On the integrated frameworks of species concepts: Mayden’s hierarchy of species concepts and de Queiroz’s unified concept of species

Richard L. Mayden and Kevin de Queiroz have devised and developed ‘a hierarchy of species concepts’ and ‘a unified species concept’, respectively. Although their integrated frameworks of species concepts are rather different as to how to integrate the diverse modern concepts of species, the end result is that they are likely to agree on species recognition in nature, because they virtually share the same major components (i.e. evolutionary or lineage concept of species; same way of delimiting species), and have the same important consequences. Both the hierarchical and unified frameworks, however, are interpreted to have shortcoming regarding the way of integrating the modern species concepts. I reformulate these ideas into a framework of species concepts as follows: It treats the idea of species as population‐level evolutionary lineages (sensu Wiley 1978 ) as the concept for species category, and it adopts the contingent biological properties of species (e.g. internal reproductive isolation, diagnosability, monophyly) as operational criteria in delimiting species. I also suggest that existing and revised versions of the integrated framework of species concepts all are not new species concepts, but versions of the evolutionary species concept, because they treat the evolutionary (or lineage) species concept as the concept for species category.     

Unpacking the species conundrum: philosophy,practice and a way forward

The history of ecology and evolutionary biology is rife with attempts to define and delimit species. However, there has been confusion between concepts and criteria, which has led to discussion, debate, and conflict, eventually leading to lack of consistency in delimitation. Here, we provide a broad review of species concepts, a clarification of category versus concept, an account of the general lineage concept (GLC), and finally a way forward for species discovery and delimitation. Historically, species were considered as varieties bound together by reproduction. After over 200 years of uncertainty, Mayr attempted to bring coherence to the definition of species through the biological species concept (BSC). This has, however, received much criticism, and the last half century has spawned at least 20 other concepts. A central philosophical problem is that concepts treat species as ‘individuals’ while the criteria for categorization treats them as ‘classes’. While not getting away from this problem entirely, the GLC attempts to provide a framework where lineage divergence is influenced by a number of different factors (and correlated to different traits) which relate to the different species concepts. We also introduce an ‘inclusive’ probabilistic approach for understanding and delimiting species. Finally, we provide a Wallacean (geography related) approach to the Linnaean problem of identifying and delimiting species, particularly for cases of allopatric divergence, and map this to the GLC. Going one step further, we take a morphometric terrain approach to visualizing and understanding differences between lineages. In summary, we argue that while generalized frameworks may work well for concepts of what species are, plurality and ‘inclusive’ probabilistic approaches may work best for delimitation.     

The hologenome concept: we need to incorporate function

Are we in the midst of a paradigm change in biology and have animals and plants lost their individuality, i.e., are even so-called ‘typical’ organisms no longer organisms in their own right? Is the study of the holobiont—host plus its symbiotic microorganisms—no longer optional, but rather an obligatory path that must be taken for a comprehensive understanding of the ecology and evolution of the individual components that make up a holobiont? Or are associated microbes merely a component of their host’s environment, and the holobiont concept is just a beautiful idea that does not add much or anything to our understanding of evolution? This article explores different aspects of the concept of the holobiont. We focus on the aspect of functional integration, a central holobiont property, which is only rarely considered thoroughly. We conclude that the holobiont comes in degrees, i.e., we regard the property of being a holobiont as a continuous trait that we term holobiontness, and that holobiontness is differentiated in several dimensions. Although the holobiont represents yet another level of selection (different from classical individual or group selection because it acts on a system that is composed of multiple species), it depends on the grade of functional integration whether or not the holobiont concept helps to cast light on the various degrees of interactions between symbiotic partners.     

The reconstruction principle

The theory of epigenesis is the undisputed paradigm of embryology, and it is still based on the classical concept proposed by Aristotle: the idea that embryonic development is a generation of structures which takes place according to a design--today we say a set of instructions--already present in the fertilized egg. This is a doctrine which can be referred to as 'pre-information', since it claims the preexistence of information exactly as the old theory of preformation claimed the preexistence of form. Here, however, it is shown that a more general version of epigenesis can be held, because of a new principle which states that it is mathematically possible to obtain not only a convergent generation of form, or structure, but also a convergent generation of information.     

