pinecone/core-2020-05-10-deduplication huggingface dataset:
Assessing Tolerance to Heavy-Metal Stress in Arabidopsis thaliana Seedlings

The deposited book chapter is a post-print version and has been submitted to peer review.The deposited book chapter version contains attached the supplementary materials within the pdf.This publication hasn't any creative commons license associated.The deposited book chapter is part of the book series:  "Environmental Responses in Plants: Methods and Protocols" (pp.197-208) published by Springer.Heavy-metal soil contamination is one of the major abiotic stress factors that, by negatively affecting plant growth and development, severely limit agricultural productivity worldwide. Plants have evolved various tolerance and detoxification strategies in order to cope with heavy-metal toxicity while ensuring adequate supply of essential micronutrients at the whole-plant as well as cellular levels. Genetic studies in the model plant Arabidopsis thaliana have been instrumental in elucidating such mechanisms. The root assay constitutes a very powerful and simple method to assess heavy-metal stress tolerance in Arabidopsis seedlings. It allows the simultaneous determination of all the standard growth parameters affected by heavy-metal stress (primary root elongation, lateral root development, shoot biomass, and chlorophyll content) in a single experiment. Additionally, this protocol emphasizes the tips and tricks that become particularly useful when quantifying subtle alterations in tolerance to a given heavy-metal stress, when simultaneously pursuing a large number of plant lines, or when testing sensitivity to a wide range of heavy metals for a single line.Fundação para a Ciência e a Tecnologia grants: (EXPL/AGR-PRO/1013/2013, SFRH/BPD/44640/2008); GREEN-it "Bioresources for Sustainability": (UID/Multi/04551/2013).info:eu-repo/semantics/publishedVersio
Generating High-Accuracy Peptide-Binding Data in High Throughput with Yeast Surface Display and SORTCERY

Library methods are widely used to study protein-protein interactions, and high-throughput screening or selection followed by sequencing can identify a large number of peptide ligands for a protein target. In this chapter, we describe a procedure called "SORTCERY" that can rank the affinities of library members for a target with high accuracy. SORTCERY follows a three-step protocol. First, fluorescence-activated cell sorting (FACS) is used to sort a library of yeast-displayed peptide ligands according to their affinities for a target. Second, all sorted pools are deep sequenced. Third, the resulting data are analyzed to create a ranking. We demonstrate an application of SORTCERY to the problem of ranking peptide ligands for the anti-apoptotic regulator Bcl-xL.National Institute of General Medical Sciences (U.S.) (Award GM096466
Single-molecule imaging to characterise the transport\ud
mechanism of the Nuclear Pore Complex

In the eukaryotic cell, a large macromolecular channel, known as the Nuclear Pore\ud
Complex (NPC), mediates all molecular transport between the nucleus and cytoplasm.\ud
In recent years, single-molecule fluorescence (SMF) imaging has emerged as a\ud
powerful tool to study the molecular mechanism of transport through the NPC. More\ud
recently, techniques such as Single-Molecule Localisation Microscopy (SMLM) have\ud
enabled the spatial and temporal distribution of cargos, transport receptors and even\ud
structural components of the NPC to be determined with nanometre accuracy. In this\ud
protocol, we describe a method to study the position and/or motion of individual\ud
molecules transiting through the NPC with high spatial and temporal precision
Gene Ontology: Pitfalls, Biases, and Remedies.

The Gene Ontology (GO) is a formidable resource, but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices
Visualizing and quantitating the spatiotemporal regulation of Ras/ERK signaling by dual-specificity mitogen-activated protein phosphatases (MKPs)

The spatiotemporal regulation of the Ras/ERK pathway is critical in determining the physiological and pathophysiological outcome of signaling. Dual-specificity mitogen-activated protein kinase (MAPK) phosphatases (DUSPs or MKPs) are key regulators of pathway activity and may also localize ERK to distinct subcellular locations. Here we present methods largely based on the use of high content microscopy to both visualize and quantitate the subcellular distribution of activated (p-ERK) and total ERK in populations of mouse embryonic fibroblasts derived from mice lacking DUSP5, a nuclear ERK-specific MKP. Such methods in combination with rescue experiments using adenoviral vectors encoding wild-type and mutant forms of DUSP5 have allowed us to visualize specific defects in ERK regulation in these cells thus confirming the role of this phosphatase as both a nuclear regulator of ERK activity and localization
A Simple Protocol for High Efficiency Protein Isolation After RNA Isolation from Mouse Thyroid and Other Very Small Tissue Samples.

