Wiley Interdisciplinary Reviews-Systems Biology and Medicine最新文献

Cell fate decisions are controlled by complex intracellular molecular regulatory networks. Studies increasingly reveal the scale of this complexity: not only do cell fate regulatory networks contain numerous positive and negative feedback loops, they also involve a range of different kinds of nonlinear protein-protein and protein-DNA interactions. This inherent complexity and nonlinearity makes cell fate decisions hard to understand using experiment and intuition alone. In this primer, we will outline how tools from mathematics can be used to understand cell fate dynamics. We will briefly introduce some notions from dynamical systems theory, and discuss how they offer a framework within which to build a rigorous understanding of what we mean by a cell "fate", and how cells change fate. We will also outline how modern experiments, particularly high-throughput single-cell experiments, are enabling us to test and explore the limits of these ideas, and build a better understanding of cellular identities. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Biological Mechanisms > Cell Fates Models of Systems Properties and Processes > Cellular Models.

An effective adaptive immune response to microbial infection relies on the generation of heterogeneous T lymphocyte fates and functions. CD8 T lymphocytes play a pivotal role in mediating immediate and long-term protective immune responses to intracellular pathogen infection. Systems-based analysis of the immune response to infection has begun to identify cell fate determinants and the molecular mechanisms underpinning CD8 T lymphocyte diversity at single-cell resolution. Resolving CD8 T lymphocyte heterogeneity during adaptive immunity highlights the advantages of single-cell technologies and computational approaches to better understand the ontogeny of CD8 T cellular diversity following infection. Future directions of integrating single-cell multiplex approaches capitalize on the importance of systems biology in the understanding of immune CD8 T cell differentiation and functional diversity. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Biological Mechanisms > Cell Fates.

Successful development depends on the precise tissue-specific regulation of genes by enhancers, genetic elements that act as switches to control when and where genes are expressed. Because enhancers are critical for development, and the majority of disease-associated mutations reside within enhancers, it is essential to understand which sequences within enhancers are important for function. Advances in sequencing technology have enabled the rapid generation of genomic data that predict putative active enhancers, but functionally validating these sequences at scale remains a fundamental challenge. Herein, we discuss the power of genome-wide strategies used to identify candidate enhancers, and also highlight limitations and misconceptions that have arisen from these data. We discuss the use of massively parallel reporter assays to test enhancers for function at scale. We also review recent advances in our ability to study gene regulation during development, including CRISPR-based tools to manipulate genomes and single-cell transcriptomics to finely map gene expression. Finally, we look ahead to a synthesis of complementary genomic approaches that will advance our understanding of enhancer function during development. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Developmental Biology > Developmental Processes in Health and Disease Laboratory Methods and Technologies > Genetic/Genomic Methods.

Decades of research in skeletal muscle physiology have provided multiscale insights into the structural and functional complexity of this important anatomical tissue, designed to accomplish the task of generating contraction, force and movement. Skeletal muscle can be viewed as a biomechanical device with various interacting components including the autonomic nerves for impulse transmission, vasculature for efficient oxygenation, and embedded regulatory and metabolic machinery for maintaining cellular homeostasis. The "omics" revolution has propelled a new era in muscle research, allowing us to discern minute details of molecular cross-talk required for effective coordination between the myriad interacting components for efficient muscle function. The objective of this review is to provide a systems-level, comprehensive mapping the molecular mechanisms underlying skeletal muscle structure and function, in health and disease. We begin this review with a focus on molecular mechanisms underlying muscle tissue development (myogenesis), with an emphasis on satellite cells and muscle regeneration. We next review the molecular structure and mechanisms underlying the many structural components of the muscle: neuromuscular junction, sarcomere, cytoskeleton, extracellular matrix, and vasculature surrounding muscle. We highlight aberrant molecular mechanisms and their possible clinical or pathophysiological relevance. We particularly emphasize the impact of environmental stressors (inflammation and oxidative stress) in contributing to muscle pathophysiology including atrophy, hypertrophy, and fibrosis. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Developmental Biology > Developmental Processes in Health and Disease Models of Systems Properties and Processes > Cellular Models.

