A semiotic framework for evolutionary and developmental biology

This work aims at constructing a semiotic framework for an expanded evolutionary synthesis grounded on Peirce's universal categories and the six space/time/function relations [Taborsky, E., 2004. The nature of the sign as a WFF--a well-formed formula, SEED J. (Semiosis Evol. Energy Dev.) 4 (4), 5-14] that integrate the Lamarckian (internal/external) and Darwinian (individual/population) cuts. According to these guide lines, it is proposed an attempt to formalize developmental systems theory by using the notion of evolving developing agents (EDA) that provides an internalist model of a general transformative tendency driven by organism's need to cope with environmental uncertainty. Development and evolution are conceived as non-programmed open-ended processes of information increase where EDA reach a functional compromise between: (a) increments of phenotype's uniqueness (stability and specificity) and (b) anticipation to environmental changes. Accordingly, changes in mutual information content between the phenotype/environment drag subsequent changes in mutual information content between genotype/phenotype and genotype/environment at two interwoven scales: individual life cycle (ontogeny) and species time (phylogeny), respectively. Developmental terminal additions along with increment minimization of developmental steps must be positively selected.     

Toward a stoichiometric framework for evolutionary biology

Ecological stoichiometry, the study of the balance of energy and materials in living systems, may serve as a useful synthetic framework for evolutionary biology. Here, we review recent work that illustrates the power of a stoichiometric approach to evolution across multiple scales, and then point to important open questions that may chart the way forward in this new field. At the molecular level, stoichiometry links hereditary changes in the molecular composition of organisms to key phenotypic functions. At the level of evolutionary ecology, a simultaneous focus on the energetic and material underpinnings of evolutionary tradeoffs and transactions highlights the relationship between the cost of resource acquisition and the functional consequences of biochemical composition. At the macroevolutionary level, a stoichiometric perspective can better operationalize models of adaptive radiation and escalation, and elucidate links between evolutionary innovation and the development of global biogeochemical cycles. Because ecological stoichiometry focuses on the interaction of energetic and multiple material currencies, it should provide new opportunities for coupling evolutionary dynamics across scales from genomes to the biosphere.     

Hierarchical phylogenetics as a quantitative analytical framework for evolutionary developmental biology

Phylogenetics has inherent utility in evolutionary developmental biology (EDB) as it is an established methodology for estimating evolutionary relationships and for making comparisons between levels of biological organization. However, explicit phylogenetic methods generally have been limited to two levels of organization in EDB-the species and the gene. We demonstrate that phylogenetic methods can be applied broadly to other organizational levels, such as morphological structures or cell types, to identify evolutionary patterns. We present examples at and between different hierarchical levels of organization to address questions central to EDB. We argue that this application of "hierarchical phylogenetics" can be a unifying analytical approach to the field of EDB.     

Driving developmental and evolutionary change: A systems biology view

Embryonic development is underpinned by ～50 core processes that drive morphogenesis, growth, patterning and differentiation, and each is the functional output of a complex molecular network. Processes are thus the natural and parsimonious link between genotype and phenotype and the obvious focus for any discussion of biological change. Here, the implications of this approach are explored. One is that many features of developmental change can be modeled as mathematical graphs, or sets of connected triplets of the general form <noun><verb><noun>. In these, the verbs (edges) are the outputs of the processes that drive change and the nouns (nodes) are the time-dependent states of biological entities (from molecules to tissues). Such graphs help unpick the multi-level complexity of developmental phenomena and may help suggest new experiments. Another comes from analyzing the effect of mutation that lead to tinkering with the dynamic properties of these processes and to congenital abnormalities; if these changes are both inherited and advantageous, they become evolutionary modifications. In this context, protein networks often represents what classical evolutionary genetics sees as genes, and the realization that traits reflect the output processes of complex networks, particularly for growth, patterning and pigmentation, rather than anything simpler clarifies some problems that the evolutionary synthesis of the 1950s has found hard to solve. In the wider context, most processes are used many times in development and cooperate to produce tissue modules (bones, branching duct systems, muscles etc.). Their underlying generative networks can thus be thought of as genomic modules or subroutines.     

