Systems acclimation to osmotic stress in zygnematophyte cells

Domain: biology
Published: 2026-01-16
Editorial outcome: minor_revision

Abstract
Zygnematophytes are the closest algal relatives of land plants. They hold key information to infer how the earliest land plants overcame the barrage of terrestrial stressors, the prime of which is osmotic stress. Here, we apply two osmotic stressors on a unicellular and a multicellular representative of zygnematophytes and study their responses over a 25-hour time course, generating 130, 60, and 30 transcriptomic, proteomic, and metabolomics samples combined with photophysiology, sugar analysis, immunocytochemical glycoprotein analysis, and microscopy. Our data highlight a shared protein chassis that shows divergent responses with the same outcome: successful acclimation to osmotic challenges. We establish a model of how the algal sisters of land plants can overcome a prime stressor in the terrestrial habitat and highlight components of the plant terrestrialization toolkit.

Introduction
Phylogenomic research over the last decade has consistently recovered the Zygnematophyceae as the closest algal relatives of embryophytes (land plants)1–5. Zygnematophyceae diversified into a species-rich class of unicellular and filamentous algae that live in diverse habitats6,7. Studying their genomes8–11 revealed a whole set of genes that are homologous to the molecular chassis known from environmental adaptation in land plants12–15. Previous studies particularly focused on signaling cascades regulating stress responses15–20. Yet, our knowledge on the proteins that constitute the stress physiology of zygnematophyte cells is very limited. In this study, we focused on the protective molecular mechanisms against hyperosmotic stress, a prime challenge on land.

A defining characteristic of terrestrial habitats compared with aquatic environments is the much more variable availability of water. These fluctuations are closely linked to frequent osmotic stress: a decrease in water availability results in hyperosmotic stress, whereas an increase can lead to hypo-osmotic stress. Land plants have adapted to these challenges through diverse strategies for managing changes in water availability. They have evolved specialized adaptations, including water-conducting tissues in vascular plants and water-conducting cells in bryophytes21–23. In addition, stomata24 and the cuticle25–27 are characteristic features of embryophytes, serving to regulate water loss and to retain water within the plant, respectively.

At the cellular level, water regulation is vital for maintaining structural integrity and function. Plant and algal cells possess cell walls, onto which intracellular fluid mediates an outward force known as turgor pressure, critical for maintaining cell structure and function. Under hyperosmotic stress—such as when osmolyte concentrations in the surrounding environment increase due to water loss—turgor pressure decreases as water movement into the cell diminishes or reverses. This pressure drop triggers a cascade of physiological and biochemical responses, including structural alterations, membrane leakage, molecular crowding, and other forms of cellular damage28,29.

To mitigate the effects of hyperosmotic stress, plants have evolved several adaptive mechanisms. A palpable response well-known from tracheophytes is the closure of stomata to minimize water loss30,31. On the cellular level, plants and algae initiate membrane reorganization and synthesize osmotically active metabolites, such as proline, sugars, and sugar alcohols, to stabilize the intracellular osmotic potential32. When dehydration results from osmotic stress, some algae can down-regulate the water-intensive process that is photosynthesis33. Reactive oxygen species (ROS) are also commonly produced during drought-related stresses, being both signals and culprits emerging from an imbalance in photosystems31,34–36. In response, plants activate ROS-scavenging systems to prevent oxidative damage; plants further produce a variety of stress-responsive proteins that play essential roles in protecting cellular membranes, maintaining ionic homeostasis, and degrading damaged proteins to facilitate repair28,37. Conserved structural modifications to the cell wall and cytoskeleton38 bolster cellular strength and resilience to the mechanical stresses associated with turgor pressure loss. Collectively, these mechanisms represent a multifaceted strategy that allows plants to survive and adapt to osmotic stress conditions. These key mechanisms of osmotic stress tolerance have been studied mainly in land plants, leaving their evolutionary conservation obscure.

Some zygnematophyceae algae exhibit exceptional adaptability to osmotic stress, thriving in habitats characterized by frequent fluctuations in water availability, including ponds, puddles, and Arctic regions39–41. Previous studies, often with a focus on one specific technical aspect, have identified key coping strategies and hyperosmotic stress-responsive genes in these algae; these include upregulated glycosyltransferase family 2 genes in Zygnema circumcarinatum42 and microscopic observations of cell wall and endomembrane adaptations in Penium margaritaceum43. Here, we employ a systems biology approach of temporal transcriptomics and proteomics to uncover the core osmotic stress response in Zygnematophyceae. From our data, we infer key components of the plant terrestrialization toolkit.

Results
Quantitative impacts of osmotic stress in Mesotaenium and Zygnema
We worked with two representatives of the closest algal relatives of land plants: the unicellular Mesotaenium endlicherianum SAG 12.97 and the filamentous Zygnema circumcarinatum SAG 698-1b, hereafter referred to as Mesotaenium and Zygnema. Next to representing the two predominant body plans in zygnematophytes, these species were selected due to (i) their natural exposure to osmotic stress in their habitats: Mesotaenium originates from a lake subject to annual drying cycles, while Zygnema is found in a meadow ditch; (ii) the availability of fully sequenced genomes and updated gene models8,10,15; and (iii) the presence of all protein components involved in the canonical abscisic acid (ABA) signaling cascade10,44, critical in osmotic stress response of embryophytes45,46—albeit these proteins likely act independent of ABA in zygnematophytes18.

Mesotaenium and Zygnema were cultivated on cellophane disks placed on agarised medium, allowing transfer to other agar plates without disturbing the algae (Fig. 1a). Unlike cultivation in liquid medium, this approach allowed for stress experiments that more closely mimic terrestrial habitats while enabling easy and rapid sampling.

The osmotic stress treatments for this study were initially based on Kilian et al.47: 300 mM mannitol and 150 mM NaCl for 24 hours. However, during preliminary trials, no clear morphological response was observed under 300 mM mannitol within 24 hours. Consequently, the mannitol concentration was increased to 800 mM. In contrast, treatment with 150 mM NaCl (both osmotic and ionic stress) led to a clear and rapid drop in the maximum quantum yield of photosystem II, Fv/Fm, that is a non-invasive and comparable measure of gross physiology48.

The highest Fv/Fm values were observed 25 hours after transferring the algae to a new growth plate without osmolytes, likely reflecting optimal conditions provided by the fresh medium. In this treatment, Fv/Fm values ranged from 0.65 ± 0.05 for Mesotaenium and 0.73 ± 0.02 for Zygnema (Fig. 1b). Following the onset of osmotic stress, Fv/Fm values decreased in both algae (P < 0.01 for both treatments after 6 h, Fig. 1b). However, recovery patterns differed: Zygnema showed a rapid rebound in the NaCl treatment, whereas Mesotaenium exhibited a slower recovery. In contrast, Fv/Fm values remained 8.8% ± 5.1% and 25.2% ± 6.1% below their starting values under mannitol treatment for Zygnema and Mesotaenium,; they never approached zero, indicating that the algae retained some potential for photosynthesis.

Water moves from regions of higher concentration to regions of lower concentration; upon hyperosmotic stress, we expected an efflux and/or a reduced influx into the cell. The water content in both species was significantly (P < 0.001) reduced upon NaCl and mannitol treatments (Fig. 1c). Notably, the dry weight of the mannitol-treated samples was substantially higher compared to the NaCl-treated and control samples, but this is explained by an accumulation of mannitol in the samples as later confirmed through metabolite fingerprinting (see below).

A rapid decrease of water content triggers plasmolysis in plants: the movement of water out of the cell decreases the volume of the protoplast, which could detach from the rigid structure of the cell wall as also previously well-documented for Zygnema circumcarinatum49. Although plasmolysis was not complete in all cells, with the plasma membrane remaining connected to the cell wall in most areas, it was the most significant feature observed during the morphological analysis of both Mesotaenium (P = 0.002) and Zygnema (P = 2.8e-5) under high osmotic stress induced by mannitol treatment (Fig. 1c, 1d). In addition to plasmolysis, other structural changes included distortions of the chloroplast, bending and breaking of cells/filaments, changes in vacuolar structures and other inclusions (Figs. 1c, 1d). In Mesotaenium “cups” were formed, which are non-green and often reddish cell-wall-enclosed compartments that can detach from the mother cell.

Dynamics in stress-responsive proteins and transcripts
To investigate the molecular response of the algae, we applied RNA sequencing at t0, 3h, 6h, 9h, and 25h and shotgun proteomics at t0, 6h, and 25h. Accurate transcript levels were determined for 21,651 transcripts in Mesotaenium and 9631 transcripts in Zygnema, with the number of analyzed genes being 28% higher for Mesotaenium and 2% higher for Zygnema compared to those analyzed in Rieseberg et al.14. Protein levels were reliably quantified for 2171 and 1713 proteins, respectively, 88% and 92% of which were detected in 100% of samples for at least one treatment, enabling their inclusion in differential abundance analyses. Further, a de novo transcriptome was assembled as a complementary database for proteomics analysis, yielding 90 and 200 additional protein groups in Mesotaenium and Zygnema, respectively. In Mesotaenium, many of these newly identified proteins corresponded to isoforms of incomplete genes located at the ends of contigs, while in Zygnema, they were predominantly new genes already annotated in Zygnema circumcarinatum UTEX 1559 (Supplementary Fig. 1 and Supplementary Data 1).

Principal component analysis (PCA, Fig. 2a) revealed that proteins from different treatments were better separated at the 25-hour timepoint compared to the 6-hour timepoint. The PCA of the transcript data provided further insights, revealing distinct differences in the speed and variation of responses between treatments between Mesotaenium and Zygnema: In Mesotaenium, controls showed minimal variation across timepoints, whereas Zygnema exhibited clear shifts along the second principal component over time. Each treatment displayed unique temporal patterns: in Mesotaenium, early NaCl-treated samples were farthest from controls but later converged, indicating a rapid and strong response. In contrast, the transcript PCA for Mesotaenium revealed greater variability among biological replicates in the latest timepoints of the mannitol treatment, with some samples clustering near the controls while others diverged substantially, suggesting an acclimation process that builds on large transcriptomic changes and bears out in a different temporal dynamic in the two species.

