Biology subjects

Zhang, H.

Publications and source records attributed to Zhang, H..

At least 487 records · Page 27Linked to original sources

bioRxiv2025

AUTO-SP: automated sample preparation for analyzing proteins and protein modifications

Liquid chromatography (LC) tandem mass spectrometry (MS/MS) is one of the widely used proteomic techniques to study the alterations occurred at protein expression level as well as post-translation modifications (PTMs) of proteins that are relevant to different physiological or pathological statuses. The mass spectrometric analysis of peptides fragmented from proteins (bottom-up proteomics) has emerged as one of the major approaches for proteomics. In this approach, proteins are first cleaved into peptides for mass spectrometric analysis and peptides with PTMs are further enriched followed by the LC-MS/MS analysis. To achieve a reproducible and quantitative proteomic characterization, a well-established protease digestion and PTM peptide enrichment protocol is critical. In this study, we developed an automated sample preparation (AUTO-SP) for analyzing proteins and protein modifications utilizing Patient-Derived Xenograft (PDX) breast cancer tumors (basal-like and luminal subtypes). The protein amount was quantified and proteins were further digested by using AUTO-SP for each PDX sample. Based on the data-independent acquisition (DIA)-MS data, we observed samples of the same breast cancer subtypes were highly correlated (>0.98). Additionally, >14,000 ubiquitinated peptides were identified in the PDX samples when using AUTO-SP for ubiquitin enrichment, while unique pathways were enriched from the basal-like and luminal subtypes. AUTO-SP demonstrated its efficacy to provide reliable and reproducible sample preparation procedure for MS-based proteomic and PTM analyses.

systems biology↗

bioRxiv2025

Cis-regulatory chromatin contacts form de novo in the absence of loop extrusion

NIPBL promotes chromatin loop extrusion by the cohesin complex until it stalls at convergently oriented CTCF sites, leading to the formation of structural loops. However, to what extent loop extrusion contributes to the establishment vs maintenance of cis-regulatory element (CRE) connectivity is poorly understood. Here, we explored the de novo establishment of chromatin folding patterns at the mitosis-to-G1-phase transition upon acute NIPBL loss. NIPBL depletion primarily impaired the formation of cohesin-mediated structural loops with NIPBL dependence being proportional to loop length. In contrast, the majority of CRE loops were established independently of loop extrusion regardless of length. However, NIPBL depletion slowed the re-formation of CRE loops with weak enhancers. Transcription of genes at NIPBL-independent loop anchors was activated normally in the absence of NIPBL. In sum, establishment of most regulatory contacts and gene transcription following mitotic exit is independent of loop extrusion.

molecular biology↗

bioRxiv2025

Intracellular tension relaxation engineered through D-enantiomeric hydrogel maneuvers neurogenesis and immunomodulation to facilitate spinal cord repair

Microenvironmental mechanics regulate morphogenesis and post-injury inflammation, however, the fragile mechanical strength and oxidative physiological environment hinder precise and consistent mechanical management after spinal cord injury (SCI). Here, we engineered self-assembling hydrogels of enantiomeric peptides with neural tissue- matching mechanical properties to persistently manipulate mechanosensing and mechanotransduction through stereo conformational recognition and consequent protein affinity difference. While hindering proliferation and morphogenesis in non-neural cells, D-hydrogel-induced intracellular tension relaxation triggered neurogenesis and ECM remolding in astrocytes, while simultaneously suppressing pro-inflammation and promoting pro-regeneration in microglia, which together enable neuroprotection from degeneration and enhance functional recovery in severe SCI rat models. These effects are mediated through neurogenic morphology changes resulting from cytoskeletal tension relaxation, leading to the opening of mechanosensitive ion channels in the cellular membrane, chromatin unfolding, and YAP nuclear translocation. This exclusive D- hydrogel-dependent neurogenesis, triggered by intracellular tension relaxation, revealed a neural-specific response to mechanical cues and provided a targeted tissue repair strategy for nerve injury. TeaserIntracellular tension relaxion activates morphogenesis specifically in neural cells through reversing neurogenic cellular morphology.

