Integrated and spatial-temporal multiscale modeling of liver guide in vivo experiments in healthy & chronic disease states: a blue print for systems medicine?

EVENT : C3BI Seminars


Main speaker : Dirk Drasdo, from INRIA / IZBI Joint Research Group Date : 20-09-2018 at 02:00 pm Location : Salle Retrovirus – Bâtiment LWOFF ,Institut Pasteur, Paris


Background and Aims:  Hyperammonemia after drug-induced peri-central liver lobule damage, as from overdosing acetaminophen (paracetamol), and can lead to encephalopathy and dead of the patient. Guided by mathematical models, the consensus set of chemical reactions for detoxification of liver from ammonia has recently been shown to fail in explaining ammonia-detoxification after drug-induced peri-central damage (Schliess et. al., 2014). Our aim is to demonstrate how integrated and spatial-temporal models mimicking detoxification of the blood from ammonia in virtual tissue samples can assist in guiding identification of missing molecular mechanisms, or predicting the impact of micro-architectural alterations due to acute or chronic damage on ammonia detoxification. Our modeling methodology is very general.     Method:The consensus and alternative detoxification mechanisms have been implemented within mathematical integrated and spatial-temporal multi-scale models to test various hypotheses on potentially missing mechanisms in ammonia detoxification during liver regeneration after drug-induced pericentral damage in silicoin a virtual liver lobule (Drasdo et. al., J. Hepat. 2014). The multi-scale model simulates blood flow and molecular transport in the spatial lobule micro-architecture and displays each individual hepatocyte in space and time. Detoxification reactions are executed in each virtual hepatocyte. This makes in silicotesting of hypothesized mechanisms feasible from the molecular up to the tissue scale. The results are directly compared to experiments in mouse. Finally, fibrotic streets have been added to the model to predict the possible impact of architectural distortions and micro-shunts.     Results:We demonstrate how multiscale and multilevel models guided experiments towards identification of a previously unrecognized ammonia detoxification mechanism, that has the potential of improving treatment in hyperammonemia (Ghallab et. al., J. Hepat. 2016). The same model predicts for CCl4-induced fibrosis a reduced detoxification capacity for ammonia. Finally we outline how the whole body scale can be included to arrive at a model spanning molecular up to whole body scale permitting to study the relation of molecular changes and micro-architecture on whole body blood circulation, and briefly summarize results of integration of APAP toxic pathway as HGF signaling.    

Conclusion:Refined multi-scale models increasingly permit realistic prediction of liver function as well as of toxic injury in acute and chronic damage states. Those models can integrate data from various sources, in vitro, different animal models or human data. The direct representation of liver micro-architecture in those models will open up the future perspective to feed these models with patient-specific data, hence generating a virtual twin of a patients’ liver to guide personalized diagnosis and therapy planning.


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Signatures of ecological processes in microbial community time series

EVENT : C3BI Seminars


Main speaker : Karoline Faust, from KU Leuven Date : 04-10-2018 at 02:00 pm Location : Auditorium Francois Jacob – BIME (26) ,Institut Pasteur, Paris


Nowadays, a number of densely sampled microbial community time series is available, where the abundance of community members is tracked over several months through sequencing. These data allow exploring community dynamics by investigating signatures of underlying ecological processes that are present in the community time series. In this seminar, I will present our work on the exploitation of time series properties to distinguish between different ecological processes behind the observed dynamics

  http://psbweb05.psb.ugent.be/conet/karoline/

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Computational microbial genomics

EVENT : C3BI Seminars


Main speaker : Zamin Iqbal, from Royal Society/Wellcome Trust Sir Henry Dale Fellow, EMBL-EBI Date : 07-03-2019 at 02:00 pm Location : Auditorium Francois Jacob – BIME (26) ,Institut Pasteur, Paris


TBA


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Unit Seminar – Lucas Husquin & Jakob Ruess

 