As a dedicated hormone-secreting organ, the thyroid gland possesses a complement of proteostatic systems, including antioxidant, unfolded protein, and autophagic responses. The vast majority of animal investigations of thyroid physiology and, more recently, proteostasis, have utilized as model the rat, rather than the mouse. This is due to the very small size of the thyroid gland in the latter, with a total weight of ~2 mg (~1 mg per thyroid lobe). However, this strategy has limited the utilization of genetic approaches, such as taking advantage of the various transgenic and knockout mouse models. Here, we describe a simple and highly efficient protocol for the simultaneous isolation of mRNA, micro-RNA and 150-200 μg of protein from as little as 1 mg of mouse thyroid tissue, the average weight of one of the two thyroid lobes, thus preserving the other lobe for immunohistochemical or other analyses. While our workflow is similar to other protocols published in the literature and/or proposed by commercial reagent providers, we have introduced a key modification that addresses efficiently the most challenging step of the protein isolation process: the solubilization of the protein pellet after RNA extraction and protein precipitation. We demonstrate the feasibility of our approach and its utility for downstream analyses (including Western blotting) that facilitate the comparative study of proteostatic pathways in the mouse thyroid. We have also successfully applied this protocol on samples from mouse liver, brown and white adipose tissue, as well as from rodent cell lines
Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile

A fast accessible surface area (ASA) predictor is presented. In this new approach no residue mutation profiles generated by multiple sequence alignments are used as inputs. Instead, we use only single sequence information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction.Full Tex
QS-21 Adjuvant: Laboratory-Scale Purification Method and Formulation Into Liposomes.

QS-21, a saponin extracted from the tree Quillaja saponaria Molina, is a vaccine adjuvant which has been shown to elicit robust antibody and cell-mediated immune responses in a variety of preclinical and clinical studies [1]. Its purification from the natural source is a lengthy and difficult process. The commercially available saponin mixture Quil-A® is a fraction of the bark extract containing a variety of saponins, including QS-21. In order to facilitate access to QS-21 at laboratory-scale amounts, we propose here a method of purification of QS-21 starting from Quil-A®. In addition, we describe a protocol to appropriately formulate QS-21 into cholesterol-containing, neutral liposomes which are known to decrease QS-21's hemolytic activity while retaining the adjuvant effect. Methods for the physicochemical characterization of purified QS-21 and of the QS-21/liposome formulations are also described
Mutagenesis and genome engineering of Epstein-Barr virus in cultured human cells by CRISPR/Cas9

The clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated protein 9 nuclease (Cas9) system is a powerful genome-editing tool for both chromosomal and extrachromosomal DNA. DNA viruses such as Epstein–Barr virus (EBV), which undergoes episomal replication in human cells, can be effectively edited by CRISPR/Cas9. We have demonstrated targeted editing of the EBV genome by CRISPR/Cas9 in several lines of EBV-infected cells. CRISPR/Cas9-based mutagenesis and genome engineering of EBV provides a new method for genetic analysis, which has some advantages over bacterial artificial chromosome-based recombineering. This approach might also prove useful in the cure of EBV infection. In this chapter, we use the knockout of the BART promoter as an example to detail the experimental procedures for construction of recombinant EBV in human cells.postprin
High-Throughput N-Glycan Analysis with Rapid Magnetic Bead-Based Sample Preparation

N-glycan profi ling of therapeutic glycoproteins is essential to ensure the activity and effi cacy of these promising new-generation drugs. The N-linked glycan moieties of these entities highly affect circulation half- life, immunogenicity and receptor-binding activity as well as physicochemical and thermal stability properties. In addition, more than half of the biopharmaceuticals are glycoproteins representing multibillion dollar worldwide business, further emphasizing the importance of their analysis. In the biomedical fi eld, on the other hand, revealing disease-related glycan structure alterations holds the promise of the discovery of new biomarkers for early diagnostics. Therefore, there is a great demand for widely applicable, high-throughput sample preparation and analysis methods for N-glycan profi ling of glycoproteins. One of the newest exciting developments of the fi eld is the magnetic bead based glycoprotein sample preparation technique. A detailed protocol of this method is given in this chapter in conjunction with rapid capillary electrophoresis analysis of the prepared samples by laser induced fl uorescence detection (CE-LIF). N-glycans are digested by the endoglycosidase PNGase F and the released carbohydrates are labeled with the charged fl uorophore dye of aminopyrenetrisulfonate (APTS). Effective glycan capture by magnetic microparticles enabled fast, easily automated sample preparation both in individual (single vial) and 96-well plate formats, including excess dye removal. Rapid separation of APTS labeled IgG glycans is also shown utilizing an optimized CE-LIF protocol
Host-derived biomarkers for risk assessment of invasive fungal diseases

