Guard cell photorespiration controls stomata behavior and development

Guard cell photorespiration controls stomata behavior and development | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Guard cell photorespiration controls stomata behavior and development Stefan Timm, Hu Sun, Inken Thiemann, Nils Schmidt, Johannes Kromdijk, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8223718/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Mar, 2026 Read the published version in New Phytologist → Version 1 posted You are reading this latest preprint version Abstract Photorespiration is often seen as a burden because it is diminishing photosynthetic efficiency. However, it is essential for safeguarding the Calvin–Benson-Bassham cycle from inhibitory byproducts of Rubisco oxygenation and highly intertwined with overall plant primary metabolism. Here we show that targeted manipulation of the entry enzyme 2-phosphoglycolate (2-PG) phosphatase (PGLP1) in Arabidopsis guard cells consistently influences growth, photosynthesis, carbohydrate allocation, and stomatal movement. Altered PGLP1 expression triggered guard cell-specific starch and H 2 O 2 accumulation patterns under photorespiratory conditions and affects stomata size, a response replicated by 2-PG feeding to Arabidopsis wildtype. These results reveal that efficient photorespiratory metabolism is essential for guard cell function and critical for acclimation to external CO 2 /O 2 ratios. By uncovering a direct metabolic link between photorespiration and stomatal behavior, our work highlights an unexpected role of this ancient pathway in shaping gas exchange and photosynthesis and opens a new avenue in optimizing plant yield and resilience. Biological sciences/Plant sciences/Photosynthesis/C3 photosynthesis Biological sciences/Plant sciences/Plant physiology Arabidopsis environmental acclimation 2-phosphoglycolate phosphatase plant growth photosynthesis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 One-sentence summary Targeted manipulation of guard cell PGLP1 reveals that efficient photorespiratory 2-PG metabolism is crucial for stomatal dynamics and plant performance. Main Document Plant photosynthesis converts atmospheric CO 2 into sugars that sustain the global food chain. Under the present day high O 2 /CO 2 ratio, photosynthetic efficiency is limited by Rubisco’s oxygenase activity, which generates 2-phosphoglycolate (2-PG), a potent inhibitor of the Calvin-Benson-Bassham (CBB) cycle enzymes sedoheptulose-1,7-bisphosphatase (SBPase) and triosephosphate isomerase (TPI) [ 1 – 2 ]. Photorespiration exclusively removes 2-PG to prevent metabolic inhibition, yet it is energetically costly and releases previously fixed CO 2 and NH 3 + [ 3 ]. Beyond its essential repair function, photorespiration supports de novo nitrogen and sulfur assimilation, amino acid biosynthesis, one-carbon metabolism, and redox balance, thereby contributing to acclimation under fluctuating conditions [ 4 – 6 ]. These Janus-faced roles, protective but metabolically expensive, make photorespiration a key target for improving plant productivity under current and future climates [ 7 – 8 ]. Leaf-mesophyll photorespiration is well-characterized, but its function in specific cell types remains largely unexplored. Although the pathway is highly compartmentalized, spanning chloroplasts, mitochondria, peroxisomes, cytosol, and vacuoles [ 6 , 9 – 10 ], its interaction with other metabolic routes is not well resolved. Recent isotopically non-stationary metabolic flux analyses (INST-MFA) showed that a substantial fraction of carbon exits the canonical cycle, feeding other biosynthetic routes including C1-carbon metabolism, mainly as serine and glycine [ 11 – 13 ]. This implies that certain reactions exert disproportionate control over the photorespiratory flux and may regulate carbon utilization and partitioning in distinct compartments. Genetic studies have highlighted two key control points: mitochondrial glycine decarboxylase (GDC) and chloroplast-localized 2-PG phosphatase 1 (PGLP1). Both enzymes share a strong positive correlation with the photorespiratory flux, CBB cycle operation, starch biosynthesis, and plant growth, making them attractive targets for improved yield [ 1 , 14 – 16 ]. Photorespiratory rates are determined by the CO 2 /O 2 ratios in chloroplast, which largely depend on opening of stomata, formed by pairs of guard cells (GC) in the leaf epidermis. In addition to flux of CO 2 and O 2 , stomatal opening regulates water vapor movements, balancing carbon gain with water conservation [ 17 – 19 ]. Stomatal size and density are inversely related and determine maximum stomatal conductance ( g smax ); small, numerous stomata support fast stomatal kinetics [ 20 ] and higher gas exchange than few, large stomata. Across evolutionary timescales, high atmospheric CO 2 concentrations ([CO 2 ]) favored fewer, larger stomata, whereas low [CO 2 ] selected for smaller, denser stomata [ 21 – 23 ]. On daily timescales, stomatal size and density will not change, but GC respond dynamically to environmental cues, including light, internal [CO 2 ], temperature, humidity, and water availability. Light is a dominant driver, red light triggers GC osmoregulation and transmits mesophyll signals that align stomatal opening with photosynthetic demand [ 24 ], while blue light acts independently of photosynthesis, directly via phototropin kinases to induce rapid opening at low fluence rates, particularly at dawn and during transient sunlight fluctuations, maximizing carbon assimilation [ 25 – 27 ]. Stomatal closure is mainly achieved via the plant hormone abscisic acid (ABA), maintaining overall plant water status [ 17 – 18 ]. Intercellular CO 2 ( C i ) is regarded as another important factor controlling stomata. For example, C i elevation with decreasing photosynthesis, darkness or via raised external [CO 2 ] promotes stomatal closure, whereas light-dependent draw-down of C i via photosynthetic CO 2 fixation maintains opening [ 28 ]. Rising global [CO 2 ] reduces stomatal aperture and density, lowering conductance and conserving water, yet potentially increasing leaf temperature under drought. At the molecular level, CO 2 responses require the protein kinase high leaf temperature 1 (HT1) and converge with abscisic acid (ABA) signaling, because elevated [CO 2 ] increases guard-cell ABA to induce closure. Thus, stomatal behavior integrates red/blue light signals, CO 2 feedback, and hormonal cues to balance carbon gain, water use, and thermal stability [ 29 – 31 ]. In addition to photorespiration, the activity of Rubisco carboxylation and the flux through the CBB cycle also responds to fluctuating CO 2 /O 2 ratios. It has been shown that SBPase activity might be a control point of the CBB cycle flux, because its overexpression in plants enhanced photosynthesis and yield [ 32 – 34 ]. Comparable effects have been observed in overexpressors of key photorespiratory enzymes such as GDC and PGLP1 [ 1 , 14 – 16 ], whereas impairment of photorespiration diminished productivity [ 35 – 36 ]. Interestingly, the recently reported GC-specific manipulation of GDC suggested a functional link between mitochondrial photorespiratory metabolism and stomatal regulation [ 37 ]. If this finding is specific for mitochondria or GDC, releasing CO 2 during photorespiration thereby eventually affecting C i , remains unknown. However, initial pharmacological studies on photorespiratory enzymes in epidermal peals indirectly supported a functional interaction between the activity of certain photorespiratory enzymes and stomatal movements [ 38 ]. Surprisingly, the role of PGLP1, the photorespiration-specific 2-PG degrading enzyme, in GC is still unclear. Gaining insights into its physiological significance is interesting because of the reduced GC chloroplast count and size, alongside with hinds for the sink-tissue-like characteristics of GC, and the ongoing debate to which extent GC rely on their own internal photosynthesis [ 39 – 41 ]. To address this question, we analyzed the impact of GC-specific manipulation of the central photorespiratory enzyme, chloroplastidal PGLP1. The transgenic lines with in- and de-creased GC-specific PGLP1 expression were assessed to study its role in GC metabolism and impact on stomata function, photosynthesis and biomass accumulation. By elucidating the role of photorespiration in these specialized cells, our work not only provides new insights into its significance for GC metabolism but also provided the foundation for new strategies to engineer crops with enhanced growth, water-use efficiency, and yield, key traits to meet the challenges of plant production under increasing climate change. Results Guard cell PGLP1 expression exerts control over growth and biomass accumulation To determine the role of photorespiration, particularly 2-PG degradation, in GC of the C3 plant Arabidopsis, we used the guard cell-specific GC1 promoter [ 42 ] to specifically manipulate GC PGLP1 expression (Supp. Fig. S1 ). Overexpression (sense lines: SL4 + 15% and SL7 + 24%) and antisense repression (antisense lines: AL4 -15% and AL5 -13%) of PGLP1 was observed in GC, while PGLP1 protein abundances remained unaltered in mesophyll cells (MC) of the same leaves (Fig. 1 A). Increased expression of PGLP1 in GC stimulated, whilst antisense repression reduced the apparent growth of Arabidopsis under photorespiratory conditions (Fig. 1 B). Diagnostic growth parameters followed this consistent pattern, as leaf number, rosette diameter, fresh and dry weights positively correlated with GC PGLP1 protein expression (Fig. 1 C; Supp. Table S1 ). However, growth alterations relied on active photorespiration, as no growth differences were observed with plants grown in high CO 2 (3000 ppm), strongly suppressing 2-PG formation and photorespiration (Fig. 1 B-C; Supp. Table S1 ). GC PGLP1 shapes photosynthetic CO assimilation and stomatal conductance To test if growth changes are due to altered photosynthesis, we measured chlorophyll a fluorescence and gas exchange parameters of plants grown under photorespiratory conditions. Whilst PSI and PSII efficiencies and related parameters associated with photosynthetic light reactions did not significantly vary among the genotypes (Supp. Fig. S2; Supp. Table S2), light-dependent net CO 2 assimilation ( A N ) and stomatal conductance ( g s ) followed the growth pattern. Thus, A N and g s displayed a positive correlation with GC PGLP1 expression (Fig. 2 A-C). Transpiration rates ( E ), maximum photosynthetic rates ( A max ) and the slope of the light response curves ( α p ) followed this tendency (Supp. Table S3). Intracellular CO 2 concentrations ( C i ) were only significantly decreased in the antisense lines, whilst intrinsic water use efficiency ( iWUE ) showed only minor alterations (Supp. Table S4). To check if photosynthetic stimulations rely on altered photorespiratory 2-PG turnover in GC, we measured photosynthesis at three different O 2 concentrations (3, 21 and 40%) to suppress or stimulate 2-PG formation. At low photorespiratory flux requirements (3% O 2 ), no significant changes on A N , g s , and the CO 2 compensations points ( Γ ) were observed (Fig. 2 D-F). However, at air O 2 levels (21%) A N was increased in overexpressor ( ~ 19%) and decreased in antisense lines (~ 13%), whilst Γ displayed inverse tendencies (~ 10% lower in overexpressors and ~ 14% higher in antisense lines). Interestingly, g s , a parameter directly related to stomatal opening, was positively correlated with GC PGLP1 protein amounts and was higher ( ~ 29%) or lower (~ 16%) in the overexpressor and antisense lines, respectively (Fig. 2 E, Supp. Table S5). The described patterns were similar at 40% O 2 , i.e. photorespiration-stimulating conditions, but with stronger specification. In the overexpression lines A N and g s were stimulated (~ 49% and 60%) and Γ decreased (~ 17%), whilst antisense repression caused a reduction in A N and g s (~ 33% and 27%) and a corresponding increase (~ 15%) in Γ (Fig. 2 D-F). The calculated O 2 sensitivity revealed overexpression lines were less and antisense lines more sensitive to O 2 compared with the wildtype (Fig. 2 D, inlet). Finally, the slope of the Γ -vs-O 2 concentration ( γ ), representing a measure of photorespiratory CO 2 release, revealed that GC PGLP1 overexpression caused a significant reduction, whilst antisense suppression an increase in photorespiratory CO 2 losses (Fig. 2 F, inlet). GC PGLP1 expression correlates with stomatal size, a morphological response that is inducible by external 2-PG feeding to wildtype Arabidopsis As GC PGLP1 amounts correlated with g s , we analysed stomata count and size of all genotypes grown in air and elevated CO 2 to compare the impact of photorespiratory and non-photorespiratory conditions. As displayed in Fig. 3 , stomata size, index, and density (significant only in the overexpressors), corelated with GC PGLP1 expression, as these parameters were in- and decreased in overexpression and antisense lines, respectively (Fig. 3 A, Supp Fig. S3). These changes were photorespiration-dependent as they were absent in high CO 2 -grown plants (Supp. Fig. S3). Based on these findings, we hypothesized if altered GC PGLP1 expression and 2-PG amounts could serve as morphogenetic signal for stomatal development. To test this assumption, increasing 2-PG concentrations (0, 10, 50, 100 µM) were externally applied to Arabidopsis wildtype-plants during cultivation on agar plates. Interestingly, characteristic stomatal determinants showed a negative correlation with external 2-PG application, as we measured gradually decreased length, width and smaller stomatal area and index compared to the control plants, lacking 2-PG in the growth media. However, 2-PG treatment had only minor effects on stomata density (Fig. 3 C). Variations in whole-leaf primary metabolism is restricted to soluble sugars, total amino acid and organic acid contents Because of the growth and photosynthetic responses of the transgenic lines, we quantified soluble sugars, starch, and 33 representatives of primary metabolism in leaves of all genotypes. Glucose and fructose levels were significantly higher in overexpression and lower in antisense lines. Sucrose was only higher in overexpressors (Fig. 4 A-C), while transitory starch did not differ among genotypes (Fig. 4 D). Further, leaf 2-PG and NAD + amounts showed a negative, whilst 3-PGA a positive correlation with GC PGLP1 expression (Fig. 4 E-F; Supp. Table S8). Among the other primary metabolites, we measured significant increases in glutamate, isoleucine, and isocitrate in the overexpression lines and significantly decreased arginine