Strigolactones optimise plant water usage by modulating vessel formation

Zhao, Jiao; Shi, Dongbo; Kaeufer, Kiara; Song, Changzheng; Both, Dominik; Thier, Anna Lea; Cao, Hui; Lassen, Linus; Xu, Xiaocai; Hamamura, Yuki; Luzzietti, Laura; Bennett, Tom; Kaufmann, Kerstin; Greb, Thomas

doi:10.1038/s41467-025-59072-y

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Published: 28 April 2025

Strigolactones optimise plant water usage by modulating vessel formation

Nature Communications volume 16, Article number: 3854 (2025) Cite this article

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Abstract

Wood formation is crucial for plant growth, enabling water and nutrient transport through vessel elements, derived from cambium stem cells (CSCs). CSCs produce vascular cell types in a bidirectional manner, but their regulation and cell fate trajectories remain unclear. Here, using single-cell transcriptome analysis in Arabidopsis thaliana, we reveal that the strigolactone (SL) signalling pathway negatively regulates vessel element formation, impacting plant water usage. While SL signalling is generally active in differentiating vascular tissues, it is low in developing vessels and CSCs, where it modulates cell fate decisions and drought response. SL-dependent changes in vessel element formation directly affect transpiration rates via stomata, underscoring the importance of vascular tissue composition in water balance. Our findings demonstrate the role of structural alignment in water-transport tissues under unstable water conditions, offering insights for enhancing drought resistance in plants through long-term modulation of vascular development.

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Introduction

Continuous growth and tissue formation are characteristic of plant development and important for aligning distinct body structures with changing environmental conditions. Cambium-driven radial growth of shoots and roots of dicotyledonous species is an important feature of this growth mode, and key for biomass production and for the long-term sequestration of CO₂¹. CSCs proliferate, usually providing wood (i.e. xylem) cells inwards and bast (i.e. phloem) cells outwards. Within xylem and phloem tissues, various cell types fulfil highly specialised functions like water transport by xylem vessel elements or sugar transport by phloem sieve elements². However, mechanisms regulating CSC-associated cell fate decisions to cope with stressful environmental conditions are largely unknown.

Driven by transpiration at leaves and the resulting negative pressure in vessel elements, xylem-associated water transport is crucial for delivering water and dissolved minerals from the roots to the leaves, where photosynthesis occurs. Thus, disruptions in water transport, such as drought or embolism, can severely impair plant performance, reducing photosynthetic efficiency and metabolic rates, ultimately boosting drought-induced mortality³. The efficiency of water transport is a central parameter to ensure constant water supply under fluctuating water availability and, to a large extent, depends on the morphology and size of vessel elements. In fact, functions describing transpiration-based water loss indicate that the xylem is limiting for water transport when water is readily available⁴. Therefore, pathways actively modulating vessel element formation in response to alternating water availability are expected but have not been identified in the context of cambium-driven xylem formation.

Here, we provide cell-resolved transcriptomes of CSCs and all CSC-derived cell types generated by single-nucleus RNA-sequencing (snRNA-seq). Based on our droplet- and plate-based high-resolution transcriptome analysis, we identify SL signalling as a modulator of vessel formation and, thereby, as a module mediating structural adaptations to fluctuating water availability and drought stress.

Results

snRNA-seq analysis of radial growth

To comprehensively reveal cell states during radial plant growth, we established an snRNA-seq-based atlas of the Arabidopsis hypocotyl, the organ connecting shoot and root systems and being a hotspot for cambium-based organ growth⁵. To this end, nuclei were extracted, filtered, and purified via a cell sorter and processed by droplet-based single nucleus transcriptome analysis⁶ (Fig. 1a, Supplementary Fig. 1a). Demonstrating the success of our approach, at least 400 transcribed genes were detected in 4722 out of 6780 processed nuclei. From those, we kept 2061 high-quality nuclei in which at least 1200 unique molecular identifier (UMI) counts were identified for further analysis. Within these high-quality nuclei, we detected 26,613 genes as being transcribed, covering nearly 70% of the annotated genes for Arabidopsis⁷. On the median level, our analysis detected 1224 transcribed genes and 1854 UMIs for each nucleus (Supplementary Data 1).

**Fig. 1: Identification of Arabidopsis hypocotyl cell types using 10x Chromium snRNA-seq.**

By unsupervised clustering of the high-quality nuclei, we obtained 18 clusters, as visualised in a ‘uniform manifold approximation and projection’ (UMAP, Fig. 1b, Supplementary Data 2). Based on publicly available cell type-specific marker genes^8,9, we annotated cluster identities representing all major cell types reported for the hypocotyl (Fig. 1c, d, Supplementary Data 3). These cell types included the cambium (see below) and the periderm, which is a secondary protective tissue characterised by MYB84, GLYCEROL-3-PHOSPHATE SN-2-ACYLTRANSFERASE5 (GPAT5), and WUSCHEL RELATED HOMEOBOX4 (WOX4) expression¹⁰. As an exception, phloem sieve elements were not detected, presumably due to the absence of nuclei in those cells. Annotations were verified by promoter reporter analyses of selected genes marking vascular clusters (Supplementary Fig. 2). Importantly, we identified a CSC-associated cluster containing 139 nuclei specifically expressing 151 genes including the known CSC markers WOX4^11,12,13, PHLOEM INTERCALATED WITH XYLEM (PXY)^11,14,15, SUPPRESSOR OF MAX2 1-LIKE5 (SMXL5)^11,16, AINTEGUMENTA (ANT)^17,18, and ARABIDOPSIS THALIANA HOMEOBOX8 (ATHB8)¹⁹ (p-value adjusted based on Bonferroni correction (p_adj) <0.01, Fig. 1d, Supplementary Data 2)²⁰. Pseudotime analyses reconstructing developmental trajectories of vascular clusters revealed that vascular-related trajectories were linked to the CSC cluster (Fig. 1b). This was in remarkable contrast to previous analyses of procambium cells, the precursors of cambium cells during apical growth, which usually localise at the end of developmental trajectories⁹. Our trajectory analyses moreover allowed a more detailed clusterization along the differentiation path, resulting in several clusters specifically representing small sections of the path (Supplementary Fig. 3, Supplementary Data 2). Collectively, our results revealed that CSCs hold a specific transcriptome and reflected the central role of CSCs as the developmental origin of cells driving radial plant growth.

