Sci Rep. 2025 Mar 11;15(1):8384. doi: 10.1038/s41598-025-92781-4.

ABSTRACT

Eld's deer (Rucervus eldii) is a rare and globally endangered tropical Southeast Asian deer species. There is no research on pathogens in Eld's deer in Hainan, China. This study aimed to understand the virus diversity and novel viruses in Eld's deer, and provided important epidemiological baseline information for conservation of this endangered species. 33 nasal swabs, 33 anal swabs, and 9 wound (bitten by ticks) swabs were collected from 33 wild Eld's deer in a nature reserve in Hainan, which constituted into 5 pools. Based on next-generation sequencing (NGS) and macrogenomic analysis, there were differences in the 5 pools of viral reads, while the overall viral reads were closely related to mammals. The novel papillomavirus (PsPV-HMU-1) and Circular Rep-encoding (replication-associated protein encoding) single-stranded DNA (CRESS DNA) virus (PsaCV-HMU-1) were identified in Eld's deer, with amino acid homology of the less than 77.20% of the L1 and less than 45.43% of the rep, respectively. PsPV-HMU-1 and PsaCV-HMU-1 are relatively independent on their phylogenetic trees, and with the overall prevalence of 24.24% (8/33) and 3.03% (1/33) in Eld's deer, respectively. Our results expanded the viral genomic information and host range, and implied that it is necessary for continued epidemiological surveillance in order to understand pathogenicity and the potential for cross-species transmission of viruses in wild Eld's deer.

PMID:40069308 | DOI:10.1038/s41598-025-92781-4

Sci Rep. 2025 Mar 12;15(1):8465. doi: 10.1038/s41598-025-92942-5.

ABSTRACT

Rice, a staple food consumed by half of the world's population, is severely affected by the combined impact of abiotic and biotic stresses, with the former causing increased susceptibility of the plant to pathogens. Four microarray datasets for drought, salinity, tungro virus, and blast pathogen were retrieved from the Gene Expression Omnibus database. A modular gene co-expression (mGCE) analysis was conducted, followed by gene set enrichment analysis to evaluate the upregulation of module activity across different stress conditions. Over-representation analysis was conducted to determine the functional association of each gene module with stress-related processes and pathways. The protein-protein interaction network of mGCE hub genes was constructed, and the Maximal Clique Centrality (MCC) algorithm was applied to enhance precision in identifying key genes. Finally, genes implicated in both abiotic and biotic stress responses were validated using RT-qPCR. A total of 11, 12, 46, and 14 modules containing 85, 106, 253, and 143 hub genes were detected in drought, salinity, tungro virus, and blast. Modular genes in drought were primarily enriched in response to heat stimulus and water deprivation, while salinity-related genes were enriched in response to external stimuli. For the tungro virus and blast pathogen, enrichment was mainly observed in the defence and stress responses. Interestingly, RPS5, PKG, HSP90, HSP70, and MCM were consistently present in abiotic and biotic stresses. The DEG analysis revealed the upregulation of MCM under the tungro virus and downregulation under blast and drought in resistant rice, indicating its role in viral resistance. HSP70 showed no changes, while HSP90 was upregulated in susceptible rice during blast and drought. PKG increased during drought but decreased in japonica rice under salinity. RPS5 was highly upregulated during blast in both resistant and susceptible rice. The RT-qPCR analysis showed that all five hub genes were upregulated in all treatments, indicating their role in stress responses and potential for crop improvement.

PMID:40069264 | DOI:10.1038/s41598-025-92942-5

Life Sci. 2025 Mar 10:123550. doi: 10.1016/j.lfs.2025.123550. Online ahead of print.

NO ABSTRACT

PMID:40069054 | DOI:10.1016/j.lfs.2025.123550

Structure. 2025 Mar 5:S0969-2126(25)00057-7. doi: 10.1016/j.str.2025.02.004. Online ahead of print.

ABSTRACT

Cryogenic electron microscopy (cryo-EM) has the potential to capture snapshots of proteins in motion and generate hypotheses linking conformational states to biological function. This potential has been increasingly realized by the advent of machine learning models that allow 100s-1,000s of 3D density maps to be generated from a single dataset. How to identify distinct structural states within these volume ensembles and quantify their relative occupancies remain open questions. Here, we present an approach to inferring variable regions directly from a volume ensemble based on the statistical co-occupancy of voxels, as well as a 3D convolutional neural network that predicts binarization thresholds for volumes in an unbiased and automated manner. We show that these tools recapitulate known heterogeneity in a variety of simulated and real cryo-EM datasets and highlight how integrating these tools with existing data processing pipelines enables improved particle curation.

