Secreting and sensing the same molecule allows cells to achieve versatile social behaviors

Synthetic Forms Most Beautiful: Engineering Insights into Self-Organization

Reflecting on the diversity of the natural world, Darwin famously observed that "from so simple a beginning endless forms most beautiful and most wonderful have been, and are being evolved." However, the examples that we are able to observe in nature are a consequence of chance, constrained by selection, drift, and epistasis. Here we explore how the efforts of synthetic biology to build new living systems can expand our understanding of the fundamental design principles that allow life to self-organize biological form, from cellular to organismal levels. We suggest that the ability to impose a length or timescale onto a biological activity is an essential strategy for self-organization in evolved systems and a key design target that is now being realized synthetically at all scales. By learning to integrate these strategies together, we are poised to expand on evolution's success and realize a space of synthetic forms not only beautiful but with diverse applications and transformative potential.

A new flavor of synthetic yeast communities sees the light

No organism is an island: organisms of varying taxonomic complexity, including genetic variants of a single species, can coexist in particular niches, cooperating for survival while simultaneously competing for environmental resources. In recent years, synthetic biology strategies have witnessed a surge of efforts focused on creating artificial microbial communities to tackle pressing questions about the complexity of natural systems and the interactions that underpin them. These engineered ecosystems depend on the number and nature of their members, allowing complex cell communication designs to recreate and create diverse interactions of interest. Due to its experimental simplicity, the budding yeast Saccharomyces cerevisiae has been harnessed to establish a mixture of varied cell populations with the potential to explore synthetic ecology, metabolic bioprocessing, biosensing, and pattern formation. Indeed, engineered yeast communities enable advanced molecule detection dynamics and logic operations. Here, we present a concise overview of the state-of-the-art, highlighting examples that exploit optogenetics to manipulate, through light stimulation, key yeast phenotypes at the community level, with unprecedented spatial and temporal regulation. Hence, we envision a bright future where the application of optogenetic approaches in synthetic communities (optoecology) illuminates the intricate dynamics of complex ecosystems and drives innovations in metabolic engineering strategies.

Open problems in synthetic multicellularity

Multicellularity is one of the major evolutionary transitions, and its rise provided the ingredients for the emergence of a biosphere inhabited by complex organisms. Over the last decades, the potential for bioengineering multicellular systems has been instrumental in interrogating nature and exploring novel paths to regeneration, disease, cognition, and behaviour. Here, we provide a list of open problems that encapsulate many of the ongoing and future challenges in the field and suggest conceptual approaches that may facilitate progress.

Limiting the Broadcast Range of a Secreting Cell during Intercellular Signaling Using Protease-Mediated Degradation

Synthetic biology is revolutionizing our approaches to biocomputing, diagnostics, and environmental monitoring through the use of designed genetic circuits that perform a function within a single cell. More complex functions can be performed by multiple cells that coordinate as they perform different subtasks. Cell-cell communication using molecular signals is particularly suited for aiding in this communication, but the number of molecules that can be used in different communication channels is limited. Here we investigate how proteases can limit the broadcast range of communicating cells. We find that adding barrierpepsin to Saccharomyces cerevisiae cells in two-dimensional multicellular networks that use α-factor signaling prevents cells beyond a specific radius from responding to α-factor signals. Such limiting of the broadcast range of cells could allow multiple cells to use the same signaling molecules to direct different communication processes and functions, provided that they are far enough from one another. These results suggest a means by which complex synthetic cellular networks using only a few signals for communication could be created by structuring a community of cells to create distinct broadcast environments.

Immune quorum sensing dictates IFN-I response dynamics in human plasmacytoid dendritic cells

Type I interferons (IFN-Is) are key in fighting viral infections, but also serve major roles beyond antiviral immunity. Crucial is the tight regulation of IFN-I responses, while excessive levels are harmful to the cells. In essence, immune responses are generated by single cells making their own decisions, which are based on the signals they perceive. Additionally, immune cells must anticipate the future state of their environment, thereby weighing the costs and benefits of each possible outcome, in the presence of other potentially competitive decision makers (i.e., IFN-I producing cells). A rather new cellular communication mechanism called quorum sensing describes the effect of cell density on cellular secretory behaviors, which fits well with matching the right amount of IFN-Is produced to fight an infection. More competitive decision makers must contribute relatively less and vice versa. Intrigued by this concept, we assessed the effects of immune quorum sensing in pDCs, specialized immune cells known for their ability to mass produce IFN-Is. Using conventional microwell assays and droplet-based microfluidics assays, we were able the characterize the effect of quorum sensing in human primary immune cells in vitro. These insights open new avenues to manipulate IFN-I response dynamics in pathological conditions affected by aberrant IFN-I signaling.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

RsaL-driven negative regulation promotes heterogeneity in Pseudomonas aeruginosa quorum sensing

IMPORTANCE

Single-cell analyses can reveal that despite experiencing identical physico-chemical conditions, individual bacterial cells within a monoclonal population may exhibit variations in gene expression. Such phenotypic heterogeneity has been described for several aspects of bacterial physiology, including QS activation. This study demonstrates that the transition of non-quorate cells to the quorate state is a graded process that does not occur at a specific cell density and that subpopulations of non-quorate cells also persist at high cell density. Here, we provide a mechanistic explanation for this phenomenon, showing that a negative feedback regulatory loop integrated into the las system has a pivotal role in promoting cell-to-cell variation in the QS activation state and in limiting the transition of non-quorate cells to the quorate state in P. aeruginosa.

Dynamic altruistic cooperation within breast tumors

BACKGROUND

Social behaviors such as altruism, where one self-sacrifices for collective benefits, critically influence an organism's survival and responses to the environment. Such behaviors are widely exemplified in nature but have been underexplored in cancer cells which are conventionally seen as selfish competitive players. This multidisciplinary study explores altruism and its mechanism in breast cancer cells and its contribution to chemoresistance.