To increase the analytic depth of our CSC characterisation, we next applied the plate-based ‘vast transcriptome analysis of single cells by dA-tailing’ (VASA-seq) method²¹ capturing both polyadenylated RNA and non-polyadenylated RNA, and used fluorescence intensity of the cambium domain reporters PXY_pro:H4-GFP and SMXL5_pro:H2B-RFP¹¹ during fluorescence-activated sorting to isolate 1134 cambium nuclei (Supplementary Fig. 1b, c). In addition, we isolated the same number of nuclei from the whole hypocotyl without PXY_pro:H4-GFP/SMXL5_pro:H2B-RFP-based sorting. In total, we processed 2,268 nuclei, resulting in 1559 high-quality nuclei showing at least 1,200 unique fragment identifier (UFI) counts/nucleus (Supplementary Fig. 4a, Supplementary Data 1). Overall, we detected transcripts of 33,195 genes, including the two reporter transgenes, covering more than 85% of the annotated genes in Arabidopsis. On the median level, our VASA-seq approach detected 2688 genes/nucleus and 5210 UFI/nucleus, which matched previous high-quality datasets for Arabidopsis nuclei²².

Unsupervised clustering of the VASA-seq processed nuclei resulted in 19 clusters, which we associated with distinct cell states using marker genes identified previously and during our droplet-based approach (Supplementary Fig. 4b, c). Again, most hypocotyl cell types were represented by a cluster in the VASA-seq dataset with a lower relative size of ‘periderm’ or ‘developing vessel’ clusters than obtained by our droplet-based approach, presumably due to the depletion of those nuclei during the cambium-centred nucleus selection (Supplementary Data 2). Moreover, CSC marker genes were expressed this time in two clusters representing CSCs (‘VASA_CSC’ cluster, 94 nuclei) and dividing CSCs (‘VASA_dividing’ cluster, 66 nuclei) (Supplementary Fig. 4c) based on transcript abundance of genes previously associated with dividing root cells⁹. Supporting the conclusion that these were CSC nuclei, both clusters showed high GFP (PXY_pro:H4-GFP) and RFP (SMXL5_pro:H2B-RFP) fluorescence intensities¹¹ (Supplementary Fig. 5a). We furthermore identified 226 and 405 marker genes for each CSC cluster, respectively (p_adj <0.01, Supplementary Data 2) demonstrating that the VASA-seq analysis substantially increased analytical depth. Moreover, 119 of 151 (72%) CSC marker genes identified by our droplet-based approach were included in the groups of CSC and/or dividing CSC marker genes (Supplementary Fig. 5b) and could be confirmed by expression analyses in plants (Supplementary Fig. 6), suggesting that results from both approaches were robust.

SL signalling activity within radial growth

Demonstrating their relevance, our cell-resolved transcriptome data recapitulated xylem-associated auxin signalling and phloem-associated cytokinin signalling²³ when we monitored transcript abundance of respective hormone-responsive genes²⁴ within identified clusters (Supplementary Fig. 7, Supplementary Data 3). Interestingly, when we mapped the activity of 94 genes induced by the synthetic SL analogue GR24^4DO²⁵, we found that the expression of these genes was particularly low in the cluster representing dividing CSCs and in a subset of the xylem cell clusters, presumably representing differentiating vessel elements (‘VASA_XPa’, Fig. 2a, b). Indeed, when analysing SL signalling levels by the genetically encoded SL signalling sensor Strigo-D2²⁶, we found that SL-signalling activity was lower in CSCs and in developing vessel elements compared to phloem and xylem parenchyma cells (Fig. 2c–e). To find further support for this conclusions and to map the activity of SL-dependent genes in radially growing organs, we expressed an SL-resistant version of the proteolytic target of the SL-signalling pathway SMXL7 (SMXL7^d53)²⁷ fused to the dexamethasone (DEX)-inducible GLUCOCORTICOID RECEPTOR (GR) under the control of the endogenous SMXL7 promoter (SMXL7_pro:SMXL7^d53-GR). When performing transcriptional profiling of hypocotyls five hours after DEX application, we identified 1,022 DEX-induced and 409 DEX-suppressed genes (Supplementary Data 4) significantly overlapping with previously-reported GR24^4DO-suppressed and GR24^4DO-induced genes²⁵, respectively (Fig. 2f). This suggested that our analysis successfully identified genes downstream of SL signalling in the Arabidopsis hypocotyl. In line with results obtained using the Strigo-D2 sensor, in both VASA and 10x snRNA-seq datasets, DEX-suppressed genes showed significantly lower expression in clusters representing developing vessels and cambium stem cells when compared to xylem parenchyma and phloem clusters (Fig. 2g, h, Supplementary Fig. 8). Taken together, these results indicated that SL signalling levels are relatively low in developing vessels and in CSCs.

**Fig. 2: Strigolactone (SL) signalling in the radially expanding hypocotyl.**

SLs are a class of carotenoid-derived phytohormones, modulating various processes including shoot branching and drought resistance^28,29. SL molecules are perceived by the α/β hydrolase DWARF14 (D14), inducing interaction with the F-box protein MORE AXILLARY GROWTH2 (MAX2) and thereby promoting degradation of the transcriptional regulators SMXL6, SMXL7, and SMXL8^25,30,31. Using fluorescent promoter reporters, we found that the genes encoding these signalling components were widely active in the hypocotyl with a particular focus on the xylem (Supplementary Fig. 9): The activity of the MAX2 reporter was detected in developing xylem vessels, xylem parenchyma cells, cambium cells and phloem parenchyma cells, whereas D14 reporter activity was only detected in xylem parenchyma cells and phloem parenchyma cells. SMXL6, SMXL7, and SMXL8 reporter activities were all detected in xylem parenchyma cells, with SMXL7 also being detected in developing vessels (Supplementary Fig. 9). The transcripts of several SL biosynthetic genes were also widely detected both in xylem parenchyma cells and developing vessels (Supplementary Fig. 10). Our analyses thus associated SL signalling components with differentiating and differentiated vascular tissues and were in line with a regulatory role of the pathway in their formation.

