Niels Grabe

High density of FOXP3-positive T cells infiltrating colorectal cancers with microsatellite instability.

High-level microsatellite instability (MSI-H) in colorectal cancer accounts for about 12% of colorectal cancers and is typically associated with a dense infiltration with cytotoxic CD8-positive lymphocytes. The role of regulatory T cells that may interfere with the hosts antitumoural immune response in MSI-H colorectal cancers has not been analysed yet. Using an antibody directed against the regulatory T-cell marker transcription factor forkhead box P3 (FOXP3), regulatory T cells were examined in 70 colorectal cancers with known MSI status (MSI-H, n=37; microsatellite stable, n=33). In MSI-H colorectal cancers, we found a significantly higher intraepithelial infiltration with FOXP3-positive cells (median: 8.5 cells per 0.25u2009mm2 vs 3.1 cells per 0.25u2009mm2 in microsatellite stable, P<0.001), and a significantly elevated ratio of intraepithelial to stromal infiltration (0.05 vs 0.01 in microsatellite stable, P<0.001). CD8-positive cell counts were related positively to the number of FOXP3-positive cells (Spearmans ρ=0.56 and 0.55, respectively). Our results show that the elevated number of CD8-positive lymphocytes found in MSI-H colorectal cancers is paralleled by an enhanced infiltration with CD8-negative FOXP3-positive cells. These data suggest that FOXP3-positive cells may play a role in the regulation of the immune response directed against MSI-H colorectal cancers at the primary tumour site.

Bridging the scales

MOTIVATIONnBiological reality can in silico only be comprehensively represented in multi-scaled models. To this end, cell behavioural models addressing the multi-cellular level have to be semantically linked with mechanistic molecular models. These requirements have to be met by flexible software workflows solving the issues of different time scales, inter-model variable referencing and flexible sub-model embedding.nnnRESULTSnWe developed a novel software workflow (EPISIM) for the semantic integration of Systems Biology Markup Language (SBML)-based quantitative models in multi-scaled tissue models and simulations. This workflow allows to import and access SBML-based models. SBML model species, reactions and parameters are semantically integrated in cell behavioural models (CBM) represented by graphical process diagrams. By this, cellular states like proliferation and differentiation can be flexibly linked to gene-regulatory or biochemical reaction networks. For a multi-scale agent-based tissue simulation executable code is automatically generated where different time scales of imported SBML models and CBM have been mapped. We demonstrate the capabilities of the novel software workflow by integrating Tysons cell cycle model in our model of human epidermal tissue homeostasis. Finally, we show the semantic interplay of the different biological scales during tissue simulation.nnnAVAILABILITYnThe EPISIM platform is available as binary executables for Windows, Linux and Mac OS X at http://www.tiga.uni-hd.de. Supplementary data are available at http://www.tiga.uni-hd.de/supplements/SemSBMLIntegration.html.nnnCONTACTnniels.grabe@bioquant.uni-heidelberg.de.

Modeling multi-cellular behavior in epidermal tissue homeostasis via finite state machines in multi-agent systems

MOTIVATIONnFor the efficient application of multi-agent systems to spatial and functional modeling of tissues flexible and intuitive modeling tools are needed, which allow the graphical specification of cellular behavior in a tissue context without presuming specialized programming skills.nnnRESULTSnWe developed a graphical modeling system for multi-agent based simulation of tissue homeostasis. An editor allows the intuitive and hierarchically structured specification of cellular behavior. The models are then automatically compiled into highly efficient source code and dynamically linked to an interactive graphical simulation environment. The system allows the quantitative analysis of the morphological and functional tissue properties emerging from the cell behavioral model. We demonstrate the relevance of the approach using a recently published model of epidermal homeostasis as well as a series of cell-cycle models.nnnAVAILABILITYnThe complete software is available in binary executables for MS-Windows and Linux at tiga.uni-hd.de.

Reconstructing protein networks of epithelial differentiation from histological sections

MOTIVATIONnFor systems biology of complex stratified epithelia like human epidermis, it will be of particular importance to reconstruct the spatiotemporal gene and protein networks regulating keratinocyte differentiation and homeostasis.nnnRESULTSnInside the epidermis, the differentiation state of individual keratinocytes is correlated with their respective distance from the connective tissue. We here present a novel method to profile this correlation for multiple epithelial protein biomarkers in the form of quantitative spatial profiles. Profiles were computed by applying image processing algorithms to histological sections stained with tri-color indirect immunofluorescence. From the quantitative spatial profiles, reflecting the spatiotemporal changes of protein expression during cellular differentiation, graphs of protein networks were reconstructed.nnnCONCLUSIONnSpatiotemporal networks can be used as a means for comparing and interpreting quantitative spatial protein expression profiles obtained from different tissue samples. In combination with automated microscopes, our new method supports the large-scale systems biological analysis of stratified epithelial tissues.

