Mechanical ventilation is a life-saving therapy for numerous critical illnesses. However, it is now recognized that ventilation with excessive tidal volumes, leading to hyperexpansion or excessive mechanical shear, is potentially directly harmful to susceptible patients. The benefits of lower tidal volumes, which reduce lung-cell stretch, have now clearly been established 1. The clinical presentation of ventilator-associated lung injury (VALI) is identical to that of other causes of acute lung injury (ALI) and is characterized by increased pulmonary edema. Important studies by Parker 23 and Webb and Tierney 4 demonstrated changes in microvascular permeability in isolated lung and intact animal models exposed to increased airway pressures, suggesting that these changes in permeability may in large part be attributed to the effects of mechanical stimuli on various cell-signaling pathways 56. Although several studies have suggested a genetic basis for susceptibility to VALI 789, few candidate genes have been implicated in this process.

To identify major genes associated with VALI, we examined gene-expression profiles of several in vivo models (rat, mouse, and dog) of ventilator-induced ALI. As a main component of ALI is presumed to involve biophysical stress-induced leakage of the pulmonary vasculature 10, we also included human lung vascular endothelial cells exposed to high-level cyclic stretch as a human in vitro model of mechanical stress. Gene-expression profiling of these models was performed and analyzed using species-specific Affymetrix GeneChips. The individual analysis of species-specific arrays produced large lists of candidate genes and several challenges, with the most notable being an excessive number of genes (ranging from 548 candidates in the rat to 963 candidates in the human model) for candidate gene selection. While meta-analysis strategies exist for narrowing candidate gene selection from multiple experimental systems 111213, this analysis can only be applied to the same species cross-platform array comparison. To use this approach for analysis of experiments involving diverse species we speculated that multi-species gene-expression profiles could be linked using the Eukaryote Gene Orthologs database (EGO 14).

Orthologs are genes in different species that have evolved from a common ancestral gene by speciation and generally retain a similar function in the course of evolution. We speculated that overlapping responses to mechanical stretch in orthologous genes across species might reveal candidate genes involved in an evolutionarily conserved defense mechanism to lung injury that might be triggered by ventilator-induced lung injury. Previous studies of three-way comparative analysis of human, mouse and dog DNA 15 showed that the majority of highly conserved human-mouse elements are also conserved in the dog. Furthermore, Frazer et al. 16 speculated that comparing human sequence with those of multiple species might be an effective approach for distinguishing actively conserved elements from elements that simply result from a shared ancestry. On the basis of these observations, we predicted that a common stimulus (mechanical stretch) across four different species will initiate actively conserved mechanisms that defend the lungs against adverse environment factors or bacterial products. To select genes involved in these defense mechanisms the functionally related genes from different species should be first identified.

Despite the availability of tools for comparing gene-expression data from Affymetrix GeneChip arrays designed for different species 1718, there are limited resources for simultaneous array-data analysis across multiple species-specific platforms (GeneChip IDs U34, U74, U95, U133). GeneHopper 1819, which uses the UniGene and HomoloGene databases to provide comparisons between arrays, is useful for linkage of selected genes of interest from different array platforms, but is less suitable for linking expression sequence tags (ESTs) and uncharacterized genes represented on arrays. Moreover, the database for this software is not yet complete, and does not include the widely used HG_U95Av2 GeneChip.

A better alternative is RESOURCERER 1720, which is based on the TIGR Eukaryotic Gene Ortholog (EGO) database 21, and contains information for all commercially available Affymetrix GeneChips. However, RESOURCERER allows comparison of only two chips simultaneously and cannot be used directly for multi-species analysis. Therefore, we assembled a database using ortholog links (identified by RESOURCERER) between the most commonly used Affymetrix rat, mouse and human GeneChips (U34A, U74A, U95A and U133A) for our multi-species cross-platform gene-expression analysis.

We first calculated gene-expression changes for each tested species and linked expression values obtained for orthologous genes. Orthologous genes exhibiting similar patterns of expression across all species were selected as VALI-related candidates under the assumption that gene-expression responses conserved across evolutionary history would be most likely to reveal fundamental biological responses to VALI. After normalizing gene-expression values across species, we next identified orthologous genes with statistically significant changes in response to VALI. A biologically significant fold-change in gene-expression level was determined using MAPPFinder 2223 by linking selected genes to Gene Ontology (GO) biological processes and identifying functional categories that were significantly regulated. This filtering produced a candidate list of 69 genes that were significantly affected by mechanical stretch. A literature search for these genes using PubMatrix 24 identified 12 genes as related to ALI as well as six new VALI-related candidate genes. Our analytical gene ortholog approach also revealed a number of changes in unsuspected GO processes and biological pathways that may provide new insights and potential therapies in ALI. Thus, this technique offers the capacity to identify genes that are likely to be missed by individual species analysis and facilitates application of a meta-analysis approach to multi-species analyses.

