MAPPINGS v1.0, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection

Abstract

Phosphorylation-based signalling implicates a complex and intertwined series of pathways and is critical to all domains of life. The interconnectivity between pathways results in the emergence of complex networks whose elucidation present a serious challenge. Large datasets of phosphorylation interactions through the activity of kinases on their numerous substrates are constantly being generated, however deciphering the complex network structure hidden in these datasets remains challenging. Many phosphorylation interactions occurring in human cells have been identified and constitute the basis for the known phosphorylation interaction network. We overlayed onto this network phosphorylation datasets obtained from an antibody microarray approach aimed at determining changes in phospho-signalling of host erythrocytes to infection with the malaria parasite Plasmodium falciparum. To analyse the datasets now mapped into the interaction network, we designed a pathway analysis tool denoted MAPPINGS that uses random walks to identify chains of phosphorylation events occurring much more or much less frequently than expected. MAPPINGS highlights pathways of phosphorylation that work synergistically, providing a rapid interpretation of the most critical pathways in each dataset. MAPPINGS confirmed several signalling interactions previously shown to be modulated by infection, and revealed additional interactions which could form the basis of numerous future studies. The MAPPINGS analysis strategy described here is widely applicable to comparative phosphorylation datasets in any context (e.g. response of cells to infection, treatment, or comparison between differentiation stages of any cell populations) and provides a rapid and reliable analysis to guide validation studies.

Mammalian cells internalize bacteriophages and utilize them as a food source to enhance cellular growth and survival

“…Briefly, microarray datasets were filtered to remove low signal intensity and/or relatively high error signals compared to control signals. The network analysis was then separately run for both up- and down-regulated phosphorylation events before being assembled into a comparative pathway map (46). Only pathways with more than two intermediates and with fold-changes greater than 5% CFC (% changes from control) were selected for further consideration.…”

“…This suggests two mechanisms, firstly, that phage uptake and transport by the mammalian cell are tightly regulated by the cell with free phages unlikely to be exposed in the cell cytoplasm, and secondly, phages are not actively degraded or triggered within the macropinosomes, and phage DNA is not exposed to TLR9 receptors (Figure 2). Further experiments are required to explore if different conditions, such as incubation time, pH, temperature, or inflammation state, as well as differences between phages applied or cell lines used, affect the transport and degradation of phages and the subsequent activation of innate immune response and cytokine production (29)(30)(31)68) We utilized an antibody microarray and a pathway analysis to identify chains of protein phosphorylation events and synergistic interaction networks to decipher cellular pathways of interest (46). From this analysis, we identified two main pathways -AKT and CDK1 -that were affected by T4 phages across our two in vitro cell lines.…”

“…For deconvolution of the microarray datasets, we used the previously developed methodology by Adderley at al. (46). The datasets were mapped onto a network and a pathway analysis, which utilizes random walks to identify chains of phosphorylation events occurring more or less frequently than expected (46).…”

“…(46). The datasets were mapped onto a network and a pathway analysis, which utilizes random walks to identify chains of phosphorylation events occurring more or less frequently than expected (46). Rather than focusing solely on the largest fold changes, this analysis instead identifies cellular pathway interactions to provide an interpretation of the most important pathways that are influenced by exposure to phages.…”

“…Microarray analysis. The analysis of the microarray dataset was performed using the MAPPINGS V1.0 network analysis program developed by (46). There was redundancy between the antibodies tested across the KAM-1325 and -2000 arrays with different antibodies targeting the same protein for more precision (Supplemental Figures S2 & S3 and Supplemental Tables S1 & S2).…”