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PubMed2025

Tractor Workflow Pipeline: A Scalable Nextflow Framework for Local Ancestry-Aware Genome-Wide Association Studies.

The routine exclusion of admixed individuals from traditional Genome-Wide Association Studies (GWAS) due to concerns about spurious associations has hindered genetic analyses involving multiple ancestries. Tractor GWAS addresses this issue by incorporating local ancestry into its analysis, empowering identification of ancestry-enriched hits and generating ancestry-specific summary statistics. However, Tractor requires accurate genomic phasing and local ancestry inference as prerequisite steps, which requires additional bioinformatics expertise and decision points regarding reference panel setup. To streamline, harmonize, and automate this process, we present a scalable Nextflow workflow that integrates all necessary steps, minimizing the need for manual intervention while remaining modular and customizable. The workflow supports multiple commonly used tools and offers flexibility in how Tractor is implemented. To demonstrate its utility, we applied this pipeline to analyze 32 blood biomarkers in 6,245 two-way AFR-EUR admixed individuals from the UK Biobank. This pipeline ran efficiently at scale, replicated known associations, and identified novel ancestry-specific loci. These novel associations were largely driven by variants present on African ancestral tracts but absent from European tracts, underscoring the value of local ancestry-aware methods in uncovering previously missed genetic signals. By enabling the efficient analysis of admixed individuals, our workflow facilitates Tractor use, paving the way for more broader genetic discovery.

Journal Article↗
PubMed2025

Mapping early PRC2 nucleation sites upon Suz12 reintroduction reveals features of de novo Polycomb recruitment.

Polycomb domains safeguard cell identity by maintaining lineage-specific chromatin states enriched in repressive histone modifications, preserving the epigenetic memory of cell lineages. While Polycomb Repressive Complex 2 (PRC2) can re-establish its occupancy after perturbation, the mechanisms that guide de novo Polycomb recruitment remain unclear. To address this, we engineered an auxin-inducible degradation system to reversibly deplete and reintroduce the endogenous PRC2 core subunit Suz12 in mouse embryonic stem cells (mESCs). Genome-wide profiling at an early recovery time point revealed ~1,100 PRC2 nucleation sites, characterized by rapid Suz12 and histone H3K27me3 re-accumulation with strong signal, with minimal impact on gene expression. These sites were significantly enriched at bivalent promoters, coinciding with unmethylated CpG islands and chromatin states associated with developmental regulation, and were largely conserved in differentiated cells. Motif analysis identified G/C-rich DNA sequences associated with E2F and zinc-finger proteins, alongside strong co-occupancy with MTF2 and JARID2, two PRC2 cofactors previously implicated in Polycomb targeting. Notably, a subset of nucleation sites overlapped with long-range chromatin interaction anchors in histone H3K27me3 HiChIP datasets. These findings reveal that PRC2 de novo nucleation sites are associated with a combination of chromatin states, DNA sequence features, cofactor co-occupancy and spatial genome organization, suggesting that epigenetic memory can be re-established through defined genomic and chromatin features.

Epigenetic memory↗
PubMed2025

The cellular associates of late life changes in white matter microstructure.

The microstructural architecture of white matter supporting information flow across local circuits and large-scale networks changes throughout the lifespan. However, the genetic and cellular factors underlying age-related variations in white matter microstructure have yet to be established. Here, we examined the genetic associates of individual differences in diffusion-based measures of white matter in a population-based cohort (N=29,862) from the UK Biobank. Estimates of heritability from Genome-Wide Association Study (GWAS) data revealed that genetic factors are linked to population variability in 96.1% of 432 tract microstructural measures. The presence of shared genetic influences was observed to be greater within, relative to between, broad tract classes (commissural, association, projection, and complex cerebellar). Age associations with microstructural changes were estimated across diffusivity measures, with association class tracts showing the greatest vulnerability to age-related decline in older adults. Analyses of imputed cellular associates of age-related changes in white matter revealed a preferential relationship with cell gene markers of oligodendrocytes and other glial cell types, with sparse relationships observed for inhibitory and excitatory cells. These data indicate that white matter tract microstructure is shaped by genetic factors and suggest a role for glial cell-related transcripts in late-life changes in the structural wiring properties of the human brain.

