Genomic imprinting and the units of adaptation

Two guiding principles identify which biological entities are able to evolve adaptations. Williams'' principle holds that, in order for an entity to evolve adaptations, there must be selection between such entities. Maynard Smith''s principle holds that, in order for an entity to evolve adaptations, selection within such entities must be absent or negligible. However, although the kinship theory of genomic imprinting suggests that parent-of-origin-specific gene expression evolves as a consequence of natural selection acting between—rather than within—individuals, it evades adaptive interpretation at the individual level and is instead viewed as an outcome of an intragenomic conflict of interest between an individual''s genes. Here, I formalize the idea that natural selection drives intragenomic conflicts of interest between genes originating from different parents. Specifically, I establish mathematical links between the dynamics of natural selection and the idea of the gene as an intentional, inclusive-fitness-maximizing agent, and I clarify the role that information about parent of origin plays in mediating conflicts of interest between genes residing in the same genome. These results highlight that the suppression of divisive information may be as important as the suppression of lower levels of selection in maintaining the integrity of units of adaptation.     

Learning Natural Selection from the Site Frequency Spectrum

Genetic adaptation to external stimuli occurs through the combined action of mutation and selection. A central problem in genetics is to identify loci responsive to specific selective constraints. Many tests have been proposed to identify the genomic signatures of natural selection by quantifying the skew in the site frequency spectrum (SFS) under selection relative to neutrality. We build upon recent work that connects many of these tests under a common framework, by describing how selective sweeps affect the scaled SFS. We show that the specific skew depends on many attributes of the sweep, including the selection coefficient and the time under selection. Using supervised learning on extensive simulated data, we characterize the features of the scaled SFS that best separate different types of selective sweeps from neutrality. We develop a test, SFselect, that consistently outperforms many existing tests over a wide range of selective sweeps. We apply SFselect to polymorphism data from a laboratory evolution experiment of Drosophila melanogaster adapted to hypoxia and identify loci that strengthen the role of the Notch pathway in hypoxia tolerance, but were missed by previous approaches. We further apply our test to human data and identify regions that are in agreement with earlier studies, as well as many novel regions.     

Natural selection in chemical evolution

We propose that chemical evolution can take place by natural selection if a geophysical process is capable of heterotrophic formation of liposomes that grow at some base rate, divide by external agitation, and are subject to stochastic chemical avalanches, in the absence of nucleotides or any monomers capable of modular heredity. We model this process using a simple hill-climbing algorithm, and an artificial chemistry that is unique in exhibiting conservation of mass and energy in an open thermodynamic system. Selection at the liposome level results in the stabilization of rarely occurring molecular autocatalysts that either catalyse or are consumed in reactions that confer liposome level fitness; typically they contribute in parallel to an increasingly conserved intermediary metabolism. Loss of competing autocatalysts can sometimes be adaptive. Steady-state energy flux by the individual increases due to the energetic demands of growth, but also of memory, i.e. maintaining variations in the chemical network. Self-organizing principles such as those proposed by Kauffman, Fontana, and Morowitz have been hypothesized as an ordering principle in chemical evolution, rather than chemical evolution by natural selection. We reject those notions as either logically flawed or at best insufficient in the absence of natural selection. Finally, a finite population model without elitism shows the practical evolutionary constraints for achieving chemical evolution by natural selection in the lab.     

The definitions of information and meaning two possible boundaries between physics and biology.

The standard approach to the definition of the physical quantities has not produced satisfactory results with the concepts of information and meaning. In the case of information we have at least two unrelated definitions, while in the case of meaning we have no definition at all. Here it is shown that both information and meaning can be defined by operative procedures, but it is also pointed out that we need to recognize them as a new type of natural entities. They are not quantities (neither fundamental nor derived) because they cannot be measured, and they are not qualities because are not subjective features. Here it is proposed to call them nominable entities, i.e., entities which can be specified only by naming their components in their natural order. If the genetic code is not a linguistic metaphor but a reality, we must conclude that information and meaning are real natural entities, and now we must also conclude that they are not equivalent to the quantities and qualities of our present theoretical framework. This gives us two options. One is to extend the definition of physics and say that the list of its fundamental entities must include information and meaning. The other is to say that physics is the science of quantities only, and in this case information and meaning become the exclusive province of biology. The boundary between physics and biology, in short, is a matter of convention, but the existence of information and meaning is not. We can decide to study them in the framework of an extended physics or in a purely biological framework, but we cannot avoid studying them for what they are, i.e., as fundamental components of the fabric of Nature.     

