Systems biology in animal sciences

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.     

Trends in computational biology: a summary based on a RECOMB plenary lecture, 1999.

Computational biology, a term coined from analogy to the role of computing in the physical sciences, is now coming into its own as a major element of contemporary biological and biomedical research. Information science and computational science provide essential tools for next generation biological science efforts, from focusing the direction of experimental studies to providing knowledge and insight that can not otherwise be obtained. Going beyond the revolution in biology reflected in the successes of the genome project and driven by the power of molecular biology techniques, computational approaches will provide an underpinning for the integration of broad disciplines for development of a quantitative systems approach to understanding the mechanisms in the life of the cell.     

合成生物学及其在生物技术中的应用进展

合成生物学是一门21世纪生物学的新兴学科,它着眼生物科学与工程科学的结合,把生物系统当作工程系统"从下往上"进行处理,由"单元"(unit)到"部件"(device)再到"系统"(system)来设计,修改和组装细胞构件及生物系统.合成生物学是分子和细胞生物学、进化系统学、生物化学、信息学、数学、计算机和工程等多学科交叉的产物.目前研究应用包括两个主要方面:一是通过对现有的、天然存在的生物系统进行重新设计和改造,修改已存在的生物系统,使该系统增添新的功能.二是通过设计和构建新的生物零件、组件和系统,创造自然界中尚不存在的人工生命系统.合成生物学作为一门建立在基因组方法之上的学科,主要强调对创造人工生命形态的计算生物学与实验生物学的协同整合.必须强调的是,用来构建生命系统新结构、产生新功能所使用的组件单元既可以是基因、核酸等生物组件,也可以是化学的、机械的和物理的元件.本文跟踪合成生物学研究及应用,对其在DNA水平编程、分子修饰、代谢途径、调控网络和工业生物技术等方面的进展进行综述.     

保护生物学概要

保护生物学的形成是对生物危机的反应和生物科学迅速发展的结果。它是应用科学解决由于人类活动干扰或其它因素引起的物种、群落和生态系统出现的问题的新学科。其”目的是提供保护生物多样性的原理和工具“,其基础科学和应用科学的综合性交叉学科。系统学、生态学、生物地理学和种群生态学的原理和方法是保护生物学重要的理论和实践基础。     

Dual Causality and the Autonomy of Biology

Ernst Mayr’s concept of dual causality in biology with the two forms of causes (proximate and ultimate) continues to provide an essential foundation for the philosophy of biology. They are equivalent to functional (=proximate) and evolutionary (=ultimate) causes with both required for full biological explanations. The natural sciences can be classified into nomological, historical nomological and historical dual causality, the last including only biology. Because evolutionary causality is unique to biology and must be included for all complete biological explanations, biology is autonomous from the physical sciences.     

Aerodynamically assisted jetting and threading for processing concentrated suspensions containing advanced structural,functional and biological materials

In recent years material sciences have been interpreted right across the physical and the life sciences. Essentially this discipline broadly addresses the materials, processing, and/or fabrication right up to the structure. The materials and structures areas can range from the micro- to the nanometre scale and, in a materials sense, span from the structural, functional to the most complex, namely biological (living cells). It is generally recognised that the processing or fabrication is fundamental in bridging the materials with their structures. In a global perspective, processing has not only contributed to the materials sciences but its very nature has bridged the physical with the life sciences. In this review we discuss one such swiftly emerging fabrication approach having a plethora of applications spanning the physical and life sciences.     

FRAP, FLIP, FRET, BRET, FLIM, PRIM...new techniques for a colourful life

Cell and tissue imaging provides scientists with wonderful tools, thanks to a fruitful dialog between chemistry, optical, mechanical, computational sciences and biology. Confocal microscopy, videomicroscopy together with a new generation of fluorochromes (especially those derived from green fluorescent protein, GFP) and image analysis software allow to visualize life in all its dimensions (space and time). Cell imaging also allows to quantify biological processes at the cellular level, to analyse both stoechiometry and dynamics of molecular interactions involved in cell and tissue regulations. Entering the new era of post-genomics requires a better knowledge of advantages and limitations of these new approaches.     

