The unforeseen challenge: from genotype-to-phenotype in cell populations

Metabolic adaptation pilots the differentiation of human hematopoietic cells

A continuous supply of energy is an essential prerequisite for survival and represents the highest priority for the cell. We hypothesize that cell differentiation is a process of optimization of energy flow in a changing environment through phenotypic adaptation. The mechanistic basis of this hypothesis is provided by the established link between core energy metabolism and epigenetic covalent modifications of chromatin. This theory predicts that early metabolic perturbations impact subsequent differentiation. To test this, we induced transient metabolic perturbations in undifferentiated human hematopoietic cells using pharmacological inhibitors targeting key metabolic reactions. We recorded changes in chromatin structure and gene expression, as well as phenotypic alterations by single-cell ATAC and RNA sequencing, time-lapse microscopy, and flow cytometry. Our observations suggest that these metabolic perturbations are shortly followed by alterations in chromatin structure, leading to changes in gene expression. We also show that these transient fluctuations alter the differentiation potential of the cells.

Biodiversity and Constrained Information Dynamics in Ecosystems: A Framework for Living Systems

The increase in ecosystem biodiversity can be perceived as one of the universal processes converting energy into information across a wide range of living systems. This study delves into the dynamics of living systems, highlighting the distinction between ex post adaptation, typically associated with natural selection, and its proactive counterpart, ex ante adaptability. Through coalescence experiments using synthetic ecosystems, we (i) quantified ecosystem stability, (ii) identified correlations between some biodiversity indexes and the stability, (iii) proposed a mechanism for increasing biodiversity through moderate inter-ecosystem interactions, and (iv) inferred that the information carrier of ecosystems is species composition, or merged genomic information. Additionally, it was suggested that (v) changes in ecosystems are constrained to a low-dimensional state space, with three distinct alteration trajectories-fluctuations, rapid environmental responses, and long-term changes-converging into this state space in common. These findings suggest that daily fluctuations may predict broader ecosystem changes. Our experimental insights, coupled with an exploration of living systems' information dynamics from an ecosystem perspective, enhance our predictive capabilities for natural ecosystem behavior, providing a universal framework for understanding a broad spectrum of living systems.

Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells

Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene can trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, to date, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and contexts. Moreover, how the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear. Here we combine computational analysis of existing datasets with stochastic mathematical modeling and machine learning to uncover the widespread prevalence of transcriptional adaptation in mammalian systems and the diverse single-cell manifestations of minimal compensatory gene networks. Regulon gene expression analysis of a pooled single-cell genetic perturbation dataset recapitulates important model predictions. Our integrative approach uncovers several putative hits-genes demonstrating possible transcriptional adaptation-to follow up on experimentally, and provides a formal quantitative framework to test and refine models of transcriptional adaptation.

A biophysical perspective on the resilience of neuronal excitability across timescales

Neuronal membrane excitability must be resilient to perturbations that can take place over timescales from milliseconds to months (or even years in long-lived animals). A great deal of attention has been paid to classes of homeostatic mechanisms that contribute to long-term maintenance of neuronal excitability through processes that alter a key structural parameter: the number of ion channel proteins present at the neuronal membrane. However, less attention has been paid to the self-regulating 'automatic' mechanisms that contribute to neuronal resilience by virtue of the kinetic properties of ion channels themselves. Here, we propose that these two sets of mechanisms are complementary instantiations of feedback control, together enabling resilience on a wide range of temporal scales. We further point to several methodological and conceptual challenges entailed in studying these processes - both of which involve enmeshed feedback control loops - and consider the consequences of these mechanisms of resilience.

Single-cell transcriptional uncertainty landscape of cell differentiation

Background: Single-cell studies have demonstrated the presence of significant cell-to-cell heterogeneity in gene expression. Whether such heterogeneity is only a bystander or has a functional role in the cell differentiation process is still hotly debated. Methods: In this study, we quantified and followed single-cell transcriptional uncertainty - a measure of gene transcriptional stochasticity in single cells - in 10 cell differentiation systems of varying cell lineage progressions, from single to multi-branching trajectories, using the stochastic two-state gene transcription model. Results: By visualizing the transcriptional uncertainty as a landscape over a two-dimensional representation of the single-cell gene expression data, we observed universal features in the cell differentiation trajectories that include: (i) a peak in single-cell uncertainty during transition states, and in systems with bifurcating differentiation trajectories, each branching point represents a state of high transcriptional uncertainty; (ii) a positive correlation of transcriptional uncertainty with transcriptional burst size and frequency; (iii) an increase in RNA velocity preceding the increase in the cell transcriptional uncertainty. Conclusions: Our findings suggest a possible universal mechanism during the cell differentiation process, in which stem cells engage stochastic exploratory dynamics of gene expression at the start of the cell differentiation by increasing gene transcriptional bursts, and disengage such dynamics once cells have decided on a particular terminal cell identity. Notably, the peak of single-cell transcriptional uncertainty signifies the decision-making point in the cell differentiation process.