To maximize the number of valid cross-species comparisons, we focused our analysis on the human, mouse and rat Affymetrix 'A' GeneChips, which contain the majority of 'named' or functionally classified genes and the least number of unannotated ESTs. Ortholog tables for each pair were generated using RESOURCERER. This software provides a table in which rows contain paired orthologous probe IDs; IDs corresponding to Affymetrix internal controls were ignored in further analysis. Because the U133A GeneChip contained the largest number of probe IDs (22,215) as compared to U95A, U74A, and U34A chips (12,588, 12,422, and 8,740 probe IDs, respectively), the U133A genes were selected as the reference gene set for orthologous comparisons. As anticipated, the total number of reference genes to participate in forming ortholog pairs (identified by RESOURCERER) was always higher than that of corresponding orthologs (Table 1), which justified our selection of the U133A array as the reference platform.

The linkage of all four arrays identified 3,077 genes common to the U133A reference gene ortholog nodes (Figure 1). An example of an ortholog node for the ODC-1 gene is shown in Figure 2a. This ortholog node was missing one link, rendering our ortholog-linked database incomplete. Therefore, we identified all orthologs with missing links (Figure 2b) and connected them as putative orthologs on the basis of homology to the common reference gene.

Gene-expression data for populating our ortholog-linked database was generated by hybridization of total mRNA from rat, mouse and dog lung tissues and human endothelial cell cultures to GeneChips U34A, U74A, U133A and U95A, respectively. All hybridizations were represented by a minimum of three control and four mechanical stretch-challenged samples, with the exception of the rat model which had two control and two stretch-affected samples (see Materials and methods). The signal intensities produced during hybridization were extracted from hybridization images using Affymetrix software MAS 5.0 and ratios of transcript abundance calls were computed. Rat, mouse, and human array assays produced 51%, 52% and 49% present (p < 0.04) and marginal (p < 0.06) transcript abundance calls, respectively. In contrast, however, the canine hetero-hybridization to the human U133A GeneChip created only 17% marginal and present calls (Figure 3a). Probe-level analysis revealed that poor cross-species hybridization to a subset of the probe pair sets was responsible for the loss of many present calls from the canine array data. To address this, we adjusted results of this cross-species hybridization by modifying U133A array probe-set compositions on the basis of differences between dog and human DNA. The poorly performing probes were also identified in the species-specific hybridizations and subsequently masked using masking protocol embedded in MAS 5.0. When modified probe sets were reprocessed by MAS 5.0, the ratio of present calls was increased on average by 25% (Figure 3b). Next, we replaced remaining absent calls with the corresponding chip background value (see Materials and methods), which allowed us to use all available data on each chip. Subsequent statistical analysis was conducted for each experimental system individually and four generated gene lists were later used for comparison with gene lists generated using the ortholog approach.

For statistical analysis of combined cross-platform expression data, we pooled control and mechanical stretch-challenged samples from all tested species into corresponding groups n_control = 11 (n_rat = 2, n_mouse = 3, n_canine = 3, and n_HPAEC = 3) and n_stretch = 14 (n_rat = 2, n_mouse = 4, n_canine = 4, and n_HPAEC = 4). Because these arrays contain multiple paralogues (similar sequences in a single organism), the multiple orthologs for the same reference gene were identified (Figure 4). Therefore, approximately 62% of formed ortholog groups failed to follow the n_control = 11/n_stretch = 14 pattern. To avoid unequal contribution of each species to the statistical analysis, the expression values of multiple paralogues were averaged and then n_control = 11/n_stretch = 14 set was built. Once the groups for comparison were formed, we used the independent variance double-tailed t-test for statistical evaluation of changes in gene expression of reference genes and their orthologs. This analysis identified significant changes in the expression of 141 reference genes and their corresponding orthologs across all experimental systems.

To further refine this list, we established a fold-change cutoff for biologically significant gene-expression changes based on the analysis of the relationship of the biological processes driven by these genes. Starting from the notion that genes coding for proteins involved in the same biological processes are regulated in coordinated manner, and that expression of members of a given bioprocess is more likely to be co-regulated rather than inversely regulated 25, we speculated that an increased ratio of inversely regulated bioprocesses at low fold-change cutoff values (Figure 5a,b) is due to the contribution of spurious (false-positive) changes in gene expression assigned to low fold-change values. As shown in Figure 5a for inflammatory response bioprocess at 1.1- and 1.15-fold-change cutoffs, this process was classified as inversely regulated. However, with a 1.2-fold-change cutoff, this becomes a co-regulated pathway. In contrast, the DNA-dependent regulation of transcription bioprocess (Figure 5b) is classified as an inversely regulated through all tested fold-change cutoffs. Although most low fold-change genes in this process were eliminated, the ratio of upregulated and downregulated genes remained constant and was stabilized beyond the 1.3-fold-change cutoff. From these observations we propose that the point at which sharp changes in the number of genes involved in GO bioprocesses subsides could be considered as biologically meaningful fold-change cutoff.

