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Biology subjects

Ma, C.

Publications and source records attributed to Ma, C..

At least 55 records · Page 3Linked to original sources

Munc13-4 mediates tumor immune evasion by regulating the sorting and secretion of PD-L1 via exosomes

Tumor-derived extracellular vesicles primarily carry PD-L1 via exosomes, which interact with PD-1 receptors on T cells, impacting immune responses in the tumor microenvironment and beyond, leading to a more extensive immunosuppressive landscape. However, the mechanisms governing exosomal PD-L1 sorting and secretion remain elusive. In this study, we identified Munc13-4 as a crucial regulator of exosomal PD-L1 sorting and secretion. Deletion of Munc13-4 in breast tumors enhances T cell-mediated anti-tumor immunity, suppresses tumor growth, and improves the efficacy of immune checkpoint inhibitors. Our results illustrate how Munc13-4 collaborates with HRS, Rab27, and SNAREs to facilitate PD-L1 sorting and secretion via exosomes. The cryo-EM structure of the Munc13-4-Rab27a complex provide new insights into its role in exosome secretion. Importantly, we discovered that Munc13-4 has a novel role in sorting PD-L1 onto exosomes, which relies on the formation of a ternary complex with PD-L1 and HRS. In addition, IFN{gamma} stimulation modifies Munc13-4 and HRS, establishing a dynamic regulatory mechanism that enables tumor cells to adapt to immune pressure by modulating PD-L1 sorting. Using a specially designed peptide to disrupt the Munc13-4-PD-L1 interaction and impede PD-L1 sorting significantly enhances anti-tumor immunity and slows tumor growth in vivo. These results highlight the potential of targeting the Munc13-4-PD-L1 axis to suppress tumor immune evasion.

cell biology↗

deepTFBS: Improving within- and cross-species prediction of transcription factor binding using deep multi-task and transfer learning

The precise prediction of transcription factor binding sites (TFBSs) is crucial in understanding gene regulation. In this study, we present deepTFBS, a comprehensive deep learning (DL) framework that builds a robust DNA language model of TF binding grammar for accurately predicting TFBSs within and across plant species. Taking advantages of multi-task DL and transfer learning, deepTFBS is capable of leveraging the knowledge learned from large-scale TF binding profiles to enhance the prediction of TFBSs under small-sample training and cross-species prediction tasks. When tested using available information on 359 Arabidopsis TFs, deepTFBS outperformed previously described prediction strategies, including position weight matrix, deepSEA and DanQ, with a 244.49%, 49.15%, and 23.32% improvement of the area under the precision-recall curve (PRAUC), respectively. Further cross-species prediction of TFBS in wheat showed that deepTFBS yielded a significant PRAUC improvement of 30.6% over these three baseline models. deepTFBS can also utilize information from gene conservation and binding motifs, enabling efficient TFBS prediction in species where experimental data availability is limited. A case study, focusing on the WUSCHEL (WUS) transcription factor, illustrated the potential use of deepTFBS in cross-species applications, in our example between Arabidopsis and wheat. deepTFBS is publically available at https://github.com/cma2015/deepTFBS. One sentence summaryThe high-performing deep learning framework deepTFBS can flexibly perform within- and cross-species prediction of TF binding, transferring the transcription regulation from model to non-model species.

