Shigeki Miyamoto, Ph.D.
Professor, McArdle Laboratory for Cancer Research – UW Carbone Cancer Center
Department of Oncology, School of Medicine and Public Health
University of Wisconsin-Madison
“Inside-out” NF-κB signaling in cancer and other pathologies
The NF-κB/Rel family of transcription factors contributes to critical cellular processes, including immune, inflammatory and cell survival responses. As such, NF-κB is implicated in immunity-related diseases, as well as multiple types of human malignancies. Indeed, genetic alterations in the NF-κB signaling pathway are frequently observed in multiple human malignancies. NF-κB is normally kept inactive in the cytoplasm by inhibitor proteins. Extracellular ligands can induce the release of NF-κB from the inhibitors to allow its migration into the nucleus to regulate a variety of target genes. NF-κB activation is also induced in response to multiple stress conditions, including those induced by DNA-damaging anticancer agents. Although precise mechanisms are still unclear, research from our group has revealed a unique nuclear-to-cytoplasmic signaling pathway. In collaboration with bioengineers, clinicians and pharmaceutical industry, our lab has developed new methods to analyze primary cancer patient samples and identified several compounds with different mechanisms that mitigate this cell survival pathway. Further contributions from other labs have also revealed additional mechanisms and molecular players in this “inside-out” signaling pathway and expanded its role in other physiological and pathological processes, including B cell development, premature aging and therapy resistance of certain cancers. Our own new findings, along with these recent developments in the field, will be highlighted.
Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
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.
