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Amiri F, Benson JD. A three-dimensional lattice-free agent-based model of intracellular ice formation and propagation and intercellular mechanics in liver tissues. ROYAL SOCIETY OPEN SCIENCE 2024; 11:231337. [PMID: 39021779 PMCID: PMC11252675 DOI: 10.1098/rsos.231337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/22/2024] [Indexed: 07/20/2024]
Abstract
A successful cryopreservation of tissues and organs is crucial for medical procedures and drug development acceleration. However, there are only a few instances of successful tissue cryopreservation. One of the main obstacles to successful cryopreservation is intracellular ice damage. Understanding how ice spreads can accelerate protocol development and enable model-based decision-making. Previous models of intracellular ice formation in individual cells have been extended to one-cell-wide arrays to establish the theory of intercellular ice propagation in tissues. The current lattice-based ice propagation models do not account for intercellular forces resulting from cell solidification, which could lead to mechanical disruption of tissue structures during freezing. Moreover, these models have not been expanded to include more realistic tissue architectures. In this article, we discuss the development and validation of a stochastic model for the formation and propagation of ice in small tissues using lattice-free agent-based model. We have improved the existing model by incorporating the mechanical effects of water crystallization within cells. Using information from previous research, we have also created a new model that accounts for ice growth in tissue slabs, spheroids and hepatocyte discs. Our model demonstrates that individual cell freezing can have mechanical consequences and is consistent with earlier findings.
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Affiliation(s)
- Fatemeh Amiri
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - James D. Benson
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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2
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Walker M, Moore H, Ataya A, Pham A, Corris PA, Laubenbacher R, Bryant AJ. A perfectly imperfect engine: Utilizing the digital twin paradigm in pulmonary hypertension. Pulm Circ 2024; 14:e12392. [PMID: 38933181 PMCID: PMC11199193 DOI: 10.1002/pul2.12392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 04/08/2024] [Accepted: 05/16/2024] [Indexed: 06/28/2024] Open
Abstract
Pulmonary hypertension (PH) is a severe medical condition with a number of treatment options, the majority of which are introduced without consideration of the underlying mechanisms driving it within an individual and thus a lack of tailored approach to treatment. The one exception is a patient presenting with apparent pulmonary arterial hypertension and shown to have vaso-responsive disease, whose clinical course and prognosis is significantly improved by high dose calcium channel blockers. PH is however characterized by a relative abundance of available data from patient cohorts, ranging from molecular data characterizing gene and protein expression in different tissues to physiological data at the organ level and clinical information. Integrating available data with mechanistic information at the different scales into computational models suggests an approach to a more personalized treatment of the disease using model-based optimization of interventions for individual patients. That is, constructing digital twins of the disease, customized to a patient, promises to be a key technology for personalized medicine, with the aim of optimizing use of existing treatments and developing novel interventions, such as new drugs. This article presents a perspective on this approach in the context of a review of existing computational models for different aspects of the disease, and it lays out a roadmap for a path to realizing it.
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Affiliation(s)
- Melody Walker
- University of Florida College of MedicineGainesvilleFloridaUSA
| | - Helen Moore
- University of Florida College of MedicineGainesvilleFloridaUSA
| | - Ali Ataya
- University of Florida College of MedicineGainesvilleFloridaUSA
| | - Ann Pham
- University of Florida College of MedicineGainesvilleFloridaUSA
| | - Paul A. Corris
- The Faculty of Medical Sciences Newcastle UniversityNewcastle upon TyneUK
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3
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Cain JY, Evarts JI, Yu JS, Bagheri N. Incorporating temporal information during feature engineering bolsters emulation of spatio-temporal emergence. BIOINFORMATICS (OXFORD, ENGLAND) 2024; 40:btae131. [PMID: 38444088 PMCID: PMC10957516 DOI: 10.1093/bioinformatics/btae131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 02/08/2024] [Accepted: 03/01/2024] [Indexed: 03/07/2024]
Abstract
MOTIVATION Emergent biological dynamics derive from the evolution of lower-level spatial and temporal processes. A long-standing challenge for scientists and engineers is identifying simple low-level rules that give rise to complex higher-level dynamics. High-resolution biological data acquisition enables this identification and has evolved at a rapid pace for both experimental and computational approaches. Simultaneously harnessing the resolution and managing the expense of emerging technologies-e.g. live cell imaging, scRNAseq, agent-based models-requires a deeper understanding of how spatial and temporal axes impact biological systems. Effective emulation is a promising solution to manage the expense of increasingly complex high-resolution computational models. In this research, we focus on the emulation of a tumor microenvironment agent-based model to examine the relationship between spatial and temporal environment features, and emergent tumor properties. RESULTS Despite significant feature engineering, we find limited predictive capacity of tumor properties from initial system representations. However, incorporating temporal information derived from intermediate simulation states dramatically improves the predictive performance of machine learning models. We train a deep-learning emulator on intermediate simulation states and observe promising enhancements over emulators trained solely on initial conditions. Our results underscore the importance of incorporating temporal information in the evaluation of spatio-temporal emergent behavior. Nevertheless, the emulators exhibit inconsistent performance, suggesting that the underlying model characterizes unique cell populations dynamics that are not easily replaced. AVAILABILITY AND IMPLEMENTATION All source codes for the agent-based model, emulation, and analyses are publicly available at the corresponding DOIs: 10.5281/zenodo.10622155, 10.5281/zenodo.10611675, 10.5281/zenodo.10621244, respectively.
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Affiliation(s)
- Jason Y Cain
- Department of Chemical Engineering, University of Washington, Seattle, WA 98195, United States
| | - Jacob I Evarts
- Department of Biology, University of Washington, Seattle, WA 98195, United States
| | - Jessica S Yu
- Department of Biology, University of Washington, Seattle, WA 98195, United States
| | - Neda Bagheri
- Department of Chemical Engineering, University of Washington, Seattle, WA 98195, United States
- Department of Biology, University of Washington, Seattle, WA 98195, United States
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4
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Azam I, Benson JD. Multiscale transport and 4D time-lapse imaging in precision-cut liver slices (PCLS). PeerJ 2024; 12:e16994. [PMID: 38426134 PMCID: PMC10903333 DOI: 10.7717/peerj.16994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 02/01/2024] [Indexed: 03/02/2024] Open
Abstract
Background Monitoring cellular processes across different levels of complexity, from the cellular to the tissue scale, is important for understanding tissue structure and function. However, it is challenging to monitor and estimate these structural and dynamic interactions within three-dimensional (3D) tissue models. Objective The aim of this study was to design a method for imaging, tracking, and quantifying 3D changes in cell morphology (shape and size) within liver tissue, specifically a precision-cut liver slice (PCLS). A PCLS is a 3D model of the liver that allows the study of the structure and function of liver cells in their native microenvironment. Methods Here, we present a method for imaging liver tissue during anisosmotic exposure in a multispectral four-dimensional manner. Three metrics of tissue morphology were measured to quantify the effects of osmotic stress on liver tissue. We estimated the changes in the volume of whole precision cut liver slices, quantified the changes in nuclei position, and calculated the changes in volumetric responses of tissue-embedded cells. Results During equilibration with cell-membrane-permeating and non-permeating solutes, the whole tissue experiences shrinkage and expansion. As nuclei showed a change in position and directional displacement under osmotic stress, we demonstrate that nuclei could be used as a probe to measure local osmotic and mechanical stress. Moreover, we demonstrate that cells change their volume within tissue slices as a result of osmotic perturbation and that this change in volume is dependent on the position of the cell within the tissue and the duration of the exposure. Conclusion The results of this study have implications for a better understanding of multiscale transport, mechanobiology, and triggered biological responses within complex biological structures.
