J Lipid Res. 2024 Oct 10:100666. doi: 10.1016/j.jlr.2024.100666. Online ahead of print.

ABSTRACT

Cellular metabolism is a complex process involving the consumption and production of metabolites, as well as the regulation of enzyme synthesis and activity. Modeling of metabolic processes is important to understand the underlying mechanisms, with a wide range of applications in metabolic engineering and health sciences. Cybernetic modeling is a powerful technique that accounts for unknown intricate regulatory mechanisms in complex cellular processes. It models regulation as goal-oriented, where the levels and activities of enzymes are modulated by the cybernetic control variables to achieve the cybernetic objective. This study employed cybernetic model to study the enzyme competition between arachidonic acid (AA) and eicosapentaenoic acid (EPA) metabolism in murine macrophages. AA and EPA compete for the shared enzyme cyclooxygenase (COX). Upon external stimuli, AA produces pro-inflammatory 2-series prostaglandins (PGs) and EPA metabolizes to anti-inflammatory 3-series PGs, where pro- and anti- inflammatory responses are necessary for homeostasis. The cybernetic model adequately captured the experimental data for control and EPA-supplemented conditions. The model is validated by performing an F-test, conducting leave-one-out-metabolite cross-validation, and predicting an unseen experimental condition. The cybernetic variables provide insights into the competition between AA and EPA for the COX enzyme. Predictions from our model suggest that the system undergoes a switch from a predominantly pro-inflammatory state in the control to an anti-inflammatory state with EPA-supplementation. The model can also be used to analytically determine the AA and EPA concentrations required for the switch to occur. The quantitative outcomes enhance understanding of pro- and anti-inflammatory metabolism in RAW 264.7 macrophages.

PMID:39395792 | DOI:10.1016/j.jlr.2024.100666

J Microbiol Methods. 2024 Oct 10:107054. doi: 10.1016/j.mimet.2024.107054. Online ahead of print.

ABSTRACT

The transfer of biocide and antibiotic resistance genes by mobile genetic elements is the most common mechanism for rapidly acquiring and spreading resistance among bacteria. The qacEΔ1 gene confers the resistance to quaternary ammonium compounds (QACs). It has also been considered a genetic marker for the presence of class 1 integrons associated with multidrug-resistant (MDR) phenotypes in Gram-negative bacteria. In this study, a TaqMan real-time PCR assay was developed to detect the qacEΔ1 gene in Gram-negative bacteria. The assay has a detection limit of 80 copies of the qacEΔ1 gene per reaction. No false-positive or false-negative results have been observed. Simultaneous amplification and detection of the 16S rRNA gene is performed as an endogenous internal amplification control (IAC). The TaqMan real-time PCR assay developed is a rapid, sensitive, and specific method that could be used to monitor resistance to QACs, the spread of class 1 integrons, and the prediction of associated MDR phenotypes in Gram-negative bacteria.

PMID:39395725 | DOI:10.1016/j.mimet.2024.107054

Ageing Res Rev. 2024 Oct 10:102540. doi: 10.1016/j.arr.2024.102540. Online ahead of print.

ABSTRACT

Age-related changes initiate a cascade of cellular and molecular alterations that lead to immune system dysfunction or abnormal activation, predisposing individuals to age-related diseases. This phenomenon, commonly referred to as immunosenescence, highlighting aging-associated progressive decline of the immune system. Moreover, mounting evidence suggests that immunosenescence contributes to a related pathological phenomenon known as inflammaging. Inflammaging refers to chronic, low-grade, and systemic inflammation associated with aging, occurring despite the absence of overt stimuli. In the body, inflammation is typically activated in response to overt stimuli such as bacterial/microbial invasion or a pathological state, however, inflammaging occurrence and its underpinning mechansisms seem to be independent and in the absence of such stimuli. Despite recent advancements in molecular characterization and the scrutiny of disease relevance, these two interconnected concepts have remained largely unexplored and unrecognized. In this comprehensive review, we aim to shed light on the mechanistic and cellular aspects of immunosenescence and inflammaging, as well as their pivotal roles in the pathogenesis of aging-related diseases, including cancer, infections, dementia, and neurodegenerative disorders.

