Qasim K. Beg

(Ph.D. Microbiology)

Department of Biomedical Engineering

Boston University, Boston, MA 02215 (Map)

Phone: (617) 358-6318; Fax: (617) 353-6766; E-mail: qasimbeg@bu.edu

Research Groups: http://prelude.bu.edu; http://gardnerlab.bu.edu

 

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Research activities:

 

1. Current (Boston University, MA): The past two decades of research on S. oneidensis MR-1 (formerly called Alteromonas putrificiens) has shown that it is an environmentally ubiquitous and metabolically-versatile bacterium with a capacity to reduce broad spectrum of undesirable metals from the environment. Its unique respiratory capabilities make this bacterium particularly suitable for bioenergy-related applications such as bioremediation, microbial fuel cells and biohydrogen production. However, in order to turn the special capabilities of this bacterium into useful applications, it is necessary to reach a thorough understanding of its physiological, metabolic, proteomic and transcriptional regulatory properties. This understanding, encoded in experimentally supported quantitative models, will make it possible to engineer and optimize the organism and its environment towards improved performance. Currently, we are in process of building an integrated understanding of the metabolic and gene regulatory systems of S. oneidensis MR-1 and their impact on the electron flux. Using a combination of experimental and computational approaches, we are trying to define regulatory coupling between catabolic and respiratory pathways, and integrating transcriptional and metabolic regulatory networks of S. oneidensis MR-1.

2. Past (University of Pittsburgh, PA; and Northwestern University, Chicago, IL):

Project 1-Metabolic Constraints in E. coli: The effect of Macromolecular Crowding (MC) on metabolic networks and cell function is still an unsolved problem in the constraint-based literature, and has received very little formal attention. To assess the effect of MC on the activity of metabolic networks, we used a modified FBA model that takes into account the constraint imposed by inherent limit on the attainable concentration of enzymes in the crowded cytoplasm. We performed experimental measurements on E. coli and analyzed intracellular fluxes, enzyme activities, extracellular substrates, and obtained the transcriptional profile using microarrays on various set of growth conditions to demonstrate that our new model (FBAwMC) up to a great extent is sufficient to predict: 1./ maximum growth rates on individual carbon substrates; 2./ selective substrate uptake and utilization from a mixed-substrate environment; and 3./ existence of the regulatory events and metabolic shifts that occur in E. coli during growth-phase shifts in both multiple-, and single-substrate limited E. coli growth.

Project 2-Motifs and Origons in E. coli’s Transcriptional Regulatory Network: Our goal was to understand the biological significance of in silico models of complex transcriptional networks that arise from dynamic interactions among a variety of components and together form various origons, motifs, modules and networks in a cell. These networks do not function in isolation, however well characterized functional origons exist in biological systems. The diverse cellular processes of growth and development are controlled by origons connected in elaborate hierarchical and feedback structures. These origons regulate the cellular growth, and the genes within these are part of several metabolic pathways and are therefore involved in cellular response. Origons are responsible for autoregulation in intracellular regulation of gene expression and also in feedback inhibition in metabolic pathways. Our goal was to understand the fundamental organizational levels of these biological systems using computational and experimental approaches.

Project 3-‘Aerobic-Anaerobic’ Switch in E. coli: We studied the dynamic transcriptional response of E. coli in a rich medium during its growth at aerobic-anaerobic shift interface in a steady state bioreactor. A new machine-learning method SEREND (SEmi-supervised REgulatory Network Discoverer) was developed and used to study gene expression changes in E. coli MG1655 during aerobic-anaerobic shift. SEREND uses a curated database of verified transcriptional factor (TF)-gene interactions, DNA sequence binding motifs, and a compendium of gene expression data in order to make thousands of new predictions about TF-gene interactions, including whether a TF activates or represses the gene. Using genome-wide binding datasets for several TFs, we demonstrated that our strategy improves the prediction of targets for a given TF on our microarray gene expression dataset for the ‘aerobic-anaerobic’ shift response in E. coli. We used our inferred interactions with the verified interactions to reconstruct a dynamic regulatory network for this response. The reconstructed network, when using our inferred interactions, was better able to correctly identify known regulators and suggested additional activators and repressors as having important roles during the ‘aerobic-anaerobic’ shift interface.

 

3. Ph.D. Microbiology (University of Delhi, India): My Ph.D. research in Microbiology was on the "Characterization and application of a Bleach-stable alkaline protease from Bacillus mojavensis in detergent formulations". B. mojavensis, a natural isolate produced an extracellular bleach-stable alkaline serine protease, which was optimally active at a high alkaline pH and exhibited 60°C as optimum temperature for maximum activity. I used this isolate for production, purification, characterization and applications of its alkaline protease in detergent formulations. Study of properties and compatibility of the B. mojavensis alkaline protease with various laboratory and commercial bleach, detergent, surfactants, and pH and temperature kinetics, and comparison of its properties with other commercially available alkaline proteases proved that this alkaline protease can be used for large-scale application in detergent formulations.

 

4. MS Microbiology (Panjab University, Chandigarh, India): The area of my research during the MS program in Microbiology was on production and characterization of alkaline xylanases and pectinases from microorganisms, and both these enzymes were also tested for their applications in biobleaching of pulp for a step towards minimizing the use of hazardous chlorine-based chemicals used by commercial paper producing industries.

 

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