Biology subjects

Cao, B.

Publications and source records attributed to Cao, B..

At least 19 recordsLinked to original sources

bioRxiv2026

VCP inhibition prevents cone photoreceptor degeneration in the cpfl1 mouse model of achromatopsia

Achromatopsia (ACHM) is a rare autosomal recessive retinal disorder characterized by absent cone photoreceptor function from early life, leading to severe visual impairment. Mutations in genes involved in the cone phototransduction cascade frequently result in elevated cyclic guanosine monophosphate (cGMP) levels and activation of stress pathways, including endoplasmic reticulum (ER) stress and the unfolded protein response. Targeting common downstream mechanisms rather than individual mutations may provide a broadly applicable therapeutic strategy. Here, we investigated whether pharmacological inhibition of valosin-containing protein (VCP), a key regulator of ER and protein homeostasis, can prevent cone degeneration in the spontaneous cone photoreceptor function loss 1 (cpfl1) mouse model of ACHM. Organotypic culture of retinal explants from cpfl1 mice were treated with the selective VCP inhibitor ML240. Cone survival, cell death, opsin expression and localization were assessed by TUNEL assay, immunohistochemistry, and quantitative image analysis. ML240 treatment significantly increased cone density and improved cone opsin expression and trafficking to the outer segments (OSs) in cpfl1 explants compared to controls. Importantly, rhodopsin trafficking in rod photoreceptors was unaffected, indicating that VCP inhibition did not impair normal rod phototransduction. These findings demonstrate that VCP inhibition by ML240 effectively preserves cone photoreceptors and improves cone-specific functional markers in the cpfl1 model. Targeting VCP may represent a mutation-independent therapeutic strategy for preventing cone death in ACHM.

neuroscience↗

bioRxiv2026

VCP inhibition preserves photoreceptor integrity under hydroquinone-induced oxidative stress in a human iPSC-RPE/porcine neuroretina co-culture model

Age-related macular degeneration (AMD) is the leading cause of irreversible vision loss in older adults. It is characterised by early retinal pigment epithelium (RPE) dysfunction followed by progressive photoreceptor degeneration. Cigarette smoking is a major environmental risk factor for AMD, and hydroquinone (HQ), a redox-active cigarette smoke component, induces oxidative stress and apoptosis in RPE cells. To analyse how RPE stress contributes to photoreceptor degeneration, we employed a retinal co-culture model composed of human induced pluripotent stem cell-derived RPE (iPSC-RPE) cells in conjunction with porcine neuroretina explants. Exposure to HQ induced oxidative stress in iPSC-RPE cells as well as retinal photoreceptors (RPR), resulting in apoptosis, executed at least in part by caspase activation. Concomitantly, HQ caused endoplasmic reticulum (ER) stress (ERAD) in RPR followed by their degeneration, evidenced by reduced outer nuclear layer (ONL) rows and shortened RPR outer segments (OS). Based on earlier results, which suggest a perturbation of proteostasis due to HQ, we tested whether ML240, a bona fide inhibitor of valosin-containing protein (VCP), would influence the degree of degenerative activities. ML240 did not prevent HQ-induced apoptosis in iPSC-RPE cells. However, it significantly preserved photoreceptor integrity, retaining OS length and cone density in HQ-stressed co-cultures. Proteomic analysis suggested that ML240 reshapes stress response patterns of the HQ-exposed neuroretina, as evidenced by a reduction in ERAD-associated markers, increased levels of antioxidant response proteins, and the preservation of cytochrome c enrichment in photoreceptor inner segments, which indicates improved mitochondrial integrity consistent with the observed preservation of photoreceptor structure. Together, these findings establish the iPSC-RPE/neuroretina co-culture as a platform to analyse pathophysiological features of AMD, dissect cell type-specific retinal responses to environmental stress and test neuroprotective pharmacological approaches to protect photoreceptors in oxidative stress-associated retinal degeneration.

cell biology↗

bioRxiv2026

Pharmacologic eIF2B Activation Rescues Neuropathy in CMT2 Subtypes by Normalizing the Integrated Stress Response

