S. Ramaswamy, Ph.D.
CEO of c-CAMP, Dean, inStem, NCBS, Bangalore, India
Discovery, engineering and applications of Blue Fish Protein with Red Fluorescence
Swagatha Ghosh, Chi-Li Yu, Daniel Ferraro, Sai Sudha, Wayne Schaefer, David T Gibson and S. Ramaswamy
Fluorescent proteins and their applications have revolutionized our understanding of biology significantly. In spite of several years since the discovery of the classic GFP, proteins of this class are used as the standard flag bearers. We have recently discovered a protein from the fish Sanders vitrius that shows interesting fluorescent properties – including a 280 nm stoke shift and infrared emission. The crystal structure of the wild type protein shows that it is a tetramer. We have engineered mutations to make a monomer with very similar fluorescent properties. We have used this protein for tissue imaging as well as for in cell-fluorescence successfully
Srisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA
Applying Machine learning for Automated Identification of Patient Cohorts
Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland
Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.
Shrikant Anant, Ph.D.
The Department of Molecular & Integrative Physiology, Kansas University Medical Center, USA
Cancer Stem Cells: Target Colon Cancers
Shrikant Anant, Deep Kwatra and Dharmalingam Subramaniam
Colon cancer is a leading cause of cancer related deaths in the US, and its rate is increasing at an alarming rate in lndia. Recent studies have suggested the drug resistance role for a mall number of cells within a tumor called cancer stem cells. We identified the colon cancer stem cell marker DCLK1, a member of the protein kinase superfamily and the doublecortin family. The protein encodes a Cterminal serinethreonine protein kinase domain, which shows substantial homology to Ca2calmodulindependent protein kinase. Our current studies have been to identify compounds that can either affect DCLK1 expression or inhibits its activity as a way to inhibit cancer stem cells. Honokiol is a biphenolic compound that has been used in the traditional Chinese Medicine for treating various ailments. In vitro kinase assays with recombinant DCLK1 demonstrated that honokiol inhibits its kinase activity in a dose dependent manner. We therefore determined the effect of honokiol on stem cells. One method to look at effects on stem cells is perform a spheroid assay, where spheroids formation is suggested to maintain stemlike characteristic of cancer cells. Honokiol significantly suppressed colonosphere formation of two colon cancer cell lines HCT116 and SW480. Flow cytometry studies confirmed that honokiol reduced the number of DCLK1cells. A critical signaling pathway known to modulate intestinal stem cell proliferation is the Hippo signaling pathway, and deregulation of the pathway leads to tumor development. DCLK1cells had high levels of YAP1, the nuclear target of Hippo signaling. We determined the effect of honokiol on components of the hipposignaling pathway. Honokiol reduced the phosphorylation of Mst1/2, Lats1/2 and YAP1. Furthermore, honokiol treatment resulted in downregulation of YAPTEAD complex protein TEAD-1. Ectopic expression of the TEAD-1 partially rescued the cells from honokiol mediated growth suppression. To determine the effect of honokiol on tumor growth in vivo, nude mice harboring HCT116 tumor xenografts in their flanks were administered the compound intraperitoneally every day for 21 days. Honokiol treatment significantly inhibited tumor xenograft growth. Western blot and immunohistochemistry analyses demonstrated significant inhibition in the expression of stem marker and Hippo signaling proteins in the honokioltreated xenograft tissues. Taken together, these data suggest that honokiol is a potent inhibitor of colon cancer that targets DCLK1 stem cells by inhibiting Hippo signaling pathway.
Aswath Balakrishnan, Kapaettu Satyamoorthy and Manjunath B Joshi
Introduction
Insulin resistance is a hall mark of metabolic disorders such as diabetes. Reduced insulin response in vasculature leads to disruption of IR/Akt/eNOS signaling pathway resulting in vasoconstriction and subsequently to cardiovascular diseases. Recent studies have demonstrated that inflammatory regulator interleukin-6 (IL-6), as one of the potential mediators that can link chronic inflammation with insulin resistance. Accumulating evidences suggest a significant role of epigenetic mechanisms such as DNA methylation in progression of metabolic disorders. Hence the present study aimed to understand the role of epigenetic mechanisms involved during IL-6 induced vascular insulin resistance and its consequences in cardiovascular diseases.
Materials and Methods
Human umbilical vein endothelial cells (HUVEC) and Human dermal microvascular endothelial cells (HDMEC) were used for this study. Endothelial cells were treated in presence or absence of IL-6 (20ng/ml) for 36 hours and followed by insulin (100nM) stimulation for 15 minutes. Using immunoblotting, cell lysates were stained for phosphor- and total Akt levels to measure insulin resistance. To investigate changes in DNA methylation, cells were treated with or without neutrophil conditioned medium (NCM) as a physiological source of inflammation or IL-6 (at various concentrations) for 36 hours. Genomic DNA was processed for HPLC analysis for methyl cytosine content and cell lysates were analyzed for DNMT1 (DNA (cytosine-5)-methyltransferase 1) and DNMT3A (DNA (cytosine-5)-methyltransferase 3A) levels using immunoblotting.
Results
Endothelial cells stimulated with insulin exhibited an increase in phosphorylation of Aktser 473 in serum free conditions but such insulin response was not observed in cells treated with IL-6, suggesting chronic exposure of endothelial cells to IL-6 leads to insulin resistance. HPLC analysis for global DNA methylation resulted in decreased levels of 5-methyl cytosine in cells treated with pro-inflammatory molecules (both by NCM and IL-6) as compared to untreated controls. Subsequently, analysis in cells treated with IL-6 showed a significant decrease in DNMT1 levels but not in DNMT3A. Other pro-inflammatory marker such as TNF-α did not exhibit such changes.
Conclusion
Our study suggests: a) Chronic treatment of endothelial cells with IL-6 results in insulin resistance b) Neutrophil conditioned medium and IL-6 decreases methyl cytosine levels c) DNMT1 but not DNMT3a levels are reduced in cells treated with IL-6.