Proteomic and gene profiling approaches to study host responses to bacterial infection Anna Walduck, Thomas Rudel and Thomas F Meyer Infectious disease is the result of an intimate relationship between the pathogen and host, which involves cross-talk. After an initial flood of mainly descriptive reports on the influence of acute bacterial infection on cells, transcriptome and proteome studies are now becoming more refined in their approach, and are shedding light on the role of pathogen-specific mechanisms/ structures in pathogenesis. In addition, studies of gene expression in vivo have shed new light on how the host influences the niche occupied by bacteria. Elegant refinements to proteomics using beads coated with bacterial invasins, or purifying subcellular fractions are producing a picture of invasion specific processes. Such approaches combined with modern functional genomics technologies such as RNAi represent the next phase in understanding host–bacteria interactions. Addresses Max-Planck-Institute for Infection Biology, Department of Molecular Biology, Schumannstrasse 21/22, 10117 Berlin, Germany Corresponding author: Thomas Meyer e-mail:
[email protected]
Current Opinion in Microbiology 2004, 7:33–38 This review comes from a themed issue on Host–microbe interactions: bacteria Edited by Craig Roy and Philippe Sansonetti 1369-5274/$ – see front matter ß 2003 Elsevier Ltd. All rights reserved. DOI 10.1016/j.mib.2003.12.010
Abbreviations 2-DE two-dimensional gel electrophoresis CPAF chlamydial protease-like activity factor PAI pathogenicity island RNAi RNA interference siRNA small interfering RNA UPEC uropathogenic E. coli
Introduction Infectious disease is the result of an intimate relationship between the pathogen and host. Understanding this complex cross-talk between host and pathogen is essential to improve our understanding of infectious disease. Genome sequencing projects and the advent of global approaches such as proteomics and transcriptional profiling have opened up exciting new possibilities and led to the creation of a new field of biology — functional genomics. In this review, we focus on the most significant recent reports that use transcriptome or proteomics approaches to investigate the host response to infection with bacterial www.sciencedirect.com
pathogens. Finally, we discuss the applications of RNAi technology, which we believe will be a key technique in the functional analysis for genes that are identified from the current transcriptome and proteomics studies.
In vitro host cell transcriptome studies In recent years there have been numerous reports of analyses of the host cell transcriptome after infection with bacteria. Most of these studies have been performed in in vitro infection models and provided the first insights into the complexity of acute host–bacterial interactions. Transcriptional responses to ‘extracellular’ pathogens
The genome of Helicobacter pylori was one of the first to be used for microarray studies. Soon after, the host response to this pathogen was also investigated, and several groups have described the acute reaction to infection in gastric carcinoma cell lines [1–4]; particular interest has been given to the role of the Cag pathogenicity island (Cag PAI) as Cag PAI positive H. pylori strains have been positively associated with gastric carcinoma development. Interestingly, two of these studies showed that H. pylori strains lacking the Cag PAI indeed stimulated a different gene expression pattern in gastric epithelial cells. Recently, a more defined approach was taken and Guillemin and co-authors [5] investigated the contribution of the various genes that make up the PAI to changes in the host cell. The type IV secretion system structural component CagE was found to be required for much of the host transcriptional response to H. pylori. The effector protein CagA influenced cell shape regulators and caused upregulation of genes encoding cell junction proteins. It should be noted that this study did not include wild-type PAI-deficient strains and it is possible that such strains have additional alterations to the genome which have more complex effects on gene expression. In a different approach, Yoshida et al. [6] found that a water extract of H. pylori also induced an inflammatory expression pattern in gastric epithelial cells (MKN45), which is in keeping with observations that secreted factors also have stimulatory effects on the epithelium and that direct contact via the type IV secretion system is not the only contributing factor in H. pylori inflammatory disease. A similar approach to that of the H. pylori PAI investigations was taken by Sauvonnet et al. [7] to dissect the role of components of the Yersinia enterocolitica Yop virulon during infection of mouse macrophages. The Yop virulon has the function of allowing the bacteria to resist the host cell pro-inflammatory response. YopP participates in this inhibition, whereas YopM induces the regulation of genes Current Opinion in Microbiology 2004, 7:33–38
