Biology subjects

Shen, L.

Publications and source records attributed to Shen, L..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Guidance receptor-mediated mechanocompliance of GBM cells facilitates immune-silent invasion

The lethality of glioblastoma (GBM) stems from diffuse infiltration and immune evasion, two hallmarks traditionally studied separately. Here, we identify as unifying mechanism how GBM cells utilize guidance receptors Plexin-D1 and Plexin-B2 to gain mechanocompliance, i.e., the ability to deform and remodel membrane/cytoskeleton during confined migration without triggering immune activation. We show that PLXND1 upregulation marks invasive fronts and predicts poor survival of glioma patients. Through live-cell imaging in microchannels, intracranial xenografts, single-nucleus transcriptomics, and lipidomics we demonstrate that Plexin-D1/B2 enable GBM cells to retract tumor microtubes (TMs), traverse constrictions, and escape microglial surveillance. Single and especially double deletion of PLXND1 and B2 resulted in TM overgrowth, membrane instability, and susceptibility to cell fragment shedding, leading to impaired migration and a shift to activation of tumor-associated myeloid cells. Our findings thus reveal a molecular strategy used by GBM cells to penetrate through interstitial space while escaping immune surveillance. SIGNIFICANCEPlexin-mediated mechanocompliance underlies the invasive yet immune-silent behavior of GBM cells, exposing a vulnerability that could be therapeutically exploited by forcing invading tumor cells into a mechanically fragile, immunogenic state.

cancer biology↗

bioRxiv2025

Epigenetic editing of Cartpt promotes acquisition and extinction of cocaine memory

In classic disease models, removing a pathological insult restores homeostasis. Yet, addiction persists far beyond the period of active drug use. Cocaine abstinence induces changes in gene expression and neuronal signaling in reward-related brain regions that limit recovery during abstinence. We found that 2 weeks of abstinence increased Cartpt (cocaine- and amphetamine-regulated transcript) in the mouse nucleus accumbens and decreased repressive H3K27me3 at the Cartpt locus. While endogenous CART peptide is best described for its anorexigenic function, it is also implicated in human addiction and dopamine homeostasis. To test the causal relevance of Cartpt chromatin remodeling, we used CRISPR-based epigenetic editing tools, dCas9-FOG1 and dCas9-JMJC-ZF, to manipulate H3K27me3 at Cartpt in vivo. Enriching H3K27me3 in D1 neurons repressed Cartpt expression and augmented acquisition and extinction of cocaine preference. These results show that CRISPR epigenetic editing can recapitulate endogenous chromatin states to modulate addiction-related behavior, highlighting broad therapeutic potential of both Cartpt and epigenetic editing. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=192 SRC="FIGDIR/small/689329v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1b84229org.highwire.dtl.DTLVardef@1ffc2d7org.highwire.dtl.DTLVardef@50cf00org.highwire.dtl.DTLVardef@1462d10_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Cortical tension as a mechanical barrier to safeguard against premature differentiation during neurogenesis

Neuronal differentiation requires coordinated gene reprogramming and morphodynamic remodeling. How mechanical forces integrate with nuclear gene programs during neurogenesis remains unresolved. Here, we identify cortical tension as a mechanical barrier that safeguards against premature neuronal differentiation. Deletion of Plexin-B2, a guidance receptor controlling actomyosin contractility, lowers this barrier, enabling neurite outgrowth and accelerating neuronal lineage commitment. We show that coupling of extrinsic differentiation cues with intrinsic morphodynamics is essential for stabilizing neuronal fate and that cortical barrier and epigenetic barrier act in concert to regulate developmental timing. In cerebral organoids, Plexin-B2 ablation triggered premature cell-cycle exit and differentiation, resulting in progenitor pool depletion and neuroepithelial disorganization, phenotypes echoing intellectual disability in patients with rare pathogenic PLXNB2 variants. Our studies demonstrate that cortical tension functions as mechano-checkpoint that regulates the onset of neurogenesis. Lowering this barrier may provide a strategy to accelerate induced neuron generation and maturation for CNS disease modeling.

neuroscience↗

bioRxiv2025

Adaptation of Perceived Animacy from Biological Motion: Evidence for a "Life Motion Detector"

