Proteomic and genomic analysis of cellular stress responses

Aspects of nearly every stage of the infectious disease process involve a highly complex series of interactions between a parasite and its host, with a pathogen typically encountering multiple, often hostile, microenvironments (stressors) during the infection process. As a consequence, cellular growth and survival of a pathogen requires they can rapidly recognise and adapt to these changing surroundings. This versatility depends on a large range of adaptive or accessory systems, a subset of these being specific genes involved in pathogenesis (the mechanisms by which disease is caused), a process which is essentially adaptation to the hostile host environment and its immune defences. Precise regulatory control of gene and protein expression is therefore crucial to a pathogens success, rapid changes in function and expression of virulence factors often depending on complex regulatory networks and interlinked control mechanisms. Typically, recognition of cues such as temperature, pH (whether the surrounding environment is acid or alkaline), or availability of certain nutrients, results in the co-ordinate regulation of multiple virulence-associated genes which ensures that genes required at specific stages of the disease process are expressed at the appropriate time(s).

A better understanding of the mechanisms and factors involved in cellular responses to stress is, accordingly, highly likely to facilitate the development of novel therapeutic interventions and improved diagnostics. Additionally, as de facto determinants of resistance to anti-infectives, a more in-depth appreciation of cellular stress responses may also lead to the identification of novel therapeutic targets

Project timeframes

The project began in 2012 and is ongoing.

 

Project aims

The application of advanced proteomics and molecular biology technologies to the analysis of cellular stress responses, with particular emphasis on the analysis of protein expression and post-translational modifications in microorganisms under stress conditions.

STRAND-Lucas-Bowler-3

Typical quantitative proteomics workflow using tandem mass tags (Diagram courtesy of Thermofisher)

Project findings and impact

The project findings were the

  • identification of proteins in a 'redox secretome' following challenge of macrophages with LPS. These may provide useful biomarkers of oxidative stress associated with inflammation.
  • demonstration that inflammatory stimuli induce release of oxidised peroxiredoxin -2. The associated data indicate that redox-dependent mechanisms in an oxidative cascade can induce inflammation.
  • exposure of the fission yeast S. pombe to osmotic stress results in the sumoylation of the translation initiation factor elF4G. This has significance in terms of DNA metabolism and in the maintenance of chromatin structure.
  • demonstration that the bacterial pathogen Streptococcus uberis is capable of biofilm formation and that a transition to this mode of growth results in differential expression at both transcriptional and translational levels. This is of significance in terms of improved understanding of the molecular pathogenesis of S. uberis disease.
  • intensity patterns of fragmentation spectra are informative and can be used to analyse the influence of peptide characteristics on their resulting fragmentation pathways. This enabled us to the identify peptide features which had most influence on their subsequent fragmentation patterns and enabled us to use these to predict spectra intensities. Such information can help develop more reliable algorithms for peptide and protein identification in proteomics and biological mass spectrometry.

strand-images-Lucas-Bowler-2

Identification of differentially expressed proteins, Scaffold output

Research team

Dr Lucas Bowler

Output

Checconi, P., Salzano, S., Bowler, L. D., Mullen, L., Mengozzi, M., Hanschmann, E. M., Lillig, C. H., Sgarbanti, R., Panella, S., Nencioni, L., Palamara, A. T., and Ghezzi, P. Redox proteomics of the inflammatory secretome identifies a common set of redoxins and other glutathionylated proteins released by inflammation, influenza virus infection and oxidative stress. (2015) PLoS ONE 10(5):e0127086

Salzano, S., Checconi, P., Hanschmann, E. M., Lillig, C. H., Bowler, L. D., Chan, P., Vaudry, D., Mengozzi, M., Coppo, L., Sacre, S., Atkuri, K. R., Sahaf, B., Herzenberg, L.A., Herzenberg, L.A., Mullen, L., and Ghezzi, P. Linkage of inflammation and oxidative stress via release of glutathionylated peroxiredoxin-2, which acts as a danger signal. (2014) Proc. Natl. Acad. Sci. USA. 19: 12157-62.

Jongjitwimol, J., Feng, M., Zhou, L., Wilkinson, O., Small, L., Baldock, R., Taylor, D. L., Smith, D., Bowler, L. D., Morley, S. J., and Watts, F. Z. The S. pombe translation initiation factors elF4G is sumoylated and associates with the SUMO protease Ulp2. (2014) PLoS ONE 9(5): e94182.

Ogilvie, L.A.,Bowler, L.D.,Caplin, J.,Dedi, C.,Diston, D., Cheek, E.,Taylor, H.,Ebdon, J., and Jones, B.V. Genome signature-based dissection of human gut metagenomes to extract subliminal viral sequences. (2013) Nature Commun. 4: 2420-35.

Ogilvie, L.A.,Caplin, J.,Dedi, C.,Diston, D., Cheek, E.,Bowler, L.D.,Taylor, H.,Ebdon, J., and Jones, B.V. Comparative (meta)genomic analysis and ecological profiling of human gut-specific bacteriophage ɸB124-14. (2012) PLoS ONE 7(4): e35053.

Crowley, R.C., Leigh, J.A., Ward, P.N, Lappin-Scott, H.M., and Bowler, L.D. Differential protein expression in Streptococcus uberis under planktonic and biofilm growth conditions. (2011) Appl. Environ. Microbiol.  77: 382-4.

Zhou, C., Bowler, L.D., and Feng, J.J. A Machine Learning Approach to Explore the Spectra Intensity Pattern of Peptides using Tandem Mass Spectrometry Data. (2008) BMC Bioinformatics, 9:325-341.

Partners

Dr Pietro Ghezzi, BSMS;

Dr Felicity Watts, University of Sussex;

Professor James Leigh, University of Nottingham;

Dr Duncan Smith, University of Manchester;

Professor Hilary Lappin-Scott, University of Swansea;

Professor Jianfeng Feng, University of Warwick:

Dr Cong Zhou, University of Manchester.