Biological Hierarchy Research Articles

Psychoneurosis beyond Oedipus: neurophysiology, drive conflict, and the resolution of emotional trauma

The concept of plasticity infused regenerative approaches to brain science in Switzerland in the mid-twentieth century, shaping a holistic tradition prominent among Zurich’s psychiatrists and neurologists. From 1910 to about 1950, they sought to objectify the dynamic unconscious using a psychobiological approach to mental pathology pioneered by the neuroanatomists August Forel and Constantin von Monakow. Little scholarship, however, has explored this tradition. Both Forel and Monakow influenced Rudolf Brun, a Zurich neurologist and ant expert, who championed parallels between biological conflicts measured in social insects and Sigmund Freud’s drive energetics. Brun’s concept of drive conflict integrated Richard Semon’s theory of plastic heredity as “species memory” with a revision of Monakow to explain mental pathology in the brain. Through them, he proposed the neuropathology underlying Freud’s “genuine” psychoneuroses: those caused by unconscious memories of traumatic experience. This paper uses primary historical sources from the Swiss scientific literature to demonstrate that (1) Brun combined Semon’s plastic heredity, Cannon’s physiology and Pavlov’s conditional reflex to objectify Freud’s dynamic unconscious; and (2) though he rejected Monakow’s teleology, Brun’s holistic mind-body approach owed much to Monakow’s theory of emotions and pathology manifest in the brain. Brun elaborated Monakow’s view that psychopathology occurs as unconscious drive conflicts produce neurotoxicity, enabling excess hormones to disrupt the brain’s protective filtering system. Brun’s ant experiments confirmed evolutionary “laws” governing drive conflict and framed the neuro-energetics underlying the resolution of repressed emotional trauma. Tests pitted conflicts between social drives and those serving self-interest. Through them, Brun extended moral conflict beyond the Oedipal domain of psychoanalysis to encompass conflicts in a biological hierarchy of drives. This drive-based account of conscience explored neural pathways reaching back from the cortex to the body, so enabling traumatic memories to generate psychoneuroses. Plasticity could then justify the use of psychotherapy to reverse these pathogenic connections. Brun’s example demonstrates both the significance of Semon’s theory of heredity for objective accounts of the unconscious mind in Central Europe and the hidden legacy of Monakow’s neuroendocrine holism. Brun combined that legacy with objective evidence and Zurich’s emphasis on plasticity to endorse—somewhat paradoxically—the reversal of psychoneuroses in the brain.

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k1 (DNA accretion rate) ranged from 0.005±0.003 and for α (constant for energy for maintenance requirement) 0.134±0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k1 and α. QTLs within genomic regions mapped for k1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

Metabolic systems biology: a brief primer.

In the early to mid-20th century, reductionism as a concept in biology was challenged by key thinkers, including Ludwig von Bertalanffy. He proposed that living organisms were specific examples of complex systems and, as such, they should display characteristics including hierarchical organisation and emergent behaviour. Yet the true study of complete biological systems (for example, metabolism) was not possible until technological advances that occurred 60years later. Technology now exists that permits the measurement of complete levels of the biological hierarchy, for example the genome and transcriptome. The complexity and scale of these data require computational models for their interpretation. The combination of these - systems thinking, high-dimensional data and computation - defines systems biology, typically accompanied by some notion of iterative model refinement. Only sequencing-based technologies, however, offer full coverage. Other 'omics' platforms trade coverage for sensitivity, although the densely connected nature of biological networks suggests that full coverage may not be necessary. Systems biology models are often characterised as either 'bottom-up' (mechanistic) or 'top-down' (statistical). This distinction can mislead, as all models rely on data and all are, to some degree, 'middle-out'. Systems biology has matured as a discipline, and its methods are commonplace in many laboratories. However, many challenges remain, especially those related to large-scale data integration.

Biologically inspired survival analysis based on integrating gene expression as mediator with genomic variants

