Biology subjects

Zheng, D.

Publications and source records attributed to Zheng, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways

Osteosarcoma (OS) is the most common primary pediatric bone malignancy. One promising new therapeutic target is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase responsible for ubiquitination and proteasome degradation of substrate p27, thus driving cellular proliferation. We have shown previously that knockout of Skp2 in an immunocompetent transgenic mouse model of OS improved survival, drove apoptosis, and induced tumor inflammation. Here, we applied single-cell RNA-sequencing (scRNA-seq) to study primary OS tumors derived from Osx-Cre driven conditional knockout of Rb1 and Trp53. We showed that murine OS models recapitulate the tumor heterogeneity and microenvironment complexity observed in patient tumors. We further compared this model with OS models with functional disruption of Skp2: one with Skp2 knockout and the other with the Skp2-p27 interaction disrupted (resulting in p27 overexpression). We found reduction of T cell exhaustion and upregulation of interferon activation, along with evidence of replicative and endoplasmic reticulum-related stress in the Skp2 disruption models, and showed that interferon induction was correlated with improved survival in OS patients. Additionally, our scRNA-seq analysis uncovered decreased activities of metastasis-related gene signatures in the Skp2-disrupted OS, which we validated by observation of a strong reduction in lung metastasis in the Skp2 knockout mice. Finally, we report several potential mechanisms of escape from targeting Skp2 in OS, including upregulation of Myc targets, DNA copy number amplification and overexpression of alternative E3 ligase genes, and potential alternative lineage activation. These mechanistic insights into OS tumor biology and Skp2 function suggest novel targets for new, synergistic therapies, while the data and our comprehensive analysis may serve as a public resource for further big data-driven OS research.

cancer biology↗

bioRxiv2024

Light regulates widespread plant alternative polyadenylation through the chloroplast

Transcription of eukaryotic protein-coding genes generates immature mRNAs that are subjected to a series of processing events, including capping, splicing, cleavage and polyadenylation (CPA) and chemical modifications of bases. Alternative polyadenylation (APA) greatly contributes to mRNA diversity in the cell. By determining the length of the 3 untranslated region, APA generates transcripts with different regulatory elements, such as miRNA and RBP binding sites, which can influence mRNA stability, turnover and translation. In the model plant Arabidopsis thaliana, APA is involved in the control of seed dormancy and flowering. In view of the physiological importance of APA in plants, we decided to investigate the effects of light/dark conditions and compare the underlying mechanisms to those elucidated for alternative splicing (AS). We found that light controls APA in approximately 30% of Arabidopsis genes. Similar to AS, the effect of light on APA requires functional chloroplasts, is not affected in mutants of the phytochrome and cryptochrome photoreceptor pathways and is observed in roots only when the communication with the photosynthetic tissues is not interrupted. Furthermore, mitochondrial activity is necessary for the effect of light in roots but not in shoots. However, unlike AS, coupling with transcriptional elongation does not seem to be involved since light-dependent APA regulation is neither abolished in mutants of the TFIIS transcript elongation factor nor universally affected by chromatin relaxation caused by the histone deacetylase inhibition. Instead, regulation seems to be linked to light-elicited changes in the abundance of constitutive CPA factors, also mediated by the chloroplast.

molecular biology↗

bioRxiv2024

scDAPP: a comprehensive single-cell transcriptomics analysis pipeline optimized for cross-group comparison

