Search bioRxiv⌕ Search

Biology subjects

Chen, Q.

Publications and source records attributed to Chen, Q..

At least 235 records · Page 13Linked to original sources

Aberrant non-canonical NF-kappaB signalling reprograms the epigenome landscape to drive oncogenic transcriptomes in multiple myeloma

In multiple myeloma, abnormal plasma cells establish oncogenic niches within the bone marrow by engaging the NF-{kappa}B pathway to nurture their survival while they accumulate pro- proliferative mutations. Under these conditions, many cases eventually develop genetic abnormalities endowing them with constitutive NF-{kappa}B activation. Here, we find that sustained NF-{kappa}B/p52 levels resulting from such mutations favours the recruitment of enhancers beyond the normal B-cell repertoire. Furthermore, through targeted disruption of p52, we characterise how such enhancers are complicit in the formation of super-enhancers and the establishment of cis-regulatory interactions with myeloma dependencies during constitutive activation of p52. Finally, we functionally validate the pathological impact of these cis- regulatory modules on cell and tumour phenotypes using in vitro and in vivo models, confirming RGS1 as a novel p52-dependent myeloma driver. We conclude that the divergent epigenomic reprogramming enforced by aberrant non-canonical NF-{kappa}B signalling potentiates transcriptional programs beneficial for multiple myeloma progression.

cancer biology↗

Multi-omic characterization of allele-specific regulatory variation in hybrid pigs

Genetic variation in the regulation of gene expression contributes substantially to phenotypic variation. Understanding how variation in DNA sequences and epigentic modifications leads to gene expression variation remains a challenging task. In hybrid animals where cellular environments are homogeneous, differences between the expression of paternal and maternal alleles must be due to cis sequence or epigenic differences. Therefore, hybrid mapping is a powerful approach to efficiently identify and characterize genes under regulation through mechanisms in cis. In this study, using reciprocal crosses of the phenotypically divergent Duroc and Lulai pig breeds, we performed a comprehensive multi-omic characterization of regulatory variation across brain, liver, muscle, and placenta in four developmental stages. We produced one of the largest multi-omic datasets to date in pigs, including 16 whole genome sequenced genomes, 48 whole genome bisulfite sequencing, 168 ATAC-Seq and 168 RNA-Seq samples. We developed a novel read count-based method to reliably assess allele-specific methylation, chromatin accessibility, and RNA expression. We showed that tissue specificity was much stronger than developmental stage specificity in all of DNA methylation, chromatin accessibility, and gene expression. We identified 573 genes showing allele specific expression, including those influenced by parent-of-origin as well as allele genotype effects. By integrating methylation, chromatin accessibility, and gene expression data, many of these allele specific expression can be explained by allele specific methylation and/or chromatin accessibility. This study provides one of the most comprehensive characterizations of regulatory variation across multiple tissues and developmental stages in pigs and offers new opportunity of genetic improvement for this important food animal species.

