Biology subjects

Ge, Z.

Publications and source records attributed to Ge, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

CUBE: Multimodal Representation Learning Reveals Biological Structure Across Histomorphology, Spatial Protein Phenotypes, and Transcriptome-Associated Signals

Integrating histological, spatial protein, and transcriptomic information into a biologically grounded representation remains challenging because these modalities are rarely available as fully paired measurements, while existing computational approaches are commonly developed around individual modality pairs. To address this, we present CUBE (Colorectal Universal Representation & Bridge Encoder), a multimodal representation-learning framework that uses hematoxylin and eosin (H&E) histology as a bridge to integrate spatial protein phenotypes with transcriptome-associated information from incompletely paired data. CUBE independently learns representations from H&E-multiplex immunohistochemistry (mIHC) and H&E-pseudo-ST relationships and integrates them through attention-based fusion with biological grounding from mIHC-derived concepts. The H&E-mIHC representation supported competitive spatial protein reconstruction, while the pseudo-ST-supervised representation transferred to experimentally measured Visium HD spatial transcriptomics data and improved further after decoder-only calibration with the encoder frozen. Importantly, the fused representation retained biological information beyond its direct training targets, capturing immune-epithelial spatial organization and an independently measured ECM-receptor interaction transcriptomic program. Together, these findings demonstrate that separately paired spatial modalities can be organized through histology into a biologically structured and testable multimodal representation, providing a proof-of-concept strategy for multimodal tissue learning without requiring fully paired molecular measurements.

bioinformatics↗

bioRxiv2026

MIRATS framework: Normative multiscale characterization of brain regulatory systems across sex and age using multimodal MRI

Deep brain systems involved in arousal, autonomic regulation, sensory integration, and homeostatic control remain underrepresented in conventional whole-brain neuroimaging frameworks. In particular, diencephalic and brainstem nuclei are often insufficiently represented in cortex-centered analyses, limiting the normative references needed to interpret systems-level variation in health and disease. To address this gap, we developed a unified multiscale framework with explicit representation of deep nuclei. By integrating cerebral, cerebellar, diencephalic, and brainstem atlases in standard space, we constructed a 220-region whole-brain parcellation and extracted complementary features at three analytical scales: nodal properties, edge-wise connectivity, and persistent-homology-based topological descriptors. We applied this framework to healthy adults from the Human Connectome Project-Aging cohort to characterize normative multiscale organization and test sex- and age-related variation. Applied to this cohort, our framework revealed pronounced heterogeneity across anatomical systems. Brainstem and diencephalic nuclei showed multiscale feature profiles distinct from those of cerebral and cerebellar regions across nodal, edge-wise, and higher-order topological scales. Sex comparisons identified selective differences across different scales, whereas age modeling revealed widespread but feature- and system-dependent variation across adulthood. Together, these findings show that normative whole-brain organization in this deep-system-aware space is structured by system-specific rather than globally uniform patterns. These findings establish a normative multiscale framework for characterizing brainstem-diencephalic-cerebellar-cerebral organization in healthy adults and provide a quantitative reference for future translational studies of disease-related abnormalities in deep regulatory systems.

bioinformatics↗

bioRxiv2026

Functional orthogonality of WRN inhibitor resistance enables alternating therapy and mutation-tolerant inhibitor design in MSI-H cancers

Werner syndrome helicase (WRN) is a synthetic-lethal vulnerability in microsatellite instability-high (MSI-H)/mismatch repair-deficient (dMMR) cancers1-5, and non-covalent and covalent WRN inhibitors are now entering clinical development6-9. A central unresolved question is whether resistance to one WRN inhibitor class inevitably compromises the target, or instead creates actionable vulnerabilities to an alternate modality. Here we generated ten stable acquired-resistance models across three MSI-H cell lines using the non-covalent inhibitor HRO761 and the covalent inhibitor VVD-214. Whole-exome sequencing, biochemical reconstitution and isogenic knock-in models identified recurrent on-target WRN missense mutations as dominant resistance drivers, but with sharply modality-specific spectra: HRO761 resistance clustered at G729/F730/I852, whereas VVD-214 resistance concentrated at E846. These mutations impaired inhibitor engagement and abolished the canonical WRN inhibitor (WRNi)-induced pharmacodynamic cascade, including WRN reduction, DNA damage response (DDR) activation and G2/M arrest. Crucially, most resistance mutations retained biochemical, cellular and in vivo sensitivity to the alternate inhibitor modality, revealing a functional orthogonality that enabled a 7-day cyclic alternating regimen to delay tumour regrowth in xenografts. We further identified F730L as an engineered cross-resistant bottleneck model and used structure-guided, artificial intelligence (AI)-enabled optimization to generate GBA-007, a proof-of-concept mutation-tolerant WRN inhibitor candidate with promising activity against F730L in vitro and in vivo. Thus, clinically relevant WRN inhibitor classes impose distinct on-target resistance trajectories that can be exploited through schedule design, while cross-resistant bottlenecks can be addressed by rapid mutation-aware inhibitor engineering.