PMID:40068687 | DOI:10.1016/j.str.2025.02.004

Cell. 2025 Mar 6:S0092-8674(25)00196-5. doi: 10.1016/j.cell.2025.02.011. Online ahead of print.

ABSTRACT

Brassinosteroid hormones are positive regulators of plant organ growth, yet their function in proliferating tissues remains unclear. Here, through integrating single-cell RNA sequencing with long-term live-cell imaging of the Arabidopsis root, we reveal that brassinosteroid activity fluctuates throughout the cell cycle, decreasing during mitotic divisions and increasing during the G1 phase. The post-mitotic recovery of brassinosteroid activity is driven by the intrinsic polarity of the mother cell, resulting in one daughter cell with enhanced brassinosteroid signaling, while the other supports brassinosteroid biosynthesis. The coexistence of these distinct daughter cell states during the G1 phase circumvents a negative feedback loop to facilitate brassinosteroid production while signaling increases. Our findings uncover polarity-guided, uneven mitotic divisions in the meristem, which control brassinosteroid hormone activity to ensure optimal root growth.

PMID:40068682 | DOI:10.1016/j.cell.2025.02.011

Cell. 2025 Mar 7:S0092-8674(25)00195-3. doi: 10.1016/j.cell.2025.02.010. Online ahead of print.

ABSTRACT

Bifidobacteria represent a dominant constituent of human gut microbiomes during infancy, influencing nutrition, immune development, and resistance to infection. Despite interest in bifidobacteria as a live biotic therapy, our understanding of colonization, host-microbe interactions, and the health-promoting effects of bifidobacteria is limited. To address these major knowledge gaps, we used a large-scale genetic approach to create a mutant fitness compendium in Bifidobacterium breve. First, we generated a high-density randomly barcoded transposon insertion pool and used it to determine fitness requirements during colonization of germ-free mice and chickens with multiple diets and in response to hundreds of in vitro perturbations. Second, to enable mechanistic investigation, we constructed an ordered collection of insertion strains covering 1,462 genes. We leveraged these tools to reveal community- and diet-specific requirements for colonization and to connect the production of immunomodulatory molecules to growth benefits. These resources will catalyze future investigations of this important beneficial microbe.

PMID:40068681 | DOI:10.1016/j.cell.2025.02.010

Cell. 2025 Mar 5:S0092-8674(25)00194-1. doi: 10.1016/j.cell.2025.02.009. Online ahead of print.

ABSTRACT

Recent breakthroughs in the genetic manipulation of mitochondrial DNA (mtDNA) have enabled precise base substitutions and the efficient elimination of genomes carrying pathogenic mutations. However, reconstituting mtDNA deletions linked to mitochondrial myopathies remains challenging. Here, we engineered mtDNA deletions in human cells by co-expressing end-joining (EJ) machinery and targeted endonucleases. Using mitochondrial EJ (mito-EJ) and mito-ScaI, we generated a panel of clonal cell lines harboring a ∼3.5 kb mtDNA deletion across the full spectrum of heteroplasmy. Investigating these cells revealed a critical threshold of ∼75% deleted genomes, beyond which oxidative phosphorylation (OXPHOS) protein depletion, metabolic disruption, and impaired growth in galactose-containing media were observed. Single-cell multiomic profiling identified two distinct nuclear gene deregulation responses: one triggered at the deletion threshold and another progressively responding to heteroplasmy. Ultimately, we show that our method enables the modeling of disease-associated mtDNA deletions across cell types and could inform the development of targeted therapies.

PMID:40068680 | DOI:10.1016/j.cell.2025.02.009

Physiol Rep. 2025 Mar;13(5):e70142. doi: 10.14814/phy2.70142.