Gene expression and the concept of the phenotype

While the definition of the 'genotype' has undergone dramatic changes in the transition from classical to molecular genetics, the definition of the 'phenotype' has remained for a long time within the classical framework. In addition, while the notion of the genotype has received significant attention from philosophers of biology, the notion of the phenotype has not. Recent developments in the technology of measuring gene-expression levels have made it possible to conceive of phenotypic traits in terms of levels of gene expression. We demonstrate that not only has this become possible but it has also become an actual practice. This suggests a significant change in our conception of the phenotype: as in the case of the 'genotype', phenotypes can now be conceived in quantitative and measurable terms on a comprehensive molecular level. We discuss in what sense gene expression profiles can be regarded as phenotypic traits and whether these traits are better described as a novel concept of phenotype or as an extension of the classical concept. We argue for an extension of the classical concept and call for an examination of the type of extension involved.     

Autopoiesis 40 years Later. A Review and a Reformulation

The concept of autopoiesis was proposed 40 years ago as a definition of a living being, with the aim of providing a unifying concept for biology. The concept has also been extended to the theory of knowledge and to different areas of the social and behavioral sciences. Given some ambiguities of the original definitions of autopoiesis, the concept has been criticized and has been interpreted in diverse and even contradictory ways, which has prevented its integration into the biological sciences where it originated. Here I present a critical review and conceptual analysis of the definition of autopoiesis, and propose a new definition that is more precise, clear, and concise than the original ones. I argue that the difficulty in understanding the term lies in its refined conceptual subtlety and not, as has been claimed by some authors, because it is a vacuous, trivial or very complex concept. I also relate the concept of autopoiesis to the concepts of closed systems, boundaries, homeostasis, self-reproduction, causal circularity, organization and multicellularity. I show that under my proposed definition the concept of a molecular autopoietic system is a good demarcation criterion of a living being, allowing its general integration into the biological sciences and enhancing its interdisciplinary use.     

Complexity of automated gene annotation

Describing the determinants of robustness of biological systems has become one of the central questions in systems biology. Despite the increasing research efforts, it has proven difficult to arrive at a unifying definition for this important concept. We argue that this is due to the multifaceted nature of the concept of robustness and the possibility to formally capture it at different levels of systemic formalisms (e.g., topology and dynamic behavior). Here we provide a comprehensive review of the existing definitions of robustness pertaining to metabolic networks. As kinetic approaches have been excellently reviewed elsewhere, we focus on definitions of robustness proposed within graph-theoretic and constraint-based formalisms.     

A generic rate law for surface-active enzymes

Many biochemical reactions are confined to interfaces, such as membranes or cell walls. Despite their importance, no canonical rate laws describing the kinetics of surface-active enzymes exist. Combining the approach chosen by Michaelis and Menten 100 years ago with concepts from surface chemical physics, we here present an approach to derive generic rate laws of enzymatic processes at surfaces. We illustrate this by a simple reversible conversion on a surface to stress key differences to the classical case in solution. The available area function, a concept from surface physics which enters the rate law, covers different models of adsorption and presents a unifying perspective on saturation effects and competition between enzymes. A remarkable implication is the direct dependence of the rate of a given enzyme on all other enzymatic species able to bind at the surface. The generic approach highlights general principles of the kinetics of surface-active enzymes and allows to build consistent mathematical models of more complex pathways involving reactions at interfaces.     