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Affiliation(s)
- Iqra Azam
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - James D. Benson
- Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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5
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Riggi M, Torrez RM, Iwasa JH. 3D animation as a tool for integrative modeling of dynamic molecular mechanisms. Structure 2024; 32:122-130. [PMID: 38183978 PMCID: PMC10872329 DOI: 10.1016/j.str.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/01/2023] [Accepted: 12/12/2023] [Indexed: 01/08/2024]
Abstract
As the scientific community accumulates diverse data describing how molecular mechanisms occur, creating and sharing visual models that integrate the richness of this information has become increasingly important to help us explore, refine, and communicate our hypotheses. Three-dimensional (3D) animation is a powerful tool to capture dynamic hypotheses that are otherwise difficult or impossible to visualize using traditional 2D illustration techniques. This perspective discusses the current and future roles that 3D animation can play in the research sphere.
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Affiliation(s)
- Margot Riggi
- Department of Biochemistry, University of Utah, Salt Lake City, UT, USA
| | - Rachel M Torrez
- Department of Biochemistry, University of Utah, Salt Lake City, UT, USA
| | - Janet H Iwasa
- Department of Biochemistry, University of Utah, Salt Lake City, UT, USA.
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6
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Morvan C, Nekoua MP, Debuysschere C, Alidjinou EK, Hober D. Antibody-dependent enhancement and neutralization against CVB4 investigated in vitro and in silico through an agent-based model. J Med Virol 2024; 96:e29399. [PMID: 38235792 DOI: 10.1002/jmv.29399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/04/2023] [Accepted: 01/02/2024] [Indexed: 01/19/2024]
Abstract
The infection with coxsackievirus B4 (CVB4) can be enhanced in vitro by antibodies directed against the viral capsid protein VP4. In peripheral blood mononuclear cells, antibody-dependent enhancement (ADE) of CVB4 infection leads to the production of interferon alpha (IFN-α). To investigate ADE of CVB4-induced production of IFN-α, an agent-based model was constructed with enhancing and neutralizing antibodies. The model recapitulates viral neutralization and ADE in silico. The enhancing and neutralizing activities of serum samples were evaluated in vitro to confront the model predictions with experimental results. Increasing the incubation time of CVB4 with serum samples improves virus neutralization in silico as well as in vitro. It also results in ADE at lower antibody numbers in silico, which is confirmed in vitro with IFN-α production at lower serum concentrations. Furthermore, incubation of CVB4 with serum at a low temperature does not induce IFN-α production in vitro. Thus, taken together our results suggest that enhancing antibodies bind cryptic epitopes, more accessible with longer incubation time and at higher temperature due to changes in capsid conformation, consistent with previous results indicating that enhancing antibodies are anti-VP4 antibodies.
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Affiliation(s)
- Corentin Morvan
- Laboratoire de Virologie ULR3610, Univ Lille et CHU Lille, Lille, France
| | | | - Cyril Debuysschere
- Laboratoire de Virologie ULR3610, Univ Lille et CHU Lille, Lille, France
| | | | - Didier Hober
- Laboratoire de Virologie ULR3610, Univ Lille et CHU Lille, Lille, France
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7
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Romero-Arias JR, González-Castro CA, Ramírez-Santiago G. A multiscale model of the role of microenvironmental factors in cell segregation and heterogeneity in breast cancer development. PLoS Comput Biol 2023; 19:e1011673. [PMID: 37992135 DOI: 10.1371/journal.pcbi.1011673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 12/06/2023] [Accepted: 11/08/2023] [Indexed: 11/24/2023] Open
Abstract
We analyzed a quantitative multiscale model that describes the epigenetic dynamics during the growth and evolution of an avascular tumor. A gene regulatory network (GRN) formed by a set of ten genes that are believed to play an important role in breast cancer development was kinetically coupled to the microenvironmental agents: glucose, estrogens, and oxygen. The dynamics of spontaneous mutations was described by a Yule-Furry master equation whose solution represents the probability that a given cell in the tissue undergoes a certain number of mutations at a given time. We assumed that the mutation rate is modified by a spatial gradient of nutrients. The tumor mass was simulated by means of cellular automata supplemented with a set of reaction diffusion equations that described the transport of microenvironmental agents. By analyzing the epigenetic state space described by the GRN dynamics, we found three attractors that were identified with cellular epigenetic states: normal, precancer and cancer. For two-dimensional (2D) and three-dimensional (3D) tumors we calculated the spatial distribution of the following quantities: (i) number of mutations, (ii) mutation of each gene and, (iii) phenotypes. Using estrogen as the principal microenvironmental agent that regulates cell proliferation process, we obtained tumor shapes for different values of estrogen consumption and supply rates. It was found that he majority of mutations occurred in cells that were located close to the 2D tumor perimeter or close to the 3D tumor surface. Also, it was found that the occurrence of different phenotypes in the tumor are controlled by estrogen concentration levels since they can change the individual cell threshold and gene expression levels. All results were consistently observed for 2D and 3D tumors.
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Affiliation(s)
- J Roberto Romero-Arias
- Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
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8
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Posner C, Mehta S, Zhang J. Fluorescent biosensor imaging meets deterministic mathematical modelling: quantitative investigation of signalling compartmentalization. J Physiol 2023; 601:4227-4241. [PMID: 37747358 PMCID: PMC10764149 DOI: 10.1113/jp282696] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 09/06/2023] [Indexed: 09/26/2023] Open
Abstract
Cells execute specific responses to diverse environmental cues by encoding information in distinctly compartmentalized biochemical signalling reactions. Genetically encoded fluorescent biosensors enable the spatial and temporal monitoring of signalling events in live cells. Temporal and spatiotemporal computational models can be used to interpret biosensor experiments in complex biochemical networks and to explore hypotheses that are difficult to test experimentally. In this review, we first provide brief discussions of the experimental toolkit of fluorescent biosensors as well as computational basics with a focus on temporal and spatiotemporal deterministic models. We then describe how we used this combined approach to identify and investigate a protein kinase A (PKA) - cAMP - Ca2+ oscillatory circuit in MIN6 β cells, a mouse pancreatic β cell system. We describe the application of this combined approach to interrogate how this oscillatory circuit is differentially regulated in a nano-compartment formed at the plasma membrane by the scaffolding protein A kinase anchoring protein 79/150. We leveraged both temporal and spatiotemporal deterministic models to identify the key regulators of this oscillatory circuit, which we confirmed with further experiments. The powerful approach of combining live-cell biosensor imaging with quantitative modelling, as discussed here, should find widespread use in the investigation of spatiotemporal regulation of cell signalling.
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Affiliation(s)
- Clara Posner
- Department of Pharmacology, University of California, San Diego, CA, USA
- Shu Chien-Gene Lay Department of Bioengineering, University of California, San Diego, CA, USA
| | - Sohum Mehta
- Department of Pharmacology, University of California, San Diego, CA, USA
| | - Jin Zhang
- Department of Pharmacology, University of California, San Diego, CA, USA
- Shu Chien-Gene Lay Department of Bioengineering, University of California, San Diego, CA, USA
- Department of Chemistry and Biochemistry, University of California, San Diego, CA, USA
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9
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Clark JC, Watson SP, Owen DM. Validation of agent-based models of surface receptor oligomerisation. Trends Pharmacol Sci 2023; 44:643-646. [PMID: 37507263 DOI: 10.1016/j.tips.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/07/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023]
Abstract
Receptor dimerisation and higher order oligomerisation regulates signalling by a wide variety of transmembrane receptors. We discuss how agent-based modelling (ABM) combined with advanced microscopy and structural studies can provide new insights into the regulation of clustering, including spatial considerations, revealing novel targets for therapeutic intervention.