Host-Derived Biomarkers for Risk Assessment of Invasive Fungal DiseasesInvasive fungal diseases are major complications associated with the treatment of hematologic malignancies. The integration of host-derived biomarkers into clinical processes to predict the risk and progression of fungal disease is a promising approach in immunocompromised patients. Recent insights into human antifungal immunity have highlighted the remarkable influence of host genetics in modulating susceptibility to infection. In this chapter, we describe protocols to examine human genetic variation and to assess its functional consequences using the pattern recognition receptor PTX3 as an example.European Society of Clinical Microbiology and Infectious Diseases (Research Grant 2012 to A.C.) and the Fundação para a Ciência e Tecnologia (FCT) (SFRH/BPD/96176/2013 to C.C. and IF/00735/2014 to A.C.). Further support was provided by FCT, cofunded by Programa Operacional Regional do Norte (ON.2—O Novo Norte), the Quadro de Referência Estratégico Nacional (QREN) through the Fundo Europeu de Desenvolvimento Regional (FEDER), and the Projeto Estratégico PEst-C/SAU/LA0026/2013info:eu-repo/semantics/publishedVersio
Liposome formulations of hydrophobic drugs

Here we report methods of preparation for liposome formulations containing lipophilic drugs. In contrast to the encapsulation of water soluble compounds into the entrapped aqueous volume of a liposome, drugs with lipophilic properties are incorporated into the phospholipid bilayer membrane. Water-soluble molecules, for example cytotoxic or antiviral nucleosides can be transformed into lipophilic compounds by attachment of long alkyl chains, allowing their stable incorporation into liposome membranes and taking advantage of the high loading capacity lipid bilayers provide for lipophilic molecules. We created a new class of cytotoxic drugs by chemical transformation of the hydrophilic drugs cytosine-arabinoside (ara-C), 5-fluoro-deoxyuridine (5-FdU), and ethinylcytidine (ETC) into lipophilic compounds and their formulation in liposomes.The concept of chemical modification of water-soluble molecules by attachment of long alkyl chains and their stable incorporation into liposome bilayer membranes represent a very promising method for the development of new drugs not only for the treatment of tumors or infections but also for many other diseases
Cloning and expression of metagenomic DNA in Streptomyces lividans and subsequent fermentation for optimized production

The choice of an expression system for the metagenomic DNA of interest is of vital importance for the detection of any particular gene or gene cluster. Most of the screens to date have used the gram-negative bacterium Escherichia coli as a host for metagenomic gene libraries. However, the use of E. coli introduces a potential host bias since only 40 % of the enzymatic activities may be readily recovered by random cloning in E. coli. To recover some of the remaining 60 %, alternative cloning hosts such as Streptomyces spp. have been used. Streptomycetes are high-GC gram-positive bacteria belonging to the Actinomycetales and they have been studied extensively for more than 15 years as an alternative expression system. They are extremely well suited for the expression of DNA from other actinomycetes and genomes of high GC content. Furthermore, due to its high innate, extracellular secretion capacity, Streptomyces can be a better system than E. coli for the production of many extracellular proteins. In this article an overview is given about the materials and methods for growth and successful expression and secretion of heterologous proteins from diverse origin using Streptomyces lividans has a host. More in detail, an overview is given about the protocols of transformation, type of plasmids used and of vectors useful for integration of DNA into the host chromosome, and accompanying cloning strategies. In addition, various control elements for gene expression including synthetic promoters are discussed, and methods to compare their strength are described. Integration of the gene of interest under the control of the promoter of choice into S. lividans chromosome via homologous recombination using pAMR4-based system is explained. Finally a basic protocol for benchtop bioreactor experiments which can form the start in the production process optimization and upscaling is provided.status: publishe
Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model.National Institute of General Medical Sciences (U.S.) (Award R01 GM110048
Long Term Effects of Small Random Perturbations on Dynamical Systems:
  Theoretical and Computational Tools

Small random perturbations may have a dramatic impact on the long time
evolution of dynamical systems, and large deviation theory is often the right
theoretical framework to understand these effects. At the core of the theory
lies the minimization of an action functional, which in many cases of interest
has to be computed by numerical means. Here we review the theoretical and
computational aspects behind these calculations, and propose an algorithm that
simplifies the geometric minimum action method to minimize the action in the
space of arc-length parametrized curves. We then illustrate this algorithm's
capabilities by applying it to various examples from material sciences, fluid
dynamics, atmosphere/ocean sciences, and reaction kinetics. In terms of models,
these examples involve stochastic (ordinary or partial) differential equations
with multiplicative or degenerate noise, Markov jump processes, and systems
with fast and slow degrees of freedom, which all violate detailed balance, so
that simpler computational methods are not applicable
Entropy and thinning of discrete random variables