SL-signalling suppresses vessel formation

To reveal a possible function of the SL-signalling pathway in vascular tissue formation, we next compared hypocotyls from d14 mutants and wild type by again applying droplet-based snRNA-seq. After clustering and cluster annotation based on our initially identified genes marking the different hypocotyl cell types (Supplementary Fig. 11, Supplementary Data 1), we found that cell composition and transcriptional states were highly similar between the two genotypes (Fig. 3a). Interestingly, as the most prominent difference, we detected a three-fold increase in the abundance of nuclei from developing vessel elements (WTd14_devV) in d14 mutants (Fig. 3b, Supplementary Fig. 11). Those were identified based on the expression of the VASCULAR-RELATED NAC-DOMAIN6 (VND6), VND7^32,33 and IRREGULAR XYLEM3 (IRX3)³⁴ and other xylem marker genes (Fig. 3c, Supplementary Fig. 11d–i). In line with an increased number of vessel elements, transcripts of VND6, VND7 and IRX3 were more abundant in d14 mutants (Fig. 3d). Indeed, histological analyses revealed a higher density and increased size of vessel elements in both the SL signalling mutants d14 and max2 (Fig. 3e–i) and the SL biosynthesis mutant max1 (Supplementary Fig. 12a–c). This alteration was not observed in BRANCHED1 (BRC1)-defective plants (Supplementary Fig. 12d–f), which, similar to d14, max1, and max2 mutants, show increased branching³⁵, arguing against the possibility that increased shoot formation causes enhanced vessel formation as a secondary effect. Moreover, KAI2-deficient plants impaired in KARRIKIN signalling, which, like SL signalling, involves the F-box protein MAX2³⁶, did not show enhanced vessel formation (Supplementary Fig. 12g–i), demonstrating that altered vessel formation specifically depends on altered SL signalling.

**Fig. 3: Effect of SL signalling on vessel development.**

In contrast to the SL signalling and biosynthesis mutants, the number and size of vessel elements was decreased in smxl6;smxl7;smxl8 (smxl6;7;8), d14;smxl6;7;8 (Fig. 3e–i) and max2;smxl6;7;8 mutants (Supplementary Fig. 12j, k) demonstrating that increased vessel formation in SL-related mutants depends on the proteolytic targets of the SL signalling pathway. To this effect, mostly SMXL7 and SMXL8 contributed in a redundant fashion, as no other max2;smxl double or triple mutant combination than max2;smxl7;8 showed a mild reduction in vessel density in comparison to max2 (Supplementary Fig. 12j, k). Further supporting a positive role of the proteolytic targets of SL-signalling in vessel formation, expressing SMXL7^d53, the SL-resistant version of SMXL7²⁷, under the control of the SMXL7 promoter (SMXL7_pro:SMXL7^d53-mVenus) was sufficient to promote cambium-associated vessel formation (Fig. 4a, b, e, f). Moreover, SMXL7^d53-GR-inducible genes were significantly upregulated and SMXL7^d53-GR-repressible genes were significantly downregulated in d14 mutants in several vascular-related clusters (Fig. 3j), indicating that SL signalling indeed regulates gene expression in vascular cells. In accordance with previous reports that SL signalling negatively regulates the expression of auxin-dependent genes²⁵, we also found that auxin-inducible genes were significantly enriched in the group of SMXL7^d53-GR-inducible genes together with abscisic acid (ABA) and methyl jasmonate (MJ)-inducible genes (Fig. 3k, Supplementary Data 3). This result suggested a systematic negative effect of SL signalling on auxin, ABA and jasmonate signalling. With three SMXL7^d53-GR-inducible and 13 SMXL7^d53-GR-repressible genes specifically expressed in xylem parenchyma (VASA_XPb cluster), including the auxin transporter genes PIN-FORMED 3 and LIKE AUXIN RESISTANT 2 (Supplementary Data 2, Supplementary Data 4), we also identified candidates regulating the ratio of vessels and xylem parenchyma downstream of SL signalling. Along these lines, when reducing the activity of the HD ZIP-III transcription factor family, an established group of auxin-dependent xylem regulators, by inducing miRNA165a expression targeting all five HD ZIP-III mRNAs^17,37, the difference in vessel formation observed between wild type and the SMXL7_pro:SMXL7^d53-mVenus line, disappeared (Fig. 4 g–j). This argued for an essential role of the HD ZIP-III transcription factors downstream of the SL signalling pathway and for an influence of SL signalling on canonical regulators of xylem development.

**Fig. 4: Analysis of *SMXL7*_pro:SMXL7^d53-mVenus, *WOX4*_pro:D14/d14, *WOX4*_pro:D14/max2, and *WOX4*_pro:D14/max1 plants.**

Furthermore, indicating a vascular-associated role of SL signalling, d14 mutants did not show an increased vessel phenotype when they carried a transgene expressing D14 under the control of the cambium- and early xylem-specific WOX4 promoter (WOX4_pro:D14) (Fig. 4a, c–f). The same transgene had no effect in max2 or max1 mutants, demonstrating that the effect of D14 depended on endogenous SL signalling and biosynthesis (Fig. 4k–q). Together with the observation that application of GR24^4DO specifically decreased vessel formation in wild type and max1 but not in d14 (Supplementary Fig. 13), we concluded that SL-signalling negatively regulates vessel formation during radial plant growth in cambium-derived cells and in an SMXL6;7;8-dependent fashion.

Vessel development influences transpiration

Relative water content is reduced in d14 and max2 mutants^38,39,40 and increased in smxl6,7,8 triple mutants when grown in water-deprived pots⁴¹, suggesting that SL signalling optimises water usage. Confirming this role, water usage was increased in d14 and max2 mutants and reduced in smxl6;7;8 mutants (Supplementary Fig. 14a). ABA-induced closure of stomata, the main transpiration site in plants, is slower in SL signalling deficient mutants and proposed as one cause for their reduced drought resistance^38,39,40. Indeed, stomatal conductance was elevated in d14 and max2 mutants and lower in smxl6;7;8 mutants compared to wild-type plants under both well-watered and water-deficiency conditions (Supplementary Fig. 14b), demonstrating that transpiration is reduced by SL signalling. In contrast, brc1 mutants showed a stomatal conductance like wild type again demonstrating that enhanced branching does not cause higher transpiration (Supplementary Fig. 14c). Moreover, we found a similar reduction of stomatal conductance in d14;smxl6;7;8 and max2;smxl6;7;8 mutants compared to smxl6;7;8 mutants (Supplementary Fig. 14c) indicating that D14 and MAX2 require their downstream targets SMXL6, SMXL7 and SMXL8 for affecting transpiration. Interestingly, we found that d14 mutants carrying a WOX4_pro:D14 transgene showed normal transpiration rates and no altered stomata density (Supplementary Fig. 15a, b), indicating that this effect depended on SL signalling in vascular tissues. In accordance with previous reports^39,40, stomata density was not changed in d14 and max2 mutants and only slightly enhanced in smxl6;7;8 mutants (Supplementary Fig. 15b–e). Moreover, cuticle thickness was comparable between wild type and d14 (Supplementary Fig. 15f), arguing against altered stomata density or cuticle defects as reasons for altered transpiration in SL-related mutants.