neuroscience↗

bioRxiv2025

PSI Atlas: a comprehensive knowledgebase of plant self-incompatibility

Self-incompatibility (SI) is an important genetic mechanism in angiosperms that prevents inbreeding and promotes outcrossing. Although significant progress has been made in understanding SI, its molecular underpinnings and evolutionary origins remain elusive in many plant families. In eudicots, SI is typically regulated by a single S-locus with diverse S-haplotypes, while in grasses, it is controlled by two separate S and Z loci. Genome assemblies of SI plants have greatly facilitated the identification and evolutionary analysis of S-loci. However, a comprehensive database that integrates information on the diverse S-loci has been lacking. To fill this gap, we create the Plant Self-Incompatibility Atlas (PSIA, http://www.plantsi.cn), a knowledgebase that offers an extensive compilation of plant SI, including genomic resources for assembled SI species, the origins and evolution of S genes, and the molecular mechanisms of the eight known SI types. In our most recent release, we have obtained more than 500 genome assemblies across 469 SI species. We have also collected 1275 nucleotide and 1130 protein sequence accessions of S genes from public databases, with a total of 3095 S genes manually identified and curated. PSIA not only thoroughly explores the S-locus information of the assembled SI species but also enables users to efficiently browse, perform BLAST searches, analyze, and download S genes. Additionally, PSIA acts as a comprehensive platform for comparative genomic studies of S-loci, aiding in the exploration of the dynamic processes involved in the origin, loss, and regain of SI. Consequently, PSIA is poised to significantly enhance our understanding of angiosperm SI and offer new perspectives on plant mating systems.

plant biology↗

bioRxiv2025

Insights into the spool-like architecture and infectionstrategy of the archaeal virus SEV1

Archaeal viruses are well known for their diverse morphologies and extreme stability. In this study, we used cryo-electron tomography to analyze the structure of SEV1 and its infection strategies in its native state. The results show that SEV1 nucleocapsid adopts a coil-stacking architecture which displays a degree of flexibility. VP4, whose homologues are widespread in the thermo-acidic environment globally, is identified as the major capsid protein and binds genomic DNA forming a "beads-on-a-string" arrangement. Simulations in various extreme environments indicate that the envelope of SEV1 is crucial to the thermostability. SEV1 infects the host by membrane fusion revealed by the membrane fusion assay. The infected cell undergoes cytoplasm condensation to form a "viral factory", leading to the successive production of nascent virions. A series of assembly intermediates of SEV1 are identified revealing an integrated picture of the virus assembly process. The nascent virions are found to be released through virus-associated pyramids (VAPs), composed of unique proteins encoded by SEV1 distinct from other known VAP proteins. Our study provides novel insights to the survival strategies of SEV1, a flexible and enveloped archaeal virus, by using the unique "coil-stacking" architecture and the characteristic infection strategies.

microbiology↗

bioRxiv2025

A Novel XACT lncRNA Transcript with Functions Transcending X-Chromosome Inactivation.

X-chromosome inactivation (XCI) is initiated during early mammalian embryogenesis by a long non-coding RNA (lncRNA) XIST, which coats one of the two X-chromosomes and facilitates epigenetic transcriptional silencing. A second, evolutionarily recent primate-specific lncRNA XACT was proposed to antagonize XISTs ability to induce XCI. XACT expression is restricted to pluripotent states and early embryonic stages and coats the active X-chromosome in both females and males. Here, we report a novel XACT transcript expressed in normal and cancerous somatic cells from both the inactive (Xi) and active (Xa) X chromosomes. It coexists with XIST on the Xi without affecting XIST expression or (re)activating X-linked genes inactivated by XCI. During hematopoietic stem cell (HSC) differentiation, XACT is primarily expressed in myeloid progenitors in both sexes. XACT expression is activated in HSCs and peaks in megakaryocyte-erythrocyte progenitor cells (MEPs) before rapidly declining as the MEPs differentiate into megakaryocytes or erythrocytes. By combining CRISPR-based XACT perturbation with epigenomic and transcriptional studies, we revealed the key role of XACT in the self-renewal and differentiation of erythroid progenitors into erythrocytes, by recruiting cis-regulatory proteins and regulating transcription through ETS and AP-1 transcription factors. Furthermore, XACT is expressed in a subset of acute myeloid leukemia (AML) patients, with high levels found in erythroid-megakaryocytic blast cells; suggesting XACTs potential as a marker for AML subtypes. Thus, we identified a novel XACT transcript with a unique expression profile and important roles in normal and cancer cells, revealing XACT lncRNA functions beyond its previously proposed role in XCI during embryogenesis.