The innate immune system is the first line of host defense against invading microorganisms. Polymorphonuclear leukocytes (PMNs or neutrophils) are the most abundant leukocyte in humans and essential to the innate immune response against invading pathogens. Compared to the acquired immune response, which requires time to develop and is dependent on previous interaction with specific microbes, the ability of neutrophils to kill microorganisms is immediate, nonspecific, and not dependent on previous exposure to microorganisms. Historically, studies of PMN-pathogen interaction focused on the events leading to killing of microorganisms, such as recruitment/chemotaxis, transmigration, phagocytosis, and activation, whereas postphagocytosis sequelae were infrequently considered. In addition, it was widely accepted that human neutrophils possessed limited capacity for new gene transcription and thus, relatively little biosynthetic capacity. This notion has changed dramatically within the past 20 years. Further, there is now more effort directed to understand the events occurring in PMNs after killing of microbes. Herein, we give an updated review of the systems biology-level approaches that have been used to gain an enhanced view of the role of neutrophils during host-pathogen interaction and neutrophil-mediated diseases. We anticipate that these and future systems-level studies will continue to provide information important for understanding, treatment, and control of diseases caused by pathogenic microorganisms. This article is categorized under: Physiology > Organismal Responses to Environment Physiology > Mammalian Physiology in Health and Disease Biological Mechanisms > Cell Fates.

Nowadays, mathematical modeling is playing a key role in many different research fields. In the context of system biology, mathematical models and their associated computer simulations constitute essential tools of investigation. Among the others, they provide a way to systematically analyze systems perturbations, develop hypotheses to guide the design of new experimental tests, and ultimately assess the suitability of specific molecules as novel therapeutic targets. To these purposes, stochastic simulation algorithms (SSAs) have been introduced for numerically simulating the time evolution of a well-stirred chemically reacting system by taking proper account of the randomness inherent in such a system. In this work, we review the main SSAs that have been introduced in the context of exact, approximate, and hybrid stochastic simulation. Specifically, we will introduce the direct method (DM), the first reaction method (FRM), the next reaction method (NRM) and the rejection-based SSA (RSSA) in the area of exact stochastic simulation. We will then present the τ-leaping method and the chemical Langevin method in the area of approximate stochastic simulation and an implementation of the hybrid RSSA (HRSSA) in the context of hybrid stochastic-deterministic simulation. Finally, we will consider the model of the sphingolipid metabolism to provide an example of application of SSA to computational system biology by exemplifying how different simulation strategies may unveil different insights into the investigated biological phenomenon. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Analytical and Computational Methods > Computational Methods.

Mathematical models and computer simulations have the great potential to substantially increase our understanding of the biophysical behavior of the neuromuscular system. This, however, requires detailed multiscale, and multiphysics models. Once validated, such models allow systematic in silico investigations that are not necessarily feasible within experiments and, therefore, have the ability to provide valuable insights into the complex interrelations within the healthy system and for pathological conditions. Most of the existing models focus on individual parts of the neuromuscular system and do not consider the neuromuscular system as an integrated physiological system. Hence, the aim of this advanced review is to facilitate the prospective development of detailed biophysical models of the entire neuromuscular system. For this purpose, this review is subdivided into three parts. The first part introduces the key anatomical and physiological aspects of the healthy neuromuscular system necessary for modeling the neuromuscular system. The second part provides an overview on state-of-the-art modeling approaches representing all major components of the neuromuscular system on different time and length scales. Within the last part, a specific multiscale neuromuscular system model is introduced. The integrated system model combines existing models of the motor neuron pool, of the sensory system and of a multiscale model describing the mechanical behavior of skeletal muscles. Since many sub-models are based on strictly biophysical modeling approaches, it closely represents the underlying physiological system and thus could be employed as starting point for further improvements and future developments. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.