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for cell cycle and growth. This type of approach is providing more information on pathogen-specific virulence mechanisms. Transcriptional responses to intracellular pathogens
Intracellular pathogens must interact intimately with their host cell and even use host proteins, it is therefore to be expected that the transcriptional response to an invasive process will differ from that of an ‘external’ pathogen such as H. pylori. The host cell response to Chlamydiae has been investigated in a variety of cell types (Hep2 cells [8], human monocytic leukemia cells [9] and HeLa [10]). Host cell signaling pathways were activated as early as 5 min after infection [11] and this progressed to induction of pro-inflammatory factors and apoptosis inhibiting factors. Factors regulating cell differentiation were regulated at later time-points. A comparison of the transcriptional response to Chlamydia trachomatis and Coxiella burnetii revealed a high degree of overlap in gene expression, although pathogen-specific responses were also detected [9]. This study raises the question as to which transcriptional responses are the non-specific response to a general ‘insult’, and which responses are pathogen specific. To date, the only published study that attempts to address this question also involves Chlamydiae. Hess and colleagues [12] made a comparative analysis of the transcriptional response to C. pneumoniae and C. trachomatis infection in HeLa cells. Viable Chlamydia induced the expression of hundreds of host-cell genes, the majority of which after 12–24 h post infection. The transcriptional response induced by C. pneumoniae and C. trachomatis was similar, the differences in expression being mainly quantitative. In addition, UVinactivated Chlamydia induced minimal or no differential gene expression, indicating that mechanisms other than innate immunity are required. In a further comparison with another intracellular pathogen, RT-PCR analysis of a subset of Chlamydia-induced genes showed that Salmonella typhimurium induced a substantially different expression pattern in HeLa cells. A similar approach was also taken by Ren et al. [9] and transcriptional responses to C. trachomatis and C. burnetii were compared, as before numerous pathogen-specific responses were observed. These pathogen-specific response patterns are a first step to explain the differences in clinical manifestations of disease induced by different organisms. Mycobacterium tuberculosis can infect a variety of cell types and establishes a persistent infection. To date, two studies have investigated the response of macrophages to infection and described a profile expression of chemokines and pro-inflammatory mediators [13,14]. The latter study was a combined transcriptomic and proteomic approach. The transcriptional profile of chemokine, cytokine and cell migratory factors was considerably more difficult to detect using the proteomics approach. Danelishvilli et al. [15] compared M. tuberculosis infection Current Opinion in Microbiology 2004, 7:33–38
in human macrophages and alveolar epithelial cells focusing on the induction of apoptosis and necrosis in these cells. Using an apoptosis-pathway-specific array, apoptosis inhibitors were found to be upregulated, and pro– apoptotic genes were downregulated in alveolar epithelial cells. However, the opposite was true for macrophages. The authors suggest that this differential induction probably represents different strategies for survival by M. tuberculosis in the host. Neisseria gonorrhoeae infection also induced expression of anti-apoptotic regulators in HPV E6/E7 transformed human urethral epithelial cells [16], which might represent a mechanism that the gonococcus employs to survive and proliferate in the host epithelium. RT-PCR analysis of these regulators (bfl-1, cox-2 and c-IAP-2) revealed that these genes were not increased in Chang cells infected with N. gonorrhoeae, suggesting that the transcriptional response is strongly influenced by the experimental model system.
