Pub Date : 2022-06-01DOI: 10.1016/S2452-3100(22)00014-2
{"title":"Editorial Board Page","authors":"","doi":"10.1016/S2452-3100(22)00014-2","DOIUrl":"https://doi.org/10.1016/S2452-3100(22)00014-2","url":null,"abstract":"","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"30 ","pages":"Article 100428"},"PeriodicalIF":3.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310022000142/pdfft?md5=3e66d4601abd1b70c484795123c5bd0b&pid=1-s2.0-S2452310022000142-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137146922","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}
Pub Date : 2022-06-01DOI: 10.1016/j.coisb.2022.100423
Christian Schmerling , Theresa Kouril , Jacky Snoep , Christopher Bräsen , Bettina Siebers
The text-book picture of a perfect, well organised metabolism with highly specific enzymes, is challenged by non-enzymatic reactions and promiscuous enzymes. This, so-called ‘underground metabolism’, is a special challenge for hyperthermophilic Archaea that thrive at temperatures above 80 °C and possess modified central metabolic pathways often with promiscuous enzymes. Hence, the question arises how extremely thermophilic Archaea can operate their unusual metabolism at temperatures where many pathway intermediates are unstable? We herein discuss current insights in the underground metabolism and metabolic thermoadaptation of (hyper)thermophilic Archaea. So far, only a few repair enzymes and salvaging pathways have been investigated in Archaea. Studies of the central carbohydrate metabolism indicate that a number of different strategies have evolved: 1) reduction of the concentration of unstable metabolites, 2) different pathway topologies are used with newly induced enzymes, and 3) damaged metabolites are removed via new metabolic pathways.
{"title":"Enhanced underground metabolism challenges life at high temperature–metabolic thermoadaptation in hyperthermophilic Archaea","authors":"Christian Schmerling , Theresa Kouril , Jacky Snoep , Christopher Bräsen , Bettina Siebers","doi":"10.1016/j.coisb.2022.100423","DOIUrl":"10.1016/j.coisb.2022.100423","url":null,"abstract":"<div><p><span><span>The text-book picture of a perfect, well organised metabolism with highly specific enzymes<span>, is challenged by non-enzymatic reactions and promiscuous enzymes. This, so-called ‘underground metabolism’, is a special challenge for hyperthermophilic Archaea that thrive at temperatures above 80 °C and possess modified central metabolic pathways often with promiscuous enzymes. Hence, the question arises how extremely </span></span>thermophilic Archaea can operate their unusual metabolism at temperatures where many pathway intermediates are unstable? We herein discuss current insights in the underground metabolism and metabolic </span>thermoadaptation<span><span> of (hyper)thermophilic Archaea. So far, only a few repair enzymes and salvaging pathways have been investigated in Archaea. Studies of the central </span>carbohydrate metabolism indicate that a number of different strategies have evolved: 1) reduction of the concentration of unstable metabolites, 2) different pathway topologies are used with newly induced enzymes, and 3) damaged metabolites are removed via new metabolic pathways.</span></p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"30 ","pages":"Article 100423"},"PeriodicalIF":3.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46353795","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}
Pub Date : 2022-06-01DOI: 10.1016/j.coisb.2022.100417
Sebastian Wenk , Nico J. Claassens , Steffen N. Lindner
Synthetic biology modifies biological systems with the aim of creating new biological parts, devices, and even organisms. Systems biology deciphers the design principles of biological systems trying to derive the mathematical logic behind biological processes. Although different in their respective research approaches and questions, both disciplines are clearly interconnected. Without sufficient understanding of the biological system, synthetic biology studies cannot be properly designed and conducted. On the other hand, systems biology can profit from new biological systems generated by synthetic biology approaches, which can reveal important insights into cellular processes and allow a better understanding of the principles of life. In this article, we present state-of-the-art synthetic biology approaches that focus on the engineering of synthetic metabolism in microbial hosts and show how their implementation has led to new fundamental discoveries on enzyme reversibility, promiscuity, and “underground metabolism”. We further discuss how the combination of rational engineering and adaptive laboratory evolution has enabled the generation of microbes with a synthetic central metabolism, leading to completely new metabolic phenotypes. These organisms provide a great resource for future studies to deepen our systems-level understanding on the principles that govern metabolic networks and evolution.
