Propeller‐Like Nanorod‐Upconversion Nanoparticle Assemblies with Intense Chiroptical Activity and Luminescence Enhancement in Aqueous Phase

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/133596/1/adma201601261-sup-0001-S1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133596/2/adma201601261_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133596/3/adma201601261.pd

The Effect of Pre-Analytical Variability on the Measurement of MRM-MS-Based Mid- to High-Abundance Plasma Protein Biomarkers and a Panel of Cytokines

Blood sample processing and handling can have a significant impact on the stability and levels of proteins measured in biomarker studies. Such pre-analytical variability needs to be well understood in the context of the different proteomics platforms available for biomarker discovery and validation. In the present study we evaluated different types of blood collection tubes including the BD P100 tube containing protease inhibitors as well as CTAD tubes, which prevent platelet activation. We studied the effect of different processing protocols as well as delays in tube processing on the levels of 55 mid and high abundance plasma proteins using novel multiple-reaction monitoring-mass spectrometry (MRM-MS) assays as well as 27 low abundance cytokines using a commercially available multiplexed bead-based immunoassay. The use of P100 tubes containing protease inhibitors only conferred proteolytic protection for 4 cytokines and only one MRM-MS-measured peptide. Mid and high abundance proteins measured by MRM are highly stable in plasma left unprocessed for up to six hours although platelet activation can also impact the levels of these proteins. The levels of cytokines were elevated when tubes were centrifuged at cold temperature, while low levels were detected when samples were collected in CTAD tubes. Delays in centrifugation also had an impact on the levels of cytokines measured depending on the type of collection tube used. Our findings can help in the development of guidelines for blood collection and processing for proteomic biomarker studies

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.</p> <p>Result</p> <p>We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.</p> <p>This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.</p> <p>Conclusions</p> <p>Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in <url>http://tools.proteomecenter.org/ATAQS/ATAQS.html</url></p

Interaction proteomics of synapse protein complexes

The brain integrates complex types of information, and executes a wide range of physiological and behavioral processes. Trillions of tiny organelles, the synapses, are central to neuronal communication and information processing in the brain. Synaptic transmission involves an intricate network of synaptic proteins that forms the molecular machinery underlying transmitter release, activation, and modulation of transmitter receptors and signal transduction cascades. These processes are dynamically regulated and underlie neuroplasticity, crucial to learning and memory formation. In recent years, interaction proteomics has increasingly been used to elucidate the constituents of synaptic protein complexes. Unlike classic hypothesis-based assays, interaction proteomics detects both known and novel interactors without bias. In this trend article, we focus on the technical aspects of recent proteomics to identify synapse protein complexes, and the complementary methods used to verify the protein–protein interaction. Moreover, we discuss the experimental feasibility of performing global analysis of the synapse protein interactome

Strong coupling between surface plasmon polaritons and Sulforhodamine 101 dye

We demonstrate a strong coupling between surface plasmon polaritons and Sulforhodamine 101 dye molecules. Dispersion curves for surface plasmon polaritons on samples with a thin layer of silver covered with Sulforhodamine 101 molecules embedded in SU-8 polymer are obtained experimentally by reflectometry measurements and compared to the dispersion of samples without molecules. Clear Rabi splittings, with energies up to 360 and 190 meV, are observed at the positions of the dye absorption maxima. The split energies are dependent on the number of Sulforhodamine 101 molecules involved in the coupling process. Transfer matrix and coupled oscillator methods are used to model the studied multilayer structures with a great agreement with the experiments. Detection of the scattered radiation after the propagation provides another way to obtain the dispersion relation of the surface plasmon polaritons and, thus, provides insight into dynamics of the surface plasmon polariton/dye interaction, beyond the refrectometry measurements

A Chemical Genetic Screen for Modulators of Asymmetrical 2,2′-Dimeric Naphthoquinones Cytotoxicity in Yeast

