Biology subjects

Song, B.

Publications and source records attributed to Song, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Pan-pediatric brain tumor microRNA networks define immune microenvironment states and responses to CAR T-cell therapy

Pediatric central nervous system (CNS) tumors remain a leading cause of cancer-related mortality in children, yet molecular programs that shape their immune microenvironments and response to immunotherapy remain poorly defined. Because microRNAs (miRNAs) coordinately regulate gene expression across multiple pathways, we hypothesized that miRNA programs may capture broader immune states than individual immune-regulatory molecules. We integrated small RNA and bulk transcriptomic profiles from diffuse midline glioma, medulloblastoma, ependymoma, and low-grade glioma to identify miRNA programs associated with tumor immune states. Across tumor histologies, dysregulated miRNAs were associated with T-cell, natural killer cell, antigen-presentation, and myeloid programs. Diffuse midline glioma exhibited a distinct miRNA program associated with reduced lymphocyte signatures and increased suppressive myeloid features. Longitudinal profiling of immunocompetent glioma models during B7-H3 CAR T-cell therapy revealed dynamic remodeling of miRNA and immune transcriptional programs. Human tumor-associated miRNAs were significantly enriched among miRNAs associated with CAR T response in vivo. Functional interrogation of miR-149 demonstrated enhanced CAR T-cell expansion and sustained antitumor activity during repeated antigen stimulation. Together, these data define miRNA programs associated with immune states across pediatric CNS tumors and identify miR-149 as a candidate regulator of CAR T-cell function, providing a genomic framework for developing miRNA-directed strategies to improve CAR T-cell therapy.

cancer biology↗

bioRxiv2026

Histotripsy-induced vascular remodeling in the tumor microenvironment enhances local and off-target intratumoral drug delivery

Solid tumors are known to be refractory to treatment due to a poorly perfused microenvironment that blocks immune cell infiltration and effective drug delivery. Histotripsy is a non-invasive focused ultrasound modality that generates cavitation microbubbles to mechanically disrupt solid tumors, resulting in decreased hypoxia and stimulation of tumor-targeted adaptive immune responses. In this study, we aim to investigate whether post-histotripsy hypoxia reduction and cytotoxic immune cell infiltration are associated with normalization of tumor vasculature and enhanced perfusion. Structural analysis of both treated and contralateral off-target tumors following partial histotripsy revealed significant vascular remodeling, enhanced vascular integrity, and decreased vascular leakage indicative of vascular normalization in multiple in vivo models of melanoma, hepatocellular carcinoma, and pancreatic adenocarcinoma. These effects appeared antigen-specific, as no remodeling was observed in contralateral off-target tumors of discordant pathology. Mechanistically, CXCR3+CD8+ T cells played a role in mediating these vascular changes, as genetic knockout of CD8 and pharmacological antagonism of CXCR3 impaired both remodeling and normalization. Additionally, significant changes in endothelial CXCR4 and Angiopoietin-1 and -2 expressions were observed following histotripsy, indicating their potential involvement in promoting vascular normalization and remodeling. Significant vascular remodeling was accompanied by enhanced tumor perfusion and intratumoral delivery of chemotherapeutic agents and therapeutic monoclonal antibodies. These findings suggest that histotripsy not only creates a more favorable microenvironment for immunotherapy, but also optimizes drug delivery into solid tumors. Combinatorial approaches using histotripsy with chemotherapy or immunotherapy may be a novel therapeutic strategy to overcome current limitations of conventional solid tumor therapies.

immunology↗

bioRxiv2026

CytosMPS: an automated multimodal pooled screening platform for protein, morphology and transcriptomics

Cytos Multimodal Pooled Screening (CytosMPS) measures CRISPR guide identity, morphology, native 3' transcriptome, and protein abundance and localization in the same fixed cells. Following IL-1{beta} stimulation, cells with higher nuclear NF-{kappa}B show lower phospho-p38/HSP27 and higher NFKBIA/DUSP1 in the same cell, a measurement neither imaging nor transcriptomics alone provides. TGFBR2 and CTNNB1 perturbations produce distinct multimodal phenotypes. Guide representation and perturbation transcriptional responses agree with an orthogonal single-cell transcriptomic platform.

cell biology↗

bioRxiv2026

Loss of TDP-43 function drives cryptic circular RNAs in neurodegenerative diseases