PMID:39395575 | DOI:10.1016/j.arr.2024.102540

Neuro Oncol. 2024 Oct 12:noae215. doi: 10.1093/neuonc/noae215. Online ahead of print.

ABSTRACT

BACKGROUND: Diffuse midline glioma (DMG) is the most aggressive primary brain tumor in children. All previous studies examining the role of systemic agents have failed to demonstrate a survival benefit; the only standard of care is radiation therapy (RT). Successful implementation of radiosensitization strategies in DMG remains an essential and promising avenue of investigation. We explore the use of Napabucasin, an NAD(P)H quinone dehydrogenase 1 (NQO1)-bioactivatable reactive oxygen species (ROS)-inducer, as a potential therapeutic radiosensitizer in DMG.

METHODS: In this study, we conduct in vitro and in vivo assays using patient-derived DMG cultures to elucidate the mechanism of action of Napabucasin and its radiosensitizing properties. As penetration of systemic therapy through the blood-brain barrier (BBB) is a significant limitation to the success of DMG therapies, we explore focused ultrasound (FUS) and convection-enhanced delivery (CED) to overcome the BBB and maximize therapeutic efficacy.

RESULTS: Napabucasin is a potent ROS-inducer and radiosensitizer in DMG, and treatment-mediated ROS production and cytotoxicity are dependent on NQO1. In subcutaneous xenograft models, combination therapy with RT improves local control. After optimizing targeted drug delivery using CED in an orthotopic mouse model, we establish the novel feasibility and survival benefit of CED of Napabucasin concurrent with RT.

CONCLUSIONS: As nearly all DMG patients will receive RT as part of their treatment course, our validation of the efficacy of radiosensitizing therapy using CED to prolong survival in DMG opens the door for exciting novel studies of alternative radiosensitization strategies in this devastating disease while overcoming limitations of the BBB.

PMID:39394920 | DOI:10.1093/neuonc/noae215

HGG Adv. 2024 Oct 10:100371. doi: 10.1016/j.xhgg.2024.100371. Online ahead of print.

ABSTRACT

The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Version 0.1.19 of Phenopacket Store includes 6668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.

PMID:39394689 | DOI:10.1016/j.xhgg.2024.100371

Nat Immunol. 2024 Oct 11. doi: 10.1038/s41590-024-01986-8. Online ahead of print.

ABSTRACT

The mechanisms that guide T helper 2 (TH2) cell differentiation in barrier tissues are unclear. Here we describe the molecular pathways driving allergen-specific TH2 cells using temporal, spatial and single-cell transcriptomic tracking of house dust mite-specific T cells in mice. Differentiation and migration of lung allergen-specific TH2 cells requires early expression of the transcriptional repressor Blimp-1. Loss of Blimp-1 during priming in the lymph node ablated the formation of TH2 cells in the lung, indicating early Blimp-1 promotes TH2 cells with migratory capability. IL-2/STAT5 signals and autocrine/paracrine IL-10 from house dust mite-specific T cells were essential for Blimp-1 and subsequent GATA3 upregulation through repression of Bcl6 and Bach2. Spatial microniches of IL-2 in the lymph node supported the earliest Blimp-1+TH2 cells, demonstrating lymph node localization is a driver of TH2 initiation. Our findings identify an early requirement for IL-2-mediated spatial microniches that integrate with allergen-driven IL-10 from responding T cells to drive allergic asthma.

PMID:39394532 | DOI:10.1038/s41590-024-01986-8

Nat Methods. 2024 Oct 11. doi: 10.1038/s41592-024-02454-9. Online ahead of print.

ABSTRACT

Expansion microscopy (ExM) is in increasingly widespread use throughout biology because its isotropic physical magnification enables nanoimaging on conventional microscopes. To date, ExM methods either expand specimens to a limited range (~4-10× linearly) or achieve larger expansion factors through iterating the expansion process a second time (~15-20× linearly). Here, we present an ExM protocol that achieves ~20× expansion (yielding <20-nm resolution on a conventional microscope) in a single expansion step, achieving the performance of iterative expansion with the simplicity of a single-shot protocol. This protocol, which we call 20ExM, supports postexpansion staining for brain tissue, which can facilitate biomolecular labeling. 20ExM may find utility in many areas of biological investigation requiring high-resolution imaging.