developmental biology↗

Identification of the potassium binding site in serotonin transporter SERT

Clearance of serotonin (5-hydroxytryptamine, 5-HT) from the synaptic cleft after neuronal signaling is mediated by serotonin transporter SERT, which couples this process to the movement of a Na+ ion down its chemical gradient. After release of 5-HT and Na+ into the cytoplasm, the transporter faces a rate-limiting challenge of resetting its conformation to be primed again for 5-HT and Na+ binding. Early studies of vesicles containing native SERT revealed that K+ gradients can provide an additional driving force, via K+ antiport. Moreover, under appropriate conditions, a H+ ion can replace K+. Intracellular K+ accelerates the resetting step. Structural studies of SERT have identified two binding sites for Na+ ions, but the K+ site remains enigmatic. Here, we show that K+ antiport can drive substrate accumulation into vesicles containing SERT extracted from a heterologous expression system, allowing us to study the residues responsible for K+ binding. To identify candidate binding residues, we examine many cation binding configurations using molecular dynamics simulations, predicting that K+ binds to the so- called Na2 site. Site directed mutagenesis of residues in this site can eliminate the ability of both K+ and H+ to drive 5-HT accumulation into vesicles and, in patch clamp recordings, prevent the acceleration of turnover rates and the formation of a channel-like state by K+ or H+. In conclusion, the Na2 site plays a pivotal role in orchestrating the sequential binding of Na+ and then K+ (or H+) ions to facilitate 5-HT uptake in SERT. Significance statementNeuronal signaling depends on efficient clearance of the neurotransmitter from the synaptic cleft. To this end, proteins such as serotonin transporter (SERT) leverage the gradients of Na+ and K+ ions across the cell membrane, generated by Na+/K+-ATPase. While the role of Na+ in neurotransmitter transport is well understood, our understanding of the role of potassium in SERT has been limited. In this study, the authors use a combination of biochemical, electrophysiological, and computational tools, to identify the Na2 site as the binding site for K+, shedding light on a critical aspect of neurotransmitter transport.

biochemistry↗

Toward Best Practice in Identifying Subtle Differential Expression with RNA-seq: A Real-World Multi-Center Benchmarking Study Using Quartet and MAQC Reference Materials

Translating RNA-seq into clinical diagnostics requires ensuring the reliability of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. Moreover, cross-laboratory reproducibility and consistency under diverse experimental and bioinformatics workflows urgently need to be addressed. As part of the Quartet project, we presented a comprehensive RNA-seq benchmarking study utilizing Quartet and MAQC RNA reference samples spiked with ERCC controls in 45 independent laboratories, each employing their in-house RNA-seq workflows. We assessed the data quality, accuracy and reproducibility of gene expression and differential gene expression and compared over 40 experimental processes and 140 combined differential analysis pipelines based on multiple ground truths. Here we show that real-world RNA-seq exhibited greater inter-laboratory variations when detecting subtle differential expressions between Quartet samples. Experimental factors including mRNA enrichment methods and strandedness, and each bioinformatics step, particularly normalization, emerged as primary sources of variations in gene expression and have a more pronounced impact on the subtle differential expression measurement. We underscored the pivotal role of experimental execution over the choice of experimental protocols, the importance of strategies for filtering low-expression genes, and optimal gene annotation and analysis tools. In summary, this study provided best practice recommendations for the development, optimization, and quality control of RNA-seq for clinical diagnostic purposes.

genomics↗

Application of slow-controlled release fertilizer coordinates the carbon flow in carbon-nitrogen metabolism to effect rice quality

Slow-controlled release fertilizers are experiencing a popularity in rice cultivation due to their effectiveness in yield and quality with low environmental costs. However, the underlying mechanism by which these fertilizers regulate grain quality remains inadequately understood. This study investigated the effects of five fertilizer management practices on rice quality in a two-year field experiment: CK, conventional fertilization, and four applications of slow-controlled release fertilizer (UF, urea formaldehyde; SCU, sulfur-coated urea; PCU, polymer-coated urea; BBF, controlled-release bulk blending fertilizer). In 2020 and 2021, the yields of UF and SCU groups showed significant decreases when compared to conventional fertilization, accompanied by a decline in nutritional quality. Additionally, PCU group exhibited poorer cooking and eating qualities. However, BBF group achieved increases in both yield (10.8 t hm-2 and 11.0 t hm-2) and grain quality reaching the level of CK group. The sufficient nitrogen supply in both the PCU and BBF groups during the grain-filling stage led to a greater capacity for the accumulation of proteins and amino acids in the PCU group compared to starch accumulation. Intriguingly, BBF group showed better carbon-nitrogen metabolism than that of PCU group. The optimal nitrogen supply present in BBF group suitable boosted the synthesis of amino acids involved in the glycolysis/ tricarboxylic acid cycle, thereby effectively coordinating carbon-nitrogen metabolism. The application of the new slow-controlled release fertilizer, BBF, is advantageous in regulating the carbon flow in the carbon-nitrogen metabolism to enhance rice quality.

