Sources of Variability in a Synthetic Gene Oscillator

Synthetic gene oscillators are small, engineered genetic circuits that produce periodic variations in target protein expression. Like other gene circuits, synthetic gene oscillators are noisy and exhibit fluctuations in amplitude and period. Understanding the origins of such variability is key to building predictive models that can guide the rational design of synthetic circuits. Here, we developed a method for determining the impact of different sources of noise in genetic oscillators by measuring the variability in oscillation amplitude and correlations between sister cells. We first used a combination of microfluidic devices and time-lapse fluorescence microscopy to track oscillations in cell lineages across many generations. We found that oscillation amplitude exhibited high cell-to-cell variability, while sister cells remained strongly correlated for many minutes after cell division. To understand how such variability arises, we constructed a computational model that identified the impact of various noise sources across the lineage of an initial cell. When each source of noise was appropriately tuned the model reproduced the experimentally observed amplitude variability and correlations, and accurately predicted outcomes under novel experimental conditions. Our combination of computational modeling and time-lapse data analysis provides a general way to examine the sources of variability in dynamic gene circuits.     

Listening to the noise: random fluctuations reveal gene network parameters

The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations show cell‐to‐cell variability that can manifest significant phenotypic differences. Noise‐induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever‐present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We show that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.     

Engineering stochasticity in gene expression

Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise.     

Attenuation of noise in ultrasensitive signaling cascades

Ultrasensitive cascades often implement thresholding operations in cell signaling and gene regulatory networks, converting graded input signals into discrete all-or-none outputs. However, the biochemical and genetic reactions involved in such cascades are subject to random fluctuations, leading to noise in output signal levels. Here we prove that cascades operating near saturation have output signal fluctuations that are bounded in magnitude, even as the number of noisy cascade stages becomes large. We show that these fluctuation-bounded cascades can be used to attenuate the noise in an input signal, and we find the optimal cascade length required to achieve the best possible noise reduction. Cascades with ultrasensitive transfer functions naturally operate near saturation, and can be made to simultaneously implement thresholding and noise reduction. They are therefore ideally suited to mediate signal transfer in both natural and artificial biological networks.     

Cellular noise regulons underlie fluctuations in Saccharomyces cerevisiae

Stochasticity is a hallmark of cellular processes, and different classes of genes show large differences in their cell-to-cell variability (noise). To decipher the sources and consequences of this noise, we systematically measured pairwise correlations between large numbers of genes, including those with high variability. We find that there is substantial pathway variability shared across similarly regulated genes. This induces quantitative correlations in the expression of functionally related genes such as those involved in the Msn2/4 stress response pathway, amino-acid?biosynthesis, and mitochondrial maintenance. Bioinformatic analyses and genetic perturbations suggest that fluctuations in PKA and Tor signaling contribute to pathway-specific variability. Our results argue that a limited number of well-delineated "noise regulons" operate across a yeast cell and that such coordinated fluctuations enable a stochastic but coherent induction of functionally related genes. Finally, we show that pathway noise is a quantitative tool for exploring pathway features and regulatory relationships in un-stimulated systems.     

External Noise and External Signal Induced Transition of Gene Switch and Coherence Resonance in the Genetic Regulatory System

The transition of gene switch induced by external noises (multiplicative external noise and additive external noise) and external signals is investigated in the genetic regulatory system. Results show that the state-to-state transition of gene switch as well as resonant behaviors, such as the explicit coherence resonance (ECR), implicit coherence resonance (ICR) and control parameter coherence biresonance (CPCBR), can appear when noises are injected into the genetic regulatory system. The ECR is increased with the increase of the control parameter value when starting from the supercritical Hopf bifurcation parameter point, and there exists a critical control parameter value for the occurrence of ECR. However, the ICR is decreased as the control parameter value is increased when starting from the subcritical Hopf bifurcation point. In particular, the coherence of ECR is higher and more sensitive to noise than that of ICR. When an external signal is introduced into the system, the enhancement or suppression of the CPCBR and the number of peaks strongly depend on the frequency and amplitude of the external signal. Furthermore, the gene regulation system can selectively enhance or decrease the noise-induced oscillation signals at preferred frequency and amplitude of an external signal.     

Noise Genetics: Inferring Protein Function by Correlating Phenotype with Protein Levels and Localization in Individual Human Cells

To understand gene function, genetic analysis uses large perturbations such as gene deletion, knockdown or over-expression. Large perturbations have drawbacks: they move the cell far from its normal working point, and can thus be masked by off-target effects or compensation by other genes. Here, we offer a complementary approach, called noise genetics. We use natural cell-cell variations in protein level and localization, and correlate them to the natural variations of the phenotype of the same cells. Observing these variations is made possible by recent advances in dynamic proteomics that allow measuring proteins over time in individual living cells. Using motility of human cancer cells as a model system, and time-lapse microscopy on 566 fluorescently tagged proteins, we found 74 candidate motility genes whose level or localization strongly correlate with motility in individual cells. We recovered 30 known motility genes, and validated several novel ones by mild knockdown experiments. Noise genetics can complement standard genetics for a variety of phenotypes.     