bioinformatics↗

Scalability of Random Forest in Myoelectric Control

ObjectiveMyoelectric control systems translate electromyographic (EMG) signals into control commands, enabling immersive human-robot interactions in the real world and the Metaverse. The variability of EMG due to various confounding factors leads to significant performance degradation. Such variability can be mitigated by training a highly generalisable but massively parameterized deep neural network, which can be effectively scaled using a vast dataset. We aim to find an alternative simple, explainable, efficient and parallelisable model, which can flexibly scale up with a larger dataset and scale down to reduce model size, will significantly facilitate the practical implementation of myoelectric control. ApproachIn this work, we discuss the scalability of a random forest (RF) for myoelectric control. We show how to scale an RF up and down during the process of pre-training, fine-tuning, and automatic self-calibration. The effects of diverse factors such as bootstrapping, decision tree editing (pre-training, pruning, grafting, appending), and the size of training data are systematically studied using EMG data from 106 participants including both low- and high-density electrodes. Main resultsWe examined several factors that affect the size and accuracy of the model. The best solution could reduce the size of RF models by{approx} 500 x, with the accuracy reduced by only 1.5%. Importantly, for the first time we report the unique merit of RF that with more EMG electrodes (higher input dimension), the RF model size would be reduced, contrasting all other models. SignificanceAll of these findings unlock the full potential of RF in real-world applications.

bioengineering↗

Structure-based analysis unveils co-origin of LPOR and nitrogenase-like proteins

Structures of nitrogenases, dark-operative protochlorophyllide oxidoreductases, and light-dependent protochlorophyllide oxidoreductases (LPOR) have been resolved. However, their evolutionary relatedness remains elusive. Here, we show, through structural alignment, that all subunits of nitrogenase-like proteins originated from a co-ancestral archaic one-subdomain precursor. LPOR evolved from the BchX/BchY subunits of nitrogenase-like chlorophyllide a oxidoreductase (COR), and the intermediary retinol dehydrogenase through possible genetic recombination. We thus establish previously unknown structural links among key enzymes involved in biological nitrogen-fixation (BNF) and photosynthesis, unraveling structure-guided functional evolution from a single-subunit iron protein to multi-subunit nitrogenase-like COR, and to the single-subunit LPOR for phototrophic metabolism via bacteriochlorophyll, retinal, and chlorophyll. This work also demonstrates structural similarities are imperative for inferring distant origins of functionally divergent proteins, particularly those lacking primary amino-acid sequence identity. Moreover, our findings coupled with AI may be exploited to design innovative light-driven CORs and/or light-utilizing nitrogenases with enhanced efficacy of photosynthesis and BNF. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC="FIGDIR/small/634645v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@9f9a2aorg.highwire.dtl.DTLVardef@4243ecorg.highwire.dtl.DTLVardef@796b4corg.highwire.dtl.DTLVardef@17373da_HPS_FORMAT_FIGEXP M_FIG C_FIG Video abstracthttps://www.youtube.com/watch?v=b0qBE1JMaH0 HighlightsO_LILPOR evolves from BchX and BchY subunits of the nitrogenase-like protein (NGLP) COR C_LIO_LIAll subunits of NGLPs can be traced back to the ancestral one-subdomain precursor C_LIO_LIRetinol dehydrogenase acts as a crucial intermediate in the COR to LPOR evolution C_LIO_LIStructure-based design of LUN is showcased to revolutionize protein engineering C_LI

evolutionary biology↗

DNA Methylation-Based Cell Type Deconvolution Reveals the Distinct Cell Composition in Brain Tumor Microenvironment