Single-cell transcriptomics profiling has increasingly been used to evaluate cross-group differences in cell population and cell-type gene expression. This often leads to large datasets with complex experimental designs that need advanced comparative analysis. Concurrently, bioinformatics software and analytic approaches also become more diverse and constantly undergo improvement. Thus, there is an increased need for automated and standardized data processing and analysis pipelines, which should be efficient and flexible too. To address these, we develop the single-cell Differential Analysis and Processing Pipeline (scDAPP), a R-based workflow for comparative analysis of single cell (or nucleus) transcriptomic data between two or more groups and at the levels of single cells or "pseudobulking" samples. The pipeline automates many steps of pre-processing using data-learnt parameters, uses previously benchmarked software, and generates comprehensive intermediate data and final results that are valuable for both beginners and experts of scRNA-seq analysis. Moreover, the analytic reports, augmented by extensive data visualization, increase the transparency of computational analysis and parameter choices, while facilitate users to go seamlessly from raw data to biological interpretation. Availability and ImplementationscDAPP is freely available for non-commercial usage as an R package under the MIT license. Source code, documentation and sample data are available at the GitHub (https://github.com/bioinfoDZ/scDAPP).

bioinformatics↗

bioRxiv2024

Lineage commitment pathways epigenetically oppose oncogenic Gαq/11-YAP signaling in dormant disseminated uveal melanoma

Uveal melanoma (UM) can remain in clinical dormancy for decades only to later produce lethal metastases. Using Gq/11mut/BAP1wt UM xenograft models and human metastatic samples, we identified NR2F1 as a key inducer of UM disseminated cancer cell (DCC) dormancy. Dormant UM DCCs upregulate NR2F1, neural crest genes and, along with suppression of proliferation programs, NR2F1 silences YAP1/TEAD1 transcription by altering histone H3 activation marks. YAP1 can reciprocally repress NR2F1, but inhibiting Gq/11 signaling or activating NR2F1 can arrest UM growth. NR2F1 knockout led to dormant DCC awakening and liver metastatic growth. NR2F1 and YAP1 inverse expression was confirmed in human livers carrying UM solitary, small DCC clusters as well as large metastases. Intriguingly, RNA-seq and Cut&Run analysis revealed that NR2F1 short-circuits oncogene signaling by repressing multiple G-protein signaling components. Our work provides previously unrecognized mechanistic insight into UM DCC dormancy and potential pathways for interception. Statement of significanceNR2F1 epigenetically suppresses genes associated with G-protein signaling, cell cycle, and YAP1/TEAD1 pathways, inducing dormancy in uveal melanoma (UM) disseminated cancer cells. This study unveils novel markers for UM dormancy and reactivation, positioning NR2F1 as a promising target for intercepting residual and UM metastatic disease.

cancer biology↗

bioRxiv2024

Facilitate integrated analysis of single cell multiomic data by binarizing gene expression values

The identity of a cell type can be revealed by its transcriptome and epigenome profiles, both of which can be in flux temporally and spatially, leading to distinct cell states or subtypes. The popular and standard workflow for single cell RNA-seq (scRNA-seq) data analysis applies feature selection, dimensional reduction, and clustering on the gene expression values quantified by read counts, but alternative approaches using a simple classification of a gene to "on" and "off" (i.e., binarization of the gene expression) has been proposed for classifying cells and other downstream analyses. Here, we demonstrate that a direct concatenation of the binarized scRNA-seq data and the standard single cell ATAC-seq data is sufficient and effective for integrated clustering analysis, after applying term-frequency-inverse document frequency (TF-IDF) and single value decomposition (also called latent semantic indexing, LSI) algorithms to the combined data, when the two modalities of omic data are collected using paired multiomic technology. This proposed approach avoids the need for converting scATAC-seq data to gene activity scores for combined analysis and furthermore enables a direct investigation into the contribution of each data type to resolving cell type identity.

bioinformatics↗

bioRxiv2024

Simulating Colloid Motion in Spinning Suspension: Internal Dynamics in Orbital Shaker

Colloid suspensions in the form of mammalian or bacterial cell mixtures in orbital shakers are commonly encountered in biomedical research. An understanding of particle motion in these conditions would provide insight into bulk colloid behavior and distribution under short and long timeframes. Such data can be used to supplement and clarify existing concepts of biological phenomena encountered in the laboratory setting. It can also aid biomedical researchers in experiment design and data interpretation. We present a MATLAB based simulation of colloid motion under rotary agitation. Our simulation setup is modular and therefore designed to act as a scaffold that can be customized to simulate different mammalian, bacterial, or particle properties in liquid suspension.

