Biology subjects

Giudice, G.

Publications and source records attributed to Giudice, G..

8 recordsLinked to original sources

bioRxiv2023

Differential regulation of the proteome and phosphosproteome along the dorso-ventral axis of the early Drosophila embryo

The initially homogeneous epithelium of the early Drosophila embryo differentiates into regional subpopulations with different behaviours and physical properties that are needed for morphogenesis. The factors at top of the genetic hierarchy that control these behaviours are known, but many of their targets are not. To understand how proteins work together to mediate differential cellular activities, we studied in an unbiased manner the proteomes and phosphoproteomes of the three main cell populations along the dorso-ventral axis during gastrulation using mutant embryos that represent the different populations. We detected 6111 protein groups and 6259 phosphosites of which 3399 and 3433 respectively, were differentially regulated. The changes in phosphosite abundance did not correlate with changes in host protein abundance, showing phosphorylation to be a regulatory step during gastrulation. Hierarchical clustering of protein groups and phosphosites identified clusters that contain known fate determinants such as Doc1, Sog, Snail and Twist. The recovery of the appropriate known marker proteins in each of the different mutants we used validated the approach, but also revealed that two mutations that both interfere with the dorsal fate pathway, Toll10B and serpin27aex do this in very different manners. Diffused network analyses within each cluster point to microtubule components as one of the main groups of regulated proteins. Functional studies on the role of microtubules provide the proof of principle that microtubules have different functions in different domains along the DV axis of the embryo.

developmental biology↗

bioRxiv2023

phuEGO: A network-based method to reconstruct active signalling pathways from phosphoproteomics datasets

Signalling networks are critical for virtually all cell functions. Our current knowledge of cell signalling has been summarised in signalling pathway databases, which, while useful, are highly biassed towards well-studied processes, and dont capture context specific network wiring or pathway cross-talk. Mass spectrometry-based phosphoproteomics data can provide a more unbiased view of active cell signalling processes in a given context, however, it suffers from low signal-to-noise ratio and poor reproducibility across experiments. Methods to extract active signalling signatures from such data struggle to produce unbiased and interpretable networks that can be used for hypothesis generation and designing downstream experiments. Here we present phuEGO, which combines three-layer network propagation with ego network decomposition to provide small networks comprising active functional signalling modules. PhuEGO boosts the signal-to-noise ratio from global phosphoproteomics datasets, enriches the resulting networks for functional phosphosites and allows the improved comparison and integration across datasets. We applied phuEGO to five phosphoproteomics data sets from cell lines collected upon infection with SARS CoV2. PhuEGO was better able to identify common active functions across datasets and to point to a subnetwork enriched for known COVID-19 targets. Overall, phuEGO provides a tool to the community for the improved functional interpretation of global phosphoproteomics datasets.

bioinformatics↗

bioRxiv2022

In silico network-based screening reveals candidates for endothelial dysfunction therapy

Endothelial dysfunction (ED) is a hallmark of cardiovascular (CV) disorders and influences their progression; however, there are currently no direct therapeutic targets, primarily due to the lack of knowledge regarding EDs molecular basis. We used a computational approach to identify candidate targets for ED treatment. We constructed an ED disease gene network by combining the integration of epigenomics (ATAC-seq and ChIP-seq-H3K27ac) and transcriptomics data (RNA-seq) from human aorta endothelial cells (HAEC) exposed to surrogates of primary CV risk factors using network propagation. We then used in silico perturbation to prioritise genes that could influence the ED network most when removed. This process resulted in identifying 17 key candidates for which chemical inhibitors are available. These are genes associated with ED and atherosclerosis, and drugs that target those genes have not yet been tested for the treatment of CV disorders. The EGLN3 target and its inhibitor displayed significant anti-inflammatory and antioxidant properties in ECs assessed using a high-content screening platform. These findings illustrate the potential of in silico knockouts to discover disease-specific candidate targets for drug development or repositioning.

systems biology↗

bioRxiv2022

Phosphoproteomic profiling highlights CDC42 and CDK2 as key players in the regulation of the TGF-β pathway in ALMS1 and BBS1 knockout models

BACKGROUNDThe primary cilium is a sensory organelle that extends from the plasma membrane. It plays a vital role in physiological and developmental processes by controlling different signalling pathways such as WNT, Sonic hedgehog (SHh), and transforming growth factor {beta} (TGF-{beta}). Ciliary dysfunction has been related to different pathologies such as Alstrom (ALMS) or Bardet-Biedl (BBS) syndrome. The leading cause of death in adults with these syndromes is chronic kidney disease (CKD), which is characterised by fibrotic and inflammatory processes often involving the TGF-{beta} pathway. METHODSUsing genomic editing with CRISPR-CAS9 and phosphoproteomics we have studied the TGF-{beta} signalling pathway in knockout (KO) models for ALMS1 and BBS1 genes. We have developed a network diffusion-based analysis pipeline to expand the data initially obtained and to be able to determine which processes were deregulated in TGF-{beta} pathway. Finally, we have analysed protein-protein and kinase-substrate interactions to prioritise candidate genes in the regulation of the TGF-{beta} pathway in ALMS and BBS. RESULTSAnalysis of differentially phosphorylated proteins identified 10 candidate proteins in the ALMS1 KO model and 41 in the BBS1 KO model. After network expansion using a random walk with a restart algorithm, we were able to identify the TGF-{beta} signalling pathway together with other related processes such as endocytosis in the case of ALMS1 or the regulation of the extracellular matrix in BBS1. Protein interaction analyses demonstrated the involvement of CDC42 as a central protein in the interactome in ALMS1 and CDK2 in the case of BBS1. CONCLUSIONIn conclusion, the depletion of ALMS1 and BBS1 affects the TGF-{beta} signalling pathway, conditioning the phosphorylation and activation of several proteins, including CDC42 in the case of ALMS1 and CDK2 in the case of BBS1.