An Experimental Framework for Generating Evolvable Chemical Systems in the Laboratory

Most experimental work on the origin of life has focused on either characterizing the chemical synthesis of particular biochemicals and their precursors or on designing simple chemical systems that manifest life-like properties such as self-propagation or adaptive evolution. Here we propose a new class of experiments, analogous to artificial ecosystem selection, where we select for spontaneously forming self-propagating chemical assemblages in the lab and then seek evidence of a response to that selection as a key indicator that life-like chemical systems have arisen. Since surfaces and surface metabolism likely played an important role in the origin of life, a key experimental challenge is to find conditions that foster nucleation and spread of chemical consortia on surfaces. We propose high-throughput screening of a diverse set of conditions in order to identify combinations of “food,” energy sources, and mineral surfaces that foster the emergence of surface-associated chemical consortia that are capable of adaptive evolution. Identification of such systems would greatly advance our understanding of the emergence of self-propagating entities and the onset of adaptive evolution during the origin of life.     

“Relevant similarity” and the causes of biological evolution: selection, fitness, and statistically abstractive explanations

Matthen (Philos Sci 76(4):464–487, 2009) argues that explanations of evolutionary change that appeal to natural selection are statistically abstractive explanations, explanations that ignore some possible explanatory partitions that in fact impact the outcome. This recognition highlights a difficulty with making selective analyses fully rigorous. Natural selection is not about the details of what happens to any particular organism, nor, by extension, to the details of what happens in any particular population. Since selective accounts focus on tendencies, those factors that impact the actual outcomes but do not impact the tendencies must be excluded. So, in order to properly exclude the factors irrelevant to selection, the relevant factors must be identified, and physical processes, environments, and populations individuated on the basis of being relevantly similar for the purposes of selective accounts. Natural selection, on this view, becomes in part a measure of the robustness of particular kinds of outcomes given variations over some kinds of inputs.     

Understanding Natural Selection: Essential Concepts and Common Misconceptions

Natural selection is one of the central mechanisms of evolutionary change and is the process responsible for the evolution of adaptive features. Without a working knowledge of natural selection, it is impossible to understand how or why living things have come to exhibit their diversity and complexity. An understanding of natural selection also is becoming increasingly relevant in practical contexts, including medicine, agriculture, and resource management. Unfortunately, studies indicate that natural selection is generally very poorly understood, even among many individuals with postsecondary biological education. This paper provides an overview of the basic process of natural selection, discusses the extent and possible causes of misunderstandings of the process, and presents a review of the most common misconceptions that must be corrected before a functional understanding of natural selection and adaptive evolution can be achieved.

Accommodating ontologies to biological reality--top-level categories of cumulative-constitutively organized material entities

Background

The Basic Formal Ontology (BFO) is a top-level formal foundational ontology for the biomedical domain. It has been developed with the purpose to serve as an ontologically consistent template for top-level categories of application oriented and domain reference ontologies within the Open Biological and Biomedical Ontologies Foundry (OBO). BFO is important for enabling OBO ontologies to facilitate in reliably communicating and managing data and metadata within and across biomedical databases. Following its intended single inheritance policy, BFO''s three top-level categories of material entity (i.e. ‘object’, ‘fiat object part’, ‘object aggregate’) must be exhaustive and mutually disjoint. We have shown elsewhere that for accommodating all types of constitutively organized material entities, BFO must be extended by additional categories of material entity.

Methodology/Principal Findings

Unfortunately, most biomedical material entities are cumulative-constitutively organized. We show that even the extended BFO does not exhaustively cover cumulative-constitutively organized material entities. We provide examples from biology and everyday life that demonstrate the necessity for ‘portion of matter’ as another material building block. This implies the necessity for further extending BFO by ‘portion of matter’ as well as three additional categories that possess portions of matter as aggregate components. These extensions are necessary if the basic assumption that all parts that share the same granularity level exhaustively sum to the whole should also apply to cumulative-constitutively organized material entities. By suggesting a notion of granular representation we provide a way to maintain the single inheritance principle when dealing with cumulative-constitutively organized material entities.

Conclusions/Significance

We suggest to extend BFO to incorporate additional categories of material entity and to rearrange its top-level material entity taxonomy. With these additions and the notion of granular representation, BFO would exhaustively cover all top-level types of material entities that application oriented ontologies may use as templates, while still maintaining the single inheritance principle.     

Characterizing the Evolutionary Path(s) to Early Homo

Numerous studies suggest that the transition from Australopithecus to Homo was characterized by evolutionary innovation, resulting in the emergence and coexistence of a diversity of forms. However, the evolutionary processes necessary to drive such a transition have not been examined. Here, we apply statistical tests developed from quantitative evolutionary theory to assess whether morphological differences among late australopith and early Homo species in Africa have been shaped by natural selection. Where selection is demonstrated, we identify aspects of morphology that were most likely under selective pressure, and determine the nature (type, rate) of that selection. Results demonstrate that selection must be invoked to explain an Au. africanus—Au. sediba—Homo transition, while transitions from late australopiths to various early Homo species that exclude Au. sediba can be achieved through drift alone. Rate tests indicate that selection is largely directional, acting to rapidly differentiate these taxa. Reconstructions of patterns of directional selection needed to drive the Au. africanus—Au. sediba—Homo transition suggest that selection would have affected all regions of the skull. These results may indicate that an evolutionary path to Homo without Au. sediba is the simpler path and/or provide evidence that this pathway involved more reliance on cultural adaptations to cope with environmental change.     

