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Kloska SM, Pałczyński K, Marciniak T, Talaśka T, Miller M, Wysocki BJ, Davis P, Wysocki TA. Conversion of fat to cellular fuel-Fatty acids β-oxidation model. Comput Biol Chem 2023; 104:107860. [PMID: 37028176 DOI: 10.1016/j.compbiolchem.2023.107860] [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: 09/04/2022] [Revised: 02/08/2023] [Accepted: 03/29/2023] [Indexed: 04/03/2023]
Abstract
β-oxidation of fatty acids plays a significant role in the energy metabolism of the cell. This paper presents a β-oxidation model of fatty acids based on queueing theory. It uses Michaelis-Menten enzyme kinetics, and literature data on metabolites' concentration and enzymatic constants. A genetic algorithm was used to optimize the parameters for the pathway reactions. The model enables real-time tracking of changes in the concentrations of metabolites with different carbon chain lengths. Another application of the presented model is to predict the changes caused by system disturbance, such as altered enzyme activity or abnormal fatty acid concentration. The model has been validated against experimental data. There are diseases that change the metabolism of fatty acids and the presented model can be used to understand the cause of these changes, analyze metabolites abnormalities, and determine the initial target of treatment.
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Affiliation(s)
- Sylwester M Kloska
- Department of Forensic Medicine, Nicolaus Copernicus University Ludwik Rydygier Collegium Medicum, Bydgoszcz, Poland.
| | - Krzysztof Pałczyński
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
| | - Tomasz Marciniak
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
| | - Tomasz Talaśka
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
| | - Marissa Miller
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, USA
| | - Beata J Wysocki
- Department of Biology, University of Nebraska at Omaha, Omaha, USA
| | - Paul Davis
- Department of Biology, University of Nebraska at Omaha, Omaha, USA
| | - Tadeusz A Wysocki
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland; Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, USA
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Kloska SM, Pałczyński K, Marciniak T, Talaśka T, Miller M, Wysocki BJ, Davis PH, Soliman GA, Wysocki TA. Queueing theory model of mTOR complexes' impact on Akt-mediated adipocytes response to insulin. PLoS One 2022; 17:e0279573. [PMID: 36574435 PMCID: PMC9794039 DOI: 10.1371/journal.pone.0279573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 12/11/2022] [Indexed: 12/28/2022] Open
Abstract
A queueing theory based model of mTOR complexes impact on Akt-mediated cell response to insulin is presented in this paper. The model includes several aspects including the effect of insulin on the transport of glucose from the blood into the adipocytes with the participation of GLUT4, and the role of the GAPDH enzyme as a regulator of mTORC1 activity. A genetic algorithm was used to optimize the model parameters. It can be observed that mTORC1 activity is related to the amount of GLUT4 involved in glucose transport. The results show the relationship between the amount of GAPDH in the cell and mTORC1 activity. Moreover, obtained results suggest that mTORC1 inhibitors may be an effective agent in the fight against type 2 diabetes. However, these results are based on theoretical knowledge and appropriate experimental tests should be performed before making firm conclusions.