The bioprocesses affected by mechanical stretch were identified using MAPPFinder 13 software designed by BayGenomics PGA group for dynamic linkage of gene-expression data to the GO 26 hierarchy. When we analyzed the gene pool that included genes with slight changes in their expression (1.1-fold), the MAPPFinder identified 432 bioprocesses, with 288 activated and 147 suppressed bioprocesses. Of these 432 bioprocesses, a total of 54 bioprocesses were common to both groups and, therefore, were classified as inversely regulated (shared) bioprocesses (Figure 5). To identify the point at which the number of the shared bioprocesses will approach the monotonic phase at which only real inversely regulated pathways will survive, we tested our gene list by gradually increasing the stringency of the fold-change cutoff. The fold-change cutoff of ±1.3 and ±1.35 satisfied this condition for inversely regulated and co-regulated bioprocesses, respectively (Figure 5). Using this filtering strategy and applying ±1.3-fold-change cutoff, we further refined our gene list to 69 genes (see Additional data files) which comprised 61 upregulated and 8 downregulated genes.

We next matched these 69 genes against the PubMed database using the PubMatrix 24 software tool. This analysis identify 12 genes that were extensively linked to lung-injury-related articles, with six of these genes also linked to mechanical ventilation-related articles, a finding that indirectly validates our approach (Table 2). Given the pre-eminent importance of the vascular component in ALI pathogenesis, our primary trait in selecting candidate genes was their expression in vascular endothelium. The PubMatrix output identified a number of genes linked to articles that included lung, endothelium, and even pulmonary endothelium terms in their context, which again facilitated our selection of new gene candidates for further studies.

We also investigated whether our gene list might reveal unsuspected biological processes and pathways activated or suppressed by VALI. To address this we linked the available GenMAPP 27 biological GO processes 23 to our gene list. The resulting picture of the biological processes affected by mechanical stretch in our models is shown in Table 3 with 'Immune Response,' 'Inflammatory Response,' 'Blood Coagulation,' and 'Cell Cycle Arrest' biological processes identified as the most significantly upregulated by mechanical stretch. As our gene list had only eight downregulated genes, the MAPPFinder output for downregulated pathways did not allow filtering (see Materials and methods). The complete list of genes and GO processes identified by our procedure is provided in our supplemental data files.

Finally, we compared our list of candidate genes with the genes obtained from four individual experimental systems using the same filtering conditions (±1.3-fold-change cutoff and p < 0.05). As shown in Table 4, analysis of gene expression in canine, human, mouse and rat models identified 9, 7, 13, and 15 genes out of our 69 candidates, respectively. The total of 28 genes (~40%) successfully identified by our ortholog approach did not survive selection by individual species analysis, and included well known ALI-related candidate genes such as IL1β, COX-2, PAI-1, BTG1, and FGA. The linkage of orthologous genes from different arrays increased the statistical power of our gene-expression analysis and allowed us to identify candidate genes that would otherwise remain unnoticed. A small fraction (~15%) of known ALI-related genes 72829 were identified by individual species analysis but not detected by our bioinformatics approach (Table 4). This is to be anticipated, as differences exist in gene representation on multiple array platforms. For example, genes coding for the ALI candidates interleukin-8 and tumor necrosis factor-alpha were not presented on the rodent arrays, and therefore were excluded from our analysis. The tissue-specific gene expression also contributed to this false-negative gene fraction. The gene coding for surfactant C, which is mainly expressed in epithelial cells, was identified during analysis of stretched canine lung tissues but was excluded by our orthologous method because of the virtual absence of expression in stretched endothelial cells (Table 4).

The procedure we have described presents a complementary and potentially useful approach in searching for candidate genes involved in specific biological processes of interest. General trends in the expression of common groups of genes in response to a specific stimulus in diverse species might relate unsuspected evolutionarily conserved responses triggered by this stimulus. At the same time, known biological pathways and genes, either activated or suppressed by a selected stimulus, can be used as a validation of this approach. In this study, we investigated the response of four different biological systems (rat, mouse, dog, and human cell culture) to levels of mechanical stretch relevant to ALI. Our ortholog approach and filtering algorithm allowed us to identified 12 VALI candidate genes previously linked to ALI, five of which went undetected using a common analytical approach. We also selected six novel endothelium-related candidate genes that warrant further investigation (Table 2).

