Biology subjects

Lee, S.

Publications and source records attributed to Lee, S..

At least 307 records · Page 17Linked to original sources

bioRxiv2024

Genetic modifiers of somatic expansion and clinical phenotypes in Huntington's disease reveal shared and tissue-specific effects

Huntingtons disease (HD), due to expansion of a CAG repeat in HTT, is representative of a growing number of disorders involving somatically unstable short tandem repeats. We find that overlapping and distinct genetic modifiers of clinical landmarks and somatic expansion in blood DNA reveal an underlying complexity and cell-type specificity to the mismatch repair-related processes that influence disease timing. Differential capture of non-DNA-repair gene modifiers by multiple measures of cognitive and motor dysfunction argues additionally for cell-type specificity of pathogenic processes. Beyond trans modifiers, differential effects are also illustrated at HTT by a 5-UTR variant that promotes somatic expansion in blood without influencing clinical HD, while, even after correcting for uninterrupted CAG length, a synonymous sequence change at the end of the CAG repeat dramatically hastens onset of motor signs without increasing somatic expansion. Our findings are directly relevant to therapeutic suppression of somatic expansion in HD and related disorders and provide a route to define the individual neuronal cell types that contribute to different HD clinical phenotypes.

genetics↗

bioRxiv2024

Determination of the absolute concentration of Rayleigh particles via scattering microscopy

Nanoparticles are crucial in diverse fields such as healthcare, electronics, and energy. Their small size allows them to cross biological barriers, enhancing drug delivery but also posing health risks. Accurate characterization of nanoparticles is essential for assessing their safety and efficacy, particularly in medical applications. Traditional methods such as dynamic light scattering and mass spectrometry have limitations in sensitivity and range of application. To address these challenges, we introduce the interferometric Concentration Analyzer and Ultrasmall Nanoparticle Tracker (iCAUNT), a technique for detecting and quantifying nanoparticles smaller than one-tenth of the imaging light wavelength. As a non-invasive method, iCAUNT provides precise size and concentration measurements of biological and synthetic nanoparticles, offering significant potential for diagnostics, therapeutics, and broader nanoscience applications.

biophysics↗

bioRxiv2024

Oryza genome evolution through a tetraploid lens

Oryza is remarkable genus - with two domesticated (i.e. Asian and African rice) and 25 diploid and tetraploid wild species, 11 extant genome types, and a [~]3.4-fold genome size variation - that possesses a virtually untapped reservoir of genes that can be used for crop improvement. Here we unveil and interrogate 11 new chromosome-level assemblies of nine tetraploid and two diploid wild Oryza species in the context of [~]15 million years of evolution of the genus. We show that the core Oryza (sub)genome across all genome types is only [~]200 Mb and largely syntenic, while the remaining nuclear fractions, spanning [~]80-600 Mb, are intermingled, extremely plastic and rapidly evolving. For the halophyte O. coarctata, we show that - despite the detection of gene fractionation in the subgenomes - homoeologous genes are expressed at higher levels in one subgenome over the other in a mosaic form, thereby showing subgenome equivalence. The integration of these 11 new ultra-high quality reference genomes with our previously published genome data sets provide a nearly complete picture of the consequences of natural and artificial selection across the evolutionary history of Oryza. This in turn opens the door to unlock their genetic potential for future crop improvement and neodomestication.

genomics↗

bioRxiv2024

Identification of 17 novel epigenetic biomarkers associated with anxiety disorders using differential methylation analysis followed by machine learning-based validation

