
Arnau MontagudInstitute for Integrative Systems Biology (I2SysBio, CSIC)
Arnau Montagud
PhD
About
78
Publications
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Introduction
Additional affiliations
April 2012 - December 2013
Education
April 2007 - April 2012
September 2006 - June 2007
September 2001 - June 2006
Publications
Publications (78)
Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when de...
Introduction
The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing.
Methods
Extensive com...
In systems biology, mathematical models and simulations play a crucial role in understanding complex biological systems. Different modelling frameworks are employed depending on the nature and scales of the system under study. For instance, signalling and regulatory networks can be simulated using Boolean modelling, whereas multicellular systems ca...
Motivation:
Mathematical models of biological processes altered in cancer are built using the knowledge of complex networks of signaling pathways, detailing the molecular regulations inside different cell types, such as tumor cells, immune and other stromal cells. If these models mainly focus on intracellular information, they often omit a descrip...
The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdi...
Mathematical models of biological processes implicated in cancer are built using the knowledge of complex networks of signaling pathways, describing the molecular regulations inside different cell types, such as tumor cells, immune and other stromal cells. If these models mainly focus on intracellular information, they often omit a description of t...
The emergence of cell resistance in cancer treatment is a complex phenomenon that emerges from the interplay of processes that occur at different scales. For instance, molecular mechanisms and population-level dynamics such as competition and cell–cell variability have been described as playing a key role in the emergence and evolution of cell resi...
Computational systems and methods are often being used in biological research, including the understanding of cancer and the development of treatments. Simulations of tumor growth and its response to different drugs are of particular importance, but also challenging complexity. The main challenges are first to calibrate the simulators so as to repr...
Prostate cancer is the second most occurring cancer in men worldwide. To better understand the mechanisms of tumorigenesis and possible treatment responses, we developed a mathematical model of prostate cancer which considers the major signalling pathways known to be deregulated. We personalised this Boolean model to molecular data to reflect the h...
Motivation
Cancer progression is a complex phenomenon that spans multiple scales from molecular to cellular and intercellular. Simulations can be used to perturb the underlying mechanisms of those systems and to generate hypotheses on novel therapies. We present a new version of PhysiBoSS, a multiscale modelling framework designed to cover multiple...
The emergence of cell resistance in cancer treatment is a complex phenomenon that emerges from the interplay of processes that occur at different scales. For instance, molecular mechanisms and population-level dynamics such as competition and cell-cell variability have been described as playing a key role in the emergence and evolution of cell resi...
We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 mole...
Multi-scale simulations require parallelization to address large-scale problems, such as real-sized tumor simulations. BioFVM is a software package that solves diffusive transport Partial Differential Equations for 3-D biological simulations successfully applied to tissue and cancer biology problems. Currently, BioFVM is only shared-memory parallel...
Agent-based modelling has proven its usefulness in several biomedical projects by explaining and uncovering mechanisms in diseases. Nevertheless, the scenarios addressed in these models usually consider a small number of cells, lack cell-specific characterisation and dynamic interactions and have a simplistic environment description. Tools that ena...
Prostate cancer is the second most occurring cancer in men worldwide. To better understand the mechanisms of tumorigenesis and possible treatment responses, we developed a mathematical model of prostate cancer which considers the major signalling pathways known to be deregulated.
We personalised this Boolean model to molecular data to reflect the h...
Computational systems and methods are being applied to solve biological problems for many years. Incorporating methods of this kind in the research for cancer treatment and related drug discovery in particular, is shown to be challenging due to the complexity and the dynamic nature of the related factors. Usually, there are two objectives in such s...
In this work we present PhysiBoSS-COVID, an effort to integrate MaBoSS, a stochastic Boolean modelling software, into PhysiCell-COVID to allow the leverage of cell- and pathway-specific Boolean models in this framework. To obtain these COVID-19-specific models, we have taken advantage of CaSQ ability to convert all Covid19 Disease maps into SBML-qu...
We present INforE, a prototype supporting non-expert program-
mers in performing optimized, cross-platform, streaming analytics
at scale. INforE offers: a) a new extension to the RapidMiner Studio
for graphical design of Big streaming Data workflows, (b) a novel
optimizer to instruct the execution of workflows across Big Data
platforms and clusters...
Dendrograms are a way to represent relationships between organisms. Nowadays, these are inferred based on the comparison of genes or protein sequences by taking into account their differences and similarities. The genetic material of choice for the sequence alignments (all the genes or sets of genes) results in distinct inferred dendrograms. In thi...
Logical models of cancer pathways are typically built by mining the literature for relevant experimental observations. They are usually generic as they apply for large cohorts of individuals. As a consequence, they generally do not capture the heterogeneity of patient tumors and their therapeutic responses. We present here a novel framework, referr...