biophysics↗

bioRxiv2023

Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs

BackgroundBy resolving cellular heterogeneity in a biological sample, single cell RNA sequencing (scRNA-seq) can detect gene expression and its dynamics in different cell types. Its application to time-series samples can thus identify temporal genetic programs active in different cell types, for example, immune cells responses to viral infection. However, current scRNA-seq analysis need improvement. Two issues are related to data generation. One is that the number of genes detected in each cell is relatively low especially when currently popular dropseq-based technology is used for analyzing thousands of cells or more. The other is the lack of sufficient replicates (often 1-2) due to high cost of library preparation and sequencing. The third issue lies in the data analysis --usage of individual cells as independent sampling data points leads to inflated statistics. MethodsTo address these issues, we explore a new data analysis framework, specifically whether "metacells" that are carefully constructed to maintain cellular heterogeneity within individual cell types (or clusters) can be used as "replicates" for statistical methods requiring multiple replicates. Toward this, we applied SEACells to a time-series scRNA-seq dataset from peripheral blood mononuclear cells (PBMCs) after SARS-Cov-2 infection to construct metacells, which were then used in maSigPro for quadratic regression to find significantly differentially expressed genes (DEGs) over time, followed by clustering analysis of the expression velocity trends. ResultsWe found that metacells generated using the SEACells algorithm retained greater between-cell variance and produced more biologically meaningful results compared to metacells generated from random cells. Quadratic regression revealed significant DEGs through time that have been previously annotated in the SARS-CoV2 infection response pathway. It also identified significant genes that have not been annotated in this pathway, which were compared to baseline expression and showed unique expression patterns through time. ConclusionsThe results demonstrated that this strategy could overcome the limitation of 1-2 replicates, as it correctly identified the known ISG15 interferon response program in almost all PBMC cell types. Its application further led to the uncovering of additional and more cell type-specific gene expression programs that potentially modulate different levels of host response after infection.

bioinformatics↗

bioRxiv2023

Liver Protects Cytoarchitecture, Neuron Viability and Electrocortical Activity in Post-Cardiac Arrest Brain Injury

BACKGROUNDBrain injury is the major reason for patient deaths in victims who survive after cardiac arrest. Clinical studies have shown that the presence of hypoxic hepatitis and pre-cardiac arrest liver disease is associated with increased mortality and inferior neurological recovery. However, how the liver might impact the pathogenesis of post-cardiac arrest is still unknown. METHODSAn in vivo global cerebral ischemia model was established to assess how simultaneous liver ischemia affected the recovery of brain ischemic injury. In addition, an ex vivo brain normothermic machine perfusion (NMP) model was established to evaluate how addition of a functioning liver might impact the circulation, cytoarchitecture, neuron viability and electrocortical activity of the reperfused brain post-cardiac arrest. RESULTSIn the in vivo model, we observed a larger infarct area in the frontal lobe, elevated tissue injury scores in the CA1 region, as well as increased intravascular immune cell adhesion in the reperfused brains with hepatic ischemia, compared to those without simultaneous hepatic ischemia. The results of the ex vivo model demonstrated that the addition of a functioning liver to the brain NMP circuit significantly reduced post-cardiac arrest brain injury, increased neuronal viability and improved electrocortical activity. Furthermore, we observed significant alterations in gene expressions and metabolites in the presence or absence of hepatic ischemia. CONCLUSIONSOur research highlights the crucial role of the liver in the pathogenesis of post-cardiac arrest brain injury. These findings shed lights on a cardio-pulmonary-hepatic brain resuscitation strategy for patients with cardiac arrest.