Cancer Biology↗

bioRxiv2026

DINMC: A Deep Learning Framework for Interpretable Normative Model Construction and Pathological Brain Alteration Detection

Background and ObjectiveNormative modeling is a key tool for understanding brain alterations in neurodegenerative diseases, such as cerebellar-type multiple system atrophy. However, existing methods lack interpretability and fail to capture clinically meaningful pathological changes. This study presents DINMC, a Deep Interpretable Normative Model Construction framework, which combines autoencoder-based learning with statistical hypothesis testing to better capture and interpret disease-specific neu-roanatomical changes. MethodsThe DINMC framework constructs normative models using neuroimaging data from multi-site large healthy cohorts. It utilizes a U-shaped convolutional autoencoder to train these models, which are then applied to reconstruct brain features from both patients and healthy controls within the same study cohort. Pathological confidence values are derived by fusing original and deviation feature spaces, offering a measure of disease-related pathology reflected in each dimension of the features. The framework was validated through statistical analysis and prognostic classification and regression tasks. ResultsThe pathological confidence provides valuable insights into the neuroanatomical regions most affected by the disease, as well as the correlation between changes in these regions and clinical assessment scales. Our optimal model outperform traditional methods in prognostic prediction tasks, with an AUC of 0.972 for classification tasks and an R2 of 0.432 for regression tasks. ConclusionDINMC provides a novel and interpretable framework for neuroimaging analysis. By combining deep learning and statistical hypothesis testing, this framework offers a unique solution to improving both the interpretability and performance of normative models in neuroimaging. The approach is scalable to other neuroimaging datasets, offering a versatile tool for broader biomedical applications.

bioinformatics↗

bioRxiv2026

Cell-nanoplastics association impacts cell proliferationand motility

Detection of micro- and nanoplastics (MNPs) in human tissues has raised growing concern about their biological effects on tissue and cell function. While previous studies have examined MNP-cell interaction, most focused on limited cell and plastic types. Here, we present a comprehensive, quantitative investigation into how different types of nanoplastics (NPs) associate with and affect diverse cell types under physiologically relevant conditions. Using microfluidic-calibrated fluorescence microscopy, we quantify NP accumulation in cells in vitro and match cellular NP concentrations to levels reported in human tissues. While cell-associated NPs could be gradually released in vitro, they persist in vivo for over one month without detectable reduction in a mouse model. We discover that NP exposure at these levels broadly impairs cell proliferation across epithelial, endothelial, fibroblast, and immune cells, with cell type-dependent sensitivity. NP exposure also reduces motility in T cells and fibroblasts, with more complex effects observed in macrophages. Mechanistically, NP-cell association and trans-epithelial transport involved not only classical endocytic regulators but also pathways related to ion and water transport. Notably, NP association and release were highly sensitive to the extracellular fluid environment within the physiological range. By testing inhibitors of these pathways, we identified molecules that reduce NP-cell association and promote release. We further compared common NPs found in human samples and widely used in research: polystyrene (PS), polyethylene (PE), and polypropylene (PP). Although these NPs similarly impaired proliferation and motility, they showed markedly different cellular association and release dynamics. These findings reveal the impact of NPs on tissue cell functions and uncover novel regulatory pathways, establishing a quantitative framework for studying NP-cell interactions in biologically relevant conditions.

cell biology↗

bioRxiv2026

G3DCT: An Interpretable Spatial Grid-based Framework with Temporal Convolution-Transformer for EEG Artifact Identification

Electroencephalography (EEG) serves as a fundamental tool in modern neurology, cognitive neuroscience, and brain-computer interfaces, but its practical application is often compromised by artifacts. Physiological artifacts are particularly intractable due to overlapping spectral features with neural signals, hindering reliable EEG interpretation. In this work, we propose Grid-based 3D Convolution-Transformer (G3DCT), an interpretable deep learning framework for EEG artifact identification. The framework embeds multi-channel EEG signals into fixed grids to leverage electrode spatial topology, employs parallel multi-branch temporal convolutions and Transformers to handle complex artifacts, and incorporates an attention module to visualize scalp activation patterns, which enhances physiological interpretability. Our evaluation on three datasets demonstrates that G3DCT outperforms existing state-of-the-art models. For challenging combined artifacts, it secures a gain of 2.8% in F1-score over the second-best model. These results demonstrate that G3DCT provides an efficient and robust solution for EEG artifact identification, which has the potential to enhance the reliability of EEG-based applications in practice.