Aging↗
PubMed2025

Validation and Optimization of Breeding Strategy for miR-141/200c Knockout Mice to Eliminate Off-Target Gene Silencing using FLPo Deleter.

MicroRNAs (miRNAs) of the miR-200 family specifically miR-141 and miR-200c regulate neurogenesis, differentiation, and epithelial-mesenchymal transitions in development and several diseases including cancer and stroke. The STOCK Mirc13tm1Mtm /Mmjax mouse line, which targets the miR-141/200c cluster, was originally generated and described by Park et al. 2012 as a conditional "knockout-first" allele requiring a two-step breeding strategy: FLP recombination to excise lacZ/neo cassettes followed by Cre recombination to delete the floxed miRNA cluster (1). However, subsequent studies either bypassed this step and reported knockouts based on direct crosses with Cre mouse lines, leaving residual lacZ/neo sequences that may silence upstream elements or introduce transcriptional artifacts or rare studies used less efficient FLPe Deleter mice. Here, we present a detailed and refined strategy to conditional miR-141/200c knockouts mice using FLPo Deleter mice to efficiently eliminate lacZ/neo cassettes. Our approach not only confirmed complete deletion of miR-141 and miR-200c in various organs such olfactory bulbs and lungs where these miRNAs are robustly expressed using various approach such as genotyping qPCR validation and in situ hybridization but showed that without the use of FLPo deleter mice deletion of miR-141/200c cluster amy also lead to loss of several close proximity physiologically important genes such as ptpn6, phb2, atn1 and eno1. By restoring a clean floxed allele using FLPo deleter mice prior to Cre deletion, we establish a reliable and interpretable mouse model for dissecting the roles of the miR-141/200c cluster miRNA in various disease models.

Journal Article↗
PubMed2025

BOGO: A Proteome-Wide Gene Overexpression Platform for Discovering Rational Cancer Combination Therapies.

Cancer drug resistance remains a major barrier to durable treatment success, often leading to relapse despite advances in precision oncology. While combination therapies are being increasingly investigated, such as chemotherapy with small molecule inhibitors, predicting drug response and identifying rational drug combinations based on resistance mechanisms remain major challenges. Therefore, a proteome-wide, single-gene overexpression screening platform is essential for guiding rational therapy selection. Here, we present BOGO (Bxb1-landing pad human ORFeome-integrated system for a proteome-wide Gene Overexpression), a robust, scalable, and reproducible screening platform that enables single-copy, site-specific integration and overexpression of ~19,000 human open across cancer cell models. Using BOGO, we identified drug-specific response drivers for 16 chemotherapeutic agents and integrated clinical datasets to uncover proliferation and resistance-associated genes with prognostic potential. Drug response similarity networks revealed both shared and unique mechanisms, highlighting key pathways such as autophagy, apoptosis, and Wnt signaling, and notable resistance-associated genes including BCL2, POLD2, and TRADD. In particular, we proposed a synergistic combination of the BCL2 family inhibitor ABT-263 (Navitoclax®) and the DNA analog TAS-102 (Lonsurf®), which revealed that lysosomal modulation is a key mechanism driving DNA analog resistance. This combination therapy selectively enhanced cytotoxicity in colorectal and pancreatic cancer cells in vitro, and demonstrated therapeutic benefit in vivo in both cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models. Together, these findings establish BOGO as a powerful gene overexpression perturbation platform for systematically identifying chemoresistance and chemosensitization drivers, and for discovering rational combination therapies. Its scalability and reproducibility position BOGO as a broadly applicable tool for functional genomics and therapeutic discovery beyond cancer resistance.

Journal Article↗
PubMed2025

PATTY corrects open chromatin bias for improved bulk and single-cell CUT&Tag profiling.

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5's preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

Journal Article↗
PubMed2025

MetaChrome: An Open-Source, User-Friendly Tool for Automated Metaphase Chromosome Analysis.

