MALDI Profiling of Human Lung Cancer Subtypes

Proteomics is expected to play a key role in cancer biomarker discovery. Although it has become feasible to rapidly analyze proteins from crude cell extracts using mass spectrometry, complex sample composition hampers this type of measurement. Therefore, for effective proteome analysis, it becomes critical to enrich samples for the analytes of interest. Despite that one-third of the proteins in eukaryotic cells are thought to be phosphorylated at some point in their life cycle, only a low percentage of intracellular proteins is phosphorylated at a given time.In this work, we have applied chromatographic phosphopeptide enrichment techniques to reduce the complexity of human clinical samples. A novel method for high-throughput peptide profiling of human tumor samples, using Parallel IMAC and MALDI-TOF MS, is described. We have applied this methodology to analyze human normal and cancer lung samples in the search for new biomarkers. Using a highly reproducible spectral processing algorithm to produce peptide mass profiles with minimal variability across the samples, lineal discriminant-based and decision tree–based classification models were generated. These models can distinguish normal from tumor samples, as well as differentiate the various non–small cell lung cancer histological subtypes.A novel, optimized sample preparation method and a careful data acquisition strategy is described for high-throughput peptide profiling of small amounts of human normal lung and lung cancer samples. We show that the appropriate combination of peptide expression values is able to discriminate normal lung from non-small cell lung cancer samples and among different histological subtypes. Our study does emphasize the great potential of proteomics in the molecular characterization of cancer

18S rRNA is a reliable normalisation gene for real time PCR based on influenza virus infected cells

Background: One requisite of quantitative reverse transcription PCR (qRT-PCR) is to normalise the data with an internal reference gene that is invariant regardless of treatment, such as virus infection. Several studies have found variability in the expression of commonly used housekeeping genes, such as beta-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), under different experimental settings. However, ACTB and GAPDH remain widely used in the studies of host gene response to virus infections, including influenza viruses. To date no detailed study has been described that compares the suitability of commonly used housekeeping genes in influenza virus infections. The present study evaluated several commonly used housekeeping genes [ACTB, GAPDH, 18S ribosomal RNA (18S rRNA), ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide (ATP5B) and ATP synthase, H+ transporting, mitochondrial Fo complex, subunit C1 (subunit 9) (ATP5G1)] to identify the most stably expressed gene in human, pig, chicken and duck cells infected with a range of influenza A virus subtypes. Results: The relative expression stability of commonly used housekeeping genes were determined in primary human bronchial epithelial cells (HBECs), pig tracheal epithelial cells (PTECs), and chicken and duck primary lung-derived cells infected with five influenza A virus subtypes. Analysis of qRT-PCR data from virus and mock infected cells using NormFinder and BestKeeper software programmes found that 18S rRNA was the most stable gene in HBECs, PTECs and avian lung cells. Conclusions: Based on the presented data from cell culture models (HBECs, PTECs, chicken and duck lung cells) infected with a range of influenza viruses, we found that 18S rRNA is the most stable reference gene for normalising qRT-PCR data. Expression levels of the other housekeeping genes evaluated in this study (including ACTB and GPADH) were highly affected by influenza virus infection and hence are not reliable as reference genes for RNA normalisation

Mechanochemical modeling of dynamic microtubule growth involving sheet-to-tube transition

Microtubule dynamics is largely influenced by nucleotide hydrolysis and the resultant tubulin configuration changes. The GTP cap model has been proposed to interpret the stabilizing mechanism of microtubule growth from the view of hydrolysis effects. Besides, the microtubule growth involves the closure of a curved sheet at its growing end. The curvature conversion also helps to stabilize the successive growth, and the curved sheet is referred to as the conformational cap. However, there still lacks theoretical investigation on the mechanical-chemical coupling growth process of microtubules. In this paper, we study the growth mechanisms of microtubules by using a coarse-grained molecular method. Firstly, the closure process involving a sheet-to-tube transition is simulated. The results verify the stabilizing effect of the sheet structure, and the minimum conformational cap length that can stabilize the growth is demonstrated to be two dimers. Then, we show that the conformational cap can function independently of the GTP cap, signifying the pivotal role of mechanical factors. Furthermore, based on our theoretical results, we describe a Tetris-like growth style of microtubules: the stochastic tubulin assembly is regulated by energy and harmonized with the seam zipping such that the sheet keeps a practically constant length during growth.Comment: 23 pages, 7 figures. 2 supporting movies have not been uploaded due to the file type restriction