AbstractThe propensity of Aureococcus anophagefferens to form harmful brown tide blooms has been linked to rapid light responses, but the underlying molecular mechanisms remain elusive. Here, we find that two glutamic residues in plastid luminal and C terminal domains in light harvesting complex (LHC) proteins are crucial to the alga’s unique photoadaptation capacity. Specifically, we demonstrate that glutamate residues contribute to the induction of non-photochemical quenching (NPQ). Protein structure analysis further indicates that these acidic residues can form stable hydrogen bonds under protonation, causing changes in the secondary structure of LHC. Our data suggest that this is the initial action of amino acids under light-induced lumen acidification, which then drives the function of NPQ through a complex process. This photoprotection mechanism, along with low light adaptation, enables this alga to thrive throughout water columns with spatially contrasting and temporally fluctuating irradiance, with implications of bloom formation.
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IntroductionThe ability to efficiently harvest light energy and protect against photodamage is crucial for the ecological success of phytoplankton. Aureococcus anophagefferens is widely distributed across the global oceans, causing large-scale brown tide blooms frequently observed in the coastal waters of the United States, South Africa, and China1,2,3,4. These outbreaks pose serious threats to shellfish farming, fishing, and tourism industries, adversely affecting local economies and ecosystems3. Brown tides typically erupt in relatively enclosed, shallow and turbid estuaries characterized by low light intensity, high organic matter concentrations, and abundant trace elements5.The competitive advantage of A. anophagefferens in low-light environments is critical for its ability to form brown tide blooms and derives from its unique cellular responses and gene regulation. This species achieves maximum growth rates under low light conditions6, enabled by its large repertoire of 62 light-harvesting protein genes, which are several times more abundant than in competing species, thereby enhancing light capture efficiency5,7. These adaptations demonstrate its exceptional light-harvesting abilities.Low-light-adaptive algae are typically more vulnerable to high-light stress8,9. A. anophagefferens, living in shallow waters, must cope with occasional oversaturated light intensities through diel cycles or vertical mixing. In algae, photoprotection is achieved by dissipating excess light energy, mostly through non-photochemical quenching (NPQ), a mechanism shared by both algae and vascular plants10. Energy-dependent fluorescence quenching (qE), triggered by the proton gradient (ΔpH) across thylakoid membranes, represents the fastest NPQ component11 and typically associates with the xanthophyll cycle12,13,14. In addition, qE is related to the protein function of photosystem II subunit S (PsbS) in vascular plants, which belongs to the light-harvesting complex (LHC) family15. Photosynthetic algae exhibit similar photoprotection mechanisms, such as the LhcSR protein in green algae and the Lhcx protein in diatoms16,17. However, the specific process by which the ΔpH ultimately triggers qE remains unclear. Diatoms utilize the xanthophyll cycle to respond to ΔpH but cannot directly trigger qE12,18,19. The decreased pH in the thylakoid lumen triggers qE through the protonation of proteins, a process sensed by acidic amino acids15,19.In vascular plants, the PsbS protein with four transmembrane helices senses the ΔpH through two glutamate residues symmetrically positioned on the two loops on the lumenal side20. Although the PsbS gene is also present in green algae, its function remains unknown21. The LhcSR or Lhcx proteins in algae contain acidic amino acid residues on the lumenal side, but unlike the PsbS protein, they both have a three-transmembrane helix structure, leaving their mechanism for sensing the proton gradient unclear. In C. reinhardtii, the D117, E221 and E224 of LhcSR3 are essential for NPQ induction19. However, the equivalent residues (D95 and E205) in Lhcx1 of the diatom Phaeodactylum tricornutum are not required for inducing NPQ22. Therefore, while acidic amino acids potentially play an important role, there is no consensus on their significance.Here, we isolate and culture A. anophagefferens from a brown tide bloom, investigating how its light-harvesting system provides competitive advantages that enable the alga to form blooms. Brown tide is one of the harmful algal blooms creating devastating impacts on the aquatic ecosystem, the coastal environment, and economy, as well as public health concerns. Focusing on the numerous LHC proteins of A. anophagefferens, we examine the roles of these proteins, particularly their association with brown tide outbreaks in estuaries, and the underlying molecular mechanisms. We discover the critical roles of two glutamic residues in the LHC proteins of A. anophagefferens. Data from multiple experiments verify their connection to thylakoid acidification. In this study, we provide insight into the proton gradient response sites and common patterns of algal LHC proteins, which suggest significant implications for understanding the effects of light on brown tide blooms.Results and discussionThe strong adaptability of A. anophagefferens to light changesSimilar to populations in the US and Africa,A. anophagefferens frequently blooms in shallow estuaries of China, particularly in the Bohai Sea. We conducted year-round sampling in Bohai Sea from 2013 to 2014 (Fig. 1a). Surface light intensity varied considerably across sampling sites, with approximately one-third receiving less than 200 μmol photons m−2 s−1 (Fig. 1b). Light attenuation increased with depth: about two-thirds of sites recorded below 200 μmol photons m−2 s−1 at one meter depth, while 91.43% of sites fell below 100 μmol photons m−2 s−1 at two meters. Field surveys revealed that A. anophagefferens maintained a uniform vertical distribution, whereas competing phytoplankton species exhibited varying distribution patterns. Dinoflagellates tended to prefer the surface with stronger light intensity. In contrast, the light intensity preferences of diatoms varied among species, resulting in non-uniform vertical distributions (Fig. 1c). These findings demonstrate A. anophagefferens’ exceptional adaptation to light variability. Its ability to adapt to low light helps them survive in the light-deficient coastal waters5, while its uniform abundance from the sea surface to depths suggests strong photoprotection. This strong photo-plasticity is exceptional. The only comparable case, best to our knowledge, is the cyanobacterium Prochlorococcus, which differentiates into different ecotypes: low-light-adapted strains that thrive in the deep euphotic zone and high-light-adapted strains that thrive at the surface23. They adjust the light capture efficiency through special pigments (Chl b and divinyl