RNA-controlled nucleocytoplasmic shuttling of mRNA decay factors regulates mRNA synthesis and a novel mRNA decay pathway

mRNA level is controlled by factors that mediate both mRNA synthesis and decay, including the 5' to 3' exonuclease Xrn1. Here we show that nucleocytoplasmic shuttling of several yeast mRNA decay factors plays a key role in determining both mRNA synthesis and decay. Shuttling is regulated by RNA-controlled binding of the karyopherin Kap120 to two nuclear localization sequences (NLSs) in Xrn1, location of one of which is conserved from yeast to human. The decaying RNA binds and masks NLS1, establishing a link between mRNA decay and Xrn1 shuttling. Preventing Xrn1 import, either by deleting KAP120 or mutating the two Xrn1 NLSs, compromises transcription and, unexpectedly, also cytoplasmic decay, uncovering a cytoplasmic decay pathway that initiates in the nucleus. Most mRNAs are degraded by both pathways - the ratio between them represents a full spectrum. Importantly, Xrn1 shuttling is required for proper responses to environmental changes, e.g., fluctuating temperatures, involving proper changes in mRNA abundance and in cell proliferation rate.

Global genome decompaction leads to stochastic activation of gene expression as a first step toward fate commitment in human hematopoietic cells

When human cord blood-derived CD34+ cells are induced to differentiate, they undergo rapid and dynamic morphological and molecular transformations that are critical for fate commitment. In particular, the cells pass through a transitory phase known as "multilineage-primed" state. These cells are characterized by a mixed gene expression profile, different in each cell, with the coexpression of many genes characteristic for concurrent cell lineages. The aim of our study is to understand the mechanisms of the establishment and the exit from this transitory state. We investigated this issue using single-cell RNA sequencing and ATAC-seq. Two phases were detected. The first phase is a rapid and global chromatin decompaction that makes most of the gene promoters in the genome accessible for transcription. It results 24 h later in enhanced and pervasive transcription of the genome leading to the concomitant increase in the cell-to-cell variability of transcriptional profiles. The second phase is the exit from the multilineage-primed phase marked by a slow chromatin closure and a subsequent overall down-regulation of gene transcription. This process is selective and results in the emergence of coherent expression profiles corresponding to distinct cell subpopulations. The typical time scale of these events spans 48 to 72 h. These observations suggest that the nonspecificity of genome decompaction is the condition for the generation of a highly variable multilineage expression profile. The nonspecific phase is followed by specific regulatory actions that stabilize and maintain the activity of key genes, while the rest of the genome becomes repressed again by the chromatin recompaction. Thus, the initiation of differentiation is reminiscent of a constrained optimization process that associates the spontaneous generation of gene expression diversity to subsequent regulatory actions that maintain the activity of some genes, while the rest of the genome sinks back to the repressive closed chromatin state.

The genotype-phenotype distinction: from Mendelian genetics to 21st century biology

The Genotype-Phenotype (G-P) distinction was proposed in the context of Mendelian genetics, in the wake of late nineteenth century studies about heredity. In this paper, we provide a conceptual analysis that highlights that the G-P distinction was grounded on three pillars: observability, transmissibility, and causality. Originally, the genotype is the non-observable and transmissible cause of its observable and non-transmissible effect, the phenotype. We argue that the current developments of biology have called the validity of such pillars into question. First, molecular biology has unveiled the putative material substrate of the genotype (qua DNA), making it an observable object. Second, numerous findings on non-genetic heredity suggest that some phenotypic traits can be directly transmitted. Third, recent organicist approaches to biological phenomena have emphasized the reciprocal causality between parts of a biological system, which notably applies to the relation between genotypes and phenotypes. As a consequence, we submit that the G-P distinction has lost its general validity, although it can still apply to specific situations. This calls for forging new frameworks and concepts to better describe heredity and development.

Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms

The rich variety of biological forms and behaviours results from one evolutionary history on Earth, via frozen accidents and selection in specific environments. This ubiquitous baggage in natural, familiar model species obscures the plasticity and swarm intelligence of cellular collectives. Significant gaps exist in our understanding of the origin of anatomical novelty, of the relationship between genome and form, and of strategies for control of large-scale structure and function in regenerative medicine and bioengineering. Analysis of living forms that have never existed before is necessary to reveal deep design principles of life as it can be. We briefly review existing examples of chimaeras, cyborgs, hybrots and other beings along the spectrum containing evolved and designed systems. To drive experimental progress in multicellular synthetic morphology, we propose teleonomic (goal-seeking, problem-solving) behaviour in diverse problem spaces as a powerful invariant across possible beings regardless of composition or origin. Cybernetic perspectives on chimaeric morphogenesis erase artificial distinctions established by past limitations of technology and imagination. We suggest that a multi-scale competency architecture facilitates evolution of robust problem-solving, living machines. Creation and analysis of novel living forms will be an essential testbed for the emerging field of diverse intelligence, with numerous implications across regenerative medicine, robotics and ethics.