Accurately linking cancer molecular profiling with survival can lead to improvements in the clinical management of cancer. However, existing survival analysis relies on statistical evidence from a single level of data, without paying much attention to the integration of interacting multi-level data and the underlying biology. Advances in genomic techniques provide unprecedented power of characterizing the cancer tissue in a more complete manner than before, offering the opportunity to design biologically informed and integrative approaches for survival data analysis. Human cancer is characterized by somatic copy number alternation and unique gene expression profiles. However, it remains largely unclear how to integrate the gene expression and genetic variant data to achieve a better prediction of patient survival and an improved understanding of disease progression. Consistent with the biological hierarchy from DNA to RNA, we prioritize each survival-relevant feature with two separate scores, predictive and mechanistic. For mRNA expression levels, predictive features are those mRNAs whose variation in expression levels is associated with survival outcome, and mechanistic features are those mRNAs whose variation in expression levels is associated with genomic variants. Further, we simultaneously integrate information from both the predictive model and the mechanistic model through our new approach, GEMPS (Gene Expression as a Mediator for Predicting Survival). Applied on two cancer types (ovarian and glioblastoma multiforme), our method achieved better prediction power (p-value: 6.18E−03–5.15E−11) than peer methods (GE.CNAs and GE.CNAs. Lasso). Gene set enrichment analysis confirms that the genes utilized for the final survival analysis are biologically important and relevant.

The levels of selection debate: taking into account existing empirical evidence

Por más de cinco décadas la visión neo-darwinista dominante de la selección natural es que esta actúa únicamente a nivel génico y organísmico, pero la ignorada evidencia empírica de selección multinivel ocurriendo en la naturaleza obtenida durante los últimos cincuenta años no es consecuente. Un largo intercambio de argumentaciones matemáticas y teóricas sobre los niveles en los que actúa la selección natural constituye lo que se denomina como el “debate de los niveles de selección”. La gran cantidad de evidencia empírica, estudiada mediante métodos de genética cuantitativa, específicamente el análisis contextual, indica que la selección natural actúa en niveles de la jerarquía biológica por encima y por debajo del nivel del gen y organismo, desde el nivel molecular hasta el ecosistémico, apoyando así lo que se denomina la teoría de selección multinivel. Más allá de argumentos teóricos, si se examina cuidadosamente la evidencia empírica de selección multinivel y los resultados del análisis contextual, se resuelve de forma sencilla el debate de los niveles de selección: la selección natural ocurre en la naturaleza en diferentes niveles de la jerarquía biológica. Este texto ofrece una revisión general de dicha evidencia empírica.

Immune competence assessment in marine medaka (Orzyias melastigma)-a holistic approach for immunotoxicology.

Many anthropogenic pollutants in coastal marine environments can induce immune impairments in wild fish and reduce their survival fitness. There is a pressing need to establish sensitive and high throughput in vivo tools to systematically evaluate the immunosuppressive effects of contaminants in marine teleosts. This study reviewed a battery of in vivo immune function detection technologies established for different biological hierarchies at molecular (immune function pathways and genes by next generation sequencing (NGS)), cellular (leukocytes profiles by flow cytometry), tissues/organ system (whole adult histo-array), and organism (host resistance assays (HRAs)) levels, to assess the immune competence of marine medaka Oryzias melastigma. This approach enables a holistic assessment of fish immune competence under different chemical exposure or environmental scenarios. The data obtained will also be useful to unravel the underlying immunotoxic mechanisms. Intriguingly, NGS analysis of hepatic immune gene expression profiles (male > female) are in support of the bacterial HRA findings, in which infection-induced mortality was consistently higher in females than in males. As such, reproductive stages and gender-specific responses must be taken into consideration when assessing the risk of immunotoxicants in the aquatic environment. The distinct phenotypic sexual dimorphism and short generation time (3months) of marine medaka offer additional advantages for sex-related immunotoxicological investigation.

Exploring intraspecific climatic niche conservatism to better understand species invasion: the case of Trachemys dorbigni (Testudines, Emydidae)

Niche conservatism at distinct levels of biological hierarchy is still a highly debated topic in ecology. The general evaluation of niche shifts is mainly addressed to species level, with few explorations at lower or higher hierarchical levels. The freshwater turtle Trachemys dorbigni (Black-Bellied Slider) has recently been divided into two subspecies that occur in very different climatic conditions and is also considered to be an invasive species in parts of eastern and southeastern regions in Brazil. Here, we aimed to explore the effects of evaluating climatic niche conservatism at subspecific levels during the invasive process of T. dorbigni. We evaluated niche conservatism based on similarity (whether niches are more similar than expected by chance) and also measured expansion, stability, and unfilling in the invaded niche. We found that the climatic niches of the T. dorbigni recognized subspecies are very different, but when they are merged, the environmental condition created is more similar to the invasive niche of the subspecies T. dorbigni dorbigni. We also found consistent evidence of niche conservatism in invaded areas, which enables the effective use of ecological niche models to forecast T. dorbigni dorbigni invasion in other geographic regions.

Pollinator specialization: from the individual to the community.