{"title":"Synthetic metabolism approaches: A valuable resource for systems biology","authors":"Sebastian Wenk , Nico J. Claassens , Steffen N. Lindner","doi":"10.1016/j.coisb.2022.100417","DOIUrl":"10.1016/j.coisb.2022.100417","url":null,"abstract":"<div><p>Synthetic biology modifies biological systems with the aim of creating new biological parts, devices, and even organisms. Systems biology deciphers the design principles of biological systems trying to derive the mathematical logic behind biological processes. Although different in their respective research approaches and questions, both disciplines are clearly interconnected. Without sufficient understanding of the biological system, synthetic biology studies cannot be properly designed and conducted. On the other hand, systems biology can profit from new biological systems generated by synthetic biology approaches, which can reveal important insights into cellular processes and allow a better understanding of the principles of life. In this article, we present state-of-the-art synthetic biology approaches that focus on the engineering of synthetic metabolism in microbial hosts and show how their implementation has led to new fundamental discoveries on enzyme reversibility, promiscuity, and “underground metabolism”. We further discuss how the combination of rational engineering and adaptive laboratory evolution has enabled the generation of microbes with a synthetic central metabolism, leading to completely new metabolic phenotypes. These organisms provide a great resource for future studies to deepen our systems-level understanding on the principles that govern metabolic networks and evolution.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"30 ","pages":"Article 100417"},"PeriodicalIF":3.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310022000038/pdfft?md5=c9f96786811b96040d981e16ebdbfe34&pid=1-s2.0-S2452310022000038-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46772608","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}
Pub Date : 2022-06-01DOI: 10.1016/j.coisb.2022.100415
Andre Zylstra, Matthias Heinemann
While we have a solid understanding of the cell biological and biochemical control aspects of the eukaryotic cell growth and division process, much less is known about the metabolic and biosynthetic dynamics during the cell cycle. Here, we review recent discoveries made at the single-cell and population level that show that budding yeast (Saccharomyces cerevisiae) metabolism oscillates in synchrony with the cell cycle in actively dividing cells, as well as independently when the cell cycle is halted. In fact, emerging evidence suggests that the cell cycle-independent metabolic oscillations interact with elements of the cell cycle machinery via several possible mechanisms. Furthermore, recent reports indicate that different biosynthetic processes exhibit temporally changing activity patterns during the cell cycle. Thus, resources are drawn from primary metabolism in a dynamic manner, potentially giving rise to metabolic oscillations. Finally, we highlight work with mammalian cells indicating that similar metabolic dynamics might also exist in higher eukaryotes.
{"title":"Metabolic dynamics during the cell cycle","authors":"Andre Zylstra, Matthias Heinemann","doi":"10.1016/j.coisb.2022.100415","DOIUrl":"10.1016/j.coisb.2022.100415","url":null,"abstract":"<div><p>While we have a solid understanding of the cell biological and biochemical control aspects of the eukaryotic cell growth and division process, much less is known about the metabolic and biosynthetic dynamics during the cell cycle. Here, we review recent discoveries made at the single-cell and population level that show that budding yeast (<em>Saccharomyces cerevisiae</em>) metabolism oscillates in synchrony with the cell cycle in actively dividing cells, as well as independently when the cell cycle is halted. In fact, emerging evidence suggests that the cell cycle-independent metabolic oscillations interact with elements of the cell cycle machinery via several possible mechanisms. Furthermore, recent reports indicate that different biosynthetic processes exhibit temporally changing activity patterns during the cell cycle. Thus, resources are drawn from primary metabolism in a dynamic manner, potentially giving rise to metabolic oscillations. Finally, we highlight work with mammalian cells indicating that similar metabolic dynamics might also exist in higher eukaryotes.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"30 ","pages":"Article 100415"},"PeriodicalIF":3.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310022000014/pdfft?md5=0ceeea28044602a21abcb5841856610a&pid=1-s2.0-S2452310022000014-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41405427","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}
Pub Date : 2022-06-01DOI: 10.1016/j.coisb.2022.100416
Julia C. Heiby, Alessandro Ori
Aging is a major risk factor for most diseases. Pathways regulating metabolism, including nutrient sensing, energy production, and synthesis and degradation of macromolecules, have been identified as key regulators of organismal lifespan and implicated in several late-onset diseases, such as most neurodegenerative disorders. In this review, we focus on emerging evidence that links the remodeling of key organelles, namely mitochondria and lysosomes, to metabolic alterations that manifest during the aging process. We highlight data demonstrating a reciprocal interaction between organelle (dys)-function and protein homeostasis in aging. We also discuss examples of cell-type-specific metabolic alterations that can influence organ function locally and whole organism aging via inter-tissue communication. Finally, we propose how emerging methods could enable to characterize in vivo the impact of aging on organelle composition and function.
