Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Tobacco smoking and somatic mutations in human bronchial epithelium

Tobacco smoking causes lung cancer, a process that is driven by more than 60 carcinogens in cigarette smoke that directly damage and mutate DNA. The profound effects of tobacco on the genome of lung cancer cells are well-documented, but equivalent data for normal bronchial cells are lacking. Here we sequenced whole genomes of 632 colonies derived from single bronchial epithelial cells across 16 subjects. Tobacco smoking was the major influence on mutational burden, typically adding from 1,000 to 10,000 mutations per cell; massively increasing the variance both within and between subjects; and generating several distinct mutational signatures of substitutions and of insertions and deletions. A population of cells in individuals with a history of smoking had mutational burdens that were equivalent to those expected for people who had never smoked: these cells had less damage from tobacco-specific mutational processes, were fourfold more frequent in ex-smokers than current smokers and had considerably longer telomeres than their more-mutated counterparts. Driver mutations increased in frequency with age, affecting 4–14% of cells in middle-aged subjects who had never smoked. In current smokers, at least 25% of cells carried driver mutations and 0–6% of cells had two or even three drivers. Thus, tobacco smoking increases mutational burden, cell-to-cell heterogeneity and driver mutations, but quitting promotes replenishment of the bronchial epithelium from mitotically quiescent cells that have avoided tobacco mutagenesis

TOM40 Mediates Mitochondrial Dysfunction Induced by α-Synuclein Accumulation in Parkinson's Disease.

Alpha-synuclein (α-Syn) accumulation/aggregation and mitochondrial dysfunction play prominent roles in the pathology of Parkinson's disease. We have previously shown that postmortem human dopaminergic neurons from PD brains accumulate high levels of mitochondrial DNA (mtDNA) deletions. We now addressed the question, whether alterations in a component of the mitochondrial import machinery -TOM40- might contribute to the mitochondrial dysfunction and damage in PD. For this purpose, we studied levels of TOM40, mtDNA deletions, oxidative damage, energy production, and complexes of the respiratory chain in brain homogenates as well as in single neurons, using laser-capture-microdissection in transgenic mice overexpressing human wildtype α-Syn. Additionally, we used lentivirus-mediated stereotactic delivery of a component of this import machinery into mouse brain as a novel therapeutic strategy. We report here that TOM40 is significantly reduced in the brain of PD patients and in α-Syn transgenic mice. TOM40 deficits were associated with increased mtDNA deletions and oxidative DNA damage, and with decreased energy production and altered levels of complex I proteins in α-Syn transgenic mice. Lentiviral-mediated overexpression of Tom40 in α-Syn-transgenic mice brains ameliorated energy deficits as well as oxidative burden. Our results suggest that alterations in the mitochondrial protein transport machinery might contribute to mitochondrial impairment in α-Synucleinopathies

Case-control study of sudden infant death syndrome in Lithuania, 1997–2000

BACKGROUND: To identify risk factors for sudden infant death syndrome relevant in Lithuania. METHODS: A nationwide case-control study surveying parents of 35 infants who died from sudden infant death syndrome during the period of 1997–2000 and parents of 145 control infants matched with SIDS infants for date of birth and for region of birth was carried out. RESULTS: Deaths incidence was greater in the warm period (60%) vs. cold period (40%). Prone and side sleeping positions both carried no increased risk of sudden infant death syndrome compared with supine because of a rare prone sleeping (4.1% of controls vs. 0% of dead infants) and more prevalent side than supine sleeping (84.8% of controls vs. 94.3% of dead infants) in the controls as well as the cases. Bed sharing for the whole night as a risk factor for sudden infant death syndrome has not been confirmed, either, as bed sharing was common only for the controls (13.8% of controls vs. 0% of dead infants). Routine sleeping environment factors such as heavy wrapping (≥4 togs) of an infant (odds ratio 8.49; 95% confidence interval 2.38 to 30.32), sleeping in a bassinet (4.22; 1.16 to 15.38) and maternal factors such as maternal education ≤12 years (4.48; 1.34 to 14.94), unplanned pregnancy (5.22; 1.49 to 18.18) and ≥2 previous live births (3.90; 1.00 to 15.10) were significantly associated with sudden infant death syndrome on multivariate analysis. CONCLUSION: The results of this first population-based case-control study have shed some light on the epidemiology of the syndrome in Lithuania. Although the mortality of sudden infant death syndrome in Lithuania is not high, it might be lowered moreover by public informing about sudden infant death syndrome and related risk factors. Special attention must be paid to mothers with low education on potentially modifiable risk factors such as routine heavy wrapping of an infant during sleep, routine sleeping in a bassinet and unplanned pregnancy

