Harvey Rubin - US grants

DESCRIPTION: (Adapted from the applicant's abstract and Specific Aims.) Inhibitors of proteolytic enzymes have multiple roles in limiting the molecular and cellular mechanisms of inflammation, which if not controlled, would result in acute and chronic lung damage. Specifically, human neutrophil elastase (HNE), and other neutrophil proteases, are controlled by plasma proteins belonging to the serine protease inhibitor (serpin) family of proteins. Inactivated or kinetically overwhelmed serpins result in unregulated proteolytic activity which often has severe and life-threatening consequences. The proposed experiments focus on the molecular biology, structural biology and biochemistry of human serpins and serine proteases in order to define the molecular interactions between these two species. Given the central role of HNE in the pathophysiology of a wide variety of lung diseases, this enzyme was chosen as the model target protease, for these studies. The Specific Aims are to determine the mechanism and structural basis of: 1) the one-to-one stoichiometry of inhibition between a serpin and HNE; 2) the rate constant of inhibition of HNE; and 3) the long-term stability of the serpin-HNE complex. The investigations proposed will utilize the high resolution crystal structure of an intact, active recombinant variant of antichymotrypsin which is an inhibitor of HNE, cathepsin G and chymotrypsin and a general kinetic scheme of serpin/enzyme reactions to guide the design and analysis of specific recombinant serpins. The three dimensional structure and biochemical properties of the newly created series of serpins will be analyzed in order to devise a structure/function algorithm that will provide a foundation on which to base a more complete understanding of the molecular properties of the serpins.

The research program proposed in this application is to understand three levels of regulation of P. falciparum (Pf) ribonucleotide reductase--the allosteric control of substrate catalysis, subunit interaction and the iron/tyrosine redox center and to use this fundamental information in the design and testing of specific antimalarial agents. Malaria remains one of the leading causes of death worldwide, being responsible for more than 2 million deaths per year. The increasing incidence of drug resistant malaria makes the development of new approaches to antimalarials a high priority. RR is a two subunit, cell cycle regulated, iron and oxygen dependent allosteric enzyme that is the first committed step in DNA replication catalyzing a radical mediated 2' reduction of ribonucleoside diphosphates to deoxyribonucleoside diphosphates. Agents that inhibit RR are known to inhibit growth patterns of P. falciparum. RR is therefore a prime target for the development of specific antimalarial agents. In this research, we plan to l) Utilize recombinant Pf RR to characterize the unique biochemical properties of the enzyme. 2) Design and synthesize peptides, peptide-mimetics and constrained peptides that disrupt the subunit interaction and test these RR inhibitors in Pf infected red cell cultures 3) Analyze the structure-function-activity properties of classes of compounds that destroy the iron/tyrosine redox center of the enzyme and test these agents in Pf infected red cell cultures.

There is a fundamentally new intersection of computer scientists, mathematicians and molecular biologists working in an area loosely known as DNA computation, in which the basic set of questions are in the process of being defined. The field was born in 1994 when Len Adleman (USC) showed how to solve a version of the traveling salesman problem using DNA (Molecular Computation of Solutions to Combinatorial Problems. Science, 266, 1021-1024, 1994). Adleman's paper had a catalytic effect on the scientific imagination even though it admittedly solved only a "toy" problem that could easily be solved using pencil and paper, let alone a teraflop supercomputer. By clearly articulating the principles of his computation, the massive parallelism inherent in DNA reactions, the energy efficiency of these reactions, and the enormous storage capacity of DNA, he challenged the community to discover the limitations of this approach. Furthermore, it is widely believed that, if these principles are scalable, the potential of DNA computation would be truly spectacular. Richard Lipton (Princeton) published a paper a few months later in Science (DNA Solution of Hard Computational Problems. Science 268, 542-545, 1995) generalizing Adleman's result to a fundamental problem in the class of problems known as NP complete. The objectives of the Third DIMACS Workshop on DNA Based Computers will be to present new work in the field and to disseminate in printed and electronic form, information in all areas that relate directly to computing with DNA including: algorithms, applications, techniques, architectures, practical obstacles to DNA based computers, proposed solutions to such obstacles, computational processes in vivo, and relevant ideas regarding biological evolution. We will encourage papers reporting experimental results. The Organizing Committee is composed of a diverse group of individuals from around the United States. The Committee has made a commitment to make sure that st udents and investigators with various and diverse backgrounds will attend the meeting. We expect approximately 200 individuals will attend. DNA Computation, is a relatively new field, without an established Journal. The June International Meetings are the focus for the field. The Conference will be held at The University of Pennsylvania, Philadelphia, Pennsylvania on June 23-25, 1997. The meeting will be announced in several scientific journals as well on as on a dedicated web site. There will be three days of talks with time for informal sessions and impromptu presentations. The Proceedings of the Conference will be disseminated, as before, by AMS- DIMACS.