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Affiliation(s)
- Joanne C Clark
- Institute of Cardiovascular Sciences, Level 1 IBR, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; Centre of Membrane Proteins and Receptors (COMPARE), The Universities of Birmingham and Nottingham, The Midlands, UK.
| | - Steve P Watson
- Institute of Cardiovascular Sciences, Level 1 IBR, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; Centre of Membrane Proteins and Receptors (COMPARE), The Universities of Birmingham and Nottingham, The Midlands, UK
| | - Dylan M Owen
- Centre of Membrane Proteins and Receptors (COMPARE), The Universities of Birmingham and Nottingham, The Midlands, UK; Institute of Immunology and Immunotherapy, IBR Building, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK
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10
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Konur S, Gheorghe M, Krasnogor N. Verifiable biology. J R Soc Interface 2023; 20:20230019. [PMID: 37160165 PMCID: PMC10169095 DOI: 10.1098/rsif.2023.0019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023] Open
Abstract
The formalization of biological systems using computational modelling approaches as an alternative to mathematical-based methods has recently received much interest because computational models provide a deeper mechanistic understanding of biological systems. In particular, formal verification, complementary approach to standard computational techniques such as simulation, is used to validate the system correctness and obtain critical information about system behaviour. In this study, we survey the most frequently used computational modelling approaches and formal verification techniques for computational biology. We compare a number of verification tools and software suites used to analyse biological systems and biochemical networks, and to verify a wide range of biological properties. For users who have no expertise in formal verification, we present a novel methodology that allows them to easily apply formal verification techniques to analyse their biological or biochemical system of interest.
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Affiliation(s)
- Savas Konur
- Department of Computer Science, University of Bradford, Richmond Building, Bradford BD7 1DP, UK
| | - Marian Gheorghe
- Department of Computer Science, University of Bradford, Richmond Building, Bradford BD7 1DP, UK
| | - Natalio Krasnogor
- School of Computing Science, Newcastle University, Science Square, Newcastle upon Tyne NE4 5TG, UK
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11
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Cowburn D, Rout M. Improving the hole picture: towards a consensus on the mechanism of nuclear transport. Biochem Soc Trans 2023; 51:871-886. [PMID: 37099395 PMCID: PMC10212546 DOI: 10.1042/bst20220494] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 04/27/2023]
Abstract
Nuclear pore complexes (NPCs) mediate the exchange of materials between the nucleoplasm and cytoplasm, playing a key role in the separation of nucleic acids and proteins into their required compartments. The static structure of the NPC is relatively well defined by recent cryo-EM and other studies. The functional roles of dynamic components in the pore of the NPC, phenylalanyl-glycyl (FG) repeat rich nucleoporins, is less clear because of our limited understanding of highly dynamic protein systems. These proteins form a 'restrained concentrate' which interacts with and concentrates nuclear transport factors (NTRs) to provide facilitated nucleocytoplasmic transport of cargoes. Very rapid on- and off-rates among FG repeats and NTRs supports extremely fast facilitated transport, close to the rate of macromolecular diffusion in cytoplasm, while complexes without specific interactions are entropically excluded, though details on several aspects of the transport mechanism and FG repeat behaviors remain to be resolved. However, as discussed here, new technical approaches combined with more advanced modeling methods will likely provide an improved dynamic description of NPC transport, potentially at the atomic level in the near future. Such advances are likely to be of major benefit in comprehending the roles the malfunctioning NPC plays in cancer, ageing, viral diseases, and neurodegeneration.
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Affiliation(s)
- David Cowburn
- Departments of Biochemistry and Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY 10461, U.S.A
| | - Michael Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, U.S.A
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12
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Bencurova E, Akash A, Dobson RC, Dandekar T. DNA storage-from natural biology to synthetic biology. Comput Struct Biotechnol J 2023; 21:1227-1235. [PMID: 36817961 PMCID: PMC9932295 DOI: 10.1016/j.csbj.2023.01.045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 01/30/2023] [Accepted: 01/31/2023] [Indexed: 02/04/2023] Open
Abstract
Natural DNA storage allows cellular differentiation, evolution, the growth of our children and controls all our ecosystems. Here, we discuss the fundamental aspects of DNA storage and recent advances in this field, with special emphasis on natural processes and solutions that can be exploited. We point out new ways of efficient DNA and nucleotide storage that are inspired by nature. Within a few years DNA-based information storage may become an attractive and natural complementation to current electronic data storage systems. We discuss rapid and directed access (e.g. DNA elements such as promotors, enhancers), regulatory signals and modulation (e.g. lncRNA) as well as integrated high-density storage and processing modules (e.g. chromosomal territories). There is pragmatic DNA storage for use in biotechnology and human genetics. We examine DNA storage as an approach for synthetic biology (e.g. light-controlled nucleotide processing enzymes). The natural polymers of DNA and RNA offer much for direct storage operations (read-in, read-out, access control). The inbuilt parallelism (many molecules at many places working at the same time) is important for fast processing of information. Using biology concepts from chromosomal storage, nucleic acid processing as well as polymer material sciences such as electronical effects in enzymes, graphene, nanocellulose up to DNA macramé , DNA wires and DNA-based aptamer field effect transistors will open up new applications gradually replacing classical information storage methods in ever more areas over time (decades).
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Affiliation(s)
- Elena Bencurova
- Department of Bioinformatics, University of Würzburg, Würzburg, Germany
| | - Aman Akash
- Department of Bioinformatics, University of Würzburg, Würzburg, Germany
| | - Renwick C.J. Dobson
- Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand,Department of Biochemistry and Pharmacology, University of Melbourne, Melbourne, Australia
| | - Thomas Dandekar
- Department of Bioinformatics, University of Würzburg, Würzburg, Germany,Structural and Computational Biology, European Molecular Biology Laboratory, Heidelberg, Germany,Corresponding author at: Department of Bioinformatics, University of Würzburg, Würzburg, Germany.
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13
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Kutumova E, Kiselev I, Sharipov R, Lifshits G, Kolpakov F. Mathematical modeling of antihypertensive therapy. Front Physiol 2022; 13:1070115. [PMID: 36589434 PMCID: PMC9795234 DOI: 10.3389/fphys.2022.1070115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 11/29/2022] [Indexed: 12/23/2022] Open
Abstract
Hypertension is a multifactorial disease arising from complex pathophysiological pathways. Individual characteristics of patients result in different responses to various classes of antihypertensive medications. Therefore, evaluating the efficacy of therapy based on in silico predictions is an important task. This study is a continuation of research on the modular agent-based model of the cardiovascular and renal systems (presented in the previously published article). In the current work, we included in the model equations simulating the response to antihypertensive therapies with different mechanisms of action. For this, we used the pharmacodynamic effects of the angiotensin II receptor blocker losartan, the calcium channel blocker amlodipine, the angiotensin-converting enzyme inhibitor enalapril, the direct renin inhibitor aliskiren, the thiazide diuretic hydrochlorothiazide, and the β-blocker bisoprolol. We fitted therapy parameters based on known clinical trials for all considered medications, and then tested the model's ability to show reasonable dynamics (expected by clinical observations) after treatment with individual drugs and their dual combinations in a group of virtual patients with hypertension. The extended model paves the way for the next step in personalized medicine that is adapting the model parameters to a real patient and predicting his response to antihypertensive therapy. The model is implemented in the BioUML software and is available at https://gitlab.sirius-web.org/virtual-patient/antihypertensive-treatment-modeling.