Trophic specialisation in a predatory group: the case of prey‐specialised spiders (Araneae)

Predators appear to be less frequently specialised (i.e. adapted to restricted diet) on their prey than herbivores, parasites or parasitoids. Here, we critically evaluate contemporary evolutionary hypotheses that might be used to explain the evolution of specialised foraging in predators. We propose a unifying concept within which we define four types of trophic categories using ecological (diet breadth) and evolutionary (degree of adaptations) contexts. We use data on spiders (Araneae), the most diversified order of terrestrial predators, to assess applicability of frameworks and evolutionary concepts related to trophic specialisation. The majority of spider species are euryphagous but a few have a restricted prey range, i.e. they are stenophagous. We provide a detailed overview of specialisation on different prey types, namely spiders, crustaceans, moths, dipterans, ants, and termites. We also review the available evidence for trophic adaptations, classified into four categories: behavioural, morphological, venomic and metabolic. Finally, we discuss the ecological and evolutionary implications of trophic specialisation and propose avenues for future research.     

Genes: philosophical analyses put to the test

This paper describes one complete and one ongoing empirical study in which philosophical analyses of the concept of the gene were operationalized and tested against questionnaire data obtained from working biologists to determine whether and when biologists conceive genes in the ways suggested. These studies throw light on how different gene concepts contribute to biological research. Their aim is not to arrive at one or more correct 'definitions' of the gene, but rather to map out the variation in the gene concept and to explore its causes and its effects.     

Role of 17beta-estradiol administration on insulin sensitivity in the rat: implications for the insulin receptor

The role of 17beta-estradiol in the early steps of insulin action is only partially known, although its effect on glucose homeostasis has been reported. In this paper, we attempt to prove the influence of 17beta-estradiol on the insulin receptor of ovariectomized rats treated with different hormonal doses. Our results show that high doses of estradiol impair insulin sensitivity while low doses improve it. We think that these results are the consequence of changes at a molecular level, because high doses of estradiol produced lower expression of the insulin receptor gene, lower content of this receptor in target tissues, and lower phosphorylation of insulin receptor in these tissues. However, low doses of estradiol seem to produce just the opposite. The possible existence of consensus response elements in the insulin receptor gene promoter to estradiol could be controlling the expression of this gene, this control being dose and timing dependent. Moreover, we cannot discard a possible effect of estradiol on the activity of protein tyrosine phosphatases, and therefore, on the activity of the insulin receptor. These new findings improve knowledge about the possible risk for insulin resistance in women taking oral contraceptives or receiving hormonal replacement therapy around the menopause, but could also open the door towards the possible utilization of 17beta-estradiol in some diabetes cases.     

AGRA: analysis of gene ranking algorithms

Often, the most informative genes have to be selected from different gene sets and several computer gene ranking algorithms have been developed to cope with the problem. To help researchers decide which algorithm to use, we developed the analysis of gene ranking algorithms (AGRA) system that offers a novel technique for comparing ranked lists of genes. The most important feature of AGRA is that no previous knowledge of gene ranking algorithms is needed for their comparison. Using the text mining system finding-associated concepts with text analysis. AGRA defines what we call biomedical concept space (BCS) for each gene list and offers a comparison of the gene lists in six different BCS categories. The uploaded gene lists can be compared using two different methods. In the first method, the overlap between each pair of two gene lists of BCSs is calculated. The second method offers a text field where a specific biomedical concept can be entered. AGRA searches for this concept in each gene lists' BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it. AVAILABILITY AND IMPLEMENTATION: Available at http://agra.fzv.uni-mb.si/, implemented in Java and running on the Glassfish server. CONTACT: simon.kocbek@uni-mb.si.     

A look to future directions in gene therapy research for monogenic diseases

The concept of gene therapy has long appealed to biomedical researchers and clinicians because it promised to treat certain diseases at their origins. In the last several years, there have been several trials in which patients have benefited from gene therapy protocols. This progress, however, has revealed important problems, including the problem of insertional oncogenesis. In this review, which focuses on monogenic diseases, we discuss the problem of insertional oncogenesis and identify areas for future research, such as developing more quantitative assays for risk and efficacy, and ways of minimizing the genotoxic effects of gene therapy protocols, which will be important if gene therapy is to fulfill its conceptual promise.     

