DirecTag: accurate sequence tags from peptide MS/MS through statistical scoring

In shotgun proteomics, tandem mass spectra of peptides are typically identified through database search algorithms such as Sequest. We have developed DirecTag, an open-source algorithm to infer partial sequence tags directly from observed fragment ions. This algorithm is unique in its implementation of three separate scoring systems to evaluate each tag on the basis of peak intensity, m/ z fidelity, and complementarity. In data sets from several types of mass spectrometers, DirecTag reproducibly exceeded the accuracy and speed of InsPecT and GutenTag, two previously published algorithms for this purpose. The source code and binaries for DirecTag are available from http://fenchurch.mc.vanderbilt.edu.     

A randomised, blinded, placebo-controlled trial in dementia patients continuing or stopping neuroleptics (the DART-AD trial)

Background

There have been increasing concerns regarding the safety and efficacy of neuroleptics in people with dementia, but there are very few long-term trials to inform clinical practice. The aim of this study was to determine the impact of long-term treatment with neuroleptic agents upon global cognitive decline and neuropsychiatric symptoms in patients with Alzheimer disease.

Methods and Findings

Design: Randomised, blinded, placebo-controlled parallel two-group treatment discontinuation trial.Setting: Oxfordshire, Newcastle and Gateshead, London and Edinburgh, United Kingdom.Participants: Patients currently prescribed the neuroleptics thioridazine, chlorpromazine, haloperidol trifluoperazine or risperidone for behavioural or psychiatric disturbance in dementia for at least 3 mo.Interventions: Continue neuroleptic treatment for 12 mo or switch to an identical placebo.Outcome measures: Primary outcome was total Severe Impairment Battery (SIB) score. Neuropsychiatric symptoms were evaluated with the Neuropsychiatric Inventory (NPI).Results: 165 patients were randomised (83 to continue treatment and 82 to placebo, i.e., discontinue treatment), of whom 128 (78%) commenced treatment (64 continue/64 placebo). Of those, 26 were lost to follow-up (13 per arm), resulting in 51 patients per arm analysed for the primary outcome. There was no significant difference between the continue treatment and placebo groups in the estimated mean change in SIB scores between baseline and 6 mo; estimated mean difference in deterioration (favouring placebo) −0.4 (95% confidence interval [CI] −6.4 to 5.5), adjusted for baseline value (p = 0.9). For neuropsychiatric symptoms, there was no significant difference between the continue treatment and placebo groups (n = 56 and 53, respectively) in the estimated mean change in NPI scores between baseline and 6 mo; estimated mean difference in deterioration (favouring continue treatment) −2.4 (95% CI −8.2 to 3.5), adjusted for baseline value (p = 0.4). Both results became more pronounced at 12 mo. There was some evidence to suggest that those patients with initial NPI ≥ 15 benefited on neuropsychiatric symptoms from continuing treatment.

Conclusions

For most patients with AD, withdrawal of neuroleptics had no overall detrimental effect on functional and cognitive status. Neuroleptics may have some value in the maintenance treatment of more severe neuropsychiatric symptoms, but this benefit must be weighed against the side effects of therapy.Trial registration: Cochrane Central Registry of Controlled Trials/National Research Register (#ISRCTN33368770).     

C. elegans Model Identifies Genetic Modifiers of α-Synuclein Inclusion Formation During Aging

Inclusions in the brain containing α-synuclein are the pathological hallmark of Parkinson's disease, but how these inclusions are formed and how this links to disease is poorly understood. We have developed a C. elegans model that makes it possible to monitor, in living animals, the formation of α-synuclein inclusions. In worms of old age, inclusions contain aggregated α- synuclein, resembling a critical pathological feature. We used genome-wide RNA interference to identify processes involved in inclusion formation, and identified 80 genes that, when knocked down, resulted in a premature increase in the number of inclusions. Quality control and vesicle-trafficking genes expressed in the ER/Golgi complex and vesicular compartments were overrepresented, indicating a specific role for these processes in α-synuclein inclusion formation. Suppressors include aging-associated genes, such as sir-2.1/SIRT1 and lagr-1/LASS2. Altogether, our data suggest a link between α-synuclein inclusion formation and cellular aging, likely through an endomembrane-related mechanism. The processes and genes identified here present a framework for further study of the disease mechanism and provide candidate susceptibility genes and drug targets for Parkinson's disease and other α-synuclein related disorders.     

C. elegans Model Identifies Genetic Modifiers of ��-Synuclein Inclusion Formation During Aging

Inclusions in the brain containing α-synuclein are the pathological hallmark of Parkinson''s disease, but how these inclusions are formed and how this links to disease is poorly understood. We have developed a C. elegans model that makes it possible to monitor, in living animals, the formation of α-synuclein inclusions. In worms of old age, inclusions contain aggregated α- synuclein, resembling a critical pathological feature. We used genome-wide RNA interference to identify processes involved in inclusion formation, and identified 80 genes that, when knocked down, resulted in a premature increase in the number of inclusions. Quality control and vesicle-trafficking genes expressed in the ER/Golgi complex and vesicular compartments were overrepresented, indicating a specific role for these processes in α-synuclein inclusion formation. Suppressors include aging-associated genes, such as sir-2.1/SIRT1 and lagr-1/LASS2. Altogether, our data suggest a link between α-synuclein inclusion formation and cellular aging, likely through an endomembrane-related mechanism. The processes and genes identified here present a framework for further study of the disease mechanism and provide candidate susceptibility genes and drug targets for Parkinson''s disease and other α-synuclein related disorders.     