合成生物学技术在材料科学中的应用

材料是人类赖以生存与发展的物质基础,科技和社会的进步都离不开材料技术的发展,未来先进材料的合成和制备必然朝着绿色可持续、低耗高产出、精细可调控、高效多功能的方向发展。以"基因调控·工程设计"为核心的合成生物学技术从分子、细胞层面极大地推动了生命科学的发展,也已经并继续为材料科学的发展注入新的思路和活力。本文将围绕合成生物学技术在材料科学中的应用,以基因回路设计为核心,概念应用为线索,重点介绍合成生物学技术在高分子生物材料和无机纳米材料领域的开发和生产,细胞展示和蛋白定向进化战略对分子材料的筛选和优化,"活体"功能材料、工程菌调节的人工光合系统功能材料体系以及基因回路在材料科学中的应用。     

Integrating Interactive Computational Modeling in Biology Curricula

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by “building and breaking it” via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the “Vision and Change” call to action in undergraduate biology education by providing a hands-on approach to biology.     

Bringing the physical sciences into your cell biology research

Historically, much of biology was studied by physicists and mathematicians. With the advent of modern molecular biology, a wave of researchers became trained in a new scientific discipline filled with the language of genes, mutants, and the central dogma. These new molecular approaches have provided volumes of information on biomolecules and molecular pathways from the cellular to the organismal level. The challenge now is to determine how this seemingly endless list of components works together to promote the healthy function of complex living systems. This effort requires an interdisciplinary approach by investigators from both the biological and the physical sciences.     

Bioinformatics

Bioinformatics is an interdisciplinary field that blends computer science and biostatistics with biological and biomedical sciences such as biochemistry, cell biology, developmental biology, genetics, genomics, and physiology. An important goal of bioinformatics is to facilitate the management, analysis, and interpretation of data from biological experiments and observational studies. The goal of this review is to introduce some of the important concepts in bioinformatics that must be considered when planning and executing a modern biological research study. We review database resources as well as data mining software tools.     

Vascular biomaterials: from biomedical engineering to tissue engineering

Biomaterials are already widely used in medical sciences. The field of biomaterials began to shift to produce materials able to stimulate specific cellular responses at the molecular level. The combined efforts of cell biologists, engineers, materials scientists, mathematicians, geneticists, and clinicians are now used in tissue engineering to restore, maintain, or improve tissue functions or organs. This rapidly expanding approach combines the fields of material sciences and cell biology for the molecular design of polymeric scaffolds with appropriate 3D configuration and biological responses. Future developments for new blood vessels will require improvements in technology of materials and biotechnology together with the increased knowledge of the interactions between materials, blood, and living tissues. Biomaterials represent a crucial mainstay for all these studies.     

Co-evolution of physical and social sciences in synthetic biology

Emerging technologies research often covers various perspectives in disciplines and research areas ranging from hard sciences, engineering, policymaking, and sociology. However, the interrelationship between these different disciplinary domains, particularly the physical and social sciences, often occurs many years after a technology has matured and moved towards commercialization. Synthetic biology may serve an exception to this idea, where, since 2000, the physical and the social sciences communities have increasingly framed their research in response to various perspectives in biological engineering, risk assessment needs, governance challenges, and the social implications that the technology may incur. This paper reviews a broad collection of synthetic biology literature from 2000–2016, and demonstrates how the co-development of physical and social science communities has grown throughout synthetic biology’s earliest stages of development. Further, this paper indicates that future co-development of synthetic biology scholarship will assist with significant challenges of the technology’s risk assessment, governance, and public engagement needs, where an interdisciplinary approach is necessary to foster sustainable, risk-informed, and societally beneficial technological advances moving forward.     

Designer Condensates: A Toolkit for the Biomolecular Architect

Protein phase separation has emerged as a novel paradigm to explain the biogenesis of membraneless organelles and other so-called biomolecular condensates. While the implication of this physical phenomenon within cell biology is providing us with novel ways for understanding how cells compartmentalize biochemical reactions and encode function in such liquid-like assemblies, the newfound appreciation of this process also provides immense opportunities for designing and sculpting biological matter. Here, we propose that understanding the cell’s instruction manual of phase separation will enable bioengineers to begin creating novel functionalized biological materials and unprecedented tools for synthetic biology. We present FASE as the synthesis of the existing sticker-spacer framework, which explains the physical driving forces underlying phase separation, with quintessential principles of Scandinavian design. FASE serves both as a designer condensates catalogue and construction manual for the aspiring (membraneless) biomolecular architect. Our approach aims to inspire a new generation of bioengineers to rethink phase separation as an opportunity for creating reactive biomaterials with unconventional properties and to encode novel biological function in living systems. Although still in its infancy, several studies highlight how designer condensates have immediate and widespread potential applications in industry and medicine.     

