Biology subjects

Phillips, R.

Publications and source records attributed to Phillips, R..

At least 55 records · Page 3Linked to original sources

bioRxiv2019

Theoretical investigation of a genetic switch for metabolic adaptation

Membrane transporters carry key metabolites through the cell membrane and, from a resource standpoint, are hypothesized to be produced when necessary. The expression of membrane transporters in metabolic pathways is often upregulated by the transporter substrate. In E. coli, such systems include for example the lacY, araFGH, and xylFGH genes, which encode for lactose, arabinose, and xylose transporters, respectively. As a case study of a minimal system, we build a generalizable physical model of the xapABR genetic circuit, which features a regulatory feedback loop through membrane transport (positive feedback) and enzymatic degradation (negative feedback) of an inducer. Dynamical systems analysis and stochastic simulations show that the membrane transport makes the model system bistable in certain parameter regimes. Thus, it serves as a genetic "on-off" switch, enabling the cell to only produce a set of metabolic enzymes when the corresponding metabolite is present in large amounts. We find that the negative feedback from the degradation enzyme does not significantly disturb the positive feedback from the membrane transporter. We investigate hysteresis in the switching and discuss the role of cooperativity and multiple binding sites in the model circuit. Fundamentally, this work explores how a stable genetic switch for a set of enzymes is obtained from transcriptional auto-activation of a membrane transporter through its substrate.

biophysics↗

bioRxiv2019

Sequence-Dependent Dynamics of Synthetic and Endogenous RSSs in V(D)J Recombination

Developing lymphocytes in the immune system of jawed vertebrates assemble antigen-receptor genes by undergoing large-scale reorganization of spatially separated V, D, and J gene segments through a process known as V(D)J recombination. The RAG protein initiates this process by binding and cutting recombination signal sequences (RSSs) composed of conserved heptamer and nonamer sequences flanking less well-conserved 12- or 23-bp spacers. Little quantitative information is known about the contributions of individual RSS positions over the course of the RAG-RSS interaction. We employ a single-molecule method known as tethered particle motion to quantify the formation, stability, and cleavage of the RAG-12RSS-23RSS paired complex (PC) for numerous synthetic and endogenous 12RSSs. We thoroughly investigate the sequence space around a RSS by making 40 different single-bp changes and characterizing the reaction dynamics. We reveal that single-bp changes affect RAG function based on their position: loss of cleavage function (first three positions of the heptamer); reduced propensity for forming the PC (the nonamer and last four bp of the heptamer); or variable effects on PC formation (spacer). We find that the rare usage of some endogenous gene segments can be mapped directly to their adjacent 12RSSs to which RAG binds weakly. The 12RSS, however, cannot explain the high-frequency usage of other gene segments. Finally, we find that RSS nicking, while not required for PC formation, substantially stabilizes the PC. Our findings provide detailed insights into the contribution of individual RSS positions to steps of the RAG-RSS re-action that previously have been difficult to assess quantitatively.\n\nSummaryV(D)J recombination is a genomic cut-and-paste process for generating diverse antigen-receptor repertoires. The RAG enzyme brings separate gene segments together by binding the neighboring sequences called RSSs, forming a paired complex (PC) before cutting the DNA. There are limited quantitative studies of the sequence-dependent dynamics of the crucial inter-mediate steps of PC formation and cleavage. Here, we quantify individual RAG-DNA dynamics for various RSSs. While RSSs of frequently-used segments do not comparatively enhance PC formation or cleavage, the rare use of some segments can be explained by their neighboring RSSs crippling PC formation and/or cleavage. Furthermore, PC lifetimes reveal DNA-nicking is not required for forming the PC, but PCs with nicks are more stable.