genetics↗

bioRxiv2025

Microbial general model: Leveraging large language model for contextualized microbiome analysis

Microbial communities significantly impact medicine, biotechnology, and agriculture. Advanced sequencing technologies have generated extensive microbiome data, enabling the discovery of substantial evolutionary and ecological patterns. However, traditional supervised learning methods struggle to capture universal patterns in microbial community data, largely due to the large data heterogeneity and profound batch effects among samples, rendering it difficult to classify samples as well as detect biomarkers from millions of samples, not to say the intricate but important dynamic patterns from a variety of contextualized sceneries. In this study, we introduce the Microbial General Model (MGM), the first microbiome community foundation model pre-trained on a dataset of 263,302 microbiome samples using language modeling techniques. MGM demonstrated significant improvements in microbial community classification compared to traditional machine learning methods. Additionally, MGM has enabled contextualized classification, effectively overcomes cross-regional limitations, showing enhanced performance on intercontinental datasets through transfer learning. Furthermore, fine-tuning MGM on a longitudinal infant dataset revealed distinct keystone genera during development, with Bacteroides and Bifidobacterium exhibiting higher attention weights in vaginal deliveries, and Haemophilus in cesarean deliveries. Finally, through in silico modeling, the model also uncovered novel microbial dynamic patterns in a Crohns disease cohort following antibiotic treatment. In conclusion, by leveraging self-attention and autoregressive pre-training, MGM serves as a versatile model for various downstream microbiome tasks and holds significant potential for achieving contextualized aims. Key pointsO_LIThe Microbial General Model (MGM) is a foundation model with millions of parameters pre-trained on sub-million microbial community data. C_LIO_LIMGM outperforms traditional methods in various microbiome classification and prediction tasks, such as microbial community classification. C_LIO_LIMGM effectively captures the spatial and temporal dynamics of microbial communities. C_LIO_LIMGM could detect the effects of perturbation on microbial community through in silico experiments. C_LI

bioinformatics↗

bioRxiv2025

Acquisition of discrete immune suppressive barriers contributes to the initiation and progression of preinvasive to invasive human lung cancer.

Computerized chest tomography (CT)-guided screening in populations at risk for lung cancer has increased the detection of preinvasive subsolid nodules, which progress to solid invasive adenocarcinoma. Despite the clinical significance, there is a lack of effective therapies for intercepting the progression of preinvasive to invasive adenocarcinoma. To uncover determinants of early disease emergence and progression, we used integrated single-cell approaches, including scRNA-seq, multiplexed imaging mass cytometry and spatial transcriptomics, to construct the first high-resolution map of the composition, lineage/functional states, developmental trajectories and multicellular crosstalk networks from microdissected non-solid (preinvasive) and solid compartments (invasive) of individual part-solid nodules. We found that early disease initiation and subsequent progression are associated with the evolution of immune-suppressive cellular phenotypes characterized by decreased cytotoxic CD8 T and NK cells, increased T cell exhaustion and accumulation of immunosuppressive regulatory T cells (Tregs) and M2-like macrophages expressing TREM2. Within Tregs, we identified a unique population of 4-1BB+ Treg subset enriched for the IL2-STAT5 suppressive pathway with transcription profiles supporting discrete metabolic alterations. Spatial analysis showed increased density of suppressive immune cells around tumor cells, increased exhaustion phenotype of both CD4 and CD8 T cells expressing chemokine CXCL13, and spatial micro-complex of endothelial and lymphocyte interactions within tertiary lymphoid structures. The single-cell architecture identifies determinants of early disease emergence and progression, which may be developed not only as diagnostic/prognostic biomarkers but also as targets for disease interception. Additionally, our dataset constitutes a valuable resource for the preinvasive lung cancer research community.

cancer biology↗

bioRxiv2025

Genomic feature of filled regions of telomere-to-telomere genomes in five model species

