Making cellular memories

Cellular forgetting, desensitisation, stress and ageing in signalling networks. When do cells refuse to learn more?

Recent findings show that single, non-neuronal cells are also able to learn signalling responses developing cellular memory. In cellular learning nodes of signalling networks strengthen their interactions e.g. by the conformational memory of intrinsically disordered proteins, protein translocation, miRNAs, lncRNAs, chromatin memory and signalling cascades. This can be described by a generalized, unicellular Hebbian learning process, where those signalling connections, which participate in learning, become stronger. Here we review those scenarios, where cellular signalling is not only repeated in a few times (when learning occurs), but becomes too frequent, too large, or too complex and overloads the cell. This leads to desensitisation of signalling networks by decoupling signalling components, receptor internalization, and consequent downregulation. These molecular processes are examples of anti-Hebbian learning and 'forgetting' of signalling networks. Stress can be perceived as signalling overload inducing the desensitisation of signalling pathways. Ageing occurs by the summative effects of cumulative stress downregulating signalling. We propose that cellular learning desensitisation, stress and ageing may be placed along the same axis of more and more intensive (prolonged or repeated) signalling. We discuss how cells might discriminate between repeated and unexpected signals, and highlight the Hebbian and anti-Hebbian mechanisms behind the fold-change detection in the NF-κB signalling pathway. We list drug design methods using Hebbian learning (such as chemically-induced proximity) and clinical treatment modalities inducing (cancer, drug allergies) desensitisation or avoiding drug-induced desensitisation. A better discrimination between cellular learning, desensitisation and stress may open novel directions in drug design, e.g. helping to overcome drug resistance.

Enhancing circuit stability under growth feedback with supplementary repressive regulation

The field of synthetic biology and biosystems engineering increasingly acknowledges the need for a holistic design approach that incorporates circuit-host interactions into the design process. Engineered circuits are not isolated entities but inherently entwined with the dynamic host environment. One such circuit-host interaction, 'growth feedback', results when modifications in host growth patterns influence the operation of gene circuits. The growth-mediated effects can range from growth-dependent elevation in protein/mRNA dilution rate to changes in resource reallocation within the cell, which can lead to complete functional collapse in complex circuits. To achieve robust circuit performance, synthetic biologists employ a variety of control mechanisms to stabilize and insulate circuit behavior against growth changes. Here we propose a simple strategy by incorporating one repressive edge in a growth-sensitive bistable circuit. Through both simulation and in vitro experimentation, we demonstrate how this additional repressive node stabilizes protein levels and increases the robustness of a bistable circuit in response to growth feedback. We propose the incorporation of repressive links in gene circuits as a control strategy for desensitizing gene circuits against growth fluctuations.

Multiorgan locked-state model of chronic diseases and systems pharmacology opportunities

With increasing human life expectancy, the global medical burden of chronic diseases is growing. Hence, chronic diseases are a pressing health concern and will continue to be in decades to come. Chronic diseases often involve multiple malfunctioning organs in the body. An imminent question is how interorgan crosstalk contributes to the etiology of chronic diseases. We conceived the locked-state model (LoSM), which illustrates how interorgan communication can give rise to body-wide memory-like properties that 'lock' healthy or pathological conditions. Next, we propose cutting-edge systems biology and artificial intelligence strategies to decipher chronic multiorgan locked states. Finally, we discuss the clinical implications of the LoSM and assess the power of systems-based therapies to dismantle pathological multiorgan locked states while improving treatments for chronic diseases.

Harnessing CRISPR-Cas adaptation for RNA recording and beyond

Prokaryotes encode clustered regularly interspaced short palindromic repeat (CRISPR) arrays and CRISPR-associated (Cas) genes as an adaptive immune machinery. CRISPR-Cas systems effectively protect hosts from the invasion of foreign enemies, such as bacteriophages and plasmids. During a process called 'adaptation', non-self-nucleic acid fragments are acquired as spacers between repeats in the host CRISPR array, to establish immunological memory. The highly conserved Cas1-Cas2 complexes function as molecular recorders to integrate spacers in a time course manner, which can subsequently be expressed as crRNAs complexed with Cas effector proteins for the RNAguided interference pathways. In some of the RNA-targeting type III systems, Cas1 proteins are fused with reverse transcriptase (RT), indicating that RT-Cas1-Cas2 complexes can acquire RNA transcripts for spacer acquisition. In this review, we summarize current studies that focus on the molecular structure and function of the RT-fused Cas1-Cas2 integrase, and its potential applications as a directional RNA-recording tool in cells. Furthermore, we highlight outstanding questions for RT-Cas1-Cas2 studies and future directions for RNA-recording CRISPR technologies. [BMB Reports 2024; 57(1): 40-49].

Temporal recording of mammalian development and precancer

Key to understanding many biological phenomena is knowing the temporal ordering of cellular events, which often require continuous direct observations [1, 2]. An alternative solution involves the utilization of irreversible genetic changes, such as naturally occurring mutations, to create indelible markers that enables retrospective temporal ordering [3-8]. Using NSC-seq, a newly designed and validated multi-purpose single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo , while incorporating assigned cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during murine embryonic development and identified new intestinal epithelial progenitor states by their unique genetic histories. NSC-seq analysis of murine adenomas and single-cell multi-omic profiling of human precancers as part of the Human Tumor Atlas Network (HTAN), including 116 scRNA-seq datasets and clonal analysis of 418 human polyps, demonstrated the occurrence of polyancestral initiation in 15-30% of colonic precancers, revealing their origins from multiple normal founders. Thus, our multimodal framework augments existing single-cell analyses and lays the foundation for in vivo multimodal recording, enabling the tracking of lineage and temporal events during development and tumorigenesis.

