A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization.

Diverse biological systems utilize fluctuations ("noise") in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that-after a noise-driven event-human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noise to stabilize HIV's commitment decision, and a noise-suppression molecule promotes stabilization. This feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.

An endogenous accelerator for viral gene expression confers a fitness advantage.

Many signaling circuits face a fundamental tradeoff between accelerating their response speed while maintaining final levels below a cytotoxic threshold. Here, we describe a transcriptional circuitry that dynamically converts signaling inputs into faster rates without amplifying final equilibrium levels. Using time-lapse microscopy, we find that transcriptional activators accelerate human cytomegalovirus (CMV) gene expression in single cells without amplifying steady-state expression levels, and this acceleration generates a significant replication advantage. We map the accelerator to a highly self-cooperative transcriptional negative-feedback loop (Hill coefficient ∼7) generated by homomultimerization of the virus's essential transactivator protein IE2 at nuclear PML bodies. Eliminating the IE2-accelerator circuit reduces transcriptional strength through mislocalization of incoming viral genomes away from PML bodies and carries a heavy fitness cost. In general, accelerators may provide a mechanism for signal-transduction circuits to respond quickly to external signals without increasing steady-state levels of potentially cytotoxic molecules.

Monocyte to macrophage differentiation and changes in cellular redox homeostasis promote cell type-specific HIV latency reactivation.

HIV latency regulation in monocytes and macrophages can vary according to signals directing differentiation, polarization, and function. To investigate these processes, we generated an HIV latency model in THP-1 monocytes and showed differential levels of HIV reactivation among clonal populations. Monocyte-to-macrophage differentiation of HIV-infected primary human CD14+ and THP-1 cells induced HIV reactivation and showed that virus production increased concomitant with macrophage differentiation. We applied the HIV-infected THP-1 monocyte-to-macrophage (MLat) model to assess the biological mechanisms regulating HIV latency dynamics during monocyte-to-macrophage differentiation. We pinpointed protein kinase C signaling pathway activation and Cyclin T1 upregulation as inherent differentiation mechanisms that regulate HIV latency reactivation. Macrophage polarization regulated latency, revealing proinflammatory M1 macrophages suppressed HIV reactivation while anti-inflammatory M2 macrophages promoted HIV reactivation. Because macrophages rely on reactive-oxygen species (ROS) to exert numerous cellular functions, we disrupted redox pathways and found that inhibitors of the thioredoxin (Trx) system acted as latency-promoting agents in T-cells and monocytes, but opposingly acted as latency-reversing agents in macrophages. We explored this mechanism with Auranofin, a clinical candidate for reducing HIV reservoirs, and demonstrated Trx reductase inhibition led to ROS induced NF-κB activity, which promoted HIV reactivation in macrophages, but not in T-cells and monocytes. Collectively, cell type-specific differences in HIV latency regulation could pose a barrier to HIV eradication strategies.

Screening for gene expression fluctuations reveals latency-promoting agents of HIV.

Upon treatment removal, spontaneous reactivation of latently infected T cells remains a major barrier toward curing HIV. Therapies that reactivate and clear the latent reservoir are only partially effective, while latency-promoting agents (LPAs) used to suppress reactivation and stabilize latency are understudied and lack diversity in their mechanisms of action. Here, we identify additional LPAs using a screen for gene-expression fluctuations (or "noise") that drive cell-fate specification and control HIV reactivation from latency. Single-cell protein dynamics of a minimal HIV gene circuit were monitored with time-lapse fluorescence microscopy. We screened 1,806 drugs, out of which 279 modulate noise magnitude or half autocorrelation time. Next, we tested the strongest noise modulators in a Jurkat T cell latency model and discovered three LPAs that would be overlooked by quantifying their mean expression levels alone. The LPAs reduced reactivation of latency in both Jurkat and primary cell models when challenged by synergistic and potent combinations of HIV activators. The two strongest LPAs, NSC 401005 and NSC 400938, are structurally and functionally related to inhibitors of thioredoxin reductase, a protein involved in maintaining redox balance in host cells. Experiments with multiple functional analogs revealed two additional LPAs, PX12 and tiopronin, and suggest a potential LPA family, within which some are commercially available and Food and Drug Administration-approved. The LPAs presented here may provide new strategies to complement antiretroviral treatments. Screening for gene expression noise holds the potential for drug discovery in other diseases.