BackgroundThe changes in DNA methylation patterns may reflect both physical and mental well-being, the latter being a relatively unexplored avenue in terms of clinical utility for psychiatric disorders. In this study, our objective was to identify the methylation-based biomarkers for anxiety disorders and subsequently validate their reliability. MethodsA comparative differential methylation analysis was performed on whole blood samples from 94 anxiety disorder patients and 296 control samples using targeted bisulfite sequencing. Subsequent validation of identified biomarkers employed an artificial intelligence- based risk prediction models: a linear calculation-based methylation risk score model and two tree-based machine learning models: Random Forest and XGBoost. Results17 novel epigenetic methylation biomarkers were identified to be associated with anxiety disorders. These biomarkers were predominantly localized near CpG islands, and they were associated with two distinct biological processes: 1) cell apoptosis and mitochondrial dysfunction and 2) the regulation of neurosignaling. We further developed a robust diagnostic risk prediction system to classify anxiety disorders from healthy controls using the 17 biomarkers. Machine learning validation confirmed the robustness of our biomarker set, with XGBoost as the best-performing algorithm, an area under the curve of 0.876. ConclusionOur findings support the potential of blood liquid biopsy in enhancing the clinical utility of anxiety disorder diagnostics. This unique set of epigenetic biomarkers holds the potential for early diagnosis, prediction of treatment efficacy, continuous monitoring, health screening, and the delivery of personalized therapeutic interventions for individuals affected by anxiety disorders.

bioinformatics↗

bioRxiv2024

GluN2B-mediated regulation of silent synapses for receptor specification and addiction memory

Psycho-stimulants including cocaine elicit stereotyped, addictive behaviors. Re-emergence of silent synapses containing only NMDA-type glutamate receptors (NMDARs) is a critical mediator of addiction memory and seeking behaviors. Despite the predominant abundance of GluN2B-containing NMDARs in silent synapses, their operational mechanisms are not fully understood. Using conditional depletion/deletion of GluN2B at D1-expressing accumbal medium spiny neurons, we examine the synaptic and behavioral actions that silent synapses incur after repeated exposure to cocaine. GluN2B ablation reduces the proportion of silent synapses, but some of them can persist by substitution to GluN2C, which drives the aberrantly-facilitated synaptic incorporation of calcium-impermeable AMPA-type glutamate receptors (AMPARs). The resultant precocious maturation of silent synapses impairs addiction memory but elevates locomotor activity, which can be normalized by blockade of calcium-impermeable AMPAR trafficking. Collectively, GluN2B supports the competence of cocaine-induced silent synapses for specifying subunit composition of AMPARs, and thereby expression of addition memory and the related behaviors.

neuroscience↗

bioRxiv2024

Nothing but lies: improving the validity of neural predictors of deception

Deception is a universal human behavior. Yet longstanding skepticism about the validity of measures used to understand the biological mechanisms underlying deceptive behavior has relegated such studies to the scientific periphery. Here we address these fundamental questions by applying novel machine learning methods and functional neuroimaging to signaling games capturing motivated deception in human participants. First, we develop an approach to test for the presence of confounding processes and thereby validate past skepticism by showing that much of the predictive power of neural predictors trained on deception data comes from confounding processes. Second, we show that the presence of confounding signals need not be fatal, and we improve the validity of our neural predictor via a novel machine learning procedure that identifies and removes these confounding signals. Together, these findings point to a scientific approach for studying a neglected class of behavior, with important methodological and societal implications.

neuroscience↗

bioRxiv2024

Noninvasive time-lapse 3D subcellular analysis of embryo development for machine learning-enabled prediction of blastocyst formation

Accurate embryo quality assessment is central to improving outcomes in in vitro fertilization (IVF), yet current practice relies mainly on subjective two-dimensional (2D) morphology. Here we present a label-free framework for quantitative three-dimensional (3D) embryo phenotyping using low-coherence holotomography (HT). Time-lapse HT enabled volumetric imaging of mouse embryos from the 2-cell stage to the blastocyst without affecting developmental competence, capturing subcellular features at high resolution. Quantitative analysis revealed that matured embryos exhibited higher blastomere counts, greater spatial variability, and tighter nuclear packing, whereas arrested embryos showed enlarged blastomeres, elevated cytoplasmic heterogeneity, and fewer, larger nuclei. Machine learning models trained on these features achieved robust prediction of blastocyst formation (AUC up to 0.958). Together, these findings demonstrate that HT provides objective and interpretable 3D biomarkers that could augment and transform embryo selection in IVF.

