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1دورية أكاديمية
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: Supporting information for: Is it selfish to be filamentous in biofilms? Individual-based modeling links microbial growth strategies with morphology using the new and modular iDynoMiCS 2.0.
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.s001Test
https://figshare.com/articles/journal_contribution/Supporting_information_for_Is_it_selfish_to_be_filamentous_in_biofilms_Individual-based_modeling_links_microbial_growth_strategies_with_morphology_using_the_new_and_modular_iDynoMiCS_2_0_/25320030Test -
2صورة
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: Interaction with the program takes place through the GUI or command line terminal. A protocol file specifying a model can be loaded to initialize the simulator. If parameters are missing from the protocol file, a default is loaded or the user is queried if no default exists. Scheduling ensures predictable handling of the compartments and the order of processes occurring within them. A species library is kept such that properties and/or behavior that are identical for agents of the same species can be looked up from the library. The simulator further ensures that the model state is saved at the end of each global time step. Spatially explicit and well-mixed compartments can be connected. Solutes concentration fields are stored as matrices, which include local solute concentrations, local diffusivity and reaction rates. The collective of agents represents the biofilm, agents may have many properties depending on user specifications, basic properties are species, mass and position of the agent. Processes act upon the information in the model system and describe the processes occurring in the model such as mechanical interactions or diffusion, or generate output from the active model state. Colors are used to distinguish between the different elements of iDynoMiCS 2.0. The core elements are orange, input elements are blue, output elements are green and helper algorithms and data structures are yellow.
العلاقة: https://figshare.com/articles/figure/The_basic_structure_of_an_iDynoMiCS_2_0_model_/25320033Test
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.g001Test
https://figshare.com/articles/figure/The_basic_structure_of_an_iDynoMiCS_2_0_model_/25320033Test -
3صورة
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: Dashed lines indicate sphere-swept volumes of ‘dots’ or line-segments. Dots are mass-points indicating position and orientation of agents. Solid lines indicate mechanical interactions between points (forces between points modeled as springs): Collision interaction (b-c), spine interaction responsible for the rigidity of rod-shaped agents (d1-2 and e1-2), connecting interactions (d2-e1, e2-f, f-g). α is the angle between two elements of a filament. This angle can be counteracted by a torsion spring applying forces on d1, d2 and e1. L1 and L2 are the moment arms. The torsion spring applies force until the angle α reaches 180°, aligning the three points.
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.g002Test
https://figshare.com/articles/figure/Different_agent_shapes_in_iDynoMiCS_2_0_/25320036Test -
4صورة
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: Steady state organic carbon (Chemical Oxygen Demand, COD) and ammonium concentrations in the bulk liquid for the three different BM3 cases (HA: High ammonium, SC: Standard case, LA: Low ammonium) across 7 model implementations (W: a one-dimensional continuum biomass model run on the AQUASIM software [ 53 ] and developed by Peter Reichert and Oskar Wanner [ 54 , 55 ], M1: a variant of the W model with a fixed boundary-layer thickness by Eberhard Morgenroth et al. [ 56 ], DN: a two-dimensional cellular automaton model developed by Daniel Noguera and colleagues [ 57 ], CP: a two-dimensional individual-based model, with biomass spreading via shoving, developed by Cristian Picioreanu and colleagues [ 58 ], NUFEB: a three-dimensional individual-based model by Li et al. [ 21 ], iD: an individual-based model by Lardon et al. [ 17 ] (iDynoMiCS 1), iD2: iDynoMiCS 2.0, either with shoving algorithm similar to iD or the new Force-based Mechanics). Data and analysis are included in Table I in S1 Text .
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.g004Test
https://figshare.com/articles/figure/Comparing_steady_states_in_BM3_/25320042Test -
5صورة
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: Rate Strategists (RS, blue) and Yield Strategists (YS, red) competed in a 3D biofilm domain (200x200x12.5 μm) for 3 weeks. In the first 4 rows, different strategies competed. Column 1 corresponds to spherical cell scenarios in Fig 2 of Ref [ 59 ] but were now simulated in 3D. In column 2, RS formed filaments and in column 3, YS formed filaments. Filaments won regardless of strategy. In column 4, both formed filaments and RS won or likely won. The last 3 rows show single species ‘controls’ with 10, 20 or 100 initial agents. The first two columns show simulations with spherical YS or RS agents while the last two columns show filament forming YS or RS agents. See Fig 7 for corresponding time courses. Duplicate simulations are shown in Fig G in S1 Text . The filamentous microbes incorporate a basic life cycle in which initially spherical agents extend into rod shaped agents to further extend into multi-segmented filaments as described in S1.14.
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.g006Test
https://figshare.com/articles/figure/Filaments_rule_and_gave_Rate_Strategists_an_advantage_/25320048Test -
6صورة
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: Rate Strategist (RS, blue) and Yield Strategist (YS, red) competitions using the shoving algorithm in BacSim [ 59 ] (reproduced from “Kreft J-U (2004). Biofilms promote altruism. Microbiology 150: 2751–2760” with permission) were replicated in iDynoMiCS 2.0 with its force-based mechanics. Cells were initially placed in alternating, equidistant positions with increasing density from 5 cells per strategy (Scenario 1: a-b), 10 cells each (Scenario 2: e-h) to 50 cells each (Scenario 3: i-l and c-d). iDynoMiCS 2.0 panels show local oxygen concentration as a linear gray-level gradient from zero oxygen (0 mg L -1 , white) to a maximum concentration (S ox_bulk = 1 mg L -1 , black). Block 1 shows 3-week-old biofilms. Block 2 zooms into panels i and j. Block 3 shows 10-week-old biofilms developed from the 3-week-old biofilms shown in the same position on the left.