Chl a) and proteins (Pcb proteins), enabling them to survive widely in the ocean24. However, studies have found that this niche differentiation involves genetic divergence. In coral symbiotic dinoflagellates, those adapted to high-light environments can avoid photodamage through photoprotective mechanisms, while those adapted to low-light environments are more susceptible to photoinhibition25. Among vascular plants, Hedera helix is sensitive to changes in light intensity and can rapidly induce non-photochemical quenching (NPQ) shortly after a slight increase in light intensity26. From this perspective, A. anophagefferens and H. helix share similar low-light response characteristics. Both species are well adapted to thrive in low-light environments, are sensitive to minor fluctuations in light intensity, and possess strong photoprotective mechanisms.Fig. 1: Distribution patterns of irradiance and dominant algal species in the brown tide outbreak area of the Bohai Sea, China.a Map of sampling stations. b Vertical profile of photosynthetically active radiation (PAR) in the study area. 35 independent replicates were performed. c Vertical distribution of abundance for dominant species at each site throughout the year. The black bars and white bars represent 1 m above the bottom and 1 m below the surface, respectively. In the boxplot, the interquartile range (IQR) is represented by the box, and the median is indicated by the center line. The whiskers extend up to 1.5 × IQR from the upper and lower quartiles. Source data are provided as a Source Data file.Full size imageHigh LHC gene abundance in A. anophagefferens with unique glutamic acid residues and evidence of their role in photoprotectionThe strong photoadaptation of A. anophagefferens observed from the uniform vertical abundance distribution is consistent with the high number of LHC protein genes (AaLHC) in its genome5. To examine the role of AaLHC proteins in the photoprotection, we conducted a response analysis for the 62 AaLHC found in A. anophagefferens to different irradiance environments. Two expression patterns emerged (Fig. 2a). The 11 AaLHC in Group I showed increased expression levels when transferred from low light to high light, and from darkness to light of white and blue spectra. In contrast, the 51 AaLHC in Group II exhibited the opposite trend, with expression levels decreasing under high light stress and only increasing after a longer period of transfer from darkness to a lighted environment. Among them, the four genes AaLhc27, AaLhc37, AaLhc42, and AaLhc52 in Group I were more sensitive to short-term exposure. Additionally, weighted gene co-expression network analysis (WGCNA) identified the 11 AaLHC almost all in the same module (blue module, Supplementary Tables 1, 2), which were associated with short-term high light stress and short-term exposure to white and blue light, suggesting that these genes respond rapidly to changes in the light environment (Fig. 2b). We further analyzed these four significantly responsive genes using qPCR. Results showed that their expression was upregulated immediately after cells were exposed to high light, and dropped quickly when the cultures were returned to a low light environment (Fig. 2c). These genes were also upregulated when the algal cultures were transferred from darkness to low light or from white light to blue light (light stress in comparison, which has a shorter wavelength and higher energy). This result suggests that AaLhc27, AaLhc37, AaLhc42, and AaLhc52, and potentially others in Group I AaLHC as well, likely play the same role in light response.Fig. 2: Apparent relationship between LHC gene expression, glutamic acid residues in LHC, and NPQ in A. anophagefferens.a Two gene transcription response patterns of AaLHC genes after the transfer from low light to high light, from darkness to white light, and from darkness to blue light. b The gene expression matrix of AaLHC after exposure to high light and low light for 1, 3, and 6 h, as well as the transfer from darkness to blue light and white light for 1 h and longer periods. Same modules have similar gene expression patterns. c The expression response of AaLhc27, AaLhc37, AaLhc42, and AaLhc52 genes in Group I to light changes, including the transfer from a low-light adapted environment to high light, from darkness to low light, and from white light to blue light, and transitioning between two different light environments. Values are shown as the mean ± s.d. of three biological replicates. The red, pink, gray, blue, and white bars represent high light, low light, darkness, blue light, and white light, respectively. d Simulated structures of AaLHCs, showing short distance between the glutamic acid residues (red) and details of the lumenal side of AaLhc27. n = 1 simulation e NPQ changes during 10 min of exposure to actinic high light (white bar) followed by 10 min of recovery in darkness (black bar) for the control and NH4Cl-added cultures. Arrows indicate the timing of NH4Cl addition. Values are shown as the mean ± s.d. of three biological replicates. Source data are provided as a Source Data file.Full size imageWe further analyzed their amino acid sequences to identify the reasons behind the differences in photoprotective capabilities between the two groups of AaLHC. We noted that the AaLHC proteins in Group I all had two conserved glutamic acid (E) residues (henceforth termed AaLhc2E), while AaLHC proteins in Group II had none (in most cases) or one (Supplementary Fig. 1). Further structural simulations revealed that these two E residues were located on the lumenal loop and the C-terminal domain within the thylakoid membrane (Fig. 2d). Moreover, the two glutamic residues were located very closely to each other (<3.0 Å apart) in all the 11 AaLhc2Es. The proximity potentially facilitates structural adjustments of the protein when they are protonated, as documented for LhcSR in the chlorophyte C. reinhardtii19. Based on the key role of the proton gradient (ΔpH) across the thylakoid membrane in NPQ, we manipulated ΔpH in A. anophagefferens by adding NH4Cl to the algal culture to disrupt ΔpH, following a previously reported protocol12. The results showed that without NH4Cl treatment, NPQ could be induced by light and relaxed in the dark. NH4Cl addition rapidly led to a NPQ decrease (Fig. 2e). This result indicates that potentially, the cross-membrane proton gradient may be modulated or sensed involving the two E residues in the luminal loop, thereby regulating NPQ.As the xanthophyll cycle is coupled with and crucial for NPQ11, we investigated the potential concerted action of them. We detected all xanthophyll pigments in A. anophagefferens, including trace amounts of violaxanthin (Vx), antheraxanthin (Ax), and zeaxanthin (Zx), and observed diadinoxanthin (Dd) de-epoxidation to diatoxanthin (Dt) under high light irradiation (Supplementary Fig. 2a). Furthermore, treatment with NH4Cl inhibited the de-epoxidation state (DPS), indicating that the Dd-Dt cycle, rather than the Vx-Ax-Zx cycle, responds