A general mechanism for network-dosage compensation in gene circuits

Successes and failures in modular genetic engineering

Synthetic biology relies on engineering concepts such as abstraction, standardization, and decoupling to develop systems that address environmental, clinical, and industrial needs. Recent advances in applying modular design to system development have enabled creation of increasingly complex systems. However, several challenges to module and system development remain, including syntactic errors, semantic errors, parameter mismatches, contextual sensitivity, noise and evolution, and load and stress. To combat these challenges, researchers should develop a framework for describing and reasoning about biological information, design systems with modularity in mind, and investigate how to predictively describe the diverse sources and consequences of metabolic load and stress.

Post-translational tools expand the scope of synthetic biology

Synthetic biology is improving our understanding of and ability to control living organisms. To date, most progress has been made by engineering gene expression. However, computational and genetically encoded tools that allow protein activity and protein-protein interactions to be controlled on their natural time and length scales are emerging. These technologies provide a basis for the construction of post-translational circuits, which are capable of fast, robust and highly spatially resolved signal processing. When combined with their transcriptional and translational counterparts, synthetic post-translational circuits will allow better analysis and control of otherwise intractable biological processes such as cellular differentiation and the growth of tissues.

Organelle growth control through limiting pools of cytoplasmic components

The critical importance of controlling the size and number of intracellular organelles has led to a variety of mechanisms for regulating the formation and growth of cellular structures. In this review, we explore a class of mechanisms for organelle growth control that rely primarily on the cytoplasm as a 'limiting pool' of available material. These mechanisms are based on the idea that, as organelles grow, they incorporate subunits from the cytoplasm. If this subunit pool is limited, organelle growth will lead to depletion of subunits from the cytoplasm. Free subunit concentration therefore provides a measure of the number of incorporated subunits and thus the current size of the organelle. Because organelle growth rates are typically a function of subunit concentration, cytoplasmic depletion links organelle size, free subunit concentration, and growth rates, ensuring that as the organelle grows, its rate of growth slows. Thus, a limiting cytoplasmic pool provides a powerful mechanism for size-dependent regulation of growth without recourse to active mechanisms to measure size or modulate growth rates. Variations of this general idea allow not only for size control, but also cell-size-dependent scaling of cellular structures, coordination of growth between similar structures within a cell, and the enforcement of singularity in structure formation, when only a single copy of a structure is desired. Here, we review several examples of such mechanisms in cellular processes as diverse as centriole duplication, centrosome and nuclear size control, cell polarity, and growth of flagella.

Mediation of Drosophila autosomal dosage effects and compensation by network interactions

BACKGROUND

Gene dosage change is a mild perturbation that is a valuable tool for pathway reconstruction in Drosophila. While it is often assumed that reducing gene dose by half leads to two-fold less expression, there is partial autosomal dosage compensation in Drosophila, which may be mediated by feedback or buffering in expression networks.

RESULTS

We profiled expression in engineered flies where gene dose was reduced from two to one. While expression of most one-dose genes was reduced, the gene-specific dose responses were heterogeneous. Expression of two-dose genes that are first-degree neighbors of one-dose genes in novel network models also changed, and the directionality of change depended on the response of one-dose genes.

CONCLUSIONS

Our data indicate that expression perturbation propagates in network space. Autosomal compensation, or the lack thereof, is a gene-specific response, largely mediated by interactions with the rest of the transcriptome.

A DNA network as an information processing system

Biomolecular systems that can process information are sought for computational applications, because of their potential for parallelism and miniaturization and because their biocompatibility also makes them suitable for future biomedical applications. DNA has been used to design machines, motors, finite automata, logic gates, reaction networks and logic programs, amongst many other structures and dynamic behaviours. Here we design and program a synthetic DNA network to implement computational paradigms abstracted from cellular regulatory networks. These show information processing properties that are desirable in artificial, engineered molecular systems, including robustness of the output in relation to different sources of variation. We show the results of numerical simulations of the dynamic behaviour of the network and preliminary experimental analysis of its main components.

The transition between stochastic and deterministic behavior in an excitable gene circuit

We explore the connection between a stochastic simulation model and an ordinary differential equations (ODEs) model of the dynamics of an excitable gene circuit that exhibits noise-induced oscillations. Near a bifurcation point in the ODE model, the stochastic simulation model yields behavior dramatically different from that predicted by the ODE model. We analyze how that behavior depends on the gene copy number and find very slow convergence to the large number limit near the bifurcation point. The implications for understanding the dynamics of gene circuits and other birth-death dynamical systems with small numbers of constituents are discussed.

