Upinder S. Bhalla, Ph.D.
Professor & Dean, NCBS, Bengaluru, India
Watching the network change during the formation of associative memory
The process of learning is measured through behavioural changes, but it is of enormous interest to understand its cellular and network basis. We used 2-photon imaging of hippocampal CA1 pyramidal neuron activity in mice to monitor such changes during the acquisition of a trace conditioning task. One of the questions in such learning is how the network retains a trace of a brief conditioned stimulus (a sound), until the arrival of a delayed unconditioned stimulus (a puff of air to the eye). During learning, the mice learn to blink when the tone is presented, well before the arrival of the air puff.
The mice learnt this task in 20-50 trials. We observed that in this time-frame the cells in the network changed the time of their peak activity, such that their firing times tiled the interval between sound and air puff. Thus the cells seem to form a relay of activity. We also observed an evolution in functional connectivity in the network, as measured by groupings of correlated cells. These groupings were stable till the learning protocol commenced, and then changed. Thus we have been able to observe two aspects of network learning: changes in activity (relay firing), and changes in connectivity (correlation groups).
Ayyappan Nair, Ph.D.
Head, Business Development (Technologies, Discovery Biology), Anthem Biosciences & DavosPharma, New Jersey, USA
Inhibition of NF-κB regulated gene expression by chrysoeriol suppresses tumorigenesis in breast cancer cells
Amrutha K1, Pandurangan Nanjan1, Sanu K Shaji1, Damu Sunilkumar1, Subhalakshmi K1, Rashmi U Nair1, Lakshmi Rajakrishna2, Asoke Banerji1, Ayyappan Ramesh Nair1*,2
- School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Clappana P.O., Kollam – 690 525, Kerala, India
- Anthem Biosciences, No 49, Canara Bank Road, Bommasandra Industrial Area, Phase 1, Hosur Road, Bangalore – 560 099, Karnataka, India
Abstract: A large number of effective cancer-preventing compounds inhibit the activation of nuclear factor-κ B (NF-κB). It has been previously demonstrated that some flavonoids that are a vital component of our diet inhibits this pathway. As a consequence, many flavonoids inhibit genes involved in various aspects of tumorigenesis and have thus emerged as potential chemopreventive candidates for cancer treatment. We studied the effect of 17 different flavonoids, including the highly evaluated quercetin on the NF-κB pathway, and on the expression of MMP-9 and COX-2 (two NF-κB regulated genes involved in metastasis) in the highly invasive human breast cancer cell line MDA-MB-231. The findings suggest that not all the quercetin like flavone backbone compounds inhibit the NF-κB pathway, and that the highly hydoxylated flavonols quercetagetin and gossypetin did not inhibit this pathway, nor did it inhibit the expression of MMP-9 and COX-2. This indicates a correlation between inhibition of NF-κB and subsequent suppression of these NF-κB regulated genes. Here, we also report the novel observation that the not so well characterized methoxylated flavone chrysoeriol inhibited the NF-κB pathway, and was most potent in reducing the expression of MMP-9 and COX-2. Based on these observations, the cellular effects of chrysoeriol were evaluated in MDA-MB-231. Chrysoeriol caused cell cycle arrest at G2/M, inhibited migration and invasion, and caused cell death of macrophages that contributed to migration of these cancer cells. These effects of chrysoeriol make it a potential therapeutic candidate for breast cancer metastasis.
Deepthy Menon, Ph.D.
Associate Professor, Centre for Nanosciences & Molecular Medicine, Health Sciences Campus, Amrita University, Kochi, India
Nanobioengineering of implant materials for improved cellular response and activity
Deepthy Menon, Divyarani V V, Chandini C Mohan, Manitha B Nair, Krishnaprasad C & Shantikumar V Nair
Abstract
Current trends in biomaterials research and development include the use of surfaces with topographical features at the nanoscale (dimensions < 100 nm), which influence biomolecular or cellular level reactions in vitro and in vivo. Progress in nanotechnology now makes it possible to precisely design and modulate the surface properties of materials used for various applications in medicine at the nanoscale. Nanoengineered surfaces, owing to their close resemblance with extracellular matrix, possess the unique capacity to directly affect protein adsorption that ultimately modulates the cellular adhesion and proliferation at the site of implantation. Taking advantage of this exceptional ability, we have nanoengineered metallic surfaces of Titanium (Ti) and its alloys (Nitinol -NiTi), as well as Stainless Steel (SS) by a simple hydrothermal method for generating non-periodic, homogeneous nanostructures. The bio- and hemocompatibility of these nanotextured metallic surfaces suggest their potential use for orthopedic, dental or vascular implants. The applicability of nanotextured Ti implants for orthopedic use was demonstrated in vivo in rat models, wherein early-stage bone formation at the tissue-implant interface without any fibrous tissue intervention was achieved. This nanoscale topography also was found to critically influence bacterial adhesion in vitro, with decreased adherence of staphylococcus aureus. The same surface nanotopography also was found to provide enhanced proliferation and functionality of vascular endothelial cells, suggesting its prospective use for developing an antithrombotic stent surface for coronary applications. Clinical SS & NiTi stents were also modified based on this strategy, which would offer a suitable solution to reduce the probability of late stent thrombosis associated with bare metallic stents. Thus, we demonstrate that nanotopography on implant surfaces has a critical influence on the fate of cells, which in turn dictates the long term success of the implant.