METHODS

MicroRNA profiling was performed on circulating tumor cells collected from the blood of treated breast cancer patients. Cancer cell lines ectopically expressing candidate miRNA were used in co-culture experiments and treated with docetaxel. Ecological parameters like relative survival and relative fitness were assessed using flow cytometry. Functional studies and characterization performed in vitro and in vivo include proliferation, iTRAQ-mass spectrometry, RNA sequencing, inhibition by small molecules and antibodies, siRNA knockdown, CRISPR/dCas9 inhibition and fluorescence imaging of promoter reporter-expressing cells. Mathematical modeling based on evolutionary game theory was performed to simulate spatial organization of cancer cells.

RESULTS

Opposing cancer processes underlie altruism: an oncogenic process involving secretion of IGFBP2 and CCL28 by the altruists to induce survival benefits in neighboring cells under taxane exposure, and a self-sacrificial tumor suppressive process impeding proliferation of altruists via cell cycle arrest. Both processes are regulated concurrently in the altruists by miR-125b, via differential NF-κB signaling specifically through IKKβ. Altruistic cells persist in the tumor despite their self-sacrifice, as they can regenerate epigenetically from non-altruists via a KLF2/PCAF-mediated mechanism. The altruists maintain a sparse spatial organization by inhibiting surrounding cells from adopting the altruistic fate via a lateral inhibition mechanism involving a GAB1-PI3K-AKT-miR-125b signaling circuit.

CONCLUSIONS

Our data reveal molecular mechanisms underlying manifestation, persistence and spatial spread of cancer cell altruism. A minor population behave altruistically at a cost to itself producing a collective benefit for the tumor, suggesting tumors to be dynamic social systems governed by the same rules of cooperation in social organisms. Understanding cancer cell altruism may lead to more holistic models of tumor evolution and drug response, as well as therapeutic paradigms that account for social interactions. Cancer cells constitute tractable experimental models for fields beyond oncology, like evolutionary ecology and game theory.

Global quantitative understanding of non-equilibrium cell fate decision-making in response to pheromone

Cell-cycle arrest and polarized growth are commonly used to characterize the response of yeast to pheromone. However, the quantitative decision-making processes underlying time-dependent changes in cell fate remain unclear. In this study, we conducted single-cell level experiments to observe multidimensional responses, uncovering diverse fates of yeast cells. Multiple states are revealed, along with the kinetic switching rates and pathways among them, giving rise to a quantitative landscape of mating response. To quantify the experimentally observed cell fates, we developed a theoretical framework based on non-equilibrium landscape and flux theory. Additionally, we performed stochastic simulations of biochemical reactions to elucidate signal transduction and cell growth. Notably, our experimental findings have provided the first global quantitative evidence of the real-time synchronization between intracellular signaling, physiological growth, and morphological functions. These results validate the proposed underlying mechanism governing the emergence of multiple cell fate states. This study introduces an emerging mechanistic approach to understand non-equilibrium cell fate decision-making in response to pheromone.

Quorum sensing going wild

The first discovered and well-characterized bacterial quorum sensing (QS) system belongs to Vibrio fischeri, which uses N-acyl homo-serine lactones (AHLs) for cell-cell signaling. AHL QS cell-cell communication is often regarded as a cell density-dependent regulatory switch. Since the discovery of QS, it has been known that AHL concentration (which correlates imperfectly with cell density) is not necessarily the only QS trigger. Additionally, not all cells respond to a QS signal. Bacteria could, via QS, exhibit phenotypic heterogeneity, resulting in sub-populations with unique phenotypes. It is time to ascribe greater importance to QS-dependent phenotypic heterogeneity, and its potential purpose in natura, with emphasis on the division of labor, specialization, and "bet-hedging". We hope that this perspective article will stimulate the awareness that QS can be more than just a cell-density switch. This basic mechanism could result in "bacterial civilizations", thus forcing us to reconsider the way bacterial communities are envisioned in natura.

Microbial models of development: Inspiration for engineering self-assembled synthetic multicellularity

While the field of synthetic developmental biology has traditionally focused on the study of the rich developmental processes seen in metazoan systems, an attractive alternate source of inspiration comes from microbial developmental models. Microbes face unique lifestyle challenges when forming emergent multicellular collectives. As a result, the solutions they employ can inspire the design of novel multicellular systems. In this review, we dissect the strategies employed in multicellular development by two model microbial systems: the cellular slime mold Dictyostelium discoideum and the biofilm-forming bacterium Bacillus subtilis. Both microbes face similar challenges but often have different solutions, both from metazoan systems and from each other, to create emergent multicellularity. These challenges include assembling and sustaining a critical mass of participating individuals to support development, regulating entry into development, and assigning cell fates. The mechanisms these microbial systems exploit to robustly coordinate development under a wide range of conditions offer inspiration for a new toolbox of solutions to the synthetic development community. Additionally, recreating these phenomena synthetically offers a pathway to understanding the key principles underlying how these behaviors are coordinated naturally.

Synergistic inter-clonal cooperation involving crosstalk, co-option and co-dependency can enhance the invasiveness of genetically distant cancer clones

BACKGROUND

Despite intensive research, cancer remains a major health problem. The difficulties in treating cancer reflect the complex nature of this disease, including high levels of heterogeneity within tumours. Intra-tumour heterogeneity creates the conditions for inter-clonal competition and selection, which could result in selective sweeps and a reduction in levels of heterogeneity. However, in addition to competing, cancer clones can also cooperate with each other, and the positive effects of these interactions on the fitness of clones could actually contribute to maintaining the heterogeneity of tumours. Consequently, understanding the evolutionary mechanisms and pathways involved in such activities is of great significance for cancer treatment. This is particularly relevant for metastasis (i.e., tumor cell migration, invasion, dispersal and dissemination), which is the most lethal phase during cancer progression. To explore if and how genetically distant clones can cooperate during migration and invasion, this study used three distinct cancer cell lines with different metastatic potentials.

RESULTS

We found that (i) the conditioned media from two invasive lines (breast and lung) increased the migration and invasion potential of a poorly metastatic line (breast), and (ii) this inter-clonal cooperative interaction involved the TGF-β1 signalling pathway. Furthermore, when the less aggressive line was co-cultured with the highly metastatic breast line, the invasive potential of both lines was enhanced, and this outcome was dependent on the co-option (through TGF-β1 autocrine-paracrine signalling) of the weakly metastatic clone into expressing an enhanced malignant phenotype that benefited both clones (i.e., a "help me help you" strategy).

