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).
Gillian Murphy, Ph.D.
Professor, Department of Oncology, University of Cambridge, UK
A novel strategy for targeting metalloproteinases in cancer
Epithelial tumours evolve in a multi-step manner, involving both inflammatory and mesenchymal cells. Although intrinsic factors drive malignant progression, the influence of the micro-environment of neoplastic cells is a major feature of tumorigenesis. Extracellular proteinases, notably the metalloproteinases, are key players in the regulation of this cellular environment, acting as major effectors of both cell-cell and cell-extracellular matrix (ECM) interactions. They are involved in modifying ECM integrity, growth factor availability and the function of cell surface signalling systems, with consequent effects on cellular differentiation, proliferation and apoptosis.This has made metalloproteinases important targets for therapeutic interventions in cancer and small molecule inhibitors focussed on chelation of the active site zinc and binding within the immediate active site pocket were developed. These were not successful in early clinical trials due to the relative lack of specificity and precise knowledge of the target proteinase(s) in specific cancers. We can now appreciate that it is essential that we understand the relative roles of the different enzymes (of which there are over 60) in terms of their pro and anti tumour activity and their precise sites of expression The next generations of metalloproteinase inhibitors need the added specificity that might be gained from an understanding of the structure of individual active sites and the role of extra catalytic domains in substrate binding and other aspects of their biology. We have prepared scFv antibodies to the extra catalytic domains of two membrane metalloproteinases, MMP-14 and ADAM17, that play key roles in the tumour microenvironment. Our rationale and experiences with these agents will be presented in more detail.
Suryaprakash Sambhara, DVM, Ph.D
Chief, Immunology Section, Influenza Division, CDC, Atlanta, USA
Making sense of pathogen sensors of Innate Immunity: Utility of their ligands as antiviral agents and adjuvants for vaccines.
Currently used antiviral agents act by inhibiting viral entry, replication, or release of viral progeny. However, recent emergence of drug-resistant viruses has become a major public health concern as it is limiting our ability to prevent and treat viral diseases. Furthermore, very few antiviral agents with novel modes of action are currently in development. It is well established that the innate immune system is the first line of defense against invading pathogens. The recognition of diverse pathogen-associated molecular patterns (PAMPs) is accomplished by several classes of pattern recognition receptors (PRRs) and the ligand/receptor interactions trigger an effective innate antiviral response. In the past several years, remarkable progress has been made towards understanding both the structural and functional nature of PAMPs and PRRs. As a result of their indispensable role in virus infection, these ligands have become potential pharmacological agents against viral infections. Since their pathways of action are evolutionarily conserved, the likelihood of viruses developing resistance to PRR activation is diminished. I will discuss the recent developments investigating the potential utility of the ligands of innate immune receptors as antiviral agents and molecular adjuvants for vaccines.
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.
Jeff Perry, Ph.D.
Assistant Professor, University of California, Riverside
Combined Crystallography and SAXS Methods for Studying Macromolecular Complexes
Recent developments in small angle X-ray scattering (SAXS) are rapidly providing new insights into protein interactions, complexes and conformational states in solution, allowing for detailed biophysical quantification of samples of interest1. Initial analyses provide a judgment of sample quality, revealing the potential presence of aggregation, the overall extent of folding or disorder, the radius of gyration, maximum particle dimensions and oligomerization state. Structural characterizations may include ab initio approaches from SAXS data alone, or enhance structural solutions when combined with previously determined crystal/NMR domains. This combination can provide definitions of architectures, spatial organizations of the protein domains within a complex, including those not yet determined by crystallography or NMR, as well as defining key conformational states. Advantageously, SAXS is not generally constrained by macromolecule size, and rapid collection of data in a 96-well plate format provides methods to screen sample conditions. Such screens include co-factors, substrates, differing protein or nucleotide partners or small molecule inhibitors, to more fully characterize the variations within assembly states and key conformational changes. These analyses are also useful for screening constructs and conditions that are most likely to promote crystal growth. Moreover, these high throughput structural determinations can be leveraged to define how polymorphisms affect assembly formations and activities. Also, SAXS-based technologies may be potentially used for novel structure-based screening, for compounds inducing shape changes or associations/diassociations. This is addition to defining architectural characterizations of complexes and interactions for systems biology-based research, and distinctions in assemblies and interactions in comparative genomics. Thus, SAXS combined with crystallography/NMR and computation provides a unique set of tools that should be considered as being part of one’s repertoire of biophysical analyses, when conducting characterizations of protein and other macromolecular interactions.
1 Perry JJ & Tainer JA. Developing advanced X-ray scattering methods combined with crystallography and computation. Methods. 2013 Mar;59(3):363-71.