Humans can readily perceive animacy from biological motion (BM) - the distinctive movement patterns of living entities. However, how the human brain extracts animacy information from BM remains largely unclear. The current study investigated this issue using visual adaptation, a non-invasive tool for revealing neural mechanisms underlying the selective processing of specific properties. Results showed that prolonged exposure to intact human walkers, compared to non-BM adaptors, biased the perception of subsequent walking stimuli towards less animate. This adaptation aftereffect persisted following adaptation to local foot motions carrying diagnostic kinematic cues, but was absent after exposure to static body forms, indicating the involvement of neuronal populations encoding animacy from BM based on motion signals. Moreover, adapting to pigeon movements also biased animacy perception for human motions, revealing a shared mechanism for encoding animacy from cross-species BM signals. These results support the existence of an inherent "life detection" system in the human brain, attuned to local foot motions and kinematic features prevalent in vertebrate movements, which may lay a foundation for perceiving life from motion across terrestrial species. Public significance statementsDiscerning whether a moving entity is animate is crucial for survival and for generating appropriate responses. This study explored how the human brain perceives animacy based on a prevalent movement pattern among vertebrates, namely, walking. Leveraging a non-invasive visual adaptation paradigm, five experiments demonstrated that pre-exposure to intact human walking, feet-only walking, and even intact pigeon walking motion sequences - but not static human forms - elicited significant adaptation aftereffects in animacy perception of human walkers. These findings support the existence of neural substrates encoding perceived animacy based on biological motion signals, particularly those carried by local foot motions and cross-species kinematic features. Such mechanisms may be integral to an inherent life detection system in the human brain.

neuroscience↗

bioRxiv2025

SARS-CoV-2 NSP14 inhibitor exhibits potent antiviral activity and reverses NSP14-driven host modulation

The emergence of SARS-CoV-2 variants and drug-resistant mutants highlights the urgent need for novel antiviral therapeutics. SARS-CoV-2 NSP14, an N7-guanosine methyltransferase, plays a critical role in viral RNA capping, enabling viral replication and immune evasion. While NSP14 has emerged as a promising drug target, its role in host-virus crosstalk and the cellular consequences of NSP14 inhibition remain poorly understood. Here, we present the identification and characterization of C10, a highly potent and selective first-in-class non-nucleoside inhibitor of the NSP14 S-adenosylmethionine (SAM)-binding pocket. C10 demonstrates robust antiviral activity against SARS-CoV-2, including its variants, with EC50 values ranging from 64.03 to 301.9 nM, comparable to the FDA-approved drug remdesivir in our cell-based assays. C10 also exhibits broad-spectrum activity against other betacoronaviruses and inhibits SARS-CoV-2 at the replication stage. C10 suppresses viral translation and exhibits immunostimulatory effect. Additionally, C10 specifically reversed NSP14-mediated alterations in host transcriptome. The antiviral efficacy of C10 was further validated in a transgenic mouse model of SARS-CoV-2 infection. Our findings highlight C10 as a promising candidate for the development of effective treatments against SARS-CoV-2 and its emerging variants. This study also uncovers a novel mechanism of NSP14 in SARS-CoV-2 pathogenesis and its therapeutic potential, providing insights that may extend to other viral capping methyltransferases.

microbiology↗

bioRxiv2025

AlphaGenome Enhances Personal Gene Expression Prediction but Retains Key Limitations

In recent years, numerous genome AI models have been developed to elucidate the relationship between DNA sequence and gene expression. However, these models have faced criticism for their limited accuracy in predicting individual-specific gene expression. AlphaGenome, the current state-of-the-art in genome AI, achieves exceptional performance across a range of sequence-based predictive tasks, but its utility for personal expression prediction has not yet been assessed. In this study, we evaluate AlphaGenomes ability to predict personal gene expression and find that it significantly outperforms its predecessor. Using GTEx data, AlphaGenome improves the prediction of expression direction over Enformer, achieving an odds ratio of 3.0. In some cases, it even reverses previously observed negative correlations into positive ones. Moreover, AlphaGenome demonstrates improved performance for genes with known nonlinear sequence-expression relationships, though it uncovers mechanisms distinct from those identified by tree-based models.

genomics↗

bioRxiv2025

CAT-APP: Contamination Analysis and Tempering--An Automated Online Platform for Plasma Proteomics with Data Rescuing Capabilities