cell biology↗

bioRxiv2022

Large-scale phage-based screening reveals extensive pan-viral mimicry of host short linear motifs

Viruses mimic host short linear motifs (SLiMs) to hijack and deregulate cellular functions. Studies of motif-mediated interactions therefore provide insight into virus-host dependencies, and reveal targets for therapeutic intervention. Here, we describe the pan-viral discovery of 1,712 SLiM-based virus-host interactions using a phage peptidome tiling the intrinsically disordered protein regions of 229 RNA viruses. We find mimicry of host SLiMs to be a ubiquitous viral strategy, reveal novel host proteins hijacked by viruses, and identify cellular pathways frequently deregulated by viral motif mimicry. Using structural and biophysical analyses, we show that viral mimicry-based interactions have similar binding strength and bound conformations as endogenous interactions. Finally, we establish polyadenylate-binding protein 1 as a potential target for broad-spectrum antiviral agent development. Our platform enables rapid discovery of mechanisms of viral interference and the identification of potential therapeutic targets which can aid in combating future epidemics and pandemics.

biochemistry↗

bioRxiv2021

Identification of phenotype-specific networks from paired gene expression-cell shape imaging data

The morphology of breast cancer cells is often used as an indicator of tumour severity and prognosis. Additionally, morphology can be used to identify more fine-grained, molecular developments within a cancer cell, such as transcriptomic changes and signaling pathway activity. Delineating the interface between morphology and signaling is important to understand the mechanical cues that a cell processes in order to undergo epithelial-to-mesenchymal transition and consequently metastasize. However, the exact regulatory systems that define these changes remain poorly characterised. In this study, we employ a network-systems approach to integrate imaging data and RNA-seq expression data. Our workflow allows the discovery of unbiased and context-specific gene expression signatures and cell signaling sub-networks relevant to the regulation of cell shape, rather than focusing on the identification of previously known, but not always representative, pathways. By constructing a cell-shape signaling network from shape-correlated gene expression modules and their upstream regulators, we found central roles for developmental pathways such as WNT and Notch as well as evidence for the fine control of NFkB signaling by numerous kinase and transcriptional regulators. Further analysis of our network implicates a gene expression module enriched in the RAP1 signaling pathway as a mediator between the sensing of mechanical stimuli and regulation of NFkB activity, with specific relevance to cell shape in breast cancer.

systems biology↗

bioRxiv2019

Proteome-wide inference of protein kinase regulatory circuits

Complex networks of regulatory relationships between protein kinases comprise a major component of intracellular signaling. Although many kinase-kinase regulatory relationships have been described in detail, these are biased towards well-studied kinases while the majority of possible relationships remains unexplored. Here, we implement data-driven, unbiased methods to predict human kinase-kinase regulatory relationships and whether they have activating or inhibiting effects. We incorporate high-throughput data, kinase specificity profiles, and structural information to produce our predictions. The results successfully recapitulate previously annotated regulatory relationships and can reconstruct known signaling pathways from the ground up. The full network of predictions is relatively sparse, with the vast majority of relationships assigned low probabilities. However, it nevertheless suggests denser modes of inter-kinase regulation than normally considered in intracellular signaling research.

systems biology↗

bioRxiv2018

Systematic Characterization of RhoGEF/RhoGAP Regulatory Proteins Reveals Organization Principles of Rho GTPase Signaling

Rho GTPases control cell morphogenesis and thus fundamental processes in all eukaryotes. They are regulated by 145 RhoGEF and RhoGAP multi-domain proteins in humans. How the Rho signaling system is organized to generate localized responses in cells and prevent their spreading is not understood. Here, we systematically characterized the substrate specificities, localization and interactome of the RhoGEFs/RhoGAPs and revealed their critical role in contextualizing and spatially delimiting Rho signaling. They localize to multiple compartments providing positional information, are extensively interconnected to jointly coordinate their signaling networks and are widely autoinhibited to remain sensitive to local activation. RhoGAPs exhibit lower substrate specificity than RhoGEFs and may contribute to preserving Rho activity gradients. Our approach led us to uncover a multi-RhoGEF complex downstream of G-protein-coupled receptors controlling a Cdc42/RhoA crosstalk. The spatial organization of Rho signaling thus differs from other small GTPases and expands the repertoire of mechanisms governing localized signaling activity.

cell biology↗