Abstract
Aquatic life is strongly structured by the distribution of light, which, besides attenuation in intensity, exhibits a continuous change in the spectrum with depth1. The extent to which these light changes are perceived by phytoplankton through photoreceptors is still inadequately known. We addressed this issue by integrating functional studies of diatom phytochrome (DPH) photoreceptors in model species2 with environmental surveys of their distribution and activity. Here, by developing an in vivo dose–response assay to light spectral variations mediated by DPH, we show that DPH can trigger photoreversible responses across the entire light spectrum, resulting in a change in DPH photoequilibrium with depth. By generating dph mutants in the diatom Thalassiosira pseudonana, we also demonstrate that under simulated low-blue-light conditions of ocean depth, DPH regulates photosynthesis acclimation, thus linking optical depth detection with a functional response. The latitudinal distribution of DPH-containing diatoms from permanently stratified regions to seasonally mixed regions suggests an adaptive value of DPH functions in coping with vertical displacements in the water column. By establishing DPH as a detector of optical depth, this study provides a new view of how information embedded in the underwater light field can be exploited by diatoms to modulate their physiology throughout the photic zone.
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Data availability
Tara Oceans data are available at https://www.genoscope.cns.fr/tara/#MATOU-1.5. Diatom genome and transcriptome sources are detailed in Supplementary Table 1, sheet 1. The metaPR2 (ref. 14) dataset is downloadable from https://shiny.metapr2.org/metapr2/. Underwater light field data are available via PANGAEA49 at https://doi.org/10.1594/PANGAEA.847820. All information extracted from these databases and used in this study is provided in Supplementary Table 1. Source data are provided with this paper.
References
Kirk, J. T. O. Light and Photosynthesis in Aquatic Ecosystems (Cambridge Univ. Press, 2011).
Fortunato, A. E. et al. Diatom phytochromes reveal the existence of far-red-light-based sensing in the ocean. Plant Cell 28, 616–628 (2016).
Rockwell, N. C. & Lagarias, J. C. Phytochrome evolution in 3D: deletion, duplication, and diversification. New Phytol. 225, 2283–2300 (2020).
Rockwell, N. C., Su, Y.-S. & Lagarias, J. C. Phytochrome structure and signaling mechanisms. Annu. Rev. Plant Biol. 57, 837–858 (2006).
Rockwell, N. C. et al. Eukaryotic algal phytochromes span the visible spectrum. Proc. Natl Acad. Sci. USA 111, 3871–3876 (2014).
Duanmu, D. et al. Marine algae and land plants share conserved phytochrome signaling systems. Proc. Natl Acad. Sci. USA 111, 15827–15832 (2014).
Mobley, C. D. in Photobiology (ed. Björn, L. O.) 77–84 (Springer, 2015).
Carradec, Q. et al. A global oceans atlas of eukaryotic genes. Nat. Commun. https://doi.org/10.1038/s41467-017-02342-1 (2018).
Zayed, A. A. et al. Cryptic and abundant marine viruses at the evolutionary origins of Earth’s RNA virome. Science 376, 156–162 (2022).
Delmont, T. O. et al. Functional repertoire convergence of distantly related eukaryotic plankton lineages abundant in the sunlit ocean. Cell Genomics 2, 100123 (2022).
Coesel, S. N. et al. Diel transcriptional oscillations of light-sensitive regulatory elements in open-ocean eukaryotic plankton communities. Proc. Natl Acad. Sci. USA 118, e2011038118 (2021).
Jaubert, M. et al. in The Molecular Life of Diatoms (eds Falciatore, A. & Mock, T.) 607–639 (Springer, 2022).
Gao, S. et al. Cryptochrome PtCPF1 regulates high temperature acclimation of marine diatoms through coordination of iron and phosphorus uptake. ISME J. 18, wrad019 (2024).
Vaulot, D. et al. metaPR2: a database of eukaryotic 18S rRNA metabarcodes with an emphasis on protists. Mol. Ecol. Resour. 22, 3188–3201 (2022).