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.g005Test
https://figshare.com/articles/figure/Biofilms_promote_altruism_case_study_/25320045Test -
7صورة
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: A nitrifying biofilm was initiated with 1 , 000 Ammonium Oxidizing Organisms (red) and 1 , 000 Nitrite Oxidizing Organisms (blue) in a 500x500x500 μm domain . Growth kinetics were adopted from Hubaux et al. [ 49 ]. Both species produced EPS particles (gray semi-transparent). Agents that dropped below 20% of their division mass as a result of endogenous respiration (maintenance metabolism) became inactive (black). The 175-day biofilm contained 1.02×10 7 agents (bacteria and EPS particles).
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.g003Test
https://figshare.com/articles/figure/iDynoMiCS_2_0_was_capable_of_simulating_large_3D_biofilms_/25320039Test -
8صورة
المؤلفون: Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft
مصطلحات موضوعية: Ecology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, undergone intensive testing, substantially enhanced ease, scalability enabling simulations, graphical user interface, 10 million agents, spherical agent morphologies, second test case, different models without, key new features, div >< p, mi , dyn , c , modular idynomics 2, new idynomics 2, 0 , , idynomics 2, case study, agent properties, based models, unit tests, unit conversions, stronger competition, specific advantages, shoving algorithm
الوصف: Duplicates are plotted with dashed lines. Divergence between replicates is most visible in panels g and p. In panel p, it is too early to definitely call the outcome of competition, but it is likely that RS would win given the biofilm structure after 3 weeks ( Fig 6P ).
الإتاحة: https://doi.org/10.1371/journal.pcbi.1011303.g007Test
https://figshare.com/articles/figure/Growth_curves_corresponding_to_competitions_of_Rate_Strategists_RS_blue_and_Yield_Strategists_YS_red_in_Fig_6_/25320051Test -
9
المصدر: Current opinion in biotechnology. 62
مصطلحات موضوعية: 0106 biological sciences, Biomedical Engineering, Bioengineering, complex mixtures, 01 natural sciences, Redox, 03 medical and health sciences, Bacteria, Anaerobic, Bioreactors, 010608 biotechnology, Organic matter, 030304 developmental biology, chemistry.chemical_classification, 0303 health sciences, Chemistry, Ecology, Oxidation reduction, equipment and supplies, Anoxic waters, Bacteria, Aerobic, Oxygen, High flux, Anaerobic exercise, Flux (metabolism), Oxidation-Reduction, Division of labour, Biotechnology
الوصف: Metabolic division of the labour of organic matter decomposition into several steps carried out by different types of microbes is typical for many anoxic — but not oxic environments. An explanation of this well-known pattern is proposed based on the combination of three key insights: (i) well-studied anoxic environments are high flux environments: they are only anoxic because their high organic matter influx leads to oxygen depletion; (ii) shorter, incomplete catabolic pathways provide the capacity for higher flux, but this capacity is only advantageous in high flux environments; (iii) longer, complete catabolic pathways have energetic happy ends but only with high redox potential electron acceptors. Thus, aerobic environments favour longer pathways. Bioreactors, in contrast, are high flux environments and therefore favour division of catabolic labour even if aeration keeps them aerobic; therefore, host strains and feeding strategies must be carefully engineered to resist this pull.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18f1032ffd5c9d04dfd620917366b552Test
https://pubmed.ncbi.nlm.nih.gov/31654858Test -
10
المؤلفون: Johan H. J. Leveau, Caroline M. Plugge, Weiwen Zhang, Clara Prats, Ferdi L. Hellweger, Jan-Ulrich Kreft
المساهمون: Universitat Politècnica de Catalunya. Departament de Física, Universitat Politècnica de Catalunya. BIOCOM-SC - Grup de Biologia Computacional i Sistemes Complexos
المصدر: Frontiers in microbiology, vol 8, iss NOV
Frontiers in Microbiology, 8(NOV)
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Recercat. Dipósit de la Recerca de Catalunya
instname
Frontiers in Microbiology 8 (2017) NOV
Frontiers in Microbiology
Frontiers in Microbiology, Vol 8 (2017)مصطلحات موضوعية: 0301 basic medicine, individuality, Microbiology (medical), Environmental Science and Management, Population, lcsh:QR1-502, Individuality, Microbiologia, Review, Variation (game tree), Biology, microbial ecology, Microbiology, lcsh:Microbiology, Microbial ecology, 03 medical and health sciences, Microbiologie, Genetics, Enginyeria agroalimentària::Ciències de la terra i de la vida::Microbiologia [Àrees temàtiques de la UPC], Ecosystem, Single cell, education, Gene, 2. Zero hunger, education.field_of_study, WIMEK, gene-centric modeling, Mechanism (biology), Ecology, agent-based modeling, 15. Life on land, single cell, Gene-centric modeling, metabolic flux modeling, Genètica microbiana, 030104 developmental biology, 13. Climate action, Evolutionary biology, Agent-based modeling, Soil Sciences, Ecosystem management, Generic health relevance, Metabolic flux modeling, heterogeneity, Heterogeneity, Flux (metabolism), Microbial genetics
الوصف: Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality) is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression), stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s) underlying it for the specific microbial system and question investigated is essential for selecting the optimal modeling strategy.
وصف الملف: application/pdf; application/octet-stream
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e305635e1a1ce2c63c0c85798ec0a3cTest
