Metabolomics can provide diagnostic, prognostic, and therapeutic biomarker profiles of individual patients because a large number of metabolites can be simultaneously measured in biological samples in an unbiased manner. Minor stimuli can result in substantial alterations, making it a valuable target for analysis. Due to the complexity and sensitivity of the metabolome, studies must be devised to maintain consistency, minimize subject-to-subject variation, and maximize information recovery. This effort has been aided by technological advances in experimental design, rodent models, and instrumentation. Proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy of biofluids, such as plasma, urine, and faeces provide the opportunity to identify biomarker change patterns that reflect the physiological or pathological status of an individual patient. Metabolomics has the ultimate potential to be useful in a clinical context, where it could be used to predict treatment response and survival and for early disease diagnosis. During drug treatment, an individual's metabolic status could be monitored and used to predict deleterious effects. Therefore, metabolomics has the potential to improve disease diagnosis, treatment, and follow-up care. In this chapter, we demonstrate how a metabolomics study can be used to diagnose a disease by classifying patients as either healthy or pathological, while accounting for individual variation.
Phage display antibody libraries have been successfully used as the essential tool to produce monoclonal antibodies against a plethora of targets ranging from diseases to native biologically important proteins as well as small molecules. It is well documented that diverse antibody genes are the major genetic source for the construction of a high-quality antibody library and selection of high-affinity antibodies. Naïve antibody libraries are derived using the IgM repertoire of healthy donors obtained from B-cells isolated from human peripheral blood mononuclear cell (PBMC). Single-chain fragment variable (scFv) is a routinely used format due to its smaller size and preference for phage display. The process involves the use of a two-step cloning method for library construction. The protocol also covers the biopanning process for target positive clone selection.