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Affiliation(s)
- Elena Kutumova
- Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia,Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia,Biosoft.Ru, Ltd., Novosibirsk, Russia,*Correspondence: Elena Kutumova,
| | - Ilya Kiselev
- Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia,Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia,Biosoft.Ru, Ltd., Novosibirsk, Russia
| | - Ruslan Sharipov
- Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia,Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia,Biosoft.Ru, Ltd., Novosibirsk, Russia,Specialized Educational Scientific Center, Novosibirsk State University, Novosibirsk, Russia
| | - Galina Lifshits
- Laboratory for Personalized Medicine, Center of New Medical Technologies, Institute of Chemical Biology and Fundamental Medicine SB RAS, Novosibirsk, Russia
| | - Fedor Kolpakov
- Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia,Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia,Biosoft.Ru, Ltd., Novosibirsk, Russia
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14
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Iwasa JH, Lyons B, Johnson GT. The dawn of interoperating spatial models in cell biology. Curr Opin Biotechnol 2022; 78:102838. [PMID: 36402095 DOI: 10.1016/j.copbio.2022.102838] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 06/01/2022] [Accepted: 10/07/2022] [Indexed: 11/18/2022]
Abstract
Spatial simulations are becoming an increasingly ubiquitous component in the cycle of discovery, experimentation, and communication across the sciences. In cell biology, many researchers share a vision of developing multiscale models that recapitulate observable behaviors spanning from atoms to cells to tissues. For this dream to become a reality, however, simulation technologies must provide a means for integration and interoperability as they advance. Already, the field has developed numerous methods that span scales of length, time, and complexity to create an extensive body of effective simulation approaches, and although these approaches rarely interoperate, they collectively cover a large spectrum of knowledge that future models may handle in a more unified manner. Here, we discuss the importance of making the data, workflows, and outputs of spatial simulations shareable and interoperable; and how democratization could encourage diverse biologists to participate more easily in developing models to advance our understanding of biological systems.
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Affiliation(s)
| | - Blair Lyons
- Visualization & Data Integration, Allen Institute for Cell Science, USA
| | - Graham T Johnson
- Visualization & Data Integration, Allen Institute for Cell Science, USA.
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15
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Rivera M, Toledo-Jacobo L, Romero E, Oprea TI, Moses ME, Hudson LG, Wandinger-Ness A, Grimes MM. Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis. Mol Biol Cell 2022; 33:ar138. [PMID: 36200848 PMCID: PMC9727804 DOI: 10.1091/mbc.e21-11-0540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Experimental and computational studies pinpoint rate-limiting step(s) in metastasis governed by Rac1. Using ovarian cancer cell and animal models, Rac1 expression was manipulated, and quantitative measurements of cell-cell and cell-substrate adhesion, cell invasion, mesothelial clearance, and peritoneal tumor growth discriminated the tumor behaviors most highly influenced by Rac1. The experimental data were used to parameterize an agent-based computational model simulating peritoneal niche colonization, intravasation, and hematogenous metastasis to distant organs. Increased ovarian cancer cell survival afforded by the more rapid adhesion and intravasation upon Rac1 overexpression is predicted to increase the numbers of and the rates at which tumor cells are disseminated to distant sites. Surprisingly, crowding of cancer cells along the blood vessel was found to decrease the numbers of cells reaching a distant niche irrespective of Rac1 overexpression or knockdown, suggesting that sites for tumor cell intravasation are rate limiting and become accessible if cells intravasate rapidly or are displaced due to diminished viability. Modeling predictions were confirmed through animal studies of Rac1-dependent metastasis to the lung. Collectively, the experimental and modeling approaches identify cell adhesion, rapid intravasation, and survival in the blood as parameters in the ovarian metastatic cascade that are most critically dependent on Rac1.
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Affiliation(s)
- Melanie Rivera
- Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131
| | - Leslie Toledo-Jacobo
- Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131
| | - Elsa Romero
- Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131
| | - Tudor I. Oprea
- Division of Translational Informatics, Department of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131,Translational Informatics, Roivant Discovery, Boston, MA 02210
| | - Melanie E. Moses
- Department of Computer Science, University of New Mexico, Albuquerque, NM 87131
| | - Laurie G. Hudson
- Cancer Research Facility, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131,Department of Pharmaceutical Sciences, College of Pharmacy, University of New Mexico Health Sciences Center, Albuquerque, NM 87131
| | - Angela Wandinger-Ness
- Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131,Cancer Research Facility, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131,*Address correspondence to: Angela Wandinger-Ness ()
| | - Martha M. Grimes
- Cancer Research Facility, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131,Department of Pharmaceutical Sciences, College of Pharmacy, University of New Mexico Health Sciences Center, Albuquerque, NM 87131
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16
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van Zuijlen PPM, Korkmaz HI, Sheraton VM, Haanstra TM, Pijpe A, de Vries A, van der Vlies CH, Bosma E, de Jong E, Middelkoop E, Vermolen FJ, Sloot PMA. The future of burn care from a complexity science perspective. J Burn Care Res 2022; 43:1312-1321. [PMID: 35267022 DOI: 10.1093/jbcr/irac029] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Healthcare is undergoing a profound technological and digital transformation and has become increasingly complex. It is important for burns professionals and researchers to adapt to these developments which may require new ways of thinking and subsequent new strategies. As Einstein has put it: 'We must learn to see the world anew'. The relatively new scientific discipline "Complexity science" can give more direction to this and is the metaphorical open door that should not go unnoticed in view of the burn care of the future. Complexity sciences studies 'why the whole is more than the sum of the parts'. It studies how multiple separate components interact with each other and their environment and how these interactions lead to 'behavior of the system'. Biological systems are always part of smaller and larger systems and exhibit the behavior of adaptivity, hence the name complex adaptive systems. From the perspective of complexity science, a severe burn injury is an extreme disruption of the 'human body system'. But this disruption also applies to the systems at the organ and cellular level. All these systems follow principles of complex systems. Awareness of the scaling process at multilevel helps to understand and manage the complex situation when dealing with severe burn cases. The aim of this paper is to create awareness of the concept of complexity and to demonstrate the value and possibilities of complexity science methods and tools for the future of burn care through examples from preclinical, clinical, and organizational perspective in burn care.
