Target Discovery and Validation Reviews and Protocols

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13 A Murine Model for Studying Hematopoiesis and Immunity in Heart Failure Per Ole Iversen and Dag R. Sørensen Summary Recent epidemiological research indicates that a coexistent anemia among patients with heart failure might worsen their prognosis. However, whether the reduced synthesis of red blood cells is a contributing factor to the development and progression to overt heart failure, or whether it simply is a mere consequence of a dysfunctional heart, remains to be elucidated. Studies in mice with experimentally induced acute myocardial infarction leading to subsequent development of a postinfarction congestive heart failure have shed some light on this problem. Careful analyses of the number and of the functions of various hematopoietic cells residing in either blood or bone marrow point to a possible inhibitory role of cytokines, such tumor necrosis factor α, on hematopoiesis. The present protocols will hopefully encourage further studies of hematopoiesis and immunity in heart failure by using a combination of animal models with state-of-the-art techniques in molecular biology to define and validate possible targets for therapy. Key Words: Cytokines; heart failure; hematopoiesis; mouse; myocardial infarction. 1. Introduction Heart failure has for a long time remained one of the most common cardiovascular disorders encountered in various Western populations (1,2). With the growing numbers of obese-related pathological conditions, heart failure also is expected to rise in developing countries in the years to come. The associated disease-burden amounts to considerable resources used in terms of money and health care. In recent years, several important advances have been made in terms of pharmacology, including both new drugs (e.g., angiotensin II receptor blockers) as well as altered dosages of established drugs (e.g., beta-blockers). We also have From: Methods in Molecular Biology, vol. 360, Target Discovery and Validation Reviews and Protocols Volume I, Emerging Strategies for Targets and Biomarker Discovery Edited by: M. Sioud © Humana Press Inc., Totowa, NJ 269
270 Iversen and Sørensen witnessed important new contributions in terms of revascularization regimens, e.g., coronary artery bypass surgery and angioplasty. However, in spite of these advances, the prognosis of the heart failure patient remains dismal with high morbidity and mortality (3). Although the heart failure syndrome is generally characterized primarily as a hemodynamic disorder with impaired left ventricular function as the main hallmark, we are still short of a comprehensive understanding of the pathology of this debilitating disorder. Refinement of tools for measuring minute concentrations of biologically active molecules as well as the advent of genetically altered mice has changed our view of heart failure as a mere circulating disorder to that of a possible inflammatory condition. In line with this changed view, several cytokines seem to play important roles in the pathogenesis of heart failure, at least in experimental models. Hence, in particular, the proinflammatory cytokine tumor necrosis factor (TNF)α, and also the interleukins (IL)-1β and -18, seem to exert cardiodepressive effects in various in vitro and in vivo settings (4–6). Paralleling this development is the recognition that patients with heart failure also suffer from conditions related to an impairment of bone marrow function, in particular, hematopoiesis. Although not well documented in the past, it has been a clinical experience that the hemoglobin concentrations of these patients usually are somewhat reduced. Based on autopsies, Bohm (7) concluded that a gelatin transformation of the bone marrow was more frequent among patients deceased from heart failure. Later, epidemiological studies concluded that anemia significantly predicted a worsened outcome among heart failure patients who were anemic compared with those with normal hemoglobin levels (8,9). The crucial question is whether the anemia has a true negative impact on the development and progression to overt heart failure or whether it simply is a result of a deteriorating bone marrow function because of the failing heart (10). Although wild mice and rats can survive almost any climatic condition, their laboratory relatives have lost the genetic background for this adaptability. When animals are bred for experimental use, one major concern is to produce individuals or populations with a minimum genetic variance, which makes the animals sensible to even small changes in the environment that may influence the outcome of the experiments. Examples of factors that may influence on the experimental results are physical parameters, such as temperature, humidity, light cycle, and chemical factors (see Notes 1–4), and also social factors, such as human contact, cage design, and animal interactions. Control of the most important of these factors may reduce “the background noise” in animal experiments and make it possible to obtain statistically significant results with a limited number of animals.
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METHODS IN MOLECULAR BIOLOGY 360 T
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M E T H O D S I N M O L E C U L A R
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© 2007 Humana Press Inc. 999 River
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vi Preface get. Approaches to targe
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viii Contents 10 Transgenic Animal
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x Contributors SAHOHIME MATSUMOTO
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xii Contents of Volume 2 12 Validat
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2 Sioud disease pathogenesis and pe
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4 Sioud A more fruitful approach fo
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6 Sioud both transient and permanen
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8 Sioud serum biomarkers. This syne
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10 Sioud Fig. 2. Schematic of targe
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12 Sioud 13. Magin, T. M. (1998) Le
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Harnessing the Human Genome 15 The
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Harnessing the Human Genome 17 Fig.