Plasma and serum proteome profiling have become central to biomarker discovery for medical research. The advent of high-throughput plasma proteomics pipelines has enabled the generation of massive datasets. However, biomarker discovery is frequently compromised by sample contamination, primarily from erythrocytes, platelets, and coagulation factors. Such contamination can lead to the false identification of contaminants as biomarkers in over 50% of studies or obscure genuine biomarkers due to contamination-induced variability. Currently, no tools are available to salvage such compromised data, and the default approach is often to discard the affected samples. To address this gap, we introduce CAT-APP (Contamination Analysis and Tempering-An Automated Online Platform for Plasma Proteomics). CAT-APP tackles contamination through three key modules: multi-dimensional contamination assessment and adaptive contamination indexing, mathematical model-based contamination tempering, and data recovery evaluation with visualization. We applied CAT-APP to 28 independent plasma proteomics datasets and found that 82% exhibited contamination issues. CAT-APP markedly improved data quality by removing false-positive biomarkers introduced by contamination and restoring true biological signals that were previously obscured in representative datasets. To promote widespread adoption, we provide CAT-APP as an freely accessible, user-friendly, and robust web platform at https://www.bloodecosystem.com/tools/CAT-APP/.

bioinformatics↗

bioRxiv2025

JASMINE: A powerful representation learning method for enhanced analysis of incomplete multi-omics data

Integrative analysis of multi-omics data provides a more comprehensive and nuanced view of a subjects biological state. However, high-dimensionality and ubiquitous modality missingness present significant analytical challenges. Existing methods for incomplete multi-omics data are scarce, do not fully leverage both modality-specific and shared information, and produce task-biased representations. We propose JASMINE, a self-supervised representation learning method for incomplete multi-omics data that preserves both modality-specific and joint information and enhances sample similarity structure. JASMINE produces embeddings that achieve superior performance across multiple tasks for two different incomplete multi-omics datasets while requiring only a single round of training per dataset.

bioinformatics↗

bioRxiv2025

Astrocytic CREB regulates transcriptional, neuronal, and behavioral responses to cocaine

Drug addiction is characterized by neuronal adaptations that support a shift from goal-directed behaviors to habitual, compulsive drug-seeking with persistent effects on cognition and decision-making. Emerging evidence increasingly indicates that astrocytes are also involved in nervous system disorders, including addiction, but the cocaine-induced astrocyte-specific transcriptome has not yet been investigated. We utilized whole cell sorting of astrocytes, RNA-sequencing, and bioinformatic approaches to characterize the astrocyte transcriptome in the nucleus accumbens (NAc), a key brain region involved in reward-processing, following cocaine self-administration, prolonged abstinence, and "relapse" in male mice. We found that astrocytes exhibit robust and contextually-specific transcriptional signatures that converge strongly with human cocaine use disorder. Bioinformatic analysis revealed CREB as a highly ranked predicted upstream regulator of cocaine-induced transcriptional regulation in NAc astrocytes, and CUT&RUN-sequencing mapped increased CREB binding across the astrocyte genome in response to cocaine. Viral-mediated manipulation of CREB activity selectively in NAc astrocytes, in combination with several measures of addiction-related behaviors including conditioned place preference and self-administration, revealed that astrocytic CREB increases the rewarding and reinforcing properties of cocaine. This effect is sex-specific, with no change in astrocytic CREB activity or CPP found in females. Subsequent experiments identify potential molecular mechanisms of astrocytic CREBs influence through modulating astrocytic Ca2+ signaling in response to cocaine. Finally, we show that astrocytic CREB selectively modulates D1-type medium spiny neurons in NAc to control cocaine-related behaviors. Together, these data demonstrate that the astrocyte transcriptome responds robustly to cocaine and that CREB mediates cocaines effects on gene expression in astrocytes, with consequent effects on neuronal activity and rewarding responses to the drug.

neuroscience↗

bioRxiv2025

PP2A METHYLESTERASE, PME-1, AND PP2A METHYLTRANSFERASE, LCMT-1, CONTROL SENSITIVITY TO IMPAIRMENTS CAUSED BY INJURY-RELATED OLIGOMERIC TAU

