Dokument: Cortical gene expression profiling in spinal cord repair: insight into the complexity of the neural regeneration program

Titel:Cortical gene expression profiling in spinal cord repair: insight into the complexity of the neural regeneration program
URL für Lesezeichen:https://docserv.uni-duesseldorf.de/servlets/DocumentServlet?id=12065
URN (NBN):urn:nbn:de:hbz:061-20090713-095855-2
Kollektion:Dissertationen
Sprache:Englisch
Dokumententyp:Wissenschaftliche Abschlussarbeiten » Dissertation
Medientyp:Text
Autor:Dipl. Biol. Kruse, Fabian [Autor]
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Dateien vom 08.07.2009 / geändert 08.07.2009
Beitragende:Prof. Dr. Müller, Hans Werner [Gutachter]
Prof. Dr. Willbold, Dieter [Gutachter]
Dewey Dezimal-Klassifikation:500 Naturwissenschaften und Mathematik » 570 Biowissenschaften; Biologie
Beschreibungen:Spezifische Veränderungen der kortikalen Genexpression nach einer Rückenmark-Verletzung wurden untersucht. Die nach traumatischen Verletzungen des Rückenmarks sich bildende kollagenhaltige fibröse Narbe stellt ein Hindernis für regenerierende Axone an der Läsionsstelle dar. Eine jüngst in diesem Labor entwickelte Therapie zur Unterdrückung dieser Narbenbildung (anti-scarring treatment, AST) durch lokale Applikation eines Eisen-Chelators und cyclisches Adenosinmonophosphat (cAMP) führt zu axonaler Regeneration über große Distanzen und funktioneller Erholung.
In dieser Arbeit wurden die Genexpressionsprofile der Schicht V des sensorimotorischen Cortex nach Transsektion des thorakalen Kortikospinaltrakts (cortico spinal tract, CST) zwischen 1 und 60 Tagen nach Operation (days post operation, dpo) mit Hilfe von Microarray-Analysen (Affymetrix) untersucht. Anhand dieses genetischen Ansatzes konnten kortikale Genregulationen identifiziert werden, welche durch die CST-Transsektion sowie die AST-induzierte axonale Regeneration hervorgerufen wurden.
Interessanterweise wurden in der Gruppe der Läsions-Kontrolltiere bereits am 1. Tag nach Operation mehr als 900 Gene signifikant reguliert gefunden. Zu späteren Zeitpunkten stieg die Anzahl der signifikant regulierten Gene noch bis zu einem Maximum von ca. 2.000 am 21. Tag an.
Basierend auf der Gene Ontology (GO, Ashburner et al., 2000) wurden regulierte Gene mit funktionellen Daten verknüpft und geclustert um besonders wichtige und durch die Rückenmarks-Verletzung beeinflusste Prozesse zu identifizieren. Wie erwartet waren zu den frühen Zeitpunkten besonders Gruppen wie „Verletzungs-Antwort“, „Wachstums-assoziierte zytoskeletale Reorganisation“ und „Zellüberleben“ betroffen, zu den späteren Zeitpunkten Gruppen wie „Proteinbiosynthese“, „Synaptische Reorganisation“ und „Apoptose“.
Ein direkter Vergleich der zeitspezifischen Expression von Läsions-Kontrolltieren und AST-behandelten Ratten dokumentierte eine starke AST-vermittelte Änderung der durch Läsion ausgelösten kortikalen Expressionsprofile. Diese Veränderungen spiegeln regenerations-assoziierte molekulare Reaktionen wieder. Tatsächlich zeigten die Microarray-Daten einen großen Anteil an Genen, die in AST-Tieren gegenläufig oder verstärkt sowie ausschließlich in behandelten Tieren reguliert waren. Viele durch AST regulierte Gene beeinflussen wichtige biologische Prozesse, die mit „Zellüberleben“, „Stress-Antwort“, „Zellschutz“ sowie „Axonaler Wegfindung“ und „Axonwachstum“ assoziiert sind.
Diese Arbeit zeigt zum ersten Mal einen umfassenden zeitlichen Vergleich der Genexpressionsprofile, welche die läsions-induzierten kortikalen Reaktionen nach traumatischer CST-Läsion sowie die Veränderungen durch erfolgreiche AST-vermittelte axonale Regeneration widerspiegeln. Zusätzlich erlauben die Ergebnisse phasen- und behandlungsabhängige Regulationsmuster zu definieren.