There are several varieties of "evolutionary computation" based on analogies from the theory of natural evolution. In molecular biology, similar analogies are the basis of experiments on "in vitro evolution." From the beginning of DNA computing there has been an obvious appeal to the idea of marrying these two approaches. This KDI project brings these two approaches together. It provides DNA implementations for executing and assessing two classes of Genetic Algorithm computations, using population sizes larger than is usually practical with conventional computers. This project has two major goals addressing two problem types from the practice of Genetic Algorithms. The first goal is to demonstrate a DNA computation of a classic Genetic Algorithms test problem known as "Max 1s." This test problem evolves a given initial population of bitstrings until some bitstrings match a predetermined target. Two-dimensional denaturing gradient gel electrophoresis (DGGE) is used in the laboratory to physically separate candidate strands of DNA according to how well they match copies of a prespecified target strand. Molecular biological techniques are adapted to perform crossover, random mutation, and amplification of candidates. The second major goal demonstrates a class of Genetic Algorithms computations known as "Cold War problems." These problems do not involve prespecified matching targets; hence they produce outcomes which are not obvious in advance. In a Cold War problem, DNA strands encode two populations of "offers." In every generation these encoded offers are separately evolved by each of two proposers according to their own private preferences. When the two populations are combined, DGGE physically separates the most nearly matched pairs of offers.
Partially matched offers are returned to their respective proposers to become the "parents" of the next generation. Cold War problems are two-party specializations of multi-party coalition games with sidepayments. This project contributes to two disciplines. Evolutionary computation gains access to populations billions of times larger than are practical with conventional computers. Molecular biology is enhanced by laboratory techniques which combine both crossover and random mutation.

DESCRIPTION (Adapted from the Applicant's Abstract): It is widely and reasonably believed that oxygen limitation, amino acid starvation and carbon source restriction are involved in establishing and maintaining Mycobacterium tuberculosis in a dormant state. Correspondingly, emergence from dormancy is related to a partial or complete amelioration of these conditions. The investigators' major hypothesis is that enzyme systems responding to and regulating the effect of these physiological conditions control the fate of the organism as it goes through the process of dormancy and recovery. They have identified three enzyme systems that comprise regulatory networks in MTb and are independent of a specific animal or culture model of dormancy: These are: 1) the ribonucleotide reductase system that reduces ribonucleotides to deoxyribonucleotides--the rate limiting step in DNA synthesis, 2) the cytochrome bd oxidase system involved in growth under microaerophilic conditions and, 3) the stringent response system, comprised of enzymes that synthesize and degrade guanosine tetra- and penta-phosphate, which regulate the synthesis of certain proteins and stable RNAs. The first two systems are oxygen responsive and the third is regulated by the availability of adequate amino acids and energy sources. The activity of the enzymes they are studying are regulated by physiological conditions relevant to the environment of dormant Mtb. In turn, the very nature of their enzymatic activity regulate the biochemical milieu in which the organism must survive. Their specific aim is to understand the molecular basis of the relationship between environmental conditions of dormancy and the protective enzymatic response. In addition to regulation at the protein level, they are interested in how the genes that encode these enzymes are regulated at the transcriptional level under various growth conditions and whether mutant strains of Mtb carrying a knock-out in the genes for these enzymes have the biochemically predicted phenotype in an animal model of Mtb dormancy. Understanding the biochemical and genetic regulation of these enzymes will provide important insights into the adaptive mycobacterial physiology that is necessary during critical phases of the life cycle of Mycobacterium tuberculosis.