Further supporting an impact of vessel development on water usage, induction of a DEX-inducible and auxin-insensitive version of the AUXIN RESPONSE FACTOR (ARF) transcription factor MONOPTEROS (MP, also known as ARF5) expressed under the control of the cambium-associated PXY promoter (PXY_pro:GR-MPΔIII/IV^11,42,43) resulted in a significant increase of vessel formation (Fig. 5a, b) and, at the same time, in elevated stomatal conductance in both well-watered and water deficiency condition (Fig. 5d). This effect was observed although stomata density was not significantly affected upon induction (Supplementary Fig. 15g, h). Interestingly, in wild type activation of auxin signalling by inducing MPΔIII/IV increased vessel number but reduced their size, while in smxl6;7;8 mutants, only the vessel number increased (Fig. 5a–c). This observation indicated that, in contrast to a common but independent effect of SL and auxin signalling on vessel number, both pathways have an interconnected effect on vessel size. Based on these findings, we rationalised that SL signalling restricts water usage in plants by modulating vessel formation and, consequently, water transport capacity. Supporting this idea, application of carboxyfluorescein diacetate (CFDA) to roots, used to study long distance transport along the xylem⁴⁴, resulted in higher fluorescence intensity in hypocotyls of d14 mutants than in wild type (Fig. 5e, f).

**Fig. 5: Effect of altered vessel formation on water usage and stomatal conductance.**

To further explore the effect of reduced water availability on vessel formation and the role of SL-signalling in this process, we subjected wild-type and d14 plants for two weeks to a soil-based water deficiency treatment. As a result, smaller vessels with a thicker cell wall were formed in wild type, while only very few of those were formed in d14 mutants (Fig. 5g, h). Likewise, when we reduced water availability for plants by adding 9% polyethylene glycol (PEG₈₀₀₀) to hydroponic cultures⁴⁵, fewer vessel elements with thickened cell walls were generated in d14 than in wild type (Supplementary Fig. 14d, e). These observations showed that SL signalling promotes structural changes in vessel elements when plants experience water deficiency.

Discussion

Taken together, by starting off with a cell-resolved transcriptome analysis of radially growing Arabidopsis organs, we revealed that SL signalling modifies the number and size of vessel elements produced during cambium-dependent radial growth. The possibility to modulate vessel anatomy in response to environmental cues like drought⁴⁶, can be assumed to be an important fitness trait and has, so far, been described as being mediated by ABA signalling during longitudinal growth⁴⁷. We did, however, neither observe any alteration of primary vessel element formation in primary d14 roots (Supplementary Fig. 16a), nor an increase of cambium-derived vessel formation in aba deficient 2 (aba2) mutants (Supplementary Fig. 16d, f), impaired in ABA biosynthesis⁴⁸ and showing higher stomatal conductance⁴⁹. Moreover, the formation of cambium-derived vessel elements was not altered in mutants displaying an increased stomatal density and a resulting increase in stomatal conductance^50,51 (Supplementary Fig. 16e, f), arguing against a positive effect of enhanced transpiration on vessel formation. These findings suggest that ABA- and SL-signalling pathways fulfil distinct functions with regard to their effect on vessel formation during primary and secondary development, respectively. Based on the observation that increased vessel formation by enhancing auxin signalling also leads to enhanced transpiration, there is indeed the possibility that increased stomatal conductance in SL-related mutants is a result of enhanced vessel element formation and an associated increase in water transport along the vascular system.

Interestingly, SL biosynthesis is enhanced in rice roots in drought conditions⁵² indicating that the pathway has the potential to lead to structural changes when plants experience growth, to possibly anticipate harsh conditions in the future. Depending on distinct ecological or agricultural niches plants have adapted to, it may be advantageous to establish a weaker or stronger impact of SL signalling on vessel element formation to cope with distinct environmental regimes.

Methods

Plant material

All plant lines used in this study were Arabidopsis thaliana (L.) Heynh. plants of the accession Columbia (Col-0). The single and higher order mutants of d14-1 (WiscDsLoxHs137_07E), smxl6-4 (SALK_049115), smxl7-3 (WiDsLox339_C04), smxl8-1 (SALK_025338C), max1-1, and max2-1 were obtained from Dave Nelson^53,54 (UC Riverside, US) and Ottoline Leyser⁵⁵ (SLCU, Cambridge, UK). The 35S_pro:XVE > >miRNA165a line was received from Ari Pekka Mähönen¹⁷ (University of Helsinki, Finland). The brc1-2 (SALK_091920) mutant was ordered from NASC and was characterised previously^35,56,57,58. Strigo-D2²⁶, PXY_pro:ER-ECFP-HDEL⁵⁹, PXY_pro:H4-GFP;SMXL5_pro:H2B-RFP¹¹, SMXL7_pro:SMXL7^d53-VENUS²⁷, PXY_pro:Myc-GR-bdl⁴², MP_pro:ER-EYFP-HDEL⁴², and PXY_pro:GR-MPΔIII/IV⁴² transgenic lines were described previously. Other transgenic lines were generated through the floral dipping method using Agrobacterium tumefaciens⁶⁰. The aba2-11 mutant⁴⁸ was obtained from Mikael Brosché (University of Helsinki, Finland). epf1-1 (SALK_137549)⁶¹ and epf2-3 (SALK_047918)⁶² single and double mutants and tmm-1 (SALK_011958)⁶³ mutants were kindly donated by Christopher Grefen (University of Bochum, Germany). PFA1_pro:PFA1-GFP⁶⁴ lines were obtained from Tatsuo Kakimoto (Osaka University, Japan).