Host cell transcriptome studies in in vivo models In vitro infection models have the obvious limitation that cells in isolation are not receiving signals from cells of different lineage types, furthermore most cell lines used for the above studies were transformed, and these cells may in any case exhibit abnormal or biased transcriptional responses. In the past two years, some groups have addressed this problem and reports of the host transcriptome after infection in vivo are appearing. Again infection with Helicobacter sp., particularly H. pylori has been a focus of attention. Mueller et al., [17] reported expression profiles from BALB/c mice infected with H. heilmannii for 12–24 months, and which developed mucosa-associated lymphoid tissue (MALT) lymphoma. Two important conclusions can be drawn from this: the major changes in gene regulation occur in the earlier stages of the disease (mild to moderate pathology), and clustering of the 300 most differentially expressed genes allow segregation of infected mice into groups that corresponded almost exactly with their pathological characterization. Late stage disease was marked by the expression of a single gene, calgranulin 8 (Mrp8). H. heilmannii caused more severe pathology in BALB/c mice and was therefore chosen by authors for long-term studies. Although H. heilmannii infection is associated with gastritis and MALT lymphoma in humans, little is known about the activity of key pathogenicity factors such as the vaculolating antigen (Vac A) gene in this species, and it remains to be shown how closely the mouse H. heilmannii model represents human H. pylori induced disease. Gene expression patterns also correlated with pathology status in a study using material from patients with H. pylori-induced gastric disease. Boussioutas et al. [18] www.sciencedirect.com
Proteomic and gene profiling approaches to study host responses to bacterial infection Walduck, Rudel and Meyer 35
investigated patterns of gene expression in biopsy material from tumor and adjacent mucosa samples from patients with diffuse, intestinal or mixed gastric cancer. The gene expression signatures related well to the disease status and identification of these molecular signatures could be used in future to predict disease outcome.
the quantification of gene expression in a global manner, quantitative and qualitative differences of a given protein can be monitored in different situations using proteome techniques. Proteomics therefore offers a perfect complement to transcriptome studies, although the complexity that results from often numerous splice variants of the same gene presents considerable technical challenges.
Studying the host response in vivo
The response of a complex tissue such as the gastric epithelium to infection is the result of combined efforts of numerous cells types. A drawback of studying the host response in vivo is that the response of a less common, but significant cell type might ‘drown’ in the more prominent response of others. Elegant studies by Mills et al. [19] and Syder et al. [20] have attempted this in an in vivo setting and were able to show that the gene expression profile in parietal cells (PC) isolated from mice remained relatively constant after H. pylori infection, whereas the PC-cell fraction demonstrated a developing host inflammatory response. A further study using transgenic mice that lack parietal cells revealed not only that the niche occupied by H. pylori is influenced by the presence of parietal cells, but that the gene expression signature in lymphoid aggregates which formed in infected mice lacking parietal cells differed from those in normal mice. This result suggests an important role for parietal cells in controlling the positioning of H. pylori in the gastric environment and also in pathogenesis. The general question in cellular microbiology as to whether the requirement of binding of a pathogen to its target cell leads to more intense signaling and therefore a more robust response has been approached in a study of uropathogenic E. coli (UPEC) which attach to superficial urethral epithelial cells via the FimH adhesin [21]. Mysorekar et al. [21] investigated patterns of gene expression in inflammation and renewal of the bladder epithelium of female mice infected with UPEC. Infection with FimHþ UPEC caused a dramatic change in gene expression in the epithelium, which manifested in an early and late phase, whereas the non-binding isogenic FimH strain induced only minor changes in gene expression. The host phenotype plays a critical role in the outcome of an infection. Huang and Hazlett [22] investigated gene expression in the murine cornea after infection with Pseudomonas aeruginosa and were able to identify gene signatures that are responsible for the susceptible (cornea perforates) or resistant (cornea heals) disease observed in C57 BL/6 or BALB/c mice respectively. Gene expression profiles related directly to the T helper (Th1 and Th2) bias observed in these mouse strains.