CONCLUSIONS

Based on our findings, we propose a model in which crosstalk, co-option, and co-dependency can facilitate the evolution of synergistic cooperative interactions between genetically distant clones. Specifically, we suggest that synergistic cooperative interactions can easily emerge, regardless of the degree of overall genetic/genealogical relatedness, via crosstalk involving metastatic clones able to constitutively secrete molecules that induce and maintain their own malignant state (producer-responder clones) and clones that have the ability to respond to those signals (responder clones) and express a synergistic metastatic behaviour. Taking into account the lack of therapies that directly affect the metastatic process, interfering with such cooperative interactions during the early steps in the metastatic cascade could provide additional strategies to increase patient survival.

A circuit for secretion-coupled cellular autonomy in multicellular eukaryotic cells

Cancers represent complex autonomous systems, displaying self-sufficiency in growth signaling. Autonomous growth is fueled by a cancer cell's ability to "secrete-and-sense" growth factors (GFs): a poorly understood phenomenon. Using an integrated computational and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Giαβγ and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control, allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose-response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimulus-proportionate secretion. Proteomic studies and protein-protein interaction network analyses pinpoint GFs (e.g., the epidermal GF) as key stimuli for such self-sustenance. Findings highlight how the enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy of growth factors.

Characterizing the Impact of Communication on Cellular and Collective Behavior Using a Three-Dimensional Multiscale Cellular Model

Communication between cells enables the coordination that drives structural and functional complexity in biological systems. Both single and multicellular organisms have evolved diverse communication systems for a range of purposes, including synchronization of behavior, division of labor, and spatial organization. Synthetic systems are also increasingly being engineered to utilize cell-cell communication. While research has elucidated the form and function of cell-cell communication in many biological systems, our knowledge is still limited by the confounding effects of other biological phenomena at play and the bias of the evolutionary background. In this work, our goal is to push forward the context-free understanding of what impact cell-cell communication can have on cellular and population behavior to more fully understand the extent to which cell-cell communication systems can be utilized, modified, and engineered. We use an in silico model of 3D multiscale cellular populations, with dynamic intracellular networks interacting via diffusible signals. We focus on two key communication parameters: the effective interaction distance at which cells are able to interact and the receptor activation threshold. We found that cell-cell communication can be divided into six different forms along the parameter axes, three asocial and three social. We also show that cellular behavior, tissue composition, and tissue diversity are all highly sensitive to both the general form and specific parameters of communication even when the cellular network has not been biased towards that behavior.

Coupling Cell Communication and Optogenetics: Implementation of a Light-Inducible Intercellular System in Yeast

Cell communication is a widespread mechanism in biology, allowing the transmission of information about environmental conditions. In order to understand how cell communication modulates relevant biological processes such as survival, division, differentiation, and apoptosis, different synthetic systems based on chemical induction have been successfully developed. In this work, we coupled cell communication and optogenetics in the budding yeast Saccharomyces cerevisiae. Our approach is based on two strains connected by the light-dependent production of α-factor pheromone in one cell type, which induces gene expression in the other type. After the individual characterization of the different variants of both strains, the optogenetic intercellular system was evaluated by combining the cells under contrasting illumination conditions. Using luciferase as a reporter gene, specific co-cultures at a 1:1 ratio displayed activation of the response upon constant blue light, which was not observed for the same cell mixtures grown in darkness. Then, the system was assessed at several dark/blue-light transitions, where the response level varies depending on the moment in which illumination was delivered. Furthermore, we observed that the amplitude of response can be tuned by modifying the initial ratio between both strains. Finally, the two-population system showed higher fold inductions in comparison with autonomous strains. Altogether, these results demonstrated that external light information is propagated through a diffusible signaling molecule to modulate gene expression in a synthetic system involving microbial cells, which will pave the road for studies allowing optogenetic control of population-level dynamics.

Compensatory Genetic and Transcriptional Cytonuclear Coordination in Allopolyploid Lager Yeast (Saccharomyces pastorianus)

Cytonuclear coordination between biparental-nuclear genomes and uniparental-cytoplasmic organellar genomes in plants is often resolved by genetic and transcriptional cytonuclear responses. Whether this mechanism also acts in allopolyploid members of other kingdoms is not clear. Additionally, cytonuclear coordination of interleaved allopolyploid cells/individuals within the same population is underexplored. The yeast Saccharomyces pastorianus provides the opportunity to explore cytonuclear coevolution during different growth stages and from novel dimensions. Using S. pastorianus cells from multiple growth stages in the same environment, we show that nuclear mitochondria-targeted genes have undergone both asymmetric gene conversion and growth stage-specific biased expression favoring genes from the mitochondrial genome donor (Saccharomyces eubayanus). Our results suggest that cytonuclear coordination in allopolyploid lager yeast species entails an orchestrated and compensatory genetic and transcriptional evolutionary regulatory shift. The common as well as unique properties of cytonuclear coordination underlying allopolyploidy between unicellular yeasts and higher plants offers novel insights into mechanisms of cytonuclear evolution associated with allopolyploid speciation.

Microfluidic-Enabled Multi-Cell-Densities-Patterning and Culture Device for Characterization of Yeast Strains’ Growth Rates under Mating Pheromone

Yeast studies usually focus on exploring diversity in terms of a specific trait (such as growth rate, antibiotic resistance, or fertility) among extensive strains. Microfluidic chips improve these biological studies in a manner of high throughput and high efficiency. For a population study of yeast, it is of great significance to set a proper initial cell density for every strain under specific circumstances. Herein, we introduced a novel design of chip, which enables users to load cells in a gradient order (six alternatives) of initial cell density within one channel. We discussed several guidelines to choose the appropriate chamber to ensure successful data recording. With this chip, we successfully studied the growth rate of yeast strains under a mating response, which is crucial for yeasts to control growth behaviors for prosperous mating. We investigated the growth rate of eight different yeast strains under three different mating pheromone levels (0.3 μM, 1 μM, and 10 μM). Strains with, even, a six-fold in growth rate can be recorded, with the available data produced simultaneously. This work has provided an efficient and time-saving microfluidic platform, which enables loading cells in a pattern of multi-cell densities for a yeast population experiment, especially for a high-throughput study. Besides, a quantitatively analyzed growth rate of different yeast strains shall reveal inspiring perspectives for studies concerning yeast population behavior with a stimulated mating pheromone.

