A Modified Protocol for Bisulfite Genomic Sequencing of Difficult Samples

The bisulfite genomic sequencing protocol is a widely used method for analyzing DNA methylation. It relies on the deamination of unmethylated cytosine residues to uracil; however, its high rates of DNA degradation and incomplete cytosine to uracil conversion often lead to failed experiments, uninformative results, and false positives. Here, we report the addition of a single-step multiple restriction enzyme digestion (MRED) designed to differentially digest polymerase chain reaction products amplified from unconverted DNA while leaving those of converted DNA intact. We show that for our model system, RARB2 P2 promoter, use of MRED increased informative sequencings ninefold, and MRED did not alter the clonal representation in one fully methylated cell line, H-596, treated or not with 5-azadeoxycytidine, a methylation inhibitor. We believe that this method may easily be adapted for analyzing other genes and provide guidelines for selecting the most appropriate MRED restriction enzymes.     

A Widely Applicable Protocol for DNA Isolation from Fecal Samples

Feces are increasingly used as sources of DNA for genetic and ecological research. This paper describes a new method for isolation of DNA from animal feces. This method combines multiple purification steps, including pretreatment with ethanol and TE, an inhibitor-absorber made of starch, the CTAB method, the phenol-chloroform extraction method, and the guanidinium thiocyanate-silica method. The new method is efficient according to PCR results of 585 fecal samples from 23 species and costs much less than the commercial kits. The protocol can be tailored to the specific purpose of examining different diets of animals and can be performed with routine laboratory reagents.     

A Revised Iron Extraction Protocol for Environmental Samples Rich in Nitrite and Carbonate

Wet-chemical iron extraction is widely applied to quantify the mineral-bound ferriferous fraction of sediments and soils. As previously shown, this method is strongly affected by the composition of the soil/sediment. Samples enriched in mostly microbially produced nitrite require the removal of the nitrite-containing aqueous phase or the replacement of HCl with sulfamic acid (SA) as the extractant. In this study, we show that sedimentary carbonate buffers SA, inhibiting the stabilization of Fe(II) and effective extraction of iron. We therefore provide a revised extraction protocol which allows the preservation of low pH conditions, leading to efficient iron extraction in nitrite- and carbonate-enriched samples.     

An Optimized Protocol to Increase Virus-Induced Gene Silencing Efficiency and Minimize Viral Symptoms in Petunia

Virus-induced gene silencing (VIGS) is used to down-regulate endogenous plant genes. VIGS efficiency depends on viral proliferation and systemic movement throughout the plant. Although tobacco rattle virus (TRV)-based VIGS has been successfully used in petunia (Petunia?×?hybrida), the protocol has not been thoroughly optimized for efficient and uniform gene down-regulation in this species. Therefore, we evaluated six parameters that improved VIGS in petunia. Inoculation of mechanically wounded shoot apical meristems induced the most effective and consistent silencing compared to other methods of inoculation. From an evaluation of ten cultivars, a compact petunia variety, 'Picobella Blue', exhibited a 1.8-fold higher CHS silencing efficiency in corollas. We determined that 20 °C day/18 °C night temperatures induced stronger gene silencing than 23 °C/18 °C or 26 °C/18 °C. The development of silencing was more pronounced in plants that were inoculated at 3–4 versus 5 weeks after sowing. While petunias inoculated with pTRV2-NbPDS or pTRV2-PhCHS showed very minimal viral symptoms, plants inoculated with the pTRV2 empty vector (often used as a control) were stunted and developed severe necrosis, which often led to plant death. Viral symptoms were eliminated by developing a control construct containing a fragment of the green fluorescent protein (pTRV2-sGFP). These optimization steps increased the area of chalcone synthase (CHS) silencing by 69 % and phytoene desaturase (PDS) silencing by 28 %. This improved VIGS protocol, including the use of the pTRV2-sGFP control plants, provides stronger down-regulation for high-throughput analyses of gene function in petunia.     

