Jason Walther: Difference between revisions
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== Contact Information == | == Contact Information == | ||
:Laboratory for Bioinformatics and Metabolic Engineering<br> | |||
Laboratory for Bioinformatics and Metabolic Engineering<br> | :Department of Chemical Engineering<br> | ||
Department of Chemical Engineering<br> | :Building 56, Room 422<br> | ||
Building 56, Room 422<br> | :77 Massachusetts Avenue<br> | ||
77 Massachusetts Avenue<br> | :Cambridge, MA 02139<br> | ||
Cambridge, MA 02139<br> | :Phone: (617) 253-6591<br> | ||
Phone: (617) 253-6591<br> | :Fax: (617) 253-7181 | ||
Fax: (617) 253-7181 | |||
== Research Interests == | == Research Interests == | ||
< | The goal of metabolic flux analysis (MFA) is the quantitative determination of all intracellular fluxes in a system of interest. Results are obtained by introducing a labeled substrate (usually a labeled carbon source) into a cell culture, measuring relative labeling in metabolic byproducts, and computationally processing these measurements to arrive at fluxes. Various computational techniques have been developed for flux analysis of isotopically stationary systems (Wiechert <i>et al</i>., 1999; Antoniewicz <i>et al</i>., 2006). These methods require that enough time elapse following the introduction of labeled substrate so that metabolites of the cells under study reach a constant state of isotopic labeling. | ||
</ | I aim to (1) adapt one of these previous models such that it can generate fluxes for isotopically instationary systems and (2) apply this new instationary model to an engineered strain of <i>E</i>. <i>coli</i>. Instationary metabolic flux analysis (IMFA), though computationally more complex, claims several advantages over its stationary analog. First, the amount of prohibitively expensive labeled substrate required for an experiment is greatly reduced. Second, the duration of such an experiment is considerably shortened, adding credibility to the metabolic steady-state assumption necessary for all flux analyses. Third, instationary flux analysis allows the pool sizes of all metabolites, including intracellular intermediates, to be estimated in addition to the fluxes themselves. | ||
== Education== | == Education== | ||
Revision as of 08:26, 15 March 2006
Contact Information
- Laboratory for Bioinformatics and Metabolic Engineering
- Department of Chemical Engineering
- Building 56, Room 422
- 77 Massachusetts Avenue
- Cambridge, MA 02139
- Phone: (617) 253-6591
- Fax: (617) 253-7181
Research Interests
The goal of metabolic flux analysis (MFA) is the quantitative determination of all intracellular fluxes in a system of interest. Results are obtained by introducing a labeled substrate (usually a labeled carbon source) into a cell culture, measuring relative labeling in metabolic byproducts, and computationally processing these measurements to arrive at fluxes. Various computational techniques have been developed for flux analysis of isotopically stationary systems (Wiechert et al., 1999; Antoniewicz et al., 2006). These methods require that enough time elapse following the introduction of labeled substrate so that metabolites of the cells under study reach a constant state of isotopic labeling.
I aim to (1) adapt one of these previous models such that it can generate fluxes for isotopically instationary systems and (2) apply this new instationary model to an engineered strain of E. coli. Instationary metabolic flux analysis (IMFA), though computationally more complex, claims several advantages over its stationary analog. First, the amount of prohibitively expensive labeled substrate required for an experiment is greatly reduced. Second, the duration of such an experiment is considerably shortened, adding credibility to the metabolic steady-state assumption necessary for all flux analyses. Third, instationary flux analysis allows the pool sizes of all metabolites, including intracellular intermediates, to be estimated in addition to the fluxes themselves.
Education
| 2003 | M.Eng. | Bioengineering | Tokyo Institute of Technology |
| 2001 | B.S. | Chemical Engineering | Case Western Reserve University |
Publications
- Walther JL, Bartlett DW, Chew W, Robertson CR, Hostetter TH, and Meyer TW. Downloadable computer models for renal replacement therapy. Kidney Int. 2006 Mar;69(6):1056-63. DOI:10.1038/sj.ki.5000196 |
- Meyer TW, Walther JL, Pagtalunan ME, Martinez AW, Torkamani A, Fong PD, Recht NS, Robertson CR, and Hostetter TH. The clearance of protein-bound solutes by hemofiltration and hemodiafiltration. Kidney Int. 2005 Aug;68(2):867-77. DOI:10.1111/j.1523-1755.2005.00469.x |
