New method for ultrasonic Doppler probe angle determination

A new method is described to determine the Doppler probe angle using a standard pulsed Doppler; the technique is based on the determination of vessel position with respect to the skin surface. The transit times of ultrasound waves toward the vessel from multiple probe positions on the skin, the distance between probe positions, and the probe-skin angle are measured. Using the probe-skin angle and the slope of the regression curve, the vessel-skin angle is determined trigonometrically. Experimental results show high accuracy within a vessel-skin angle range of 5–40°.     

Cytochemical detection systems for in situ hybridization, and the combination with immunocytochemistry. ‘Who is still afraid of red, green and blue?’

Summary An overview is given of the different non-radioactive cytochemical detection methodologies that are currently utilized to localize nucleic acid sequences in chromosomes, cells and tissue sections. Dependent on the reporter molecule (fluorochrome, enzyme or hapten) that is used to modify the appropriate nucleic acid probe, and the sensitivity that is required, the in situ hybridized sequences can be detected either directly after hybridization or indirectly, using cytochemical detection and amplification layers. These may then contain antibody and/or avidin molecules conjugated to fluorochromes, enzymes or colloidial gold particles. Since the choice of a suitable probe-labelling method in combination with a fluorescence, enzyme cytochemical or immunogold-silver detection procedure is often determined by the user's own practical experience and applications, the different detection methodologies are compared with each other in detail with respect to sensitivity, resolution, applicability for multiple probe detection, and signal evaluation. Furthermore, procedures are reviewed for the combination of in situ hybridization with immunocytochemical detection of proteins and/or incorporated bromodeoxyuridine, which allow the simultaneous visualization of genomic phenotypic and/or cell cycle parameters in the same sample. Possible improvements with respect to sensitivity, specificity and multiplicity of the detection methods, which may be interesting for one's own experimental design, are finally being discussed.     

Optimization of probe coverage for high-resolution oligonucleotide aCGH

MOTIVATION: The resolution at which genomic alterations can be mapped by means of oligonucleotide aCGH (array-based comparative genomic hybridization) is limited by two factors: the availability of high-quality probes for the target genomic sequence and the array real-estate. Optimization of the probe selection process is required for arrays that are designed to probe specific genomic regions in very high resolution without compromising probe quality constraints. RESULTS: In this paper we describe a well-defined optimization problem associated with the problem of probe selection for high-resolution aCGH arrays. We propose the whenever possible in-cover as a formulation that faithfully captures the requirement of probe selection problem, and provide a fast randomized algorithm that solves the optimization problem in O(n logn) time, as well as a deterministic algorithm with the same asymptotic performance. We apply the method in a typical high-definition array design scenario and demonstrate its superiority with respect to alternative approaches. AVAILABILITY: Address requests to the authors.     

Model-based probe set optimization for high-performance microarrays

A major challenge in microarray design is the selection of highly specific oligonucleotide probes for all targeted genes of interest, while maintaining thermodynamic uniformity at the hybridization temperature. We introduce a novel microarray design framework (Thermodynamic Model-based Oligo Design Optimizer, TherMODO) that for the first time incorporates a number of advanced modelling features: (i) A model of position-dependent labelling effects that is quantitatively derived from experiment. (ii) Multi-state thermodynamic hybridization models of probe binding behaviour, including potential cross-hybridization reactions. (iii) A fast calibrated sequence-similarity-based heuristic for cross-hybridization prediction supporting large-scale designs. (iv) A novel compound score formulation for the integrated assessment of multiple probe design objectives. In contrast to a greedy search for probes meeting parameter thresholds, this approach permits an optimization at the probe set level and facilitates the selection of highly specific probe candidates while maintaining probe set uniformity. (v) Lastly, a flexible target grouping structure allows easy adaptation of the pipeline to a variety of microarray application scenarios. The algorithm and features are discussed and demonstrated on actual design runs. Source code is available on request.     

A nested array of rRNA targeted probes for the detection and identification of enterococci by reverse hybridization

Complete 23S and almost complete 16S rRNA gene sequences were determined for the type strains of the validly described Enterococcus species, Melissococcus pluton and Tetragenococcus halophilus. A comprehensive set of rRNA targeted specific oligonucleotide hybridization probes was designed according to the multiple probe concept. In silico probe design and evaluation was performed using the respective tools of the ARB program package in combination with the ARB databases comprising the currently available 16S as well as 23S rRNA primary structures. The probes were optimized with respect to their application for reverse hybridization in microplate format. The target comprising 16S and 23S rDNA was amplified and labeled by PCR (polymerase chain reaction) using general primers targeting a wide spectrum of bacteria. Alternatively, amplification of two adjacent rDNA fragments of enterococci was performed by using specific primers. In vitro evaluation of the probe set was done including all Enterococcus type strains, and a selection of other representatives of the gram-positive bacteria with a low genomic DNA G+C content. The optimized probe set was used to analyze enriched drinking water samples as well as original samples from waste water treatment plants.     