neuroscience↗

bioRxiv2026

Acute priming using elevated fluid viscosity recovers young-like single-cellsurveillance behaviors in aged human T cells

Aging is a complex biological process, often characterized by increased vulnerability to disease, infection, and death. This increased vulnerability is mechanistically linked to a progressive and functional decline of the immune system. In humans, aged lymphocytes lose their capacity to effectively surveil within diverse microenvironments, decreasing their capability for clearing infections and maintaining physiological homeostasis. However, specific mechanisms by which aged lymphocytes, specifically T cells, lose this capacity to surveil remain unclear. We profiled three core characteristics of T cell surveillance at single-cell resolution, specifically migration, deformability, and sensing. While aged T cells retained their capacity for spontaneous migration, they exhibited impaired cellular deformability and deficiencies in sensing local signaling cues. To modulate this surveillance defect, we performed mechanical reprogramming using elevated fluid viscosity. Results showed that acute priming of aged T cells with elevated fluid viscosity recovered a transient young-like surveillance phenotype, which was mechanistically linked to membrane tension, cortical F-actin, and Arp3 expression. These findings reveal a key source of surveillance defects in aged T cells and provide an effective mechanical approach to tuning their single-cell behaviors. TeaserRecovery of young-like surveillance phenotypes in aging human T cells via viscosity priming

bioengineering↗

bioRxiv2025

Anionic Lipid Trafficking and Cell Mechanics RegulateMembrane Electrical Potential in Non-Excitable Tissue Cells

1The membrane potential of eukaryotic cells, classically described by the Goldman-Hodgkin-Katz model, is conventionally attributed to the steady-state balance of transmembrane ionic fluxes. Here, we demonstrate that non-excitable cells maintain stable, spatially heterogeneous membrane voltage gradients. Using the ratiometric voltage indicator JEDI-2P-cyOFP1, we quantitatively map membrane potential in live cells and find that cellular protrusions are consistently depolarized, whereas lateral membrane regions are hyperpolarized. These voltage gradients strongly correlate with anisotropic distributions of anionic lipids, including phosphatidylserine (PS) and phosphatidylinositol 3,4,5-trisphosphate (PIP3). Perturbation of cytoskeletal integrity, the ion exchanger NHE1, or vesicular trafficking disrupts both voltage anisotropy and lipid polarization, revealing an uncharacterized electromechanical regulatory mechanism. Moreover, membrane potential dynamically responds to cell shape, substrate stiffness, external electric fields, and cell cycle progression. To account for these phenomena, we develop a quantitative model that integrates ionic fluxes and lipid charge distributions, thereby explaining the emergence of voltage gradients. This framework establishes that membrane potential is governed not solely by ionic currents but also by lipid dynamics and mechanical signaling. Collectively, these findings identify membrane voltage as a global integrator of electrochemical and mechanical cues in eukaryotic cells.

biophysics↗

bioRxiv2025

MAKR6 targets TMK and CAMEL-CANAR receptor complexes for auxin canalization in Arabidopsis

Adaptive plant development is orchestrated, among others, by directional, intercellular transport of the phytohormone auxin. Self-organizing development, such as flexible vasculature formation, depends on so-called auxin canalization, manifested by the gradual formation of auxin transport channels through feedback between auxin signalling and transport. Herein, we identify MAKR6 as an important, novel component in this feedback. MAKR6 expression accumulates strongly in vascular cells and is tightly regulated by auxin via the Aux/IAA-ARF-WRKY23 transcriptional network. MAKR6 is required for auxin canalization-dependent processes, including leaf venation, vasculature regeneration, and de novo auxin channel formation from local auxin sources. Mechanistically, MAKR6 interacts with the PIN1 auxin transporter, modulating its trafficking and polarization. MAKR6 also associates with and integrates two key receptor-like kinase complexes involved in canalization, TMK1/4 and the CAMEL-CANAR. Together, our study establishes MAKR6 as a multifaceted regulator that couples transcriptional auxin signalling to PIN1 repolarization and coordinates multiple RLK-mediated signalling pathways during canalization. This provides mechanistic insights into auxin canalization and exemplifies a framework for exploring similar regulatory nodes in other developmental contexts.

