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Massachusetts Institute of Technology

A synthetic biology platform for malaria parasites based on orthogonal transcriptional control

Abstract

dc:description.abstract

Malaria is responsible for half a million deaths each year in some of the poorest communities around the world. Furthermore, the evolution of drug resistance among malaria parasites threatens to continue this trend. However, our understanding of malaria parasite biology is held back by a lack of tools with which to study the function of their genes. In light of this, we have created systems that control gene expression in the malaria parasite Plasmodium falciparum using bacterial repressor proteins. These are the first tools to reliably control malaria parasite transcription and offer the most robust method of conditional gene expression in Plasmodium parasites to date. We develop automated DNA design software to apply this technology to study essential parasite genes for functional genomics and confirm compound-protein interactions for drug discovery. We hope these tools advance efforts to engineer and control malaria parasites in the future.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Biological Engineering
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cárdenas Ramírez, Pablo
Advisor dc:contributor.advisor
  • Niles, Jacquin C.

Rights

dc:rights
Statement dc:rights
  • Attribution 4.0 International (CC BY 4.0)
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/157237
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/157237

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Cárdenas Ramírez, Pablo. A synthetic biology platform for malaria parasites based on orthogonal transcriptional control. Massachusetts Institute of Technology, 2024. https://hdl.handle.net/1721.1/157237