Host cell proteomic studies Proteome approaches have been widely used in many different systems to investigate host–microbe interactions. In contrast to transcriptome analyses, which allow www.sciencedirect.com
Few of the proteome studies have analyzed protein modifications induced by bacterial pathogens in the host cell. This might be due to the high complexity of host cells and the relatively low sensitivity and resolution of common proteome techniques. A way to overcome these limitations is the enrichment of cellular compartments, which are important for infection. The isolation and analysis of phagosomes containing bacteria has been used to define the modification of the host vesicular trafficking by the pathogen [23,24]. However, pathogens engage different pathways to enter host cells and this might influence the way phagosomes are modulated. An elegant way to study modulation of entry-specific vesicular trafficking is the use of latex beads coated with bacterial adhesins or invasins. In the case of Listeria monocytogenes, invasion is mediated by proteins InlA and InlB that engage the cellular receptors E-cadherin and c-Met, respectively. 2-DE of isolated phagosomes containing latex beads coated either with InlA or InlB revealed different patterns, suggesting that beads entered either via E-cadherin or c-Met and are sorted differently [25]. One protein specifically sorted to InlB phagosomes was the GTPase MSF (MLL septin-like fusion), a factor probably involved in internalization of L. monocytogenes into host cells [25]. Metabolic labeling and simultaneous suppression of host cell protein synthesis is a common approach to study the modification of bacterial proteins during infection of host cells [14,26,27]. In the case of C. pneumoniae, differences in the expression and modification of proteins of actively growing bacteria versus bacteria induced by INF-g treatment to persist in the host cell was investigated in vitro [26]. Unexpectedly, persistent bacteria upregulated rather than downregulated proteins involved in diverse functions, suggesting that persistency is an active stage rather than a dormant stage. An additional method to investigate host–pathogen interaction by proteomics is the definition of so-called ‘immune proteomes’ covering the proteins recognized by patient sera [28,29]. In general, patient sera are used for 2-DE immunoblots and the proteins recognized are identified by mass spectrometry from the corresponding protein gel. The use of immunoblots for screening patient sera may be a limitation of this approach because important antigens might not be recognized owing to the denaturing conditions used. Nevertheless, this approach has the potential to be used for the identification of new vaccine candidates. Current Opinion in Microbiology 2004, 7:33–38
36 Host–microbe interactions: bacteria
Moreover, as sera from gastritis and ulcer patients recognize characteristic sets of proteins immunoproteomics could become a powerful tool for diagnosis [28]. Effect of secreted bacterial products on the host response
Many bacterial pathogens secret proteins either into the culture supernatant from where they interact with the host cell or directly into the host cell. Secreted proteins play a dominant role as immunogens and in pathogenesis. Numerous novel secreted proteins have been identified by analyzing culture supernatants of Pseudomonas aeruginosa, Staphylococcus aureus and H. pylori by 2-DE and mass spectrometry [27,30,31–33]. Secreted proteins of the obligate intracellular bacterium C. pneumoniae were screened by comparing bacterial proteins present in infected cells but absent in isolated bacteria. Using this approach, Shaw et al. [34] identified the secreted ‘chla-
mydial protease-like activity factor’ (CPAF). H. pylori, besides secreting other proteins into the culture supernatant, uses a type IV secretion apparatus to directly inject the CagA protein into host cells. Proteome approaches have been successfully employed to investigate the processing and phosphorylation of the CagA protein secreted into host cells [35,36].
Functional genomics analysis of the host–microbe interaction Global approaches have led to the identification of novel genes involved in host–bacterial interactions, and in the post genomic era the challenge faced by biologists is to characterize these genes and their functions. Highthroughput approaches have been developed to complement more traditional approaches and for further information on these technologies the reader is referred in particular to recent publications on tools for functional
Table 1 Web links: sites of interest for functional genomics in infection biology. Name
Link
Comments
Eurit
https://www.rzpd.de/eurit/
H. pylori protein – protein interaction map.
http://pim.hybrigenics.com/pimrider/ pimriderlobby/PimRiderLobby.jsp
ENU mutagenesis program ‘immunology screen’
http://www.mikrobio.med. tu-muenchen.de/forschung/enu.html also http://www.gsf.de/ ieg/groups/enu/enu_cpt.html http://www.gsf.de/ieg/gmc/
RNA interference (RNAi) technology has a growing impact on functional genomics. The RNAi platform EURIT aims to foster European RNAi technology and focuses on the generation and dissemination of functional RNAi inhibitors for mammalian systems for specific knock-down of gene expression. A high-throughput strategy of the yeast two-hybrid assay to screen 261 H. pylori proteins against a highly complex library of genome-encoded polypeptides resulted in identification of over 1,200 interactions between H. pylori proteins. This project links to the mouse ENU project which as a part of the human genome project aims to create mutant mouse strains that will be models of human disease. The immunology screen aims to characterize these models by studying immunological responses to bacterial infection. Selected mouse mutants will be extensively genetically characterized to identify the genetic mutation(s) responsible for the immunological phenotype.