plant biology↗

Flexible and Controllable Protein Design by Prefix-tuning Large-Scale Protein Language Models

The design of novel proteins with tailored functionalities, particularly in drug discovery and vaccine development, presents a transformative approach to addressing pressing biomedical challenges. Inspired by the remarkable success of pre-trained language models in natural language processing (NLP), protein language models (ProtLMs) have emerged as powerful tools in advancing protein science. While NLP leverages flexible text-based control tags to prompt language model generation, the restricted amino acid space (limited to 20 residues) imposes inherent constraints on achieving analogous controllability. In this study, we propose PrefixProt, a framework for controllable protein design that employs prefix tuning to learn virtual tokens as control tags. These virtual tokens are adaptively tailored to diverse protein properties through a data-driven manner and can be combinatorially integrated to enable multi-objective control over protein generation. The effectiveness of PrefixProt was validated through extensive experiments encompassing both protein structure design (e.g. alpha-helix or beta-sheet topologies) and protein function design (e.g. antimicrobial or anticancer peptide activities). Benchmark results demonstrate that prefix virtual tokens efficiently guide the pre-trained ProtLM by optimizing a smaller number of trainable parameters, out-performing other parameter-efficient fine-tuning methods and text-guided ProtLMs, particularly in scenarios with limited data availability. More importantly, the compositional flexibility of virtual tokens facilitates the generation of proteins with multiple target properties, substantially expanding the scope of design possibilities. By harmonizing controllability, efficiency and generalizability, PrefixProt establishes a robust framework for de novo protein design, with promising applications in drug discovery and biomedicine. Availability and implementationThe models and code are available at: https://github.com/chen-bioinfo/PrefixProt

bioinformatics↗

The change of lymphocyte subsets and inflammatory cytokine in BK viruria

BackgroundPolyomavirus BK (BKV) infection as a serious complication after kidney transplantation. The process of infections in kidney transplant recipients is viruria, viremia, and BKVAN. The difference between BK negative and BK viruria in kidney recipients has not been defined. Patients and MethodsWe compared post-transplant lymphocyte subsets blood cytokinesurine cytokines levels of 19 renal transplant outpatients with (BK-positive) or without BK viruria (BK-negative, n=20), and 20 healthy controls (HCs). Group of BK-positive divide into low-(n=4) and high-level (n=15) According to BK viral load (VL).Immune cells including T cells, B cells, and natural killer (NK) cellsinterleukin-2(IL-2),IL-5,IL-6, IL-1{beta}, IL-10, IL-8, IL-17A,IL-4,IL-12P70, interferon-(IFN-), IFN-{gamma},and tumor necrosis factor- (TNF-)were determined by flow cytometry. ResultsBK-positive patients showed higher urine IL-1{beta} (P=0.040), IL-10 (P= 0.010), IFN-{gamma} (P =0.002), and TNF- (P =0.027) than BK-negative patients. Compared with HCs, BK-negative patients had lower urine IL-1{beta} (P=0.04), IL-10 (P=0.01), TNF- (P =0.027) and IFN-{gamma} (P =0.004),suggesting that cytokine expression regulation BK-infection. ConclusionBK-positive renal transplant recipients, especially those with high VL, showed strong inflammatory cytokine responses with increases of urine IL-1{beta}, IL-10, IFN-{gamma}, and TNF-. Our data suggest that monocyte- and Th-2-induced cytokines are involved in the pathogenesis of BKV-associated nephropathy.

immunology↗

Light-adaptation clamp: a tool to predictably manipulate photoreceptor light responses

Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

neuroscience↗

Bioinfo-Bench: A Simple Benchmark Framework for LLM Bioinformatics Skills Evaluation

