Wiley Interdisciplinary Reviews-Systems Biology and Medicine最新文献

Recent advances in chromosome conformation capture technologies have led to the discovery of previously unappreciated structural features of chromatin. Computational analysis has been critical in detecting these features and thereby helping to uncover the building blocks of genome architecture. Algorithms are being developed to integrate these architectural features to construct better three-dimensional (3D) models of the genome. These computational methods have revealed the importance of 3D genome organization to essential biological processes. In this article, we review the state of the art in analytic and modeling techniques with a focus on their application to answering various biological questions related to chromatin structure. We summarize the limitations of these computational techniques and suggest future directions, including the importance of incorporating multiple sources of experimental data in building a more comprehensive model of the genome. This article is categorized under: Analytical and Computational Methods > Computational Methods Laboratory Methods and Technologies > Genetic/Genomic Methods Models of Systems Properties and Processes > Mechanistic Models.

As cell and molecular biology is becoming increasingly quantitative, there is an upsurge of interest in mechanistic modeling at different levels of resolution. Such models mostly concern kinetics and include gene and protein interactions as well as cell population dynamics. The final goal of these models is to provide experimental predictions, which is now taking on. However, even without matured predictions, kinetic models serve the purpose of compressing a plurality of experimental results into something that can empower the data interpretation, and importantly, suggesting new experiments by turning "knobs" in silico. Once formulated, kinetic models can be executed in terms of molecular rate equations for concentrations or by stochastic simulations when only a limited number of copies are involved. Developmental processes, in particular those of stem and progenitor cell commitments, are not only topical but also particularly suitable for kinetic modeling due to the finite number of key genes involved in cellular decisions. Stem and progenitor cell commitment processes have been subject to intense experimental studies over the last decade with some emphasis on embryonic and hematopoietic stem cells. Gene and protein interactions governing these processes can be modeled by binary Boolean rules or by continuous-valued models with interactions set by binding strengths. Conceptual insights along with tested predictions have emerged from such kinetic models. Here we review kinetic modeling efforts applied to stem cell developmental systems with focus on hematopoiesis. We highlight the future challenges including multi-scale models integrating cell dynamical and transcriptional models. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Developmental Biology > Stem Cell Biology and Regeneration.

The germ line is a crucial cell lineage that is distinct from somatic cells, and solely responsible for the trans-generational transmission of hereditary information in metazoan sexual reproduction. Primordial germ cells (PGCs)-the precursors to functional germ cells-are among the first cell types to be allocated in embryonic development, and this lineage commitment is a critical event in partitioning germ line and somatic tissues. Classically, mammalian PGC development has been largely informed by investigations on mouse embryos and embryonic stem cells. Recent findings from corresponding nonrodent systems, however, have indicated that murine PGC specification may not be fully archetypal. In this review, we outline the current understanding of molecular mechanisms in PGC specification, emphasizing key transcriptional events, and focus on salient differences between early human and mouse PGC commitment. Beyond these latest findings, we also contemplate the future outlook of inquiries in this field, highlighting the importance of comprehensively understanding early fate decisions that underlie the segregation of this unique lineage. This article is categorized under: Developmental Biology > Stem Cell Biology and Regeneration Biological Mechanisms > Cell Fates Physiology > Mammalian Physiology in Health and Disease.

Pioneer transcription factors play a primary role in establishing competence for gene expression and initiating cellular programming and reprogramming, and their dysregulation causes severe effects on human health, such as promoting tumorigenesis. Although more than 200 transcription factors are expressed in each cell type, only a small number of transcription factors are necessary to elicit dramatic cell-fate changes in embryonic development and cell-fate conversion. Among these key transcription factors, a subset called "pioneer transcription factors" have a remarkable ability to target nucleosomal DNA, or closed chromatin, early in development, often leading to the local opening of chromatin, thereby establishing competence for gene expression. Although more key transcription factors have been identified as pioneer transcription factors, the molecular mechanisms behind their special properties are only beginning to be revealed. Understanding the pioneering mechanisms will enhance our ability to precisely control cell fate at will for research and therapeutic purposes. This article is categorized under: Biological Mechanisms > Cell Fates Biological Mechanisms > Regulatory Biology Developmental Biology > Lineages.

Folate-mediated one-carbon metabolism (FOCM) comprises a network of interconnected folate-dependent metabolic pathways responsible for serine and glycine interconversion, de novo purine synthesis, de novo thymidylate synthesis and homocysteine remethylation to methionine. These pathways are compartmentalized in the cytosol, nucleus and mitochondria. Individual enzymes within the FOCM network compete for folate cofactors because intracellular folate concentrations are limiting. Although there are feedback mechanisms that regulate the partitioning of folate cofactors among the folate-dependent pathways, less recognized is the impact of cell cycle regulation on FOCM. This review summarizes the evidence for temporal regulation of expression, activity and cellular localization of enzymes and pathways in the FOCM network in mammalian cells through the cell cycle. This article is categorized under: Biological Mechanisms > Metabolism Physiology > Mammalian Physiology in Health and Disease.