Web resource on gene expression and microarray technologies Functional genomics
http://industry.ebi.ac.uk/alan/ MicroArray/ http://www.functionalgenomics. org.uk/
Science functional genomics resources
http://www.sciencemag.org/ feature/plus/sfg/education/
Genomes to Life
http://www.ornl.gov/ TechResources/Human_Genome/
The Welcome Trust Sanger Institute
http://www.sanger.ac.uk/genetics/
Standford microarray database
http://genome-www5.stanford.edu/
MPI- Infection Biology Berlin 2D-PAGE database
http://www.mpiib-berlin. mpg.de/2D-PAGE/
Current Opinion in Microbiology 2004, 7:33–38
The website of the European Science Foundation Programme on Integrated Approaches for Functional Genomics. Links to genomics resources on the web. A collection of links to functional genomics resources on the web. The genomics glossaries are a good way to stay on top of the terminology in this field. Website of the US department of energy office of science. Information on the human genome project and links to microbial genome projects. In addition, links to information regarding functional genomics. A comprehensive set of links to genomic resources and databases on the web, including a link to the Human Epigenome Consortium, a public/private collaboration that aims to identify and catalog methylation variable positions (MVPs) in the human genome SMD stores raw and normalized data from microarray experiments, as well as their corresponding image files. In addition, links to software and analysis tools are available This database provides the opportunity to retrieve descriptive information interactively by mouse clicking on a protein spot within a 2-DE gel image or to retrieve the position of a protein when its protein name or search expression is given.
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Proteomic and gene profiling approaches to study host responses to bacterial infection Walduck, Rudel and Meyer 37
genomics including the application of protein arrays [37], large scale screens for interaction partners such as the yeast two-hybrid system [38], an ambitious program for screening mouse mutants for in vivo response to bacterial infection (‘immunology screen’, see Table 1) and RNA interference (RNAi) [39]. The potential of RNAi technology for functional analysis in infection biology is detailed below.
2.
Chiou CC, Chan CC, Sheu DL, Chen KT, Li YS, Chan EC: Helicobacter pylori infection induced alteration of gene expression in human gastric cells. Gut 2001, 48:598-604.
3.
Cox JM, Clayton CL, Tomita T, Wallace DM, Robinson PA, Crabtree JE: cDNA array analysis of cag pathogenicity islandassociated Helicobacter pylori epithelial cell response genes. Infect Immun 2001, 69:6970-6980.
4.
Nagasako T, Sugiyama T, Mizushima T, Miura Y, Kato M, Asaka M: Up-regulated smad5 mediates apoptosis of gastric epithelial cells induced by Helicobacter pylori infection. J Biol Chem 2003, 278:4821-4825.
Use of RNAi to study host–bacterial interactions
5.
Guillemin K, Salama NR, Tompkins LS, Falkow S: Cag pathogenicity island-specific responses of gastric epithelial cells to Helicobacter pylori infection. Proc Natl Acad Sci USA 2002, 99:15136-15141.
6.
Yoshida N, Ishikawa T, Ichiishi E, Yoshida Y, Hanashiro K, Kuchide M, Uchiyama K, Kokura S, Ichikawa H, Naito Y et al.: The effect of rebamipide on Helicobacter pylori extractmediated changes of gene expression in gastric epithelial cells. Aliment Pharmacol Ther 2003, 18(Suppl 1):63-75.
7.
Sauvonnet N, Pradet-Balade B, Garcia-Sanz JA, Cornelis GR: Regulation of mRNA expression in macrophages after Yersinia enterocolitica infection. Role of different Yop effectors. J Biol Chem 2002, 277:25133-25142.
8.
Mahony JB: Chlamydiae host–cell interactions revealed using DNA microarrays. Ann NY Acad Sci 2002, 975:192-201.
9.
Ren Q, Robertson SJ, Howe D, Barrows LF, Heinzen RA: Comparative DNA microarray analysis of host cell transcriptional responses to infection by Coxiella burnetii or Chlamydia trachomatis. Ann NY Acad Sci 2003, 990:701-713.