to pH changes. In addition, the conversion of fucoxanthin (Fx) to 19′-butanoyloxyfucoxanthin (19′-BFx)7 also appeared to occur under high light but was unaffected by ΔpH (Supplementary Fig. 2b), indicating that the role of Fx-to-19′-BFx conversion in photoprotection is independent of the ΔpH-modulated NPQ pathway.Similarity of AaLHC with glutamic acid residues to the photoprotective Lhcx/LhcSR in other algaeAs Lhcx/LhcSR is the best known photoprotective protein complex and shared by Archaeplastids, Stramenopiles, Alveolates and Rhizaria27, we compared AaLHCs with it and other light-harvesting proteins. Our phylogenetic analysis results showed that the 62 AaLHC proteins were divided into three categories, which clustered with Lhcf, Lhcr, and Lhcx/LhcSR, respectively (Fig. 3a). Among them, all the 11 AaLhc2E proteins clustered with Lhcx/LhcSR. This indicates that the two E residues are ancient and play a crucial functional role.Fig. 3: The phylogeny, evolution and sequence characteristics of LHCs in A. anophagefferens and other algae.a Phylogenetic tree of LHC-related proteins. Blue font depicts Lhcf, orange font Lhcr, and red font Lhcx/LhcSR. Glutamic residues are represented by red semicircles. Bootstrap values greater than 70% and 90% are indicated by black and gray circles, respectively. Abbreviation explanation: Aa, Aureococcus anophagefferens; Bn, Bigelowiella natans; Ce, Chlamydomonas eugametos; Cr, Chlamydomonas reinhardtii; Cc, Cyclotella cryptica; Ig, Isochrysis galbana; Km, Karlodinium micrum; Mv, Mesostigma viride; Msp, Micromonas sp.; Ol, Ostreococcus lucimarinus; Ot, Ostreococcus tauri; Pt, Phaeodactylum tricornutum; Pp, Physcomitrella patens; So, Scenedesmus obliquus; Tp, Thalassiosira pseudonana. b Protein sequence alignment of Lhcx/LhcSR from 15 Plantae species, with the positions of two glutamic residues highlighted in red and pink.Full size imageAlignment analysis of the 11 AaLhc2E proteins and the Lhcx/LhcSR proteins (Fig. 3a) revealed that transmembrane helices 1 and 3 were relatively conserved (Fig. 3b). The two conserved E residues of the three-transmembrane Lhcx/LhcSR were located at the ends of the helices extending into the lumen. Differently, the two E residues (E122 and E226) in the four-transmembrane PsbS of vascular plants are both located on the loop in the thylakoid lumen28. So far, it has been unclear whether algal LHC proteins all possess conserved acidic residues that respond to pH and are crucial to NPQ. In C. reinhardtii, residues D117, E221, and E224 in LhcSR3 are considered essential for inducing NPQ19. In the model diatom P. tricornutum, residues with potential protonation functions (D95 and E205 in Lhcx1) appear to be unnecessary for NPQ, while tryptophan residues located in the transmembrane helices may be essential22,29. Therefore, it is necessary to experimentally demonstrate that the two conserved glutamate residues in AaLhc2E are directly involved in inducing NPQ in A. anophagefferens. Such experimental evidence is presented in the next section.Crucial role of E residues in the function of AaLHC for NPQAs a functional genetic system is not yet available for A. anophagefferens, we chose a diatom model for the functional demonstration of AaLhc2Es. Based on the conservation of transmembrane helices 1 and 3 of the Lhcx/LhcSR among photosynthetic species, we compared the LHC protein sequences of A. anophagefferens and the model diatom Thalassiosira pseudonana. Results showed that the transmembrane regions of LHC proteins between these two species are also highly similar (Fig. 4a). We used T. pseudonana as the model to determine the function of a AaLhc2E for photoprotection. We overexpressed AaLhc27 in T. pseudonana (Tp_AaLhc27E). To verify the function of the E residues, we mutated E102 and E210 in AaLhc27E to Q102 and Q210, respectively, and included them in the heterologous expression experiment (Tp_AaLhc27Q) (Fig. 4b, Supplementary Fig. 3). We chose to replace the glutamic acid (E) residues with glutamine (Q) to minimize biochemical alterations except for the charge change. As a result, the AaLhc27E-expressing T. pseudonana strain (Tp_AaLhc27E) exhibited a greater NPQ under high light, while the AaLhc27Q-expressing strain (Tp_AaLhc27Q) displayed a smaller change in NPQ induction compared to the wild-type (Fig. 4c), indicating that the E residues play a crucial role in the function of AaLHC27 for NPQ. The capacity of NPQ is closely related to the expression of photoprotective LHCs and xanthophyll pigments bound to them30,31. Compared to the wild-type and Tp_AaLhc27Q, the DPS of Tp_AaLhc27E increased more rapidly upon light induction (Fig. 4d), indicating that the xanthophyll cycle is involved in the AaLHC27E-based NPQ regulation. Notably, the centric diatom T. pseudonana exhibits lower DPS values than the pennate diatom P. tricornutum32. Apart from the influence of growth conditions and light history33, this difference may result from the distinct topologies of NADPH-dehydrogenases (type-1 and type-2)32. The suppression of DPS elevation upon DCMU addition (Fig. 4d) suggests that T. pseudonana likely possesses a non-membrane-spanning type-2 NADPH dehydrogenase, which is probably not involved in generating the lumenal proton gradient that facilitates DDE-mediated de-epoxidation. Whether this enzyme releases protons on the stromal side and, together with abundant NADPH, promotes the epoxidation of Dt also warrants further investigation. Furthermore, our growth measurements indicated that the promoted high light adaptation by AaLHC27E enabled the AaLhc27E-expressing T. pseudonana to grow better under higher light conditions (200 and 800 µmol photons m−2 s−1) compared to the AaLhc27Q-expressing strain and the wild type strain (Fig. 4e). Given that T. pseudonana was transformed with only one AaLhc2E, whereas A. anophagefferens possesses eleven AaLhc2Es, this suggests that the multiple AaLhc2Es in A. anophagefferens may provide greater advantages in dissipating excess energy and growing well under intense and fluctuating light conditions.Fig. 4: Cross-species expression of AaLhc27 and analysis of NPQ-inducing function and growth rate based on the conservation of LHC protein transmembrane sequences.a Comparison of transmembrane sequences of LHC proteins from A. anophagefferens and T. pseudonana. b Schematic diagram of the expression of AaLhc2E gene, AaLhc27E, and its mutant AaLhc27Q in T. pseudonana. c NPQ induction differences in mutants and wild type. Values are shown as the mean ± s.d. of three biological replicates. d De-epoxidation state (DPS) of T. pseudonana and its two mutants, together with their responses after DCMU addition. Values are shown as the mean ± s.d. of three biological replicates. e Growth rates in T. pseudonana mutants and wild type under different light intensities. Values are shown as the mean ± s.d. of three biological replicates. Source data are provided as a Source Data file.Full size imageTo shed light on how proton gradient dynamics may alter AaLhc2E structures and modulate