in the antisense lines. However, the calculation of total soluble sugars, amino and organic acid contents revealed all to increase and decrease in the GC PGLP1 overexpressors and antisense lines, respectively (Fig. 4 G-H; Supp. Tab. S8). Manipulation of GC PGLP1 expression impacts on guard cell starch and HO contents Previous work suggested that GC starch and H 2 O 2 amounts are involved in the energization and regulation of stomatal movements [ 44 – 46 ]. Hence, these parameters were measured under photorespiratory conditions, as no phenotypic or stomatal size variation were observed in high CO 2 -grown plants. At one hand, we found a strong positive correlation between GC PGLP1 amounts and GC starch, which was significantly higher (~ 19–25%) in the overexpression and lower (~ 29–32%) in the antisense lines. On the other hand, H 2 O 2 amounts were negative correlated with GC PGLP1 expression, being lower (~ 31–36%) in overexpression and higher (~ 27–29%) in antisense lines compared to the wildtype (Fig. 4 I-J). Again, alterations in guard cell starch and H 2 O 2 are photorespiration-dependent as both were statistically invariant among the analysed genotypes when grown under non-photorespiratory conditions, i.e. high CO 2 (Suppl. Table S8). Guard cell SBPase expression has no major impact on growth and photosynthesis Given SBPase expression in leaves of various plants species positively correlates with growth and photosynthesis, and the fact that 2-PG is a potent inhibitor of SBPase activity [ 1 , 32 – 34 ], we also manipulated the GC-specific SBPase protein expression. In clear contrast to PGLP1 manipulations, we did not observe any significant impact on the visual phenotype and quantitative growth parameters of overexpression (+ 11.3–15.7% GC SBPase protein expression) and antisense (-12.6-22.48% GC SBPase protein expression) lines under the same growth conditions (Supp. Fig. S4-S5). Furthermore, no significant change was seen on selected photosynthetic parameters, including A N , g s , and Γ (Supp. Fig. S4), measured as functions of varying light and CO 2 . Discussion Photorespiration is an unavoidable process in the primary C and N metabolism of plants, because it enables photosynthetic CO 2 assimilation by detoxifying the Rubisco oxygenation product 2-PG [ 5 – 6 ]. While the toxic effect of 2-PG on plant metabolism is well established [ 1 – 2 , 47 ], it could also play a role as low CO 2 -sensing molecule in oxygenic phototrophs as discussed to occur among cyanobacteria [ 48 ]. However, if 2-PG plays such a role among plants remained uncertain to date. To address the question if 2-PG is involved in CO 2 -dependent stomata movements, we specifically manipulated the expression of the 2-PG-metabolizing enzyme PGLP1 in stomatal guard cells. This approach revealed a previously unrecognized function of PGLP1 or 2-PG in coordinating GC metabolism with stomatal behavior (Fig. 5 ). Photorespiration is a highly compartmentalized process involving reactions in the chloroplast, peroxisome, mitochondrion, cytosol, and vacuole. While its roles and physiological implications are well established at the whole-leaf level, particularly in the mesophyll, its function in specific tissues and cell types remains largely enigmatic. Guard cell-specific manipulation of photorespiratory 2-PG removal, achieved through upregulation or antisense repression of PGLP1, reveals photorespiration as a key component of guard cell metabolism as well as stomatal behavior and development. Mechanistically, we propose that changes in CO 2 availability are sensed via the capacity of the photorespiratory flux, with the amount of the photorespiration-specific entrance metabolite 2-PG in chloroplasts serving as a key determinant. On the one hand, high chloroplast PGLP1 activity maintains low 2-PG levels and alleviates negative impacts on CBBC performance, starch biosynthesis, and ROS accumulation, particularly H 2 O 2 , thereby supporting the carbohydrate and energy status required to drive stomatal movements. On the other hand, reduced PGLP1 activity leads to 2-PG accumulation in chloroplasts, which slows the CBBC, decreases carbohydrate availability and metabolism, and promotes H 2 O 2 accumulation. Consequently, stomata tend to remain more closed to prevent further damage to guard cells and the whole leaf resulting from Rubisco oxygenation and impaired photorespiration. Abbreviations: 2-PG − 2-phosphoglycolate; 3-PGA − 3-phosphoglycerate; 3-HP – 3-hydroxypyruvate; CBBC – Calvin-Benson-Bassham cycle; CAT – catalase; ETR – electron transport chain; GDC – glycine decarboxylase; g s – stomatal conductance; Hex-P – hexose phosphates; OAA – oxaloacetate; PEP – phosphoenolpyruvate; PGLP – 2-PG phosphatase; Pyr – pyruvate; ROS – reactive oxygen species; SHMT1 – serine-hydroxymethyltransferase 1; TCA – tricarboxylic acid cycle Our results provide a consistent picture: enhanced expression of PGLP1 in GC resulted in improved photosynthesis, higher stomatal conductance and enhanced growth, whereas antisense repression had opposite effects compared to wildtype (Fig. 1 – 2 ). Importantly, growth stimulation depended on Rubisco-mediated 2-PG formation and its subsequent photorespiratory metabolization, as the transgenic lines were indistinguishable from the wildtype under photorespiration-suppressing conditions (Fig. 1 ; Supp. Table S1 ). Similarly, the differences in the photosynthetic parameters became larger when gas exchange measurements were done under high O 2 conditions, stimulating photorespiration, while at lowered O 2 levels they were virtually absent (Fig. 2 ). These findings suggest that GC metabolism is naturally constrained by PGLP1 activity under ambient, i.e., by the capacity of photorespiratory flux, and that increasing this capacity can benefit stomatal function through enhanced movement dynamics and energization (Fig. 5 ). This is particularly noteworthy given the ongoing debate regarding the extent to which GC perform photosynthesis and, perhaps, rely on active photorespiratory metabolism. Furthermore, GC PGLP1 limitation could be explained by specific features of these specialized cells, as they contain significantly fewer and smaller chloroplasts ([ 49 – 51 ] and, thus, have generally naturally lower abundances of photorespiratory proteins. Until recently, the overall significance of photorespiratory metabolism in GC remained unclear due to the absence of guard cell-specific transgenic approaches. The first GC-specific manipulation of the mitochondrial photorespiratory enzyme glycine decarboxylase (GDC) provided evidence that these specialized cells are indeed capable of, and to some extent dependent on, active mitochondrial photorespiration [ 37 ]. This conclusion is consistent with two recent proteomic studies on mitochondria isolated from GC and their specific ATP metabolism [ 52 – 53 ] and earlier omics studies, showing the transcription and translation of the full photorespiratory core cycle in GC [ 42 , 54 ]. The stimulation of growth, photosynthesis and stomatal conductance is consistent with earlier studies showing that GC-specific modifications of different processes can positively influence g s and A N [ 37 , 55 ]. Interestingly, the photorespiration-specific results presented here, in conjunction with our earlier report, show that reprogrammed photorespiration fluxes in different subcellular organelles have a clear and consistent impact on overall plant performance under ambient laboratory conditions. However, it remains unresolved whether higher photosynthetic rates arise directly from changes in g s or whether PGLP1, and thereby photorespiratory flux, modifications in GC signals increased CO 2 demand, which in turn prompts stomata to open more widely to support mesophyll photosynthesis and facilitate a higher energy status of the cells. Notably, the latter interpretation aligns with reports of photorespiratory optimizations, mainly PGLP1 and GDC overexpression, at the whole-leaf level, which also resulted in higher stomatal conductance [ 1 , 14 – 16 ]. Given the previously used ST-LSI promoter is not fully mesophyll-specific and also drives expression in GC, it could well be that the observed responses are also caused by expression changes of both enzymes in GC. Taken together, these observations support the hypothesis that photorespiratory flux capacity, mediated through reinforcement or alleviation of negative feedback on carbon utilization, could serve as a key determinant for sensing and translating changes in external ( C a ) and internal ( C i ) CO 2 availability. More specifically, and supported by our findings, we suggest that chloroplastidal 2-PG could mechanistically serve as signaling metabolite translating altered photorespiratory fluxes in response to changes in CO 2 availability. The ultimate readout of such a mechanism could be shifts in the availability of photosynthates and other biomolecules at the whole-leaf level. Indeed, the metabolite profiles of the transgenic models support this hypothesis, given GC PGLP1 protein expression positively correlated with soluble sugars, as well as the total amino acid and organic acid contents (Fig. 4 ; Supp. Table S8). It should also be noted that changes in the GC photorespiratory flux, i.e. the chloroplastidal 2-PG amount, seem to be causative for optimized photosynthesis and growth, rather than alleviated negative feedback inhibition of the central CBB cycle enzyme SBPase as GC overexpression of the latter did not result in similar physiological responses (Supp. Figure 3 – 4 ). GC starch availability and metabolism were reported to be a key determinate of GC energization and their rapid movements to acclimate to environmental fluctuations ([ 45 , 56 – 57 ]. Although transitory starch stocks underwent no significant changes on the whole leaf basis among our transgenic plants, GC starch accumulation correlated with GC PGLP expression in the transgenic lines (Fig. 1 , 4 ; Supp. Table S6). Hence, starch availability and turnover seem to be, at least to some extent, controlled by GC photorespiration. Similar alterations were found before, i.e., lowered 2-PG levels due to PGLP1 overexpression stimulated starch synthesis and elevated 2-PG levels due to PGLP1 antisense repressed starch accumulation on whole leaf basis [ 1 ]. However, if the different starch amounts in GC are a direct effect of altered GC photorespiration or its reprogrammed mesophyll metabolism and carbon import thereof has to be analyzed at higher resolution in the future. Nevertheless, increased GC starch seems to be a general response of GC overexpression of photorespiratory enzymes as similar observations were made on corresponding GDC manipulations [ 37 ]. In addition to starch, the GC-localized amounts of H 2 O 2 , another central player in stomatal regulation [ 44 , 46 , 58 – 59 ], were inversely correlated with GC PGLP1 expression in air (Fig. 4 J). The exact origin of the altered H 2 O 2 in our lines remains an open question. Photorespiratory H 2 O 2 production seems unlikely, as flux scaling would predict opposite trends between overexpression and antisense lines, and the lack of H 2 O 2 variations in high CO 2 (Supp. Table S8). Alternative sources, such as imbalances in mitochondrial or chloroplastidial electron transport and thereby produced H 2 O 2 , also lack support from our fluorescence and rETR(i) data. By contrast, NADPH oxidase activity emerges as a plausible candidate, potentially explaining the observed discrepancy between H 2 O 2 accumulation and stomatal aperture. An additional possibility is that changes in ROS detoxification capacity contribute to the altered H 2 O 2 profiles. Hence, in addition to the observed metabolic alterations, our findings highlight a potential role of H 2 O 2 in linking GC PGLP1 activity and its potential role in CO 2 sensing to stomatal function. Typically, low concentrations of H 2 O 2 promote stomatal opening via nuclear localization of KIN10 and subsequent induction of BAM1 and AMY3, driving starch degradation [ 46 , 58 ]. At higher concentrations, however, H 2 O 2 triggers stomatal closure through activation of Ca 2+ channels and the anion channel SLAC1, largely mediated by NADPH oxidases (RBOHs) [ 60 – 61 ]. As discussed above, stomatal conductance could be directly or indirectly related to the reprogrammed GC metabolism via GC-specific PGLP1 manipulation. However, in contrast to the manipulation of GC-specific photorespiration due to GDC expression changes ([ 37 ], GC-specific PGLP1 manipulations also affected stomatal morphology. Specifically, GC PGLP1 abundance positively correlated with stomatal size and, to some extent, density (Fig. 3 ; Supp. Fig. S3 and Table S6). These morphological adaptations can certainly contribute to altered stomatal conductance, as maximal conductance ( g smax ) largely depends on stomatal size and density [ 62 ]. Thus, it seems reasonable to assume that enhanced PGLP1 activity, and thereby more efficient degradation of GC 2-PG, leading to lower steady-state GC 2-PG levels, could underlie the observed changes in stomatal size. Given direct quantification of GC 2-PG remains technically challenging, we tested whether exogenous 2-PG influences stomatal traits in Arabidopsis wild type. Indeed, increasing external 2-PG supply gradually reduced stomatal dimensions (Fig. 4 C; Supp. Table S7), supporting the hypothesis that optimal GC PGLP1 activity, through 2-PG detoxification, is fundamental for maintaining proper GC and stomatal morphology. This observation also provides evidence that not changed amounts of GC PGLP1, but directly its substrate 2-PG, serves as signaling molecule. This finding, thus, could be taken as direct hint for its role in the signaling of different CO 2 levels not only via impacting on GC movements, but also GC development in plants. This statement is in line with evolutionary observations that low CO2 (high 2-PG) selected for smaller, whilst high CO2 (low 2-PG) for larger stomata [ 21 – 23 ]. Overall, our findings strongly support the view that GC photorespiration, including GC-specific 2-PG degradation, is a fundamental component of stomatal metabolism and behavior. This metabolic framework may serve as the basis for coordinating environmental variations that strongly influence photorespiratory fluxes with GC behavior and mesophyll metabolism. By modulating 2-PG detoxification and ROS homeostasis within GC, PGLP1 influences both stomatal size and conductance, thereby regulating CO₂ availability for photosynthesis. Together, these results highlight GC photorespiration as an underappreciated target for enhancing crop productivity, particularly under conditions where photorespiration is active. Material and Methods