ABSTRACT

The respiratory control system can exhibit neuronal plasticity following exposures to repetitive respiratory challenges. For example, repeated obstructive apneas can trigger a form of respiratory plasticity that results in the enhancement of inspiratory hypoglossal (XII) motoneuron activity. This increase in respiratory motor output is known as hypoglossal long-term facilitation (hLTF). In adult male Sprague-Dawley rats, we demonstrate that hLTF can also be triggered in the absence of repeated apneas by intermittent optogenetic stimulation of locus coeruleus (LC) neurons, or through pharmacological activation of adenosine-A2a-receptors at the level of brainstem XII motor pool. Both our pharmacological and optogenetic approaches that trigger hLTF require noradrenergic signaling through activation of α1-noradrenergic receptors on hypoglossal motoneurons. We also use optical LC inhibition to reaffirm the importance of the LC in mediating apnea-induced hLTF. These results demonstrate that hLTF can be triggered by multiple hypoxia-independent stimuli, and for the first time, identify the LC as a key brainstem source for noradrenaline necessary for the expression of hLTF.

PMID:40067835 | DOI:10.14814/phy2.70142

Front Plant Sci. 2025 Feb 24;15:1442324. doi: 10.3389/fpls.2024.1442324. eCollection 2024.

ABSTRACT

Cassava is a crucial source of daily calorie intake for millions of people in sub-Saharan Africa (SSA) but has an inferior protein content. Despite numerous attempts utilizing both traditional and biotechnological methods, efforts to address protein deficiency in cassava have yet to meet with much success. We aim to leverage modern biotechnologies to enhance cassava's nutritional value by creating bioengineered cassava cultivars with increased protein and starch content. In this study, we utilized Qui-Quine Starch (QQS), a novel orphan gene unique to Arabidopsis thaliana, to develop transgenic cassava plants with increased protein and starch accumulation in their tissues. A total of 10 independent transgenic cassava lines expressing QQS were successfully regenerated in this study, among which line R7 (F) demonstrated superior growth vigor. Quantitative RT-PCR verified the expression of the QQS gene in the transgenic lines. Data showed that QQS expression in cassava plants increased leaf protein content by 36% in line R''' (LA) L2 and root protein by 17% for the same line compared to their wild-type and empty vector (NPTII) control plants. Moreover, leaf-soluble total carbohydrates increased by 51.76% in line R (G) L2, and root-soluble total carbohydrates increased by 46.75% in line R7 (F). The novel function of QQS in increasing the starch content in the transgenic biomass is demonstrated. No significant change in the content of specific amino acids was observed among the lines and various plant parts. In addition, QQS expression revealed increased biomass, plant vigor, and early In vitro mini-tubers production for line R7 (F). Gene interaction study between AtQQS and 59 interacting partners generated 184 interactions or edges. These gene networks comprised several functional categories regulating the starch metabolic and auxin biosynthetic processes. The role of QQS in imparting starch and protein content of transgenic cassava plants is validated. The next logical step is the evaluation of biochemical profiles of cassava lines expressing QQS that reach maturity and the transferability of these findings to consumer-preferred cassava cultivars and local landraces grown in SSA. This study represents the first biotechnological report demonstrating a simultaneous increase of protein and starch content in bioengineered cassava.

PMID:40066347 | PMC:PMC11891011 | DOI:10.3389/fpls.2024.1442324

NPJ Drug Discov. 2025;2(1):3. doi: 10.1038/s44386-025-00006-5. Epub 2025 Mar 4.

ABSTRACT

Identification of novel drug targets is a key component of modern drug discovery. While antimalarial targets are often identified through the mechanism of action studies on phenotypically derived inhibitors, this method tends to be time- and resource-consuming. The discoverable target space is also constrained by existing compound libraries and phenotypic assay conditions. Leveraging recent advances in protein structure prediction, we systematically assessed the Plasmodium falciparum genome and identified 867 candidate protein targets with evidence of small-molecule binding and blood-stage essentiality. Of these, 540 proteins showed strong essentiality evidence and lack inhibitors that have progressed to clinical trials. Expert review and rubric-based scoring of this subset based on additional criteria such as selectivity, structural information, and assay developability yielded 27 high-priority antimalarial target candidates. This study also provides a genome-wide data resource for P. falciparum and implements a generalizable framework for systematically evaluating and prioritizing novel pathogenic disease targets.

PMID:40066064 | PMC:PMC11892419 | DOI:10.1038/s44386-025-00006-5

J Infect Dis. 2025 Mar 11:jiaf125. doi: 10.1093/infdis/jiaf125. Online ahead of print.