Cancer progression as a learning process

Drug resistance and metastasis—the major complications in cancer—both entail adaptation of cancer cells to stress, whether a drug or a lethal new environment. Intriguingly, these adaptive processes share similar features that cannot be explained by a pure Darwinian scheme, including dormancy, increased heterogeneity, and stress-induced plasticity. Here, we propose that learning theory offers a framework to explain these features and may shed light on these two intricate processes. In this framework, learning is performed at the single-cell level, by stress-driven exploratory trial-and-error. Such a process is not contingent on pre-existing pathways but on a random search for a state that diminishes the stress. We review underlying mechanisms that may support this search, and show by using a learning model that such exploratory learning is feasible in a high-dimensional system as the cell. At the population level, we view the tissue as a network of exploring agents that communicate, restraining cancer formation in health. In this view, disease results from the breakdown of homeostasis between cellular exploratory drive and tissue homeostasis.

Observation of universal ageing dynamics in antibiotic persistence

Stress responses allow cells to adapt to changes in external conditions by activating specific pathways¹. Here we investigate the dynamics of single cells that were subjected to acute stress that is too strong for a regulated response but not lethal. We show that when the growth of bacteria is arrested by acute transient exposure to strong inhibitors, the statistics of their regrowth dynamics can be predicted by a model for the cellular network that ignores most of the details of the underlying molecular interactions. We observed that the same stress, applied either abruptly or gradually, can lead to totally different recovery dynamics. By measuring the regrowth dynamics after stress exposure on thousands of cells, we show that the model can predict the outcome of antibiotic persistence measurements. Our results may account for the ubiquitous antibiotic persistence phenotype², as well as for the difficulty in attempts to link it to specific genes³. More generally, our approach suggests that two different cellular states can be observed under stress: a regulated state, which prepares cells for fast recovery, and a disrupted cellular state due to acute stress, with slow and heterogeneous recovery dynamics. The disrupted state may be described by general properties of large random networks rather than by specific pathway activation. Better understanding of the disrupted state could shed new light on the survival and evolution of cells under stress.

Reduction of a stochastic model of gene expression: Lagrangian dynamics gives access to basins of attraction as cell types and metastabilty

Differentiation is the process whereby a cell acquires a specific phenotype, by differential gene expression as a function of time. This is thought to result from the dynamical functioning of an underlying Gene Regulatory Network (GRN). The precise path from the stochastic GRN behavior to the resulting cell state is still an open question. In this work we propose to reduce a stochastic model of gene expression, where a cell is represented by a vector in a continuous space of gene expression, to a discrete coarse-grained model on a limited number of cell types. We develop analytical results and numerical tools to perform this reduction for a specific model characterizing the evolution of a cell by a system of piecewise deterministic Markov processes (PDMP). Solving a spectral problem, we find the explicit variational form of the rate function associated to a large deviations principle, for any number of genes. The resulting Lagrangian dynamics allows us to define a deterministic limit of which the basins of attraction can be identified to cellular types. In this context the quasipotential, describing the transitions between these basins in the weak noise limit, can be defined as the unique solution of an Hamilton-Jacobi equation under a particular constraint. We develop a numerical method for approximating the coarse-grained model parameters, and show its accuracy for a symmetric toggle-switch network. We deduce from the reduced model an approximation of the stationary distribution of the PDMP system, which appears as a Beta mixture. Altogether those results establish a rigorous frame for connecting GRN behavior to the resulting cellular behavior, including the calculation of the probability of jumps between cell types.

Baseline cell proliferation rates and response to UV differ in lymphoblastoid cell lines derived from healthy individuals of extreme constitution types

Differences in human phenotypes and susceptibility to complex diseases are an outcome of genetic and environmental interactions. This is evident in diseases that progress through a common set of intermediate patho-endophenotypes. Precision medicine aims to delineate molecular players for individualized and early interventions. Functional studies of lymphoblastoid cell line (LCL) model of phenotypically well-characterized healthy individuals can help deconvolute and validate these molecular mechanisms. In this study, LCLs are developed from eight healthy individuals belonging to three extreme constitution types, deep phenotyped on the basis of Ayurveda. LCLs were characterized by karyotyping and immunophenotyping. Growth characteristics and response to UV were studied in these LCLs. Significant differences in cell proliferation rates were observed between the contrasting groups such that one type (Kapha) proliferates significantly slower than the other two (Vata, Pitta). In response to UV, one of the fast growing groups (Vata) shows higher cell death but recovers its numbers due to an inherent higher rates of proliferation. This study reveals that baseline differences in cell proliferation could be a key to understanding the survivability of cells under UV stress. Variability in baseline cellular phenotypes not only explains the cellular basis of different constitution types but can also help set priors during the design of an individualized therapy with DNA damaging agents. This is the first study of its kind that shows variability of intermediate patho-phenotypes among healthy individuals with potential implications in precision medicine.