immunology↗

bioRxiv2019

Defining the Energetic Costs of Cellular Structures

All cellular structures are assembled from molecular building blocks, and molecular building blocks incur energetic costs to the cell. In an energy-limited environment, the energetic cost of a cellular structure imposes a fitness cost and impacts a cells evolutionary trajectory. While the importance of energetic considerations was realized for decades, the distinction between direct energetic costs expended by the cell and potential energy that the cell diverts into cellular biomass components, which we define as the opportunity cost, was not explicitly made, leading to large differences in values for energetic costs of molecular building blocks used in the literature. We describe a framework that defines and separates various components relevant for estimating the energetic costs of molecular building blocks and the resulting cellular structures. This distinction among energetic costs is an essential step towards discussing the conversion of an energetic cost to a corresponding fitness cost.

biophysics↗

bioRxiv2019

Differential Effects of Afferent and Efferent Vagus Nerve Stimulation on Gastric Motility Assessed with Magnetic Resonance Imaging

BackgroundVagus nerve stimulation (VNS) is an emerging bioelectronic therapy for regulating food intake and controlling gastric motility. However, the functional impact of different VNS parameters on postprandial gastric motility remains incompletely characterized. Moreover, while most studies focused on stimulating the motor limb (i.e. efferent VNS) of the vagovagal circuitry, the contribution of electrically activating the reflex arc of the circuitry (i.e. afferent VNS) to downstream control of gastric function has seldom been investigated.\n\nMethodsHere, we used dynamic gastric magnetic resonance imaging (MRI) to assess antropyloric motility in anesthetized rats during which VNS was applied to the left cervical vagus. The configuration of VNS was varied in terms of directionality (i.e. afferent, efferent or combined afferent and efferent VNS) as well as parameter settings (i.e. pulse amplitude, pulse width, and frequency). The motility measurements were computed using a previously developed computer-assisted image processing pipeline.\n\nKey ResultsWe found that electrical activation that favored the afferent pathway could promote gastric motility and coordination more effectively than direct activation of the efferent pathway. A reduction in antral contraction amplitude and pyloric tone under high-dose efferent VNS highlighted the inhibitory role of the efferent vagovagal circuitry.\n\nConclusions & InferencesThis study demonstrated the direct and reflex gastric responses to cervical VNS measured with MRI. Our findings suggest that selective stimulation of vagal afferents is potentially more favorable than stimulation of vagal efferents in facilitating coordinated antropyloric motility.\n\nKey PointsO_LIVagus nerve stimulation is emerging as a new bioelectronic therapy for remedying gastric symptoms. However, the effects of graded VNS settings and directionality preferences of VNS on gastric functions remain incompletely characterized.\nC_LIO_LIDynamic gastric MRI revealed that electrical activation of the afferent pathway could promote antropyloric motility more effectively than direct activation of the efferent pathway.\nC_LIO_LIMRI can noninvasively characterize post-prandial gastric motility with high spatial and temporal resolution that could be used to guide the selection of VNS settings.\nC_LI

bioengineering↗

bioRxiv2019

The Energetics of Molecular Adaptation in Transcriptional Regulation

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only a subset of the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.\n\nSummaryWe present a biophysical model of allosteric transcriptional regulation that directly links the location of a mutation within a repressor to the biophysical parameters that describe its behavior. We explore the phenotypic space of a repressor with mutations in either the inducer binding or DNA binding domains. Using the LacI repressor in E. coli, we make sharp, falsifiable predictions and use this framework to generate a null hypothesis for how double mutants behave given knowledge of the single mutants. Linking mutations to the parameters which govern the system allows for quantitative predictions of how the free energy of the system changes as a result, permitting coarse graining of high-dimensional data into a single-parameter description of the mutational consequences.

biophysics↗

bioRxiv2019

How the Avidity of Polymerase Binding to the -35/-10 Promoter Sites Affects Gene Expression