Plant growth conditions and biomass quantification Arabidopsis thaliana (L.) Heynh., ecotype Columbia.0 (Col.0), was used as the wild-type control and as the background for generating GC-specific overexpression and antisense repression lines of photorespiratory 2-phosphoglycolate (2-PG) phosphatase 1 (PGLP1; At5g36700) and the CBB cycle enzyme sedoheptulose-1,7-bisphosphatase (SBPase; At3g55800). Seeds were surface sterilized using chlorine gas (generated by mixing 25 mL of 12% sodium hypochlorite with 1.5 mL concentrated HCl in a sealed desiccator) for 3 h. Sterilized seeds were sown on a soil–vermiculite mixture (4:1, v/v; MiniTray soil, Einheitserdewerk, Uetersen, Germany), stratified at 4°C for 48 h in darkness to break dormancy, and then transferred to growth chambers. Plants were cultivated under controlled environmental conditions (Percival or SANYO growth chambers) with the following standard settings, unless otherwise stated: photoperiod; 12 h light / 12 h dark, temperature; 22°C (day) / 20°C (night), light intensity; 120–140 µmol m − 2 s − 1 (cool-white fluorescent lamps), relative humidity; ~70%, CO₂ concentration; 400 ppm (air) or for high CO₂ (HC) treatments; 3000 ppm, with otherwise identical conditions. Plants were watered to maintain uniform soil moisture and fertilized weekly with 0.2% Wuxal liquid fertilizer (Aglukon, Düsseldorf, Germany). Pots were randomized within the chamber weekly to minimize positional effects. Unless otherwise specified, all physiological experiments were performed using plants at growth stage 5.1 [ 43 ]. Selected quantitative growth parameters were determined from all side-by-side grown genotypes, using 10 independent biological replicates per genotype. Rosette diameters were measured as the maximum distance across the fully expanded rosette and only fully expanded leaves were considered to determine the leaf-count. Next, rosettes were excised, weighed immediately to determine fresh weight, dried at 100°C to constant weight (~ 24–30 h), and reweighed for dry biomass determination. For 2-PG feeding assays, wild-type plants were grown in vitro on freshly prepared half-strength Murashige and Skoog (MS) medium (pH 5.7), supplemented with 0, 10, 50, or 100 µM of 2-PG (Sigma-Aldrich, Taufkirchen, Germany). Leaves of seedlings at growth stage 1.04 [ 43 ] from at least three independent plates per treatment were used for microscopic analysis of stomatal parameters. Cloning and plant transformation procedures Guard cell-specific transgenic Arabidopsis lines were generated to achieve overexpression or antisense-mediated reduction of PGLP1 and SBPase expression. The binary plant transformation vector pG0229:AtGC1:35STer, containing the guard cell-specific GC1 promoter [ 37 , 42 ], served as the expression backbone. The full coding sequence (CDS) of Solanum lycopersicum PGLP1 ( SlPGLP1 ; 1119 bp) was synthesized de novo (BaseClear, Leiden, The Netherlands). The CDS of Arabidopsis SBPase ( AtSBPase ; 1182 bp) was PCR-amplified from Col.0 cDNA using primers P967 and P968 (sequences listed in Supp. Table S9) with a proof-reading DNA polymerase and cloned into pJET2.1 (ThermoFisher Scientific, Schwerte, Germany) for sequence verification and amplification. The coding fragments were excised from their entry vectors using BamHI ( SlPGLP1 ) and XmaI ( AtSBPase ), respectively, and ligated into pG0229:AtGC1:35STer in sense and antisense orientations to create overexpression constructs pG0229:AtGC1:SlPGLP1_sense:35STer and pG0229:AtGC1:AtSBPase_sense:35STer and antisense constructs pG0229:AtGC1:SlPGLP1_antisense:35STer and pG0229:AtGC1:AtSBPase_antisense:35STer (see Supp. Fig. S1 and S3). All final constructs were verified by sequencing (Microsynth, Göttingen, Germany). Subsequently, the constructs were introduced into Agrobacterium tumefaciens GV3101 + pSOUP, the drug resistant colonies verified via standard PCR procedures, and used for Arabidopsis floral dip transformation [ 63 ]. T1 seeds were surface sterilized and selected on half-strength MS media supplemented with 20 µg mL − 1 phosphinothricin (BASTA). Resistant seedlings were transplanted to soil, PCR-verified for the presence of the transgene, and propagated to homozygous T3 or T4 lines, used for all physiological experiments. For comprehensive characterization, two independent SlPGLP1 and three independent AtSBPase overexpression and antisense lines were used. Verification of transgenic lines and Immunological Studies Genomic DNA was isolated from rosette leaves according to standard procedures. Transgene integration was verified by PCR using primers specific for the exogenous SlPGLP1 (P953 for sense and P954 for antisense orientation) or AtSBPase (P967 for sense and P968 for antisense orientation) in combination with the AtGC1 promoter primer P950. PCR reactions were performed using a standard DNA polymerase under the following conditions: 94°C for 1 min, 58°C for 1 min, 72°C for 2 min, for 35 cycles. DNA integrity was confirmed by amplifications of the S16 gene (At2g09990) using primers P444 and P445 under identical cycling conditions, except for a 30 s extension step (see Supp. Fig. S1 C and S3C). Transcript accumulation of SlPGLP1 and AtPGLP1 was assessed by semiquantitative RT-PCR. Total RNA (2.5 µg) was extracted using the Nucleospin RNA Plant Kit (Macherey-Nagel, Düren, Germany) and treated with DNaseI to remove genomic DNA contamination. First-strand cDNA synthesis was performed with the RevertAid cDNA Synthesis Kit (Thermo Fisher Scientific, Osterode, Germany) using oligo(dT) primers. Diagnostic transcript fragments were amplified using primers P974/P975 ( SlPGLP1 , 336 bp) and P977/P978 ( AtPGLP1 , 288 bp). Amplification of S16 (432 bp) with primers P444/P445 served as an internal control. PGLP1 and SBPase protein abundance was determined by immunoblotting. Total soluble protein was extracted from mesophyll and guard cell-enriched fractions from the same leaves, and equal amounts (5 µg per lane) were separated by SDS-PAGE and electroblotted onto polyvinylidene difluoride (PVDF) membranes. Blots were probed with specific anti-PGLP1 ([ 1 ] or anti-SBPase [64] antibodies. GDC-H and RbcL antibodies (Agrisera, Vännäs, Sweden) were used as loading and normalization controls. Signal detection was performed via chemiluminescence, and densitometric quantification was carried out using ImageJ ( https://imagej.net/ ) from at least three independent biological replicates. Isolation of mesophyll and guard cell protein extracts Mesophyll- and guard cell-enriched fractions were obtained as described previously, [65] with minor modifications. Fully expanded leaves from 5-6-week-old plants grown under standard conditions were harvested at mid of the day (~ 6 h illumination). Transparent adhesive tape was applied to either the abaxial (for guard cell enrichment) or adaxial (for mesophyll enrichment) leaf surface. Peels (~ 20–50 per genotype, as mixture from at least 4 biological replicates) were gently removed, pooled by fraction, and immediately frozen in liquid nitrogen. Protein extraction was performed essentially as described earlier [65] and protein concentrations were determined using the BCA Protein Assay Kit (Thermo Scientific, Osterode, Germany) according to manufacturers instruction, with bovine serum albumin (BSA) as standard. Guard cell properties and guard cell starch content To determine diagnostic parameters associated with GC morphology, epidermal peels were prepared from fully expanded rosette leaves of plants grown under standard conditions, harvested at midday (~ 6 h of illumination). Nail polish was applied to the abaxial surface of each leaf and allowed to dry for 10 min. The epidermis was gently peeled off, mounted in water on microscope slides, and covered with a coverslip. Four biological individuals per genotype were analyzed. GC parameters (area, length, width, density and index) were measured using an Olympus U-LH100HG microscope (Olympus Corporation, Japan) and the manufacturer’s image analysis software. Starch content in GC was assessed in epidermal peels harvested at midday (~ 6 h of illumination) following propidium iodide staining as described before [ 45 ]. Four biological replicates per genotype were used, with 10 guard cells randomly selected per stained peel. Fluorescence images were acquired using a Keyence BZ-X800 fluorescence microscope (Keyence Deutschland GmbH, Neu-Isenburg, Germany) equipped with a Plan Fluorite 20-100x LD PH objective at 100x magnification. Fluorescence was visualized with the BZ-X GFP filter cube (exposure time: 1/70 s) and captured with BZ-X800 Viewer software. Quantitative analysis of GC starch was performed by measuring fluorescence intensity per cell using the manufacturer’s software. Guard Cell H 2 O 2 Content Determination Reactive oxygen species (ROS), primarily H 2 O 2 , in GC were visualized using 2′,7′-Dichlorodihydrofluorescein diacetate (H 2 DCFDA) fluorescence staining as described previously [ 46 ], using plants grown in air to stage 5.1 [ 43 ]. The lower epidermis was carefully excised and incubated in 100 µM H 2 DCFDA prepared in 10 mM Tris-HCl buffer (pH 7.2) in the dark for 10 min. Excess dye was removed, and the peels were washed three times with 10 mM Tris-HCl (pH 7.2). Fluorescence images were captured using a Keyence BZ-X800 fluorescence microscope (Keyence Deutschland GmbH, Neu-Isenburg, Germany) equipped with a Plan Fluorite 100x LD PH objective. H 2 DCFDA fluorescence was visualized using the GFP filter cube, and images were acquired with the BZ-X800 Viewer software. Quantification of fluorescence intensity in GC was performed using the same software. Gas Exchange Measurements Gas exchange was measured using LI-6400 and LI-6400XT Portable Photosynthesis Systems equipped with a 2 cm − 2 LED leaf chamber fluorometer and red/blue light source (LI-COR Biosciences, Lincoln, NE, USA). Prior to each measurement day, CO 2 and H 2 O analyzers were calibrated according to the manufacturer’s instructions. Fully expanded rosette leaves from plants grown under standard conditions (light intensity ~ 120–140 mmol m − 2 s − 1 ) were clamped in the cuvette and pre-acclimated for 10 min at 1000 µmol m − 2 s − 1 photosynthetic photon flux density (PPFD; 10% blue light) to reach stable steady-state photosynthesis. Basic settings were as follows: 25°C block temperature, 400 µmol mol − 1 CO 2 , 300 µmol s − 1 flow rate, and ~ 50–70% relative humidity. CO 2 response ( A / C i ) curves were measured under constant 21% O 2 and varying CO 2 concentrations as follows: 400, 300, 200, 100, 50, 25, 0, 400 ppm. To determine the oxygen-dependence of the net CO 2 compensation point, the O 2 concentration was adjusted to 3%, 21% and 40% O₂ (balanced with N 2 ), using the gas mixing device GMS600 (QCAL Messtechnik, München, Germany). The net CO 2 assimilation rate ( A N ), stomatal conductance ( g s ), intercellular CO₂ concentration ( C i ), transpiration rate ( E ), intrinsic water-use efficiency ( WUE int ), and CO₂ compensation point ( Γ ) were calculated by the LI-6400 and Excel software. O 2 inhibition of A N was calculated from measurements at 21% and 40% O 2 using equation: O 2 inhibition = (A 21 – A 40 ) / A 21 × 100. Calculation of γ (measure of the photorespiratory CO 2 -release) was performed by linear regression of the Γ -versus-O 2 concentration curves and is given as slopes of the respective functions. Light response curves were measured under ambient CO 2 and O 2 levels (10 min acclimation at 1000 µmol m − 2 s − 1 PPFD), followed by stepwise reduction of PPFD to 1600, 1200, 800, 400, 200, 100, 50, 25, and 0 µmol m − 2 s − 1 , allowing 2–3 min for stabilization at each step. At least six independent plants per genotype were measured and values are given as means ± SD. Chlorophyll fluorescence measurements Selected PSI and PSII parameters associated with photosynthetic light reactions were determined by standard chlorophyll fluorescence measurements on a Dual-PAM 100 (Heinz Walz, Effeltrich, Germany). Chlorophyll fluorescence measurements were performed on the adaxial leaf surface. PSI activity was determined by monitoring P700 absorbance, which reflects excitation across the entire leaf tissue, whereas PSII activity was assessed via chlorophyll fluorescence, which predominantly originates from a defined layer of chloroplasts within the leaf mesophyll. Following 10 min dark adaptation, F v / F m (maximum quantum efficiency of PSII) and P m (maximum photo-oxidizable P700) values were recorded. Next, plants were exposed to 1000 µmol photons m − 2 s − 1 for 10 min to fully induce photosynthesis and, subsequently, light response curves were measured (PPFD: 1759, 1144, 757, 488, 236, 143, 62, 36, and 0 µmol photons m − 2 s − 1 ) at 400 ppm CO 2 and 21% O 2 . Metabolite analysis For absolute quantification of metabolites associated with primary metabolism, we used liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and gas chromatography (GC) analysis. Fully expanded rosettes were harvested under growth light at the end of the photoperiod (after 11 h illumination). All samples were collected within a 10-min window to minimize variation, immediately quenched in liquid nitrogen, and stored at − 80°C. Prior further processing, the frozen material was lyophilized, and ~ 2–3 mg dry weight per sample was aliquoted for extraction. For metabolite extraction and LC-MS/MS measurements, we used LC-MS grade chemicals and the procedure described before [66]. Measurements were carried out on a high-performance liquid chromatograph mass spectrometer LCMS-8050 system (Shimadzu, Japan) and the incorporated LC-MS/MS method package for primary metabolites (version 2, Shimadzu). Selected soluble sugars and starch were measured on the gas chromatograph 6890 N GC System (Agilent Technologies, Waldbronn, Baden-Württemberg, Germany) and spectrophotometrically measurements essentially as described previously [ 37 ]. For each metabolite, absolute concentrations were determined using calibration curves generated from authentic standards measured in parallel. Results were normalized to dry weight and reported as nmol mg − 1 DW (LC-MS/MS) or µg g − 1 DW (GC). Statistical Analysis We used the programs Microsoft Excel (Microsoft Corporation, 2018) and SigmaPlot vol. 13.0 (Systat Software Inc., 2014) for data processing and graph generation, CorelDraw (Graphics Suite 2017; www.corel.com ) was used for image compilation. Statistical differences were determined through analysis of variance analysis (ANOVA; SPSS Statistics 27, IBM). The term significant is used here only if the change in question has been confirmed to be significant at the level of p < 0.05. Declarations Acknowledgements We thank Prof. Hendrik Schubert and Junior Professor´s Andreas Richter and Klaus Herburger for providing access and support with the Dual PAM-100, microscopy facilities, and gas chromatography. We are grateful to Klaudia Michl and Kathrin Jahnke (University of Rostock) for excellent technical assistance, and to Emeritus Prof. Hermann Bauwe and Prof. Christine Raines for kindly sharing the PGLP1 and SBPase antibodies. H.S. acknowledges a scholarship from the China Scholarship Council (CSC). This work was supported by the University of Rostock (to M.H. and S.T.). Competing interests The authors declare no competing interests. Author Contributions: S.T. conceived and supervised the project. H.S., I.T., and S.T. designed the research. N.S. and S.T. performed cloning procedures and established the transgenic lines. H.S. and I.T. performed the research. H.S., I.T., J.K., T.L., M.H., and S.T. analyzed the data. M.H. provided experimental equipment and tools. H.S. and S.T. wrote the article, with additions and revisions from J.K., T.L., and M.H. All authors have read and approved the final version of the manuscript. Data availability: All relevant data are provided in the main text and Supplemental data area of the manuscript. 