PMID:39394503 | DOI:10.1038/s41592-024-02454-9

Nat Biotechnol. 2024 Oct 11. doi: 10.1038/s41587-024-02422-w. Online ahead of print.

ABSTRACT

CRISPR guide RNA sequences deriving exactly from natural sequences may not perform optimally in every application. Here we implement and evaluate algorithms for designing maximally fit, artificial CRISPR-Cas13a guides with multiple mismatches to natural sequences that are tailored for diagnostic applications. These guides offer more sensitive detection of diverse pathogens and discrimination of pathogen variants compared with guides derived directly from natural sequences and illuminate design principles that broaden Cas13a targeting.

PMID:39394482 | DOI:10.1038/s41587-024-02422-w

ACS Synth Biol. 2024 Oct 10. doi: 10.1021/acssynbio.4c00405. Online ahead of print.

ABSTRACT

Genetic approaches have been traditionally used to understand microbial metabolism, but this process can be slow in nonmodel organisms due to limited genetic tools. An alternative approach is to study metabolism directly in the cell lysate. This avoids the need for genetic tools and is routinely used to study individual enzymatic reactions but is not generally used to study systems-level properties of metabolism. Here we demonstrate a new approach that we call "cell-free systems biology", where we use well-characterized enzymes and multienzyme cascades to serve as sources or sinks of intermediate metabolites. This allows us to isolate subnetworks within metabolism and study their systems-level properties. To demonstrate this, we worked with a three-enzyme cascade reaction that converts pyruvate to 2,3-butanediol. Although it has been previously used in cell-free systems, its pH dependence was not well characterized, limiting its utility as a sink for pyruvate. We showed that improved proton accounting allowed better prediction of pH changes and that active pH control allowed 2,3-butanediol titers of up to 2.1 M (189 g/L) from acetoin and 1.6 M (144 g/L) from pyruvate. The improved proton accounting provided a crucial insight that preventing the escape of CO2 from the system largely eliminated the need for active pH control, dramatically simplifying our experimental setup. We then used this cascade reaction to understand limits to product formation in Clostridium thermocellum, an organism with potential applications for cellulosic biofuel production. We showed that the fate of pyruvate is largely controlled by electron availability and that reactions upstream of pyruvate limit overall product formation.

PMID:39387698 | DOI:10.1021/acssynbio.4c00405

J Exp Bot. 2024 Oct 10:erae424. doi: 10.1093/jxb/erae424. Online ahead of print.

ABSTRACT

Adenine metabolism is important for common bean (Phaseolus vulgaris L) productivity since this legume uses ureides derived from the oxidation of purine nucleotides, as their primary nitrogen storage molecules. Purine nucleotides are produced from de novo synthesis or through salvage pathways. Adenine phosphoribosyl transferase (APRT) is the enzyme dedicated to adenine nucleobase salvage for nucleotide synthesis, but it also acts on the inactivation of cytokinin bases. In common bean, the APRT enzyme is encoded by four genes. Gene expression analysis, biochemical properties and subcellular location suggest functional differences among the common bean APRT isoforms. CRISPR/Cas9 targeted downregulation of two of the four PvAPRTs followed by metabolomics and physiological analyses of targeted hairy roots reveals that, although the two proteins have redundant functions, PvAPRT1 mostly participates in the salvage of adenine, whereas PvAPRT5 is the predominant form in the regulation of cytokinin homeostasis and stress responses with a high impact in root and nodule growth.

PMID:39387692 | DOI:10.1093/jxb/erae424

Elife. 2024 Oct 10;13:e104070. doi: 10.7554/eLife.104070.

ABSTRACT

Early-career researchers in the Global South have to overcome obstacles that are not found in high-income countries, but in Morocco at least, the future is looking brighter than the past.

PMID:39387675 | PMC:PMC11466452 | DOI:10.7554/eLife.104070

Phytopathology. 2024 Oct 10. doi: 10.1094/PHYTO-08-24-0269-FI. Online ahead of print.