Negative feedback confers mutational robustness in yeast transcription factor regulation

Organismal fitness depends on the ability of gene networks to function robustly in the face of environmental and genetic perturbations. Understanding the mechanisms of this stability is one of the key aims of modern systems biology. Dissecting the basis of robustness to mutation has proven a particular challenge, with most experimental models relying on artificial DNA sequence variants engineered in the laboratory. In this work, we hypothesized that negative regulatory feedback could stabilize gene expression against the disruptions that arise from natural genetic variation. We screened yeast transcription factors for feedback and used the results to establish ROX1 (Repressor of hypOXia) as a model system for the study of feedback in circuit behaviors and its impact across genetically heterogeneous populations. Mutagenesis experiments revealed the mechanism of Rox1 as a direct transcriptional repressor at its own gene, enabling a regulatory program of rapid induction during environmental change that reached a plateau of moderate steady-state expression. Additionally, in a given environmental condition, Rox1 levels varied widely across genetically distinct strains; the ROX1 feedback loop regulated this variation, in that the range of expression levels across genetic backgrounds showed greater spread in ROX1 feedback mutants than among strains with the ROX1 feedback loop intact. Our findings indicate that the ROX1 feedback circuit is tuned to respond to perturbations arising from natural genetic variation in addition to its role in induction behavior. We suggest that regulatory feedback may be an important element of the network architectures that confer mutational robustness across biology.

Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit.

Adjusting phenotypes by noise control

Genetically identical cells can show phenotypic variability. This is often caused by stochastic events that originate from randomness in biochemical processes involving in gene expression and other extrinsic cellular processes. From an engineering perspective, there have been efforts focused on theory and experiments to control noise levels by perturbing and replacing gene network components. However, systematic methods for noise control are lacking mainly due to the intractable mathematical structure of noise propagation through reaction networks. Here, we provide a numerical analysis method by quantifying the parametric sensitivity of noise characteristics at the level of the linear noise approximation. Our analysis is readily applicable to various types of noise control and to different types of system; for example, we can orthogonally control the mean and noise levels and can control system dynamics such as noisy oscillations. As an illustration we applied our method to HIV and yeast gene expression systems and metabolic networks. The oscillatory signal control was applied to p53 oscillations from DNA damage. Furthermore, we showed that the efficiency of orthogonal control can be enhanced by applying extrinsic noise and feedback. Our noise control analysis can be applied to any stochastic model belonging to continuous time Markovian systems such as biological and chemical reaction systems, and even computer and social networks. We anticipate the proposed analysis to be a useful tool for designing and controlling synthetic gene networks.

Stochastic gene expression at the single cell level can lead to significant phenotypic variation at the population level. To obtain a desired phenotype, the noise levels of intracellular protein concentrations may need to be tuned and controlled. Noise levels often decrease in relative amount as the mean values increase. This implies that the noise levels can be passively controlled by changing the mean values. In an engineering perspective, the noise levels can be further controlled while the mean values can be simultaneously adjusted to desired values. Here, systematic schemes for such simultaneous control are described by identifying where and by how much the system needs to be perturbed. The schemes can be applied to the design process of a potential therapeutic HIV-drug that targets a certain set of reactions that are identified by the proposed analysis, to prevent stochastic transition to the lytic state. In some cases, the simultaneous control cannot be performed efficiently, when the noise levels strongly change with the mean values. This problem is shown to be resolved by applying extra noise and feedback.

A two-dimensional ERK-AKT signaling code for an NGF-triggered cell-fate decision

Growth factors activate Ras, PI3K, and other signaling pathways. It is not well understood how these signals are translated by individual cells into a decision to proliferate or differentiate. Here, using single-cell image analysis of nerve growth factor (NGF)-stimulated PC12 cells, we identified a two-dimensional phospho-ERK (pERK)-phospho-AKT (pAKT) response map with a curved boundary that separates differentiating from proliferating cells. The boundary position remained invariant when different stimuli were used or upstream signaling components perturbed. We further identified Rasa2 as a negative feedback regulator that links PI3K to Ras, placing the stochastically distributed pERK-pAKT signals close to the decision boundary. This allows for uniform NGF stimuli to create a subpopulation of cells that differentiates with each cycle of proliferation. Thus, by linking a complex signaling system to a simpler intermediate response map, cells gain unique integration and control capabilities to balance cell number expansion with differentiation.

Robust signal processing in living cells

Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations.

