Our lab is interested in quantitative analysis of biological processes. We use experiment and/or computational approaches to understand biological systems. In particular, we focus on following areas:
Physiological function of double-stranded RNAs and innate immune response proteins
Cellular dsRNAs are emerging as a new class of signaling molecules that regulate multiple signaling pathways. dsRNAs were originally considered as signature of viral RNAs and hence, the amount and type of cellular dsRNAs were believed to be highly limited. However, single-stranded RNAs can locally adapt secondary structure and can form intramolecular dsRNAs. Studies on cellular dsRNAs are necessary to understand and unravel the extent to which this new class of biomolecules plays a role in cell fate determination. As dsRNAs are often recognized by immune response proteins, investigating regulation of these RNAs in cells will also provide an important step toward better understanding of host immune response during infection or autoimmune disease.
We have developed formaldehyde crosslinking precipitation and sequencing (fCLIP-seq) technique to capture and identify cellular dsRNAs. In particular, we investigated dsRNAs that can bind to innate immune response protein PKR and regulate its activation status. We find that numerous noncoding RNAs from the nuclear genome can adopt double-stranded secondary structure and be recognized by PKR. Moreover, mitochondrial RNAs occupy the majority of PKR-interacting cellular dsRNA repertoire. Bidirectional transcription of mitochondrial genome results in generation of complementary RNA pairs which can bind with each other to form intermolecular double stranded RNAs. More importantly, these mt-dsRNAs are recognized by PKR and may regulate PKR activation without any external stimuli. Currently, we are activly investigating the regulation of these cellular dsRNAs and their role with respect to various human disease.
Image-based cancer diagnosis and classification
Currently, cancer diagnoses are done based on cell morphology, identifying fusion genes through DNA FISH analysis, and protein biomarker expression using FACS. Recently, post-transcriptional regulation such as RNA modification and splicing has been investigated in order to develop new biomarkers and device patient-specific treatment strategy. In our laboratory, we investigate and develop a novel cancer diagnosis method using RNA FISH and analysis of gene expression pattern using fluorescent images. We establish clinically applicable FISH assay using both cell lines and clinical samples to systematically diagnose and classify cancer. We also present guidelines for the development of new chemotherapy by quantifying the gene expression changes after administration of anticancer drugs using RNA FISH.
Quantitative imaging analysis of cell cycle
Cell cycle is a highly orchestrated process where gene expression is controlled through multiple regulatory layers to ensure proper DNA replication and chromosome segregation. Immunofluorescence and live-imaging techniques have allowed us to observe expression of key regulatory proteins and their dynamics during cell cycle progression. Our goal here is to develop computational tools to quantitatively assess the protein expression, localization, and kinetics to formulate mathematical models and elucidate processes that governs the cell cycle.