AO_SCPLOWBSTRACTC_SCPLOWLarge Language Models (LLMs) have garnered significant recognition in the life sciences for their capacity to comprehend and utilize knowledge. The contemporary expectation in diverse industries extends beyond employing LLMs merely as chatbots; instead, there is a growing emphasis on harnessing their potential as adept analysts proficient in dissecting intricate issues within these sectors. The realm of bioinformatics is no exception to this trend. In this paper, we introduce BO_SCPLOWIOINFOC_SCPLOW-BO_SCPLOWENCHC_SCPLOW, a novel yet straightforward benchmark framework suite crafted to assess the academic knowledge and data mining capabilities of foundational models in bioinformatics. BO_SCPLOWIOINFOC_SCPLOW-BO_SCPLOWENCHC_SCPLOW systematically gathered data from three distinct perspectives: knowledge acquisition, knowledge analysis, and knowledge application, facilitating a comprehensive examination of LLMs. Our evaluation encompassed prominent models ChatGPT, Llama, and Galactica. The findings revealed that these LLMs excel in knowledge acquisition, drawing heavily upon their training data for retention. However, their proficiency in addressing practical professional queries and conducting nuanced knowledge inference remains constrained. Given these insights, we are poised to delve deeper into this domain, engaging in further extensive research and discourse. It is pertinent to note that project BO_SCPLOWIOINFOC_SCPLOW-BO_SCPLOWENCHC_SCPLOW is currently in progress, and all associated materials will be made publicly accessible.1

bioinformatics↗

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

bioinformatics↗

Structural insights into the distinct protective mechanisms of human antibodies targeting ZIKV NS1

Zika virus (ZIKV) Non-structural protein 1 (NS1) plays an essential role in viral replication and immune evasion. Our understanding of the differential protective mechanism of NS1-targeting antibodies is limited. Here, we determined the cryoEM structures of ZIKV NS1 in complex with two group antibodies at 2.6-2.9[A]. Group I antibodies (3G2 and 4B8) potently recognize cell surface form of NS1 and multiple oligomeric forms of NS1 by occupy the epitopes on outer surface of dimeric NS1. IgG and Fab from group I antibodies completely abrogate sNS1-mediated endothelial dysfunction in vitro. Group II antibodies (4F10, 2E11, and 14G5) recognize the previously reported epitopes in distal end of the {beta}-ladder domain of monomeric NS1, and their blockade efficiency depends on the affinity with NS1 protein. These findings elucidate the correlation between the epitope recognition and the protective efficacy of anti-NS1 antibodies and highlight the distinct mechanisms of therapeutic potential of 3G2 and 4B8.

microbiology↗

Generalized Reporter Score-based Enrichment Analysis for Diverse Omics Data

Enrichment analysis contextualizes biological features in pathways to facilitate a systematic understanding of high-dimensional data and is widely used in biomedical research. The emerging reporter score-based analysis (RSA) method shows more promising sensitivity, as it relies on p-values instead of raw values of features. However, RSA cannot be directly applied to multi-group experimental designs and is often misused due to the lack of a proper tool. Here, we propose the Generalized Reporter Score-based Analysis (GRSA) method for multi-group and longitudinal omics data. A comparison with other popular enrichment analysis methods demonstrated that GRSA had increased sensitivity across multiple benchmark datasets. We applied GRSA to microbiome, transcriptome, and metabolome data and discovered new biological insights in omics studies. Finally, we demonstrated the application of GRSA beyond functional enrichment using a taxonomy database. We implemented GRSA in an R package, ReporterScore, integrating with a powerful visualization module and updatable pathway databases (https://github.com/Asa12138/ReporterScore). We believe the ReporterScore package will be a valuable asset for broad biomedical research fields.

bioinformatics↗

Antibodies utilizing VL6-57 light chains target a convergent cryptic epitope on SARS-CoV-2 spike protein driving the genesis of Omicron variants

