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Correlative adaptation between Rubisco and CO2-concentrating mechanisms in seagrasses

Nature Plants volume 8, pages 706–716 (2022)Cite this article

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An Author Correction to this article was published on 29 June 2022

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Abstract

Submerged angiosperms sustain some of the most productive and diverse ecosystems worldwide. However, their carbon acquisition and assimilation mechanisms remain poorly explored, missing an important step in the evolution of photosynthesis during the colonization of aquatic environments by angiosperms. Here we reveal a convergent kinetic adaptation of Rubisco in phylogenetically distant seagrass species that share catalytic efficiencies and CO2 and O2 affinities up to three times lower than those observed in phylogenetically closer angiosperms from terrestrial, freshwater and brackish-water habitats. This Rubisco kinetic convergence was found to correlate with the effectiveness of seagrass CO2-concentrating mechanisms (CCMs), which probably evolved in response to the constant CO2 limitation in marine environments. The observed Rubisco kinetic adaptation in seagrasses more closely resembles that seen in eukaryotic algae operating CCMs rather than that reported in terrestrial C4 plants. Our results thus demonstrate a general pattern of co-evolution between Rubisco function and biophysical CCM effectiveness that traverses distantly related aquatic lineages.

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Fig. 1: Box plots of the indirect proxies for the CCMs of aquatic angiosperms.
Fig. 2: Box plots of the Rubisco kinetic parameters from the analysed species compared with the Rubisco kinetic parameters from terrestrial plants (C3 and C4 species) and eukaryotic algae (form IB or ID Rubisco) possessing CCMs, compiled by Iñiguez et al.21 and Goudet et al.23.
Fig. 3: CCM effectiveness in delivering CO2 to Rubisco.
Fig. 4: Ratio of the modelled ARub between either brackish-water or marine Rubisco and freshwater Rubisco.
Fig. 5: Modelled leaf net photosynthetic rate as a function of Cc using equations of the photosynthetic C3 model of Farquhar et al.41 and average Rubisco kinetic data of the species from each environment.

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Data availability

All processed data are contained in the manuscript or in the supplementary data files. The 61 rbcL sequences used in this study were extracted from GenBank at https://www.ncbi.nlm.nih.gov/nuccore (see the accession numbers in Supplementary Fig. 1). The reference rbcL sequence of Spinacia oleracea is under accession number NC 002202.1 in GenBank. The kinetic data used for Fig. 2 were extracted from Iñiguez et al.21 (the data are freely available at https://onlinelibrary.wiley.com/doi/10.1111/tpj.14643) and Goudet et al.23 (the data are freely available at https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.16577). The spinach three-dimensional Rubisco structure used in Extended Data Fig. 3 is available at PDB under accession number 1UPM (https://www.rcsb.org/structure/1UPM). Source data are provided with this paper.

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Acknowledgements

This work was financially supported by the Spanish Ministry of Sciences, Innovation and Universities, the Spanish State Research Agency and the European Regional Development Funds (project no. PGC2018-094621-B-I00) awarded to J.G. S.C.-B. was supported by an FPU Grant from the Spanish Ministry of Education. C.I. was supported by a postdoctoral grant from the government of the Balearic Islands. We thank T. Garcia for technical help and organization of the radioisotope installation at the Serveis Científico-Tècnics (UIB); M. Ribas-Carbó, C. Douthe and B. Martorell for their technical help on the IRMS; and Jardí Botànic de Sóller, M. Mus, A. Martínez, J. Rita, X. Gago, F. Tomas, J. Máñez-Crespo, Á. Mateo-Ramírez, M. Fullana and M. Del Río Buzón for their help in the identification and sampling of the species. We thank X. Niell for comments that helped improve this manuscript.

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Authors and Affiliations

  1. Research Group on Plant Biology under Mediterranean Conditions, Universitat de les Illes Balears–INAGEA, Palma, Spain

    Sebastià Capó-Bauçà, Concepción Iñiguez, Pere Aguiló-Nicolau & Jeroni Galmés

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  1. Sebastià Capó-Bauçà
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Contributions

C.I. and J.G. conceived and designed the study. S.C.-B. performed the experiments, analysed the data and produced the figures with help from all authors. P.A.-N. collaborated in the processing of the samples. S.C.-B. wrote most of the manuscript with help from all authors.

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Correspondence to Concepción Iñiguez.

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Extended data

Extended Data Fig. 1 Net photosynthetic rates under different pH.

a, freshwater species (P = 8.3 ×10−7 in C. demersum and P = 0.0002 in V. gigantea); b, brackish water species (P = 3.3 ×10−8 in S. pectinata and P = 8.6 ×10−11 in R. cirrhosa); c, seawater species (P = 8.2 ×10−5 in P. oceanica, P = 0.1601 in C. nodosa, P = 0.3993 in Z. noltii and P = 5.7 ×10−6 in Z. marina). Points are means ± s.e. Different letters show significant differences among net photosynthetic rates. P values were obtained from the F-statistic of one-way ANOVA or from the chi-squared value of Kruskal–Wallis test in the case of non-parametric data. Duncan’s test and Kruskal–Wallis test followed by Bonferroni correction for non-parametric data were used to detect differences among means.