T2T genome is a telomere-to-telomere high-quality genome with exceptional accuracy, continuity and integrity. It significantly filled some gaps of chromosome. However, the genomic features unique to the filled regions assembled in the T2T genome across species remain unclear. Here, we collected and compared T2T genomes with their older version from human (Homo sapiens), animal (Mus musculus), and plants (Arabidopsis thaliana, Musa acuminata, and Fragaria vesca). We explored the newly filled regions generated by the T2T genome in comparison to the old one, and focused on: (1) the comparison of their locations, (2) the distribution of genomic features, and (3) gene annotation and gene function for filled regions. Research indicated that the filled regions of the T2T genome ordinarily appear in the centromere and telomere regions, contain a great number of repetitive sequences. The T2T genome revealed the identification of a certain number of newly annotated genes, alongside significant variations in common annotated genes. Interestingly, the genomic features of filled regions exhibit distinct patterns between plants and human/animal. T2T genomes feature analysis serves as a crucial resource for studying pattern characteristics across diverse species and advancing the in-depth development of genomics.

genomics↗

bioRxiv2025

Auditory tract maturation in early infancy: Links to speech production

Infants exhibit remarkable language acquisition abilities, supported by highly plastic neural substrates that dynamically interact with early speech experiences. However, the developmental mechanisms of these neural substrates and their specific role in speech acquisition remain incompletely understood. Here, we present NeoAudi Tract (NAT), a robust automated toolbox for extracting the full set of auditory tracts in infants from birth to 24 months using 3T diffusion MRI data. By characterizing the microstructural changes in these tracts, we demonstrate a gradual and continuous maturation process of the auditory system. Additionally, we identify significant correlations between auditory tract maturation and both fine-motor skills and expressive language t-scores from the Mullen Scales of Early Learning tests. Our findings highlight the role of the auditory system in speech production and indicate the intertwined development of auditory and motor systems that underlies speech acquisition, particularly during perceptual reorganization.

neuroscience↗

bioRxiv2024

The Basal Ciliary but not Cytosol PKA Specifically Regulates HH Pathway Downstream of Smoothened

Effectors of the vertebrate Hedgehog (HH) signaling pathway are organized through primary cilia (PC) that grow and retract in lockstep with the cell cycle in response to extracellular signals. Protein kinase A (PKA), a kinase with ubiquitous distribution in most cells, functions as a specific negative regulator of the HH pathway. Its functional specificity in the HH pathway has been suggested to be controlled by cAMP in the PC. However, the regulation of PKA and its functions in PC remain unclear, in part due to the lack of observation of PKA localization in PC during HH resting state as well as conflicting reports of the dynamic changes of cAMP in cilia and HH pathway activity. To address this issue, we have developed a ciliary-localized FRET-based A-kinase activity probe (Nphp3N-AKAR2-CR) as an improved biosensor for monitoring real-time PKA activity in the PC of both cultured cells and living zebrafish embryos. Although the PKA catalytic subunit (PKA-C) was not observed in PC, basal PKA activity in cells could be detected with this probe. In addition, we have found that only ciliary-targeted PKA and not cytosolic PKA, can modulate the HH pathway, even when the integrity of the PC is disrupted. Notably, ciliary PKA activity was barely changed either by inhibition or activation of the HH pathway at the level of Smoothened (SMO), the obligate HH signal transducer. Moreover, we found that even low concentration of the adenylyl cyclase agonist forskolin (FSK) can efficiently inhibit the HH pathway in the presence of the constitutively active variant SMOA1, suggesting that the activation of the HH pathway by SMO may not be due solely to direct regulation of PKA activity in the PC.

cell biology↗

bioRxiv2024

Maize TIR-only Proteins ZmTIR1 and ZmTIR2, but not ZmTIR3 Confer Auto-active Hypersensitive Response Likely by Forming Condensation

Nucleotide binding, leucine-rich-repeat (NLR) proteins are the major intracellular receptors for defending against pathogen infection. The recognition between NLRs and pathogen secreted effectors often triggers a localized programmed cell death termed hypersensitive response (HR). Despite significant progresses have been achieved in understanding canonical NLRs with the N-terminal Toll/interleukin-1 receptor (TIR) domains, the molecular mechanisms underlying TIR-only proteins in plant immune responses remain unclear. In this study, we identified six TIR-containing proteins in maize, including three TIR-only proteins. Functional analysis showed that ZmTIR1 and ZmTIR2, but not ZmTIR3, confer autoactive HR when transiently expressed in N. benthamiana. The autoactivity conferred by ZmTIR1 and ZmTIR2 depends on EDS1-PAD4-RNL module and their putative NADase activities. Interestingly, ZmTIR1 and ZmTIR2 predominantly localize in the punctate dots and likely form condensation, while ZmTIR3 mainly localizes in the cytoplasm and the nucleus. Two specific amino acids in the BB-loop region were identified to be required for ZmTIR1- and ZmTIR2-mediated condensation formation and auto-HR. Furthermore, ZmTIR and ZmTIR2 are induced by Cochliobolus heterostrophus, the causal agent of southern leaf blight (SLB) in maize, and knock-down the expression of ZmTIR1 or ZmTIR2 decreased the resistance to SLB in maize. Our study reveals a novel mechanism of monocot TIR-only proteins in maize immune responses.