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily targets ciliated cells during the initial infection of the upper respiratory tract. Since uncertainties persist regarding other involved epithelial cell types, we here utilized viral replication analysis, single-cell RNA sequencing, and spectral microscopy on infected air-liquid interface cultures of human primary nasal and bronchial epithelial cells to discern cell type proportions in relation to SARS-CoV-2 tropism and immune activation. We revealed that, next to ciliated and secretory cells, SARS-CoV-2 (wild type and lineage B1.1.7 [Alpha variant]) strongly infects basal cells, significantly contributing to the epithelial immune response in a donor-specific manner. Moreover, local Camostat mesylate treatment was effective on both the basal and apical cell compartment, resulting in a notable reduction in viral load and reduced immune activation. Collectively, our data emphasize the critical role of basal cells in facilitating SARS-CoV-2 dissemination within the upper respiratory tract and their substantial contribution to the epithelial immune response. Furthermore, our results highlight the potential of local application of Camostat mesylate as an effective strategy for inhibiting SARS-CoV-2 infection and mitigating associated immune activation early on.

PMID:40065723 | DOI:10.1093/infdis/jiaf125

Nat Rev Genet. 2025 Mar 10. doi: 10.1038/s41576-025-00821-6. Online ahead of print.

ABSTRACT

Systems biology aims to achieve holistic insights into the molecular workings of cellular systems through iterative loops of measurement, analysis and perturbation. This framework has had remarkable success in unicellular model organisms, and recent experimental and computational advances - from single-cell and spatial profiling to CRISPR genome editing and machine learning - have raised the exciting possibility of leveraging such strategies to prevent, diagnose and treat human diseases. However, adapting systems-inspired approaches to dissect human disease complexity is challenging, given that discrepancies between the biological features of human tissues and the experimental models typically used to probe function (which we term 'translational distance') can confound insight. Here we review how samples, measurements and analyses can be contextualized within overall multiscale human disease processes to mitigate data and representation gaps. We then examine ways to bridge the translational distance between systems-inspired human discovery loops and model system validation loops to empower precision interventions in the era of single-cell genomics.

PMID:40065155 | DOI:10.1038/s41576-025-00821-6

EMBO J. 2025 Mar 10. doi: 10.1038/s44318-025-00406-3. Online ahead of print.

ABSTRACT

Bacteria in polymicrobial habitats are constantly exposed to biotic threats from bacteriophages (or "phages"), antagonistic bacteria, and predatory eukaryotes. These antagonistic interactions play crucial roles in shaping the evolution and physiology of bacteria. To survive, bacteria have evolved mechanisms to protect themselves from such attacks, but the fitness costs of resisting one threat and rendering bacteria susceptible to others remain unappreciated. Here, we examined the fitness consequences of phage resistance in Salmonella enterica, revealing that phage-resistant variants exhibited significant fitness loss upon co-culture with competitor bacteria. These phage-resistant strains display varying degrees of lipopolysaccharide (LPS) deficiency and increased susceptibility to contact-dependent interbacterial antagonism, such as the type VI secretion system (T6SS). Utilizing mutational analyses and atomic force microscopy, we show that the long-modal length O-antigen of LPS serves as a protective barrier against T6SS-mediated intoxication. Notably, this competitive disadvantage can also be triggered independently by phages possessing LPS-targeting endoglycosidase in their tail spike proteins, which actively cleave the O-antigen upon infection. Our findings reveal two distinct mechanisms of phage-mediated LPS modifications that modulate interbacterial competition, shedding light on the dynamic microbial interplay within mixed populations.

PMID:40065098 | DOI:10.1038/s44318-025-00406-3

Sci Rep. 2025 Mar 10;15(1):8314. doi: 10.1038/s41598-025-92289-x.

ABSTRACT

Coxsackievirus B3 (CVB3), a member of the Enterovirus genus within the Picornaviridae family, has emerged as a key model for studying viral evolution and pathogenesis. Although traditionally considered obligate lytic viruses, recent research reveals that enteroviruses can also be released non-lytically within extracellular vesicles (EVs). This study explores the impact of mutations at position 63 of the VP3 capsid protein on CVB3 fitness and release mechanisms by substituting asparagine at this position with aromatic, charged, and aliphatic amino acids. We show that mutations at position 63 significantly affect viral release mechanisms and viral spread in cell culture. Specifically, aromatic mutations (N63H, N63Y, N63F, N63W) and the N63D mutation reduce the release of membrane-associated viral particles, while aromatic residues increase viral spread in cell culture and plaque size under specific conditions. These findings suggest that N63 mutations alter protomer interactions, influencing viral release, spread, and plaque formation, providing insights into the molecular mechanisms of CVB3 egress.

