Prediction of source nutrients for microorganisms using metabolic networks
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866915816615706624 |
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| author | Bulka, Olivia Nedjad, Chabname Ghassemi Paulevé, Loïc Prigent, Sylvain Frioux, Clémence |
| author_facet | Bulka, Olivia Nedjad, Chabname Ghassemi Paulevé, Loïc Prigent, Sylvain Frioux, Clémence |
| contents | Metagenomics has lowered the barrier to microbial discovery--enabling the identification of novel microbes without isolation--but cultures remain imperative for the deep study of microbes. Cultivation and isolation of non-model microbes remains a major challenge, despite advances in high-throughput culturomic methods. The quantity of simultaneous experimental variables is constrained by time and resources, but the list can be reduced using computational biology. Given an annotated genome, metabolic modelling can be used to predict source nutrients required for the growth of a microbe, which acts as an initial screen to inform culture and isolation experiments. This chapter provides an overview of metabolic networks and modelling and how they can be used to predict the nutrient requirements of a microorganism, followed by a sample protocol using a toy metabolic network, which is then expanded to a genome-scale metabolic network application. These methods can be applied to any metabolic network of interest--which in turn can be created from any genome of interest--and are a starting point for experimental validation of source nutrients required for microorganisms that remain uncultivated to date. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_21993 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Prediction of source nutrients for microorganisms using metabolic networks Bulka, Olivia Nedjad, Chabname Ghassemi Paulevé, Loïc Prigent, Sylvain Frioux, Clémence Molecular Networks Quantitative Methods Metagenomics has lowered the barrier to microbial discovery--enabling the identification of novel microbes without isolation--but cultures remain imperative for the deep study of microbes. Cultivation and isolation of non-model microbes remains a major challenge, despite advances in high-throughput culturomic methods. The quantity of simultaneous experimental variables is constrained by time and resources, but the list can be reduced using computational biology. Given an annotated genome, metabolic modelling can be used to predict source nutrients required for the growth of a microbe, which acts as an initial screen to inform culture and isolation experiments. This chapter provides an overview of metabolic networks and modelling and how they can be used to predict the nutrient requirements of a microorganism, followed by a sample protocol using a toy metabolic network, which is then expanded to a genome-scale metabolic network application. These methods can be applied to any metabolic network of interest--which in turn can be created from any genome of interest--and are a starting point for experimental validation of source nutrients required for microorganisms that remain uncultivated to date. |
| title | Prediction of source nutrients for microorganisms using metabolic networks |
| topic | Molecular Networks Quantitative Methods |
| url | https://arxiv.org/abs/2602.21993 |