系统生物学对医学的影响

系统生物学是21世纪最前沿的科学之一,它是随着生命科学飞速发展而产生的一门新兴生物学分支[1],它综合数学、信息科学和生物学的各种工具来阐明和理解大量的数据所包含的生物医学意义,从而使人们能够从整体上理解生物医学系统并精确、量化地预测生物医学系统的行为。随着系统生物学的发展及其理论的突破,将在疾病诊治、新药开发、预防医学方面发挥重要的作用,有助于弥补传统医学缺陷并促进其发展。     

How can calibrated research-based models be improved for use as a tool in identifying genes controlling crop tolerance to environmental stresses in the era of genomics—from an experimentalist's perspective

Almost four decades have passed since the new field of ecosystem simulation sprang into full force as an added tool for a sound research in an ever-advancing scientific front. The enormous advances and new discoveries that recently took place in the field of molecular biology and basic genetics added more effective tools, have strengthened and increased the efficiency of science outputs in various areas, particularly in basic biological sciences. Now, we are entering into a more promising stage in science, i.e. ‘post-genomics’, where both simulation modelling and molecular biology tools are integral parts of experimental research in agricultural sciences. I briefly review the history of simulation of crop/environment systems in the light of advances in molecular biology, and most importantly the essential role of experimental research in developing and constructing more meaningful and effective models and technologies. Such anticipated technologies are expected to lead into better management of natural resources in relation to crop communities in particular and plant ecosystems in general, that might enhance productivity faster. Emphasis is placed on developing new technologies to improve agricultural productivity under stressful environments and to ensure sustainable economic development. The latter is essential since available natural resources, particularly land and water, are increasingly limiting. An erratum to this article is available at .     

Grand challenges in organismal biology

A renaissance in organismal biology has been sparked by recent conceptual, theoretical, methodological, and computational advances in the life sciences, along with an unprecedented interdisciplinary integration with Mathematics, Engineering, and the physical sciences. Despite a decades-long trend toward reductionist approaches to biological problems, it is increasingly recognized that whole organisms play a central role in organizing and interpreting information from across the biological spectrum. Organisms represent the nexus where sub- and supra-organismal processes meet, and it is the performance of organisms within the environment that provides the material for natural selection. Here, we identify five "grand challenges" for future research in organismal biology. It is intended that these challenges will spark further discussion in the broader community and identify future research priorities, opportunities, and directions, which will ultimately help to guide the allocation of support for and training in organismal biology.     

Ins and Outs of Systems Biology vis-à-vis Molecular Biology: Continuation or Clear Cut?

The comprehension of living organisms in all their complexity poses a major challenge to the biological sciences. Recently, systems biology has been proposed as a new candidate in the development of such a comprehension. The main objective of this paper is to address what systems biology is and how it is practised. To this end, the basic tools of a systems biological approach are explored and illustrated. In addition, it is questioned whether systems biology ‘revolutionizes’ molecular biology and ‘transcends’ its assumed reductionism. The strength of this claim appears to depend on how molecular and systems biology are characterised and on how reductionism is interpreted. Doing credit to molecular biology and to methodological reductionism, it is argued that the distinction between molecular and systems biology is gradual rather than sharp. As such, the classical challenge in biology to manage, interpret and integrate biological data into functional wholes is further intensified by systems biology’s use of modelling and bioinformatics, and by its scale enlargement.     

