Common patterns of glomerular gene expression profiles in different murine models of early nephropathy [Elektronische Ressource] / Andreas Falko Blutke

Andreas Falko Blutke

Sujets

• Gesundheit

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2007
• Nombre de lectures: 5
• Langue: English
• Poids de l'ouvrage: 5 Mo

Extrait

From the
Institute of Veterinary Pathology
Chair of General Pathology and Pathological Anatomy

Head: Prof. Dr. W. Hermanns
Ludwig-Maximilians-University, Munich, Germany

and the
Department of Internal Medicine
Division of Nephrology

Head: Prof. Dr. F. Brosius III
University of Michigan, Ann Arbor, United States of America

Under the supervision of
Prof. Dr. R. Wanke and Prof. Dr. M. Kretzler


Common patterns of glomerular gene expression profiles
in different murine models of early nephropathy



Inaugural - Dissertation
to achieve the doctor title of veterinary medicine
at the Faculty of Veterinary Medicine of the
Ludwig-Maximilians-University, Munich



Andreas Falko Blutke
from Stuttgart

Munich 2007

- 1 -


Gedruckt mit Genehmigung der Tierärztlichen Fakultät
der Ludwig-Maximilians-Universität München









Dekan: Univ.-Prof. Dr. Braun

Berichterstatter: Univ.-Prof. Dr. Wanke

Korreferent/en: Univ.-Prof. Dr. Hartmann
Univ.-Prof. Dr. Kaspers
Univ.-Prof. Dr. Müller
Univ.-Prof. Dr. Poulsen-Nautrup