Graphical models for inferring single molecule dynamics

<p>Abstract</p> <p>Background</p> <p>The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM). The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET)<it> versus</it> time data, where the smFRET time series is modeled as a hidden Markov model (HMM) with Gaussian observables. A detailed description of smFRET is provided as well.</p> <p>Results</p> <p>The VBEM algorithm returns the model’s evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME), and the latter a description of the model’s parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML) optimized by the expectation maximization (EM) algorithm, the most important being a natural form of model selection and a well-posed (non-divergent) optimization problem.</p> <p>Conclusions</p> <p>The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics.</p

Database: The Journal of Biological Databases and Curation

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.Database URL: http://www.ensembl.org

High exposures to bioactivated cyclophosphamide are related to the occurrence of veno-occlusive disease of the liver following high-dose chemotherapy

We investigated whether the occurrence of veno-occlusive disease of the liver (VOD) may be associated with individual variations in the pharmacokinetics of high-dose cyclophosphamide. Patients received single or multiple courses of cyclophosphamide (1000 or 1500 mg m−2 day−1), thiotepa (80 or 120 mg m−2 day−1) and carboplatin (265–400 mg m−2 day−1) (CTC) for 4 consecutive days. The area under the plasma concentration–time curves (AUCs) were calculated for cyclophosphamide and its activated metabolites 4-hydroxycyclophosphamide and phosphoramide mustard based on multiple blood samples. Possible relationships between the AUCs and the occurrence of VOD were studied. A total of 59 patients (115 courses) were included. Four patients experienced VOD after a second CTC course. The first-course AUC of 4-hydroxycyclophosphamide (P=0.003) but not of phosphoramide mustard (P=0.101) appeared to be predictive of the occurrence of VOD after multiple courses. High exposures to bioactivated cyclophosphamide may lead to increased organ toxicity

Somatostatin Receptor 1 and 5 Double Knockout Mice Mimic Neurochemical Changes of Huntington's Disease Transgenic Mice

Selective degeneration of medium spiny neurons and preservation of medium sized aspiny interneurons in striatum has been implicated in excitotoxicity and pathophysiology of Huntington's disease (HD). However, the molecular mechanism for the selective sparing of medium sized aspiny neurons and vulnerability of projection neurons is still elusive. The pathological characteristic of HD is an extensive reduction of the striatal mass, affecting caudate putamen. Somatostatin (SST) positive neurons are selectively spared in HD and Quinolinic acid/N-methyl-D-aspartic acid induced excitotoxicity, mimic the model of HD. SST plays neuroprotective role in excitotoxicity and the biological effects of SST are mediated by five somatostatin receptor subtypes (SSTR1-5). and R6/2 mice. Conversely, the expression of somatostatin receptor subtypes, enkephalin and phosphatidylinositol 3-kinases were strain specific. SSTR1/5 appears to be important in regulating NMDARs, DARPP-32 and signaling molecules in similar fashion as seen in HD transgenic mice.This is the first comprehensive description of disease related changes upon ablation of G- protein coupled receptor gene. Our results indicate that SST and SSTRs might play an important role in regulation of neurodegeneration and targeting this pathway can provide a novel insight in understanding the pathophysiology of Huntington's disease

Selective laser melting–enabled electrospinning: Introducing complexity within electrospun membranes

Additive manufacturing technologies enable the creation of very precise and well-defined structures that can mimic hierarchical features of natural tissues. In this article, we describe the development of a manufacturing technology platform to produce innovative biodegradable membranes that are enhanced with controlled microenvironments produced via a combination of selective laser melting techniques and conventional electrospinning. This work underpins the manufacture of a new generation of biomaterial devices that have significant potential for use as both basic research tools and components of therapeutic implants. The membranes were successfully manufactured and a total of three microenvironment designs (niches) were chosen for thorough characterisation. Scanning electron microscopy analysis demonstrated differences in fibre diameters within different areas of the niche structures as well as differences in fibre density. We also showed the potential of using the microfabricated membranes for supporting mesenchymal stromal cell culture and proliferation. We demonstrated that mesenchymal stromal cells grow and populate the membranes penetrating within the niche-like structures. These findings demonstrate the creation of a very versatile tool that can be used in a variety of tissue regeneration applications including bone healing