NPQ, we conducted fourier transform infrared (FTIR) spectroscopy analysis of AaLHC27 under varying pH conditions. D2O (D = deuterium) detergent buffer was used to avoid interference from O–H bending absorption, which overlaps with the Amide I region corresponding to the C = O vibrations in the protein backbone. Therefore, the FTIR results will be discussed in terms of pD instead of pH (pD = pH + 0.4). At pD 7.5, the FTIR spectrum of AaLHC27E exhibited a prominent band at 1570 cm−1, which originated from the stretching vibrations of the deprotonated carboxylic acid in the deprotonated E residues (Fig. 5a)34. Notable alteration in the FTIR spectrum was detected at pD 5.0, where a broad positive band in the region of 1700 to 1750 cm−1 was observed, indicative of the presence of deuterated carboxyls (COOD). The characteristic of protonated (deuterated) carboxyls suggests that nearly all E residues were protonated at pD 5.0. In addition, comparing the FTIR spectra at pD 5.0 and pD 7.5 revealed changes in the Amide I region from 1600 to 1700 cm−1, where a negative band at 1640 cm−1 and a broad positive band at 1690 cm−1 indicated a change in the Amide I band, and hence a conformational change in the secondary structure of the AaLHC27E. In contrast, only a minimal change was detected in the FTIR spectra of the AaLHC27Q mutant under different pD conditions. Clearly, mutating the two E residues to Q abolished proton response sensitivity while the general secondary structure of the protein was not altered.Fig. 5: FTIR spectroscopy and pH responses of AaLhc2E.a FTIR spectra of AaLHC27E and AaLHC27Q at pD 7.5 (blue), pD 5.0 (red), and the difference spectra of pD 5.0 minus 7.5 (black). b Structural presentation of stable interactions between lumenal E residues (yellow) and other residues (blue) in an acidic environment. The distance between amino acid residues was indicated by red dashed lines, and hydrogen bonds were represented by purple dashed lines. c Interaction between E residues and other amino acid residues in 11 AaLhc2E proteins at acidic pH. d Schematic diagram of the response of E residues under the influence of the proton gradient. The left and right figures represent the neutral and acidic environments, respectively. Source data are provided as a Source Data file.Full size imageAt acidic pH, the E102 and E210 of AaLHC27 were in close proximity to I217 and I116 (2.4 Å), respectively, which likely contributes to the formation of stable interactions (Fig. 5b). Similarly, the two E residues of AaLhc2E proteins could form stable hydrogen bonds with amino acid residues on the lumenal side, and these residues are located in the C-terminal domain and the lumenal loop, respectively (Fig. 5c). Therefore, in an acidic lumenal environment, the glutamic residues on helix1 and helix3 become protonated and can easily approach the amino acid residues of the other within a very short range to establish stable interactions, thereby leading to changes in the protein’s secondary structure (Fig. 5d). Through 1000 ns of constant pH molecular dynamics (CpHMD) simulations, the dynamic stability changed little from a neutral environment to an acidic environment (Supplementary Fig. 4, Supplementary Tables 3–6). To further observe the major motion states of the four systems (AaLHC27E_pH_4.5, AaLHC27E_pH_7, AaLHC27Q_pH_4.5, and AaLHC27Q_pH_7), the slowest motions were captured using time-lagged independent component analysis (tICA), and Markov state models (MSMs) were built to examine the differences in state transitions across the systems. The MSM models showed that each state transition varied in time and conformation across the four systems. Specifically, in the AaLHC27E system, both neutral and acidic conditions led to the formation of three metastable states, while the AaLHC27Q system formed four metastable states under both conditions. The most significant structural difference among the four systems was in the lumenal side (e.g., residues 118-130). Under both acidic and neutral conditions, the AaLHC27Q system exhibited a clear helix secondary structure. In contrast, the AaLHC27E system exhibited a partial loop structure along with the helix structure under both conditions (Supplementary Figs. 5, 6).Our results clearly indicate the crucial role of the two luminal E residues in AaLHC27 for NPQ in A. anophagefferens. Given the highly similarity in sequence and simulated structure, including the spatial proximity of the two glutamate residues, the other 10 AaLhc2E proteins likely serve the same function. However, experimental proof remains to be obtained in future research. Further research is also required to understand if the structurally conserved E residues in LHCs in other algae play the same role. It is worth noting that the total of 11 AaLhc2E proteins (and 62 total LHC proteins) in A. anophagefferens far exceeds that of many other algae but is comparable to some lineages living in highly light-variable environments. The intertidal brown alga Ectocarpus siliculosus and the polar ocean-adapted diatom Fragilariopsis cylindrus both contain 11 Lhcx-like/Lhcx proteins35,36. The intertidal environment undergoes extreme light changes daily. The polar environment experiences complete light to complete dark annually, but F. cylindrus flourishes and forms blooms there37. Emiliania huxleyi, which thrives and forms large-scale blooms in habitats ranging from the equator to the subarctic, possesses even more (17) LHCs with photoprotective functions38, although the apparent plasticity within species can potentially be attributed to genetic differentiation into distinct geographic populations. Our findings provide insights into a molecular mechanism by which LHCs mediate photoprotection in A. anophagefferens, with implications in other variable light-adapted lineages.Our results on AaLhc2Es also have significant ecological implications for the brown tide alga A. anophagefferens, which thrives and forms massive blooms in turbid coastal waters with dynamic light radiation, high organic matter and metals concentrations5. Harmful algal blooms occur when the causative alga outgrows co-existing species due to competitive advantages in photoenergy harvesting (E), nutrient acquisition (N), defense against environmental stress, grazing, and microbial attacks (D), and sometimes sexual reproduction (S)- known as ENDS drivers- with photoprotection being one significant D component39. While the high number of LHC genes in A. anophagefferens have been linked to the species’ ability to grow in a dim light environment5, we demonstrate here that at least some are crucial for protection against photodamages. Combined with the substantial genetic capacity for utilizing organic nutrients, trace metal, and vitamins5,40,41, the large LHC protein repertoire means A. anophagefferens is strongly equipped in “END” and poised to thrive in its coastal habitat and form brown tides.MethodsSampling design and algal cultivationA total of 20 phytoplankton sampling sites were established in the brown tide outbreak