The overall goal of the research program is to understand the regulation of serine proteases involved in inflammation and host defenses. An imbalance between serine protease activity and inhibition generates biochemical cascades that often establish and propagate the pathophysiological basis of a wide variety of diseases. We are studying a family of high molecular weight plasma and cellular proteins, the serpins--serine protease inhibitors, some of which have evolved the remarkable property of inhibiting these proteases with astonishingly fast rates. In particular, we are interested the regulation of human neutrophil elastase (HNE) because of its well documented role in inflammation. We will focus on the reaction between HNE and alpha1-protease inhibitor (sometimes referred to as alpha1- antitrypsin) which is physiologically the most important inhibitor of the enzyme. How serpins inhibit their target enzymes is only partially understood but is presumed to involve a series of exquisitely timed chemical and conformational steps. There are three critical features of the general inhibitory mechanism, 1) the recognition and binding event, 2) the initial chemical reaction in cleaving the scissile bond, i.e., acylation, of the serpin by the protease, 3) a conformational change in the serpin that starts to occur either prior to, or following, the acylation step leading to an alteration of the conformation of the enzyme. This last step results in the enzyme and serpin trapped in a covalent complex that prevents continued catalysis and release of free enzyme. Our approach to the problem of how a serpin recognizes, binds and then inhibits HNE is to systematically examine the basic structural and kinetic features of each step in the reaction pathway. We propose a structural model for each step and will test these models using combinations of analytical tools including rapid kinetic techniques, probes of chemical reactivity--pH and solvent isotope effects, and X-ray crystallographic and spectroscopic determinations of protein conformation.

EIA-0130385
Russell J. Deaton
University of Arkansas

Title: Modeling and Manufacture of Huge DNA Oligonucleotide Libraries for Computation

Computing with DNA, with its advantages of massive parallelism and huge information density, promises a number of revolutionary applications, as well as the potential to solve problems beyond the capabilities of conventional computers. A critical barrier, however, is unplanned crosshybridization among oligonucleotides. In order for the computations to be reliable and efficient, and to scale to larger problems, the DNA sequences have to be designed to minimize these unplanned crosshybridizations. Though pairwise hybridization is well modeled and understood, design of such libraries is challenging because of the huge number of pairwise hybridization's, and the conflicting constraints of maximizing the library size while minimizing crosshybridization.Therefore, to overcome these limitations, huge libraries of non-crosshybridizing DNA oligonucleotides are manufactured by in vitro evolution with a PCR-based protocol that selects from a random pool those oligonucleotides that are maximally mismatched. In addition, because enumeration of all pairwise hybridization energetic in a huge library is computationally prohibitive, a statistical approach, which is based upon spin glass physics, is used to model the library. The model is the basis for a set of analysis and design tools for application to the libraries.

Because of the fundamental importance of DNA hybridization in DNA computing, the modeling and manufacture of huge libraries of DNA oligonucleotides is producing foundational principles and results for the field. The size of the largest libraries of non-crosshybridizing oligonucleotides is also the limit on the size of feasible computation. The libraries are an enabling resource not only for large-scale DNA computations, but also biotechnology applications, such as reusable, universal DNA microarrays. In addition, the libraries, as well as the software tools, are available for reproduction and use by other researchers in DNA computing and biotechnology.

EIA-0130797 -Harvey Rubin-University of Pennsylvania-Modeling and Analysis of Biological and Information Networks

The overall goals of our research are to: 1) create enabling technologies and experimental systems that are necessary to understand and predict the integrated functions of two bacterial sensing and regulatory networks--porim osmo-regulation in E.coli and oxygen sensing regulation of DNA synthesis in Mycobacterium tuberculosis; 2) model and abstract principles of organization, design control and coordination of biological systems. We believe that a better understanding of networked, hybrid models in biology will provide deeper insights into networked, embedded systems. No systematic approach to designing and developing such hybrid systems exists today.

Our research on the porin osmo-regulatory system in E. coli will investigate crosstalk between the porin osmo-regulatory system and other signaling systems. We suggest that the ability of the sensing element of the system, EnvZ, to act as both a kinase and phosphatase is crucial for the control of information flow and to minimize crosstalk. We will extend our models in a related series of experiments on the PhoQ/PhoP two component systems, which responds to changes in the extracellular magnesium concentration. Since the levels of the histidine kinase PhoQ and response regulator PhoP are modulated by the concentration of phosphorylated PhoP, we will be able to establish the effect of this feedback and its influence on robustness of the overall system behavior.

