Nucleic acid recovery from complex environmental samples

Effective extraction of nucleic acid from environmental samples is an essential starting point in the molecular analysis of microbial communities in the environment. However, there are many different extraction methods in the literature and deciding which one is best suited to a particular sample is very difficult. This article details the important steps and choices in deciding how to extract nucleic acids from environmental samples and gives specific details of one method that has proven very successful at extracting DNA and RNA from a range of different samples.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

Complex formation of bovine serum albumin with a poly(ethylene glycol) lipid conjugate

In this work, we report the formation of complexes by self-assembly of bovine serum albumin (BSA) with a poly(ethylene glycol) lipid conjugate (PEG(2000)-PE) in phosphate saline buffer solution (pH 7.4). Three different sets of samples have been studied. The BSA concentration remained fixed (1, 0.01, or 0.001 wt % BSA) within each set of samples, while the PEG(2000)-PE concentration was varied. Dynamic light scattering (DLS), rheology, and small-angle X-ray scattering (SAXS) were used to study samples with 1 wt % BSA. DLS showed that BSA/PEG(2000)-PE aggregates have a size intermediate between a BSA monomer and a PEG(2000)-PE micelle. Rheology suggested that BSA/PEG(2000)-PE complexes might be surrounded by a relatively compact PEG-lipid shell, while SAXS results showed that depletion forces do not take an important role in the stabilization of the complexes. Samples containing 0.01 wt % BSA were studied by circular dichroism (CD) and ultraviolet fluorescence spectroscopy (UV). UV results showed that at low concentrations of PEG-lipid, PEG(2000)-PE binds to tryptophan (Trp) groups in BSA, while at high concentrations of PEG-lipid the Trp groups are exposed to water. CD results showed that changes in Trp environment take place with a minimal variation of the BSA secondary structure elements. Finally, samples containing 0.001 wt % BSA were studied by zeta-potential experiments. Results showed that steric interactions might play an important role in the stabilization of the BSA/PEG(2000)-PE complexes.

Synthesis of cationic water-soluble copolymers and hydrogels based on [2-(methacryloyloxy)ethyl]trimethylammonium cloride and 2-hydroxyethylacrylate and their complex formation with poly(acrylic acid)

Water-soluble cationic copolymers and hydrogels were synthesized by radical copolymerization of [2-(methacryloyloxy)ethyl]trimetilylammonium chloride (MADQUAT) and 2-hydroxyethylacrylate (HEA). The kinetics of copolymerization has been studied and the reactivity ratios were determined. It was found that MADQUAT exhibits higher reactivity in copolymerization. The complexation between linear MADQUAT-HEA and linear poly(acrylic acid) (PAA) has been studied in aqueous solutions at different pH. It results in the formation of insoluble polyelectrolyte complexes, whose composition and stability to aggregate depends on MADQUAT content in copolymers and pH. The hydrogels were synthesized by three-dimensional radical copolymerization of MADQUAT and HEA in the presence of a crosslinker. The effects of the feed mixture composition on yield and swelling properties of the hydrogels were studied. The interactions of these hydrogels with linear PAA result in formation of gel-polyelectrolyte complexes and contraction of the samples. It was found that the contraction depends on copolymer composition, PAA molecular weight, and solution pH. (c) 2006 Wiley Periodicals, Inc.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

Background: Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results: We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions: Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

A combined vacuum crushing and sieving (CVCS) system designed to determine noble gas palaeo-temperatures from stalagmite samples

This paper presents a novel extraction device for water and noble gases from speleothem samples for noble gas paleotemperature determination. The “combined vacuum crushing and sieving (CVCS) system” was designed to reduce the atmospheric noble gas contents from air inclusions in speleothem samples by up to 2 orders of magnitude without adsorbing atmospheric noble gases onto the freshly produced grain surfaces, a process that had often hampered noble gas temperature (NGT) determination in the past. We also present the results from first performance tests of the CVCS system processing stalagmite samples grown at a known temperature. This temperature is reliably reproduced by the NGTs derived from Ar, Kr, and Xe extracted from the samples. The CVCS system is, therefore, suitable for routine determinations of accurate NGTs. In combination with stalagmite dating, these NGTs will allow reconstructing past regional temperature evolutions, and also support the interpretation of the often complex stable isotope records preserved in the stalagmites' calcite.