Biology subjects

Matallanas, D.

Publications and source records attributed to Matallanas, D..

9 recordsLinked to original sources

bioRxiv2026

OrthoGather: a local platform for orthology-based proteome and proteomics comparisons and Gene Ontology enrichment

MotivationComparative proteomic analysis may reveal common and unique pathways regulated by the same stimulus across species using data from differential protein expression studies or curated protein sets. Functional annotations are key but vary in quality, as many proteins, particularly in prokaryotes and non-model eukaryotes, are poorly or inconsistently annotated, complicating comparative studies. Orthology inference provides a robust framework to address this, but existing tools require technical expertise, command-line use, and manual processing of complex outputs, creating barriers for researchers without computational training. ResultsWe developed OrthoGather, a locally hosted web application that streamlines comparative proteomic analysis by integrating homologous protein groups across species and Gene Ontology (GO) enrichment. It leverages functional annotations from any orthogroup member to enable functional inference even when individual species lack comprehensive annotation. Its flexible design supports cross-species exploration of conserved and unique orthogroups across proteomes or user-defined protein sets, revealing functional patterns through orthogroup relationships. OrthoGather generates publication-ready, easy-to-interpret outputs including downloadable graphs and data files, lowering barriers for researchers without computational expertise. Availability and implementationSource code, documentation and tutorials are available at Zenodo (https://doi.org/10.5281/zenodo.18603238) and GitHub (https://github.com/CarlosVivasR/OrthoGather). Supplementary materials, including the example dataset analysis are available online at Bioinformatics.

systems biology↗

bioRxiv2024

Binucleated cell formation and oncogene expression after particulate matter exposure is preceded by microtubule disruption, dysregulated cell cycle, prolonged mitosis, and septin binding

Several biopersistent high aspect ratio nanomaterials show pronounced pathogenic effects, from chronic lung inflammation and fibrosis to cancer. For example, asbestos fibers are classified as carcinogens, whereas the carcinogenicity of highly inflammatory multi-wall carbon nanotubes (MWCNTs), and TiO2 nanomaterials is still being evaluated. The exact early mechanisms of their pathogenicity towards inflammation and cancer remains uncertain, but it is likely not due to genotoxic or mutagenic activity. A proposed early mode of action that might lead to the formation of cancerous cells for asbestos fibers is the formation of binucleated and multinucleated cells, resulting in genetic instability. Here, we show that two high aspect ratio nanomaterials, MWCNTs and TiO2 nanotubes, which both induce chronic lung inflammation, induce very different cancer-related changes in vitro. TiO2 nanotubes - but not low aspect-ratio nanocubes of the same crystalline structure - disrupt microtubule organization and prolong mitosis, as well as deform nuclear shape, induce the formation of binucleated cells, and downregulate the tumour suppressor protein p53, whereas only the MWCNTs activate the stimulator of the interferon genes (STING) pathway, a hallmark of lung cancer. The observed differences in cellular responses to different high aspect ratio materials imply the need for assessing each nanomaterial individually with a broad range of tests rather than relying solely on a single marker or pathway, or even morphological or bulk chemical properties to infer possible carcinogenic properties.

cancer biology↗

bioRxiv2022

Proteasomal downregulation of the pro-apoptotic MST2 pathway contributes to BRAF inhibitor resistance in melanoma

The RAS-RAF-MEK-ERK pathway is hyperactivated in almost all malignant melanomas, and mutations in BRAF or NRAS account for most of these cases. BRAF inhibitors are highly efficient for treating patients with BRAFV600E mutations, but tumours frequently acquire resistance within a few months. Multiple resistance mechanisms have been identified, due to mutations or network adaptations that revive ERK signalling. We have previously shown that RAF proteins inhibit the MST2 proapoptotic pathway in a kinase independent fashion. Here, we have investigated the role of the MST2 pathway in mediating resistance to BRAF inhibitors. We show that the BRAFV600E mutant protein, but not the wildtype BRAF protein, strongly binds to MST2 and inhibits MST2 pro-apoptotic signalling. Downregulation of MST2 reduces BRAF inhibitor induced apoptosis. In BRAF inhibitor resistant cell lines MST2 pathway proteins are downregulated by ubiquitination and subsequent proteasomal degradation rendering cells refractory to MST2 pathway induced apoptosis. Restoration of apoptosis can be achieved by increasing MST2 pathway protein expression using proteasome inhibitors. In summary, we show that the MST2 pathway plays a role in the acquisition of BRAF inhibitor resistance in melanoma.