EIA 0332251
Harvey Rubin
University of Pennsylvania
Project Summary


Biologically-Inspired Reliable Computing Systems:

Biologically-inspired computing seeks to understand and replicate some of the fundamental computational principles by which natural biological information processing systems operate. Traditional computing systems today are extremely brittle in situations for which they have not been explicitly designed. In comparison, biological systems are adaptable to new environments, can handle a large amount of uncertainty in their perception and processing of the surrounding world, and can collaborate with other biological systems to solve complex problems. Biological systems also have sophisticated protection and repair mechanisms. Is it possible for computing systems to display the same degree of robustness and reliability across a wide range of situations? What types of computational architectures and algorithms are needed to achieve this reliability? How can such systems be developed and organized to ensure they can deal with faults? How can these systems be put together to leverage their individual capabilities? Can their survivability be ensured? These are some of the questions this workshop seeks to address.

The workshop brings together researchers who work in areas close to biology and computer and information science to discuss how biological systems are able to achieve their robustness and reliability, and how some of these computing principles can be incorporated into artificial systems. The main focus of the workshop will be the reliability of biological computation and information processing, and will explore how this reliability is achieved in four areas: cognitive computing processes, development and self-organization, social interactions, and protection and immunity. The format will bring together researchers in each of these fields to delve into the relevant questions of how biological systems operate robustly and their applicability to computing systems.

The resulting presentations and discussions of the workshop will be made available through web-based publications as well as printed materials.

Garbage collection is a crucial component of many modern computer programming languages. Garbage collection frees programmers from the burden of explicit memory management, and is necessary for the independence of functional data objects in object-oriented programming paradigms. Unfortunately, traditional garbage collection algorithms are not ideally suited for concurrent operation in real-time embedded systems. On the other hand, cellular systems must also be able to identify and reclaim proteins that are no longer being used or are damaged or incomplete. The selective destruction and recycling of proteins is accomplished by the ubiquitin system in the cell. Proteins to be selectively destroyed are first identified and tagged with ubiquitin through a series of enzymatic reactions. These proteins are then degraded in the proteosome, and their constituent amino acids are recycled for the construction of new proteins.
We propose using hybrid systems to model the enzymatic pathways in the ubiquitin system to gain insight into their computational properties. Our modeling and simulation efforts will describe how the ubiquitin conjugation ligases and the proteosome interact to selectively recognize the appropriate protein substrates. Our results on the ubiquitin system will help motivate new garbage recognition algorithms for memory management in computer systems. These algorithms will be based upon the hierarchical composition of classifiers that recognize characteristic features of the objects in memory.
The educational goals of this proposal are closely tied to our research agenda. We hope to introduce students as well as other researchers to the importance of viewing biomolecular sytems as computational systems. The ubiquitin system will serve as a teaching illustration for students in seminars and future workshops, as well as for the public community through our collaboration with the Franklin Institute, the university's AMP summer program, and our annual Robotics for Girls workshop. Other educational activities will serve to inform and open dialogue between researchers in the engineering, biological sciences, and medical communities.

[unreadable] DESCRIPTION (provided by applicant): Type II NADH oxidoreductase (NDH-2), the initial step in the electron transport respiratory chain, is a critical enzyme in the life cycle of Mycobacterium tuberculosis (Mtb), the bacterium that kills more people world-wide than any other bacterial organism. The central role of NDH-2 in Mtb is supported by extensive evidence from biochemical (Weinstein 2005) and transcriptional studies (Boshoff 2005), gene network analysis (Cabusora 2005), gene deletion analysis, investigation of bacterial growth in various media and under various culture conditions (Xie 2005), and animal experiments (Weinstein 2005). Furthermore, isoniazid (INH) and ethambutol (ETH) are two of the standard anti-TB medications used throughout the world and increasing resistance to these medications is recognized as one of the most serious global public health threats. The discovery that a mechanism of INH drug resistance in Mycobacterium tuberculosis is linked to mutations in Mtb NDH-2 that decrease its activity is profoundly important (Miesel 1998; Lee 2001; Vilcheze 2005). Not only is NDH-2 an important enzyme in its biomedical context, it is has certain unique biochemical and structural properties compared to other bacterial type II NADH oxidoreductases. However, very little is known about 1) the catalytic reaction mechanism of wild-type Mtb NDH-2 and INH resistant forms of Mtb NDH-2, 2) the mode of action of inhibitors of the enzyme and 3) the effect of alterations in concentration and activity of NDH-2 on the bioenergetics and biochemistry of the bacterial membrane and the growth phenotypes. Therefore, the overall goals of this grant proposal are (1) to understand the molecular mechanism of the catalytic reaction of wild-type Mtb NDH-2 and INH resistant forms of Mtb NDH-2, (2) to understand the molecular basis of phenothiazine inhibition of these enzymes, and 3) to determine the bacteriologic effects of mutations in NDH-2 and inhibitors of the enzyme in Mtb, M. bovis and M. smegmatis. [unreadable] [unreadable] [unreadable]

