Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence

Abstract

Cells use protein-DNA and protein-protein interactions to regulate transcription. A biophysical understanding of this process has, however, been limited by the lack of methods for quantitatively characterizing the interactions that occur at specific promoters and enhancers in living cells. Here we show how such biophysical information can be revealed by a simple experiment in which a library of partially mutated regulatory sequences are partitioned according to their in vivo transcriptional activities and then sequenced en masse. Computational analysis of the sequence data produced by this experiment can provide precise quantitative information about how the regulatory proteins at a specific arrangement of binding sites work together to regulate transcription. This ability to reliably extract precise information about regulatory biophysics in the face of experimental noise is made possible by a recently identified relationship between likelihood and mutual information. Applying our experimental and computational techniques to the Escherichia coli lac promoter, we demonstrate the ability to identify regulatory protein binding sites de novo, determine the sequence-dependent binding energy of the proteins that bind these sites, and, importantly, measure the in vivo interaction energy between RNA polymerase and a DNA-bound transcription factor. Our approach provides a generally applicable method for characterizing the biophysical basis of transcriptional regulation by a specified regulatory sequence. The principles of our method can also be applied to a wide range of other problems in molecular biology.gene regulation | lac promoter | mutual information | thermodynamic models | parallel tempering Monte Carlo C ells regulate transcription primarily through the binding of proteins to DNA-binding sites within transcriptional regulatory sequences (TRSs). Understanding how TRSs use different arrangements of binding sites to encode regulatory programs remains a major challenge for molecular biology. High-throughput methods have spurred great progress in cataloging the genomewide distribution of binding sites (1 and 2), and many techniques exist for characterizing the sequence specificity of individual regulatory proteins (3-6). However, determining how a specific TRS integrates information from multiple DNA-bound proteins still requires a laborious series of biochemical experiments that typically provide only qualitative information (reviewed in ref. 7).The E. coli lac promoter (8 and 9) is one of the few TRSs whose function is well understood at the biophysical level (10 and 11). Kuhlman et al. (11) were the first to prove that a certain aspect of this system-the up-regulation of transcription by the protein CRP (12)-could be quantitatively explained by a simple energetic interaction between CRP and the σ 70 -dependent RNA polymerase holoenzyme (henceforth RNAP). To do this, Kuhlman et al. measured transcriptional activity resulting from different in vivo concentrations of active CRP and showed that the resulting functi...

Composability of regulatory sequences controlling transcription and translation in Escherichia coli

“…The first approach seeks to predict expression levels by elucidating the biophysical relationships between sequence and function. For example, several groups have modified promoters (12,13) and ribosome binding sites (RBSs) (14)(15)(16) to see how small sequence changes affect transcription or translation. Such studies are fundamentally challenging due to the vastness of sequence space.…”

Massively parallel measurements of molecular interaction kinetics on a microfluidic platform

“…The principal goals of these methods are to establish the genomic binding locations of TFs and to determine their consensus binding sequences, position weight matrixes, and binding energy landscapes (32,41). Absolute affinities can be acquired with only a few high-throughput methods (17,(42)(43)(44), and kinetic information on protein-DNA interactions has so far only come from low-throughput, complex, and tedious methods such as electrophoretic mobility shift assays (EMSA) (45,46), SPR (18), isothermal titration calorimetry (ITC) (47), and single molecule experiments (48). Completely defining the kinetic parameters of TF-DNA interactions would provide a better understanding of how TF binding to promoters is integrated and translated into transcriptional output.…”

“…The principal goals of these methods are to establish the genomic binding locations of TFs and to determine their consensus binding sequences, position weight matrixes, and binding energy landscapes (32, 41). Absolute affinities can be acquired with only a few high-throughput methods (17,(42)(43)(44), and kinetic information on protein-DNA …”

Determinants of specificity in two-component signal transduction

“…Because individual residues do not contribute to specificity additively, traditional mutagenesis approaches that examine one position at a time will be of limited value so new, combinatorial methods are needed. High-throughput, deep sequencing-based approaches have recently been applied to other sequence-phenotype relationships and should prove powerful when applied to two-component signaling [52,53]. Such work promises to help inform prediction algorithms and bioengineering efforts, and will provide important new insights into the specificity and evolution of two-component signaling pathways.…”