Scientific Overview

Modern DNA, RNA, and protein expression technologies are revolutionizing our view and understanding of current neurological diseases, particularly neurodegenerative disorders like AD, and enable researchers to analyze the concurrent expression patterns of very large numbers of genes. These new high-throughput genomic and proteomic technologies (commonly referred to as the Systems Biology approach), such as DNA and protein micro arrays, allow for the simultaneous study of thousands of genes and protein end products, and their alterations in regulation and modulation patterns in relation to disease state, time, and tissue specificity. However, due to post-transcriptional and post-translational modifications, the relationship between the level of mRNA and those of the protein end product is not always the same. In many instances, there is a positive correlation between the mRNA and protein levels in a tissue sample, but often there is no correlation, and frequently a negative correlation is observed. Thus, protein expression profiling is necessary as a follow-up procedure to any DNA microarray finding.

 

Systems Biology represents a paradigm-shift in biology where an organism is viewed as an integrated and interacting network of genes, proteins, and biochemical reactions that give rise to life. Instead of analyzing individual components or aspects of the organism, such as sugar metabolism or a cell nucleus, Systems Biology focuses on all the components and the interactions among them (all as part of one system), which ultimately are responsible for an organism’s form and functions. This approach is fundamentally based on the idea that disease-perturbed protein and gene regulatory networks differ from their normal counterparts. It requires that all of the elements of a system be examined at multiple levels of the information hierarchy and in the context of their responses to perturbations. The data generated from these studies are to be integrated and graphically displayed, and the responses modeled mathematically to predict the structure and behavior of the informational pathway. In addition, the Systems Biology approach involves an iterative and strategic interplay between discovery- and hypothesis-driven scientific efforts in which global observations (i.e., discoveries) are compared against model predictions (i.e., hypotheses) in a repetitive manner that leads to the formation of novel models, predictions, and experiments to test them (see Figure 1). Thus, within this context human diseases (e.g., AD) are considered as genetic or environmental reprogramming of cells to gain or lose specific functions that are characteristics of the disease (Ideker et al., 2001).

Figure 1. Overview of the Systems Biology approach. From Ideker et al. (2001).

Due to its predictive and preventive nature, the Systems Biology approach naturally leads to personalized medicine (i.e., pharmacogenomics). Modern pharmacogenomic techniques have already rapidly accelerated disease associated gene discovery, which in turn has dramatically increased the pace that novel drug compounds are developed. The application of these technologies enable the development of novel therapeutics “custom tailored” to an individual’s genetic make-up, which allows drug compounds to be designed with minimal damaging effects and maximal efficiency.

Finally, current methodologies from the fields of nanotechnology, such as quantum dot (QD) nanocrystals and large-scale integrated microfluidics (i.e., nanolab), and molecular imaging can further be implemented and integrated within the overall Systems Biology framework, which in turn gives rise to the view of NanoSystems Biology. NanoSystems Biology. According to this approach, various molecular and nano-based tools, such as the nanolab, can be employed to solve a Systems Biology problem and to apply that solution to a drug discovery process (see Figure 2). Thus, through a global analysis of proteins and mRNA levels in a few cells, such as representative hippocampal and/or frontal cortical neurons from mice brains, the nanolab may be used to perform a rapid and informative molecular analysis of a biological system. This data may turn be coupled with an informatics algorithm that generates a hypothesis for the system. The hypothesis can then be tested using top-down perturbations in the form of molecular probes and thereby identifying novel therapeutic (i.e., drug) targets. The most effective of these molecular probes may ultimately be transformed into an imaging probe or a drug and applied toward imaging and treating disease within a living patient (Heath et al., 2003).

Figure 2. Overview of how the NanoSystems Biology model may be used to facilitate the drug discovery process. From Heath et al. (2003).

References

Heath, J.R., Phelps, M.E., and Hood, L.  2003.  NanoSystems Biology. Mol Imaging Biol. 5(5):312-325.

Ideker, T., Galitski, T., and Hood, L. 2001. A new approach to decoding life: Systems Biology. Annu Rev Genomics Hum Genet. 2:343-372.