Mancinelli, A. L. in Photomorphogenesis in Plants (eds. Kendrick, R. E. & Kronenberg, G. H. M.) 211–269 (Springer, 1994).
Kusuma, P. & Bugbee, B. Improving the predictive value of phytochrome photoequilibrium: consideration of spectral distortion within a leaf. Front. Plant Sci. 12, 596943 (2021).
Giraud, E. et al. Bacteriophytochrome controls photosystem synthesis in anoxygenic bacteria. Nature 417, 202–205 (2002).
Morel, A. & Maritorena, S. Bio-optical properties of oceanic waters: a reappraisal. J. Geophys. Res. Oceans 106, 7163–7180 (2001).
Yu, Z. et al. Genome-wide analyses of light-regulated genes in Aspergillus nidulans reveal a complex interplay between different photoreceptors and novel photoreceptor functions. PLoS Genet. 17, e1009845 (2021).
Legris, M., Ince, Y. Ç. & Fankhauser, C. Molecular mechanisms underlying phytochrome-controlled morphogenesis in plants. Nat. Commun. 10, 5219 (2019).
Shinomura, T. et al. Action spectra for phytochrome A- and B-specific photoinduction of seed germination in Arabidopsis thaliana. Proc. Natl Acad. Sci. USA 93, 8129–8133 (1996).
Schäfer, E. A new approach to explain the “high irradiance responses” of photomorphogenesis on the basis of phytochrome. J. Math. Biol. 2, 41–56 (1975).
Chen, S., Lory, N., Stauber, J. & Hoecker, U. Photoreceptor specificity in the light-induced and COP1-mediated rapid degradation of the repressor of photomorphogenesis SPA2 in Arabidopsis. PLoS Genet. 11, e1005516 (2015).
Jia, X. et al. Arabidopsis phytochromes A and B synergistically repress SPA1 under blue light. J. Integr. Plant Biol. https://doi.org/10.1111/jipb.13412 (2022).
Lariguet, P. & Fankhauser, C. Hypocotyl growth orientation in blue light is determined by phytochrome A inhibition of gravitropism and phototropin promotion of phototropism. Plant J. 40, 826–834 (2004).
Yuan, J., Xu, T. & Hiltbrunner, A. Phytochrome higher order mutants reveal a complex set of light responses in the moss Physcomitrium patens. New Phytol. 239, 1035–1050 (2023).
Chun, L., Kawakami, A. & Christopher, D. A. Phytochrome A mediates blue light and UV-A-dependent chloroplast gene transcription in green leaves. Plant Physiol. 125, 1957–1966 (2001).
Goessling, J. W. et al. Structure-based optics of centric diatom frustules: modulation of the in vivo light field for efficient diatom photosynthesis. New Phytol. 219, 122–134 (2018).
Rausenberger, J. et al. Photoconversion and nuclear trafficking cycles determine phytochrome A’s response profile to far-red light. Cell 146, 813–825 (2011).
Klose, C. et al. Systematic analysis of how phytochrome B dimerization determines its specificity. Nat. Plants 1, 15090 (2015).
Li, H., Burgie, E. S., Gannam, Z. T. K., Li, H. & Vierstra, R. D. Plant phytochrome B is an asymmetric dimer with unique signalling potential. Nature 604, 127–133 (2022).
Petroutsos, D. et al. A blue-light photoreceptor mediates the feedback regulation of photosynthesis. Nature 537, 563–566 (2016).
Li, Z., Wakao, S., Fischer, B. B. & Niyogi, K. K. Sensing and responding to excess light. Annu. Rev. Plant Biol. 60, 239–260 (2009).
Lepetit, B. et al. High light acclimation in the secondary plastids containing diatom Phaeodactylum tricornutum is triggered by the redox state of the plastoquinone pool. Plant Physiol. 161, 853–865 (2013).
Behrenfeld, M. J. et al. Revaluating ocean warming impacts on global phytoplankton. Nat. Clim. Change 6, 323–330 (2016).
Schellenberger Costa, B. et al. Aureochrome 1a is involved in the photoacclimation of the diatom Phaeodactylum tricornutum. PLoS ONE 8, e74451 (2013).