Although the key promoter elements necessary to drive transcription in Escherichia coli have long been understood, we still cannot predict the behavior of arbitrary novel promoters, hampering our ability to characterize the myriad of sequenced regulatory architectures as well as to design novel synthetic circuits. This work builds on a beautiful recent experiment by Urtecho et al. who measured the gene expression of over 10,000 promoters spanning all possible combinations of a small set of regulatory elements. Using this data, we demonstrate that a central claim in energy matrix models of gene expression - that each promoter element contributes independently and additively to gene expression - contradicts experimental measurements. We propose that a key missing ingredient from such models is the avidity between the -35 and -10 RNA polymerase binding sites and develop what we call a refined energy matrix model that incorporates this effect. We show that this the refined energy matrix model can characterize the full suite of gene expression data and explore several applications of this framework, namely, how multivalent binding at the -35 and -10 sites can buffer RNAP kinetics against mutations and how promoters that bind overly tightly to RNA polymerase can inhibit gene expression. The success of our approach suggests that avidity represents a key physical principle governing the interaction of RNA polymerase to its promoter.\n\nSignificance StatementCellular behavior is ultimately governed by the genetic program encoded in its DNA and through the arsenal of molecular machines that actively transcribe its genes, yet we lack the ability to predict how an arbitrary DNA sequence will perform. To that end, we analyze the performance of over 10,000 regulatory sequences and develop a model that can predict the behavior of any sequence based on its composition. By considering promoters that only vary by one or two elements, we can characterize how different components interact, providing fundamental insights into the mechanisms of transcription.

biophysics↗

bioRxiv2019

First-principles prediction of the information processing capacity of a simple genetic circuit

Given the stochastic nature of gene expression, genetically identical cells exposed to the same environmental inputs will produce different outputs. This heterogeneity has been hypothesized to have consequences for how cells are able to survive in changing environments. Recent work has explored the use of information theory as a framework to understand the accuracy with which cells can ascertain the state of their surroundings. Yet the predictive power of these approaches is limited and has not been rigorously tested using precision measurements. To that end, we generate a minimal model for a simple genetic circuit in which all parameter values for the model come from independently published data sets. We then predict the information processing capacity of the genetic circuit for a suite of biophysical parameters such as protein copy number and protein-DNA affinity. We compare these parameter-free predictions with an experimental determination of protein expression distributions and the resulting information processing capacity of E. coli cells. We find that our minimal model captures the scaling of the cell-to-cell variability in the data and the inferred information processing capacity of our simple genetic circuit up to a systematic deviation.

biophysics↗

bioRxiv2019

Human Phageprints: A high-resolution exploration of oral phages reveals globally-distributed phage families with individual-specific and temporally-stable community compositions

Metagenomic studies have revolutionized the study of novel phages. However these studies trade the depth of coverage for breadth. In this study we show that the targeted sequencing of a phage genomic region as small as 200-300 base pairs, can provide sufficient sequence diversity to serve as an individual-specific barcode or \"Phageprint\". The targeted approach reveals a high-resolution view of phage communities that is not available through metagenomic datasets. By creating instructional videos and collection kits, we enabled citizen scientists to gather [~]700 oral samples spanning [~]100 individuals residing in different parts of the world. In examining phage communities at 6 different oral sites, and by comparing phage communities of individuals living across the globe, we were able to study the effect of spatial separation, ranging from several millimeters to thousands of kilometers. We found that the spatial separation of just a few centimeters (the distance between two oral sites) can already result in highly distinct phage community compositions. For larger distances, spanning the phage communities of different individuals living in different parts of the world, we did not observe any correlation between spatial distance and phage community composition as individuals residing in the same city did not have any more similar phage communities than individuals living on different continents. Additionally, we found that neither genetics nor cohabitation seem to play a role in the relatedness of phage community compositions across individuals. Cohabitating siblings and even identical twins did not have phage community compositions that were any more similar than those of unrelated individuals. The primary factor contributing to phage community composition relatedness is direct contact between two habitats, as is demonstrated by the similarity between oral phage community compositions of partners. Furthermore, by exploring phage communities across the span of a month, and in some cases several years, we observed highly stable community compositions. These studies consistently point to the existence of remarkably diverse and personal phage families that are stable in time and apparently present in people around the world.

