Biology subjects

Song, J.

Publications and source records attributed to Song, J..

At least 109 records · Page 6Linked to original sources

bioRxiv2024

A novel pan class-I glucose transporter inhibitor DRB18 exhibits synergistic effects in vitro and in vivo with paclitaxel against human non-small cell lung cancer

PurposeCancer cells depend on glucose for biomass synthesis, cell proliferation, and drug resistance. Glucose transporter (GLUT) transcripts as well as proteins are upregulated in human lungs and other cancers and are negatively correlated with patient survival, particularly GLUT1 and GLUT3. Thus, inhibiting GLUT function has been an attractive anticancer strategy. We previously characterized WZB117 and DRB18, first- and second-generation pan-class I GLUT inhibitors, respectively. DRB18 strongly inhibits glucose transport mediated by GLUT1-4 in non-small lung cancer (NSCLC) A549 cells in vitro and in vivo. Here, we report DRB18 as a more stable and potent anticancer compound, compared to WZB117. MethodsImmunohistochemistry analysis was performed in Lung adenocarcinoma (LUAD) tissue array to investigate GLUT1 and GLUT3 protein expression between normal, lower and higher stage LUAD patients. Bioinformatics analysis was performed to examine additive effect of GLUT3 to GLUT1 mediated prognosis in LUAD. Glucose uptake and resazurin dye-based proliferation assays were used to determine glucose uptake inhibitory and cell proliferation inhibitory against panel of human cancer cell lines A549, Panc1 and Hela. DRB18 potency was tested against the presence of extracellular nutrients glucose, glutamine and ATP. Synergism between DRB18 and clinically approved anticancer drugs was tested against cancer cells. DRB18 and advanced NSCLC drug Paclitaxel were tested for synergy in vitro and in vivo. ResultsGLUT1/3 combination exhibited higher hazard ratio than either GLUT1 and GLUT3 alone in many cancer types including LUAD. DRB18 reduced glucose uptake in NSCLC A549, pancreatic Panc1, and cervical Hela cancer cells with varied but strong anticancer potencies in the presence or absence of extracellular nutrients such as ATP and glucose. Combined with different clinical and pre-clinical anticancer compounds such as V9302, CB839, Sutent, Brigatinib, DRB18 significantly increased death of A549 and Panc1 cells. Noteworthy, DRB18 exhibited strong anticancer synergy with paclitaxel, an approved chemo drug for NSCLC, drastically reducing cancer cell proliferation in vitro and growth of A549 tumors grafted on the flank of nude mice without significant side effects, compared to single drug treatments. ConclusionsCollectively, our results demonstrate anticancer efficacy of pan class-I GLUT inhibitor DRB18 in combination with paclitaxel, providing a potentially more efficacious therapeutic strategy for treating advanced NSCLC and other cancers.

cancer biology↗

bioRxiv2024

Bridging the Dimensional Gap from Planar Spatial Transcriptomics to 3D Cell Atlases

Spatial transcriptomics (ST) has revolutionized our understanding of tissue architecture, yet constructing comprehensive three-dimensional (3D) cell atlases remains challenging due to technical limitations and high cost. Current approaches typically capture only sparsely sampled two-dimensional sections, leaving substantial gaps that limit our understanding of continuous organ organization. Here, we present SpatialZ, a computational framework that bridges these gaps by generating virtual slices between experimentally measured sections, enabling the construction of dense 3D cell atlases from planar ST data. SpatialZ is designed to operate at single-cell resolution and function independently of gene coverage limitations inherent to specific spatial technologies. Comprehensive validation using real 3D ST and independent serial sectioning datasets demonstrates that SpatialZ accurately reconstructs virtual slices while preserving cell identities, gene expression patterns, and spatial relationships. Leveraging the BRAIN Initiative Cell Census Network data, we constructed a 3D hemisphere atlas comprising over 38 million cells, a scale not feasible experimentally. This dense atlas enables unprecedented capabilities, including in silico sectioning at arbitrary angles, explorations of gene expression across both 3D volumes and surfaces, and 3D mapping of query tissue sections. While currently validated for spatial transcriptomics, the underlying principles of SpatialZ could potentially be adapted for spatial proteomics, spatial metabolomics, and even spatial multi-omics. Validated through internal and external testing, our computationally generated atlas maintains biological accuracy, providing unprecedented resolution of spatial molecular landscapes and demonstrating the potential of computational approaches in advancing 3D ST.