Source data

Extended Data Fig. 2 Principal Component Analysis of the CO2 concentrating mechanism proxies analysed.

Variables included are: isotopic discrimination of 13C of leaf biomass (δ13C), pH compensation point determined by pH-drift assay (pH*), in vivo photosynthetic semi-saturation constant for CO2 (Km CO2) and for dissolved inorganic carbon (Km DIC), percentage of the net photosynthetic rate inhibition after addition of acetazolamide (AZ), ethoxyzolamide (EZ), TRIS-buffer (TRIS) and 4,40-diisothiocyanatostilbene-2,20-disulfonate (DIDS), and the percentage of the net photosynthetic rate variation at pH 9-9.5 (An rate at high pH) and at pH 7-7.5 (An rate at low pH) relative to water environmental pH (pH ~8).

Source data

Extended Data Fig. 3 rbcL and amino acid Rubisco large subunit analyses.

a, Maximum likelihood tree inferred from the rbcL of the species selected in this study. Bootstrap values (from 1000 replicates) are indicated at the nodes. Colour names indicate the environment of the species: blue are seagrasses species, red are brackish- water species, green are freshwater species and orange terrestrial species. b, Alignment of the rbcL amino acid sequences from the species belonging to the two main branches identified in the previous maximum likelihood tree containing the analysed seagrasses. In blue, amino acid changes among Stuckenia pectinata, and Zostera species; in red, amino acid changes between Ruppia cirrhosa and Posidonia oceanica; in green, amino acid changes between Ruppia cirrhosa and Cymodocea nodosa. Amino acids in boxes denote differences between Z. noltii and Z. marina and amino acid changes shared by C. nodosa and P. oceanica. c, localisation of variable amino acid sites between R. cirrhosa and P. oceanica. d, localisation of variable amino acid sites between R. cirrhosa and C. nodosa. e, localisation of variable amino acid sites between Stuckenia pectinata and Zostera species. f, localisation of variable amino acid sites between Z. noltii and Z. marina. Two L-subunits forming a functional dimer are highlighted in green and cyan in all Rubisco structures showed. Rubisco L-subunit residues are presented on the structure of spinach Rubisco (1UPM) using UCSF Chimera V1.12. Note: The large phylogenetic distance among the species made difficult to relate the particularities of Rubisco catalytic properties of seagrasses to specific amino acid changes. However, the two congeneric Zostera species included in the study only differed at positions 249 and 353 of the Rubisco large subunit sequence (Extended Data Fig. 3f), which coincide with a significantly lower Sc/o in Z. noltii compared with Z. marina (Table 1).

Source data

Extended Data Fig. 4 Modelled Rubisco gross assimilation rate (ARub) for the analysed aquatic species.

Solid line, seagrasses; dotted line, brackish water species; dashed line, freshwater species. The photosynthesis model of Farquhar et al. 41 was used to model ARub at the different concentrations of chloroplastic CO2 (Cc). This modelling exercise was done assuming CO2 assimilation rates under saturating light conditions and Rubisco content standardized to 1 g m−2.

Source data

Extended Data Fig. 5 Modelled leaf net photosynthetic rate as a function of chloroplastic CO2 (Cc) using equations of the photosynthetic C3 model of Farquhar et al. 7 and the Rubisco kinetic data for each species.

a, P. oceanica; b, Z. noltii; c, Z. marina; d, C. nodosa; e, S. pectinata; f, R. cirrhosa; g, C. demersum; h, V. gigantea; i, T. maritima; j, A. lanceolatum. In blue is respresented the Rubisco-limited rate of CO2 assimilation (Ac) and in green, the electron-transport limited rate of CO2 assimilation (Aj). The equivalent extracellular CO2 concentration (Ca) is shown in the upper x axis.The Cc and Ca where Aj = Ac are indicated by black and red arrows, respectively.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 and Tables 1–5.

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Supplementary Data 1

Source data for Table 2.

Supplementary Data 2

Source data for Supplementary Table 2.

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Source Data Extended Data Fig. 1

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Source Data Extended Data Fig. 3

Nucleotide sequences.

Source Data Extended Data Fig. 4

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Source Data Extended Data Fig. 5

Statistical source data.

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Capó-Bauçà, S., Iñiguez, C., Aguiló-Nicolau, P. et al. Correlative adaptation between Rubisco and CO2-concentrating mechanisms in seagrasses. Nat. Plants 8, 706–716 (2022). https://doi.org/10.1038/s41477-022-01171-5

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