Three-dimensional Biomimetic Technology: Novel Biorubber Creates Defined Micro- and Macro-scale Architectures in Collagen Hydrogels

Tissue scaffolds play a crucial role in the tissue regeneration process. The ideal scaffold must fulfill several requirements such as having proper composition, targeted modulus, and well-defined architectural features. Biomaterials that recapitulate the intrinsic architecture of in vivo tissue are vital for studying diseases as well as to facilitate the regeneration of lost and malformed soft tissue. A novel biofabrication technique was developed which combines state of the art imaging, three-dimensional (3D) printing, and selective enzymatic activity to create a new generation of biomaterials for research and clinical application. The developed material, Bovine Serum Albumin rubber, is reaction injected into a mold that upholds specific geometrical features. This sacrificial material allows the adequate transfer of architectural features to a natural scaffold material. The prototype consists of a 3D collagen scaffold with 4 and 3 mm channels that represent a branched architecture. This paper emphasizes the use of this biofabrication technique for the generation of natural constructs. This protocol utilizes a computer-aided software (CAD) to manufacture a solid mold which will be reaction injected with BSA rubber followed by the enzymatic digestion of the rubber, leaving its architectural features within the scaffold material.     

What is hierarchical selection?

It has been proposed that natural selection occurs on a hierarchy of levels, of which the organismic level is neither the top nor the bottom. This hypothesis leads to the following practical problem: in general, how does one tell if a given phenomenon is a result of selection on level X or level Y. How does one tell what the units of selection actually are? It is convenient to assume that a unit of selection may be defined as a type of entity for which there exists, among all entities on the same “level” as that entity, an additive component of variance for some specific component F of fitness which does not appear as an additive component of variance in any decomposition of this F among entities at any lower level. But such a definition implicitly assumes that if f(x, y) depends nonadditively on its arguments, there must be interaction between the quantities which x and y represent. This assumption is incorrect. And one cannot avoid this error by speaking of “transformability to additivity” instead of merely “additivity”. A general mathematical formulation of the concepts of interaction and non-interaction is proposed, followed by a correspondingly modified approach to the definition of a unit of selection. The practical difficulty of verifying the presence of hierarchical selection is discussed.     

Yeast competence for exogenous DNA uptake: towards understanding its genetic component

The demonstration of spontaneous yeast competence shows that artificial transformation rests on naturally occurring cellular processes. Such natural competence is either biologically mediated or environmentally induced. For instance, wild yeast might be transformed through conjugation by cell-to-cell contact mediated either by Escherichia coli or Agrobacterium tumefaciens. Moreover, natural competence can be enhanced by mechanical and physiological mechanisms. On the other hand, artificial yeast competence is usually achieved by biological, chemical and physical manipulations. These eliminate or weaken natural obstacles blocking the way of the transforming DNA in order to mitigate its entrance into the cell (biological and chemical approach) or simply to bridge it by either electrical or biolistic force (physical). Thus yeast competence is controlled by intrinsic (genetic) and external (environmental) factors. Both intrinsic and external parameters affecting yeast competence were scrutinized leading to the identification of genes and biological processes participating in the phenomenon. Therefore natural yeast competence is a complex, quantitative genetic trait which may have allowed yeast to better adapt over evolutionary times.     

New V1a receptor antagonist. Part 2. Identification and optimization of triazolobenzazepines

Solid preclinical evidence links vasopressin to social behavior in animals, so, extensive work has been initiated to find new vasopressin V1a receptor antagonists which can improve deteriorated social behavior in humans and can treat the core symptoms of autistic behavior, as well. Our aim was to identify new chemical entities with antagonizing effects on vasopressin V1a receptors. Continuing our previous work, we found an in vitro and in vivo orally active V1a selective antagonist molecule (40) among [1,2,4]triazolo[4,3-a][1]benzazepines.     

Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features

OBJECTIVES: To analyze the distant metastasis possibility based on computed tomography (CT) radiomic features in patients with lung cancer. METHODS: This was a retrospective analysis of 348 patients with lung cancer enrolled between 2014 and February 2015. A feature set containing clinical features and 485 radiomic features was extracted from the pretherapy CT images. Feature selection via concave minimization (FSV) was used to select effective features. A support vector machine (SVM) was used to evaluate the predictive ability of each feature. RESULTS: Four radiomic features and three clinical features were obtained by FSV feature selection. Classification accuracy by the proposed SVM with SGD method was 71.02%, and the area under the curve was 72.84% with only the radiomic features extracted from CT. After the addition of clinical features, 89.09% can be achieved. CONCLUSION: The radiomic features of the pretherapy CT images may be used as predictors of distant metastasis. And it also can be used in combination with the patient's gender and tumor T and N phase information to diagnose the possibility of distant metastasis in lung cancer.     