TAR DNA-binding protein 43 (TDP-43) is a key pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) and a critical regulator of RNA splicing. While loss of TDP-43 induces aberrant splicing in linear transcripts, its impact on circular RNA (circRNA) biogenesis remains unexplored. Here, we show that TDP-43 depletion in human neurons induces widespread circRNA changes, especially upregulation of a distinct class of cryptic circRNAs that arise specifically upon loss of TDP-43. Some of these cryptic circRNAs incorporate cryptic exons derived from intronic sequences. Notably, these cryptic circRNAs exhibit greater stability than their corresponding linear RNA isoforms and accumulate progressively in neurons. Moreover, cryptic circRNAs are elevated in postmortem brain tissues from ALS, FTD and Alzheimer's disease (AD) patients. These findings reveal a previously unrecognized role for TDP-43 in repressing cryptic circRNA formation and establish these circRNAs as stable molecular signatures of TDP-43 dysfunction.

neuroscience↗

bioRxiv2026

A quantum state of mitochondria in the living cell

The high energy-efficiency of life is hard to understand only with classical physics. Many efforts have been made to study its mechanism based on quantum mechanics; the progress is nevertheless slow due to lack of experimental evidence with living cells. Here, combining experiments on cells, tissues and mitochondria with a theoretical model, we demonstrate a quantum state of mitochondria, which can be employed to modulate ATP production in living cells. We found an anomalous 71.0-THz oscillation mode only in living cells and tissues, which is highly determined by intact structure of mitochondria, and cannot be assigned to any specific molecules. Based on experimental data, a quantum model of light-matter coupling was introduced to trace the origin of this mode. Our calculations suggest a quantum superposition state of functional mitochondrion that forms by the coupling of light and lipid CH2 bonds in functional cristae, and induces a splitting of the intrinsic CH2 vibration mode of 87 THz to two levels at 71 THz and 103 THz, respectively. The former can be observed only in living cells and tissues; whereas the latter falls in the range (90-110 THz) of biomolecular and water vibrations, thus indistinguishable. Additional experiments revealed this mitochondrial quantum state able to serve as an efficient channel to modulate ATP production. Our findings provide a quantum mechanics view for understanding living cells, and it will be interesting to further explore whether such quantum state could act as a channel for energy metabolism, and even information transmission in life.

biophysics↗

bioRxiv2026

Bias-aware versus bias-blind confidence in humans and machines

Confidence evaluates the likely accuracy of a current decision. However, to be maximally informative about accuracy, confidence judgments should incorporate information about ones broader decision tendencies, such as their propensity to favor specific alternatives. We distinguish bias-aware confidence, which considers such tendencies, from bias-blind confidence, which relies only on evidence available on the current trial. To adjudicate between bias-aware and bias-blind confidence, we identified a signature of bias-aware confidence: the down-weighting of confidence for alternatives that a participant is biased toward. We then used a large dataset (N = 200) spanning 4- and 8-choice digit-classification tasks to show that humans reliably exhibit this signature of bias-aware confidence. This effect was reduced under speed pressure and could not be explained by guessing. In contrast to the human results, artificial neural networks (ANNs) trained for object recognition lacked this signature of bias- aware confidence. Importantly, augmenting ANNs with a metacognitive module that allows confidence to take the networks biases into account led to the emergence of human-like bias- aware confidence. These findings show that human confidence incorporates not only information from the current trial but also longer-term decision tendencies, and that this capacity - absent in standard ANNs - can be conferred through specialized metacognitive mechanisms.

neuroscience↗

bioRxiv2026

Decoding the oxytocinergic and behavioral signatures of milk ejection

Oxytocin-mediated milk ejection (ME) is pivotal to effective breastfeeding and productive health, yet behaviorally decoding and revealing neural mechanisms of ME remains challenging. Here, we combined in vivo calcium imaging and intramammary pressure recording to uncover the temporal connections between episodic activity of oxytocin neurons and ME in conscious lactating rats. Leveraging the association and behavioral responses in dam and pup, we developed a supervised machine learning framework (ME Decoder) to enable automated analyses of ME. Inspired by its interpretable features, we defined the activity-coupled dam-pup interactions (ADPI), manifested by high kyphosis of the dam followed by pup treading and stretch, as the behavioral signatures of ME. By ME Decoder and ADPI analyses, we detected reduced ME but unaffected activity of oxytocinergic neurons after systemic blockade of oxytocin receptor. Our study uncovers the oxytocinergic and behavioral signatures of ME and provides a generalizable approach for further investigation.