bioinformatics↗

bioRxiv2024

NicheTrans: Spatial-aware Cross-omics Translation

Spatial omics technologies have revolutionized our studies on tissue architecture and cellular interactions at single-cell resolution. While spatial multi-omics approaches offer unprecedented insights into complex biological systems, their widespread adoption is hindered by technical challenges, specialized requirements, and limited accessibility. To address these limitations, we present NicheTrans, the first spatially-aware cross-omics translation method and a flexible Transformer-based multi-modal deep learning framework. Unlike existing single-cell (non-spatial) translation methods, NicheTrans uniquely incorporates both cellular microenvironment information and flexible integration of multi-modal data, such as morphology and prior knowledge. We validated NicheTrans across diverse biological cases: Parkinsons Disease (PD), Alzheimers Disease (AD), breast cancer, and lymph nodes. Our approach demonstrated superior performance compared to existing single-cell methods, highlighting the crucial role of spatial and multi-modal information in cross-omics translation. Through NicheTrans, we uncovered spatial multi-omics domains that were not detectable through single-omics analysis alone. Model interpretation revealed key molecular relationships, including gene programs associated with dopamine metabolism and amyloid {beta}-associated cell states. Additionally, using translated protein markers as spatial landmarks, we quantified the spatial organization of key glial cell subtypes in the AD brain. NicheTrans represents a powerful tool for generating comprehensive spatial multi-omics insights from more accessible single-omics measurements, making multi-omics analysis more feasible for the broader research community.

bioinformatics↗

bioRxiv2024

Failed Double-Blind Replication of Offline 5Hz-rTUS-Induced Corticospinal Excitability

IntroductionTranscranial ultrasound stimulation (TUS) is a promising new form of non-invasive neuromodulation. As a nascent technique, replication of its effects on brain function is important. Of particular interest is offline 5Hz repetitive TUS (5Hz-rTUS), originally reported by Zeng and colleagues [1] to elicit lasting corticospinal excitability increases, with large effect sizes. Material and methodHere, we conducted a pre-registered (https://osf.io/p5n4q) replication of this protocol that benefitted from three additional features: double-blind application of TUS, neuronavigation for consistent TMS positioning, and acoustic simulations to assess M1 target exposure to TUS. Changes in resting motor thresholds (rMT), motor-evoked potential (MEP) amplitude, short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) in response to TUS (5Hz-rTUS vs. sham) were measured in the right first dorsal interosseous (FDI), abductor digiti minimi (ADM) and abductor pollicis brevis (APB) muscles, with unbiased selection of participants. Transducer location was determined by the TMS-hotspot for motor representations of the right FDI, as in the original work. ResultsNo significant effects of 5Hz-TUS (vs sham) were observed. Post-hoc simulations showed considerable variability of the acoustic focus, which was outside the anatomical M1-hand area in 67% of participants - in line with the known poor correspondence of TMS-hotspot location and M1-hand area. ConclusionOur results indicate that the effect sizes of the neuromodulatory effects of 5Hz-rTUS on M1 may be more variable than previously appreciated. We suggest that double-blinding, neuronavigated TMS, individualised acoustic simulations for TUS targeting and pre-registration will aid reproducibility across studies.

neuroscience↗

bioRxiv2024

Beta-DIA: Integrating learning-based and function-based feature scores to optimize the proteome profiling of single-shot diaPASEF mass spectrometry data

We present a freely available diaPASEF data analysis software, Beta-DIA, that utilizes deep learning methods to score coelution consistency in retention time-ion mobility dimensions and spectrum similarity. Beta-DIA integrates these learning-based scores with traditional function-based scores, enhancing the qualitative analysis performance. In some low detection datasets, Beta-DIA identifies twice as many protein groups as DIA-NN. The success of Beta-DIA has paved another way for the application of deep learning in fundamental proteome profiling.

bioinformatics↗

bioRxiv2024

Accurate prediction of CRISPR editing outcomes in somatic cell lines and zygote with few-shot learning

The CRISPR-Cas system has revolutionized gene editing, while its outcome prediction remains unsatisfactory, especially in new cell states due to their distinct DNA repair preferences. In this study, we introduce inDecay, a flexible system for predicting CRISPR editing outcomes from target sequence, returning probabilities of nearly the full spectrum of indel events. Uniquely, inDecay utilizes informative and parameter-efficient features for each indel event and incorporates cell-type-specific repair preferences through a multi-stage design. While both inDecay and existing methods achieve accurate results for prediction within cell lines, only inDecay with transfer learning can retain the high performance for cross-cell line prediction. We then applied inDecay to mouse embryo editing using our newly generated data and observed remarkable accuracy by including as few as 30 fine-tuning embryonic samples. Notably, inDecay is the first software to predict embryonic editing. Therefore, our few-shot learning-supported system may accelerate guide RNA prioritization in mouse model generation, mammal embryonic gene editing, and cellular therapeutics.