neuroscience↗

bioRxiv2023

Trojan horse virus delivering CRISPR-AsCas12f1 controls plant bacterial wilt caused by Ralstonia solanacearum

Plant bacterial wilt caused by the Ralstonia solanacearum species complex results in huge food and economic losses. Accordingly, the development of an effective control method for this disease is urgently required. Traditional lytic phage biocontrol methods have inherent limitations. However, filamentous phages, which do not lyse host bacteria and exert minimal burden, offer a potential solution. A filamentous phage RSCq that infects R. solanacearum was isolated in this study through genome mining. We constructed engineered filamentous phages based on RSCq by employing our proposed approach with a wide applicability to non-model phages, enabling the infection of R. solanacearum in medium and soil and delivering exogenous genes into bacterial cells. Similar to the Greek soldiers hidden within the Trojan horse, CRISPR-AsCas12f1 gene editing system that targets the key virulence regulator gene hrpB was implanted into the engineered phage, generating the engineered phage RSCqCRISPR-Cas. Our findings demonstrated that RSCqCRISPR-Cas could disarm the key "weapon", hrpB, of R. solanacearum, in medium and in plants. Remarkably, pretreatment with RSCqCRISPR-Cas significantly controlled tobacco bacterial wilt, highlighting the potential of engineered filamentous phages as promising biocontrol agents against plant bacterial wilt and other bacterial diseases.

microbiology↗

bioRxiv2023

Addressing preferred orientation in single-particle cryo-EM through AI-generated auxiliary particles.

The single-particle cryo-EM field faces the persistent challenge of preferred orientation, lacking general computational solutions. We introduce cryoPROS, an AI-based approach designed to address the above issue. By generating the auxiliary particles with a conditional deep generative model, cryoPROS addresses the intrinsic bias in orientation estimation for the observed particles. We effectively employed cryoPROS in the cryo-EM single particle analysis of the hemagglutinin trimer, showing the ability to restore the near-atomic resolution structure on non-tilt data. Moreover, the enhanced version named cryoPROS-MP significantly improves the resolution of the membrane protein NaX using the no-tilted data that contains the effects of micelles. Compared to the classical approaches, cryoPROS does not need special experimental or image acquisition techniques, providing a purely computational yet effective solution for the preferred orientation problem. Finally, we conduct extensive experiments that establish the low risk of model bias and the high robustness of cryoPROS.

biophysics↗

bioRxiv2023

Molecular and network disruptions in neurodevelopment uncovered by single cell transcriptomics analysis of CHD8 heterozygous cerebral organoids

About 100 genes have been associated with significantly increased risks of autism spectrum disorders (ASD) with an estimate of [~]1000 genes that may be involved. The new challenge now is to investigate the molecular and cellular functions of these genes during neural and brain development, and then even more challenging, to link the altered molecular and cellular phenotypes to the ASD clinical manifestations. In this study, we use single cell RNA-seq analysis to study one of the top risk gene, CHD8, in cerebral organoids, which models early neural development. We identify 21 cell clusters in the organoid samples, representing non-neuronal cells, neural progenitors, and early differentiating neurons at the start of neural cell fate commitment. Comparisons of the cells with one copy of the CHD8 knockout and their isogenic controls uncover thousands of differentially expressed genes, which are enriched with function related to neural and brain development, with genes and pathways previously implicated in ASD, but surprisingly not for Schizophrenia and intellectual disability risk genes. The comparisons also find cell composition changes, indicating potential altered neural differential trajectories upon CHD8 reduction. Moreover, we find that cell-cell communications are affected in the CHD8 knockout organoids, including the interactions between neural and glial cells. Taken together, our results provide new data for understanding CHD8 functions in the early stages of neural lineage development and interaction.