1190 I. 1190 II. 1191 III. 1191 IV. 1193 V. 1193 1194 References 1194 SUMMARY: Most spermatophytes need conspecific pollen in order to produce seed. This need for specialization seems to conflict with the generalized nature of most plant-pollinator interactions. Specialization and generalization are dynamic - not fixed - and exist simultaneously in multiple states at different levels of biological hierarchy. Over the short term, specialization ensures conspecific pollen transfer, whereas over the long term, generalization improves system-level robustness. The balance between specialization and generalization at different scales is critical for different kinds of ecological functioning and is an important factor in plant speciation and the evolution of plant mating systems. Community context, including diversity and interaction network structure at different levels of aggregation, is a key driver of specialization dynamics.

Transcriptomic changes underlie altered egg protein production and reduced fecundity in an estuarine model fish exposed to bifenthrin

Pyrethroid pesticides are a class of insecticides found to have endocrine disrupting properties in vertebrates such as fishes and in human cell lines. Endocrine disrupting chemicals (EDCs) are environmental contaminants that mimic or alter the process of hormone signaling. In particular, EDCs that alter estrogen and androgen signaling pathways are of major concern for fishes because these EDCs may alter reproductive physiology, behavior, and ultimately sex ratio. Bifenthrin, a pyrethroid with escalating usage, is confirmed to disrupt estrogen signaling in several species of fish, including Menidia beryllina (inland silverside), an Atherinid recently established as a euryhaline model. Our main objective was to broadly assess the molecular and physiological responses of M. beryllina to the ng/L concentrations of bifenthrin typically found in the environment, with a focus on endocrine-related effects, and to discern links between different tiers of the biological hierarchy. As such, we evaluated the response of juvenile Menidia to bifenthrin using a Menidia-specific microarray, quantitative real-time polymerase chain reaction (qPCR) on specific endocrine-related genes of interest, and a Menidia-specific ELISA to the egg-coat protein choriogenin, to evaluate a multitude of molecular-level responses that would inform mechanisms of toxicity and any underlying causes of change at higher biological levels of organization. The sublethal nominal concentrations tested (0.5, 5 and 50ng/L) were chosen to represent the range of concentrations observed in the environment and to provide coverage of a variety of potential responses. We then employed a 21-day reproductive assay to evaluate reproductive responses to bifenthrin (at 0.5ng/L) in a separate group of adult M. beryllina. The microarray analysis indicated that bifenthrin influences a diverse suite of molecular pathways, from baseline metabolic processes to carcinogenesis. A more targeted examination of gene expression via qPCR demonstrated that bifenthrin downregulates a number of estrogen-related transcripts, particularly at the lowest exposure level. Choriogenin protein also decreased with exposure to increasing concentrations of bifenthrin, and adult M. beryllina exposed to 0.5ng/L had significantly reduced reproductive output (fertilized eggs per female). This reduction in fecundity is consistent with observed changes in endocrine-related gene expression and choriogenin production. Taken together, our results demonstrate that environmental concentrations of bifenthrin have potential to interfere with metabolic processes, endocrine signaling, and to decrease reproductive output.

Cognition and Culture in Evolutionary Context.

In humans and other animals, the individuals' ability to adapt efficiently and effectively to the niches they have actively contributed to construct relies heavily on an evolved psychology which has been shaped by biological, social, and cultural processes over evolutionary time. As expected, although many of the behavioral and cognitive components of this evolved psychology are widely shared across species, many others are species-unique. Although many animal species are known to acquire group-specific traditions (or cultures) via social learning, human culture is unique in terms of its contents and characteristics (observable and unobservable products, cumulative effects, norm conformity, and norm enforcement) and of its cognitive underpinnings (imitation, instructed teaching, and language). Here we provide a brief overview of some of the issues that are currently tackled in the field. We also highlight some of the strengths of a biological, comparative, non-anthropocentric and evolutionarily grounded approach to the study of culture. The main contributions of this approach to the science of culture are its emphasis (a) on the integration of information on mechanisms, function, and evolution, and on mechanistic factors located at different levels of the biological hierarchy, and (b) on the search for general principles that account for commonalities and differences between species, both in the cultural products and in the processes of innovation, dissemination, and accumulation involved that operate during developmental and evolutionary timespans.