EVENT : C3BI Unit Seminars


Main speaker : Lucas Husquin, from Human evolutionary genetics unit Date : 15-02-2018 at 02:00 pm Location : Auditorium Francois Jacob – BIME (26) ,Institut Pasteur, Paris


Lucas Husquin (Human evolutionary genetics unit) : “Dissecting the impact of population variation in DNA methylation on transcriptional responses to immune activation”

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Jakob Ruess (InBio : Experimental and computational methods for modeling cellular processes) : “Virtual reality for bacteria”


Unit Seminar – Frédéric Lemoine & Lyam Baudry

 

EVENT : C3BI Unit Seminars


Main speaker : Frederic Lemoine from Bioinformatique evolutive Unit Date : 18-01-2018 at 02:00 pm Location : Auditorium Francois Jacob – BIME (26) ,Institut Pasteur, Paris


Frederic Lemoine (Bioinformatique Evolutive) : “Renewing Felsenstein’s Phylogenetic Bootstrap in the Era of Big Data”

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Lyam Baudry (Spatial Regulation of Genomes) : “Metagenome binning using chromosome conformation capture (3C) data”


Seminars – Statistical design and analysis of reproducible quantitative mass spectrometry-based experiments

EVENT : C3BI Seminars

Statistical design and analysis of reproducible quantitative mass spectrometry-based experiments


Main speaker : Olga Vitek, from Northeastern University, Boston, MA, USA
Date : 07/12/2017 at 02:00 pm
Location : Salle Retrovirus-LWOFF, Institut Pasteur, Paris


Statistical methodology is key for quantitative proteomics, as it helps reduce bias and inefficiencies,  distinguish the systematic variation from random artifacts, and maximize the reproducibility of the results. This talk will overview the statistical methodology implemented in MSstats, an open-source R package for statistical relative quantification of proteins and peptides. MSstats supports experiments with complex designs, such as comparisons of multiple groups or time course comparisons. It handles quantitative shotgun DDA (data-dependent acquisition) experiments, targeted SRM (selected reaction monitoring), and SWATH/DIA (data independent acquisition) experiments. It can be used in conjunction with label-free experimental workflows, or with workflows that utilize stable isotope reference proteins or peptides. MSstats contains functionalities for data processing, model-based statistical analysis (including testing proteins and peptides for differential abundance, or estimating protein abundance on a relative scale), and model-based calculation of a sample size for a future experiment. It also contains functionalities for systems suitability and statistical process control, and for quantification of figures of merit (such as limit of detection) of mass spectrometric assays. MSstats is available stand-alone or via graphical user interface as an external tool in the software framework Skyline. It can be interfaced with numerous spectral processing tools, such as MaxQuant.


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Unit Seminar – Marie Lopez & Bradley Worley

EVENT : C3BI Seminars

Marie Lopez: “The demographic history and mutational load of African hunter-gatherers and farmers”

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 Bradley Worley :”Statistical model-based methods of sampling in nuclear magnetic resonance” 


Main speaker : Marie Lopez & Bradley Worley, from C3BI Department Date : 26/10/2017 at 02:00 pm Location : Retrovirus room – LWOFF (22) ,Institut Pasteur, Paris


Marie Lopez from the Unit Génétique évolutive humaine and Bradley Worley from the INBIO Unit (Méthodes expérimentales et computationnelles pour la modélisation des processus cellulaires) will present their current research.


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Seminars – Perturbing the interactome: multi-omics and personalized methods for network medicine

EVENT : C3BI Seminars

Perturbing the interactome: multi-omics and personalized methods for network medicine


Main speaker : Marc Santolini, from Network Science Institute at Northeastern University, Boston Date : 19/10/2017 at 03:00 pm Location : Module 1-2-3 – SOCIAL BUILDING (06) ,Institut Pasteur, Paris