We performed a differential abundance analysis, comparing each treatment to the control for all timepoints (Fig. 2b, 2c). Consistent with the PCA results, protein fold changes were more pronounced at 25h than at 6h, whereas transcript levels began to change earlier, indicating a faster transcriptomic response compared to the proteomic response. The latter was most apparent in the salt treatment, which showed the strongest transcriptional changes between 3 and 9 hours, followed by a partial recovery—resembling the control more closely—after 25 hours. This pattern was especially clear in Mesotaenium, where the control timepoints showed minimal variation among themselves, and the final salt-treatment timepoint appeared more similar to the controls than to the earlier treatment stages. An intriguing difference was observed between Zygnema and Mesotaenium: in Mesotaenium, the fold changes for mannitol and NaCl treatments were similar, whereas in Zygnema, the mannitol treatment exhibited more pronounced fold changes than NaCl. These trends were consistent across both transcriptomic and proteomic levels.

Several proteins changed significantly in differential abundance (151 proteins summed in all analysis in both timepoints and both species; FDR < 0.05; Supplementary Data 2). Focusing on those identified in both Mesotaenium and Zygnema, five types were found. Among these, SVR3, a putative chloroplast TypA translation elongation GTPase, was the only protein downregulated. SVR3 has been implicated in chloroplast development under cold stress in plants50, but its broader functional roles remain largely unexplored. Among the upregulated proteins, one of the most differentially abundant during osmotic stress was an NADPH-dependent aldo-keto reductase (AKR). AKR catalyzes the reduction of carbonyl groups to primary and secondary alcohols. It is frequently associated with abiotic stress responses, functioning in detoxification, osmolyte production, or the synthesis of secondary metabolites51. The remaining three upregulated proteins are predicted to localize in the cell wall: an exordium-like protein (EXL), xyloglucan endotransglucosylase/hydrolase (XTH), and proteins containing at least one fasciclin-like (FAS1) domain. XTH likely contributes to cell wall remodeling by modifying xyloglucan, whereas the functions of the other cell wall-associated proteins are less well understood. The number of transcripts showing significant changes is substantial (>4000 with P_adj < 0.01), making it impractical to analyze all of them individually (see Supplementary Data 3). Focusing on the top five differentially expressed transcripts, we observe that both Zygnema and Mesotaenium share a common upregulated gene encoding a LEA (Late Embryogenesis Abundant) protein. LEA proteins play a crucial protective role during environmental stress in plants and are frequently upregulated in response to osmotic-related stressors across various species52.

Integrated analysis of transcript and protein correlations
Using transcriptome and proteome samples from the same plate, our parallelized experimental setup enabled robust comparisons that exposed discrepancies possibly attributable to translational control, post translation modification, or protein turnover. When examining how osmotic-stress-induced changes in specific transcript–protein pairs correlate (Figs. 3a, 3c, and Supplementary Fig. 2), we observe a strong correlation in Mesotaenium (R = 0.63) and a moderate correlation in Zygnema (R = 0.39). The correlations improve on average by 1.8x when using 25h protein samples compared to 6h samples, a difference that exceeds the variability observed across transcript timepoints (maximum 1.2x). In this study, conserved stress responders such as AKR (both species), ELIP (Mesotaenium), and heat shock proteins (HSP, Zygnema) exhibited the strongest correlations, suggesting that their increased abundances result primarily from direct translation of elevated transcripts. For both species, several FAS1 proteins displayed a reversed pattern: higher protein abundance under hyperosmotic stress conditions but lower transcript levels. This pattern was also observed for the photosystem II subunit S (PsbS, Mesotaenium), ribosomal protein S5B (RPS5B, Zygnema) and expansin (Zygnema), suggesting the involvement of post-transcriptional regulatory mechanisms.

Examining the same data from a different perspective, we compared absolute transcript and protein levels (Figs. 3b, 3d, and Supplementary Fig. 2), finding a moderate correlation for Zygnema (R ≥ 0.34), except under mannitol treatment at 25h, which suggests the potential involvement of post-transcriptional regulatory mechanisms. For Mesotaenium, the initial correlation between absolute protein and transcript levels was overall poor (R ≤ 0.28). Upon further examination, we found that many proteins with high abundance but unexpectedly low transcript levels are encoded on extremely small contigs (<4096 bp) or the plastome. Excluding genes located on small contigs significantly improves the correlation (P = 0.00026), surpassing that observed in Zygnema. In the following, we worked with integrating the consistent changes for specific protein-coding genes and proteins, detected via RNAseq and proteomics, to glean the molecular cell biological mechanisms that zygnematophytes use for acclimation to osmotic challenge.

Temporal clustering unveils conserved osmotic stress responses
To delve deeper into the biological significance of the proteomic and transcriptomic datasets, we first divided the proteomic dataset into quadrants (Fig. 4a, Methods). Functional enrichment analysis yielded results consistent with the manual annotation performed for the statistically relevant genes. To cluster the substantially larger transcriptomic dataset we grouped temporal patterns for each transcript while retaining the distinctions between the treatment conditions. Temporal patterns were first grouped using a Gaussian Mixture Model (GMM) clustering; groups were normalized and further clustered using the same algorithm to reduce complexity. This approach resulted in 12 and 9 temporal modules for Mesotaenium and Zygnema, respectively, which were then subjected to functional enrichment analysis (Fig. 4b). In Mesotaenium, most modules exhibited a control pattern that remained consistently flat. Conversely, in Zygnema, transcript levels in the control treatment fluctuated markedly over time. Interestingly, in Zygnema, the temporal patterns of the salt treatment often appeared intermediate between those of the control and mannitol treatments. For Mesotaenium, the largest modules displayed similar response patterns for both mannitol and salt treatments, albeit with slightly faster responses observed in the salt treatment. Yet, the smaller modules also revealed treatment-specific responses unique to the mannitol and salt conditions.

A total of 670 and 320 enriched terms (p < 0.01) were identified for Mesotaenium and Zygnema, respectively. Intersection network analysis (Fig. 5) revealed several highly connected terms, including oxidoreductase activity, membrane, and chlorophyll binding. These terms are functionally broad and are represented by both upregulated and downregulated proteins under osmotic stress. For instance, “chlorophyll binding” includes both Early Light-Induced Proteins (ELIPs), commonly stress-inducible53, and classical Light-Harvesting Complexes (LHCs).

The two most interconnected modules are Module 9 of Mesotaenium and Module 7 of Zygnema. Both modules exhibit an upregulated pattern under osmotic stress (Fig. 4b), suggesting a conserved osmotic stress response within the Zygnematophyceae. The uniquely shared terms within these modules are represented in both Mesotaenium and Zygnema by autoinhibited plasma membrane proton (H⁺) ATPases (AHA), sucrose synthase (SuSy), tonoplast intrinsic protein (TIP), and synaptotagmin (SYT). The AHA proteins are responsible for generating an electrochemical proton gradient across the plasma membrane, a crucial process for pH regulation and transport across the membrane54. Sucrose synthase catalyzes the reversible reaction converting sucrose into fructose and UDP-glucose, playing a vital role in energy metabolism, osmolyte production, and complex carbohydrate biosynthesis55. TIPs are aquaporins located in the tonoplast—the vacuolar membrane—that facilitate the transport of water and small solutes across this membrane56. SYTs are membrane-associated proteins with an N-terminal domain located in a membrane, e.g. the AtSYT1 is located in the ER-membrane; their C-terminal domain binds to other membranes, enabling them to bring membranes together, organize membrane structure, and facilitate lipid transfer57.

Several terms merit closer examination, particularly two that exhibit opposing regulation under osmotic stress in Mesotaenium and Zygnema: the Hsp20 domain and 2Fe-2S-binding. These terms encompass multiple proteins, but in both Mesotaenium and Zygnema, they include Heat Shock Protein Family 20 (Hsp20) and the Rieske iron-sulfur protein PetC, respectively. Hsp20 is a small heat shock protein with a protective role, while PetC, part of the cytochrome b6/f complex, is crucial for electron transport in photosynthesis. Both proteins are involved in stress response mechanisms: Hsp20 prevents the aggregation of proteins and lipids58, while PetC contributes to photosynthetic redox control59. In our experimental setup, Zygnema predominantly relies on the Hsp20 family, whereas Mesotaenium utilizes PetC, reflecting distinct strategies to cope with osmotic stress.

We attempted to predict Gene Regulatory Networks (GRNs) from temporal transcriptional data using Sliding Window Inference for Network Generation (SWING; supplementary Fig. 3). While the GRNs were not conclusive (likely due to lack of additional and earlier time points), examination of differentially expressed transcripts revealed various signaling components. For instance, the ABA-responsive Element Binding Factor (ABF) was strongly upregulated in both Zygnema and Mesotaenium (Supplementary Fig. 4).

Conserved feedback at the cell wall under osmotic and ionic stress
The cell wall is the first barrier of a plant cell. Plants sense the integrity of their cell wall during growth and stress through mechanisms that concertedly maintain cell wall integrity (CWI)60. In previous work, we found that homologs that could constitute a CWI sensing and signaling loop co-express in Mesotaenium12,15. Our combined proteomic and transcriptomic data point to several layers of such biophysical feedback, integrating homeostasis of the cell wall into the overall response (Fig. 5).

Cell wall remodeling is key during acclimation to osmotic challenges61. Several cell wall-associated proteins were highlighted in the overlap between both species, including expansins, xyloglucan metabolism and more (Fig. 5). Zygnematophytes are rich in glycosyl hydrolases (GH) akin to land plants10. We screened the proteome (FDR < 0.05) and transcriptome (FC > 3) for increases in GHs. While a cellulase (GH5) was identified in the proteome, its increase was relatively modest. The most pronounced increases were observed in the XTHs and enzymes involved in starch degradation, whose transcript were upregulated in the NaCl treatment and the mannitol treatment. To follow upon this, we used LC-MS-based metabolite fingerprinting on Mesotaenium and identified a small set of robust features that significantly differed between treatments (Fig. 6a, Supplementary Fig. 5). These features were classified into three main categories: (1) Mannitol, which was expectedly abundant in the mannitol treatment and not detected in the other samples. (2) Sodium formate, a known artifact resulting from the addition of NaCl to biological samples62. (3) Carbohydrates build from aldo/keto-hexoses, predominantly detected with sodium adducts in the NaCl treatment. Among the carbohydrate-associated features, several were identified as corresponding to a disaccharide, a trisaccharide, a tetrasaccharide, and a pentasaccharide eluted in the same retention time range. When scanning specifically for glycosides in negative ion mode, several features showed a marked increase in intensity following hyperosmotic treatment. This suggests that Mesotaenium may utilize glycosides, such as sucrose or maltose, as osmolytes. Interestingly, the feature corresponding best to proline, often seen as osmolyte in plants63, did not exhibit any increase upon osmotic treatment, nor were the homologs to the proline biosynthetic proteins P5CS1 and P5CR or the proline transporter BAC2 upregulated.