The current consensus recognizes four main medulloblastoma subgroups (wingless, Sonic hedgehog, group 3 and group 4). While medulloblastoma subgroups have been characterized extensively at the (epi-)genomic and transcriptomic levels, the proteome and phosphoproteome landscape remain to be comprehensively elucidated. Using quantitative (phospho)-pro...
Motivation:
Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaB...
Due to the complexity of biological systems, their heterogeneity, and the internal regulation of each cell and its surrounding, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful to understand such complex systems. However, very few of these tools, freely...
Mathematical models can serve as a tool to formalize biological knowledge from diverse sources, to investigate biological questions in a formal way, to test experimental hypotheses, to predict the effect of perturbations and to identify underlying mechanisms. We present a pipeline of computational tools that performs a series of analyses to explore...
Deregulations in fundamental signaling pathways are key events in pathogenesis of cancer. One intriguing illustration that still holds blind spots is the pediatric brain tumor arising from the developing cerebellum: medulloblastoma (MB). Extensive high-throughput sequencing led to the characterization of four MB subgroups (WNT, SHH, Group 3 and Gro...
The present thesis is devoted to the development of models and algorithms to improve metabolic simulations of cyanobacterial metabolism. Cyanobacteria are photosynthetic bacteria of great biotechnological interest to the development of sustainable bio-based manufacturing processes. For this purpose, it is fundamental to understand metabolic behavio...
Dendrograms are a way to represent evolutionary relationships between organisms. Nowadays, these are inferred based on the comparison of genes or protein sequences by taking into account their differences and similarities. The genetic material of choice for the sequence alignments (all the genes or sets of genes) results in distinct inferred dendro...
The use of microorganisms as cell factories frequently requires extensive molecular manipulation. Therefore, the identification
of genomic neutral sites for the stable integration of ectopic DNA is required to ensure a successful outcome. Here we describe
the genome mapping and validation of five neutral sites in the chromosome of Synechocystis sp....
Currently, the reconstruction of genome-scale metabolic models is a non-automatized and interactive process based on decision making. This lengthy process usually requires a full year of one person’s work in order to satisfactory collect, analyze, and validate the list of all metabolic reactions present in a specific organism. In order to write thi...
Nowadays, there are many efforts for designing comprehensive systems that provide the information needed for constructing model organism databases. One of them is WholeCellKB that provides an extensive and customizable data model that describes the structure and function of each gene, protein, reaction and pathway. The philosophy of this kind of sy...
The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing pr...
The complexity of genome-scale metabolic models and networks associated to biological systems makes the use of computational tools an essential element in the field of systems biology. Here we present PyNetMet, a Python library of tools to work with networks and metabolic models. These are open-source free tools for use in a Python platform, which...
Currently, the in silico calculation of intracellular fluxes in biological systems is a widely used tool in Systems Biology. This method is based on the hypothesis that these systems work optimally with respect to certain biological criteria. Jointly, they are considered a set of constraints that pass since the imposition of a steady-state to the s...
Abstract A wide range of applications and research has been done with genome-scale metabolic models. In this work, we describe an innovative methodology for comparing metabolic networks constructed from genome-scale metabolic models and how to apply this comparison in order to infer evolutionary distances between different organisms. Our methodolog...
Abstract In the present economy, difficulties to access energy sources are real drawbacks to maintain our current lifestyle. In fact, increasing interests have been gathered around efficient strategies to use energy sources that do not generate high CO2 titers. Thus, science-funding agencies have invested more resources into research on hydrogen am...
Abstract Nowadays, the reconstruction of genome-scale metabolic models is a nonautomatized and interactive process based on decision making. This lengthy process usually requires a full year of one person's work in order to satisfactory collect, analyze, and validate the list of all metabolic reactions present in a specific organism. In order to wr...
A wide range of applications and research has been done with genome-scale
metabolic models. In this work we describe a methodology for comparing
metabolic networks constructed from genome-scale metabolic models and how to
apply this comparison in order to infer evolutionary distances between
different organisms. Our methodology allows a quantificat...
Background / Purpose:
Create a parameter for comparing metabolic networks. Use this parameter for reconstructing phylogenetic trees.
Main conclusion:
A parameter can be defined and used for phylogenetic tree reconstruction.
Many physiological studies have addressed the effects of environmental factors affecting cyanobacteria growth and Synechocystis sp. PCC 6803 in particular. However, multifactorial
studies are scarce.
In this work, the influence of different parameters such as temperature, irradiance, nitrate concentration, pH, and an external carbon source on Syn...
Background: Nowadays, the reconstruction of genome scale metabolic models is a non-automatized and interactive process based on decision taking. This lengthy process usually requires a full year of one person's work in order to satisfactory collect, analyze and validate the list of all metabolic reactions present in a specific organism. In order to...
