Biology subjects

Colombo, E.

Publications and source records attributed to Colombo, E..

12 recordsLinked to original sources

bioRxiv2026

Sephin1 rewires proteostasis through actin-dependent signaling

The maintenance of protein homeostasis is vital for all cells. Alteration in protein handling underlies several diseases. The small molecule sephin1 is a promising clinical candidate against proteostasis disruption, but its mechanism of action is still uncertain. Our experimental evidence shows that sephin1 binds G-actin and drives actin cytoskeleton misfolding, and eventually, Golgi disintegration. At first, sephin1 impairs the autophagic flux and elicits the phosphorylation of the subunit of eIF2 and the ER-stress independent expression of CHOP via GCN2 kinase. Sephin1 also inhibits the mammalian target of rapamycin (mTORC1), activates the transcription Factor EB (TFEB), drives the expression of TFEB-direct target genes, and eventually stimulates the autophagy lysosomal pathway. Our results reveal that the actin cytoskeleton may regulate autophagy via mTORC1-TFEB complemented with the GCN2-eIF2-CHOP signaling pathway.

cell biology↗

bioRxiv2026

NF-κB transcriptionally enhances p53 accumulation dynamics hampering DNA repair

Cells integrate multiple, often concurrent signals through intertwined genetic circuits whose dynamics shape transcriptional programs and cell fate decisions. Among these, the tumor suppressor p53 and the inflammatory transcription factor NF-{kappa}B are central regulators of stress responses in normal and cancer cells, yet their dynamic crosstalk under co-activation remains poorly characterized. Here, we combine genetic approaches, live cell imaging, transcriptomic analysis and mathematical modeling to dissect their dynamic interplay. We find that co-activation of NF-{kappa}B by the inflammatory cytokines TNF- and IL-1{beta} significantly enhance p53 nuclear accumulation upon genotoxic stress or Nutlin3a, and this effect is absent in NF-{kappa}B-deficient cells. Mechanistically, we show that cytokines induce an NF-{kappa}B-mediated increase of TP53 transcription, and mathematical modeling indicates that it is sufficient to account for the observed increased p53 accumulation. Functionally, NF-{kappa}B co-activation rewires p53-dependent transcriptional programs and impairs p53-mediated DNA repair following genotoxic stress, due to a shift of p53 dynamics from oscillatory to more sustained accumulation; p53 oscillatory dynamics and DNA repair remain largely unaltered in absence of NF-{kappa}B. Our results uncover an amplification of p53 response in presence of inflammatory cues that is transcriptionally mediated by NF-{kappa}B and that results, counterintuitively, in functional antagonism. SIGNIFICANCE STATEMENTp53 dynamics have been shown to correlate with the cellular responses of cancer cells to genotoxic insults such as those delivered by chemo- and radiotherapies. However, these dynamics have been mostly studied in settings that do not account for the pro-inflammatory cues that cancer cells might receive from the microenvironment. By addressing this gap, our study uncovers a previously unappreciated mechanism by which inflammatory signals induce an increased p53 accumulation, leading to reduced DNA repair capacity. Our results provide mechanistic understanding on the origin of p53-NF-{kappa}B antagonism and show how dynamically interconnected signalling pathways can produce counterintuitive functional outcomes. Translationally, the contribution of inflammation to the sensitivity of normal and cancer cells to DNA damage might be exploited in the management of chemo- and radiotherapies.

systems biology↗

bioRxiv2025

MicroSplit: Semantic Unmixing of Fluorescent Microscopy Data

Fluorescence microscopy, a key driver for progress in the life sciences, faces limitations due to the microscopes optics, fluorophore chemistry, and photon exposure limits, necessitating trade-offs in imaging speed, resolution, and depth. Here, we introduce Micro[S]plit, a computational multiplexing technique based on deep learning that allows multiple cellular structures to be imaged in a single fluorescent channel and then unmix them by computational means, allowing faster imaging and reduced photon exposure. We show that Micro[S]plit efficiently separates up to four superimposed noisy structures into distinct denoised fluorescent image channels. Furthermore, using Variational Splitting Encoder-Decoder (VSE) networks, our approach can sample diverse predictions from a trained posterior of solutions. The diversity of these samples scales with the uncertainty in a given input, allowing us to estimate the true prediction errors by computing the variability between posterior samples. We demonstrate the robustness of Micro[S]plit networks, which are trained for each splitting task at hand, across various datasets and noise levels and show its utility to image more, to image faster, and to improve downstream analysis. We provide Micro[S]plit along with all associated training and evaluation datasets as open resources, enabling life scientists to immediately benefit from the potential of computational multiplexing and thus help accelerate the rate of their scientific discovery process.

bioinformatics↗

bioRxiv2024

Development of a high-throughput 3D culture microfluidic platform for multi-parameter phenotypic and omics profiling of patient-derived organoids

