Laboratory models for studying ectopic pregnancy

PURPOSE OF REVIEW: Understanding of the aetiology of tubal ectopic pregnancy (tEP) remains incomplete. We aim to summarize the latest advances in laboratory models of tEP that we believe will, ultimately, contribute to improving the diagnosis and management of the condition. RECENT FINDINGS: Progress in proteome pre-fractionation and multidimensional protein identification technology has proved particularly effective in identifying novel biomarkers of tEP. These, and related global proteomic and genomic approaches, have as yet to be fully exploited in this context but do have substantial potential to inform future hypothesis driven studies. The majority of data generated since 2009 to explain the aetiology of tEP continues to derive from descriptive human ex-vivo studies. In-vitro models of Fallopian tube ciliary and smooth muscle function have improved to a limited degree, on the back of continuing advances in imaging and data acquisition. We believe that the recent development of a primary human Fallopian tube epithelium culture system represents the most significant recent advance in laboratory models for studying ectopic pregnancy. There remain no good animal models of tEP. SUMMARY: The establishment of a viable animal model of tEP remains the key obstacle to a complete understanding the aetiology of the condition

A Systematic Analysis of Eluted Fraction of Plasma Post Immunoaffinity Depletion: Implications in Biomarker Discovery

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample

A novel strategy using MASCOT Distiller for analysis of cleavable isotope-coded affinity tag data to quantify protein changes in plasma

A novel strategy consisting of cleavable Isotope-Coded Affinity Tag (cICAT) combined with MASCOT Distiller was evaluated as a tool for the quantification of proteins in "abnormal" patient plasma, prepared by pooling samples from patients with acute stroke. Quantification of all light and heavy cICAT-labelled peptide ion pairs was obtained using MASCOT Distiller combined with a proprietary software. Peptides displaying differences were selected for identification by MS. These preliminary results show the promise of our approach to identify potential biomarkers