VisANT: an integrative framework for networks in systems biology

The essence of a living cell is adaptation to a changing environment, and a central goal of modern cell biology is to understand adaptive change under normal and pathological conditions. Because the number of components is large, and processes and conditions are many, visual tools are useful in providing an overview of relations that would otherwise be far more difficult to assimilate. Historically, representations were static pictures, with genes and proteins represented as nodes, and known or inferred correlations between them (links) represented by various kinds of lines. The modern challenge is to capture functional hierarchies and adaptation to environmental change, and to discover pathways and processes embedded in known data, but not currently recognizable. Among the tools being developed to meet this challenge is VisANT (freely available at http://visant.bu.edu) which integrates, mines and displays hierarchical information. Challenges to integrating modeling (discrete or continuous) and simulation capabilities into such visual mining software are briefly discussed.     

A biomolecular isolation framework for eco-systems biology

Mixed microbial communities are complex, dynamic and heterogeneous. It is therefore essential that biomolecular fractions obtained for high-throughput omic analyses are representative of single samples to facilitate meaningful data integration, analysis and modeling. We have developed a new methodological framework for the reproducible isolation of high-quality genomic DNA, large and small RNA, proteins, and polar and non-polar metabolites from single unique mixed microbial community samples. The methodology is based around reproducible cryogenic sample preservation and cell lysis. Metabolites are extracted first using organic solvents, followed by the sequential isolation of nucleic acids and proteins using chromatographic spin columns. The methodology was validated by comparison to traditional dedicated and simultaneous biomolecular isolation methods. To prove the broad applicability of the methodology, we applied it to microbial consortia of biotechnological, environmental and biomedical research interest. The developed methodological framework lays the foundation for standardized molecular eco-systematic studies on a range of different microbial communities in the future.     

A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis

Background  

Because metabolism is fundamental in sustaining microbial life, drugs that target pathogen-specific metabolic enzymes and pathways can be very effective. In particular, the metabolic challenges faced by intracellular pathogens, such as Mycobacterium tuberculosis, residing in the infected host provide novel opportunities for therapeutic intervention.     

New model systems for studying the evolutionary biology of aging: Crustacea

Progress in any area of biology has generally required work on a variety of organisms. This is true because particular species often have characteristics that make them especially useful for addressing specific questions. Recent progress in studying the evolutionary biology of senescence has been made through the use of new species, such asCaenorhabditis elegans andDrosophila melanogaster, because of the ease of working with them in the laboratory and because investigators have used theories for the evolution of aging as a basis for discovering the underlying mechanisms.I describe ways of finding new model systems for studying the evolutionary mechanisms of aging by combining the predictions of theory with existing information about the natural history of organisms that are well-suited to laboratory studies. Properties that make organisms favorable for laboratory studies include having a short generation time, high fecundity, small body size, and being easily cultured in a laboratory environment. It is also desirable to begin with natural populations that differ in their rate of aging. I present three scenarios and four groups of organisms which fulfill these requirements. The first two scenarios apply to well-documented differences in age/size specific predation among populations of guppies and microcrustacea. The third is differences among populations of fairy shrimp (anostraca) in habitat permanence. In all cases, there is an environmentla factor that is likely to select for changes in the life history, including aging, plus a target organism which is well-suited for laboratory studies of aging.     

A unified framework for connectionist systems

Pattern classification using connectionist (i.e., neural network) models is viewed within a statistical framework. A connectionist network's subjective beliefs about its statistical environment are derived. This belief structure is the network's subjective probability distribution. Stimulus classification is interpreted as computing the most probable response for a given stimulus with respect to the subjective probability distribution. Given the subjective probability distribution, learning algorithms can be analyzed and designed using maximum likelihood estimation techniques, and statistical tests can be developed to evaluate and compare network architectures. The framework is applicable to many connectionist networks including those of Hopfield (1982, 1984), Cohen and Grossberg (1983), Anderson et al. (1977), and Rumelhart et al. (1986b).     