Simultaneous delimitation of species and quantification of interspecific hybridization in Amazonian peacock cichlids (genus Cichla) using multi-locus data

ABSTRACT: BACKGROUND: Introgression likely plays a significant role in evolution, but understanding the extent and consequences of this process requires a clear identification of species boundaries in each focal group. The delimitation of species, however, is a contentious endeavor. This is true not only because of the inadequacy of current tools to identify species lineages, but also because of the inherent ambiguity between natural populations and species paradigms. The result has been a debate about the supremacy of various species concepts and criteria. Here, we utilized multiple separate sources of molecular data, mtDNA, nuclear sequences, and microsatellites, to delimit species under a polytypic species concept (PTSC) and estimate the frequency and genomic extent of introgression in a Neotropical genus of cichlid fishes (Cichla). We compared our inferences of species boundaries and introgression under this paradigm to those when species are identified under a diagnostic species concept (DSC). RESULTS: We find that, based on extensive molecular data and an inclusive species concept, 8 separate biological entities should be recognized rather than the 15 described species of Cichla. Under the PTSC, fewer individuals are expected to exhibit hybrid ancestry than under the DSC (~2% vs. ~12%), but more of the species exhibit introgression from at least one other species (75% vs. 60%). Under either species concept, the phylogenetic breadth of introgression in this group is notable, with both sister species and species from different major mtDNA clades exhibiting introgression. CONCLUSIONS: Introgression was observed to be a widespread phenomenon for delimited species in this group. While several instances of introgressive hybridization were observed in anthropogenically altered habitats, most were found in undisturbed natural habitats, suggesting that introgression is a natural but ephemeral part of the evolution of many tropical species. Nevertheless, even transient introgression may facilitate an increase in genetic diversity or transfer of adaptive mutations that have important consequences in the evolution of tropical biodiversity.     

Wohin steuert die Taxonomie?

In taxonomy, the organisms may be grouped into species according to different criteria, e.g. according to phenotypic and genetic characteristics or according to reproductive connections. In nature, there is no universal unit that can be called “species”, because different biological mechanisms are responsible for how individuals are grouped together or delimitated from each other. Different species concepts do not necessarily define the same entity existing in nature. One and the same individual can be assigned to different species depending on the species concept. In the last two decades, the barcode taxonomy has played a dominant role. A major advantage of the barcode taxonomy is the time‐saving automated mass detection of species without the need for taxonomically trained experts. Especially in evolutionarily young species, however, there are considerable discrepancies between the classification according to the barcode concept and the classification according to reproductive communities or phenotypic characteristics. The barcode species must therefore be understood as a species in addition to other species concepts.     

A conceptual framework for the evolution of ecological specialisation

Ecology Letters (2011) 14: 841-851 ABSTRACT: Ecological specialisation concerns all species and underlies many major ecological and evolutionary patterns. Yet its status as a unifying concept is not always appreciated because of its similarity to concepts of the niche, the many levels of biological phenomena to which it applies, and the complexity of the mechanisms influencing it. The evolution of specialisation requires the coupling of constraints on adaptive evolution with covariation of genotype and environmental performance. This covariation itself depends upon organismal properties such as dispersal behaviour and life history and complexity in the environment stemming from factors such as species interactions and spatio-temporal heterogeneity in resources. Here, we develop a view on specialisation that integrates across the range of biological phenomena with the goal of developing a more predictive conceptual framework that specifically accounts for the importance of biotic complexity and coevolutionary events.     

