A fast method using a new hydrophilic–lipophilic balanced sorbent in combination with ultra-high performance liquid chromatography for quantification of significant bioactive metabolites in wines

This manuscript describes the development and validation of an ultra-fast, efficient, and high throughput analytical method based on ultra-high performance liquid chromatography (UHPLC) equipped with a photodiode array (PDA) detection system, for the simultaneous analysis of fifteen bioactive metabolites: gallic acid, protocatechuic acid, (−)-catechin, gentisic acid, (−)-epicatechin, syringic acid, p-coumaric acid, ferulic acid, m-coumaric acid, rutin, trans-resveratrol, myricetin, quercetin, cinnamic acid and kaempferol, in wines. A 50-mm column packed with 1.7-μm particles operating at elevated pressure (UHPLC strategy) was selected to attain ultra-fast analysis and highly efficient separations. In order to reduce the complexity of wine extract and improve the recovery efficiency, a reverse-phase solid-phase extraction (SPE) procedure using as sorbent a new macroporous copolymer made from a balanced ratio of two monomers, the lipophilic divinylbenzene and the hydrophilic N-vinylpyrrolidone (Oasis™ HLB), was performed prior to UHPLC–PDA analysis. The calibration curves of bioactive metabolites showed good linearity within the established range. Limits of detection (LOD) and quantification (LOQ) ranged from 0.006 μg mL−1 to 0.58 μg mL−1, and from 0.019 μg mL−1 to 1.94 μg mL−1, for gallic and gentisic acids, respectively. The average recoveries ± SD for the three levels of concentration tested (n = 9) in red and white wines were, respectively, 89 ± 3% and 90 ± 2%. The repeatability expressed as relative standard deviation (RSD) was below 10% for all the metabolites assayed. The validated method was then applied to red and white wines from different geographical origins (Azores, Canary and Madeira Islands). The most abundant component in the analysed red wines was (−)-epicatechin followed by (−)-catechin and rutin, whereas in white wines syringic and p-coumaric acids were found the major phenolic metabolites. The method was completely validated, providing a sensitive analysis for bioactive phenolic metabolites detection and showing satisfactory data for all the parameters tested. Moreover, was revealed as an ultra-fast approach allowing the separation of the fifteen bioactive metabolites investigated with high resolution power within 5 min.

Cloning, overexpression, and purification of functional human purine nucleoside phosphorylase

Purine nucleoside phosphorylase (PNP) catalyzes the phosphorolysis of the N-ribosidic bonds of purine nucleosides and deoxynucleosides. A genetic deficiency due to mutations in the gene encoding for human PNP causes T-cell deficiency as the major physiological defect. Inappropriate activation of T-cells has been implicated in several clinically relevant human conditions such as transplant tissue rejection, psoriasis, rheumatoid arthritis, lupus, and T-cell lymphomas. Human PNP is therefore a target for inhibitor development aiming at T-cell immune response modulation. In addition, bacterial PNP has been used as reactant in a fast and sensitive spectrophotometric method that allows both quantitation of inorganic phosphate (Pi) and continuous assay of reactions that generate P i such as those catalyzed by ATPases and GTPases. Human PNP may therefore be an important biotechnological tool for P i detection. However, low expression of human PNP in bacterial hosts, protein purification protocols involving many steps, and low protein yields represent technical obstacles to be overcome if human PNP is to be used in either high-throughput drug screening or as a reagent in an affordable P i detection method. Here, we describe PCR amplification of human PNP from a liver cDNA library, cloning, expression in Escherichia coli host, purification, and activity measurement of homogeneous enzyme. Human PNP represented approximately 42% of total soluble cell proteins with no induction being necessary to express the target protein. Enzyme activity measurements demonstrated a 707-fold increase in specific activity of cloned human PNP as compared to control. Purification of cloned human PNP was achieved by a two-step purification protocol, yielding 48 mg homogeneous enzyme from 1 L cell culture, with a specific activity value of 80 U mg -1. © 2002 Elsevier Science (USA). All rights reserved.