In the differential abundance analysis, we noted an upregulation of cell wall-situated proteins, including the aforementioned XTHs and cell wall-associated (predicted) proteins containing a fasciclin-like (FAS1) domain. XTH is a well-characterized enzyme belonging to the GH family 16, which remodels xyloglucan chains. XTH has been frequently reported to be strongly upregulated in response to osmotic stress in land plants64, assumingly contributing to cell wall strengthening and thereby indirectly preventing water loss65. We constructed a phylogenetic framework encompassing all glycosyl hydrolases from GH family 16 (Fig. 6f) and recovered the XTHs (GH16, subfamily 20) exclusively for Embryophyta and Zygnematophyceae—not in any other streptophyte or chlorophyte algae; in Coleochaetophyceae, some proteins were initially annotated as GH16 subfamily 20 using dbCAN3 but were phylogenetically closer to those of subfamily 27. The XTHs from Embryophyta and Zygnematophyceae each form distinct monophyletic groups, in case of the latter further divided into two deep clades (Fig. 6f). Notably, all XTHs responsive to osmotic stress clustered within the same clade.

The FAS1 domain is a conserved structural motif found in extracellular proteins across diverse life forms, with a notable prevalence in plants. This domain provides multiple interaction surfaces, facilitating binding to a variety of ligands. In plants, FAS1 domains occur almost exclusively in the form of fasciclin-like arabinogalactan-proteins (FLA)66. Their precise biochemical mechanism is obscure but likely includes interaction and signaling processes within the extracellular matrix67. FLAs are a subgroup of the highly O-glycosylated plant glycoproteins called arabinogalactan-proteins (AGPs)68. They contain one or two (or more) FAS1 domains as well as glycosylated and non-glycosylated intrinsically disordered regions69. We examined our significantly differentially abundant proteins for potential AG glycosylation sites and identified one FLA in Zygnema, two FLAs in Mesotaenium, as well as one pectin methylesterase with potential AG glycosylation sites (Fig. 6c). All can be defined as chimeric AGPs, consisting of a functional, structured protein domain and disordered regions70. To investigate the influence of osmotic stress on AGP glycosylation, we analyzed cellular extracts from different treatments using the β-Yariv reagent and various AGP-specific antibodies. In Mesotaenium, radial diffusion assays indicated an increase in the galactose backbone of AGPs under salt and mannitol treatments compared to the control (Fig. 6d). Conversely, the two AGP-specific antibodies71,72 KM1 and JIM13 showed signal decrease in both treatments (Fig. 6d). Both treatments showed significantly elevated levels of hydroxyproline (Hyp) per glycan (Supplementary Fig. 6) corresponding to a more condensed glycan structure with reduced side-chain length while the overall galactose content remains relatively stable. The β-Yariv reagent did not stain Zygnema extracts (Fig. 6b), possibly due to differences in AGP glycosylation structure with higher levels of uronic acids (Fig. 6d, Supplementary Fig. 6). Nonetheless, trends in the KM1 antibody results in Zygnema were similar to those in Mesotaenium. The discrepancy in signals from the backbone and side chains under osmotic stress suggests alterations at the post-translational level. We further scanned upregulated transcripts for glycosyl hydrolases that might hydrolyze AGP side chains. This analysis proved challenging due to the limited functional characterization of many glycosyl hydrolases and the incomplete understanding of AGP glycosylation structure in the investigated algae73. Among the identified candidates, GH30—a galactosidase74—was upregulated in both species. However, these proteins lacked signal peptides, complicating their functional interpretation.

We stained live Mesotaenium with β-Yariv reagent after 25h of stress treatment (Fig. 6e, Supplementary Fig. 7). Substantially more staining was observed inside the cells subjected to mannitol treatment. However, when staining with an unrelated dye, fuchsin red, we also noted an increase in intracellular staining, suggesting higher cell membrane permeability in general (Supplementary Fig. 7). This could be attributed to a hypotonic shock following the stress treatment. In contrast, during salt treatment, we frequently observed staining of extracellular material, indicating the release of AGPs into the extracellular space (Fig. 6e). This phenomenon of AGP release has previously been documented in tobacco75,76. It was hypothesized that phospholipase C could cleave the glycosylphosphatidylinositol (GPI) anchor of FLAs, thereby releasing them into the extracellular space76. However, in our experiments, especially the smaller FLA isoform lacking a GPI anchor was significantly upregulated in protein abundance under salt treatment and simultaneously downregulated at the transcriptional level. Additionally, none of the predicted phospholipase C genes were upregulated, making this mechanism unlikely. To further investigate, we analyzed two modules of transcripts that were strongly upregulated exclusively during salt treatment, Module 3 and Module 10 (Fig. 4), likely reflecting the ionic-specific stress response in Mesotaenium. The modules contained some genes related to photosynthesis, many uncharacterized proteins, and pectin methylesterases (PMEs) alongside a PME inhibitor. PMEs are enzymes that demethylate galacturonic acid residues, a key component of the pectin backbone in plant cell walls. Random demethylation loosens the pectin structure, enhancing enzymatic degradation while block-wise demethylation exposes free carboxyl groups on galacturonic acid residues, which can then crosslink with calcium ions to form a gel-like, compact pectin structure77. The PME in Mesotaenium predicted to have AG sites shares its closest Arabidopsis homolog with PME53, and thus likely removes methyl groups in a random manner78.

Both pectin and AG groups exhibit a strong affinity for binding calcium ions. However, sodium ions, introduced in large quantities during NaCl treatment, can compete with calcium for these binding sites79. This competition can disrupt the calcium-mediated crosslinks between pectin molecules, potentially resulting in cell wall softening and destabilization80. During long-term (>26 days) NaCl treatment, we observed significant deterioration of the cell walls in Zygnema (Fig. 6b). While the algae survived, no growth was recorded under these conditions. In contrast, Mesotaenium showed remarkable resilience: it remained healthy, maintained active growth, and preserved chloroplasts with a proper shape and vibrant green pigmentation. Notably, some differences were observed compared to the control treatment, including the formation of short filaments up to eight cells in length and an increased accumulation of cell wall remnants (see Fig. 6b and Supplementary Fig. 8).

Overall, our data pinpoint deeply conserved proteins that zygnematophyte cells use in homeostatic mechanisms—that include cell wall remodeling—to successfully acclimate to osmotic stress (Fig. 7).

Methods
Cultivation of the algae
Mesotaenium endlicherianum SAG 12.97 and Zygnema circumcarinatum SAG 698-1b were sourced from the Culture Collection of Algae at Göttingen University (SAG). They were cultivated on cellophane disks90, with the modification that Mesotaenium was grown on 1.5% agar-solidified C medium110 for a total of 8 days at 60-80 μmol photons m−2s−1 and Zygnema was grown on 1% agar-solidified WHM medium (MZCH recipe) for a total of 14 days at 15-20 μmol photons m−2s−1.

Stress treatments
The stress treatments were performed under the same conditions as the algae cultivation. After two hours of light exposure within their 16/8h light-dark cycle, the algae cultures were transferred to a sterile workbench. Within a maximum of 15 minutes—during which minor fluctuations in light, temperature, and humidity could occur—the cellophane disks with algae were placed onto fresh plates containing the same medium used for cultivation, supplemented with either no additive (control), 0.15 M NaCl, or 0.8 M D-mannitol. For the C-medium and WHM medium, respectively, this resulted in osmolarities of 0.015 Osm/L and 0.018 Osm/L for the control medium, 0.315 Osm/L and 0.318 Osm/L for the salt medium, and 0.815 Osm/L and 0.818 Osm/L for the mannitol medium, with the contribution of agar (which consists of long polymers) to the total osmolarity neglected. The treated algae were then returned to the cultivation chamber to resume growth.

Physiological measurements
At 0, 3, 6, 9, and 25 hours during the stress treatments, algae samples were incubated in the dark for 20 ± 5 minutes. Each sample was then placed on the sensor of the Walz PAM-210 Chlorophyll Fluorometer, and the maximum quantum yield of PSII (Fv/Fm) was measured. The following instrument settings were used: ML=6, AL=3, FR=8, and SP=10. For each biological replicate, two technical replicates were measured, and the mean Fv/Fm value was recorded. Algal samples used for PAM measurements were excluded from further stress experiments to prevent potential measurement interference.

Microscopy
At 25 hours, algae samples were transferred to a liquid medium, and microscopic images were immediately captured using a Zeiss Axioscope 7 light microscope at 400× magnification. For Mesotaenium, individual cells were counted, while for Zygnema, individual filaments were enumerated. Additionally, the presence or absence of specific traits was recorded. For each trait, the percentage of cells or filaments exhibiting the trait was calculated per biological replicate. Detailed definitions of all traits, along with the number of cells or filaments analyzed, are provided in the Source Data.

For microscopical analysis using the β-Yariv reagent, treated algae (control, 0.15 M NaCl, or 0.8 M D-mannitol) were returned to the growth chamber and incubated for 25 hours. Staining was performed with β-Yariv reagent and 0.05–1% Fuchsin stain, the latter serving as a control for nonspecific staining. Algae were then incubated with 100–200 µM β-Yariv dissolved in C-medium for 10 minutes. Imaging was conducted as described above. To ensure direct comparison, images of each biological replicate were acquired in a staggered manner over approximately 10 minutes. For quantification, additional imaging was carried out for up to 2 hours, with treatments observed for about 3 minutes each. A total of 176 photos were captured, and extracellular staining was quantified by assessing the presence or absence of red-brown staining of extracellular material in each image (see Source Data).

Measurements of AGPs, sugar, and weight
After 25 hours of stress treatment, eight technical replicates (equals eight petri dishes) were collected into Eppendorf tubes (making one biological bulk replicate) and immediately frozen in liquid nitrogen. The samples were then lyophilized using a VaCo 2 Zirbus lyophilizer at −80°C. The weight of each Eppendorf tube was recorded at three stages: empty, with the frozen sample, and with the lyophilized sample. Two biological bulk replicates were used for analyses. The lyophilized samples were ground with a beat-mill (VWR Star-Beater, VWR International, UK) and pre-extracted two times (2 h and 21 h, respectively) with acetone:water (70:30, v/v) in a ratio of 1:100 (v/v) at 4°C on a shaker. Afterwards, the samples were extracted with double-distilled water for 21 h at 4°C on a shaker. In between all extraction steps, the supernatant was separated from the pellet by centrifugation at 19,000 × g, 20 min, 4°C (Heraeus Multifuge X3R, Thermo Fisher Scientific Corp., USA). The resulting aqueous extract was lyophilized (Christ Alpha 1-4 LSC, Martin Christ GmbH, Germany) and afterwards dissolved at a concentration of 10 mg/ml under homogenization in the beat-mill (VWR Star-Beater, VWR International, UK, 10 Hz, 1 h with a metal beat). All following experiments were performed with aliquots of this solution.