Tag der Promotion: 8. Februar 2008

- 2 -








Meinem Bruder

























- 3 - Table of contents
Page
1. Introduction 1
2. Scientific background 3
2.1 Importance of chronic kidney diseases 3
2.1.2 Common pathological features of chronic kidney diseases 4
2.2 Glomerulosclerosis 5
2.3 Pathogenesis of progressive glomerulosclerosis 7
2.3.1 Glomerular hypertrophy 7
2.3.2 Podocyte function and the importance of podocyte damage for 12
the development of glomerulosclerosis
2.3.3 Proteinuria 16
2.4.1 Animal models of glomerulosclerosis 19
dn2.4.2 GIPR -transgenic mice: a novel mouse model of diabetes 21
mellitus
2.4.3 Growth hormone-transgenic mice 23
2.5.1 Transcript profiling analysis in nephrology 25
2.5.2 Real-time polymerase chain reaction 27
2.5.3 Microarray analysis 29
2.6 Methods of glomerulus isolation 33
3. Research design and methods 36
3.1 Experimental design 38
3.2 Animals 41
3.2.1 Breeding, animal husbandry and numbers of mice used for 41
analyses
3.2.2 Identification of transgenic mice by Polymerase chain reaction 44
3.2.2.1 Primers 44
3.2.2.2 DNA isolation 45
3.2.2.3 Polymerase chain reaction 45
3.2.2.4 Gel electrophoresis 46
3.3 Urine analysis 48
3.3.1 Definition of stages, time points and intervals of investigation 48
dn3.3.2 Detection of glucosuria in GIPR -transgenic mice 50
3.3.3 Urine protein analysis 50
- 4 - 3.3.3.1 Detection of absence or onset of albuminuria (SDS-PAGE) 50
3.3.3.2 Western-blot analysis 53
3.3.3.3 Determination of urine albumin concentrations by Enzyme- 54
Linked Immunosorbent Assay (ELISA)
3.4.1 Generation of sample materials and acquisition of additional 56
data
3.4.2 Kidney perfusion and glomerulus isolation 57
3.4.3 Tissue preparation for histology and electron microscopy 63
3.4.3.1 Plastic histology 63
3.4.3.2 Tissue preparation for transmission electron microscopy 65
3.5.1 Estimation of the mean glomerular volume 67
3.5.2 Estimation of numbers of glomerular cells 68
3.5.3 Determination of the filtration slit frequency 72
3.5.4 Measurement of the true harmonic mean thickness of the 73
glomerular basement membrane
3.6 Microarray analyses of samples of isolated glomeruli 75
3.6.1 Work-flow of microarray analysis 75
3.6.2 RNA preparation 77
3.6.3 Determination of quantity and quality of isolated total RNA by 78
microfluid electrophoresis
3.6.4 Preparation of amplified, biotin-labeled cDNA from total RNA 79
3.6.5.1 DNA microarray experiments 80
3.6.5.2 Quality controls of microarrays and cluster analyses 80
3.7 Statistical analysis of microarray data 81
3.7.1 Nomenclature of “differentially expressed transcripts” and 81
“genes”
3.7.2 Identification of differentially expressed transcripts 82
3.7.3 of commonly differentially expressed genes 84
3.7.3.1 Identification of commonly differentially expressed genes in the 84
single stages of investigation
3.7.3.2 Identificatessed genes in both 85
stages of investigation
3.7.4 Estimation of statistical enrichment of commonly differentially 85
expressed genes by Monte Carlo simulation
- 5 - 3.8 Cluster analyses 86
3.9.1 Confirmation of array data by quantitative real-time PCR 86
3.9.2 Reverse transcription of RNA into cDNA 87
3.9.3 Performance of real-time PCR 87
3.10 Bioinformatical analyses 90
3.11 Statistical analysis and data presentation 90
4. Results 91
4.1 Characterization of nephropathy stages 91
4.1.1 Age of animals 91
4.1.2 Body weight 92
4.1.3 Kidney weight and relative kidney weight 92
4.1.4 Glomerular histology 94
4.1.5 Morphometric analysis and quantitative stereology 95
4.1.5.1 Mean glomerular volume 95
4.1.5.2 Numerical density of glomerular cells 97
4.1.5.3 Number of cells per glomerulus 98
4.1.5.4 Filtration slit frequency 99
4.1.5.5 Thickness of the glomerular basement membrane 99
4.1.6 Results of urine analyses 100
dn4.1.6.1 Detection of glucosuria in GIPR -transgenic mice 100
4.1.6.2 Urine creatinine concentrations 100
4.1.6.3 Urinary protein excretion patterns (SDS-PAGE) 101
4.1.4.4 Western blot analysis 104
4.1.4.5 Quantification of urine albumin concentrations by ELISA 104
4.2 Magnetic large scale isolation of kidney glomeruli 105
4.2.1 Pilot experiments 105
4.2.2 Quantity and purity of generated glomerulus isolates 107
4.3 Results of transcript profiling analyses 109
4.3.1.1 Quantities and quality of total glomerular RNA 109
4.3.1.2 Quality of target cDNA 109
4.3.2.1 Control of quality and comparability of microarray data 110
4.3.2.2 Cluster analysis of normalized microarray data 111
4.3.3.1 Identification of differentially expressed genes in the specific 113
groups and stages of investigation
- 6 - 4.3.3.2 Commonly differentially expressed genes in stage I 114
4.3.3.3 y expressed genes in stage II 114
4.3.3.4 Commonly differentially expressed genes in both stages of 115
investigation
4.3.4 Estimation of statistical enrichment of commonly differentially 117
expressed genes by Monte Carlo simulation
4.3.5 Cluster analyses of common expression profiles 118
4.3.6 Confirmation of array data by real time polymerase chain 120
reaction
4.3.7 Bioinformatical analysis 124
4.3.7.1 Molecular functions of gene products of commonly differentially
expressed genes in the single stages of investigation
4.3.7.2 Molecular functions and subcellular distributions of gene 126
products of commonly differentially expressed genes in all
investigated stages and groups
4.3.7.3 Identification of known interactions of single gene products 127
corresponding to commonly differentially expressed genes in all
groups and stages of investigation
128 5. Discussion
5.1 General aspects 128
5.2 Experimental design 129
5.3 Quality of glomerulus isolates 131
5.4 Morphological and functional investigations 133
5.4.1 Histology 133
5.4.2 Glomerular hypertrophy and numbers of cells per glomerulus 133
5.4.3 Thickness of the glomerular basement membrane 136
5.4.4 Filtration slit frequency 137
5.4.5 Urine analyses 138
5.4.6 Ages of animals and further parameters 141
5.5 Transcript profiling analyses 142
5.5.1 Microarray analyses: Patterns of glomerular gene expression 142
5.5.2 Microarray analyses: Differential glomerular gene expression 144
profiles

- 7 - 5.5.3 Microarray analyses: Common differential gene expression 145
profiles
5.5.4 Confirmation of array data by real-time PCR 146
5.5.5 Relative depletion of podocytic RNA in samles of hypertrophied 147
glomeruli: A potential pitfall of interpretation of glomerular gene
expression profiles
5.6.1 Bioinformatical analyses 149
5.6.2 Commonly differentially expressed genes involved in lipid 150
metabolism
5.6.3 Commonly differentially expressed genes involved in oxidative 154
stress
5.6.4 Commonly differentially expressed genes involved in cytokine 156
and chemokine signaling pathways
5.6.5 Commonly differentially expressed genes involved in 159
extracellular matrix turnover
5.6.6 Commonly differentially expressed genes involved in mediation 160
of cell-matrix contacts
5.6.7 olved in 164
cytoskeletal functions
5.6.8 d g