Nuclear staining and relative distance for quantifying epidermal differentiation in biomarker expression profiling

BackgroundThe epidermal physiology results from a complex regulated homeostasis of keratinocyte proliferation, differentiation and death and is tightly regulated by a specific protein expression during cellular maturation. Cellular in silico models are considered a promising and inevitable tool for the understanding of this complex system. Hence, we need to incorporate the information of the differentiation dependent protein expression in cell based systems biological models of tissue homeostasis. Such methods require measuring tissue differentiation quantitatively while correlating it with biomarker expression intensities.ResultsDifferentiation of a keratinocyte is characterized by its continuously changing morphology concomitant with its movement from the basal layer to the surface, leading to a decreased average nuclei density throughout the tissue. Based thereon, we designed and evaluated three different mathematical measures (nuclei based, distance based, and joint approach) for quantifying differentiation in epidermal keratinocytes. We integrated them with an immunofluorescent staining and image analysis method for tissue sections, automatically quantifying epidermal differentiation and measuring the corresponding expression of biomarkers. When studying five well-known differentiation related biomarkers in an epidermal neck sample only the resulting biomarker profiles incorporating the relative distance information of cells to the tissue borders (distance based and joint approach) provided a high-resolution view on the whole process of keratinocyte differentiation. By contrast, the inverse nuclei density approach led to an increased resolution at early but heavily decreased resolution at late differentiation. This effect results from the heavy non-linear decay of DAPI intensity per area, probably caused by cytoplasmic growth and chromatin decondensation. In the joint approach this effect could be compensated again by incorporating distance information.ConclusionWe suppose that key mechanisms regulating tissue homeostasis probably depend more on distance information rather than on nuclei reorganization. Concluding, the distance approach appears well suited for comprehensively observing keratinocyte differentiation.

Virtual microscopy in systems pathology

Genomics and proteomics have evolved towards systems biology. The general goal here is the construction of complex, functional models of biological systems on the basis of molecular networks. Such models enable improved quality in interpretation and evaluation of quantitative measurements and afford a substantially deeper functional understanding. Systems pathology differs from systems biology by attaching the same importance to spatial modelling of tissue alterations as to gene regulatory modelling. In this way, systems pathology is able to deploy disease models for improved diagnosis, prognosis and therapy. In the present work a generic process for systems pathology is created, integrating gene regulatory and morphological models towards molecular disease models. For this purpose, fluorescent virtual microscopy will be essential as it delivers morphological and molecular tissue data with high spatial resolution and high throughput. Using epidermal differentiation as an example, it is shown how - using virtual microscopy - the spatiotemporal expression of biomarkers can be modelled by reconstructing protein networks from fluorescent tissue sections.ZusammenfassungGenomics und Proteomics haben sich zur Systembiologie weiterentwickelt. Grundsätzliches Ziel ist hierbei die Erstellung komplexer funktionaler Modelle biologischer Systeme über molekulare Netzwerke. Derartige Modelle erlauben die Interpretation und Bewertung quantitativer Messergebnisse in einer neuen Qualität und einem erheblich vertieften funktionalen Verständnis. Im Unterschied zur reinen Systembiologie wird bei der Systempathologie die morphologische Gewebeebene gleichberechtigt neben der molekularen genregulatorischen Ebene stehen. Hierdurch kann die Systempathologie realistische Krankheitsmodelle entwerfen, die von direktem Nutzen für Diagnose, Prognose und Therapie sein werden. In der vorliegenden Arbeit wird ein generischer Prozess der Systempathologie entworfen, der ein morphologisches mit einem genregulatorischen Modell zu einem molekularen Krankheitsmodell integriert. Die fluoreszente virtuelle Mikroskopie wird hierbei von essenzieller Bedeutung sein. Sie liefert morphologische und molekulare Gewebedaten in hoher Auflösung und großem Durchsatz. Am Beispiel der epidermalen Differenzierung wird gezeigt, wie – mithilfe der virtuellen Mikroskopie – aus fluoreszenten Gewebeschnitten Proteinnetzwerke rekonstruiert werden können, die die räumlich-zeitliche Expression von Biomarkern quantitativ modellieren.AbstractGenomics and proteomics have evolved towards systems biology. The general goal here is the construction of complex, functional models of biological systems on the basis of molecular networks. Such models enable improved quality in interpretation and evaluation of quantitative measurements and afford a substantially deeper functional understanding. Systems pathology differs from systems biology by attaching the same importance to spatial modelling of tissue alterations as to gene regulatory modelling. In this way, systems pathology is able to deploy disease models for improved diagnosis, prognosis and therapy. In the present work a generic process for systems pathology is created, integrating gene regulatory and morphological models towards molecular disease models. For this purpose, fluorescent virtual microscopy will be essential as it delivers morphological and molecular tissue data with high spatial resolution and high throughput. Using epidermal differentiation as an example, it is shown how – using virtual microscopy – the spatiotemporal expression of biomarkers can be modelled by reconstructing protein networks from fluorescent tissue sections.