area (the northwestern part of the Bohai Sea, China) (Fig. 1a, Supplementary Table 7). Samples were collected monthly from June 2013 to May 2014. At each site, phytoplankton samples were collected from the surface layer (1 m) and the bottom layer (1 m above seafloor), and preserved in 1.5% Lugol’s solution. Phytoplankton species identification and counting were conducted under a microscope (Olympus CX31, Japan). Dominant species was classified based on the dominance index (Y ≥ 0.02). Light intensity was measured for 35 sampling sites at the water surface, 1 meter below the water surface, and at the bottom. Light intensities were measured with a PAR sensor (Onset HOBO MX2202, USA).A. anophagefferens used in this study was isolated from the coastal waters of Qinhuangdao in the Bohai Sea in July 2012 during a brown tide event. It was preserved in the algal collection of the Research Center of Harmful Algae and Marine Biology at Jinan University, China. Cultures were grown in artificial seawater supplemented with f/2 nutrients42 at 20 °C, under a light intensity of 50 μmol photons m−2 s−1 with a 12:12 light:dark cycle, and experiments were initiated during the logarithmic growth phase. T. pseudonana (CCMP 1335) was cultivated under the same conditions. Wild-type and two genotypes of T. pseudonana were maintained in semi-continuous cultures under 50, 200, and 800 μmol photons m−2 s−1. Cultures were diluted daily according to their respective growth rates. Steady state was reached at final dilution rates of 0.37, 0.60 and 0.50 d−1 under 50, 200 and 800 μmol photons m−2 s−1, respectively. To accurately calculate growth rate, one-mL samples were collected daily before and after dilution from each culture and fixed using Lugol’s solution. Cells were counted using a hemocytometer under an inverted microscope (BX53, Olympus, Tokyo, Japan). Growth rates (μ, in d−1) were calculated as: μ = (lnN2 – lnN1) / (t2 – t1), where N2 and N1 represent the cellular concentrations at t2 (before dilution on day 2) and t1 (after dilution on day 1), respectively.Experiment with different light conditions and fluorescence analysesDifferent light environments were used for the study of algal responses to light, including low light (LL, 50 μmol photons m−2 s−1), high light (HL, 800 μmol photons m−2 s−1), white light (WL, 100 μmol photons m−2 s−1), blue light (BL, 100 μmol photons m−2 s−1 at 450 nm), and darkness (D). The growth of T. pseudonana and its AaLhc-overexpressing strains were conducted under an irradiance of 50, 200, and 800 μmol photons m−2 s−1. The determination of NPQ capacity was conducted using a Phyto-PAM Phytoplankton Analyzer (Walz, Germany). After different algal strains were calibrated to the same chlorophyll a concentration, kinetic NPQ measurements were initiated. In the experiment on A. anophagefferens, NPQ was induced by 10 min of 764 μmol photons m−2 s−1, followed by a 10-min recovery phase in darkness to provide information on the relaxation kinetics. After 5 min high light exposure, 1 mM and 20 mM NH4Cl were added, respectively. In the experiment on T. pseudonana and its AaLhc-overexpressing mutants, NPQ was induced by 30-min exposure to a photon flux of 764 μmol photons m−2 s−1, followed by a 30-min recovery phase in the dark. The experiment was conducted with 3–5 parallel samples. NPQ was calculated as Fm/Fm’ −1.Pigment analysisA. anophagefferens in the exponential growth phase was collected for pigment detection at 0 h, 0.5 h, and 1 h under HL and LL irradiation. NH4Cl was added 25 min after HL exposure. Samples of T. pseudonana and its mutants in the exponential growth phase were taken at 0 h and 0.5 h under HL irradiation and after an additional 0.5 h in darkness. Under identical experimental conditions, 40 μM DCMU was added to inhibit linear electron transport. The samples obtained by filtration (25 mm GF/F membrane, 0.7 µm pore size) were immediately flash-frozen in liquid nitrogen and stored at −80 °C. Pure methanol was added for pigment extraction. Pigment analysis was performed using a 1200 Series HPLC system (Agilent Technologies, Santa Clara, CA, USA) equipped with an automatic sampler (Agilent 1100 series G1329A). The system was fitted with a reversed-phase Inertsil C8 column (150 × 4.6 mm, 5 μm particle size; GL Science) and eluted with mobile phase A (methanol: acetonitrile: 0.25 M pyridine solvent, 50: 25: 25, v: v: v) and mobile phase B (methanol: acetonitrile: acetone, 20: 60: 20, v: v: v)43. Elution was performed following the method described in ref. 44. with a flow rate of 0.9 mL min-1.RNA-seqIn the high-light induction experiment, algae cells cultured under LL were transferred to a HL environment for 1 h, 3 h, and 6 h. Additionally, cells that had been kept in darkness for 12 h were transferred to WL (1 h and long-term) and BL (1 h and long-term). Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, US). After the total RNA was qualified, RNA-seq libraries was sequenced in BGI-tech (Shenzhen, China) using an Illumina NovaSeq 6000 (San Diego, CA, USA) at Sangon Biotech (Shanghai, China). Sequencing quality was assessed using FastQC and MultiQC43,45. For the significance of gene expression difference, a cut off of: qValue < 0.05 and |log2FC | ≥ 1 was used. RNA-seq data were uploaded to the NCBI Sequence Read Archive (SRA) database (PRJNA680884 and PRJNA787041).WGCNAThe gene expression matrix, which contained HL and LL (1 h, 3 h, and 6 h), was employed to perform the gene co-expression network analysis using WGCNA46, followed by the identification of the modules that clustered with LHC-encoding genes. Similarly, the gene co-expression network analysis was also performed within BL (1 h and long-term), WL (1 h and long-term) and D (darkness).Real-time quantitative PCR (RT-qPCR)In the high-light induction experiment, the process involves transferring from LL to HL for 0.5 h, 1 h, 2 h, and 3 h, then exposing to LL again (0.5 h, 1 h, 2 h, 3 h), followed by HL exposure (0.5 h, 1 h, 2 h, 3 h). For low light experiments, the transfer is from D to LL for 1 h, 2 h, and 3 h, with the LL + D group receiving LL exposure for 1 h followed by D for 1 h and 2 h. In the blue light induction experiment, the transfer is from WL to BL for 1 h of exposure, followed by 1 h of WL exposure. For the validation of the exogenous genes AaLhc27E and AaLhc27Q in T. pseudonana, HL exposure was applied to the algae cells cultured under LL conditions for 0.5 h, 1 h, and 3 h. Algal cells were collected by centrifugation and performed RNA extraction. RNA was reverse transcribed using the HiScript II 1st Strand cDNA Synthesis Kit (Vazyme-Biotect, China). Reverse transcription PCR was performed using 50 ng cDNA with the AceQ qPCR SYBR Green Master Mix (Vazyme-Biotect, China). RT-qPCR was performed with the CFX Connect Real-Time PCR Detection System (Bio-Rad, CA, USA). The 18S rRNA and ACT4 were used as reference genes for experiments with A. anophagefferens and T. pseudonana, respectively. The gene-specific primers used for this study were listed in Supplementary Table 