In this contribution, a design of a synthetic calibration genetic circuit to characterize the relative strength of different sensing promoters is proposed and its specifications and performance are analyzed via an effective mathematical model. Our calibrator device possesses certain novel and useful features like modularity (and thus the possibilit...
The influence of different parameters such as temperature, irradiance, nitrate concentration, pH, and an external carbon source on Synechocystis PCC 6803 growth was evaluated.
4.5-ml cuvettes containing 2 ml of culture, a high-throughput system equivalent to batch cultures, were used with gas exchange ensured by the use of a Parafilm™ cover. The ef...
Cyanobacteria are photosynthetic prokaryotes that are promising 'low-cost' microbial cell factories due to their simple nutritional requirements and metabolic plasticity, and the availability of tools for their genetic manipulation. The unicellular non-nitrogen-fixing Synechocystis sp. PCC 6803 is the best studied cyanobacterial strain and its geno...
Reordering of S. warneri and W. paramesenteroides contigs from the metagenome of lab population based on the sequences of their reference genomes with MAUVE. (A) W. paramesenteroides ATCC 33313 (top) VS W. paramesenteroides contigs; (B) S. warneri L37603 (top) VS S. warneri contigs. The height of the colored lines in the collinear blocks represents...
Phylogenetic reconstruction of 34 complete 16S genes including the two complete 16S identified in the metagenome of the lab population (contig00689_Ostrinia nubilalis and contig00725_Ostrinia nubilalis). For details of the phylogenetic reconstruction method see Materials and Methods section.
(TIF)
Genome relative abundance of lab and field O. nubilalis metagenomes based on the GAAS program results [34].
(TIF)
Complete non-redundant gene sets predicted in O. nubilalis field metagenome with their corresponding annotation.
(XLS)
Taxonomic binning of O. nubilalis lab and field metagenomes based on compositional features of sequence assemblies.
(XLS)
Number of genes assigned to different bacterial species in both metagenomes based on BLASTP best hits.
(XLS)
Complete non-redundant gene sets predicted in O. nubilalis lab metagenome with their corresponding annotation.
(XLS)
Background:
Insects are associated with microorganisms that contribute to the digestion and processing of nutrients. The European Corn Borer (ECB) is a moth present world-wide, causing severe economical damage as a pest on corn and other crops. In the present work, we give a detailed view of the complexity of the microorganisms forming the ECB mid...
Synechocystis sp. PCC6803 is a model cyanobacterium capable of producing biofuels with CO(2) as carbon source and with its metabolism fueled by light, for which it stands as a potential production platform of socio-economic importance. Compilation and characterization of Synechocystis genome-scale metabolic model is a pre-requisite toward achieving...
In this study, we show the use of direct external electrical stimulation of a jellyfish luminescent calcium-activated protein, aequorin, expressed in a transgenic yeast strain. Yeast cultures were electrically stimulated through two electrodes coupled to a standard power generator. Even low (1.5 V) electric pulses triggered a rapid light peak and s...
Synthetic biology focuses on the design and construction of artificial genetic systems that are capable of carrying out a specific function after being inserted into a living system. With the development of synthetic biology a new generation of bioengineers has appeared who develop complex, highly integrated genetic biological pathways. The improve...
iSyn669 metabolic fluxes simulated under four conditions. Excel file with all the reactions simulations and resulting flux ranges from the model simulated under four growth conditions: autotrophy, dark o pure heterotrophy, light-activated heterotrophy and mixotrophy.
Fluxes of reactions around pyruvate. Flux values (in mmol/g DCW/h) for reactions that produce or drain pyruvate in Synechocystis sp. PCC6803 metabolism. Negative sign in bidirectional reactions means pyruvate consumption. Reactions names can be traced in reaction list in Additional files 2 and fluxes can be found in Additional file 4.
FBA and MOMA simulation values for biomass growth in Synechocystis sp. PCC6803, Escherichia coli and Saccharomyces cerevisiae genome-scale metabolic models. Excel file with the growth values under MOMA simulation for Synechocystis sp. PCC6803, Escherichia coli and Saccharomyces cerevisiae. Data for Synechocystis is original from present work, data...
iSyn669 groups of correlated genes in the three sets of arrays of light shift experiments. Word file with the list of iSyn669 correlated genes in "All time points", "Dark to light" and "Light to dark" analyses.
iSyn669 reactions to gene connections. Excel file with the list of iSyn669 reactions and its cognate list of genes.
iSyn669 genome-scale metabolic model in OptGene format. Text file with the stoichiometric model, in OptGene [37] format, with all the constraints needed for its simulation with FBA algorithm.
Most connected metabolites with filtered cofactors. Supplementary table with most connected metabolites once the cofactors have been filtered.