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06:50:51","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":175801,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/3a22fd07224ccb7457c6f7cc.html"},{"id":97850707,"identity":"77c08e85-6009-4b3c-8107-f1bb4e0c4851","added_by":"auto","created_at":"2025-12-10 06:50:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":393136,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProtein expression and growth of Arabidopsis lines with GC-specific \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePGLP1 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eoverexpression or antisense repression under ambient and elevated CO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e levels.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e PGLP1 protein expression in GC (left panel) and MC (right panel). GDC-H and RbcL protein amounts were quantified from the same membrane as control. \u003cstrong\u003e(B)\u003c/strong\u003e Photographs of the transgenic lines and the wildtype after 6 weeks in air (upper panel) or 4 weeks in high CO\u003csub\u003e2\u003c/sub\u003e (lower panel) with a 12/12 h day-/night-cycle. \u003cstrong\u003e(C)\u003c/strong\u003e Correlation plots of growth parameters and GC PGLP1 protein abundances in air (upper panel) and high CO\u003csub\u003e2\u003c/sub\u003e (lower panel). Given are means ± SD of (A) three independent immunoblots and (C) six biological replicates (for full numerical growth data see Supp. Table S1).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/1dd914b8e1bee888183fc4b7.png"},{"id":97898894,"identity":"88697dc9-19b7-43f2-a94b-bc161556e8e3","added_by":"auto","created_at":"2025-12-10 15:40:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":214538,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhotosynthetic gas exchange in Arabidopsis lines with GC-specific \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePGLP1 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eoverexpression or antisense repression under different light and O\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e levels.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlant were grown in air to stage 5.1 [43] to determine photosynthetic gas exchange as functions of light intensity and O\u003csub\u003e2\u003c/sub\u003e concentrations. Selected parameters of the light response curves are given as follows: \u003cstrong\u003e(A)\u003c/strong\u003e Net CO\u003csub\u003e2\u003c/sub\u003e uptake rates (\u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e), \u003cstrong\u003e(B)\u003c/strong\u003e stomatal conductance (\u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e), and \u003cstrong\u003e(C)\u003c/strong\u003e correlation plot of \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e versus \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e. Selected parameters of the CO\u003csub\u003e2\u003c/sub\u003e response curves are presented as follows: \u003cstrong\u003e(D)\u003c/strong\u003e \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e, including the oxygen inhibition of photosynthesis as inlet, \u003cstrong\u003e(E)\u003c/strong\u003e \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e, and \u003cstrong\u003e(F)\u003c/strong\u003e CO\u003csub\u003e2\u003c/sub\u003e compensation points (\u003cem\u003eΓ\u003c/em\u003e), including the slope of the \u003cem\u003eΓ\u003c/em\u003e-versus-O\u003csub\u003e2\u003c/sub\u003e concentration functions (\u003cem\u003eγ\u003c/em\u003e) as inlet. Correlation plots of \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eΓ\u003c/em\u003e at 21% O\u003csub\u003e2\u003c/sub\u003e (air) are displayed at the bottom of each figure. Given are means ± SD of 6 biological replicates. Values that do not share the same letter are significantly different from each other as determined by ANOVA. Further photosynthetic parameters and full numerical data, including statistical evaluation, are provided as Supp. Tables S2-S5.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/cca09e3ea01a1468026b128f.png"},{"id":97850711,"identity":"40e20cf5-e13e-4b95-a549-22e9b6a117e2","added_by":"auto","created_at":"2025-12-10 06:50:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":149983,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacteristic stomata parameters in Arabidopsis lines with GC-specific \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePGLP1 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eoverexpression or antisense repression and Arabidopsis wildtype-plants grown with 2-PG supplementation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlant were grown on soil in \u003cstrong\u003e(A) \u003c/strong\u003eair (400 ppm CO\u003csub\u003e2\u003c/sub\u003e) to stage 5.1 [43] to determine stomata parameters. Displayed are correlation plots of selected stomatal parameters and GC-specific PGLP1 protein expression in the transgenic lines and the wildtype. Displayed are means ± SD (Σ 120 stomata per genotype was analyzed, from 4 biological replicates and 30 stomata per leaf) The corresponding high CO\u003csub\u003e2\u003c/sub\u003e and all uncorrelated data are shown in Supp. Fig. S3. The full numerical data is also provided as Supp. Table S6). Values that do not share the same letter are significantly different from each other as determined by ANOVA. \u003cstrong\u003e(B)\u003c/strong\u003e Arabidopsis wildtype in air (400 ppm CO\u003csub\u003e2\u003c/sub\u003e) on half strength MS media supplemented with different 2-PG concentrations (0, 10, 50 and 100 µM). After 2-3 weeks stomatal parameters were determined by microscopic analysis as means ± SD (Σ 120 stomata per genotype, from 4 biological replicates and 30 stomata per leaf). Numbers in brackets indicate the reduction (in %, compared to control) with increased 2-PG amounts: stomatal area (-3.2%, -11.4% and -22.3%), stomatal length (-2.3%, -5.9% and -9.5%), stomatal width (-2.7%, -3.0% and -11.5%), stomatal density (no significant changes), and stomatal index (-10.7%, -20.4% and -27.7%). Full numerical data is provided in Supp. Table S7). Values that do not share the same letter are significantly different from each other as determined by ANOVA.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/90a04531dd1a9ef6e4ab71b0.png"},{"id":97850718,"identity":"9b77933b-ab2b-422e-9122-6f975693e34c","added_by":"auto","created_at":"2025-12-10 06:50:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":179895,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelected metabolites in leaves and guard cells of Arabidopsis lines with GC-specific \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePGLP1 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eoverexpression and antisense repression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlants were grown in air (400 ppm CO\u003csub\u003e2\u003c/sub\u003e) to growth stage 5.1 [43]. Leaf-material was harvested at end of the day (11 h illumination) and analysed by \u003cstrong\u003e(A-C) \u003c/strong\u003egas chromatography (GC), \u003cstrong\u003e(D) \u003c/strong\u003espectrophotometrically, LC-MS/MS) liquid chromatography coupled to tandem mass spectrometry \u003cstrong\u003e(E-H)\u003c/strong\u003e and microscopic \u003cstrong\u003e(I-J)\u003c/strong\u003e analysis. Values are means ± SD (n \u0026gt; 6). Values that do not share the same letter are significantly different from each other as determined by ANOVA. Full numerical data set of all metabolites are provided in Supp. Table S8).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/efa83060ed14e743feed7765.png"},{"id":97898692,"identity":"41394c9c-a16a-4a61-a785-6cf103d8f5c3","added_by":"auto","created_at":"2025-12-10 15:39:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":289000,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eModel illustrating the impact of guard cell PGLP1 on stomatal behavior\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePhotorespiration is a highly compartmentalized process involving reactions in the chloroplast, peroxisome, mitochondrion, cytosol, and vacuole. While its roles and physiological implications are well established at the whole-leaf level, particularly in the mesophyll, its function in specific tissues and cell types remains largely enigmatic. Guard cell-specific manipulation of photorespiratory 2-PG removal, achieved through upregulation or antisense repression of PGLP1, reveals photorespiration as a key component of guard cell metabolism as well as stomatal behavior and development. Mechanistically, we propose that changes in CO\u003csub\u003e2\u003c/sub\u003e availability are sensed via the capacity of the photorespiratory flux, with the amount of the photorespiration-specific entrance metabolite 2-PG in chloroplasts serving as a key determinant. On the one hand, high chloroplast PGLP1 activity maintains low 2-PG levels and alleviates negative impacts on CBBC performance, starch biosynthesis, and ROS accumulation, particularly H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, thereby supporting the carbohydrate and energy status required to drive stomatal movements. On the other hand, reduced PGLP1 activity leads to 2-PG accumulation in chloroplasts, which slows the CBBC, decreases carbohydrate availability and metabolism, and promotes H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2 \u003c/sub\u003eaccumulation. Consequently, stomata tend to remain more closed to prevent further damage to guard cells and the whole leaf resulting from Rubisco oxygenation and impaired photorespiration. Abbreviations: 2-PG - 2-phosphoglycolate; 3-PGA - 3-phosphoglycerate; 3-HP – 3-hydroxypyruvate; CBBC – Calvin-Benson-Bassham cycle; CAT – catalase; ETR – electron transport chain; GDC – glycine decarboxylase; \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e – stomatal conductance; Hex-P – hexose phosphates; OAA – oxaloacetate; PEP – phosphoenolpyruvate; PGLP – 2-PG phosphatase; Pyr – pyruvate; ROS – reactive oxygen species; SHMT1 – serine-hydroxymethyltransferase 1; TCA – tricarboxylic acid cycle\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/754237a78c58d8a03f6095c8.png"},{"id":105750356,"identity":"4f10302d-40a8-4dcb-b69b-e4a969062bdc","added_by":"auto","created_at":"2026-03-30 15:16:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3535407,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/14939dc2-2b0f-4702-85e7-605eccf3c243.pdf"},{"id":97850728,"identity":"00ed3588-4067-4912-968f-76dabf878d00","added_by":"auto","created_at":"2025-12-10 06:50:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1724663,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"GuardcellphotorespirationcontrolsstomatabehavioranddevelopmentSupplementaryMaterialvol.01.docx","url":"https://assets-eu.researchsquare.com/files/rs-8223718/v1/56fae14f2d1315f2a2a81282.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Guard cell photorespiration controls stomata behavior and development","fulltext":[{"header":"One-sentence summary","content":"\u003cp\u003eTargeted manipulation of guard cell \u003cem\u003ePGLP1\u003c/em\u003e reveals that efficient photorespiratory 2-PG metabolism is crucial for stomatal dynamics and plant performance.\u003c/p\u003e"},{"header":"Main Document","content":"\u003cp\u003ePlant photosynthesis converts atmospheric CO\u003csub\u003e2\u003c/sub\u003e into sugars that sustain the global food chain. Under the present day high O\u003csub\u003e2\u003c/sub\u003e/CO\u003csub\u003e2\u003c/sub\u003e ratio, photosynthetic efficiency is limited by Rubisco\u0026rsquo;s oxygenase activity, which generates 2-phosphoglycolate (2-PG), a potent inhibitor of the Calvin-Benson-Bassham (CBB) cycle enzymes sedoheptulose-1,7-bisphosphatase (SBPase) and triosephosphate isomerase (TPI) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Photorespiration exclusively removes 2-PG to prevent metabolic inhibition, yet it is energetically costly and releases previously fixed CO\u003csub\u003e2\u003c/sub\u003e and NH\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Beyond its essential repair function, photorespiration supports \u003cem\u003ede novo\u003c/em\u003e nitrogen and sulfur assimilation, amino acid biosynthesis, one-carbon metabolism, and redox balance, thereby contributing to acclimation under fluctuating conditions [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These Janus-faced roles, protective but metabolically expensive, make photorespiration a key target for improving plant productivity under current and future climates [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLeaf-mesophyll photorespiration is well-characterized, but its function in specific cell types remains largely unexplored. Although the pathway is highly compartmentalized, spanning chloroplasts, mitochondria, peroxisomes, cytosol, and vacuoles [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], its interaction with other metabolic routes is not well resolved. Recent isotopically non-stationary metabolic flux analyses (INST-MFA) showed that a substantial fraction of carbon exits the canonical cycle, feeding other biosynthetic routes including C1-carbon metabolism, mainly as serine and glycine [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This implies that certain reactions exert disproportionate control over the photorespiratory flux and may regulate carbon utilization and partitioning in distinct compartments. Genetic studies have highlighted two key control points: