Self-organization vs Watchmaker: stochastic gene expression and cell differentiation

Perspective: Controlling Epidermal Terminal Differentiation with Transcriptional Bursting and RNA Bodies

The outer layer of the skin, the epidermis, is the principal barrier to the external environment: post-mitotic cells terminally differentiate to form a tough outer cornified layer of enucleate and flattened cells that confer the majority of skin barrier function. Nuclear degradation is required for correct cornified envelope formation. This process requires mRNA translation during the process of nuclear destruction. In this review and perspective, we address the biology of transcriptional bursting and the formation of ribonuclear particles in model organisms including mammals, and then examine the evidence that these phenomena occur as part of epidermal terminal differentiation.

Fundamental awareness: A framework for integrating science, philosophy and metaphysics

The ontologic framework of Fundamental Awareness proposed here assumes that non-dual Awareness is foundational to the universe, not arising from the interactions or structures of higher level phenomena. The framework allows comparison and integration of views from the three investigative domains concerned with understanding the nature of consciousness: science, philosophy, and metaphysics. In this framework, Awareness is the underlying reality, not reducible to anything else. Awareness and existence are the same. As such, the universe is non-material, self-organizing throughout, a holarchy of complementary, process driven, recursive interactions. The universe is both its own first observer and subject. Considering the world to be non-material and comprised, a priori, of Awareness is to privilege information over materiality, action over agency and to understand that qualia are not a “hard problem,” but the foundational elements of all existence. These views fully reflect main stream Western philosophical traditions, insights from culturally diverse contemplative and mystical traditions, and are in keeping with current scientific thinking, expressible mathematically.

Evolution of Self-Organized Task Specialization in Robot Swarms

Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as "task partitioning", whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

BACKGROUND

The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression.

RESULTS

We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization.

CONCLUSIONS

Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks.

Expansion of multipotent stem cells from the adult human brain

The discovery of stem cells in the adult human brain has revealed new possible scenarios for treatment of the sick or injured brain. Both clinical use of and preclinical research on human adult neural stem cells have, however, been seriously hampered by the fact that it has been impossible to passage these cells more than a very few times and with little expansion of cell numbers. Having explored a number of alternative culturing conditions we here present an efficient method for the establishment and propagation of human brain stem cells from whatever brain tissue samples we have tried. We describe virtually unlimited expansion of an authentic stem cell phenotype. Pluripotency proteins Sox2 and Oct4 are expressed without artificial induction. For the first time multipotency of adult human brain-derived stem cells is demonstrated beyond tissue boundaries. We characterize these cells in detail in vitro including microarray and proteomic approaches. Whilst clarification of these cells' behavior is ongoing, results so far portend well for the future repair of tissues by transplantation of an adult patient's own-derived stem cells.

Theoretical aspects of Systems Biology

The natural world consists of hierarchical levels of complexity that range from subatomic particles and molecules to ecosystems and beyond. This implies that, in order to explain the features and behavior of a whole system, a theory might be required that would operate at the corresponding hierarchical level, i.e. where self-organization processes take place. In the past, biological research has focused on questions that could be answered by a reductionist program of genetics. The organism (and its development) was considered an epiphenomenona of its genes. However, a profound rethinking of the biological paradigm is now underway and it is likely that such a process will lead to a conceptual revolution emerging from the ashes of reductionism. This revolution implies the search for general principles on which a cogent theory of biology might rely. Because much of the logic of living systems is located at higher levels, it is imperative to focus on them. Indeed, both evolution and physiology work on these levels. Thus, by no means Systems Biology could be considered a 'simple' 'gradual' extension of Molecular Biology.

The self-organizing fractal theory as a universal discovery method: the phenomenon of life

A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy.An application of the new discovery method to life sciences reveals that moving electrons represent a keystone physical force (flux) that powers, animates, informs, and binds all living structures-processes into a planetary-wide, multiscale system of electron flow/circulation, and that all living organisms and their larger-scale organizations emerge to function as electron transport networks that are supported by and, at the same time, support the flow of electrons down the Earth's redox gradient maintained along the core-mantle-crust-ocean-atmosphere axis of the planet. The presented findings lead to a radically new perspective on the nature and origin of life, suggesting that living matter is an organizational state/phase of nonliving matter and a natural consequence of the evolution and self-organization of nonliving matter.The presented paradigm opens doors for explosive advances in many disciplines, by uniting them within a single conceptual framework and providing a discovery method that allows for the systematic generation of knowledge through comparison and complementation of empirical data across different sciences and disciplines.