Transcriptional burst frequency and burst size are equally modulated across the human genome.

Gene expression occurs either as an episodic process, characterized by pulsatile bursts, or as a constitutive process, characterized by a Poisson-like accumulation of gene products. It is not clear which mode of gene expression (constitutive versus bursty) predominates across a genome or how transcriptional dynamics are influenced by genomic position and promoter sequence. Here, we use time-lapse fluorescence microscopy to analyze 8,000 individual human genomic loci and find that at virtually all loci, episodic bursting--as opposed to constitutive expression--is the predominant mode of expression. Quantitative analysis of the expression dynamics at these 8,000 loci indicates that both the frequency and size of the transcriptional bursts varies equally across the human genome, independent of promoter sequence. Strikingly, weaker expression loci modulate burst frequency to increase activity, whereas stronger expression loci modulate burst size to increase activity. Transcriptional activators such as trichostatin A (TSA) and tumor necrosis factor α (TNF) only modulate burst size and frequency along a constrained trend line governed by the promoter. In summary, transcriptional bursting dominates across the human genome, both burst frequency and burst size vary by chromosomal location, and transcriptional activators alter burst frequency and burst size, depending on the expression level of the locus.

Dynamics of protein noise can distinguish between alternate sources of gene-expression variability.

Within individual cells, two molecular processes have been implicated as sources of noise in gene expression: (i) Poisson fluctuations in mRNA abundance arising from random birth and death of individual mRNA transcripts or (ii) promoter fluctuations arising from stochastic promoter transitions between different transcriptional states. Steady-state measurements of variance in protein levels are insufficient to discriminate between these two mechanisms, and mRNA single-molecule fluorescence in situ hybridization (smFISH) is challenging when cellular mRNA concentrations are high. Here, we present a perturbation method that discriminates mRNA birth/death fluctuations from promoter fluctuations by measuring transient changes in protein variance and that can operate in the regime of high molecular numbers. Conceptually, the method exploits the fact that transcriptional blockage results in more rapid increases in protein variability when mRNA birth/death fluctuations dominate over promoter fluctuations. We experimentally demonstrate the utility of this perturbation approach in the HIV-1 model system. Our results support promoter fluctuations as the primary noise source in HIV-1 expression. This study illustrates a relatively simple method that complements mRNA smFISH hybridization and can be used with existing GFP-tagged libraries to include or exclude alternate sources of noise in gene expression.

Principles for the design of multicellular engineered living systems.

Remarkable progress in bioengineering over the past two decades has enabled the formulation of fundamental design principles for a variety of medical and non-medical applications. These advancements have laid the foundation for building multicellular engineered living systems (M-CELS) from biological parts, forming functional modules integrated into living machines. These cognizant design principles for living systems encompass novel genetic circuit manipulation, self-assembly, cell-cell/matrix communication, and artificial tissues/organs enabled through systems biology, bioinformatics, computational biology, genetic engineering, and microfluidics. Here, we introduce design principles and a blueprint for forward production of robust and standardized M-CELS, which may undergo variable reiterations through the classic design-build-test-debug cycle. This Review provides practical and theoretical frameworks to forward-design, control, and optimize novel M-CELS. Potential applications include biopharmaceuticals, bioreactor factories, biofuels, environmental bioremediation, cellular computing, biohybrid digital technology, and experimental investigations into mechanisms of multicellular organisms normally hidden inside the "black box" of living cells.

Using noise to probe and characterize gene circuits.

