The 3rd Annual BME Symposium in Quantitative Biology and Physiology
Friday, December 1, 2006
Life Science and Engineering Building (24 Cummington Street) Rm. B01
Program
- 1:00 pm – John White (BME Chair)
Opening Remarks - 1:10 pm – Henry Lee
Computational Hints at Bifunctional Regulatory Roles for Protease Lon - 1:30 pm – Nathan Spencer
Microenvironmental Factors in Hair Cell Regeneration - 1:50 pm – Jaafar N. Sleiman Haidar
Measuring Residual Entropy of Folded Protein Backbone to Aid Prediction of Protein Stability and Interaction - 2:10 pm – Gavrielle Price
Quantitative Physiology of Engineered Microvessels - 2:30 pm – Andrew Krueger
Understanding Network Connectivity with Combination Chemicals - 2:50 pm – Keynote – Dr. Douglas Lauffenburger, MIT
Signaling Network Governance of Tumor Cell Migration and Invasiveness: Connecting Biochemical Pathways to Biophysical Processes and Cell Phenotypic Function - 3:50 pm – Coffee Break
- 4:20 pm – Emmanouela Filippidi
Biomaterial Self-Assembly in Microfluidic Devices - 4:35 pm – Eric Berns
Neuronal Excitation Thresholds for Amplitude-Modulated and Interferential Current Stimulation are Similar to Threshold for Carrier - 4:55 pm – Yingchun Zhou
Drug Target Prediction Using Sparse Simultaneous Equation Models of Gene Regulatory Networks - 5:15 pm – Harikrishnan Parameswaran
Imaging the Alveolar Structure of Mice in Three Dimensions - 5:35 pm – John White (BME Chair)
Closing Remarks
Abstracts
1:10 pm – Henry Lee
Computational Hints at Bifunctional Regulatory Roles for Protease Lon
Proteases degrade endogenous proteins and are critical for maintaining their function, concentration, and quality. This process is thought to occur by substrate recognition, and many degradome mapping studies seek to identify these protein substrates. We study the ATPase dependent protease, Lon, which is conserved from archaea to eukaryotes. In addition to having a well-characterized degradome, Lon has been shown to have a unique ability to tightly bind DNA. A role for this secondary function, however, is not yet understood. We hypothesize that Lon also acts as a negative regulator of transcription. We use a systems biology approach to study Lon in Escherichia coli. Starting with a compendium of microarray experiments, we first reverse engineer a genome-wide regulatory network. Overlaying protein-protein interactions on our network predicts that Lon regulates major heat shock genes. We apply time series analysis and motif searching to these genes to generate a more detailed hypothesis of Lon’s role in transcription.
1:30 pm – Nathan Spencer
Microenvironmental Factors in Hair Cell Regeneration
The chicken inner ear is unique in that adult hair cells regenerate after noise or gentamicin-induced damage. However, limited viability and very little regeneration have been achieved in culture. Thus, it is reasonable to suspect that the behavior of these cells is guided by their microenvironment. Moreover, they should survive and regenerate in response to damage in an optimal culture system. In current studies, the sensory epithelium of hair cells and supporting cells was displaced from the inner ear and placed on a series of artificial matrices with a broad range of biochemical compositions. The cells were labeled with Phalloidin, a marker for F-Actin in the stereocilia. This enabled us to quantify the size of the epithelium and density of hair cells with time as quantitative assessments of hair cell viability. Future studies will further attempt to mimic the in vivo system, so that viability and regeneration can be studied as a function of time and the microenvironment.
1:50 pm – Jaafar N. Sleiman Haidar
Measuring Residual Entropy of Folded Protein Backbone to Aid Prediction of Protein Stability and Interaction
Protein backbone flexibility is an important component of both folding and binding energetics; however, there is no accurate and rapid method for computing this major entropic factor. In this study, we have developed a simple measure for backbone entropy, using the distributions of 20 amino acids within helix, sheet or coil separately. Amino acid backbones within a secondary structure type form clusters that recapitulate the branching and hydrogen bonding properties of the side-chains. Unexpectedly, the same types of residues in coil and sheet have nearly identical backbone entropies. We further established an approach for computing the backbone entropy change of a mutation or upon the formation of a protein complex. When we applied our approach to all point mutations in the ProTherm database, we discovered that mutations that restrict backbone flexibility on average led to increased protein stability. We also discovered that computed backbone entropy loss had a strong correlation with experimentally determined association rate, when applied to 20 complexes of antibody and T-cell receptor with their ligands. Our results reveal that the backbones of folded proteins contain significant residual entropy that is proportional to the backbone entropy of the molten globule state of proteins. Our Findings should prove useful for designing mutations that improve protein stability or binding affinity.
2:10 pm – Gavrielle Price
Quantitative Physiology of Engineered Microvessels
My work examines the effect of flow on in vitro microvascular physiology. I exposed perfused engineered microvessels to different pressures, flow rates, pressure gradients, or shear stress, and measured the permeability of these vessels to albumin and 10 kD dextran. I found that large pressure gradients lowered permeability; conversely, low pressure gradients caused leaks to form. These results suggest that pressure gradients play an important role in the establishment of normal microvascular barrier, in vivo.