Consequences of eukaryotic enhancer architecture for gene expression dynamics, development, and fitness

The regulatory logic of time- and tissue-specific gene expression has mostly been dissected in the context of the smallest DNA fragments that, when isolated, recapitulate native expression in reporter assays. It is not known if the genomic sequences surrounding such fragments, often evolutionarily conserved, have any biological function or not. Using an enhancer of the even-skipped gene of Drosophila as a model, we investigate the functional significance of the genomic sequences surrounding empirically identified enhancers. A 480 bp long "minimal stripe element" is able to drive even-skipped expression in the second of seven stripes but is embedded in a larger region of 800 bp containing evolutionarily conserved binding sites for required transcription factors. To assess the overall fitness contribution made by these binding sites in the native genomic context, we employed a gene-replacement strategy in which whole-locus transgenes, capable of rescuing even-skipped(-) lethality to adulthood, were substituted for the native gene. The molecular phenotypes were characterized by tagging Even-skipped with a fluorescent protein and monitoring gene expression dynamics in living embryos. We used recombineering to excise the sequences surrounding the minimal enhancer and site-specific transgenesis to create co-isogenic strains differing only in their stripe 2 sequences. Remarkably, the flanking sequences were dispensable for viability, proving the sufficiency of the minimal element for biological function under normal conditions. These sequences are required for robustness to genetic and environmental perturbation instead. The mutant enhancers had measurable sex- and dose-dependent effects on viability. At the molecular level, the mutants showed a destabilization of stripe placement and improper activation of downstream genes. Finally, we demonstrate through live measurements that the peripheral sequences are required for temperature compensation. These results imply that seemingly redundant regulatory sequences beyond the minimal enhancer are necessary for robust gene expression and that "robustness" itself must be an evolved characteristic of the wild-type enhancer.

Mathematical model of GAL regulon dynamics in Saccharomyces cerevisiae

Genetic switches are prevalent in nature and provide cells with a strategy to adapt to changing environments. The GAL switch is an intriguing example which is not understood in all detail. The GAL switch allows organisms to metabolize galactose, and controls whether the machinery responsible for the galactose metabolism is turned on or off. Currently, it is not known exactly how the galactose signal is sensed by the transcriptional machinery. Here we utilize quantitative tools to understand the S. cerevisiae cell response to galactose challenge, and to analyze the plausible molecular mechanisms underlying its operation. We work at a population level to develop a dynamic model based on the interplay of the key regulatory proteins Gal4p, Gal80p, and Gal3p. To our knowledge, the model presented here is the first to reproduce qualitatively the bistable network behavior found experimentally. Given the current understanding of the GAL circuit induction (Wightman et al., 2008; Jiang et al., 2009), we propose that the most likely in vivo mechanism leading to the transcriptional activation of the GAL genes is the physical interaction between galactose-activated Gal3p and Gal80p, with the complex Gal3p-Gal80p remaining bound at the GAL promoters. Our mathematical model is in agreement with the flow cytometry profiles of wild type, gal3Δ and gal80Δ mutant strains from Acar et al. (2005), and involves a fraction of actively transcribing cells with the same qualitative features as in the data set collected by Acar et al. (2010). Furthermore, the computational modeling provides an explanation for the contradictory results obtained by independent laboratories when tackling experimentally the issue of binary versus graded response to galactose induction.

Noise characteristics of the Escherichia coli rotary motor

Background

The chemotaxis pathway in the bacterium Escherichia coli allows cells to detect changes in external ligand concentration (e.g. nutrients). The pathway regulates the flagellated rotary motors and hence the cells' swimming behaviour, steering them towards more favourable environments. While the molecular components are well characterised, the motor behaviour measured by tethered cell experiments has been difficult to interpret.

Results

We study the effects of sensing and signalling noise on the motor behaviour. Specifically, we consider fluctuations stemming from ligand concentration, receptor switching between their signalling states, adaptation, modification of proteins by phosphorylation, and motor switching between its two rotational states. We develop a model which includes all signalling steps in the pathway, and discuss a simplified version, which captures the essential features of the full model. We find that the noise characteristics of the motor contain signatures from all these processes, albeit with varying magnitudes.

Conclusions

Our analysis allows us to address how cell-to-cell variation affects motor behaviour and the question of optimal pathway design. A similar comprehensive analysis can be applied to other two-component signalling pathways.

Strong negative feedback from Erk to Raf confers robustness to MAPK signalling

This study shows that MAPK signalling is robust against protein level changes due to a strong negative feedback from Erk to Raf. Surprisingly, robustness is provided through a fast post-translational mechanism although variation of Erk levels occurs on a timescale of days.

