Biology subjects

David, M.

Publications and source records attributed to David, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Dishevelled2 Condensates control Axon Initial Segment (AIS) assembly and function through MTCL1-Dependent microtubule recruitment.

In the epithelium, Planar Cell Polarity (PCP) signaling coordinates cellular organization along the plane of the tissue, perpendicular to the apicobasal axis. In neurons, polarity is instead expressed through the structural and molecular asymmetry that separates the axon from the somatodendritic compartment. Core PCP proteins are essential for neuronal development and function, and have been linked to neurodevelopmental disorders, including autism spectrum disorders and epilepsy. However, their precise roles in the establishment of neuronal polarity remain incompletely understood. Here, we identify Dishevelled2 (Dvl2), a central PCP signaling scaffold, as a novel component of the axon initial segment (AIS), the proximal axonal domain that maintains neuronal polarity and initiates action potentials. We show that Dvl2 defines, both in vivo and in cultured hippocampal neurons, a proximal subdomain positioned upstream of the major AIS marker Ankyrin-G (Ank-G) and is closely associated with microtubule bundles. Dvl2 is already detected during early axon specification, suggesting that it participates in the initial organization of the proximal axon. Functional depletion of Dvl proteins disrupts AIS architecture, reduces the accumulation of Ankyrin-G and other core AIS components, and impairs the organization of AIS microtubule bundles. These structural defects translate into altered neuronal excitability, with a reduced AIS-dependent component of the action potential. Mechanistically, we identify MTCL1 as a microtubule-associated partner that recruits Dvl2 from biomolecular condensate assemblies onto microtubules. This recruitment requires the DIX and PDZ domains of Dvl2. Notably, selective intracellular binders targeting the Dvl2 PDZ domain perturb Dvl2 condensate organization and compromise AIS formation. Together, our data identify Dvl2 as an organizer of the proximal AIS and reveal a Dvl2-MTCL1-dependent mechanism coupling condensate scaffolding, microtubule organization, and neuronal excitability.

neuroscience↗

bioRxiv2026

Widespread detection of Polyethylene glycol reveals chronic human exposure through pharmaceutical drugs

Polyethylene glycol (PEG) is a synthetic polymer ubiquitous in pharmaceuticals, personal care products, food additives, and industrial manufacturing. Despite its widespread use and potential importance as an exposure chemical, the prevalence of PEG exposure and its excretion in human populations remain largely uncharacterized. Moreover, PEG detected in human biofluids is frequently assumed to arise from analytical contamination during sample preparation, potentially obscuring its contribution to the human exposome and confounding metabolic phenotyping studies. Here, we show that PEG is as component of the human xenobiotic exposome and is further metabolized into PEG hydoxy acid and diacid metabolites in humans. We further find that PEG exposure is associated with alterations in microbiome composition and short-chain fatty acid metabolism, suggesting its biological impact of its exposure. We identify PEG exposure in approximately 2.3% of publicly available metabolomics data files and provide a reusable 85,484 candidate PEG and PEGylated MS/MS spectral library for future use for the metabolomic community. Together, these findings establish PEG signal in human biofluids can reflect genuine exposure, and that PEG exposure is neither metabolically inert nor biologically silent.

biochemistry↗

bioRxiv2026

A Female-Specific Microglial Redox Program Gates Susceptibility to Obesity

Chronic consumption of energy-dense, high-fat foods persistently exposes hypothalamic circuits that govern body weight to nutrient excess, progressively altering their activity and thereby promoting obesity. Microglia, the brain resident immune cells, sense circulating lipids, but how their intracellular metabolic programs adapt to chronic dietary excess, and how this contributes to obesity risk, is unclear. Here, we reveal a sex-dependent control of calorie overload by hypothalamic microglial cells. In females, but not males, microglia engage a protective metabolic program with increased antioxidant capacity and mitochondrial network remodeling, conferring resistance to early weight gain. Over time, activation of mTORC1 signaling in microglia disrupts mitochondrial functions and dismantles this transient resilience, culminating in weight gain. These findings identify microglial mTORC1 as a sex-specific switch between resilience and vulnerability to obesity and position microglial metabolism as a tractable target for sex-informed weight control.