developmental biology↗

bioRxiv2024

Untargeted Plasma Metabolomics Unveils Distinct Metabolite Profiles in Parkinson Disease Subtypes: A Focus on idiopathic REM Sleep Behavior Disorders

BackgroundParkinsons disease (PD) is characterized by diverse clinical presentations and etiological complexities, with rapid eye movement (REM) sleep behavior disorder (RBD) serving as a prodromal marker. While extensive unbiased metabolic profiling of plasma samples from PD subjects has been conducted to identify novel PD metabolic biomarkers, comprehensive metabolic profiling of PD subtypes based on RBD status remains limited. MethodsWe conducted a comprehensive metabolic profiling of PD subtypes at disease onset, considering the presence or absence of RBD, utilizing an untargeted metabolomics approach. Plasma samples were collected from subjects with PD with and without RBD at the initial stages of disease, idiopathic RBD, and healthy controls to elucidate similarities and differences among PD subtypes. Based on ordination analysis and metabolome-wide association study (Wilcoxon rank-sum tests and generalized fold changes), we identified specific groups of metabolites enriched in the PD_Only group and RBD groups (iRBD & PD_RBD+), with few metabolites shared between groups. Furthermore, pathway enrichment analysis (hypergeometric tests) identified specific groups enriched with metabolites from specific origins and associated biospecimens, as well as disease-associated metabolites. Finally, we evaluated the biomarker potential of the identified disease metabolites by ROC curves and proposed logistic regression models of key biomarkers and clinical parameters for predicting disease status. ResultsMetabolomic analysis revealed distinct metabolic profiles between PD subtypes with and without RBD. Our analysis confirmed previously reported PD metabolic markers, such as a reduction in caffeine and urate, as well as an increase in cortisol, secondary bile acids, and p-cresol sulfate. However, our stratified analyses based on the presence of RBD discriminated RBD-associated metabolites from those associated with PD_Only (without RBD). PD patients with RBD exhibited enrichment of gut microbial-origin metabolites, including secondary bile acids and p-cresol sulfate, compared to PD patients without RBD. Conversely, metabolites associated with neuro-psychiatric diseases were enriched in PD patients without RBD. ConclusionsOur study elucidates the heterogeneous nature of PD subtypes, particularly differentiated with the presence of RBD. The metabolic features of PD with RBD subtype supports the "body-first" concept of PD pathogenesis originating from the gut.

systems biology↗

bioRxiv2024

Deep Quantitative Proteomics Identifies Conserved Proteome Alterations in Low and High-Grade Serous Ovarian Cancers

BackgroundLow-grade serous ovarian carcinoma (LGSOC) is a rare and largely chemoresistant subtype of epithelial ovarian cancer. Unlike treatment for high-grade serous ovarian cancer (HGSOC), management options for LGSOC patients are limited, in part, due to a lack of deep molecular characterization of this disease. To address this limitation, we aimed to define highly conserved proteome alterations in LGSOC by performing deep quantitative proteomic analysis of tumors collected from LGSOC (n=12) and HGSOC (n=24) patients or normal fallopian tube tissues (n=12) and validating proteins within two independent proteomic datasets of LGSOC (n=25) and HGSOC (n=49) tumors. ResultsOur efforts identified 275 protein alterations conserved between LGSOC and HGSOC tumors that exhibit high quantitative correlation between discovery and validation cohorts (Spearman Rho [≥] 0.82, P < 1E-4). Conserved proteins elevated in LGSOC tumors were enriched for pathways regulating cell adhesion and defective cellular apoptosis signaling and candidates mapping as putative drug targets included 5-nucleotidase/ cluster of differentiation 73 (NT5E/CD73). We also identified MUC16 (CA125) as significantly elevated in LGSOC versus HGSOC tumors and confirmed this by immunohistochemistry analysis between three independent reviewers. We also find that MUC16 exhibits a more apical versus membrane-staining pattern in LGSOC tumors, suggesting unique regulation of MUC16 in this disease subtype. ConclusionOur efforts define highly conserved protein alterations distinguishing LGSOC from HGSOC tumors, including CD73, as well as the novel identification that MUC16 is elevated and exhibits more apical staining pattern in LGSOC tumor tissues. These findings deepen our molecular understanding of LGSOC and provide unique insights into highly conserved proteome alterations in LGSOC tumors.