The Use of Normobaric Hypoxic Training to Increase the Physical Working Capacity of Healthy Individuals

The study of the tolerability of a bicycle exercise test before and after normobaric hypoxic training (NHT) in different regimens was conducted to assess the influence of NHT on the state of the physical working capacity of healthy individuals. A biocybernetic approach allowing the assessment of the dynamics of the physiological variables during the performance of the load test was proposed for a detailed determination of the physiological cost of muscle activity. Hypoxic training was shown to significantly increase the tolerance of physical work, especially when more strenuous NHT regimes were used. The high information content of dynamic physiological criteria for assessing the physical working capacity was revealed.     

A Likelihood Approach to Populations Samples of Microsatellite Alleles

This paper presents a likelihood approach to population samples of microsatellite alleles. A Markov chain recursion method previously published by GRIFFITHS and TAVARE is applied to estimate the likelihood function under different models of microsatellite evolution. The method presented can be applied to estimate a fundamental population genetics parameter θ as well as parameters of the mutational model. The new likelihood estimator provides a better estimator of θ in terms of the mean square error than previous approaches. Furthermore, it is demonstrated how the method may easily be applied to test models of microsatellite evolution. In particular it is shown how to compare a one-step model of microsatellite evolution to a multi-step model by a likelihood ratio test.     

A Protocol to Infect Caenorhabditis elegans with Salmonella typhimurium

In the last decade, C. elegans has emerged as an invertebrate organism to study interactions between hosts and pathogens, including the host defense against gram-negative bacterium Salmonella typhimurium. Salmonella establishes persistent infection in the intestine of C. elegans and results in early death of infected animals. A number of immunity mechanisms have been identified in C. elegans to defend against Salmonella infections. Autophagy, an evolutionarily conserved lysosomal degradation pathway, has been shown to limit the Salmonella replication in C. elegans and in mammals. Here, a protocol is described to infect C. elegans with Salmonella typhimurium, in which the worms are exposed to Salmonella for a limited time, similar to Salmonella infection in humans. Salmonella infection significantly shortens the lifespan of C. elegans. Using the essential autophagy gene bec-1 as an example, we combined this infection method with C. elegans RNAi feeding approach and showed this protocol can be used to examine the function of C. elegans host genes in defense against Salmonella infection. Since C. elegans whole genome RNAi libraries are available, this protocol makes it possible to comprehensively screen for C. elegans genes that protect against Salmonella and other intestinal pathogens using genome-wide RNAi libraries.     

A Phase Function to Quantify Serial Dependence between Discrete Samples

Auto- and cross-correlation methods, when applied to discrete events, can determine periodicity and correlation times within and between event train sequences. However, if the number of available events for analysis is too few, the correlation techniques yield ambiguous and insufficient results. Here we report a technique based on measurements of phases of event times that could detect the periodicity even among very few discrete data points. The results are demonstrated on in vitro neuronal spike time data, and are found to be highly contrasting when compared with the correlation techniques. The technique could become invaluable, for example, for treating in vivo spike time records that often last very short duration, or for determining short timescales in discrete biophysical experimental data.     

A Highly Selective PCR Protocol for Detecting 16S rRNA Genes of the Genus Pseudomonas (Sensu Stricto) in Environmental Samples