Noise and the molecular processes underlying cell fate decision-making

Cell fate decision-making events involve the interplay of many molecular processes, ranging from signal transduction to genetic regulation, as well as a set of molecular and physiological feedback loops. Each aspect offers a rich field of investigation in its own right, but to understand the whole process, even in simple terms, we need to consider them together. Here we attempt to characterise this process by focussing on the roles of noise during cell fate decisions. We use a range of recent results to develop a view of the sequence of events by which a cell progresses from a pluripotent or multipotent to a differentiated state: chromatin organisation, transcription factor stoichiometry, and cellular signalling all change during this progression, and all shape cellular variability, which becomes maximal at the transition state.

Prebiotic Reaction Networks in Water

A prevailing strategy in origins of life studies is to explore how chemistry constrained by hypothetical prebiotic conditions could have led to molecules and system level processes proposed to be important for life's beginnings. This strategy has yielded model prebiotic reaction networks that elucidate pathways by which relevant compounds can be generated, in some cases, autocatalytically. These prebiotic reaction networks provide a rich platform for further understanding and development of emergent "life-like" behaviours. In this review, recent advances in experimental and analytical procedures associated with classical prebiotic reaction networks, like formose and Miller-Urey, as well as more recent ones are highlighted. Instead of polymeric networks, i.e., those based on nucleic acids or peptides, the focus is on small molecules. The future of prebiotic chemistry lies in better understanding the genuine complexity that can result from reaction networks and the construction of a centralised database of reactions useful for predicting potential network evolution is emphasised.

Paradoxes of cancer: Survival at the brink

The fundamental understanding of how Cancer initiates, persists and then progresses is evolving. High-resolution technologies, including single-cell mutation and gene expression measurements, are now attainable, providing an ever-increasing insight into the molecular details. However, this higher resolution has shown that somatic mutation theory itself cannot explain the extraordinary resistance of cancer to extinction. There is a need for a more Systems-based framework of understanding cancer complexity, which in particular explains the regulation of gene expression during cell-fate decisions. Cancer displays a series of paradoxes. Here we attempt to approach them from the view-point of adaptive exploration of gene regulatory networks at the edge of order and chaos, where cell-fate is changed by oscillations between alternative regulators of cellular senescence and reprogramming operating through self-organisation. On this background, the role of polyploidy in accessing the phylogenetically pre-programmed "oncofetal attractor" state, related to unicellularity, and the de-selection of unsuitable variants at the brink of cell survival is highlighted. The concepts of the embryological and atavistic theory of cancer, cancer cell "life-cycle", and cancer aneuploidy paradox are dissected under this lense. Finally, we challenge researchers to consider that cancer "defects" are mostly the adaptation tools of survival programs that have arisen during evolution and are intrinsic of cancer. Recognition of these features should help in the development of more successful anti-cancer treatments.

Successional Categorization of European Hemi-boreal Forest Tree Species

Developing forest harvesting regimes that mimic natural forest dynamics requires knowledge on typical species behaviors and how they respond to environmental conditions. Species regeneration and survival after disturbance depends on a species' life history traits. Therefore, forest succession determines the extent to which forest communities are able to cope with environmental change. The aim of this review was to (i) review the life history dynamics of hemi-boreal tree species in the context of ecological succession, and (ii) categorize each of these tree species into one of four successional development groups (gap colonizers, gap competitors, forest colonizers, or forest competitors). To do this we embraced the super-organism approach to plant communities using their life history dynamics and traits. Our review touches on the importance and vulnerability of these four types of successional groups, their absence and presence in the community, and how they can be used as a core component to evaluate if the development of the community is progressing towards the restoration of the climatic climax. Applying a theoretical framework to generate ideas, we suggest that forests should be managed to maintain environmental conditions that support the natural variety and sequence of tree species' life histories by promoting genetic invariance and to help secure ecosystem resilience for the future. This could be achieved by employing harvesting methods that emulate natural disturbances and regeneration programs that contribute to maintenance of the four successional groups.

Metabolic cost of rapid adaptation of single yeast cells

Cells can rapidly adapt to changing environments through nongenetic processes; however, the metabolic cost of such adaptation has never been considered. Here we demonstrate metabolic coupling in a remarkable, rapid adaptation process (1 in 1,000 cells adapt per hour) by simultaneously measuring metabolism and division of thousands of individual Saccharomyces cerevisiae cells using a droplet microfluidic system: droplets containing single cells are immobilized in a two-dimensional (2D) array, with osmotically induced changes in droplet volume being used to measure cell metabolism, while simultaneously imaging the cells to measure division. Following a severe challenge, most cells, while not dividing, continue to metabolize, displaying a remarkably wide diversity of metabolic trajectories from which adaptation events can be anticipated. Adaptation requires a characteristic amount of energy, indicating that it is an active process. The demonstration that metabolic trajectories predict a priori adaptation events provides evidence of tight energetic coupling between metabolism and regulatory reorganization in adaptation. This process allows S. cerevisiae to adapt on a physiological timescale, but related phenomena may also be important in other processes, such as cellular differentiation, cellular reprogramming, and the emergence of drug resistance in cancer.