neuroscience↗

bioRxiv2026

Evolutionary-scale protein language models uncover beneficial variants in a Sorghum bicolor diversity panel

Quantitative genetic approaches such as genome-wide association studies and genomic prediction are widely used to identify favourable genetic variation, but they have limited resolution due to linkage disequilibrium. Comparative genomics approaches, especially Protein Language Models (PLMs), have emerged as powerful alternatives, by detecting phylogenetic residue conservation (PRC) across evolutionary time scales. However, the extent to which these tools can guide the detection of impactful variants for field agronomic traits is still unclear. In this study, we used the pre-trained PLM ESM2 to predict PRC scores of nonsynonymous mutations segregating within a diverse panel of 387 accessions in sorghum (SAP). The distribution of fitness effects (DFE) of the same set of nonsynonymous mutations was inferred using unfolded site frequency spectra to assess whether the DFE distribution covaried with PRC scores. Furthermore, we estimated the load of putatively nonneutral mutations of SAP accessions and evaluated associations between this mutation load and phenotypic performance across multiple agronomic traits. Our results show that ESM2 can detect mutations associated with fitness-enhancing effects in SAP, as indicated by enrichments in positive selection signatures among the variants with positive PRC scores. Significant associations were also detected between phenotypic performance and mutation load for several agronomic traits, indicating that PLMs can identify functionally important genetic variation. However, these signals were not consistent across all traits in the SAP population. Altogether, our findings suggest that large language models may support breeding efforts, as PLM predictions covaried with fitness effects and captured agronomic performance for some traits in plant populations.

genetics↗

bioRxiv2026

OpenAc4C: A gateway to decode the landscape, regulation and pathogenesis of N4-acetylcytidine (ac4C) epitranscriptome

N4-acetylcytidine (ac4C) is an ancient and highly conserved chemical marker found in all domains of life. Recent advancements in sequencing techniques have enabled the functional analysis of ac4C occurrence by accurately capturing its locations and levels, shedding light on its significant regulatory potential and emerging role in diseases. The OpenAc4C, the first comprehensive knowledgebase exclusively designed for unraveling the ac4C epitranscriptome across diverse species, spanning vertebrates, mammals, insects, fungi, plants, bacteria, archaea, and viruses. By mining a large array of ac4C epitranscriptome datasets with deep learning-based pipelines, OpenAc4C features a collection of 536,745 ac4C sites identified from four distinct next-generation sequencing (NGS)-based techniques, alongside novel insights from Oxford Nanopore direct RNA sequencing (ONT)-based samples, encompassing a total of 33 species. Beyond the ac4C landscape, a total of 536,986 ac4C-affecting variants were identified in seven species. Among them, 4,766 pathogenic ac4C-SNPs may drive ac4C dysregulation with implications for disease pathogenesis. In addition, OpenAc4C offers a user-friendly graphical interface and a web-based analysis platform for comprehensive querying and interactive exploration of the database collections. Together, OpenAc4C will serve as a valuable integrated resource to facilitate studies of ac4C modification. It is freely accessible at: www.rnamd.org/ac4cportal.

bioinformatics↗

bioRxiv2026

pertTF: context-aware AI modeling for genome-scale and cross-system perturbation prediction

Predicting genetic perturbation responses at a single-cell level is central to building models for cell state and disease. However, existing approaches are limited on predicting phenotypic outcomes beyond expression changes and generalizing predictions across genome-scale perturbations in biologically relevant contexts. Here we introduce pertTF, a transformer-based single-cell genetic perturbation model. pertTF was trained from a unique dataset capturing single cell expressions profiles of 30 full gene knockouts across 14 relevant cell types during human pancreatic development and beta-cell differentiation. pertTF outperforms current methods in predicting expression changes of perturbing unseen genes in unseen cellular contexts. In addition, pertTF infers perturbation-induced shifts in cell identity and population composition, an important phenotypic outcome of perturbation in many physiology and disease settings. Through transfer learning, pertTF operates in physiologically relevant systems, including primary human islets, where large-scale perturbation experiments are challenging. The generalizability of pertTF is further demonstrated by in silico pooled and single-cell CRISPR screens, capturing critical regulators of stem cells and early pancreatic cell development. These results establish pertTF as a framework for integrating large-scale single-cell perturbation data with AI models to predict genetic perturbation effects across cellular systems and disease contexts.