基于组合探针识别的大规模细菌分类16 S rRNA基因芯片设计

随着16 S rRNA序列资源的不断丰富,以及寡核苷酸微阵列基因芯片技术的不断进步,检测复杂微生物菌落中的微生物种群构成成为可能．现有的序列特异性探针设计算法缺乏足够的覆盖度、灵活性以及效率,不能满足大规模细菌检测基因芯片的设计要求．很多组特异性探针设计算法的思路多局限于针对某个目标序列组设计唯一的组特异性探针．在很多应用场合,设计单个探针检测组内所有目标序列的目标是很难达到的．因此,设计多个探针通过组合方式进行检测是很有必要的．每个探针能特异性地检测组内一部分目标序列,通过组合就能提高覆盖率．然而,在所有可能的探针组合中找到一个优化的探针组合是很耗时的．提出了一个可行的基于相对熵和遗传算法的组合探针设计算法．     

Evaluating oligonucleotide properties for DNA microarray probe design

Most current microarray oligonucleotide probe design strategies are based on probe design factors (PDFs), which include probe hybridization free energy (PHFE), probe minimum folding energy (PMFE), dimer score, hairpin score, homology score and complexity score. The impact of these PDFs on probe performance was evaluated using four sets of microarray comparative genome hybridization (aCGH) data, which included two array manufacturing methods and the genomes of two species. Since most of the hybridizing DNA is equimolar in CGH data, such data are ideal for testing the general hybridization properties of almost all candidate oligonucleotides. In all our data sets, PDFs related to probe secondary structure (PMFE, hairpin score and dimer score) are the most significant factors linearly correlated with probe hybridization intensities. PHFE, homology and complexity score are correlating significantly with probe specificities, but in a non-linear fashion. We developed a new PDF, pseudo probe binding energy (PPBE), by iteratively fitting dinucleotide positional weights and dinucleotide stacking energies until the average residue sum of squares for the model was minimized. PPBE showed a better correlation with probe sensitivity and a better specificity than all other PDFs, although training data are required to construct a PPBE model prior to designing new oligonucleotide probes. The physical properties that are measured by PPBE are as yet unknown but include a platform-dependent component. A practical way to use these PDFs for probe design is to set cutoff thresholds to filter out bad quality probes. Programs and correlation parameters from this study are freely available to facilitate the design of DNA microarray oligonucleotide probes.     

Comprehensive aligned sequence construction for automated design of effective probes (CASCADE-P) using 16S rDNA

MOTIVATION: Prokaryotic organisms have been identified utilizing the sequence variation of the 16S rRNA gene. Variations steer the design of DNA probes for the detection of taxonomic groups or specific organisms. The long-term goal of our project is to create probe arrays capable of identifying 16S rDNA sequences in unknown samples. This necessitated the authentication, categorization and alignment of the >75 000 publicly available '16S' sequences. Preferably, the entire process should be computationally administrated so the aligned collection could periodically absorb 16S rDNA sequences from the public records. A complete multiple sequence alignment would provide a foundation for computational probe selection and facilitates microbial taxonomy and phylogeny. RESULTS: Here we report the alignment and similarity clustering of 62 662 16S rDNA sequences and an approach for designing effective probes for each cluster. A novel alignment compression algorithm, NAST (Nearest Alignment Space Termination), was designed to produce the uniform multiple sequence alignment referred to as the prokMSA. From the prokMSA, 9020 Operational Taxonomic Units (OTUs) were found based on transitive sequence similarities. An automated approach to probe design was straightforward using the prokMSA clustered into OTUs. As a test case, multiple probes were computationally picked for each of the 27 OTUs that were identified within the Staphylococcus Group. The probes were incorporated into a customized microarray and were able to correctly categorize Staphylococcus aureus and Bacillus anthracis into their correct OTUs. Although a successful probe picking strategy is outlined, the main focus of creating the prokMSA was to provide a comprehensive, categorized, updateable 16S rDNA collection useful as a foundation for any probe selection algorithm.     

