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Maren Depke Results Gene Expression Pattern of Bone-Marrow Derived Macrophages after Interferon-gamma Treatment Fig. R.3.1: Transcriptome data visualization using Principal Component Analysis (PCA). Log-intensity data were used to derive a PCA plot containing 12 arrays (analyzing 3 biological replicates of 2 strains and 2 treatment groups). Resulting principal components were set to cover 95 % of total variation, while the total number of principal components was not limited. The analysis was restricted to noncontrol probe sets that were not absent on all 12 arrays, when absence of expression is defined via a p-value > 0.01 on profile level in Rosetta Resolver. Differences on the axis for principal component 1 are by a factor of approximately 250 smaller than differences on the axis for principal components 2 and 3, which is shown in the small insert that depicts the same PCA but is turned by 90° to the right around the axis of principle component 2. Arrays of BALB/c BMM samples are represented by dots (•), arrays of C57BL/6 BMM samples by rhombi (). IFN-γ treated samples are indicated in gray, and non-treated control level samples are colored in black. As transcriptome data demonstrated a high reproducibility of biological replicates in the model system, selected samples were used for different proteome applications rather than analyzing different biological replicates with only one proteomics approach (Dinh Hoang Dang Khoa). For a general comparison, gelfree proteome analysis and transcriptome analysis are more comparable than 2-DE proteome analysis and transcriptome analysis. Therefore, further data examination focused on that. Overall comparison of transcriptome [Maren Depke] and LC-MS/MS proteome [Dinh Hoang Dang Khoa] analyses 900 of 946 identified proteins from gel-free LC-MS/MS approach could be mapped to the 20074 EntrezGene records that were specified to be represented on the Affymetrix GeneChip Mouse Gene 1.0 ST array by the Rosetta Resolver software (Table R.3.1). As expected, a much bigger number of genes was accessible by transcriptome analysis than proteins by gelfree proteome analysis. Nevertheless, for almost all identified proteins the gene expression pattern could be recorded. Table R.3.1: Overall comparison transcriptome [Maren Depke] and LC-MS/MS proteome [Dinh Hoang Dang Khoa] analyses and numbers of differentially regulated genes and proteins with differing abundance resulting from LC-MS/MS analysis. total number of detected genes or proteins in BALB/c BMM IFN-γ effects a in C57BL/6 BMM at non-treated control level strain differences a at IFN-γ treated level microarray 20074 442 (2.2 %) 396 (2.0 %) 222 (1.1 %) 230 (1.1 %) LC-MS/MS 946 45 (4.8 %) 52 (5.5 %) 218 (23.0 %) 308 (32.6 %) a Percentage values indicate the proportion of regulation in both approaches. Values were calculated by dividing the number of regulated genes by the total number of genes available on the array or the number of regulated proteins by the total number of identified proteins. 92
Maren Depke Results Gene Expression Pattern of Bone-Marrow Derived Macrophages after Interferon-gamma Treatment Surprisingly, the percentage of proteins with significant difference in abundance between BMM of BALB/c and C57BL/6 mice compared to the total of all identified proteins was noticeably higher than the percentage of differentially expressed genes between BMM of BALB/c and C57BL/6 mice compared to the total of all genes available on the array (Table R.3.1). IFN-γ influence on gene expression [Maren Depke] and protein abundances [Dinh Hoang Dang Khoa] in BMM of BALB/c and C57BL/6 mice The comparison of IFN-γ treated BMM with the non-treated medium control revealed that IFN-γ mainly led to induction of gene expression or increase in protein abundance in both strains (Table R.3.2 A). From the total of 442 (BALB/c BMM) and 396 (C57BL/6 BMM) differentially expressed genes, 388 (BALB/c BMM) and 330 (C57BL/6 BMM) were induced, while only 54 (BALB/c BMM) and 66 (C57BL/6 BMM) were repressed. IFN-γ treatment increased the abundance of 41 (BALB/c BMM) and 43 (C57BL/6 BMM) proteins and reduced the abundance of 4 (BALB/c BMM) and 9 (C57BL/6 BMM) from the total of 45 (BALB/c BMM) and 52 (C57BL/6 BMM) regulated proteins. The overlap of the list of proteins that differed significantly in their abundance between IFN-γ treated BMM and the non-treated medium control and the list of differentially expressed genes that were found after IFN-γ treatment