Jane A. English

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2‐DE technique of protein separation, and by first covering signal analysis for MS, we also explain the current image analysis workflow for the emerging high‐throughput ‘shotgun’ proteomics platform of LC coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whereas existing commercial and academic packages and their workflows are described from both a user's and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot‐centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2‐DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image‐based alignment and differential analysis in 2‐DE, Bayesian peak mixture models, and functional mixed modelling in MS, and group‐wise consensus alignment methods for LC/MS.

The mechanisms underlying white matter changes in psychiatric disease are not known. We aimed to characterise the differential protein expression in deep white matter from the dorsolateral prefrontal cortex from 35 schizophrenia, 35 bipolar disorder, and 35 control subjects, from the Stanley Array Collection. We used 2‐D DIGE to profile for protein expression changes in the brain. We found 70 protein spots to be significantly differentially expressed between disease and control subjects (ANCOVA, p<0.05), 46 of which were subsequently identified by LC‐MS/MS. The proteins identified included novel disease candidates as well as proteins that have previously been reported as abnormal in schizophrenia, thus reinforcing their association with the disease. Furthermore, we confirmed the direction of change for three proteins using ELISA, namely neurofilament‐light, amphiphysin II, and Rab‐GDP‐α, in a subset of the Stanley Array Collection. In addition, altered expression of neurofilament‐light, amphiphysin II, and Rab‐GDP‐α was not observed in the cortex of mice chronically treated with haloperidol, making it less likely that these alterations are a consequence of neuroleptic medication. The data presented here strongly suggest disruption of the cytoskeleton and its associated signal transduction proteins in schizophrenia, and to a lesser extent in bipolar disorder.

The workshop assembled an excellent collection of speakers from across Ireland and beyond who presented many interesting and diverse topical issues. Various proteomic applications were discussed throughout the day ranging from 2‐DE and 2‐D DIGE, to GeLC‐MS/MS, high density Protein and Antibody Arrays, with a particular focus on the importance of quantitative mass spectrometry in proteomics.