Stochastic fluctuations (or "noise") in the single-cell populations of molecular species are shaped by the structure and biokinetic rates of the underlying gene circuit. The structure of the noise is summarized by its autocorrelation function. In this article, we introduce the noise regulatory vector as a generalized framework for making inferences concerning the structure and biokinetic rates of a gene circuit from its noise autocorrelation function. Although most previous studies have focused primarily on the magnitude component of the noise (given by the zero-lag autocorrelation function), our approach also considers the correlation component, which encodes additional information concerning the circuit. Theoretical analyses and simulations of various gene circuits show that the noise regulatory vector is characteristic of the composition of the circuit. Although a particular noise regulatory vector does not map uniquely to a single underlying circuit, it does suggest possible candidate circuits, while excluding others, thereby demonstrating the probative value of noise in gene circuit analysis.

Internetwork connectivity of molecular networks across species of life.

Molecular interactions are studied as independent networks in systems biology. However, molecular networks do not exist independently of each other. In a network of networks approach (called multiplex), we study the joint organization of transcriptional regulatory network (TRN) and protein-protein interaction (PPI) network. We find that TRN and PPI are non-randomly coupled across five different eukaryotic species. Gene degrees in TRN (number of downstream genes) are positively correlated with protein degrees in PPI (number of interacting protein partners). Gene-gene and protein-protein interactions in TRN and PPI, respectively, also non-randomly overlap. These design principles are conserved across the five eukaryotic species. Robustness of the TRN-PPI multiplex is dependent on this coupling. Functionally important genes and proteins, such as essential, disease-related and those interacting with pathogen proteins, are preferentially situated in important parts of the human multiplex with highly overlapping interactions. We unveil the multiplex architecture of TRN and PPI. Multiplex architecture may thus define a general framework for studying molecular networks. This approach may uncover the building blocks of the hierarchical organization of molecular interactions.

A transient heritable memory regulates HIV reactivation from latency.

Reactivation of human immunodeficiency virus 1 (HIV-1) from latently infected T cells is a critical barrier to cure patients. It remains unknown whether reactivation of individual latent cells occurs stochastically in response to latency reversal agents (LRAs) or is a deterministic outcome of an underlying cell state. To characterize these single-cell responses, we leverage the classical Luria-Delbrück fluctuation test where single cells are isolated from a clonal population and exposed to LRAs after colony expansion. Data show considerable colony-to-colony fluctuations with the fraction of reactivating cells following a skewed distribution. Modeling systematic measurements of fluctuations over time uncovers a transient heritable memory that regulates HIV-1 reactivation, where single cells are in an LRA-responsive state for a few weeks before switching back to an irresponsive state. These results have enormous implications for designing therapies to purge the latent reservoir and further utilize fluctuation-based assays to uncover hidden transient cellular states underlying phenotypic heterogeneity.

Synergistic Chromatin-Modifying Treatments Reactivate Latent HIV and Decrease Migration of Multiple Host-Cell Types.

Upon infection of its host cell, human immunodeficiency virus (HIV) establishes a quiescent and non-productive state capable of spontaneous reactivation. Diverse cell types harboring the provirus form a latent reservoir, constituting a major obstacle to curing HIV. Here, we investigate the effects of latency reversal agents (LRAs) in an HIV-infected THP-1 monocyte cell line in vitro. We demonstrate that leading drug treatments synergize activation of the HIV long terminal repeat (LTR) promoter. We establish a latency model in THP-1 monocytes using a replication incompetent HIV reporter vector with functional Tat, and show that chromatin modifiers synergize with a potent transcriptional activator to enhance HIV reactivation, similar to T-cells. Furthermore, leading reactivation cocktails are shown to differentially affect latency reactivation and surface expression of chemokine receptor type 4 (CXCR4), leading to altered host cell migration. This study investigates the effect of chromatin-modifying LRA treatments on HIV latent reactivation and cell migration in monocytes. As previously reported in T-cells, epigenetic mechanisms in monocytes contribute to controlling the relationship between latent reactivation and cell migration. Ultimately, advanced "Shock and Kill" therapy needs to successfully target and account for all host cell types represented in a complex and composite latency milieu.