Total sugar and uronic acid contents were determined colorimetrically by the protocols of Dubois et al.111 and Blumenkrantz and Asboe-Hansen112, respectively. Radial gel diffusion assay for interaction of samples with β-D-glucosyl-Yariv (β-D-GlcY) reagent was performed by using the protocol of Castilleux et al.113 with modifications. In brief, 20 µl of the aqueous extracts were loaded into cavities of an agarose gel containing 0.25 mol/l NaCl and 10 µg/ml β-D-GlcY. Gum arabic solutions in different concentrations (1.0, 0.5, 0.25, 0.125, 0.063 mg/ml in double-distilled water) were used as controls. Hydroxyproline content was determined by colorimetric quantification using the protocol of Stegemann and Stalder114. Reactivity of aqueous extracts with the monoclonal antibodies KM1, LM2, LM6, and JIM13 was determined by enzyme-linked immunosorbent assays following the workflow of Mueller et al.115. Neutral monosaccharide composition was determined the derivatization of Blakeney et al.116 with modifications (see Mueller et al.115). To determine mannitol content, the hydrolysis and reduction steps of the derivatization were omitted. All experiments were performed in three technical replicates per biological bulk replicate.

Transcriptomics
At 0, 3, 6, 9, and 25 hours, algae samples were collected and immediately frozen in liquid nitrogen, followed by storage at −70°C. For each timepoint and biological replicate (5 replicates in total), two halves of a culture plate were sampled using a spatula, pooled into an Eppendorf tube, and frozen in liquid nitrogen. The remaining plate halves were reserved for proteomics or metabolomics analyses. RNA was extracted using the Spectrum™ Plant Total RNA Kit following the supplemented protocol A, with modifications made to the cell lysis step: Zygnema samples were lyophilized for 48 hours, then ground using a Retch mill at 20 Hz for 1 minute. One milliliter of lysis buffer was added to the ground, dried samples, which were vortexed for 40 seconds and heated at 56°C for 5 minutes. Mesotaenium samples were placed in 500 µL of lysis buffer, vortexed for 30 seconds, sonicated in a DK SONIC™ ultrasonic cleaner, and heated at 56°C for 5 minutes. Following lysis, DNase treatment with DNase I was performed. For Zygnema, this step was carried out directly on the binding column, while for Mesotaenium, it was performed post-elution of the binding column. RNA sequencing, as well as quality control and raw data trimming, were conducted according to the methods detailed in Dadras et al.15. The sample “salt_9hours_BR2” from Zygnema was excluded from further analysis due to a low read count (<0.1 million reads). Trimmed reads were mapped to the transcriptome (see section Transcript-Based Proteome Assembly for details) using Kallisto with bootstrap-samples set to 100. Quantified reads were adjusted in Sleuth to account for technical variability in transcript quantification, and the transcripts per million (TPM) values were subsequently exported. Within the Sleuth visualization environment, the distribution of TPM values was examined. Based on this analysis, the sample “mannitol_3hours_BR3” from Mesotaenium was excluded from further analysis due to an abnormal TPM distribution. Transcripts were filtered based on abundance thresholds to ensure data quality. Transcripts where a single sample had a TPM value below 2−6 and the average abundance across all samples was less than 2 TPM were removed. Additionally, transcripts with more than five values below 2−6 and an average abundance across all samples below 4 TPM were excluded from the dataset. Remaining TPM values below 2−6 were set to 2−6. All TPM values were log-transformed prior to further analysis to normalize the data.

Proteomics
Proteomics analysis was performed on the transcriptomics-paired samples from Mesotaenium (0, 6, and 25 hours) and Zygnema (6 and 25 hours). Protein extraction followed an adapted version of the methods of Niu et al.117, with species-specific protocols. For extraction, each sample was homogenized in extraction buffer (Mesotaenium buffer: 1 mL/sample, 50 mM Tris-HCl, pH 7.5, 10 mM KCl, 0.2 mM PMSF; Zygnema buffer: 1.5 mL/sample, 1% SDS, 0.1 M Tris-HCl, pH 6.8, 2 mM EDTA-Na₂, 20 mM DTT, 2 mM PMSF). Samples were ground in a Ten Broek grinder on ice for 1 minute (Mesotaenium) or 4 minutes (Zygnema), transferred to clean 1.5 mL eppendorf tubes, and centrifuged (Mesotaenium: 1000 × g for 10 seconds; Zygnema: 10,400 × g at 4°C for 7 minutes). The supernatant was then processed further. For precipitation, 100 µL (Mesotaenium) or 2 × 200 µL (Zygnema) of supernatant was added to 1 mL of pre-cooled ethanol (Mesotaenium) or acetone with 5 mM DTT (Zygnema), briefly vortexed, and incubated overnight at 4°C (Mesotaenium) or −20°C (Zygnema). After precipitation, samples were centrifuged (Mesotaenium: 2000 × g at 4°C for 15 minutes; Zygnema: 5000 × g at 4°C for 10 minutes) and the supernatant discarded. The pellets were washed twice with pre-cooled ethanol (Mesotaenium) or acetone with 5 mM DTT (Zygnema). Mesotaenium samples were dried in a speed-vac at 50°C for 30 minutes, while Zygnema samples were air-dried for 5–8 minutes. The pellets were dissolved in either 30 µL of 5% SDS with 6 M urea (Mesotaenium) or 100 µL of the extraction buffer (Zygnema). Protein concentration was determined using a 20× dilution of the protein solution in water and the Thermo Scientific™ Pierce™ BCA Protein Assay Kit. We noticed that the Zygnema protocol, particularly the acetone-based precipitation, also performed slightly better for Mesotaenium compared to ethanol precipitation.

Protein samples (50 µg) were loaded onto 12% polyacrylamide SDS-PAGE gels (1 mm thickness) and electrophoresed at 100 V using a Bio-Rad™ Mini-PROTEAN® 3 Cell system. The gels were run until the dye front had migrated approximately 1.8 mm into the separation gel. Following electrophoresis, gels were briefly rinsed with distilled water and incubated for 60 minutes in a fixation solution containing 40% (v/v) ethanol and 10% (v/v) acetic acid. For staining, gels were immersed in Coomassie Brilliant Blue stain (0.1% (w/v) Coomassie Brilliant Blue G-250, 5% (w/v) aluminum sulfate-(14–18)-hydrate, 10% (v/v) ethanol, and 2% (v/v) ortho-phosphoric acid) for 30 minutes. Excess stain was removed by washing the gels three times with distilled water for 10 minutes per wash. All staining and washing steps were performed on a rocking platform. Protein-containing gel pieces were excised using a scalpel and subjected to an overnight wash in fixation solution, followed by three additional washes with distilled water (10 minutes each) on a rotating platform. Proteins were subsequently digested and peptides extracted in-gel according to the method described by Shevchenko et al.118. Peptides were then desalted, and LC-MS/MS analysis was performed as described in the methods of Niemeyer et al.119.

For initial quality control of the acquired LC-MS/MS data, the raw files were converted to mzML format using MSconvert with the Peak Picking algorithm. Two-dimensional LC-MS chromatograms were plotted in MSnbase to identify abnormalities in the spectra. Based on this assessment, the sample “mannitol_25hours_BR3” from Zygnema and the samples “mannitol_25hours_BR1” and “0hours_BR2” from Mesotaenium were excluded from further analysis. Subsequently, the raw files were analyzed using MaxQuant with mono on a high-performance computing cluster. Quality reports were generated with the R package PTXQC in two consecutive runs. The first MaxQuant analysis aimed to identify batch effects and discover novel protein groups (details provided in the “Transcript-Based Proteome Assembly” section and a schematic overview of the data-analysis in Supplementary Fig. 9). During this analysis, it was observed that the variation of Mesotaenium samples in the PCA was more strongly influenced by batch effects than by the experimental treatment. As a result, samples from Mesotaenium originating from two SDS-PAGE gels were excluded from the second run. For the second MaxQuant run, the updated FASTA database was employed, and LFQ as well as iBAQ values were calculated. The LFQ values were imported into Perseus for further processing. These values were divided into three distinct matrices: 1) A matrix for the 6-hour timepoint (used for 6-hour differential expression analysis). 2) A matrix for the 25-hour timepoint (used for 25-hour differential expression analysis). 3) A comprehensive matrix containing all samples (used for PCA analysis). Within each matrix, protein groups in which all conditions contained ≥1 missing value were excluded. For the remaining missing values, imputation was performed using random sampling from a normal distribution (downshift = 1.9, width = 0.3). The resulting imputed data were utilized for differential abundance analysis, relative protein-RNA comparison, and functional enrichment analysis. The iBAQ values, in contrast, were not processed in Perseus. Instead, they were directly used for absolute protein-RNA comparisons.

Metabolomics
The transcriptomics-paired samples from Mesotaenium (3 and 9 hours) were lyophilized using a VaCo 2 Zirbus lyophilizer at −80°C. The dry mass of each sample was adjusted to 9–11 mg per technical replicate. Two types of metabolite extracts were prepared for subsequent LC-MS analysis: methanol-based extracts and lipid extracts. For the methanol-based extracts, 1 mL of 70% (v/v) methanol (pre-cooled to 8°C) was added to the lyophilized, ground samples. The samples were ultrasonicated twice, each for 15 minutes. Following ultrasonication, the samples were centrifuged at 16,000 × g for 20 minutes at 4°C. From the resulting supernatant, 200 µL was transferred to a vial containing an insert. The extracts were dried using a SpeedVac concentrator and reconstituted sequentially: first in 20 µL of 100% methanol, followed by 40 µL of H₂O, with vortexing after each addition. The reconstituted extracts were stored at 4°C until LC-MS analysis. For the lipid extractions, 600 µL of tert-butyl methyl ether (MTBE):methanol (2:1, v/v) was added per 10 mg of lyophilized, ground sample. The mixture was vortexed and then sonicated for 15 minutes. After adding 100 µL of H₂O, the samples were vortexed again and centrifuged at 14,000 × g for 20 minutes at 4°C. From the upper (MTBE) phase, 200 µL was transferred to a vial containing an insert and dried using a nitrogen evaporator. The dried extracts were reconstituted by adding 40 µL of methanol, followed by 10 µL of H₂O, with vortexing after each addition. Extracts were analyzed by LC QTOF MS as described in Kasper et al.120. The raw Agilent “.d” data files were converted to “.mzML” format using MSConvert with the Peak Picking algorithm applied. The resulting “.mzML” files were processed in MZmine 4 through the following sequential steps: (1) Mass Detection: Initial detection of mass-to-charge (m/z) values, (2) Chromatogram Builder: Construction of chromatograms based on m/z values and retention time. (3) Local Minimum Feature Resolver: Refinement of chromatographic peaks to resolve overlapping features. (4) Join Aligner: Alignment of features across samples to account for retention time shifts. (5) Feature Filtering: Retention of features based on minimal intensity thresholds and presence in a minimum number of samples. (6) Gap Filling: Use of the Peak Finder algorithm to fill gaps in feature matrices where peaks were not initially detected. The identified features were exported and imported into Perseus for statistical analysis. Within Perseus, the data were log-transformed, missing values were imputed from a normal distribution (width = 0.3, downshift = 1.8) or with the constant value of 1000 when combining features from both ion modes, and an ANOVA test with FDR-correction was conducted to identify statistically significant differences between groups (see Supplementary Data 4). Additionally, auto MSMS files where available, were integrated into the MZmine analysis to match fragmentation spectra with their corresponding features. However, their quantification data were excluded from the statistical analysis in Perseus.