Biotechnology of polyketides: new breath of life for the novel antibiotic genetic pathways discovery through metagenomics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Taxonomia e potencial antimicrobiano de fungos depositados no acervo de pesquisa da Central de Recursos Microbianos da UNESP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data

Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.

Structured antibody surfaces for bio-recognition and a label-free detection of bacteria

Antibody microarrays are of great research interest because of their potential application as biosensors for high-throughput protein and pathogen screening technologies. In this active area, there is still a need for novel structures and assemblies providing insight in binding interactions such as spherical and annulus-shaped protein structures, e.g. for the utilization of curved surfaces for the enhanced protein-protein interactions and detection of antigens. Therefore, the goal of the presented work was to establish a new technique for the label-free detection of bio-molecules and bacteria on topographically structured surfaces, suitable for antibody binding.rnIn the first part of the presented thesis, the fabrication of monolayers of inverse opals with 10 μm diameter and the immobilization of antibodies on their interior surface is described. For this purpose, several established methods for the linking of antibodies to glass, including Schiff bases, EDC/S-NHS chemistry and the biotin-streptavidin affinity system, were tested. The employed methods included immunofluorescence and image analysis by phase contrast microscopy. It could be shown that these methods were not successful in terms of antibody immobilization and adjacent bacteria binding. Hence, a method based on the application of an active-ester-silane was introduced. It showed promising results but also the need for further analysis. Especially the search for alternative antibodies addressing other antigens on the exterior of bacteria will be sought-after in the future.rnAs a consequence of the ability to control antibody-functionalized surfaces, a new technique employing colloidal templating to yield large scale (~cm2) 2D arrays of antibodies against E. coli K12, eGFP and human integrin αvβ3 on a versatile useful glass surface is presented. The antibodies were swept to reside around the templating microspheres during solution drying, and physisorbed on the glass. After removing the microspheres, the formation of annuli-shaped antibody structures was observed. The preserved antibody structure and functionality is shown by binding the specific antigens and secondary antibodies. The improved detection of specific bacteria from a crude solution compared to conventional “flat” antibody surfaces and the setting up of an integrin-binding platform for targeted recognition and surface interactions of eukaryotic cells is demonstrated. The structures were investigated by atomic force, confocal and fluorescence microscopy. Operational parameters like drying time, temperature, humidity and surfactants were optimized to obtain a stable antibody structure.

Analysis of Two Component Systems in Group B Streptococcus Shows that RgfAC and the Novel FspSR Modulate Virulence and Bacterial Fitness

Group B Streptococcus (GBS), in its transition from commensal to pathogen, will encounter diverse host environments and thus require coordinately controlling its transcriptional responses to these changes. This work was aimed at better understanding the role of two component signal transduction systems (TCS) in GBS pathophysiology through a systematic screening procedure. We first performed a complete inventory and sensory mechanism classification of all putative GBS TCS by genomic analysis. Five TCS were further investigated by the generation of knock-out strains, and in vitro transcriptome analysis identified genes regulated by these systems, ranging from 0.1-3% of the genome. Interestingly, two sugar phosphotransferase systems appeared differently regulated in the knock-out mutant of TCS-16, suggesting an involvement in monitoring carbon source availability. High throughput analysis of bacterial growth on different carbon sources showed that TCS-16 was necessary for growth of GBS on fructose-6-phosphate. Additional transcriptional analysis provided further evidence for a stimulus-response circuit where extracellular fructose-6-phosphate leads to autoinduction of TCS-16 with concomitant dramatic up-regulation of the adjacent operon encoding a phosphotransferase system. The TCS-16-deficient strain exhibited decreased persistence in a model of vaginal colonization and impaired growth/survival in the presence of vaginal mucoid components. All mutant strains were also characterized in a murine model of systemic infection, and inactivation of TCS-17 (also known as RgfAC) resulted in hypervirulence. Our data suggest a role for the previously unknown TCS-16, here named FspSR, in bacterial fitness and carbon metabolism during host colonization, and also provide experimental evidence for TCS-17/RgfAC involvement in virulence.

