Biological signal processing filters via engineering allosteric transcription factors

Signal processing is critical to a myriad of biological phenomena (natural and engineered) that involve gene regulation. Biological signal processing can be achieved by way of allosteric transcription factors. In canonical regulatory systems (e.g., the lactose repressor), an INPUT signal results in the induction of a given transcription factor and objectively switches gene expression from an OFF state to an ON state. In such biological systems, to revert the gene expression back to the OFF state requires the aggressive dilution of the input signal, which can take 1 or more d to achieve in a typical biotic system. In this study, we present a class of engineered allosteric transcription factors capable of processing two-signal INPUTS, such that a sequence of INPUTS can rapidly transition gene expression between alternating OFF and ON states. Here, we present two fundamental biological signal processing filters, BANDPASS and BANDSTOP, that are regulated by D-fucose and isopropyl-β-D-1-thiogalactopyranoside. BANDPASS signal processing filters facilitate OFF–ON–OFF gene regulation. Whereas, BANDSTOP filters facilitate the antithetical gene regulation, ON–OFF–ON. Engineered signal processing filters can be directed to seven orthogonal promoters via adaptive modular DNA binding design. This collection of signal processing filters can be used in collaboration with our established transcriptional programming structure. Kinetic studies show that our collection of signal processing filters can switch between states of gene expression within a few minutes with minimal metabolic burden—representing a paradigm shift in general gene regulation.

Biomolecular Systems Engineering: Unlocking the Potential of Engineered Allostery via the Lactose Repressor Topology

Allosteric function is a critical component of many of the parts used to construct gene networks throughout synthetic biology. In this review, we discuss an emerging field of research and education, biomolecular systems engineering, that expands on the synthetic biology edifice—integrating workflows and strategies from protein engineering, chemical engineering, electrical engineering, and computer science principles. We focus on the role of engineered allosteric communication as it relates to transcriptional gene regulators—i.e., transcription factors and corresponding unit operations. In this review, we ( a) explore allosteric communication in the lactose repressor LacI topology, ( b) demonstrate how to leverage this understanding of allostery in the LacI system to engineer non-natural BUFFER and NOT logical operations, ( c) illustrate how engineering workflows can be used to confer alternate allosteric functions in disparate systems that share the LacI topology, and ( d) demonstrate how fundamental unit operations can be directed to form combinational logical operations. Expected final online publication date for the Annual Review of Biophysics, Volume 50 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

“Multiplex” rheostat positions cluster around allosterically critical regions of the lactose repressor protein

Amino acid variation at “rheostat” positions provides opportunity to modulate various aspects of protein function – such as binding affinity or allosteric coupling – across a wide range. Previously a subclass of “multiplex” rheostat positions was identified at which substitutions simultaneously modulated more than one functional parameter. Using the Miller laboratory’s dataset of ∼4000 variants of lactose repressor protein (LacI), we compared the structural properties of multiplex rheostat positions with (i) “single” rheostat positions that modulate only one functional parameter, (ii) “toggle” positions that follow textbook substitution rules, and (iii) “neutral” positions that tolerate any substitution without changing function. The combined rheostat classes comprised >40% of LacI positions, more than either toggle or neutral positions. Single rheostat positions were broadly distributed over the structure. Multiplex rheostat positions structurally overlapped with positions involved in allosteric regulation. When their phenotypic outcomes were interpreted within a thermodynamic framework, functional changes at multiplex positions were uncorrelated. This suggests that substitutions lead to complex changes in the underlying molecular biophysics. Bivariable and multivariable analyses of evolutionary signals within multiple sequence alignments could not differentiate single and multiplex rheostat positions. Phylogenetic analyses – such as ConSurf – could distinguish rheostats from toggle and neutral positions. Multivariable analyses could also identify a subset of neutral positions with high probability. Taken together, these results suggest that detailed understanding of the underlying molecular biophysics, likely including protein dynamics, will be required to discriminate single and multiplex rheostat positions from each other and to predict substitution outcomes at these sites.