plant biology↗

bioRxiv2024

A poly(A) polymerase and oligo(dT)-dependent method for the purification of engineering circular RNAs that enhances protein expression in eukaryotic cells

Circular RNA (circRNA) has garnered significant attention as a promising therapeutic tool due to its remarkable stability and resistance to exonuclease degradation. However, the development of scalable and efficient purification methods remains a critical challenge. In this study, we propose and evaluate a novel purification strategy for engineered circular RNA (PAPdt), which leverages poly(A) polymerase and oligo(dT) affinity chromatography. Using poly(A) polymerase, we add poly(A) tails of over 200 nucleotides to the 3-OH ends of all linear RNA impurities in a circular RNA preparation. These linear RNAs are then separated from the circular RNA via oligo(dT) affinity chromatography. The linear impurities, bearing longer poly(A) tails, exhibit extended retention on the oligo(dT) column, whereas the circular RNA, with a shorter poly(A) sequence, elutes more quickly. By stepwise elution with ultrapure water, we effectively separate the circular RNA from the linear contaminants. This method offers a fundamental solution to the purification of circular RNA, combining high efficiency, purity, and cost-effectiveness.

bioengineering↗

bioRxiv2024

Systematic Benchmarking of High-Throughput Subcellular Spatial Transcriptomics Platforms

Recent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. To address this, we collected clinical samples from three cancer types - colon adenocarcinoma, hepatocellular carcinoma, and ovarian cancer - and generated serial tissue sections for systematic evaluation. Using these uniformly processed samples, we generated spatial transcriptomics data across five high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, Visium HD FF, CosMx 6K, and Xenium 5K. To establish ground truth datasets, we profiled proteins from adjacent tissue sections corresponding to all five platforms using CODEX and performed single-cell RNA sequencing on the same samples. Leveraging manual cell segmentation and detailed annotations, we systematically assessed each platforms performance across key metrics, including capture sensitivity, specificity, diffusion control, cell segmentation, cell annotation, spatial clustering, and transcript-protein alignment with adjacent CODEX. The uniformly generated, processed, and annotated multi-omics dataset is valuable for advancing computational method development and biological discoveries. The dataset is accessible via SPATCH, a user-friendly web server for visualization and download (http://spatch.pku-genomics.org/).

genomics↗

bioRxiv2024

A universal single-cell transcriptomics atlas of human lung decodes multiple pulmonary diseases

Human lung is a complex organ susceptible to various diseases. Single-cell transcriptomic studies provide rich data to targeting specific research questions. Here, we present uniLUNG, the largest lung transcriptomic cell atlas, comprising over 10 million cells across 20 disease states and healthy controls. We ensembled a universal hierarchical annotation framework and conducted a full benchmarking of data integration to define a standardized nomenclature and marker genes for lung cell types. Using uniLUNG, we identified Lym-monocyte and T-like B cells, new cell types in specific lung diseases, confirming their existence by comparing with external single-cell atlases. Additionally, we discovered the NSCLC-like SCLC subpopulation, a transitional malignant cell population associated with the transition from NSCLC to SCLC, which was validated and further characterized in spatial dimensions, revealing its complex role in tumour progression. Overall, uniLUNG represents a comprehensive range of human lung cell diversity, providing valuable data resources and a reliable foundation for lung single-cell research. HIGHLIGHTSO_LIThe largest scRNA atlas for human lung covers 10 million cells from 20 lung states. C_LIO_LIA four-level universal cell annotation framework encompasses 120 lung cell types. C_LIO_LIComprehensive benchmarking on 18 strategies guides data integration. C_LIO_LISpecific distribution of Lym-monocytes and T-like B cells in specific lung diseases. C_LIO_LIThe NSCLC-like SCLC subpopulation in transitional events of malignant cells from NSCLC to SCLC. C_LI

bioinformatics↗

bioRxiv2024

Electron-density informed effective and reliable de novo molecular design and lead optimization with ED2Mol