bioinformatics↗

bioRxiv2024

Positive impact of Type-A and -C response regulator genes on growth and panicle architecture in rice

Cytokinin signal transduction occurs through a "two-component system." Type-A and -C response regulators (RRs) are groups of proteins of similar structures constituting significant components of cytokinin signal transduction. In rice, 13 (Type-A) and two (Type-C) RRs have been identified to date; however, their functions remain partially known. In this study, we examined the expression patterns of Type-A and Type-C RRs in rice using RNA-Seq and confirmed their functions by constructing mutants of the 15 genes with CRISPR/Cas9. Almost all Type-A RRs played positive roles in the development of secondary branches and secondary spikelets, particularly RR2 and RR4. Notably, rr1 rr2 and rr8 rr12 rr13 higher-order mutants displayed small panicle sizes and decreased plant height. Additionally, both Type-C RRs played positive roles in regulating heading date. RNA-seq revealed several genes with significantly altered expression in the rr2 and rr4 mutants, with almost half of the differentially expressed genes (DEGs) overlapping between the two mutants. Many of the DEGs were associated with the cytokinin and abscisic acid pathways. Our findings provide new insights into the functions of Type-A and -C RRs in rice growth and may serve as a foundation for future studies focusing on cytokinin signaling.

plant biology↗

bioRxiv2024

MethylGPT: a foundation model for the DNA methylome

DNA methylation serves as a powerful biomarker for disease diagnosis and biological age assessment. However, current analytical approaches often rely on linear models that cannot capture the complex, context-dependent nature of methylation regulation. Here we present MethylGPT, a transformer-based foundation model trained on 226,555 (154,063 after QC and deduplication) human methylation profiles spanning diverse tissue types from 5,281 datasets, curated 49,156 CpG sites, and 7.6 billion training tokens. MethylGPT learns biologically meaningful representations of CpG sites, capturing both local genomic context and higher-order chromosomal features without external supervision. The model demonstrates robust methylation value prediction (Pearson R=0.929) and maintains stable performance in downstream tasks with up to 70% missing data. Applied to age prediction across multiple tissue types, MethylGPT achieves superior accuracy compared to existing methods. Analysis of the models attention patterns reveals distinct methylation signatures between young and old samples, with differential enrichment of developmental and aging-associated pathways. When finetuned to mortality and disease prediction across 60 major conditions using 18,859 samples from Generation Scotland, MethylGPT achieves robust predictive performance and enables systematic evaluation of intervention effects on disease risks, demonstrating potential for clinical applications. Our results demonstrate that transformer architectures can effectively model DNA methylation patterns while preserving biological interpretability, suggesting broad utility for epigenetic analysis and clinical applications.

systems biology↗

bioRxiv2024

Assembling Ruthenium Complexes to Form Ruthenosome Unleashing Ferritinophagy-mediated Tumor Suppression

AbstactWe introduce ruthenosomes, a fusion of liposomal and reactive oxygen species (ROS)-generating properties meticulously engineered as potent ferroptosis inducers (FINs), marking a significant advancement in metallodrug design for cancer therapy. Formed through the self-assembly of oleate-conjugated ruthenium complexes, these ruthenosomes exhibit exceptional cellular uptake, selectively accumulating in mitochondria and causing substantial disruption. This targeted mitochondrial damage significantly elevates ROS levels, triggering autophagy and selectively activating ferritinophagy. Together, these processes sensitize cancer cells to ferroptosis. In vivo, ruthenosomes effectively suppress colorectal tumor growth, underscoring their therapeutic potential. Our study pioneers a design strategy that transforms ruthenium complexes into liposome-like structures capable of inducing ferroptosis independent of light activation. By leveraging ruthenosomes as multifunctional nanocarriers, this research offers a versatile and powerful platform for ROS-mediated, ferroptosis-driven cancer cell eradication.

