Tandem mass spectrometry data quality assessment by self-convolution

<p>Abstract</p> <p>Background</p> <p>Many algorithms have been developed for deciphering the tandem mass spectrometry (MS) data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on <it>de novo </it>sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified.</p> <p>Results</p> <p>The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current) component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores.</p> <p>Conclusion</p> <p>We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the predicted results. We conclude that the algorithm performs well and could potentially be used as a pre-processing for all mass spectrometry based protein identification tools.</p

A mass accuracy sensitive probability based scoring algorithm for database searching of tandem mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has become one of the most used tools in mass spectrometry based proteomics. Various algorithms have since been developed to automate the process for modern high-throughput LC-MS/MS experiments.</p> <p>Results</p> <p>A probability based statistical scoring model for assessing peptide and protein matches in tandem MS database search was derived. The statistical scores in the model represent the probability that a peptide match is a random occurrence based on the number or the total abundance of matched product ions in the experimental spectrum. The model also calculates probability based scores to assess protein matches. Thus the protein scores in the model reflect the significance of protein matches and can be used to differentiate true from random protein matches.</p> <p>Conclusion</p> <p>The model is sensitive to high mass accuracy and implicitly takes mass accuracy into account during scoring. High mass accuracy will not only reduce false positives, but also improves the scores of true positive matches. The algorithm is incorporated in an automated database search program MassMatrix.</p

Biallelic loss of function variants in PPP1R21 cause a neurodevelopmental syndrome with impaired endocytic function

Next‐generation sequencing (NGS) has been instrumental in solving the genetic basis of rare inherited diseases, especially neurodevelopmental syndromes. However, functional workup is essential for precise phenotype definition and to understand the underlying disease mechanisms. Using whole exome (WES) and whole genome sequencing (WGS) in four independent families with hypotonia, neurodevelopmental delay, facial dysmorphism, loss of white matter, and thinning of the corpus callosum, we identified four previously unreported homozygous truncating PPP1R21 alleles: c.347delT p.(Ile116Lysfs*25), c.2170_2171insGGTA p.(Ile724Argfs*8), c.1607dupT p.(Leu536Phefs*7), c.2063delA p.(Lys688Serfs*26) and found that PPP1R21 was absent in fibroblasts of an affected individual, supporting the allele's loss of function effect. PPP1R21 function had not been studied except that a large scale affinity proteomics approach suggested an interaction with PIBF1 defective in Joubert syndrome. Our co‐immunoprecipitation studies did not confirm this but in contrast defined the localization of PPP1R21 to the early endosome. Consistent with the subcellular expression pattern and the clinical phenotype exhibiting features of storage diseases, we found patient fibroblasts exhibited a delay in clearance of transferrin‐488 while uptake was normal. In summary, we delineate a novel neurodevelopmental syndrome caused by biallelic PPP1R21 loss of function variants, and suggest a role of PPP1R21 within the endosomal sorting process or endosome maturation pathway

Urinary Aminopeptidase Activities as Early and Predictive Biomarkers of Renal Dysfunction in Cisplatin-Treated Rats

This study analyzes the fluorimetric determination of alanyl- (Ala), glutamyl- (Glu), leucyl-cystinyl- (Cys) and aspartyl-aminopeptidase (AspAp) urinary enzymatic activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats. Male Wistar rats (n = 8 each group) received a single subcutaneous injection of either saline or cisplatin 3.5 or 7 mg/kg, and urine samples were taken at 0, 1, 2, 3 and 14 days after treatment. In urine samples we determined Ala, Glu, Cys and AspAp activities, proteinuria, N-acetyl-β-D-glucosaminidase (NAG), albumin, and neutrophil gelatinase-associated lipocalin (NGAL). Plasma creatinine, creatinine clearance and renal morphological variables were measured at the end of the experiment. CysAp, NAG and albumin were increased 48 hours after treatment in the cisplatin 3.5 mg/kg treated group. At 24 hours, all urinary aminopeptidase activities and albuminuria were significantly increased in the cisplatin 7 mg/kg treated group. Aminopeptidase urinary activities correlated (p0.259) with plasma creatinine, creatinine clearance and/or kidney weight/body weight ratio at the end of the experiment and they could be considered as predictive biomarkers of renal injury severity. ROC-AUC analysis was made to study their sensitivity and specificity to distinguish between treated and untreated rats at day 1. All aminopeptidase activities showed an AUC>0.633. We conclude that Ala, Cys, Glu and AspAp enzymatic activities are early and predictive urinary biomarkers of the renal dysfunction induced by cisplatin. These determinations can be very useful in the prognostic and diagnostic of renal dysfunction in preclinical research and clinical practice.This study was supported by a grant (R1/12/2010/66) from the University of Jaén with the participation of Caja Rural of Jaén, and from the Carlos III Health Institute of the Spanish Ministry of Health and Consumer Affairs (Red de Investigación Renal, REDinREN RD06/0016/0017 and RD07/0016/2008), “FEDER una manera de hacer Europa.

