Rarely in human disease can a single host factor be identified as the primary causal factor of a disease, syndrome, or disorder. Rather, the clinical manifestations that culminate in a symptomatic state are usually triggered by a perturbation of multiple factors derived from several distinct, but integrated, domains of cellular regulation. Host immune responses, such as antimicrobial peptide (AMP) production and regulation, are the result of interdependent dynamic interactions between host cells, extracellular milieu, and the external environment. In order to truly elucidate disease pathogenesis, it is imperative to consider the entire system at play from a global perspective, which is the promise of “omics” technology. The term “omics” was originally coined as a discipline in molecular biology that examines global sets of biological molecules (Micheel et al., 2012), which consequently stimulated an “Omics Revolution” throughout the scientific community. Genomics emerged following the sequencing of the human genome in the 1990s and early 2000s. This subsequently led to proteomics, which includes the entire complement of proteins and their related structure, modifications, and function. Pauling et al. (1971) proposed that estimating the abundance of metabolites in biological fluids may indicate the functional status of a specific biological system. Consequently, metabolomics has recently surfaced as an approach to comprehensively identify and quantify low molecular weight exogenous and endogenous metabolites and compounds in a biological system using high-throughput methods. Using 16S rRNA gene sequencing tools originally developed in the field of environmental microbiology, we can now generate a site-specific microbiome profile for any given patient. The Human Microbiome Project and numerous other projects aim to discern relationships between human-associated microbes and health and disease (Zoetendal et al., 2006). Such research has generated massive and complex data sets, which requires further advancement and refinement of bioinformatics and biostatistical applications. Often, the data is used to produce computational models to distinguish specific characteristics of a given population. Due to the unavoidable complexities and required statistical sophistication, few medical fields have developed clinically useful applications for the resulting data. Thus, AMPs are an ideal set of biological molecules to assess, since there biological role spans numerous areas of clinical research. Due to their diverse microbicidal and immunomodulatory functions (Steinstraesser et al., 2011), AMPs comprise a major aspect of the host innate immune response (Nakatsuji and Gallo, 2012). Alterations in AMP production and/or localization are associated with several cutaneous dermatoses. Patients diagnosed with atopic dermatitis and psoriasis ultimately develop epidermal barrier defects and microbial susceptibility, or a hyperproliferative/inflammatory epidermis, respectively (Schauber and Gallo, 2008; Schroder, 2011). The contributions of AMPs to tissue integrity and epithelial defense was also established in the brain (Schluesener et al., 2012; Williams et al., 2012), urinary tract (Saemann et al., 2007; Zasloff, 2007; Ali et al., 2009), gastrointestinal tract (Lisitsyn et al., 2012), and certain malignancies (Kesting et al., 2012; Scola et al., 2012). However, altered AMP regulation does not occur exclusively, but instead embodies dynamic transformations that emerge as a disturbed system. The integration of several different “omics” techniques may provide a more complete understanding of the diverse factors contributing to a specific disease state, responses to pharmacologic agents, or novel alternatives to current treatment modalities.
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Open Access
Apr 18, 2018
Ao Yuan 