How to fit in: The learning principles of cell differentiation

Cell differentiation in multicellular organisms requires cells to respond to complex combinations of extracellular cues, such as morphogen concentrations. Some models of phenotypic plasticity conceptualise the response as a relatively simple function of a single environmental cues (e.g. a linear function of one cue), which facilitates rigorous analysis. Conversely, more mechanistic models such those implementing GRNs allows for a more general class of response functions but makes analysis more difficult. Therefore, a general theory describing how cells integrate multi-dimensional signals is lacking. In this work, we propose a theoretical framework for understanding the relationships between environmental cues (inputs) and phenotypic responses (outputs) underlying cell plasticity. We describe the relationship between environment and cell phenotype using logical functions, making the evolution of cell plasticity equivalent to a simple categorisation learning task. This abstraction allows us to apply principles derived from learning theory to understand the evolution of multi-dimensional plasticity. Our results show that natural selection is capable of discovering adaptive forms of cell plasticity associated with complex logical functions. However, developmental dynamics cause simpler functions to evolve more readily than complex ones. By using conceptual tools derived from learning theory we show that this developmental bias can be interpreted as a learning bias in the acquisition of plasticity functions. Because of that bias, the evolution of plasticity enables cells, under some circumstances, to display appropriate plastic responses to environmental conditions that they have not experienced in their evolutionary past. This is possible when the selective environment mirrors the bias of the developmental dynamics favouring the acquisition of simple plasticity functions–an example of the necessary conditions for generalisation in learning systems. These results illustrate the functional parallelisms between learning in neural networks and the action of natural selection on environmentally sensitive gene regulatory networks. This offers a theoretical framework for the evolution of plastic responses that integrate information from multiple cues, a phenomenon that underpins the evolution of multicellularity and developmental robustness.

In organisms composed of many cell types, the differentiation of cells relies on their ability to respond to complex extracellular cues, such as morphogen concentrations, a phenomenon known as cell plasticity. Although cell plasticity plays a crucial role in development and evolution, it is not clear how, and if, cell plasticity can enhance adaptation to a novel environment and/or facilitate robust developmental processes. In some models, the relationships between the environmental cues (inputs) and the phenotypic responses (outputs) are conceptualised as one-to-one (i.e. simple ‘reaction norms’); whereas the phenotype of plastic cells commonly depends on several simultaneous inputs (i.e. many-to-one, multi-dimensional reaction norms). One alternative is the use of a gene-regulatory network (GRN) models that allow for much more general responses; but this can make analysis difficult. In this work we use a theoretical framework based on logical functions and learning theory to characterize such multi-dimensional reaction norms produced by GRNs. This allows us to reveal a strong and previously unnoticed bias towards the acquisition of simple forms of cell plasticity, which increases their ability to adapt to novel environments. Recognising this bias helps us to understand when the evolution of cell plasticity will increase the ability of plastic cells to adapt to novel environments, to respond appropriately to complex extracellular cues and to enhance developmental robustness. Since this set of properties are required for the evolution of multicellularity, our approach can also contribute to our understanding of this evolutionary transition.

Epigenetic Ratchet: Spontaneous Adaptation via Stochastic Gene Expression

Adaptation to unforeseen environmental changes is one of the most prominent features that characterize the living system. Although signal transduction and gene regulation networks evolved to adapt specific environmental conditions that they frequently experience, it is also reported that bacteria can modify their gene expression patterns to survive a huge variety of environmental conditions even without such pre-designed networks to adapt specically to each environment. Here we propose a general mechanism of cells for such "spontaneous" adaptation, on the basis of stochastic gene expression and epigenetic modication. First, a variety of gene expression states that are marginally stable states are generated by epigenetic modication. Then by taking advantage of stochastic gene expression and dilution by cellular growth, it is shown that, a gene expression pattern that achieves greater cell growth is generically selected, as conrmed by simulations and analysis of several models. The mechanism does not require any design of gene regulation networks. General relevance of the mechanism to cell biology is also discussed.

Computational modeling demonstrates that glioblastoma cells can survive spatial environmental challenges through exploratory adaptation

Glioblastoma (GBM) is an aggressive type of brain cancer with remarkable cell migration and adaptation capabilities. Exploratory adaptation-utilization of random changes in gene regulation for adaptive benefits-was recently proposed as the process enabling organisms to survive unforeseen conditions. We investigate whether exploratory adaption explains how GBM cells from different anatomic regions of the tumor cope with micro-environmental pressures. We introduce new notions of phenotype and phenotype distance, and determine probable spatial-phenotypic trajectories based on patient data. While some cell phenotypes are inherently plastic, others are intrinsically rigid with respect to phenotypic transitions. We demonstrate that stochastic exploration of the regulatory network structure confers benefits through enhanced adaptive capacity in new environments. Interestingly, even with exploratory capacity, phenotypic paths are constrained to pass through specific, spatial-phenotypic ranges. This work has important implications for understanding how such adaptation contributes to the recurrence dynamics of GBM and other solid tumors.