ABSTRACT

Passifloraceae is a plant family that includes several species of interest in the food, medicinal, and ornamental industries. The most relevant species are the purple and yellow varieties of P. edulis, which are among the most highly prized tropical fruits in the international markets. Unfortunately, the rapid expansion of this crop worldwide has resulted in the emergence of several viral diseases that endangered the productivity of this crop. In this work, we performed an integrated analysis of the Passifloraceae virome using public data. We investigated Pubmed and Genbank records and analyzed all the transcriptome data available for members of this plant family. This analysis resulted in the identification of six novel virus associations and six putative new viral species. We also used RNAseq to inspect virus accumulation levels and mixed infections. Using network analysis, we also examined the global distribution of Passiflora viruses and their associations with alternative hosts, which is valuable information in implementing viral disease management strategies. Our data suggest that a large diversity of viruses remains to be discovered. Finally, we used the information gathered in this work to estimate the cross-transmission risk of viruses in Colombian Passiflora fields.

PMID:39387526 | DOI:10.1094/PHYTO-08-24-0269-FI

Biol Open. 2024 Jul 15;13(10):bio061721. doi: 10.1242/bio.061721. Epub 2024 Oct 10.

ABSTRACT

Regulation of gene expression is critical for fate commitment of stem and progenitor cells during tissue formation. In the context of mammalian brain development, a plethora of studies have described how changes in the expression of individual genes characterize cell types across ontogeny and phylogeny. However, little attention has been paid to the fact that different transcripts can arise from any given gene through alternative splicing (AS). Considered a key mechanism expanding transcriptome diversity during evolution, assessing the full potential of AS on isoform diversity and protein function has been notoriously difficult. Here, we capitalize on the use of a validated reporter mouse line to isolate neural stem cells, neurogenic progenitors and neurons during corticogenesis and combine the use of short- and long-read sequencing to reconstruct the full transcriptome diversity characterizing neurogenic commitment. Extending available transcriptional profiles of the mammalian brain by nearly 50,000 new isoforms, we found that neurogenic commitment is characterized by a progressive increase in exon inclusion resulting in the profound remodeling of the transcriptional profile of specific cortical cell types. Most importantly, we computationally infer the biological significance of AS on protein structure by using AlphaFold2, revealing how radical protein conformational changes can arise from subtle changes in isoforms sequence. Together, our study reveals that AS has a greater potential to impact protein diversity and function than previously thought, independently from changes in gene expression.

PMID:39387301 | DOI:10.1242/bio.061721

NAR Genom Bioinform. 2024 Sep 3;6(3):lqae114. doi: 10.1093/nargab/lqae114. eCollection 2024 Sep.

ABSTRACT

Unraveling metabolite-protein interactions is key to identifying the mechanisms by which metabolism affects the function of other cellular layers. Despite extensive experimental and computational efforts to identify the regulatory roles of metabolites in interaction with proteins, it remains challenging to achieve a genome-scale coverage of these interactions. Here, we leverage established gold standards for metabolite-protein interactions to train supervised classifiers using features derived from genome-scale metabolic models and matched data on protein abundance and reaction fluxes to distinguish interacting from non-interacting pairs. Through a comprehensive comparative study, we explore the impact of different features and assess the effect of gold standards for non-interacting pairs on the performance of the classifiers. Using data sets from Escherichia coli and Saccharomyces cerevisiae, we demonstrate that the features constructed by integrating fluxomic and proteomic data with metabolic phenotypes predicted from genome-scale metabolic models can be effectively used to train classifiers, accurately predicting metabolite-protein interactions in the context of metabolism. Our results reveal that the high performance of classifiers trained on these features is unaffected by the method used to generate gold standards for non-interacting pairs. Overall, our study introduces valuable features that improve the performance of identifying metabolite-protein interactions in the context of metabolism.

PMID:39229256 | PMC:PMC11369697 | DOI:10.1093/nargab/lqae114

bioRxiv [Preprint]. 2024 Aug 19:2024.08.16.608329. doi: 10.1101/2024.08.16.608329.