genomics↗

bioRxiv2023

CodonBERT: Large Language Models for mRNA Design and Optimization

AO_SCPLOWBSTRACTC_SCPLOWmRNA based vaccines and therapeutics are gaining popularity and usage across a wide range of conditions. One of the critical issues when designing such mRNAs is sequence optimization. Even small proteins or peptides can be encoded by an enormously large number of mRNAs. The actual mRNA sequence can have a large impact on several properties including expression, stability, immunogenicity, and more. To enable the selection of an optimal sequence, we developed CodonBERT, a large language model (LLM) for mRNAs. Unlike prior models, CodonBERT uses codons as inputs which enables it to learn better representations. CodonBERT was trained using more than 10 million mRNA sequences from a diverse set of organisms. The resulting model captures important biological concepts. CodonBERT can also be extended to perform prediction tasks for various mRNA properties. CodonBERT outperforms previous mRNA prediction methods including on a new flu vaccine dataset.

bioinformatics↗

bioRxiv2023

Brd4-Nutm1 fusion gene initiates NUT carcinoma in vivo

Nut carcinoma (NC) is an aggressive cancer with no effective treatment. The majority (70%) of NUT carcinoma is associated with chromosome translocation events that lead to the formation of a BRD4::NUTM1 fusion gene. However, because the BRD4::NUTM1 gene is unequivocally cytotoxic when ectopically expressed in cell lines, questions remain on whether the fusion gene can initiate NC. Here, we report the first genetically engineered mouse model (GEMM) for NUT carcinoma recapitulating the human mutation. By stochastically inducing a chromosome translocation mirroring the human event, we demonstrated that the Brd4::Nutm1 fusion gene could induce aggressive carcinomas in mice. The tumors present histopathological and molecular features similar to human NC, with an enrichment of undifferentiated cells. Similar to the reports of human NC incidence, Brd4::Nutm1 can induce NC from a broad range of tissues, demonstrating that its oncogenic potential is not lineage-restricted. The consistent induction of tumors of squamous phenotypes, even from ductal epithelial and mesenchymal tissues, demonstrated a strong reprogramming activity of BRD4::NUTM1. The new mouse model provided a critical preclinical model for NC and opens new opportunities for understanding the oncogenic mechanism and developing new therapies.

cancer biology↗

bioRxiv2023

Targeted inhibition of SCF-SKP2 confers anti-tumor activities resulting in a survival benefit in osteosarcoma

Osteosarcoma(OS) is a highly aggressive bone cancer for which treatment has remained essentially unchanged for decades. Although OS is characterized by extensive genomic heterogeneity and instability, RB1 and TP53 have been shown to be the most commonly inactivated tumor suppressors in OS. We previously generated a mouse model with a double knockout (DKO) of Rb1 and Trp53 within cells of the osteoblastic lineage, which largely recapitulates human OS with nearly complete penetrance. SKP2 is a repression target of pRb and serves as a substrate recruiting subunit of the SCFSKP2 complex. In addition, SKP2 plays a central role in regulating the cell cycle by ubiquitinating and promoting the degradation of p27. We previously reported the DKOAA transgenic model, which harbored a knock-in mutation in p27 that impaired its binding to SKP2. Here, we generated a novel p53-Rb1-SKP2 triple-knockout model (TKO) to examine SKP2 function and its potential as a therapeutic target in OS. First, we observed that OS tumorigenesis was significantly delayed in TKO mice and their overall survival was markedly improved. In addition, the loss of SKP2 also promoted an apoptotic microenvironment and reduced the stemness of DKO tumors. Furthermore, we found that small-molecule inhibitors of SKP2 exhibited anti-tumor activities in vivo and in OS organoids as well as synergistic effects when combined with a standard chemotherapeutic agent. Taken together, our results suggest that SKP2 inhibitors may reduce the stemness plasticity of OS and should be leveraged as next-generation adjuvants in this cancer.

cancer biology↗

bioRxiv2023

SKP2 knockout in Rb1/p53 deficient mouse models of osteosarcoma induces immune infiltration and drives a transcriptional program with a favorable prognosis