Optimal phenotypic adaptation in fluctuating environments

Phenotypic adaptation is a universal feature of biological systems navigating highly variable environments. Recent empirical data support the role of memory-driven decision making in cellular systems navigating uncertain future nutrient landscapes, wherein a distinct growth phenotype emerges in fluctuating conditions. We develop a simple stochastic mathematical model to describe memory-driven cellular adaptation required for systems to optimally navigate such uncertainty. In this framework, adaptive populations traverse dynamic environments by inferring future variation from a memory of prior states, and memory capacity imposes a fundamental trade-off between the speed and accuracy of adaptation to new fluctuating environments. Our results suggest that the observed growth reductions that occur in fluctuating environments are a direct consequence of optimal decision making and result from bet hedging and occasional phenotypic-environmental mismatch. We anticipate that this modeling framework will be useful for studying the role of memory in phenotypic adaptation, including in the design of temporally varying therapies against adaptive systems.

Fibrillar adhesion dynamics govern the timescales of nuclear mechano-response via the vimentin cytoskeleton

The cell nucleus is continuously exposed to external signals, of both chemical and mechanical nature. To ensure proper cellular response, cells need to regulate not only the transmission of these signals, but also their timing and duration. Such timescale regulation is well described for fluctuating chemical signals, but if and how it applies to mechanical signals reaching the nucleus is still unknown. Here we demonstrate that the formation of fibrillar adhesions locks the nucleus in a mechanically deformed conformation, setting the mechanical response timescale to that of fibrillar adhesion remodelling (~1 hour). This process encompasses both mechanical deformation and associated mechanotransduction (such as via YAP), in response to both increased and decreased mechanical stimulation. The underlying mechanism is the anchoring of the vimentin cytoskeleton to fibrillar adhesions and the extracellular matrix through plectin 1f, which maintains nuclear deformation. Our results reveal a mechanism to regulate the timescale of mechanical adaptation, effectively setting a low pass filter to mechanotransduction.

Next generation synthetic memory via intercepting recombinase function

Here we present a technology to facilitate synthetic memory in a living system via repurposing Transcriptional Programming (i.e., our decision-making technology) parts, to regulate (intercept) recombinase function post-translation. We show that interception synthetic memory can facilitate programmable loss-of-function via site-specific deletion, programmable gain-of-function by way of site-specific inversion, and synthetic memory operations with nested Boolean logical operations. We can expand interception synthetic memory capacity more than 5-fold for a single recombinase, with reconfiguration specificity for multiple sites in parallel. Interception synthetic memory is ~10-times faster than previous generations of recombinase-based memory. We posit that the faster recombination speed of our next-generation memory technology is due to the post-translational regulation of recombinase function. This iteration of synthetic memory is complementary to decision-making via Transcriptional Programming - thus can be used to develop intelligent synthetic biological systems for myriad applications.

Chemically Fueled Supramolecular Materials

In biology, the function of many molecules is regulated through nonequilibrium chemical reaction cycles. The prototypical example is the phosphorylation of an amino acid in an enzyme which induces a functional change, e.g., it folds or unfolds, assembles or disassembles, or binds a substrate. Such phosphorylation does not occur spontaneously but requires a phosphorylating agent with high chemical potential (for example, adenosine triphosphate (ATP)) to be converted into a molecule with lower chemical potential (adenosine diphosphate (ADP)). When this energy is used to regulate an assembly, we speak of chemically fueled assemblies; i.e., the molecule with high potential, the fuel, is used to regulate a self-assembly process. For example, the binding of guanosine triphosphate (GTP) to tubulin induces self-assembly. The bound GTP is hydrolyzed to guanosine diphosphate (GDP) upon assembly, which induces tubulin disassembly. The result is a dynamic assembly endowed with unique characteristics, such as time-dependent behavior and the ability to self-heal. These intriguing, unique properties have inspired supramolecular chemists to create similar chemically fueled molecular assemblies from the bottom up. While examples have been designed, they remain scarce partly because chemically fueled reaction cycles are rare and often complex. Thus, we recently developed a carbodiimide-driven reaction cycle that is versatile and easy to use, quantitatively understood, and does not suffer from side reactions. In the reaction cycle, a carboxylate precursor reacts with a carbodiimide to form an activated species like an anhydride or ester. The activated state reacts with water and thereby reverts to its precursor state; i.e., the activated state is deactivated. Effectively, the precursor catalyzes carbodiimides' conversion into waste and forms a transient activated state. We designed building blocks to regulate a range of assemblies and supramolecular materials at the expense of carbodiimide fuel. The simplicity and versatility of the reaction cycles have democratized and popularized the field of chemically fueled assemblies. In this Account, we describe what we have "learned" on our way. We introduce the field exemplified by biological nonequilibrium self-assembly. We describe the design of the carbodiimide-driven reaction cycle. Using examples from our group and others, we offer design rules for the building block's structure and strategies to create the desired morphology or supramolecular materials. The discussed morphologies include fibers, colloids, crystals, and oil- and coacervate-based droplets. We then demonstrate how these assemblies form supramolecular materials with unique material properties like the ability to self-heal. Besides, we discuss the concept of reciprocal coupling in which the assembly exerts feedback on its reaction cycle and we also offer examples of such feedback mechanisms. Finally, we close the Account with a discussion and an outlook on this field. This Account aims to provide our fundamental understanding and facilitate further progress toward conceptually new supramolecular materials.

A combined experimental-computational approach uncovers a role for the Golgi matrix protein Giantin in breast cancer progression

Our understanding of how speed and persistence of cell migration affects the growth rate and size of tumors remains incomplete. To address this, we developed a mathematical model wherein cells migrate in two-dimensional space, divide, die or intravasate into the vasculature. Exploring a wide range of speed and persistence combinations, we find that tumor growth positively correlates with increasing speed and higher persistence. As a biologically relevant example, we focused on Golgi fragmentation, a phenomenon often linked to alterations of cell migration. Golgi fragmentation was induced by depletion of Giantin, a Golgi matrix protein, the downregulation of which correlates with poor patient survival. Applying the experimentally obtained migration and invasion traits of Giantin depleted breast cancer cells to our mathematical model, we predict that loss of Giantin increases the number of intravasating cells. This prediction was validated, by showing that circulating tumor cells express significantly less Giantin than primary tumor cells. Altogether, our computational model identifies cell migration traits that regulate tumor progression and uncovers a role of Giantin in breast cancer progression.