mitochondrial glycine decarboxylase (GDC) and chloroplast-localized 2-PG phosphatase 1 (PGLP1). Both enzymes share a strong positive correlation with the photorespiratory flux, CBB cycle operation, starch biosynthesis, and plant growth, making them attractive targets for improved yield [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePhotorespiratory rates are determined by the CO\u003csub\u003e2\u003c/sub\u003e/O\u003csub\u003e2\u003c/sub\u003e ratios in chloroplast, which largely depend on opening of stomata, formed by pairs of guard cells (GC) in the leaf epidermis. In addition to flux of CO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e2\u003c/sub\u003e, stomatal opening regulates water vapor movements, balancing carbon gain with water conservation [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Stomatal size and density are inversely related and determine maximum stomatal conductance (\u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003esmax\u003c/em\u003e\u003c/sub\u003e); small, numerous stomata support fast stomatal kinetics [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and higher gas exchange than few, large stomata. Across evolutionary timescales, high atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentrations ([CO\u003csub\u003e2\u003c/sub\u003e]) favored fewer, larger stomata, whereas low [CO\u003csub\u003e2\u003c/sub\u003e] selected for smaller, denser stomata [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. On daily timescales, stomatal size and density will not change, but GC respond dynamically to environmental cues, including light, internal [CO\u003csub\u003e2\u003c/sub\u003e], temperature, humidity, and water availability. Light is a dominant driver, red light triggers GC osmoregulation and transmits mesophyll signals that align stomatal opening with photosynthetic demand [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], while blue light acts independently of photosynthesis, directly via phototropin kinases to induce rapid opening at low fluence rates, particularly at dawn and during transient sunlight fluctuations, maximizing carbon assimilation [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Stomatal closure is mainly achieved via the plant hormone abscisic acid (ABA), maintaining overall plant water status [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIntercellular CO\u003csub\u003e2\u003c/sub\u003e (\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e) is regarded as another important factor controlling stomata. For example, \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e elevation with decreasing photosynthesis, darkness or via raised external [CO\u003csub\u003e2\u003c/sub\u003e] promotes stomatal closure, whereas light-dependent draw-down of \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e via photosynthetic CO\u003csub\u003e2\u003c/sub\u003e fixation maintains opening [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Rising global [CO\u003csub\u003e2\u003c/sub\u003e] reduces stomatal aperture and density, lowering conductance and conserving water, yet potentially increasing leaf temperature under drought. At the molecular level, CO\u003csub\u003e2\u003c/sub\u003e responses require the protein kinase high leaf temperature 1 (HT1) and converge with abscisic acid (ABA) signaling, because elevated [CO\u003csub\u003e2\u003c/sub\u003e] increases guard-cell ABA to induce closure. Thus, stomatal behavior integrates red/blue light signals, CO\u003csub\u003e2\u003c/sub\u003e feedback, and hormonal cues to balance carbon gain, water use, and thermal stability [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to photorespiration, the activity of Rubisco carboxylation and the flux through the CBB cycle also responds to fluctuating CO\u003csub\u003e2\u003c/sub\u003e/O\u003csub\u003e2\u003c/sub\u003e ratios. It has been shown that SBPase activity might be a control point of the CBB cycle flux, because its overexpression in plants enhanced photosynthesis and yield [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Comparable effects have been observed in overexpressors of key photorespiratory enzymes such as GDC and PGLP1 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], whereas impairment of photorespiration diminished productivity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Interestingly, the recently reported GC-specific manipulation of GDC suggested a functional link between mitochondrial photorespiratory metabolism and stomatal regulation [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. If this finding is specific for mitochondria or GDC, releasing CO\u003csub\u003e2\u003c/sub\u003e during photorespiration thereby eventually affecting \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e, remains unknown. However, initial pharmacological studies on photorespiratory enzymes in epidermal peals indirectly supported a functional interaction between the activity of certain photorespiratory enzymes and stomatal movements [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Surprisingly, the role of PGLP1, the photorespiration-specific 2-PG degrading enzyme, in GC is still unclear. Gaining insights into its physiological significance is interesting because of the reduced GC chloroplast count and size, alongside with hinds for the sink-tissue-like characteristics of GC, and the ongoing debate to which extent GC rely on their own internal photosynthesis [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo address this question, we analyzed the impact of GC-specific manipulation of the central photorespiratory enzyme, chloroplastidal PGLP1. The transgenic lines with in- and de-creased GC-specific \u003cem\u003ePGLP1\u003c/em\u003e expression were assessed to study its role in GC metabolism and impact on stomata function, photosynthesis and biomass accumulation. By elucidating the role of photorespiration in these specialized cells, our work not only provides new insights into its significance for GC metabolism but also provided the foundation for new strategies to engineer crops with enhanced growth, water-use efficiency, and yield, key traits to meet the challenges of plant production under increasing climate change.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eGuard cell PGLP1 expression exerts control over growth and biomass accumulation\u003c/h2\u003e\n \u003cp\u003eTo determine the role of photorespiration, particularly 2-PG degradation, in GC of the C3 plant Arabidopsis, we used the guard cell-specific GC1 promoter [\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e] to specifically manipulate GC \u003cem\u003ePGLP1\u003c/em\u003e expression (Supp. Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). Overexpression (sense lines: SL4\u0026thinsp;+\u0026thinsp;15% and SL7\u0026thinsp;+\u0026thinsp;24%) and antisense repression (antisense lines: AL4 -15% and AL5 -13%) of \u003cem\u003ePGLP1\u003c/em\u003e was observed in GC, while PGLP1 protein abundances remained unaltered in mesophyll cells (MC) of the same leaves (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). Increased expression of \u003cem\u003ePGLP1\u003c/em\u003e in GC stimulated, whilst antisense repression reduced the apparent growth of Arabidopsis under photorespiratory conditions (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). Diagnostic growth parameters followed this consistent pattern, as leaf number, rosette diameter, fresh and dry weights positively correlated with GC PGLP1 protein expression (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC; Supp. Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, growth alterations relied on active photorespiration, as no growth differences were observed with plants grown in high CO\u003csub\u003e2\u003c/sub\u003e (3000 ppm), strongly suppressing 2-PG formation and photorespiration (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB-C; Supp. Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eGC PGLP1 shapes photosynthetic CO assimilation and stomatal conductance\u003c/h3\u003e\n\u003cp\u003eTo test if growth changes are due to altered photosynthesis, we measured chlorophyll a fluorescence and gas exchange parameters of plants grown under photorespiratory conditions. Whilst PSI and PSII efficiencies and related parameters associated with photosynthetic light reactions did not significantly vary among the genotypes (Supp. Fig. S2; Supp. Table S2), light-dependent net CO\u003csub\u003e2\u003c/sub\u003e assimilation (\u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e) and stomatal conductance (\u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e) followed the growth pattern. Thus, \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e displayed a positive correlation with GC \u003cem\u003ePGLP1\u003c/em\u003e expression (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). Transpiration rates (\u003cem\u003eE\u003c/em\u003e), maximum photosynthetic rates (\u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e) and the slope of the light response curves (\u003cem\u003e\u0026alpha;\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e) followed this tendency (Supp. Table S3). Intracellular CO\u003csub\u003e2\u003c/sub\u003e concentrations (\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e) were only significantly decreased in the antisense lines, whilst intrinsic water use efficiency (\u003cem\u003eiWUE\u003c/em\u003e) showed only minor alterations (Supp. Table S4). To check if photosynthetic stimulations rely on altered photorespiratory 2-PG turnover in GC, we measured photosynthesis at three different O\u003csub\u003e2\u003c/sub\u003e concentrations (3, 21 and 40%) to suppress or stimulate 2-PG formation. At low photorespiratory flux requirements (3% O\u003csub\u003e2\u003c/sub\u003e), no significant changes on \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e, and the CO\u003csub\u003e2\u003c/sub\u003e compensations points (\u003cem\u003e\u0026Gamma;\u003c/em\u003e) were observed (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD-F). However, at air O\u003csub\u003e2\u003c/sub\u003e levels (21%) \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e was increased in overexpressor (\u003cem\u003e~\u003c/em\u003e\u0026thinsp;19%) and decreased in antisense lines (~\u0026thinsp;13%), whilst \u003cem\u003e\u0026Gamma;\u003c/em\u003e displayed inverse tendencies (~\u0026thinsp;10% lower in overexpressors and ~\u0026thinsp;14% higher in antisense lines). Interestingly, \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e, a parameter directly related to stomatal opening, was positively correlated with GC PGLP1 protein amounts and was higher (\u003cem\u003e~\u003c/em\u003e\u0026thinsp;29%) or lower (~\u0026thinsp;16%) in the overexpressor and antisense lines, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE, Supp. Table S5). The described patterns were similar at 40% O\u003csub\u003e2\u003c/sub\u003e, i.e. photorespiration-stimulating conditions, but with stronger specification. In the overexpression lines \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e were stimulated (~\u0026thinsp;49% and 60%) and \u003cem\u003e\u0026Gamma;\u003c/em\u003e decreased (~\u0026thinsp;17%), whilst antisense repression caused a reduction in \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e (~\u0026thinsp;33% and 27%) and a corresponding increase (~\u0026thinsp;15%) in \u003cem\u003e\u0026Gamma;\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD-F). The calculated O\u003csub\u003e2\u003c/sub\u003e sensitivity revealed overexpression lines were less and antisense lines more sensitive to O\u003csub\u003e2\u003c/sub\u003e compared with the wildtype (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD, inlet). Finally, the slope of the \u003cem\u003e\u0026Gamma;\u003c/em\u003e-vs-O\u003csub\u003e2\u003c/sub\u003e concentration (\u003cem\u003e\u0026gamma;\u003c/em\u003e), representing a measure of photorespiratory CO\u003csub\u003e2\u003c/sub\u003e release, revealed that GC \u003cem\u003ePGLP1\u003c/em\u003e overexpression caused a significant reduction, whilst antisense suppression an increase in photorespiratory CO\u003csub\u003e2\u003c/sub\u003e losses (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eF, inlet).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGC PGLP1 expression correlates with stomatal size, a morphological response that is inducible by external 2-PG feeding to wildtype Arabidopsis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs GC PGLP1 amounts correlated with \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e, we analysed stomata count and size of all genotypes grown in air and elevated CO\u003csub\u003e2\u003c/sub\u003e to compare the impact of photorespiratory and non-photorespiratory conditions. As displayed in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, stomata size, index, and density (significant only in the overexpressors), corelated with GC PGLP1 expression, as these parameters were in- and decreased in overexpression and antisense lines, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, Supp Fig. S3). These changes were photorespiration-dependent as they were absent in high CO\u003csub\u003e2\u003c/sub\u003e-grown plants (Supp. Fig. S3). Based on these findings, we hypothesized if altered GC PGLP1 expression and 2-PG amounts could serve as morphogenetic signal for stomatal development. To test this assumption, increasing 2-PG concentrations (0, 10, 50, 100 \u0026micro;M) were externally applied to Arabidopsis wildtype-plants during cultivation on agar plates. Interestingly, characteristic stomatal determinants showed a negative correlation with external 2-PG application, as we measured gradually decreased length, width and smaller stomatal area and index compared to the control plants, lacking 2-PG in the growth media. However, 2-PG treatment had only minor effects on stomata density (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariations in whole-leaf primary metabolism is restricted to soluble sugars, total amino acid and organic acid contents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause of the growth and photosynthetic responses of the transgenic lines, we quantified soluble sugars, starch, and 33 representatives of primary metabolism in leaves of all genotypes. Glucose and fructose levels were significantly higher in overexpression and lower in antisense lines. Sucrose was only higher in overexpressors (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA-C), while transitory starch did not differ among genotypes (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD). Further, leaf 2-PG and NAD\u003csup\u003e+\u003c/sup\u003e amounts showed a negative, whilst 3-PGA a positive correlation with GC PGLP1 expression (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eE-F; Supp. Table S8). Among the other primary metabolites, we measured significant increases in glutamate, isoleucine, and isocitrate in the overexpression lines and significantly decreased arginine in the antisense lines. However, the calculation of total soluble sugars, amino and organic acid contents revealed all to increase and decrease in the GC \u003cem\u003ePGLP1\u003c/em\u003e overexpressors and antisense lines, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eG-H; Supp. Tab. S8).