microbiology↗

bioRxiv2018

Combinatorial Control through Allostery

Many instances of cellular signaling and transcriptional regulation involve switch-like molecular responses to the presence or absence of input ligands. To understand how these responses come about and how they can be harnessed, we develop a statistical mechanical model to characterize the types of Boolean logic that can arise from allosteric molecules following the Monod-Wyman-Changeux (MWC) model. Building upon previous work, we show how an allosteric molecule regulated by two inputs can elicit AND, OR, NAND and NOR responses, but is unable to realize XOR or XNOR gates. Next, we demonstrate the ability of an MWC molecule to perform ratiometric sensing - a response behavior where activity depends monotonically on the ratio of ligand concentrations. We then extend our analysis to more general schemes of combinatorial control involving either additional binding sites for the two ligands or an additional third ligand and show how these additions can cause a switch in the logic behavior of the molecule. Overall, our results demonstrate the wide variety of control schemes that biological systems can implement using simple mechanisms.

biophysics↗

bioRxiv2018

Controlling Organization and Forces in Active Matter Through Optically-Defined Boundaries

Living systems are capable of locomotion, reconfiguration, and replication. To perform these tasks, cells spatiotemporally coordinate the interactions of force-generating, \"active\" molecules that create and manipulate non-equilibrium structures and force fields that span up to millimeter length scales [1-3]. Experimental active matter systems of biological or synthetic molecules are capable of spontaneously organizing into structures [4, 5] and generating global flows [6-9]. However, these experimental systems lack the spatiotemporal control found in cells, limiting their utility for studying non-equilibrium phenomena and bioinspired engineering. Here, we uncover non-equilibrium phenomena and principles by optically controlling structures and fluid flow in an engineered system of active biomolecules. Our engineered system consists of purified microtubules and light-activatable motor proteins that crosslink and organize microtubules into distinct structures upon illumination. We develop basic operations, defined as sets of light patterns, to create, move, and merge microtubule structures. By composing these basic operations, we are able to create microtubule networks that span several hundred microns in length and contract at speeds up to an order of magnitude faster than the speed of an individual motor. We manipulate these contractile networks to generate and sculpt persistent fluid flows. The principles of boundary-mediated control we uncover may be used to study emergent cellular structures and forces and to develop programmable active matter devices.

biophysics↗

bioRxiv2018

Resting-State Brain Fluctuation and Functional Connectivity Dissociate Moral Injury from Posttraumatic Stress Disorder

Moral injury is closely associated with posttraumatic stress disorder (PTSD) and is characterized by disturbances in social and moral cognition. Little is known about the neural underpinnings of moral injury, and whether the neural correlates are different between moral injury and PTSD.\n\nA sample of 26 US military veterans (2 females; 28~55 years old) were investigated to determine how moral injury experiences and PTSD symptoms are differentially related to spontaneous fluctuations indexed by low frequency fluctuation (ALFF) as well as functional connectivity during resting-state functional magnetic resonance imaging (fMRI) scanning.\n\nALFF in the left inferior parietal lobule (L IPL) was positively associated with moral injury sub-scores of transgressions, negatively associated with sub-scores of betrayals, and not related with PTSD symptoms. Moreover, functional connectivity between the L IPL and bilateral precuneus was positively related with PTSD symptoms and negatively related with moral injury total scores.\n\nOur results provide the first evidence that moral injury and PTSD have dissociable neural underpinnings, and behaviorally distinct sub-components of moral injury are different in neural responses. The findings increase our knowledge of the neural distinctions between moral injury and PTSD and may contribute to developing nosology and interventions for military veterans afflicted with moral injury.

neuroscience↗

bioRxiv2018

Biophysical mechanisms in the mammalian respiratory oscillator re-examined with a new data-driven computational model