Among the many subtypes of Charcot-Marie-Tooth (CMT) disease, several result from mutations in genes encoding aminoacyl-tRNA synthetases, enzymes required for tRNA charging during cytoplasmic and mitochondrial translation. We report that activation of the integrated stress response (ISR) pathway is a shared molecular feature of tRNA synthetase-associated and other axonal CMT subtypes. RTX-117, a CNS-penetrant small molecule currently in Phase 1 clinical trials, targets eukaryotic initiation factor 2B (eIF2B), a key modulator of protein synthesis and the ISR pathway. Using cryo-EM studies, we have characterized the binding mode of RTX-117 to the eIF2B decamer. In GarsP278KY/+ mice, which develop early onset motor defects and axonal pathology that recapitulate CMT2D symptoms from tRNA synthetase mutations, RTX-117 treatment started after disease onset reduced chronic ISR activation and produced significant functional and electrophysiological improvement. We further identify ISR targets, including secreted proteins such as GDF15 and FGF21 that may serve as translational biomarkers for treatment response to RTX-117 in CMT disease. Broader surveillance of the ISR pathway across models of neurodegeneration reveals strong activation in several diseases and a correlation with disease progression, particularly in models of Alzheimers disease. These findings identify chronic ISR activation as a recurrent, though not universal, pathological mechanism of neurodegenerative disease models. Overall, our study identifies candidate biomarkers for CMT disease subtypes associated with defects in translational homeostasis and supports eIF2[a]-ATF4 axis modulation as a promising therapeutic strategy for this disease class. One Sentence SummaryRTX-117, a clinical stage eIF2B activator, blunts chronic ISR activation and improves nerve and motor function in a mouse model of Charcot-Marie-Tooth Disease Type 2D.

cell biology↗

bioRxiv2026

A distributed neural architecture of sustained affect across external and internal experience

AO_SCPLOWBSTRACTC_SCPLOWSustained affect shapes well-being, yet its neural architecture across externally elicited and internally generated experience remains unclear. Using whole-brain functional connectivity during minutes-long naturalistic movie viewing, we derived positive and negative affective experience signatures and their underlying neural architecture. These signatures predicted valence-specific affective intensity and generalized to independent movie-viewing data and internally generated affect, discriminating sad memory and rumination from neutral distraction while tracking subjective experience. Importantly, their expression showed little relation to vigilance or cognitive demand. Characterization of these signatures revealed coherent community structure and a shared distributed backbone, alongside valence-preferential components, consistent with a partially separable architecture. Extending beyond experimentally evoked states, in four resting-state depression cohorts, these signatures distinguished patients from controls with reduced positive and elevated negative signature expression, and predicted symptom burden and anhedonia. These findings identify a generalizable distributed architecture bridging external and internal affective experience and extending to clinically relevant affective dysregulation.

neuroscience↗

bioRxiv2025

DNACSE: Enhancing Genomic LLMs with Contrastive Learning for DNA Barcode Identification

DNA barcoding is a powerful tool for exploring biodiversity, and DNA language models have significantly facilitated its construction and identification. However, since DNA barcodes come from a specific region of mitochondrial DNA and there are structural differences between DNA barcodes and reference genomes used to train existing DNA language models, it is difficult to directly apply the existing DNA language models to the DNA barcoding task. To address this, this paper introduce DNACSE (DNA Contrastive Learning for Sequence Embeddings), an unsupervised noise contrastive learning framework designed to fine-tune the DNA language foundation model while enhancing the distribution of the embedding space. The results demonstrate that DNACSE outperforms direct usage of DNA language models in DNA barcoding-related tasks. Specifically, in fine-tuning and linear probe tasks, it achieves accuracy rates of 99.17% and 98.31%, respectively, surpassing the current state-of-the-art BarcodeBERT by 6.44% and 6.44%. In zero-shot clustering tasks, it raises the Adjusted Mutual Information (AMI) score to 92.25%, an improvement of 8.36%. In addition, zero-shot benchmarking and genomic benchmarking tests are evaluated, indicating that DNACSE enhances the performance of DNA language models in generalized genomic tasks. In summary, DNACSE has demonstrated excellent performance in DNA barcode species classification by making full use of multi-species information and DNA barcode information, providing a feasible way to further explore and protect biodiversity. The code repository is available at https://github.com/Kavicy/DNACSE.

bioinformatics↗

bioRxiv2025

From short-lived to persistent: The significance of extracellular RNA in disinfected drinking water microbiomes