This project seeks to address fundamental gaps in the understanding of collective behavior, and to develop a methodology for software design for cyber physical systems that use sensing, communication, and actuation to accomplish tasks that are well beyond the capabilities of individual units. Specifically, the focus is on methodologies that will allow cyber physical systems to adapt to changing environmental conditions and be resilient to disturbances and attacks, and tools to translate design specifications for the group to software design specifications for individual units by essentially solving the inverse problem for networked cyber physical systems.

This research represents the cross pollination of research in molecular, cell and population biology, systems modeling, control theory and robotics. It brings novel modeling approaches and recent results in systems biology to bear on the problem of designing and architecting cyber physical systems. Specifically, it will establish a framework for designing and realizing algorithms for real-time, aggregated networked systems across multiple time-scales, and help develop the foundation for high-confidence software for reconfigurable, adaptive and resilient systems.

The project is expected to lay the foundation for a new community of researchers that include biologists, control theorists and roboticists through research workshops.

This award supports a workshop on Federal Workforce Capabilities for Biosecurity, June 8-10, 2007, Linthicum, MD. The purpose of the workshop is to advance technical understanding of emerging challenges in biosecurity and to develop new strategies for training the Federal biosecurity workforce. The focus of the workshop is on training and assessment approaches that will enhance capability of the workforce to address new developments in biotechnology.

This workshop on Mathematical Foundations of Open Systems explores new research directions towards a logical/mathematical foundation for modeling the behavior of dynamic open systems that evolve over time through self-organization, regulation, and adaptation to changing environments and structures. Such a framework should provide a unified approach for obtaining an advanced understanding of natural systems, the ability to fix and modify them, and to design cyber-physical systems (CPS) in principled ways using new notions of control and coordination. The workshop, held May 23-25, 2010, Philadelphia, PA, is supported by the NSF and other agency members of the interagency coordinating group on High Confidence Software and Systems.

Project Summary (Abstract): The overall goal of this research is to develop the genetic and bacterial systems to investigate the role of the widely encountered bacterial ?bet-hedging? strategy in the adaption to fluctuating environments. In the bet- hedging strategy, the bacterial colony bets that optimal growth conditions may not be sustained. To protect itself against these potential future threats, a very few number of individual cells, which remain isogenic with the rest of the colony, behave as if they sensed a stressful environment even prior to encountering the stress. Such environments could include changes in pH, temperature fluctuations, carbon source deprivation, or antibiotics. Currently there are no techniques to identify, track and study these rare bet-hedging cells in vitro or in vivo. Therefore, in order to achieve our research goal, we intend to design and validate a method to track individual bacteria that transiently express rare phenotypes. Once we are able to study these bet-hedgers before and after the stress is applied, we will be able to determine: i) what fraction of the population express this phenotype, ii) the number of cells expressing this altered phenotype that can be tolerated by the population, iii) what alterations in transcription, protein expression, enzyme pathways and metabolome contribute to this behavior, iv) whether these cells lie on the pathway to mutations that fix adaptive phenotypic traits in the emergent population, and v) the effect that delays in sensing the environment and the mean and variance of stochastic expression have on the cell types that eventually survive the environmental fluctuation. By the end of the two-year R21 grant we are confident that we will have developed a robust, useful cell lineage tracking system for E. coli.