cancer biology↗

bioRxiv2024

Sacrificing Adaptability for Functionality: The Ivory Tower of Macular Muller Cells

The predilection of many retinal diseases for the macula suggests it may be less resistant to stress than the peripheral retina. Profiling of single-cell level transcriptional changes found that the peripheral retina exhibited more transcriptional changes than the macula in response to stress. One pronounced change was in a subgroup of Muller cells (MCs) that were dominant in the peripheral retina. Genes more abundantly expressed in peripheral MCs were mainly associated with stress responses and were more influenced by light stress. In contrast, genes highly expressed in MCs that predominated in the macula had roles in cellular function and were less influenced by light stress. Metallothionein 1, A Kinase Anchor Protein 12 and MAF BZIP Transcription Factor F were more abundantly expressed in peripheral MCs than in macular MCs. Knockdown of these genes in primary MCs reduced their viability under stress. Our findings indicate that macular MCs are more directed toward maintaining retinal function rather than mounting a stress response when exposed to stress, which may contribute to the maculas vulnerability to degenerative diseases.

neuroscience↗

bioRxiv2024

SN-FPN: Self-attention Nested Feature Pyramid Network for Digital Pathology Image Segmentation

Digital pathology has played a key role in replacing glass slides with digital images, enhancing various pathology workflows. Whole slide images are digitized pathological images improving the capabilities of digital pathology and contributing to the overall turnaround time for diagnoses. The digitized images have been successfully integrated with artificial intelligence algorithms assisting pathologists in many tasks, but there are still demands to develop a new algorithm for a better diagnosis process. In this paper, we propose a new deep convolutional neural network model integrating a feature pyramid network with a self-attention mechanism in three pathways: encoder, decoder, and self-attention nested for providing accurate tumor region segmentation on whole slide images. The encoder pathway adopts ResNet50 architecture for the bottom-up network. The decoder pathway adopts the feature pyramid network for the top-down network. The self-attention nested pathway forms the attention map represented by the distribution of attention scores focusing on localizing tumor regions and avoiding irrelevant information. The results of our experiment show that the proposed model outperforms the state-of-the-art deep convolutional neural network models in terms of tumor and stromal region segmentation. Moreover, various encoder networks were equipped with the proposed model and compared with each other. The results indicate that the ResNet series using the proposed model outperforms other encoder networks.

bioinformatics↗

bioRxiv2024

Genome-Wide Transcriptome Dynamics in Auxin Homeostasis During Fruit Development in Strawberry (F. x ananassa)