BackgroundCentral Nervous System (CNS) tumors have sophisticated tumor microenvironment (TME) with different cell types such as astrocytes, microglia, neurons, vascular endothelial cells and immune cells. These non-cancerous cells orchestrate the brain TME to regulate cancer progression and therapeutic response. This study aimed to develop a cell composition deconvolution method for CNS tumor and to determine the impact of these cell compositions on patients outcomes. MethodsWe identified the cell type-specific CpG loci using the pairwise differential methylation analysis for 13 major cell types in CNS. Using non-negative least squares (NNLS) methods, we established this cell-type deconvolution approach, MDBrainT, for brain tumors. The predictive accuracy of our MDBrainT model was tested in the DNA methylation profiling of the purified cell samples and compared against another algorithm. Cell composition was predicted by MDBrainT in several brain tumor (glioma, ependymoma, medulloblastoma and ATRT) cohorts and the correlation between cell composition and tumor molecular subtypes and patient outcomes was also assessed. ResultsCell type-specific CpG loci for CNS TME was used to build MDBrainT model. Based on these DNA methylation markers, MDBrainT predicted the cell composition in the TME including tumor cells with high accuracy. Endothelial cells were predominately presented in glioblastomas while the percentage of CD8 T cells wassignificantly higher in ATRT. A substantial difference of cell composition was two molecular groups of posterior fossa ependymoma (PFA vs PFB). A higher percentage of cells in TME was usually associated with worse outcomes. ConclusionsMDBrainT is a robust algorithm for cell composition prediction for brain TME. Cell composition in brain TME is distinct across different pathological types and molecular subtypes. Key PointsO_LIMDBrainT is a robust DNA methylation-based deconvolution approach for brain tumor microenvironment (TME). C_LIO_LIDifferent molecular subtypes of brain tumors have distinct cell composition patterns. C_LIO_LICell composition in brain TME informs patients of outcomes. C_LI Importance of this studyDNA methylation is a cell type specific marker that has been utilized for tumor molecular diagnosis, disease progression and therapeutic monitoring. A DNA methylation-based classifier for brain tumors precisely predicts the molecular subtypes but not the cell composition of tumor microenvironment. Brain tumors are a complex cell mixture where tumor microenvironment is critical for tumorigenesis and therapeutic resistance. Here, we developed a novel deconvolution approach (MDBrainT) to predict cell composition for brain tumors. Our model has revealed the heterogeneity of cell composition between tumor types. In addition, tumors with different molecular subtypes have distinct cell composition. Cell percentage in TME also informs patients of outcomes. The tumor microenvironment including cell composition of each patient may direct the different regimen of precision medicine.

cancer biology↗

ca-circSCN8A promotes HPASMCs ferroptosis via LLPS initiated R-Loop

BACKGROUNDFerroptosis has been implicated in pulmonary hypertension. Chromatin-associated RNAs are linked to ferroptosis. However, their role in pulmonary vascular ferroptosis in PH is unexplored. METHODSBioinformatics, Sanger sequencing, RNase R and others were employed to identify differentially higher expression of ca-circSCN8A. Functional gain and loss assays were employed to unveil the role of ca-circSCN8A in hypoxia-induced redox-dependent ferroptosis in HPASMCs and PH mice model. Interaction between ca-circSCN8A and FUS was detected via RNA immunoprecipitation and pull-down assays. FRAP, CHIRP-qPCR, MDA, GSH and GSSG were conducted to explore the potential molecular mechanism. RESULTSca-circSCN8A was firstly identified and confirmed to be upregulated in PH. Upregulation of ca-circSCN8A can promote hypoxia induced ferroptosis in HPASMCs. Under hypoxic conditions, ca-circSCN8A promoted the lactylation of FUS by recruiting EP300, leading to formation of LLPS of ca-circSCN8A/FUS/EP300. LLPS maintained the stability of the R-Loop formed by ca-circSCN8A and ferroptosis related-gene SLC7A11 promoter that inhibit the transcription of the SLC7A11 gene, further result in the disruption of the redox balance and causes ferroptosis in HPASMCs. CONCLUSIONSca-circSCN8A recruits EP300 to promote the lactylation of FUS, thereby promoting LLPS formation of ca-circSCN8A/EP300/FUS. Further, the LLPS motivates ca-circSCN8A to form R-loop with its non-host SLC7A11 and participating in the regulation of hypoxic induced HPASMCs redox-dependent ferroptosis. This is the first confirmation that circRNAs forming R-loops with non-host genes regulated by LLPS. Our findings indicated that ca-circSCN8A plays an important role in ferroptosis of hypoxic induced HPASMCs and may be a potential target for the treatment of PH.

molecular biology↗

Infectivity of a pathogenicity-attenuated Chlamydia muridarum mutant in the genital tract