To assure the safe distribution of drinking water, it is critical to identify adaptations that allow microorganisms to thrive in an oligotrophic system under disinfectant stress. Microbial adaptive responses are determined using RNA-based differential transcriptomics which cannot be performed in environmental settings due to lack of a baseline. This study introduces the concept of using extracellular RNA (eRNA) as a reference to determine important adaptive features in disinfected drinking water microbiome. Using this method, we determined energy efficiency, dynamic membrane composition, oxidative stress response, and proper protein folding to be extremely important for survival in drinking water systems. Additionally, multiple antibiotic resistance genes are expressed and upregulated in intracellular RNA fraction, indicating selection pressure. Non-coding RNA and transfer-messenger RNA found in eRNA suggest important regulatory functions. This study advances our understanding of eRNA in drinking water microbiomes and provides a framework for exploration in other environmental systems.

ecology↗

bioRxiv2025

DNA Sequence Trace Reconstruction Using Deep Learning

Deciphering DNA sequences is fundamental to unlocking the mysteries of life, but the high dimensionality and complexity of biological sequence data significantly hinder knowledge discovery. In particular, the challenges of sequence length, repetitive regions, and structural complexity make it difficult to directly reconstruct complete DNA sequences from raw data. Therefore, this paper proposes a DNA sequence trace reconstruction model, DNARetrace, which performs preprocessing and dataset construction, and then employs a Bidirectional Fourier-Kolmogorov-Arnold Network (Bi-FKGAT), using an extremely unbalanced loss function for link prediction, so as to reconstruct the original DNA sequence. In multi-angle experiments using both simulated and real data, DNARetrace successfully reconstructs DNA sequence traces across large-scale datasets derived from various DNA sequencing methods, overcoming the bias of current approaches toward specific sequencing platforms, and achieves competitive outcomes in DNA storage and genomics downstream tasks. We further validated the expandability of the proposed methods in DNA sequence classification and metagenomic binning tasks. In summary, DNARetrace is compatible with various sequencing scenarios; it reduces the difficulty of discovering novelty knowledge directly from high-complexity raw data, and it provides a reusable tool to accelerate DNA sequence processing and applications.

genomics↗

bioRxiv2025

Ocular delivery of different VCP inhibitory formulations prevents retinal degeneration in rhodopsin 255 isoleucine deletion mice

Rhodopsin-mediated autosomal dominant retinitis pigmentosa (RHO-adRP) is a progressive inherited retinal degenerative disorder currently lacking effective treatments. A recurrent 3-base pair deletion in the RHO gene, resulting in the loss of isoleucine at codon 255 or 256 (RHO{Delta}I255 or RHO{Delta}I256), has been identified in patients from the United Kingdom, Germany, Belgium, China, and Korea, suggesting a broad geographic distribution. This mutation leads to rhodopsin (RHO) misfolding, its retention in the endoplasmic reticulum (ER), and aggregation with wild-type (WT) RHO, ultimately triggering ER stress and photoreceptor degeneration. These aggregates are primarily cleared via the ER-associated degradation (ERAD) pathway, with valosin-containing protein (VCP) playing a key role in their retrotranslocation and proteasomal degradation. Pharmacological or genetic inhibition of VCP has shown neuroprotective effects in other models of adRP, but the poor aqueous solubility of VCP inhibitors and challenges in retinal drug delivery hinders clinical translation. To overcome these limitations, we evaluated and compared three VCP-targeted therapeutic strategies in Rho{Delta}I255 knock-in mouse retinae: (1) small-molecule inhibitors (ML240, NMS-873) solubilized in DMSO, (2) ML240 encapsulated in monomethoxy-polyethylene glycol (mPEG)-cholane nanoparticles, and (3) small interfering RNA (siRNA) targeting VCP, delivered via magnetic nanoparticles. Neuroprotective effects were assessed in vitro in retinal explants and in vivo following intravitreal injection. Our findings provide the first evidence that VCP inhibition restores RHO trafficking to the outer segments and prevents photoreceptor cell death in the Rho{Delta}I255 model. Among the three approaches, nanocarrier-encapsulated ML240 exhibited superior efficacy, enabling sustained drug delivery and enhanced photoreceptor protection. These results establish a preclinical proof-of-concept for nanocarrier-mediated VCP inhibition as a promising therapeutic strategy for RHO-adRP and potentially other ER-stress-related retinal degenerations. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/661245v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@12f9366org.highwire.dtl.DTLVardef@76437dorg.highwire.dtl.DTLVardef@48dd6corg.highwire.dtl.DTLVardef@1c11812_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