Scale-free flow of life: on the biology, economics, and physics of the cell

The present work is intended to demonstrate that most of the paradoxes, controversies, and contradictions accumulated in molecular and cell biology over many years of research can be readily resolved if the cell and living systems in general are re-interpreted within an alternative paradigm of biological organization that is based on the concepts and empirical laws of nonequilibrium thermodynamics. In addition to resolving paradoxes and controversies, the proposed re-conceptualization of the cell and biological organization reveals hitherto unappreciated connections among many seemingly disparate phenomena and observations, and provides new and powerful insights into the universal principles governing the emergence and organizational dynamics of living systems on each and every scale of biological organizational hierarchy, from proteins and cells to economies and ecologies.

Emergent genome-wide control in wildtype and genetically mutated lipopolysaccarides-stimulated macrophages

Large-scale gene expression studies have mainly focused on highly expressed and 'discriminatory' genes to decipher key regulatory processes. Biological responses are consequence of the concerted action of gene regulatory network, thus, limiting our attention to genes having the most significant variations is insufficient for a thorough understanding of emergent whole genome response. Here we comprehensively analyzed the temporal oligonucleotide microarray data of lipopolysaccharide (LPS) stimulated macrophages in 4 genotypes; wildtype, Myeloid Differentiation factor 88 (MyD88) knockout (KO), TIR-domain-containing adapter-inducing interferon-beta (TRIF) KO and MyD88/TRIF double KO (DKO). Pearson correlations computed on the whole genome expression between different genotypes are extremely high (>0.98), indicating a strong co-regulation of the entire expression network. Further correlation analyses reveal genome-wide response is biphasic, i) acute-stochastic mode consisting of small number of sharply induced immune-related genes and ii) collective mode consisting of majority of weakly induced genes of diverse cellular processes which collectively adjust their expression level. Notably, temporal correlations of a small number of randomly selected genes from collective mode show scalability. Furthermore, in collective mode, the transition from large scatter in expression distributions for single ORFs to smooth linear lines emerges as an organizing principle when grouping of 50 ORFs and above. With this emergent behavior, the role of MyD88, TRIF and novel MyD88, TRIF-independent processes for gene induction can be linearly superposed to decipher quantitative whole genome differential control of transcriptional and mRNA decay machineries. Our work demonstrates genome-wide co-regulated responses subsequent to specific innate immune stimulus which have been largely neglected.

Generation of synthetic transcriptome data with defined statistical properties for the development and testing of new analysis methods

We have previously developed a combined signal/variance distribution model that accounts for the particular statistical properties of datasets generated on the Applied Biosystems AB1700 transcriptome system. Here we show that this model can be efficiently used to generate synthetic datasets with statistical properties virtually identical to those of the actual data by aid of the JAVA application ace.map creator 1.0 that we have developed. The fundamentally different structure of AB1700 transcriptome profiles requires re-evaluation, adaptation, or even redevelopment of many of the standard microarray analysis methods in order to avoid misinterpretation of the data on the one hand, and to draw full benefit from their increased specificity and sensitivity on the other hand. Our composite data model and the ace.map creator 1.0 application thereby not only present proof of the correctness of our parameter estimation, but also provide a tool for the generation of synthetic test data that will be useful for further development and testing of analysis methods.

High-sensitivity transcriptome data structure and implications for analysis and biologic interpretation

Novel microarray technologies such as the AB1700 platform from Applied Biosystems promise significant increases in the signal dynamic range and a higher sensitivity for weakly expressed transcripts. We have compared a representative set of AB1700 data with a similarly representative Affymetrix HG-U133A dataset. The AB1700 design extends the signal dynamic detection range at the lower bound by one order of magnitude. The lognormal signal distribution profiles of these high-sensitivity data need to be represented by two independent distributions. The additional second distribution covers those transcripts that would have gone undetected using the Affymetrix technology. The signal-dependent variance distribution in the AB1700 data is a non-trivial function of signal intensity, describable using a composite function. The drastically different structure of these high-sensitivity transcriptome profiles requires adaptation or even redevelopment of the standard microarray analysis methods. Based on the statistical properties, we have derived a signal variance distribution model for AB1700 data that is necessary for such development. Interestingly, the dual lognormal distribution observed in the AB1700 data reflects two fundamentally different biologic mechanisms of transcription initiation.

