro-cess of “actin filament-based process”, “actin filament organization”, “actin cortical patch or-ganization”, regulation of “actin filament bundle assembly”. Moreover, the other enriched cat-egories in GO enrichment mostly contained actin associate proteins. In total, 11 actin-associated proteins were identified in the protein targets of Sub5. Protein family (PFAM) enrichment anal-ysis shows protein domain enriched in actin binding, i.e., “Cytoskeletal-regulatory complex EF hand (helix E-loop-helix F motif)”. Being consistent with GO analysis, Search Tool for the Re-trieval of Interacting Genes/Proteins (STRING) analysis of the protein targets of Sub5 showed ac-tin network with involvement of 15 protein targets. Along with actin-network, STRING analysis showed protein–protein interaction network in ribonucleoprotein, transcription and translation, chromosome, histone, and ubiquitin related, DNA repair, and chaperone. Multiple Expression motifs for Motif Elicitation (MEME) suite provided a consensus binding motif of [ED][ED]EEE[ED][ED][ED][ED][ED], in total of 75 protein targets of Sub5. This motif was present in 9 out of 15 actin-related proteins identified among protein targets of Sub5.

Objective Serum proteomic analysis of tuberculosis (TB) antigens to identify biomarkers enabling discrimination of active TB (ATB) from latent TB infection (LTBI). Methods Serum samples from patients with ATB, individuals with LTBI and healthy controls (HCs) were used to probe proteome microarrays. Based on signal intensities of IgG and IgM antibodies, 100 TB proteins were selected for fabrication of mini-protein microarrays, which were then used to screen 204 serum samples. Results Proteome microarray analyses showed that 58 IgG or IgM specific antibodies were significantly more abundant in ATB patients than in individuals with LTBI or HCs. Serological evaluation of mini-protein microarrays demonstrated that average levels of 15 specific antibodies were higher in ATB patients than in individuals with LTBI or HCs. This combination of 15 TB serum biomarkers had a sensitivity of 85.4% and specificity of 90.3% in discriminating ATB from LTBI. Conclusion Combinations of serum biomarkers can offer improved diagnostic performance in discriminating ATB from LTBI. Five biomarkers (MT1560.1, Rv0049, Rv0270, Rv1597 and Rv3480c) associated with ATB induced stronger IgM responses in these patients.

To screen the differential expression cytokines (DECs) in hemolysis, elevated liver enzymes, and low platelet (HELLP) syndrome, establish its differential cytokines spectra, and provide the clues for its diagnosis and pathogenic mechanism researches. Sera from four HELLP syndrome patients and four healthy controls were detected by proteome microarray. Then the analysis of Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein–protein interaction (PPI) network were performed and possible hub proteins were selected out, further verified by Enzyme Linked Immunosorbent Assay (ELISA) in sera from 21 HELLP syndrome patients and 21 healthy controls. Thirty DECs were defined according to P-value and fold change between HELLP group and control group. GO enrichment analysis showed that DECs were mainly involved in the regulation of inflammatory response and have relationship to growth factor binding, transmembrane receptor protein kinase, and cytokine receptor activity. Seven possible hub proteins were defined by PPI analysis, including IGFBP-3/Follistatin-like 1/FLRG/Fetuin A and MMP-13/Thrombospondin-5/Aggrecan. ELISA showed higher serum levels of Fetuin A/IGFBP-3/FLGR/MMP-13/Thrombospondin-5 in HELLP group than those in controls, while the levels of Follistatin-like 1 and Aggrecan were lower in HELLP patients (all P < 0.05 or

Systems biology holds the key for understanding biological systems on a system level. It eventually holds the key for the treatment and cure of complex diseases such as cancer, diabetes, obesity, mental disorders, and many others. The ‘-omics' technologies, such as genomics, transcriptomics, proteomics, and metabonomics, are among the major driving forces of systems biology. Featured as high-throughput, miniaturized, and capable of parallel analysis, protein microarrays have already become an important technology platform for systems biology. In this review, we will focus on the system level or global analysis of biological systems using protein microarrays. Four major types of protein microarrays will be discussed: proteome microarrays, antibody microarrays, reverse-phase protein arrays, and lectin microarrays. We will also discuss the challenges and future directions of protein microarray technologies and their applications for systems biology. We strongly believe that protein microarrays will soon become an indispensable and invaluable tool for systems biology.