A C. muridarum mutant designated as intrOv was evaluated as an intracellular Oral vaccine vector because it can induce protection in the genital tract following oral inoculation but does not elicit genital pathology following intravaginal infection. However, the mechanism of intrOvs attenuation is unclear. Here we report that few live organisms were recovered from vaginal swabs during the early stage of intrOv intravaginal infection in mice. At a low inoculating dose, an isogenic wild-type control strain established a productive infection, while intrOv failed to do so. Although a higher inoculating dose allowed intrOv and its control to productively infect mice, fewer live intrOv than the control organisms were recovered from the lower genital tract tissues on day 3 post-infection. By day 7, animals infected with intrOv or the control shed similar numbers of live organisms, suggesting the intrOvs deficiency on day 3 was transient. Consistently, intrOv reduced invasion of epithelial cells but maintained as robust intracellular replication as its control. Our results correlate intrOvs delay in infecting the lower genital tissues and reduction in invading epithelial cells with its attenuation in genital pathogenicity, laying the foundation for further revealing the mechanisms of the intrOvs attenuation in pathogenicity during genital tract infection.

microbiology↗

Dynamic p21-dependency during quiescence arrest unveiled by a rapid p21 depletion system

Stress- or developmentally-induced signals can trigger G0/G1 cell cycle arrest through the upregulation of p21, a key inhibitor that halts proliferation. While p21 is widely recognized as essential for establishing this arrest, its degradation is generally assumed to be a prerequisite for the exit from arrest and cell cycle re-entry. Using a rapid p21 degradation system that allows for both endogenous p21 tracking and controlled depletion, we uncovered an extended role for p21 during the exit from G0/G1 arrest. Our results showed that removal of the arrest inducing signals did not lead to an immediate decline of p21 during the exit process; instead, p21 levels continued to maintain for a period before its gradual down-regulation. Importantly, premature depletion of p21 during this process weakened the capacity of cell cycle re-entry, particularly in cells with high levels of pre-existent p21. We found that during the release from arrest, cells with high levels of pre-existent p21 but a premature p21 depletion exhibited reduced capacity to restore KRAS/ERK activity, and supplementing KRAS/ERK activity rescued the failure of cell cycle re-entry in these cells. These findings reveal a previously unappreciated function for p21 during the exit from G0/G1 arrest, aside and distinct from its role in initiating the arrest. This new paradigm extends across multiple cell lines and stress-induced arrest contexts, offering a new framework for understanding p21 function in response to anticancer therapies and in development.

cell biology↗

Two distinct structural variants involving EDN3 cause hyperpigmentation in chicken

Phenotypic diversity and its genetic basis are central questions in biology, with domesticated animals offering valuable insights due to their rapid evolution the last 10,000 years. In chickens, fibromelanosis (FM) is a striking pigmentation phenotype characterized by hyperpigmentation. A previous study identified a complex structural variant causing upregulated expression of the Endothelin 3 (EDN3) gene. However, the detailed structural arrangement and functional consequences of the variant remained unclear. In this study, we conducted a comprehensive genomic survey of 692 FM chickens representing 55 breeds and uncovered two distinct structural variants causing the FM phenotype: FM*A, the previously reported complex rearrangement involving the EDN3 locus1, and FM*B, a tandem duplication of a 16 kb region upstream of EDN3. We demonstrate that both structural variants (SVs) significantly upregulate EDN3 expression, with FM*B associated with even higher expression than FM*A. A luciferase reporter assays showed that the 16 kb region in FM*B contains powerful enhancers and the copy number expansion of this element is a likely explanation for EDN3 upregulation and hyperpigmentation. Furthermore, our analysis of linkage disequilibrium patterns allowed us to resolve the complex arrangement of duplications and inversion on the FM*A haplotype.

genomics↗

Coordination of flux-related leaf and root traits impacts forest community assembly