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Affiliation(s)
- Sylwester M. Kloska
- Department of Forensic Medicine, Nicolaus Copernicus University Ludwik Rydygier Collegium Medicum, Bydgoszcz, Poland
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
| | - Krzysztof Pałczyński
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
| | - Tomasz Marciniak
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
| | - Tomasz Talaśka
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
| | - Marissa Miller
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, Nebraska, United States of America
| | - Beata J. Wysocki
- Department of Biology, University of Nebraska at Omaha, Omaha, Nebraska, United States of America
| | - Paul H. Davis
- Department of Biology, University of Nebraska at Omaha, Omaha, Nebraska, United States of America
| | - Ghada A. Soliman
- Department of Environmental, Occupational, and Geospatial Health Sciences, City University of New York, Graduate School of Public Health and Healthy Policy, New York, NY, United States of America
| | - Tadeusz A. Wysocki
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, Nebraska, United States of America
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Bonomo OL, Pal A, Reuveni S. Mitigating long queues and waiting times with service resetting. PNAS NEXUS 2022; 1:pgac070. [PMID: 36741459 PMCID: PMC9896945 DOI: 10.1093/pnasnexus/pgac070] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 05/25/2022] [Indexed: 02/07/2023]
Abstract
What determines the average length of a queue, which stretches in front of a service station? The answer to this question clearly depends on the average rate at which jobs arrive at the queue and on the average rate of service. Somewhat less obvious is the fact that stochastic fluctuations in service and arrival times are also important, and that these are a major source of backlogs and delays. Strategies that could mitigate fluctuations-induced delays are, thus in high demand as queue structures appear in various natural and man-made systems. Here, we demonstrate that a simple service resetting mechanism can reverse the deleterious effects of large fluctuations in service times, thus turning a marked drawback into a favorable advantage. This happens when stochastic fluctuations are intrinsic to the server, and we show that service resetting can then dramatically cut down average queue lengths and waiting times. Remarkably, this strategy is also useful in extreme situations where the variance, and possibly even mean, of the service time diverge-as resetting can then prevent queues from "blowing up." We illustrate these results on the M/G/1 queue in which service times are general and arrivals are assumed to be Markovian. However, the main results and conclusions coming from our analysis are not specific to this particular model system. Thus, the results presented herein can be carried over to other queueing systems: in telecommunications, via computing, and all the way to molecular queues that emerge in enzymatic and metabolic cycles of living organisms.
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Affiliation(s)
- Ofek Lauber Bonomo
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel,Center for the Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv 6997801, Israel,The Sackler Center for Computational Molecular and Materials Science, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Arnab Pal
- School of Chemistry, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel,Center for the Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv 6997801, Israel,The Institute of Mathematical Sciences, IV Cross Road, CIT Campus, Taramani, Chennai 600113, Tamil Nadu, India,Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai 400094, India
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Kloska SM, Pałczyński K, Marciniak T, Talaśka T, Miller M, Wysocki BJ, Davis P, Wysocki TA. Queueing theory model of pentose phosphate pathway. Sci Rep 2022; 12:4601. [PMID: 35301361 PMCID: PMC8930976 DOI: 10.1038/s41598-022-08463-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/08/2022] [Indexed: 11/25/2022] Open
Abstract
Due to its role in maintaining the proper functioning of the cell, the pentose phosphate pathway (PPP) is one of the most important metabolic pathways. It is responsible for regulating the concentration of simple sugars and provides precursors for the synthesis of amino acids and nucleotides. In addition, it plays a critical role in maintaining an adequate level of NADPH, which is necessary for the cell to fight oxidative stress. These reasons prompted the authors to develop a computational model, based on queueing theory, capable of simulating changes in PPP metabolites’ concentrations. The model has been validated with empirical data from tumor cells. The obtained results prove the stability and accuracy of the model. By applying queueing theory, this model can be further expanded to include successive metabolic pathways. The use of the model may accelerate research on new drugs, reduce drug costs, and reduce the reliance on laboratory animals necessary for this type of research on which new methods are tested.
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Affiliation(s)
- Sylwester M Kloska
- Faculty of Medicine, Nicolaus Copernicus University Ludwik Rydygier Collegium Medicum, 85-094, Bydgoszcz, Poland.
| | - Krzysztof Pałczyński
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, 85-796, Bydgoszcz, Poland
| | - Tomasz Marciniak
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, 85-796, Bydgoszcz, Poland
| | - Tomasz Talaśka
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, 85-796, Bydgoszcz, Poland
| | - Marissa Miller
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, NE, 68182, USA
| | - Beata J Wysocki
- Department of Biology, University of Nebraska at Omaha, Omaha, NE, 68182, USA
| | - Paul Davis
- Department of Biology, University of Nebraska at Omaha, Omaha, NE, 68182, USA
| | - Tadeusz A Wysocki
- Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, 85-796, Bydgoszcz, Poland. .,Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, NE, 68182, USA.