neuroscience↗

bioRxiv2026

Delivery of small interfering RNA and antisense oligonucleotides across the blood-brain barrier with monovalent transferrin receptor 1 binding VHH-Fc fusion proteins

The blood-brain barrier (BBB) is a highly selective cell layer that restricts the diffusion of diverse chemical entities into the central nervous system (CNS) from systemic circulation. Macromolecular therapeutics including oligonucleotides, peptides, and monoclonal antibodies exhibit only minimal brain distribution after systemic dosing due to exclusion by the BBB. Receptor-mediated transcytosis (RMT) has evolved to transport vital cargo across the BBB through a specialized vesicular transport pathway. Transferrin receptor 1 (TfR1) shuttles transferrin, its natural ligand, across the BBB, as well as TfR1-binding IgG antibodies and conjugates. Here, we describe a novel monovalent TfR1-binding VHH-Fc for the delivery of oligonucleotide cargo, including antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs) across the BBB in rodents and non-human primates (NHPs), supporting the translational potential of the VHH-antisense RMT platform for the treatment of neurological disorders. We explore the role of binding affinity, conjugation site, drug-antibody ratio (DAR), and conjugation chemistry, and determine that binding affinity, DAR and conjugation site are major determinants of RMT capacity and brain activity of siRNAs delivered across the BBB. Graphical Abstract / Highlights O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/744307v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@d1d648org.highwire.dtl.DTLVardef@4b22d3org.highwire.dtl.DTLVardef@db8b6borg.highwire.dtl.DTLVardef@19e5ac3_HPS_FORMAT_FIGEXP M_FIG C_FIG - Anti-TfR1 (-TfR1) VHH ligands formatted as heterodimeric, 2-chain monovalent VHH-Fc were engineered for conjugation to siRNA and ASO. - Systematic in vivo evaluation of VHH clones spanning a range of TfR1 binding affinities revealed a relationship between TfR1 binding affinity and the CNS activity of intravenously dosed VHH-Fc-siRNA conjugates. - By optimizing TfR1 binding affinity, conjugation site, and conjugation chemistry, we identified VHH-Fc-siRNA molecules that efficiently cross the BBB via receptor-mediated transcytosis and reduce target mRNA across CNS tissues, including deeper brain regions, after intravenous (IV) or subcutaneous (SC) dosing in mice and non-human primates (NHPs).

neuroscience↗

bioRxiv2026

Metagenomic contextualization of proteins with state space models

Since the early adoption of metagenomics (the culture-free sequencing of microbial community genomes) in 2011, sequence data has increased over 500-fold across ecosystems. This surge in data has outpaced reliable taxonomic and functional annotation, with over half of sequences lacking confident functional assignment. These unknown sequences limit our understanding of microbial processes central to planetary health and human health. Recent advances in genomic language modeling have made progress in the interpretation of metagenomics datasets. Most state-of-the-art models rely on transformer architectures, which limit the maximum sequence length and therefore capture only a fraction of assembled metagenomic sequences due to the quadratic scaling of attention. This prevents training and inference on sequences with broad context, including multiple coding and non-coding regions. To overcome this limitation, we propose leveraging new model architectures that scale linearly with sequence length, making them more suitable for modeling longer metagenomic sequences. Here, we introduce Nammu, a mixed-modality Mamba-based foundation model with 167M parameters trained on the OpenMetaGenomic (OMG) corpus. Nammu is a bidirectional encoder trained with a 20K context length using a curriculum strategy, first on 64M protein sequences and then on 32M mixed-modality metagenomic contigs. We compared Nammu to gLM2, a mixed-modality transformer also trained on OMG using 37% more tokens, using taxonomy inference on a marine dataset from the Critical Assessment of Metagenome Interpretation (CAMI). Nammu outperforms gLM2 at every taxonomic level. We further assessed function via KEGG Orthology prediction in deep-sea metagenome-assembled genomes, where Nammu outperforms gLM2 (150M). These results demonstrate improved performance.