A new era for evolutionary developmental biology in non-model organisms

正Since the publication of The Origin of Species by Charles Darwin, evolutionary biology has developed into a key discipline of biology and experienced several important expansions contributed by the sequential integration of Mendelian genetics, Morgan’s chromosome heredity mechanism, and Crick’s genetic central dogma theory. Especially in recent decades, next-generation sequencing has     

A framework for integrating thermal biology into fragmentation research

Habitat fragmentation changes thermal conditions in remnant patches, and thermal conditions strongly influence organism morphology, distribution, and activity patterns. However, few studies explore temperature as a mechanism driving ecological responses to fragmentation. Here we offer a conceptual framework that integrates thermal biology into fragmentation research to better understand individual, species, community, and ecosystem‐level responses to fragmentation. Specifically, the framework addresses how fragmentation changes temperature and how the effects of those temperature changes spread through the ecosystem, from organism response via thermal sensitivity, to changes in species distribution and activity patterns, to shifts in community structure following species' responses, and ultimately to changes in ecosystem functions. We place a strong emphasis on future research directions by outlining “Critical gaps” for each step of the framework. Empirical efforts to apply and test this framework promise new understanding of fragmentation's ecological consequences and new strategies for conservation in an increasingly fragmented and warmer world.     

Bridging the gap between developmental systems theory and evolutionary developmental biology

Many scientists and philosophers of science are troubled by the relative isolation of developmental from evolutionary biology. Reconciling the science of development with the science of heredity preoccupied a minority of biologists for much of the twentieth century, but these efforts were not corporately successful. Mainly in the past fifteen years, however, these previously dispersed integrating programmes have been themselves synthesized and so reinvigorated. Two of these more recent synthesizing endeavours are evolutionary developmental biology (EDB, or "evo-devo") and developmental systems theory (DST). While the former is a bourgeoning and scientifically well-respected biological discipline, the same cannot be said of DST, which is virtually unknown among biologists. In this review, we provide overviews of DST and EDB, summarize their key tenets, examine how they relate to one another and to the study of epigenetics, and survey the impact that DST and EDB have had (and in future should have) on biological theory and practice.     

A formal language for computational systems biology

The post-genomic era has opened new insights into the complex biochemical reaction systems present in the cell and has generated huge amount of information. The biological systems are highly complex and can overwhelm the numerically computable models. Therefore, models employing symbolical techniques might provide a faster insight. This paper presents some preliminary results and recent trends in the above direction. Specifically, it presents an overview of the main features of some formalisms and techniques from the field of specification languages for concurrency and mobility, which have been proposed to model and simulate the dynamics of the interaction of complex biological systems. The ultimate goal of these symbolic approaches is the modeling, analysis, simulation, and hopefully prediction of the behavior of biological systems (vs. biological components).     

Phylogeny and evolutionary biology

The phylogenetic system of Hennig, which was designed for classification of synchronous organisms, has only been adapted secondarily to total reconstruction of phylogeny. All fields of fundamental biology are related to the development of evolutionary theory. A better understanding of the origin of life requires new concepts of the historical geology of prebiological environment and new concepts of molecular genetics and biochemistry concerning ribonucleic acids as the initial units for the origin of life.     

Iconometrographics in evolutionary biology

The essential dialogue between Apollinian and Dionysiac poles required for the advance of music and art was likened to the scientific debate between «justifiers» and «innovators». The use of ratios and simple algorithms was indicted as being retrogressive in terms of modern microcomputer technology and iconometrographic models. Three examples were used to illustrate the approach in the resolution of complex data sets comparing samples: (1) 45,XO with a 46,XY controls, (2) sexual dimorphism in young adults and (3) Black and White Olympic athletes. The iconometrographic approach was proposed as a primary orientation in human biology, particularly in secular trend studies concerned with the recognition and assessment of complex evolutionary trends.