Diversifying the picture of explanations in biological sciences: ways of combining topology with mechanisms

Besides mechanistic explanations of phenomena, which have been seriously investigated in the last decade, biology and ecology also include explanations that pinpoint specific mathematical properties as explanatory of the explanandum under focus. Among these structural explanations, one finds topological explanations, and recent science pervasively relies on them. This reliance is especially due to the necessity to model large sets of data with no practical possibility to track the proper activities of all the numerous entities. The paper first defines topological explanations and then explains why topological explanations and mechanisms are different in principle. Then it shows that they are pervasive both in the study of networks—whose importance has been increasingly acknowledged at each level of the biological hierarchy—and in contexts where the notion of selective neutrality is crucial; this allows me to capture the difference between mechanisms and topological explanations in terms of practical modelling practices. The rest of the paper investigates how in practice mechanisms and topologies are combined. They may be articulated in theoretical structures and explanatory strategies, first through a relation of constraint, second in interlevel theories (Sect. 3), or they may condition each other (Sect. 4). Finally, I explore how a particular model can integrate mechanistic informations, by focusing on the recent practice of merging networks in ecology and its consequences upon multiscale modelling (Sect. 5).

Complex watersheds, collaborative teams: Assessing pollutant presence and effects in the San Francisco Delta.

There is a great diversity of sources of chemical contaminants and stressors over large geographic areas. Chemical contaminant inputs and magnitude can potentially exhibit wide seasonal variation over large geographic areas. Together, these factors make linking exposure to monitored chemical contaminants and effects difficult. In practice, this linkage typically relies on relatively limited chemical occurrence data loosely coupled with individual effects, and population- or community-level assessments. Increased discriminatory power may be gained by approaching watershed level assessment in a more holistic manner, drawing from a number of disciplines that target endpoints spanning levels of the biological hierarchy. Using the Sacramento River as a case study, the present study aimed to 1) evaluate the performance of new analytical and biomarker tools in a real world setting and their potential for linking occurrence and effect; 2) characterize the effects of geographic and temporal variability through the integration of suborganismal, tissue, and individual level endpoints, as well as extensive chemical analyses; 3) identify knowledge gaps and research needs that limit the implementation of this holistic approach; and 4) provide an experimental design workflow for these types of assessments. Sites were selected to target inputs into the Sacramento River as it transitions from an agricultural to a mixed but primarily urban landscape. Chemical analyses were conducted on surface water samples at each site in both the spring and fall for pesticides, hormones, and active pharmaceutical ingredients (APIs). Active pharmaceutical ingredients were more often detected across sampling events in the fall; however, at the most downstream site the number of analytes detected and their concentrations were greater in the spring, which may be due to seasonal differences in rainfall. Changes in gene and protein expression targeting endocrine and reproductive effects were observed within each sampling event; however, they were inconsistent across seasons. Larval mortality at the most downstream site was seen in both seasons; however, behavioral changes were only observed in the spring. No clear linkages of specific analyte exposure to biological response were observed, nor were linkages across biological levels of organization. This failure may have resulted from limitations of the scope of molecular endpoints used, inconsistent timing of exposure, or discordance of analytical chemistry through grab sampling and longer term, integrative exposure. Together, results indicate a complicated view of the watershed.

Multiple-geographic-scale genetic structure of two mangrove tree species: the roles of mating system, hybridization, limited dispersal and extrinsic factors.

Mangrove plants comprise a unique group of organisms that grow within the intertidal zones of tropical and subtropical regions and whose distributions are influenced by both biotic and abiotic factors. To understand how these extrinsic and intrinsic processes influence a more fundamental level of the biological hierarchy of mangroves, we studied the genetic diversity of two Neotropical mangrove trees, Avicenniagerminans and A. schaueriana, using microsatellites markers. As reported for other sea-dispersed species, there was a strong differentiation between A. germinans and A. schaueriana populations sampled north and south of the northeastern extremity of South America, likely due to the influence of marine superficial currents. Moreover, we observed fine-scale genetic structures even when no obvious physical barriers were present, indicating pollen and propagule dispersal limitation, which could be explained by isolation-by-distance coupled with mating system differences. We report the first evidence of ongoing hybridization between Avicennia species and that these hybrids are fertile, although this interspecific crossing has not contributed to an increase in the genetic diversity the populations where A. germinans and A. schaueriana hybridize. These findings highlight the complex interplay between intrinsic and extrinsic factors that shape the distribution of the genetic diversity in these sea-dispersed colonizer species.