bioinformatics↗

bioRxiv2026

A TRANSLATIONAL LC-MS/MS FRAMEWORK FOR LIPID BIOMARKER IDENTIFICATION AND QUANTIFICATION IN HUMAN PLASMA

Lipid metabolism is increasingly recognized as a hallmark of cancer, yet translating lipidomic discoveries into clinically actionable biomarkers remains constrained by analytical variability and limited standardized validation frameworks. This challenge is further compounded by a chicken-or-egg problem, where expensive standards and labelled internal standards are required to identify and quantitate target lipids, but the diagnostic importance of these targets is uncertain until they can be reliably measured. Previous work had indicated the potential of 48 lipid biomarker species for the prediction of breast cancer from plasma samples using high resolution liquid chromatography mass spectrometry. This study aimed to identify each of these 48 species and develop a quantitative method to determine the absolute concentrations of these lipids in plasma to provide the basis for the development of a clinical assay for use in breast cancer detection. In doing so, we present a pragmatic workflow that bridges lipid discovery with lipid identification and robust quantitative analysis. A curated library of 48 lipid species was established using authentic standards to verify plasma lipids through retention-time matching and high-resolution spectral comparison. In plasma, 41 lipids were confidently identified based on co-elution with standards and diagnostic fragment ions. Method qualification, including assessment of accuracy, precision, recovery, and linearity, was performed across all 48 lipids in parallel with identification, and 46 lipids ultimately met all predefined qualification criteria. Notably, practical constraints, including time, cost, and availability of authentic standards, necessitated performing identification and targeted method development in parallel, highlighting challenges inherent to translating lipidomics into commercial or clinical assays. This workflow provides a reproducible framework for harmonizing lipid identification and quantification, enabling the reliable integration of lipidomic data into biomarker discovery and clinical applications.

biochemistry↗

bioRxiv2026

Chemiluminescent probes allow for the rapid identification of colibactin-producing bacteria

The pks (or clb) gene cluster, which produces the genotoxic natural product colibactin, is encoded by human gut Enterobacteriaceae, including many commensal strains of E. coli. Colibactin crosslinks DNA and is implicated in colorectal cancer development, highlighting the importance of identifying colibactin-producing gut bacteria within biological samples. In this study, we develop phenoxy-dioxetane chemiluminescent probes that selectively react with a critical colibactin biosynthetic enzyme, the serine peptidase ClbP. We show that these chemiluminescent probes have superior sensitivity, speed, and detection capabilities compared to previously reported fluorescent ClbP probes. Furthermore, we employ these chemiluminescent probes to detect pks+ E. coli directly in complex stool suspensions. These probes will enable multiple applications requiring detection of colibactin-producing bacteria, including the identification of ClbP inhibitors and the screening of clinical samples.

biochemistry↗

bioRxiv2025

BioGeoFormer: A deep learning approach to classify unknown genes associated with critical biogeochemical cycles

Remote functional annotation continues to impede progress in microbial ecology, as alignment-based approaches still leave over one-third of microbial sequences functionally unresolved. In contrast, pre-trained natural-language-processing approaches have shown strong potential for inferring functions from diverse biological sequences, and here we introduce a protein language modeling approach allowing us to classify sequences into 37 defined key pathway categories involved in 4 major biogeochemical cycles (methane, sulfur, nitrogen and phosphorus cycles). To do so, we fine-tuned ESM2-8m using databases curated for biogeochemical cycling pathways. Our resultant BioGeochemical cycling transFormer (BioGeoFormer or BGF) was high-performing on validation and test sets, producing embeddings that exhibit an ability to infer protein function at a metabolic pathway level. BGF was applied to a dataset of metagenome-assembled genomes (MAGs) constructed from methane-fueled, deep-sea, "cold seep" environments to demonstrate its utility in contrast to current informatics approaches. We employed multiple gene assignments to identify gene function within these MAGs. A total of 1.05M genes were assigned biogeochemical functions, with BGF alone suggesting putative ecosystem roles for 0.49M (46%) of these at a confidence of 85% or greater; these genes were classified as unknown by the other approaches. Across the pathways of interest, BGF identified 6 times as many genes, on average, as Hidden Markov models (HMMs) as well as alignment-based approaches across the various pathways. BGF provides a novel tool that is capable of informing process-based hypotheses in diverse systems, highlighting cryptic proteins most notably linked to methane, nitrogen, and phosphorus cycling while uncovering the mysteries within microbial dark matter. Author summaryWhen investigating the function of microbes in the environment, scientists are often left with vast amounts of genes or proteins where no knowledge about their function is available. This represents a huge amount of information left to be discovered in many fields of biology. One recent approach that has shown significant potential in further understanding unknown proteins are protein language models, which are deep-learning methods leveraging large datasets to understand the language of proteins. We aimed to apply protein language modeling to further understand the function of proteins as they relate to large-scale environmental transformation of nutrients and carbon. Specifically, we designed our approach to further understand the metabolism of microbes that affect methane, nitrogen, phosphorus, and sulfur, all elements that are highly impactful to the planets function and health. We used our new approach on a deep-sea microbiology dataset, and showed the methods utility in further understanding the function of proteins and their impact on the environment. Overall, we found our method is an important new tool in the toolset of environmental scientists working to better understand the function of microbes and their proteins.

