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Current Opinion in Systems Biology最新文献

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Metabolism as a signal generator in bacteria 作为细菌信号发生器的新陈代谢
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100404
Daniela Ledezma-Tejeida , Evgeniya Schastnaya , Uwe Sauer
{"title":"Metabolism as a signal generator in bacteria","authors":"Daniela Ledezma-Tejeida ,&nbsp;Evgeniya Schastnaya ,&nbsp;Uwe Sauer","doi":"10.1016/j.coisb.2021.100404","DOIUrl":"10.1016/j.coisb.2021.100404","url":null,"abstract":"<div><p>Bacteria constantly monitor their environment to adapt their inner makeup. Beyond providing chemical sustenance, metabolism provides most of the feedback on the cellular environment via metabolite binding to regulatory proteins or mRNA. Although first metabolite-protein interactions were discovered more than 60 years ago, identification of new interactions is still technically challenging and time-consuming. Here, we compiled and quantified the current knowledge on metabolite-protein interactions and review recent advances in the identification of interactions and in understanding how metabolites act as signals to transcription factors, two-component systems, protein kinases, and riboswitches. New systematic methods of metabolite-protein identification and omics integration will accelerate the pace of discovery, a remaining challenge is understanding of functionality and the coordination of local and global metabolic signals across different regulatory layers.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310021000998/pdfft?md5=fbcde72423083c27973f1b0a79ce304b&pid=1-s2.0-S2452310021000998-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46324043","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: 4
External control of microbial populations for bioproduction: A modeling and optimization viewpoint 生物生产中微生物种群的外部控制:建模和优化观点
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100394
François Bertaux , Jakob Ruess , Grégory Batt
{"title":"External control of microbial populations for bioproduction: A modeling and optimization viewpoint","authors":"François Bertaux ,&nbsp;Jakob Ruess ,&nbsp;Grégory Batt","doi":"10.1016/j.coisb.2021.100394","DOIUrl":"10.1016/j.coisb.2021.100394","url":null,"abstract":"<div><p>When engineering microbes for bioproduction, one is necessarily confronted with the existing tradeoff between efficient bioproduction and maintenance of the cell physiology and growth. Moreover, because cellular processes at the single-cell level are coupled with population dynamics via selection mechanisms, this question should be investigated at the population level. Identifying the temporal induction profile that maximizes production in the long term is highly challenging. External control allows to dynamically adapt the strength of the induction from the outside based on intracellular readouts. It allows benchmarking various regulation functions and, coupled with modeling approaches, identifying and applying optimal strategies. In this review, we describe recent advances using quantitative approaches, modeling, and control theory that pave the way to compute external stimulations maximizing long-term production.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45785173","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: 3
Mechanistic models of blood cell fate decisions in the era of single-cell data 单细胞数据时代血细胞命运决定的机制模型
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100355
Ingmar Glauche , Carsten Marr
{"title":"Mechanistic models of blood cell fate decisions in the era of single-cell data","authors":"Ingmar Glauche ,&nbsp;Carsten Marr","doi":"10.1016/j.coisb.2021.100355","DOIUrl":"10.1016/j.coisb.2021.100355","url":null,"abstract":"<div><p>Billions of functionally distinct blood cells emerge from a pool of hematopoietic stem cells in our bodies every day. This progressive differentiation process is hierarchically structured and remarkably robust. We provide an introductory review to mathematical approaches addressing the functional aspects of how lineage choice is potentially implemented on a molecular level. Emerging from studies on the mutual repression of key transcription factors, we illustrate how those simple concepts have been challenged in recent years and subsequently extended. Especially, the analysis of omics data on the single-cell level with computational tools provides descriptive insights on a yet unknown level, while their embedding into a consistent mechanistic and mathematical framework is still incomplete.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.coisb.2021.100355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39761096","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: 2
Systems biology at the giga-scale: Large multiscale models of complex, heterogeneous multicellular systems 千兆级的系统生物学:复杂、异质多细胞系统的大型多尺度模型
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100385
Arnau Montagud , Miguel Ponce-de-Leon , Alfonso Valencia