Continued evolution of SARS-CoV-2 generates variants to challenge antibody immunity established by infection and vaccination. A connection between population immunity and genesis of virus variants has long been suggested but its molecular basis remains poorly understood. Here, we identify a class of SARS-CoV-2 neutralising public antibodies defined by their shared usage of VL6-57 light chains. Although heavy chains of diverse genotypes are utilized, convergent HCDR3 rearrangements have been observed among these public antibodies to cooperate with germline VL6-57 LCDRs to target a convergent epitope defined by RBD residues S371-S373-S375. Antibody repertoire analysis identifies that this class of VL6-57 antibodies is present in SARS-CoV-2-naive individuals and is clonally expanded in most COVID-19 patients. We confirm that Omicron specific substitutions at S371, S373 and S375 mediate escape of antibodies of the VL6-57 class. These findings support that this class of public antibodies constitutes immune pressure promoting the introduction of S371L/F-S373P-S375F in Omicron variants. The results provide further molecular evidences to support that antigenic evolution of SARS-CoV-2 is driven by antibody mediated population immunity.

biochemistry↗

Cnot3 is required for male germ cell development and spermatogonial stem cell maintenance

The foundation of spermatogenesis and lifelong fertility is provided by spermatogonial stem cells (SSCs). SSCs divide asymmetrically to either replenish their numbers (self-renewal) or produce undifferentiated progenitors that proliferate before committing to differentiation. However, regulatory mechanisms governing SSC maintenance are poorly understood. Here, we show that the CCR4-NOT mRNA deadenylase complex subunit CNOT3 plays a critical role in maintaining spermatogonial populations in mice. Cnot3 is highly expressed in undifferentiated spermatogonia, and its deletion in spermatogonia resulted in germ cell loss and infertility. Single cell analyses revealed that Cnot3 deletion led to the de-repression of transcripts encoding factors involved in spermatogonial differentiation, including those in the glutathione redox pathway that are critical for SSC maintenance. Together, our study reveals that CNOT3 - likely via the CCR4-NOT complex - actively degrades transcripts encoding differentiation factors to sustain the spermatogonial pool and ensure the progression of spermatogenesis, highlighting the importance of CCR4-NOT-mediated post-transcriptional gene regulation during male germ cell development. HighlightsO_LICnot3 is predominantly expressed in undifferentiated spermatogonia, and its expression decreases in later stages. C_LIO_LIConditional deletion of Cnot3 leads to total germ cell loss and male infertility. C_LIO_LICNOT3 represses transcripts encoding factors involved in spermatogonial differentiation. C_LIO_LICNOT3 protects spermatogonial stem cells maintenance via GSH/redox pathway. C_LI Graphical AbstractCnot3 promotes SSC self-renewal by balancing ROS production via the regulation of GSH production O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/562256v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@3afef9org.highwire.dtl.DTLVardef@139cb19org.highwire.dtl.DTLVardef@1450c47org.highwire.dtl.DTLVardef@293300_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

Progressive community, biogeochemical and evolutionary remodeling of the soil microbiome underpins long-term desert ecosystem restoration

