Biomarkers – Multimedia

We introduce a unique tool for the determination of relative abundances for human serum biomarkers. Conceptually similar to DNA microarrays, the S&S® Serum Biomarker Chip (SBC) is a single capture antibody array that was developed for comparative analysis of serum samples in order to identify differences or similarities in protein expression profiles.

MicroRNAs (miRNAs) comprise a recently identified class of small, non-protein-coding regulatory molecules that play important roles in many physiologic and pathologic processes, including differentiation, viral infection, and oncogenesis. In cancer, abnormal miRNA expression suggests that these molecules may serve as valuable diagnostic and prognostic molecular signatures.

A recently developed Metabolomics informatics solution from raw data processing to metabolite database searching, compatible with multiple instruments, has been successfully applied to the analysis of 1H NMR human serum spectra of diabetic and non-diabetic subjects. This study also highlights Overlap Density Heatmap, a novel technology that complements the use of chemometrics in biomarker identification.

The novel quantitative technique of "Targeted Profiling" of 1H 1D NMR data is applied to a unique model of rheumatoid arthritis. A number of candidate biomarkers not previously identified using NMR techniques are identified related to inflammation and immune response. The pharmaceutical relevance of several of these metabolites is discussed.

At present, metabolite profiling is of growing importance in herbal medicine fields such as breeding, formulation, quality control and clinical trials. Herbal metabolic profiling allows direct detection of down-stream derivatives of metabolites, arising from herbal formulation process, using metabolite profiling ultra performance liquid chromatography time-of-flight mass spectrometry.

In order to improve the efficiency of NMR-based metabolomics studies, we have developed KnowItAll® Informatics System, Metabolomics Edition as a consistent and integrated software environment that covers the entire process from processing raw NMR data —to multivariate analysis—to biomarker identification. Using two datasets of 1H NMR spectra of mouse urine and human serum, we demonstrate the high efficiency of this integrated workflow for metabolomics data analysis.

To facilitate both prediction and mechanism-based assessment of human cancer risk, a liver gene expression signature was derived from short term experiments in the rat to predict non-genotoxic hepatocarcinogenicity. The signature was shown to classify 47 independent chemicals with 85% accuracy, much greater than other putative early biomarkers.

Characteristic 2D fractions are rapidly identified among thousands using interactive visualization, filtering and data mining with VisualCockpit. Biomarker candidates are found therein after identifying proteins from sequence tags. VisualCockpit correlates their concentrations, reflected by normalized MS peptide peak height sum, enzyme activity and immunoreactivity, to donor conditions.

We have developed a high throughput expression of recombinant proteins containing hexahistidine affinity tag in Escherichia coli followed by one step affinity purification of proteins on Ni²⁺ agarose beads.

The data presented herein demonstrate the unique profiling capabilities of each ProFACT™ surface library subfraction and the collective resolution of 69 non-redundant proteins, calibrated and quantified from image analysis of SDS-PAGE profiles.