ABSTRACT

The rapid expansion of multi-omics data has transformed biological research, offering unprecedented opportunities to explore complex genomic relationships across diverse organisms. However, the vast volume and heterogeneity of these datasets presents significant challenges for analyses. Here we introduce SocialGene, a comprehensive software suite designed to collect, analyze, and organize multi-omics data into structured knowledge graphs, with the ability to handle small projects to repository-scale analyses. Originally developed to enhance genome mining for natural product drug discovery, SocialGene has been effective across various applications, including functional genomics, evolutionary studies, and systems biology. SocialGene's concerted Python and Nextflow libraries streamline data ingestion, manipulation, aggregation, and analysis, culminating in a custom Neo4j database. The software not only facilitates the exploration of genomic synteny but also provides a foundational knowledge graph supporting the integration of additional diverse datasets and the development of advanced search engines and analyses. This manuscript introduces some of SocialGene's capabilities through brief case studies including targeted genome mining for drug discovery, accelerated searches for similar and distantly related biosynthetic gene clusters in biobank-available organisms, integration of chemical and analytical data, and more. SocialGene is free, open-source, MIT-licensed, designed for adaptability and extension, and available from github.com/socialgene.

PMID:39229008 | PMC:PMC11370487 | DOI:10.1101/2024.08.16.608329

J Transl Med. 2024 Sep 3;22(1):821. doi: 10.1186/s12967-024-05611-y.

ABSTRACT

BACKGROUND: Myeloid-derived suppressor cells (MDSCs) are the major factor in gastric cancer (GC) immune evasion. Nevertheless, the molecular process underlying the expansion of MDSCs induced by tumor-derived exosomes (TDEs) remains elusive.

METHODS: The levels of exosomal and soluble PD-L1 in ninety GC patients were examined via enzyme-linked immunosorbent assay (ELISA) to determine their prognostic value. To investigate the correlation between exosomal PD-L1 and MDSCs, the percentage of MDSCs in the peripheral blood of 57 GC patients was assessed via flow cytometry. Through ultracentrifugation, the exosomes were separated from the GC cell supernatant and detected via Western blotting, nanoparticle tracking analysis (NTA), and transmission electron microscopy (TEM). The function of exosomal PD-L1 in MDSCs was evaluated via immunofluorescence, Western blotting and flow cytometry in a GC cell-derived xenograft (CDX) model.

RESULTS: The overall survival (OS) of GC patients in the high exosomal PD-L1 group was significantly lower than that of patients in the low exosomal PD-L1 group (P = 0.0042); however, there was no significant correlation between soluble PD-L1 and OS in GC patients (P = 0.0501). Furthermore, we found that the expression of exosomal PD-L1 was positively correlated with the proportions of polymorphonuclear MDSCs (PMN-MDSCs, r = 0.4944, P < 0.001) and monocytic MDSCs (M-MDSCs, r = 0.3663, P = 0.005) in GC patients, indicating that exosomal PD-L1 might induce immune suppression by promoting the aggregation of MDSCs. In addition, we found that exosomal PD-L1 might stimulate MDSC proliferation by triggering the IL-6/STAT3 signaling pathway in vitro. The CDX model confirmed that exosomal PD-L1 could stimulate tumor development and MDSC amplification.

CONCLUSIONS: Exosomal PD-L1 has the potential to become a prognostic and diagnostic biomarker for GC patients. Mechanistically, MDSCs can be activated by exosomal PD-L1 through IL-6/STAT3 signaling and provide a new strategy against GC through the use of exosomal PD-L1 as a treatment target.

PMID:39227816 | DOI:10.1186/s12967-024-05611-y

Nat Cancer. 2024 Sep 3. doi: 10.1038/s43018-024-00817-x. Online ahead of print.

ABSTRACT

The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE) are foundational resources in cancer research, providing extensive molecular and phenotypic data. However, large-scale proteomic data across various cancer types for these cohorts remain limited. Here, we expand upon our previous work to generate high-quality protein expression data for approximately 8,000 TCGA patient samples and around 900 CCLE cell line samples, covering 447 clinically relevant proteins, using reverse-phase protein arrays. These protein expression profiles offer profound insights into intertumor heterogeneity and cancer dependency and serve as sensitive functional readouts for somatic alterations. We develop a systematic protein-centered strategy for identifying synthetic lethality pairs and experimentally validate an interaction between protein kinase A subunit α and epidermal growth factor receptor. We also identify metastasis-related protein markers with clinical relevance. This dataset represents a valuable resource for advancing our understanding of cancer mechanisms, discovering protein biomarkers and developing innovative therapeutic strategies.

PMID:39227745 | DOI:10.1038/s43018-024-00817-x

Nat Genet. 2024 Sep 3. doi: 10.1038/s41588-024-01874-9. Online ahead of print.