microbiology↗

bioRxiv2025

Igniting full-length isoform analysis in single-cell and spatial RNA-seq data with FLAMESv2

Long-read single-cell RNA-sequencing enables the profiling of RNA isoform expression and alternative splicing at single cell resolution. However, diverse single-cell technologies and sparse isoform data demand flexible and accurate analysis tools. We introduce FLAMESv2, a highly modular and protocol-agnostic R/Bioconductor package for long-read single-cell RNA-seq data analysis. FLAMESv2 supports a wide range of single-cell and spatial protocols, is highly configurable, scales to allow multi-sample analysis and provides versatile visualisation and analysis outputs. We demonstrate its compatibility with both droplet-based and combinatorial barcoding single-cell methods, as well as spatial transcriptomics workflows. Benchmarking confirms FLAMESv2 achieves field-leading performance across key analysis tasks. Applying FLAMESv2 to in vitro differentiation of stem cells into neurons, we identify cell-types, differentiation trajectories, expression of annotated and novel isoforms and isoform expression diversity and heterogeneity within individual cells. FLAMESv2 provides a comprehensive, flexible approach to analysing long-read single-cell RNA-sequencing, unlocking this powerful methodology for RNA isoform characterisation.

bioinformatics↗

bioRxiv2025

3D-printing-assisted, microfabricated devices reveal hierarchical and temporal mechanosensing in high-density fibroblast culture

Understanding how cells integrate mechanical forces across multiple directions, length scales, and timescales remains a fundamental challenge in mechanobiology. Deciphering how cells integrate this information is particularly important in the context of wound healing, where the timing and duration of the fibroblast-to-myofibroblast transition can determine healing outcomes. Here, we discovered that fibroblasts in engineered tissues respond to directional anisotropy in stress through a hierarchical temporal cascade, with individual cell elongation (24 hr) preceding collective alignment (40 hr), which then drives -smooth muscle actin expression and myofibroblast transition (96h). To enable this discovery, we developed a modified hydrogel-assisted stereolithographic elastomer (HASTE) prototyping platform to incorporate a detergent that improves wettability of template agar hydrogels by poly(dimethylsiloxane) elastomer. HASTE allowed rapid prototyping of intricate 3D micropost arrays that provides isotropic (8-post) versus anisotropic (4-post) boundary conditions. Fibroblasts sensed and responded to stress directionality before bulk tissue reorganization occurs. Computational modeling predicted steady-state activation patterns based on initial stress anisotropy rather than magnitude, and our experiments reveal that reaching this state requires sequential mechanosensitive processes operating across distinct timescales. This temporal hierarchy persists even when extensive cell-cell contacts might be expected to mask matrix-mediated mechanical signals. Our findings demonstrate that fibroblast mechanosensing involves adaptive responses encoded through progressive cell and tissue reorganization. Results provide insight into how nanoscale mechanosensing scales up to direct tissue-level organization, with implications for understanding wound healing, understanding fibrosis, and engineering functional tissue replacements.

bioengineering↗

bioRxiv2025

Benchmarking long-read RNA-sequencing technologies with LongBench: a cross-platform reference dataset profiling cancer cell lines with bulk and single-cell approaches