8. Experiments were repeated three times independently.Prediction of the LHC protein structureAlphaFold3 [https://alphafoldserver.com/] was used to predict the three-dimensional structures. The 50 AaLHC prediction models are selected based on predicted template modeling (pTM) score (range from 0.62 to 0.92) for the best ranking. A pTM score above 0.5 indicates that the predicted fold might be the true structure47. The structures were visualized using PyMOL [http://www.pymol.org].Phylogenetic analysisA total of 151 amino acid sequences of LHC proteins were obtained by the NCBI database (https://www.ncbi.nlm.nih.gov/) and JGI genome portal (https://genome.jgi.doe.gov/) from A. anophagefferens, Bigelowiella natans, Chlamydomonas eugametos, C. reinhardtii, Cyclotella cryptica, I. galbana, Karlodinium micrum, Mesostigma viride, Micromonas sp., Ostreococcus lucimarinus, Ostreococcus tauri, P. tricornutum, Physcomitrella patens, Scenedesmus obliquus and T. pseudonana (Supplementary Table 9)48. These sequences were aligned using MUSCLE (v5.1)49 and Clustal Omega (v1.2.4)50 with default parameters. The maximum likelihood (ML) phylogenetic tree was estimated using IQ-TREE (v1.6.5)51. The recommended best-fitting model LG + F + R5 was selected by using ModelFinder in IQ-TREE (v1.6.5). ML analysis was run with 1000 replicates via a bootstrap test. WebLogo was used to build sequence logos from LHCs52.Molecular dynamics (MDs) simulationsMDs simulations were performed using the Gromacs constant pH program53, with the CHARMM36m force field selected, and the TIP3P water model was employed. The pHbuilder tool was used to generate topology files for CphHMD, with pH values set to 4.5 and 7, respectively, to determine all titratable protein residues in the protein. A cubic box with a distance of 1.5 nm from the protein was established, and water molecules were added. The pHbuilder tool was used to add an appropriate number of positive/negative ions (sodium ions/chloride ions) and buffer to ensure the system is a net-neutral system, and to generate the corresponding structural and topology files for the system. Four systems were constructed, namely AaLHC27E_pH_4.5, AaLHC27E_pH_7, AaLHC27Q_pH_4.5, and AaLHC27Q_pH_7, respectively. Each protein was solvated in a cubic box (1.5 nm buffer) with water molecules, followed by ion addition (Na⁺/Cl⁻) and buffer components to ensure charge neutrality. Energy minimization utilized the steepest descent algorithm (5000 steps) with Verlet cutoffs, PME electrostatics (rcoulomb = 1.2 nm, fourierspacing = 0.14), and force-switch vdW treatment (rvdw = 1.2 nm). Bond constraints were applied via LINCS. Equilibration comprised NVT (100 ps, leap-frog integrator, V-rescale thermostat at 300 K, tau_t = 0.5 ps) and NPT phases (100 ps, C-rescale barostat at 1 bar, isotropic coupling, tau_p = 5.0 ps, refcoord_scaling = com). Production runs employed CpHMD with identical parameters to NPT, excluding refcoord_scaling. During the 1000 ns production simulations, conformational snapshots were recorded at 1 ns intervals for all systems. System stability was assessed using built-in modules for root-mean-square deviation (RMSD), residue fluctuations (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA). Markov state models (MSMs) and time-lagged independent component analysis (tICA) were computed via PyEMMA54. To encode secondary structural integrity, protein backbone root-mean-square deviation (RMSD) relative to the energy-minimized reference structure was employed as the primary feature for tICA dimensionality reduction. This RMSD-based metric explicitly captures global conformational variations while preserving secondary structure signatures.Construction of vectors for Lhc and overexpressionpTHa-K1 vector, containing the fcp8 promoter from T. pseudonana, was used for overexpression55. The encoding gene sequence of AaLhc27 was cloned into the pTHa-K1 vector to generate a pTHa-AaLhc27E plasmid. The Mut Express II Fast Mutagenesis Kit V2 (Vazyme-Biotect, China) was used for site-directed mutagenesis of E102 and E210 to Q102 and Q210, respectively, to generate another pTHa-AaLhc27Q plasmid. Plasmids were transformed into wild-type T. pseudonana cells by microprojectile bombardment using the Bio-Rad Biolistic PDS-1000/He Particle delivery system (Bio-Rad, CA, USA)56. With the 100 μg mL−1 nourseothricin resistance screening, colonies appeared after 14 days. The colonies were verified for successful transformation through PCR sequencing.Plasmid construction, expression, purification and refolding of AaLHC27E and AaLHC27QThe pET-28a-AaLHC27E and pET-28a-AaLHC27Q vectors containing a C-terminal His6-tag were transformed into Escherichia coli BL21 (DE3) cells, respectively. All transformants were incubated in LB medium with 100 mg/L kanamycin at 37 °C. To induce protein expression, isopropyl-beta-D-thiogalactopyranoside (IPTG) was added to a final concentration of 1 mM when the bacterial solution was cultured to OD 600 = 0.6. Cells were incubated at 37 °C for 5 h, collected by centrifugation at 4 °C and resuspended in lysis buffer (50 mM Tris-base, 500 mM NaCl, 8 M Urea, pH 7.4, Sangon-Biotect, China). After sonication and centrifugation (10,000 × g, 4 °C, 30 min), the supernatant was collected. His-tag Protein Purification Kit (Beyotime, China) was used to purify the unfolded AaLHC27E and AaLHC27Q. Then exchange buffer to 50 mM Hepes, 0.1% LDS, pH 5.0 (Dialysis Membranes, 14 kDa, Beyotime, China) for removing the high concentration of urea and adjusting the pH. Recombinant proteins of AaLHC27E and AaLHC27Q were refolded following the method described in refs. 57,58. SDS-page gel electrophoresis analysis (Sangon-Biotect, China) was carried out to check the yield of recombinant protein at each step (Supplementary Fig. 7).FTIR spectroscopySamples of AaLHC27E and AaLHC27Q were loaded in a Specac Omni Cell demountable cell with calcium fluoride (CaF2) windows with a 6 μm path length Mylar spacer. Infrared spectra were recorded using an FTIR spectrometer (IRTracer-100, Shimadzu, Japan) equipped with a Deuterated L-Alanine Triglycine Sulfate detector. Samples were solubilized in D2O detergent buffer. Measurements for the pD 5.0 and 7.5 samples were conducted sequentially, and differential FTIR spectra were generated by normalizing to the integrated absorbance of the amide I band (1550–1750 cm−1).Reporting summaryFurther information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Data availability
All relevant data supporting the conclusions of this study are included within the main text and/or the Supplementary Information. The raw sequencing data have been deposited in the NCBI BioProject database under accession numbers PRJNA680884 and PRJNA787041. The transcription response patterns in this study are available in Supplementary Dataset S1. The Gene expression modules based on WGCNA in this study are available in Supplementary Dataset S2. AlphaFold3 models and confidence metrics are provided in Supplementary Dataset S3. Source data are provided with this paper.