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Affiliation(s)
- Paul P M van Zuijlen
- Burn Center, Red Cross Hospital, Beverwijk, The Netherlands.,Department of Plastic and Reconstructive Surgery, Red Cross Hospital, Beverwijk, The Netherlands.,Department of Plastic Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Paediatric Surgical Centre, Emma Children's Hospital, Amsterdam UMC, location AMC, Amsterdam, The Netherlands
| | - H Ibrahim Korkmaz
- Burn Center, Red Cross Hospital, Beverwijk, The Netherlands.,Department of Plastic Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Department of Molecular Cell Biology and Immunology, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Association of Dutch Burn Centres (ADBC), Beverwijk, The Netherlands
| | - Vivek M Sheraton
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
| | | | - Anouk Pijpe
- Burn Center, Red Cross Hospital, Beverwijk, The Netherlands
| | - Annebeth de Vries
- Burn Center, Red Cross Hospital, Beverwijk, The Netherlands.,Paediatric Surgical Centre, Emma Children's Hospital, Amsterdam UMC, location AMC, Amsterdam, The Netherlands.,Department of Surgery, Red Cross Hospital, Beverwijk, The Netherlands
| | - Cornelis H van der Vlies
- Burn Centre, Maasstad Ziekenhuis, Rotterdam, The Netherlands.,Trauma Research Unit, Department of Surgery, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Eelke Bosma
- Burn Centre and Department of Surgery, Martini Ziekenhuis, Groningen, The Netherlands
| | - Evelien de Jong
- Burn Center, Red Cross Hospital, Beverwijk, The Netherlands.,Intensive Care Unit, Red Cross Hospital, Beverwijk, The Netherlands
| | - Esther Middelkoop
- Burn Center, Red Cross Hospital, Beverwijk, The Netherlands.,Department of Plastic Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Association of Dutch Burn Centres (ADBC), Beverwijk, The Netherlands
| | - Fred J Vermolen
- Delft Institute of Applied Mathematics, Delft University of Technology, Delft, The Netherlands.,Computational Mathematics, Hasselt University, Diepenbeek, Belgium
| | - Peter M A Sloot
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands.,Complexity Institute, Nanyang Technological University, Singapore.,ITMO University, Saint Petersburg, Russian Federation
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17
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Korkmaz HI, Niessen FB, Pijpe A, Sheraton VM, Vermolen FJ, Krijnen PA, Niessen HW, Sloot PM, Middelkoop E, Gibbs S, van Zuijlen PP. Scar formation from the perspective of complexity science: a new look at the biological system as a whole. J Wound Care 2022; 31:178-184. [PMID: 35148632 DOI: 10.12968/jowc.2022.31.2.178] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
A burn wound is a complex systemic disease at multiple levels. Current knowledge of scar formation after burn injury has come from traditional biological and clinical studies. These are normally focused on just a small part of the entire process, which has limited our ability to sufficiently understand the underlying mechanisms and to predict systems behaviour. Scar formation after burn injury is a result of a complex biological system-wound healing. It is a part of a larger whole. In this self-organising system, many components form networks of interactions with each other. These networks of interactions are typically non-linear and change their states dynamically, responding to the environment and showing emergent long-term behaviour. How molecular and cellular data relate to clinical phenomena, especially regarding effective therapies of burn wounds to achieve minimal scarring, is difficult to unravel and comprehend. Complexity science can help bridge this gap by integrating small parts into a larger whole, such that relevant biological mechanisms and data are combined in a computational model to better understand the complexity of the entire biological system. A better understanding of the complex biological system of post-burn scar formation could bring research and treatment regimens to the next level. The aim of this review/position paper is to create more awareness of complexity in scar formation after burn injury by describing the basic principles of complexity science and its potential for burn care professionals.
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Affiliation(s)
- H Ibrahim Korkmaz
- Department of Plastic Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Department of Molecular Cell Biology and Immunology, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Burn Center and Department of Plastic and Reconstructive Surgery, Red Cross Hospital, Beverwijk, The Netherlands.,Association of Dutch Burn Centres (ADBC), Beverwijk, The Netherlands
| | - Frank B Niessen
- Department of Plastic Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Anouk Pijpe
- Burn Center and Department of Plastic and Reconstructive Surgery, Red Cross Hospital, Beverwijk, The Netherlands
| | - Vivek M Sheraton
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands
| | - Fred J Vermolen
- Delft Institute of Applied Mathematics, Delft University of Technology, Delft, The Netherlands.,Computational Mathematics, Hasselt University, Diepenbeek, Belgium
| | - Paul Aj Krijnen
- Department of Pathology and Cardiac Surgery, Amsterdam Cardiovascular Sciences (ACS), Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Hans Wm Niessen
- Department of Pathology and Cardiac Surgery, Amsterdam Cardiovascular Sciences (ACS), Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Peter Ma Sloot
- Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands.,Complexity Institute, Nanyang Technological University, Singapore.,ITMO University, Saint Petersburg, Russian Federation
| | - Esther Middelkoop
- Department of Plastic Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Burn Center and Department of Plastic and Reconstructive Surgery, Red Cross Hospital, Beverwijk, The Netherlands.,Association of Dutch Burn Centres (ADBC), Beverwijk, The Netherlands
| | - Susan Gibbs
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Department of Oral Cell Biology, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Paul Pm van Zuijlen
- Department of Plastic Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Burn Center and Department of Plastic and Reconstructive Surgery, Red Cross Hospital, Beverwijk, The Netherlands.,Paediatric Surgical Centre, Emma Children's Hospital, Amsterdam UMC, location AMC, Amsterdam, The Netherlands
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18
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Mc Auley MT. Modeling cholesterol metabolism and atherosclerosis. WIREs Mech Dis 2021; 14:e1546. [PMID: 34931487 DOI: 10.1002/wsbm.1546] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 10/11/2021] [Accepted: 10/14/2021] [Indexed: 12/19/2022]
Abstract
Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality among Western populations. Many risk factors have been identified for ASCVD; however, elevated low-density lipoprotein cholesterol (LDL-C) remains the gold standard. Cholesterol metabolism at the cellular and whole-body level is maintained by an array of interacting components. These regulatory mechanisms have complex behavior. Likewise, the mechanisms which underpin atherogenesis are nontrivial and multifaceted. To help overcome the challenge of investigating these processes mathematical modeling, which is a core constituent of the systems biology paradigm has played a pivotal role in deciphering their dynamics. In so doing models have revealed new insights about the key drivers of ASCVD. The aim of this review is fourfold; to provide an overview of cholesterol metabolism and atherosclerosis, to briefly introduce mathematical approaches used in this field, to critically discuss models of cholesterol metabolism and atherosclerosis, and to highlight areas where mathematical modeling could help to investigate in the future. This article is categorized under: Cardiovascular Diseases > Computational Models.
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19
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Lennon KM, Soheilypour M, Peyro M, Wakefield DL, Choo GE, Mofrad MRK, Jovanovic-Talisman T. Characterizing Binding Interactions That Are Essential for Selective Transport through the Nuclear Pore Complex. Int J Mol Sci 2021; 22:10898. [PMID: 34639238 PMCID: PMC8509584 DOI: 10.3390/ijms221910898] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 12/13/2022] Open
Abstract
Specific macromolecules are rapidly transported across the nuclear envelope via the nuclear pore complex (NPC). The selective transport process is facilitated when nuclear transport receptors (NTRs) weakly and transiently bind to intrinsically disordered constituents of the NPC, FG Nups. These two types of proteins help maintain the selective NPC barrier. To interrogate their binding interactions in vitro, we deployed an NPC barrier mimic. We created the stationary phase by covalently attaching fragments of a yeast FG Nup called Nsp1 to glass coverslips. We used a tunable mobile phase containing NTR, nuclear transport factor 2 (NTF2). In the stationary phase, three main factors affected binding: the number of FG repeats, the charge of fragments, and the fragment density. We also identified three main factors affecting binding in the mobile phase: the avidity of the NTF2 variant for Nsp1, the presence of nonspecific proteins, and the presence of additional NTRs. We used both experimentally determined binding parameters and molecular dynamics simulations of Nsp1FG fragments to create an agent-based model. The results suggest that NTF2 binding is negatively cooperative and dependent on the density of Nsp1FG molecules. Our results demonstrate the strengths of combining experimental and physical modeling approaches to study NPC-mediated transport.