Modular, robust and extendible multicellular circuit design in yeast

Division of labor between cells is ubiquitous in biology but the use of multi-cellular consortia for engineering applications is only beginning to be explored. A significant advantage of multi-cellular circuits is their potential to be modular with respect to composition but this claim has not yet been extensively tested using experiments and quantitative modeling. Here, we construct a library of 24 yeast strains capable of sending, receiving or responding to three molecular signals, characterize them experimentally and build quantitative models of their input-output relationships. We then compose these strains into two- and three-strain cascades as well as a four-strain bistable switch and show that experimentally measured consortia dynamics can be predicted from the models of the constituent parts. To further explore the achievable range of behaviors, we perform a fully automated computational search over all two-, three- and four-strain consortia to identify combinations that realize target behaviors including logic gates, band-pass filters and time pulses. Strain combinations that are predicted to map onto a target behavior are further computationally optimized and then experimentally tested. Experiments closely track computational predictions. The high reliability of these model descriptions further strengthens the feasibility and highlights the potential for distributed computing in synthetic biology.

A novel biotechnology based on periphytic biofilms with N-acyl-homoserine-lactones stimulation and lanthanum loading for phosphorus recovery

This study presents an approach for developing periphytic biofilm with N-acyl-homoserine-lactones (AHLs) stimulation and lanthanum (La, a rare earth element) loading, to achieve highly efficient and stable phosphorus (P) recovery from wastewater. AHLs stimulated biofilm growth and formation, also improved stable P entrapment by enhancing extracellular polymeric substance (EPS) production and optimizing P-entrapment bacterial communities. Periphytic biofilms loading La is based on ligand exchanges, and La loading achieved initial rapid P entrapment by surface adsorption. The combination of AHLs stimulation and La loading achieved 99.0% P entrapment. Interestingly, the enhanced EPS production stimulated by AHLs protected biofilms against La. Moreover, a method for P and La separately recovery from biofilms was developed, achieving 89-96% of P and 88-93% of La recovery. This study offers a promising biotechnology to reuse La from La-rich wastewater and recover P by biofilm doped with La, which results in a win-win situation for resource sustainability.

Predictive landscapes hidden beneath biological cellular automata

To celebrate Hans Frauenfelder's achievements, we examine energy(-like) "landscapes" for complex living systems. Energy landscapes summarize all possible dynamics of some physical systems. Energy(-like) landscapes can explain some biomolecular processes, including gene expression and, as Frauenfelder showed, protein folding. But energy-like landscapes and existing frameworks like statistical mechanics seem impractical for describing many living systems. Difficulties stem from living systems being high dimensional, nonlinear, and governed by many, tightly coupled constituents that are noisy. The predominant modeling approach is devising differential equations that are tailored to each living system. This ad hoc approach faces the notorious "parameter problem": models have numerous nonlinear, mathematical functions with unknown parameter values, even for describing just a few intracellular processes. One cannot measure many intracellular parameters or can only measure them as snapshots in time. Another modeling approach uses cellular automata to represent living systems as discrete dynamical systems with binary variables. Quantitative (Hamiltonian-based) rules can dictate cellular automata (e.g., Cellular Potts Model). But numerous biological features, in current practice, are qualitatively described rather than quantitatively (e.g., gene is (highly) expressed or not (highly) expressed). Cellular automata governed by verbal rules are useful representations for living systems and can mitigate the parameter problem. However, they can yield complex dynamics that are difficult to understand because the automata-governing rules are not quantitative and much of the existing mathematical tools and theorems apply to continuous but not discrete dynamical systems. Recent studies found ways to overcome this challenge. These studies either discovered or suggest an existence of predictive "landscapes" whose shapes are described by Lyapunov functions and yield "equations of motion" for a "pseudo-particle." The pseudo-particle represents the entire cellular lattice and moves on the landscape, thereby giving a low-dimensional representation of the cellular automata dynamics. We outline this promising modeling strategy.

Nucleic acid-based molecular computation heads towards cellular applications

Nucleic acids, with the advantages of programmability and biocompatibility, have been widely used to design different kinds of novel biocomputing devices. Recently, nucleic acid-based molecular computing has shown promise in making the leap from the test tube to the cell. Such molecular computing can perform logic analysis within the confines of the cellular milieu with programmable modulation of biological functions at the molecular level. In this review, we summarize the development of nucleic acid-based biocomputing devices that are rationally designed and chemically synthesized, highlighting the ability of nucleic acid-based molecular computing to achieve cellular applications in sensing, imaging, biomedicine, and bioengineering. Then we discuss the future challenges and opportunities for cellular and in vivo applications. We expect this review to inspire innovative work on constructing nucleic acid-based biocomputing to achieve the goal of precisely rewiring, even reconstructing cellular signal networks in a prescribed way.

DNA-Based Artificial Signaling System Mimicking the Dimerization of Receptors for Signal Transduction and Amplification

Transmembrane signal transduction is of profound significance in many biological processes. The dimerization of cell-surface receptors is one prominent mechanism by which signals are transmitted across the membrane and trigger intracellular cascade amplification reactions. Recreating such processes in artificial systems has potential applications in sensing, drug delivery, bioengineering, and providing a new route for a deep understanding of fundamental biological processes. However, it remains a challenge to design artificial signal transduction systems working by the receptor dimerization mechanism in a predictable and smart manner. Here, benefitting from DNA with features of programmability, controllability, and flexible design, we use DNA as a building material to construct an artificial system mimicking dimerization of receptors for signal transduction and cascade amplification. DNA-based membrane-spanning receptor analogues are designed to recognize external signals, which drives two receptors into close spatial proximity to activate DNAzymes inside the cell-mimicking system. The activation of the DNAzyme initiates the catalyzed cleavage of encapsulated substrates and leads to the release of fluorescent second messengers for signal amplification. Such an artificial signal transduction system extends the range of biomimetic DNA-based signaling systems, providing a new avenue to study natural cell signaling processes and artificially regulate biological processes.