Patient-derived organoids (PDOs) are poised to become central tools both in clinical practice, to preemptively identify patient optimal treatments, and in drug discovery, overcoming the limitations of cancer cell lines. However, the use of PDOs in these settings has been hampered by several bottlenecks, including sample requirements, assay time, and handling in the context of high-throughput assays. We developed a Microfluidic Platform for Organoids culture (MPO) that miniaturises and simplifies PDOs cultures in a 384-plate format. Both retrospective and prospective clinical studies demonstrate MPO predictive value and the straightforward implementation in the clinical setting. MPO allows subcellular phenotypic screenings, as imaging-based applications like Cell Painting, target engagement analyses, alongside the comprehensive definition of PDOs genomic, transcriptomic, proteomic, lipidomic, and metabolomic landscapes. Harnessing the pleiotropic capabilities of MPO, we uncovered the role of EZH2 inhibitors to prevent the long-term emergence of resistance to RAS inhibitors in metastatic colon cancer. In all, we demonstrate the potential of MPO to impact clinical practice, alongside exploration of the mechanisms underlying compound response and resistance.

cancer biology↗

bioRxiv2024

NPMc+ and Flt3-ITD cooperation promotes a new oncogenic HSC state that supports transformation and leukemia stem cell maintenance

NPMc+ and FLT3-ITD are the most frequently co-occurring mutations in Acute Myeloid Leukemia (AML). Cellular and molecular mechanisms of their cooperation are largely unknown. We investigated their effects on pre-leukemic and leukemic hematopoietic stem cells (HSCs) in mouse models that recapitulate the human disease. Both oncogenes increase proliferation of pre-leukemia HSCs, however, only NPMc+ extends self-renewal, by preventing depletion of quiescent HSCs. Quiescent HSCs include dormant and active HSCs, which are dynamic and alternative phenotypic states supporting, respectively, self-renewal and regenerative haematopoiesis. Analyses of the dormant and active transcriptional programs showed that NPMc+ stimulates the dormant-to-active transition but also enforces dormancy, thus allowing dormant HSCs to be replenished. Co-expression of NPMc+ and Flt3-ITD induces a new phenotypic state of quiescent HSCs whereby dormancy and activity co-exist at single-cell level. This new state likely supports in vivo proliferation of self-renewing HSCs and rapid selection of leukemia initiating cells. Pharmacological inhibition of the TGFb cell-dormancy pathway reduces self-renewal of leukemia SCs and prolongs mouse survival allowing to conclude that enforcement of HSC dormancy is a critical determinant of unrestricted self-renewal during leukemia development and represents a target for novel anti-leukemic strategies.

cancer biology↗

bioRxiv2024

Systematic Evaluation of High-Throughput PBK Modelling Strategies for the Prediction of Intravenous and Oral Pharmacokinetics in Humans

Physiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing with in vitro or in silico methods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for Non-Animal Methods. To address this limitation, High-throughput PBK modelling aims to rely exclusively on in vitro and in silico data for model generation. Here, we evaluate a variety of in silico tools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000+ publicly available human in vivo concentration-time profiles of 200+ compounds (IV and oral administration), as well as in silico, in vitro and in vivo determined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collected in vivo concentration-time profiles. Our results show that even simple, generic High-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within 10-fold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for High-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of High-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.

pharmacology and toxicology↗

bioRxiv2023

Dissecting the neurotropism and neurovirulence of MPXV using human stem cell-based models

Mpox is a zoonotic illness of international concern that can lead to severe disease including neurological sequelae. However, the neurotropism of monkeypox virus (MPXV) and the mechanisms regulating cell-intrinsic antiviral immunity within the central nervous system (CNS) remain poorly understood. Here, we investigated the neurotropism of MPXV using astrocytes, cortical neurons, and microglia derived from human pluripotent stem cells (hPSCs) and ex vivo human brain tissue to demonstrate that MPXV infects and replicates more efficiently in astrocytes and microglia compared to cortical neurons. Upon MPXV exposure, glial cells, in contrast to cortical neurons, inhibit type I IFN antiviral programs potentially conferring differential susceptibility to MPXV. Furthermore, we demonstrate that treatment using either IFN-beta or tecovirimat inhibits MPXV infection. Together, our results suggest that MPXV has a broad tropism within the CNS and that differential type I IFN signaling underpins cell type-specific susceptibility to MPXV infection.

microbiology↗

bioRxiv2023

GASOLINE: detecting germline and somatic structural variants from long-reads data.

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30x sequencing coverage experiments requires 4-5 hours with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified 6 genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

bioinformatics↗

bioRxiv2022

Chromatin organization drives the exploration strategy of nuclear factors

Nuclear Factors (NFs) rapidly scan the genome for their targets, but the role of nuclear organization in such search is uncharted. Here we analyzed how multiple NFs explore chromatin, by combining live-cell single-molecule tracking with multifocal structured illumination of DNA density. We find that NFs displaying higher bound fractions sample DNA dense regions more exhaustively. Focusing on the tumor-suppressor p53, we demonstrated that this NF search for its targets by alternating between rapid diffusion in the interchromatin compartment and compact sampling of chromatin dense regions. Efficient p53 targeting requires balanced IDR/chromatin interactions: adding an exogenous IDR potentiates p53-mediated target gene activation, but excessive IDR/IDR interactions lead to p53 condensates, derailing its search and downregulating transcription. Our findings highlight the role of NF IDRs on their search and showcase a powerful method to generate traffic maps of the eukaryotic nucleus and dissect how nuclear organization guides NFs action.

biophysics↗

bioRxiv2022

High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias.