Referencesde Vargas, C. et al. Eukaryotic plankton diversity in the sunlit ocean. Science 348, 1261605 (2015).Article
PubMed
Google Scholar
Tang, Y. Z. et al. 3,000 km and 1,500-year presence of Aureococcus anophagefferens reveals indigenous origin of brown tides in China. Mol. Ecol. 28, 4065–4076 (2019).Article
PubMed
Google Scholar
Gobler, C. J., Lonsdale, D. J. & Boyer, G. L. A review of the causes, effects, and potential management of harmful brown tide blooms caused by Aureococcus anophagefferens (Hargraves et sieburth). Estuaries 28, 726–749 (2005).Article
Google Scholar
Zhang, Q.-C. et al. Emergence of brown tides caused by Aureococcus anophagefferens Hargraves et Sieburth in China. Harmful Algae 19, 117–124 (2012).Article
Google Scholar
Gobler, C. J. et al. Niche of harmful alga Aureococcus anophagefferens revealed through ecogenomics. Proc. Natl Acad. Sci. 108, 4352 (2011).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
MacIntyre, H. L. et al. Mediation of benthic–pelagic coupling by microphytobenthos: an energy- and material-based model for initiation of blooms of Aureococcus anophagefferens. Harmful Algae 3, 403–437 (2004).Article
CAS
Google Scholar
Alami, M., Lazar, D. & Green, B. R. The harmful alga Aureococcus anophagefferens utilizes 19’-butanoyloxyfucoxanthin as well as xanthophyll cycle carotenoids in acclimating to higher light intensities. Biochim Biophys. Acta 1817, 1557–1564 (2012).Article
CAS
PubMed
Google Scholar
Strzepek, R. F. & Harrison, P. J. Photosynthetic architecture differs in coastal and oceanic diatoms. Nature 431, 689–692 (2004).Article
ADS
CAS
PubMed
Google Scholar
Blommaert, L., Huysman, M. J. J., Vyverman, W., Lavaud, J. & Sabbe, K. Contrasting NPQ dynamics and xanthophyll cycling in a motile and a non-motile intertidal benthic diatom. Limnol. Oceanogr. 62, 1466–1479 (2017).Article
ADS
CAS
Google Scholar
Ruban, A. V. Nonphotochemical chlorophyll fluorescence quenching: Mechanism and effectiveness in protecting plants from photodamage. Plant Physiol. 170, 1903–1916 (2016).Article
CAS
PubMed
PubMed Central
Google Scholar
Goss, R. & Lepetit, B. Biodiversity of NPQ. J. Plant Physiol. 172, 13–32 (2015).Article
CAS
PubMed
Google Scholar
Goss, R., Ann Pinto, E., Wilhelm, C. & Richter, M. The importance of a highly active and ΔpH-regulated diatoxanthin epoxidase for the regulation of the PS II antenna function in diadinoxanthin cycle-containing algae. J. Plant Physiol. 163, 1008–1021 (2006).Article
CAS
PubMed
Google Scholar
Schaller, S. et al. The investigation of violaxanthin de-epoxidation in the primitive green alga Mantoniella squamata (Prasinophyceae) indicates mechanistic differences in xanthophyll conversion to higher plants. Phycologia 51, 359–370 (2012).Article
CAS
Google Scholar
Lavaud, J., Rousseau, B., van Gorkom, H. J. & Etienne, A.-L. Influence of the diadinoxanthin pool size on photoprotection in the marine planktonic diatom Phaeodactylum tricornutum. Plant Physiol. 129, 1398–1406 (2002).Article
CAS
PubMed
PubMed Central
Google Scholar
Li, X.-P. et al. A pigment-binding protein essential for regulation of photosynthetic light harvesting. Nature 403, 391–395 (2000).Article
ADS
CAS
PubMed
Google Scholar
Girolomoni, L. et al. LHCSR3 is a nonphotochemical quencher of both photosystems in Chlamydomonas reinhardtii. Proc. Natl Acad. Sci. 116, 4212–4217 (2019).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Buck, J. M. et al. Lhcx proteins provide photoprotection via thermal dissipation of absorbed light in the diatom Phaeodactylum tricornutum. Nat. Commun. 10, 4167 (2019).Article
ADS
PubMed
PubMed Central
Google Scholar
Grouneva, I., Jakob, T., Wilhelm, C. & Goss, R. In Photosynthesis. Energy from the Sun. (eds John F. Allen, Elisabeth Gantt, John H. Golbeck, & Barry Osmond) 1013–1016 (Springer Netherlands).Ballottari, M. et al. Identification of pH-sensing sites in the light-harvesting complex stress-related 3 protein essential for triggering non-photochemical quenching in Chlamydomonas reinhardtii. J. Biol. Chem. 291, 7334–7346 (2016).Article
CAS
PubMed
PubMed Central
Google Scholar
Li, X.-P., Phippard, A., Pasari, J. & Niyogi, K. K. Structure–function analysis of photosystem II subunit S (PsbS) in vivo. Funct. Plant Biol. 29, 1131–1139 (2002).Article
PubMed
Google Scholar
Tibiletti, T., Auroy, P., Peltier, G. & Caffarri, S. Chlamydomonas reinhardtii PsbS protein is functional and accumulates rapidly and transiently under high light. Plant Physiol. 171, 2717–2730 (2016).Article
CAS
PubMed
PubMed Central
Google Scholar
Buck, J. M., Kroth, P. G. & Lepetit, B. Identification of sequence motifs in Lhcx proteins that confer qE-based photoprotection in the diatom Phaeodactylum tricornutum. Plant J. 108, 1721–1734 (2021).Article
ADS
CAS
PubMed
Google Scholar
Moore, L. R. & Chisholm, S. W. Photophysiology of the marine cyanobacterium prochlorococcus: ecotypic differences among cultured isolates. Limnol. Oceanogr. 44, 628–638 (1999).Article
ADS
Google Scholar
Bibby, T. S., Mary, I., Nield, J., Partensky, F. & Barber, J. Low-light-adapted Prochlorococcus species possess specific antennae for each photosystem. Nature 424, 1051–1054 (2003).Article
ADS
CAS
PubMed
Google Scholar
Jones, R. J. & Hoegh-Guldberg, O. Diurnal changes in the photochemical efficiency of the symbiotic dinoflagellates (Dinophyceae) of corals: photoprotection, photoinactivation and the relationship to coral bleaching. Plant, Cell Environ. 24, 89–99 (2001).Article
CAS
Google Scholar
Ruban, A. V. Evolution under the sun: optimizing light harvesting in photosynthesis. J. Exp. Bot. 66, 7–23 (2015).Article
CAS
PubMed
Google Scholar
Giovagnetti, V. & Ruban, A. V. The evolution of the photoprotective antenna proteins in oxygenic photosynthetic eukaryotes. Biochem. Soc. Trans. 46, 1263–1277 (2018).Article
CAS
PubMed
Google Scholar
Li, X.-P. et al. Regulation of photosynthetic light harvesting involves intrathylakoid lumen pH sensing by the PsbS protein*. J. Biol. Chem. 279, 22866–22874 (2004).Article
CAS
PubMed
Google Scholar
Giovagnetti, V. et al. Biochemical and molecular properties of LHCX1, the essential regulator of dynamic photoprotection in diatoms. Plant Physiol. 188, 509–525 (2022).Article
CAS
PubMed
Google Scholar
Pi, X. et al. The pigment-protein network of a diatom photosystem II–light-harvesting antenna supercomplex. Science 365, eaax4406 (2019).Article
CAS
PubMed
Google Scholar
Feng, Y. et al. Structure of a diatom photosystem II supercomplex containing a member of Lhcx family and dimeric FCPII. Sci. Adv. 9, eadi8446 (2023).Article
CAS
PubMed
PubMed Central
Google Scholar
Lacour, T., Babin, M. & Lavaud, J. Diversity in xanthophyll cycle pigments content and related nonphotochemical quenching (NPQ) among microalgae: Implications for growth strategy and ecology. J. Phycol. 56, 245–263 (2020).Article
CAS
PubMed
Google Scholar