bioinformatics↗

bioRxiv2026

Mid-infrared light produces anti-ageing effects through resonant absorption by living organisms

Aging is commonly viewed as a consequence of cumulative molecular damage and declining stress resilience. However, this perspective overlooks the possibility that aging may primarily arise from an efficiency loss of integrated cellular operation. Here, we show that aging can be systemically prevented by enhancing cellular efficiency using frequency-specific mid-infrared (MIR) light, as revealed by organismal-, cellular- and molecular-level analyses of Caenorhabditis elegans. Remarkably, super-weak 34-THz MIR light ([~]1 W mm-{superscript 2}) prolonged the median lifespan of worms by 60%, delaying aging onset and preventing abrupt "cliff-edge" mortality, without detectable thermal effects. At the cellular level, MIR exposure enhanced global gene transcription in parallel with the establishment of a mitochondrial state of high-efficiency energy metabolism, together preserving youthful cellular homoeostasis during aging. These cellular effects were associated with vibrational modes of phosphate groups in nucleic acids and mitochondrial phospholipids within the 33-35 THz range, providing a frequency-matched molecular context for MIR modulation. Together, our results support an efficiency-first, systemic anti-aging model in which frequency-specific MIR light enhances the integrated kinetic efficiency of cellular systems, spanning gene transcriptional dynamics and mitochondrial bioenergetic flux, rather than the activation of damage-repair or stress-response pathways. These findings advance our understanding of light-matter interactions in living systems and establish a non-biochemical, physical strategy for modulating aging.

biophysics↗

bioRxiv2025

A stem cell knockout village reveals lineage rewiring and a non-canonical islet cell fate in monogenic diabetes

Genetics studies have identified a core set of regulators essential for pancreatic {beta} cell development, many of which are mutated in monogenic diabetes. However, how these mutations alter developmental trajectories to produce pathological cell states remains elusive. Here we introduce a knockout village framework that enables longitudinal scRNA-seq profiling of 79 human pluripotent stem cell mutant lines targeting 30 developmental regulators, including 15 diabetes genes, across five islet differentiation stages. We show that loss of lineage regulators impairs {beta} cell formation in a stage-specific manner and rewires developmental trajectories towards competing lineages. Notably, several monogenic diabetes gene mutations drive a shift from {beta} cells to enterochromaffin (EC)-like cells, a recently recognized non-canonical islet cell fate. These EC-like cells exhibit incomplete activation of hormone regulation programs, along with elevated neuron signatures. Leveraging the diversity of cell fate outcomes across mutants, we predicted and experimentally validated ISL1 as a key downstream effector of PDX1 and PAX6 that safeguards {beta} cell identity against an EC-like fate. Together, our findings reveal cell fate rewiring as a widespread, previously underappreciated pathological mechanism in monogenic diabetes and establish a scalable platform for uncovering developmental vulnerabilities in human genetic disorders.

developmental biology↗

bioRxiv2025

Multicolored, Sonosensitizer-optimized Organic Mechanoluminescent Nanoparticles for Functional Sono-optogenetics

Light enables precise visualization and control of cellular processes, but its utility in deep tissues is fundamentally limited by poor optical penetration, particularly in the deep brain. Ultrasound-triggered mechanoluminescence offers a non-invasive strategy for remote light delivery, yet existing organic systems remain monochromatic and low-intensity, largely due to an incomplete understanding of ultrasound-induced emission. Here, we report a multicolor mechanoluminescence platform that couples reactive oxygen species-responsive chemiluminescent donors with fluorescent acceptors via Forster resonance energy transfer, generating tunable emission from blue (459 nm) to red (592 nm). Systematic screening potentially reveals that electronic energy gap-dependent reactive oxygen species generation serves as a predictive design principle for high-performance mechanoluminescent materials. The emitted spectrum and intensity are sufficient to activate ChR2 and ChRmine and inhibit eOPN3, enabling bidirectional, fiber-free neuromodulation under focused ultrasound. By integrating spatially precise ultrasound with programmable photon output, this platform establishes a non-invasive strategy for deep-tissue neural monitoring and provides a foundation for applications in bioimaging, gene editing, and precision therapeutics.