biochemistry↗

bioRxiv2024

DEMINERS enables clinical metagenomics and comparative transcriptomic analysis by increasing throughput and accuracy of nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) advances RNA biology but is limited by relatively low basecalling accuracy, low throughput, yet high RNA input and costs. Here we introduce a novel DRS toolkit, DEMINERS, which integrates an RNA multiplexing experimental workflow, a machine-learning barcode classifier based on Random Forest and a novel basecaller built on an optimized convolutional neural network providing an additional species-specific training module. With the increased accuracy in barcode classification and basecalling, DEMINERS can demultiplex up to 24 samples and the required RNA input and running time are both substantially reduced. We demonstrated the applications of DEMINERS in clinical metagenomics, cancer transcriptomics and parallel comparison of transcriptomic features in different biological conditions, revealing altered airway microbial diversity in COVID-19 and a potential role of m6A in increasing transcriptomic diversity in glioma and the mature blood-stage of malaria parasites. Overall, DEMINERS is a simple, robust, high-throughput DRS method for accurately estimating transcript levels, poly(A) lengths, and mutation and RNA modification heterogeneity at single-read level, with minimal sequencing biases.

bioinformatics↗

bioRxiv2024

Design of linked-domain protein inhibitors of UBE2D as tools to study cellular ubiquitination

Ubiquitin (Ub) is a post-translational modification that largely controls proteostasis through mechanisms spanning transcription, translation, and notably, protein degradation. Ub conjugation occurs through a hierarchical cascade of three enzyme classes (E1, E2, and E3s) involving >1000 proteins that regulate the ubiquitination of proteins. The E2 Ub-conjugating enzymes are the midpoint, yet their cellular roles remain under-characterized, partly due to a lack of inhibitors. For example, the cellular roles of the promiscuous E2 UBE2D/UBCH5 are not well described. Here, we develop a highly selective, multivalent, engineered protein inhibitor for the UBE2D family that simultaneously targets the RING- and backside-binding sites. In HeLa cells, these inhibitors phenocopy knockdown of UBE2D by reducing the IC50 to cisplatin and whole-cell proteomics reveal an increased abundance of [~]20% of the identified proteins, consistent with reduced Ub degradation and proteotoxic stress. These precision tools will enable new studies probing UBE2Ds central role in proteome management.

biochemistry↗

bioRxiv2024

Diverse RNA Structures Induce PRC2 Dimerization and Inhibit Histone Methyltransferase Activity

Methyltransferase PRC2 (Polycomb Repressive Complex 2) deposits histone H3K27 trimethylation to establish and maintain epigenetic gene silencing. PRC2 is precisely regulated by accessory proteins, histone post-translational modifications and, particularly, RNA. Research on PRC2-associated RNA has mostly focused on the tight-binding G-quadruplex (G4) RNAs, which inhibit PRC2 enzymatic activity in vitro and in cells, a mechanism explained by our recent cryo-EM structure showing G4 RNA-mediated PRC2 dimerization. However, PRC2 binds a wide variety of RNA sequences, and it remains unclear how diverse RNAs beyond G4 associate with and regulate PRC2. Here, we show that variations in RNA sequence elicit distinct effects on PRC2 function. A single-stranded G-rich RNA and an atypical G4 structure called a pUG-fold mediate PRC2 dimerization nearly identical to that induced by G4 RNA. In contrast, pyrimidine-rich RNAs, including a motif identified by CLIPseq in cells, do not induce PRC2 dimerization and instead bind PRC2 monomers with retention of methyltransferase activity. Only RNAs that dimerize PRC2 compete with nucleosome binding and inhibit PRC2 methyltransferase activity. CRISPR-dCas9 was adapted to localize different RNA elements onto a PRC2-targeted gene, revealing RNA sequence specificity for PRC2 regulation in cells. Thus, PRC2 binds many different RNAs with similar affinity, however, the functional effect on enzymatic activity depends entirely on the sequence of the bound RNA, a conclusion potentially applicable to any RNA- binding protein with a large transcriptome.