Diffusive wave dynamics beyond the continuum limit

Scientists have observed and studied diffusive waves in contexts as disparate as population genetics and cell signaling. Often, these waves are propagated by discrete entities or agents, such as individual cells in the case of cell signaling. For a broad class of diffusive waves, we characterize the transition between the collective propagation of diffusive waves, in which the wave speed is well described by continuum theory, and the propagation of diffusive waves by individual agents. We show that this transition depends heavily on the dimensionality of the system in which the wave propagates and that disordered systems yield dynamics largely consistent with lattice systems. In some system dimensionalities, the intuition that closely packed sources more accurately mimic a continuum can be grossly violated.

Quorum sensing governs collective dendritic cell activation in vivo

Dendritic cell (DC) activation by viral RNA sensors such as TLR3 and MDA-5 is critical for initiating antiviral immunity. Optimal DC activation is promoted by type I interferon (IFN) signaling which is believed to occur in either autocrine or paracrine fashion. Here, we show that neither autocrine nor paracrine type I IFN signaling can fully account for DC activation by poly(I:C) in vitro and in vivo. By controlling the density of type I IFN-producing cells in vivo, we establish that instead a quorum of type I IFN-producing cells is required for optimal DC activation and that this process proceeds at the level of an entire lymph node. This collective behavior, governed by type I IFN diffusion, is favored by the requirement for prolonged cytokine exposure to achieve DC activation. Furthermore, collective DC activation was found essential for the development of innate and adaptive immunity in lymph nodes. Our results establish how collective rather than cell-autonomous processes can govern the initiation of immune responses.

Collective metastasis: coordinating the multicellular voyage

The metastatic process is arduous. Cancer cells must escape the confines of the primary tumor, make their way into and travel through the circulation, then survive and proliferate in unfavorable microenvironments. A key question is how cancer cells overcome these multiple barriers to orchestrate distant organ colonization. Accumulating evidence in human patients and animal models supports the hypothesis that clusters of tumor cells can complete the entire metastatic journey in a process referred to as collective metastasis. Here we highlight recent studies unraveling how multicellular coordination, via both physical and biochemical coupling of cells, induces cooperative properties advantageous for the completion of metastasis. We discuss conceptual challenges and unique mechanisms arising from collective dissemination that are distinct from single cell-based metastasis. Finally, we consider how the dissection of molecular transitions regulating collective metastasis could offer potential insight into cancer therapy.

Context-aware synthetic biology by controller design: Engineering the mammalian cell

The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.

A Circuit for Secretion-coupled Cellular Autonomy in Multicellular Eukaryotes.. [DOI: 10.1101/2021.03.18.436048]

Cancers represent complex autonomous systems, displaying self-sufficiency in growth signaling. Autonomous growth is fueled by a cancer cell’s ability to ‘secrete-and-sense’ growth factors: a poorly understood phenomenon. Using an integrated systems and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Giαβγ and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control (CLC), allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimulus-proportionate secretion. Proteomic studies and protein-protein interaction network analyses pinpoint growth factors (e.g., the epidermal growth factor; EGF) as a key stimuli for such self-sustenance. Findings highlight how enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy of growth factors.

SYNOPSIS IMAGE

STANDFIRST TEXT

This work defines the inner workings of a Golgi-localized molecular circuitry comprised of coupled GTPases, which empowers cells to achieve self-sufficiency in growth factor signaling by creating a secrete-and-sense autocrine loop.

HIGHLIGHTS/MAIN FINDINGS

Modeling and experimental approaches were used to dissect a coupled GTPase circuit.

Coupling enables closed loop feedback and mutual control of GTPases.

Coupling generates dose response alignment behavior of sensing and secretion of growth factors.

Coupling is critical for multiscale feedback control to achieve secretion-coupled autonomy.

Robustness and timing of cellular differentiation through population-based symmetry breaking

During mammalian development and homeostasis, cells often transition from a multilineage primed state to one of several differentiated cell types that are marked by the expression of mutually exclusive genetic markers. These observations have been classically explained by single-cell multistability as the dynamical basis of differentiation, where robust cell-type proportioning relies on pre-existing cell-to-cell differences. We propose a conceptually different dynamical mechanism in which cell types emerge and are maintained collectively by cell-cell communication as a novel inhomogeneous state of the coupled system. Differentiation can be triggered by cell number increase as the population grows in size, through organisation of the initial homogeneous population before the symmetry-breaking bifurcation point. Robust proportioning and reliable recovery of the differentiated cell types following a perturbation is an inherent feature of the inhomogeneous state that is collectively maintained. This dynamical mechanism is valid for systems with steady-state or oscillatory single-cell dynamics. Therefore, our results suggest that timing and subsequent differentiation in robust cell-type proportions can emerge from the cooperative behaviour of growing cell populations during development.

Dynamics of diffusive cell signaling relays

In biological contexts as diverse as development, apoptosis, and synthetic microbial consortia, collections of cells or subcellular components have been shown to overcome the slow signaling speed of simple diffusion by utilizing diffusive relays, in which the presence of one type of diffusible signaling molecule triggers participation in the emission of the same type of molecule. This collective effect gives rise to fast-traveling diffusive waves. Here, in the context of cell signaling, we show that system dimensionality – the shape of the extracellular medium and the distribution of cells within it – can dramatically affect the wave dynamics, but that these dynamics are insensitive to details of cellular activation. As an example, we show that neutrophil swarming experiments exhibit dynamical signatures consistent with the proposed signaling motif. We further show that cell signaling relays generate much steeper concentration profiles than does simple diffusion, which may facilitate neutrophil chemotaxis.