An autorhythmic population of excitatory neurons in the brainstem pre-Botzinger complex is a critical component of the mammalian respiratory oscillator. Two intrinsic neuronal biophysical mechanisms--a persistent sodium current (INaP) and a calcium-activated non-selective cationic current (ICAN)--were proposed to individually or in combination generate cellular-and circuit-level oscillations, but their roles are debated without resolution. We re-examined these roles with a new computational model of an excitatory population with randomly distributed INaP and ICAN conductances and synaptic connections. This model robustly reproduces experimental data showing contrary to previous hypotheses, rhythm generation is independent of ICAN activation, which instead determines population activity amplitude. The novel insight is that this occurs when ICAN is primarily activated by neuronal calcium fluxes driven by synaptic mechanisms. Rhythm depends critically on INaP in a subpopulation forming the rhythmogenic kernel. The model explains how the rhythm and amplitude of respiratory oscillations involve distinct biophysical mechanisms.

bioinformatics↗

bioRxiv2018

Quantifying the Entropic and Energetic Effects of Linker Length and Rigidity within Synthetic HIV-1 Antibodies designed to Bind Bivalently to Env Spikes

Due to the low density of envelope (Env) spikes on the surface of HIV-1, neutralizing IgG antibodies rarely bind bivalently using both antigen-binding arms (Fabs) to crosslink between spikes (inter-spike crosslinking), instead resorting to weaker monovalent binding that is more sensitive to Env mutations. Synthetic antibodies designed to bivalently bind a single Env trimer (intra-spike crosslinking) were previously shown to exhibit increased neutralization potencies. In initial work, diFabs joined by varying lengths of rigid double-stranded DNA (dsDNA) were considered. Anticipating future experiments to improve synthetic antibodies, we investigate whether linkers with different rigidities could enhance diFab potency by modeling DNA-Fabs containing different combinations of rigid dsDNA and flexible single-stranded DNA (ssDNA) and characterizing their neutralization potential. Model predictions suggest that while a long flexible polymer may be capable of bivalent binding, it exhibits weak neutralization due to the large loss in entropic degrees of freedom when both Fabs are bound. In contrast, the strongest neutralization potencies are predicted to require a rigid linker that optimally spans the distance between two Fab binding sites on an Env trimer, and avidity can be further boosted by incorporating more Fabs into these constructs. These results inform the design of multivalent anti-HIV-1 therapeutics that utilize avidity effects to remain potent against HIV-1 in the face of the rapid mutation of Env spikes.\n\nSignificanceIgG antibodies utilize avidity to increase their apparent affinities through simultaneous binding of two antigen-binding Fabs - if one Fab dissociates from an antigen, the other Fab can remain attached, allowing rebinding. HIV-1 foils this strategy by having few, and highly-separated, Envelope spike targets for antibodies, forcing most IgGs to bind monovalently. Here we develop a statistical mechanics model of synthetic diFabs joined by DNA linkers of different lengths and flexibilities. This framework enables us to translate the energetic and entropic effects of the linker into the neutralization potency of a diFab. We demonstrate that the avidity of multivalent binding is enhanced by using rigid linkers or including additional Fabs capable of simultaneous binding, providing the means to quantitatively predict the potencies of other antibody designs.

immunology↗

bioRxiv2018

Precision measurement of cis-regulatory energetics in living cells

Gene expression in all organisms is controlled by cooperative interactions between DNA-bound transcription factors (TFs), but quantitatively measuring TF-DNA and TF-TF interactions remains difficult. Here we introduce a strategy for precisely measuring the Gibbs free energy of such interactions in living cells. This strategy centers on the measurement and modeling of \"allelic manifolds\", a multidimensional generalization of the classical genetics concept of allelic series. Allelic manifolds are measured using reporter assays performed on strategically designed cis-regulatory sequences. Quantitative biophysical models are then fit to the resulting data. We used this strategy to study regulation by two Escherichia coli TFs, CRP and {sigma}70 RNA polymerase. Doing so, we consistently obtained energetic measurements precise to ~ 0.1 kcal/mol. We also obtained multiple results that deviate from the prior literature. Our strategy is compatible with massively parallel reporter assays in both prokaryotes and eukaryotes, and should therefore be highly scalable and broadly applicable.

biophysics↗

bioRxiv2018

Connecting the dots between mechanosensitive channel abundance, osmotic shock, and survival at single-cell resolution