plant biology↗

bioRxiv2025

Cancer cells surviving cisplatin chemotherapy increase stress-induced OMA1 activity and mitochondrial fragmentation

Cancer is one of the leading causes of deaths worldwide. Once cancer cells acquire therapy resistance, they become the main driver of cancer lethality in patients. Thus, mechanisms of therapy resistance must be investigated to improve patient outcomes. Mitochondria are critical organelles in the cellular stress responses, undergoing dynamic morphological and functional changes in response to external stimuli. We and others have identified a chemotherapy-resistant cancer cell state where cells that survive treatment exhibit a dramatic increase in cell size and remain non-proliferative for weeks. In this study, we demonstrate that cancer cells that enter this resistant cell state in response to cisplatin increase OMA1 activity and decrease mitochondrial fusion and function to combat oxidative stress. These findings contribute to further understanding the role of the mitochondrial stress responses in therapy resistance in cancer and provide a potential therapeutic avenue to targeting cancer cells that enter this chemotherapy-resistant cell state.

cancer biology↗

bioRxiv2025

Coupling Anaerobic Oxic and Integrated Fixed Activated Sludge Processes for Removal and Transformation of Refractory Organic Matter in Livestock and Poultry Digestate

Effective treatment of livestock and poultry digestate remains challenging due to its high content of refractory organic matter. In this study, a coupled anaerobic-oxic (A/O) and integrated fixed-film activated sludge (IFAS) system was investigated to evaluate its capacity for organic removal and molecular transformation. The IFAS system outperformed the A/O system, achieving an organic removal efficiency of 43%, compared to 17% in the A/O process. Molecular analyses revealed distinct transformation pathways: the A/O process tended to increase the molecular weight and structural complexity of dissolved organic matter, whereas the IFAS process promoted oxidative fragmentation, resulting in the formation of smaller, oxygen-rich compounds. These changes were reflected in key molecular indices (DBE, NOSC, AImod) and the accumulation of carboxyl-rich intermediates. Microbial community analysis associated Bacteroidota with the degradation of oxygenated compounds via hydrolytic processes, while Actinobacteria and Deinococcota were linked to the transformation of lignin- derived aromatics. The integration of advanced molecular characterization with microbial profiling highlights the IFAS systems enhanced capability for both structural simplification and biodegradation of complex organics, providing a promising strategy for the treatment of high-strength organic wastewater.

microbiology↗

bioRxiv2025

Chemical Compensation to Mechanical Loss in CellMechanosensation

Mammalian cells sense and respond to environmental changes using a complex and intelligent system that integrates chemical and mechanical signals. The transduction of mechanical cues into chemical changes modulates cell physiology, allowing a cell to adapt to its microenvironment. Understanding how the chemical and mechanical regulatory modules interact is crucial for elucidating mechanisms of mechanosensation and cellular homeostasis. In this study, we find that cells exhibit non-monotonic changes in cell volume and intracellular pH when subjected to physical stimuli and varying degrees of actomyosin cytoskeleton disruption. We discover that these non-monotonic responses are mediated by a chemical compensation mechanism, where the attenuation of actomyosin activity stimulates the activity of PI3K/Akt pathway. This, in turn, activates sodium-hydrogen exchanger 1 (NHE1), resulting in elevated intracellular pH and increased cell volume. Furthermore, we identify a competitive interaction between the PI3K/Akt and MAPK/ERK pathways - two major regulators of cell proliferation and motility. This competition modulates the chemical compensation based on the relative activities of these pathways. Our mathematical modeling reveals the network structure that is essential for establishing the non-monotonic response. Interestingly, this regulatory system is altered in HT1080 fibrosarcoma, highlighting a potential mechanistic divergence in cancer cells in contrast to their normal-like counterpart, such as NIH 3T3 and HFF-1 fibroblasts. Overall, our work reveals a compensatory mechanism between chemical and mechanical signals, providing a novel infrastructure to elucidate the integrated mechanochemical response to environmental stimuli.