Biology with information and meaning

It is shown that information and meaning can be defined by operative procedures, and that we need to recognize them as new types of natural entities. They are not quantities (neither fundamental nor derived) because they cannot be measured, and they are not qualities because they are not subjective features. Here it is proposed to call them nominable entities, i.e., entities which can be specified only by naming their components in their natural order.     

Evaluation of local field potential signals in decoding of visual attention

In the field of brain research, attention as one of the main issues in cognitive neuroscience is an important mechanism to be studied. The complicated structure of the brain cannot process all the information it receives at any moment. Attention, in fact, is considered as a possible useful mechanism in which brain concentrates on the processing of important information which is required at any certain moment. The main goal of this study is decoding the location of visual attention from local field potential signals recorded from medial temporal (MT) area of a macaque monkey. To this end, feature extraction and feature selection are applied in both the time and the frequency domains. After applying feature extraction methods such as the short time Fourier transform, continuous wavelet transform (CWT), and wavelet energy (scalogram), feature selection methods are evaluated. Feature selection methods used here are T-test, Entropy, receiver operating characteristic, and Bhattacharyya. Subsequently, different classifiers are utilized in order to decode the location of visual attention. At last, the performances of the employed classifiers are compared. The results show that the maximum information about the visual attention in area MT exists in the low frequency features. Interestingly, low frequency features over all the time-axis and all of the frequency features at the initial time interval in the spectrogram domain contain the most valuable information related to the decoding of spatial attention. In the CWT and scalogram domains, this information exists in the low frequency features at the initial time interval. Furthermore, high performances are obtained for these features in both the time and the frequency domains. Among different employed classifiers, the best achieved performance which is about 84.5 % belongs to the K-nearest neighbor classifier combined with the T-test method for feature selection in the time domain. Additionally, the best achieved result (82.9 %) is related to the spectrogram with the least number of selected features as large as 200 features using the T-test method and SVM classifier in the time−frequency domain.     

Neurons in area V4 of the macaque translate attended visual features into behaviorally relevant categories

Neural processing at most stages of the primate visual system is modulated by selective attention, such that behaviorally relevant information is emphasized at the expenses of irrelevant, potentially distracting information. The form of attention best understood at the cellular level is when stimuli at a given location in the visual field must be selected (space-based attention). In contrast, fewer single-unit recording studies have so far explored the cellular mechanisms of attention operating on individual stimulus features, specifically when one feature (e.g., color) of an object must guide behavioral responses while a second feature (e.g., shape) of the same object is potentially interfering and therefore must be ignored. Here we show that activity of neurons in macaque area V4 can underlie the selection of elemental object features and their "translation" into a categorical format that can directly contribute to the control of the animal's behavior.     

On the Crucial Stages in the Origin of Animate Matter

Theories of the origin of life have proposed hypotheses to link inanimate to animate matter. The theory proposed here derived the crucial stages in the origin of animate matter directly from the basic properties of inanimate matter. It asked what were the general characteristics of the link, rather than what might have been its chemical details. Life and its origin are shown to be one continuous physicochemical process of replication, random variation, and natural selection. Since life exists here and now, animate properties must have been initiated in the past somewhere. According to the theory, life originated from an as yet unknown elementary autocatalyst which occurred spontaneously, then replicated autocatalytically. As it multiplied to macroscopic abundance, its replicas gradually exhausted their reactants. Random chemical drift initiated diversity among autocatalysts. Diversity led to competition. Competition and depletion of reactants slowed down the rates of net replication of the autocatalysts. Some reached negative rates and became extinct, while those which stayed positive ``survived.' Thus chemical natural selection appeared, the first step in the transition from inanimate to animate matter. It initiated the first animate property, fitness, i.e., the capacity to adapt to the environment and to survive. As the environment was depleted of reactants, it was enriched with sequels—namely, with decomposition products and all other products which accompany autocatalysis. The changing environment exerted a selective pressure on autocatalysts to replace dwindling reactants by accumulating sequels. Sequels that were incorporated into the autocatalytic process became internal components of complex autocatalytic systems. Primitive forms of metabolism and organization were thus initiated. They evolved further by the same mechanism to ever higher levels of complexity, such as homochirality (handedness) and membranal enclosure. Subsequent evolution by the same mechanism generated cellular metabolism, cell division, information carriers, and a genetic code. Theories of self-organization without natural selection are refuted. Received: 29 March 1996 / Accepted: 30 May 1996