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Affiliation(s)
- Kathleen M. Lennon
- Department of Molecular Medicine, Beckman Research Institute of the City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA; (K.M.L.); (D.L.W.); (G.E.C.)
| | - Mohammad Soheilypour
- Department of Bioengineering and Mechanical Engineering, Molecular Cell Biomechanics Laboratory, University of California, Berkeley, CA 94720, USA; (M.S.); (M.P.)
| | - Mohaddeseh Peyro
- Department of Bioengineering and Mechanical Engineering, Molecular Cell Biomechanics Laboratory, University of California, Berkeley, CA 94720, USA; (M.S.); (M.P.)
| | - Devin L. Wakefield
- Department of Molecular Medicine, Beckman Research Institute of the City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA; (K.M.L.); (D.L.W.); (G.E.C.)
| | - Grace E. Choo
- Department of Molecular Medicine, Beckman Research Institute of the City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA; (K.M.L.); (D.L.W.); (G.E.C.)
| | - Mohammad R. K. Mofrad
- Department of Bioengineering and Mechanical Engineering, Molecular Cell Biomechanics Laboratory, University of California, Berkeley, CA 94720, USA; (M.S.); (M.P.)
- Molecular Biophysics and Integrative Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Tijana Jovanovic-Talisman
- Department of Molecular Medicine, Beckman Research Institute of the City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA; (K.M.L.); (D.L.W.); (G.E.C.)
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20
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Luo Y, Kurian V, Ogunnaike BA. Bioprocess systems analysis, modeling, estimation, and control. Curr Opin Chem Eng 2021. [DOI: 10.1016/j.coche.2021.100705] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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21
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Nourisa J, Zeller-Plumhoff B, Helmholz H, Luthringer-Feyerabend B, Ivannikov V, Willumeit-Römer R. Magnesium ions regulate mesenchymal stem cells population and osteogenic differentiation: A fuzzy agent-based modeling approach. Comput Struct Biotechnol J 2021; 19:4110-4122. [PMID: 34527185 PMCID: PMC8346546 DOI: 10.1016/j.csbj.2021.07.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 07/05/2021] [Accepted: 07/07/2021] [Indexed: 12/17/2022] Open
Abstract
Mesenchymal stem cells (MSCs) are proliferative and multipotent cells that play a key role in the bone regeneration process. Empirical data have repeatedly shown the bioregulatory importance of magnesium (Mg) ions in MSC growth and osteogenesis. In this study, we propose an agent-based model to predict the spatiotemporal dynamics of the MSC population and osteogenic differentiation in response to Mg2+ ions. A fuzzy-logic controller was designed to govern the decision-making process of cells by predicting four cellular processes of proliferation, differentiation, migration, and mortality in response to several important bioregulatory factors such as Mg2+ ions, pH, BMP2, and TGF-β1. The model was calibrated using the empirical data obtained from three sets of cell culture experiments. The model successfully reproduced the empirical observations regarding live cell count, viability, DNA content, and the differentiation-related markers of alkaline phosphate (ALP) and osteocalcin (OC). The simulation results, in agreement with the empirical data, showed that Mg2+ ions within 3-6 mM concentration have the highest stimulation effect on cell population growth. The model also correctly reproduced the stimulatory effect of Mg2+ ions on ALP and its inhibitory effect on OC as the early and late differentiation markers, respectively. Besides, the numerical simulation shed light on the innate cellular differences of the cells cultured in different experiments in terms of the proliferative capacity as well as sensitivity to Mg2+ ions. The proposed model can be adopted in the study of the osteogenesis around Mg-based implants where ions released due to degradation interact with local cells and regulate bone regeneration.
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Affiliation(s)
- Jalil Nourisa
- Helmholtz Zentrum Hereon, Institute of Metallic Biomaterials, Max-Planck-Straße 1, 21502 Geesthacht, Germany
| | - Berit Zeller-Plumhoff
- Helmholtz Zentrum Hereon, Institute of Metallic Biomaterials, Max-Planck-Straße 1, 21502 Geesthacht, Germany
| | - Heike Helmholz
- Helmholtz Zentrum Hereon, Institute of Metallic Biomaterials, Max-Planck-Straße 1, 21502 Geesthacht, Germany
| | | | - Vladimir Ivannikov
- Helmholtz Zentrum Hereon, Institute of Metallic Biomaterials, Max-Planck-Straße 1, 21502 Geesthacht, Germany
| | - Regine Willumeit-Römer
- Helmholtz Zentrum Hereon, Institute of Metallic Biomaterials, Max-Planck-Straße 1, 21502 Geesthacht, Germany
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22
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Moradian N, Moallemian M, Delavari F, Sedikides C, Camargo CA, Torres PJ, Sorooshian A, Mehdiabadi SP, Nieto JJ, Bordas S, Ahmadieh H, Abdollahi M, Hamblin MR, Sellke FW, Cuzick J, Biykem B, Schreiber M, Eshrati B, Perry G, Montazeri A, Saboury AA, Kelishadi R, Sahebkar A, Moosavi-Movahed AA, Vatandoost H, Gorji-Bandpy M, Mobasher B, Rezaei N. Interdisciplinary Approaches to COVID-19. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1318:923-936. [PMID: 33973220 DOI: 10.1007/978-3-030-63761-3_52] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has been a significant concern worldwide. The pandemic has demonstrated that public health issues are not merely a health concern but also affect society as a whole. In this chapter, we address the importance of bringing together the world's scientists to find appropriate solutions for controlling and managing the COVID-19 pandemic. Interdisciplinary cooperation, through modern scientific methods, could help to handle the consequences of the pandemic and to avoid the recurrence of future pandemics.
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Affiliation(s)
- Negar Moradian
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Marjan Moallemian
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, National Nutrition and food technology Research Institute, Shahihd Beheshti University of Medical Sciences, Tehran, Iran
| | - Farnaz Delavari
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Department of Psychiatry, School of Medicine, University of Geneva, Geneva, Switzerland
| | - Constantine Sedikides
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Centre for Research on Self Identity, Department of Psychology, School of Psychology, University of Southampton, Southampton, UK
| | - Carlos A Camargo
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Pedro J Torres
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Departamento de Matemática Aplicada, Universidad de Granada, Granada, Spain
| | - Armin Sorooshian
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Department of Chemical and Environmental Engineering, University of Arizona, Tucson, Arizona, USA.,Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, Arizona, USA
| | - Saeid Paktinat Mehdiabadi
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Physics Department, Elementary Particle, Yazd University, Yazd, Iran.,Faculty of Physics, Yazd University, Yazd, Iran
| | - Juan J Nieto
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Instituto de Matemáticas, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Stephane Bordas
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,University of Luxembourg, Institute of Computational Engineering Sciences, Luxembourg, Cardiff University, Department of Applied and Computational Mechanics, Wales, UK
| | - Hamid Ahmadieh
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Ophthalmic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Abdollahi
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Pharmaceutical Sciences Research Center (PSRC), The Institute of Pharmaceutical Sciences (TIPS), and School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Michael R Hamblin
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, USA.,Laser Research Centre, Faculty of Health Science, University of Johannesburg, Doornfontein, South Africa
| | - Frank W Sellke
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Division of Cardiothoracic Surgery, Department of Surgery, Rhode Island Hospital, Alpert Medical School of Brown University, Providence, RI, USA
| | - Jack Cuzick
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Cancer Research UK Centre for Epidemiology, Mathematics and Statistics, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - Bozkurt Biykem
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Winters Center for Heart Failure Research, Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX, USA
| | - Michael Schreiber
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Institute of Physics, Technische Universität Chemnitz, Chemnitz, Germany
| | - Babak Eshrati
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Centre for Communicable Diseases Control, Ministry of Health and Medical Education, Tehran, Iran
| | - Georg Perry
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,University of Texas at San Antonio, Biology and Chemistry, One UTSA Circle, San Antonio, TX, USA
| | - Ali Montazeri
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Population Health Research Group, Health Metrics Research Center, Institute for Health Sciences Research, ACECR, Tehran, Iran
| | - Ali Akbar Saboury
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Roya Kelishadi
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Amirhossein Sahebkar
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.,Neurogenic Inflammation Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Ali A Moosavi-Movahed
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Hassan Vatandoost
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Department of Environmental Chemical Pollutants and Pesticides, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
| | - Mofid Gorji-Bandpy
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Department of Mechanical Engineering, Babol Noshirvany University of Technology, Babol, Iran
| | - Bahram Mobasher
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran.,Department of Physics and Astronomy University of California, Riverside, CA, USA
| | - Nima Rezaei
- Universal Scientific Education and Research Network (USERN), The World, Tehran, Iran. .,Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.