DNA Fluorescence In Situ Hybridization (FISH) is an essential technique to study chromosome biology and genetics, enabling precise visualization of specific genomic loci to study structural abnormalities, gene mapping, and chromosomal rearrangements. High-Throughput Imaging (HTI) can automate the analysis of DNA-FISH chromosome images, but the accurate and automated segmentation of mitotic chromosomes and simultaneous colocalization of FISH signals remains a challenge. While several commercial automated karyotyping tools partially solve these issues, open-source software that effectively combines robust chromosome segmentation with comprehensive colocalization analysis capabilities remains necessary. To address this unmet need, we developed MetaChrome, an open-source software platform built around a graphical user interface and explicitly designed for automated metaphase chromosome analysis. MetaChrome leverages fine-tuned deep learning models to automate metaphase chromosome segmentation, together with colocalization analysis of chromosome-specific FISH probes and immunofluorescent-labeled proteins. Importantly, MetaChrome achieves enhanced segmentation accuracy compared to traditional image processing methods by adopting a Cellpose segmentation model fine-tuned with manually annotated metaphase chromosome datasets. The fine-tuned model ensures precise assignment of DNA-FISH spots to individual chromosomes in an automated manner. This facilitates rapid identification of chromosomal abnormalities, reduces human error, and advances high-throughput chromosome analysis workflows, addressing a key bottleneck in chromosome biology research.

Chromosome segmentation↗
PubMed2025

Modeling Alternative Conformational States in CASP16.

The CASP16 Ensemble Prediction experiment assessed advances in methods for modeling proteins, nucleic acids, and their complexes in multiple conformational states. Targets included systems with experimental structures determined in two or three states, evaluated by direct comparison to experimental coordinates, as well as domain-linker-domain (D-L-D) targets assessed against statistical models from NMR and SAXS data. This paper focuses on the former class of multi-state targets. Ten ensembles were released as community challenges, including ligand-induced conformational changes, protein-DNA complexes, a trimeric protein, a stem-loop RNA, and multiple oligomeric states of a single RNA. For five targets, some groups produced reasonably accurate models of both reference states (best TM-score >0.75). However, with the exception of one protein-ligand complex (T1214), where an apo structure was available as a template, predictors generally failed to capture key structural details distinguishing the states. Overall, accuracy was significantly lower than for single-state targets in other CASP experiments. The most successful approaches generated multiple AlphaFold2 models using enhanced multiple sequence alignments and sampling protocols, followed by model quality based selection. While the AlphaFold3 server performed well on several targets, individual groups outperformed it in specific cases. By contrast, predictions for one protein-DNA complex, three RNA targets, and multiple oligomeric RNA states consistently fell short (TM-score <0.75). These results highlight both progress and persistent challenges in multi-state prediction. Despite recent advances, accurate modeling of conformational ensembles, particularly RNA and large multimeric assemblies, remains a critical frontier for structural biology.

AlphaFold2↗
PubMed2025

PARTAGE: Parallel analysis of replication timing and gene expression.

The human genome is partitioned into functional compartments that replicate at specific times during the S-phase. This temporal program, referred to as replication timing (RT), is co-regulated with the 3D genome organization, is cell type-specific, and changes during development in coordination with gene expression. Moreover, RT alterations are linked to abnormal gene expression, genome instability, and structural variation in multiple diseases, including cancer. However, mechanistic links between RT, large-scale 3D genome architecture, and transcriptional regulation remain poorly understood. A major limitation is that current approaches require the separate profiling of RT and transcriptomes from independent batches of samples, obscuring the complex co-regulation between the epigenome and transcriptome. Here, we developed PARTAGE, a multiomics approach that enables joint profiling of copy number variation (CNV), RT, and gene expression from the same sample, providing a more accurate integrative view of the complex relationships between RT and gene regulation.

Journal Article↗
PubMed2025

SH2-mediated steric occlusion of the C2 domain regulates autoinhibition of SHIP1 inositol 5-phosphatase.