PlateletBase: A Comprehensive Knowledgebase for Platelet Research and Disease Insights

Platelets are vital in many pathophysiological processes, yet there is a lack of a comprehensive resource dedicated specifically to platelet research. To fill this gap, we have developed PlateletBase, a knowledge base aimed at enhancing the understanding and study of platelets and related diseases. Our team retrieved information from various public databases, specifically extracting and analyzing RNA-seq data from 3,711 samples across 41 different conditions available on NCBI. PlateletBase offers six analytical and visualization tools, enabling users to perform gene similarity analysis, pair correlation, multi-correlation, expression ranking, clinical information association, and gene annotation for platelets. The current version of PlateletBase includes 10,278 genomic entries, 31,758 transcriptomic entries, 4,869 proteomic entries, 2,614 omics knowledge entries, 1,833 drugs, 97 platelet resources, 438 diseases/traits, and six analysis modules. Each entry has been carefully curated and supported by experimental evidence. Additionally, PlateletBase features a user-friendly interface designed for efficient querying, manipulation, browsing, visualization, and analysis of detailed platelet protein and gene information. Case study results, such as those from gray platelet syndrome and angina pectoris, demonstrate that this tool can aid in identifying diagnostic biomarkers and exploring disease mechanisms, significantly advancing research in platelet functionality and its applications. PlateletBase is accessible at http://plateletbase.clinlabomics.org.cn/.

bioinformatics↗

bioRxiv2024

Synergistic effects of tRNA modification defects in Escherichia coli K12.

Transfer RNAs (tRNAs) are essential components of the translation machinery and carry numerous post-transcriptional modifications that contribute to decoding accuracy, efficiency and cellular fitness. In Escherichia coli K-12, all tRNA modification pathways have been identified, yet the functional interactions between these pathways remain largely unexplored. Here, we systematically analyze genetic interactions between 29 non-essential tRNA modification genes using a pairwise synthetic lethal screen based on P1 transduction. Most combinations of tRNA modification gene deletions are tolerated during growth in rich medium; however, we identify five synthetically lethal pairs and fifteen additional combinations that display negative genetic interactions. Deletions of truA, which encodes the pseudouridine synthase responsible for modifications at positions 38-40 of multiple tRNAs, show the highest frequency of negative epistasis. Synthetic lethality associated with truA can be complemented by expression of truA in trans and, in specific cases, partially suppressed by overexpression of its tRNA substrates, indicating substrate-specific functional dependencies. Analysis of tRNA abundance by northern blotting and AQRNA-seq demonstrates that loss of individual tRNA modification enzymes does not generally lead to widespread tRNA destabilization. Instead, further phenotypic characterization of viable double mutants reveals condition-dependent growth defects influenced by carbon source, temperature and metabolic stress, as well as toxicity associated with overexpression of specific tRNAs. Together, these results reveal a limited but distinct set of genetic interactions among bacterial tRNA modification pathways and highlight the importance of physiological context in uncovering their cellular roles.

microbiology↗

bioRxiv2024

Autosomal dominant Retinitis Pigmentosa caused by the rhodopsin isoleucine 255 deletion features rapid neuroretinal degeneration, decreased synaptic connectivity, and neuroinflammation.