Vector construction

The WOX4_pro:D14 (pVJ13) construct was generated using In-Fusion cloning (Takara Bio) using the amplified D14 coding region and BamHI-digested pTOM49¹³. Other plasmids were generated using the GreenGate cloning system^65,66. SMXL7^d53 in pGGC (pJZ60) was mutagenised based on the template of the SMXL7 CDS in pGGC (pKR07) according to the manual of the QuickChange Site-Directed Mutagenesis Kit (Agilent, Santa Clara, USA). See Supplementary Data 5 for oligo sequences used for molecular cloning and Supplementary Data 6 for each module used during the cloning process.

Growth conditions

Arabidopsis seeds were surface sterilised by 70% ethanol containing 0.02% Tween-20, stratified at 4 °C for 2-3 days in the dark, and sown on 0.8% w/v agar in 1/2 Murashige and Skoog (MS) medium supplemented with 1% w/v sucrose. Seedlings were grown in short-day conditions (SD; 10 h light and 14 h darkness) at 21–22 °C. For morphological observations and reporter activity analyses, five-day-old seedlings were transferred to pots filled with a 4:1 mixture of soil and vermiculite. After 21 days, plants were transferred to long day conditions (LD; 16 h light and 8 h darkness) at 21–22 °C. Plants for stomatal conductance measurements were grown for six weeks in SD conditions (8.5 h light and 15.5 h darkness).

Single-nucleus RNA-seq analysis

Hypocotyls were dissected and collected in petri dishes incubated on ice. 2 ml of 1× nuclei isolation buffer (CelLytic™ PN Isolation/Extraction Kit, Sigma #CELLYTPN1) supplemented with 20 µl RiboLock RNase inhibitor 40 U/µL (Thermo Fisher #EO0381) and Hoechst 33342 at 10 µg/ml final concentration were prepared and a minimum amount of buffer was applied to submerge the collected hypocotyls¹⁰. Hypocotyls were chopped using razor blades (Wilkinson Sword) for up to 5 min and then gently shaken at 4 °C for 15 min. Samples were then filtered through a 50 µm filter (CellTrics, Sysmex #04-004-2327) and passed to a low-protein-binding tube (Eppendorf #0030108132).

For 10x genomics application, 50,000 nuclei were sorted into 33 µl collection buffer (10 µl PBS (Corning, #21-040-CV), 5 µl BSA (Thermo Fisher, #AM2616), 6 µl RNAse inhibitor (Thermo Fisher, #AM2682), 12 µl RNAse inhibitor (Thermo Fisher, #AM2694)), modified from a previous report⁶⁷, by a BD FACSAria IIIu cell sorter (Becton Dickinson) using a 100-µm sort nozzle (see Supplementary Fig. 1). A sheath pressure of 35 psi and a drop drive frequency of 60 kHz were applied. 43.2 µl of sorted nuclei solution was applied to a Chromium Next GEM Chip without dilution and Chromium Next GEM Single Cell 3’ GEM, Library & Gel Bead Kit (v3.1) was used to generate libraries following the manufacturer’s instructions. Nuclei concentration was monitored by a fluorescent cell counter (Thermo Fisher, Countess 3 FL) using the DAPI channel to obtain approximately 200 nuclei/µl. Libraries were sequenced using a NextSeq (Illumina) machine at high output mode.

For initial wild-type analyses, about 100 hypocotyls from a PXY_pro:H4-GFP;SMXL5_pro:H2B-RFP line collected four weeks after germination were used. Sequencing reads were mapped to the Arabidopsis genome (with H4GFP and H2BRFP transgene sequences added) using STAR (2.7.8a)⁶⁸ with the “--alignIntronMax 10000 --alignMatesGapMax 10000” option. “GeneFull” option was used in STAR solo to include reads mapped to introns. Seurat⁶⁹ (4.0.6, 4.1.0 or 4.3.0) was used for further analysis. Cells with nCount_RNA between 1201 and 9999 and a mitochondrial genome read fraction of less than 20% were kept for further analysis. Clustering and UMAP were generated using default settings of Seurat with the parameters “dims = 1:15, resolution =1.2, algorithm =2”. Monocle 3 (1.3.1)⁷⁰ was used for trajectory analysis and the region around the CSC cluster was selected as the root node for pseudotime calculation.

For wild type and d14 mutant analysis, about 200 hypocotyls collected 19 days after germination were used. Sequencing reads were mapped to the Arabidopsis nuclear genome with cell ranger (6.0.1, 10x genomics) using the “--include-introns” and “--alignIntronMax 10000 --alignMatesGapMax 10000” alignment options. nCount_RNA between 1501 and 14999 were kept for comparing wild type and d14 mutants. Clustering was carried out using parameters “dims = 1:15, resolution =1.2, algorithm =2”, and UMAPs were generated after randomly resampling 500 nuclei from each genotype.

For VASA-seq analysis²¹, about 100 hypocotyls from a PXY_pro:H4-GFP;SMXL5_pro:H2B-RFP line were collected four weeks after germination to obtain 1134 ‘cambium region’ nuclei (three 384-well plates). Additional 100 hypocotyls were used for collecting 1134 ‘all region’ nuclei (three 384-well plates) (see Supplementary Fig. 1). Single nuclei were sorted into individual wells of 384-well plates containing well index oligos purchased from Single Cell Discoveries B.V. (Utrecht, The Netherlands), using the index sorting mode of the BD FACSAria IIIu cell sorter, recording the fluorescence signal of each nucleus (Supplementary Data 7). Multi-well plates were frozen and further processed according to the VASA-seq protocol²¹ of Single Cell Discoveries with the following modifications. (1) In the end, repair and polyA reactions, our added mix per well contained 7.5 μM ATP and 3.75 mU of polyA polymerase. (2) We used 6 μl of ExoSAP after in vitro transcription. (3) The composition of our 2.5× RNaseH buffer used during the rRNA depletion step was 125 mM Tris-HCl pH 7.5, 250 mM NaCl, 10 mM MgCl₂. Sequencing reads were similarly mapped to the Arabidopsis genome (with H4GFP and H2BRFP transgene sequences added) using STAR with the same options mentioned above. Well barcodes were obtained from Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/; Accession ID: GSE112438, celseq2_bc.csv.gz). Fluorescent signals were combined in Seurat with a 150 offset value to avoid negative values in the 488 nm and 561 nm channels, and all nucleus data were merged. Cells with nCount_RNA values between 1201 and 14,999, a mitochondrial genome read fraction lower than 20%, fluorescent signals in the 405 nm and 488 nm channels lower than 75,000 were kept for further analysis. Clustering and UMAP were performed with parameters “dims = 1:15, resolution =1.8, algorithm =2”.