Drugs modulating stochastic gene expression affect the erythroid differentiation process

To better understand the mechanisms behind cells decision-making to differentiate, we assessed the influence of stochastic gene expression (SGE) modulation on the erythroid differentiation process. It has been suggested that stochastic gene expression has a role in cell fate decision-making which is revealed by single-cell analyses but studies dedicated to demonstrate the consistency of this link are still lacking. Recent observations showed that SGE significantly increased during differentiation and a few showed that an increase of the level of SGE is accompanied by an increase in the differentiation process. However, a consistent relation in both increasing and decreasing directions has never been shown in the same cellular system. Such demonstration would require to be able to experimentally manipulate simultaneously the level of SGE and cell differentiation in order to observe if cell behavior matches with the current theory. We identified three drugs that modulate SGE in primary erythroid progenitor cells. Both Artemisinin and Indomethacin decreased SGE and reduced the amount of differentiated cells. On the contrary, a third component called MB-3 simultaneously increased the level of SGE and the amount of differentiated cells. We then used a dynamical modelling approach which confirmed that differentiation rates were indeed affected by the drug treatment. Using single-cell analysis and modeling tools, we provide experimental evidence that, in a physiologically relevant cellular system, SGE is linked to differentiation.

Darwinian selection of host and bacteria supports emergence of Lamarckian-like adaptation of the system as a whole

Background

The relatively fast selection of symbiotic bacteria within hosts and the potential transmission of these bacteria across generations of hosts raise the question of whether interactions between host and bacteria support emergent adaptive capabilities beyond those of germ-free hosts.

Results

To investigate possibilities for emergent adaptations that may distinguish composite host-microbiome systems from germ-free hosts, we introduce a population genetics model of a host-microbiome system with vertical transmission of bacteria. The host and its bacteria are jointly exposed to a toxic agent, creating a toxic stress that can be alleviated by selection of resistant individuals and by secretion of a detoxification agent (“detox”). We show that toxic exposure in one generation of hosts leads to selection of resistant bacteria, which in turn, increases the toxic tolerance of the host’s offspring. Prolonged exposure to toxin over many host generations promotes anadditional form of emergent adaptation due to selection of hosts based on detox produced by their bacterial community as a whole (as opposed to properties of individual bacteria).

Conclusions

These findings show that interactions between pure Darwinian selections of host and its bacteria can give rise to emergent adaptive capabilities, including Lamarckian-like adaptation of the host-microbiome system.

Reviewers

This article was reviewed by Eugene Koonin, Yuri Wolf and Philippe Huneman.

Electronic supplementary material

The online version of this article (10.1186/s13062-018-0224-7) contains supplementary material, which is available to authorized users.

Dissociation of Rpb4 from RNA polymerase II is important for yeast functionality

Rpb4 is an RNA polymerase II (Pol II) subunit that binds Pol II transcripts co-transcriptionally, accompanies them to the cytoplasm and modulates mRNA export, translation and decay by interacting with cytoplasmic RNA modulators. The importance of the cytoplasmic roles of Rpb4 was challenged by a study reporting that the phenotype of rpb2Δ rpb4Δ cells can be rescued by an Rpb2-Rpb4 fusion protein, assuming that its Rpb4 moiety cannot dissociate from Pol II and functions in the cytoplasm. Here we demonstrate that although the fusion protein supports normal transcription, it adversely affects mRNA decay, cell proliferation and adaptability-e.g., response to stress. These defects are similar, albeit milder, than the defects that characterize rpb4Δ cells. At least two mechanisms alleviate the deleterious effect of the fusion protein. First, a portion of this fusion protein is cleaved into free Rpb2 and Rpb4. The free Rpb4 is functional, as it binds mRNAs and polysomes, like WT Rpb4. Second, the fusion protein is also capable of binding poly(A)+ mRNAs in the cytoplasm, in an Rpb7-mediated manner, probably complementing the functions of the diminished Rpb4. Collectively, normal coupling between mRNA synthesis and decay requires wild-type configuration of Rpb4, and fusing Rpb4 to Rpb2 compromises this coupling.

Epigenetically facilitated mutational assimilation: epigenetics as a hub within the inclusive evolutionary synthesis

