RNA interference of three up-regulated transcripts associated with insecticide resistance in an imidacloprid resistant population of Leptinotarsa decemlineata

AbstractThe Colorado potato beetle, Leptinotarsa decemlineata (Say), is a major agricultural pest of potatoes in the Central Sands production region of Wisconsin. Previous studies have shown that populations of L. decemlineata have become resistant to many classes of insecticides, including the neonicotinoid insecticide, imidacloprid. Furthermore, L. decemlineata has multiple mechanisms of resistance to deal with a pesticide insult, including enhanced metabolic detoxification by cytochrome p450s and glutathione S-transferases. With recent advances in the transcriptomic analysis of imidacloprid susceptible and resistant L. decemlineata populations, it is possible to investigate the role of candidate genes involved in imidacloprid resistance. A recently annotated transcriptome analysis of L. decemlineata was obtained from select populations of L. decemlineata collected in the Central Sands potato production region, which revealed a subset of mRNA transcripts constitutively up-regulated in resistant populations. We hypothesize that a portion of the up-regulated transcripts encoding for genes within the resistant populations also encode for pesticide resistance and can be suppressed to re-establish a susceptible phenotype. In this study, a discrete set of three up-regulated targets were selected for RNA interference experiments using a resistant L. decemlineata population. Following the successful suppression of transcripts encoding for a cytochrome p450, a cuticular protein, and a glutathione synthetase protein in a select L. decemlineata population, we observed reductions in measured resistance to imidacloprid that strongly suggest these genes control essential steps in imidacloprid metabolism in these field populations

Precessing jets from a moving source and bright X-ray filaments in galaxy clusters

We present hydrodynamical calculations carried out with the 3D yguazu-a code of a precessing jet model, which interacts with a plane parallel wind. This scenario describes an extragalactic jet, in which the jet source is in motion with respect to the surrounding intra-cluster medium. From the numerical results, synthetic emission maps and spectra in X-ray band were obtained. We compare these predictions with observations of the radio jets emanating from the radio-galaxy 4C 26.42 (in the Abell 1795 galaxy cluster). We find that the general morphology of the radio jets can be described by a point-symmetric precessing jet system interacting with a plane parallel wind (i.e., the intra-cluster medium flowing past the galaxy). We also find that our synthetic X-ray emission maps reproduce the observed large scale structures (with sizes of the order of tens of kpc).Comment: Accepted for publication in A&A - 7 Pages, 6 figure

A variational method based on weighted graph states

In a recent article [Phys. Rev. Lett. 97 (2006), 107206], we have presented a class of states which is suitable as a variational set to find ground states in spin systems of arbitrary spatial dimension and with long-range entanglement. Here, we continue the exposition of our technique, extend from spin 1/2 to higher spins and use the boson Hubbard model as a non-trivial example to demonstrate our scheme.Comment: 36 pages, 13 figure

Unbinned maximum-likelihood estimators for low-count data: Applications to faint X-ray spectra in the Taurus Molecular Cloud

Traditional binned statistics such as $\chi^2$ suffer from information loss and arbitrariness of the binning procedure. We point out that the underlying statistical quantity (the log likelihood $L$) does not require any binning beyond the one implied by instrumental readout channels, and we propose to use it for low-count data. The performance of $L$ in the model classification and point estimation problems is explored by Monte-Carlo simulations of Chandra and XMM X-ray spectra, and is compared to the performances of the binned Poisson statistic ($C$), Pearson's $\chi^2$ and Neyman's $\chi^2_N$, the Kolmogorov- Smirnov, and Kuiper' statistics. It is found that the unbinned log likelihood $L$ performs best with regard to the expected chi-square distance between true and estimated spectra, the chance of a successful identification among discrete candidate models, the area under the receiver-operator curve of reduced (two-model) binary classification problems, and generally also with regard to the mean square errors of individual spectrum parameters. The $\chi^2$ ($\chi^2_{\rm N}$) statistics should only be used if more than 10 (15) predicted counts per bin are available. From the practical point of view, the computational cost of evaluating $L$ is smaller than for any of the alternative methods if the forward model is specified in terms of a Poisson intensity and normalization is a free parameter. The maximum-$L$ method is applied to 14 observations from the Taurus Molecular Cloud, and the unbinned results are compared to binned XSPEC results, and found to generally agree, with exceptions explained by instability under re-binning and by background fine structures. The maximum-$L$ method has no lower limit on the available counts, and allows to treat weak sources which are beyond the means of binned methods.Comment: accepted for publication in A&

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Assessing Recent Smoking Status by Measuring Exhaled Carbon Monoxide Levels

