NIH grant: Transcription Accuracy as a Driver of Phenotypic Variability (1R01GM164395-01)

retained text

NIH grant 1R01GM164395-01: Transcription Accuracy as a Driver of Phenotypic Variability
Institute: {'code': 'GM', 'abbreviation': 'NIGMS', 'name': 'National Institute of General Medical Sciences', 'admin_org_id': '12500024', 'admin_funding_url': ''}. PI: Christophe  Herman. Award: $415523.
Start: 2026-07-17T00:00:00.
Accurate transcription is essential for faithful gene expression, yet even rare misincorporation
events can generate aberrant proteins or regulatory RNAs that profoundly alter cellular
physiology. In bacteria, transient bursts of transcription errors have been implicated in phenotypic
heterogeneity, enabling a subpopulation to survive sudden environmental stresses, such as
antibiotic exposure, without permanent genetic changes. The long-term objective of this proposal
is to define the mechanisms and consequences of transcription errors in Escherichia coli. The
objective of this proposal is to uncover the core processes behind transcription fidelity, discern its
impact on antibiotic survival, and determine the elements that control its accuracy. To achieve
these objectives, we are developing a targeted Accurate RNA consensus sequencing approach
(t-ARC-seq) to quantify transcription errors in specific mRNAs of low abundance. We will compare
RNA error patterns to DNA mutations, using lacI repressor gene as a benchmark. To further
explore the role of transcription errors, we will study how transcription accuracy impact antibiotic
tolerance. Specifically, we will investigate how transcription errors might activate antibiotic efflux
pumps that are regulated by the Multiple Antibiotic Resistance Activator, MarA. MarA activates
itself and is part of an operon including a repressor, MarR, inhibiting the synthesis of MarA. We
hypothesize that transcription errors in the marR mRNA could trigger burst in marA expression,
leading to activation of antibiotic efflux pumps and transient antibiotic tolerance. To validate this
hypothesis, we will utilize single-cell microscopy techniques coupled with classical genetic
approaches. Finally, we will characterize a new transcription-fidelity factors. Using a genetic
screen, we identified the UvrD helicase as a factor promoting transcription errors. We will dissect
UvrD’s impact on misincorporation frequency (via t-ARC-seq), define its RNAP-binding
requirements, and determine how its activation by the SOS response influence transcription
fidelity. The expected outcomes of this project are: (1) precise mapping of transcription errors in
specific mRNAs using t-ARC-seq, with comparison to known DNA mutations to better understand
fidelity mechanisms; (2) elucidation of how transcription errors contribute to antibiotic tolerance,
focusing on the stochastic activation of the marRAB operon; and (3) identification and functional
characterization of UvrD as a key modulator of transcription fidelity during stress. Collectively, this
work aims to bridge a fundamental gap in our understanding of transcription fidelity and its
physiological significance, offering new insights into bacterial survival strategies such as transient
antibiotic survival.

document fetched 2026-07-26 08:23