Ecological restoration of degraded lands is essential to human sustainability. Yet, an in-depth community, functional, and evolutionary microbial perspective of long-term restoration of damaged ecosystems is lacking. Herein, we comprehensively assessed the impact of long-term (up to 17 years) restoration of Tengger Desert, China, by multi-omic profiling of 1,910 topsoil samples. The soil biophysiochemical properties, especially soil hydraulics, microbiome stability, and functional diversity, significantly improved during restoration. The soil microbiome transitioned from an extreme oligotrophic and autotrophic community to a diverse copiotrophic ecosystem. The soil microbiota, including fungi, could mediate the soil physicochemical changes through metabolites. Importantly, the systematic rewiring of nutrient cycles featured the multi-domain preference of an efficient carbon fixation strategy in the extreme desert environment. Finally, the microbiome was evolving via positive selections of genes of biogeochemical cycles, resistance, and motility. In summary, we present a comprehensive community, functional, biogeochemical, and evolutionary landscape of the soil microbiome during the long-term restoration of desert environments. We highlight the crucial microbial role in restoration from soil hydraulic and biogeochemical perspectives, offering promising field applications. HighlightsO_LIThe desert soil microbiome transformed from simple oligotrophic to a diverse, stable, and nutrient-rich ecosystem with expanded functional diversity. C_LIO_LIRestoration led to systematically rewired biogeochemical cycles, which are highly efficient in carbon fixation in the desert environment. C_LIO_LIThe microbiome was evolving via positive selections of genes involved in biogeochemical cycles and environmental adaptations. C_LIO_LIMicrobes and metabolites could facilitate desert restoration from hydraulic and biogeochemical aspects, offering promising field applications. C_LI

microbiology↗

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [18F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a bench to bedside translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

neuroscience↗

Higher-order combinatorial chromatin perturbations by engineered CRISPR-Cas12a for functional genomics

Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting 1-3 genomic sites per cell. To develop a tool for higher-order (>3) combinatorial targeting of genomic sites with CRISPRi in functional genomics screens, we engineered an Acidaminococcus Cas12a variant -- referred to as multiplexed transcriptional interference AsCas12a (multiAsCas12a). multiAsCas12a incorporates a key mutation, R1226A, motivated by the hypothesis of nicking-induced stabilization of the ribonucleoprotein:DNA complex for improving CRISPRi activity. multiAsCas12a significantly outperforms prior state-of-the-art Cas12a variants in combinatorial CRISPRi targeting using high-order multiplexed arrays of lentivirally transduced CRISPR RNAs (crRNA), including in high-throughput pooled screens using 6-plex crRNA array libraries. Using multiAsCas12a CRISPRi, we discover new enhancer elements and dissect the combinatorial function of cis-regulatory elements. These results instantiate a group testing framework for efficiently surveying potentially numerous combinations of chromatin perturbations for biological discovery and engineering.

genetics↗

Progesterone induces meiosis through two obligate co-receptors with PLA2 activity

The steroid hormone progesterone (P4) regulates multiple aspects of reproductive and metabolic physiology. Classical P4 signaling operates through nuclear receptors that regulate transcription. In addition, P4 signals through membrane P4 receptors (mPRs) in a rapid nongenomic modality. Despite the established physiological importance of P4 nongenomic signaling, the details of its signal transduction cascade remain elusive. Here, using Xenopus oocyte maturation as a well- established physiological readout of nongenomic P4 signaling, we identify the lipid hydrolase ABHD2 (/{beta} hydrolase domain-containing protein 2) as an essential mPR{beta} co-receptor to trigger meiosis. We show using functional assays coupled to unbiased and targeted cell-based lipidomics that ABHD2 possesses a phospholipase A2 (PLA2) activity that requires mPR{beta}. This PLA2 activity bifurcates P4 signaling by inducing clathrin-dependent endocytosis of mPR{beta}, resulting in the production of lipid messengers that are G-protein coupled receptors agonists. Therefore, P4 drives meiosis by inducing an ABHD2 PLA2 activity that requires both mPR{beta} and ABHD2 as obligate co-receptors. Significance StatementNongenomic progesterone signaling is important for many physiological functions yet the details of its signaling remain elusive. Here we define the early signaling steps downstream of membrane progesterone receptor {beta} (mPR{beta}) during Xenopus oocyte meiosis. We show that progesterone requires two cell membrane receptors to work in unison to signal. The co-receptor complex possesses lipase activity that produces lipid messenger and induces receptor endocytosis to trigger meiosis progression. Our findings have broad physiological implications because nongenomic progesterone signaling operates in many tissues and regulates reproduction and metabolism.

cell biology↗