Rapid changes in extracellular osmolarity are one of many insults microbial cells face on a daily basis. To protect against such shocks, Escherichia coli and other microbes express several types of transmembrane channels which open and close in response to changes in membrane tension. In E. coli, one of the most abundant channels is the mechanosensitive channel of large conductance (MscL). While this channel has been heavily characterized through structural methods, electrophysiology, and theoretical modeling, our understanding of its physiological role in preventing cell death by alleviating high membrane tension remains tenuous. In this work, we examine the contribution of MscL alone to cell survival after osmotic shock at single cell resolution using quantitative fluorescence microscopy. We conduct these experiments in an E. coli strain which is lacking all mechanosensitive channel genes save for MscL whose expression is tuned across three orders of magnitude through modifications of the Shine-Dalgarno sequence. While theoretical models suggest that only a few MscL channels would be needed to alleviate even large changes in osmotic pressure, we find that between 500 and 700 channels per cell are needed to convey upwards of 80% survival. This number agrees with the average MscL copy number measured in wild-type E. coli cells through proteomic studies and quantitative Western blotting. Furthermore, we observe zero survival events in cells with less than 100 channels per cell. This work opens new questions concerning the contribution of other mechanosensitive channels to survival as well as regulation of their activity.

biophysics↗

bioRxiv2018

Mapping DNA sequence to transcription factor binding energy in vivo

Despite the central importance of transcriptional regulation in systems biology, it has proven difficult to determine the regulatory mechanisms of individual genes, let alone entire gene networks. It is particularly difficult to analyze a promoter sequence and identify the locations, regulatory roles, and energetic properties of binding sites for transcription factors and RNA polymerase. In this work, we present a strategy for interpreting transcriptional regulatory sequences using in vivo methods (i.e. the massively parallel reporter assay Sort-Seq) to formulate quantitative models that map a transcription factor binding sites DNA sequence to transcription factor-DNA binding energy. We use these models to predict the binding energies of transcription factor binding sites to within 1 kBT of their measured values. We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts. Specifically, we show that our models can be used to design specific induction responses, analyze the effects of amino acid mutations on DNA sequence preference, and determine how regulatory context affects a transcription factors sequence specificity.

biophysics↗

bioRxiv2017

A systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria

Gene regulation is one of the most ubiquitous processes in biology. But while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here we show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect bacterial promoters in a systematic and scalable way. We demonstrate this method on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli. In all cases we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input-output relationships. This method opens up the possibility of exhaustively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.

biophysics↗

bioRxiv2017

Theoretical Analysis of Inducer and Operator Binding for Cyclic-AMP Receptor Protein Mutants

Allosteric transcription factors undergo binding events both at their inducer binding sites as well as at distinct DNA binding domains, and it is often difficult to disentangle the structural and functional consequences of these two classes of interactions. In this work, we compare the ability of two statistical mechanical models - the Monod-Wyman-Changeux (MWC) and the Koshland-Nemethy-Filmer (KNF) models of protein conformational change - to characterize the multi-step activation mechanism of the broadly acting cyclic-AMP receptor protein (CRP). We first consider the allosteric transition resulting from cyclic-AMP binding to CRP, then analyze how CRP binds to its operator, and finally investigate the ability of CRP to activate gene expression. In light of these models, we examine data from a beautiful recent experiment that created a single-chain version of the CRP homodimer, thereby enabling each subunit to be mutated separately. Using this construct, six mutants were created using all possible combinations of the wild type subunit, a D53H mutant subunit, and an S62F mutant subunit. We demonstrate that both the MWC and KNF models can explain the behavior of all six mutants using a small, self-consistent set of parameters. In comparing the results, we find that the MWC model slightly outperforms the KNF model in the quality of its fits, but more importantly the parameters inferred by the MWC model are more in line with structural knowledge of CRP. In addition, we discuss how the conceptual framework developed here for CRP enables us to not merely analyze data retrospectively, but has the predictive power to determine how combinations of mutations will interact, how double mutants will behave, and how each construct would regulate gene expression.

biophysics↗