Mann, M., Serif, M., Jakob, T., Kroth, P. G. & Wilhelm, C. PtAUREO1a and PtAUREO1b knockout mutants of the diatom Phaeodactylum tricornutum are blocked in photoacclimation to blue light. J. Plant Physiol. 217, 44–48 (2017).
Juhas, M. et al. A novel cryptochrome in the diatom Phaeodactylum tricornutum influences the regulation of light-harvesting protein levels. FEBS J. 281, 2299–2311 (2014).
Huysman, M. J. J. et al. AUREOCHROME1a-mediated induction of the diatom-specific cyclin dsCYC2 controls the onset of cell division in diatoms (Phaeodactylum tricornutum). Plant Cell 25, 215–228 (2013).
Coesel, S. et al. Diatom PtCPF1 is a new cryptochrome/photolyase family member with DNA repair and transcription regulation activity. EMBO Rep. 10, 655–661 (2009).
Mann, M. et al. The Aureochrome photoreceptor PtAUREO1a is a highly effective blue light switch in diatoms. iScience 23, 101730 (2020).
Mann, K. H. & Lazier, J. R. N. Dynamics of Marine Ecosystems: Biological-Physical Interactions in the Oceans (Blackwell, 2006).
Behrenfeld, M. J. Abandoning Sverdrup’s critical depth hypothesis on phytoplankton blooms. Ecology 91, 977–989 (2010).
Lacour, L. et al. Unexpected winter phytoplankton blooms in the North Atlantic subpolar gyre. Nat. Geosci. 10, 836–839 (2017).
Pesant, S. et al. Open science resources for the discovery and analysis of Tara Oceans data. Sci. Data 2, 150023 (2015).
Ardyna, M., Tara Oceans Consortium, Coordinators & Tara Oceans Expedition, Participants. Environmental context of all stations from the Tara Oceans Expedition (2009–2013), about the annual cycle of key parameters estimated daily from remote sensing products at a spatial resolution of 100km. PANGAEA https://doi.org/10.1594/PANGAEA.883614 (2017).
Holte, J., Talley, L. D., Gilson, J. & Roemmich, D. An Argo mixed layer climatology and database. Geophys. Res. Lett. 44, 5618–5626 (2017).
Ibarbalz, F. M. et al. Global trends in marine plankton diversity across kingdoms of life. Cell 179, 1084–1097 (2019).
Bracher, A. et al. Using empirical orthogonal functions derived from remote-sensing reflectance for the prediction of phytoplankton pigment concentrations. Ocean Sci. 11, 139–158 (2015).
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).
Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).
Zallot, R., Oberg, N. & Gerlt, J. A. The EFI web resource for genomic enzymology tools: leveraging protein, genome, and metagenome databases to discover novel enzymes and metabolic pathways. Biochemistry 58, 4169–4182 (2019).
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).
Wood, S. N. Generalized Additive Models: An Introduction with R (Chapman & Hall/CRC, 2017).
Mukougawa, K., Kanamoto, H., Kobayashi, T., Yokota, A. & Kohchi, T. Metabolic engineering to produce phytochromes with phytochromobilin, phycocyanobilin, or phycoerythrobilin chromophore in Escherichia coli. FEBS Lett. 580, 1333–1338 (2006).
Studier, F. W. Protein production by auto-induction in high-density shaking cultures. Protein Expr. Purif. 41, 207–234 (2005).
Giraud, E., Lavergne, J. & Verméglio, A. in Methods in Enzymology Vol. 471 (eds Simon, M. I. et al.) 135–159 (Elsevier, 2010).
Pollak, B. et al. Universal loop assembly: open, efficient and cross-kingdom DNA fabrication. Synth. Biol. 5, ysaa001 (2020).
Buck, J. M., Río Bártulos, C., Gruber, A. & Kroth, P. G. Blasticidin-S deaminase, a new selection marker for genetic transformation of the diatom Phaeodactylum tricornutum. PeerJ 6, e5884 (2018).
Siaut, M. et al. Molecular toolbox for studying diatom biology in Phaeodactylum tricornutum. Gene 406, 23–35 (2007).
