Biomedical subjects

Maciej Lalowski

Publications and source records attributed to Maciej Lalowski.

6 recordsLinked to original sources

PubMed2006

Analytical model of peptide mass cluster centres with applications.

BACKGROUND: The elemental composition of peptides results in formation of distinct, equidistantly spaced clusters across the mass range. The property of peptide mass clustering is used to calibrate peptide mass lists, to identify and remove non-peptide peaks and for data reduction. RESULTS: We developed an analytical model of the peptide mass cluster centres. Inputs to the model included, the amino acid frequencies in the sequence database, the average length of the proteins in the database, the cleavage specificity of the proteolytic enzyme used and the cleavage probability. We examined the accuracy of our model by comparing it with the model based on an in silico sequence database digest. To identify the crucial parameters we analysed how the cluster centre location depends on the inputs. The distance to the nearest cluster was used to calibrate mass spectrometric peptide peak-lists and to identify non-peptide peaks. CONCLUSION: The model introduced here enables us to predict the location of the peptide mass cluster centres. It explains how the location of the cluster centres depends on the input parameters. Fast and efficient calibration and filtering of non-peptide peaks is achieved by a distance measure suggested by Wool and Smilansky.

Journal Article↗

PubMed2005

Transformation and other factors of the peptide mass spectrometry pairwise peak-list comparison process.

BACKGROUND: Biological Mass Spectrometry is used to analyse peptides and proteins. A mass spectrum generates a list of measured mass to charge ratios and intensities of ionised peptides, which is called a peak-list. In order to classify the underlying amino acid sequence, the acquired spectra are usually compared with synthetic ones. Development of suitable methods of direct peak-list comparison may be advantageous for many applications. RESULTS: The pairwise peak-list comparison is a multistage process composed of matching of peaks embedded in two peak-lists, normalisation, scaling of peak intensities and dissimilarity measures. In our analysis, we focused on binary and intensity based measures. We have modified the measures in order to comprise the mass spectrometry specific properties of mass measurement accuracy and non-matching peaks. We compared the labelling of peak-list pairs, obtained using different factors of the pairwise peak-list comparison, as being the same or different to those determined by sequence database searches. In order to elucidate how these factors influence the peak-list comparison we adopted an analysis of variance type method with the partial area under the ROC curve as a dependent variable. CONCLUSION: The analysis of variance provides insight into the relevance of various factors influencing the outcome of the pairwise peak-list comparison. For large MS/MS and PMF data sets the outcome of ANOVA analysis was consistent, providing a strong indication that the results presented here might be valid for many various types of peptide mass measurements.

Algorithms↗

PubMed2005

A human protein-protein interaction network: a resource for annotating the proteome.

Protein-protein interaction maps provide a valuable framework for a better understanding of the functional organization of the proteome. To detect interacting pairs of human proteins systematically, a protein matrix of 4456 baits and 5632 preys was screened by automated yeast two-hybrid (Y2H) interaction mating. We identified 3186 mostly novel interactions among 1705 proteins, resulting in a large, highly connected network. Independent pull-down and co-immunoprecipitation assays validated the overall quality of the Y2H interactions. Using topological and GO criteria, a scoring system was developed to define 911 high-confidence interactions among 401 proteins. Furthermore, the network was searched for interactions linking uncharacterized gene products and human disease proteins to regulatory cellular pathways. Two novel Axin-1 interactions were validated experimentally, characterizing ANP32A and CRMP1 as modulators of Wnt signaling. Systematic human protein interaction screens can lead to a more comprehensive understanding of protein function and cellular processes.

Axin Protein↗

PubMed2005

Calibration of mass spectrometric peptide mass fingerprint data without specific external or internal calibrants.

BACKGROUND: Peptide Mass Fingerprinting (PMF) is a widely used mass spectrometry (MS) method of analysis of proteins and peptides. It relies on the comparison between experimentally determined and theoretical mass spectra. The PMF process requires calibration, usually performed with external or internal calibrants of known molecular masses. RESULTS: We have introduced two novel MS calibration methods. The first method utilises the local similarity of peptide maps generated after separation of complex protein samples by two-dimensional gel electrophoresis. It computes a multiple peak-list alignment of the data set using a modified Minimum Spanning Tree (MST) algorithm. The second method exploits the idea that hundreds of MS samples are measured in parallel on one sample support. It improves the calibration coefficients by applying a two-dimensional Thin Plate Splines (TPS) smoothing algorithm. We studied the novel calibration methods utilising data generated by three different MALDI-TOF-MS instruments. We demonstrate that a PMF data set can be calibrated without resorting to external or relying on widely occurring internal calibrants. The methods developed here were implemented in R and are part of the BioConductor package mscalib available from http://www.bioconductor.org. CONCLUSION: The MST calibration algorithm is well suited to calibrate MS spectra of protein samples resulting from two-dimensional gel electrophoretic separation. The TPS based calibration algorithm might be used to correct systematic mass measurement errors observed for large MS sample supports. As compared to other methods, our combined MS spectra calibration strategy increases the peptide/protein identification rate by an additional 5-15%.

Algorithms↗

PubMed2004

A protein interaction network links GIT1, an enhancer of huntingtin aggregation, to Huntington's disease.

Analysis of protein-protein interactions (PPIs) is a valuable approach for characterizing proteins of unknown function. Here, we have developed a strategy combining library and matrix yeast two-hybrid screens to generate a highly connected PPI network for Huntington's disease (HD). The network contains 186 PPIs among 35 bait and 51 prey proteins. It revealed 165 new potential interactions, 32 of which were confirmed by independent binding experiments. The network also permitted the functional annotation of 16 uncharacterized proteins and facilitated the discovery of GIT1, a G protein-coupled receptor kinase-interacting protein, which enhances huntingtin aggregation by recruitment of the protein into membranous vesicles. Coimmunoprecipitations and immunofluorescence studies revealed that GIT1 and huntingtin associate in mammalian cells under physiological conditions. Moreover, GIT1 localizes to neuronal inclusions, and is selectively cleaved in HD brains, indicating that its distribution and function is altered during disease pathogenesis.

Adaptor Proteins, Signal Transducing↗

PubMed2003

Myotilin, the limb-girdle muscular dystrophy 1A (LGMD1A) protein, cross-links actin filaments and controls sarcomere assembly.

The assembly and maintenance of the muscle sarcomere requires a complex interplay of actin- and myosin-associated proteins. Myotilin is a thin filament-associated Z-disc protein that consists of two Ig-domains flanked by a unique serine-rich amino-terminus and a short carboxy-terminal tail. It binds to alpha-actinin and filamin c and is mutated in limb girdle muscular dystrophy 1A (LGMD1A). Here we show that myotilin also directly binds F-actin, efficiently cross-links actin filaments alone or in concert with alpha-actinin and prevents filament disassembly induced by Latrunculin A. Myotilin forms dimers via its carboxy-terminal half, which may be necessary for the actin-bundling activity. Overexpression of full-length myotilin but not the carboxy-terminal half induces formation of thick actin cables in non-muscle cells devoid of endogenous myotilin. The expression of myotilin in muscle cells is tightly regulated to the later stages of in vitro myofibrillogenesis, when preassembled myofibrils begin to align. Expression of either amino- or carboxy-terminally truncated myotilin fragments but not wild-type myotilin in differentiating myocytes leads to myofibril disarray. The disease association and functional characteristics indicate an indispensable role for myotilin in stabilization and anchorage of thin filaments, which may be a prerequisite for correct Z-disc organization.

Actin Cytoskeleton↗