Synthesis of a highly metal-selective rhodamine-based probe and its use for the in vivo monitoring of mercury

This protocol describes detailed procedures for the preparation of a rhodamine-based mercury probe and for its applications to the detection of mercury in cells and vertebrate organisms. The mercury probe 1, which is prepared in two steps from rhodamine 6G, responds rapidly to Hg2+ in aqueous solutions with a 1:1 stoichiometry. Owing to the fact that the probe reacts with Hg2+ in an irreversible manner, it has advantages over other reversible mercury probes in in vivo assays with respect to both sensitivity and selectivity. In addition, fluorescent imaging assays of Hg2+ in live cells and zebrafish by using this mercury probe are detailed in this protocol. The approximate time frame for the preparation of the probe is 24 h and for its use in imaging assays is 1.5 h.     

Recognition of thymine by triazine fluorescent probe through intermolecular multiple hydrogen bonding

In order to design a fluorescent probe with a long wavelength and multiple hydrogen bond sites for thymine, 3-(4-chloro-6-methylamino-1,3,5-triazinylamino)-7-dimethylamino-2-methylphenazine is synthesized by subsequently reacting neutral red and methylamine with cyanuric chloride. Its recognition behavior for thymine and its spectroscopic properties in different solvents are studied. The probe's fluorescence can be selectively quenched by thymine instead of guanine, indicating that fully complementary hydrogen bonding plays a key role in such recognition processes. In addition, the recognition mechanism of the probe for thymine and the bathochromic shift of its fluorescence spectra with the solvent polarity are also discussed.     

Application of multiple response optimization design to quantum dot-encoded microsphere bioconjugates hybridization assay

The optimization of DNA hybridization for genotyping assays is a complex experimental problem that depends on multiple factors such as assay formats, fluorescent probes, target sequence, experimental conditions, and data analysis. Quantum dot-doped particle bioconjugates have been previously described as fluorescent probes to identify single nucleotide polymorphisms even though this advanced fluorescent material has shown structural instability in aqueous environments. To achieve the optimization of DNA hybridization to quantum dot-doped particle bioconjugates in suspension while maximizing the stability of the probe materials, a nonsequential optimization approach was evaluated. The design of experiment with response surface methodology and multiple optimization response was used to maximize the recovery of fluorescent probe at the end of the assay simultaneously with the optimization of target–probe binding. Hybridization efficiency was evaluated by the attachment of fluorescent oligonucleotides to the fluorescent probe through continuous flow cytometry detection. Optimal conditions were predicted with the model and tested for the identification of single nucleotide polymorphisms. The design of experiment has been shown to significantly improve biochemistry and biotechnology optimization processes. Here we demonstrate the potential of this statistical approach to facilitate the optimization of experimental protocol that involves material science and molecular biology.     

An efficient technique for estimating the two-dimensional temperature distributions around multiple cryo-surgical probes based on combining contributions of unit circles

This study presents an efficient, fast and accurate method for estimating the two-dimensional temperature distributions around multiple cryo-surgical probes. The identical probes are inserted into the same depth and are operated simultaneously and uniformly. The first step in this method involves numerical derivation of the temporal performance data of a single probe, embedded in a semi-infinite, tissue-like medium. The results of this derivation are approximated by algebraic expressions that form the basis for computing the temperature distributions of multiple embedded probes by combining the data of a single probe. Comparison of isothermal contours derived by this method to those computed numerically for a variety of geometrical cases, up to 15 inserted probes and 2–10 min times of operation, yielded excellent results. Since this technique obviates the solution of the differential equations of multiple probes, the computational time required for a particular case is several orders of magnitude shorter than that needed for obtaining the full numerical solution. Blood perfusion and metabolic heat generation rates are demonstrated to inhibit the advancement of isothermal fronts. Application of this method will significantly shorten computational times without compromising the accuracy of the results. It may also facilitate expeditious consideration of the advantages of different modes of operation and the number of inserted probes at the early design stage.     