The most commonly cited upregulated ALI genes in our list were those for IL-1β and interleukin-6 (IL-6), which were cited as lung-injury-related proteins in 287 and 173 references, respectively. Importantly, IL-1β did not survive standard selection as a candidate gene and was undetected by the same-species analytical approach. IL-6 had the highest number of links (75 citations) to mechanical ventilation (Table 2). Clinical studies showed that IL-1β and IL-6 concentrations in broncho-alveolar lavage fluid (BALF) from patients with established adult respiratory distress syndrome (ARDS) were higher than in BALF from normal volunteers 30. Moreover, IL-1β was self-sufficient in causing ALI when overexpressed in mouse lungs 31 and was directly related to VALI in another mouse model 32. IL-6 levels in ALI patients correlated with the mode of mechanical ventilation, as low tidal volume was associated with lower IL-6 and elevated tidal volume with high IL-6 concentrations 33.

Predictably, we identified several genes encoding enzymes that are highly conserved throughout evolution, including the ALI-related enzyme prostaglandin-endoperoxide synthase 2/cyclooxygenase-2 (PTGS-2/COX-2). COX-2 is involved in eicosanoid synthesis and appears to be important to both edemagenesis and the pattern of pulmonary perfusion in experimental ALI. Gust et al. showed that the effect of endotoxin on pulmonary perfusion in ALI could be, in part, the result of activation of inducible COX-2 34. Upregulation of the COX-2 gene is also linked to increased pulmonary microvascular permeability in a sheep model of combined burn and smoke inhalation injury 35.

We also showed that the lung-specific surfactant protein regulation transcription factor, CCAAT enhancer-binding protein (C/EBP), was upregulated in all VALI models. C/EBP has an important role in the regulation of expression of surfactant proteins A and D, which are heavily involved in pulmonary host defense and innate immunity 36, with increased gene expression in patients with ALI 3738. Upregulation of C/EBP by severe lung injury 39 is highly correlated with our findings (1.4-fold increase in C/EBP expression, p = 0.013, Table 2). As endothelium does not generate surfactant, it will be of interest to identify the molecular targets of C/EBP in endothelium; these may include interleukin-13 (IL-13) 40 and cell chemokine 2 (CCL2) 41. These genes belong to the 'Inflammatory Response' GO biological process that was rated by MAPPFinder as highly upregulated (Table 3).

The second most highly represented ontology in the ALI-related genes bioprocess was 'Blood Coagulation' (Table 3), a finding consistent with previous reports of increased levels of coagulation factor III (thromboplastin, tissue factor, F3) and plasminogen activator inhibitor type 1 (PAI-1) in patients with ALI 424344 or VALI 4546. Fibrinogen A (FGA) and plasminogen activator - the urokinase receptor (PLAUR) - are involved in IL-1β signaling and regulation, respectively. Fibrinogen indirectly activates transcription of IL-1β 47, which in turn increases expression of the urokinase receptor 48. Interestingly, this bioprocess was identified by MAPPFinder solely on the basis of data generated by our ortholog algorithm, as in a single-species analysis, three out of four genes related to the blood coagulation bioprocess did not survive statistical filtering (Table 4).

The interconnection of coagulation and inflammation is well recognized in that inflammation leads to increased coagulation, relevant to ALI (for a review see 8) and a likely link is vascular endothelium. There is some evidence that the 'cross-talk' between coagulation and inflammation could be reversed. Blood coagulation in vitro stimulates release of inflammatory mediators from neutrophils and endothelial cells 4950. On the basis of these findings and data generated by our cross-species analysis of VALI, we speculate that mechanical stretch may produce either injury or activation of the pulmonary endothelium with activation of a coagulation cascade that may involve platelet aggregation. Procoagulation genes are therefore key participants in the early stages of VALI. Given that a multitude of inflammatory cytokines produce upregulation of the coagulation cascade, further studies of the time-course analysis of expression patterns of selected candidate genes in response to VALI are needed to clarify this paradigm.

In summary, our findings indicate that alterations in gene expression in response to mechanical ventilation alone can be detected by microarray techniques applied across diverse biological systems. Our data suggest that ortholog-link gene-expression analysis of multi-species VALI-simulating experimental systems is a useful tool in selecting candidate genes involved in this pathobiological process, with clear advantages over single-species analysis. We anticipate that predicted drawbacks such as incompleteness of gene representation on different array platforms and tissue-specific gene expression can be overcome by careful selection of array platforms and experimental models, respectively, as well as further improvements or refinements in the Affymetrix platform itself.

The ortholog gene-expression approach promotes application of the meta-analysis of multi-species gene-expression profiles in diverse human pathologic conditions and facilitates the selection of candidate genes of interest, with the emphasis on actively evolutionarily conserved genes.

The following additional data files are available with the online version of this article: a final list of reference genes (Additional data file 1), a list of gene candidates (Additional data file 2), the full GO results (Additional data file 3), and data for Table 4 (Additional data file 4).