In this talk, I will describe several recently developed methods to study disease perturbations through the lens of network science. First I will present an investigation of the personalized gene expression responses when inducing hypertrophy and heart failure in 100+ strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). I will show that genes whose expression change significantly correlates with the severity of the disease are either up- or down-regulated across strains, and therefore missed by traditional population-wide analyses of differential gene expression. These uncovered personalised genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome, the set of molecular interactions in the cell. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes, demonstrating that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies. Then, I will present a novel approach to identify the collective impact of miRNAs in disease. Instead of focusing on the magnitude of miRNA differential expression, here we address the secondary consequences for the interactome. We developed the Impact of Differential Expression Across Layers (IDEAL), a network-based algorithm to prioritize disease-relevant miRNAs based on the central role of their targets in the molecular interactome. This method was used in the context of asthmatic Th2 inflammation and identified five Th2-related miRNAs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. This result offers novel approaches for therapeutic interventions. Finally, I will present evidence that one can accurately predict perturbation patterns from the topology of biological networks, even when lacking measurements on the kinetic parameters governing the dynamics of these interactions. Using 87 biochemical networks with experimentally measured kinetic parameters, we show that a knowledge of the network topology offers 65% to 80% accuracy in predicting the impact of perturbations. In other words, we can use the increasingly accurate topological models to approximate perturbation patterns, bypassing expensive kinetic constant measurement. These results open new avenues in modeling drug action, and in identifying drug targets relying on the human interactome only.


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Seminars – A leap forward in biological link prediction

EVENT : C3BI Seminars

A leap forward in biological link prediction


Main speaker : Itsvan Kovacs, from Network Science Institute at Northeastern University, Boston Date : 19/10/2017 at 02:00 pm Location : Module 1-2-3 – SOCIAL BUILDING (06) ,Institut Pasteur, Paris


Biological function emerges from the complex interplay between molecules in our cells, comprising the human interactome. While interactions between proteins play a central role in the interactome, current maps are still missing the majority of these interactions. State-of-the-art network-based link prediction tools rely on the triadic closure principle, stating that proteins are likely to interact if they share many of their interaction partners, utilizing network paths of length l=2. We show that this principle is valid only for the small fraction of self-interacting proteins, while it fails completely for the rest of the network. Supported by both evolutionary and protein structural arguments, we identify missing protein interactions based on l=3 paths. Our top predictions validate as well experimentally as known protein-protein interactions, outperforming previous methods at least 2-3 fold. Our Length 3 Association Prediction (L3AP) approach provides a fundamental biological principle with a broad potential applicability, including also protein associations (i.e. co-complex membership) information, enabling us to better understand the emergence of biological function under both healthy and pathological conditions.


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Seminars – Emergence of de novo protein coding genes from ‘dark genomic matter’ — fact or fiction?

EVENT : C3BI Seminars

Emergence of de novo protein coding genes from ‘dark genomic matter’ — fact or fiction?


Main speaker : Erich Bornberg-Bauer, from The Westfalian Wilhelms University of Muenster, Germany
Date : 09/11/2017 at 02:00 pm
Location : Auditorium Francois Jacob – BIME (26) ,Institut Pasteur, Paris


Proteins are the workhorses of the cell and, over billions of years, they have evolved an amazing plethora of extremely diverse and versatile structures with equally diverse functions. Therefore, their evolution echoes the evolution of all forms of life. Evolutionary emergence of new proteins and transitions between existing ones are widely believed to be rare or even impossible.
However, recent advances in comparative genomics have repeatedly called some 10%-30% of all genes without any detectable similarity to existing proteins. Even after careful scrutiny, some of those “orphan” genes contain protein coding reading frames with detectable transcription and translation. Thus some proteins seem to have emerged from previously non-coding ‘dark genomic matter’. These ‘de novo’ proteins tend to be disordered, fast evolving, weakly expressed but also rapidly assuming novel and physiologically important functions. I will review mechanisms by which ‘de novo’ proteins might be created, under which circumstances they may become fixed and why they are elusive. I will present a couple of studies which mostly focus on metazoan genomes.


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