Hopes, A., Nekrasov, V., Kamoun, S. & Mock, T. Editing of the urease gene by CRISPR-Cas in the diatom Thalassiosira pseudonana. Plant Methods 12, 49 (2016).
Haeussler, M. et al. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol. 17, 148 (2016).
Madronich, S. Photodissociation in the atmosphere: 1. Actinic flux and the effects of ground reflections and clouds. J. Geophys. Res. 92, 9740 (1987).
Babin, M. et al. Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe. J. Geophys. Res. 108, 3211 (2003).
Gorbunov, M. Y., Shirsin, E., Nikonova, E., Fadeev, V. V. & Falkowski, P. G. A multi-spectral fluorescence induction and relaxation (FIRe) technique for physiological and taxonomic analysis of phytoplankton communities. Mar. Ecol. Prog. Ser. 644, 1–13 (2020).
Serôdio, J. & Lavaud, J. A model for describing the light response of the nonphotochemical quenching of chlorophyll fluorescence. Photosynth. Res. 108, 61–76 (2011).
Acknowledgements
We thank R. Dorrell and F.-A. Wollman for critical reading of the manuscript; W. Kooistra and M. Montresor for discussions on the distribution of DPH-containing diatoms; and E. Pelletier for inputs for analysis of Tara Oceans data. This work was supported by funding from Fondation Bettencourt-Schueller (Coups d’élan pour la recherche francaise-2018), DYNAMO (ANR-11-LABX-0011-01), ANR-DFG grant DiaRhythm (KR1661/20-1) and ANR ClimaClock (20-CE20-0024) to A.F.; the Gordon and Betty Moore Foundation (GBMF4981.01) and the Centre National de la Recherche Scientifique (MITI interdisciplinary programme Lumiere et Vie and 80PRIME) to M.J.; the European Research Council PhotoPHYTOMIX project (grant agreement no. 715579) to B.B.; Fonds Français pour l’Environnement Mondial, French Government Investissements d’Avenir programmes OCEANOMICS (ANR-11-BTBR-0008), FRANCE GENOMIQUE (ANR-10-INBS-09-08), MEMO LIFE (ANR-10-LABX-54) and PSL Research University (ANR-11-IDEX-0001-02), the European Research Council under the European Union’s Horizon 2020 research and innovation programme (Diatomic; grant agreement no. 835067) and ANR ‘DIM’ (ANR-21-CE02-0021) to C.B.; ANR BrownCut (ANR-19-CE20-0020) and the European Union’s Horizon Europe Programme BlueRemediomics (grant agreement no. 101082304; views and opinions expressed are those of the author(s) alone and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them) to A.F. and C.B.; and a PhD grant from the French Ministry for Higher Education, Research and Innovation (MESRI) to C.D. This is Tara Oceans article number 154.
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A.F., M.J. and J.-P.B. conceptualized the study, with A.F. playing a key role in bridging the laboratory experiments with in situ observations and facilitating collaboration among the working groups, M.J. playing a key role in the coordination of molecular and functional investigations and supervision of C.D., and J.-P.B. playing a key role in the photoreceptor biophysics and modelling. A.F., M.J. and J.-P.B. designed the experimental strategy with C.D.; C.D. performed -omic investigations, with the support of J.J.P.K. and C.B. for the analysis and interpretation of the Tara Oceans data; C.D., J.-P.B. and M.J. performed cloning, purification and spectral analysis of the different DPH proteins with the assistance of J.S.; C.D. and M.J. generated the GFP reporter lines; C.D. performed the induction and reversion spectra with support from J.S.; M.J. generated resources (complementation of Ptdph reporter lines with TpDPH and the dph mutant lines of T. pseudonana) and designed the strategy for phenotypic characterization; C.D., M.J. and A.F. performed the gene expression analysis; C.D. performed the modelling analyses with J.-P.B. and the support of B.B. and M.R.d'A.; M.R.d'A. provided comments on the oceanographic context; B.B., E.V. and M.J. performed the photosynthetic measurements, guided by B.B., who also analysed the data; C.D. generated all of the figures and wrote the original draft, with A.F., M.J. and J.-P.B.; and C.B., B.B. and M.R.d'A. substantially contributed to the writing of the final version. All of the authors discussed the results and commented on the manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Pennate DPH distribution.