Effects of Hydrogen Peroxide on Wound Healing in Mice in Relation to Oxidative Damage

10.1371/journal.pone.0049215PLoS ONE711

Human and mouse neuroinflammation markers in Niemann‐Pick disease, type C1

Niemann‐Pick disease, type C1 (NPC1) is an autosomal recessive lipid storage disorder in which a pathological cascade, including neuroinflammation occurs. While data demonstrating neuroinflammation is prevalent in mouse models, data from NPC1 patients is lacking. The current study focuses on identifying potential markers of neuroinflammation in NPC1 from both the Npc1 mouse model and NPC1 patients. We identified in the mouse model significant changes in expression of genes associated with inflammation and compared these results to the pattern of expression in human cortex and cerebellar tissue. From gene expression array analysis, complement 3 (C3) was increased in mouse and human post‐mortem NPC1 brain tissues. We also characterized protein levels of inflammatory markers in cerebrospinal fluid (CSF) from NPC1 patients and controls. We found increased levels of interleukin 3, chemokine (C‐X‐C motif) ligand 5, interleukin 16 and chemokine ligand 3 (CCL3), and decreased levels of interleukin 4, 10, 13 and 12p40 in CSF from NPC1 patients. CSF markers were evaluated with respect to phenotypic severity. Miglustat treatment in NPC1 patients slightly decreased IL‐3, IL‐10 and IL‐13 CSF levels; however, further studies are needed to establish a strong effect of miglustat on inflammation markers. The identification of inflammatory markers with altered levels in the cerebrospinal fluid of NPC1 patients may provide a means to follow secondary events in NPC1 disease during therapeutic trials.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147148/1/jimd0083.pd

Proteomics of industrial fungi: trends and insights for biotechnology

Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

<p>Abstract</p> <p>Background</p> <p>Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function.</p> <p>Results</p> <p>We experimentally annotated the bacterial pathogen <it>Salmonella </it>Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in <it>Salmonella </it>and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in <it>Salmonella </it>pathogenesis. We also characterized post-translational features in the <it>Salmonella </it>genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our <it>in vivo </it>proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.</p> <p>Conclusion</p> <p>This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of <it>Salmonella </it>as a resource for systems analysis.</p

Transcriptome Analysis of the Hippocampal CA1 Pyramidal Cell Region after Kainic Acid-Induced Status Epilepticus in Juvenile Rats

Molecular mechanisms involved in epileptogenesis in the developing brain remain poorly understood. The gene array approach could reveal some of the factors involved by allowing the identification of a broad scale of genes altered by seizures. In this study we used microarray analysis to reveal the gene expression profile of the laser microdissected hippocampal CA1 subregion one week after kainic acid (KA)-induced status epilepticus (SE) in 21-day-old rats, which are developmentally roughly comparable to juvenile children. The gene expression analysis with the Chipster software generated a total of 1592 differently expressed genes in the CA1 subregion of KA-treated rats compared to control rats. The KEGG database revealed that the identified genes were involved in pathways such as oxidative phosporylation (26 genes changed), and long-term potentiation (LTP; 18 genes changed). Also genes involved in Ca2+ homeostasis, gliosis, inflammation, and GABAergic transmission were altered. To validate the microarray results we further examined the protein expression for a subset of selected genes, glial fibrillary protein (GFAP), apolipoprotein E (apo E), cannabinoid type 1 receptor (CB1), Purkinje cell protein 4 (PEP-19), and interleukin 8 receptor (CXCR1), with immunohistochemistry, which confirmed the transcriptome results. Our results showed that SE resulted in no obvious CA1 neuronal loss, and alterations in the expression pattern of several genes during the early epileptogenic phase were comparable to previous gene expression studies of the adult hippocampus of both experimental epileptic animals and patients with temporal lobe epilepsy (TLE). However, some changes seem to occur after SE specifically in the juvenile rat hippocampus. Insight of the SE-induced alterations in gene expression and their related pathways could give us hints for the development of new target-specific antiepileptic drugs that interfere with the progression of the disease in the juvenile age group