Pseudomonas species are plant, animal, and human pathogens; exhibit plant pathogen-suppressing properties useful in biological control; or express metabolic versatilities valued in biotechnology and bioremediation. Specific detection of Pseudomonas species in the environment may help us gain a more complete understanding of the ecological significance of these microorganisms. The objective of this study was to develop a PCR protocol for selective detection of Pseudomonas (sensu stricto) in environmental samples. Extensive database searches identified a highly selective PCR primer pair for amplification of Pseudomonas 16S rRNA genes. A protocol that included PCR amplification and restriction analysis, a general cloning and sequencing strategy, and phylogenetic analyses was developed. The PCR protocol was validated by testing 50 target and 14 nontarget pure cultures, which confirmed the selectivity to 100%. Further validation used amplification of target sequences from purified bulk soil DNA followed by cloning of PCR products. Restriction analysis with HaeIII revealed eight different fragmentation patterns among 36 clones. Sequencing and phylogenetic analysis of 8 representative clones indicated that 91.7% of the products were derived from target organisms of the PCR protocol. Three patterns, representing only 8.3% of the 36 clones, were derived from non-Pseudomonas or chimeric PCR artifacts. Three patterns, representing 61.1% of the clones, clustered with sequences of confirmed Pseudomonas species, whereas two patterns, representing 30.6% of the clones, formed a novel phylogenetic cluster closely associated with Pseudomonas species. The results indicated that the Pseudomonas-selective PCR primers were highly specific and may represent a powerful tool for Pseudomonas population structure analyses and taxonomic confirmations.     

Bi-Epitope SPR Surfaces: A Solution to Develop Robust Immunoassays

Surface plasmon resonance (SPR)-based immunoassays have numerous applications and require high affinity reagents for sensitive and reliable measurements. We describe a quick approach to turn low affinity antibodies into appropriate capture reagents. We used antibodies recognizing human ephrin type A receptor 2 (EphA2) and a ProteOn XPR36 as a model system. We generated so-called ‘bi-epitope’ sensor surfaces by immobilizing various pairs of anti-EphA2 antibodies using standard amine coupling. The apparent binding affinities to EphA2 and EphA2 detection sensitivities of the bi-epitope and ‘single-epitope’ surfaces were then compared. For all antibody pairs tested, bi-epitope surfaces exhibited an ∼10–100-fold improvement in apparent binding affinities when compared with single-epitope ones. When pairing 2 antibodies of low intrinsic binding affinities (∼10⁻⁸ M) and fast dissociation rates (∼10⁻² s⁻¹), the apparent binding affinity and dissociation rate of the bi-epitope surface was improved up to ∼10^–10 M and 10⁻⁴ s⁻¹, respectively. This led to an ∼100–200-fold enhancement in EphA2 limit of detection in crude cell supernatants. Our results show that the use of antibody mixtures in SPR applications constitutes a powerful approach to develop sensitive immunoassays, as previously shown for non-SPR formats. As SPR-based assays have significantly expanded their reach in the last decade, such an approach promises to further accelerate their development.     

A Robust Classifier to Distinguish Noise from fMRI Independent Components

Analyzing Functional Magnetic Resonance Imaging (fMRI) of resting brains to determine the spatial location and activity of intrinsic brain networks–a novel and burgeoning research field–is limited by the lack of ground truth and the tendency of analyses to overfit the data. Independent Component Analysis (ICA) is commonly used to separate the data into signal and Gaussian noise components, and then map these components on to spatial networks. Identifying noise from this data, however, is a tedious process that has proven hard to automate, particularly when data from different institutions, subjects, and scanners is used. Here we present an automated method to delineate noisy independent components in ICA using a data-driven infrastructure that queries a database of 246 spatial and temporal features to discover a computational signature of different types of noise. We evaluated the performance of our method to detect noisy components from healthy control fMRI (sensitivity = 0.91, specificity = 0.82, cross validation accuracy (CVA) = 0.87, area under the curve (AUC) = 0.93), and demonstrate its generalizability by showing equivalent performance on (1) an age- and scanner-matched cohort of schizophrenia patients from the same institution (sensitivity = 0.89, specificity = 0.83, CVA = 0.86), (2) an age-matched cohort on an equivalent scanner from a different institution (sensitivity = 0.88, specificity = 0.88, CVA = 0.88), and (3) an age-matched cohort on a different scanner from a different institution (sensitivity = 0.72, specificity = 0.92, CVA = 0.79). We additionally compare our approach with a recently published method [1]. Our results suggest that our method is robust to noise variations due to population as well as scanner differences, thereby making it well suited to the goal of automatically distinguishing noise from functional networks to enable investigation of human brain function.     

