The Effect of Using an Inappropriate Protein Database for Proteomic Data Analysis

A recent study by Bromenshenk et al., published in PLoS One (2010), used proteomic analysis to identify peptides purportedly of Iridovirus and Nosema origin; however the validity of this finding is controversial. We show here through re-analysis of a subset of this data that many of the spectra identified by Bromenshenk et al. as deriving from Iridovirus and Nosema proteins are actually products from Apis mellifera honey bee proteins. We find no reliable evidence that proteins from Iridovirus and Nosema are present in the samples that were re-analyzed. This article is also intended as a learning exercise for illustrating some of the potential pitfalls of analysis of mass spectrometry proteomic data and to encourage authors to observe MS/MS data reporting guidelines that would facilitate recognition of analysis problems during the review process

Extensive Crosstalk between O-GlcNAcylation and Phosphorylation Regulates Akt Signaling

O-linked N-acetylglucosamine glycosylations (O-GlcNAc) and O-linked phosphorylations (O-phosphate), as two important types of post-translational modifications, often occur on the same protein and bear a reciprocal relationship. In addition to the well documented phosphorylations that control Akt activity, Akt also undergoes O-GlcNAcylation, but the interplay between these two modifications and the biological significance remain unclear, largely due to the technique challenges. Here, we applied a two-step analytic approach composed of the O-GlcNAc immunoenrichment and subsequent O-phosphate immunodetection. Such an easy method enabled us to visualize endogenous glycosylated and phosphorylated Akt subpopulations in parallel and observed the inhibitory effect of Akt O-GlcNAcylations on its phosphorylation. Further studies utilizing mass spectrometry and mutagenesis approaches showed that O-GlcNAcylations at Thr 305 and Thr 312 inhibited Akt phosphorylation at Thr 308 via disrupting the interaction between Akt and PDK1. The impaired Akt activation in turn resulted in the compromised biological functions of Akt, as evidenced by suppressed cell proliferation and migration capabilities. Together, this study revealed an extensive crosstalk between O-GlcNAcylations and phosphorylations of Akt and demonstrated O-GlcNAcylation as a new regulatory modification for Akt signaling

Transforming Growth Factor: β Signaling Is Essential for Limb Regeneration in Axolotls

Axolotls (urodele amphibians) have the unique ability, among vertebrates, to perfectly regenerate many parts of their body including limbs, tail, jaw and spinal cord following injury or amputation. The axolotl limb is the most widely used structure as an experimental model to study tissue regeneration. The process is well characterized, requiring multiple cellular and molecular mechanisms. The preparation phase represents the first part of the regeneration process which includes wound healing, cellular migration, dedifferentiation and proliferation. The redevelopment phase represents the second part when dedifferentiated cells stop proliferating and redifferentiate to give rise to all missing structures. In the axolotl, when a limb is amputated, the missing or wounded part is regenerated perfectly without scar formation between the stump and the regenerated structure. Multiple authors have recently highlighted the similarities between the early phases of mammalian wound healing and urodele limb regeneration. In mammals, one very important family of growth factors implicated in the control of almost all aspects of wound healing is the transforming growth factor-beta family (TGF-β). In the present study, the full length sequence of the axolotl TGF-β1 cDNA was isolated. The spatio-temporal expression pattern of TGF-β1 in regenerating limbs shows that this gene is up-regulated during the preparation phase of regeneration. Our results also demonstrate the presence of multiple components of the TGF-β signaling machinery in axolotl cells. By using a specific pharmacological inhibitor of TGF-β type I receptor, SB-431542, we show that TGF-β signaling is required for axolotl limb regeneration. Treatment of regenerating limbs with SB-431542 reveals that cellular proliferation during limb regeneration as well as the expression of genes directly dependent on TGF-β signaling are down-regulated. These data directly implicate TGF-β signaling in the initiation and control of the regeneration process in axolotls

Repressive LTR Nucleosome Positioning by the BAF Complex Is Required for HIV Latency

The SWI/SNF BAF chromatin remodeling complex generates a repressive nucleosome structure at the HIV LTR conducive to establishment and maintenance of HIV latency, while PBAF augments HIV transcription

What determines cell size?

AbstractFirst paragraph (this article has no abstract) For well over 100 years, cell biologists have been wondering what determines the size of cells. In modern times, we know all of the molecules that control the cell cycle and cell division, but we still do not understand how cell size is determined. To check whether modern cell biology has made any inroads on this age-old question, BMC Biology asked several heavyweights in the field to tell us how they think cell size is controlled, drawing on a range of different cell types. The essays in this collection address two related questions - why does cell size matter, and how do cells control it

Matching cross-linked peptide spectra: only as good as the worse identification.

Chemical cross-linking mass spectrometry identifies interacting surfaces within a protein assembly through labeling with bifunctional reagents and identifying the covalently modified peptides. These yield distance constraints that provide a powerful means to model the three-dimensional structure of the assembly. Bioinformatic analysis of cross-linked data resulting from large protein assemblies is challenging because each cross-linked product contains two covalently linked peptides, each of which must be correctly identified from a complex matrix of potential confounders. Protein Prospector addresses these issues through a complementary mass modification strategy in which each peptide is searched and identified separately. We demonstrate this strategy with an analysis of RNA polymerase II. False discovery rates (FDRs) are assessed via comparison of cross-linking data to crystal structure, as well as by using a decoy database strategy. Parameters that are most useful for positive identification of cross-linked spectra are explored. We find that fragmentation spectra generally contain more product ions from one of the two peptides constituting the cross-link. Hence, metrics reflecting the quality of the spectral match to the less confident peptide provide the most discriminatory power between correct and incorrect matches. A support vector machine model was built to further improve classification of cross-linked peptide hits. Furthermore, the frequency with which peptides cross-linked via common acylating reagents fragment to produce diagnostic, cross-linker-specific ions is assessed. The threshold for successful identification of the cross-linked peptide product depends upon the complexity of the sample under investigation. Protein Prospector, by focusing the reliability assessment on the least confident peptide, is better able to control the FDR for results as larger complexes and databases are analyzed. In addition, when FDR thresholds are calculated separately for intraprotein and interprotein results, a further improvement in the number of unique cross-links confidently identified is achieved. These improvements are demonstrated on two previously published cross-linking datasets