Genome-wide DNA methylation variability in adolescent monozygotic twins followed since birth

DNA methylation patterns are characterized by highly conserved developmental programs, but allow for divergent gene expression resulting from stochastic epigenetic drift or divergent environments. Genome-wide methylation studies in monozygotic (MZ) twins are providing insight into the extent of epigenetic variation that occurs, irrespective of genotype. However, little is known about the variability of DNA methylation patterns in adolescence, a period involving significant and rapid physical, emotional, social, and neurodevelopmental change. Here, we assessed genome-wide DNA methylation using the 450?K Illumina BeadChip in a sample of 37 MZ twin pairs followed longitudinally since birth to investigate: 1) the extent of variation in DNA methylation in identical genetic backgrounds in adolescence and; 2) whether these variations are randomly distributed or enriched in particular functional pathways. We also assessed stability of DNA methylation over 3–6 months to distinguish stable trait-like and variable state-like genes. A pathway analysis found high within-pair variability in genes associated with development, cellular mechanisms, tissue and cell morphology, and various disorders. Test-retest analyses performed in a sub-sample of 8 twin pairs demonstrated enrichment in gene pathways involved in organismal development, cellular growth and proliferation, cell signaling, and particular disorders. The variability found in functional gene pathways may plausibly underlie phenotypic differences in this adolescent MZ twin sample. Furthermore, we assessed stability of methylation over 3–6 months and found that some genes were stable while others were unstable, suggesting that the methylome remains dynamic in adolescence and that dynamic sites tend to be organized in certain gene pathways.     

Genome-wide DNA methylation variability in adolescent monozygotic twins followed since birth

DNA methylation patterns are characterized by highly conserved developmental programs, but allow for divergent gene expression resulting from stochastic epigenetic drift or divergent environments. Genome-wide methylation studies in monozygotic (MZ) twins are providing insight into the extent of epigenetic variation that occurs, irrespective of genotype. However, little is known about the variability of DNA methylation patterns in adolescence, a period involving significant and rapid physical, emotional, social, and neurodevelopmental change. Here, we assessed genome-wide DNA methylation using the 450 K Illumina BeadChip in a sample of 37 MZ twin pairs followed longitudinally since birth to investigate: 1) the extent of variation in DNA methylation in identical genetic backgrounds in adolescence and; 2) whether these variations are randomly distributed or enriched in particular functional pathways. We also assessed stability of DNA methylation over 3–6 months to distinguish stable trait-like and variable state-like genes. A pathway analysis found high within-pair variability in genes associated with development, cellular mechanisms, tissue and cell morphology, and various disorders. Test-retest analyses performed in a sub-sample of 8 twin pairs demonstrated enrichment in gene pathways involved in organismal development, cellular growth and proliferation, cell signaling, and particular disorders. The variability found in functional gene pathways may plausibly underlie phenotypic differences in this adolescent MZ twin sample. Furthermore, we assessed stability of methylation over 3–6 months and found that some genes were stable while others were unstable, suggesting that the methylome remains dynamic in adolescence and that dynamic sites tend to be organized in certain gene pathways.     

Computational design of synthetic regulatory networks from a genetic library to characterize the designability of dynamical behaviors

The engineering of synthetic gene networks has mostly relied on the assembly of few characterized regulatory elements using rational design principles. It is of outmost importance to analyze the scalability and limits of such a design workflow. To analyze the design capabilities of libraries of regulatory elements, we have developed the first automated design approach that combines such elements to search the genotype space associated to a given phenotypic behavior. Herein, we calculated the designability of dynamical functions obtained from circuits assembled with a given genetic library. By designing circuits working as amplitude filters, pulse counters and oscillators, we could infer new mechanisms for such behaviors. We also highlighted the hierarchical design and the optimization of the interface between devices. We dissected the functional diversity of a constrained library and we found that even such libraries can provide a rich variety of behaviors. We also found that intrinsic noise slightly reduces the designability of digital circuits, but it increases the designability of oscillators. Finally, we analyzed the robust design as a strategy to counteract the evolvability and noise in gene expression of the engineered circuits within a cellular background, obtaining mechanisms for robustness through non-linear negative feedback loops.     

Factor-induced Reprogramming and Zinc Finger Nuclease-aided Gene Targeting Cause Different Genome Instability in β-Thalassemia Induced Pluripotent Stem Cells (iPSCs)

The generation of personalized induced pluripotent stem cells (iPSCs) followed by targeted genome editing provides an opportunity for developing customized effective cellular therapies for genetic disorders. However, it is critical to ascertain whether edited iPSCs harbor unfavorable genomic variations before their clinical application. To examine the mutation status of the edited iPSC genome and trace the origin of possible mutations at different steps, we have generated virus-free iPSCs from amniotic cells carrying homozygous point mutations in β-hemoglobin gene (HBB) that cause severe β-thalassemia (β-Thal), corrected the mutations in both HBB alleles by zinc finger nuclease-aided gene targeting, and obtained the final HBB gene-corrected iPSCs by excising the exogenous drug resistance gene with Cre recombinase. Through comparative genomic hybridization and whole-exome sequencing, we uncovered seven copy number variations, five small insertions/deletions, and 64 single nucleotide variations (SNVs) in β-Thal iPSCs before the gene targeting step and found a single small copy number variation, 19 insertions/deletions, and 340 single nucleotide variations in the final gene-corrected β-Thal iPSCs. Our data revealed that substantial but different genomic variations occurred at factor-induced somatic cell reprogramming and zinc finger nuclease-aided gene targeting steps, suggesting that stringent genomic monitoring and selection are needed both at the time of iPSC derivation and after gene targeting.