Epigenetic inheritance of gene silencing is maintained by a self-tuning mechanism based on resource competition

Biological systems can maintain memories over long timescales, with examples including memories in the brain and immune system. It is unknown how functional properties of memory systems, such as memory persistence, can be established by biological circuits. To address this question, we focus on transgenerational epigenetic inheritance in Caenorhabditis elegans. In response to a trigger, worms silence a target gene for multiple generations, resisting strong dilution due to growth and reproduction. Silencing may also be maintained indefinitely upon selection according to silencing levels. We show that these properties imply the fine-tuning of biochemical rates in which the silencing system is positioned near the transition to bistability. We demonstrate that this behavior is consistent with a generic mechanism based on competition for synthesis resources, which leads to self-organization around a critical state with broad silencing timescales. The theory makes distinct predictions and offers insights into the design principles of long-term memory systems.

Cattle Cloning by Somatic Cell Nuclear Transfer

Cloning by somatic cell Nuclear Transfer (SCNT) is a powerful technology capable of reprograming terminally differentiated cells to totipotency for generating whole animals or pluripotent stem cells for use in cell therapy, drug screening, and other biotechnological applications. However, the broad usage of SCNT remains limited due to its high cost and low efficiency in obtaining live and healthy offspring. In this chapter, we first briefly discuss the epigenetic constraints responsible for the low efficiency of SCNT and current attempts to overcome them. We then describe our bovine SCNT protocol for delivering live cloned calves and addressing basic questions about nuclear reprogramming. Other research groups can benefit from our basic protocol and build up on it to improve SCNT in the future. Strategies to correct or mitigate epigenetic errors (e.g., correcting imprinting loci, overexpression of demethylases, chromatin-modifying drugs) can integrate the protocol described here.

Emerging Approaches to DNA Data Storage: Challenges and Prospects

With the total amount of worldwide data skyrocketing, the global data storage demand is predicted to grow to 1.75 × 10¹⁴ GB by 2025. Traditional storage methods have difficulties keeping pace given that current storage media have a maximum density of 10³ GB/mm³. As such, data production will far exceed the capacity of currently available storage methods. The costs of maintaining and transferring data, as well as the limited lifespans and significant data losses associated with current technologies also demand advanced solutions for information storage. Nature offers a powerful alternative through the storage of information that defines living organisms in unique orders of four bases (A, T, C, G) located in molecules called deoxyribonucleic acid (DNA). DNA molecules as information carriers have many advantages over traditional storage media. Their high storage density, potentially low maintenance cost, ease of synthesis, and chemical modification make them an ideal alternative for information storage. To this end, rapid progress has been made over the past decade by exploiting user-defined DNA materials to encode information. In this review, we discuss the most recent advances of DNA-based data storage with a major focus on the challenges that remain in this promising field, including the current intrinsic low speed in data writing and reading and the high cost per byte stored. Alternatively, data storage relying on DNA nanostructures (as opposed to DNA sequence) as well as on other combinations of nanomaterials and biomolecules are proposed with promising technological and economic advantages. In summarizing the advances that have been made and underlining the challenges that remain, we provide a roadmap for the ongoing research in this rapidly growing field, which will enable the development of technological solutions to the global demand for superior storage methodologies.

Discussing the final size and shape of the reconstructed tissues in tissue engineering

Tissue engineering (TE) has made a revolution in repairing, replacing, or regenerating tissues or organs, but it has still a long way ahead. The mechanical properties along with suitable physicochemical and biological characteristics are the initial criteria for scaffolds in TE that should be fulfilled. This research will provide another point of view toward TE challenges concerning the morphological and geometrical aspects of the reconstructed tissue and which parameters may affect it. Based on our survey, there is a high possibility that the final reconstructed tissue may be different in size and shape compared to the original design scaffold. Thereby, the 3D-printed scaffold might not guarantee an accurate tissue reconstruction. The main justification for this is the unpredicted behavior of cells, specifically in the outer layer of the scaffold. It can also be a concern when the scaffold is implanted while cell migration cannot be controlled through the in vivo signaling pathways, which might cause cancer challenges. To sum up, it is concluded that more studies are necessary to focus on the size and geometry of the final reconstructed tissue.

Identification of a polycomb responsive region in human HoxA cluster and its long-range interaction with polycomb enriched genomic regions

Polycomb and Trithorax group proteins (PcG, TrxG) epigenetically regulate developmental genes. These proteins bind with specific DNA elements, the Polycomb Response Element (PRE). Apart from mutations in polycomb/ trithorax proteins, altered cis-elements like PRE underlie the modified function and thus disease etiology. PREs are well studied in Drosophila, while only a few human PREs have been reported. We have identified a polycomb responsive DNA element, hPRE-HoxA3, in the intron of the HoxA3 gene. The hPRE-HoxA3 represses luciferase reporter activity in a PcG-dependent manner. The endogenous hPRE-HoxA3 element recruits PcG proteins and is enriched with repressive H3K27me3 marks, demonstrating that hPRE-HoxA3 is a part of the PcG-dependent gene regulatory network. Furthermore, it interacts with D11-12, the well-known PRE in the human Hox cluster. hPRE-Hox3 is a part of the 3-dimensional chromosomal domain organization as it is involved in the long-range interaction with other PcG enriched regions of Hox A, B, C, and D clusters.

Scalable biological signal recording in mammalian cells using Cas12a base editors

Biological signal recording enables the study of molecular inputs experienced throughout cellular history. However, current methods are limited in their ability to scale up beyond a single signal in mammalian contexts. Here, we develop an approach using a hyper-efficient dCas12a base editor for multi-signal parallel recording in human cells. We link signals of interest to expression of guide RNAs to catalyze specific nucleotide conversions as a permanent record, enabled by Cas12's guide-processing abilities. We show this approach is plug-and-play with diverse biologically relevant inputs and extend it for more sophisticated applications, including recording of time-delimited events and history of chimeric antigen receptor T cells' antigen exposure. We also demonstrate efficient recording of up to four signals in parallel on an endogenous safe-harbor locus. This work provides a versatile platform for scalable recording of signals of interest for a variety of biological applications.