To date, almost all published RNAi studies in infectious disease performed in mammalian cells have involved viral infections [39,40]; the RNAi technique is also well suited to study the influence of bacteria on mammalian cells. After initial identification of a target gene using a microarray approach, Nagasako and colleagues [4] used RNAi to confirm the crucial role of Smad5 in H. pylori-induced apoptosis in gastric epithelial cells. Bacteria do not possess the correct machinery for the RNAi effect, therefore, small interfering RNA (siRNA) specifically inhibit only host gene products, which are regulated in response to infection. This, and its applicability to high-throughput methods make RNAi technology ideal to investigate bacterial pathogenesis and potential targets for therapy in the host cell. Furthermore, functional RNAi has also been reported in vivo in adult mice [41,42,43]. Most relevant to the study of host–bacteria interactions were results from the latter study where a delay in the onset of lipopolysaccharide-induced sepsis by administration of siRNA that inhibited tumor necrosis factor (TNF)-a was reported [43]. Such studies have laid the foundation for a new era of functional analysis.
Conclusions After an initial flood of mostly descriptive studies of acute host–bacteria interactions in vitro, transcriptome and proteome studies are now becoming more refined in their approach. The effect of pathogen-specific virulence mechanisms can now be dissected using bacterial mutants [5,7] and comparing different species [11,12]. Furthermore, cell fractionation approaches in proteomics have provided a clearer picture of invasion — one of the critical phases in intracellular bacterial pathogenesis. In vivo studies are still in their infancy but promising results are already appearing, particularly in the area of diagnostics [18]. For the future, carefully designed studies followed by functional genomics approaches such as RNAi will be required to further dissect the mechanisms of pathogenesis.
References and recommended reading Papers of particular interest, published within the annual period of review, have been highlighted as: of special interest of outstanding interest 1.
Bach S, Makristathis A, Rotter M, Hirschl AM: Gene expression profiling in AGS cells stimulated with Helicobacter pylori isogenic strains (cagA positive or cagA negative). Infect Immun 2002, 70:988-992.
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10. Xia M, Bumgarner RE, Lampe MF, Stamm WE: Chlamydia trachomatis infection alters host cell transcription in diverse cellular pathways. J Infect Dis 2003, 187:424-434. Despite its intravacuolar location, C. trachomatis altered transcription of a broad range of host genes and expression patterns in the early and late phases of the infection cycle were distinct. 11. Mahony JB: Chlamydiae host–cell interactions revealed using DNA microarrays. Ann NY Acad Sci 2002, 975:192-201. 12. Hess S, Peters J, Bartling G, Rheinheimer C, Hegde P, Magid-Slav M, Tal-Singer R, Klos A: More than just innate immunity: comparative analysis of Chlamydophila pneumoniae and Chlamydia trachomatis effects on host-cell gene regulation. Cell Microbiol 2003, 5:785-795. 13. Ehrt S, Schnappinger D, Bekiranov S, Drenkow J, Shi S, Gingeras TR, Gaasterland T, Schoolnik G, Nathan C: Reprogramming of the macrophage transcriptome in response to interferon-gamma and Mycobacterium tuberculosis: signaling roles of nitric oxide synthase-2 and phagocyte oxidase. J Exp Med 2001, 194:1123-1140. 14. Ragno S, Romano M, Howell S, Pappin DJ, Jenner PJ, Colston MJ: Changes in gene expression in macrophages infected with Mycobacterium tuberculosis: a combined transcriptomic and proteomic approach. Immunology 2001, 104:99-108. 15. Danelishvilli L, McGarvey J, Li YJ, Bermudez LE: Mycobacterium tuberculosis infection causes different levels of apoptosis and necrosis in human macrophages and alveolar epithelial cells. Cell Microbiol 2003, 5:649-660. 16. Binnicker MJ, Williams RD, Apicella MA: Infection of human urethral epithelium with Neisseria gonorrhoeae elicits an upregulation of host anti-apoptotic factors and protects cells from staurosporine-induced apoptosis. Cell Microbiol 2003, 5:549-560. 17. Mueller A, O’Rourke J, Grimm J, Guillemin K, Dixon MF, Lee A, Falkow S: Distinct gene expression profiles characterize the histopathological stages of disease in Helicobacter-induced mucosa-associated lymphoid tissue lymphoma. Proc Natl Acad Sci USA 2003, 100:1292-1297. This paper describes the progression of gene expression in a long-term infection model where mice infected with H. heilmannii developed mucosa-associated lymphoid tissue (MALT) disease. In addition, further microarray analysis of microdissected tissue from either lymphocyte Current Opinion in Microbiology 2004, 7:33–38