Transcript-based proteome assembly
A transcriptome for both Zygnema and Mesotaenium was assembled using Trinity, incorporating the samples “mannitol_9hours_BR1,” “salt_3hours_BR4,” and “salt_25hours_BR5.” The quality-trimming parameters, adapter sequences, and settings applied during trimming were consistent with those used in Trimmomatic during the regular transcriptomics analysis. Subsequently, Kallisto was employed to quantify the read counts for the newly assembled transcriptome across the aforementioned samples. Transcripts with read counts below 2 TPM for Mesotaenium and below 3 TPM for Zygnema were excluded from the transcriptome (see Supplementary Data 5 for assembled transcriptomes). Coding sequences were then identified using TransDecoder with default settings. For Mesotaenium, the --complete_orfs_only flag was applied, ensuring only complete open reading frames were included. This setting was unintentionally omitted for Zygnema, leading to the grouping of incomplete translations with their corresponding complete transcripts for gene ontology (GO) enrichment analysis. The inferred proteome was analyzed using MaxQuant, incorporating .raw files from test runs and samples disqualified due to batch effects. This analysis was performed with the following existing protein databases: Mesotaenium assembly version 1 with annotation version 2 gene models15 and Mesotaenium chloroplast-encoded proteins121 for Mesotaenium, and Zygnema circumcarinatum SAG 698-1b (the exact strain used for experimentation) gene model10 and UTEX 1559 (a strain relative) plastome122 for Zygnema. Only protein groups with at least one unique peptide and a Q-value of 0 were retained. Protein groups exclusively originating from the newly transcriptome-based proteome were incorporated into the standard proteome to generate an updated database. This database was subsequently assessed for completeness and quality using BUSCO with the l_viridiplantae_odb10 dataset.

Downstream analysis of protein and transcript data: differential abundance analysis
The log2 fold changes of the processed LFQ values were calculated for mannitol-treated samples versus control samples and NaCl-treated samples versus control samples. These calculations were performed for both the 6-hour and 25-hour timepoints. The data were visualized using the ggplot package in R, with points color-coded by p-values. P-values were computed per matrix in Perseus using an ANOVA test with parameters S0 = 0.15 and permutation-based FDR = 0.05 to determine significance. Significant protein groups were manually annotated using blastp (default settings, databases nr and SwissProt), domain annotations from SMART, and, where necessary, results from TargetP, dbCAN3, and NetGPI. For the filtered TPM values, log2 fold changes were computed for each combination of NaCl-treated and mannitol-treated time points relative to their respective controls. Statistical analysis was conducted using Python’s scipy.stats and statsmodels packages, where one-way ANOVA tests were performed, followed by FDR correction using a multitest adjustment. These data were visualized similarly to the LFQ results, but with the Seaborn package in Python.

Downstream analysis of protein and transcript data: comparative analysis
Transcript and corresponding protein levels were compared using both relative and absolute approaches. For the relative comparison, the computed log2 fold changes for LFQ and TPM values from the differential abundance analysis were directly plotted against each other without further processing. Additionally, log2 fold changes of the integrated TPM levels for all transcripts were calculated for each treatment-control pair and plotted against the log2 fold changes for LFQ values as well.

For the absolute comparison, transcript and protein group levels were compared on a sample-by-sample basis. This was feasible as the RNA sequencing and shotgun proteomics were performed on the same biological samples. Biological replicates were analyzed individually without grouping. Protein levels were quantified using iBAQ values, which were ranked within each sample, with a rank of 1 assigned to the most abundant protein group. The TPM levels were ranked in the same way. The ranks of the protein groups were then matched with the ranks of their corresponding transcripts, and the relationships were visualized using the R package ggplot2. In cases where a protein group corresponded to multiple transcripts, the transcript with the highest abundance was selected for comparison. For the Mesotaenium dataset, each protein-transcript pair was further annotated by coloring points according to contig length from the genome8.

Downstream analysis of protein and transcript data: functional enrichment
InterProScan123 results published in Rieseberg et al.14 were utilized for Gene Ontology (GO) term and InterPro domain annotation. Newly identified transcripts were also annotated using InterProScan. For the functional enrichment analysis at the protein level, the data from the 6-hour and 25-hour timepoints were merged. Proteins were grouped into nine quadrants based on their log2 fold change (log2FC), using thresholds of 1 and −1. These protein groups were then mapped back to the gene level, and functional enrichment was performed for all quadrants except the central one (where |log2FC| < 1). The analysis was conducted using FuncE with an e-value cutoff of < 0.01.

To analyze transcript functional enrichment, a time-dependent clustering approach was employed. Log2 fold changes were computed for each treatment-timepoint combination relative to timepoint 0. Transcripts were filtered based on criteria: max(tpm) > 5, max(log2 fold change) > 1, and adjusted p-value < 0.01. The filtered log2 fold changes were clustered using a Gaussian Mixture Model (GMM) implemented in Python’s Scikit-learn library (sklearn.mixture.GaussianMixture). To determine the optimal number of clusters, the Bayes Information criterion (BIC) were calculated for models with 1 to 100 clusters, and the configuration with the lowest BIC score was selected. Transcripts were then grouped into temporal patterns based on the selected number of clusters (see Supplementary Fig. 10). Next, these patterns were normalized, and the clustering process was refined with GMM. Starting with 15 clusters, the number was progressively reduced until two seemingly distinct patterns were emerged, indicating the final grouping. These final transcript groups, referred to as modules, were mapped back to their corresponding genes. Functional enrichment analysis of these gene modules was performed using FUNC-E with an e-value cutoff of < 0.01.

An overview was created of enriched terms showing overlap between transcript modules and/or protein quadrants from Zygnema and/or Mesotaenium (see Zenodo). Terms associated with only a single gene were excluded, as were terms with 100% gene overlap. In cases of identical overlap, the term with the best p-value was retained; if p-values were equal, one term was selected at random. The resulting list of terms was visualized as a network using the igraph package in R.

Phylogenetic analysis XTH
The protein data for 16 embryophytes, 11 streptophyte algae, and 8 chlorophytes, building on the dataset used in de Vries et al.124, were combined into a single database, incorporating the updated Mesotaenium gene model15. CAZyme families were identified using dbCAN3 with default settings. Based on results from the HMMer search, proteins identified and annotated as Glycosyl Hydrolase family 16 (GH16) or any of its subfamilies were selected for phylogenetic analysis. The selected protein sequences were aligned using MAFFT125 with the L-INS-i algorithm. From these aligned sequences, a maximum likelihood phylogenetic tree was constructed using IQ-Tree126 with 1000 ultrafast bootstrap replicates127. Automatic model selection identified WAG+R9 as the best-fit model. The resulting phylogeny was visualized using iTOL128 (Supplementary Fig. 11).

Downstream analysis of transcript data: Gene Regulatory Network (GRN)
From the time-series transcriptomics data, a Gene Network Reconstruction (GNR) was constructed for each species and treatment individually using Sliding Window Inference for Network Generation (SWING). Log-transformed TPM values were utilized, and the data was filtered for transcripts with significant temporal variation (ANOVA, unadjusted p-value < 0.0001) across all timepoints (0, 3, 6, 9, and 25 hours). Edges were computed in SWING using the following parameters: k_min = 1, k_max = 3, window size (w) = 3, method = “RandomForest,” and trees = 500. To construct the GNRs, the top 0.1% of scoring edges were retained, consistent with the cut-off that proved effective in comparing streptophyte algal GRNs in light of evolution14. For the osmotic stress GNR of each species, common edges between the salt and mannitol time-series networks were retained, except for edges that were also present in the control time-series network. Unfortunately, no edges remained for constructing a network for either Zygnema or Mesotaenium.

Long term salt stress
For one Zygnema and one Mesotaenium plate, cellophane discs containing algae were transferred onto fresh plates with the same cultivation medium, supplemented with 0.15 M NaCl. These plates were then placed in a long-term storage cabinet under constant light conditions (light intensity ≈ 10 µE) and a temperature of 14°C. After 26 days, we examined the algal morphology using a Zeiss Axioscope 7 light microscope. In Zygnema, we observed deterioration of the cell wall, while in Mesotaenium, we noted the formation of short filaments (maximum observed length = 10 cells/filament). This prompted us to setup a growth experiment: The strains SAG 12.97 Mesotaenium endlicherianum and SAG 698-1b Zygnema circumcarinatum were cultivated on solid Warris-H medium under standard culture conditions (20°C, 30 µE, 14:10 L/D cycle). In the middle of log-phase after 14 days of growth, the algae were resuspended in 2 ml of liquid Warris-H medium containing 0.15 M NaCl. 300 µl of this suspension was placed on Petri dishes (Ø 9 cm) with solid Warris-H medium containing 0.15 M NaCl with and without sterile cellophane disks. The suspension was carefully spread out on the top of the agar surface with sterile Delta™ Disposable Cell Spreader (Merck, Darmstadt, Germany). The algae were grown for eight weeks. The microscopical control was performed every seven days. The Olympus BX-60 microscope (Olympus, Tokyo, Japan) equipped with camera Gryphax Prokyon and the software Gryphax ver. 2.2.0.1234 (both from Jenoptik, Jena, Germany) was used for taking microphotographs. The experiments were performed in three technical replicates.