Memory, switches, and an OR-port through bistability in chemically fueled crystals

The ability to store information in chemical reaction networks is essential for the complex behavior we associate with life. In biology, cellular memory is regulated through transcriptional states that are bistable, i.e., a state that can either be on or off and can be flipped from one to another through a transient signal. Such memory circuits have been realized synthetically through the rewiring of genetic systems in vivo or through the rational design of reaction networks based on DNA and highly evolved enzymes in vitro. Completely bottom-up analogs based on small molecules are rare and hard to design and thus represent a challenge for systems chemistry. In this work, we show that bistability can be designed from a simple non-equilibrium reaction cycle that is coupled to crystallization. The crystals exert the necessary feedback on the reaction cycle required for the bistability resulting in an on-state with assemblies and an off-state without. Each state represents volatile memory that can be stored in continuously stirred tank reactors indefinitely even though molecules are turned over on a minute-timescale. We showcase the system’s abilities by creating a matrix display that can store images and by creating an OR-gate by coupling several switches together.

In biology, information is stored and processed using highly evolved molecules in bistable states. Here, the authors demonstrate bistability in a synthetic system without the need for evolved biomolecules or autocatalytic networks.

Virtual Parts Repository 2: Model-Driven Design of Genetic Regulatory Circuits

Engineering genetic regulatory circuits is key to the creation of biological applications that are responsive to environmental changes. Computational models can assist in understanding especially large and complex circuits for which manual analysis is infeasible, permitting a model-driven design process. However, there are still few tools that offer the ability to simulate the system under design. One of the reasons for this is the lack of accessible model repositories or libraries that cater to the modular composition of models of synthetic systems. Here, we present the second version of the Virtual Parts Repository, a framework to facilitate the model-driven design of genetic regulatory circuits, which provides reusable, modular, and composable models. The new framework is service-oriented, easier to use in computational workflows, and provides several new features and access methods. New features include supporting hierarchical designs via a graph-based repository or compatible remote repositories, enriching existing designs, and using designs provided in Synthetic Biology Open Language documents to derive system-scale and hierarchical Systems Biology Markup Language models. We also present a reaction-based modeling abstraction inspired by rule-based modeling techniques to facilitate scalable and modular modeling of complex and large designs. This modeling abstraction enhances the modeling capability of the framework, for example, to incorporate design patterns such as roadblocking, distributed deployment of genetic circuits using plasmids, and cellular resource dependency. The framework and the modeling abstraction presented in this paper allow computational design tools to take advantage of computational simulations and ultimately help facilitate more predictable applications.

Using a new HSPC senescence model in vitro to explore the mechanism of cellular memory in aging HSPCs

BACKGROUND

Age-associated changes attenuate human blood system functionality through the aging of hematopoietic stem and progenitor cells (HSPCs), manifested in human populations an increase in myeloproliferative disease and even leukemia; therefore, study on HSPC senescence bears great significance to treat hematopoietic-associated disease. Furthermore, the mechanism of HSPC aging is lacking, especially the cellular memory mechanism. Here, we not only reported a new HSPC senescence model in vitro, but also propose and verify the cellular memory mechanism of HSPC aging of the Polycomb/Trithorax system.

METHODS

HSPCs (Lin^-c-kit⁺ cells) were isolated and purified by magnetic cell sorting (MACS). The proportions and cell cycle distribution of cells were determined by flow cytometry; senescence-related β-galactosidase assay, transmission electron microscope (TEM), and colony-forming unit (CFU)-mix assay were detected for identification of the old HSPC model. Proteomic tests and RNA-seq were applied to analyze differential pathways and genes in the model cells. qPCR, Western blot (WB), and chromatin immunoprecipitation PCR (CHIP-PCR) were used to detect the gene expression of cell memory-related proteins. Knockdown of cell memory-related key genes was performed with shRNA interference.

RESULTS

In the model old HSPCs, β-gal activity, cell cycle, colony-forming ability, aging-related cell morphology, and metabolic pathway were significantly changed compared to the young HSPCs. Furthermore, we found the model HSPCs have more obvious aging manifestations than those of natural mice, and IL3 is the major factor contributing to HSPC aging in the model. We also observed dramatic changes in the expression level of PRC/TrxG complexes. After further exploring the downstream molecules of PRC/TrxG complexes, we found that Uhrf1 and TopII played critical roles in HSPC aging based on the HSPC senescence model.

CONCLUSIONS

These findings proposed a new HSPC senescence model in vitro which we forecasted could be used to preliminary screen the drugs of the HSPC aging-related hemopathy and suggested cellular memory mechanism of HSPC aging.

Enhanced regulation of prokaryotic gene expression by a eukaryotic transcriptional activator

Expanding the genetic toolbox for prokaryotic synthetic biology is a promising strategy for enhancing the dynamic range of gene expression and enabling new engineered applications for research and biomedicine. Here, we reverse the current trend of moving genetic parts from prokaryotes to eukaryotes and demonstrate that the activating eukaryotic transcription factor QF and its corresponding DNA-binding sequence can be moved to E. coli to introduce transcriptional activation, in addition to tight off states. We further demonstrate that the QF transcription factor can be used in genetic devices that respond to low input levels with robust and sustained output signals. Collectively, we show that eukaryotic gene regulator elements are functional in prokaryotes and establish a versatile and broadly applicable approach for constructing genetic circuits with complex functions. These genetic tools hold the potential to improve biotechnology applications for medical science and research.

Expanded toolkits for prokaryotic synthetic biology can enhance the dynamic range of gene expression. Here the authors move the eukaryotic transcription factor QF into E. coli and integrate it into genetic devices.