BACKGROUND: Dimeric naphthoquinones (BiQ) were originally synthesized as a new class of HIV integrase inhibitors but have shown integrase-independent cytotoxicity in acute lymphoblastic leukemia cell lines suggesting their use as potential anti-neoplastic agents. The mechanism of this cytotoxicity is unknown. In order to gain insight into the mode of action of binaphthoquinones we performed a systematic high-throughput screen in a yeast isogenic deletion mutant array for enhanced or suppressed growth in the presence of binaphthoquinones. METHODOLOGY/PRINCIPAL FINDINGS: Exposure of wild type yeast strains to various BiQs demonstrated inhibition of yeast growth with IC(50)s in the microM range. Drug sensitivity and resistance screens were performed by exposing arrays of a haploid yeast deletion mutant library to BiQs at concentrations near their IC(50). Sensitivity screens identified yeast with deletions affecting mitochondrial function and cellular respiration as having increased sensitivity to BiQs. Corresponding to this, wild type yeast grown in the absence of a fermentable carbon source were particularly sensitive to BiQs, and treatment with BiQs was shown to disrupt the mitochondrial membrane potential and lead to the generation of reactive oxygen species (ROS). Furthermore, baseline ROS production in BiQ sensitive mutant strains was increased compared to wild type and could be further augmented by the presence of BiQ. Screens for resistance to BiQ action identified the mitochondrial external NAD(P)H dehydrogenase, NDE1, as critical to BiQ toxicity and over-expression of this gene resulted in increased ROS production and increased sensitivity of wild type yeast to BiQ. CONCLUSIONS/SIGNIFICANCE: In yeast, binaphthoquinone cytotoxicity is likely mediated through NAD(P)H:quonine oxidoreductases leading to ROS production and dysfunctional mitochondria. Further studies are required to validate this mechanism in mammalian cells

Quantitative Mass Spectrometry Analysis Using PAcIFIC for the Identification of Plasma Diagnostic Biomarkers for Abdominal Aortic Aneurysm

BACKGROUND: Abdominal aortic aneurysm (AAA) is characterized by increased aortic vessel wall diameter (>1.5 times normal) and loss of parallelism. This disease is responsible for 1-4% mortality occurring on rupture in males older than 65 years. Due to its asymptomatic nature, proteomic techniques were used to search for diagnostic biomarkers that might allow surgical intervention under nonlife threatening conditions. METHODOLOGY/PRINCIPAL FINDINGS: Pooled human plasma samples of 17 AAA and 17 control patients were depleted of the most abundant proteins and compared using a data-independent shotgun proteomic strategy, Precursor Acquisition Independent From Ion Count (PAcIFIC), combined with spectral counting and isobaric tandem mass tags. Both quantitative methods collectively identified 80 proteins as statistically differentially abundant between AAA and control patients. Among differentially abundant proteins, a subgroup of 19 was selected according to Gene Ontology classification and implication in AAA for verification by Western blot (WB) in the same 34 individual plasma samples that comprised the pools. From the 19 proteins, 12 were detected by WB. Five of them were verified to be differentially up-regulated in individual plasma of AAA patients: adiponectin, extracellular superoxide dismutase, protein AMBP, kallistatin and carboxypeptidase B2. CONCLUSIONS/SIGNIFICANCE: Plasma depletion of high abundance proteins combined with quantitative PAcIFIC analysis offered an efficient and sensitive tool for the screening of new potential biomarkers of AAA. However, WB analysis to verify the 19 PAcIFIC identified proteins of interest proved inconclusive save for five proteins. We discuss these five in terms of their potential relevance as biological markers for use in AAA screening of population at risk

Reproducible Cancer Biomarker Discovery in SELDI-TOF MS Using Different Pre-Processing Algorithms

BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS) studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE) peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR) control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers

'Omic approaches to preventing or managing metastatic breast cancer

Early detection of metastasis-prone breast cancers and characterization of residual metastatic cancers are important in efforts to improve management of breast cancer. Applications of genome-scale molecular analysis technologies are making these complementary approaches possible by revealing molecular features uniquely associated with metastatic disease. Assays that reveal these molecular features will facilitate development of anatomic, histological and blood-based strategies that may enable detection prior to metastatic spread. Knowledge of these features also will guide development of therapeutic strategies that can be applied when metastatic disease burden is low, thereby increasing the probability of a curative response