Identification and characterisation of alveolar epithelial biomarkers

Abstract

The alveolar epithelial surface has been shown to be important in many forms of lung injury (e.g. ARDS, pneumonia and fibrosis). Markers of cell specific injury to the lung that can be measured in bronchioalveolar lavage would be advantageous as they might allow study of damage to the alveoli in a non-invasive mariner. In this thesis a strategy is described, using a bacterial model of pneumonia, for identifying markers specific for individual cell types within the alveoli. Also, two putative cell specific antibodies (MMC4 and MMC6) are further characterised to establish their potential as markers of alveoli injury. A rat model of pneumonia, caused by instillation of Staphylococcus aureus, has shown a decrease in alveolar epithelial type I cells (AETI cells) and an increase in alveolar epithelial type II cells (AETII cells) seventy two hours post-infection. Injured regions from seventy two hour post Staphylococcus aureus infected lungs were analysed via global gene analysis using Affymetrix® U34 gene chips. Overall 67 genes were found to increase greater than 2 fold (F>0.05, P≤0.001); of which 49 encode from known proteins. 197 genes decreased 2 fold of greater (F>0.05, P≤0.001) of which 125 translate to known proteins. Searching the genes that decreased identified some proteins associated with AETI cells (e.g. caveolin: 7 fold decease, P=0.017 and aquaporin 5:2 fold decrease, P =0.01). This suggests that this group of down regulated genes could potentially contain novel markers that could identify reduced numbers of AETI cells. Within this group CD9 was found to decrease. This was unexpected due to the influx of macrophages (known to be CD9 positive) into the site of injury. However, a literature search showed that CD9 is known to be expressed in the alveoli, but is not thought to be cell specific. Immunohistochemistry of frozen lung sections showed that anti-CD9 antibodies co-localised with AETI markers (caveolin, MMC6) but not AETII markers (RTII₇₀, MMC4). MMC4 monoclonal antibody (IgG2a) has been proposed as an AETII and Clara cell marker that recognises a protein novel to these two cell types within the lung, but the antigen has not been characterised. MMC4 antigen was immunoprecipitated from detergent-solubilized fractions of organ homogenates using antibody-bound magnetic beads. The resulting purified protein was trypsin digested and analysed via MALDI-TOF and tandem mass spectrometry. The top 'hit' in SWISSPROT for the antigen was aminopeptidase N (APN). The MMC4 monoclonal antibody was found to recognise a commercially purified APN. Further analysis showed that the MMC4 monoclonal antibody was not a functional inhibitor of APN and that the antibody was not binding to a glycans attached to APN. MMC6 monoclonal antibody (IgG2b) was created at the same time as the MMC4 antibody. Initial studies showed that MMC6 recognises AETI cells within the lung. This study shows that the antibody is recognising an antigen that is specific for the lung and is only located on AETI cells within the lung. The antigen has been found to be an integral membrane protein. Attempts at solubilizing the MMC6 antigen from the cell membranes were not successful; however mechanical disruption did partially remove the antigen from the cell membranes. Magnetic bead immuno-precipitation eluted a protein of 60kDa. Unfortunately, due to low yields of the protein, identification was not possible by MALDI-TOF or Edman degradation. This thesis proposes a new way of interpreting global gene data to find proteins specific to different cell types. We cast doubts on the specificity of some previously proposed "specific" markers. It also highlights the pitfalls of claiming an antibody is a useful marker of injury until the candidate biomarker has been fully investigated. The continued emergence of CD proteins on alveolar epithelial cells within this study suggest that the alveolar epithelium may have more influence over the immune response within the lung than previously realised

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