Understanding the functions and coordination of plant traits is critical for predicting how diverse species respond to climate change. According to hydraulic and economic theories, leaves and roots--key organs for resource acquisition--are expected to function in coordination, such that species with faster resource utilization would possess leaf and root traits that facilitate rapid carbon, nutrient, and water uptake and fluxes. However, there has been limited evidence supporting leaf-root trait coordination and a role for that coordination on community structure. Here, we measured 13 leaf and root functional traits for 101 woody species from six tropical and subtropical forests, and assessed coordination and its association with community dominance. Hydraulic traits, such as leaf vein density and root vessel density, were coordinated between organs and showed compensation trade-offs between traits within organs, such as, leaf vein density and diameter. Economic traits relating to composition, such as nitrogen concentration, were coordinated between organs, whereas economic structural traits were decoupled, such as leaf mass per area and specific root length. Overall, hydraulic traits and economics traits were partially independent. The coordination of flux-related leaf and root traits was associated with ectomycorrhizal symbiosis and with dominance within the community. These findings indicate how trait organization within and across organs contributes to optimal whole plant function, with implications for performance in natural communities.

ecology↗

Regulating of Koisio technology-produced fluid on Vascular Adventitial Interstitial Fluid flow and its Effect on heart rate by delivering Esmolol

Acupoint-originated interstitial fluid (ISF) circulatory network along the vasculature has been demonstrated to play a role as an extravascular drug delivery pathway. We aim to reveal the regulation of Koisio technology-produced fluid (KF), which is rich in Ultra-small Particle Size Nanobubbles (UsNBs), on vascular adventitial ISF flow and its Effect on heart rate by delivering Esmolol. In animal experiments, using real-time fluorescent imaging technology, it was found that: when normal saline-fluorescent liquid was given at Kunlun acupoint, the velocity of the adventitial ISF along the femoral vein was measured to be about 600 m/sec, and the width of the tunica ISF channel on the adventitia surface of the femoral vein was about 210m; when KF-fluorescent liquid was injected into the subcutaneous tissue of Kunlun acupoint, the velocity of the adventitia ISF slowed down by about 24% compared with before; the width of the tunica ISF channel on the adventitia surface of the femoral vein increased by about 35% compared with before; When 150L of KF with high-concentration UsNBs was injected into Kunlun acupoint, it was observed that the adventitial ISF flow velocity was decreased by 43%, and recovered after 30 minutes. Administration of normal saline-esmolol solution at Kunlun acupoint caused the heart rate to drop from 410 bpm to 380 bpm, a decrease of 7.3%, which continued for 5 minutes before recovery. Administration of KF-esmolol solution at Kunlun acupoint caused the heart rate to drop from 410 bpm to 371 bpm, a decrease of 9.5%, which continued for 15 minutes before recovery. Thus, acupoint injection of KF can regulate the velocity of the adventitia ISF flow along the femoral vein and increase the width of the tunica ISF channel. These results may reveal a new mechanism of the physiological effect of Koisio drinking water rich in ultra-small particle size nanobubbles. KF may not only regulate the acupoint-originated ISF circulatory system, but also play a role in adventitial drug delivery, nutrient supply, and waste removal.

physiology↗

Deep Learning with Evolutionary Scale Modeling to discover Antibiotic-Resistance Drug against Klebsiella Pneumoniae

The development of effective antibiotics is crucial in combating antibiotic-resistant pathogens such as Klebsiella pneumoniae (KP). This study utilizes deep learning, specifically Evolutionary Scale Modeling (ESM), to identify potential drug candidates. By analyzing molecular similarities between known drugs and KP strains, we aim to accelerate the discovery of new treatments and reduce the risks associated with clinical trials. This approach may shed new lights in the field of drug repositioning.

bioinformatics↗

OsMORF protein selectively promotes the dual-localized RNA editing factor OsPGL1 binding to its target RNA

