From OpenWetWare

Neidi Negron Rodriguez, E.I.T.
Ph.D. Candidate

Massachusetts Institute of Technology
Department of Chemical Engineering
77 Massachusetts Avenue, Room 66-425
Cambridge, MA 02139

  • Phone: (617)-258-8037
  • Fax: (617)-258-5042
  • Email:

Biographical Information

  • Birthday: August 9
  • Birthplace: Puerto Rico
  • My Resume

Research Description

In many biopharmaceutical processes the use of high copy plasmids for the production of foreign proteins in host organisms is preferred in order to maximize product yields. However, the introduction of foreign genetic material directly interferes with the physiology of the host cell, altering the cell’s metabolic activities. This effect, generally known as metabolic burden, has the potential to reduce the productive capability of processes that require certain metabolites as substrates for small molecule production. In these cases, the expression level must be optimized to ensure maximum productivity. My work aims to explore the effects of changes in expression level by varying the gene dosage in a system for the production of polyphosphates (polyP) in E.coli. PolyP molecules are produced in a one-step reaction in which a terminal phosphate from an ATP molecule is transferred to a growing polyP chain by the action of the enzyme polyphosphate kinase (PPK). PolyP is ubiquitous in nature, but its production can be enhanced by the introduction and induction of additional copies of the ppk gene. Three different plasmids are used for this study: a low-copy mini-F plasmid; a medium-copy p15A type plasmid; and a high-copy pMB1 type plasmid. Measurements of copy number, mRNA levels, specific polyP content and PPK activity as a function of copy number are made during a 24-hour period. The time course experiments indicate the relationship between copy number and final product concentration and allow us to establish the optimal gene dosage for the system. The ultimate goal of this research is to derive some fundamental relationships that will allow the construction of optimal recombinant microorganisms for metabolic engineering purposes.