Propagation of protein glycation damage involves modification of tryptophan residues via reactive oxygen species: inhibition by pyridoxamine

Nonenzymatic modification of proteins is one of the key pathogenic factors in diabetic complications. Uncovering the mechanisms of protein damage caused by glucose is fundamental to understanding this pathogenesis and in the development of new therapies. We investigated whether the mechanism involving reactive oxygen species can propagate protein damage in glycation reactions beyond the classical modifications of lysine and arginine residues. We have demonstrated that glucose can cause specific oxidative modification of tryptophan residues in lysozyme and inhibit lysozyme activity. Furthermore, modification of tryptophan residues was also induced by purified albumin-Amadori, a ribose-derived model glycation intermediate. The AGE inhibitor pyridoxamine (PM) prevented the tryptophan modification, whereas another AGE inhibitor and strong carbonyl scavenger, aminoguanidine, was ineffective. PM specifically inhibited generation of hydroxyl radical from albumin-Amadori and protected tryptophan from oxidation by hydroxyl radical species. We conclude that oxidative degradation of either glucose or the protein-Amadori intermediate causes oxidative modification of protein tryptophan residues via hydroxyl radical and can affect protein function under physiologically relevant conditions. This oxidative stress-induced structural and functional protein damage can be ameliorated by PM via sequestration of catalytic metal ions and scavenging of hydroxyl radical, a mechanism that may contribute to the reported therapeutic effects of PM in the complications of diabetes.     

Mhc haplotype H6 is associated with sustained control of SIVmac251 infection in Mauritian cynomolgus macaques

The restricted diversity of the major histocompatibility complex (MHC) of Mauritian cynomolgus macaques provides powerful opportunities for insight into host-viral interactions and cellular immune responses that restrict lentiviral infections. However, little is known about the effects of Mhc haplotypes on control of SIV in this species. Using microsatellite-based genotyping and allele-specific PCR, Mhc haplotypes were deduced for 35 macaques infected with the same stock of SIVmac251. Class I haplotype H6 was associated with a reduction in chronic phase viraemia (p = 0.0145) while a similar association was observed for H6 class II (p = 0.0063). An increase in chronic phase viraemia, albeit an insignificant trend, was observed in haplotype H5-positive animals. These results further emphasise the value of genetically defined populations of non-human primates in AIDS research and provide a foundation for detailed characterisation of MHC restricted cellular immune responses and the effects of host genetics on SIV replication in cynomolgus macaques. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Role of CLASP2 in microtubule stabilization and the regulation of persistent motility

In motile fibroblasts, stable microtubules (MTs) are oriented toward the leading edge of cells. How these polarized MT arrays are established and maintained, and the cellular processes they control, have been the subject of many investigations. Several MT "plus-end-tracking proteins," or +TIPs, have been proposed to regulate selective MT stabilization, including the CLASPs, a complex of CLIP-170, IQGAP1, activated Cdc42 or Rac1, a complex of APC, EB1, and mDia1, and the actin-MT crosslinking factor ACF7. By using mouse embryonic fibroblasts (MEFs) in a wound-healing assay, we show here that CLASP2 is required for the formation of a stable, polarized MT array but that CLIP-170 and an APC-EB1 interaction are not essential. Persistent motility is also hampered in CLASP2-deficient MEFs. We find that ACF7 regulates cortical CLASP localization in HeLa cells, indicating it acts upstream of CLASP2. Fluorescence-based approaches show that GFP-CLASP2 is immobilized in a bimodal manner in regions near cell edges. Our results suggest that the regional immobilization of CLASP2 allows MT stabilization and promotes directionally persistent motility in fibroblasts.     

Bayesian Markov Random Field Analysis for Protein Function Prediction Based on Network Data

Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction are urgently needed. Established methods use sequence or structure similarity to infer functions but those types of data do not suffice to determine the biological context in which proteins act. Current high-throughput biological experiments produce large amounts of data on the interactions between proteins. Such data can be used to infer interaction networks and to predict the biological process that the protein is involved in. Here, we develop a probabilistic approach for protein function prediction using network data, such as protein-protein interaction measurements. We take a Bayesian approach to an existing Markov Random Field method by performing simultaneous estimation of the model parameters and prediction of protein functions. We use an adaptive Markov Chain Monte Carlo algorithm that leads to more accurate parameter estimates and consequently to improved prediction performance compared to the standard Markov Random Fields method. We tested our method using a high quality S.cereviciae validation network with 1622 proteins against 90 Gene Ontology terms of different levels of abstraction. Compared to three other protein function prediction methods, our approach shows very good prediction performance. Our method can be directly applied to protein-protein interaction or coexpression networks, but also can be extended to use multiple data sources. We apply our method to physical protein interaction data from S. cerevisiae and provide novel predictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and we evaluate the predictions using the available literature.