Prediction of protein function from protein sequence and structure

The sequence of a genome contains the plans of the possible life of an organism, but implementation of genetic information depends on the functions of the proteins and nucleic acids that it encodes. Many individual proteins of known sequence and structure present challenges to the understanding of their function. In particular, a number of genes responsible for diseases have been identified but their specific functions are unknown. Whole-genome sequencing projects are a major source of proteins of unknown function. Annotation of a genome involves assignment of functions to gene products, in most cases on the basis of amino-acid sequence alone. 3D structure can aid the assignment of function, motivating the challenge of structural genomics projects to make structural information available for novel uncharacterized proteins. Structure-based identification of homologues often succeeds where sequence-alone-based methods fail, because in many cases evolution retains the folding pattern long after sequence similarity becomes undetectable. Nevertheless, prediction of protein function from sequence and structure is a difficult problem, because homologous proteins often have different functions. Many methods of function prediction rely on identifying similarity in sequence and/or structure between a protein of unknown function and one or more well-understood proteins. Alternative methods include inferring conservation patterns in members of a functionally uncharacterized family for which many sequences and structures are known. However, these inferences are tenuous. Such methods provide reasonable guesses at function, but are far from foolproof. It is therefore fortunate that the development of whole-organism approaches and comparative genomics permits other approaches to function prediction when the data are available. These include the use of protein-protein interaction patterns, and correlations between occurrences of related proteins in different organisms, as indicators of functional properties. Even if it is possible to ascribe a particular function to a gene product, the protein may have multiple functions. A fundamental problem is that function is in many cases an ill-defined concept. In this article we review the state of the art in function prediction and describe some of the underlying difficulties and successes.     

Canonical wnt signaling regulates hematopoiesis in a dosage-dependent fashion

Canonical Wnt signaling has been implicated in the regulation of hematopoiesis. By employing a Wnt-reporter mouse, we observed that Wnt signaling is differentially activated during hematopoiesis, suggesting an important regulatory role for specific Wnt signaling levels. To investigate whether canonical Wnt signaling regulates hematopoiesis in?a dosage-dependent fashion, we analyzed the effect of different mutations in the Adenomatous polyposis coli gene (Apc), a negative modulator of the canonical Wnt pathway. By combining different targeted hypomorphic alleles and a conditional deletion allele of Apc, a gradient of five different Wnt signaling levels was obtained in?vivo. We here show that different, lineage-specific Wnt dosages regulate hematopoietic stem cells (HSCs), myeloid precursors, and T lymphoid precursors during hematopoiesis. Differential, lineage-specific optimal Wnt dosages provide a unifying concept that explains the differences reported among inducible gain-of-function approaches, leading to either HSC expansion or depletion of the HSC pool.     

Missing value imputation for gene expression data: computational techniques to recover missing data from available information

Microarray gene expression data generally suffers from missing value problem due to a variety of experimental reasons. Since the missing data points can adversely affect downstream analysis, many algorithms have been proposed to impute missing values. In this survey, we provide a comprehensive review of existing missing value imputation algorithms, focusing on their underlying algorithmic techniques and how they utilize local or global information from within the data, or their use of domain knowledge during imputation. In addition, we describe how the imputation results can be validated and the different ways to assess the performance of different imputation algorithms, as well as a discussion on some possible future research directions. It is hoped that this review will give the readers a good understanding of the current development in this field and inspire them to come up with the next generation of imputation algorithms.     

Literature-aided interpretation of gene expression data with the weighted global test

Most methods for the interpretation of gene expression profiling experiments rely on the categorization of genes, as provided by the Gene Ontology (GO) and pathway databases. Due to the manual curation process, such databases are never up-to-date and tend to be limited in focus and coverage. Automated literature mining tools provide an attractive, alternative approach. We review how they can be employed for the interpretation of gene expression profiling experiments. We illustrate that their comprehensive scope aids the interpretation of data from domains poorly covered by GO or alternative databases, and allows for the linking of gene expression with diseases, drugs, tissues and other types of concepts. A framework for proper statistical evaluation of the associations between gene expression values and literature concepts was lacking and is now implemented in a weighted extension of global test. The weights are the literature association scores and reflect the importance of a gene for the concept of interest. In a direct comparison with classical GO-based gene sets, we show that use of literature-based associations results in the identification of much more specific GO categories. We demonstrate the possibilities for linking of gene expression data to patient survival in breast cancer and the action and metabolism of drugs. Coupling with online literature mining tools ensures transparency and allows further study of the identified associations. Literature mining tools are therefore powerful additions to the toolbox for the interpretation of high-throughput genomics data.