From virtual microscopy to systems pathology

Virtual microscopy encompasses the high-resolution scanning of tissue slides and cell preparation and derived technologies including automatic digitalization and computational processing of whole microscopic slides, cytological preparations and tissue arrays, and web-based easy accessibility and analyses. For the first time, it enables highthroughput imaging and quantitative measurements of tissue structures. By integrating mass tissue data and derived analyses, virtual microscopy creates novel synergies between technological disciplines such as pathology/ histology, bioinformatics, medical informatics, image analysis, as well as cell and molecular biology. These technical synergies may pave the way for new structures in research, clinical diagnostics, education, and training and fundamentally support newly arising disciplines like medical systems biology. The 1st European Workshop on Tissue Imaging and Analysis, held in Heidelberg on 13th and 14th February 2009 intended to provide a discussion forum for multiple disciplines related to virtual microscopy, like pathology, systems biology and pathology, computer-assisted highthroughput diagnostics, cell-based cancer diagnostics, bioinformatics and image processing, and the scientific exchange of key players in the field. Over 140 participants from 10 European countries as well as USA and Japan took part in the meeting.

A 3D self-organizing multicellular epidermis model of barrier formation and hydration with realistic cell morphology based on EPISIM

The epidermis and the stratum corneum (SC) as its outermost layer have evolved to protect the body from evaporative water loss to the environment. To morphologically represent the extremely flattened cells of the SC - and thereby the epidermal barrier - in a multicellular computational model, we developed a 3D biomechanical model (BM) based on ellipsoid cell shapes. We integrated the BM in the multicellular modelling and simulation platform EPISIM. We created a cell behavioural model (CBM) with EPISIM encompassing regulatory feedback loops between the epidermal barrier, water loss to the environment, and water and calcium flow within the tissue. This CBM allows a small number of stem cells to initiate self-organizing epidermal stratification, yielding the spontaneous emergence of water and calcium gradients comparable to experimental data. We find that the 3D in silico epidermis attains homeostasis most quickly at high ambient humidity, and once in homeostasis the epidermal barrier robustly buffers changes in humidity. Our model yields an in silico epidermis with a previously unattained realistic morphology, whose cell neighbour topology is validated with experimental data obtained from in vivo images. This work paves the way to computationally investigate how an impaired SC barrier precipitates disease.

Automated model-driven generation of software components for the simulation of epithelial tissues

Quantitative in silico modeling is a powerful means to enhance our understanding of complex biological systems. Accordingly, intuitive and flexible computational tools are needed to support the development of such models. We previously developed the platform EPISIM for graphical modeling and simulation of cellular behavior in epithelia. In this work we demonstrate how computationally efficient software components for epithelial tissue simulations can be automatically generated. We introduce a model-driven workflow to generate extendable and exchangeable software components for both the modeling and the simulation of epithelial tissues. We distinguish two levels of abstraction in our workflow and thus two kinds of models: (i) the meta-model of our modeling language and (ii) particular systems biological cell behavioral models. The model-driven component generation allows optimization of the underlying code and the automated integration in our EPISIM platform. We evaluated the computational performance and the correctness of the generated software components. In this work we focus on the evaluation of the computational performance. It could be shown that the execution time increases nearly linearly with the size of the generated components underlying model.

Molekulare Bioinformatik — Informationsfusion zur Genregulation

Die Methoden der Bioinformatik haben zum Ziel unbekannte, grose genomische Datenmengen auf ihre Funktion hin zu analysieren. Da dies unter Nutzung bekannter genomischer Datenmengen geschieht, konnen Methoden der Bioinformatik im weiteren Sinne als algorithmische Fusion verschiedener Informationsquellen verstanden werden. Beispielhaft wird unter dieser Sichtweise ein neues Verfahren vorgestellt, das Genschaltersequenzen in DNA identifiziert, ohne vorher eine Modellreprasentation dieser zu bilden. Statt dessen werden hochspezifische Modelle der Genschaltersequenzen erst in Zusammenhang mit der zu analysierenden Sequenz gebildet. Das vorgestellte Verfahren ist das derzeit einzige, das Modelle von Genschaltersequenzen selbstandig und anwendungsbezogen aus entsprechenden Informationsquellen erzeugt und somit die Vorhersagemethode als Prozes der Informationsfusion begreift. Das Verfahren wurde implementiert und ist uber obige WWW-Adresse als AliBaba2 verfugbar.1