English

Xochimilco’s lacustrine zone is a network of channels that, along with the chinampas, conform a unique ecosystem which has served as source of aquatic resources. Duckweeds are small free-floating monocotyledon aquatic plants classified as macrophytes that serve as nutrient pumps and reduce eutrophication effects. Recently, there are number of new studies related to the aquatic plant-microbial interaction focused on the direct functional analysis that investigate plant microbe interactions at full biological hierarchy. The aim of this study was to compare the auxin in vitro production efficiency of the endophyte phytobacteria isolated from Lemna gibba L. plants collected nearby the Xochimilco aquatic agrosystem. There were 17 isolates obtained from the L. gibba plants collected in the dry season and 14 isolates for the rainy season. The environmental conditions and seasonal characteristics determined the number and identity of the isolated endophyte phytobacteria in L. gibba plants according to the several apparent differences in the water quality. This work contributes to the knowledge of the phytobacteria diversity in aquatic plants, particularly in Lemnaceae species; here the majority of the isolates have been characterized as higher indole acetic acid producers, recommended as candidates for their use as biofertilizers. Key words: Plant growth-promoting bacteria, biofertilizers, Lemna gibba , Xochimilco.

Out of sight, out of mind.

Out of sight, out of mind.

Biomarkers as New Monitoring Method of Coastal Pollutants

The measurement of various contamination of costal water by classic chemical monitoring of few pollutants is possible, but also through examination for indicators of adverse effects of pollution on organisms is more effective. Selected biochemical parameters, so called biomarkers in an indicator fish, can be used for this purpose [1]. Application of biomarkers in environmental monitoring of coastal areas may resolve many challenges by providing a measure of availability of an environmental chemical to an aquatic organism by providing a direct measure of the response of an organism to chemical exposure. One of the benefits of the biomarker approach is the identification of early-onset changes, which predict increased risk of adverse effects following exposure to environmental chemicals [2]. There are many definitions of biomarkers e.g.: “A biomarker is a xenobiotically induced variation in cellular or biochemical components or processes, structures, or functions that is measurable in a biological system or sample”. Peakall suggested the term Biomarker to indicate effects relating to individual organisms and bioindicator to indicate effects measured at the population or community levels of biological hierarchy [3].

Approach to a Comparative Study of the Metabolism of Porphyrins and Chlorophylls

Metabolic pathways are series of successive biochemical reactions catalyzed by enzymes which together constitute a process of extraordinary complexity, the cellular metabolism. Like any other biological phenomenon, metabolism is the result of evolution. Different techniques are used to compare characteristics of living entities seeking to analyze the similarity between them. The features or characteristics that define species are of different types: molecular, metabolic, cellular, environmental, behavioral, etc. Depending on the similarity, biological species and any entity of the biological hierarchy, are sorted and classified. This paper focuses on studying a characteristic of organisms that is metabolism of porphyrins and chlorophylls using cladistic procedures, unlike others, allow crawl the changes in this feature. The result of a cladistic analysis is an evolutionary hypothesis, a hypothesis about the evolution of metabolism of porphyrins and chlorophylls. The work raises two objectives: firstly, hypotheses about the evolution of metabolism of porphyrins and chlorophylls; otherwise, hypotheses on the evolution of enzymes involved in cellular metabolism this part, opening the possibility that some of them serve as phylogenetic marker.

Heuristic identification of biological architectures for simulating complex hierarchical genetic interactions.

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects.

Organized Modularity in the Interactome: Evidence from the Analysis of Dynamic Organization in the Cell Cycle.

The organization of global protein interaction networks (PINs) has been extensively studied and heatedly debated. We revisited this issue in the context of the analysis of dynamic organization of a PIN in the yeast cell cycle. Statistically significant bimodality was observed when analyzing the distribution of the differences in expression peak between periodically expressed partners. A close look at their behavior revealed that date and party hubs derived from this analysis have some distinct features. There are no significant differences between them in terms of protein essentiality, expression correlation and semantic similarity derived from gene ontology (GO) biological process hierarchy. However, date hubs exhibit significantly greater values than party hubs in terms of semantic similarity derived from both GO molecular function and cellular component hierarchies. Relating to three-dimensional structures, we found that both single- and multi-interface proteins could become date hubs coordinating multiple functions performed at different times while party hubs are mainly multi-interface proteins. Furthermore, we constructed and analyzed a PPI network specific to the human cell cycle and highlighted that the dynamic organization in human interactome is far more complex than the dichotomy of hubs observed in the yeast cell cycle.

Populations and Individuals in Heterokaryotic Fungi: A Multilevel Perspective

Among mycologists, questions persist about what entities should be treated as the fundamental units of fungal populations. This article articulates a coherent view about populations of heterokaryotic fungi and the individuals that comprise them. Using Godfrey-Smith’s minimal concept of a Darwinian population, I argue that entities at two levels of the biological hierarchy satisfy the minimal concept in heterokaryotic fungi: mycelia and nuclei. I provide a preliminary answer to the question of how to understand the relation between these two populations. This article contributes to discussions about the nature of biological individuality, organismality, and evolutionary transitions.