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23
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Roychoudhury S, Das A, Sengupta P, Dutta S, Roychoudhury S, Choudhury AP, Ahmed ABF, Bhattacharjee S, Slama P. Viral Pandemics of the Last Four Decades: Pathophysiology, Health Impacts and Perspectives. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E9411. [PMID: 33333995 PMCID: PMC7765415 DOI: 10.3390/ijerph17249411] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/11/2020] [Accepted: 12/14/2020] [Indexed: 01/08/2023]
Abstract
The twenty-first century has witnessed some of the deadliest viral pandemics with far-reaching consequences. These include the Human Immunodeficiency Virus (HIV) (1981), Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) (2002), Influenza A virus subtype H1N1 (A/H1N1) (2009), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) (2012) and Ebola virus (2013) and the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) (2019-present). Age- and gender-based characterizations suggest that SARS-CoV-2 resembles SARS-CoV and MERS-CoV with regard tohigher fatality rates in males, and in the older population with comorbidities. The invasion-mechanism of SARS-CoV-2 and SARS-CoV, involves binding of its spike protein with angiotensin-converting enzyme 2 (ACE2) receptors; MERS-CoV utilizes dipeptidyl peptidase 4 (DPP4), whereas H1N1 influenza is equipped with hemagglutinin protein. The viral infections-mediated immunomodulation, and progressive inflammatory state may affect the functions of several other organs. Although no effective commercial vaccine is available for any of the viruses, those against SARS-CoV-2 are being developed at an unprecedented speed. Until now, only Pfizer/BioNTech's vaccine has received temporary authorization from the UK Medicines and Healthcare products Regulatory Agency. Given the frequent emergence of viral pandemics in the 21st century, proper understanding of their characteristics and modes of action are essential to address the immediate and long-term health consequences.
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Affiliation(s)
| | - Anandan Das
- Department of Life Science and Bioinformatics, Assam University, Silchar 788011, India;
| | - Pallav Sengupta
- Department of Physiology, Faculty of Medicine and Biomedical Sciences, MAHSA University, SP2, Bandar Saujana Putra, Jenjarom, Selangor 42610, Malaysia;
| | - Sulagna Dutta
- Department of Oral Biology and Biomedical Sciences, Faculty of Dentistry, MAHSA University, SP2, Bandar Saujana Putra, Jenjarom, Selangor 42610, Malaysia;
| | - Shatabhisha Roychoudhury
- Department of Microbiology, R. G. Kar Medical College and Hospital, Kolkata 700004, India;
- Health Centre, Assam University, Silchar 788011, India
| | - Arun Paul Choudhury
- Department of Obstetrics and Gynecology, Silchar Medical College and Hospital, Silchar 788014, India; (A.P.C.); (A.B.F.A.)
| | - A. B. Fuzayel Ahmed
- Department of Obstetrics and Gynecology, Silchar Medical College and Hospital, Silchar 788014, India; (A.P.C.); (A.B.F.A.)
| | | | - Petr Slama
- Department of Animal Morphology, Physiology and Genetics, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 613 00 Brno, Czech Republic;
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24
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Abstract
Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.
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Affiliation(s)
| | - Edgar G Engleman
- Department of Pathology, Stanford University School of MedicineStanfordUnited States
- Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of MedicineStanfordUnited States
- Stanford Cancer Institute, Stanford UniversityStanfordUnited States
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25
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Integrative Approaches to Cancer Immunotherapy. Trends Cancer 2020; 5:400-410. [PMID: 31311655 DOI: 10.1016/j.trecan.2019.05.010] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 05/17/2019] [Accepted: 05/30/2019] [Indexed: 12/11/2022]
Abstract
Cancer immunotherapy aims to arm patients with cancer-fighting immunity. Many new cancer-specific immunotherapeutic drugs have gained approval in the past several years, demonstrating immunotherapy's efficacy and promise as an anticancer modality. Despite these successes, several outstanding questions remain for cancer immunotherapy, including how to make immunotherapy more efficacious in a broader range of cancer types and patients, and how to predict which patients will respond or not respond to therapy. We present a case for integrative systems approaches that will answer these questions. This involves applying mechanistic and statistical modeling, establishing consistent and widely adopted experimental tools to generate systems-level data, and creating sustained mechanisms of support. If implemented, these approaches will lead to major advances in cancer treatment.
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26
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Moradian N, Ochs HD, Sedikies C, Hamblin MR, Camargo CA, Martinez JA, Biamonte JD, Abdollahi M, Torres PJ, Nieto JJ, Ogino S, Seymour JF, Abraham A, Cauda V, Gupta S, Ramakrishna S, Sellke FW, Sorooshian A, Wallace Hayes A, Martinez-Urbistondo M, Gupta M, Azadbakht L, Esmaillzadeh A, Kelishadi R, Esteghamati A, Emam-Djomeh Z, Majdzadeh R, Palit P, Badali H, Rao I, Saboury AA, Jagan Mohan Rao L, Ahmadieh H, Montazeri A, Fadini GP, Pauly D, Thomas S, Moosavi-Movahed AA, Aghamohammadi A, Behmanesh M, Rahimi-Movaghar V, Ghavami S, Mehran R, Uddin LQ, Von Herrath M, Mobasher B, Rezaei N. The urgent need for integrated science to fight COVID-19 pandemic and beyond. J Transl Med 2020; 18:205. [PMID: 32430070 PMCID: PMC7236639 DOI: 10.1186/s12967-020-02364-2] [Citation(s) in RCA: 94] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 05/04/2020] [Indexed: 12/17/2022] Open
Abstract
The COVID-19 pandemic has become the leading societal concern. The pandemic has shown that the public health concern is not only a medical problem, but also affects society as a whole; so, it has also become the leading scientific concern. We discuss in this treatise the importance of bringing the world's scientists together to find effective solutions for controlling the pandemic. By applying novel research frameworks, interdisciplinary collaboration promises to manage the pandemic's consequences and prevent recurrences of similar pandemics.