Monitoring reactivation of latent HIV by label-free gradient light interference microscopy.

Human immunodeficiency virus (HIV) can infect cells and take a quiescent and nonexpressive state called latency. In this study, we report insights provided by label-free, gradient light interference microscopy (GLIM) about the changes in dry mass, diameter, and dry mass density associated with infected cells that occur upon reactivation. We discovered that the mean cell dry mass and mean diameter of latently infected cells treated with reactivating drug, TNF-α, are higher for latent cells that reactivate than those of the cells that did not reactivate. Cells with mean dry mass and diameter less than approximately 10 pg and 8 µm, respectively, remain exclusively in the latent state. Also, cells with mean dry mass greater than approximately 28-30 pg and mean diameter greater than 11-12 µm have a higher probability of reactivating. This study is significant as it presents a new label-free approach to quantify latent reactivation of a virus in single cells.

Cell size dependent migration of T-cells latently infected with HIV.

Human immunodeficiency virus (HIV) preferentially infects T-lymphocytes by integrating into host DNA and forming a latent transcriptionally silent provirus. As previously shown, HIV-1 alters migration modes of T-lymphocytes by co-regulating viral gene expression with human C-X-C chemokine receptor-4 (CXCR4). Here, we show that motility of infected T-lymphocytes is cell size dependent. In cell migration assays, migrating cells are consistently larger than non-migrating cells. This effect is drug-treatment independent. The cell size dependent motility observed in a previously generated Jurkat latency model correlates with the motility of primary human CD4+ T-cells containing a modified HIV-1 full-length construct JLatd2GFP. In addition, large migrating T-cells, latently infected with HIV, show a slightly decreased rate of reactivation from latency. these results demonstrate that HIV reactivation is cell migration-dependent, where host cell size acts as a catalyst for altered migration velocity. We believe that host cell size controlled migration uncovers an additional mechanism of cellular controlled viral fate determination important for virus dissemination and reactivation from latency. This observation may provide more insights into viral-host interactions regulating cell migration and reactivation from latency and helps in the design and implementation of novel therapeutic strategies.

Perspective: Engineering noise in biological systems towards predictive stochastic design.

Significant progress has been made towards engineering both single-cell and multi-cellular systems through a combination of synthetic and systems biology, nanobiotechnology, pharmaceutical science, and computational approaches. However, our ability to engineer systems that begin to approach the complexity of natural pathways is severely limited by important challenges, e.g. due to noise, or the fluctuations in gene expression and molecular species at multiple scales (e.g. both intra- and inter-cellular fluctuations). This barrier to engineering requires that biological noise be recognized as a design element with fundamentals that can be actively controlled. Here we highlight studies of an emerging discipline that collectively strives to engineer noise towards predictive stochastic design using interdisciplinary approaches at multiple-scales in diverse living systems.

Cell Size-Based Decision-Making of a Viral Gene Circuit.

Latently infected T cells able to reinitiate viral propagation throughout the body remain a major barrier to curing HIV. Distinguishing between latently infected cells and uninfected cells will advance efforts for viral eradication. HIV decision-making between latency and active replication is stochastic, and drug cocktails that increase bursts of viral gene expression enhance reactivation from latency. Here, we show that a larger host-cell size provides a natural cellular mechanism for enhancing burst size of viral expression and is necessary to destabilize the latent state and bias viral decision-making. Latently infected Jurkat and primary CD4+ T cells reactivate exclusively in larger activated cells, while smaller cells remain silent. In addition, reactivation is cell-cycle dependent and can be modulated with cell-cycle-arresting compounds. Cell size and cell-cycle dependent decision-making of viral circuits may guide stochastic design strategies and applications in synthetic biology and may provide important determinants to advance diagnostics and therapies.

Fine-tuning of noise in gene expression with nucleosome remodeling.