Autonomous and Assisted Control for Synthetic Microbiology

The control of microbes and microbial consortia to achieve specific functions requires synthetic circuits that can reliably cope with internal and external perturbations. Circuits that naturally evolved to regulate biological functions are frequently robust to alterations in their parameters. As the complexity of synthetic circuits increases, synthetic biologists need to implement such robust control "by design". This is especially true for intercellular signaling circuits for synthetic consortia, where robustness is highly desirable, but its mechanisms remain unclear. Cybergenetics, the interface between synthetic biology and control theory, offers two approaches to this challenge: external (computer-aided) and internal (autonomous) control. Here, we review natural and synthetic microbial systems with robustness, and outline experimental approaches to implement such robust control in microbial consortia through population-level cybergenetics. We propose that harnessing natural intercellular circuit topologies with robust evolved functions can help to achieve similar robust control in synthetic intercellular circuits. A "hybrid biology" approach, where robust synthetic microbes interact with natural consortia and-additionally-with external computers, could become a useful tool for health and environmental applications.

Light-Activated Signaling in DNA-Encoded Sender-Receiver Architectures

Collective decision making by living cells is facilitated by exchange of diffusible signals where sender cells release a chemical signal that is interpreted by receiver cells. A variety of nonliving artificial cell models have been developed in recent years that mimic various aspects of diffusion-based intercellular communication. However, localized secretion of diffusive signals from individual protocells, which is critical for mimicking biological sender-receiver systems, has remained challenging to control precisely. Here, we engineer light-responsive, DNA-encoded sender-receiver architectures, where protein-polymer microcapsules act as cell mimics and molecular communication occurs through diffusive DNA signals. We prepare spatial distributions of sender and receiver protocells using a microfluidic trapping array and set up a signaling gradient from a single sender cell using light, which activates surrounding receivers through DNA strand displacement. Our systematic analysis reveals how the effective signal range of a single sender is determined by various factors including the density and permeability of receivers, extracellular signal degradation, signal consumption, and catalytic regeneration. In addition, we construct a three-population configuration where two sender cells are embedded in a dense array of receivers that implement Boolean logic and investigate spatial integration of nonidentical input cues. The results offer a means for studying diffusion-based sender-receiver topologies and present a strategy to achieve the congruence of reaction-diffusion and positional information in chemical communication systems that have the potential to reconstitute collective cellular patterns.

Interpretation of morphogen gradients by a synthetic bistable circuit

During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but isolating the role of this specific motif within a natural network remains a challenge. Here, we engineer a synthetic morphogen-induced mutual inhibition circuit in E. coli populations and show that mutual inhibition alone is sufficient to produce stable domains of gene expression in response to dynamic morphogen gradients, provided the spatial average of the morphogens falls within the region of bistability at the single cell level. When we add sender devices, the resulting patterning circuit produces theoretically predicted self-organised gene expression domains in response to a single gradient. We develop computational models of our synthetic circuits parameterised to timecourse fluorescence data, providing both a theoretical and experimental framework for engineering morphogen-induced spatial patterning in cell populations.

Morphogen gradients can be dynamic and transient yet give rise to stable cellular patterns. Here the authors show that a synthetic morphogen-induced mutual inhibition circuit produces stable boundaries when the spatial average of morphogens falls within the region of bistability.

Dormancy-to-death transition in yeast spores occurs due to gradual loss of gene-expressing ability

Dormancy is colloquially considered as extending lifespan by being still. Starved yeasts form dormant spores that wake-up (germinate) when nutrients reappear but cannot germinate (die) after some time. What sets their lifespans and how they age are open questions because what processes occur-and by how much-within each dormant spore remains unclear. With single-cell-level measurements, we discovered how dormant yeast spores age and die: spores have a quantifiable gene-expressing ability during dormancy that decreases over days to months until it vanishes, causing death. Specifically, each spore has a different probability of germinating that decreases because its ability to-without nutrients-express genes decreases, as revealed by a synthetic circuit that forces GFP expression during dormancy. Decreasing amounts of molecules required for gene expression-including RNA polymerases-decreases gene-expressing ability which then decreases chances of germinating. Spores gradually lose these molecules because they are produced too slowly compared with their degradations, causing gene-expressing ability to eventually vanish and, thus, death. Our work provides a systems-level view of dormancy-to-death transition.

Leveraging synthetic particles for communication: from passive to active systems

Communication is one of the most remarkable behaviors in the living world. It is an important prerequisite for building an artificial cell which can be considered as alive. Achieving complex communicative behaviors leveraging synthetic particles will likely fill the gap between artificial vesicles and natural counterpart of cells and allow for the discovery of new therapies in medicine. In this review, we highlight recent endeavors for constructing communication with synthetic particles by revealing the principles underlying the communicative behaviors. Emergent progress using active particles to achieve communication is also discussed, which resembles the dynamic and out-of-equilibrium properties of communication in nature.

Stochastic reaction networks in dynamic compartment populations

Many biochemical processes in living systems take place in compartmentalized environments, where individual compartments can interact with each other and undergo dynamic remodeling. Studying such processes through mathematical models poses formidable challenges because the underlying dynamics involve a large number of states, which evolve stochastically with time. Here we propose a mathematical framework to study stochastic biochemical networks in compartmentalized environments. We develop a generic population model, which tracks individual compartments and their molecular composition. We then show how the time evolution of this system can be studied effectively through a small number of differential equations, which track the statistics of the population. Our approach is versatile and renders an important class of biological systems computationally accessible.

Compartmentalization of biochemical processes underlies all biological systems, from the organelle to the tissue scale. Theoretical models to study the interplay between noisy reaction dynamics and compartmentalization are sparse, and typically very challenging to analyze computationally. Recent studies have made progress toward addressing this problem in the context of specific biological systems, but a general and sufficiently effective approach remains lacking. In this work, we propose a mathematical framework based on counting processes that allows us to study dynamic compartment populations with arbitrary interactions and internal biochemistry. We derive an efficient description of the dynamics in terms of differential equations which capture the statistics of the population. We demonstrate the relevance of our approach by analyzing models inspired by different biological processes, including subcellular compartmentalization and tissue homeostasis.