Substitutions at Nonconserved Rheostat Positions Modulate Function by Rewiring Long-Range, Dynamic Interactions

Amino acid substitutions at nonconserved protein positions can have noncanonical and “long-distance” outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities and dynamic coupling for positions in the linker region of the lactose repressor protein. This region contains nonconserved positions for which substitutions alter DNA-binding affinity. We first chose to study 11 substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA-binding positions, and the degree of flexibility change correlated with experimentally measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA-binding positions in a manner that captured other experimentally determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA-binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated hardly any substitutions (“toggle”), ten nonconserved positions showed progressive changes from a range of substitutions (“rheostat”), and three nonconserved positions tolerated almost all substitutions (“neutral”). In computations with wild-type lactose repressor protein, the dynamic couplings between the DNA-binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and noncanonical substitutions outcomes at nonconserved positions arise from rewiring long-range communication among functionally important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.

Transcriptional programming using engineered systems of transcription factors and genetic architectures

The control of gene expression is an important tool for metabolic engineering, the design of synthetic gene networks, and protein manufacturing. The most successful approaches to date are based on modulating mRNA synthesis via an inducible coupling to transcriptional effectors. Here we present a biological programming structure that leverages a system of engineered transcription factors and complementary genetic architectures. We use a modular design strategy to create 27 non-natural and non-synonymous transcription factors using the lactose repressor topology as a guide. To direct systems of engineered transcription factors we employ parallel and series genetic (DNA) architectures and confer fundamental and combinatorial logical control over gene expression. Here we achieve AND, OR, NOT, and NOR logical controls in addition to two non-canonical half-AND operations. The basic logical operations and corresponding parallel and series genetic architectures represent the building blocks for subsequent combinatorial programs, which display both digital and analog performance.

Long Time-Scale Atomistic Simulations of the Structure and Dynamics of Transcription Factor-DNA Recognition

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Helvetica Neue'} <p>Recent years have witnessed an explosion of interest in computational studies of DNA binding proteins, including both coarse grained and atomistic simulations of transcription factor-DNA recognition, in order to understand how these transcription factors recognize their binding sites on the DNA with such exquisite specificity. The present study performs μs-timescale all-atom simulations of the dimeric form of the lactose repressor (LacI), both in the absence of any DNA, and in the presence of both specific and non-specific complexes, considering three different DNA sequences. We examine, specifically, the conformational differences between specific and non-specific protein-DNA interactions, as well as the behavior of the helix-turn-helix motif of LacI when interacting with the DNA. Our simulations suggest that stable LacI binding occurs primarily to bent A-form DNA, with a loss of LacI conformational entropy and optimization of correlated conformational equilibria across the protein. In addition, binding to the specific operator sequence involves a slightly larger number of stabilizing DNA-protein hydrogen bonds (in comparison to non-specific complexes), that may account for the experimentally observed specificity for this operator. In doing so, our simulations provide a detailed atomistic description of potential structural drivers for LacI selectivity.</p>

Long Time-Scale Atomistic Simulations of the Structure and Dynamics of Transcription Factor-DNA Recognition

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Helvetica Neue'} <p>Recent years have witnessed an explosion of interest in computational studies of DNA binding proteins, including both coarse grained and atomistic simulations of transcription factor-DNA recognition, in order to understand how these transcription factors recognize their binding sites on the DNA with such exquisite specificity. The present study performs μs-timescale all-atom simulations of the dimeric form of the lactose repressor (LacI), both in the absence of any DNA, and in the presence of both specific and non-specific complexes, considering three different DNA sequences. We examine, specifically, the conformational differences between specific and non-specific protein-DNA interactions, as well as the behavior of the helix-turn-helix motif of LacI when interacting with the DNA. Our simulations suggest that stable LacI binding occurs primarily to bent A-form DNA, with a loss of LacI conformational entropy and optimization of correlated conformational equilibria across the protein. In addition, binding to the specific operator sequence involves a slightly larger number of stabilizing DNA-protein hydrogen bonds (in comparison to non-specific complexes), that may account for the experimentally observed specificity for this operator. In doing so, our simulations provide a detailed atomistic description of potential structural drivers for LacI selectivity.</p>