\u003c/p\u003e\n\u003ch3\u003eManipulation of GC PGLP1 expression impacts on guard cell starch and HO contents\u003c/h3\u003e\n\u003cp\u003ePrevious work suggested that GC starch and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e amounts are involved in the energization and regulation of stomatal movements [\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]. Hence, these parameters were measured under photorespiratory conditions, as no phenotypic or stomatal size variation were observed in high CO\u003csub\u003e2\u003c/sub\u003e-grown plants. At one hand, we found a strong positive correlation between GC PGLP1 amounts and GC starch, which was significantly higher (~\u0026thinsp;19\u0026ndash;25%) in the overexpression and lower (~\u0026thinsp;29\u0026ndash;32%) in the antisense lines. On the other hand, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e amounts were negative correlated with GC PGLP1 expression, being lower (~\u0026thinsp;31\u0026ndash;36%) in overexpression and higher (~\u0026thinsp;27\u0026ndash;29%) in antisense lines compared to the wildtype (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eI-J). Again, alterations in guard cell starch and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e are photorespiration-dependent as both were statistically invariant among the analysed genotypes when grown under non-photorespiratory conditions, i.e. high CO\u003csub\u003e2\u003c/sub\u003e (Suppl. Table S8).\u003c/p\u003e\n\u003ch3\u003eGuard cell SBPase expression has no major impact on growth and photosynthesis\u003c/h3\u003e\n\u003cp\u003eGiven SBPase expression in leaves of various plants species positively correlates with growth and photosynthesis, and the fact that 2-PG is a potent inhibitor of SBPase activity [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e], we also manipulated the GC-specific SBPase protein expression. In clear contrast to PGLP1 manipulations, we did not observe any significant impact on the visual phenotype and quantitative growth parameters of overexpression (+\u0026thinsp;11.3\u0026ndash;15.7% GC SBPase protein expression) and antisense (-12.6-22.48% GC SBPase protein expression) lines under the same growth conditions (Supp. Fig. S4-S5). Furthermore, no significant change was seen on selected photosynthetic parameters, including \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e, and \u003cem\u003e\u0026Gamma;\u003c/em\u003e (Supp. Fig. S4), measured as functions of varying light and CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePhotorespiration is an unavoidable process in the primary C and N metabolism of plants, because it enables photosynthetic CO\u003csub\u003e2\u003c/sub\u003e assimilation by detoxifying the Rubisco oxygenation product 2-PG [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While the toxic effect of 2-PG on plant metabolism is well established [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], it could also play a role as low CO\u003csub\u003e2\u003c/sub\u003e-sensing molecule in oxygenic phototrophs as discussed to occur among cyanobacteria [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. However, if 2-PG plays such a role among plants remained uncertain to date. To address the question if 2-PG is involved in CO\u003csub\u003e2\u003c/sub\u003e-dependent stomata movements, we specifically manipulated the expression of the 2-PG-metabolizing enzyme PGLP1 in stomatal guard cells. This approach revealed a previously unrecognized function of PGLP1 or 2-PG in coordinating GC metabolism with stomatal behavior (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePhotorespiration is a highly compartmentalized process involving reactions in the chloroplast, peroxisome, mitochondrion, cytosol, and vacuole. While its roles and physiological implications are well established at the whole-leaf level, particularly in the mesophyll, its function in specific tissues and cell types remains largely enigmatic. Guard cell-specific manipulation of photorespiratory 2-PG removal, achieved through upregulation or antisense repression of PGLP1, reveals photorespiration as a key component of guard cell metabolism as well as stomatal behavior and development. Mechanistically, we propose that changes in CO\u003csub\u003e2\u003c/sub\u003e availability are sensed via the capacity of the photorespiratory flux, with the amount of the photorespiration-specific entrance metabolite 2-PG in chloroplasts serving as a key determinant. On the one hand, high chloroplast PGLP1 activity maintains low 2-PG levels and alleviates negative impacts on CBBC performance, starch biosynthesis, and ROS accumulation, particularly H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, thereby supporting the carbohydrate and energy status required to drive stomatal movements. On the other hand, reduced PGLP1 activity leads to 2-PG accumulation in chloroplasts, which slows the CBBC, decreases carbohydrate availability and metabolism, and promotes H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e accumulation. Consequently, stomata tend to remain more closed to prevent further damage to guard cells and the whole leaf resulting from Rubisco oxygenation and impaired photorespiration. Abbreviations: 2-PG \u0026minus;\u0026thinsp;2-phosphoglycolate; 3-PGA \u0026minus;\u0026thinsp;3-phosphoglycerate; 3-HP \u0026ndash; 3-hydroxypyruvate; CBBC \u0026ndash; Calvin-Benson-Bassham cycle; CAT \u0026ndash; catalase; ETR \u0026ndash; electron transport chain; GDC \u0026ndash; glycine decarboxylase; \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e \u0026ndash; stomatal conductance; Hex-P \u0026ndash; hexose phosphates; OAA \u0026ndash; oxaloacetate; PEP \u0026ndash; phosphoenolpyruvate; PGLP \u0026ndash; 2-PG phosphatase; Pyr \u0026ndash; pyruvate; ROS \u0026ndash; reactive oxygen species; SHMT1 \u0026ndash; serine-hydroxymethyltransferase 1; TCA \u0026ndash; tricarboxylic acid cycle\u003c/p\u003e\u003cp\u003eOur results provide a consistent picture: enhanced expression of PGLP1 in GC resulted in improved photosynthesis, higher stomatal conductance and enhanced growth, whereas antisense repression had opposite effects compared to wildtype (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Importantly, growth stimulation depended on Rubisco-mediated 2-PG formation and its subsequent photorespiratory metabolization, as the transgenic lines were indistinguishable from the wildtype under photorespiration-suppressing conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Supp. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Similarly, the differences in the photosynthetic parameters became larger when gas exchange measurements were done under high O\u003csub\u003e2\u003c/sub\u003e conditions, stimulating photorespiration, while at lowered O\u003csub\u003e2\u003c/sub\u003e levels they were virtually absent (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These findings suggest that GC metabolism is naturally constrained by PGLP1 activity under ambient, i.e., by the capacity of photorespiratory flux, and that increasing this capacity can benefit stomatal function through enhanced movement dynamics and energization (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This is particularly noteworthy given the ongoing debate regarding the extent to which GC perform photosynthesis and, perhaps, rely on active photorespiratory metabolism. Furthermore, GC PGLP1 limitation could be explained by specific features of these specialized cells, as they contain significantly fewer and smaller chloroplasts ([\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and, thus, have generally naturally lower abundances of photorespiratory proteins. Until recently, the overall significance of photorespiratory metabolism in GC remained unclear due to the absence of guard cell-specific transgenic approaches. The first GC-specific manipulation of the mitochondrial photorespiratory enzyme glycine decarboxylase (GDC) provided evidence that these specialized cells are indeed capable of, and to some extent dependent on, active mitochondrial photorespiration [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This conclusion is consistent with two recent proteomic studies on mitochondria isolated from GC and their specific ATP metabolism [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and earlier omics studies, showing the transcription and translation of the full photorespiratory core cycle in GC [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe stimulation of growth, photosynthesis and stomatal conductance is consistent with earlier studies showing that GC-specific modifications of different processes can positively influence \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Interestingly, the photorespiration-specific results presented here, in conjunction with our earlier report, show that reprogrammed photorespiration fluxes in different subcellular organelles have a clear and consistent impact on overall plant performance under ambient laboratory conditions. However, it remains unresolved whether higher photosynthetic rates arise directly from changes in \u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e or whether PGLP1, and thereby photorespiratory flux, modifications in GC signals increased CO\u003csub\u003e2\u003c/sub\u003e demand, which in turn prompts stomata to open more widely to support mesophyll photosynthesis and facilitate a higher energy status of the cells. Notably, the latter interpretation aligns with reports of photorespiratory optimizations, mainly PGLP1 and GDC overexpression, at the whole-leaf level, which also resulted in higher stomatal conductance [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Given the previously used ST-LSI promoter is not fully mesophyll-specific and also drives expression in GC, it could well be that the observed responses are also caused by expression changes of both enzymes in GC. Taken together, these observations support the hypothesis that photorespiratory flux capacity, mediated through reinforcement or alleviation of negative feedback on carbon utilization, could serve as a key determinant for sensing and translating changes in external (\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e) and internal (\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e) CO\u003csub\u003e2\u003c/sub\u003e availability. More specifically, and supported by our findings, we suggest that chloroplastidal 2-PG could mechanistically serve as signaling metabolite translating altered photorespiratory fluxes in response to changes in CO\u003csub\u003e2\u003c/sub\u003e availability. The ultimate readout of such a mechanism could be shifts in the availability of photosynthates and other biomolecules at the whole-leaf level. Indeed, the metabolite profiles of the transgenic models support this hypothesis, given GC PGLP1 protein expression positively correlated with soluble sugars, as well as the total amino acid and organic acid contents (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; Supp. Table S8). It should also be noted that changes in the GC photorespiratory flux, i.e. the chloroplastidal 2-PG amount, seem to be causative for optimized photosynthesis and growth, rather than alleviated negative feedback inhibition of the central CBB cycle enzyme SBPase as GC overexpression of the latter did not result in similar physiological responses (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGC starch availability and metabolism were reported to be a key determinate of GC energization and their rapid movements to acclimate to environmental fluctuations ([\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Although transitory starch stocks underwent no significant changes on the whole leaf basis among our transgenic plants, GC starch accumulation correlated with GC PGLP expression in the transgenic lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; Supp. Table S6). Hence, starch availability and turnover seem to be, at least to some extent, controlled by GC photorespiration. Similar alterations were found before, i.e., lowered 2-PG levels due to \u003cem\u003ePGLP1\u003c/em\u003e overexpression stimulated starch synthesis and elevated 2-PG levels due to \u003cem\u003ePGLP1\u003c/em\u003e antisense repressed starch accumulation on whole leaf basis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, if the different starch amounts in GC are a direct effect of altered GC photorespiration or its reprogrammed mesophyll metabolism and carbon import thereof has to be analyzed at higher resolution in the future. Nevertheless, increased GC starch seems to be a general response of GC overexpression of photorespiratory enzymes as similar observations were made on corresponding GDC manipulations [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to starch, the GC-localized amounts of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, another central player in stomatal regulation [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], were inversely correlated with GC PGLP1 expression in air (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ). The exact origin of the altered H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in our lines remains an open question. Photorespiratory H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e production seems unlikely, as flux scaling would predict opposite trends between overexpression and antisense lines, and the lack of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e variations in high CO\u003csub\u003e2\u003c/sub\u003e (Supp. Table S8). Alternative sources, such as imbalances in mitochondrial or chloroplastidial electron transport and thereby produced H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, also lack support from our fluorescence and rETR(i) data. By contrast, NADPH oxidase activity emerges as a plausible candidate, potentially explaining the observed discrepancy between H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e accumulation and stomatal aperture. An additional