Acknowledgement: Authors gratefully acknowledge the financial support from Department of Biotechnology, Government of India through the Bioengineering program.
Binu K Aa, Jem Prabhakarb, Thara Sc and Lakshmi Sd,∗
aDepartment of Clinical Diagnostics Services and Translational Research, Malabar Cancer Centre, Thalassery, Kerala, India.
bDivision of Surgical Oncology, Division of Pathology
dDivision of Cancer Research, Regional Cancer Centre, Thiruvananthapuram, Kerala, India.
Introduction
AIB1, a member of the nuclear co activators, promotes the transcriptional activity of multiple nuclear receptors such as the ER and other transcription factors. Chemokines produced by stromal cells have potential to influence ERα-positive breast cancer progression to metastasis. CXCR4 is the physiological receptor for SDF1, together shown to stimulate the chemotactic and invasive behavior of breast cancer cells to serve as a homing mechanism to sites of metastasis. We propose that over expression of AIB1 in breast cancer cells leads to increased SDF1 and CXCR4 expression, which induces invasion and metastasis of cancer cells.
Materials and Methods
Breast tumor and normal breast tissues from patients in Regional Cancer Centre, Thiruvananthapuram were used for study. The modulatory effect of AIB1 was studied in MCF-7 cells with AIB1 siRNA transfection along with treatment of 17β-Estradiol (E2), 4-hydroxytamoxifen (4OHT), combinations of E2 and 4OHT. The gene expression pattern and protein localization were assessed by RT-PCR and immunofluorescence microscopy respectively. The metastatic and invasive properties were assessed by wound healing assay. Quantitative colocalization analyses were done to assess the association of proteins using Pearson’s correlation coefficient.
Result and Conclusion
The mRNA and protein level expression of AIB1, CXCR4 and SDF1 were higher in tumor samples than in normal samples. AIB1 was localized to the nuclei whereas CXCR4 and SDF1 immunoreactivity were observed in the cytoplasm and to a lesser extent in the nuclei of tumor epithelial cells. In tumor samples the gene level expressions of AIB1 showed significant positive correlations with SDF1(r = 0.213, p = 0.018). CXCR4 showed significant positive correlation with SDF1 in gene (r = 0.498, p = 0.000) and protein levels(r = 0.375, p = 0.002). Quantitative colocalization analyses showed a marked reduction in expression of CXCR4 and SDF1 in siAIB1MCF-7 cells than MCF-7 cells with different treatment groups. Wound healing assay shows reduced wound healing in siAIB1 treated MCF-7 cells.
In recent years, targeting specific cancer pathways and key molecules to arrest tumor growth and achieve tumor eradication have proven a challenge; due to acquired resistance and homing of cancer cells to various metastatic sites. The present study revealed that silencing AIB1 can prevent the over expression of SDF1 and CXCR4. Co activator levels determine the basal and estrogen-inducible expression of SDF1, a secreted protein that controls breast cancer cell proliferation and invasion through autocrine and paracrine mechanisms (Hall et al. 2003). The effects of CXCR4 overexpression has been correlated with SDF1 mediated activation of downstream signaling via ERK1/2 and p38 MAPK and with an enhancement of ER-mediated gene expression (Rhodes et al. 2011). It is possible that over expression of AIB1 as a stimulant involved in the expression of CXCR4 might up-regulate the expression of prometastatic and angiogenic genes. Thus based on these observations it can be concluded that SDF1/CXCR4 overexpression, with significant association with AIB1 expression, itself contribute to the development of mammary cancer and metastatic progression.
Kal Ramnarayan, Ph.D.
Co-founder President & Chief Scientific Officer, Sapient Discovery, San Diego, CA, USA
A cost-effective approach to Protein Structure-guided Drug Discovery: Aided by Bioinformatics, Chemoinformatics and computational chemistry
With the mapping of the human genome completed almost a decade ago, efforts are still underway to understand the gene products (i.e., proteins) in the human biological and disease pathways. Deciphering such information is very important for the discovery and development of small molecule drugs as well as protein therapeutics for various human diseases for which no cure exists. As an example, with more than 500 members, the kinase family of protein targets continues to be an important and attractive class for drug discovery. While how many of the members in this family are actually druggable is still to be established, there are several ongoing efforts on this class of proteins across a broad spectrum of disease categories. Even though in general the protein structural topology might looks similar, there are issues with respect selectivity of identified small molecule inhibitors when, the lead molecule discovery is carried out at the ATP binding site. As an added complexity, allosteric modulators are needed for some of the members, but the actual site for such modulation on the protein target can not resolved with uncertainty. In this presentation we will describe a bioinformatics and computational based platform for small molecule discovery for protein targets that are involved in protein-protein interactions as well as targets like kinases and phosphatases. We will describe a computational approach in which we have used an informatics based platform with several hundred kinases to sort through in silico and identify inhibitors that are likely to be highly selective in the lead generation phase. We will discuss the implication of this approach on the drug discovery of the kinase and phosphatase classes in general and independent of the disease category.