Current Proteomics - Volume 6, Issue 2, 2009

Honey bees play a crucial role in pollinating wild and cultivated vegetation, with substantial implications on our economy and food supply. Our scientific knowledge of bees consists largely of behavioral or macroscopic-level biological studies. Although in the past several decades there have been some advances in our knowledge of specific hormones, genes, and proteins, molecular biology of bees remain poorly understood relative to the depth to which we understand humans, and typical model organisms such as the mouse or fruit fly. This is due in part to the lack of available reagents for interrogating protein-specific information in standard assays such as Western blot, immunolocalization, and immunoaffinity purification, as well as a relatively difficult system for introducing small, interfering RNAs. Given the available genome sequence then, mass spectrometry-based proteomics techniques are ideally suited to studies in bees; starting from so little knowledge, the discovery-based nature of proteomics should allow for a very steep learning curve relative to better-studied systems such as fruit fly. To this end, twenty-two honey bee proteomics papers have been published since 2005. Here we present a brief summary of biochemical/molecular biological research in bees, including some of the challenges; we focus on the proteomics work to date, and relate these findings to recent transcriptomic work and proteomic studies in other social insects. We end with some speculation on where proteomics is most likely able to provide insight into bee biology where other methods would fail. As the general population and scientific community become increasingly aware of the value of honey bees to both our economy and ecosystem, proteomics will play an important role in improving our understanding of this beneficial insect.

Over the past decade the large use of genomic approaches has resulted in the impressive generation of complete genomic sequences for over 800 bacterial species. However, the use of different bioinformatic approaches to determine the presence of a gene or open reading frame (ORF) in those genomes cause divergent gene annotations, even for data generated from the same genomic sequences. The use of a correct dataset for protein identification is a key step in many fields as phylogenetics, protein expression experiments, and has an impact on the identification capacity of a proteomic workflow. In this review, we describe successful attempts performed by proteomic groups to improve gene annotation in bacteria using different bioinformatic and mass spectrometry technologies. The review emphasizes the most recent advances in high resolution MS technology, which has increased the sequence coverage and peptide identification reliability by several fold. The capacity to perform deeper and more complete catalogations allows correction of several known genes, plus the discovery of protein products of regions of the genome not yet predicted to be coding areas. Recent results from our group show how such technology can be used as a guide to correct mistakes in transcriptional starting site (TSS) choices of proteins of Mycobacterium tuberculosis and Mycobacterium leprae, as well as to identify N-terminal peptides resulting from signal peptidase cleavages.

Systems biology promises to describe and model complete biological systems quantitatively. Recently, in many areas of biological research, focus has shifted from detailed characterization of an individual gene or gene function in terms of its effect on a cellular process (the reductionist approach) to understanding the behavior of networks of genes or gene products from a genome-wide perspective (the systems biology approach). Here we review how analyses that allowed genome-wide investigations (by mining and integrating data from various “omics”) have contributed to our understanding of biological processes from genes to networks. We will discuss these advances in terms of quantitative leaps in which the scope of a known process was only revealed by genome studies (e.g., fraction of genes with alternative transcription start sites, splicing isoforms, or protein isoforms) and qualitative leaps in which completely new phenomena have been revealed (e.g., dark matter in the genome, functional pseudogenes, scale-free protein networks, fluidity of microbial genomes, and the diversity of the microbiome). We will discuss what the future holds for systems biology in terms of unrealized leaps that may provide new surprises from the viewpoints of academic and biomedical research.

Recently, we developed a novel type of phosphate-affinity gel electrophoresis. The phosphate-affinity site is a polyacrylamide-bound dinuclear manganese(II) complex of a phosphate-binding tag nanomolecule, Phos-tag, which enables the mobility shift detection of phosphorylated proteins from their nonphosphorylated counterparts in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and the quantitative analysis of protein kinase and phosphatase reactions on a polyacrylamide gel without any special apparatuses, radioactive isotopes, or chemical labels. This review article summarizes four applications of protein phosphorylation profiling using a type of affinity electrophoresis, Mn2+-Phos-tag SDS-PAGE, as follows: i) in vitro kinase activity profiling for the analysis of the phosphoprotein isotypes derived from various kinase reactions, ii) in vivo kinase activity profiling for the analysis of extracellular signal-dependent protein phosphorylation, iii) in vitro kinase inhibition profiling for the quantitative analysis of a kinase-specific inhibitor, and iv) a two-dimensional mobility-shifting procedure using Mn2+-Phos-tag SDS-PAGE for the detailed analysis of phosphoprotein isotypes. In addition, we describe the significant advantages, including a higher resolution power for the separation of protein phosphoisotypes compared with the conventional gel-based electrophoresis methods. Protein phosphorylation profiling can provide the basis for understanding the molecular origins of diseases and potentially developing tools toward therapeutic intervention. Therefore, the phosphate-affinity gel electrophoresis methodologies established by using Phos-tag can greatly facilitate the phosphoproteomics for the determination of protein phosphorylation status in life science laboratories worldwide.

Proteomic analysis of clinical samples has been traditionally performed using fresh or frozen tissues. However, millions of embedded samples are stored worldwide in pathology repositories with linked long-term outcome data. Such samples are believed to be unsuitable for proteome analysis because of the extensive protein modification attained during tissue processing. Formaldehyde, in the form of buffered formalin, is the most commonly used fixative during processing before embedding in paraffin. These formalin-fixed paraffin embedded (FFPE) tissue samples are widely used in pathology labs for qualitative protein analysis using immunohistochemistry (IHC). For this purpose, FFPE tissues are treated in different ways in order to reverse chemical modifications by formaldehyde that limit protein antigen detection by specific antibodies. Accordingly, intensive research efforts are now attempting to adapt the sample pretreatments used in immunohistochemistry to facilitate high throughput proteome analysis of FFPE tissues. Two such approaches have been successful: a liquid-based proteomic approach and an in situ approach, mainly based on separation and identification technologies such as liquid chromatography and mass spectrometry. These efforts have proven that similar protein profiles and numbers of polypeptides can be attained as using frozen sections. In this article, a review is provided of methods and current trends for the extraction of peptides and proteins from FFPE tissues for use proteomic analysis. Limitations in these methods and future directions to overcome these are also outlined. Ongoing improvements in protein extraction technology and analysis techniques will enable identification of novel disease biomarkers from FFPE tissues.