possibility is that changes in ROS detoxification capacity contribute to the altered H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e profiles. Hence, in addition to the observed metabolic alterations, our findings highlight a potential role of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in linking GC PGLP1 activity and its potential role in CO\u003csub\u003e2\u003c/sub\u003e sensing to stomatal function. Typically, low concentrations of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e promote stomatal opening via nuclear localization of KIN10 and subsequent induction of BAM1 and AMY3, driving starch degradation [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. At higher concentrations, however, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e triggers stomatal closure through activation of Ca\u003csup\u003e2+\u003c/sup\u003e channels and the anion channel SLAC1, largely mediated by NADPH oxidases (RBOHs) [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs discussed above, stomatal conductance could be directly or indirectly related to the reprogrammed GC metabolism via GC-specific PGLP1 manipulation. However, in contrast to the manipulation of GC-specific photorespiration due to GDC expression changes ([\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], GC-specific PGLP1 manipulations also affected stomatal morphology. Specifically, GC PGLP1 abundance positively correlated with stomatal size and, to some extent, density (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Supp. Fig. S3 and Table S6). These morphological adaptations can certainly contribute to altered stomatal conductance, as maximal conductance (\u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003esmax\u003c/em\u003e\u003c/sub\u003e) largely depends on stomatal size and density [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Thus, it seems reasonable to assume that enhanced PGLP1 activity, and thereby more efficient degradation of GC 2-PG, leading to lower steady-state GC 2-PG levels, could underlie the observed changes in stomatal size. Given direct quantification of GC 2-PG remains technically challenging, we tested whether exogenous 2-PG influences stomatal traits in Arabidopsis wild type. Indeed, increasing external 2-PG supply gradually reduced stomatal dimensions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC; Supp. Table S7), supporting the hypothesis that optimal GC PGLP1 activity, through 2-PG detoxification, is fundamental for maintaining proper GC and stomatal morphology. This observation also provides evidence that not changed amounts of GC PGLP1, but directly its substrate 2-PG, serves as signaling molecule. This finding, thus, could be taken as direct hint for its role in the signaling of different CO\u003csub\u003e2\u003c/sub\u003e levels not only via impacting on GC movements, but also GC development in plants. This statement is in line with evolutionary observations that low CO2 (high 2-PG) selected for smaller, whilst high CO2 (low 2-PG) for larger stomata [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOverall, our findings strongly support the view that GC photorespiration, including GC-specific 2-PG degradation, is a fundamental component of stomatal metabolism and behavior. This metabolic framework may serve as the basis for coordinating environmental variations that strongly influence photorespiratory fluxes with GC behavior and mesophyll metabolism. By modulating 2-PG detoxification and ROS homeostasis within GC, PGLP1 influences both stomatal size and conductance, thereby regulating CO₂ availability for photosynthesis. Together, these results highlight GC photorespiration as an underappreciated target for enhancing crop productivity, particularly under conditions where photorespiration is active.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003ePlant growth conditions and biomass quantification\u003c/h2\u003e\n \u003cp\u003e\u003cem\u003eArabidopsis thaliana\u003c/em\u003e (L.) Heynh., ecotype Columbia.0 (Col.0), was used as the wild-type control and as the background for generating GC-specific overexpression and antisense repression lines of photorespiratory 2-phosphoglycolate (2-PG) phosphatase 1 (PGLP1; At5g36700) and the CBB cycle enzyme sedoheptulose-1,7-bisphosphatase (SBPase; At3g55800). Seeds were surface sterilized using chlorine gas (generated by mixing 25 mL of 12% sodium hypochlorite with 1.5 mL concentrated HCl in a sealed desiccator) for 3 h. Sterilized seeds were sown on a soil\u0026ndash;vermiculite mixture (4:1, v/v; MiniTray soil, Einheitserdewerk, Uetersen, Germany), stratified at 4\u0026deg;C for 48 h in darkness to break dormancy, and then transferred to growth chambers. Plants were cultivated under controlled environmental conditions (Percival or SANYO growth chambers) with the following standard settings, unless otherwise stated: photoperiod; 12 h light / 12 h dark, temperature; 22\u0026deg;C (day) / 20\u0026deg;C (night), light intensity; 120\u0026ndash;140 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (cool-white fluorescent lamps), relative humidity; ~70%, CO₂ concentration; 400 ppm (air) or for high CO₂ (HC) treatments; 3000 ppm, with otherwise identical conditions. Plants were watered to maintain uniform soil moisture and fertilized weekly with 0.2% Wuxal liquid fertilizer (Aglukon, D\u0026uuml;sseldorf, Germany). Pots were randomized within the chamber weekly to minimize positional effects. Unless otherwise specified, all physiological experiments were performed using plants at growth stage 5.1 [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eSelected quantitative growth parameters were determined from all side-by-side grown genotypes, using 10 independent biological replicates per genotype. Rosette diameters were measured as the maximum distance across the fully expanded rosette and only fully expanded leaves were considered to determine the leaf-count. Next, rosettes were excised, weighed immediately to determine fresh weight, dried at 100\u0026deg;C to constant weight (~\u0026thinsp;24\u0026ndash;30 h), and reweighed for dry biomass determination. For 2-PG feeding assays, wild-type plants were grown \u003cem\u003ein vitro\u003c/em\u003e on freshly prepared half-strength Murashige and Skoog (MS) medium (pH 5.7), supplemented with 0, 10, 50, or 100 \u0026micro;M of 2-PG (Sigma-Aldrich, Taufkirchen, Germany). Leaves of seedlings at growth stage 1.04 [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e] from at least three independent plates per treatment were used for microscopic analysis of stomatal parameters.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eCloning and plant transformation procedures\u003c/h3\u003e\n\u003cp\u003eGuard cell-specific transgenic Arabidopsis lines were generated to achieve overexpression or antisense-mediated reduction of \u003cem\u003ePGLP1\u003c/em\u003e and \u003cem\u003eSBPase\u003c/em\u003e expression. The binary plant transformation vector pG0229:AtGC1:35STer, containing the guard cell-specific GC1 promoter [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e], served as the expression backbone. The full coding sequence (CDS) of \u003cem\u003eSolanum lycopersicum PGLP1\u003c/em\u003e (\u003cem\u003eSlPGLP1\u003c/em\u003e; 1119 bp) was synthesized \u003cem\u003ede novo\u003c/em\u003e (BaseClear, Leiden, The Netherlands). The CDS of Arabidopsis SBPase (\u003cem\u003eAtSBPase\u003c/em\u003e; 1182 bp) was PCR-amplified from Col.0 cDNA using primers P967 and P968 (sequences listed in Supp. Table S9) with a proof-reading DNA polymerase and cloned into pJET2.1 (ThermoFisher Scientific, Schwerte, Germany) for sequence verification and amplification. The coding fragments were excised from their entry vectors using BamHI (\u003cem\u003eSlPGLP1\u003c/em\u003e) and XmaI (\u003cem\u003eAtSBPase\u003c/em\u003e), respectively, and ligated into pG0229:AtGC1:35STer in sense and antisense orientations to create overexpression constructs pG0229:AtGC1:SlPGLP1_sense:35STer and pG0229:AtGC1:AtSBPase_sense:35STer and antisense constructs pG0229:AtGC1:SlPGLP1_antisense:35STer and pG0229:AtGC1:AtSBPase_antisense:35STer (see Supp. Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e and S3). All final constructs were verified by sequencing (Microsynth, G\u0026ouml;ttingen, Germany). Subsequently, the constructs were introduced into \u003cem\u003eAgrobacterium tumefaciens\u003c/em\u003e GV3101\u0026thinsp;+\u0026thinsp;pSOUP, the drug resistant colonies verified via standard PCR procedures, and used for Arabidopsis floral dip transformation [\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e]. T1 seeds were surface sterilized and selected on half-strength MS media supplemented with 20 \u0026micro;g mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e phosphinothricin (BASTA). Resistant seedlings were transplanted to soil, PCR-verified for the presence of the transgene, and propagated to homozygous T3 or T4 lines, used for all physiological experiments. For comprehensive characterization, two independent \u003cem\u003eSlPGLP1\u003c/em\u003e and three independent \u003cem\u003eAtSBPase\u003c/em\u003e overexpression and antisense lines were used.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eVerification of transgenic lines and Immunological Studies\u003c/h2\u003e\n \u003cp\u003eGenomic DNA was isolated from rosette leaves according to standard procedures. Transgene integration was verified by PCR using primers specific for the exogenous \u003cem\u003eSlPGLP1\u003c/em\u003e (P953 for sense and P954 for antisense orientation) or \u003cem\u003eAtSBPase\u003c/em\u003e (P967 for sense and P968 for antisense orientation) in combination with the \u003cem\u003eAtGC1\u003c/em\u003e promoter primer P950. PCR reactions were performed using a standard DNA polymerase under the following conditions: 94\u0026deg;C for 1 min, 58\u0026deg;C for 1 min, 72\u0026deg;C for 2 min, for 35 cycles. DNA integrity was confirmed by amplifications of the \u003cem\u003eS16\u003c/em\u003e gene (At2g09990) using primers P444 and P445 under identical cycling conditions, except for a 30 s extension step (see Supp. Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003eC and S3C).\u003c/p\u003e\n \u003cp\u003eTranscript accumulation of \u003cem\u003eSlPGLP1\u003c/em\u003e and \u003cem\u003eAtPGLP1\u003c/em\u003e was assessed by semiquantitative RT-PCR. Total RNA (2.5 \u0026micro;g) was extracted using the Nucleospin RNA Plant Kit (Macherey-Nagel, D\u0026uuml;ren, Germany) and treated with DNaseI to remove genomic DNA contamination. First-strand cDNA synthesis was performed with the RevertAid cDNA Synthesis Kit (Thermo Fisher Scientific, Osterode, Germany) using oligo(dT) primers. Diagnostic transcript fragments were amplified using primers P974/P975 (\u003cem\u003eSlPGLP1\u003c/em\u003e, 336 bp) and P977/P978 (\u003cem\u003eAtPGLP1\u003c/em\u003e, 288 bp). Amplification of \u003cem\u003eS16\u003c/em\u003e (432 bp) with primers P444/P445 served as an internal control. PGLP1 and SBPase protein abundance was determined by immunoblotting. Total soluble protein was extracted from mesophyll and guard cell-enriched fractions from the same leaves, and equal amounts (5 \u0026micro;g per lane) were separated by SDS-PAGE and electroblotted onto polyvinylidene difluoride (PVDF) membranes. Blots were probed with specific anti-PGLP1 ([\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e] or anti-SBPase [64] antibodies. GDC-H and RbcL antibodies (Agrisera, V\u0026auml;nn\u0026auml;s, Sweden) were used as loading and normalization controls. Signal detection was performed via chemiluminescence, and densitometric quantification was carried out using ImageJ (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.net/\u003c/span\u003e\u003c/span\u003e) from at least three independent biological replicates.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eIsolation of mesophyll and guard cell protein extracts\u003c/h2\u003e\n \u003cp\u003eMesophyll- and guard cell-enriched fractions were obtained as described previously, [65] with minor modifications. Fully expanded leaves from 5-6-week-old plants grown under standard conditions were harvested at mid of the day (~\u0026thinsp;6 h illumination). Transparent adhesive tape was applied to either the abaxial (for guard cell enrichment) or adaxial (for mesophyll enrichment) leaf surface. Peels (~\u0026thinsp;20\u0026ndash;50 per genotype, as mixture from at least 4 biological replicates) were gently removed, pooled by fraction, and immediately frozen in liquid nitrogen. Protein extraction was performed essentially as described earlier [65] and protein concentrations were determined using the BCA Protein Assay Kit (Thermo Scientific, Osterode, Germany) according to manufacturers instruction, with bovine serum albumin (BSA) as standard.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eGuard cell properties and guard cell starch content\u003c/h2\u003e\n \u003cp\u003eTo determine diagnostic parameters associated with GC morphology, epidermal peels were prepared from fully expanded rosette leaves of plants grown under standard conditions, harvested at midday (~\u0026thinsp;6 h of illumination). Nail polish was applied to the abaxial surface of each leaf and allowed to dry for 10 min. The epidermis was gently peeled off, mounted in water on microscope slides, and covered with a coverslip. Four biological individuals per genotype were analyzed. GC parameters (area, length, width, density and index) were measured using an Olympus U-LH100HG microscope (Olympus Corporation, Japan) and the manufacturer\u0026rsquo;s image analysis software.\u003c/p\u003e\n \u003cp\u003eStarch content in GC was assessed in epidermal peels harvested at midday (~\u0026thinsp;6 h of illumination) following propidium iodide staining as described before [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e]. Four biological replicates per genotype were used, with 10 guard cells randomly selected per stained peel. Fluorescence images were acquired using a Keyence BZ-X800 fluorescence microscope (Keyence Deutschland GmbH, Neu-Isenburg, Germany) equipped with a Plan Fluorite 20-100x LD PH objective at 100x magnification. Fluorescence was visualized with the BZ-X GFP filter cube (exposure time: 1/70 s) and captured with BZ-X800 Viewer software. Quantitative analysis of GC starch was performed by measuring fluorescence intensity per cell using the manufacturer\u0026rsquo;s software.