Zygnema bleached out after 48 hours of exposure to the salt stress and was therefore excluded from further experiments. In contrast, Mesotaenium showed satisfied growth on medium containing salt. The number of short filaments were measured for all taken images; chains of loosely connected cells were counted as individual cells, while a continuous cell wall spanning multiple cells was required for a structure to be considered a filament.

Software list
The following software has been used: BLAST129 (v2.16.0), BUSCO130 (v5.4.3), dbCAN131 (v3), FASTQC132 (v0.11.9), FUNC-E133 (v2.0.1), ggplot2134 (v3.5.1), igraph135 (v2.0.3), imageJ136 (v1.54g), iqtree126 (v2.1.3), iTOL137 (v7), InterProScan123 (v5.72), Kallisto138 (v0.46.2), MAFFT125 (v7.304b), Maxqant139 (v2.4.14.0), MSconvert140 (v3), MSnbase141 (v2.28.1), MultiQC142 (v1.11), mzmine143 (v4.3.0), NetGPI144 (v1.1), Perseus145 (v2.1.1.0 and v2.0.7.0), PTXQC146 (v1.1.1), Python v3.9.7, Scikit-learn147 (0.24.2), R 4.3.2, scipy148 (v1.7.1), Seaborn149 (v0.13.2), Sleuth150 (v0.30), SMART151 (v9.0), Snakemake152 (v7.7.0), statsmodels 0.12.2, SWING153, TargetP154 (v2.0), TransDecoder155 (v5.7.1), Trinity156,157 (v2.15.1), trimmomatic158 (v0.36).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This paper compares response to osmotic stress in two forms of zygnematophyte cells in order to provide insight into the\nadaptation to terrestrial environments. The authors analyze transcriptomic, proteomic, and metabolic data at several\ntimepoints after exposed to osmotic stress in the form of salt and manitol. Changes in the cell wall were identified and follow\nup experiments performed to obtain further insight into the cell wall changes. I believe this is an important study of the\nevolution to land plants. to my knowledge, the methods used were appropriate.\nIn general, the manuscript is well written, but the figures are complex and need more information in the figure legends to\nimprove understanding. I recommend some minor changes to improve readability of the manuscript:\n1. Line 45, \"Here the focus was particularly on signaling cascades\". This is unclear because signal cascades were not\nmentioned in the manuscript and a sentence on line 46, \"Here, we focused\n47 on osmotic stress, the prime challenge on land.\" details a different focus.\n2. In Figure 1 it would be helpful to explicitly mention the meanings of each color, instead of the information only being in\none of the images. B and C should be switched in the figure description. Please explain what the P values are\ncorresponding to in the graphs.\n3. Line 133 and 135 should say figs 1D, 1E\n4. Should Line 123 say 1C only?\n5. I could use more information in the figure text on how to interpret 3a and 3b. What is the white line? What is negative\nrank?\n6. Fig 4 needs A and B labeled. Need more information on how to interpret the graphs. What are the red dotted lines?\n7. Can you separate figure 5 into A and B for better clarity?\n8. Figure 6D bottom, what are the units on the ELiSA measurements?\n9. Data accessibility: Line 812 Please specify that the RNAseq data has been deposited to NCBI. Line 813 Please clarify\nhow to access micrographs. Please make sure all the data is accessible upon publication. I was unable to find the\nproteomics and metabolomics data in their respective repositories.\n10. The discussion may benefit from a conclusion paragraph integrating a broader discussion on the evolution of algae to\nthe terrestrial habitat and how your results fit into that narrative.", "reviewer_2": "The study investigated the response of two algae, Mesotaenium and Zygnema, to osmotic stress. The algae were exposed\nto high concentrations of mannitol and NaCl to simulate osmotic stress. Both algae responded to osmotic stress by reducing\ntheir water content and undergoing plasmolysis, with Mesotaenium showing a more pronounced response. Proteomic and\ntranscriptomic analysis revealed a complex response to osmotic stress, with many proteins and transcripts changing in\nabundance.\nThe study found that both algae underwent cell wall remodeling in response to osmotic stress, with the up regulation of\ncell wall-associated proteins such as XTH and expansins. The cell wall of Mesotaenium became more compact and rigid, while\nthat of Zygnema became looser and more fragile. The study also found that Mesotaenium AGPs were released into\nthe extracellular space in response to osmotic stress. The study highlights the complex response of algae to osmotic stress,\nwith multiple layers of biophysical feedback mechanisms involved, and suggests that the response of algae to osmotic\nstress is highly conserved across species.\nThe manuscript presents important data of interest to a broad community, highlighting the conserved background present in\nextant zygnematophyte algae for abiotic stress resilience. As expected from this lab, the bioinformatic analyses are state of\nthe art and the figures and illustrations are of high quality.\nHowever, I am not entirely convinced that osmotic stress is the best model for abiotic stress during land colonization (as\nsomehow claimed in the introduction). It is easier to do than any desiccation stress, but much milder. That said, I still think\nthis is a very important contribution to the field and should be published. I have a few minor comments that the authors\nshould consider and address prior to publication.\nLine 47: Main challenge on land: I doubt that osmotic change is the main challenge on land. It is desiccation or drought,\nwhich has many similarities but also clear differences to osmotic stress, especially if you incubate with a salt! See also\nbelow.\nLine 49: Vascular plants are homoiohydric: Not all, e.g. resurrection plants, and seeds in general are also poikilohydric.\nVascular plants have just transferred desiccation tolerance to spores and seeds.\nLine 53: Waxy cuticle: As far as I know, this is really rare. I find water conducting tissues and stomata in sporophytes a better\nexample.\nLine 55: delves into poikilohyry: Reading this I would expect a desiccation-drought study, not osmolarity, see above!\nLine 79: on osmotic stress, thriving in habitats subject to frequent desiccation: Again, you are confusing osmotic stress and\ndesiccation stress. When a ditch in which Zygnema thrives dries out, there is a good chance that there will be initial osmotic\nstress due to increasing osmolarity, but I doubt that there will ever be anything like the 800 mM mannitol you used in your\nexperiments. When the water is gone, the real desiccation stress starts, which will cause much more water loss than osmotic\nstress. However, osmotic stress can acclimate the alga to desiccation stress. In desiccation you can always reach a YII of\nzero in PAM, which shows how much stronger the desiccation stress is!\nLine 106 to 108: Osmolarity of the media: The total osmolarity is slightly higher because you added 150 mM NaCl or 800 mM\nmannitol to the growth medium. Do you know the osmolarity of your media? Or did you change the media to 800 mM\nmannitol so that you have not only osmotic stress but also nutrient starvation!\nLine 115: Decreased in both algae: Not true for Zygnema and mannitol, if I interpret Fig. 1 A correctly.\nLine 118 - 119: never approached zero: confirms that osmotic stress is much milder than desiccation. When you desiccate,\nyou always reach zero!\nLine 133: structures induced by mannitol treatment Figure 1D visible tonoplast: I doubt that you can see a tonoplast\nmembrane in a light microscope. Be more precise! Better vacuolated. Many of the LM observations are not significant. And\nthe results are strange. For example, if you compare curved and cupped for Mesotaenium, I would have thought that both\nwould be insignificant. Why show all the insignificant results? For Mesotaenium 12 out of 16 comparisons are not\nsignificant P = 0.07 - 0.642! For Zygnema it is much better, but you show all the insignificant cell shapes for Mesotaenium,\nbut not all for Zygnema -\nLane 143: 9600 Zygnema tanscripts. This is a rather low value for Zygnema. The genome paper has 16,617 annotated\ngenes. Very often you have more transcripts than genes in RNASeq. I am not sure if the RNASeq data are reliable for\nZygnema.\nFig. 2 A: Why are there three PCAs for each species at the protein level? Give time points!!! This is not explained anywhere.\nIt is very difficult to see the differences for the treatments. And I think the differences at the protein level are much smaller\nthan at the RNA level. For the RNA Seq data, the effect arrows do not always show the correct direction of the effect. For\nexample, for the mannitol treatment and mesotaenium, the effect is clearly in the direction of the upper left corner, not\nvertical! Similarly, the effect vectors for Zygnema control and Salt are not correct.\nLine 145. Why did you assemble de novo? Genomes are available?\nLine 164: Difference in effect strength between protein and RNA. I do not see this. Also in the PCA (Fig. 2 A), I see a\nstronger effect for 25 h (darkest color). The most surprising result for me is that there is no variation in the control for\nmesotaenium and the longest salt treatment is again identical to the control! But these are not even mentioned in the text.\nMinor: The legneds for the figures should be improved. They should be understandable without text.", "reviewer_3": "The details surrounding the colonization of land by early embryophytes are poorly understood. These organisms likely\ninhabited a freshwater environment, perhaps with periodic desiccation, ultimately selecting for adaptations that would lead to\nthe colonization of dry land. Although osmotic stress responses in embryophytes are well studied, such responses are\npoorly characterized in zygnematophytes, the closest relatives of land plants. Understanding the modern biology of both the\nzygnematophytes and embryophytes is crucial to reconstructing the biology of their common ancestor. It has practical\nimplications as well, because plant stress causes substantial losses in agricultural productivity, and these losses are likely\nto increase as the climate changes. To better understand these stress responses, Zegers et al. characterized the osmotic\nstress responses of two zygnematophytes, Mesotaenium endlicherianum and Zygnema circumcarinatum, using\ntranscriptomic, proteomic, and metabolomic techniques. The authors provide evidence that some of the responses to\nosmotic stress utilized by modern-day embryophytes may also be present in some taxa of zygnematophytes.\nThe authors performed classic drought stress experiments on these zygnematophytes, echoing work that has been done on\nembryophytes. Their transcriptomic results show that both zygnematophytes display a rapid response to salt stress with\nadaptation to .15M NaCl after 25 hours. Mannitol treatment on the other hand showed a stronger response which suggests\nthese organisms have a much more difficult time adapting to the osmotic stress that mannitol causes. However, as the\nauthors state, Zygnema has a “temporally dynamic response in the control condition” which makes it difficult to draw any\nconclusions from that species’ given data.\nThis is emblematic of the fundamental problem with the manuscript: although the work is of high quality and the data will\nsignificantly contribute to the field, some analyses feel unmotivated or out of place. For example, the short discussion of the\nprincipal component analysis seemed disconnected from the discussion. What is the significance of movement in this\nfeature space over time? How should this be interpreted? Can the results be extended beyond the two organisms studied?\nIt is also unclear what conclusions, if any, can be obtained from analyzing the correlation between transcript and protein\nlevels. There appears to be a correlation between Mesotaenium and the response to salt stress over time but because of the\nnature of PCA no significant conclusions can be drawn from this. The protein and transcript levels at a given point in time\ncannot be easily interpreted without knowledge of protein/transcript turnover rates and transcription/translation rates.