Assessing the activation/inhibition of tyrosine kinase-related pathways with a newly developed platform

The phosphorylation of cellular proteins plays a crucial role in the transduction of various signals from outside the cell into the nucleus. The signals are transduced by phosphorylation chain reactions within multiple pathways; however, determining which pathways are responsible for each defined signal has proven challenging. To estimate the activity of each pathway, we developed a phosphorylation array platform comprising a protein array with 1200 proteins belonging to 376 signalling pathways and an analytical method to estimate pathway activity based on the phosphorylation levels of proteins. The performance of our system was assessed by reconstructing kinase-substrate relationships, as well as by estimating pathway activity upon epidermal growth factor (EGF) stimulation and the pharmacological inhibition of epidermal growth factor receptor (EGFR). As a result, kinase-substrate relationships were reliably reconstructed based on the precise measurement of phosphorylation levels of constituent proteins on the array. Furthermore, the pathway activities associated with EGF stimulation and EGFR inhibition were successfully traced through the related pathways from the outer membrane to the nucleus along a time course. Thus, our phosphorylation array system can effectively assess the activity of specific signalling pathways that are perturbed by extracellular stimuli, such as various drugs.

Quantifying persistence in the T-cell signaling network using an optically controllable antigen receptor

T cells discriminate between healthy and infected cells with remarkable sensitivity when mounting an immune response, which is hypothesized to depend on T cells combining stimuli from multiple antigen-presenting cell interactions into a more potent response. To quantify the capacity for T cells to accomplish this, we have developed an antigen receptor that is optically tunable within cell conjugates, providing control over the duration, and intensity of intracellular T-cell signaling. We observe limited persistence within the T-cell intracellular network on disruption of receptor input, with signals dissipating entirely in ~15 min, and directly show sustained proximal receptor signaling is required to maintain gene transcription. T cells thus primarily accumulate the outputs of gene expression rather than integrate discrete intracellular signals. Engineering optical control in a clinically relevant chimeric antigen receptor (CAR), we show that this limited signal persistence can be exploited to increase CAR-T cell activation threefold using pulsatile stimulation. Our results are likely to apply more generally to the signaling dynamics of other cellular networks.

Memorizing environmental signals through feedback and feedforward loops

Cells in diverse organisms can store the information of previous environmental conditions for long periods of time. This form of cellular memory adjusts the cell's responses to future challenges, providing fitness advantages in fluctuating environments. Many biological functions, including cellular memory, are mediated by specific recurring patterns of interactions among proteins and genes, known as 'network motifs.' In this review, we focus on three well-characterized network motifs - negative feedback loops, positive feedback loops, and feedforward loops, which underlie different types of cellular memories. We describe the latest studies identifying these motifs in various molecular processes and discuss how the topologies and dynamics of these motifs can enable memory encoding and storage.

Model-based robustness and bistability analysis for methylation-based, epigenetic memory systems

In recent years, epigenetic memory systems have been developed based on DNA methylation and positive feedback systems. Achieving a robust design for these systems is generally a challenging and multifactorial task. We developed and validated a novel mathematical model to describe methylation-based epigenetic memory systems that capture switching dynamics of methylation levels and methyltransferase amounts induced by different inputs. A bifurcation analysis shows that the system operates in the bistable range, but in its current setup is not robust to changes in parameters. An expansion of the model captures heterogeneity of cell populations by accounting for distributed cell division rates. Simulations predict that the system is highly sensitive to variations in temperature, which affects cell division and the efficiency of the zinc finger repressor. A moderate decrease in temperature leads to a highly heterogeneous response to input signals and bistability on a single-cell level. The predictions of our model were confirmed by flow cytometry experiments conducted in this study. Overall, the results of our study give insights into the functional mechanisms of methylation-based memory systems and demonstrate that the switching dynamics can be highly sensitive to experimental conditions.

Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration

Nervous systems' computational abilities are an evolutionary innovation, specializing and speed-optimizing ancient biophysical dynamics. Bioelectric signalling originated in cells' communication with the outside world and with each other, enabling cooperation towards adaptive construction and repair of multicellular bodies. Here, we review the emerging field of developmental bioelectricity, which links the field of basal cognition to state-of-the-art questions in regenerative medicine, synthetic bioengineering and even artificial intelligence. One of the predictions of this view is that regeneration and regulative development can restore correct large-scale anatomies from diverse starting states because, like the brain, they exploit bioelectric encoding of distributed goal states-in this case, pattern memories. We propose a new interpretation of recent stochastic regenerative phenotypes in planaria, by appealing to computational models of memory representation and processing in the brain. Moreover, we discuss novel findings showing that bioelectric changes induced in planaria can be stored in tissue for over a week, thus revealing that somatic bioelectric circuits in vivo can implement a long-term, re-writable memory medium. A consideration of the mechanisms, evolution and functionality of basal cognition makes novel predictions and provides an integrative perspective on the evolution, physiology and biomedicine of information processing in vivo. This article is part of the theme issue 'Basal cognition: multicellularity, neurons and the cognitive lens'.

Cell memory of epithelial-mesenchymal plasticity in cancer

Fundamental biological processes of cell identity and cell fate determination are controlled by complex regulatory networks. These processes require molecular mechanisms that confer cellular phenotypic memory and state persistence. In this minireview, we will summarize mechanisms of cell memory based on regulatory hysteretic feedback loops and explore epigenetic mechanisms widely represented in nature, with special focus on epithelial-to-mesenchymal plasticity. We will also discuss the functional consequences of cell memory and epithelial-to-mesenchymal plasticity dynamics during development and cancer metastasis.

Hematopoietic stem cell (HSC) divisional memory: The journey of mitochondrial metabolism through HSC division

Hematopoietic stem cells (HSCs) are characterized by their ability to produce all cells of the blood and immune system and have been used for transplantation for decades. Although the regenerative potential of HSCs is high, their self-renewal potential is limited. HSC functions are inversely correlated with their divisional history. Recent advances in our understanding of the regulation of HSCs through cell division suggest that HSCs may never replicate into identical self, but rather replicate into progeny that gradually lose functionality at each round of division. HSC division is accompanied by major transcriptional and metabolic changes. In this perspective, the possibility that mitochondrial metabolism confers HSC division memory and programs HSCs for extinction is discussed.