Long-read RNA sequencing enables full-length transcript profiling and improved isoform resolution, but variable platforms and evolving chemistries demand careful benchmarking for reliable application. We present LongBench, a matched, multi-platform reference dataset spanning bulk, single-cell, and single-nucleus transcriptomics across eight human lung cancer cell lines with synthetic spike-in controls. LongBench in-corporates three state-of-the-art long-read protocols alongside Illumina short reads: Oxford Nanopore Technologies (ONT) PCR-cDNA, ONT direct RNA, and PacBio Kinnex. We systematically evaluate transcript capture, quantification accuracy, differential expression, isoform usage, variant detection, and allele-specific analyses. Our results show high concordance in gene-level differential analyses across protocols, but reduced consistency for transcript-level and isoform analyses due to length- and platform-dependent biases. Single-cell long-read data are highly concordant with bulk for high-confidence features, though single-nuclei data show reduced feature detection. LongBench provides one of the largest publicly available long-read benchmarking resources, enabling rigorous cross-platform evaluation and guiding technology selection for transcriptomic research.

genomics↗

bioRxiv2025

Improving angiogenesis ameliorates the efficacy of ASO-based exon-skipping for the treatment of Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a severe X-linked disease caused by mutations in the DMD gene, resulting in the absence of functional dystrophin. Antisense oligonucleotide (ASO)-based therapies aim to restore the open reading frame and produce a truncated but functional dystrophin protein. Although several ASOs are FDA-approved, dystrophin restoration in patient biopsies remains low, underlining the need to improve ASO efficacy. One major limitation is poor ASO biodistribution to skeletal muscle, influenced by both ASO chemistry and pathological features of dystrophic tissue. In DMD patients and mdx mice, microvascular abnormalities and impaired angiogenesis likely restrict ASO delivery. Here, we hypothesized that enhancing muscle vascularization could improve ASO biodistribution and therapeutic outcomes. Mdx mice were treated with a pro-angiogenic treatment prior to ASO administration targeting exon 23 of dystrophin pre-mRNA. Angiogenic stimulation increased capillary density and improved ASO delivery, exon skipping, and dystrophin expression compared to ASO alone. These molecular improvements were associated with increased myofiber size, larger mean cross-sectional area, and decreased serum myomesin levels, without signs of toxicity. This study provides proof-of-concept that promoting angiogenesis can enhance the efficacy of ASO-based treatments, offering a complementary strategy to improve therapeutic outcomes in DMD.

molecular biology↗

bioRxiv2025

Mutations in specific MT5-MMP domains prevent the accumulation of toxic APP metabolites and serve as templates for peptide-based therapeutics in cell models of Alzheimer's disease

Our prior work established a pivotal role for membrane-type 5-matrix metalloproteinase (MT5-MMP) in Alzheimers disease (AD) pathogenesis, particularly through its C-terminal transmembrane (TM) and intracellular (IC) domains, which influence the fate of major toxic metabolites of toxic amyloid precursor protein (APP) metabolites, particularly C99 and A{beta}. Hypothesizing that modifications in these domains could modulate C99 and A{beta} levels, we engineered MT5-MMP variants with deletions or substitutions in the TM/IC domains or specific IC amino acid clusters. When co-transfected into human cell lines accumulating C99, certain IC domain mutations promoted C99 degradation and reduced A{beta} levels, while other mutations had divergent effects. High content imaging further revealed that MT5-MMP IC domain modification altered C99 subcellular trafficking within the endomembrane system, impacting its processing. Proximity ligation assays confirmed the importance of the IC domain in MT5-MMP colocalization and potential interaction with C99. To translate these findings, we synthetized peptides mimicking the MT5-MMP IC domain, incorporating mutations that reduce C99 and/or A{beta} levels. One peptide effectively lowered C99 levels in an in vitro AD model. Overall, this study highlights the importance of specific amino acids in the C-terminal domains of MT5-MMP for regulating C99 and A{beta} metabolism. It also provides new insights for developing MT5-MMP-based therapeutic strategies against AD, exploiting the unique properties of specific mutations in MT5-MMP to prevent toxic accumulation of C99 and A{beta}. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=86 SRC="FIGDIR/small/655451v3_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@a6b04aorg.highwire.dtl.DTLVardef@1800721org.highwire.dtl.DTLVardef@542505org.highwire.dtl.DTLVardef@4a6d7b_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGRAPHICAL ABSTRACTC_FLOATNO C_FIG

cell biology↗

bioRxiv2025

Identification and optimization of trans-species reactive TfR1-binding VHH as tools for drug delivery across the blood brain barrier