A Lectin HPLC Method to Enrich Selectively-glycosylated Peptides from Complex Biological Samples

Glycans are an important class of post-translational modifications. Typically found on secreted and extracellular molecules, glycan structures signal the internal status of the cell. Glycans on tumor cells tend to have abundant sialic acid and fucose moieties. We propose that these cancer-associated glycan variants be exploited for biomarker development aimed at diagnosing early-stage disease. Accordingly, we developed a mass spectrometry-based workflow that incorporates chromatography on affinity matrices formed from lectins, proteins that bind specific glycan structures. The lectins Sambucus nigra (SNA) and Aleuria aurantia (AAL), which bind sialic acid and fucose, respectively, were covalently coupled to POROS beads (Applied Biosystems) and packed into PEEK columns for high pressure liquid chromatography (HPLC). Briefly, plasma was depleted of the fourteen most abundant proteins using a multiple affinity removal system (MARS-14; Agilent). Depleted plasma was trypsin-digested and separated into flow-through and bound fractions by SNA or AAL HPLC. The fractions were treated with PNGaseF to remove N-linked glycans, and analyzed by LC-MS/MS on a QStar Elite. Data were analyzed using Mascot software. The experimental design included positive controls—fucosylated and sialylated human lactoferrin glycopeptides—and negative controls—high mannose glycopeptides from Saccharomyces cerevisiae—that were used to monitor the specificity of lectin capture. Key features of this workflow include the reproducibility derived from the HPLC format, the positive identification of the captured and PNGaseF-treated glycopeptides from their deamidated Asn-Xxx-Ser/Thr motifs, and quality assessment using glycoprotein standards. Protocol optimization also included determining the appropriate ratio of starting material to column capacity, identifying the most efficient capture and elution buffers, and monitoring the PNGaseF-treatment to ensure full deglycosylation. Future directions include using this workflow to perform mass spectrometry-based discovery experiments on plasma from breast cancer patients and control individuals.     

A Simple Method to fix and Extract ATP from Rat Liver Samples

Abstract

A simple one-step method to fix and extract ATP from rat liver samples is described. The results show that this method is suitable for fixation and extraction of the hepatic ATP content, whereas its simplicity leads to consider it the procedure of choice.     

A New Rapid Protocol for Eyeblink Conditioning to Assess Cerebellar Motor Learning

Mice with spontaneous and induced mutations causing cerebellar phenotypes have provided key insights into how motor-related memories are stored in cerebellar circuits. Delayed eyeblink conditioning is a form of associative motor learning that depends on the cerebellum. However, neurochemical investigation of the underlying mechanisms has been hampered by the long training period (usually several days) required to establish conditioning. Here, we report a new rapid-training protocol that reliably induced delayed eyeblink conditioning within a single day. The associative memory formation depended on the expression of the δ2 glutamate receptor (GluD2) in cerebellar Purkinje cells. It lasted for several weeks, but could be erased by extinction sessions in a single day. In addition, using the rapid protocol, we found that eyeblink conditioning could be induced in juvenile mice at postnatal day 21, and that the Sindbis-virus-mediated expression of GluD2 could rescue the impaired eyeblink conditioning in GluD2-null mice in vivo.     

A New Nonparametric Approach to the Comparison of K Independent Samples of Response Curves

Two simultaneous distribution free test procedures to test the homogeneity of K samples of response curves measured at T points of time each are proposed which react upon the shape of the response curve. One procedure is based on the comparison of K T-tupels of FRIEDMAN-rank sums, the other on the comparison of K T × T-incidence tables, which first were introduced by KANNEMANN (1976). The application of the two procedures is illustrated by a numerical example. In the discussion the tests are compared with each other and with concurring tests.