Engineering stochastic fluctuations of gene expression (or "noise") is integral to precisely bias cellular-fate decisions and statistical phenotypes in both single-cell and multi-cellular systems. Epigenetic regulation has been shown to constitute a large source of noise, and thus, engineering stochasticity is deeply intertwined with epigenetics. Here, utilizing chromatin remodeling, we report that Caffeic acid phenethyl ester (CA) and Pyrimethamine (PYR), two inhibitors of BAF250a, a subunit of the Brahma-associated factor (BAF) nucleosome remodeling complex, enable differential and tunable control of noise in transcription and translation from the human immunodeficiency virus long terminal repeat promoter in a dose and time-dependent manner. CA conserves noise levels while increasing mean abundance, resulting in direct tuning of the transcriptional burst size, while PYR strictly increases transcriptional initiation frequency while conserving a constant transcriptional burst size. Time-dependent treatment with CA reveals non-continuous tuning with noise oscillating at a constant mean abundance at early time points and the burst size increasing for treatments after 5 h. Treatments combining CA and Protein Kinase C agonists result in an even larger increase of abundance while conserving noise levels with a highly non-linear increase in variance of up to 63× untreated controls. Finally, drug combinations provide non-antagonistic combinatorial tuning of gene expression noise and map a noise phase space for future applications with viral and synthetic gene vectors. Active remodeling of nucleosomes and BAF-mediated control of gene expression noise expand a toolbox for the future design and engineering of stochasticity in living systems.

Perspective: The promise of multi-cellular engineered living systems.

Recent technological breakthroughs in our ability to derive and differentiate induced pluripotent stem cells, organoid biology, organ-on-chip assays, and 3-D bioprinting have all contributed to a heightened interest in the design, assembly, and manufacture of living systems with a broad range of potential uses. This white paper summarizes the state of the emerging field of "multi-cellular engineered living systems," which are composed of interacting cell populations. Recent accomplishments are described, focusing on current and potential applications, as well as barriers to future advances, and the outlook for longer term benefits and potential ethical issues that need to be considered.

Similarity in viral and host promoters couples viral reactivation with host cell migration.

Viral-host interactomes map the complex architecture of an evolved arms race during host cell invasion. mRNA and protein interactomes reveal elaborate targeting schemes, yet evidence is lacking for genetic coupling that results in the co-regulation of promoters. Here we compare viral and human promoter sequences and expression to test whether genetic coupling exists and investigate its phenotypic consequences. We show that viral-host co-evolution is imprinted within promoter gene sequences before transcript or protein interactions. Co-regulation of human immunodeficiency virus (HIV) and human C-X-C chemokine receptor-4 (CXCR4) facilitates migration of infected cells. Upon infection, HIV can actively replicate or remain dormant. Migrating infected cells reactivate from dormancy more than non-migrating cells and exhibit differential migration-reactivation responses to drugs. Cells producing virus pose a risk for reinitiating infection within niches inaccessible to drugs, and tuning viral control of migration and reactivation improves strategies to eliminate latent HIV. Viral-host genetic coupling establishes a mechanism for synchronizing transcription and guiding potential therapies.

Transcriptional Bursting Explains the Noise-Versus-Mean Relationship in mRNA and Protein Levels.

Recent analysis demonstrates that the HIV-1 Long Terminal Repeat (HIV LTR) promoter exhibits a range of possible transcriptional burst sizes and frequencies for any mean-expression level. However, these results have also been interpreted as demonstrating that cell-to-cell expression variability (noise) and mean are uncorrelated, a significant deviation from previous results. Here, we re-examine the available mRNA and protein abundance data for the HIV LTR and find that noise in mRNA and protein expression scales inversely with the mean along analytically predicted transcriptional burst-size manifolds. We then experimentally perturb transcriptional activity to test a prediction of the multiple burst-size model: that increasing burst frequency will cause mRNA noise to decrease along given burst-size lines as mRNA levels increase. The data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.

The Low Noise Limit in Gene Expression.

Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can-and in the case of E. coli does-control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1) a global noise floor uniformly imposed on all genes by expression bursting; and (2) high noise distributed to only a select group of genes.