biophysics↗

bioRxiv2024

Cells Prioritize the Regulation of Cell Mass Density

A cells global physical state is characterized by its volume and dry mass. The ratio of cell mass to volume is the cell mass density (CMD), which is also a measure of macromolecular crowding and concentrations of all proteins. Using the Fluorescence eXclusion method (FXm) and Quantitative Phase Microscopy (QPM), we investigate CMD dynamics after exposure to sudden media osmolarity change. We find that while the cell volume and mass exhibit complex behavior after osmotic shock, CMD follows a straightforward monotonic recovery in 48 hours. The recovery is cell-cycle independent and relies on a coordinated adjustment of protein synthesis and volume growth rates. Surprisingly, we find that the protein synthesis rate decreases when CMD increases. This result is explained by CMD-dependent nucleoplasm-cytoplasm transport, which serves as negative regulatory feedback on CMD. The Na+/H+ exchanger NHE plays a role in regulating CMD by affecting both protein synthesis and volume change. Taken together, we reveal that cells possess a robust control system that actively regulates CMD during environmental change.

biophysics↗

bioRxiv2024

Vgamma1+ gammadelta T cell-derived IL-4 initiates CD8 T cell immunity

Dendritic cells (DC) are pivotal for initiating adaptive immunity, a process triggered by the activation of DC via pathogen products or damage. Here, we describe an additional layer to this process, essential when pathogen-derived signals alone cannot directly achieve full DC activation. Immunisation with sporozoites from Plasmodium leads to CD8 T cell priming in a complex response that is initiated by a collaboration between conventional type 1 DC (cDC1) and {gamma}{delta} T cells. We unveil a pivotal initiating role for V{gamma}1+ {gamma}{delta} T cells, as they directly supply IL-4 to DC and CD8 T cells. IL-4 synergises with a CD4 T cell-derived CD40L signal to induce IL-12 production by cDC1. Both IL-12 and IL-4 then directly signal CD8 T cells, with synergy between these cytokines driving enhanced IL-12 receptor expression and expansion of responding CD8 T cells. This study reveals a key role for V{gamma}l+ {gamma}{delta} T cells in initiating CD8 T cell immunity to Plasmodium. More broadly, it shows that responses to some pathogens require help from innate-like T cells to pass an initiation threshold and further amplify the response in a process underscored by IL-4 production.

immunology↗

bioRxiv2024

Long lived liver-resident memory T cells of biased specificities for abundant sporozoite antigens drive malaria protection by radiation-attenuated sporozoite vaccination

Vaccination with radiation-attenuated sporozoites (RAS) can provide highly effective protection against malaria in both humans and mice. To extend understanding of malaria immunity and inform the development of future vaccines, we studied the protective response elicited by this vaccine in C57BL/6 mice. We reveal that successive doses of Plasmodium berghei RAS favour the generation of liver CD8+ tissue-resident memory T cells (TRM cells) over circulating memory cells, and markedly enhance their longevity. Importantly, RAS immunisation strongly skews the composition of the liver CD8+ TRM compartment towards cells specific for abundant sporozoite antigens, such as thrombospondin-related adhesive protein (TRAP) and circumsporozoite protein (CSP), which become major mediators of protection. The increased prevalence of sporozoite specificities is associated with limited intrahepatic parasite development and inhibition of naive T cell responses to all parasite antigens in previously vaccinated mice. This leads to the exclusive expansion of effector T cells formed upon initial immunisation, ultimately reducing the diversity of the liver TRM pool later established. These findings provide novel insights into the mechanisms governing malaria immunity induced by attenuated sporozoite vaccination and highlight the susceptibility of this vaccine to limitations imposed by strain-specific immunity associated with the abundant, yet highly variable sporozoite antigens CSP and TRAP. Author SummaryMalaria remains a significant global health challenge. An efficient vaccine could significantly enhance malaria control. Vaccination with radiation-attenuated sporozoites (RAS) can induce highly efficient protection against malaria, and our study brings critical insights into the protective mechanisms elicited by this vaccine. We show that RAS stimulates the formation of parasite-specific cytotoxic memory T cells that permanently reside in the liver (liver TRM cells). These cells are critical mediators of protection. Interestingly, multiple doses of RAS extend the lifespan of these memory cells, potentially improving long term immunity. However, we found that the induced memory T cell response is strongly skewed towards abundant, but highly variable, sporozoite proteins. Thus, this phenomenon exposes a potential limitation of the RAS vaccine against the great parasite diversity in the field, as it focuses the T cell response away from less abundant, but more conserved, parasite antigens.

immunology↗

bioRxiv2024

Adapting C4 photosynthesis to atmospheric change and increasing productivity by elevating Rubisco content in Sorghum and Sugarcane

