GenProMarkers™, Inc.

Microarray, Bioinformatics and Systems Biology for Discovery of Gene and Protein Biomarkers

hMitChip3 representative image and quality. (A) Representative microarray image. This pseudocolored image represents a hMitChip3 microarray hybridized with the Cy5-labeled target cDNA reverse-transcribed from a UACC903 RNA sample. Four printing heads were used to print four subarrays of the image, and each element was printed as triplicate. The pixel intensities on spotted probes reflect abundances of hybridized target cDNA.  Inset shows four genes with high (HNRPA1 and TUBB), moderate (HIP2), and low (MDH1) signal intensities. (B) Bar graph illustrates mean pixel intensities of the positive (n = 438) and negative (n =237) control spots, test gene spots (n = 3405), and the background of all the spots (n = 4080). The mean and standard deviation of the positive, test gene, negative, and background were 4456±1068, 3437±602, 464±75, and 430±41, respectively. P values (P) between comparisons are indicated. P* means statistically significant P value (3.62 × 10-6 < 0.05).


Microarray Products and Services


The third-generation human mitochondria-focused cDNA microarray (hMitChip3) and bioinformatic tools facilitate profiling mitochondrial transcriptomes.  Mitochondrial abnormalities frequently occur in common diseases, such as neurodegeneration, obesity, diabetes, cancer (the Warburg effect), cardiomyopathy, and migraine.  In addition, reactive oxygen species, inevitable byproducts of mitochondrial oxidative phosphorylation, may damage DNA and have been implicated in neurodegenerative disease, cancer, and aging.  Furthermore, mitochondria at the intersection of many molecular pathways are a central target of diverse pharmacological agents.  Finally, many drugs have direct effects on mitochondrial ultra-structure and function.  hMitChip3 contains all mitochondrial proteins-related genes including the 37 mtDNA-encoded and 1,098 nDNA-encoded genes, each in triplicate, involved in 645 molecular functions; 646 biological processes; 339 cellular components; 149 biological chemistry pathways; 373 genetic disorders; and 87 drugs targets.


The Powerhouse of the Cell Takes on the DNA Chip

Mitochondria, intracellular organelles widely known as the energy factories of the cell, play fundamental roles in many metabolic pathways, such as β-oxidation, the tricarboxylic acid, and urea cycles, the synthesis of steroid hormones and heme, and calcium signaling. Mitochondria are the only subcellular structures possessing distinct DNA (mitochondrial DNA or mtDNA) and transcription and translation machineries. Yet, the vast majority of mitochondrial proteins are encoded by the nuclear DNA, synthesized by ribosomes in the cytoplasm, and imported into the organelles.  The highly integrated cross-functionality of nuclear and mitochondrial genomes is essential for maintenance of cellular homeostasis. Defects and abnormal expression of either nuclear DNA-encoded and/or mtDNA-encoded genes can be deleterious for human organs. While nuclear DNA mutations are rare as primary mitochondrial genetic disorders (i.e., Leigh syndrome, Friedreich’s ataxia, lethal infantile cardiomyopathy, carnitine palmitoyl transferase deficiency, to name a few), abnormalities in mitochondrial structure and function are increasingly recognized in common diseases, such as obesity, diabetes, cardiomyopathy, and migraine. In addition, reactive oxygen species, an inevitable by-product of mitochondrial oxidative phosphorylation, can damage DNA and have been implicated in cancer, neurodegenerative diseases, and aging. Furthermore, mitochondria at the intersection of many molecular pathways are a central target of diverse pharmacological agents. Many drugs have direct effects on mitochondrial ultrastructure and function, either at the DNA level or upon targeting proteins located in the inner or outer mitochondrial membrane. For example, curcumin and arsenic induce apoptosis via a mitochondria-mediated pathway.

Microarray analysis has proved a powerful method to study gene expression changes at a global level.  One problem often encountered by researchers using microarrays is the best way to understand and interpret the mountains of data produced from these analyses.  Constructing microarrays that are more specific is one way to decrease experimental noise and obtain biologically relevant data.  hMitChip3 and related bioinformatics tools have been applied to successfully profile the gene expression in a number of hypothesis-driven studies.

From Generic to Diagnostic Microarrays

The whole genome gene chips can be used to identify a particular set of genes in order to design and fabricate disease-specific diagnostic gene chips as illustrated below

Generic and Diagnostic Microarrays.  (A) Generic Microarrays for screening of differentially expressed genes.  (B) Diagnostic Microarrays constructed with the resultant differentially expressed genes from generic microarrays. The genes in the diagnostic microarray were printed in triplicate.  For example, 1a, 1b and 1c are the identical genes without the significant changes in expression levels; 2a, 2b and 2c are the identical genes with the significant decrease in their RNA levels; 3a, 3b and 3c are the identical genes with the significant increase in their RNA levels.  (C) The consistency between sub-arrays of the triplicate microarrays on the same gene chip demonstrated by the results of linear regression analysis of RNA levels detected by all the genes of the corresponding sub-arrays.  (D)  The reproducibility between the different gene chips demonstrated by the results of linear regression analysis of RNA levels detected by all the genes of the two different gene chips. 

Reproducible microarray findings are guaranteed by experimental design including the technical triplicate (three measurements per gene probe), the experimental triplicate (three microarray experiments per sample), and appropriate biological repeats (the sample size or power calculation).