Post-transcriptional RNA editing plays a key regulatory role and serves as a genetic information proofreading mechanism. In flowering plants, RNA editing typically involves the removal of amino groups from cytidine to produce uridine in both plastids and mitochondria. In our previous work, we identified OsPGL1 as a rare organelle editing factor that regulates both mitochondrial and chloroplast RNA in rice. This protein mediates RNA editing and is associated with several OsMORFs. We speculated that they may form editing complex to regulate editing events, but we are still unclear about the detailed mechanism between OsMORF proteins and OsPGL1, as well as their roles in target RNA recognition and binding. In this study, we found that three OsMORFs can significantly promote the binding of OsPGL1 to target RNA in vitro. Notably, OsMORF8 can promote OsPGL1 to form a homologous dimer, thereby enhancing RNA binding to a greater extent. The E and DYW motifs do not affect the role of MORF proteins in RNA editing events, ruling out the potential influence of these two special motifs. In addition, we predicted a series of supercomplex structures of OsPGL1, the OsPGL1-RNA ligand complex, the OsPGL1-OsMORF2-OsMORF8-OsMORF9 complex, and the OsPGL1-OsMORF2-OsMORF8-OsMORF9-RNA complex. We determined that the conformational changes and newly added positively charged surface caused by OsMORF on OsPGL1 are the main reasons for MORF to promote the binding of OsPGL1 to RNA. Based on some new discoveries, we have expanded the RNA editing complex model, which greatly enhances our understanding of plant RNA editing complexes. Short summaryPPRs and MORFs are two kinds of RNA editing factors, both can mediate organelle RNA editing, the difference between them is that PPR can directly bind target RNA, MORF does not directly bind RNA, but can independently or assist PPR in performing RNA editing. Function of MORF protein in post-transcriptional processing is not clear, our study verifies the function of MORFs in the process of PPR binding RNA through molecular biology. We also analyzed the interaction network between PPR-MORF-RNA from the perspective of structural biology.

plant biology↗

Plug-and-Play Myoelectric Control via a Self-Calibrating Random Forest Common Model

ObjectiveElectromyographic (EMG) signals show large variabilities over time due to factors such as electrode shifting, user behaviour variations, etc., substantially degrading the performance of myoelectric control models in long-term use. Previously one-time model calibration was usually required each time before usage. However, the EMG characteristics could change even within a short period of time. Our objective is to develop a self-calibrating model, with an automatic and unsupervised self-calibration mechanism. ApproachWe developed a computationally efficient random forest (RF) common model, which can (1) be pre-trained and easily adapt to a new user via one-shot calibration, and (2) keep calibrating itself once in a while by boosting the RF with new decision trees trained on pseudo-labels of testing samples in a data buffer. Main resultsOur model has been validated in both offline and real-time, both open and closed-loop, both intra-day and long-term (up to 5 weeks) experiments. We tested this approach with data from 66 able-bodied participants. We also explored the effects of bidirectional user-model co-adaption in closed-loop experiments. We found that the self-calibrating model could gradually improve its performance in long-term use. With visual feedback, users will also adapt to the dynamic model meanwhile learn to perform hand gestures with significantly lower EMG amplitudes (less muscle effort). SignificanceOur random forest-approach provides a new alternative built on simple decision tree for myoelectric control, which is explainable, computationally efficient, and requires minimal data for model calibration. Source codes are avaiable at: https://github.com/MoveR-Digital-Health-and-Care-Hub/self-calibrating-rf

neuroscience↗

SLB-msSIM: a spectral library-based multiplex segmented SIM platform for single-cell proteomic analysis

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies.

systems biology↗

Advanced deep-tissue imaging and manipulation enabled by biliverdin reductase knockout.

