High throughput gene expression profiling: a molecular approach to integrative physiology

Abstract

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions.

Figure 1. Basic process of a typical cDNA microarray experiment

RT, reverse transcription.

Figure 2. Multi-dimensional integrative physiology

The availability of genome sequences and a variety of high-throughput techniques (several examples shown in italic font) has made it possible to integrate physiology across functional pathways (1st dimension), regulatory levels (2nd dimension), and various conditions (3rd dimension). MS, mass spectrometry; SAGE, serial analysis of gene expression; SNP, single nucleotide polymorphism.

Figure 3. A network of genes potentially related to the reduction of blood pressure salt-sensitivity in SS-13^BN/Mcw rats identified by cDNA microarray (based on data from Liang et al. 2003b)

Each panel depicts the expression pattern of a gene, which is followed by a brief description of the relevant functions of this gene. Text in the boxes indicates potential functional consequences in SS-13^BN/Mcw compared to SS as a result of the expression patterns. The thickness of arrow indicates the strength of support for those links based on current literature. LS, low-salt (0.4% NaCl) diet; HS, high-salt (4% NaCl) diet.

Figure 4. Question-driven researches can complement traditional hypothesis-driven researches

Figure 5. Reliability of cDNA microarray data

A, partial images from duplication microarray hybridizations. B, significant correlation between ln(ratio)s obtained from microarrays and Northern blots examining approximately 60 randomly selected genes under various treatment conditions (based on data from Liang et al. 2002, 2003b; Yuan et al. 2003).