SARS病毒再测序DNA微阵列的探针设计

探针设计是SARS病毒再测序DNA微阵列制作的关键步骤,为了保证探针的杂交条件尽可能一致,采用了作者提出的两种等长变覆盖的探针设计方法,即基于Tm距离的算法和遗传算法。针对SAILS病毒基因组中的两段特异序列设计了一组探针,并与等长移位法和变长变覆盖法的设计结果进行了比较。等长变覆盖法得到的探针集在探针长度一致的情况下,探针的Tm值有较小的标准差和变化范围。结果表明,等长变覆盖法得到的探针具有更好的杂交条件一致性。     

Metallo-β-lactamase: Inhibitors and reporter substrates

Metallo-β-lactamases represent an emerging clinical threat due to their ability to render ineffective an entire class of antibiotics. Accordingly, this family of enzymes has been suggested as an attractive target for drug design. Progress toward developing effective inhibitors as well as the development of reporter substrates is reviewed. Inhibitors are classified into six classes and known binding interactions with metallo-β-lactamases are summarized. The development of chromogenic and fluorogenic reporter substrates is also reviewed with respect to current and prospective applications to future inhibitor and diagnostic discovery, mechanistic studies, and biological imaging. Despite progress in molecular probe development, the sequence and structural diversity within the metallo-β-lactamase family continue to present substantial hurdles for rational ligand design.     

On the Use of Multiple Probe Insertions at the Same Site for Repeated Intracerebral Microdialysis Experiments in the Nigrostriatal Dopamine System of Rats

The effects of implantation of a dialysis probe into the striatum of awake rats on indices of dopamine (DA) and serotonin neurotransmission were assessed, first over 24 h following initial insertion of a probe, and then again following reinsertion of a probe at the same site 1 week later. It was found that the basal concentration of DA in dialysate stabilized within 20-40 min after probe implantation, although DA showed a modest decline 24 h later. There was, however, no significant difference in basal DA between two test sessions separated by 1 week. On the other hand, the basal concentrations of the DA metabolites, 3,4-dihydroxyphenylacetic acid and homovanillic acid, progressively increased for 2-3 h after probe implantation and decreased markedly by 24 h later. Furthermore, in contrast to DA, the DA metabolites decreased even further after the second probe insertion. Amphetamine-stimulated DA release was also greatly attenuated following the second probe insertion, relative to the first probe insertion. Two probe insertions had only modest effects on the concentration of 5-hydroxyindoleacetic acid in dialysate, relative to the DA metabolites. It is suggested the effects of two probe insertions on DA metabolism and amphetamine-stimulated DA release described here are indicative of probe-induced damage to the nigrostriatal DA system. If this is the case, multiple probe insertions may not provide a feasible strategy for within-subjects design dialysis experiments over extended periods of time, at least in the DA system of small animals. It is suggested further that a stable basal concentration of DA in dialysate may be an especially poor indicator of the integrity of the dopaminergic input to the striatum.     

Ultraconserved element (UCE) probe set design: Base genome and initial design parameters critical for optimization

Targeted capture and enrichment approaches have proven effective for phylogenetic study. Ultraconserved elements (UCEs) in particular have exhibited great utility for phylogenomic analyses, with the software package phyluce being among the most utilized pipelines for UCE phylogenomics, including probe design. Despite the success of UCEs, it is becoming increasing apparent that diverse lineages require probe sets tailored to focal taxa in order to improve locus recovery. However, factors affecting probe design and methods for optimizing probe sets to focal taxa remain underexplored. Here, we use newly available beetle (Coleoptera) genomic resources to investigate factors affecting UCE probe set design using phyluce . In particular, we explore the effects of stringency during initial design steps, as well as base genome choice on resulting probe sets and locus recovery. We found that both base genome choice and initial bait design stringency parameters greatly alter the number of resultant probes included in final probe sets and strongly affect the number of loci detected and recovered during in silico testing of these probe sets. In addition, we identify attributes of base genomes that correlated with high performance in probe design. Ultimately, we provide a recommended workflow for using Phyluce to design an optimized UCE probe set that will work across a targeted lineage, and use our findings to develop a new, open‐source UCE probe set for beetles of the suborder Adephaga.     

Removing batch effects in analysis of expression microarray data: an evaluation of six batch adjustment methods

The expression microarray is a frequently used approach to study gene expression on a genome-wide scale. However, the data produced by the thousands of microarray studies published annually are confounded by "batch effects," the systematic error introduced when samples are processed in multiple batches. Although batch effects can be reduced by careful experimental design, they cannot be eliminated unless the whole study is done in a single batch. A number of programs are now available to adjust microarray data for batch effects prior to analysis. We systematically evaluated six of these programs using multiple measures of precision, accuracy and overall performance. ComBat, an Empirical Bayes method, outperformed the other five programs by most metrics. We also showed that it is essential to standardize expression data at the probe level when testing for correlation of expression profiles, due to a sizeable probe effect in microarray data that can inflate the correlation among replicates and unrelated samples.