Single-cell metabolic flux analysis reveals coexisting optimal sub-groups, cross-feeding, and mixotrophy in a cyanobacterial population
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
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2025
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| _version_ | 1866918047440175104 |
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| author | Ferrero-Fernández, Arián Prondzinsky, Paula Gastoldi, Lucia Fike, David A. Smith, Harrison B. De Martino, Daniele De Martino, Andrea McGlynn, Shawn Erin |
| author_facet | Ferrero-Fernández, Arián Prondzinsky, Paula Gastoldi, Lucia Fike, David A. Smith, Harrison B. De Martino, Daniele De Martino, Andrea McGlynn, Shawn Erin |
| contents | We derive a single-cell level understanding of metabolism in an isogenic cyanobacterial population by integrating secondary ion mass spectrometry (SIMS) derived multi-isotope uptake measurements of Synechocystis sp. PCC6803 with a statistical inference protocol based on Liebig's law of the minimum, the maximum entropy principle, and constraint-based modeling. We find the population is structured in two metabolically distinct clusters: cells optimizing carbon yield while excessively turning over nitrogen, and cells which act reciprocally, optimizing nitrogen yield and excessively turning over carbon. This partition enables partial heterotrophy within the population via metabolic exchange, likely in the form of organic acids. Exchange increases the feasible metabolic space, and mixotrophic cells achieve the fastest growth rates. Metabolic flux analysis at the single-cell level reveals heterogeneity in carbon fixation rates, Rubisco specificity, and nitrogen assimilation. Our results provide a necessary foundation for understanding how population level phenotypes arise from the collective contributions of distinct individuals. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_05916 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Single-cell metabolic flux analysis reveals coexisting optimal sub-groups, cross-feeding, and mixotrophy in a cyanobacterial population Ferrero-Fernández, Arián Prondzinsky, Paula Gastoldi, Lucia Fike, David A. Smith, Harrison B. De Martino, Daniele De Martino, Andrea McGlynn, Shawn Erin Populations and Evolution Biological Physics Molecular Networks We derive a single-cell level understanding of metabolism in an isogenic cyanobacterial population by integrating secondary ion mass spectrometry (SIMS) derived multi-isotope uptake measurements of Synechocystis sp. PCC6803 with a statistical inference protocol based on Liebig's law of the minimum, the maximum entropy principle, and constraint-based modeling. We find the population is structured in two metabolically distinct clusters: cells optimizing carbon yield while excessively turning over nitrogen, and cells which act reciprocally, optimizing nitrogen yield and excessively turning over carbon. This partition enables partial heterotrophy within the population via metabolic exchange, likely in the form of organic acids. Exchange increases the feasible metabolic space, and mixotrophic cells achieve the fastest growth rates. Metabolic flux analysis at the single-cell level reveals heterogeneity in carbon fixation rates, Rubisco specificity, and nitrogen assimilation. Our results provide a necessary foundation for understanding how population level phenotypes arise from the collective contributions of distinct individuals. |
| title | Single-cell metabolic flux analysis reveals coexisting optimal sub-groups, cross-feeding, and mixotrophy in a cyanobacterial population |
| topic | Populations and Evolution Biological Physics Molecular Networks |
| url | https://arxiv.org/abs/2506.05916 |