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eGuard Cell H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e Content Determination\u003c/h2\u003e\n \u003cp\u003eReactive oxygen species (ROS), primarily H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, in GC were visualized using 2\u0026prime;,7\u0026prime;-Dichlorodihydrofluorescein diacetate (H\u003csub\u003e2\u003c/sub\u003eDCFDA) fluorescence staining as described previously [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e], using plants grown in air to stage 5.1 [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]. The lower epidermis was carefully excised and incubated in 100 \u0026micro;M H\u003csub\u003e2\u003c/sub\u003eDCFDA prepared in 10 mM Tris-HCl buffer (pH 7.2) in the dark for 10 min. Excess dye was removed, and the peels were washed three times with 10 mM Tris-HCl (pH 7.2). Fluorescence images were captured using a Keyence BZ-X800 fluorescence microscope (Keyence Deutschland GmbH, Neu-Isenburg, Germany) equipped with a Plan Fluorite 100x LD PH objective. H\u003csub\u003e2\u003c/sub\u003eDCFDA fluorescence was visualized using the GFP filter cube, and images were acquired with the BZ-X800 Viewer software. Quantification of fluorescence intensity in GC was performed using the same software.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eGas Exchange Measurements\u003c/h2\u003e\n \u003cp\u003eGas exchange was measured using LI-6400 and LI-6400XT Portable Photosynthesis Systems equipped with a 2 cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e LED leaf chamber fluorometer and red/blue light source (LI-COR Biosciences, Lincoln, NE, USA). Prior to each measurement day, CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO analyzers were calibrated according to the manufacturer\u0026rsquo;s instructions. Fully expanded rosette leaves from plants grown under standard conditions (light intensity\u0026thinsp;~\u0026thinsp;120\u0026ndash;140 mmol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were clamped in the cuvette and pre-acclimated for 10 min at 1000 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e photosynthetic photon flux density (PPFD; 10% blue light) to reach stable steady-state photosynthesis. Basic settings were as follows: 25\u0026deg;C block temperature, 400 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e CO\u003csub\u003e2\u003c/sub\u003e, 300 \u0026micro;mol s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e flow rate, and ~\u0026thinsp;50\u0026ndash;70% relative humidity. CO\u003csub\u003e2\u003c/sub\u003e response (\u003cem\u003eA\u003c/em\u003e/\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e) curves were measured under constant 21% O\u003csub\u003e2\u003c/sub\u003e and varying CO\u003csub\u003e2\u003c/sub\u003e concentrations as follows: 400, 300, 200, 100, 50, 25, 0, 400 ppm. To determine the oxygen-dependence of the net CO\u003csub\u003e2\u003c/sub\u003e compensation point, the O\u003csub\u003e2\u003c/sub\u003e concentration was adjusted to 3%, 21% and 40% O₂ (balanced with N\u003csub\u003e2\u003c/sub\u003e), using the gas mixing device GMS600 (QCAL Messtechnik, M\u0026uuml;nchen, Germany). The net CO\u003csub\u003e2\u003c/sub\u003e assimilation rate (\u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e), stomatal conductance (\u003cem\u003eg\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e), intercellular CO₂ concentration (\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e), transpiration rate (\u003cem\u003eE\u003c/em\u003e), intrinsic water-use efficiency (\u003cem\u003eWUE\u003c/em\u003e\u003csub\u003e\u003cem\u003eint\u003c/em\u003e\u003c/sub\u003e), and CO₂ compensation point (\u003cem\u003e\u0026Gamma;\u003c/em\u003e) were calculated by the LI-6400 and Excel software. O\u003csub\u003e2\u003c/sub\u003e inhibition of \u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003eN\u003c/em\u003e\u003c/sub\u003e was calculated from measurements at 21% and 40% O\u003csub\u003e2\u003c/sub\u003e using equation: O\u003csub\u003e2\u003c/sub\u003e inhibition = (A\u003csub\u003e21\u003c/sub\u003e \u0026ndash; A\u003csub\u003e40\u003c/sub\u003e) / A\u003csub\u003e21\u003c/sub\u003e \u0026times; 100. Calculation of \u003cem\u003e\u0026gamma;\u003c/em\u003e (measure of the photorespiratory CO\u003csub\u003e2\u003c/sub\u003e-release) was performed by linear regression of the \u003cem\u003e\u0026Gamma;\u003c/em\u003e-versus-O\u003csub\u003e2\u003c/sub\u003e concentration curves and is given as slopes of the respective functions. Light response curves were measured under ambient CO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e2\u003c/sub\u003e levels (10 min acclimation at 1000 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e PPFD), followed by stepwise reduction of PPFD to 1600, 1200, 800, 400, 200, 100, 50, 25, and 0 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, allowing 2\u0026ndash;3 min for stabilization at each step. At least six independent plants per genotype were measured and values are given as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eChlorophyll fluorescence measurements\u003c/h2\u003e\n \u003cp\u003eSelected PSI and PSII parameters associated with photosynthetic light reactions were determined by standard chlorophyll fluorescence measurements on a Dual-PAM 100 (Heinz Walz, Effeltrich, Germany). Chlorophyll fluorescence measurements were performed on the adaxial leaf surface. PSI activity was determined by monitoring P700 absorbance, which reflects excitation across the entire leaf tissue, whereas PSII activity was assessed via chlorophyll fluorescence, which predominantly originates from a defined layer of chloroplasts within the leaf mesophyll. Following 10 min dark adaptation, \u003cem\u003eF\u003c/em\u003e\u003csub\u003ev\u003c/sub\u003e/\u003cem\u003eF\u003c/em\u003e\u003csub\u003em\u003c/sub\u003e (maximum quantum efficiency of PSII) and \u003cem\u003eP\u003c/em\u003e\u003csub\u003em\u003c/sub\u003e (maximum photo-oxidizable P700) values were recorded. Next, plants were exposed to 1000 \u0026micro;mol photons m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for 10 min to fully induce photosynthesis and, subsequently, light response curves were measured (PPFD: 1759, 1144, 757, 488, 236, 143, 62, 36, and 0 \u0026micro;mol photons m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) at 400 ppm CO\u003csub\u003e2\u003c/sub\u003e and 21% O\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eMetabolite analysis\u003c/h2\u003e\n \u003cp\u003eFor absolute quantification of metabolites associated with primary metabolism, we used liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and gas chromatography (GC) analysis. Fully expanded rosettes were harvested under growth light at the end of the photoperiod (after 11 h illumination). All samples were collected within a 10-min window to minimize variation, immediately quenched in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C. Prior further processing, the frozen material was lyophilized, and ~\u0026thinsp;2\u0026ndash;3 mg dry weight per sample was aliquoted for extraction. For metabolite extraction and LC-MS/MS measurements, we used LC-MS grade chemicals and the procedure described before [66]. Measurements were carried out on a high-performance liquid chromatograph mass spectrometer LCMS-8050 system (Shimadzu, Japan) and the incorporated LC-MS/MS method package for primary metabolites (version 2, Shimadzu). Selected soluble sugars and starch were measured on the gas chromatograph 6890 N GC System (Agilent Technologies, Waldbronn, Baden-W\u0026uuml;rttemberg, Germany) and spectrophotometrically measurements essentially as described previously [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. For each metabolite, absolute concentrations were determined using calibration curves generated from authentic standards measured in parallel. Results were normalized to dry weight and reported as nmol mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e DW (LC-MS/MS) or \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e DW (GC).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eWe used the programs Microsoft Excel (Microsoft Corporation, 2018) and SigmaPlot vol. 13.0 (Systat Software Inc., 2014) for data processing and graph generation, CorelDraw (Graphics Suite 2017; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.corel.com\u003c/span\u003e\u003c/span\u003e) was used for image compilation. Statistical differences were determined through analysis of variance analysis (ANOVA; SPSS Statistics 27, IBM). The term significant is used here only if the change in question has been confirmed to be significant at the level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Prof. Hendrik Schubert and Junior Professor´s Andreas Richter and Klaus Herburger for providing access and support with the Dual PAM-100, microscopy facilities, and gas chromatography. We are grateful to Klaudia Michl and Kathrin Jahnke (University of Rostock) for excellent technical assistance, and to Emeritus Prof. Hermann Bauwe and Prof. Christine Raines for kindly sharing the PGLP1 and SBPase antibodies. H.S. acknowledges a scholarship from the China Scholarship Council (CSC). This work was supported by the University of Rostock (to M.H. and S.T.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eS.T. conceived and supervised the project. H.S., I.T., and S.T. designed the research. N.S. and S.T. performed cloning procedures and established the transgenic lines. H.S. and I.T. performed the research. H.S., I.T., J.K., T.L., M.H., and S.T. analyzed the data. M.H. provided experimental equipment and tools. H.S. and S.T. wrote the article, with additions and revisions from J.K., T.L., and M.H. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e All relevant data are provided in the main text and Supplemental data area of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003cstrong\u003eFl\u0026uuml;gel F, Timm S, Arrivault S, Florian A, Stitt M, Fernie AR, Bauwe H\u003c/strong\u003e (2017) The Photorespiratory Metabolite 2-Phosphoglycolate Regulates Photosynthesis and Starch Accumulation in Arabidopsis, \u003cem\u003eThe Plant Cell\u003c/em\u003e 29: 2537\u0026ndash;2551\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eLi J, Weraduwage SM, Preiser AL, Tietz S, Weise SE, Strand DD, Froehlich JE, Kramer DM, Hu J, Sharkey TD \u003c/strong\u003e(2019) A cytosolic bypass and G6P shunt in plants lacking peroxisomal hydroxypyruvate reductase. \u003cem\u003ePlant Physiology\u003c/em\u003e 180: 783\u0026ndash;792\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eWalker BJ, VanLoocke A, Bernacchi CJ, Ort DR\u003c/strong\u003e (2016) The Costs of Photorespiration to Food Production Now and in the Future. \u003cem\u003eAnnual Reviews in Plant Biology\u003c/em\u003e 67: 107-29\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eFoyer CH, Bloom AJ, Queval G, Noctor G \u003c/strong\u003e(2009) Photorespiratory metabolism: genes, mutants, energetics, and redox signaling. \u003cem\u003eAnnual Review in Plant Biolog\u003c/em\u003ey 60: 455-84\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eBusch FA \u003c/strong\u003e(2020) Photorespiration in the context of Rubisco biochemistry, CO\u003csub\u003e2\u003c/sub\u003e diffusion and metabolism. \u003cem\u003ePlant Journal\u003c/em\u003e 101: 919-939\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eTimm S, Sun H, Hagemann M, Huang W, Fernie AR \u003c/strong\u003e(2025)An old dog with new tricks-the value of photorespiration as a central metabolic hub with implications for environmental acclimation. \u003cem\u003ePlant Physiology\u003c/em\u003e 198(4): kiaf258\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eCavanagh AP, South PF, Bernacchi CJ, Ort DR\u003c/strong\u003e (2022) Alternative pathway to photorespiration protects growth and productivity at elevated temperatures in a model crop. \u003cem\u003ePlant Biotechnology Journal\u003c/em\u003e 20(4): 711-721\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eSmith EN, van Aalst M, Weber APM, Ebenh\u0026ouml;h O, Heinemann M \u003c/strong\u003e(2025) Alternatives to photorespiration: A system-level analysis reveals mechanisms of enhanced plant productivity. \u003cem\u003eScience Advances\u003c/em\u003e 11(13): eadt9287\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eLin YC, Tsay YF\u003c/strong\u003e (2023) Study of vacuole glycerate transporter NPF8.4 reveals a new role of photorespiration in C/N balance. 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However, it is essential for safeguarding the Calvin\u0026ndash;Benson-Bassham cycle from inhibitory byproducts of Rubisco oxygenation and highly intertwined with overall plant primary metabolism. Here we show that targeted manipulation of the entry enzyme 2-phosphoglycolate (2-PG) phosphatase (PGLP1) in Arabidopsis guard cells consistently influences growth, photosynthesis, carbohydrate allocation, and stomatal movement. Altered \u003cem\u003ePGLP1\u003c/em\u003e expression triggered guard cell-specific starch and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e accumulation patterns under photorespiratory conditions and affects stomata size, a response replicated by 2-PG feeding to Arabidopsis wildtype. These results reveal that efficient photorespiratory metabolism is essential for guard cell function and critical for acclimation to external CO\u003csub\u003e2\u003c/sub\u003e/O\u003csub\u003e2\u003c/sub\u003e ratios. By uncovering a direct metabolic link between photorespiration and stomatal behavior, our work highlights an unexpected role of this ancient pathway in shaping gas exchange and photosynthesis and opens a new avenue in optimizing plant yield and resilience.\u003c/p\u003e","manuscriptTitle":"Guard cell photorespiration controls stomata behavior and development","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-10 06:50:45","doi":"10.21203/rs.3.rs-8223718/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e0b2540a-3020-459f-8a9e-7949086c799a","owner":[],"postedDate":"December 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":59342929,"name":"Biological sciences/Plant sciences/Photosynthesis/C3 photosynthesis"},{"id":59342930,"name":"Biological sciences/Plant sciences/Plant physiology"}],"tags":[],"updatedAt":"2026-03-30T15:16:11+00:00","versionOfRecord":{"articleIdentity":"rs-8223718","link":"https://doi.org/10.1111/nph.71137","journal":{"identity":"new-phytologist","isVorOnly":true,"title":"New Phytologist"},"publishedOn":"2026-03-26 00:00:00","publishedOnDateReadable":"March 26th, 2026"},"versionCreatedAt":"2025-12-10 06:50:45","video":"","vorDoi":"10.1111/nph.71137","vorDoiUrl":"https://doi.org/10.1111/nph.71137","workflowStages":[]},"version":"v1","identity":"rs-8223718","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8223718","identity":"rs-8223718","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}