The plant hormone auxin plays a crucial role in regulating important functions in strawberry fruit development. Although a few studies have described the complex auxin biosynthetic and signaling pathway in wild diploid strawberry (Fragaria vesca), the molecular mechanisms underlying auxin biosynthesis and crosstalk in octoploid strawberry fruit development are not fully characterized. To address this knowledge gap, comprehensive transcriptomic analyses were conducted at different stages of fruit development and compared between the achene and receptacle to identify developmentally regulated auxin biosynthetic genes and transcription factors during the fruit ripening process. Similar to wild diploid strawberry, octoploid strawberry accumulates high levels of auxin in achene compared to receptacle. Consistently, genes functionating in auxin biosynthesis and conjugation, such as TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS (TAAs), YUCCA (YUCs), and GRETCHEN HAGEN 3 (GH3s) were found to be primarily expressed in the achene, with low expression in the receptacle. Interestingly, several genes involved in auxin transport and signaling like PIN-FORMED (PINs), AUXIN/INDOLE-3-ACETIC ACID proteins (Aux/IAAs), TRANSPORT INHIBITOR RESPONSE 1 / AUXIN-SIGNALING F-BOX (TIR/AFBs) and AUXIN RESPONSE FACTOR (ARFs) were more abundantly expressed in the receptacle. Moreover, by examining DEGs and their transcriptional profiles across all six developmental stages, we identified key auxin-related genes co-clustered with transcription factors from the NAM-ATAF1,2-CUC2/ WRKYGQK motif (NAC/WYKY), BASIC REGION/ LEUCINE ZIPPER motif (bZIP), and APETALA2/Ethylene Responsive Factor (AP2/ERF) groups. These results elucidate the complex regulatory network of auxin biosynthesis and its intricate crosstalk within the achene and receptacle, enriching our understanding of fruit development in octoploid strawberries.

developmental biology↗

bioRxiv2024

Calculating Protein-Ligand Residence Times Through State Predictive Information Bottleneck based Enhanced Sampling

Understanding drug residence times in target proteins is key to improving drug efficacy and understanding target recognition in biochemistry. While drug residence time is just as important as binding affinity, atomiclevel understanding of drug residence times through molecular dynamics (MD) simulations has been difficult primarily due to the extremely long timescales. Recent advances in rare event sampling have allowed us to reach these timescales, yet predicting protein-ligand residence times remains a significant challenge. Here we present a semi-automated protocol to calculate the ligand residence times across 12 orders of magnitudes of timescales. In our proposed framework, we integrate a deep learning-based method, the state predictive information bottleneck (SPIB), to learn an approximate reaction coordinate (RC) and use it to guide the enhanced sampling method metadynamics. We demonstrate the performance of our algorithm by applying it to six different protein-ligand complexes with available benchmark residence times, including the dissociation of the widely studied anti-cancer drug Imatinib (Gleevec) from both wild-type Abl kinase and drug-resistant mutants. We show how our protocol can recover quantitatively accurate residence times, potentially opening avenues for deeper insights into drug development possibilities and ligand recognition mechanisms. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/589710v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@11dc13borg.highwire.dtl.DTLVardef@79103dorg.highwire.dtl.DTLVardef@194b67org.highwire.dtl.DTLVardef@a570e3_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Comprehensive Whole Genome Sequencing Reveals Origins of Mutational Signatures Associated with Aging and Temozolomide Chemotherapy

In a comprehensive study to decipher the multi-layered response to the chemotherapeutic agent temozolomide (TMZ), we analyzed 427 genomes and determined mutational patterns in a collection of [~]40 isogenic DNA repair-deficient human TK6 lymphoblast cell lines. We demonstrate that the spontaneous mutational background is very similar to the aging-associated mutational signature SBS40 and mainly caused by polymerase zeta-mediated translesion synthesis (TLS). MSH2-/- mismatch repair knockout in conjunction with additional repair deficiencies uncovers cryptic mutational patterns. We report how distinct mutational signatures are induced by TMZ upon sequential inactivation of DNA repair pathways, mirroring the acquisition of chemotherapy resistance by glioblastomas. The most toxic adduct induced by TMZ, O6-meG, is directly repaired by the O6-methylguanine-DNA methyltransferase (MGMT). In MGMT-/- cells, mismatch repair (MMR) leads to cell death and limits mutagenesis. MMR deficiency results in TMZ resistance, allowing the accumulation of [~]105 C>T substitutions corresponding to signature SBS11. Under these conditions, N-alkylated bases, processed by base excision repair (BER), limit cell survival. Without BER, 3-meA is read through via error-prone TLS, causing T>A substitutions but not affecting survival. Blocking BER after abasic site formation results in large deletions and TMZ hypersensitization. Our findings reveal potential vulnerabilities of TMZ-resistant tumors.