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aggregates or epithelial cells allowed the cellular source of gene expression to be identified. Calgranulin A was the only gene that marked the transition to severe pathology and lymphoma was found to be expressed in both fractions. 18. Boussioutas A, Li H, Liu J, Waring P, Lade S, Holloway AJ, Taupin D, Gorringe K, Haviv I, Desmond PV, Bowtell DD: Distinctive patterns of gene expression in premalignant gastric mucosa and gastric cancer. Cancer Res 2003, 63:2569-2577. Apart from identifying gene expression patterns characteristic for different stages of H. pylori disease, material from patients from two distinct genetic backgrounds were tested (Chinese and Australian, presumably Anglo Saxon). No difference was observed in the gene expression patterns in patients from different genetic backgrounds. 19. Mills JC, Syder AJ, Hong CV, Guruge JL, Raaii F, Gordon JI: A molecular profile of the mouse gastric parietal cell with and without exposure to Helicobacter pylori. Proc Natl Acad Sci USA 2001, 98:13687-13692. 20. Syder AJ, Oh JD, Guruge JL, O’Donnell D, Karlsson M, Mills JC, Bjorkholm BM, Gordon JI: The impact of parietal cells on Helicobacter pylori tropism and host pathology: an analysis using gnotobiotic normal and transgenic mice. Proc Natl Acad Sci USA 2003, 100:3467-3472. A continuation of the studies by Mills et al. [19] on the role of parietal cells H. pylori infection. 21. Mysorekar IU, Mulvey MA, Hultgren SJ, Gordon JI: Molecular regulation of urothelial renewal and host defenses during infection with uropathogenic Escherichia coli. J Biol Chem 2002, 277:7412-7419. 22. Huang X, Hazlett LD: Analysis of Pseudomonas aeruginosa corneal infection using an oligonucleotide microarray. Invest Ophthalmol Vis Sci 2003, 44:3409-3416. 23. Ferrari G, Langen H, Naito M, Pieters J: A coat protein on phagosomes involved in the intracellular survival of mycobacteria. Cell 1999, 97:435-447. 24. Kovarova H, Halada P, Man P, Golovliov I, Krocova Z, Spacek J, Porkertova S, Necasova R: Proteome study of Francisella tularensis live vaccine strain-containing phagosome in Bcg/ Nramp1 congenic macrophages: resistant allele contributes to permissive environment and susceptibility to infection. Proteomics 2002, 2:85-93. 25. Pizarro-Cerda J, Jonquieres R, Gouin E, Vandekerckhove J, Garin J, Cossart P: Distinct protein patterns associated with Listeria monocytogenes InlA- or InlB-phagosomes. Cell Microbiol 2002, 4:101-115. An interesting approach to study the very early events in uptake of Listeria. Latex beads coated with invasions InlA or InlB were taken up and proteomics analysis of the early phagosomes was performed. In this way a specific effector of InlB-mediated internalization could be identified. 26. Molestina RE, Klein JB, Miller RD, Pierce WH, Ramirez JA, Summersgill JT: Proteomic analysis of differentially expressed Chlamydia pneumoniae genes during persistent infection of HEp-2 cells. Infect Immun 2002, 70:2976-2981. 27. Nouwens AS, Willcox MD, Walsh BJ, Cordwell SJ: Proteomic comparison of membrane and extracellular proteins from invasive (PAO1) and cytotoxic (6206) strains of Pseudomonas aeruginosa. Proteomics 2002, 2:1325-1346. 28. Haas G, Karaali G, Ebermayer K, Metzger WG, Lamer S, Zimny-Arndt U, Diescher S, Goebel UB, Vogt K, Roznowski AB et al.: Immunoproteomics of Helicobacter pylori infection and relation to gastric disease. Proteomics 2002, 2:313-324. 29. Utt M, Nilsson I, Ljungh A, Wadstrom T: Identification of novel immunogenic proteins of Helicobacter pylori by proteome technology. J Immunol Methods 2002, 259:1-10.