Oligomeric species of tau are a hallmark of multiple neurodegenerative diseases such as Alzheimers disease (AD) and chronic traumatic encephalopathy (CTE). Given the evidence implicating protein phosphatase 2A (PP2A) in the molecular pathogenesis of tau-related neurodegenerative disorders, we sought to determine whether manipulating the expression of enzymes that regulate PP2A activity, such as leucine carboxyl methyltransferase 1 (LCMT-1) and protein methyl esterase 1 (PME-1), might impact pathological responses to oligomeric tau. Here, we tested the effect of transgenic overexpression of LCMT-1 or PME-1 on cognitive and electrophysiological impairments caused by exposure to either recombinant oligomeric human tau or oligomeric tau prepared from mice subjected to blast-induced traumatic brain injury. We found that overexpression of LCMT-1 reduced sensitivity to tau-induced impairments, while overexpression of PME-1 increased sensitivity to these impairments. Moreover, we found that shockwave exposure increased the propensity of endogenous tau to form toxic oligomers. These results suggest that manipulating LCMT-1 or PME-1 activity may represent novel therapeutic approaches for disorders involving exposure to pathogenic forms of oligomeric tau.

neuroscience↗

bioRxiv2025

SPLiCR-seq: A CRISPR-Based Screening Platform for RNA splicing Identifies Novel Regulators of IRE1-XBP1 Signaling Under ER Stress

RNA splicing is fundamental to cellular function, yet systematic investigation of its complex regulation has been limited by existing methods. Here, we present SPLiCR-seq (SPLicing regulator identification through CRISPR screening), a high-throughput CRISPR screening platform that enables direct measurement of RNA splicing outcomes for pooled genetic perturbations, overcoming limitations of traditional fluorescence-based approaches. Applying SPLiCR-seq to investigate XBP1 splicing during the unfolded protein response (UPR), we conducted targeted and genome-wide screens across diverse cellular contexts, revealing both common and cell-type specific regulators. Notably, we identified GADD34 (PPP1R15A) as a novel modulator of IRE1-XBP1 signaling, demonstrating that it directly interacts with IRE1 and functions independently of its canonical role in eIF2 dephosphorylation. Pharmacological inhibition of GADD34 using Sephin1 effectively suppressed XBP1 splicing and alleviated CAR-T cell exhaustion in an ex vivo model, leading to enhanced tumor-killing capacity across multiple cancer models. This work not only establishes a powerful new tool for systematically studying RNA splicing regulation but also uncovers a promising therapeutic strategy for improving CAR-T cell immunotherapy through modulation of the IRE1-XBP1 pathway.

genetics↗

bioRxiv2025

Representational dynamics during extinction of fear memories in the human brain

Extinction learning - the suppression of a previously acquired fear response - is critical for adaptive behavior and core for understanding the etiology and treatment of anxiety disorders. Electrophysiological studies in rodents have revealed critical roles of theta (4-12Hz) oscillations in amygdala and hippocampus during both fear learning and extinction, and engram research has shown that extinction relies on the formation of novel, highly context-dependent memory traces that suppress the initial fear memories. Whether similar processes occur in humans and how they relate to previously described neural mechanisms of episodic memory formation and retrieval remains unknown. Intracranial EEG (iEEG) recordings in epilepsy patients provide direct access to the deep brain structures of the fear and extinction network, while representational similarity analysis (RSA) allows characterizing the memory traces of specific cues and contexts. Here we combined these methods to show that amygdala theta oscillations during extinction learning signal safety rather than threat and that extinction memory traces are characterized by stable and context-specific neural representations that are coordinated across the extinction network. We further demonstrate that context specificity during extinction learning predicts the reoccurrence of fear memory traces during a subsequent test period, while reoccurrence of extinction memory traces predicts safety responses. Our results reveal the neurophysiological mechanisms and representational characteristics of context-dependent extinction learning in the human brain. In addition, they show that the mutual competition of fear and extinction memory traces provides a mechanistic basis for clinically important phenomena such as fear renewal and extinction retrieval.

neuroscience↗

bioRxiv2025

Predicting 3D Chromatin Interactions Using Transformer-Enhanced Deep Learning Models