Retinitis Pigmentosa (RP) is a group of inherited retinal diseases that initially affects rod photoreceptors and causes progressive vision loss and blindness. Mutations in rhodopsin (RHO) can cause both autosomal recessive (ar) and dominant (ad) forms of RP, yet, the underlying degenerative mechanisms remain largely unknown, rendering the disease untreatable. Here, we focus on an in-frame, 3-base pair deletion, eliminating the isoleucine residue at codon 255 (i.e., RHO{Delta}I255) and resulting in adRP. We generated a novel knock-in mouse homologous to the human RHO{Delta}I255 mutation. This new mouse model displays a severe disruption of photoreceptor structure and function, as is seen in human patients. Our results indicate that this form of RP is a systems disease of the neuroretina that also impacts neuronal connectivity of bipolar- and horizontal cells, initiates neuroinflammation, and reduces the structural and functional integrity of the retina. Typical for adRP, Rho{Delta}I255 mice exhibit primary rod photoreceptor loss, followed by secondary cone degeneration, rhodopsin protein (RHO) mislocalization, progressive shortening of outer segments (OS), and disorganized OS structures. Subsequently, increasing gliosis, morphologic abnormalities of the inner retina, and impaired cone-driven visual function developed. In adRP, a single mutated allele is sufficient to cause the disease, as confirmed here in Rho{Delta}I255/+ heterozygous animals, where most photoreceptors were lost within two months after birth. Compared to this, homozygous Rho{Delta}I255/{Delta}I255 mutants exhibit an accelerated onset and even faster progression of retinal degeneration. The degeneration of Rho{Delta}I255-mutant photoreceptors was linked to the activation of both caspase- and calpain-type proteases, as well as poly(ADP-ribose) polymerase (PARP), indicating a parallel execution of both apoptotic and non-apoptotic processes. In conclusion, our data indicate that this form of RP affects the neuroretina beyond photoreceptor cell loss sharing features typical for other degenerative central nervous systems diseases, an insight, which may bear critical impact to understand and eventually develop treatment for these currently untreatable forms of blindness. Author summaryDominant mutations in the human rhodopsin gene are among the most common causes for the blinding disease retinitis pigmentosa (RP). To date, the underlying pathophysiological mechanisms are still largely unknown and dominant RP remains untreatable. Here, we introduce a new knock-in mouse model carrying the dominant human Rho{Delta}I255 mutation. As in humans, the Rho{Delta}I255 mouse suffers from a rapid degeneration of rod photoreceptors followed by subsequent cell death of cone photoreceptors and complete loss of visual function. The new mouse model displays sign of neuroinflammation and the concomitant activation of both apoptotic and non-apoptotic cell death mechanisms. These results will likely stimulate further studies into the degenerative processes governing dominant RP and may facilitate future therapy development for inherited retinal diseases that are still untreatable to this day.

pathology↗

bioRxiv2024

SUV39H1 Preserves Cancer Stem Cell Chromatin State and Properties in Glioblastoma

Of the more than 100 types of brain cancer, glioblastoma (GBM) is the deadliest. As GBM stem cells (GSCs) are considered to be responsible for therapeutic resistance and tumor recurrence, effective targeting and elimination of GSCs could hold promise for preventing GBM recurrence and achieving potential cures. We show here that SUV39H1, which encodes a histone-3, lysine-9 methyltransferase, plays a critical role in GSC maintenance and GBM progression. Upregulation of SUV39H1 was observed in GBM samples compared to normal brain tissues, and knockdown of SUV39H1 in patient-derived GSCs impaired their proliferation and stemness. Single-cell RNA-seq analysis demonstrated restricted expression of SUV39H1 is in GSCs relative to non-stem GBM cells, likely due to super-enhancer-mediated transcriptional activation, while whole cell RNA-seq analysis revealed that SUV39H1 regulates G2/M cell cycle progression, stem cell maintenance, and cell death pathways in GSCs. By integrating the RNA-seq data with ATAC-seq (assay for transposase-accessible chromatin followed by sequencing), we further demonstrated altered chromatin accessibility in key genes associated with these pathways following SUV39H1 knockdown. Treatment with chaetocin, a SUV39H1 inhibitor, mimicked the functional effects of SUV39H1 knockdown in GSCs and sensitized GSCs to the GBM chemotherapy drug temozolomide. Furthermore, targeting SUV39H1 in vivo using a patient-derived xenograft model for GBM inhibited GSC-driven tumor formation. This is the first report demonstrating a critical role for SUV39H1 in GSC maintenance. SUV39H1-mediated targeting of GSCs could enhance the efficacy of existing chemotherapy, presenting a promising strategy for improving GBM treatment and patient outcomes. HighlightsO_LISUV39H1 is upregulated in GBM, especially GSCs C_LIO_LITargeting SUV39H1 disrupts GSC maintenance and sensitizes GSCs to TMZ C_LIO_LITargeting SUV39H1 alters chromatin accessibility at cell cycle and stemness genes C_LIO_LITargeting SUV39H1 suppresses GSC-driven tumors in a patient-derived xenograft model C_LI

cancer biology↗

bioRxiv2024

Achieve Handle Level Random Access in Encrypted DNA Archival Storage System via Frequency Dictionary Mapping Coding