MAPK signalling is robust against variation in protein level.

Robustness is mediated by a negative feedback to Raf.

Loss of negative feedback due to mutation in B-Raf opens the door for targeted intervention.

Protein levels within signal transduction pathways vary strongly from cell to cell. For example, it has been reported that concentrations of the last kinase within the MAPK signalling module, Erk, varies about four-fold between clonal cells under the same conditions. In the present study, we analysed how signalling pathways can still process information quantitatively despite strong heterogeneity in protein levels. Mathematical analysis of isolated phosphorylation–dephosphorylation cycles predicts that phosphorylation of a signalling molecule is proportional to the protein concentration. We systematically perturbed the protein levels of Erk in human cell lines by siRNA. We found that the steady-state phosphorylation of Erk is very robust against perturbations of Erk protein level, suggesting that there are mechanisms that provide robustness to the pathway against protein fluctuations. Using mathematical modelling, we identified three potential mechanisms that may provide robustness against fluctuating protein levels:

1. Kinetic effects (saturation of the activating kinase Mek),

2. Transcriptional negative feedbacks,

3. Negative feedbacks on the post-translational level.

By experimental analysis of the systems, which included analysis of Erk phosphorylation under Mek overexpression, measuring transcript levels of negative feedback regulators, and application of generic inhibitors of transcription and translation, we could exclude kinetic effects and transcriptional negative feedback as mechanisms of robustness.

By analysing a panel of cell lines, we found that cells are robust as long as the signal passes through Raf-1. In contrast, cells where the pathway is activated by a mutation in B-Raf lose robustness. Detailed molecular analysis of the system shows that a single post-translational feedback to Raf mediates robustness. Thus, robustness is provided through a fast post-translational mechanism although variation of Erk levels occurs on a timescale of days.

Protein levels within signal transduction pathways vary strongly from cell to cell. Here, we analysed how signalling pathways can still process information quantitatively despite strong heterogeneity in protein levels. We systematically perturbed the protein levels of Erk, the terminal kinase in the MAPK signalling pathway in a panel of human cell lines. We found that the steady-state phosphorylation of Erk is very robust against perturbations of Erk protein level. Although a multitude of mechanisms exist that may provide robustness against fluctuating protein levels, we found that one single feedback from Erk to Raf-1 accounts for the observed robustness. Surprisingly, robustness is provided through a fast post-translational mechanism although variation of Erk levels occurs on a timescale of days.

Adaptation of cells to new environments

The evolutionary success of an organism is a testament to its inherent capacity to keep pace with environmental conditions that change over short and long periods. Mechanisms underlying adaptive processes are being investigated with renewed interest and excitement. This revival is partly fueled by powerful technologies that can probe molecular phenomena at a systems scale. Such studies provide spectacular insight into the mechanisms of adaptation, including rewiring of regulatory networks via natural selection of horizontal gene transfers, gene duplication, deletion, readjustment of kinetic parameters, and myriad other genetic reorganizational events. Here, we discuss advances in prokaryotic systems biology from the perspective of evolutionary principles that have shaped regulatory networks for dynamic adaptation to environmental change.

What does physics have to do with cancer?

Large-scale cancer genomics, proteomics and RNA-sequencing efforts are currently mapping in fine detail the genetic and biochemical alterations that occur in cancer. However, it is becoming clear that it is difficult to integrate and interpret these data and to translate them into treatments. This difficulty is compounded by the recognition that cancer cells evolve, and that initiation, progression and metastasis are influenced by a wide variety of factors. To help tackle this challenge, the US National Cancer Institute Physical Sciences-Oncology Centers initiative is bringing together physicists, cancer biologists, chemists, mathematicians and engineers. How are we beginning to address cancer from the perspective of the physical sciences?

Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template

Natural and synthetic biological networks must function reliably in the face of fluctuating stoichiometry of their molecular components. These fluctuations are caused in part by changes in relative expression efficiency and the DNA template amount of the network-coding genes. Gene product levels could potentially be decoupled from these changes via built-in adaptation mechanisms, thereby boosting network reliability. Here, we show that a mechanism based on an incoherent feedforward motif enables adaptive gene expression in mammalian cells. We modeled, synthesized, and tested transcriptional and post-transcriptional incoherent loops and found that in all cases the gene product adapts to changes in DNA template abundance. We also observed that the post-transcriptional form results in superior adaptation behavior, higher absolute expression levels, and lower intrinsic fluctuations. Our results support a previously hypothesized endogenous role in gene dosage compensation for such motifs and suggest that their incorporation in synthetic networks will improve their robustness and reliability.