ABSTRACT

Functional genomic screens in two-dimensional cell culture models are limited in identifying therapeutic targets that influence the tumor microenvironment. By comparing targeted CRISPR-Cas9 screens in a two-dimensional culture with xenografts derived from the same cell line, we identified MEN1 as the top hit that confers differential dropout effects in vitro and in vivo. MEN1 knockout in multiple solid cancer types does not impact cell proliferation in vitro but significantly promotes or inhibits tumor growth in immunodeficient or immunocompetent mice, respectively. Mechanistically, MEN1 knockout redistributes MLL1 chromatin occupancy, increasing H3K4me3 at repetitive genomic regions, activating double-stranded RNA expression and increasing neutrophil and CD8+ T cell infiltration in immunodeficient and immunocompetent mice, respectively. Pharmacological inhibition of the menin-MLL interaction reduces tumor growth in a CD8+ T cell-dependent manner. These findings reveal tumor microenvironment-dependent oncogenic and tumor-suppressive functions of MEN1 and provide a rationale for targeting MEN1 in solid cancers.

PMID:39227744 | DOI:10.1038/s41588-024-01874-9

Nat Genet. 2024 Sep 3. doi: 10.1038/s41588-024-01890-9. Online ahead of print.

ABSTRACT

In combination with cell-intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with neoadjuvant chemotherapy and radiotherapy. We developed spatially constrained optimal transport interaction analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid coculture system. We identified enrichment in interleukin-6 family signaling that functionally confers resistance to chemotherapy. Overall, this study demonstrates that characterization of the tumor microenvironment using single-cell spatial transcriptomics allows for the identification of molecular interactions that may play a role in the emergence of therapeutic resistance and offers a spatially based analysis framework that can be broadly applied to other contexts.

PMID:39227743 | DOI:10.1038/s41588-024-01890-9

J Neurosci. 2024 Sep 3:e0072242024. doi: 10.1523/JNEUROSCI.0072-24.2024. Online ahead of print.

ABSTRACT

Reelin, a secreted glycoprotein, plays a crucial role in guiding neocortical neuronal migration, dendritic outgrowth and arborization, and synaptic plasticity in the adult brain. Reelin primarily operates through the canonical lipoprotein receptors apolipoprotein E receptor 2 (Apoer2) and very low-density lipoprotein receptor (Vldlr). Reelin also engages with non-canonical receptors and unidentified co-receptors; however, the effects of which are less understood. Using high-throughput tandem mass tag LC-MS/MS-based proteomics and gene set enrichment analysis, we identified both shared and unique intracellular pathways activated by Reelin through its canonical and non-canonical signaling in primary murine neurons of either sex during dendritic growth and arborization. We observed pathway crosstalk related to regulation of cytoskeleton, neuron projection development, protein transport, and actin filament-based process. We also found enriched gene sets exclusively by the non-canonical Reelin pathway including protein translation, mRNA metabolic process and ribonucleoprotein complex biogenesis suggesting Reelin fine-tunes neuronal structure through distinct signaling pathways. A key discovery is the identification of aldolase A, a glycolytic enzyme and actin binding protein, as a novel effector of Reelin signaling. Reelin induced de novo translation and mobilization of aldolase A from the actin cytoskeleton. We demonstrated that aldolase A is necessary for Reelin-mediated dendrite growth and arborization in primary murine neurons and mouse brain cortical neurons. Interestingly, the function of aldolase A in dendrite development is independent of its known role in glycolysis. Altogether, our findings provide new insights into the Reelin-dependent signaling pathways and effector proteins that are crucial for dendritic development.Significance Statement Reelin is an extracellular glycoprotein that exerts its function primarily by binding to the canonical lipoprotein receptors Apoer2 and Vldlr. Reelin is best known for its role in neuronal migration during prenatal brain development. Reelin also signals through a non-canonical pathway outside of Apoer2/Vldlr; however, these receptors and signal transduction pathways are less defined. Here, we examined Reelin's role during dendritic outgrowth in primary murine neurons and identified shared and distinct pathways activated by canonical and non-canonical Reelin signaling. We also found aldolase A as a novel effector of Reelin signaling, that functions independently of its known metabolic role, highlighting Reelin's influence on neuronal structure and growth.

PMID:39227156 | DOI:10.1523/JNEUROSCI.0072-24.2024