biochemistry↗

bioRxiv2024

The role of TRPV4 in acute sleep deprivation-induced fear memory impairment

Acute sleep deprivation (ASD) negatively impacts fear memory, but the underlying mechanisms are not fully understood. Transient receptor potential vanilloid 4 (TRPV4), a cation channel which is closely correlated with the concentration of Ca2+, and neuronal Ca2+ overloading is a crucial inducement of learning and memory impairment. This study utilized an acute sleep-deprived mouse model combined with fear conditioning to investigate these mechanisms. mRNA sequencing revealed increased expression of TRPV4 in mice with ASD-induced fear memory impairment. Notably, knockdown of TRPV4 reversed ASD-induced fear memory impairment. ASD leads to the increased concentration of Ca2+. Additionally, we observed a reduction in spine density and a significant decrease in postsynaptic density protein 95 (PSD95), which is associated with synaptic plasticity, in sleep-deprived fear memory impairment mice. This indicates that ASD may cause overloaded Ca2+, disrupting synaptic plasticity and impairing fear memory. Moreover, TRPV4 knockdown significantly decreased Ca2+ concentration, mitigated the loss of dendritic spines and reduction of PSD95, contributing to the restoration of fear memory. These findings indicate a potential protective role of TRPV4 knockdown in counteracting ASD-induced fear memory deficits. Collectively, our results highlight that TRPV4 may be a potential therapeutic target in mediating fear memory impairment due to ASD and underscore the importance of sleep management for conditions like PTSD.

neuroscience↗

bioRxiv2024

A Small Interfering Peptide Potentiates AMPA Receptor Diffusional Trapping and Prevents Social-Isolation-Induced Forgetting of Fear Memory

Synaptic trapping of AMPA receptors (AMPARs) is a key mechanism regulating excitatory synaptic transmission and activity-dependent plasticity underlying learning and memory. Destabilization of synaptic AMPARs is increasingly implicated in cognitive dysfunction across neurological and neuropsychiatric disorders, yet strategies to directly modulate this process in vivo remain limited, constraining both mechanistic insight and therapeutic development. Here we present a peptide-based strategy to enhance AMPAR synaptic trapping by targeting the interaction between transmembrane AMPA receptor regulatory proteins (TARPs) and activity-regulated cytoskeleton-associated protein (ARC/Arg3.1). We designed a 21-amino-acid TAT-fused peptide (TARP-pep) mimicking the TARP C-terminal motif that binds the ARC N-lobe. TARP-pep disrupted the TARP-ARC interaction and increased the stabilization of AMPARs at synaptic surfaces in cultured hippocampal neurons. In vivo, acute intrahippocampal infusion of TARP-pep enhanced perforant path-evoked synaptic transmission in the rat dentate gyrus (DG) and strengthened the interaction between TARPs and postsynaptic density protein 95 (PSD-95), a key mechanism underlying AMPAR anchoring. Consistent with a long-term potentiation (LTP)-like synaptic state, TARP-pep increased basal phosphorylation of Ca2+/calmodulin-dependent protein kinase II (CaMKII) and occluded further chemical LTP (cLTP)-induced increases in phosphorylated CaMKII (p-CaMKII). Notably, a 7-day regimen of daily bilateral DG injections of TARP-pep prevented social isolation (SI)-induced impairment of fear memory in mice. Together, these findings identify the TARP-ARC interaction as a druggable regulator of AMPAR diffusional trapping and highlight synaptic AMPAR stabilization as a promising therapeutic strategy for preserving cognitive function under conditions of circuit vulnerability.

neuroscience↗

bioRxiv2024

Paradoxical SERCA dysregulation contributes to atrial fibrillation in a model of diet-induced obesity

Obesity is a major risk factor for atrial fibrillation (AF) the most common serious cardiac arrhythmia, but the molecular mechanisms underlying diet-induced AF remain unclear. In this study, we subjected mice to a chronic high-fat diet and acute sympathetic activation ( two-hit model) to study the mechanisms by which diet-induced obesity promotes AF. Surface electrocardiography revealed that diet-induced obesity and sympathetic activation synergize during intracardiac tachypacing to induce AF. At the cellular level, diet-induced obesity and acute adrenergic stimulation facilitate the formation of delayed afterdepolarizations in atrial myocytes, implicating altered Ca2+ dynamics as the underlying cause of AF. We found that diet-induced obesity does not alter the expression of major Ca2+-handling proteins in atria, including the sarcoplasmic reticulum Ca2+-ATPase (SERCA), a major component of beat-to-beat Ca2+ cycling in the heart. Paradoxically, obesity reduces phospholamban phosphorylation, suggesting decreased SERCA activity, yet atrial myocytes from obese mice showed a significantly increased Ca2+ transient amplitude and SERCA-mediated Ca2+ uptake. Adrenergic stimulation further increases the Ca2+ transient amplitude but does not affect Ca2+ reuptake in atrial myocytes from obese mice. Transcriptomics analysis showed that a high-fat diet prompts upregulation of neuronatin, a protein that has been implicated in obesity and is known to stimulate SERCA activity. We propose a mechanism in which obesity primes SERCA for paradoxical activation, and adrenergic stimulation facilitates AF conversion through a Ca2+-induced Ca2+ release gain in atrial myocytes. Overall, this study links obesity, altered Ca2+ signaling, and AF, and targeting this mechanism may prove effective for treating obesity-induced AF.