The blood-brain barrier (BBB) is a major obstacle for delivering therapeutic agents to the central nervous system (CNS), posing significant challenges for treating neurological disorders. Among current strategies to improve brain drug exposure, hijacking physiological pathways involved in receptor-mediated transcytosis (RMT) has emerged as a promising strategy. While targeting transferrin receptor 1 (TfR1) is widely explored, many TfR1-antibodies lack cross-species reactivity, limiting translational development. In the present study, we identified and characterized camelid-derived single-domain antibodies (VHHs) with robust cross-reactivity to rodent, rhesus monkey, and human TfR1. Epitope mapping of the VHH revealed a novel binding site at the interface of the TfR1 dimer. When fused to a human IgG1 Fc domain, these VHHs, as monomers or homodimers, were efficiently internalized by engineered CHO cells and brain endothelial cells expressing TfR1 from different species. Systemic administration of VHH-Fc constructs in mice demonstrated significantly improved brain uptake compared to irrelevant controls. Functional delivery was confirmed using neurotensin (NT)-induced hypothermia, and we established correlations between in vivo effects and TfR1 VHH binding properties determined by surface plasmon resonance. Notably, efficient BBB transcytosis was associated with intermediate affinity and rapid dissociation rates. Engineered variants maintained favorable cross-species binding, including similar affinities to human and non-human primate TfR1, facilitating translational studies. The cross-reactive anti-TfR1 VHHs we developed offer a versatile and modular platform for CNS drug delivery and hold promise as molecular shuttles for transporting therapeutic agents across the BBB. Our work establishes a robust foundation for developing next-generation brain-targeted biotherapeutics, including peptides, enzyme replacement therapies, antibody-based treatments for neurodegenerative diseases, and oligonucleotide delivery for CNS disorders, enabling seamless translation from preclinical to clinical applications.

neuroscience↗

bioRxiv2024

A haplotype-based evolutionary history of barley domestication

Barley is an old crop with a complex history. Its evolution and the molecular basis of domestication have been intensely studied. This research has ruled out a single origin of the crop and motivated a model of mosaic genomics ancestry. As more and better genome sequences have become available, this concept can be refined: where do the building blocks of the mosaic, that is, the haplotypes come from? Were all cultivated barleys created equal or did some wild barley populations contribute more to some domesticated lineages? To answer these and other questions, we pursue a haplotype-based approach to connect diversity and population structure in wild and domesticated barley. We sequence the genomes of 628 genebank accessions and 23 archaeological specimens. Using these data, we infer the spatiotemporal origins of haplotypes and map the contributions of different wild barley populations either during the initial phase of domestication or through later gene flow. Ancient DNA sequences corroborate our genome-wide analysis in present-day samples. Our results indicate that an early domesticated founder population formed in the Fertile Crescent during an extended period of pre-domestication cultivation. A practical implication of our findings is that the high haplotype differentiation between barley populations, which arose possibly without, and most likely on top of, selective forces, complicates the mapping of adaptive loci.

plant biology↗

bioRxiv2024

Enhanced anti-tumor activity by Zinc Finger Repressor-driven epigenetic silencing of immune checkpoints and TGFBR2 in CAR-T cells and TILs