After decades of debate about the existence of non‐genetic inheritance, the focus is now slowly shifting towards dissecting its underlying mechanisms. Here, we propose a new mechanism that, by integrating non‐genetic and genetic inheritance, may help build the long‐sought inclusive vision of evolution. After briefly reviewing the wealth of evidence documenting the existence and ubiquity of non‐genetic inheritance in a table, we review the categories of mechanisms of parent–offspring resemblance that underlie inheritance. We then review several lines of argument for the existence of interactions between non‐genetic and genetic components of inheritance, leading to a discussion of the contrasting timescales of action of non‐genetic and genetic inheritance. This raises the question of how the fidelity of the inheritance system can match the rate of environmental variation. This question is central to understanding the role of different inheritance systems in evolution. We then review and interpret evidence indicating the existence of shifts from inheritance systems with low to higher transmission fidelity. Based on results from different research fields we propose a conceptual hypothesis linking genetic and non‐genetic inheritance systems. According to this hypothesis, over the course of generations, shifts among information systems allow gradual matching between the rate of environmental change and the inheritance fidelity of the corresponding response. A striking conclusion from our review is that documented shifts between types of inherited non‐genetic information converge towards epigenetics (i.e. inclusively heritable molecular variation in gene expression without change in DNA sequence). We then interpret the well‐documented mutagenicity of epigenetic marks as potentially generating a final shift from epigenetic to genetic encoding. This sequence of shifts suggests the existence of a relay in inheritance systems from relatively labile ones to gradually more persistent modes of inheritance, a relay that could constitute a new mechanistic basis for the long‐proposed, but still poorly documented, hypothesis of genetic assimilation. A profound difference between the genocentric and the inclusive vision of heredity revealed by the genetic assimilation relay proposed here lies in the fact that a given form of inheritance can affect the rate of change of other inheritance systems. To explore the consequences of such inter‐connection among inheritance systems, we briefly review published theoretical models to build a model of genetic assimilation focusing on the shift in the engraving of environmentally induced phenotypic variation into the DNA sequence. According to this hypothesis, when environmental change remains stable over a sufficient number of generations, the relay among inheritance systems has the potential to generate a form of genetic assimilation. In this hypothesis, epigenetics appears as a hub by which non‐genetically inherited environmentally induced variation in traits can become genetically encoded over generations, in a form of epigenetically facilitated mutational assimilation. Finally, we illustrate some of the major implications of our hypothetical framework, concerning mutation randomness, the central dogma of molecular biology, concepts of inheritance and the curing of inherited disorders, as well as for the emergence of the inclusive evolutionary synthesis.

Cellular function given parametric variation in the Hodgkin and Huxley model of excitability

How is reliable physiological function maintained in cells despite considerable variability in the values of key parameters of multiple interacting processes that govern that function? Here, we use the classic Hodgkin-Huxley formulation of the squid giant axon action potential to propose a possible approach to this problem. Although the full Hodgkin-Huxley model is very sensitive to fluctuations that independently occur in its many parameters, the outcome is in fact determined by simple combinations of these parameters along two physiological dimensions: structural and kinetic (denoted S and K, respectively). Structural parameters describe the properties of the cell, including its capacitance and the densities of its ion channels. Kinetic parameters are those that describe the opening and closing of the voltage-dependent conductances. The impacts of parametric fluctuations on the dynamics of the system-seemingly complex in the high-dimensional representation of the Hodgkin-Huxley model-are tractable when examined within the S-K plane. We demonstrate that slow inactivation, a ubiquitous activity-dependent feature of ionic channels, is a powerful local homeostatic control mechanism that stabilizes excitability amid changes in structural and kinetic parameters.

Exploratory adaptation in large random networks

The capacity of cells and organisms to respond to challenging conditions in a repeatable manner is limited by a finite repertoire of pre-evolved adaptive responses. Beyond this capacity, cells can use exploratory dynamics to cope with a much broader array of conditions. However, the process of adaptation by exploratory dynamics within the lifetime of a cell is not well understood. Here we demonstrate the feasibility of exploratory adaptation in a high-dimensional network model of gene regulation. Exploration is initiated by failure to comply with a constraint and is implemented by random sampling of network configurations. It ceases if and when the network reaches a stable state satisfying the constraint. We find that successful convergence (adaptation) in high dimensions requires outgoing network hubs and is enhanced by their auto-regulation. The ability of these empirically validated features of gene regulatory networks to support exploratory adaptation without fine-tuning, makes it plausible for biological implementation.

Recent works suggest that cellular networks may respond to novel challenges on the time-scale of cellular lifetimes through large-scale perturbation of gene expression and convergence to a new state. Here, the authors demonstrate the theoretical feasibility of exploratory adaptation in cellular networks by showing that convergence to new states depends on known features of these networks.

Chemical Analysis of a "Miller-Type" Complex Prebiotic Broth : Part II: Gas, Oil, Water and the Oil/Water-Interface

We have analyzed the chemical variety obtained by Miller-Urey-type experiments using nuclear magnetic resonance (NMR) spectroscopy and coherent anti-Stokes Raman scattering (CARS) spectroscopy, gas chromatography followed by mass spectrometry (GC/MS) and two-dimensional gas chromatography followed by mass spectrometry (GCxGC/MS). In the course of a running Miller-Urey-type experiment, a hydrophobic organic layer emerged besides the hydrophilic aqueous phase and the gaseous phase that were initially present. The gas phase mainly consisted of aromatic compounds and molecules containing C≡C or C≡N triple bonds. The hydrophilic phase contained at least a few thousands of different molecules, primarily distributed in a range of 50 and 500 Da. The hydrophobic phase is characterized by carbon-rich, oil-like compounds and their amphiphilic derivatives containing oxygen with tensioactive properties. The presence of a wide range of oxidized molecules hints to the availability of oxygen radicals. We suggest that they intervene in the formation of alkylated polyethylene glycol (PEG) in the oil/water interface. CARS spectroscopy revealed distinct vibrational molecular signatures. In particular, characteristic spectral bands for cyanide compounds were observed if the broth was prepared with electric discharges in the gaseous phase. The characteristic spectral bands were absent if discharges were released onto the water surface. NMR spectroscopy on the same set of samples independently confirmed the observation. In addition, NMR spectroscopy revealed overall high chemical variability that suggests strong non-linearities due to interdependent, sequential reaction steps.

