Priming mass spectrometry-based sulfoglycomic mapping for identification of terminal sulfated lacdiNAc glycotope

In an effort to prime our mass spectrometry (MS)-based sulfoglycomic mapping platform technology for facile identification of sulfated lacdiNAc (GalNAcβ1-4GlcNAcβ1-), we have re-examined the N-glycans of bovine thyroid stimulating hormone. We showed that MALDI-MS mapping of permethylated glycans in negative ion mode can give an accurate representation of the sulfated glycans and, through MS/MS, diagnostic ions can be derived that we can collectively define the presence of a terminal sulfated lacdiNAc moiety at high sensitivity. Based on these ions, which can also be produced by nanoESI-MSⁿ, we demonstrated that the glycome of an ovarian carcinoma cell line, RMG-1, comprises a high abundance of sulfated lacdiNAc epitopes carried on multiantennary complex type N-glycans alongside fucosylated, sialylated and/or sulfated lacNAc antennae. This represents the first report of a natural glycomic occurrence of sulfated lacdiNAc on a cell line, as opposed to other better-characterized presence on secreted glycoproteins from a handful of sources. It is anticipated that with improved methods of detection such as that developed in this work, we are likely to identify a wider occurrence of sulfated lacdiNAc and be able to more accurately delineate the regulatory mechanism dictating the choice of a cell type in synthesizing sulfated, sialylated, fucosylated and/or non-substituted lacdiNAc.     

Multi-model recursive identification for nonlinear systems with non-uniformly sampling

A recursive least squares based on Multi-model is proposed for non-uniformly sampled-data nonlinear (NUSDN) systems. The corresponding state space model of an NUSDN system is derived using lifting technique. Taking advantage of the Fuzzy c-Mean Clustering algorithm, NUSDN is divided into several local models. The basic idea is that the NUSDN system is viewed as a model switching system under a given rule. Once the local models are identified, the global model is determined. A pH neutralization process validate the performance of the proposed algorithm.     

Decoupling dynamical systems for pathway identification from metabolic profiles

RATIONALE: Modern molecular biology is generating data of unprecedented quantity and quality. Particularly exciting for biochemical pathway modeling and proteomics are comprehensive, time-dense profiles of metabolites or proteins that are measurable, for instance, with mass spectrometry, nuclear magnetic resonance or protein kinase phosphorylation. These profiles contain a wealth of information about the structure and dynamics of the pathway or network from which the data were obtained. The retrieval of this information requires a combination of computational methods and mathematical models, which are typically represented as systems of ordinary differential equations. RESULTS: We show that, for the purpose of structure identification, the substitution of differentials with estimated slopes in non-linear network models reduces the coupled system of differential equations to several sets of decoupled algebraic equations, which can be processed efficiently in parallel or sequentially. The estimation of slopes for each time series of the metabolic or proteomic profile is accomplished with a 'universal function' that is computed directly from the data by cross-validated training of an artificial neural network (ANN). CONCLUSIONS: Without preprocessing, the inverse problem of determining structure from metabolic or proteomic profile data is challenging and computationally expensive. The combination of system decoupling and data fitting with universal functions simplifies this inverse problem very significantly. Examples show successful estimations and current limitations of the method. AVAILABILITY: A preliminary Web-based application for ANN smoothing is accessible at http://bioinformatics.musc.edu/webmetabol/. S-systems can be interactively analyzed with the user-friendly freeware PLAS (http://correio.cc.fc.ul.pt/~aenf/plas.html) or with the MATLAB module BSTLab (http://bioinformatics.musc.edu/bstlab/), which is currently being beta-tested.     

Biological pathway selection through nonlinear dimension reduction

In the analysis of high-throughput biological data, it is often believed that the biological units such as genes behave interactively by groups, that is, pathways in our context. It is conceivable that utilization of priorly available pathway knowledge would greatly facilitate both interpretation and estimation in statistical analysis of such high-dimensional biological data. In this article, we propose a 2-step procedure for the purpose of identifying pathways that are related to and influence the clinical phenotype. In the first step, a nonlinear dimension reduction method is proposed, which permits flexible within-pathway gene interactions as well as nonlinear pathway effects on the response. In the second step, a regularized model-based pathway ranking and selection procedure is developed that is built upon the summary features extracted from the first step. Simulations suggest that the new method performs favorably compared to the existing solutions. An analysis of a glioblastoma microarray data finds 4 pathways that have evidence of support from the biological literature.     

The power and the limitations of cross-species protein identification by mass spectrometry-driven sequence similarity searches

Mass spectrometry-driven BLAST (MS BLAST) is a database search protocol for identifying unknown proteins by sequence similarity to homologous proteins available in a database. MS BLAST utilizes redundant, degenerate, and partially inaccurate peptide sequence data obtained by de novo interpretation of tandem mass spectra and has become a powerful tool in functional proteomic research. Using computational modeling, we evaluated the potential of MS BLAST for proteome-wide identification of unknown proteins. We determined how the success rate of protein identification depends on the full-length sequence identity between the queried protein and its closest homologue in a database. We also estimated phylogenetic distances between organisms under study and related reference organisms with completely sequenced genomes that allow substantial coverage of unknown proteomes.     

Priming and elongation: dissection of the lipoteichoic acid biosynthetic pathway in Gram-positive bacteria

The biosynthesis of lipoteichoic acids is a potential target for the development of novel antimicrobials against significant Firmicute pathogens. Excellent progress has been made in recent years towards understanding the biochemistry and genetics of polyglycerophosphate lipoteichoic acid biosynthesis but it has remained unclear whether this pathway requires an initial ‘priming’ reaction to initiate synthesis on the glycolipid anchor. Recent work from the laboratory of Angelika Gründling, including a new study by Wörmann et al. in this issue of Molecular Microbiology, provides confirmation of the priming step and further insights into the functional redundancy of lipoteichoic acid biosynthesis enzymes in Bacillus subtilis.     

Priming: getting ready for battle

Infection of plants by necrotizing pathogens or colonization of plant roots with certain beneficial microbes causes the induction of a unique physiological state called "priming." The primed state can also be induced by treatment of plants with various natural and synthetic compounds. Primed plants display either faster, stronger, or both activation of the various cellular defense responses that are induced following attack by either pathogens or insects or in response to abiotic stress. Although the phenomenon has been known for decades, most progress in our understanding of priming has been made over the past few years. Here, we summarize the current knowledge of priming in various induced-resistance phenomena in plants.     

Mastering seeds for genomic size nucleotide BLAST searches

One of the most common activities in bioinformatics is the search for similar sequences. These searches are usually carried out with the help of programs from the NCBI BLAST family. As the majority of searches are routinely performed with default parameters, a question that should be addressed is how reliable the results obtained using the default parameter values are, i.e. what fraction of potential matches have been retrieved by these searches. Our primary focus is on the initial hit parameter, also known as the seed or word, used by the NCBI BLASTn, MegaBLAST and other similar programs in searches for similar nucleotide sequences. We show that the use of default values for the initial hit parameter can have a big negative impact on the proportion of potentially similar sequences that are retrieved. We also show how the hit probability of different seeds varies with the minimum length and similarity of sequences desired to be retrieved and describe methods that help in determining appropriate seeds. The experimental results described in this paper illustrate situations in which these methods are most applicable and also show the relationship between the various BLAST parameters.     

BlastR--fast and accurate database searches for non-coding RNAs

We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.