The three-dimensional (3D) structure of the human genome is essential for regulating gene expression and cellular functions. Chromatin interactions bring distant genomic regions into physical contact, enabling processes like gene regulation, DNA replication, and repair. Disruptions in this organization can lead to diseases such as cancer and genetic disorders. In this study, we propose a Transformer-based deep learning model to predict the chromatin interactions from DNA sequences. By developing a streamlined and efficient data pipeline to handle the sparse and noisy high-throughput chromosome conformation capture (Hi-C) sequencing data, our approach improves both data processing speed and model performance. The Transformers ability to capture long-range interactions among genomic regions via attention mechanism, combined with nucleotide position encoding, enables more accurate predictions than purely convolution-based models. This work highlights the potential of Transformer-based network architectures to advance our understanding of genome organization and paves the way for future research with large datasets and advanced network designs.

bioinformatics↗

bioRxiv2025

Autism-associated Scn2a haploinsufficiency disrupts in vivo dendritic signaling and impairs flexible decision-making

SCN2A is a high-confidence risk gene for autism spectrum disorder. Loss-of-function mutations in Scn2a reduce dendritic excitability in neocortical pyramidal cells. However, the impact of Scn2a haploinsufficiency on dendritic signaling in vivo, particularly during behavior, is unknown. In this study, we used two-photon microscopy to image dendritic calcium transients in deep layer pyramidal cells in the mouse medial frontal cortex. Scn2a+/- mice had diminished coupling between apical and proximal dendritic compartments. Pyramidal tract neurons had abnormal event rates, while intratelencephalic neurons had compartment-specific alterations indicative of diminished dendritic integration. In a matching pennies task, Scn2a+/- mice were inflexible in the face of changing competitive pressure. Apical dendritic tuft in IT neurons typically encoded reward and strategy, but these task-specific representations were altered in Scn2a+/- mice. Collectively, the findings demonstrate that Scn2a haploinsufficiency weakens dendritic integration in vivo and disrupts the dendritic encoding of decision variables, potentially contributing to the cognitive rigidity in autism spectrum disorder.

neuroscience↗

bioRxiv2025

Au18(L-NIBC)14 targets ASC oligomerization for autoimmune disease treatment

Gold nanoclusters (AuNCs), unlike conventional nanoparticles, possess molecular characteristics besides ultrasmall nano-features. Recently, we and others showed that AuNCs are promising in treatments of various major diseases. However, the AuNCs used were usually mixtures, and the specific target and their relationship with AuNC structures are unclear, which largely restrict their druggability. Multiple sclerosis (MS) is an autoimmune disease (AID) implicating central nervous system (CNS), in which drug discovery is challenging. Here we used Au18(L-N-isobutyryl-L-cysteine)14 (Au18(L-NIBC)14) and Au25(L-NIBC)18, two AuNCs with the same ligand, to report their much different therapeutic effects in experimental autoimmune encephalomyelitis (EAE). We show that, Au18(L-NIBC)14, but not Au25(L-NIBC)18, specifically targets apoptosis-associated speck-like protein containing a CARD (ASC) oligomerization, thus inhibit the activation of ASC-dependent inflammasomes, resulting in comprehensive restoration of cytokine homeostasis in the CNS of EAE mice. Au18(L-NIBC)14 significantly prevents axon demyelination, protects blood-brain barrier, blocks immune cell infiltration into CNS, and completely prevents motor deficits and relieve the early-cognitive impairments of EAE mice. Remarkable efficacies were also observed in animal models of inflammatory bowel disease, psoriasis, systemic lupus erythematosus, indicating a broad prospect in AIDs treatments. Especially, definite molecular structure, specific target, clear mechanism, and exact therapeutic effects imply a good druggability of Au18(L-NIBC)14.

pharmacology and toxicology↗

bioRxiv2025

Transcriptional Profiles in Nucleus Accumbens of Antidepressant Resistance in Chronically Stressed Mice