Basic statistics of all single-cell analyses can be found in Supplementary Data 1. Marker genes for each cluster were generated by using the FindAllMarkers function in Seurat (Supplementary Data 2) (only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25, test =“wilcox”, return.thresh = 0.01). Seurat object files for each dataset are deposited at Gene Expression Omnibus under accession code GSE224928. Phytohormone responsive genes^24,25 and marker genes for cell clusters generated by single cell transcriptome analyses^8,9,71 were curated from previous reports and integrated in Seurat by using the AddModuleScore function (Supplementary Data 3). Differential expression was tested by the Steel-Dwass test using an R script (http://aoki2.si.gunma-u.ac.jp/R/src/Steel-Dwass.R) authored by Shigenobu Aoki (Gunma University, Japan).

Confocal microscopy

Hypocotyl samples were fixed overnight at 4 °C in 4% (w/v) PFA dissolved in PBS. The tissue was washed twice with PBS, optionally embedded in 5% low gelling temperature agarose, sectioned by razor blades (Wilkinson basic), and then stained with 0.1% DirectRed 23, 0.1% Renaissance SR2200 (Renaissance Chemicals Ltd, UK) or 10 μg/ml Hoechst 33342 for 5 min at room temperature. Excess staining was removed by clearing the sample in 1× PBS. Confocal microscopy experiments were carried out on a Leica TCS SP8 (Leica Microsystems Mannheim, Germany). 458 nm, 514 nm and 561 nm lasers were used to excite mTurquoise2 (CFP), YFP (mVenus), and mCherry/Direct Red, and emissions were detected at 465–509 nm, 524–540 nm and 571–630 nm, respectively. Hoechst 33342 and Calcofluor White, together with lignin in differentiated xylem vessel elements, were visualised using a 405 nm laser, and collection of the emission at 410–450 nm. Basic Fuchsin was visualised using a 561 nm laser by STELLARIS 8 (Leica Microsystems, Mannheim, Germany) or Leica TCS SP8 (Leica Microsystems, Mannheim, Germany), collecting the emission in a range of 586–650 nm. Imaging of promoter reporter lines for cluster annotation validation and in situ hybridisation was carried out on an LSM 710 (Carl Zeiss Microscopy GmbH, Oberkochen, Germany) or on a STELLARIS 8 (Leica Microsystems, Mannheim, Germany). 405 nm, 488 nm and 561 nm lasers were used to excite Renaissance SR2200, GFP, Direct Red 23 and ATTO550, respectively.

Hybridisation chain reaction (HCR)-based in situ hybridisation

Arabidopsis hypocotyls from four-week-old plants were fixed overnight at 4 °C in 4% (w/v) PFA. After washing off the fixative, sections were produced manually and immediately transferred to 100% methanol for more than 5 min. Hybridisation and amplification were carried out with ISHpalette Short hairpin amplifier ATTO550-S41 (#IPL-R-S41, Nepa Gene Co., Ltd., Ichikawa, Japan) according to the manufacturer’s instructions. See Supplementary Data 5 for oligo sequences used as probes for each gene.

Strigo-D2 ratio analysis

False colour images were generated using ImageJ by calculating intensity ratios of each pixel from mVenus and mCherry channels after being Gaussian Blurred and subtracting background signals. For calculating the ratio value of each nucleus, nuclear regions were detected by using the Particle Analyzer function in ImageJ after masking the nuclear region through thresholding. Then, nuclear mVenus and mCherry signal intensity were measured and intensity ratios were determined. Nuclei within cambium, phloem, and xylem zones, as well as in developing vessel elements, were manually defined as follows: around six cell layers counting from the vessel element border toward the organ periphery were defined as the cambium zone. Nuclei distal to the cambium were defined as phloem, and the nuclei proximal to the cambium were defined as xylem. The enlarged nuclei within the xylem region were considered to be located in developing vessel elements.

Histological analyses

The harvested hypocotyls from five week-old (3 weeks SD+2 weeks LD) plants or four week-old plants subjected to two weeks of water deficiency treatment (SD conditions) were infiltrated by 70% ethanol for at least three days at 4 °C before being paraffin embedded by the Leica ASP200 S processor (Leica Microsystems, Mannheim, Germany). After embedding in paraffin, the microtome RM2235 (Leica Microsystems, Mannheim, Germany) was used to produce 10-μm-thick sections. The sections were harvested from the upper part of the hypocotyl, 1 mm below the leaf primordia. Dried sections were deparaffinized, stained with 0.05% toluidine blue (#52040, AppliChem, Darmstadt, Germany) and fixed by Micromount Mounting Media (Leica Microsystems; Mannheim, Germany) on microscope slides (Thermo Scientific; Waltham, USA). Slides were scanned using the Pannoramic SCAN II scanner (3DHistech, Budapest, Hungary) and analysed by the CaseViewer 2.2 software (3DHistech, Budapest, Hungary). Vessel elements were either automatically detected using a developed vessel-counting macro in Fiji or the VesselWizard tool, both established for this purpose⁷² and corrected manually to eliminate false positives or negatives (using the Wand Tool in Fiji).

Dexamethasone and estradiol treatment

For SMXL7_pro:SMXL7^d53-GR induction by DEX, a stock solution of 25 mM DEX was dissolved in DMSO, and a 15 μM working solution was freshly prepared by diluting the stock solution with tap water. Control treatments contained an equivalent amount of solvent. Plants were initially grown in SD conditions for three weeks without treatment, and treatment was started when plants were transferred to LD conditions by watering twice a week with either 50 ml 15 μM DEX or mock solution per pot until harvest. For estradiol induction of 35S:XVE > >miRNA165a expression¹⁷, a 20 mM stock solution of 17β-Estradiol (Sigma-Aldrich, E2758) was prepared in DMSO and stored at −20 °C. Five-day-old seedlings were transferred to plates supplemented with either 5 μM 17β-Estradiol or an equal volume of DMSO until they reached two weeks of age. Hypocotyls were harvested and fixed in 4% PFA at 4 °C. Cross-sections, 200 μm thick, were obtained using a Vibratome (Leica VT1000 S) after embedding the samples in low-melting agarose (Sigma-Aldrich, A9414). The sections were stained overnight at 4 °C with 0.0 2% Basic Fuchsin in ClearSee.