PurposeOsteosarcoma (OS) is an aggressive bone malignancy with a poor prognosis. One putative proto-oncogene in OS is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase. We previously demonstrated that SKP2 knockout in murine OS improved survival and delayed tumorigenesis. Here we aim to define the SKP2 drives transcriptional program and its clinical implication in OS. Experimental DesignWe performed RNA-sequencing (RNA-seq) on tumors from a transgenic OS mouse model with conditional Trp53 and Rb1 knockouts in the osteoblast lineage ("DKO": Osx1-Cre;Rb1lox/lox;p53lox/lox) and a triple-knockout model with additional Skp2 germline knockout ("TKO": Osx1-Cre;Rb1lox/lox;p53lox/lox;SKP2-/-). We validated our RNA-seq findings using qPCR and immunohistochemistry. To investigate the clinical implications of our results, we analyzed a human OS patient cohort ("NCI-TARGET OS") with RNA-seq and clinical data. ResultsWe found large differences in gene expression after SKP2 knockout. Strikingly, we observed increased expression of genes related to immune microenvironment infiltration in TKO tumors. We observed significant increases in signature genes for macrophages and to a lesser extent, T cells, B cells and vascular cells. We also uncovered a set of relevant transcription factors that may mediate the changes. In OS patient cohorts, high expression of genes upregulated in TKO was correlated with favorable overall survival, which was largely explained by the macrophage gene signatures. This relationship was further supported by our finding that SKP2 expression was negatively correlated with macrophage infiltration in the NCI-TARGET OS and the TCGA Sarcoma cohort. ConclusionOur findings indicate that SKP2 may mediate immune exclusion from the OS tumor microenvironment, suggesting that SKP2 modulation in OS may induce anti-tumor immune activation. Translational RelevanceOsteosarcoma (OS) is an aggressive bone malignancy. Standard care treatment involving chemotherapy and surgery remains unchanged for decades. OS prognosis remains poor and targeted therapies are critically needed. Immunotherapy failed in clinical trials despite extensive genomic instability, suggesting OS tumors employ active immune exclusion. One putative oncogene in OS is SKP2, which activates cell proliferation. SKP2 is correlated with worse prognosis in patients and knockout of SKP2 improved survival in murine OS. Here, we performed comparative transcriptomic analysis between transgenic OS murine models with SKP2 knockout and controls. We showed that SKP2 knockout dramatic increased immune gene expression largely due to macrophage, and to a lesser extent lymphocytes, infiltration. Interestingly, we found that the increased gene program uncovered from our SKP2 knockout model was correlated with improved survival in OS patients. Our findings indicate a completely new function for SKP2 in mediating immune exclusion in sarcoma and suggest that SKP2 inhibition may lead to improved immune activation and potential treatment.

cancer biology↗

bioRxiv2023

Six3 and Six6 jointly regulate the identities and developmental trajectories of multipotent retinal progenitor cells in the mouse retina

Formation, maintenance, and differentiation of tissue-specific progenitor cells are fundamental tasks during organogenesis. Retinal development is an excellent model for dissecting these processes; mechanisms of retinal differentiation can be harnessed for retinal regeneration toward curing blindness. Using single-cell RNA sequencing of embryonic mouse eye cups in which transcription factor Six3 was conditionally inactivated in peripheral retinas on top of germline deletion of its close paralog Six6 ("DKO"), we identified cell clusters and then inferred developmental trajectories in the integrated dataset. In control retinas, naive retinal progenitor cells had two major trajectories leading to ciliary margin cells and retinal neurons, respectively. The ciliary margin trajectory was directly from naive retinal progenitor cells at G1 phase, and the retinal neuron trajectory was through a neurogenic state marked by Atoh7 expression. Upon Six3 and Six6 dual deficiency, both naive and neurogenic retinal progenitor cells were defective. Ciliary margin differentiation was enhanced, and multi-lineage retinal differentiation was disrupted. An ectopic neuronal trajectory lacking the Atoh7+ state led to ectopic neurons. Differential expression analysis not only confirmed previous phenotype studies but also identified novel candidate genes regulated by Six3/Six6. Six3 and Six6 were jointly required for balancing the opposing gradients of the Fgf and Wnt signaling in the central-peripheral patterning of the eye cups. Taken together, we identify transcriptomes and developmental trajectories jointly regulated by Six3 and Six6, providing deeper insight into molecular mechanisms underlying early retinal differentiation.