The Src homology 2 (SH2) domain containing inositol polyphosphate 5-phosphatase 1 (SHIP1) is an immune cell specific enzyme that regulates phosphatidylinositol-(3,4,5)-trisphosphate signaling at the plasma membrane following receptor activation. SHIP1 plays an important role in processes such as directed cell migration, endocytosis, and cortical membrane oscillations. Alterations in SHIP1 expression have been shown to perturb myeloid cell chemotaxis and differentiation. In the brain, SHIP1 regulate microglial cell behaviors, which has been linked to Alzheimer's disease. Understanding the structural and functional relationships of SHIP1 is critical for developing ways to modulate SHIP1 membrane localization and lipid phosphatase activity during immune cell signaling. Recently, we discovered that the N-terminal SH2 domain of SHIP1 suppresses lipid phosphatase activity. SHIP1 autoinhibition can be relieved through interactions with receptor-derived phosphotyrosine (pY) peptides presented on membranes or in solution. Using hydrogen-deuterium exchange mass spectrometry (HDX-MS) we identified intramolecular contacts between the N-terminal SH2 domain and CBL1 motif of the C2 domain that limit SHIP1 membrane localization and activity. Single molecule measurements of purified SHIP1 on supported lipid bilayers and in neutrophil-like cells support a model in which the SH2 domain blocks membrane binding of the central catalytic module. Mutations that disrupt autoinhibition enhance the membrane binding frequency and increase the catalytic efficiency of SHIP1. Although dimerization of SHIP1 enhances membrane localization and the apparent phosphatase activity, it is not required for SHIP1 autoinhibition. Overall, our results provide new insight concerning SHIP1's structural organization, membrane binding dynamics, and the mechanism of autoinhibition.

Journal Article↗
PubMed2025

A New Type of Nonsuppressible Viremia Produced by HIV-Infected Macrophage.

BACKGROUND: HIV-1 RNA typically declines rapidly after initiation of antiretroviral therapy (ART); often reaching undetectable levels within a few weeks and remaining undetectable by standard assays. However, some patients on ART have persistent nonsuppressible viremia (NSV) that does not respond to treatment optimization or intensification. NSV can emerge at the time of ART initiation (primary NSV) or after being ART-suppressed (secondary NSV). Here, we examine mechanisms producing primary NSV in four people on ART. METHODS: Blood samples were collected from four participants who, despite being adherent to ART, required approximately a year or more to become virologically suppressed. Viral RNA and proviral DNA genomes were sequenced to examine HIV-1 drug resistance, genome intactness and genetic diversity. The ability of HIV-1 Envs to facilitate efficient entry into cells expressing low levels of CD4 (a proxy for macrophage tropism) was assessed. RESULTS: Before ART, the blood contained HIV-1 RNA genomes that were adapted to replication in CD4+ T cells and rapidly decayed after ART initiation. During ART, the blood contained HIV-1 genomes that were drug sensitive, genetically diverse, macrophage-tropic, not evolving and often had defects in vpr. CONCLUSIONS: Our results suggest that in individuals with primary NSV, ART stopped virus replication, but large pools of long-lived, HIV-infected macrophage continued to produce virus. This is mechanistically distinct from secondary NSV produced by CD4+ T cell clones. In addition, defects in vpr independently accumulation in macrophage-tropic lineages found in three participants, suggesting that vpr may impact survival of, or virus production from, HIV-infected macrophage.

Journal Article↗
PubMed2025

Predicting emergent phenotypes from single cell populations using CELLECTION.

Biological systems exhibit emergent phenotypes that arise from the collective behavior of individual components, such as whole-organ functions that arise from the coordinated activity of its individual cells, or organism-level phenotypes that result from the functional interplay of collections of genes in the genome. We present CELLECTION, a deep learning framework that learns to associate subgroups of instances with different emergent phenotypes. We show CELLECTION enables interpretable predictions for heterogeneous tasks, including disease classification, identification of disease-associated cell subtypes, alignment of developmental stages between human model systems, and even predicting relative hand-wing indices across the avian lineage. CELLECTION therefore provides a scalable and flexible framework for identifying key cellular or genetic signatures underlying complex traits in development, disease, and evolution.

Journal Article↗
PubMed2025

Incubator-Free Organoid Culture in a Sealed Recirculatory System.