bioengineering↗

bioRxiv2025

Beyond magnetosomes: ubiquitous and diverse intracellular inclusions expand the role of magnetotactic bacteria in biogeochemical cycling

Magnetotactic bacteria (MTB) are capable of accumulating and storing intercellular pools containing phosphorus, sulfur, nitrogen and carbon. Yet, the metabolic pathways connected with their intracellular storage of polyphosphate, elemental sulfur, nitrate, and calcium carbonate, and the environmental influence on MTB inclusions and their quantitative contribution to sedimentary chemical budgets remain underexplored. Using a combination of chemical characterization, ultrastructural and compositional analyses, and phylogenetic and genomic insights into microbial assemblages, we investigated the influence of geochemical parameters on the diversity, ecophysiology, and distribution of MTB in freshwater and brackish sediments. Special focus is given to intracellular inclusions and their metabolic pathways to uncover functional traits and ecological roles in elemental cycling. Of the 118 examined MTB cells, polyphosphate granules (75%) and nitrate-containing vacuoles (67%) were the most common inclusions followed by sulfur globules (25%) and calcium carbonate granules (8%). The intracellular phosphorus, nitrogen, and sulfur stored in MTB cells were conservatively estimated to account for 0.60%, 0.91%, and 0.23% of the total sedimentary P, N, and S in the investigated freshwater sediments, respectively. The ubiquitous nature and important ecological role of MTB can be explained by their ability to sequester chemical elements into intracellular inclusions, giving them a metabolic advantage in dynamic chemically stratified environments. The extraordinary phylogenetic diversity of MTB, coupled with their capability to hyperaccumulate and store a wide range of elements and compounds, represents a significant resource for biotechnology innovation.

microbiology↗

bioRxiv2025

Altered striatal dopamine dynamics and behavior in Grin2a mutant mice, a genetic mouse model of schizophrenia

Schizophrenia (SCZ), a complex psychiatric disorder with a strong genetic basis, is thought to involve, at least in part, dopamine dysregulation in the striatum. Recent large-scale exome sequencing has identified multiple SCZ risk genes, including GRIN2A (encoding an NMDA (N-methyl-D-aspartate) receptor subunit) and AKAP11 (encoding a protein kinase A binding protein), which is also a risk gene for bipolar disorder (BD). However, the mechanisms by which these genetic risk factors perturb dopamine circuits and cause psychotic symptoms remain poorly understood. We asked how behavior, dorsomedial striatal dopamine (DA) dynamics and the activity of D1-/D2-spiny projection neurons (SPNs) were altered in Grin2a and Akap11 mutants. In the open field, Grin2a knockout mice display hyperlocomotion and an abnormal organization of naturalistic behaviors. They also displayed heightened behavioral responses to objects and auditory stimuli. Grin2a heterozygous animals mostly showed intermediate phenotypes, suggesting a dose-dependent effect of Grin2a loss. Further, Grin2a knockout mutants exhibited aberrant dopamine events, altered coupling of dopamine with locomotor features, and exaggerated stimuli-evoked dopamine responses. Notably, heterozygous animals also showed altered striatal SPN events in the open field reflecting dysregulated neural activity in both dSPNs and iSPNs. Compared to Grin2a mutants, Akap11 mutants displayed opposite phenotypes, showing reduced locomotion with a shift from high- to low-velocity movement and distinct alterations in striatal neural activity. Together, GRIN2A (SCZ risk) and AKAP11 (BD/SCZ risk) mutations induce different, often opposite, effects on striatal dopamine signaling and behavior, suggesting that these two risk genes act through distinct mechanisms.

neuroscience↗

bioRxiv2025

PTPRJ-Targeting Peptide Agonist Induces Broad Cellular Signaling Perturbations and DNA Damage in Lung Cancer Cells

