Rockefeller University maps genetic interactions of essential genes in M. tuberculosis
Researchers built a dual-sgRNA CRISPRi platform and mapped interactions among nearly all essential genes of M. tuberculosis and M. smegmatis, finding thousands of new ones.

Researchers at Rockefeller University, in Jeremy Rock's Laboratory of Host-Pathogen Biology, have published in Nature a map of genetic interactions among essential genes of Mycobacterium tuberculosis (Mtb) and the model species Mycobacterium smegmatis (Msm). The paper is available via dx.doi.org, and the university announced it on 4 November 2026 dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗. The maps cover nearly all essential genes of both species and, according to the authors, reveal thousands of previously unrecognized interactions
dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗.
Mtb causes tuberculosis, which the authors call the world's leading infectious cause of death. Many of its genes remain uncharacterized, which limits understanding of the disease and constrains drug development dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗. Treatment typically requires several antibiotics taken over months, and drug-resistant infections take longer to clear.
Dual-sgRNA CRISPRi platform
A genetic interaction is a combined phenotype that deviates from the expectation based on single-gene perturbations. Negative interactions, including synthetic lethality, give a more severe phenotype than expected, and positive ones a milder one dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗. Earlier transposon-based approaches in Mtb were typically restricted to non-essential genes, which excludes most antibiotic targets
dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗.
The team adapted the CombiGEM framework to the Mtb CRISPR-interference platform. Each sgRNA received a unique barcode, and the cloning workflow keeps the sgRNA–barcode link and places paired barcodes close together. This allows the abundance of each dual-sgRNA strain to be quantified by barcode sequencing dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗. The authors also implemented a statistical pipeline for detecting interactions with high confidence
dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗.
Results and validation
The maps recapitulate known biology and identify functional connections between essential genes and drug targets dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗. The authors also ran structure-based protein–protein interaction predictions for about 600,000 gene pairs represented in the maps. They report that a subset of the interactions likely reflects physical associations between proteins
dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗.
Selected interactions were tested experimentally. The validation covered drug–drug interactions and roles in the electron transport chain for several genes of unknown function dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗. The authors state that the work provides a generalizable framework for dual-gene perturbation and defines the architecture of essential-gene networks in mycobacteria
dx.doi.org
dx.doi.orgdx.doi.orgOpen source ↗.
All experiments were done in bacterial cultures. The paper does not report testing of new drugs or treatment regimens. Rock said this is the first comprehensive map of interactions among essential genes in a pathogen.
Sources · 2
Found a mistake?Read also



