Current Opinion in Systems Biology最新文献_第9页

Metabolic dynamics during the cell cycle 细胞周期中的代谢动力学

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-06-01 DOI: 10.1016/j.coisb.2022.100415

Andre Zylstra, Matthias Heinemann

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引用次数: 4

Organelle dysfunction and its contribution to metabolic impairments in aging and age-related diseases 细胞器功能障碍及其对衰老和年龄相关疾病代谢损伤的贡献

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-06-01 DOI: 10.1016/j.coisb.2022.100416

Julia C. Heiby, Alessandro Ori

引用次数: 1

Editorial overview: Control engineering in synthetic biology: Foundations and applications 编辑概述:合成生物学中的控制工程:基础和应用

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI: 10.1016/j.coisb.2021.100406

Ron Weiss, Velia Siciliano

引用次数: 0

Editorial Board Page 编委会页面

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI: 10.1016/S2452-3100(22)00004-X

引用次数: 0

Metabolomics in diagnostics of inborn metabolic disorders 代谢组学在先天性代谢紊乱诊断中的应用

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI: 10.1016/j.coisb.2021.100409

Judith JM. Jans , Melissa H. Broeks , Nanda M. Verhoeven-Duif

{"title":"Metabolomics in diagnostics of inborn metabolic disorders","authors":"Judith JM. Jans , Melissa H. Broeks , Nanda M. Verhoeven-Duif","doi":"10.1016/j.coisb.2021.100409","DOIUrl":"10.1016/j.coisb.2021.100409","url":null,"abstract":"<div><p>Finding a diagnosis for patients with a rare inborn metabolic disorder can be a long and difficult path. Whereas next generation sequencing is now a commonly used modality, which has significantly impacted the diagnostic yield and speed, next generation metabolic screening through untargeted metabolomics is next in line to prove its value in the diagnostic trajectory.</p><p>Untargeted metabolomics, often based on mass spectrometry platforms, is a well-established technology for the identification of novel disease markers. However, untargeted metabolomics as first line diagnostics for rare disease is now only gradually making its way into clinical practice. Most retrospective studies show that the majority of inborn metabolic disorder can be detected through untargeted metabolomics. Some diseases will still go undetected, which diagnoses are missed depends on the specific metabolomics method chosen; there is no single all-encompassing platform. Therefore, careful assessments of the opportunities and limitations are currently undertaken in prospective studies, combining untargeted metabolomics in the diagnostics setting with the current gold standard genetic and biochemical diagnostic modalities. These studies show an increased diagnostic yield when implementing untargeted metabolomics. Given the continuing technological advances, defining the optimal timing, place, and order of the various diagnostic modalities will keep on evolving in the foreseen future.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"29 ","pages":"Article 100409"},"PeriodicalIF":3.7,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310021001049/pdfft?md5=967143ed4644a1e92c1cb82efc3ba605&pid=1-s2.0-S2452310021001049-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42607685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Compartmentalization of metabolism between cell types in multicellular organisms: A computational perspective 多细胞生物中细胞类型间代谢的区隔化:计算视角

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI: 10.1016/j.coisb.2021.100407

Xuhang Li, L. Safak Yilmaz, Albertha J.M. Walhout

{"title":"Compartmentalization of metabolism between cell types in multicellular organisms: A computational perspective","authors":"Xuhang Li, L. Safak Yilmaz, Albertha J.M. Walhout","doi":"10.1016/j.coisb.2021.100407","DOIUrl":"10.1016/j.coisb.2021.100407","url":null,"abstract":"<div><p><span>In multicellular organisms, metabolism is compartmentalized at many levels, including tissues and organs, different cell types, and subcellular compartments. Compartmentalization<span> creates a coordinated homeostatic system where each compartment contributes to the production of energy and biomolecules that the organism needs to carry out specific metabolic tasks. Experimentally studying metabolic compartmentalization and metabolic interactions between cells and tissues in multicellular organisms is challenging at a systems level. However, recent progress in computational modeling<span> provides an alternative approach to this problem. Here, we discuss how integrating metabolic network modeling<span> with omics data offers an opportunity to reveal metabolic states at the level of organs, tissues and, ultimately, individual cells. We review the current status of genome-scale metabolic network models in multicellular organisms, methods to study metabolic compartmentalization </span></span></span></span><em>in silico</em>, and insights gained from computational analyses. We also discuss outstanding challenges and provide perspectives for the future directions of the field.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"29 ","pages":"Article 100407"},"PeriodicalIF":3.7,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10800315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Lessons from metabolic perturbations in lysosomal storage disorders for neurodegeneration 神经退行性疾病溶酶体贮积障碍的代谢扰动的教训

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI: 10.1016/j.coisb.2021.100408

Uche N. Medoh , Julie Y. Chen , Monther Abu-Remaileh

{"title":"Lessons from metabolic perturbations in lysosomal storage disorders for neurodegeneration","authors":"Uche N. Medoh , Julie Y. Chen , Monther Abu-Remaileh","doi":"10.1016/j.coisb.2021.100408","DOIUrl":"10.1016/j.coisb.2021.100408","url":null,"abstract":"<div><p><span>Age-related neurodegenerative diseases are a clinically unmet need with unabated prevalence around the world. Several genetic studies link these diseases with lysosomal dysfunction; however, a mechanistic understanding of how lysosomal perturbations result in neurodegeneration is unclear. Neuronopathic lysosomal storage disorders represent an attractive model for elucidating such mechanisms as they share several metabolic pathological hallmarks with common neurodegenerative diseases. This review explores how altered lipid metabolism, calcium dyshomeostasis, mitochondrial dysfunction, </span>oxidative stress, and impaired autophagic flux contribute to cellular pathobiology in age-related neurodegeneration and neuronopathic lysosomal storage disorders. It further debates whether general lysosomal dysfunction owing to toxic substrate accumulation or extralysosomal nutrient deprivation drives these downstream processes. With increasing evidence for the latter, future studies should investigate additional lysosomal nutrients that protect against neurodegeneration using emerging subcellular ‘omics’-based technologies with the promise of identifying therapeutic targets for the treatment of neurodegenerative diseases.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"29 ","pages":"Article 100408"},"PeriodicalIF":3.7,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41515878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Editorial overview: ‘Mathematical modelling of high-throughput and high-content data’ 编辑概述:“高通量和高含量数据的数学建模”

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI: 10.1016/j.coisb.2021.100405

Jan Hasenauer, Julio R. Banga

引用次数: 1

Using resource constraints derived from genomic and proteomic data in metabolic network models 利用代谢网络模型中基因组和蛋白质组学数据得出的资源约束

IF 3.7

Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI: 10.1016/j.coisb.2021.100400

Kobe De Becker , Niccolò Totis , Kristel Bernaerts , Steffen Waldherr

引用次数: 3

The evolution of the metabolic network over long timelines 长时间内代谢网络的进化