The stochastic model of non-equilibrium mutagen-induced alterations of DNA: implication to genetic instability in cancer

Genetic alterations such as point mutations, chromosomal rearrangements, modification of DNA methylation and chromosome aberrations accumulate during the lifetime of an organism. They can be caused by intrinsic errors in the DNA replication and repair as well as by external factors such as exposure to mutagenic substances or radiation. The main purpose of the present work is to begin an exploration of the stochastic nature of non-equilibrium DNA alteration caused by events such as tautomeric shifts. This is done by modeling the genetic DNA code chain as a sequence of DNA-bit values ('1' for normal bases and '-1' for abnormal bases). We observe the number of DNA-bit changes resulting from the random point mutation process which, in the model, is being induced by a stochastic Brownian mutagen (BM) as it diffuses through the DNA-bit systems. Using both an analytical and Monte Carlo (MC) simulation techniques, we observe the local and global number of DNA-bit changes. It is found that in 1D, the local DNA-bit density behaves like 1/t, the global total number of the switched (abnormal) DNA-bit increases as t. The probability distribution P(b, 0, t) of b(0, t) is log-normal. It is also found that when the number of mutagens is increased, the number of the total abnormal DNA-bits does not grow linearly with the number of mutagens. All analytic results are in good agreement with the simulation results.

Lineage specification of hematopoietic stem cells: mathematical modeling and biological implications

Lineage specification of hematopoietic stem cells is considered a progressive restriction in lineage potential. This view is consistent with observations that differentiation and lineage specification is preceded by a low-level coexpression of lineage specific, potentially antagonistic genes in early progenitor cells. This coexistence, commonly referred to as priming, disappears in the course of differentiation when certain lineage-restricted genes are upregulated while others are downregulated. Based on this phenomenological description, we propose a quantitative model that describes lineage specification as a competition process between different interacting lineage propensities. The competition is governed by environmental stimuli promoting a drift from a multipotent coexpression to the dominance of one lineage. The assumption of a context-dependent intracellular differentiation control is consistently embedded into our previously proposed model of hematopoietic stem cell organization. The extended model, which comprises self-renewal and lineage specification, is verified using available data on the lineage specification potential of primary hematopoietic stem cells and on the differentiation kinetics of the FDCP-mix cell line. The model provides a number of experimentally testable predictions. From our results, we conclude that lineage specification is best described as a flexible and temporally extended process in which lineage commitment emerges as the result of a sequence of small decision steps. The proposed model provides a novel systems biological view on the functioning of lineage specification in adult tissue stem cells and its connections to the self-renewal properties of these cells. Disclosure of potential conflicts of interest is found at the end of this article.

A network-based analysis of polyanion-binding proteins utilizing human protein arrays

The existence of interactions between many cellular proteins and various polyanionic surfaces within a cell is now well established. The functional role of such interactions, however, remains to be clearly defined. The existence of protein arrays, with a large selection of different kinds of proteins, provides a way to better address a number of aspects of this question. We have therefore investigated the interaction between five cellular polyanions (actin, tubulin, heparin, heparan sulfate, and DNA) and approximately 5,000 human proteins using protein microarrays in an attempt to better understand the functional nature of such interaction(s). We demonstrate that a large number of polyanion-binding proteins exist that contain multiple positively charged regions, are often disordered, are involved in phosphorylation processes, and appear to play a role in protein-protein interaction networks. Considering the crowded nature of cellular interiors, we propose that polyanion-binding proteins interact with a wide variety of polyanionic surfaces in cells in a functionally significant manner.

Self-organization versus Watchmaker: ambiguity of molecular recognition and design charts of cellular circuitry

A large body of experimental evidence indicates that the specific molecular interactions and/or chemical conversions depicted as links in the conventional diagrams of cellular signal transduction and metabolic pathways are inherently probabilistic, ambiguous and context-dependent. Being the inevitable consequence of the dynamic nature of protein structure in solution, the ambiguity of protein-mediated interactions and conversions challenges the conceptual adequacy and practical usefulness of the mechanistic assumptions and inferences embodied in the design charts of cellular circuitry. It is argued that the reconceptualization of molecular recognition and cellular organization within the emerging interpretational framework of self-organization, which is expanded here to include such concepts as bounded stochasticity, evolutionary memory, and adaptive plasticity offers a significantly more adequate representation of experimental reality than conventional mechanistic conceptions do. Importantly, the expanded framework of self-organization appears to be universal and scale-invariant, providing conceptual continuity across multiple scales of biological organization, from molecules to societies. This new conceptualization of biological phenomena suggests that such attributes of intelligence as adaptive plasticity, decision-making, and memory are enforced by evolution at different scales of biological organization and may represent inherent properties of living matter.

A weakened transcriptional enhancer yields variegated gene expression

Identical genes in the same cellular environment are sometimes expressed differently. In some cases, including the immunoglobulin heavy chain (IgH) locus, this type of differential gene expression has been related to the absence of a transcriptional enhancer. To gain additional information on the role of the IgH enhancer, we examined expression driven by enhancers that were merely weakened, rather than fully deleted, using both mutations and insulators to impair enhancer activity. For this purpose we used a LoxP/Cre system to place a reporter gene at the same genomic site of a stable cell line. Whereas expression of the reporter gene was uniformly high in the presence of the normal, uninsulated enhancer and undetectable in its absence, weakened enhancers yielded variegated expression of the reporter gene; i.e., the average level of expression of the same gene differed in different clones, and expression varied significantly among cells within individual clones. These results indicate that the weakened enhancer allows the reporter gene to exist in at least two states. Subtle aspects of the variegation suggest that the IgH enhancer decreases the average duration (half-life) of the silent state. This analysis has also tested the conventional wisdom that enhancer activity is independent of distance and orientation. Thus, our analysis of mutant (truncated) forms of the IgH enhancer revealed that the 250 bp core enhancer was active in its normal position, ∼1.4 kb 3′ of the promoter, but inactive ∼6 kb 3′, indicating that the activity of the core enhancer was distance-dependent. A longer segment – the core enhancer plus ∼1 kb of 3′ flanking material, including the 3′ matrix attachment region – was active, and the activity of this longer segment was orientation-dependent. Our data suggest that this 3′ flank includes binding sites for at least two activators.

Self-organization versus Watchmaker: Molecular motors and protein translocation

Generation of directional movement at the molecular scale is a phenomenon crucial for biological organization and dynamics. It is traditionally described in mechanistic terms, in consistency with the conventional machine-like image of the cell. The designated and highly specialized protein machines and molecular motors are presumed to bring about most of cellular motion. A review of experimental data suggests, however, that uncritical adherence to mechanistic interpretations may limit the ability of researchers to comprehend and model biology. Specifically, this article illustrates that the interpretation of molecular motors and protein translocation in terms of stochasticity and self-organization appears to provide a more adequate and fruitful conceptual framework for understanding of biological organization at the molecular scale.

Implications of 'postmodern biology' for pathology: the Cell Doctrine

Recent insights regarding stem cells, repression and de-repression of gene expression, and the application of Complexity Theory to cell and molecular biology require a re-evaluation of many long-held dogmas regarding the nature of the human body in health and disease. Greater than expected cell plasticity, trafficking of cells between organs, 'cellular uncertainty', stochasticity of cell origins and fates, and a reconsideration of Cell Doctrine itself all logically follow from these observations and conceptual approaches. In this paper, these themes will be considered and some implications for the investigative pathologist will be explored.