2:30 pm – Andrew Krueger
Understanding Network Connectivity with Combination Chemicals
A major goal in the systems biology community is to develop network models of cellular systems. More generally, there is a demand for the discovery of gene functions and their role in a biological system. Directed graphs, or networks offer a tidy representation of numerous functional interactions. Yet the network building problem is challenging because biological networks are complex systems and connections are not know a priori. Diverse network probes and analysis methods will be necessary to develop biological models. This work offers a network inference technique that uses cellular responses to combination chemical inhibitors to deduce target connectivity within a biological network. To understand how combination data reflects a topological relationship between targets, mathematical models of protein targets and inhibitors will be developed. Theoretical responses will be compared to an experiment where combination chemicals with known enzymatic targets are applied to a culture of Sacchromyces Cerevisiae. This methodology can be used in a model building process. An initial network model based on observed connections between components can be adjusted to minimize inconsistencies from a combination experiment. The resulting network can be used to predict the systems response to untested conditions, to identify sensitive loci within the system that can be manipulated for a desired outcome, or to gain insight into the principles that underlie biological function.
2:50 pm – Keynote – Dr. Douglas Lauffenburger, MIT
Signaling Network Governance of Tumor Cell Migration and Invasiveness: Connecting Biochemical Pathways to Biophysical Processes and Cell Phenotypic Function
Cell migration is critically involved in tumor progression, underlying proximal tiesue invasion and distal metastasis. Effective therapeutic interventions will require an improved understanding of how tumor cell migration is controlled, in terms of underlying biophysical processes and their regulation by biochemical signaling pathways. Because of the high degree of complexity involved in relating molecular-level mechanisms to cell- and tissue-level pathophysiological events, computational modeling across these scales appears to offer an attractive approach. This talk will present an overview of our combined experimental and computational efforts to develop models ascertaining how cell migration behavior depends on biophysical interactions between the cell and its environment and how those biophysical interactions are governed by signaling network activities integrating inputs from growth factor and extracellular matrix cues.
4:20 pm – Emmanouela Filippidi
Biomaterial Self-Assembly in Microfluidic Devices
The nano- and micron-scale structure of biomaterials may have significant implications on cell phenotype and activity. We are investigating the controlled micron-sized fiber and tube formation of biomaterials, such as collagen, in microfluidic devices. Finite element analysis complements our description of self-assembly under flow. In the future, we plan to perform X-ray diffraction under flow to elucidate the packing and self-assembly mechanisms of various biopolymers.
4:35 pm – Eric Berns
Neuronal Excitation Thresholds for Amplitude-Modulated and Interferential Current Stimulation are Similar to Threshold for Carrier
Sinusoidal, amplitude-modulated and interferential current were applied to the perirhinal cortex in brain slices of 15-19 day old rats. Carrier frequencies of 1-50 kHz were used with a modulation or beat frequency of 100 Hz. Fluorescent microscopy of the intracellular calcium concentration was utilized to observe the neuronal population response and to infer excitation thresholds for the different types of applied extracellular stimulation. Relative excitation thresholds were also measured using intracellular recordings via whole-cell patch clamp. Results show an increase in threshold with frequency for sinusoidal stimulation above 1 kHz. Thresholds for amplitude-modulated stimuli were slightly higher than the threshold for sinusoidal stimulation at the carrier frequency. Enhanced stimulation during interferential current stimulation (relative to the carrier alone) was not observed in the region of theoretical maximal beat. Together, these results strongly refute previous assertions that neurons demodulate the beating current produced by interferential therapy.
4:55 pm – Yingchun Zhou
Drug Target Prediction Using Sparse Simultaneous Equation Models of Gene Regulatory Networks
A major challenge in the development of new therapeutic drugs is the identification of the molecular targets of drug compound candidates. We consider the problem of identifying such candidates from DNA microarray data. Our approach is to cast the problem as one of identifying outliers in a large, sparse system of simultaneous equations, describing the influence of both the underlying gene regulatory structure and the external effects of the potential drug candidate. Inference is conducted in two stages: (i) a LASSO-type regression for extracting the influence of the gene regulatory network, and (ii) a residual analysis for outlier detection. We present empirical results demonstrating the capabilities of our method.
5:15 pm – Harikrishnan Parameswaran
Imaging the Alveolar Structure of Mice in Three Dimensions
Emphysema is a pulmonary disease characterized by the progressive destruction of alveolar walls and the associated abnormal enlargement of airspaces. Quantifying such structural alterations in three dimensions (3D) is essential to understanding the progressive nature of emphysema. Currently available methods for characterizing alveolar structure are limited to estimating 3D structure based on measurements from two dimensional (2D) tissue sections. Direct measurements in 3D have not been possible so far due of the lack of an imaging methodology that allows visualization of alveolar structure with the resolution and image quality required to identify individual alveoli. In this study, we used microfocal Computed Tomography (micro CT) imaging to visualize the structure of mouse lungs in 3D. Mouse lungs were isolated and fixed in formalin at total lung capacity. Small samples were cut from subpleural regions, stained with silver using a newly developed protocol, and imaged using micro CT. Continuous slices, 6 microns in thickness with 6 micron in-plane resolution, were obtained. Besides airway structure, we were also able to isolate individual alveoli from the micro CT images. The volume of individual alveoli was estimated and their equivalent alveolar diameters were calculated. The mean alveolar diameter in normal mouse was found to be in agreement with previously published values measured in 2D. The direct measurements of 3D structural properties should provide essential new information that can help better understand the progressive nature of emphysema.