{"title":"Organelle dysfunction and its contribution to metabolic impairments in aging and age-related diseases","authors":"Julia C. Heiby, Alessandro Ori","doi":"10.1016/j.coisb.2022.100416","DOIUrl":"10.1016/j.coisb.2022.100416","url":null,"abstract":"<div><p>Aging is a major risk factor for most diseases. Pathways regulating metabolism, including nutrient sensing, energy production, and synthesis and degradation of macromolecules, have been identified as key regulators of organismal lifespan and implicated in several late-onset diseases, such as most neurodegenerative disorders. In this review, we focus on emerging evidence that links the remodeling of key organelles, namely mitochondria and lysosomes, to metabolic alterations that manifest during the aging process. We highlight data demonstrating a reciprocal interaction between organelle (dys)-function and protein homeostasis in aging. We also discuss examples of cell-type-specific metabolic alterations that can influence organ function locally and whole organism aging via inter-tissue communication. Finally, we propose how emerging methods could enable to characterize <em>in vivo</em> the impact of aging on organelle composition and function.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"30 ","pages":"Article 100416"},"PeriodicalIF":3.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310022000026/pdfft?md5=f704136af8bba1493575582fb5a97f28&pid=1-s2.0-S2452310022000026-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44582994","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}
Pub Date : 2022-03-01DOI: 10.1016/j.coisb.2021.100406
Ron Weiss, Velia Siciliano
{"title":"Editorial overview: Control engineering in synthetic biology: Foundations and applications","authors":"Ron Weiss, Velia Siciliano","doi":"10.1016/j.coisb.2021.100406","DOIUrl":"10.1016/j.coisb.2021.100406","url":null,"abstract":"","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"29 ","pages":"Article 100406"},"PeriodicalIF":3.7,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44412707","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}
Pub Date : 2022-03-01DOI: 10.1016/j.coisb.2021.100409
Judith JM. Jans , Melissa H. Broeks , Nanda M. Verhoeven-Duif
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.
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.
{"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}
Pub Date : 2022-03-01DOI: 10.1016/S2452-3100(22)00004-X
{"title":"Editorial Board Page","authors":"","doi":"10.1016/S2452-3100(22)00004-X","DOIUrl":"https://doi.org/10.1016/S2452-3100(22)00004-X","url":null,"abstract":"","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"29 ","pages":"Article 100418"},"PeriodicalIF":3.7,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S245231002200004X/pdfft?md5=6bb36100a0d60d40d0fc6462805d6ca8&pid=1-s2.0-S245231002200004X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137355923","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}
Pub Date : 2022-03-01DOI: 10.1016/j.coisb.2021.100407
Xuhang Li, L. Safak Yilmaz, Albertha J.M. Walhout
In multicellular organisms, metabolism is compartmentalized at many levels, including tissues and organs, different cell types, and subcellular compartments. Compartmentalization 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 provides an alternative approach to this problem. Here, we discuss how integrating metabolic network modeling 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 in silico, and insights gained from computational analyses. We also discuss outstanding challenges and provide perspectives for the future directions of the field.
{"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}
Pub Date : 2022-03-01DOI: 10.1016/j.coisb.2021.100408
Uche N. Medoh , Julie Y. Chen , Monther Abu-Remaileh
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, 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.
{"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}