GR24^4DO application

2 µM GR24^4DO (StrigoLab S.r.l., c/o Dept. of Chemistry, Turin University, Italy) was prepared through a 5000× dilution of a stock solution (10 mM GR24^4DO dissolved in acetone). Seedlings were initially grown on plates containing solid 1/2 MS medium with 1% sucrose supplemented for five days (SD conditions) without treatment, subsequently transferred to culture vessels (C1958, PhytoTechLabs, USA) supplemented either with 2 μM GR24^4DO or mock solution containing an equivalent amount of acetone, grown in SD condition and harvested four weeks after germination for histological analyses.

RNAseq and qRT-PCR analysis

RNAseq

DEX (Sigma-Aldrich, USA) was dissolved in DMSO as a 25 mM stock solution and stored at −20 °C. The working concentration of DEX was 15 μM diluted from the stock solution by tap water. The DEX-based induction of SMXL7_pro:SMXL7^d53-GR lines was conducted by directly watering 15 μM DEX or an equal volume of DMSO (mock) to four-week-old plants (three weeks SD conditions, then transferred to LD conditions) grown on soil. After five hours of incubation, the hypocotyls from DEX- and mock-treated plants were immediately harvested and ground using a pestle and mortar after being immersed in liquid nitrogen. RNA was isolated using the RNeasy Mini Kit (QIAGEN, Netherlands) and genomic DNA contamination was removed by referring to the protocol of the TURBO DNA-free™ Kit (Thermo Scientific; USA). Subsequent clean-up of RNA was performed by using RNeasy Mini Kit. 1.2 µg of total RNA/sample was used for library preparation using NEBNext Ultra II RNA Library Prep Kit for Illumina (NEB) using the polyA mRNA workflow and Unique Dual Index primers (NEB). 12 cycles of amplification were performed, and the libraries were sequenced using NextSeq 550 (Illumina). Obtained reads were mapped by STAR-2.7.8a with “--alignIntronMax 10000 --alignMatesGapMax 10000 --outFilterMultimapNmax 1” option. Reads per gene were counted by summarizeOverLaps function (GenomicAlignments v1.30.0)⁷³ with “mode = “union”, ignore.strand = TRUE” option. Differentially expressed genes were detected using DESeq2 (v1.34.0)⁷⁴ applying a threshold of “baseMean>50, |log2FoldChange|>0.585, padj<0.01”. Functional enrichment analysis was performed using g:GOSt (version: e111_eg58_p18_f463989d)⁷⁵.

qRT-PCR

Hypocotyls of four-week-old wild-type and d14 mutant plants grown on soil were harvested. Total RNA was extracted using the method mentioned above. cDNA synthesis was performed according to the instructions of the Thermo Revert Aid Kit (Thermo Scientific; Waltham, USA). Real-time PCR assays were conducted using SYBR Green Mix (Thermo Scientific; Waltham, USA) and gene-specific primers (Supplementary Data 5) on a qTOWER3 thermal cycler and using the EF1-a (AT5G60390) gene as an internal reference.

Water deficiency treatments

To grow plants under comparable conditions, each pot contained 70 g of soil. For watering, pots were placed in petri dishes to soak 25 ml of water overnight from below. Next, 20 ml of nematode-containing solution was added to each pot from above. For pot weight measurement, pots were kept in petri dishes during subsequent watering (20 ml every week during the first three weeks and 25 ml twice a week for the last two weeks). Pot weight was measured starting five weeks after germination for the consecutive 12 days. For histological analysis of stress-related phenotypes, plants were grown well watered for two weeks (20 ml every week), before water deficiency treatment was applied for two weeks. The control group was kept in well-watered conditions during the treatment.

Stomatal conductance measurements

Wild type, d14, max2 and smxl6;7;8 plants were grown in growth chambers with sufficient watering for four weeks, followed by water deficiency treatments for 12 days. During the first three weeks, plants were watered with 20 ml every week during the first three weeks and 30 ml twice a week for the next three weeks. DEX or mock-treated PXY_pro:GR-MPΔIII/IV plants were not watered for 10 days after the DEX or DMSO treatment. Stomatal conductance of wild type, d14, max2 and smxl6;7;8 plants was measured after 12 days of water deficiency treatment and DEX or mock-treated PXY_pro:GR-MPΔIII/IV plants were analysed after 10 days of water deficiency treatment. For the measurements, the SC-1 Leaf Porometer (METER Environment®, Meter Group, Pullman, US) was clipped on the abaxial side of the leaf. The 9th, 10th and 11th produced leaves of wild type, smxl6;7;8, DEX or mock-treated PXY_pro:GR-MPΔIII/IV plants and three well expanded upper leaves from d14 or max2 mutants were chosen for the measurement. The SC-1 Leaf Porometer was used according to the user manual. Single measurements were temporarily randomised across the course of the day and across genotypes.

Stomata imprints

Water deficiency-treated plants used for the stomatal conductance measurement were taken to imprint the abaxial leaf side for stomata density quantification (stomata/mm²). For the imprint, a small drop of instant adhesive glue (UHU Sekundenkleber blitzschnell; UHU, Bühl, Germany) was placed on a Superfrost™ Microscope slide, and the leaf was gently pressed on the glue for two seconds. The imprints were visualised using a Contrast Microscope DMIRB microscope with a 20× objective and the bright field mode. Five images of the central leaf regions of each imprint were taken. The number of stomata was counted using Fiji.

CFDA application

Roots of three-week-old plants (grown on plates) were cut 2 cm below the hypocotyl, and 5 µl of 1 mM CFDA (5(6)-Carboxyfluorescein diacetate N-succinimidyl ester, Sigma-Aldrich, USA) or DMSO were applied. After 30 min, hypocotyls were harvested, fixed with 4% PFA and embedded in 9% low-gelling temperature agarose. 100 µm thick vibratome sections were used for confocal microscopy.

Basic Fuchsin staining

To observe xylem strands in roots, five-day-old seedlings were stained and fixed in 0.2% (m/v) Basic Fuchsin dissolved in ClearSee^76,77 (10% xylitol, 15% sodium deoxycholate, and 25% urea) solution overnight. Next, the fuchsin solution was removed, and samples were washed once with ClearSee for 30 min. Subsequently, seedlings were stored in ClearSee solution and analysed.