\nImportantly, the discussion of their findings is quite short and cursory, meaning that the manuscript as a whole lacks a\ncoherent message. It may be that this is because very few of the transcripts and proteins found significantly upregulated in\nthe study were identified. The manuscript presents a lot of data, but doesn’t address what it means for early land plant\nevolution. Similarly, the biological functions of probable embryophyte homologs are discussed, but the authors do not\nsynthesize a clear image of what this means for zygnematophyte biology.\nIt is an impressive dataset and ultimately will contribute to a better understanding of stress responses in both\nzygnematophyte algae and in embryophtyes, but in its current form seems likely to be of interest only to specialists in the\nfield. They, however, will be very interested.\nThere are a few typos and grammatical errors here and there, but on the whole the manuscript was carefully prepared. The\nsentence on lines 273-274 is malformed.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "RESPONSE TO REVIEWERS’ COMMENTS\nReviewer #1 (Remarks to the Author):\nThis paper compares response to osmotic stress in two forms of zygnematophyte cells in order to provide insight into the\nadaptation to terrestrial environments. The authors analyze transcriptomic, proteomic, and metabolic data at several\ntimepoints after exposed to osmotic stress in the form of salt and manitol. Changes in the cell wall were identified and follow\nup experiments performed to obtain further insight into the cell wall changes. I believe this is an important study of the\nevolution to land plants. to my knowledge, the methods used were appropriate.\n>>>>AU: Thank you for appreciating our work.\nIn general, the manuscript is well written, but the figures are complex and need more information in the figure legends to\nimprove understanding. I recommend some minor changes to improve readability of the manuscript:\n>>>>AU: We have made sure to address all of the throughout very helpful comments.\n1. Line 45, \"Here the focus was particularly on signaling cascades\". This is unclear because signal cascades were not\nmentioned in the manuscript and a sentence on line 46, \"Here, we focused\n47 on osmotic stress, the prime challenge on land.\" details a different focus.\n>>>>AU: The “signaling” focus refers to previous conducted studies and the general osmotic stress response to this study,\nbut we see that using 2 times the word “here” is confusing. We rephrased this in the revised version.\n2. In Figure 1 it would be helpful to explicitly mention the meanings of each color, instead of the information only being in\none of the images. B and C should be switched in the figure description. Please explain what the P values are corresponding\nto in the graphs.\n>>>>AU: All added and corrected.\n3. Line 133 and 135 should say figs 1D, 1E\n>>>>AU: Thanks for spotting this. We were indeed not consistent. Now all was changed from “(Fig 1c,d)” to the style “(Figs.\n1c, 1d)”.\n4. Should Line 123 say 1C only?\n>>>>AU: Indeed, has been corrected.\n5. I could use more information in the figure text on how to interpret 3a and 3b. What is the white line? What is negative\nrank?\n>>>>AU: Good point. Explanation has been added to the figure description.\n6. Fig 4 needs A and B labeled. Need more information on how to interpret the graphs. What are the red dotted lines?\n>>>>AU: True. We added labels. The red dotted lines are just to make it easier to figure out which term is shown in\nZygnema without the reader having to use a ruler. This has been slightly changed in Figure and Figure description to avoid\nconfusion.\n7. Can you separate figure 5 into A and B for better clarity?\n>>>>AU: Good point; done.\n8. Figure 6D bottom, what are the units on the ELiSA measurements?\n>>>>AU: The units are arbitrary and show the relative value to the highest measured signal for each antibody seperately.\nWe added this in the description for clarification.\n9. Data accessibility: Line 812 Please specify that the RNAseq data has been deposited to NCBI. Line 813 Please clarify how\nto access micrographs. Please make sure all the data is accessible upon publication. I was unable to find the\nproteomics and metabolomics data in their respective repositories.\n>>>>AU: We have added the information that this is on NCBI; regarding all other datasets. Everything is online now.\n10. The discussion may benefit from a conclusion paragraph integrating a broader discussion on the evolution of algae to\nthe terrestrial habitat and how your results fit into that narrative.\n>>>>AU: True, a small conclusive paragraph has been added.\nReviewer #2 (Remarks to the Author):\nThe study investigated the response of two algae, Mesotaenium and Zygnema, to osmotic stress. The algae were exposed\nto high concentrations of mannitol and NaCl to simulate osmotic stress. Both algae responded to osmotic stress by\nreducing their water content and undergoing plasmolysis, with Mesotaenium showing a more pronounced response.\nProteomic and transcriptomic analysis revealed a complex response to osmotic stress, with many proteins and transcripts\nchanging in abundance.\nThe study found that both algae underwent cell wall remodeling in response to osmotic stress, with the up regulation of\ncell wall-associated proteins such as XTH and expansins. The cell wall of Mesotaenium became more compact and rigid,\nwhile that of Zygnema became looser and more fragile. The study also found that Mesotaenium AGPs were released into\nthe extracellular space in response to osmotic stress. The study highlights the complex response of algae to osmotic stress,\nwith multiple layers of biophysical feedback mechanisms involved, and suggests that the response of algae to osmotic\nstress is highly conserved across species.\nThe manuscript presents important data of interest to a broad community, highlighting the conserved background present\nin extant zygnematophyte algae for abiotic stress resilience. As expected from this lab, the bioinformatic analyses are state\nof the art and the figures and illustrations are of high quality.\n>>>>AU: Thank you for the kind words and appreciating our work.\nHowever, I am not entirely convinced that osmotic stress is the best model for abiotic stress during land colonization (as\nsomehow claimed in the introduction). It is easier to do than any desiccation stress, but much milder. That said, I still think\nthis is a very important contribution to the field and should be published. I have a few minor comments that the authors\nshould consider and address prior to publication.\nLine 47: Main challenge on land: I doubt that osmotic change is the main challenge on land. It is desiccation or drought,\nwhich has many similarities but also clear differences to osmotic stress, especially if you incubate with a salt! See also\nbelow.\n>>>>AU: Thank you for this comment — it is a good point. We have clarified that desiccation and drought are a form of\nosmotic stress: By removing water from the environment (desiccation), the concentrations of osmolytes and other solutes\naround the cells increase, which leads to hyperosmotic stres. We extensively clarified this in the text. Further, we have\ncreated an all-new figure (Fig. 7) that illustrates the cell biological consequences and places them in a phylogenetic\ncontext.\nLine 49: Vascular plants are homoiohydric: Not all, e.g. resurrection plants, and seeds in general are also poikilohydric.\nVascular plants have just transferred desiccation tolerance to spores and seeds.\n>>>>AU: Thank you for pointing the case of resurrection plants out. We changed the second paragraph so that it better\nfits the overal story and omittted poikilohydricity altogether.\nLine 53: Waxy cuticle: As far as I know, this is really rare. I find water conducting tissues and stomata in sporophytes a better\nexample.\n>>>>AU: We now condensed this while briefly mention all.\nLine 55: delves into poikilohyry: Reading this I would expect a desiccation-drought study, not osmolarity, see above!\n>>>>AU: Thank you. This issue has been solved in the point above (line 47 and line 49).\nLine 79: on osmotic stress, thriving in habitats subject to frequent desiccation: Again, you are confusing osmotic stress and\ndesiccation stress. When a ditch in which Zygnema thrives dries out, there is a good chance that there will be initial osmotic\nstress due to increasing osmolarity, but I doubt that there will ever be anything like the 800 mM mannitol you used in your\nexperiments. When the water is gone, the real desiccation stress starts, which will cause much more water loss than osmotic\nstress. However, osmotic stress can acclimate the alga to desiccation stress. In desiccation you can always reach a YII of zero\nin PAM, which shows how much stronger the desiccation stress is!\n>>>>AU: Thank you for sparking this important discussion. It was not our intention to intermingle desiccation (complete\nremoval of water, leading to increased extracellular osmolyte concentrations) with osmotic stress (stress due to changes\nin extracellular osmolyte concentrations). Indeed, as the title of our manuscript indicates, the focus is indeed on\nacclimation to osmotic stress. However, we see that wording we used could imply that we tried to mimick these extreme\ncircumstances. (which we did not as we liked to stay inside the stress response range of our organisms were we could\ntheoratically obtain a clear transcriptomic and proteomic change.) Hence, this sentences has been adapted.\nLine 106 to 108: Osmolarity of the media: The total osmolarity is slightly higher because you added 150 mM NaCl or 800 mM\nmannitol to the growth medium. Do you know the osmolarity of your media? Or did you change the media to 800 mM\nmannitol so that you have not only osmotic stress but also nutrient starvation!\n>>>>AU: Good point – we did indeed calculate the osmolarity of the medium, albeit neglecting the contribution of agar,\nwhich consist of long polymers and therefor contributes close to 0 to the osmolarity. The osmolarity of the standard C\nmedium is 0.015 Osm/L and for WHM medium the osmolarity is 0.018 Osm/L. Adding NaCl raises the osmolarities to 0.315\nOsm/L and 0.318 Osm/L, whereas adding the mannitol raises the osmolarities to 0.815 Osm/L and 0.818 Osm/L. The\nnumbers were added to the method section.\nWe hope that it is now more precisely written that the media was (of course) not replaced with just mannitol/salt medium,\nbut it was supplemented to the excisting media (all in the method section). The final concentrations of micronutrients\nremained equal to prevent nutrient stress.\nLine 115: Decreased in both algae: Not true for Zygnema and mannitol, if I interpret Fig. 1 A correctly.\n>>>>AU: Error well spot, it should say 6 hours our, not 3 hours. Has been adapted.\nLine 118 - 119: never approached zero: confirms that osmotic stress is much milder than desiccation. When you desiccate,\nyou always reach zero!\n>>>>AU: Correct. The osmotic stress applied here is indeed milder than full desiccation, which is also a form of osmotic\nstress in which the osmolarity increases towards indefinitely and due to the absence of water poses a much larger risk of\ncell wall collapse than in our experiments.\nLine 133: structures induced by mannitol treatment Figure 1D visible tonoplast: I doubt that you can see a tonoplast\nmembrane in a light microscope. Be more precise! Better vacuolated. Many of the LM observations are not significant. And\nthe results are strange. For example, if you compare curved and cupped for Mesotaenium, I would have thought that both\nwould be insignificant. Why show all the insignificant results? For Mesotaenium 12 out of 16 comparisons are not\nsignificant P = 0.07 - 0.642! For Zygnema it is much better, but you show all the insignificant cell shapes for Mesotaenium,\nbut not all for Zygnema\n>>>>AU: With regard to the tonoplast: to distinguish tonoplast from another membrane with light microscope is indeed\nhard and you cannot be certain. Hence we added right above it in the figure “presumably, see method section for\ndetailed description”. We enlarged the text in the figure a bit so it would not be missed. Also, the algae should also have\nvacuole in control conditions, so vacoluated (=having a vacuole) we think is not a better term.