Moving beyond molecular mechanisms

A major goal in cell biology is to bridge the gap in our understanding of how molecular mechanisms contribute to cell and organismal physiology. Approaches well established in the physical sciences could be instrumental in achieving this goal. A better integration of the physical sciences with cell biology will therefore be an important step in our quest to decipher how cells work together to construct a living organism.Over the past 60 years, the field of cell biology has been firmly rooted in understanding the molecular basis of complex cellular processes including genome replication, migration, metabolism, and adhesion. This progress has been enabled by advances in molecular biology, biochemistry, physical chemistry, single-molecule physics, and microscopy. Bringing together these disciplines has been successful in identifying the molecular composition of macromolecular machines, characterizing the structure and physical properties of single proteins within cells, reconstituting complex macromolecular machinery in vitro, and imaging the dynamics and function of these machines in vivo.Despite this amazing progress, a major challenge facing cell biology is understanding how the chemical and physical properties of molecular machinery come together to guide cell processes. How do varied physical and chemical signals in the environment determine whether a cell survives, proliferates, or migrates? What circuitry allows for a complex body plan to be constructed out of a single-celled embryo? The signals in the environment are noisy, with fluctuations in both time and space. Moreover, as anyone who has tried to characterize cells is aware, cell phenotypes are variable both across individual cells and within a single cell over time. In the presence of all this noise, cells execute some processes exceedingly reliably (e.g., DNA segregation in cell division). Others, such as the determination of protrusive activity in a migrating cell, appear to be more variable. How does this complex network of stochastic chemical and mechanical machinery enable robust and complex decision making at the cell scale?The answers to these questions require knowledge of cell structure at the scale between single molecules and whole cells (Fig. 1). This intermediate, or mesoscopic, length scale has different names depending on who you ask. You can think of it as a “system” or interconnected network of biochemical interactions that provide a logic circuit as to how cells process a signal to decide on an output. It can be a subcellular machine consisting of a collection of macromolecules designed to work together for a desired mechanical output, such as cargo transport, DNA segregation, or cell movement. There is a significant gap in our understanding at this scale. To make an analogy between a cell and a car: most of us have a good understanding of the car’s component materials (e.g., rubber, metal), and in some cases we understand the individual machines that make up parts of the whole (e.g., the engine, transmission). However, we do not have a good understanding of the essential control parameters of the machines or how these are wired together to form productive, more complex machinery (e.g., creating the forward, backward, and turning motions). Understanding the control parameters that regulate macromolecular assemblies, and how these are wired together to enable complex cell outputs, represents an exciting frontier in cell biology.Open in a separate windowFigure 1.The scales of cell biology. Shown are images illustrating the range of scales in cell biology. At the smallest (∼10⁻⁹ m) is that of molecules represented by the structure of G-actin (left; reproduced from Paavilainen et al. 2008. J. Cell Biol. http://dx.doi.org/10.1083/jcb.200803100) and the largest (10⁻⁵ to 10⁻⁴ meters) is that of cell physiology, represented by a migrating fibroblast with a labeled actin cytoskeleton (right; image courtesy of Patrick Oakes). In between these length scales reside: macromolecular assemblies (10⁻⁸ to 10⁻⁷ m) of individual proteins, represented by a schematic of an Arp2/3-mediated F-actin branch (second from the left); and organelles (10⁻⁷ to 10⁻⁵ m), such as lamellipodia (third from the left), which are formed by the integration of macromolecular assemblies into a mechanochemical machine depicted as a pathway diagram. At the next level are organelle systems (10⁻⁴ to 10⁻⁵ m) that integrate organelles together for a specific aspect of cell physiology, represented by a fluorescent image of actin overlaid with vectors of actin flow at the leading edge that result from the coordination of numerous regulatory organelles across the cell (second from the right; reproduced from Thievessen et al. 2013. J. Cell Biol. http://dx.doi.org/10.1083/jcb.201303129). Understanding the processes at this intermediate scale will greatly aid in our knowledge of how molecules construct living cells.Many areas of the physical sciences have been devoted to studying how collections of objects work together to construct a material or machine. In this construction, new properties emerge that could not be predicted or understood by studies of objects in isolation. For instance, electrical engineers need to know how circuit elements are connected in order to predict the circuit response. Or, in condensed matter physics, interactions between atoms and/or molecules result in properties such as elasticity or viscosity. In these areas of science, it is well appreciated that knowledge of individual components (in isolation) cannot predict the output of the entire system. By analogy, this would imply that understanding the molecular components of a cell, which has been the gold standard of cell biology, is insufficient. As cell biology starts to address questions wherein cells are thought of as “systems,” “materials,” or “machines,” there are numerous challenges that can be informed by approaches that have proven successful in the studies of materials and machines in the physical world.