From physical to biological individuation

In this paper, we insist on stressing the epistemic and metaphysical difference between individual and individuation, a distinction originally developed by Gilbert Simondon. Individuation occurs in complex physical systems by the coupling (R₁) between the system and its outside conditions. As such the system is not well defined by its sole constituents. Let's characterize (R₂) as follows: the system is not entirely defined by its structure at a given time because this structure will change and global emergent properties will appear, as in the paradigmatic example of phase transition. Thus physical individuation is defined both by the coupling of a physical system with its environment (R₁) and by its diachronic dynamics taking place (R₂). We interpret biological individuation as a second order one, i.e. as a recursive procedure through which physical individuation is also acting on "its own theatre". We represent this procedure like a mapping through which (R₁R₂) are applied to themselves, so that: R_N = (R₁R₂)^N. We highlight the relation between this assumption and the concept of extended criticality developed by Bailly, Longo and Montévil.

Emergence and maintenance of excitability: kinetics over structure

The capacity to generate action potentials in neurons and other excitable cells requires tuning of both ionic channel expression and kinetics in a large parameter space. Alongside studies that extend traditional focus on control-based regulation of structural parameters (channel densities), there is a budding interest in self-organization of kinetic parameters. In this picture, ionic channels are continually forced by activity in-and-out of a pool of states not available for the mechanism of excitability. The process, acting on expressed structure, provides a bed for generation of a spectrum of excitability modes. Driven by microscopic fluctuations over a broad range of temporal scales, self-organization of kinetic parameters enriches the concepts and tools used in the study of development of excitability.

A principle of organization which facilitates broad Lamarckian-like adaptations by improvisation

BACKGROUND

During the lifetime of an organism, every individual encounters many combinations of diverse changes in the somatic genome, epigenome and microbiome. This gives rise to many novel combinations of internal failures which are unique to each individual. How any individual can tolerate this high load of new, individual-specific scenarios of failure is not clear. While stress-induced plasticity and hidden variation have been proposed as potential mechanisms of tolerance, the main conceptual problem remains unaddressed, namely: how largely non-beneficial random variation can be rapidly and safely organized into net benefits to every individual.

PRESENTATION OF THE HYPOTHESIS

We propose an organizational principle which explains how every individual can alleviate a high load of novel stressful scenarios using many random variations in flexible and inherently less harmful traits. Random changes which happen to reduce stress, benefit the organism and decrease the drive for additional changes. This adaptation (termed 'Adaptive Improvisation') can be further enhanced, propagated, stabilized and memorized when beneficial changes reinforce themselves by auto-regulatory mechanisms. This principle implicates stress not only in driving diverse variations in cells tissues and organs, but also in organizing these variations into adaptive outcomes. Specific (but not exclusive) examples include stress reduction by rapid exchange of mobile genetic elements (or exosomes) in unicellular, and rapid changes in the symbiotic microorganisms of animals. In all cases, adaptive changes can be transmitted across generations, allowing rapid improvement and assimilation in a few generations.

TESTING THE HYPOTHESIS

We provide testable predictions derived from the hypothesis.

IMPLICATIONS OF THE HYPOTHESIS

The hypothesis raises a critical, but thus far overlooked adaptation problem and explains how random variation can self-organize to confer a wide range of individual-specific adaptations beyond the existing outcomes of natural selection. It portrays gene regulation as an inseparable synergy between natural selection and adaptation by improvisation. The latter provides a basis for Lamarckian adaptation that is not limited to a specific mechanism and readily accounts for the remarkable resistance of tumors to treatment.

Universality, complexity and the praxis of biology: Two case studies

The phenomenon of biology provides a prime example for a naturally occurring complex system. The approach to this complexity reflects the tension between a reductionist, reverse-engineering stance, and more abstract, systemic ones. Both of us are reductionists, but our observations challenge reductionism, at least the naive version of it. Here we describe the challenge, focusing on two universal characteristics of biological complexity: two-way microscopic-macroscopic degeneracy, and lack of time scale separation within and between levels of organization. These two features and their consequences for the praxis of experimental biology, reflect inherent difficulties in separating the dynamics of any given level of organization from the coupled dynamics of all other levels, including the environment within which the system is embedded. Where these difficulties are not deeply acknowledged, the impacts of fallacies that are inherent to naive reductionism are significant. In an era where technology enables experimental high-resolution access to numerous observables, the challenge faced by the mature reductionist-identification of relevant microscopic variables-becomes more demanding than ever. The demonstrations provided here are taken from two very different biological realizations: populations of microorganisms and populations of neurons, thus making the lesson potentially general.