physiology↗

bioRxiv2024

Metagenome-based diversity and functional analysis of culturable microbes in sugarcane

Sugarcane, widely acknowledged as the foremost crop for sugar and energy production on a worldwide scale, is confronted with many diseases that pose serious threats to its production. Biological control has become more popular as an approach for preventing and controlling diseases because of its environment-friendly characteristics. However, there is a lack of thorough investigation and use of microbial resources in sugarcane. This study conducted a thorough analysis of culturable microbes and their functional features in different tissues and rhizosphere soil of four diverse sugarcane species using metagenomics techniques. The results revealed significant microbial diversity in sugarcanes tissues and rhizosphere soil, including several important biomarker bacterial taxa identified, which are reported to engage in several processes that support plant growth. The LEfSe studies identified unique microbial communities in different parts of the same sugarcane species, particularly Burkholderia, which exhibited significant variations across the sugarcane species. Microbial analysis of carbohydrate-active enzymes (CAZymes) indicated that genes related to sucrose metabolism were mostly present in specific bacterial taxa, including Burkholderia, Pseudomonas, Paraburkholderia, and Chryseobacterium. This study improves understanding of the diversities and functions of endophytes and rhizosphere soil microbes in sugarcane. Moreover, the approaches and findings of this study provide valuable insights for microbiome research and the use of comparable technologies in other agricultural fields.

microbiology↗

bioRxiv2024

Intraperitoneal programming of tailored CAR macrophages via mRNA-LNP to boost cancer immunotherapy

Therapeutic strategies for peritoneal metastasis in solid tumors are urgently needed in the clinic. Programming chimeric antigen receptor macrophages (CAR-Ms) in situ offers opportunities for an unmet demand. However, potential intracellular domains (ICDs) for CAR design and their antitumor mechanisms for macrophage empowerment remain to be explored systematically. By developing a targeted mRNA-LNP delivery system for macrophages, we have investigated 36 CAR combinations to determine the impact of CAR-Ms on immune regulation in vitro and in vivo. In two solid tumor mouse models, intraperitoneal programming of CAR-Ms was shown to elicit robust adaptive immune activation and significantly synergize with PD-1/L1 therapy. Single-cell RNA sequencing (scRNA-seq) analysis revealed that CAR-Ms could reshape the immunosuppressive tumor microenvironment (TME) and boost the TCF1+PD-1+ progenitor- exhausted CD8+ T cells (Tpex) population. Meanwhile, we found that tailored CAR-M with CD3{zeta}/TLR4 ICDs could favorably maintain proinflammatory phenotype and simultaneously upregulate MHC I and PD-L1 expression by perturbing NF-{kappa}B pathways. Moreover, the synergism between macrophage PD-L1 knockdown and CAR-M therapy highlighted the need to block the PD-1/L1 axis in antigen cross-presentation. In short, we developed an mRNA-LNP delivery system for intraperitoneal programming of tailored CAR-Ms in vivo and broadened understanding of both regulatory and feedback mechanisms for CAR-M therapies against solid tumors.

bioengineering↗

bioRxiv2024

Modulation of Neuronal Excitability and Plasticity by BHLHE41 Conveys Lithium Non-Responsiveness

Many bipolar disorder (BD) patients are non-responsive to lithium. The mechanisms underlying lithium (non-)responsiveness are largely unknown. By using gene-set enrichment analysis methods, we found that core clock gene-sets are significantly associated with lithium response. Among the top hits was BHLHE41, a modulator of the molecular clock and homeostatic sleep. Since BHLHE41 and its paralog BHLHE40 are functionally redundant, we assessed chronic lithium response in double-knockout mutant mice (DKO). We demonstrated that DKOs are non-responsive to lithiums effect in various behavioral tasks. Cellular assays and patch clamp recordings revealed lowered excitability and reduced lithium-response in prefrontal cortical layer 2/3 DKO neurons and on hippocampal long-term potentiation. Single-cell RNA sequencing identified that lithium deregulated mitochondrial respiration, cation channel and postsynapse associated gene-sets specifically in upper layer excitatory neurons. Our findings show that lithium acts in a highly cell-specific way on neuronal metabolism and excitability and modulates synaptic plasticity depending on BHLHE40/41.

neuroscience↗