Receptor protein tyrosine phosphatases (RPTPs) are key regulators of cell signaling. However, their study and therapeutic targeting have been limited by the lack of known natural ligands or selective agonists, as well as an incomplete understanding of their structure-function relationships. Nonetheless, receptor homodimerization has been shown to suppress RPTP catalytic activity by restricting substrate access, offering a promising strategy for examining and modulating their function. Our previous work on PTPRJ, a member of the RPTP family, showed that its transmembrane domain regulates homodimerization, thereby controlling access to receptor tyrosine kinase (RTK) substrates and their phosphorylation levels. We also developed peptides that disrupt this dimerization, thereby inhibiting RTK phosphorylation and reducing cancer cell migration. These peptides were then engineered for selective, pH-sensitive insertion into the acidic tumor microenvironment to enhance efficacy while limiting off-target effects. Yet how broadly PTPRJ activation reshapes the phosphotyrosine landscape and whether those changes yield coherent cellular phenotypes remains unclear. In this study, we employed tyrosine phosphoproteomics, immunoblotting, immunofluorescence, and functional assays to assess the global impact of our lead peptide candidate, Hybrid 7, in A549 lung cancer cells that endogenously express PTPRJ. We find that Hybrid 7 decreases EGFR phosphorylation and selectively reduces phosphorylation across additional RTKs and motility adaptors, producing strong inhibition of EGF-driven migration and reduced proliferation. Hybrid 7 also elevates reactive oxygen species and DNA damage, and enforces CDK1-dependent G2/M arrest, indicating a primarily cytostatic, checkpoint-mediated response. These findings highlight the potential of RPTP-targeting peptides as valuable tools for dissecting RPTP function and as possible therapeutic agents capable of modulating key oncogenic pathways and inhibiting cancer progression.

biochemistry↗

bioRxiv2025

SpaceSequest: A unified pipeline for spatial transcriptomics data analysis

BackgroundSpatial transcriptomics has emerged as one of the most powerful tools for gaining biological insights, enabling researchers to uncover intricate relationships between gene expression patterns and tissue architecture. Recent advances in the field have resulted in a variety of new platforms, including Visium, Visium HD, and Xenium from 10x Genomics, as well as GeoMx and CosMx from NanoString Technologies, which has now been acquired by the Bruker Corporation. However, the existence of diverse spatial transcriptomics platforms and various data formats poses challenges in standardizing data analysis. Thus, there remains a critical gap in the availability of a comprehensive pipeline capable of conducting end-to-end analysis that is necessary to extract biological insights from multiple spatial transcriptomics platforms. ResultsHere, we present SpaceSequest, a tailored pipeline that utilizes cutting-edge computational methodologies to conduct a thorough analysis, enabling the extraction of crucial biological insights from five major spatial transcriptomics technologies. SpaceSequest performs (1) standardized quality control and general data processing, (2) key analyses customized for each spatial platform, (3) automated cell type annotation and deconvolution, and (4) high-quality figure and analysis result generation. In addition, SpaceSequest allows for smooth integration with cellxgene VIP and Quickomics for user-friendly data access and interactive visualization. ConclusionsSpaceSequest is a unified and comprehensive pipeline designed for the analysis, visualization, and publication of spatial transcriptomics data from various platforms. The source code is available at https://github.com/interactivereport/SpaceSequest. To facilitate seamless installation and usage, we have also created a detailed Bookdown tutorial that can be accessed through https://interactivereport.github.io/SpaceSequest/tutorial/docs/index.html.

bioinformatics↗

bioRxiv2025

A Phosphorelay Circuit Drives Extracellular Alkalinization in Plant Receptor Kinase Signaling

Extracellular alkalinization has long been recognized as a hallmark of plant cell-surface receptor activation, including during pattern-triggered immunity (PTI); yet the mechanisms driving elicitor-induced alkalinization and its role in immune signaling remain unclear. Here, we demonstrate that inhibition of autoinhibited H+-ATPases (AHAs) is required for elicitor-induced extracellular alkalinization. This alkalinization is essential for immune signaling mediated by diverse plasma membrane-localized receptor kinases (RKs) through modulation of ligand-receptor interactions. Notably, RKs transduce elicitor-triggered signaling via BOTRYTIS-INDUCED KINASE 1 (BIK1), which inhibits AHA activity by disrupting AHA-GENERAL REGULATORY FACTOR (GRF) interactions through a conserved phosphorylation event. Interestingly, this pathway is crucial for cell wall damage (CWD) responses involving the RK MALE DISCOVERER 1-INTERACTING RECEPTOR LIKE KINASE 2 (MIK2) and its ligand, SERINE RICH ENDOGENOUS PEPTIDE 18 (SCOOP18). Our findings reveal a conserved phospho-regulatory pathway that governs extracellular alkalinization to coordinate plant immune signaling, offering new insights into plant stress resilience.

plant biology↗