amounted to 24 (BALB/c BMM) and 20 (C57BL/6 BMM). Compared to 43 (BALB/c BMM) and 50 (C57BL/6 BMM) regulated proteins also available by transcriptome analysis and 52 (BALB/c BMM) and 53 (C57BL/6 BMM) differentially expressed genes also accessible by LC-MS/MS proteome analysis, the overlap of regulated proteins and genes added up to 38 % to 56 % (Table R.3.2 A). Table R.3.2: Comparison of differentially regulated genes resulting from transcriptome analysis [Maren Depke] with differentially regulated proteins resulting from LC-MS/MS analysis [Dinh Hoang Dang Khoa]. A Direction of regulation by IFN-γ in BALB/c BMM and in C57BL/6 BMM. IFN-γ treatment effects B Direction of strain difference between C57BL/6 BMM and BALB/c BMM at non-treated medium-control and IFN-γ treated level. strain differences LC- a intersection a microarray MS/MS LC- a intersection a microarray MS/MS a BALB/c BMM control condition BMM induced 39 (41) 41 (388) 24 higher in C57BL/6 102 (112) 10 (100) 7 repressed 4 (4) 11 (54) 0 higher in BALB/c 101 (106) 10 (122) 4 total 43 (45) 52 (442) 24 total 203 (218) 20 (222) 12 C57BL/6 BMM treatment condition BMM induced 42 (43) 41 (330) 20 higher in C57BL/6 +IFN-γ 123 (135) 13 (93) 10 repressed 8 (9) 12 (66) 0 higher in BALB/c +IFN-γ 165 (173) 11 (137) 7 total 50 (52) 53 (396) 20 Total 288 (308) 24 (230) 19 The first number in the table always refers to the proteins or genes that were available for analysis with both approaches, microarray and LC-MS/MS analysis. In brackets, the number of regulated proteins or genes without restriction to the accessibility by both methods is given. The comparison of IFN-γ effects in BMM of the two strains BALB/c and C57BL/6 resulted in a high overlap of 307 differentially expressed genes (Fig. R.3.2 A) and 29 proteins with significantly different abundance (Fig. R.3.2 C). Even when the gene or protein was not significantly expressed in one of the strains a similar expression trend in BMM of both strains was observed (Fig. R.3.2 B, D). 93
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G E N O M E W I D E C H A R A C T E
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Maren Depke C O N T E N T S GENOMEW
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Maren Depke Z U S A M M E N F A S S
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Maren Depke Zusammenfassung der Dis
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Maren Depke S U M M A R Y O F D I S
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Maren Depke Summary of Dissertation
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Maren Depke I N T R O D U C T I O N
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Maren Depke Introduction Besides op
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Maren Depke Introduction 2005). SaP
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Maren Depke Introduction STUDIES OF
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Maren Depke M A T E R I A L A N D M
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mean normalized intensity mean norm
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Maren Depke D I S C U S S I O N A N
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Maren Depke Discussion and Conclusi
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Maren Depke References Athanasopoul
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Maren Depke References Byrne GI, Le
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Maren Depke References Demling R. T
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Maren Depke References Foss GS, Pry
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Maren Depke References Hagopian K,
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Maren Depke References Jin T, Bokar
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Maren Depke References Kwan T, Liu
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Maren Depke References Luster AD, U
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Maren Depke References Namiki S, Na
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Maren Depke References Puccetti P.
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Maren Depke References Siewert E, B
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Maren Depke References Yang XL, Sch
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Maren Depke A F F I D A V I T / E R
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Maren Depke Acknowledgments Kidney
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