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30. Bumann D, Aksu S, Wendland M, Janek K, Zimny-Arndt U, Sabarth N, Meyer TF, Jungblut PR: Proteome analysis of secreted proteins of the gastric pathogen Helicobacter pylori. Infect Immun 2002, 70:3396-3403. Secreted proteins (the secretome) of the human pathogen Helicobacter pylori may mediate important pathogen–host interactions, but such proteins are technically difficult to analyze. The approach used here lead to the identification of 26 secreted proteins, which are potential targets for vaccines or therapeutics. 31. Nouwens AS, Beatson SA, Whitchurch CB, Walsh BJ, Schweizer HP, Mattick JS, Cordwell SJ: Proteome analysis of extracellular proteins regulated by the las and rhl quorum sensing systems in Pseudomonas aeruginosa PAO1. Microbiology 2003, 149:1311-1322. 32. Wehmhoner D, Haussler S, Tummler B, Jansch L, Bredenbruch F, Wehland J, Steinmetz I: Inter- and intraclonal diversity of the Pseudomonas aeruginosa proteome manifests within the secretome. J Bacteriol 2003, 185:5807-5814. 33. Ziebandt AK, Weber H, Rudolph J, Schmid R, Hoper D, Engelmann S, Hecker M: Extracellular proteins of Staphylococcus aureus and the role of SarA and sigma B. Proteomics 2001, 1:480-493. 34. Shaw AC, Vandahl BB, Larsen MR, Roepstorff P, Gevaert K, Vandekerckhove J, Christiansen G, Birkelund S: Characterization of a secreted Chlamydia protease. Cell Microbiol 2002, 4:411-424. 35. Backert S, Muller EC, Jungblut PR, Meyer TF: Tyrosine phosphorylation patterns and size modification of the Helicobacter pylori CagA protein after translocation into gastric epithelial cells. Proteomics 2001, 1:608-617. 36. Moese S, Selbach M, Zimny-Arndt U, Jungblut PR, Meyer TF, Backert S: Identification of a tyrosine-phosphorylated 35 kDa carboxy-terminal fragment (p35CagA) of the Helicobacter pylori CagA protein in phagocytic cells: processing or breakage? Proteomics 2001, 1:618-629. 37. Khandurina J, Guttman A: Microchip-based high-throughput screening analysis of combinatorial libraries. Curr Opin Chem Biol 2002, 6:359-366. 38. Rain JC, Selig L, De Reuse H, Battaglia V, Reverdy C, Simon S, Lenzen G, Petel F, Wojcik J, Schachter V et al.: The protein– protein interaction map of Helicobacter pylori. Nature 2001, 409:211-215. 39. Lieberman J, Song E, Lee SK, Shankar P: Interfering with disease: opportunities and roadblocks to harnessing RNA interference. Trends Mol Med 2003, 9:397-403. 40. Wang QC, Nie QH, Feng ZH: RNA interference: antiviral weapon and beyond. World J Gastroenterol 2003, 9:1657-1661. 41. McCaffrey AP, Meuse L, Pham TT, Conklin DS, Hannon GJ, Kay MA: RNA interference in adult mice. Nature 2002, 418:38-39. 42. McCaffrey AP, Nakai H, Pandey K, Huang Z, Salazar FH, Xu H, Wieland SF, Marion PL, Kay MA: Inhibition of hepatitis B virus in mice by RNA interference. Nat Biotechnol 2003, 21:639-644. 43. Sorensen DR, Leirdal M, Sioud M: Gene silencing by systemic delivery of synthetic siRNAs in adult mice. J Mol Biol 2003, 327:761-766. The authors were able to show that synthetic siRNAs delivered in cationic liposomes were able to silence expression of GFP when co-administered with a GFP-expressing plasmid. They were also able to show suppression of tumor necrosis factor (TNF)-a after intraperitoneal injection and, of greater interest, to delay the onset of lipopolysaccharide-induced sepsis by administration of siRNA, which inhibited TNF-a.
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