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Affiliation(s)
- Negar Moradian
- Universal Scientific Education and Research Network (USERN),.,Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, 14194, Iran
| | - Hans D Ochs
- Universal Scientific Education and Research Network (USERN),.,Department of Pediatrics, University of Washington and Seattle Children's Research Institute, Seattle, WA, USA
| | - Constantine Sedikies
- Universal Scientific Education and Research Network (USERN),.,Centre for Research on Self Identity, Department of Psychology, School of Psychology, University of Southampton, Southampton, UK
| | - Michael R Hamblin
- Universal Scientific Education and Research Network (USERN),.,Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, USA.,Laser Research Centre, Faculty of Health Science, University of Johannesburg, Doornfontein, 2028, South Africa
| | - Carlos A Camargo
- Universal Scientific Education and Research Network (USERN),.,Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - J Alfredo Martinez
- Universal Scientific Education and Research Network (USERN),.,University of Navarra, CIBERobn and IMDEA food, International Union of Nutritional Sciences (IUNS), Navarra, Spain.,International Union of Nutritional Sciences (IUNS), London, UK
| | - Jacob D Biamonte
- Universal Scientific Education and Research Network (USERN),.,Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Mohammad Abdollahi
- Universal Scientific Education and Research Network (USERN),.,Pharmaceutical Sciences Research Center (PSRC), The Institute of Pharmaceutical Sciences (TIPS), and School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Pedro J Torres
- Universal Scientific Education and Research Network (USERN),.,Departamento de Matemática Aplicada, Universidad de Granada, 18071, Granada, Spain
| | - Juan J Nieto
- Universal Scientific Education and Research Network (USERN),.,Instituto de Matemáticas, Universidade de Santiago de Compostela, Santiago De Compostela, Spain
| | - Shuji Ogino
- Universal Scientific Education and Research Network (USERN),.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.,Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - John F Seymour
- Universal Scientific Education and Research Network (USERN),.,The Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia.,Department of Haematology, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, Australia
| | - Ajith Abraham
- Universal Scientific Education and Research Network (USERN),.,Machine Intelligence Research Labs, Auburn, WA, USA
| | - Valentina Cauda
- Universal Scientific Education and Research Network (USERN),.,Department of Applied Science and Technology, Politecnico di Torino Corso, Duca degli Abruzzi 24, 10129, Turin, Italy
| | - Sudhir Gupta
- Universal Scientific Education and Research Network (USERN),.,Division of Basic and Clinical Immunology, University of California Irvine, California, USA
| | - Seeram Ramakrishna
- Universal Scientific Education and Research Network (USERN),.,National University of Singapore, Singapore, Singapore
| | - Frank W Sellke
- Universal Scientific Education and Research Network (USERN),.,Division of Cardiothoracic Surgery, Department of Surgery, Rhode Island Hospital, Alpert Medical School of Brown University, Providence, RI, 02903, USA
| | - Armin Sorooshian
- Universal Scientific Education and Research Network (USERN),.,Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA.,Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - A Wallace Hayes
- Universal Scientific Education and Research Network (USERN),.,A. Wallace Hayes, University of South, Florida College of Public Health and Institute for Integrative Toxicology, Michigan State University, East Lansing, USA
| | | | - Manoj Gupta
- Universal Scientific Education and Research Network (USERN),.,Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore
| | - Leila Azadbakht
- Universal Scientific Education and Research Network (USERN),.,Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore
| | - Ahmad Esmaillzadeh
- Universal Scientific Education and Research Network (USERN),.,Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Roya Kelishadi
- Universal Scientific Education and Research Network (USERN),.,Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Alireza Esteghamati
- Universal Scientific Education and Research Network (USERN),.,Endocrinology and Metabolism Research Center, Tehran University of Medical Sciences, Tehran, Tehran, Iran
| | - Zahra Emam-Djomeh
- Universal Scientific Education and Research Network (USERN),.,Department of Food Science, Engineering and Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj Campus, Karaj, Iran; Transfer Phenomena Laboratory (TPL), Controlled Release Center, University of Tehran, Karaj Campus, Karaj, Iran
| | - Reza Majdzadeh
- Universal Scientific Education and Research Network (USERN),.,Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Partha Palit
- Universal Scientific Education and Research Network (USERN),.,Department of Pharmaceutical Sciences, Drug Discovery Research Laboratorty, Assam University, Silchar, Assam, India
| | - Hamid Badali
- Universal Scientific Education and Research Network (USERN),.,Invasive Fungi Research Center and Department of Medical Mycology, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran.,Fungus Testing Laboratory, Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at San Antonio, San Antonio, USA
| | - Idupulapati Rao
- Universal Scientific Education and Research Network (USERN),.,Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia
| | - Ali Akbar Saboury
- Universal Scientific Education and Research Network (USERN),.,Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - L Jagan Mohan Rao
- Universal Scientific Education and Research Network (USERN),.,Spice and Flavour Science Department, CSIR-Central Food Technological Research Institute, Mysore, India
| | - Hamid Ahmadieh
- Universal Scientific Education and Research Network (USERN),.,Ophthalmic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ali Montazeri
- Universal Scientific Education and Research Network (USERN),.,Population Health Research Group, Health Metrics Research Center, Institute for Health Sciences Research, ACECR, Tehran, Iran
| | - Gian Paolo Fadini
- Universal Scientific Education and Research Network (USERN),.,Department of Medicine, Division of Metabolic Diseases and, Padova Hospital, University of Padova, Padua, Italy
| | - Daniel Pauly
- Universal Scientific Education and Research Network (USERN),.,Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, Canada
| | - Sabu Thomas
- Universal Scientific Education and Research Network (USERN),.,School of Chemical Sciences, Mahatma Gandhi University, Kerala, 686 560, India
| | - Ali A Moosavi-Movahed
- Universal Scientific Education and Research Network (USERN),.,Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Asghar Aghamohammadi
- Universal Scientific Education and Research Network (USERN),.,Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, 14194, Iran
| | - Mehrdad Behmanesh
- Universal Scientific Education and Research Network (USERN),.,Department of Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Vafa Rahimi-Movaghar
- Universal Scientific Education and Research Network (USERN),.,Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Saeid Ghavami
- Universal Scientific Education and Research Network (USERN),.,Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, R3E 3P4, Canada.,Faculty of Medicine, Katowice School of Technology, 40-555, Katowice, Poland
| | - Roxana Mehran
- Universal Scientific Education and Research Network (USERN),.,Zena and Michael A. Weiner Cardiovascular Institute, Icahn School of Medicine at Mount Sinai and Cardiovascular Research Foundation, New York, NY, USA
| | - Lucina Q Uddin
- Universal Scientific Education and Research Network (USERN),.,Department of Psychology, University of Miami, Miami, USA
| | - Matthias Von Herrath
- Universal Scientific Education and Research Network (USERN),.,Center for Type 1, Diabetes Research, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Bahram Mobasher
- Universal Scientific Education and Research Network (USERN),.,Department of Physics and Astronomy, University of California Riverside, Riverside, CA, 92521, USA
| | - Nima Rezaei
- Universal Scientific Education and Research Network (USERN), , . .,Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, 14194, Iran.
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27
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Ewald J, Sieber P, Garde R, Lang SN, Schuster S, Ibrahim B. Trends in mathematical modeling of host-pathogen interactions. Cell Mol Life Sci 2020; 77:467-480. [PMID: 31776589 PMCID: PMC7010650 DOI: 10.1007/s00018-019-03382-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 11/05/2019] [Accepted: 11/12/2019] [Indexed: 12/18/2022]
Abstract
Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host-pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.
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Affiliation(s)
- Jan Ewald
- Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany
| | - Patricia Sieber
- Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany
| | - Ravindra Garde
- Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany
- Max Planck Institute for Chemical Ecology, Hans-Knöll-Str. 8, 07745, Jena, Germany
| | - Stefan N Lang
- Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany
| | - Stefan Schuster
- Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany.
| | - Bashar Ibrahim
- Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany.
- Centre for Applied Mathematics and Bioinformatics, Gulf University for Science and Technology, 32093, Hawally, Kuwait.
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28
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Maia P, Pérez-Rodríguez G, Pérez-Pérez M, Fdez-Riverola F, Lourenço A, Azevedo NF. Application of agent-based modelling to assess single-molecule transport across the cell envelope of E. coli. Comput Biol Med 2019; 107:218-226. [DOI: 10.1016/j.compbiomed.2019.02.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/20/2019] [Accepted: 02/21/2019] [Indexed: 01/16/2023]
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