{"title":"Systems biology at the giga-scale: Large multiscale models of complex, heterogeneous multicellular systems","authors":"Arnau Montagud ,&nbsp;Miguel Ponce-de-Leon ,&nbsp;Alfonso Valencia","doi":"10.1016/j.coisb.2021.100385","DOIUrl":"10.1016/j.coisb.2021.100385","url":null,"abstract":"<div><p>Agent-based modelling has proven its usefulness in several biomedical projects by explaining and uncovering mechanisms in diseases. Nevertheless, the scenarios addressed in these models usually consider a small number of cells, lack cell-specific characterisation and dynamic interactions and have a simplistic environment description. Tools that enable scalable, real-sized simulations of biological systems that require complex setups are needed to have simulations closer to biomedical scenarios that can capture cell-to-cell heterogeneity and system-wide emerging properties. To deliver simulations at the giga-scale (10<sup>9</sup> cells), different tools have implemented technologies to run in high-performance computing clusters. We hereby review these efforts and detail the main areas of improvement the field needs to focus on to have simulations that are a step closer to having digital twins.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310021000792/pdfft?md5=7797269073a56e3d5733626dc36a5f79&pid=1-s2.0-S2452310021000792-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42512765","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: 18
Data integration in logic-based models of biological mechanisms 基于逻辑的生物机制模型中的数据集成
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100386
Benjamin A. Hall , Anna Niarakis
{"title":"Data integration in logic-based models of biological mechanisms","authors":"Benjamin A. Hall ,&nbsp;Anna Niarakis","doi":"10.1016/j.coisb.2021.100386","DOIUrl":"https://doi.org/10.1016/j.coisb.2021.100386","url":null,"abstract":"<div><p>Discrete, logic-based models are increasingly used to describe biological mechanisms. Initially introduced to study gene regulation, these models evolved to cover various molecular mechanisms, such as signaling, transcription factor cooperativity, and even metabolic processes. The abstract nature and amenability of discrete models to robust mathematical analyses make them appropriate for addressing a wide range of complex biological problems. Recent technological breakthroughs have generated a wealth of high-throughput data. Novel, literature-based representations of biological processes and emerging algorithms offer new opportunities for model construction. Here, we review up-to-date efforts to address challenging biological questions by incorporating omic data into logic-based models and discuss critical difficulties in constructing and analyzing integrative, large-scale, logic-based models of biological mechanisms.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310021000809/pdfft?md5=94355530bdb10d0fd95691ad6df8a013&pid=1-s2.0-S2452310021000809-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137298375","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: 0
Control engineering meets synthetic biology: Foundations and applications 控制工程与合成生物学:基础与应用
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100397
Iacopo Ruolo , Sara Napolitano , Davide Salzano , Mario di Bernardo , Diego di Bernardo
{"title":"Control engineering meets synthetic biology: Foundations and applications","authors":"Iacopo Ruolo ,&nbsp;Sara Napolitano ,&nbsp;Davide Salzano ,&nbsp;Mario di Bernardo ,&nbsp;Diego di Bernardo","doi":"10.1016/j.coisb.2021.100397","DOIUrl":"10.1016/j.coisb.2021.100397","url":null,"abstract":"<div><p>Synthetic Biology enables the construction of new genetic<span> circuits with the final goal of controlling cellular behaviour. However, the noisy nature of biomolecular interactions renders a fine regulation of such circuits necessary for their correct operation. A possible solution is cybergenetics, a new discipline merging the tools of Synthetic biology with those of control theory. Biomolecular controllers can be classified into three different categories (i) embedded, in which the controller is implemented as a genetic circuit co-existing in the same cell with the process to be controlled; (ii) external, where the controller is implemented as a software in a computer; (iii) multicellular, in which the controller and the process to be controlled are in two different cell populations. Here, we describe the advantages and drawbacks of each one of the approaches, expounding their main advantages, limitations, and applications.</span></p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43232528","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: 11
Quorum sensing in synthetic biology: A review 合成生物学中的群体感应:综述
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100378
Alice Boo , Rodrigo Ledesma Amaro , Guy-Bart Stan