Map of the presence (filled symbols) and absence (empty symbols) of pennate DPH genes. Data sources include Tara Oceans sequence data (triangles) and sequenced genomes and transcriptomes from isolated pennate diatom strains at the corresponding sampling location (circles). Equator and Tropics of Cancer and Capricorn are shown.
Extended Data Fig. 2 Analysis of centric DPH distribution.
a, Map of the relative abundance of centric DPH genes and transcripts in Tara Oceans sampling stations at surface (SUR), Deep Chlorophyll Maximum (DCM), and mesopelagic layer (MES). b, Relative DPH abundance as a function of depth. c, Boxplot of the ratio of DPH relative abundance at surface compared to depth (DCM or MES). Boxplots represent minimum, lower quartile, median, upper quartile and maximum of the dataset. Datapoints at more than 1.5 time the interquartile range from the first or third quartile are plotted as outliers (dots). Median for metaG: 1.25 (n = 27 samples), median for metaT: 1.18 (n = 25 samples); the ratios are not significantly different from 1 based on a 2-sided wilcox test (metaG p-value = 0.2847, metaT p-value = 0.1123). d, Spearman’s correlation of AUREO and DPH relative abundance with different environmental parameters (measured in situ or computed from oceanographic models and satellite data45,46,47). The color gradient corresponds to the values of the Spearman ρ correlation coefficient and the dot size to their absolute value. Crosses indicate non-significant correlations in a two-tailed t-test for each correlation, not corrected for multiple comparison (NS: non significant, p-value > 0.05). e, Generalized additive models (GAM) of AUREO and DPH relative abundances with individual environmental parameters. Explained deviance is show as color gradient, while crosses indicate non significant p-value of the smooth term in the individual GAMs (see54), not corrected for multiple comparison. f, Complex GAMs explaining DPH relative abundance with a combination of environmental parameters. Stars indicate p-value of the smooth term in the complex GAM (***, p < 0.001; **, p < 0.01; *, p < 0.05; NS, non significant), and bar height represents the variance explained by each environmental parameters, estimated by removing individually each parameter from the complex GAM (MetaT: R-sq.(adj) = 0.435, deviance explained = 52.7%, n = 109; MetaG: R-sq.(adj) = 0.579, deviance explained = 70.6%, n = 87). All the analysis are done on the 0.8–2000 µm size fraction and removing stations with low centric diatom abundance.
Extended Data Fig. 3 Distribution of DPH containing diatoms in environmental genomic data.
a, Total abundance of diatoms of the Thalassiosirales or Cymatosirales orders in Tara Oceans in metagenomic and metatranscriptomic reads mapped onto the MATOUv1.5 gene atlas9, as a function of absolute latitude for different filter size fractions (in µm). Rpkm: reads per kilobase covered per million of mapped reads. b, Distribution of Thalassiosirales and Cymatosirales metagenome-assembled genomes (MAGs) from Tara Oceans SMAGs. Presence or absence of the MAG was retrieved from Delmont et al.10, with least 25% of the MAG length covered by metagenomic reads). c Distribution of DPH-containing diatoms in the metabarcoding 18S database MetaPR214 (which includes Tara Oceans metabarcoding data). ASVs (amplicon sequence variants) that are 100 % identical to ASVs from diatom cultures with confirmed DPH gene show a distinct latitudinal gradient, while ASVs with lesser identity but still at least 98% identical to a DPH-containing ASV are present in the tropical regions. d, Example of DPH-containing diatom distribution within a species using the metaPR2 database: the ASV 100% identical to DPH-containing Skeletonema menzelii CCMP793 is only detected in temperate regions, while other ASV annotated as Skeletonema menzelii can also be found in the Tropics.