genomics↗

bioRxiv2024

Source-to-Tap Investigation of the Occurrence of Nontuberculous Mycobacteria in a Full-Scale Chloraminated Drinking Water System

Nontuberculous mycobacteria (NTM) in drinking water are a significant public health concern. However, an incomplete understanding of the factors that influence the occurrence of NTM in drinking water limits our ability to characterize risk and prevent infection. This study sought to evaluate the influence of season and water treatment, distribution, and stagnation on NTM in drinking water. Samples were collected source-to-tap in a full-scale, chloraminated drinking water system approximately monthly from December 2019 to November 2020. NTM were characterized using culture-dependent (plate culture with matrix-assisted laser desorption ionization-time of flight mass spectrometry [MALDI-TOF MS] isolate analysis) and culture-independent methods (quantitative PCR and genome resolved metagenomics). Sampling locations included source waters, three locations within the treatment plant, and five buildings receiving water from the distribution system. Building plumbing samples consisted of first draw, five-minute flush, and full flush cold-water samples. As the study took place during the COVID-19 pandemic, the influence of reduced water usage in three of the five buildings was also investigated. The highest concentrations of NTM source-to-tap were found in the summer first draw building water samples (107 gene copies/L), which also had the lowest chloramine concentrations. Flushing was found to be effective for reducing NTM and restoring disinfectant residuals, though flush times necessary to improve water quality varied by building. Clinically-relevant NTM species, including Mycobacterium avium, were recovered via plate culture, with increased occurrence observed in buildings with higher water age. Four of five NTM metagenome-assembled genomes were identified to the species level and matched identified isolates. ImportanceNTM infections are increasing in prevalence, difficult to treat, and associated with high mortality rates. Our lack of understanding of the factors that influence NTM occurrence in drinking water limits our ability to prevent infections, accurately characterize risk, and focus remediation efforts. In this study, we comprehensively evaluated NTM in a full-scale drinking water system, showing that various steps in treatment and distribution influence NTM presence. Stagnant building water contained the highest NTM concentrations source-to-tap and was associated with low disinfectant residuals. We illustrated the differences in NTM detection and characterization obtained from culture-based and culture-independent methods, highlighting the complementarity between these approaches. We demonstrated that focusing NTM mitigation efforts in building plumbing systems, which have the highest NTM concentrations source-to-tap, has potential for immediate positive effects. We also identified steps during treatment that increase NTM levels, which provides beneficial information for utilities seeking to reduce NTM in finished water.

microbiology↗

bioRxiv2024

Rbpj deletion in hepatic progenitor cells attenuates endothelial responses in a mouse model of cholestatic liver disease

BackgroundAs the role of hepatic progenitor cells (HPCs) constituting ductular reactions in pathogenesis remains ambiguous, we aimed to establish the in vivo cause-and-effect relationship between HPCs and chronic liver disease progression. We previously demonstrated that peritumoral ductules are associated with angiogenesis in liver tumors and forkhead box L1 (Foxl1)-expressing murine HPCs secrete angiogenic factors in vitro. Therefore, we hypothesized that HPCs are capable of remodeling the portal vascular microenvironment and regulating overall liver disease progression, and this function of HPCs is dependent on recombination signal binding protein for immunoglobulin kappa J region (RBPJ), a key effector of the Notch signaling pathway. Methods and ResultsWe generated HPC-specific Rbpj conditional knockout mice (CKO) using Foxl1-Cre and treated them with the DDC diet to induce chronic liver disease. CKO mice exhibited a significant reduction in serum levels of liver injury markers, ductular reactions, vascular and fibrotic areas, and hepatic expression of fibrosis and inflammation markers compared to control mice (WT). Single-nucleus RNA sequencing comparing CKO and WT livers detected transcriptome changes across multiple cell types, including endothelial cells, hepatic stellate cells, and cholangiocytes. Expression of several reactive cholangiocyte markers, including vascular cell adhesion molecule 1 (VCAM1), in HPCs was significantly downregulated in response to anti-Rbpj shRNAs in vitro. Immunofluorescence analysis indicated that the percentage of VCAM1+ cells was reduced in both HPC and cholangiocyte populations in CKO compared to WT in vivo. ConclusionsOur findings reveal Rbpj-dependent expression of reactive cholangiocyte markers in HPCs and demonstrate that Rbpj deletion in HPCs attenuates not only endothelial responses but also liver injury, fibrosis, and VCAM1 expression in cholangiocytes, highlighting the crucial role of HPCs in pathogenic progression.