{"title":"Quorum sensing in synthetic biology: A review","authors":"Alice Boo ,&nbsp;Rodrigo Ledesma Amaro ,&nbsp;Guy-Bart Stan","doi":"10.1016/j.coisb.2021.100378","DOIUrl":"10.1016/j.coisb.2021.100378","url":null,"abstract":"<div><p><span>In nature, quorum sensing is one of the mechanisms bacterial populations use to communicate with their own species or across species to coordinate behaviours. For the last 20 years, synthetic biologists have recognised the remarkable properties of quorum sensing to build </span>genetic<span> circuits responsive to population density. This has led to progress in designing dynamic, coordinated and sometimes multicellular systems for bioproduction in metabolic engineering and for increased spatial and temporal complexity in synthetic biology. In this review, we highlight recent works focused on using quorum sensing to engineer cell–cell behaviour.</span></p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.coisb.2021.100378","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46556397","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: 26
Experimental analysis and modeling of single-cell time-course data 单细胞时程数据的实验分析与建模
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100359
Eline Yafelé Bijman, Hans-Michael Kaltenbach, Jörg Stelling
{"title":"Experimental analysis and modeling of single-cell time-course data","authors":"Eline Yafelé Bijman,&nbsp;Hans-Michael Kaltenbach,&nbsp;Jörg Stelling","doi":"10.1016/j.coisb.2021.100359","DOIUrl":"10.1016/j.coisb.2021.100359","url":null,"abstract":"<div><p>Contemporary single-cell experiments produce vast amounts of data, but the interpretation of these data is far from straightforward. In particular, understanding mechanisms and sources of cell-to-cell variability, given highly complex and nonlinear cellular networks, precludes intuitive interpretation. It requires careful computational and mathematical analysis instead. Here, we discuss different types of single-cell data and computational, model-based methods currently used to analyze them. We argue that mechanistic models incorporating subpopulation or cell-specific parameters can help to identify sources of variation and to understand experimentally observed behaviors. We highlight how data types and qualities, together with the nonlinearity of single-cell dynamics, make it challenging to identify the correct underlying biological mechanisms and we outline avenues to address these challenges.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.coisb.2021.100359","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47681251","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: 4
Metabolic pathways fuelling protumourigenic cancer-associated fibroblast functions 代谢途径促进致癌原纤维细胞功能
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100377
Emily J. Kay , Sara Zanivan
{"title":"Metabolic pathways fuelling protumourigenic cancer-associated fibroblast functions","authors":"Emily J. Kay ,&nbsp;Sara Zanivan","doi":"10.1016/j.coisb.2021.100377","DOIUrl":"https://doi.org/10.1016/j.coisb.2021.100377","url":null,"abstract":"<div><p>Cancer-associated fibroblasts (CAFs) play many roles in supporting tumour growth and progression, and metabolic rewiring is known to be a hallmark of CAF activation. How to effectively target CAF metabolism is still an open question, however. Recent research shows that CAFs and cancer cells engage in complex metabolic crosstalk, which may offer strategies to metabolically target both tumour and stroma. CAF metabolic rewiring also regulates intrinsic CAF protumourigenic functions, by inducing epigenetic changes to maintain CAF activation and by promoting hallmarks of CAFs such as extracellular matrix (ECM) production and immunosuppression. Finally, the emerging field of CAF subpopulations has opened up possibilities for metabolically targeting specific protumourigenic subgroups and raises new questions about how we define and target CAFs.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.coisb.2021.100377","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137298478","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: 1
Light express 光的表达
IF 3.7
Current Opinion in Systems Biology Pub Date : 2021-12-01 DOI: 10.1016/j.coisb.2021.100356
Giada Forlani , Barbara Di Ventura
{"title":"Light express","authors":"Giada Forlani ,&nbsp;Barbara Di Ventura","doi":"10.1016/j.coisb.2021.100356","DOIUrl":"https://doi.org/10.1016/j.coisb.2021.100356","url":null,"abstract":"<div><p>Each of us is a unique individual despite carrying almost the same genetic<span> information as anyone else. Zooming in into our body, we find the same pattern: all cells share the same genome, and yet they look and behave differently. The process of gene expression is the reason behind this fascinating phenomenon whereby the same genome is translated in different sets of molecules being present in the cell at any given time. The ability to precisely control this process endows researchers with great power, not only for basic science purposes but also for biotechnological and biomedical applications. In this review, we will discuss the current arsenal of tools that consent to control gene expression using light as the external trigger. These tools are, in most cases, preferable to those based on chemical triggers owing to the many favorable properties of light, foremost its spatial confineability and easy removal.</span></p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.coisb.2021.100356","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137298481","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: 0
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