PMID:40064995 | DOI:10.1038/s41598-025-92289-x

Eur Geriatr Med. 2025 Mar 10. doi: 10.1007/s41999-025-01180-5. Online ahead of print.

ABSTRACT

PURPOSE: In this prospective external validation study, we examined the performance of the Supporting SURgery with GEriatric Co-Management and AI (SURGE-Ahead) postoperative delirium (POD) prediction algorithm. SURGE-Ahead is a collaborative project that aims to develop a clinical decision support system that uses predictive models to support geriatric co-management in surgical wards. Delirium is a common complication in older adults after surgery, leading to poor outcomes and increased healthcare costs. Early and accurate prediction of POD is crucial for timely intervention and prevention strategies.

METHODS: The SURGE-Ahead algorithm utilizes a linear support vector machine model with a comprehensive set of 15 clinical and demographic features. In our validation, we analyzed 173 study participants, of which 50 developed POD.

RESULTS: The study found that the SURGE-Ahead POD prediction algorithm yielded state-of-the-art performance, using only preoperative data, with a receiver operating characteristics area under the curve of 0.86. In addition, the SURGE-Ahead algorithm exhibited good calibration as shown by a Brier Score of 0.14. The algorithm is openly available on GitHub, facilitating its implementation and adaptation to different surgical settings.

CONCLUSION: Our findings contribute to the development of reliable POD prediction tools, ultimately supporting the improvement of patient care in hospitalized older adults.

PMID:40064822 | DOI:10.1007/s41999-025-01180-5

Methods Mol Biol. 2025;2912:191-204. doi: 10.1007/978-1-0716-4454-6_17.

ABSTRACT

Full-length viral genome sequencing is key for virus distribution profiling, new virus discovery, and understanding virus populations across different samples. Circular DNA Enrichment Sequencing (CIDER-Seq) allows unbiased enrichment and long-read sequencing of circular DNA viruses. CIDER-Seq produces single-read full-length virus genomes, combining PCR-free enrichment with Single Molecule Real-Time sequencing and de-concatenation algorithm. CIDER-Seq data analysis package, using the DeConcat algorithm, processes PacBio sequencing data into intact circular DNA sequences, generating fully annotated and highly accurate circular DNA virus genome sequences.

PMID:40064783 | DOI:10.1007/978-1-0716-4454-6_17

J Prev Alzheimers Dis. 2025 Mar 9:100129. doi: 10.1016/j.tjpad.2025.100129. Online ahead of print.

ABSTRACT

BACKGROUND: Type 2 diabetes (T2D) is commonly co-morbid with Alzheimer's disease (AD). However, it remains unclear whether T2D itself or the antidiabetic drug metformin contributes to the progression of AD.

OBJECTIVE: This study aimed to investigate the overall and independent effects of T2D and metformin use on the risk of AD.

METHODS: Summary genome-wide association study datasets were utilized for the Mendelian randomization (MR) and multivariable MR (MVMR) analyses, including ones for T2D (N = 455,017), metformin (N = 456,276), and AD (N = 453,733). Additionally, using the proportional imbalance method, we analyzed AD-related adverse drug events in the FDA Adverse Event Reporting System (FAERS) database (covering Q1 2004 to Q2 2024).

RESULTS: Our two-sample MR analysis indicated that T2D is not associated with the risk of AD (OR: 1.03, CI: 0.99-1.08, P = 0.128). However, while not statistically significant, genetic signature for metformin exposure demonstrated a trend toward an increased risk of AD (OR: 1.05, CI: 1.00-1.09, P = 0.053). Interestingly, in MVMR analysis, which evaluates independent effects of T2D and metformin exposure on T2D, we found a robust association of T2D with a decrease in the risk of AD (OR: 0.82, CI: 0.68-0.98, P = 0.031), while the use of metformin was associated with a higher risk of AD (OR: 1.26, CI: 1.06-1.50, P = 9.45E-3). In the FAERS database, a total of 228,283 metformin-related adverse event reports from 67,742 cases were found. For metformin as the target drug and AD as the target adverse event, signal analysis reported 29 cases of AD (ROR: 0.83, 95 % CI: 0.58-1.19, P = 0.3126).

CONCLUSIONS: Our study reveals the opposite independent causal effects of T2D and metformin exposure on AD. These findings highlight the importance of assessing AD risk when prescribing metformin to patients with T2D.

