Introduction

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 (1). Mitochondria are the only subcellular structures possessing distinct DNA (mitochondrial DNA or mtDNA) and transcription and translation machineries (2). Yet, the vast majority of mitochondrial proteins are encoded by the nuclear DNA, synthesized by ribosomes in the cytoplasm, and imported into the organelles (3). 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) (4,5), abnormalities in mitochondrial structure and function are increasingly recognized in common diseases, such as obesity, diabetes, cardiomyopathy, and migraine (6,7,8). 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 (9). 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 (10,11). For example, curcumin and arsenic induce apoptosis via a mitochondria-mediated pathway (12,13).

A high-throughput tool for profiling transcriptomes of the entire mitochondrion would be of great importance, as it would further improve our understanding of the mitochondria centered physiology, pathology, pharmacology, and toxicology for better diagnosis, prevention, and treatment of disease. To provide such a tool, we previously developed a first-generation human mitochondrial-focused cDNA microarray (hMitChip1, unpublished) and a second-generation human mitochondrial-focused cDNA microarray (hMitChip2) (14). hMitChip2, which contained only 501 nuclear DNA-encoded genes, was tested and validated in human skeletal muscle cells in an attempt to better understand mitochondrial involvement in glucocorticoid-induced myopathy (15). To make a comprehensively useful tool, we developed an integrated tool including a third-generation human mitochondria-focused cDNA micro-array (hMitChip3; with 37 mtDNA-encoded genes and 1098 nuclear DNA-encoded and mitochondria-related genes), computing procedures, database, and gene informatics. We tested these tools by comparing the transcriptomes of a rapidly dividing melanoma cell line UACC903 and a slowly dividing derivative cell line UACC903(+6) (16,17). Our results demonstrate that the high quality hMitChip3 and the accompanying software provide a novel integrated tool to facilitate human mitochondria-oriented research.

Materials and Methods

Gene Selection, Microarray Design, and Fabrication

Genes listed in the Mitoproteome database (www.mitoproteome.org/html/database.html) were selected for hMitChip3. In addition, the National Center for Biotechnology Information (NCBI) and other public databases were searched using keywords mitochondrial biogenesis and oxidative stress as previously described (14). Transcriptional loci predicted from sequences were not included. cDNA clones for the 37 human mtDNA-encoded genes were synthesized and sequence-verified by Geneart (Regensburg, Germany) based on GenBank® sequence (accession no. AP008773). Sequence-verified cDNA clones for nuclear DNA-encoded genes were purchased from Invitrogen (Carlsbad, CA, USA) and Origene (Rockville, MD, USA). Gene information was updated based on Unigene Build 189 (www.ncbi.nlm.nih.gov/UniGene). Test genes (1135), 146 positive controls (housekeeping and duplicate genes), and 79 negative controls (print-buffer without DNA) were printed in triplicate onto each hMitChip3 slide (see Supplementary Table S1 available online at www.gwumc.edu/biochem/faculty/su.html) as previously described (18), using the OmniGrid® 100 microarrayer (Genomic Solutions, Ann Arbor, MI, USA). Spike-in DNA controls for possible contamination (plasmid DNA), blocking efficiency (salmon sperm DNA), and cross-hybridization (human Cot-1 repetitive DNA), previously included in hMitChip2, were not necessarily repeated here (14,15).