Treatment-resistant depression (TRD), defined by unsuccessful response to multiple antidepressants, affects approximately one-third of individuals with major depressive disorder, yet its underlying molecular mechanisms remain poorly understood. Here, we developed a preclinical model of TRD in which mice exposed to chronic social defeat stress were sequentially treated with fluoxetine (FLX) and ketamine (KET), allowing behavioral stratification into antidepressant responsive and non-responsive mice. RNA sequencing of the nucleus accumbens (NAc) and prefrontal cortex (PFC) revealed transcriptional signatures associated with treatment outcomes. Prior exposure to FLX exerted a priming effect that facilitated molecular and behavioral responsiveness to KET in a subset of animals in both the NAc and PFC. However, this priming effect was absent in non-responders, despite identical treatment regimes, suggesting a transcriptional divergence underlying differential outcomes. Gene co-expression network analysis identified modules enriched for differentially expressed genes unique to stress-susceptible and FLX-KET nonresponsive mice, as well as modules overlapping with both stress susceptibility and antidepressant resistance. These findings suggest that failed antidepressant treatment can shape the brains molecular landscape in a way that influences subsequent treatment outcomes, and that resistance arises not simply from treatment failure but from an absence of adaptive molecular priming. This work provides insight into the gene networks contributing to antidepressant non-response and highlights a mechanistic framework for modeling TRD in preclinical systems. By identifying molecular correlates of sequential pharmacological resistance, our findings may inform the development of novel therapeutic strategies for individuals with TRD.

neuroscience↗

bioRxiv2025

Deep Learning to Predict Future Cognitive Decline: A Multimodal Approach Using Brain MRI and Clinical Data

Predicting the trajectory of clinical decline in aging individuals is a pressing challenge, especially for people with mild cognitive impairment, Alzheimers disease, Parkinsons disease, or vascular dementia. Accurate predictions can guide treatment decisions, identify risk factors, and optimize clinical trials. In this study, we compared two deep learning approaches for forecasting changes, over a 2-year interval, in the Clinical Dementia Rating scale sum of boxes score (sobCDR). This is a key metric in dementia research, and scores range from 0 (no impairment) to 18 (severe impairment). To predict decline, we trained a hybrid convolutional neural network that integrates 3D T1-weighted brain MRI scans with tabular clinical and demographic features (including age, sex, body mass index (BMI), and baseline sobCDR). We benchmarked its performance against AutoGluon, an automated multimodal machine learning framework that selects an appropriate neural network architecture. Our results demonstrate the importance of combining image and tabular data in predictive modeling for clinical applications. Deep learning algorithms can fuse image-based brain signatures and tabular clinical data, with potential for personalized prognostics in aging and dementia.

neuroscience↗

bioRxiv2025

Fructose-1,6-bisphosphatase (FBPase) fine-tunes heterotrophic growth in cyanobacteria

Cyanobacteria switch their carbon metabolism between photoautotrophy and heterotrophy during diurnal cycles. In cyanobacteria, the classical glycolytic control point is characterized by two catabolic phosphofructokinases (PFKs) and a bifunctional anabolic fructose-1,6-biphosphatase/sedoheptulose-1,7-biphosphatase (F/SBPase; slr2094) catalyzing two key reactions in the Calvin-Benson-Bassham (CBB) cycle. In addition, Synechocystis possesses a fructose-1,6-bisphosphatase (FBPase; slr0952) with yet unknown physiological function and biochemical properties. Hence, our aim was to investigate the FBPase and the interplay of the four enzymes in photoautotrophic and heterotrophic carbon metabolism. We discovered that FBPase is specific for FBP, showing no SBPase activity, and unlike F/SBPase does not exhibit any biochemical regulatory properties. Growth studies with deletion mutants revealed that FBPase and PFKs play a major role under heterotrophic conditions. In contrast to F/SBPase, FBPase is not involved in the CBB cycle, but instead fine-tunes heterotrophic growth. Transaldolase cannot replace the function of SBPase in the CBB cycle. In conclusion, the classical Embden-Meyerhoff-Parnass pathway control point, which is known to be mediated by the antagonistic enzyme pair PFK and FBPase in heterotrophic bacteria and eukaryotes, is also present in Synechocystis. We found redox-insensitive FBPases from plant chloroplasts to be closely related to Synechocystis FBPase, indicating that they might serve a similar function. HighlightSynechocystis fructose-1,6-bisphosphatase (slr0952) is unlike fructose-1,6-biphosphatase/sedoheptulose-1,7-biphosphatase (slr2094) monofunctional, not redox-regulated, and supports heterotrophy in darkness, despite catalyzing an anabolic reaction. Thus, presumably Slr2094 alone drives two Calvin-Benson-Bassham cycle key reactions.

plant biology↗