DNA as a storage medium has the characteristics of high storage density and durability, but the existing DNA storage system has a high latency, and lacks the consideration of data security. In order to improve the availability of DNA storage, this paper proposes that Frequency Dictionary Mapping Coding (FDMC) implements handle-level random access in DNA Archival storage, and a hybrid e-molecular encryption strategy and multi-level error correction algorithm are provided to ensure data security and integrity. The results of the simulation and wet experiments demonstrate that FDMC can achieve handle-level random access in lossless encrypted DNA storage systems, which balances security and convenience. In terms of read and write consistency, FDMC has significant advantages in storage density and robustness of data recovery. Even in the extreme case of DNA sequence loss of 10%, it can still recover 91.74% of the original data while ensuring storage density above 1.80 bits/nt. In summary, FDMC improves the application range of DNA as a storage medium and bridges the gap between DNA storage and traditional storage modes in the storage and reading of large-scale archives.

bioengineering↗

bioRxiv2024

Predicting mutation-disease associations through protein interactions via deep learning

Disease is one of the primary factors affecting life activities, with complex etiologies often influenced by gene expression and mutation. Currently, wet-lab experiments have analyzed the mechanisms of mutations, but these are usually limited by the costs of wet experiments and constraints in sample types and scales. Therefore, this paper constructs a real-world mutation-induced disease dataset and proposes Capsule networks and Graph topology networks with multi-head attention (CGM) to predict the mutation-disease associations. CGM can accurately predict protein mutation-disease associations, and in order to further elucidate the pathogenicity of protein mutations, we also verified that protein mutations lead to protein structural alterations by Swiss-model, which suggests that mutation-induced conformational changes may be an important pathogenic factor. Limited by the size of the mutated protein dataset, we also performed experiments on benchmark and imbalanced datasets, where CGM mined 22 unknown protein interaction pairs from the benchmark dataset, better illustrating the potential of CGM in predicting mutation-disease associations. In summary, this paper curates a real dataset and proposes CGM to predict the protein mutations-disease associations, providing a novel tool for further understanding of biomolecular pathways and disease mechanisms.

bioinformatics↗

bioRxiv2024

CGPA: multi-context insights from the cancer gene prognosis atlas

Cancer transcriptomic data are used extensively to interrogate the prognostic value of targeted genes, yet basic scientists and clinicians have predominantly relied on univariable survival analysis for this purpose. This method often fails to capture the full prognostic potential and contextual relevance of the genes under study, inadvertently omitting a group of genes we term univariable missed-opportunity prognostic (UMOP) genes. Recognizing the complexity of revealing multifaceted prognostic implications, especially when extending the analysis to include various covariates and thresholds, we present the Cancer Gene Prognosis Atlas (CGPA). This platform greatly enhances gene-centric biomarker research across cancer types by offering an interactive and user-friendly interface for highly customized, in-depth prognostic analysis. CGPA notably supports data-driven exploration of gene pairs and gene-hallmark relationships, elucidating key composite biological mechanisms like synthetic lethality and immunosuppression. It further expands its capabilities to assess multi-gene panels using both public and user-provided data, facilitating a seamless mechanism-to-machine analysis. Additionally, CGPA features a designated portal for discovering prognostic gene modules using curated cancer immunotherapy data. Ultimately, CGPAs comprehensive, accessible tools allow cancer researchers, including those without statistical expertise, to precisely investigate the prognostic landscape of genes, customizing the model to fit specific research hypotheses and enhancing biomarker discovery and validation through a synergy of mechanistic and data-driven strategies. SignificanceCGPA is a streamlined, interactive platform for multi-context gene-centric prognostic analysis, simplifying biomarker discovery and validation in oncology for clinicians and basic scientists, and bridging a critical gap in translational cancer research.

bioinformatics↗

bioRxiv2024

The Identification Markers of activated myofibroblast subsets in the Human Lung Fibrosis Ecosystem via integrated omics Analysis