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Kloska S, Pałczyński K, Marciniak T, Talaśka T, Nitz M, Wysocki BJ, Davis P, Wysocki TA. Queueing theory model of Krebs cycle. Bioinformatics 2021; 37:2912-2919. [PMID: 33724355 DOI: 10.1093/bioinformatics/btab177] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 03/08/2021] [Accepted: 03/11/2021] [Indexed: 02/02/2023] Open
Abstract
MOTIVATION Queueing theory can be effective in simulating biochemical reactions taking place in living cells, and the article paves a step toward development of a comprehensive model of cell metabolism. Such a model could help to accelerate and reduce costs for developing and testing investigational drugs reducing number of laboratory animals needed to evaluate drugs. RESULTS The article presents a Krebs cycle model based on queueing theory. The model allows for tracking of metabolites concentration changes in real time. To validate the model, a drug-induced inhibition affecting activity of enzymes involved in Krebs cycle was simulated and compared with available experimental data. AVAILABILITYAND IMPLEMENTATION The source code is freely available for download at https://github.com/UTP-WTIiE/KrebsCycleUsingQueueingTheory, implemented in C# supported in Linux or MS Windows. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Sylwester Kloska
- Faculty of Medicine, Nicolaus Copernicus University Ludwik Rydygier Collegium Medicum, 85-067 Bydgoszcz, Poland
| | - Krzysztof Pałczyński
- Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland
| | - Tomasz Marciniak
- Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland
| | - Tomasz Talaśka
- Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland
| | - Marissa Nitz
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, NE 68182, USA
| | - Beata J Wysocki
- Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA
| | - Paul Davis
- Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA
| | - Tadeusz A Wysocki
- Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland.,Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, NE 68182, USA
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Clement EJ, Schulze TT, Soliman GA, Wysocki BJ, Davis PH, Wysocki TA. Stochastic Simulation of Cellular Metabolism. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2020; 8:79734-79744. [PMID: 33747671 PMCID: PMC7971159 DOI: 10.1109/access.2020.2986833] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Increased technological methods have enabled the investigation of biology at nanoscale levels. Such systems require the use of computational methods to comprehend the complex interactions that occur. The dynamics of metabolic systems have been traditionally described utilizing differential equations without fully capturing the heterogeneity of biological systems. Stochastic modeling approaches have recently emerged with the capacity to incorporate the statistical properties of such systems. However, the processing of stochastic algorithms is a computationally intensive task with intrinsic limitations. Alternatively, the queueing theory approach, historically used in the evaluation of telecommunication networks, can significantly reduce the computational power required to generate simulated results while simultaneously reducing the expansion of errors. We present here the application of queueing theory to simulate stochastic metabolic networks with high efficiency. With the use of glycolysis as a well understood biological model, we demonstrate the power of the proposed modeling methods discussed herein. Furthermore, we describe the simulation and pharmacological inhibition of glycolysis to provide an example of modeling capabilities.
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Affiliation(s)
- Emalie J. Clement
- Department of Biology, University of Nebraska at Omaha, Omaha, Nebraska, USA
| | - Thomas T. Schulze
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Ghada A. Soliman
- Graduate School of Public Health and Health Policy, City University of New York, New York, USA
| | - Beata J. Wysocki
- Department of Biology, University of Nebraska at Omaha, Omaha, Nebraska, USA
| | - Paul H. Davis
- Department of Biology, University of Nebraska at Omaha, Omaha, Nebraska, USA
| | - Tadeusz A. Wysocki
- Department of Electrical and Computer Engineering, University of Nebraska – Lincoln, Omaha, Nebraska, USA
- UTP University, Bydgoszcz, Poland
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