A mechanistic model of the BLADE platform predicts performance characteristics of 256 different synthetic DNA recombination circuits

Boolean logic and arithmetic through DNA excision (BLADE) is a recently developed platform for implementing inducible and logical control over gene expression in mammalian cells, which has the potential to revolutionise cell engineering for therapeutic applications. This 2-input 2-output platform can implement 256 different logical circuits that exploit the specificity and stability of DNA recombination. Here, we develop the first mechanistic mathematical model of the 2-input BLADE platform based on Cre- and Flp-mediated DNA excision. After calibrating the model on experimental data from two circuits, we demonstrate close agreement between model outputs and data on the other 111 circuits that have so far been experimentally constructed using the 2-input BLADE platform. Model simulations of the remaining 143 circuits that have yet to be tested experimentally predict excellent performance of the 2-input BLADE platform across the range of possible circuits. Circuits from both the tested and untested subsets that perform less well consist of a disproportionally high number of STOP sequences. Model predictions suggested that circuit performance declines with a decrease in recombinase expression and new experimental data was generated that confirms this relationship.

Clusters of cooperative ion channels enable a membrane-potential-based mechanism for short-term memory

Across biological systems, cooperativity between proteins enables fast actions, supra-linear responses, and long-lasting molecular switches. In the nervous system, however, the function of cooperative interactions between voltage-dependent ionic channels remains largely unknown. Based on mathematical modeling, we here demonstrate that clusters of strongly cooperative ion channels can plausibly form bistable conductances. Consequently, clusters are permanently switched on by neuronal spiking, switched off by strong hyperpolarization, and remain in their state for seconds after stimulation. The resulting short-term memory of the membrane potential allows to generate persistent firing when clusters of cooperative channels are present together with non-cooperative spike-generating conductances. Dynamic clamp experiments in rodent cortical neurons confirm that channel cooperativity can robustly induce graded persistent activity - a single-cell based, multistable mnemonic firing mode experimentally observed in several brain regions. We therefore propose that ion channel cooperativity constitutes an efficient cell-intrinsic implementation for short-term memories at the voltage level.

Organization at criticality enables processing of time-varying signals by receptor networks

How cells utilize surface receptors for chemoreception is a recurrent question spanning between physics and biology over the past few decades. However, the dynamical mechanism for processing time-varying signals is still unclear. Using dynamical systems formalism to describe criticality in non-equilibrium systems, we propose generic principle for temporal information processing through phase space trajectories using dynamic transient memory. In contrast to short-term memory, dynamic memory generated via "ghost" attractor enables signal integration depending on stimulus history and thereby uniquely promotes integrating and interpreting complex temporal growth factor signals. We argue that this is a generic feature of receptor networks, the first layer of the cell that senses the changing environment. Using the experimentally established epidermal growth factor sensing system, we propose how recycling could provide self-organized maintenance of the critical receptor concentration at the plasma membrane through a simple, fluctuation-sensing mechanism. Processing of non-stationary signals, a feature previously attributed only to neural networks, thus uniquely emerges for receptor networks organized at criticality.

Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation

BACKGROUND

Cellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network.

RESULTS

We find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory.

CONCLUSIONS

Our work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity when designing synthetic circuits with memory function.

Molecular digital data storage using DNA

Molecular data storage is an attractive alternative for dense and durable information storage, which is sorely needed to deal with the growing gap between information production and the ability to store data. DNA is a clear example of effective archival data storage in molecular form. In this Review, we provide an overview of the process, the state of the art in this area and challenges for mainstream adoption. We also survey the field of in vivo molecular memory systems that record and store information within the DNA of living cells, which, together with in vitro DNA data storage, lie at the growing intersection of computer systems and biotechnology.

Synthetic biology for improving cell fate decisions and tissue engineering outcomes

Synthetic biology is a relatively new field of science that combines aspects of biology and engineering to create novel tools for the construction of biological systems. Using tools within synthetic biology, stem cells can then be reprogrammed and differentiated into a specified cell type. Stem cells have already proven to be largely beneficial in many different therapies and have paved the way for tissue engineering and regenerative medicine. Although scientists have made great strides in tissue engineering, there still remain many questions to be answered in regard to regeneration. Presented here is an overview of synthetic biology, common tools built within synthetic biology, and the way these tools are being used in stem cells. Specifically, this review focuses on how synthetic biologists engineer genetic circuits to dynamically control gene expression while also introducing emerging topics such as genome engineering and synthetic transcription factors. The findings mentioned in this review show the diverse use of stem cells within synthetic biology and provide a foundation for future research in tissue engineering with the use of synthetic biology tools. Overall, the work done using synthetic biology in stem cells is in its early stages, however, this early work is leading to new approaches for repairing diseased and damaged tissues and organs, and further expanding the field of tissue engineering.

Hysteretic Genetic Circuit for Detection of Proteasomal Degradation in Mammalian Cells

Synthetic hysteretic mammalian gene circuits generating sustained cellular responses to transient perturbations provide important tools to investigate complex cellular behaviors and reprogram cells for a variety of applications, ranging from protein production to cell fate decisions. The design rules of synthetic gene circuits with controlled hysteretic behaviors, however, remain uncharacterized. To identify the criteria for achieving predictable control of hysteresis, we built a genetic circuit for detection of proteasomal degradation (Hys-Deg). The Hys-Deg circuit is based on a tetracycline-controlled transactivator (tTA) variant engineered to interface with the ubiquitin proteasome system (UPS). The tTA variant activates its own expression, generating a positive feedback loop that is triggered by expression of another tTA gene that is constitutively regulated. Guided by predictive modeling, we characterized the hysteretic response of the Hys-Deg circuit. We demonstrated that control of the hysteretic response is achieved by modulating the ratio of expression of constitutive to inducible tTA. We also showed that the system can be finely tuned through dosage of the inducer tetracycline to calibrate the circuit for detection of the desired levels of UPS activation. This study establishes the design rules for building a hysteretic genetic circuit with an autoregulatory feedback loop and provides a synthetic memory module that could be easily integrated into regulatory gene networks to study and engineer complex cellular behaviors.