We developed near-infrared (NIR) photoacoustic and fluorescence probes, as well as optogenetic tools from bacteriophytochromes, and enhanced their performance using biliverdin reductase-A knock-out model (Blvra-/-). Blvra-/- elevates endogenous heme-derived biliverdin chromophore for bacteriophytochrome-derived NIR constructs. Consequently, light-controlled transcription with IsPadC-based optogenetic tool improved up to 25-fold compared to wild-type cells, with 100-fold activation in Blvra-/- neurons. In vivo, light-induced insulin production in Blvra-/- reduced blood glucose in diabetes by [~]60%, indicating high potential for optogenetic therapy. Using 3D photoacoustic, ultrasound, and two-photon fluorescence imaging, we overcame depth limitations of recording NIR probes. We achieved simultaneous photoacoustic imaging of DrBphP in neurons and super-resolution ultrasound localization microscopy of blood vessels [~]7 mm deep in the brain, with intact scalp and skull. Two-photon microscopy provided cell-level resolution of miRFP720-expressing neurons [~]2.2 mm deep. Blvra-/- significantly enhances efficacy of biliverdin-dependent NIR systems, making it promising platform for interrogation and manipulation of biological processes.

cell biology↗

m6A-mediated epi-transcriptomic dysregulation underlies synaptic dysfunction in fragile X syndrome

Fragile X syndrome (FXS), the leading genetic cause of intellectual disability, arises from FMR1 gene silencing and loss of the FMRP protein. N6-methyladenosine (m6A) is a prevalent mRNA modification essential for post-transcriptional regulation. FMRP is known to bind to and regulate the stability of m6A-containing transcripts. However, how loss of FMRP impacts on transcriptome-wide m6A modifications in FXS patients remains unknown. To answer this question, we generated cortical neurons differentiated from induced pluripotent stem cells (iPSC) derived from healthy subjects and FXS patients. In electrophysiology recordings, we validated that synaptic and neuronal network defects in iPSC-derived FXS neurons corresponded to the clinical EEG data of the patients from which the corresponding iPSC line was derived. In analysis of transcriptome-wide methylation, we show that FMRP deficiency led to increased translation of m6A writers, resulting in hypermethylation that primarily affecting synapse-associated transcripts and increased mRNA decay. Conversely, in the presence of an m6A writer inhibitor, synaptic defects in FXS neurons were rescued. Taken together, our findings uncover that an FMRP-dependent epi-transcriptomic mechanism contributes to FXS pathogenesis by disrupting m6A modifications in FXS, suggesting a promising avenue for m6A- targeted therapies.

neuroscience↗

A CXCR4 partial agonist improves immunotherapy by targeting polymorphonuclear myeloid-derived suppressor cells and cancer-driven granulopoiesis

Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) are pathologically activated neutrophils that potently impair immunotherapy responses. The chemokine receptor CXCR4, a central regulator of hematopoiesis, represents an attractive PMN-MDSC target1. Here, we fused a secreted CXCR4 partial agonist TFF2 to mouse serum albumin (MSA) and demonstrated that TFF2-MSA peptide synergized with anti-PD-1 to induce tumor regression or eradication, inhibited distant metastases, and prolonged survival in multiple gastric cancer (GC) models. Using histidine decarboxylase (Hdc)-GFP transgenic mice to track PMN-MDSC in vivo, we found TFF2-MSA selectively reduced the immunosuppressive Hdc-GFP+ CXCR4hi tumor PMN-MDSCs while preserving proinflammatory neutrophils, thereby boosting CD8+ T cell-mediated anti-tumor response together with anti-PD-1. Furthermore, TFF2-MSA systemically reduced PMN-MDSCs and bone marrow granulopoiesis. In contrast, CXCR4 antagonism plus anti-PD-1 failed to provide a similar therapeutic benefit. In GC patients, expanded PMN-MDSCs containing a prominent CXCR4+LOX-1+ subset are inversely correlated with the TFF2 level and CD8+ T cells in circulation. Collectively, our studies introduce a strategy of using CXCR4 partial agonism to restore anti-PD-1 sensitivity in GC by targeting PMN-MDSCs and granulopoiesis.

cancer biology↗