Modelling microbial metabolic rewiring during growth in a complex medium
Abstract Background In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes...
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ftdatacite:10.6084/m9.figshare.c.3621479 2023-05-15T13:58:34+02:00 Modelling microbial metabolic rewiring during growth in a complex medium Fondi, Marco Bosi, Emanuele Presta, Luana Natoli, Diletta Fani, Renato 2016 https://dx.doi.org/10.6084/m9.figshare.c.3621479 https://figshare.com/collections/Modelling_microbial_metabolic_rewiring_during_growth_in_a_complex_medium/3621479 unknown Figshare https://dx.doi.org/10.1186/s12864-016-3311-0 CC BY 4.0 https://creativecommons.org/licenses/by/4.0 CC-BY Medicine Genetics FOS Biological sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences Computational Biology Collection article 2016 ftdatacite https://doi.org/10.6084/m9.figshare.c.3621479 https://doi.org/10.1186/s12864-016-3311-0 2021-11-05T12:55:41Z Abstract Background In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. Results We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. Conclusions Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA. Article in Journal/Newspaper Antarc* Antarctic DataCite Metadata Store (German National Library of Science and Technology) Antarctic The Antarctic Moma ENVELOPE(143.184,143.184,66.437,66.437) |
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Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
Medicine Genetics FOS Biological sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences Computational Biology |
spellingShingle |
Medicine Genetics FOS Biological sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences Computational Biology Fondi, Marco Bosi, Emanuele Presta, Luana Natoli, Diletta Fani, Renato Modelling microbial metabolic rewiring during growth in a complex medium |
topic_facet |
Medicine Genetics FOS Biological sciences Ecology 69999 Biological Sciences not elsewhere classified Inorganic Chemistry FOS Chemical sciences Computational Biology |
description |
Abstract Background In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. Results We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. Conclusions Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA. |
format |
Article in Journal/Newspaper |
author |
Fondi, Marco Bosi, Emanuele Presta, Luana Natoli, Diletta Fani, Renato |
author_facet |
Fondi, Marco Bosi, Emanuele Presta, Luana Natoli, Diletta Fani, Renato |
author_sort |
Fondi, Marco |
title |
Modelling microbial metabolic rewiring during growth in a complex medium |
title_short |
Modelling microbial metabolic rewiring during growth in a complex medium |
title_full |
Modelling microbial metabolic rewiring during growth in a complex medium |
title_fullStr |
Modelling microbial metabolic rewiring during growth in a complex medium |
title_full_unstemmed |
Modelling microbial metabolic rewiring during growth in a complex medium |
title_sort |
modelling microbial metabolic rewiring during growth in a complex medium |
publisher |
Figshare |
publishDate |
2016 |
url |
https://dx.doi.org/10.6084/m9.figshare.c.3621479 https://figshare.com/collections/Modelling_microbial_metabolic_rewiring_during_growth_in_a_complex_medium/3621479 |
long_lat |
ENVELOPE(143.184,143.184,66.437,66.437) |
geographic |
Antarctic The Antarctic Moma |
geographic_facet |
Antarctic The Antarctic Moma |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
https://dx.doi.org/10.1186/s12864-016-3311-0 |
op_rights |
CC BY 4.0 https://creativecommons.org/licenses/by/4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.6084/m9.figshare.c.3621479 https://doi.org/10.1186/s12864-016-3311-0 |
_version_ |
1766266917763416064 |