We describe five types of results concerning information and concentration of
discrete random variables, and relationships between them, motivated by their
counterparts in the continuous case. The results we consider are information
theoretic approaches to Poisson approximation, the maximum entropy property of
the Poisson distribution, discrete concentration (Poincar\'{e} and logarithmic
Sobolev) inequalities, monotonicity of entropy and concavity of entropy in the
Shepp--Olkin regime.Comment: Draft for Proceedings of IMA theme year in Discrete Structure
Structured Random Matrices

Random matrix theory is a well-developed area of probability theory that has
numerous connections with other areas of mathematics and its applications. Much
of the literature in this area is concerned with matrices that possess many
exact or approximate symmetries, such as matrices with i.i.d. entries, for
which precise analytic results and limit theorems are available. Much less well
understood are matrices that are endowed with an arbitrary structure, such as
sparse Wigner matrices or matrices whose entries possess a given variance
pattern. The challenge in investigating such structured random matrices is to
understand how the given structure of the matrix is reflected in its spectral
properties. This chapter reviews a number of recent results, methods, and open
problems in this direction, with a particular emphasis on sharp spectral norm
inequalities for Gaussian random matrices.Comment: 46 pages; to appear in IMA Volume "Discrete Structures: Analysis and
  Applications" (Springer
Rates of convergence for empirical spectral measures: a soft approach

Understanding the limiting behavior of eigenvalues of random matrices is the
central problem of random matrix theory. Classical limit results are known for
many models, and there has been significant recent progress in obtaining more
quantitative, non-asymptotic results. In this paper, we describe a systematic
approach to bounding rates of convergence and proving tail inequalities for the
empirical spectral measures of a wide variety of random matrix ensembles. We
illustrate the approach by proving asymptotically almost sure rates of
convergence of the empirical spectral measure in the following ensembles:
Wigner matrices, Wishart matrices, Haar-distributed matrices from the compact
classical groups, powers of Haar matrices, randomized sums and random
compressions of Hermitian matrices, a random matrix model for the Hamiltonians
of quantum spin glasses, and finally the complex Ginibre ensemble. Many of the
results appeared previously and are being collected and described here as
illustrations of the general method; however, some details (particularly in the
Wigner and Wishart cases) are new.
  Our approach makes use of techniques from probability in Banach spaces, in
particular concentration of measure and bounds for suprema of stochastic
processes, in combination with more classical tools from matrix analysis,
approximation theory, and Fourier analysis. It is highly flexible, as evidenced
by the broad list of examples. It is moreover based largely on "soft" methods,
and involves little hard analysis
Methods for Real-Time PCR-Based Diagnosis of Chlamydia pneumoniae, Chlamydia psittaci, and Chlamydia abortus Infections in an Opened Molecular Diagnostic Platform.

The advances in molecular biology of the last decades have dramatically improved the field of diagnostic bacteriology. In particular, PCR-based technologies have impacted the diagnosis of infections caused by obligate intracellular bacteria such as pathogens from the Chlamydiacae family. Here, we describe a real-time PCR-based method using the Taqman technology for the diagnosis of Chlamydia pneumoniae, Chlamydia psittaci, and Chlamydia abortus infection. The method presented here can be applied to various clinical samples and can be adapted on opened molecular diagnostic platforms
In vitro cryopreservation of date palm caulogenic meristems

Cryopreservation is the technology of choice not only for plant genetic resource preservation but also for virus eradication and for the efficient management of large-scale micropropagation. In this chapter, we describe three cryopreservation protocols (standard vitrification, droplet vitrification, and encapsulation vitrification) for date palm highly proliferating meristems that are initiated from vitro-cultures using plant growth regulator-free MS medium. The positive impact of sucrose preculture and cold hardening treatments on survival rates is significant. Regeneration rates obtained with standard vitrification, encapsulation-vitrification, and droplet-vitrification protocols can reach 30, 40, and 70%, respectively. All regenerated plants from non-cryopreserved or cryopreserved explants don't show morphological variation by maintaining genetic integrity without adverse effect of cryogenic treatment. Cryopreservation of date palm vitro-cultures enables commercial tissue culture laboratories to move to large-scale propagation from cryopreserved cell lines producing true-to-type plants after clonal field-testing trials. When comparing the cost of cryostorage and in-field conservation of date palm cultivars, tissue cryopreservation is the most cost-effective. Moreover, many of the risks linked to field conservation like erosion due to climatic, edaphic, and phytopathologic constraints are circumvented. (Résumé d'auteur