Extended Data Fig. 4 Spectral properties of DPH from various species and environmental sequences are conserved.
a, Table showing information about the taxonomy and sampling locations of the diatom species from which DPH has been characterized. b, Normalized absorption spectra of 810-nm illuminated (red line) and 630-nm illuminated (darker red line) recombinant photosensory domains of DPH expressed with biliverdin as the conjugate chromophore. c, Normalized differential absorption spectra between 630-nm and 810-nm illuminated DPH. d, Table showing spectral and photochemical properties of the recombinant DPH. Max and min ΔA: maximum and minimum of the differential absorption spectra in the B, R, and FR bands. ND: not determined. η, ratio of quantum yield of the Pr to Pfr reaction to the Pfr to Pr reaction, were calculated with the method from15. Acor Arcocellulus cornucervis, Ccry Cyclotella cryptica, Mspi Minidiscus spinulatus, Sbio Shionodiscus bioculatus, Scos Skeletonema costatum, Tpse Thalassiosira pseudonana; Mini-like: synthetic environmental sequence close to M. spinulatus DPH, Acor-like synthetic environmental sequence close to A. cornucervis DPH.
Extended Data Fig. 5 Validation of the DPH-dependence of the action spectra.
a, Fluence rate-response curves induction of YFP in response to different lights in reporter lines with different genetic backgrounds: two lines in P. tricornutum wild-type (WT), two in Ptdph mutants (KO), and two in non-mutated cells originated from the same transformed colony than the KO (WT (Tc), Transformation control), treated as in Fig. 3b, upper panel. Cells were exposed for 10 min to an intensity gradient of monochromatic lights. YFP signal was measured after 6 h in the dark by flow cytometry and rescaled between minimum and maximum for each light treatment and each line (mean of the 3 minimum and the 3 maximum values). Curves represent the smooth trend (obtained with geom_smooth in R). WT panel are the same data as in Fig. 3b, upper panel, with a different scaling for visualization. b, Western blot analysis of PtDPH-HA protein in a P. tricornutum transgenic line expressing a HA-tagged version PtDPH (under the control of PtDPH promoter and terminator2), cultivated and illuminated as for the induction spectra experiments (i.e., acclimated to constant green (G) light (530 nm) for at least 10 days, and exposed to 10 µmol photons.m−2.s−1 of B (445 nm), R (660 nm), or NIR (765 nm) light for 10 min and then left for 6 h in darkness (BD, RD, NIRD, respectively), or directly put in darkness for 6 h. Experiments were repeated 3 times with the similar results. c, TpDPH restores B- and NIR-dependent YFP induction in Ptdph KO line. Ptdph reporter line (KO #1) was transformed with TpDPH gene under the control of PtDPH promoter and terminator, and subjected to a gradient of B (430 nm) or NIR (765 nm) lights, according to the same experimental setup used for the induction spectra (Fig. 3b). The YFP increase compared to value in the dark was normalized to the maximal YFP increase, i.e., after exposure to saturating NIR light. The different symbols represent data for 2 independent lines.
Extended Data Fig. 6 DPH-dependent gene expression regulation under NIR and B light.
Expression analysis of PtDPH-regulated (HSF4.6a (Phatr3_J49557), Phatr3_J15138, Phatr3_J18096, Phatr3_J45662, Phatr3_J46431) and -non regulated (Phatr3_J18180) genes. P. tricornutum WT, dph mutants (KO) and their corresponding non-mutated transformant (Tc) cells were collected in continuous G light growth condition and following a 30 min of irradiation with 445-nm LED at 30 μmol photon. m−2.s−1 (B), 800 nm LED at 200 μmol photon.m−2.s−1 (NIR), or kept in the dark for the same time (D). Gene expression quantifications were performed by RT-qPCR, with H4 used as normalization gene and relativized to the G light condition. Values are the mean ± sem on 3 independent biological replicates.