The main expectations of applying proteomics technologies to clinical questions are the discovery of disease related biomarkers. Despite technological advancement to increase proteome coverage and depth to meet these expectations the number of generated biomarkers for clinical use is small. One of the reasons is that found potential biomarkers often are false discoveries. Small sample sizes, in combination with patient sample heterogeneity increase the risk of false discoveries. To be able to extract relevant biological information from such data, high demands are put on the experimental design and the use of sensitive and quantitatively accurate technologies. The overall aim of this thesis was to apply quantitative proteomics methods for biomarker discovery in clinical samples. A method for reducing bias by controlling for individual variation in smoking habits is described in paper I. The aim of the method was objective assessment of recent smoking in clinical studies on inflammatory responses. In paper II, the proteome of alveolar macrophages obtained from smoking subjects with and without the inflammatory lung disease chronic obstructive pulmonary disease (COPD) were quantified by two-dimensional gel-electrophoresis (2-DE). A gender focused analysis showed protein level differences within the female group, with down-regulation of lysosomal pathway and up-regulation of oxidative pathway in COPD patients. Paper III, a mass spectrometry based proteomics analysis of tumour samples, contributes to the molecular understanding of vulvar squamous cell carcinoma (VSCC) and we identified a high risk patient subgroup of HPV-negative tumours based on the expression of four proteins, further suggesting that this subgroup is characterized by an altered ubiquitin-proteasome signalling pathway. Paper III describes a data analysis workflow for the extraction of biological information from quantitative mass spectrometry based proteomics data. High patient-to-patient tumour proteome variability was addressed by using pathway profiling on individual tumour data, followed by comparison of pathway association ranks in a multivariate analysis. We show that pathway data on individual tumour level can detect subpopulations of patients and identify pathways of specific importance in pre-defined clinical groups by the use of multivariate statistics. In paper IV, the potentials and limits of quantitative mass spectrometry on clinical samples was evaluated by defining the quantitative accuracy of isobaric labels and label-free quantification. Quantification by isobaric labels in combination with pI pre-fractionation showed a lower limit of quantification (LOQ) than a label-free analysis without pI pre-fractionation, and 6-plex TMT were more sensitive than 8-plex iTRAQ. Precursor mixing measured by isolation interference (MS1 interference) is more linked to the quantitative accuracy of isobaric labels than reporter ion interference (MS2 interference). Based on that we could define recommendations for how much isolation interference that can be accepted; in our data <30% isolation interference had little effect the quantitative accuracy. In conclusion, getting biological knowledge from proteomics studies requires a careful study design, control of possible confounding factors and the use of clinical data to identify disease subtypes. Further, to be able to draw conclusions from the data, the analysis requires accurate quantitative data and robust statistical tools to detect significant protein alterations. Methods around these issues are developed and discussed in this thesis

Direct immobilization of DNA probes on non-modified plastics by UV irradiation and integration in microfluidic devices for rapid bioassay

DNA microarrays have become one of the most powerful tools in the field of genomics and medical diagnosis. Recently, there has been increased interest in combining microfluidics with microarrays since this approach offers advantages in terms of portability, reduced analysis time, low consumption of reagents, and increased system integration. Polymers are widely used for microfluidic systems, but fabrication of microarrays on such materials often requires complicated chemical surface modifications, which hinders the integration of microarrays into microfluidic systems. In this paper, we demonstrate that simple UV irradiation can be used to directly immobilize poly(T)poly(C)-tagged DNA oligonucleotide probes on many different types of plastics without any surface modification. On average, five- and fourfold improvement in immobilization and hybridization efficiency have been achieved compared to surface-modified slides with aminated DNA probes. Moreover, the TC tag only costs 30% of the commonly used amino group modifications. Using this microarray fabrication technique, a portable cyclic olefin copolymer biochip containing eight individually addressable microfluidic channels was developed and used for rapid and parallel identification of Avian Influenza Virus by DNA hybridization. The one-step, cost-effective DNA-linking method on non-modified polymers significantly simplifies microarray fabrication procedures and permits great flexibility to plastic material selection, thus making it convenient to integrate microarrays into plastic microfluidic systems

Single-cell RNA-sequencing resolves self-antigen expression during mTEC development

The crucial capability of T cells for discrimination between self and non-self peptides is based on negative selection of developing thymocytes by medullary thymic epithelial cells (mTECs). The mTECs purge autoreactive T cells by expression of cell-type specific genes referred to as tissue-restricted antigens (TRAs). Although the autoimmune regulator (AIRE) protein is known to promote the expression of a subset of TRAs, its mechanism of action is still not fully understood. The expression of TRAs that are not under the control of AIRE also needs further characterization. Furthermore, expression patterns of TRA genes have been suggested to change over the course of mTEC development. Herein we have used single-cell RNA-sequencing to resolve patterns of TRA expression during mTEC development. Our data indicated that mTEC development consists of three distinct stages, correlating with previously described jTEC, mTEChi and mTEClo phenotypes. For each subpopulation, we have identified marker genes useful in future studies. Aire-induced TRAs were switched on during jTEC-mTEC transition and were expressed in genomic clusters, while otherwise the subsets expressed largely overlapping sets of TRAs. Moreover, population-level analysis of TRA expression frequencies suggested that such differences might not be necessary to achieve efficient thymocyte selection.RM is supported by a PhD Fellowship from the Fundação para a Ciência e Tecnologia, Portugal (SFRH/ BD/51950/2012). XZ is supported by an Advanced Postdoc Mobility Fellowship from the Swiss National Science Foundation (SNSF, grant number P300P2_151352). Part of the work was performed during XZ’s visit to the Simons Institute for the Theory of Computing. TL is supported by the Academy of Finland (Decision 311081). The authors would like to thank Bee Ling Ng and the staff of the Cytometry Core Facility, and Stephan Lorenz and the staff of the Single Cell Genomics Core Facility for their contribution. Mark Lynch is acknowledged for technical assistance with the Fluidigm C1 platform. Mike Stubbington and Kylie James are acknowledged for revising the language of the manuscript. We thank Sarah Teichmann for help and discussions regarding the manuscript.info:eu-repo/semantics/publishedVersio