Rapid optimization of gene dosage in E. coli using DIAL strains

BACKGROUND

Engineers frequently vary design parameters to optimize the behaviour of a system. However, synthetic biologists lack the tools to rapidly explore a critical design parameter, gene expression level, and have no means of systematically varying the dosage of an entire genetic circuit. As a step toward overcoming this shortfall, we have developed a technology that enables the same plasmid to be maintained at different copy numbers in a set of closely related cells. This provides a rapid method for exploring gene or cassette dosage effects.

RESULTS

We engineered two sets of strains to constitutively provide a trans-acting replication factor, either Pi of the R6K plasmid or RepA of the ColE2 plasmid, at different doses. Each DIAL (different allele) strain supports the replication of a corresponding plasmid at a constant level between 1 and 250 copies per cell. The plasmids exhibit cell-to-cell variability comparable to other popular replicons, but with improved stability. Since the origins are orthogonal, both replication factors can be incorporated into the same cell. We demonstrate the utility of these strains by rapidly assessing the optimal expression level of a model biosynthetic pathway for violecein.

CONCLUSIONS

The DIAL strains can rapidly optimize single gene expression levels, help balance expression of functionally coupled genetic elements, improve investigation of gene and circuit dosage effects, and enable faster development of metabolic pathways.

Directed evolution of a small-molecule-triggered intein with improved splicing properties in mammalian cells

Laboratory-created small-molecule-dependent inteins enable protein structure and function to be controlled posttranslationally in living cells. Previously we evolved inteins that splice efficiently in Saccharomyces cerevisiae only in the presence of the cell-permeable small molecule 4-hydroxytamoxifen (4-HT). In mammalian cells, however, these inteins exhibited lower splicing efficiencies and slower splicing in the presence of 4-HT, as well as higher background splicing in the absence of 4-HT. Here we further evolved ligand-dependent inteins in yeast at 30°C and 37°C. The resulting second-generation evolved inteins exhibit substantially improved splicing yields and kinetics. The improvements carried over to mammalian cells, in which the newly evolved inteins spliced with substantially greater (∼2- to 8-fold) efficiency while maintaining low background splicing levels. These second-generation inteins augment the promise of ligand-dependent protein splicing for probing protein function in mammalian cells.

X-chromosome inactivation: molecular mechanisms from the human perspective

X-chromosome inactivation is an epigenetic process whereby one X chromosome is silenced in mammalian female cells. Since it was first proposed by Lyon in 1961, mouse models have been valuable tools to uncover the molecular mechanisms underlying X inactivation. However, there are also inherent differences between mouse and human X inactivation, ranging from sequence content of the X inactivation center to the phenotypic outcomes of X-chromosome abnormalities. X-linked gene dosage in males, females, and individuals with X aneuploidies and X/autosome translocations has demonstrated that many human genes escape X inactivation, implicating cis-regulatory elements in the spread of silencing. We discuss the potential nature of these elements and also review the elements in the X inactivation center involved in the early events in X-chromosome inactivation.

Transcriptional robustness and protein interactions are associated in yeast

Background

Robustness to insults, both external and internal, is a characteristic feature of life. One level of biological organization for which noise and robustness have been extensively studied is gene expression. Cells have a variety of mechanisms for buffering noise in gene expression, but it is not completely clear what rules govern whether or not a given gene uses such tools to maintain appropriate expression.

Results

Here, we show a general association between the degree to which yeast cells have evolved mechanisms to buffer changes in gene expression and whether they possess protein-protein interactions. We argue that this effect bears an affinity to epistasis, because yeast appears to have evolved regulatory mechanisms such that distant changes in gene copy number for a protein-protein interaction partner gene can alter a gene's expression. This association is not unexpected given recent work linking epistasis and the deleterious effects of changes in gene dosage (i.e., the dosage balance hypothesis). Using gene expression data from artificial aneuploid strains of bakers' yeast, we found that genes coding for proteins that physically interact with other proteins show less expression variation in response to aneuploidy than do other genes. This effect is even more pronounced for genes whose products interact with proteins encoded on aneuploid chromosomes. We further found that genes targeted by transcription factors encoded on aneuploid chromosomes were more likely to change in expression after aneuploidy.

Conclusions

We suggest that these observations can be best understood as resulting from the higher fitness cost of misexpression in epistatic genes and a commensurate greater regulatory control of them.