Designing cell function: assembly of synthetic gene circuits for cell biology applications

Synthetic biology is the discipline of engineering application-driven biological functionalities that were not evolved by nature. Early breakthroughs of cell engineering, which were based on ectopic (over)expression of single sets of transgenes, have already had a revolutionary impact on the biotechnology industry, regenerative medicine and blood transfusion therapies. Now, we require larger-scale, rationally assembled genetic circuits engineered to programme and control various human cell functions with high spatiotemporal precision in order to solve more complex problems in applied life sciences, biomedicine and environmental sciences. This will open new possibilities for employing synthetic biology to advance personalized medicine by converting cells into living therapeutics to combat hitherto intractable diseases.

Diversity, versatility and complexity of bacterial gene regulation mechanisms: opportunities and drawbacks for applications in synthetic biology

Gene expression occurs in two essential steps: transcription and translation. In bacteria, the two processes are tightly coupled in time and space, and highly regulated. Tight regulation of gene expression is crucial. It limits wasteful consumption of resources and energy, prevents accumulation of potentially growth inhibiting reaction intermediates, and sustains the fitness and potential virulence of the organism in a fluctuating, competitive and frequently stressful environment. Since the onset of studies on regulation of enzyme synthesis, numerous distinct regulatory mechanisms modulating transcription and/or translation have been discovered. Mostly, various regulatory mechanisms operating at different levels in the flow of genetic information are used in combination to control and modulate the expression of a single gene or operon. Here, we provide an extensive overview of the very diverse and versatile bacterial gene regulatory mechanisms with major emphasis on their combined occurrence, intricate intertwinement and versatility. Furthermore, we discuss the potential of well-characterized basal expression and regulatory elements in synthetic biology applications, where they may ensure orthogonal, predictable and tunable expression of (heterologous) target genes and pathways, aiming at a minimal burden for the host.

Adaptation and memory in immune responses

Adaptation is the ability of cells, tissues and organisms to rapidly and reversibly modify their properties to maximize fitness in a changing environment. The activity of immune-system components unfolds in the remarkably heterogeneous milieus to which they are exposed in different tissues, during homeostasis or during various acute or chronic pathological states. Therefore, adaptation is essential for immune cells to tune their responses to a large variety of contexts and conditions. The adaptation of immune cells reflects the integration of multiple inputs acting simultaneously or in a temporal sequence, which eventually leads to transcriptional reprogramming and to various functional consequences, some of which extend beyond the duration of the stimulus. A range of adaptive responses have been observed in both adaptive immune cells and innate immune cells; these are referred to with terms such as 'plasticity', 'priming', 'training', 'exhaustion' and 'tolerance', among others, all of which can be useful for defining a certain immunological process or outcome but whose underlying molecular frameworks are often incompletely understood. Here we review and analyze mechanisms of adaptation and memory in immunity with the aim of providing basic concepts that rationalize the properties and molecular bases of these essential processes.

Mitochondria are a substrate of cellular memory

Cellular memory underlies cellular identity, and thus constitutes a unifying mechanism of genetic disposition, environmental influences, and cellular adaptation. Here, we demonstrate that enduring physicochemical changes of mitochondrial networks invoked by transient stress, a phenomenon we term 'mitoengrams', underlie the transgenerational persistence of epigenetically scripted cellular behavior. Using C2C12 myogenic stem-like cells, we show that stress memory elicited by transient, low-level arsenite exposure is stored within a self-renewing subpopulation of progeny cells in a mitochondrial-dependent fashion. Importantly, we demonstrate that erasure of mitoengrams by administration of mitochondria-targeted electron scavenger was sufficient to reset key epigenetic marks of cellular memory and redirect the identity of the mitoengram-harboring progeny cells to a non-stress-like state. Together, our findings indicate that mnemonic information emanating from mitochondria support the balance between the persistence and transience of cellular memory.

DNA-based memory devices for recording cellular events

Measuring biological data across time and space is critical for understanding complex biological processes and for various biosurveillance applications. However, such data are often inaccessible or difficult to directly obtain. Less invasive, more robust and higher-throughput biological recording tools are needed to profile cells and their environments. DNA-based cellular recording is an emerging and powerful framework for tracking intracellular and extracellular biological events over time across living cells and populations. Here, we review and assess DNA recorders that utilize CRISPR nucleases, integrases and base-editing strategies, as well as recombinase and polymerase-based methods. Quantitative characterization, modelling and evaluation of these DNA-recording modalities can guide their design and implementation for specific application areas.

Cellular checkpoint control using programmable sequential logic

Biological processes that require orderly progression, such as growth and differentiation, proceed via regulatory checkpoints where the cell waits for signals before continuing to the next state. Implementing such control would allow genetic engineers to divide complex tasks into stages. We present genetic circuits that encode sequential logic to instruct Escherichia coli to proceed through a linear or cyclical sequence of states. These are built with 11 set-reset latches, designed with repressor-based NOR gates, which can connect to each other and sensors. The performance of circuits with up to three latches and four sensors, including a gated D latch, closely match predictions made by using nonlinear dynamics. Checkpoint control is demonstrated by switching cells between multiple circuit states in response to external signals over days.

Emergent memory in cell signaling: Persistent adaptive dynamics in cascades can arise from the diversity of relaxation time-scales

The mitogen-activated protein kinase (MAPK) signaling cascade, an evolutionarily conserved motif present in all eukaryotic cells, is involved in coordinating crucial cellular functions. While the asymptotic dynamical behavior of the pathway stimulated by a time-invariant signal is relatively well-understood, we show using a computational model that it exhibits a rich repertoire of transient adaptive responses to changes in stimuli. When the signal is switched on, the response is characterized by long-lived modulations in frequency as well as amplitude. On withdrawing the stimulus, the activity decays over long timescales, exhibiting reverberations characterized by repeated spiking in the activated MAPK concentration. The long-term persistence of such post-stimulus activity suggests that the cascade retains memory of the signal for a significant duration following its removal. The molecular mechanism underlying the reverberatory activity is related to the existence of distinct relaxation rates for the different cascade components. This results in the imbalance of fluxes between different layers of the cascade, with the reuse of activated kinases as enzymes when they are released from sequestration in complexes. The persistent adaptive response, indicative of a cellular “short-term” memory, suggests that this ubiquitous signaling pathway plays an even more central role in information processing by eukaryotic cells.