developmental biology↗

bioRxiv2023

A single amino acid substitution in MdLAZY1A dominantly impairs shoot gravitropism in Malus

Plant architecture is one of the most important factors that determines crop yield potential and productivity. In apple (Malus), genetic improvement of tree architecture has been challenging due to a long juvenile phase and their growth as complex trees composed of a distinct scion and a rootstock. To better understand the genetic control of apple tree architecture, the dominant weeping growth phenotype was investigated. We report the identification of MdLAZY1A (MD13G1122400) as the genetic determinant underpinning the Weeping (W) locus that largely controls weeping growth in Malus. MdLAZY1A is one of the four paralogs in apple that are most closely related to AtLAZY1 involved in gravitropism in Arabidopsis. The weeping allele (MdLAZY1A-W) contains a single nucleotide mutation c.584T>C that leads to a leucine to proline (L195P) substitution within a predicted transmembrane domain that co-localizes with Region III, one of the five conserved regions in LAZY1-like proteins. Subcellular localization revealed that MdLAZY1A localizes to the plasma membrane and nucleus in plant cells. Over-expressing the weeping allele in apple cultivar Royal Gala (RG) with standard growth habit impaired its gravitropic response and altered the growth to weeping-like. Suppressing the standard allele (MdLAZY1A-S) by RNA interference (RNAi) in RG similarly changed the branch growth direction to downward. Overall, the L195P mutation in MdLAZY1A is genetically causal for weeping growth, underscoring not only the crucial roles of residue L195 and Region III in MdLAZY1A-mediated gravitropic response, but also a potential DNA base editing target for tree architecture improvement in Malus and other crops.

plant biology↗

bioRxiv2023

Fine-tuning spatial-temporal dynamics and surface receptor expression support plasma cell-intrinsic longevity

Durable serological memory following vaccination is critically dependent on the production and survival of long-lived plasma cells (LLPCs). Yet, the factors that control LLPC specification and survival remain poorly resolved. Using intra-vital two-photon imaging, we find that in contrast to most plasma cells in the bone marrow (BM), LLPCs are uniquely sessile and organized into clusters that are dependent on APRIL, an important survival factor. Using deep, bulk RNA sequencing, and surface protein flow-based phenotyping, we find that LLPCs express a unique transcriptome and phenotype compared to bulk PCs, fine tuning expression of key cell surface molecules, CD93, CD81, CXCR4, CD326, CD44 and CD48, important for adhesion and homing. Conditional deletion of Cxcr4 in PCs following immunization leads to rapid mobilization from the BM, reduced survival of antigen-specific PCs, and ultimately accelerated decay of antibody titer. In naive mice, the endogenous LLPCs BCR repertoire exhibits reduced diversity, reduced somatic mutations, and increased public clones and IgM isotypes, particularly in young mice, suggesting LLPC specification is non-random. As mice age, the BM PC compartment becomes enriched in LLPCs, which may outcompete and limit entry of new PCs into the LLPC niche and pool. HIGHLIGHTSO_LILLPCs have reduced motility and increased clustering in the BM C_LIO_LILLPCs accumulate in the BM PC pool, with mouse age C_LIO_LILLPCs have unique surfaceome, transcriptome, and BCR clonality C_LIO_LICXCR4 controls maintenance of PCs and antibody titers C_LI

immunology↗