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Harnessing the Human Genome 23 The
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Harnessing the Human Genome 27 repr
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Harnessing the Human Genome 29 14.
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Harnessing the Human Genome 31 45.
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34 Imoto et al. (4,5), and Bayesian
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36 Imoto et al. 2. Materials Two ty
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38 Imoto et al. Fig. 3. Graphical v
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40 Imoto et al. Fig. 5. Result of t
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42 Imoto et al. p(D |G) = ∫ p(D,
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44 Imoto et al. β k (k = 1,…,q j
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46 Imoto et al. Fig. 7. Partial res
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48 Imoto et al. Fig. 8. Strategy to
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50 Imoto et al. Fig. 9. (continued)
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52 Imoto et al. Table 3 List of Roo
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54 Imoto et al. 5. De Hoon, M. J. L
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56 Imoto et al. 39. Kamimura, T., S
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58 Beaty et al. cytotoxic drugs and
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60 Beaty et al. Fig. 1. Principles
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62 Beaty et al. oligonucleotide mic
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64 Beaty et al. 3. The 12% polyacry
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66 Beaty et al. 2.3.3. Protein Stai
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68 Beaty et al. 3.1.3. Labeling of
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70 Beaty et al. 1 µL of the anneal
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72 Beaty et al. 4. Phenol:cholorfor
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74 Beaty et al. 19. Wash twice with
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76 Beaty et al. The Following Volum
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78 Beaty et al. using a protein ass
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80 Beaty et al. 6. Shake the gel fo
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82 Beaty et al. Fig. 2. Preparation
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84 Beaty et al. search in. A widely
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86 Beaty et al. 3. Kern, S. E., Hru
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88 Beaty et al. 34. Peters, D. G.,
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5 Molecular Classification of Breas
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Molecular Profiling of Breast Cance
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Fig. 2. (Continued) the right ident
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6 Discovery of Differentially Expre
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Gene Target Discovery 117 In the fi
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Gene Target Discovery 119 sequences
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Gene Target Discovery 121 There is
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Gene Target Discovery 123 digestion
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Gene Target Discovery 125 Fig. 1. P
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Gene Target Discovery 127 5. Sargen
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Gene Target Discovery 129 41. Berry
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132 Matsumoto, Miyagishi, and Taira
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144 Fig. 1. The ribozyme-expression
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146 Sano and Taira 5. 10X L (low-sa
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148 Sano and Taira ribozymes may cl
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150 Fig. 3. A system for the identi
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152 Sano and Taira 4. Notes 1. We r
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9 Production of siRNA- and cDNA-Tra
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Transfected Cell Arrays 157 Fig. 1.
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Transfected Cell Arrays 159 2. The
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Transfected Cell Arrays 161 5. Simp
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164 Houdebine Fig. 1. Different met
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166 Houdebine concentrations become
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168 Houdebine Fig. 2. Major methods
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170 Houdebine integrate into the me
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172 Houdebine 2.2.3. Knock-In Into
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174 Houdebine as insulators. The co
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176 Houdebine Fig. 5. Different met
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178 Houdebine systems. Moreover, st
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180 Houdebine contribute to generat
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184 Houdebine more extensively. Tra
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186 Houdebine and stroma. Several o
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188 Houdebine explained at the mole
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190 Houdebine of the intestinal epi
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192 Houdebine interference of the g
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194 Houdebine 17. Whitelaw, C. B. A
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196 Houdebine 51. Bell, A. C., West
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198 Houdebine 86. Carmichael, G. G.
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200 Houdebine 121. Pailhoux, E., Vi
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202 Houdebine 156. Auerbach, A. B.,
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204 Vijayaraj, Söhl, and Magin 1.
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206 Vijayaraj, Söhl, and Magin Fig
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208 Vijayaraj, Söhl, and Magin fil
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210 Table 1 Orthologous Human and M
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212 Table 2 Orthologous Human and M
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214 Vijayaraj, Söhl, and Magin ulc
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15 Potential Target Antigens for Im
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Tumor Antigen Discovery 321 develop
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Tumor Antigen Discovery 323 panel b
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Tumor Antigen Discovery 325 16. Joc
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16 Identification of Tumor Antigens
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Immunoproteomics 329 by “shot gun
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Immunoproteomics 331 isoelectric fo
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Immunoproteomics 333 3. 2D-PAGE is
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17 Protein Arrays A Versatile Toolb
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Protein Arrays 337 Table 1 Classifi
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Protein Arrays 339 fractions from c
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Protein Arrays 341 combinatorial sc
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Protein Arrays 343 The ideal proteo
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Protein Arrays 345 18. Cekaite, H.
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Protein Arrays 347 49. Yuko Kawahas
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Index 349 Index A Acetyl-CoA carbox
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Index 351 conditional by using FRT
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Index 353 Recombinant tumor antigen
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