Grouneva, I., Jakob, T., Wilhelm, C. & Goss, R. The regulation of xanthophyll cycle activity and of non-photochemical fluorescence quenching by two alternative electron flows in the diatoms Phaeodactylum tricornutum and Cyclotella meneghiniana. Biochim. Biophys. Acta (BBA) – Bioenerg. 1787, 929–938 (2009).Article
CAS
Google Scholar
Barth, A. The infrared absorption of amino acid side chains. Prog. Biophys. Mol. Biol. 74, 141–173 (2000).Article
CAS
PubMed
Google Scholar
Cock, J. M. et al. The Ectocarpus genome and the independent evolution of multicellularity in brown algae. Nature 465, 617–621 (2010).Article
ADS
CAS
PubMed
Google Scholar
Mock, T. et al. Evolutionary genomics of the cold-adapted diatom Fragilariopsis cylindrus. Nature 541, 536–540 (2017).Article
ADS
CAS
PubMed
Google Scholar
Otte, A. et al. The diatom Fragilariopsis cylindrus: a model alga to understand cold-adapted life. J. Phycol. 59, 301–306 (2023).Article
CAS
PubMed
Google Scholar
Read, B. A. et al. Pan genome of the phytoplankton Emiliania underpins its global distribution. Nature 499, 209–213 (2013).Article
CAS
PubMed
Google Scholar
Lin, S. Harmful algal blooms: Environmental factors and molecular mechanisms. 306, (Academic Press, Cambridge, MA, 2025).Tang, Y. Z., Koch, F. & Gobler, C. J. Most harmful algal bloom species are vitamin B1 and B12 auxotrophs. Proc. Natl Acad. Sci. 107, 20756–20761 (2010).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Gobler, C. J. et al. The central role of selenium in the biochemistry and ecology of the harmful pelagophyte, Aureococcus anophagefferens. ISME J. 7, 1333–1343 (2013).Article
CAS
PubMed
PubMed Central
Google Scholar
Berges, J. A., Franklin, D. J. & Harrison, P. J. Evolution of an artificial seawater medium: improvements in enriched seawater, artificial water over the last two decades. J. Phycol. 37, 1138–1145 (2001).Article
Google Scholar
Andrews, S. FastQC a quality control tool for high-throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2014).Manuel, Z., Rodríguez, F. & Garrido, J. L. Separation of chlorophylls and carotenoids from marine phytoplankton: a new HPLC method using a reversed phase C8 column and pyridine-containing mobile phases. Mar. Ecol. Prog. Ser. 195, 29–45 (2000).Article
ADS
Google Scholar
Ewels, P., Magnusson, M., Lundin, S. & Käller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048 (2016).Article
CAS
PubMed
PubMed Central
Google Scholar
Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma. 9, 559 (2008).Article
Google Scholar
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Bailleul, B. et al. An atypical member of the light-harvesting complex stress-related protein family modulates diatom responses to light. Proc. Natl Acad. Sci. 107, 18214 (2010).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Edgar, R. C. Muscle5: high-accuracy alignment ensembles enable unbiased assessments of sequence homology and phylogeny. Nat. Commun. 13, 6968 (2022).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011).Article
PubMed
PubMed Central
Google Scholar
Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).Article
CAS
PubMed
Google Scholar
Crooks, G. E., Hon, G., Chandonia, J.-M. & Brenner, S. E. WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004).Article
CAS
PubMed
PubMed Central
Google Scholar
Jansen, A., Aho, N., Groenhof, G., Buslaev, P. & Hess, B. phbuilder: A tool for efficiently setting up constant pH molecular dynamics simulations in GROMACS. J. Chem. Inf. Model. 64, 567–574 (2024).Article
CAS
PubMed
PubMed Central
Google Scholar
Scherer, M. K. et al. PyEMMA 2: a software package for estimation, validation, and analysis of Markov models. J. Chem. Theory Comput. 11, 5525–5542 (2015).Article
CAS
PubMed
Google Scholar
Tanaka, R., Kikutani, S., Mahardika, A. & Matsuda, Y. Localization of enzymes relating to C4 organic acid metabolisms in the marine diatom, Thalassiosira pseudonana. Photosynthesis Res. 121, 251–263 (2014).Article
CAS
Google Scholar
Hopes, A. et al. Genome editing in diatoms using CRISPR-Cas to induce precise bi-allelic deletions. Bio-Protoc. 7, e2625 (2017).Article
PubMed
PubMed Central
Google Scholar
Krishnan-Schmieden, M., Konold, P. E., Kennis, J. T. M. & Pandit, A. The molecular pH-response mechanism of the plant light-stress sensor PsbS. Nat. Commun. 12, 2291 (2021).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Krishnan, M., Moolenaar, G. F., Gupta, K. B. S. S., Goosen, N. & Pandit, A. Large-scale in vitro production, refolding and dimerization of PsbS in different microenvironments. Sci. Rep. 7, 15200 (2017).Article
ADS
PubMed
PubMed Central
Google Scholar
Download referencesAcknowledgmentsDr. Tao Cheng from Qilu University of Technology is greatly acknowledged for assistance with the FTIR spectroscopy. This work was supported by the National Natural Science Foundation of China (No. 42176142 [L.C.], 41906111 [Y.D.] and 41806127 [L.C.]), the Guangdong Provincial Key R&D Program (No. 2023B1111050011 [SH.L.]), and the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (No. 311022009 [L.C.]), and the Basic and applied basic research project of Guangzhou (2023A04J1548 [Y.D.] and 2023A04J1549 [L.C.]).Author informationAuthor notesThese authors contributed equally: Lei Cui, Lei Xie.Authors and AffiliationsKey Laboratory of Eutrophication and Red Tide Prevention of Guangdong Higher Education Institute, College of Life Science and Technology, Jinan University, Guangzhou, ChinaLei Cui, Lei Xie, Lei Zhang, Baoling Yang, Juanchan Xu, Liying Tan, Bingqing Xiao, Yuelei Dong & Songhui LuCollege of Food Science and Engineering, Foshan University, Foshan, ChinaJianwei ZhengDepartment of Marine Sciences, University of Connecticut, Groton, CT, USASenjie LinGuangzhou Key Laboratory of Subtropical Biodiversity and Biomonitoring, College of Life Science, South China Normal University, Guangzhou, ChinaYuelei DongAuthorsLei CuiView author publicationsSearch author on:PubMed Google ScholarLei XieView author publicationsSearch author on:PubMed Google ScholarJianwei ZhengView author publicationsSearch author on:PubMed Google ScholarLei ZhangView author publicationsSearch author on:PubMed Google ScholarBaoling YangView author publicationsSearch author on:PubMed Google ScholarJuanchan XuView author publicationsSearch author on:PubMed Google ScholarLiying TanView author publicationsSearch author on:PubMed Google ScholarBingqing XiaoView author publicationsSearch author on:PubMed Google ScholarSenjie LinView author publicationsSearch author on:PubMed Google ScholarYuelei DongView author publicationsSearch author on:PubMed Google ScholarSonghui LuView author publicationsSearch author on:PubMed Google ScholarContributionsL.C., Y.D., and SH.L. designed research; L.C., L.X., Y.D., L.T., J.X., and B.X. performed research; L.C., Y.D., L.X., J.Z., L.Z., B.Y., and SJ.L. analyzed data; and L.C., Y.D., SJ.L., and SH.L. wrote the paper.Corresponding authorsCorrespondence to
Lei Cui, Senjie Lin, Yuelei Dong or Songhui Lu.Ethics declarations
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