Developing a common community

Cell biology is an inherently multidisciplinary science, requiring approaches from genetics, chemistry, physics, applied mathematics, and engineering. While biochemical and genetic approaches have been successfully integrated into the field, other disciplines require more effort. Physical scientists that join the field of cell biology retain the training and language from their physical discipline, which has been specialized for specific purposes. Applied mathematicians, condensed matter physicists, and mechanical engineers all have unique perspectives on how to model complex biological phenomena (Fig. 2). This has led to the development of parallel theoretical and experimental approaches for modeling cell biological phenomena that are difficult to directly compare or rigorously test. A challenge for the future is to develop a community of researchers that will integrate these diverse physical approaches to identify strengths, resolve differences, and determine the best approaches for modeling cell behaviors.Open in a separate windowFigure 2.The integration of physical sciences with cell biology. A flow chart showing examples of how various disciplines from the physical sciences (bottom) have optimized a variety of theoretical/modeling tools (left) as well as experimental techniques (right) that have been applied to cell biological problems. However, these experimental and theoretical tools have been optimized for their home disciplines. A current challenge is to systematically have them benchmarked against each other and identify their weaknesses and strengths before using them to provide a new framework optimized for mesoscale cell biology.

Precision in language

One of the simplest solutions to implement is to develop a consistent and precise language to describe measurements or ideas. In my field, which centers on how mechanical forces are sensed and generated by cells, terms like “mechanosensing” or even “stiffness sensing” are used without precision, resulting in confusion of what is known versus just “thought to be true.” Precision of language is essential for standardizing experimental protocols and measurements and in being able to clearly communicate conclusions and ideas.

Construction and validation of physical methods

One historical role of physical scientists in biology has been the introduction of new experimental and analytical tools. Some of these tools, such as microscopy and scattering techniques, have been developed extensively. However, in other cases, the nature of measurements require small apparatuses that can be difficult to replicate or operate (magnetic tweezers are a notorious example), making it difficult for other laboratories to build upon this knowledge. Similar issues arise in analysis and methods. It is extremely important for these methods to be used and validated by different laboratories to confirm results independently and by many individuals so that the language used to describe physical concepts and results can be made more precise. Being able to directly compare two different measurement techniques so that the same parameters can be used is essential for resolving discrepancies.Even though the goal is to understand cell physiology, model testing will require physical characterization that may not immediately inform a biological process. To use an analogous example: the work in basic materials science of magnetism that needed to be performed before we could construct and build computer hard drives. It is my hope that the cell biology community will remain interested in these advances in characterization of biological materials and systems, as they are crucial to uncovering synergies that are not currently apparent.

Feedback between modeling and experiments

In the physical sciences, research has evolved so that individuals typically focus on either theory or experimentation. Of course, each of these can be further subdivided into analytical theory versus computer modeling, as well as sample preparation versus characterization. This specialization has emerged as both the questions and fields themselves become more mature. It also has led to a vigorous feedback between theoretical prediction, experimental measurement, and new materials development. To be useful, models need to be falsifiable. There is increasing evidence that many of the models used in biology are over-parameterized and, consequently, difficult (or impossible) to falsify. That is, when parameters are assigned with molecular-level details, the number of parameters quickly becomes large. In these scenarios, changes in the parameter value have little effect on the model predictions and make it difficult to verify the accuracy of the model (for more details, see http://www.lassp.cornell.edu/sethna/Sloppy/). Identifying order parameters that encompass the physical quantities or metrics (e.g., elastic modulus, organelle transport) that make up many of the molecular details is essential for developing models with fewer control parameters. Such order parameters will provide crucial insight into understanding regulation of the individual macromolecular machinery.The word mechanism in cell biology typically refers to a molecular mechanism that is explored rigorously by genetic and biochemical testing. Understanding the physical mechanism requires both identification of the parameters controlling a system and then elucidation of the regulation of parameter values. Thus, seldom does a single molecular mechanism tie directly into a physical parameter. Moreover, understanding how molecular interactions give rise to a single physical parameter is not straightforward, and may require years of work. It is quite natural to apply models and approaches that we have used to engineer machines, such as the flow of decision making in electrical circuits or mechanic designs. However, cells are working under different sets of constraints, and a future challenge of understanding cellular machines is that completely different design principles may be used.Establishing a culture that encourages dynamic feedback between theory, experimentation, and physiology is crucial to advancing the integration of physical sciences with cell biology. A potentially very exciting possibility is that understanding the physical mechanisms controlling biological machines will enable a completely new set of design principles that provide insight into how living cells are able to respond and adapt to highly variable environments. This will enable understanding of how these states change during disease progression and the capability of engineering biological cells to maintain a healthy phenotype.