Organoids are powerful tools for studying development and disease, offering realistic organ-like human and animal tissues and facilitating experimental observation compared to live animal models. However, traditional organoid culture methods require a humidified incubator. This requirement complicates culture due to evaporative losses and restricted access to instrumentation, hindering the potential of organoids as physiologically accurate models easily subjected to detailed experimental observation. We introduce a compact, automated, sealed, incubator-free recirculatory organoid culture platform that replaces the air-liquid interface with a nonporous polymer gas exchanger and a liquid-phase gas buffer. This design prevents evaporation and stabilizes oxygen, pH, and osmolarity without feedback control. It enables single-actuator media exchange, simplifying automation. Dispensing with the incubator, we improve access for instruments such as live cell microscopes. We demonstrate compatibility with continuous multi-week live imaging of vascular organoids and show that brain organoids in this system maintain metabolic viability, structural fidelity, and electrophysiological activity comparable to traditional shaker-based cultures in an incubator.

Journal Article↗
PubMed2025

Design Rules for Expanding PAM Compatibility in CRISPR-Cas9 from the VQR, VRER and EQR variants.

Expanding the range of Protospacer Adjacent Motifs (PAMs) recognized by CRISPR-Cas9 is essential for broadening genome-editing applications. Here, we combine molecular dynamics simulations with graph-theory and centrality analyses to dissect the principles of PAM recognition in three Cas9 variants - VQR, VRER, and EQR - that target non-canonical PAMs. We show that efficient recognition is not dictated solely by direct contacts between PAM-interacting residues and DNA, but also by a distal network that stabilizes the PAM-binding domain and preserves long-range communication with REC3, a hub that relays signals to the HNH nuclease. A key role emerges for the D1135V/E substitution, which enables stable DNA binding by K1107 and preserves key DNA phosphate locking interactions via S1109, securing stable PAM engagement. In contrast, variants carrying only R-to-Q substitutions at PAM-contacting residues, though predicted to enhance adenine recognition, destabilize the PAM-binding cleft, perturb REC3 dynamics, and disrupt allosteric coupling to HNH. Together, these findings establish that PAM recognition requires local stabilization, distal coupling, and entropic tuning, rather than a simple consequence of base-specific contacts. This framework provides guiding principles for engineering Cas9 variants with expanded PAM compatibility and improved editing efficiency.

Journal Article↗
PubMed2025

MondoA mediates transcriptional coordination between the MYC network and the integrated stress response in pancreatic ductal adenocarcinoma.

MYC amplification contributes to poor survival and outcome in pancreatic ductal adenocarcinoma (PDAC). Here we show that in PDAC cell lines with amplified MYC, MondoA is required for viability, facilitating proliferation while suppressing apoptosis in vitro and in vivo. Transcriptional and genomic profiling demonstrates that loss of MondoA leads to altered expression of direct MondoA targets as well as MYC target genes and is accompanied by shifts in genomic occupancy of MYC, MNT, and the MondoA paralog ChREBP. This altered genomic binding by MYC network members is associated with transcriptional perturbation of multiple metabolic and stress pathways, as well as global changes in N6-methyladenosine modification (m6A) of mRNA. MondoA inhibition disrupts coordination between MYC network members and the Integrated Stress Response (ISR), resulting in decreased translation of ATF4 mRNA, discordant gene regulation of shared targets of MYC and ATF4 and, ultimately, apoptosis. Re-establishing ATF4 protein expression rescues the diminished viability due to loss of MondoA expression or activity, providing direct evidence of a link between deregulated MYC and the transcriptional machinery of the ISR. Lastly, we find that small-molecule inhibition of MondoA is lethal in a subset of PDAC cell lines, including patient-derived organoids, suggesting that the ability to target MYC via chemical inhibition of MondoA transcriptional activity may have broad efficacy.

Cell Biology↗
PubMed2025

STRUMP-I: Structure-based machine learning approach to pMHC-I binding prediction using force field energy features.