Bottom-up approaches in synthetic biology and biomaterials for tissue engineering applications

Synthetic biologists use engineering principles to design and construct genetic circuits for programming cells with novel functions. A bottom-up approach is commonly used to design and construct genetic circuits by piecing together functional modules that are capable of reprogramming cells with novel behavior. While genetic circuits control cell operations through the tight regulation of gene expression, a diverse array of environmental factors within the extracellular space also has a significant impact on cell behavior. This extracellular space offers an addition route for synthetic biologists to apply their engineering principles to program cell-responsive modules within the extracellular space using biomaterials. In this review, we discuss how taking a bottom-up approach to build genetic circuits using DNA modules can be applied to biomaterials for controlling cell behavior from the extracellular milieu. We suggest that, by collectively controlling intrinsic and extrinsic signals in synthetic biology and biomaterials, tissue engineering outcomes can be improved.

Simulating lateral distraction osteogenesis

Distraction osteogenesis is an effective method for generating large amounts of bone in situ for treating pathologies such as large bone defects or skeletal malformations, for instance leg-length discrepancies. While an optimized distraction procedure might have the potential to reduce the rate of complications significantly, our knowledge of the underlying mechanobiological processes is still insufficient for systematic optimization of treatment parameters such as distraction rate or fixation stiffness. We present a novel numerical model of lateral distraction osteogenesis, based on a mechanically well-controlled in vivo experiment. This model extends an existing numerical model of callus healing with viscoplastic material properties for describing stress relaxation and stimuli history-dependent tissue differentiation, incorporating delay and memory effects. A reformulation of appositional growth based non-local biological stimuli in terms of spatial convolution as well as remeshing and solution-mapping procedures allow the model to cope with severe mesh distortions associated with large plastic deformations. With these enhancements, our model is capable of replicating the in vivo observations for lateral distraction osteogenesis in sheep using the same differentiation rules and the same set of parameters that successfully describes callus healing in sheep, indicating that tissue differentiation hypotheses originally developed for fracture healing scenarios might indeed be applicable to distraction as well. The response of the model to modified distraction parameters corresponds to existing studies, although the currently available data is insufficient for rigorous validation. As such, this study provides a first step towards developing models that can serve as tools for identifying both interesting research questions and, eventually, even optimizing clinical procedures once better data for calibration and validation becomes available.

Hematopoietic stem/progenitor cell senescence is associated with altered expression profiles of cellular memory-involved gene

To evaluate the contributions of cellular memory mechanisms to hematopoietic stem/progenitor cell (HSPC) senescence. HSPCs (Lin^-CD117⁺, hereafter referred to as HSPC) were separated from young (6-week-old) and aged (18-month-old) mice using Magnetic Activated Cell Sorting (MACS). Cell cycle distribution of HSPCs was determined using flow cytometry. The mixed colony forming unit (CFU-Mix) assay was used to study the HSPCs' ability to proliferate. The mRNA expression levels of cellular memory-implicated PCG family (enhancer of zeste homolog 2 (Ezh2), B lymphoma mo-MLV insertion region 1 (Bmi-1), embryonic ectoderm development (Eed), melanoma nuclear protein 18 (Mel18), Mph1/polyhomeotic-like protein 1 (Rae-28)) and Trithorax group (TrxG) family (mixed lineage leukemia (Mll), thioredoxin (Trx)) were determined by quantitative real-time PCR. We obtained highly purified populations of mouse HSPCs (Lin^-CD117⁺) (92.2 ± 4.5% CD117⁺). The percentage of HSPCs was significantly higher in older mice compared with younger control mice and the percentage of SA-β-galactosidase positive cells was significantly higher in HSPCs isolated from older mice (P<0.05). The percentage of HSPCs in G₀/G₁ was significantly higher in older mice compared with younger control mice (52.0 compared with 47.1%), indicating increased cell cycle arrest in senescent HSPCs. The amount of CFU-Mix was significantly decreased in aged group (13.8 compared with 40.0), indicating a diminished ability to proliferate in senescent HSPCs. Ezh1, Bmi-1, Eed, Rae-28 gene mRNA expression was significantly lower in HSPCs from older mice compared to younger controls, while Mel18 mRNA expression was significantly higher in HSPCs from older mice (P<0.05). The expression of genes associated with cellular memory is altered in senescent (Lin^- CD117⁺) HSPCs, which may affect the potential plasticity of aged hematopoietic stem cells (HSCs) and thereby contribute to senescence-associated disease processes.

A novel optogenetically tunable frequency modulating oscillator

Synthetic biology has enabled the creation of biological reconfigurable circuits, which perform multiple functions monopolizing a single biological machine; Such a system can switch between different behaviours in response to environmental cues. Previous work has demonstrated switchable dynamical behaviour employing reconfigurable logic gate genetic networks. Here we describe a computational framework for reconfigurable circuits in E.coli using combinations of logic gates, and also propose the biological implementation. The proposed system is an oscillator that can exhibit tunability of frequency and amplitude of oscillations. Further, the frequency of operation can be changed optogenetically. Insilico analysis revealed that two-component light systems, in response to light within a frequency range, can be used for modulating the frequency of the oscillator or stopping the oscillations altogether. Computational modelling reveals that mixing two colonies of E.coli oscillating at different frequencies generates spatial beat patterns. Further, we show that these oscillations more robustly respond to input perturbations compared to the base oscillator, to which the proposed oscillator is a modification. Compared to the base oscillator, the proposed system shows faster synchronization in a colony of cells for a larger region of the parameter space. Additionally, the proposed oscillator also exhibits lesser synchronization error in the transient period after input perturbations. This provides a strong basis for the construction of synthetic reconfigurable circuits in bacteria and other organisms, which can be scaled up to perform functions in the field of time dependent drug delivery with tunable dosages, and sets the stage for further development of circuits with synchronized population level behaviour.

Losing supramolecular orientational memory via self-organization of a misfolded secondary structure

Comparing the self-organization of two dendronized perylene bisimides reveals how structurally defective primary structure eliminates memory function via hierarchical self-organization.