PMID:40064559 | DOI:10.1016/j.tjpad.2025.100129

Proc Natl Acad Sci U S A. 2025 Mar 18;122(11):e2424470122. doi: 10.1073/pnas.2424470122. Epub 2025 Mar 10.

ABSTRACT

The cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel whose dysfunction leads to intracellular accumulation of chloride ions, dehydration of cell surfaces, and subsequent damage to airway and ductal organs. Beyond its function as a chloride channel, interactions between CFTR, epithelium sodium channel, and solute carrier (SLC) transporter family membrane proteins and cytoplasmic proteins, including calmodulin and Na+/H+ exchanger regulatory factor-1 (NHERF-1), coregulate ion homeostasis. CFTR has also been observed to form mesoscale membrane clusters. However, the contributions of multivalent protein and lipid interactions to cluster formation are not well understood. Using a combination of computational modeling and biochemical reconstitution assays, we demonstrate that multivalent interactions with CFTR protein binding partners, calcium, and membrane cholesterol can induce mesoscale CFTR cluster formation on model membranes. Phosphorylation of the intracellular domains of CFTR also promotes mesoscale cluster formation in the absence of calcium, indicating that multiple mechanisms can contribute to CFTR cluster formation. Our findings reveal that coupling of multivalent protein and lipid interactions promotes CFTR cluster formation consistent with membrane-associated biological phase separation.

PMID:40063811 | DOI:10.1073/pnas.2424470122

Microb Genom. 2025 Mar;11(3). doi: 10.1099/mgen.0.001365.

ABSTRACT

Diabetes mellitus is a complex metabolic disorder and one of the fastest-growing global public health concerns. The gut microbiota is implicated in the pathophysiology of various diseases, including diabetes. This study utilized 16S rRNA metagenomic data from a volunteer citizen science initiative to investigate microbial markers associated with diabetes status (positive or negative) and type (type 1 or type 2 diabetes mellitus) using supervised machine learning (ML) models. The diversity of the microbiome varied according to diabetes status and type. Differential microbial signatures between diabetes types and negative group revealed an increased presence of Brucellaceae, Ruminococcaceae, Clostridiaceae, Micrococcaceae, Barnesiellaceae and Fusobacteriaceae in subjects with diabetes type 1, and Veillonellaceae, Streptococcaceae and the order Gammaproteobacteria in subjects with diabetes type 2. The decision tree, elastic net, random forest (RF) and support vector machine with radial kernel ML algorithms were trained to screen and type diabetes based on microbial profiles of 76 subjects with type 1 diabetes, 366 subjects with type 2 diabetes and 250 subjects without diabetes. Using the 1000 most variable features, tree-based models were the highest-performing algorithms. The RF screening models achieved the best performance, with an average area under the receiver operating characteristic curve (AUC) of 0.76, although all models lacked sensitivity. Reducing the dataset to 500 features produced an AUC of 0.77 with sensitivity increasing by 74% from 0.46 to 0.80. Model performance improved for the classification of negative-status and type 2 diabetes. Diabetes type models performed best with 500 features, but the metric performed poorly across all model iterations. ML has the potential to facilitate early diagnosis of diabetes based on microbial profiles of the gut microbiome.

PMID:40063675 | DOI:10.1099/mgen.0.001365

J Vis Exp. 2025 Feb 21;(216). doi: 10.3791/67911.

ABSTRACT

Mitochondrial membrane potential (MMP, ΔΨm) is critical for mitochondrial functions, including ATP synthesis, ion transport, reactive oxygen species (ROS) generation, and the import of proteins encoded by the nucleus. Existing methods for measuring ΔΨm typically use lipophilic cation dyes, such as Rhodamine 800 and tetramethylrhodamine methyl ester (TMRM), but these are limited by low specificity and are not well-suited for in vivo applications. To address these limitations, we have developed a novel protocol utilizing genetically encoded voltage indicators (GEVIs). Genetically encoded voltage indicators (GEVIs), which generate fluorescent signals in response to membrane potential changes, have demonstrated significant potential for monitoring plasma membrane and neuronal potentials. However, their application to mitochondrial membranes remains unexplored. Here, we developed protein-based mitochondrial-targeted GEVIs capable of detecting ΔΨm fluctuations in cells and the motor cortex of living animals. The mitochondrial potential indicator (MPI)offers a non-invasive approach to study ΔΨm dynamics in real-time, providing a method to investigate mitochondrial function under both normal and pathological conditions.

PMID:40063520 | DOI:10.3791/67911