Generative drug design opens new avenues for discovering novel compounds within the vast chemical space rather than conventional screening against limited compound libraries. However, the practical utility of the generated molecules is frequently constrained, as many designs prioritize a narrow range of pharmacological properties while neglecting physical reliability, which hinders the success rate of subsequent wet-lab evaluations. To address this, we propose ED2Mol, a deep learning-based approach that leverages fundamental electron density information to improve de novo molecular generation and lead optimization. The extensive evaluations across multiple benchmarks demonstrate that ED2Mol surpasses existing methods in terms of generation success rate and >97% physical reliability. It also facilitates automated lead optimization that is not fully implemented by other methods using fragment-based strategies. Furthermore, ED2Mol exhibits generalizability to more challenging, unseen allosteric pocket benchmarks, attaining consistent performance in both de novo molecule generation and lead optimization. More importantly, ED2Mol has been applied to various real-world essential targets, successfully identifying wet-lab validated bioactive compounds, ranging from FGFR3 orthosteric inhibitors to CDC42 allosteric inhibitors and GCK allosteric activators. The directly generated binding modes of these compounds with target proteins are close to predictions through molecular docking and further validated via the X-ray co-crystal structure. All these results highlight ED2Mols potential as a useful tool in realistic drug design with enhanced effectiveness, physical reliability, and practical applicability.

bioinformatics↗

bioRxiv2024

A comprehensive benchmark for multiple highly efficient base editors with broad targeting scope

As the toolbox of base editors (BEs) expands, selecting appropriate BE and guide RNA (gRNA) to achieve optimal editing efficiency and outcome for a given target becomes challenging. Here, we construct a set of 10 adenine and cytosine BEs with high activity and broad targeting scope, and comprehensively evaluate their editing profiles and properties head-to-head with 34,040 BE-gRNA-target combinations using genomically integrated long targets and tiling gRNA strategies. Interestingly, we observe widespread non-canonical protospacer adjacent motifs (PAMs) for these BEs. Using this large-scale benchmark data, we build a deep learning model, named BEEP (Base Editing Efficiency Predictor), for predicting the editing efficiency and outcome of these BEs. Guided by BEEP, we experimentally test and validate the installment of 3,558 disease-associated single nucleotide variants (SNVs) via BEs, including 20.1% of target sites that would be generally considered as "uneditable", due to the lack of canonical PAMs. We further predict candidate BE-gRNA-target combinations for modeling 1,752,651 ClinVar SNVs. We also identify several cancer-associated SNVs that drive the resistance to BRAF inhibitors in melanoma. These efforts benchmark the performance and illuminate the capabilities of multiple highly useful BEs for interrogating functional SNVs. A practical webserver (http://beep.weililab.org/) is freely accessible to guide the selection of optimal BEs and gRNAs for a given target.

molecular biology↗

bioRxiv2024

Genetically Encoded Red Fluorescent Indicators for Imaging Intracellular and Extracellular Potassium Ions

Potassium ion (K+) dynamics are vital for various biological processes. However, the limited availability of detection tools for tracking intracellular and extracellular K+ has impeded a comprehensive understanding of the physiological roles of K+ in intact biological systems. In this study, we developed two novel red genetically encoded potassium indicators (RGEPOs), RGEPO1 and RGEPO2, through a combination of directed evolution in E. coli and subsequent optimization in mammalian cells. RGEPO1, targeted to the extracellular membrane, and RGEPO2, localized in the cytoplasm, exhibited positive K+-specific fluorescence response with affinities of 3.55 mM and 14.81 mM in HEK293FT cells, respectively. We employed RGEPOs for real-time monitoring of subsecond K+ dynamics in cultured neurons, astrocytes, acute brain slices, and the awake mouse in both intracellular and extracellular environments. Using RGEPOs, we were able, for the first time, to visualize intracellular and extracellular potassium transients during seizures in the brains of awake mice. Furthermore, molecular dynamics simulations provided new insights into the potassium-binding mechanisms of RGEPO1 and RGEPO2, revealing distinct K+-binding pockets and structural features. Thus, RGEPOs represent a significant advancement in potassium imaging, providing enhanced tools for real-time visualization of K+ dynamics in various cell types and cellular environments.

biochemistry↗