Computational investigation of systemic pathway responses in severe pneumonia among the Gambian children and infants

Pneumonia remains the leading cause of infectious mortality in under-five children, and the burden is highest in sub-Saharan Africa. To mitigate this burden, further knowledge is required to accelerate the development of innovative and cost-effective approaches. To gain a deeper insight into the pathogenesis of pneumonia, I investigated the central hypothesis that systemic pathway (cellular and molecular) responses underpin the development of severe pneumonia outcomes. Mainly, I compared whole blood transcriptomes between severe pneumonia cases (clinically stratified as mild, severe and very severe) and non-pneumonia community controls (prospectively matched by age and sex). In total, 803 whole blood RNA samples were collected from Gambian children (aged 2-59 months) between 2007 and 2010, of which, 518 passed laboratory quality control criteria for the microarray analysis. After data cleaning, the final database reduced to 503 samples including the training (n=345) and independent validation (n=158) data sets. To investigate the cellular responses, I applied computational deconvolution analysis to assess the variations of immune cell type proportions with pneumonia severity. To further enhance the computational performance, I applied a data fusion approach on 3,475 immune marker genes from different resources to derive an optimal and integrated blood marker list (IBML, m=277) for Neutrophils, Monocytes, NK, Dendritic, B and T cell types; which robustly performed better than the existing individual resources. Using the IBML resource, pneumonia severity was significantly associated with the depletion of B, T, Dendritic and NK cell types, and the elevation of Monocytes and neutrophil proportions (P-value<0.001). At the molecular level, pneumonia severity was associated (false discovery rate<0.05) with a battery of systemic pathway (innate, adaptive and metabolic) responses in a range of biomedical databases. While the up-regulation of inflammatory innate responses was also observed in mild cases, severe pneumonia cases were predominantly associated with the co-inhibition of the cells of the adaptive immune response (B and T) and Natural killer cells, and the up-regulation of fatty acid and lipid metabolism. While most of these findings were anticipated, the involvement of NK cells was unexpected, and potentially presents a novel immune-modulation target for mitigating the burden of pneumonia. Together, the cellular and molecular pathways responses consistently support the central hypothesis that systemic pathway responses contribute significantly to the development of severe pneumonia outcomes. Clinically, the identification and appropriate treatment of patients at the higher risk of developing severe pneumonia outcomes remains the major challenge. To address that, I applied supervised machine-learning approaches on cellular pathway based transcriptomic features; and derived a 33-gene classifier (representing the NK, T, and neutrophils cell types), which accurately detected severe pneumonia cases in both the training (leave-one-out cross-validated accuracy=99%) and independent validation (accuracy=98%) datasets. Independently, similar performance (98% in each dataset) was associated with a subset (m=18) of the validated 52-gene neonatal sepsis classifier. Conversely, at least 75% of the cellular biomarkers were differentially expressed (false discovery rate<0.05) in bacterial neonatal sepsis. Further, very severe pneumonia cases were predominantly associated with antibacterial responses; and mild pneumonia cases with blood-culture-confirmed positivity were also associated with an increased frequency of differentially expressed genes. These findings suggest the significant contribution of bacterial septicaemia in the development of serious pneumonia outcomes. Together, this study highlights the future potential of host-derived systemic biomarkers for early identification and novel treatment modalities of high-risk cases presenting at a resource-constrained clinic with mild pneumonia. However, further validation studies are required

Earthworm system immunity and its modulation by nanoparticles

The particulate nature of nanoparticles (NPs) dictates a preferential interaction with cells of the immune system assigned to recognition and elimination of foreign particulates. Probing safety of nano-objects by defining immune responses of environmental organisms is therefore key to environmental nanosafety. Earthworms represent major immunosafety models representing keystone ecosystem engineers and being in intimate contact with soils ensuring exposure to terrestrial NPs. Innate immunity represents the first line of defence against pathogens in invertebrates and despite extensive description of cell populations involved a dearth of information about the associated molecular components exists. This thesis aimed to use genomics approaches to generate a comprehensive systems immunity description of earthworm prior to exploiting transcriptomics to explore the interaction of NPs and earthworms. A tissue-specific transcriptomic atlas has been established for Eisenia fetida and Eisenia andrei representing six tissues from each species. The resultant comparative transcriptomic resource represented an innate immunity database containing immune-related genes from major immune signalling pathways. To refine the tissue-specific database we generated a de novo genome for E. fetida with high contiguity and completeness. Finally, to enhance insight into the different immune functions of the individual types of coelomocytes we generated transcriptomic datasets from eleocytes, hyaline and granular amoebocytes. The interaction between NPs and the earthworm immune system was then explored by combining the direct introduction of copper oxide NPs with bacterial challenge and following the transcript changes within individual coelomocytes cell populations. This resolved the spatial-temporal impact on the immune system into three distinct phases: direct, systemic and differentiation responses. A complementary soil-based exposure using a range of CuNPs, Silicon-CuNPs and copper ion doses explored the comparative response after soil-based biotransformation. This revealed Si-CuNPs to elicit a negligible response whilst differentially regulated genes under high CuNPs were distinct from equivalent copper ion exposure the pathways impacted intersected substantially

Evaluation of PD-L1 expression in various formalin-fixed paraffin embedded tumour tissue samples using SP263, SP142 and QR1 antibody clones

Background & objectives: Cancer cells can avoid immune destruction through the inhibitory ligand PD-L1. PD-1 is a surface cell receptor, part of the immunoglobulin family. Its ligand PD-L1 is expressed by tumour cells and stromal tumour infltrating lymphocytes (TIL). Methods: Forty-four cancer cases were included in this study (24 triple-negative breast cancers (TNBC), 10 non-small cell lung cancer (NSCLC) and 10 malignant melanoma cases). Three clones of monoclonal primary antibodies were compared: QR1 (Quartett), SP 142 and SP263 (Ventana). For visualization, ultraView Universal DAB Detection Kit from Ventana was used on an automated platform for immunohistochemical staining Ventana BenchMark GX. Results: Comparing the sensitivity of two different clones on same tissue samples from TNBC, we found that the QR1 clone gave higher percentage of positive cells than clone SP142, but there was no statistically significant difference. Comparing the sensitivity of two different clones on same tissue samples from malignant melanoma, the SP263 clone gave higher percentage of positive cells than the QR1 clone, but again the difference was not statistically significant. Comparing the sensitivity of two different clones on same tissue samples from NSCLC, we found higher percentage of positive cells using the QR1 clone in comparison with the SP142 clone, but once again, the difference was not statistically significant. Conclusion: The three different antibody clones from two manufacturers Ventana and Quartett, gave comparable results with no statistically significant difference in staining intensity/ percentage of positive tumour and/or immune cells. Therefore, different PD-L1 clones from different manufacturers can potentially be used to evaluate the PD- L1 status in different tumour tissues. Due to the serious implications of the PD-L1 analysis in further treatment decisions for cancer patients, every antibody clone, staining protocol and evaluation process should be carefully and meticulously validated