Das experimentelle Setup sowie die anschließende Datenauswertung und statistische Analyse wurden entsprechend ausgelegt um von heterogenem kortikalem Gewebe in solch komplexem Rahmen Genexpressionsprofile von multiplen Konditionen und Zeitpunkten zu ermöglichen. Ein auf Excel-VBA basierendes Programm und Python-basierte Skripte wurden zur Datenauswertung sowie Interaktion mit online frei zugänglichen Datamining-Tools programmiert. Basierend auf Schwellenwerten für Regulationsstärke und p-Werte können die gemeinsamen Expressionsprofile von fünf verschiedenen Analyse-Algorithmen visualisiert und mit funktionellen Informationen verknüpft werden. Besonders bei komplexen Expressionsmustern welche aus mehreren Zeitpunkten und Konditionen bestehen, lässt sich so ein komplettes Bild der Expressionsprofile erstellen. Die in dieser Arbeit vorgestellten Konzepte und Methoden zur Analyse und statistischen Auswertung von Microarray-Daten haben bereits zu mehreren Publikationen beigetragen (Kruse et al., 2008; Barbaria et al., 2009; Heinen et al., 2008; Kury et al., 2004; Kruse et al., 2009; Bosse et al., in preparation).

Traumatic injury of the spinal cord results in formation of a collagenous fibrous scar acting as a growth barrier for regenerating axons in the lesion centre. Recently, an anti-scarring treatment (AST) to suppress fibrous scarring by local application of an iron chelator and cyclic adenosin monophosphat (cAMP) was developed in this lab. AST led to long distance axon regeneration and functional recovery in adult rat (Klapka et al., 2005).
In this thesis, gene expression profiles of layer V of sensorimotor cortex following thoracic corticospinal tract (CST) transection from day 1 up to 60 days post-operation (dpo) were investigated by the means of microarray hybridization (Affymetrix). Using this genomic approach, cortical gene regulations triggered by CST-transection as well as by AST-induced axonal regeneration were identified.
Interestingly, more than 900 significantly regulated genes were detected as early as 1 dpo in the lesion-affected sensorimotor cortex. Subsequently, the number of significant regulations further increased to a maximum of approx. 2.000 genes at 21 dpo.
By means of Gene Ontology (GO)-categories (Ashburner et al., 2000) the genes were linked to functional information. GO clustering was than used to reveal processes that were of particular importance and were affected by spinal cord injury. As expected, ontologies representing “wound response”, “growth-associated cytoskeletal reorganization”, and “cell survival” were injury-affected at the early time points, whereas “protein biosynthesis”, “synaptic reorganization” and “apoptosis” were enriched at 21 dpo and/or 60 dpo.
Direct comparison of the temporal expression profiles of lesioned control rats and AST-treated animals documented strong AST-mediated modulation of the lesion-triggered cortical expression profiles, reflecting regeneration-associated molecular responses. Indeed, these data revealed substantial proportions of AST-counter-regulated and AST-boosted genes as well as discrete AST-specific gene regulations. Interestingly, numerous AST-regulated genes affect crucial biological processes associated with “cell survival“, “stress response”, “cellular protection” as well as “axon guidance” and “axonal outgrowth”.
For the first time, this work presents a comprehensive temporal comparison of gene expression profiles reflecting both the lesion-induced cortical response after traumatic CST lesion, and responses during successful AST-mediated axonal regeneration. Moreover, the results allow to define both distinct phase- and treatment-dependent associated regulation patterns.
Given the complex task of assessing genetic profiles at multiple conditions and stages from such a heterogeneous tissue, like the cerebral cortex, the experimental setup as well as the subsequent data processing and statistical analysis procedures had to be adjusted to cope with the expected variations. An Excel VBA-based analysis tool and Python-based scripts for automated low-level analysis were developed. Using these tools, based on thresholds for fold-changes and p-values the combined expression patterns calculated from five different analysis algorithms can be visualized and linked with functional information. Especially in the case of expression patterns comprised of multiple timepoints and treatments this method helps in generating a full picture of genetic profiles. The procedures for data analysis and statistical evaluations developed in this thesis have contributed to several publications (Kruse et al., 2008; Barbaria et al., 2009; Heinen et al., 2008; Kury et al., 2004; Kruse et al., 2009; Bosse et al., in preparation).
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