molecular biology↗

bioRxiv2019

BAX and SMAC Regulate Bistable Properties of the Apoptotic Caspase System

The initiation of apoptosis is a core mechanism in cellular biology by which organisms control the removal of damaged or unnecessary cells. The irreversible activation of caspases is essential for apoptosis, and mathematical models have demonstrated that the process is tightly regulated by positive feedback and a bistable switch. BAX and SMAC are often dysregulated in diseases such as cancer or neurodegeneration and are two key regulators that interact with the caspase system generating the apoptotic switch. Here we present a mathematical model of how BAX and SMAC control the apoptotic switch. Formulated as a system of ordinary differential equations, the model summarises experimental and computational evidence form the literature and incorporates the biochemical mechanisms of how BAX and SMAC interact with the components of the caspase system. Using simulations and bifurcation analysis, we find that both BAX and SMAC regulate the time-delay and activation threshold of the apoptotic switch. Interestingly, the model predicted that BAX (not SMAC) controls the amplitude of the apoptotic switch. Cell culture experiments using siRNA mediated BAX and SMAC knockdowns this model prediction. We further validated the model on data of the NCI-60 cell line panel using BAX protein expression as cell-line specific parameter and show that model simulations correlated with the cellular response to DNA damaging drugs and established a defined threshold for caspase activation that could distinguish between sensitive and resistant melanoma cells. In summary, we present an experimentally validated dynamic model that summarises our current knowledge of how BAX and SMAC regulate the bistable properties of irreversible caspase activation during apoptosis.

systems biology↗

bioRxiv2019

Accurate Prediction of Kinase-Substrate Networks Using Knowledge Graphs

Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinase-substrate relationships is timeconsuming and often rather serendipitous. Computational predictions alleviate these challenges, but the current approaches suffer from limitations like restricted kinome coverage and inaccuracy. They also typically utilise only local features without reflecting broader interaction context. To address these limitations, we have developed an alternative predictive model. It uses statistical relational learning on top of phosphorylation networks interpreted as knowledge graphs, a simple yet robust model for representing networked knowledge. Compared to a representative selection of six existing systems, our model has the highest kinome coverage and produces biologically valid high-confidence predictions not possible with the other tools. Specifically, we have experimentally validated predictions of previously unknown phosphorylations by the LATS1, AKT1, PKA and MST2 kinases in human. Thus, our tool is useful for focusing phosphoproteomic experiments, and facilitates the discovery of new phosphorylation reactions. Our model can be accessed publicly via an easy-to-use web interface (LinkPhinder). Author SummaryLinkPhinder is a new approach to prediction of protein signalling networks based on kinase-substrate relationships that outperforms existing approaches. Phosphorylation networks govern virtually all fundamental biochemical processes in cells, and thus have moved into the centre of interest in biology, medicine and drug development. Fundamentally different from current approaches, LinkPhinder is inherently network-based and makes use of the most recent AI de-velopments. We represent existing phosphorylation data as knowledge graphs, a format for large-scale and robust knowledge representation. Training a link prediction model on such a structure leads to novel, biologically valid phosphorylation network predictions that cannot be made with competing tools. Thus our new conceptual approach can lead to establishing a new niche of AI applications in computational biology.

bioinformatics↗

bioRxiv2019

Subcellular localization of the immunoregulatory protein MACIR by TNPO1 is mediated by a C terminal PY motif

Expression of the macrophage immunometabolism regulator gene (MACIR) is associated with severity of autoimmune disease pathology and the regulation of macrophage biology through unknown mechanisms. The 206 amino acid protein lacks homology to any characterized protein sequence and is a disordered protein according to structure prediction algorithms. Here we identify specific interactions of MACIR using a fragment complementation-based affinity pull down of cellular proteins prepared with a membrane solubilization buffer. Quantitative mass spectrometry showed enrichment of nuclear and mitochondrial proteins and of 63 significant interacting proteins, binding to the nuclear transport receptor TNPO1 and trafficking proteins UNC119 homolog A and B were validated by immunoprecipitation. Analysis of mutations in two candidate recognition motifs in the MACIR amino acid sequence confirmed TNPO1 binds via a PY-NLS motif (aa98-117). Characterizing nuclear MACIR activity in macrophage and fibroblasts is a priority with respect to developing strategies for treatment of autoimmune disease.