De novo design of an intercellular signaling toolbox for multi-channel cell-cell communication and biological computation

Intercellular signaling is indispensable for single cells to form complex biological structures, such as biofilms, tissues and organs. The genetic tools available for engineering intercellular signaling, however, are quite limited. Here we exploit the chemical diversity of biological small molecules to de novo design a genetic toolbox for high-performance, multi-channel cell-cell communications and biological computations. By biosynthetic pathway design for signal molecules, rational engineering of sensing promoters and directed evolution of sensing transcription factors, we obtain six cell-cell signaling channels in bacteria with orthogonality far exceeding the conventional quorum sensing systems and successfully transfer some of them into yeast and human cells. For demonstration, they are applied in cell consortia to generate bacterial colony-patterns using up to four signaling channels simultaneously and to implement distributed bio-computation containing seven different strains as basic units. This intercellular signaling toolbox paves the way for engineering complex multicellularity including artificial ecosystems and smart tissues.

Rosa26 docking sites for investigating genetic circuit silencing in stem cells

Approaches in mammalian synthetic biology have transformed how cells can be programmed to have reliable and predictable behavior, however, the majority of mammalian synthetic biology has been accomplished using immortalized cell lines that are easy to grow and easy to transfect. Genetic circuits that integrate into the genome of these immortalized cell lines remain functional for many generations, often for the lifetime of the cells, yet when genetic circuits are integrated into the genome of stem cells gene silencing is observed within a few generations. To investigate the reactivation of silenced genetic circuits in stem cells, the Rosa26 locus of mouse pluripotent stem cells was modified to contain docking sites for site-specific integration of genetic circuits. We show that the silencing of genetic circuits can be reversed with the addition of sodium butyrate, a histone deacetylase inhibitor. These findings demonstrate an approach to reactivate the function of genetic circuits in pluripotent stem cells to ensure robust function over many generations. Altogether, this work introduces an approach to overcome the silencing of genetic circuits in pluripotent stem cells that may enable the use of genetic circuits in pluripotent stem cells for long-term function.

Design of a MAPK signalling cascade balances energetic cost versus accuracy of information transmission

Cellular processes are inherently noisy, and the selection for accurate responses in presence of noise has likely shaped signalling networks. Here, we investigate the trade-off between accuracy of information transmission and its energetic cost for a mitogen-activated protein kinase (MAPK) signalling cascade. Our analysis of the pheromone response pathway of budding yeast suggests that dose-dependent induction of the negative transcriptional feedbacks in this network maximizes the information per unit energetic cost, rather than the information transmission capacity itself. We further demonstrate that futile cycling of MAPK phosphorylation and dephosphorylation has a measurable effect on growth fitness, with energy dissipation within the signalling cascade thus likely being subject to evolutionary selection. Considering optimization of accuracy versus the energetic cost of information processing, a concept well established in physics and engineering, may thus offer a general framework to understand the regulatory design of cellular signalling systems.

Cellular signalling networks provide information to the cell, but the trade-off between accuracy of information transfer and energetic cost of doing so has not been assessed. Here, the authors investigate a MAPK signalling cascade in budding yeast and find that information is maximised per unit energetic cost.

Regulated repression governs the cell fate promoter controlling yeast meiosis

Intrinsic signals and external cues from the environment drive cell fate decisions. In budding yeast, the decision to enter meiosis is controlled by nutrient and mating-type signals that regulate expression of the master transcription factor for meiotic entry, IME1. How nutrient signals control IME1 expression remains poorly understood. Here, we show that IME1 transcription is regulated by multiple sequence-specific transcription factors (TFs) that mediate association of Tup1-Cyc8 co-repressor to its promoter. We find that at least eight TFs bind the IME1 promoter when nutrients are ample. Remarkably, association of these TFs is highly regulated by different nutrient cues. Mutant cells lacking three TFs (Sok2/Phd1/Yap6) displayed reduced Tup1-Cyc8 association, increased IME1 expression, and earlier onset of meiosis. Our data demonstrate that the promoter of a master regulator is primed for rapid activation while repression by multiple TFs mediating Tup1-Cyc8 recruitment dictates the fate decision to enter meiosis.

Protein-coding changes preceded cis-regulatory gains in a newly evolved transcription circuit

Changes in both the coding sequence of transcriptional regulators and in the cis-regulatory sequences recognized by these regulators have been implicated in the evolution of transcriptional circuits. However, little is known about how they evolved in concert. We describe an evolutionary pathway in fungi where a new transcriptional circuit (a-specific gene repression by the homeodomain protein Matα2) evolved by coding changes in this ancient regulator, followed millions of years later by cis-regulatory sequence changes in the genes of its future regulon. By analyzing a group of species that has acquired the coding changes but not the cis-regulatory sites, we show that the coding changes became necessary for the regulator's deeply conserved function, thereby poising the regulator to jump-start formation of the new circuit.

A role for cell-autocrine interleukin-2 in regulatory T-cell homeostasis

Activated T-cells make both interleukin-2 (IL2) and its high-affinity receptor component CD25. Regulatory CD4 T-cells (Treg cells) do not make IL2, and the IL2-CD25 circuit is considered a paracrine circuit crucial in their generation and maintenance. Yet, all T-cells are capable of making IL2 at some stage during differentiation, making a cell-intrinsic autocrine circuit additionally possible. When we re-visited experiments with mixed bone marrow chimeras using a wide range of ratios of wild-type (WT) and IL2-/- genotype progenitors, we found that, as expected, thymic Treg cells were almost equivalent between WT and IL2-/- genotypes at ratios with WT prominence. However, at WT-limiting ratios, the IL2-/- genotype showed lower thymic Treg frequencies, indicating a role for cell-intrinsic autocrine IL2 in thymic Treg generation under IL2-limiting conditions. Further, peripheral IL2-/- naive CD4 T-cells showed poor conversion to inducible Tregs (pTregs) both in vivo and in vitro, again indicating a significant role for cell-intrinsic autocrine IL2 in their generation. Peripherally, the IL2-/- genotype was less prominent at all WT:IL2-/- ratios among both thymic Tregs (tTregs) and pTregs, adoptively transferred IL2-/- Tregs showed poorer survival than WT Tregs did, and RNA-seq analysis of WT and IL2-/- Tregs showed interesting differences in the T-cell receptor and transforming growth factor-beta-bone morphogenetic protein-JNK pathways between them, suggesting a non-titrating role for cell-intrinsic autocrine IL2 in Treg programming. These data indicate that cell-intrinsic autocrine IL2 plays significant roles in Treg generation and maintenance.