Chromatin code, local non-equilibrium dynamics, and the emergence of transcription regulatory programs

Chromatin is a, if not the, hallmark of eukaryotic life. Any molecular process entailing genomic DNA or the nucleus by default provokes or depends on chromatin structural dynamics on various space and time scales. Chromatin dynamics are result of changes in the physico-chemical properties of the chromatin constituents themselves or the nuclear environment. Chromatin has been found in the former case to undergo many different covalent enzyme-mediated chemical modifications. Their identification sheds light on the molecular mechanisms and the physico-chemical properties underlying chromatin dynamics, and allows the development of quantitative models for the chromatin fiber. The abundance of the different modifications, their dynamics, and short- as well as long-range correlation phenomena between different modifications also point to a second layer of genomic coding implemented at the level of chromatin. Especially, gene regulatory coding seems to depend on such a second-level code. The information-theoretical properties of chromatin in the context of gene regulatory coding are discussed. A model for the emergence of cellular differentiation from the intricate interplay between genomic and chromatin code is presented and discussed in light of recent experimental insights.

Models of spliceosomal intron proliferation in the face of widespread ectopic expression

It is now certain that today living organisms can acquire new spliceosomal introns in their genes. The proposed sources of spliceosomal introns are exons, transposons, and other introns, including spliceosomal and group II self-splicing introns. Spliceosomal introns are thought to be the most likely source, because the inserted sequence would immediately be endowed with the essential set of intron recognition sequences, thereby preventing the deleterious effects associated with incorrect splicing. The most obvious spliceosomal intron duplication pathways involve an RNA transcript intermediate step. Therefore, for a spliceosomal intron to be originated by duplication, either the source gene from which the novel intron is derived, or that gene and the recipient gene, which contains the novel intron, would need to be expressed in the germ line. Intron proliferation surveys indicate that putative intron duplicate-containing genes do not always match detectable expression in the germ line, which casts doubt on the generality of the duplication model. However, judging mechanisms of intron gain (or loss) from present-day gene expression profiles could be erroneous, if expression patterns were different at the time the introns arose. In fact, this may likely be so in most cases. Ectopic expression, i.e., the expression of genes at times and locations where the target gene is not known to have a function, is a much more common phenomenon than previously realized. We conclude with a speculation on a possible interplay between spliceosomal introns and ectopic expression at the origin of multicellularity.

Classification of Self-Organization and Emergence in Chemical and Biological Systems

Most chemical and biological systems are complex, but the application of complex systems science to these fields is relatively new compared to the traditional reductionist approaches. Complexity can provide a new paradigm for understanding the behaviour of interesting chemical and biological systems, and new tools for studying, modelling, and simulating them. It is also likely that some very important, but very complicated systems may not be accessible by reductionist approaches. This paper provides a brief review of two important concepts in complexity, self-organization and emergence, and describes why they are relevant to chemical and biological systems

Stochastic cell

Accumulating experimental evidence of stochasticity, self-organization and abrupt non-linear transitions underlying the dynamics of cellular structure and function is increasingly more consistent with the concepts and models of phase transitions, critical phenomena and non-linear thermodynamics rather than with the conventional clockwork description of the cell. The novel emerging image of the stochastic cell suggests that familiar and convenient classico-mechanical interpretations may be limiting our ability to understand the behavior of biological systems and calls for active exploration of alternative interpretational frameworks.

Stochasticity in gene expression: from theories to phenotypes

Genetically identical cells exposed to the same environmental conditions can show significant variation in molecular content and marked differences in phenotypic characteristics. This variability is linked to stochasticity in gene expression, which is generally viewed as having detrimental effects on cellular function with potential implications for disease. However, stochasticity in gene expression can also be advantageous. It can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.

Stochastic gene expression, disruption of tissue averaging effects and cancer as a disease of development

Despite the extensive literature describing the somatic genetic alterations in cancer cells, the precise origins of cancer cells remain controversial. In this article, I suggest that the etiology of cancer and the generation of genetic instability in cancer cells should be considered in the light of recent findings on both the stochastic nature of gene expression and its regulation at tissue level. By postulating that gene expression is intrinsically probabilistic and that stabilization of gene expression arises by cellular interactions in "morphogenetic fields", development and cellular differentiation can be rethought in an evolutionary perspective. In particular, this article proposes that disruptions of cellular interactions are the initial source of abnormal gene expression in cancer cells. Consequently, cancer phenotypes such as genetic and epigenetic instabilities, and also the presence of cells with stem cell-like properties, may result from inaccurate and aberrant patterns of gene expression generated by microenvironmental alterations. Finally, the therapeutic implications of this view are discussed.