Sequencing data—genomics, transcriptomics, epigenomics, proteomics, and metabolomics—have revolutionized biological research, enabling a more detailed study of processes, ranging from subcellular to evolutionary, that drive biological organization. These processes, collectively, are responsible for generating patterns of phenotypic variation and can operate over dramatically different timescales (milliseconds to billions of years). While researchers often study phenotypic variation at specific levels of biological organization to isolate processes operating at that particular scale, the varying types of sequence data, or ‘omics, can also provide complementary inferences to link molecular and phenotypic variation to produce an integrated view of evolutionary biology, ranging from molecular pathways to speciation. We briefly describe how ‘omics has been used across biological levels and then demonstrate the utility of integrating different types of sequencing data across multiple biological levels within the same study to better understand biological phenomena. However, single-time-point studies cannot evaluate the temporal dynamics of these biological processes. Therefore, we put forward temporal ‘omics as a framework that can better enable researchers to study the temporal dynamics of target processes. Temporal ‘omics is not infallible, as the temporal sampling regime directly impacts inferential ability. Thus, we also discuss the role the temporal sampling regime plays in deriving inferences about the environmental conditions driving biological processes and provide examples that demonstrate the impact of the sampling regime on biological inference. Finally, we forecast the future of temporal ‘omics by highlighting current methodological advancements that will enable temporal ‘omics to be extended across species and timescales. We extend this discussion to using temporal multi-omics to integrate across the biological hierarchy to evaluate and link the temporal dynamics of processes that generate phenotypic variation.
Reintegrating Biology Through the Nexus of Energy, Information, and Matter
Synopsis Information, energy, and matter are fundamental properties of all levels of biological organization, and life emerges from the continuous flux of matter, energy, and information. This perspective piece defines and explains each of the three pillars of this nexus. We propose that a quantitative characterization of the complex interconversions between matter, energy, and information that comprise this nexus will help us derive biological insights that connect phenomena across different levels of biological organization. We articulate examples from multiple biological scales that highlight how this nexus approach leads to a more complete understanding of the biological system. Metrics of energy, information, and matter can provide a common currency that helps link phenomena across levels of biological organization. The propagation of energy and information through levels of biological organization can result in emergent properties and system-wide changes that impact other hierarchical levels. Deeper consideration of measured imbalances in energy, information, and matter can help researchers identify key factors that influence system function at one scale, highlighting avenues to link phenomena across levels of biological organization and develop predictive models of biological systems.
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- PAR ID:
- 10295534
- Date Published:
- Journal Name:
- Integrative and Comparative Biology
- ISSN:
- 1540-7063
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The cytoskeleton – a collection of polymeric filaments, molecular motors, and crosslinkers – is a foundational example of active matter, and in the cell assembles into organelles that guide basic biological functions. Simulation of cytoskeletal assemblies is an important tool for modeling cellular processes and understanding their surprising material properties. Here, we present aLENS (a Living Ensemble Simulator), a novel computational framework designed to surmount the limits of conventional simulation methods. We model molecular motors with crosslinking kinetics that adhere to a thermodynamic energy landscape, and integrate the system dynamics while efficiently and stably enforcing hard-body repulsion between filaments. Molecular potentials are entirely avoided in imposing steric constraints. Utilizing parallel computing, we simulate tens to hundreds of thousands of cytoskeletal filaments and crosslinking motors, recapitulating emergent phenomena such as bundle formation and buckling. This simulation framework can help elucidate how motor type, thermal fluctuations, internal stresses, and confinement determine the evolution of cytoskeletal active matter.more » « less
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Abstract The relationship between structure and function is a major constituent of the rules of life. Structures and functions occur across all levels of biological organization. Current efforts to integrate conceptual frameworks and approaches to address new and old questions promise to allow a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization. Here, we provide unifying and generalizable definitions of both structure and function that can be applied across all levels of biological organization. However, we find differences in the nature of structures at the organismal level and below as compared to above the level of the organism. We term these intrinsic and emergent structures, respectively. Intrinsic structures are directly under selection, contributing to the overall performance (fitness) of the individual organism. Emergent structures involve interactions among aggregations of organisms and are not directly under selection. Given this distinction, we argue that while the functions of many intrinsic structures remain unknown, functions of emergent structures are the result of the aggregate of processes of individual organisms. We then provide a detailed and unified framework of the structure–function relationship for intrinsic structures to explore how their unknown functions can be defined. We provide examples of how these scalable definitions applied to intrinsic structures provide a framework to address questions on structure–function relationships that can be approached simultaneously from all subdisciplines of biology. We propose that this will produce a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization.more » « less
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Synopsis Temperature is one of the most important environmental factors driving the genome-to-phenome relationship. Metabolic rates and related biological processes are predicted to increase with temperature due to the biophysical laws of chemical reactions. However, selection can also act on these processes across scales of biological organization, from individual enzymes to whole organisms. Although some studies have examined thermal responses across multiple scales, there is no general consensus on how these responses vary depending on the level of organization, or whether rates actually follow predicted theoretical patterns such as Arrhenius-like exponential responses or thermal performance curves (TPCs) that show peak responses. Here, we performed a meta-analysis on studies of ectotherms where biological rates were measured across the same set of temperatures, but at multiple levels of biological organization: enzyme activities, mitochondrial respiration, and/or whole-animal metabolic rates. Our final dataset consisted of 235 pairwise comparisons between levels of organization from 13 publications. Thermal responses differed drastically across levels of biological organization, sometimes showing completely opposite patterns. We developed a new effect size metric, “organizational disagreement” (OD) to quantify the difference in responses among levels of biological organization. Overall, rates at higher levels of biological organization (e.g., whole animal metabolic rates) increased more quickly with temperature than rates at lower levels, contrary to our predictions. Responses may differ across levels due to differing consequences of biochemical laws with increasing organization or due to selection for different responses. However, taxa and tissues examined generally did not affect OD. Theoretical TPCs, where rates increase to a peak value and then drop, were only rarely observed (12%), possibly because a broad range of test temperatures was rarely investigated. Exponential increases following Arrhenius predictions were more common (29%). This result suggests a classic assumption about thermal responses in biological rates is rarely observed in empirical datasets, although our results should be interpreted cautiously due to the lack of complete thermal profiles. We advocate for authors to explicitly address OD in their interpretations and to measure thermal responses across a wider, more incremental range of temperatures. These results further emphasize the complexity of connecting the genome to the phenome when environmental plasticity is incorporated: the impact of the environment on the phenotype can depend on the scale of organization considered.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/icb/icab174
