A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p

The cycling hair follicle as an ideal systems biology research model

In the postgenomic era, systems biology has rapidly emerged as an exciting field predicted to enhance the molecular understanding of complex biological systems by the use of quantitative experimental and mathematical approaches. Systems biology studies how the components of a biological system (e.g. genes, transcripts, proteins, metabolites) interact to bring about defined biological function or dysfunction. Living systems may be divided into five dimensions of complexity: (i) molecular; (ii) structural; (iii) temporal; (iv) abstraction and emergence; and (v) algorithmic. Understanding the details of these dimensions in living systems is the challenge that systems biology aims to address. Here, we argue that the hair follicle (HF), one of the signature features of mammals, is a perfect and clinically relevant model for systems biology research. The HF represents a stem cell-rich, essentially autonomous mini-organ, whose cyclic transformations follow a hypothetical intrafollicular “hair cycle clock” (HCC). This prototypic neuroectodermal-mesodermal interaction system, at the cross-roads of systems and chronobiology, encompasses various levels of complexity as it is subject to both intrafollicular and extrafollicular inputs (e.g. intracutaneous timing mechanisms with neural and systemic stimuli). Exploring how the cycling HF addresses the five dimensions of living systems, we argue that a systems biology approach to the study of hair growth and cycling, in man and mice, has great translational medicine potential. Namely, the easily accessible human HF invites preclinical and clinical testing of novel hypotheses generated with this approach

Multi-laboratory compilation of atmospheric carbon dioxide data for the year 2023-2024; obspack_ch4_1_NRT_v6.2_2024-06-27

This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products

Multi-laboratory compilation of atmospheric carbon dioxide data for the period 1957-2023; obspack_co2_1_GLOBALVIEWplus_v10.0_2024-09-26

This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products. This product includes 625 atmospheric carbon dioxide datasets derived from observations made by 79 laboratories from 28 countries. Data for the period 1957-2023 (where available) are included

Using transcranial electrical stimulation to enhance cognitive functions in the typical and atypical brain

Transcranial electrical stimulation (TES) includes methods such as transcranial direct current stimulation, transcranial random noise stimulation, and transcranial alternating current stimulation. These methods provide novel ways of enhancing human cognitive abilities for restorative purposes, or for general cognitive enhancement, by modulating neuronal activity. I discuss here the basic principles behind these methods and provide some illustrations of their efficacy in cognitive enhancement in those with typical and atypical brain function. Next, I outline some future directions for research that are have been largely neglected, such as the issue of individual differences, cognitive side effects, the efficacy of TES for use with healthy elderly populations, children with atypical development, and sports. The results observed thus far with TES as well as its future possibilities have significant implications for both basic and translational neuroscience. © 2013 Versita Warsaw and Springer-Verlag Wien