Meta-analyses and theory show that with rising atmospheric [CO2], Rubisco has become the greatest limitation to light-saturated leaf CO2 assimilation rates (Asat) in C4 crops. So would transgenically increasing Rubisco increase Asat and result in increased productivity in the field? Here, we successfully overexpressed the Rubisco small subunit (RbcS) with Rubisco accumulation factor 1 (Raf1) in both sorghum and sugarcane, resulting in significant increases in Rubisco content of 13-25% and up to 90% respectively. Asat increased 12-15% and Rubisco enzyme activity [~]40% in three independent transgenic events of both species. Sorghum plants also showed increased speeds of photosynthetic induction and decreased bundle sheath leakiness. These improvements translated into average increases of 15.5% in biomass in field-grown sorghum and a 37-81% increase in greenhouse-grown sugarcane. This suggests a potential opportunity to achieve substantial increases in productivity of this key economically important clade of C4 crops, future proofing their value under global atmospheric change. Significance StatementThe world is projected to need a 60% increase in food supply by 2050 (UN), and this must be achieved under conditions of global change without expanding onto yet more land. C4 crops, while few in number, account for a large proportion of agricultural productivity. We reason that rising atmospheric [CO2] has very recently made Rubisco, the enzyme used for all carbon fixation in plants, the greatest limitation to light saturated photosynthesis in C4 crops. We demonstrate that transgenically increasing Rubisco content in sorghum and sugarcane, increases their photosynthetic efficiency and productivity, including in a field trial of sorghum. This shows a means to sustainably increase the productivity of this key group of crops.

plant biology↗

bioRxiv2024

Machine learning driven image segmentation and shape clustering of algal microscopic images obtained from various water types

Algae and cyanobacteria are microorganisms found in almost all fresh and marine waters, where they can pose environmental and public health risks when they grow excessively and produce blooms. Accurate identification and quantification of these microorganisms are vital for ecological research, water quality monitoring, and public health safety. However, traditional methods of manually counting and morphologically identifying these microorganisms are time-consuming and prone to human error. Application of the machine learning-driven Fast Segment Anything Model (FastSAM), an image segmentation model, automates and potentially enhances the accuracy and efficiency of cell identification and enumeration from microscopic images. We assessed FastSAM for algal cell image segmentation, and three clustering evaluation metrics. Segmentation of microscopic images of algal and cyanobacterial cells in water and treated wastewater samples using the Convolutional Neural Network based FastSAM algorithm demonstrated benefits and challenges of this machine learning-driven image processing. Notably, the pre-trained algorithm segmented entire elements in all microscopic images used in this study. Depending on the shape, 50-100% similarity was observed between machine-based segmentation and manual validation of all segmented elements, with 100% of single cells being correctly segmented by FastSAM. The performance of clustering metrics varied between 57-94% with the Spectral Angle Mapper achieving the most accurate performance, 84-94%, compared to the manually chosen clustering benchmarks. Cyanobacterial and algal communities are biologically diverse and have ecological significance. The application of image clustering techniques in studying their cell shapes marks an important advancement in microbial ecology and environmental monitoring. As technology progresses, these methods will become increasingly utilised to decipher the complex roles that algae and cyanobacteria play in our ecosystems supporting mitigation and public health protection measures.

microbiology↗

bioRxiv2024

Reducing stomatal density by expression of a synthetic EPF increases leaf intrinsic water use efficiency and reduces plant water use in a C4 crop

Enhancing crop water use efficiency (WUE) is a key target trait for climatic resilience and expanding cultivation on marginal lands. Reducing stomatal conductance (gs) through manipulating stomatal density has been observed to translate to improved WUE in multiple C3 crop species. However, reducing gs in C3 species often reduces photosynthetic carbon gain. A different response is expected in C4 plants because they possess specialized anatomy and biochemistry which concentrates CO2 at the site of fixation. This modifies the photosynthesis (AN) relationship with intracellular CO2 concentration (ci) so that photosynthesis is CO2-saturated and reductions in gs are unlikely to impair AN. To test this hypothesis, genetic strategies were investigated to reduce stomatal density in the C4 crop sorghum. Constitutive expression of a synthetic epidermal patterning factor (EPF) transgenic allele in sorghum, lead to reduced stomatal densities. A moderate reduction in stomatal density did not strengthen stomatal limitation to AN, improved WUE, reduced water use, and avoided loss of carbon fixation during a period of water deprivation. However, these positive outcomes were associated with negative pleiotropic effects on reproductive development and photosynthetic capacity. Avoiding pleiotropy by targeting expression of the transgene to specific tissues provides a potential pathway to optimal agronomic outcomes.

plant biology↗