biochemistry↗

bioRxiv2019

Rab28 is localised to photoreceptor outer segments, regulates outer segment shedding but is not linked to retinal degeneration in zebrafish

The photoreceptor outer segment is the canonical example of a modified and highly specialised cilium, with an expanded membrane surface area in the form of discs or lamellae for efficient light detection. Many ciliary proteins are essential for normal photoreceptor function and cilium dysfunction often results in retinal degeneration leading to impaired vision. Herein, we investigate the function and localisation of the ciliary G-protein RAB28 in zebrafish cone photoreceptors. CRISPR-Cas9 generated rab28 mutant zebrafish display a reduction in shed outer segment material in the RPE at 1 month post fertilisation (mpf), but otherwise normal retinal structure and visual function up to 12 mpf. Cone photoreceptor-specific transgenic reporter lines show Rab28 localises almost exclusively to outer segments, independently of nucleotide binding. Co-immunoprecipitation analysis demonstrates tagged Rab28 interacts with components of the phototransduction cascade, including opsins, Phosphodiesterase 6C and Guanylate Cyclase 2D. Our data shed light on RAB28 function in cones and provide a model for RAB28-associated cone-rod dystrophy.

cell biology↗

bioRxiv2018

Transcriptional regulatory mechanisms of fibrosis development in mouse lung tissue exposed to carbon nanotubes

BackgroundCarbon nanotubes (CNTs) usage has rapidly increased in the last few decades due to their unique properties, exploited in various industrial and commercial products. Certain types of CNTs cause adverse health effects, including chronic inflammation and fibrosis. Despite the large number of in vitro and in vivo studies evaluating these effects, many important questions remain unanswered due to a lack of mechanistic understanding of how CNTs induce cellular stress responses. In order to predict CNT toxicity, it is important to understand which transcriptional programs are specifically activated in response to CNTs, and what similarities and differences exist in relation to other toxic inducers exerting similar adverse effects.\n\nResultsA systems biology approach was applied to reveal complex interactions at the molecular level in mouse lung tissue in response to different fibrosis inducers: two types of multi-walled CNTs, NM-401 and NRCWE-26, and bleomycin (BLM). Based on mRNA gene expression profiles, we inferred gene regulatory networks (GRNs) to capture functional hierarchical regulatory structures between genes and their regulators. We found that activities of the transcription factors (TFs) Myc, Arid5a and Mxd1 were associated with the regulation of cytokine transcription in response to CNTs, while in response to BLM treatment, Myc was associated with p53 signaling. TF Litaf was identified as the essential regulator for noncanonical signaling of TLR2/4 driven by CNTs. Despite the different nature of the lung injury caused by CNTs and BLM, we identified common stress response modules, that included DNA damage (TFs: E2f8, E2f1, Foxm1), M1/M2 macrophage polarization (TF: Mafb), Interferon response (TFs: Irf7, Stat2 and Irf9) for all agents.\n\nConclusionsThese results suggest that the reconstruction and analysis of TF-centric gene interaction networks can reveal key targets and regulators of cellular stress responses to toxic agents.

pharmacology and toxicology↗

bioRxiv2017

A compendium of co-regulated protein complexes in breast cancer reveals collateral loss events

Protein complexes are responsible for the bulk of activities within the cell, but how their behavior and composition varies across tumors remains poorly understood. By combining proteomic profiles of breast tumors with a large-scale protein-protein interaction network, we have identified a set of 258 high-confidence protein complexes whose subunits have highly correlated protein abundance across tumor samples. We used this set to identify complexes that are reproducibly under- or over-expressed in specific breast cancer subtypes. We found that mutation or deletion of one subunit of a complex was often associated with a collateral reduction in protein expression of additional complex members. This collateral loss phenomenon was evident from proteomic, but not transcriptomic, profiles suggesting post-transcriptional control. Mutation of the tumor suppressor E-cadherin (CDH1) was associated with a collateral loss of members of the adherens junction complex, an effect we validated using an engineered model of E-cadherin loss.

cancer biology↗