Extended Data Fig. 7 PtDPH integrates different light wavelength in the visible range.
a, PtDPH activity in response to mono and bichromatic illuminations. Plot shows relative YFP signal at saturating monochromatic lights (same data as in Fig. 3c) and different mixed wavelengths. The black curve indicates the η (ratio of quantum yield). Pie charts indicate the relative intensity of each LED color. The mixed illumination demonstrates that PtDPH can detect variation of the R/NIR ratio, but also the NIR/B, B/R and B/G ratios. Values are means ± sem from the four independent reporter WT lines, each measured in 4 independent experiments for the bichromatic illuminations and in 3 independent experiments for the monochromatic illuminations. b, Table showing the different estimations of η from in vivo data depending on the different scenari of DPH mode of action as described in Supplementary Method.
Extended Data Fig. 8 DPH modeled activity and stability in the water column.
a, Projection of PtDPH response (%PrPr) in in situ measured marine light field representative of bloom conditions (station PS75-299 in49) over the whole sampled water column. The effect of long wavebands on DPH activity was assessed by removing FR to NIR (700–800 nm) or FR to NIR and R (600–800 nm) wavebands. b, PtDPH photoconversion rate constant in in situ light field. Vertical lines indicate photoconversion rate constants required to reach DPH equilibrium in 10 min, 1 h or 12 h. c, Western blot analysis of PtDPH-HA protein in a P. tricornutum transgenic line (expressing a HA-tagged version of PtDPH under the control of PtDPH promoter and terminator2), acclimated in conditions mimicking “depth” or “surface” light conditions (constant 445-nm illumination, ~1.4 µmol photons.m−2.s−1; or white sunlight-like spectrum, ~130 µmol photons. m−2.s−1). Two replicas are shown for each condition. “Pt” corresponds to the P. tricornutum WT cells as negative control for HA detection. The anti-Hemagglutinin antibody (α-HA) and the α-βCF1 antibody as loading control, were used for protein detection. Experiment were repeated 3 times with the similar results.
Extended Data Fig. 9 DPH activity in modeled light fields (350 to 700 nm) mimicking different underwater scenarios of phytoplankton concentration (variations of chlorophyll a concentration (Chl a)).
a, Proportion of PrPr formed (%PrPr) for PtDPH based on measured in vivo data and contribution of the R band (removing the R band, i.e. 350 to 600 nm spectra, triangles). b, Photoconversion rate constant calculated for PtDPH. Vertical lines indicate the limit for DPH to reach equilibrium in 12 h, 1 h or 10 min. c to h, Projections of % PrPr formed using properties determined in vitro from the recombinant protein absorption spectra (Extended Data Fig. 4d) for: c, Phaeodactylum tricornutum (Ptri); d, Thalassiosira pseudonana (Tpse); e, Arcocellulus cornucervis-like (Acor-like) synthetic; f, Cyclotella cryptica (Ccry); g, Arcocellulus cornucervis (Acor); h, Minidiscus spinulatus (Mspi). Chlorophyll a concentration scale is the same for a and b, and c to h.
Extended Data Fig. 10 Analysis of photosystem II (PSII) parameters in WT and dph Thalassiosira pseudonana grown in light conditions mimicking “depth” (445 nm, at 1.4 μmol photon.m−2.s−1) or “surface” conditions (sun-like LED at 130 μmol photon.m−2.s−1) (spectra in Supplementary Fig. 3).
Fv/Fm, maximal PSII capacity in the dark; sigma, PSII antenna size; ETR max, maximal Electron Transfer Rate; Ek, Intensity for ETR half saturation; NPQ max, maximal Non-Photochemical Quenching capacity; E50NPQ, intensity for half saturation of NPQ. Stars represent p-value for t-tests between Tpdph and WT (ns, non-significant; *, p < 0.05, **; p < 0.01, ***, p < 0.001). Values are mean + or - sem for n = 12 independent measurements on each Tpdph and n = 24 on WT.
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Detailed description of DPH activity model construction based on equations described in ref. 15.
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DPH and AUREO data mining.
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Oligonucleotide list.
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Duchêne, C., Bouly, JP., Pierella Karlusich, J.J. et al. Diatom phytochromes integrate the underwater light spectrum to sense depth. Nature 637, 691–697 (2025). https://doi.org/10.1038/s41586-024-08301-3
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DOI: https://doi.org/10.1038/s41586-024-08301-3