cell biology↗

bioRxiv2024

Tunable Universal OR-gated CAR T cells for AML

Abstract/SummaryAcute myeloid leukemia (AML) is a hematopoietic malignancy characterized by antigen heterogeneity and poor prognosis. A potential therapeutic approach to address this heterogeneity is targeting multiple surface antigens to prevent antigen escape and relapse. Chimeric antigen receptor (CAR) T cells are an adoptive cell therapy that have demonstrated remarkable clinical success in the treatment of B cell malignancies, and many efforts are underway to adapt them to myeloid malignancies. To tackle the heterogeneity of AML, logically targeting multiple antigens through an "A OR B" gated CAR circuit would be desirable. Here we combined FLT3 antigen targeting with the well characterized CD33 myeloid marker as a combinatorial OR gate approach using our split, universal, programmable (SUPRA) CAR platform. The split platform affords tunability over activation levels and multiplexed targeting that cannot be achieved through a tandem bispecific approach. We systematically characterized the specificity and sensitivity of different SUPRA CAR adapters against each target individually and in combination against a panel of target cell lines. Our results demonstrate that this CAR system can effectively target two antigens with equivalent efficacy to conventional CARs while reducing the engineering burden associated with designing CAR T cells against multiple antigens. Furthermore, we can characterize an effective dose range where off-target cytotoxicity against hematopoietic stem and progenitor cells is minimized. With the recent clinical advances in universal CAR designs, our SUPRA OR gate has the potential to provide an effective and safer solution to treating AML.

synthetic biology↗

bioRxiv2024

Inhibiting CRF Projections from the Central Amygdala to Lateral Hypothalamus and Amygdala Deletion of CRF Alters Binge-Like Ethanol Drinking in a Sex-Dependent Manner

BackgroundBinge alcohol drinking is a dangerous pattern of consumption that can contribute to the development of more severe alcohol use disorders (AUDs). Importantly, the rate and severity of AUDs has historically differed between men and women, suggesting that there may be sex differences in the central mechanisms that modulate alcohol (ethanol) consumption. Corticotropin releasing factor (CRF) is a centrally expressed neuropeptide that has been implicated in the modulation of binge-like ethanol intake, and emerging data highlight sex differences in central CRF systems. MethodsIn the present report we characterized CRF+ neurocircuitry arising from the central nucleus of the amygdala (CeA) and innervating the lateral hypothalamus (LH) in the modulation of binge-like ethanol intake in male and female mice. ResultsUsing chemogenetic tools we found that silencing the CRF+ CeA to LH circuit significantly blunted binge-like ethanol intake in male, but not female, mice. Consistently, genetic deletion of CRF from neurons of the CeA blunted ethanol intake exclusively in male mice. Furthermore, pharmacological blockade of the CRF type-1 receptor (CRF1R) in the LH significantly reduced binge-like ethanol intake in male mice only, while CRF2R activation in the LH failed to alter ethanol intake in either sex. Finally, a history of binge-like ethanol drinking blunted CRF mRNA in the CeA regardless of sex. ConclusionsThese observations provide novel evidence that CRF+ CeA to LH neurocircuitry modulates binge-like ethanol intake in male, but not female mice, which may provide insight into the mechanisms that guide known sex differences in binge-like ethanol intake.

neuroscience↗