The adaptive immune system monitors cellular integrity by recognizing short peptides from intracellular proteins presented on Major Histocompatibility Complex class I (MHC-I) molecules, collectively termed peptide-MHC complexes (pMHC), enabling detection of foreign or mutated proteins. With the rising importance of immunotherapies targeting neoantigens in cancers, the ability to accurately predict which peptides will bind to the diverse population of MHC alleles is critically important. Current computational methods for pMHC-I prediction fall broadly into sequence-based methods, which rely heavily on large training datasets, and structure-based methods that leverage structural modeling and energetics of pMHC binding. While sequence-based methods have been popularly used, their performance is dependent on the size and quality of training data. On the other hands, while structure-based approaches can generalize better across diverse MHC alleles, they traditionally depend on identifying a single global minimum energy conformation, an assumption that often fails due to the inherent binding promiscuity of MHC-I molecules. To address these limitations, we developed a STRUMP-I (STRUcture-based pMHC Prediction (for class I)), a novel pMHC binding prediction tool that directly leverages a broad set of force-field-derived energy terms as machine-learning features. STRUMP-I achieves performance comparable to state-of-the-art sequence-based models while significantly outperforming them on MHC alleles with limited representation in training data. Furthermore, STRUMP-I demonstrates strong synergy when integrated with sequence-based methods, notably enhancing prediction precision. The robustness and generalizability of STRUMP-I were confirmed by evaluating its predictive performance on independent, previously unseen datasets, including an experimentally validated cancer neoantigen dataset. This combined approach advances our capability to reliably identify clinically relevant neoantigen targets. The source code and trained models are available at https://github.com/yoonjoolab/STRUMP-I.

energy optimization↗
PubMed2025

kSanity: A k-mer based application for precision bacterial strain detection and quantification.

MOTIVATION: Accurate detection and quantification of bacterial strains in clinical samples is necessary to measure their colonization and persistence. Past methods to achieve this relied either on strain-specific qPCR assays, or shotgun metagenomic read mapping approaches. The resident microbial community is a major source of interference in both assays because it can contain conspecific strains bearing similarity to the focal strain(s). RESULTS: We present kSanity, a k-mer based application for the detection and quantification of targeted bacterial strains in shotgun metagenomic data. Because kSanity uses exact string matches between the reads and reference, it is less sensitive to interference by conspecific strains. We test the performance of kSanity using a combination of in silico spike-in experiments, and in vivo observational data. Our results demonstrate that kSanity provides precise and accurate quantification of targeted bacterial strains, even when they are present at low sequence coverage in the metagenome. AVAILABILITY AND IMPLEMENTATION: kSanity is available at: https://github.com/ravel-lab/kSanity.

bacterial strain detection↗
PubMed2025

Inhibition of autophagy-lysosomal function exacerbates microglial and monocyte lipid metabolism reprograming and dysfunction after brain injury.

CNS has an overall higher level of lipids than all tissues except adipose and contains up to 25% of total body cholesterol. Recent data demonstrate a complex crosstalk between lipid metabolism and inflammation, suggesting potential contribution of the lipid-rich brain environment to neuroinflammation. While recent data support the importance of brain lipid environment to inflammatory changes observed in age related chronic neurodegenerative diseases, in vivo interactions between lipid environment, lipid metabolism and neuroinflammation in acute brain disease and injury remain poorly understood. Here we utilize a mouse model of traumatic brain injury (TBI) to demonstrate that acute neurotrauma leads to widespread lipid metabolism reprograming in all microglial and brain associated and infiltrating monocyte populations. Additionally, we identify unique microglial and monocyte populations with higher degree of lipid metabolism reprograming and pronounced accumulation of neutral storage lipids, including cholesteryl esters and triglycerides. These lipids accumulate not only in lipid droplets but also in the microglial and monocyte lysosomes and are associated with lysosomal dysfunction and inhibition of autophagy after TBI. Our data indicate that lipid accumulation in these cells is the result of altered lipid handling rather than lipid synthesis and is triggered by phagocytosis of lipid-rich myelin debris generated after TBI. Finally, we use mice with autophagy defects in microglia and monocytes to demonstrate that further inhibition of autophagy leads to more pronounced lipid metabolism reprograming and exacerbated cellular lipid accumulation. Our data suggest a pathological feedback loop, where lipid phagocytosis causes inhibition of autophagy-lysosomal function, which in turn exacerbates cellular lipid retention, reprograming and inflammation.

Journal Article↗