eIF4E and Interactors from Unicellular Eukaryotes

eIF4E, the mRNA cap-binding protein, is well known as a general initiation factor allowing for mRNA-ribosome interaction and cap-dependent translation in eukaryotic cells. In this review we focus on eIF4E and its interactors in unicellular organisms such as yeasts and protozoan eukaryotes. In a first part, we describe eIF4Es from yeast species such as Saccharomyces cerevisiae, Candida albicans, and Schizosaccharomyces pombe. In the second part, we will address eIF4E and interactors from parasite unicellular species—trypanosomatids and marine microorganisms—dinoflagellates. We propose that different strategies have evolved during evolution to accommodate cap-dependent translation to differing requirements. These evolutive “adjustments” involve various forms of eIF4E that are not encountered in all microorganismic species. In yeasts, eIF4E interactors, particularly p20 and Eap1 are found exclusively in Saccharomycotina species such as S. cerevisiae and C. albicans. For protozoan parasites of the Trypanosomatidae family beside a unique cap4-structure located at the 5′UTR of all mRNAs, different eIF4Es and eIF4Gs are active depending on the life cycle stage of the parasite. Additionally, an eIF4E-interacting protein has been identified in Leishmania major which is important for switching from promastigote to amastigote stages. For dinoflagellates, little is known about the structure and function of the multiple and diverse eIF4Es that have been identified thanks to widespread sequencing in recent years.

Macrophages employ quorum licensing to regulate collective activation

Macrophage-initiated inflammation is tightly regulated to eliminate threats such as infections while suppressing harmful immune activation. However, individual cells’ signaling responses to pro-inflammatory cues are heterogeneous, with subpopulations emerging with high or low activation states. Here, we use single-cell tracking and dynamical modeling to develop and validate a revised model for lipopolysaccharide (LPS)-induced macrophage activation that invokes a mechanism we term quorum licensing. The results show that bimodal phenotypic partitioning of macrophages is primed during the resting state, dependent on cumulative history of cell density, predicted by extrinsic noise in transcription factor expression, and independent of canonical LPS-induced intercellular feedback in the tumor necrosis factor (TNF) response. Our analysis shows how this density-dependent coupling produces a nonlinear effect on collective TNF production. We speculate that by linking macrophage density to activation, this mechanism could amplify local responses to threats and prevent false alarms.

Macrophage activation is tightly regulated to maintain immune homeostasis, yet activation is also heterogeneous. Here, the authors show that macrophages coordinate activation by partitioning into two phenotypes that can nonlinearly amplify collective inflammatory cytokine production as a function of cell density.

Synthetic Biology for Terraformation Lessons from Mars, Earth, and the Microbiome

What is the potential for synthetic biology as a way of engineering, on a large scale, complex ecosystems? Can it be used to change endangered ecological communities and rescue them to prevent their collapse? What are the best strategies for such ecological engineering paths to succeed? Is it possible to create stable, diverse synthetic ecosystems capable of persisting in closed environments? Can synthetic communities be created to thrive on planets different from ours? These and other questions pervade major future developments within synthetic biology. The goal of engineering ecosystems is plagued with all kinds of technological, scientific and ethic problems. In this paper, we consider the requirements for terraformation, i.e., for changing a given environment to make it hospitable to some given class of life forms. Although the standard use of this term involved strategies for planetary terraformation, it has been recently suggested that this approach could be applied to a very different context: ecological communities within our own planet. As discussed here, this includes multiple scales, from the gut microbiome to the entire biosphere.

Cellular Dialogues: Cell-Cell Communication through Diffusible Molecules Yields Dynamic Spatial Patterns

Cells form spatial patterns by coordinating their gene expressions. How a group of mesoscopic numbers (hundreds to thousands) of cells, without pre-existing morphogen gradients and spatial organization, self-organizes spatial patterns remains poorly understood. Of particular importance are dynamic spatial patterns such as spiral waves that perpetually move and transmit information. We developed an open-source software for simulating a field of cells that communicate by secreting any number of molecules. With this software and a theory, we identified all possible "cellular dialogues"-ways of communicating with two diffusing molecules-that yield diverse dynamic spatial patterns. These patterns emerge despite widely varying responses of cells to the molecules, gene-expression noise, spatial arrangements, and cell movements. A three-stage, "order-fluctuate-settle" process forms dynamic spatial patterns: cells form long-lived whirlpools of wavelets that, following erratic dynamics, settle into a dynamic spatial pattern. Our work helps in identifying gene-regulatory networks that underlie dynamic pattern formations.

Interaction variability shapes succession of synthetic microbial ecosystems

Cellular interactions are a major driver for the assembly and functioning of microbial communities. Their strengths are shown to be highly variable in nature; however, it is unclear how such variations regulate community behaviors. Here we construct synthetic Lactococcus lactis consortia and mathematical models to elucidate the role of interaction variability in ecosystem succession and to further determine if casting variability into modeling empowers bottom-up predictions. For a consortium of bacteriocin-mediated cooperation and competition, we find increasing the variations of cooperation, from either altered labor partition or random sampling, drives the community into distinct structures. When the cooperation and competition are additionally modulated by pH, ecosystem succession becomes jointly controlled by the variations of both interactions and yields more diversified dynamics. Mathematical models incorporating variability successfully capture all of these experimental observations. Our study demonstrates interaction variability as a key regulator of community dynamics, providing insights into bottom-up predictions of microbial ecosystems.

Cellular interactions are a major driver of microbial communities and shown highly variable in strength. Here the authors construct synthetic consortia and mathematical models to elucidate the role of interaction variability in driving ecosystem succession.

Cytokine-mediated communication: a quantitative appraisal of immune complexity

Intercellular communication mediated by cytokines is the main mechanism by which cells of the immune system talk to each other. Many aspects of cytokine signalling in the immune system have been explored in great detail at the structural, biophysical, biochemical and cellular levels. However, a systematic understanding of the quantitative rules that govern cytokine-mediated cell-to-cell communication is still lacking. Here, we discuss recent efforts in the field of systems immunology to bring about a quantitative understanding of cytokine-mediated communication between leukocytes and to provide novel insights into the orchestration of immune responses and inflammation.