Aberrant DNA methylation at CpG dinucleotides is a hallmark of cancer and is associated with the emergence of resistance to anti cancer treatment, though molecular mechanisms and biological significance remain elusive. Genome scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG rich regions (CpG islands). We report the first high coverage whole genome map in cancer using the long read nanopore technology, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, after chemotherapy. Long read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution, and showed that the relapse methylome is characterized by hypermethylation at both CpG islands and sparse CpGs regions. Most differentially methylated genes, however, were not differentially expressed nor enriched for chemoresistance genes. A small fraction of under-expressed and hyper-methylated genes at sparse CpGs, in the gene body, was significantly enriched in transcription factors (TFs). Remarkably, these few TFs supported large gene-regulatory networks including 50% of all differentially expressed genes in the relapsed AMLs and highly-enriched in chemoresistance genes. Notably, hypermethylated regions at sparse CpGs were poorly conserved in the relapsed AMLs, under-represented at their genomic positions and showed higher methylation entropy, as compared to CpG islands. Relapsed AMLs carried few patient specific structural variants and DNA mutations, apparently not involved in drug resistance. Thus, drug resistance in AMLs can be mainly ascribed to the selection of random epigenetic alterations at sparse CpGs of a few transcription factors, which then induce reprogramming of the relapsing phenotype, independently of clonal genomic evolution.

genomics↗

bioRxiv2022

P3HT-GRAPHENE DEVICE FOR THE RESTORATION OF VISUAL PROPERTIES IN A RAT MODEL OF RETINITIS PIGMENTOSA

Retinal degeneration is one of the prevalent causes of blindness worldwide, for which no effective treatment has yet been identified. Inorganic photovoltaic devices have been investigated for visual restoration in advanced stage Retinitis pigmentosa (RP), although lack of implant flexibility and foreign-object reactions have limited their application. Organic photoactive retinal prostheses may overcome these limitations, being biomimetic and tissue friendly. Inspired by organic photovoltaic strategies involving graphene, a hybrid retinal prosthesis was recently engineered consisting of a dual poly-3-hexylthiophene (P3HT) and graphene layer onto a flexible substrate. Here, this hybrid prosthesis was subretinally implanted in vivo in 5-month-old Royal College of Surgeons (RCS) rats, a rodent model of RP. Implanted dystrophic rats restored visual performances at both subcortical and cortical levels in response to light stimuli, in the absence of marked inflammatory responses. Moreover, the analysis of the physical-mechanical properties after prolonged permanence in the eye showed excellent biocompatibility and robustness of the device. Overall, the results demonstrate that graphene-enhanced organic photovoltaic devices can be suitably employed for the rescue of retinal dystrophies and supports the translation of the organic strategy into the medical practice. TABLE OF CONTENTSInspired by organic photovoltaic, a hybrid retinal prosthesis consisting of poly-3-hexylthiophene (P3HT) and graphene on a flexible substrate was subretinally implanted in vivo in Royal College of Surgeons (RCS) rats, a model of Retinitis pigmentosa. Implanted dystrophic rats restored visual performances at both subcortical and cortical levels in response to light stimuli, in the absence of marked inflammatory responses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=37 SRC="FIGDIR/small/507903v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1cb30a0org.highwire.dtl.DTLVardef@e57c2corg.highwire.dtl.DTLVardef@3b3c8corg.highwire.dtl.DTLVardef@10442d7_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2019

A Membrane-Targeted Photoswitch Potently Modulates Neuronal Firing

Optical technologies allowing modulation of neuronal activity at high spatio-temporal resolution are becoming paramount in neuroscience. We engineered novel light-sensitive molecules by adding polar groups to a hydrophobic backbone containing azobenzene and azepane moieties. We demonstrate that the probes stably partition into the plasma membrane, with affinity for lipid rafts, and cause thinning of the bilayer through their trans-dimerization in the dark. In neurons pulse-labeled with the compound, light induces a transient hyperpolarization followed by a delayed depolarization that triggers action potential firing. The fast hyperpolarization is attributable to a light-dependent decrease in capacitance due to membrane relaxation that follows disruption of the azobenzene dimers. The physiological effects are persistent and can be evoked in vivo after labeling the mouse somatosensory cortex. These data demonstrate the possibility to trigger neural activity in vitro and in vivo by modulating membrane capacitance, without directly affecting ion channels or local temperature.

neuroscience↗