CAR-T therapies have shown remarkable success in treating hematological malignancies. However, effectiveness against solid tumors remains limited due to the immunosuppressive tumor microenvironment (TME), such as TGF-{beta} signaling and upregulated immune checkpoints (ICs). Furthermore, identifying universal, tumor-specific targets for CAR-T cells in solid tumors is challenging, but using reinvigorated, immunosuppressive-resistant tumor-infiltrating lymphocytes (TILs) could be a promising alternative approach. Unlike nucleases, which may induce genotoxic DNA double-strand breaks, multiplexed Zinc Finger Repressors (ZFR) offer a safer alternative for knocking out TME-related immunosuppressive factors. We epigenetically repressed PD-1 expression both in CAR-T cells and TILs from colorectal liver metastases. PD-1 repression did not affect T cell viability, proliferation, or functionality. In a murine B cell lymphoma model, PD-1-repressed CD19-CAR-T cells exhibited enhanced anti-tumor activity and improved survival. Notably, PD-1 repression alone did not increase cytotoxicity against a PD-L1-positive colorectal cell line in vitro. To further increase anti-tumor potency in this context, ZFR-expressing lentiviral vectors targeting PD-1 and other ICs (LAG-3, TIM-3, TIGIT) or TGFBR2 were developed, improving significantly the cytotoxic activity in TILs. This strategy highlights the potential to enhance tumor-reactive T cells and improve anti-cancer immunotherapies by epigenetically repressing immunosuppressive factors in the TME using multiplexed ZFRs.

cancer biology↗

bioRxiv2024

A peptide-neurotensin conjugate that crosses the blood-brain barrier induces pharmacological hypothermia associated with anticonvulsant, neuroprotective and anti-inflammatory properties following status epilepticus in mice

Preclinical and clinical studies show that mild to moderate hypothermia is neuroprotective in sudden cardiac arrest, ischemic stroke, perinatal hypoxia/ischemia, traumatic brain injury and seizures. Induction of hypothermia largely involves physical cooling therapies, which induce several clinical complications, while some molecules have shown to be efficient in pharmacologically induced hypothermia (PIH). Neurotensin (NT), a 13 amino-acid neuropeptide that regulates body temperature, interacts with various receptors to mediate its peripheral and central effects. NT induces PIH when administered intracerebrally. However, these effects are not observed if NT is administered peripherally, due to its rapid degradation and poor passage of the blood brain barrier (BBB). We conjugated NT to peptides that bind the low-density lipoprotein receptor (LDLR) to generate "vectorized" forms of NT with enhanced BBB permeability. We evaluated their effects in epileptic conditions following peripheral administration. One of these conjugates, VH-N412, displayed improved stability, binding potential to both the LDLR and NTSR-1, rodent/human cross-reactivity and improved brain distribution. In a mouse model of kainate (KA)-induced status epilepticus (SE), VH-N412 elicited rapid hypothermia associated with anticonvulsant effects, potent neuroprotection and reduced hippocampal inflammation. VH-N412 also reduced sprouting of the dentate gyrus mossy fibers and preserved learning and memory skills in the treated mice. In cultured hippocampal neurons, VH-N412 displayed temperature-independent neuroprotective properties. To the best of our knowledge, this is the first report describing the successful treatment of SE with PIH. In all, our results show that vectorized NT may elicit different neuroprotection mechanisms mediated either by hypothermia and/or by intrinsic neuroprotective properties.

neuroscience↗

bioRxiv2024

Epigenetic control of multiple genes with a single lentiviral vector encoding transcriptional repressors fused to compact zinc finger arrays

Gene silencing without gene editing holds great potential for the development of safe therapeutic applications. Here, we describe a novel strategy to concomitantly repress multiple genes using zinc finger proteins fused to Kruppel-Associated Box repression domains (ZF-Rs). This was achieved via the optimization of a lentiviral system tailored for the delivery of ZF-Rs in hematopoietic cells. We showed that an optimal design of the lentiviral backbone is crucial to multiplex up to three ZF-Rs or two ZF-Rs and a chimeric antigen receptor. ZF-R expression had no impact on the integrity and functionality of transduced cells. Furthermore, gene repression in ZF-R-expressing T cells was highly efficient in vitro and in vivo during the entire monitoring period (up to ten weeks), and it was accompanied by epigenetic remodeling events. Finally, we described an approach to improve ZF-R specificity to illustrate the path towards the generation of ZF-Rs with a safe clinical profile. In conclusion, we successfully developed an epigenetic-based cell engineering approach for concomitant modulation of multiple gene expressions that bypass the risks associated with DNA editing.

bioengineering↗