Statistics and reproducibility

All the measurements were done on distinct samples. Statistical tests were applied in a two-sided mode. Box plots indicate the 25th (Q1, box limit), 50th (median, centre line) and 75th (Q3, box limit) percentiles and whiskers indicate the value range or up to the 1.5× interquartile range from the Q1 or Q3 limit, respectively. Data points beyond this range were plotted individually as outliers. Statistical analyses were carried out using R (v4.0.4 or v4.0.5), ggplot2 (v3.3.3), or Python (v3.10.7), pandas (v1.5.0), rstatix (v0.7.2) and seaborne (v0.12.0).

No statistical methods were used for sample-size calculation. Sample sizes have been maximised according to practical considerations. No data were excluded from the analyses except in snRNA-seq analysis, nuclei with a low number of molecules detected were excluded from further analysis according to the standard pre-established analysis pipeline. All the findings were confirmed by usually three but at least two replicates. snRNA-seq analyses were not replicated using the exact same method and type of samples, however, findings were confirmed in each analysis using different technologies and types of samples, suggesting their universality. Plant pot positions were randomised in possible cases, however, randomisation was not applied to all the experiments due to practical reasons (enhanced physical handling of plants). Covariates were controlled by applying the exact same conditions (growth substrate, temperature, light) to all individuals. The investigators were not blinded to allocation during experiments and outcome assessment.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The raw sequencing data of snRNA-seq and bulk RNA-seq analyses, and Seurat object files of snRNA-seq data generated in this study have been deposited at NCBI’s Gene Expression Omnibus database under accession code GSE224928 or GSE270808. The authors declare that all other data supporting the findings of this study are mentioned in the main text or the supplementary materials. Source data are provided with this paper.

Code availability

General codes used for analyses and specific parameters are provided in the “Methods” section. Codes for the presented vessel identification tools are deposited at GitHub [https://github.com/thomasgreb/Zhao-et-al_SL-vessels]⁷².

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Acknowledgements

10x Chromium operation, library preparation and next-generation sequencing were carried out by David Ibberson (The CellNetworks Deep Sequencing Core Facility, Heidelberg University, Germany). For data storage, we used the SDS@hd service of Heidelberg University. Nucleus sorting was carried out by Monika Langlotz (Flow Cytometry and FACS Core Facility, ZMBH, Heidelberg University, Germany). VASA-seq processing was carried out by Single Cell Discoveries B.V. (Utrecht, The Netherlands). We thank David Nelson (University of California Riverside, USA), Christopher Grefen (University of Bochum, Germany), Mikael Brosché (University of Helsinki, Finland), Ottoline Leyser (University of Cambridge, UK) for providing plant material, Virginie Jouannet (Heidelberg University, Germany) for generating plant material, Arun Sampathkumar (Max Planck Institute of Molecular Plant Physiology, Germany) and Jan Lohmann (Heidelberg University, Germany) for sharing equipment. We also thank Tiago Daniel Gomes Nunes (Heidelberg University, Germany) and Michael Raissig (University of Bern, Switzerland) for support in stomatal conductance measurements. Moreover, we thank Kiyoshi Mashiguchi and Shinjiro Yamaguchi (Kyoto University, Kyoto, Japan) for technical support. This work was supported by a fellowship of the Chinese Scholarship Council (CSC) and a Peterson scholarship (http://www.peterson-elites.sdu.edu.cn/jxjjj.htm) to J.Z., an overseas research fellowship of the Japan Society for the Promotion of Science [JSPS Overseas 201960008] to D.S. Ki.K. was supported by a doctoral fellowship of the Landesgraduiertenförderung of the state Baden-Württemberg. Y.H. was supported by the Max Planck Gesellschaft. Work in T.G.’s group was furthermore supported by the SFB 1101 of the Deutsche Forschungsgemeinschaft (DFG), the DFG project GR 2104/10-1 and the ERC consolidator grant PLANTSTEMS. Work in the D.S.’s group was supported by the JST PRESTO grant [JPMJPR2046] and the DFG projects 504847536 and 512328399. Work in the Ke.K. group was supported by the DFG projects 438774542 and 512328399. For the publication fee we acknowledge financial support by Heidelberg University.

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Open Access funding enabled and organized by Projekt DEAL.

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These authors contributed equally: Jiao Zhao, Dongbo Shi, Kiara Kaeufer.

Authors and Affiliations

Developmental Physiology, Centre for Organismal Studies, Heidelberg University, Heidelberg, Germany
Jiao Zhao, Dongbo Shi, Kiara Kaeufer, Changzheng Song, Dominik Both, Anna Lea Thier, Laura Luzzietti & Thomas Greb
Genetics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
Dongbo Shi, Hui Cao & Linus Lassen
RIKEN Center for Sustainable Resource Science, Yokohama, Japan
Dongbo Shi
Plant Cell and Molecular Biology, Institute of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
Xiaocai Xu & Kerstin Kaufmann
Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
Yuki Hamamura
School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK
Tom Bennett

Authors

Jiao Zhao
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Dongbo Shi
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Kiara Kaeufer
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Changzheng Song
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Dominik Both
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Hui Cao
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Linus Lassen
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Xiaocai Xu
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Yuki Hamamura
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Laura Luzzietti
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Kerstin Kaufmann
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Contributions

J.Z., D.S., Ki.K. and T.G. designed the study. J.Z., D.S., H.C., Li.L., Ki.K., D.B., A.L.T., and La.L. performed experiments. J.Z., D.S., Ki.K. and C.S. analysed the data. X.X. and Ke.K. provided technical support on single-nucleus RNA-seq analysis. Y.H. provided technical support on microscopy. T.B. provided essential material. J.Z., D.S. and T.G. wrote the manuscript with input from all the authors.

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Correspondence to Dongbo Shi or Thomas Greb.

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Zhao, J., Shi, D., Kaeufer, K. et al. Strigolactones optimise plant water usage by modulating vessel formation. Nat Commun 16, 3854 (2025). https://doi.org/10.1038/s41467-025-59072-y

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Received: 15 January 2025
Accepted: 08 April 2025
Published: 28 April 2025
Version of record: 28 April 2025
DOI: https://doi.org/10.1038/s41467-025-59072-y

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