The nonlinear systems models of computational anatomy that have emerged over the past several decades are a synthesis of three significant areas of computational science and biological modeling. First is the algebraic model of biological shape as a Riemannian orbit, a set of objects under diffeomorphic action. Second is the embedding of anatomical shapes into the soft condensed matter physics continuum via the extension of the Euler equations to geodesic, smooth flows with inverses, encoding divergence for the compressibility of atrophy and expansion of growth. Third, is making human shape and form a metrizable space via geodesic connections of coordinate systems. These three themes place our formalism into the modern data science world of personalized medicine supporting inference of high-dimensional anatomical phenotypes for studying neurodegeneration and neurodevelopment. The dynamical systems model of growth and atrophy that emerges is one which is organized in terms of forces, accelerations, velocities, and displacements, with the associated Hamiltonian momentum and the diffeomorphic flow acting as the state, and the smooth vector field the control. The forces that enter the model derive from external measurements through which the dynamical system must flow, and the internal potential energies of structures making up the soft condensed matter. We examine numerous examples on growth and atrophy. This article is categorized under: Analytical and Computational Methods > Computational Methods Laboratory Methods and Technologies > Imaging Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.

Over the last 30 years, deep brain stimulation (DBS) has been used to treat chronic neurological diseases like dystonia, obsessive-compulsive disorders, essential tremor, Parkinson's disease, and more recently, dementias, depression, cognitive disorders, and epilepsy. Despite its wide use, DBS presents numerous challenges for both clinicians and engineers. One challenge is the design of novel, more efficient DBS therapies, which are hampered by the lack of complete understanding about the cellular mechanisms of therapeutic DBS. Another challenge is the existence of redundancy in clinical outcomes, that is, different DBS programs can result in similar clinical benefits but very little information (e.g., predictive models, longitudinal data, metrics, etc.) is available to select one program over another. Finally, there is high variability in patients' responses to DBS, which forces clinicians to carefully adjust the stimulation settings to each patient via lengthy programming sessions. Researchers in neural engineering and systems biology have been tackling these challenges over the past few years with the specific goal of developing novel DBS therapies, design methodologies, and computational tools that optimize the therapeutic effects of DBS in each patient. Furthermore, efforts are being made to automatically adapt the DBS treatment to the fluctuations of disease symptoms. A review of the quantitative approaches currently available for the treatment of Parkinson's disease is presented here with an emphasis on the contributions that systems theoretical approaches have provided to understand the global dynamics of complex neuronal circuits in the brain under DBS. This article is categorized under: Translational, Genomic, and Systems Medicine > Therapeutic Methods Analytical and Computational Methods > Computational Methods Analytical and Computational Methods > Dynamical Methods Physiology > Mammalian Physiology in Health and Disease.

The Wnt signaling pathway is a highly conserved system that regulates complex biological processes across all metazoan species. At the cellular level, secreted Wnt proteins serve to break symmetry and provide cells with positional information that is critical to the patterning of the entire body plan. At the organismal level, Wnt signals are employed to orchestrate fundamental developmental processes, including the specification of the anterior-posterior body axis, induction of the primitive streak and ensuing gastrulation movements, and the generation of cell and tissue diversity. Wnt functions extend into adulthood where they regulate stem cell behavior, tissue homeostasis, and damage repair. Disruption of Wnt signaling activity during embryonic development or in adults results in a spectrum of abnormalities and diseases, including cancer. The molecular mechanisms that underlie the myriad of Wnt-regulated biological effects have been the subject of intense research for over three decades. This review is intended to summarize our current understanding of how Wnt signals are generated and interpreted. This article is categorized under: Biological Mechanisms > Cell Signaling Developmental Biology > Stem Cell Biology and Regeneration.

Sequence-specific transcription factors (TFs) bind short DNA sequences in the genome to regulate the expression of target genes. In the last decade, numerous technical advances have enabled the determination of the DNA-binding specificities of many of these factors. Large-scale screens of many TFs enabled the creation of databases of TF DNA-binding specificities, typically represented as position weight matrices (PWMs). Although great progress has been made in determining and predicting binding specificities systematically, there are still many surprises to be found when studying a particular TF's interactions with DNA in detail. Paralogous TFs' binding specificities can differ in subtle ways, in a manner that is not immediately apparent from looking at their PWMs. These differences affect gene regulatory outputs and enable TFs to rewire transcriptional networks over evolutionary time. This review discusses recent observations made in the study of TF-DNA interactions that highlight the importance of continued in-depth analysis of TF-DNA interactions and their inherent complexity. This article is categorized under: Biological Mechanisms > Regulatory Biology.

As precision medicine becomes increasingly relevant in healthcare, the field of pharmacogenomics (PGx) also continues to gain prominence in the clinical setting. Leading institutions have begun to implement PGx testing and the amount of published PGx literature increases yearly. The Pharmacogenomics Knowledgebase (PharmGKB; www.pharmgkb.org) is one of the foremost worldwide resources for PGx knowledge, and the organization has been adapting and refocusing its mission along with the current revolution in genomic medicine. The PharmGKB website provides a diverse array of PGx information, from annotations of the primary literature to guidelines for adjusting drug treatment based on genetic information. It is freely available and accessible to everyone from researchers to clinicians to everyday citizens. PharmGKB was found over 17 years ago, but continues to be a vital resource for the entire PGx community and the general public. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine.