Sequence-function relationships in E. coli transcriptional regulation

Understanding how transcriptional regulatory sequence maps to regulatory function remains a difficult problem in regulatory biology. Given a particular DNA sequence for a bacterial promoter region, we would like to be able to say which transcription factors bind there, how strongly they bind, and whether they interact with each other and/or RNA polymerase, with the ultimate objective of integrating knowledge of these parameters into a prediction of gene expression levels. The theoretical framework of statistical thermodynamics provides a useful framework for doing so, enabling us to predict how gene expression levels depend on transcription factor binding energies and concentrations. We used thermodynamic models, coupled with models of the sequence-dependent binding energies of transcription factors and RNAP, to construct a genotype to phenotype map for the level of repression exhibited by the lac promoter, and tested it experimentally using a set of promoter variants from E. coli strains isolated from different natural environments. For this work, we sought to ``reverse engineer'' naturally occurring promoter sequences to understand how variations in promoter sequence affects gene expression. The natural inverse of this approach is to ``forward engineer'' promoter sequences to obtain targeted levels of gene expression. We used a high precision model of RNAP-DNA sequence dependent binding energy, coupled with a thermodynamic model relating binding energy to gene expression, to predictively design and verify a suite of synthetic E. coli promoters whose expression varied over nearly three orders of magnitude.

However, although thermodynamic models enable predictions of mean levels of gene expression, it has become evident that cell-to-cell variability or ``noise'' in gene expression can also play a biologically important role. In order to address this aspect of gene regulation, we developed models based on the chemical master equation framework and used them to explore the noise properties of a number of common E. coli regulatory motifs; these properties included the dependence of the noise on parameters such as transcription factor binding strength and copy number. We then performed experiments in which these parameters were systematically varied and measured the level of variability using mRNA FISH. The results showed a clear dependence of the noise on these parameters, in accord with model predictions.

Finally, one shortcoming of the preceding modeling frameworks is that their applicability is largely limited to systems that are already well-characterized, such as the lac promoter. Motivated by this fact, we used a high throughput promoter mutagenesis assay called Sort-Seq to explore the completely uncharacterized transcriptional regulatory DNA of the E. coli mechanosensitive channel of large conductance (MscL). We identified several candidate transcription factor binding sites, and work is continuing to identify the associated proteins.

Structural and Biophysical Characterization of Variants of the Mechanosensitive Channel of Large Conductance (MSCL)

The ability to sense mechanical force is vital to all organisms to interact with and respond to stimuli in their environment. Mechanosensation is critical to many physiological functions such as the senses of hearing and touch in animals, gravitropism in plants and osmoregulation in bacteria. Of these processes, the best understood at the molecular level involve bacterial mechanosensitive channels. Under hypo-osmotic stress, bacteria are able to alleviate turgor pressure through mechanosensitive channels that gate directly in response to tension in the membrane lipid bilayer. A key participant in this response is the mechanosensitive channel of large conductance (MscL), a non-selective channel with a high conductance of ~3 nS that gates at tensions close to the membrane lytic tension.

It has been appreciated since the original discovery by C. Kung that the small subunit size (~130 to 160 residues) and the high conductance necessitate that MscL forms a homo-oligomeric channel. Over the past 20 years of study, the proposed oligomeric state of MscL has ranged from monomer to hexamer. Oligomeric state has been shown to vary between MscL homologues and is influenced by lipid/detergent environment. In this thesis, we report the creation of a chimera library to systematically survey the correlation between MscL sequence and oligomeric state to identify the sequence determinants of oligomeric state. Our results demonstrate that although there is no combination of sequences uniquely associated with a given oligomeric state (or mixture of oligomeric states), there are significant correlations. In the quest to characterize the oligomeric state of MscL, an exciting discovery was made about the dynamic nature of the MscL complex. We found that in detergent solution, under mild heating conditions (37 °C – 60 °C), subunits of MscL can exchange between complexes, and the dynamics of this process are sensitive to the protein sequence.

Extensive efforts were made to produce high diffraction quality crystals of MscL for the determination of a high resolution X-ray crystal structure of a full length channel. The surface entropy reduction strategy was applied to the design of S. aureus MscL variants and while the strategy appears to have improved the crystallizability of S. aureus MscL, unfortunately the diffraction qualities of these crystals were not significantly improved. MscL chimeras were also screened for crystallization in various solubilization detergents, but also failed to yield high quality crystals.

MscL is a fascinating protein and continues to serve as a model system for the study of the structural and functional properties of mechanosensitive channels. Further characterization of the MscL chimera library will offer more insight into the characteristics of the channel. Of particular interest are the functional characterization of the chimeras and the exploration of the physiological relevance of intercomplex subunit exchange.