Non-linear population dynamics in chemostats associated with live–dead cell cycling in Escherichia coli strain K12-MG1655
Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simpl...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Chi Fru, Ernest [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2010 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag 2010 |
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| Übergeordnetes Werk: |
Enthalten in: Applied microbiology and biotechnology - Springer-Verlag, 1984, 89(2010), 3 vom: 03. Okt., Seite 791-798 |
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| Übergeordnetes Werk: |
volume:89 ; year:2010 ; number:3 ; day:03 ; month:10 ; pages:791-798 |
| Links: |
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| DOI / URN: |
10.1007/s00253-010-2895-6 |
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OLC2050732627 |
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| 520 | |a Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. | ||
| 650 | 4 | |a Bacteria | |
| 650 | 4 | |a Chemostats | |
| 650 | 4 | |a Population dynamics | |
| 650 | 4 | |a Cell death | |
| 650 | 4 | |a Carrying capacity | |
| 700 | 1 | |a Ofiţeru, Irina Dana |4 aut | |
| 700 | 1 | |a Lavric, Vasile |4 aut | |
| 700 | 1 | |a Graham, David W. |4 aut | |
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10.1007/s00253-010-2895-6 doi (DE-627)OLC2050732627 (DE-He213)s00253-010-2895-6-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Chi Fru, Ernest verfasserin aut Non-linear population dynamics in chemostats associated with live–dead cell cycling in Escherichia coli strain K12-MG1655 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. Bacteria Chemostats Population dynamics Cell death Carrying capacity Ofiţeru, Irina Dana aut Lavric, Vasile aut Graham, David W. aut Enthalten in Applied microbiology and biotechnology Springer-Verlag, 1984 89(2010), 3 vom: 03. Okt., Seite 791-798 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:89 year:2010 number:3 day:03 month:10 pages:791-798 https://doi.org/10.1007/s00253-010-2895-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_23 GBV_ILN_40 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_130 GBV_ILN_147 GBV_ILN_267 GBV_ILN_2004 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4307 AR 89 2010 3 03 10 791-798 |
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10.1007/s00253-010-2895-6 doi (DE-627)OLC2050732627 (DE-He213)s00253-010-2895-6-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Chi Fru, Ernest verfasserin aut Non-linear population dynamics in chemostats associated with live–dead cell cycling in Escherichia coli strain K12-MG1655 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. Bacteria Chemostats Population dynamics Cell death Carrying capacity Ofiţeru, Irina Dana aut Lavric, Vasile aut Graham, David W. aut Enthalten in Applied microbiology and biotechnology Springer-Verlag, 1984 89(2010), 3 vom: 03. Okt., Seite 791-798 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:89 year:2010 number:3 day:03 month:10 pages:791-798 https://doi.org/10.1007/s00253-010-2895-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_23 GBV_ILN_40 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_130 GBV_ILN_147 GBV_ILN_267 GBV_ILN_2004 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4307 AR 89 2010 3 03 10 791-798 |
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10.1007/s00253-010-2895-6 doi (DE-627)OLC2050732627 (DE-He213)s00253-010-2895-6-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Chi Fru, Ernest verfasserin aut Non-linear population dynamics in chemostats associated with live–dead cell cycling in Escherichia coli strain K12-MG1655 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. Bacteria Chemostats Population dynamics Cell death Carrying capacity Ofiţeru, Irina Dana aut Lavric, Vasile aut Graham, David W. aut Enthalten in Applied microbiology and biotechnology Springer-Verlag, 1984 89(2010), 3 vom: 03. Okt., Seite 791-798 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:89 year:2010 number:3 day:03 month:10 pages:791-798 https://doi.org/10.1007/s00253-010-2895-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_23 GBV_ILN_40 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_130 GBV_ILN_147 GBV_ILN_267 GBV_ILN_2004 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4307 AR 89 2010 3 03 10 791-798 |
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10.1007/s00253-010-2895-6 doi (DE-627)OLC2050732627 (DE-He213)s00253-010-2895-6-p DE-627 ger DE-627 rakwb eng 570 VZ 12 ssgn BIODIV DE-30 fid Chi Fru, Ernest verfasserin aut Non-linear population dynamics in chemostats associated with live–dead cell cycling in Escherichia coli strain K12-MG1655 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. Bacteria Chemostats Population dynamics Cell death Carrying capacity Ofiţeru, Irina Dana aut Lavric, Vasile aut Graham, David W. aut Enthalten in Applied microbiology and biotechnology Springer-Verlag, 1984 89(2010), 3 vom: 03. Okt., Seite 791-798 (DE-627)129942634 (DE-600)392453-1 (DE-576)015507750 0175-7598 nnns volume:89 year:2010 number:3 day:03 month:10 pages:791-798 https://doi.org/10.1007/s00253-010-2895-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_23 GBV_ILN_40 GBV_ILN_69 GBV_ILN_70 GBV_ILN_100 GBV_ILN_130 GBV_ILN_147 GBV_ILN_267 GBV_ILN_2004 GBV_ILN_2018 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4307 AR 89 2010 3 03 10 791-798 |
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Enthalten in Applied microbiology and biotechnology 89(2010), 3 vom: 03. Okt., Seite 791-798 volume:89 year:2010 number:3 day:03 month:10 pages:791-798 |
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Enthalten in Applied microbiology and biotechnology 89(2010), 3 vom: 03. Okt., Seite 791-798 volume:89 year:2010 number:3 day:03 month:10 pages:791-798 |
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non-linear population dynamics in chemostats associated with live–dead cell cycling in escherichia coli strain k12-mg1655 |
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Non-linear population dynamics in chemostats associated with live–dead cell cycling in Escherichia coli strain K12-MG1655 |
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Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. © Springer-Verlag 2010 |
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Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. © Springer-Verlag 2010 |
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Abstract Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between $ OD_{600} $ and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local $ OD_{600} $ maxima and lowest at local $ OD_{600} $ minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. © Springer-Verlag 2010 |
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