VEGF inhibitor (Iressa) arrests histone deacetylase expression: single-cell cotransfection imaging cytometry for multi-target-multi-drug analysis

Development of Fangjiomics for Systems Elucidation of Synergistic Mechanism Underlying Combination Therapy

The rapid development of omics technology provides an opportunity for fulfilling the understanding of the synergistic mechanism of combination therapy. However, a systems theory to analyze synergy remains an ongoing challenge. Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism which has been utilized to systematically elucidate the synergistic mechanisms underlying combination therapy using multi-target-, pathway- or network-based quantitative methods. Besides, our ability to understand the polyhierarchical structure in synergy is driven based on multi-level omics data fusion in Fangjiomics. According to the basic principle of “Jun-Chen-Zuo-Shi”, further global integration across various omics platforms and phenotype-driven quantitative multi-scale modeling would accelerate development in Fangjiomics-based dissection of synergy in multi-drug combination therapies.

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Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism.

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We developed the pathway-based analysis of synergistic mechanisms in Fangjiomics.

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The theory of network-based synergistic targets is proposed in Fangjiomics.

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The hierarchical relationship of synergy in multilevel omics is dissected in Fangjiomics.

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The principle of “Jun-Chen-Zuo-Shi” is proposed to accelerate the development in Fangjiomics-based dissection of synergy.

Cell lysis-free quantum dot multicolor cellular imaging-based mechanism study for TNF-α-induced insulin resistance

Background

TNF-α is an inflammatory cytokine that plays an important role in insulin resistance observed in obesity and chronic inflammation. Many cellular components involved in insulin signaling cascade are known to be inhibited by TNF-α. Insulin receptor substrate (IRS)-1 is one of the major targets in TNF-α-induced insulin resistance. The serine phosphorylation of IRS-1 enables the inhibition of insulin signaling. Until now, many studies have been conducted to investigate the mechanism of TNF-α-induced insulin resistance based on Western blot. Intracellular protein kinase crosstalk is commonly encountered in inflammation-associated insulin resistance. The crosstalk among the signaling molecules obscures the precise role of kinases in insulin resistance. We have developed a cell lysis-free quantum dots (QDots) multicolor cellular imaging to identify the biochemical role of multiple kinases (p38, JNK, IKKβ, IRS1^ser, IRS1^tyr, GSK3β, and FOXO1) in inflammation-associated insulin resistance pathway with a single assay in one run. QDot-antibody conjugates were used as nanoprobes to simultaneously monitor the activation/deactivation of the above seven intracellular kinases in HepG2 cells. The effect of the test compounds on the suppression of TNF-α-induced insulin resistance was validated through kinase monitoring. Aspirin, indomethacin, cinnamic acid, and amygdalin were tested.

Results

Through the measurement of the glycogen level in HepG2 cell treated with TNF-α, it was found that aspirin and indomethacin increased glycogen levels by almost two-fold compared to amygdalin and cinnamic acid. The glucose production assay proved that cinnamic acid was much more efficient in suppressing glucose production, compared with MAP kinase inhibitors and non-steroidal anti-inflammatory drugs. QDot multicolor cellular imaging demonstrated that amygdalin and cinnamic acid selectively acted via the JNK1-dependent pathway to suppress the inflammation-induced insulin resistance and improve insulin sensitivity.

Conclusion

The regulatory function of multiple kinases could be monitored concurrently at the cellular level. The developed cellular imaging assay provides a unique platform for the understanding of inflammation and insulin resistance signaling pathways in type II diabetes mellitus and how they regulate each other. The results showed that amygdalin and cinnamic acid inhibit serine phosphorylation of IRS-1 through targeting JNK serine kinase and enhance insulin sensitivity.

Non-biased and efficient global amplification of a single-cell cDNA library

Analysis of single-cell gene expression promises a more precise understanding of molecular mechanisms of a living system. Most techniques only allow studies of the expressions for limited numbers of gene species. When amplification of cDNA was carried out for analysing more genes, amplification biases were frequently reported. A non-biased and efficient global-amplification method, which uses a single-cell cDNA library immobilized on beads, was developed for analysing entire gene expressions for single cells. Every step in this analysis from reverse transcription to cDNA amplification was optimized. By removing degrading excess primers, the bias due to the digestion of cDNA was prevented. Since the residual reagents, which affect the efficiency of each subsequent reaction, could be removed by washing beads, the conditions for uniform and maximized amplification of cDNAs were achieved. The differences in the amplification rates for randomly selected eight genes were within 1.5-folds, which could be negligible for most of the applications of single-cell analysis. The global amplification gives a large amount of amplified cDNA (>100 μg) from a single cell (2-pg mRNA), and that amount is enough for downstream analysis. The proposed global-amplification method was used to analyse transcript ratios of multiple cDNA targets (from several copies to several thousand copies) quantitatively.