\nFor transparency, we showed all microscopic features that were statistically analysed. For Mesotaenium, we thought we\nsaw or suspected more colouration and more lipid droplets within the stress treatments, but after counting it turned out\nthat it was not the case (or at least not significant). Negative results are also results. We now highlighted all P-values\nbelow 0.05 for better visualisation.\nLane 143: 9600 Zygnema tanscripts. This is a rather low value for Zygnema. The genome paper has 16,617 annotated\ngenes. Very often you have more transcripts than genes in RNASeq. I am not sure if the RNASeq data are reliable for\nZygnema.\n>>>>AU: We compared our numbers with the very recent manuscript of Rieseberg et al and our number of genes (they\nanalysed on gene-level) were very similar (9445 genes in the other work and 9620 genes in our case), so even slightly\nhigher in our case. One should take into account that the genome paper took a complementing approach of very diverse\nconditions (our focus was „just“ on osmotic stress, whereas in the genome paper various stressors and the diurnal cycle\nwere sampled, where the night alone causes a complete change in the active gene set), which often lead to the\ndetection of more genes as some are only expressed under certain conditions. On top of that, we filtered extremely low\nabundant transcript over all conditions (around 1500 transcipts, who can hinder the DEanalysis with relative high\nLOG2foldchanges when absolute the change is minimal) out and Zygnema has for the majority of genes only a single\nhighly abundant transcript. We added 1 sentence to the manuscript were the numbers of Rieseberg et al are being\ncompared.\nFig. 2 A: Why are there three PCAs for each species at the protein level?\n>>>>AU: Since PC1, PC2, and PC3 combined best explain the variation in the data, we provided all to show a more\ncomplete picture of separation of the data points.\nGive time points!!! This is not explained anywhere. It is very difficult to see the differences for the treatments.\n>>>>AU: While it was given in the legend at the bottom, it can indeed be made clearer. We thus adapted it.\nAnd I think the differences at the protein level are much smaller than at the RNA level.\n>>>>AU: Correct, which is why this combined approach is very valuable in our opinion.\nFor the RNA Seq data, the effect arrows do not always show the correct direction of the effect. For example, for the\nmannitol treatment and mesotaenium, the effect is clearly in the direction of the upper left corner, not vertical! Similarly,\nthe effect vectors for Zygnema control and Salt are not correct.\n>>>>AU: The vectors have been slightly corrected\nLine 145. Why did you assemble de novo? Genomes are available?\n>>>>AU: We used both the genome annotation that are available, but as a complementing approach we also added de\nnovo assembled information. Both with these non-model systems (or budding models) and even established model\nspecies, gene models get frequently updated. The genome of Mesotaenium is a point in case (V2 in Dadras et al. 2023,\nowing to the increase in RNAseq coverage). Both for Mesotaenium and for Zygnema, we found proteins that were not in\nthe established database. Doing the transcriptome assembly was in hindsight not strictly nescesary for this work, but a\nnice addition – we considered it better to be as comprehensive and careful as possible rather than omitting this to save\ntime and work.\nLine 164: Difference in effect strength between protein and RNA. I do not see this. Also in the PCA (Fig. 2 A), I see a\nstronger effect for 25 h (darkest color).\n>>>>AU: While we do not see this stronger effect at 25 hours, we agree that this effect is not that clear for each\ncondition: for salt stress it is, but for mannitol it is less pronounced. Hence, we amended this part of the text.\nThe most surprising result for me is that there is no variation in the control for mesotaenium and the longest salt\ntreatment is again identical to the control! But these are not even mentioned in the text.\n>>>>AU: We briefly mention the lack of changes in control treatment (which is indeed a very nice circumstance for DE\nanalyses) in Mesotaenium later when talking about the clustering. We will mention it as well when describing the\nPCA+DEanalysis.\nMinor: The legneds for the figures should be improved. They should be understandable without text.\n>>>>AU: Good point. We took several measures: (i) Fig2b+Fig2c legend improved. (ii) Fig3b: axis improved. (iii) Fig5a:\nminor legend change. (iv) Fig6a: minor legen visualisation improvement. (v) Fig6b: addition of NaCl labels. (vi) Fig6F:\naddition of “Osmo-responsive subfam.”.\nReviewer #3 (Remarks to the Author):\nThe details surrounding the colonization of land by early embryophytes are poorly understood. These organisms likely\ninhabited a freshwater environment, perhaps with periodic desiccation, ultimately selecting for adaptations that would\nlead to the colonization of dry land. Although osmotic stress responses in embryophytes are well studied, such responses\nare poorly characterized in zygnematophytes, the closest relatives of land plants. Understanding the modern biology of\nboth the zygnematophytes and embryophytes is crucial to reconstructing the biology of their common ancestor. It has\npractical implications as well, because plant stress causes substantial losses in agricultural productivity, and these losses\nare likely to increase as the climate changes. To better understand these stress responses, Zegers et al. characterized the\nosmotic stress responses of two zygnematophytes, Mesotaenium endlicherianum and Zygnema circumcarinatum, using\ntranscriptomic, proteomic, and metabolomic techniques. The authors provide evidence that some of the responses to\nosmotic stress utilized by modern-day embryophytes may also be present in some taxa of zygnematophytes.\nThe authors performed classic drought stress experiments on these zygnematophytes, echoing work that has been done\non embryophytes. Their transcriptomic results show that both zygnematophytes display a rapid response to salt stress with\nadaptation to .15M NaCl after 25 hours. Mannitol treatment on the other hand showed a stronger response which\nsuggests these organisms have a much more difficult time adapting to the osmotic stress that mannitol causes. However,\nas the authors state, Zygnema has a “temporally dynamic response in the control condition” which makes it difficult to\ndraw any conclusions from that species’ given data.\nThis is emblematic of the fundamental problem with the manuscript: although the work is of high quality and the data will\nsignificantly contribute to the field, some analyses feel unmotivated or out of place.\n>>>>AU: Thank you for the assessment of our manuscript which sparked many important discussion points amongst us.\nWe have taken all your feedback into account and improved the discussions, phrasing, and framing in our manuscript.\nRegarding the temporal dynamic in Zygnema: we explain in the manuscript what the biological meaning of this could –\nbut more importantly, we have taken this in our clustering and functional enrichment into account, which is what all\nmajor conclusions are based on; more below.\nFor example, the short discussion of the principal component analysis seemed disconnected from the discussion. What is\nthe significance of movement in this feature space over time? How should this be interpreted?\n>>>>AU: This is the response and acclimation process over time. We expanded the explanation on this.\nCan the results be extended beyond the two organisms studied?\n>>>>AU: Indeed, we think they can. We have pronouncedly extended the discussion on this aspect\nIt is also unclear what conclusions, if any, can be obtained from analyzing the correlation between transcript and protein\nlevels.\n>>>>AU: If the reviewer is referring to fig. 3, the main aim of this is to first show a bird’s eye view of the correlation. We\nthen move to talking about specific proteins/protein coding genes that show consistent patterns on RNA and protein\nlevel, and we highlight also proteins/transcript were the opposite is the case.\nThere appears to be a correlation between Mesotaenium and the response to salt stress over time but because of the\nnature of PCA no significant conclusions can be drawn from this\n>>>>AU: Both for salt and mannitol, the PCA shows clear clustering of all control treatments and seperation of the\ntreatments in Mesotaenium, not hinting towards possible underlying mechanisms that play a more prominent role than\nthe applied osmotic stress. The main aim of the PCA is to provide an overview. Our inferences of the mechanisms are\nwhat follows next. We have made sure to provide a better red thread for the section on the PCA and the correlation to\nhlighlight this.\nThe protein and transcript levels at a given point in time cannot be easily interpreted without knowledge of\nprotein/transcript turnover rates and transcription/translation rates.\n>>>>AU: We mitigate by performing differential analysis that build on the correct statistics (always comparing to a\ncontrol or another timepoint) and not just looking at the raw abundances. The only case where raw abundances were\nused was for the absolute abundance analyses, where the point is exactly the conclusion that a straightforward\ncorrelation is poor. We thus turned in all the remaining – and major conclusion determining – parts of the paper to the\ndifferential analyses as also outlined in the main text. This also applies to the clustering, and subsequent functional\nenrichment – all of which is always compared to t0 and proper controls.\nImportantly, the discussion of their findings is quite short and cursory, meaning that the manuscript as a whole lacks a\ncoherent message. It may be that this is because very few of the transcripts and proteins found significantly upregulated in\nthe study were identified. The manuscript presents a lot of data, but doesn’t address what it means for early land plant\nevolution. Similarly, the biological functions of probable embryophyte homologs are discussed, but the authors do not\nsynthesize a clear image of what this means for zygnematophyte biology.\n>>>>AU: Good point, which also the other reviewers noticed. Due to the initial space limitation we tried to keep this\nshort. We expanded the discussion with a concluding paragraph.\nIt is an impressive dataset and ultimately will contribute to a better understanding of stress responses in both\nzygnematophyte algae and in embryophtyes, but in its current form seems likely to be of interest only to specialists in the\nfield. They, however, will be very interested.\n>>>>AU: We thank the reviewer for appreciating the scope of our work.\nThere are a few typos and grammatical errors here and there, but on the whole the manuscript was carefully prepared.\nThe sentence on lines 273-274 is malformed\n>>>>AU: Corrected.\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts.\n>>>>AU: Thank you for contributing to the constructive feedback.\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts.\n>>>>AU: Thank you for contributing to the constructive feedback."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Thank you for addressing my suggestions/concerns. The updated images, legends and conclusion have improved the\nreadability of this article.", "reviewer_2": "Dear authors, I appreciate the changes you made to the manuscript. As far as I am concerned, the manuscript can be now\npublished.", "reviewer_3": "I am satisfied by the revisions. The paper has always been interesting, and as revised the motivation behind individual\ncomponents of the project is clearer, and the implications of the observations are easier to understand. I appreciate the\nclearer discussion of the relative effects of hypo- and hyper-osmotic stresses and their environmental significance. I feel the\nmanuscript is now ready for publication with no further modification.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": ""}]

Decision letter