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1.
Nat Commun ; 12(1): 325, 2021 01 12.
Article in English | MEDLINE | ID: mdl-33436562

ABSTRACT

A crucial step towards engineering biological systems is the ability to precisely tune the genetic response to environmental stimuli. In the case of Escherichia coli inducible promoters, our incomplete understanding of the relationship between sequence composition and gene expression hinders our ability to predictably control transcriptional responses. Here, we profile the expression dynamics of 8269 rationally designed, IPTG-inducible promoters that collectively explore the individual and combinatorial effects of RNA polymerase and LacI repressor binding site strengths. We then fit a statistical mechanics model to measured expression that accurately models gene expression and reveals properties of theoretically optimal inducible promoters. Furthermore, we characterize three alternative promoter architectures and show that repositioning binding sites within promoters influences the types of combinatorial effects observed between promoter elements. In total, this approach enables us to deconstruct relationships between inducible promoter elements and discover practical insights for engineering inducible promoters with desirable characteristics.


Subject(s)
Isopropyl Thiogalactoside/pharmacology , Logic , Promoter Regions, Genetic , Binding Sites , Biophysical Phenomena , DNA-Directed RNA Polymerases/metabolism , Escherichia coli/drug effects , Escherichia coli/metabolism , Fluorescence , Genes, Reporter , Mutation/genetics , Operator Regions, Genetic/genetics , Protein Binding , Reproducibility of Results , Thermodynamics , Transcription Factors/metabolism
2.
Cell Syst ; 11(1): 75-85.e7, 2020 07 22.
Article in English | MEDLINE | ID: mdl-32603702

ABSTRACT

In eukaryotes, transcription factors (TFs) orchestrate gene expression by binding to TF-binding sites (TFBSs) and localizing transcriptional co-regulators and RNA polymerase II to cis-regulatory elements. However, we lack a basic understanding of the relationship between TFBS composition and their quantitative transcriptional responses. Here, we measured expression driven by 17,406 synthetic cis-regulatory elements with varied compositions of a model TFBS, the c-AMP response element (CRE) by using massively parallel reporter assays (MPRAs). We find CRE number, affinity, and promoter proximity largely determines expression. In addition, we observe expression modulation based on the spacing between CREs and CRE distance to the promoter, where expression follows a helical periodicity. Finally, we compare library expression between an episomal MPRA and a genomically integrated MPRA, where a single cis-regulatory element is assayed per cell at a defined locus. These assays largely recapitulate each other, although weaker, non-canonical CREs exhibit greater activity in a genomic context.


Subject(s)
Adenosine Monophosphate/metabolism , Genomics/methods , Plasmids/metabolism , Response Elements/genetics , Humans
3.
Biochemistry ; 58(11): 1539-1551, 2019 03 19.
Article in English | MEDLINE | ID: mdl-29388765

ABSTRACT

Promoters are the key drivers of gene expression and are largely responsible for the regulation of cellular responses to time and environment. In Escherichia coli, decades of studies have revealed most, if not all, of the sequence elements necessary to encode promoter function. Despite our knowledge of these motifs, it is still not possible to predict the strength and regulation of a promoter from primary sequence alone. Here we develop a novel multiplexed assay to study promoter function in E. coli by building a site-specific genomic recombination-mediated cassette exchange system that allows for the facile construction and testing of large libraries of genetic designs integrated into precise genomic locations. We build and test a library of 10898 σ70 promoter variants consisting of all combinations of a set of eight -35 elements, eight -10 elements, three UP elements, eight spacers, and eight backgrounds. We find that the -35 and -10 sequence elements can explain approximately 74% of the variance in promoter strength within our data set using a simple log-linear statistical model. Simple neural network models explain >95% of the variance in our data set by capturing nonlinear interactions with the spacer, background, and UP elements.


Subject(s)
Promoter Regions, Genetic/genetics , Promoter Regions, Genetic/physiology , Sigma Factor/genetics , Base Sequence/genetics , DNA-Directed RNA Polymerases/metabolism , Escherichia coli/genetics , Escherichia coli/metabolism , Escherichia coli Proteins/genetics , Escherichia coli Proteins/metabolism , Gene Expression Regulation, Bacterial/genetics , Gene Library , Genomics/methods , Nerve Net/metabolism , Protein Binding/genetics , Sigma Factor/metabolism , Transcription, Genetic/genetics
4.
Mol Cell ; 73(1): 183-194.e8, 2019 01 03.
Article in English | MEDLINE | ID: mdl-30503770

ABSTRACT

Mutations that lead to splicing defects can have severe consequences on gene function and cause disease. Here, we explore how human genetic variation affects exon recognition by developing a multiplexed functional assay of splicing using Sort-seq (MFASS). We assayed 27,733 variants in the Exome Aggregation Consortium (ExAC) within or adjacent to 2,198 human exons in the MFASS minigene reporter and found that 3.8% (1,050) of variants, most of which are extremely rare, led to large-effect splice-disrupting variants (SDVs). Importantly, we find that 83% of SDVs are located outside of canonical splice sites, are distributed evenly across distinct exonic and intronic regions, and are difficult to predict a priori. Our results indicate extant, rare genetic variants can have large functional effects on splicing at appreciable rates, even outside the context of disease, and MFASS enables their empirical assessment at scale.


Subject(s)
Exons , Gene Expression Profiling/methods , High-Throughput Nucleotide Sequencing/methods , Mutation , RNA Splicing , Sequence Analysis, DNA/methods , Cell Separation , Computational Biology , Flow Cytometry , HEK293 Cells , HeLa Cells , Hep G2 Cells , Humans , Introns , K562 Cells , Oligonucleotide Array Sequence Analysis , Reproducibility of Results
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