BackgroundThe aberrant remodeling of the extracellular matrix (ECM) is closely associated with lung fibrosis. However, the mechanisms underlying ECM remodeling in pulmonary fibrosis (PF) remain unclear. The advent of single-cell RNA sequencing (scRNA-seq) has provided valuable insights into the diverse phenotypic and functional characteristics of human PF. Nevertheless, the dynamic of ECM remodeling in terms of ECM synthesizing and the potential activating markers of myofibroblasts in the human PF microenvironment still needs to be investigated. MethodsWe performed integrative scRNA-seq analyses on high-fidelity PF data from a public platform by filtering out the low-quality counts and doublets using two doublet prediction methods. Next, we investigated the dynamic of the ECM signature in diverse cells in PF and screened the potential markers of myofibroblasts via fitting a successful polynomial regression model. Finally, the markers of activated myofibroblasts were identified using bulk RNA-seq of pulmonary tissue. ResultsFirst, we depicted the pathogenic landscape and demonstrated the heterogeneity of ECM in PF by integratively analyzing single-cell RNA-seq data, and we hypothesized that myofibroblasts played a significant role in ECM formation. Second, our results successfully displayed the biological dynamic changes of ECM and investigated the 73 positive correlated genes of myofibroblasts in PF via a polynomial regression model. Then, the bulk RNA-seq results further identified eight new activating markers of myofibroblasts, such as MFAP2, MXRA5, and LRRC17 via transcriptomic signature, correlation and ROC scores. Finally, the results of cell-cell interaction indicated that myeloid cells may be involved in regulating ECM remodeling through proliferation mediated by myofibroblasts that secrete POSTN, suggesting that ECM remodeling in PF is a complex and multi-participated process. ConclusionsIn summary, we provided insights into the contributions of ECM in human PF by integrative analysis and highlighted potential clinical utilities of myofibroblast subsets as therapeutic targets.

bioinformatics↗

bioRxiv2024

A pan-cancer gamma delta T cell repertoire

This report presents the largest collection of gamma-delta T cell receptor ({gamma}{delta} TCR) reads in human cancer to date, analyzing about 11,000 patient tumor samples across 33 cancer types using the TRUST4 algorithm. Despite {gamma}{delta} T cells being a small fraction of the T cell population, they play a key role in both innate and adaptive immunity. Our comprehensive analysis reveals their significant presence across all cancer types, specifically highlighting the diverse spectrum and clonality patterns of their {gamma}{delta} receptors. This research highlights the complex roles of {gamma}{delta} T cells in tumor tissues and their potential as prognostic biomarkers. We also demonstrate the utility of T cell receptor gamma (TRG) and delta (TRD) gene expression values from standard RNA-seq data. Ultimately, our work establishes a fundamental resource for future tumor-infiltrating {gamma}{delta} T cell research and may facilitate the development of novel {gamma}{delta}-T-cell-based therapeutic strategies. Together, we demonstrate the strong diversity and prognostic potential of {gamma}{delta} T cells in multiple cancer types. HighlightsComprehensive analysis of {gamma}{delta} TCRs from 11,473 tumor samples Significant variability and overall consistency in {gamma}{delta} gene expression and clonotype {gamma}{delta}TCR expression and diversity as prognostic biomarkers across multiple cancers Centralized {gamma}{delta} TCR repertoire database for future therapeutic discovery

genomics↗

bioRxiv2024

Photoactivated SOPP3 enables APEX2-mediated proximity labeling with high spatio-temporal resolution in live cells

Protein interactome characterized via proximity labeling (PL) and proteomic analysis is important for mechanism study in biomedical research. However, exogenous H2O2 required for engineered peroxidase, like APEX2, is cytotoxic, while biotin ligases-based PL have poor temporal resolution. Here, we showed that SOPP3, an engineered photosensitizer, could trigger APEX2 mediated PL within seconds under blue light illumination, without exogenous H2O2 or cytotoxicity. We demonstrated that APEX2 plus photoactivated SOPP3 could catalyze spatially restricted biotinylation at endoplasmic reticulum-mitochondria contact sites and cell-cell interface. Through fusing APEX2 and SOPP3 as a chimeric probe, we showed that APEX2-SOPP3 also works well in multiple subcellular locations, including cell surface. Notably, either APEX2 plus SOPP3, or chimeric APEX2-SOPP3 requires 10 folds lower illumination power, compared to that for light-oxygen-voltage protein alone mediated PL, and has better response to illumination in terms of PL in time course with little cytotoxicity. Thus, this new PL technology paves an avenue to characterize molecular dynamics of key biomedical events with high spatial-temporal resolution, efficiency, and flexible applicability.

molecular biology↗