Identifizierung chemischer Transportinhibitoren zur Modulation (patho)biologischer Genprodukte

Die intrazelluläre Lokalisation von Proteinen und Makromolekülen unterliegt in Eukaryoten einer strengen Regulation. Insbesondere erlaubt die Kompartimentierung eukaryotischer Zellen in Zellkern und Zytoplasma den simultanen Ablauf räumlich getrennter biochemischer Reaktionen, und damit die unabhängige Regulation zellulärer Programme. Da trotz intensiver Forschungsbemühungen bis dato die molekularen Details sowie die (patho)biologische Bedeutung von Kern-Zytoplasma-Transportprozessen noch immer nicht vollkommen verstanden sind, wurde im Rahmen der vorliegenden Arbeit ein Fokus auf die Identifizierung von chemischen Transportinhibitoren gelegt. Das zu diesem Zweck entwickelte Translokations-Biosensor-System basiert auf der Kombination von autofluoreszierenden Proteinen, sowie spezifisch ausgewählten Kernexport- und Kernimportsignalen. Nach Etablierung geeigneter Zellmodelle, die effizient und stabil die Translokations-Biosensoren exprimieren, wurde die 17 000 Substanzen umfassende Bibliothek der ChemBioNet-Initiative nach Kernexportinhibitoren mittels einer Fluoreszenzmikroskopie-basierten Hochdurchsatzanalyse-Plattform durchmustert. Zunächst wurden Translokations-Algorithmen, welche eine zuverlässige automatisierte Erkennung von Zellkern und Zytoplasma erlauben, optimiert. Im Folgenden konnten acht neue niedermolekulare Kernexport-Inhibitoren identifiziert werden, die sich in der Stärke, der Geschwindigkeit, sowie in der Beständigkeit der vermittelten Inhibition unterscheiden. Die Aktivität der Inhibitoren konnte auf den isolierten nukleären Exportsignalen (NES) von HIV-1 Rev und Survivin als auch auf den entsprechenden Volllängeproteinen mittels Mikroinjektionsexperimenten sowie durch umfassende in vitro und biochemische Methoden bestätigt werden. Zur Untersuchung der funktionellen Einheiten der Inhibitoren wurden homologe Substanzen auf Ihre Aktivität hin getestet. Dabei konnten für die Aktivität wichtige chemische Gruppen definiert werden. Alle Substanzen stellen neue Inhibitoren des Crm1-abhängigen Exports dar und zeigen keine nachweisbare NES-Selektivität. Interessanterweise konnte jedoch eine zytotoxische und Apoptose-induzierende Wirkung auf verschiedene Krebszellarten festgestellt werden. Da diese Wirkung unabhängig vom p53-Status der Tumorzellen ist und die Inhibitoren C3 und C5 die Vitalität nicht-maligner humaner Zellen signifikant weniger beeinträchtigen, wurden diese Substanzen zum internationalen Patent angemeldet. Da der nukleäre Export besonders für Tumorzellen einen wichtigen Überlebenssignalweg darstellt, könnte dessen reversible Hemmung ausgenutzt werden, um besonders in Kombination mit gängigen Krebstherapien eine therapeutisch relevante Tumorinhibition zu erzeugen. Eine weitere Anwendungsmöglichkeit der neuen Exportinhibitoren ist auf dem Gebiet der Infektionskrankheiten zu sehen, da auch die Aktivität des essentiellen HIV-1 Rev-Proteins inhibiert wird. Zusätzlich konnte in der Arbeit gezeigt werden, dass der zelluläre Kofaktor des Crm1-abhängigen Exports des HIV-1 Rev-Proteins, die RNA-Helikase DDX3, ein eigenes NES enthält. Der Nachweis einer direkten Interaktion des HIV-1 Rev- mit dem DDX3-Protein impliziert, dass multiple Angriffstellen für chemische Modulatoren hinsichtlich einer antiviralen Therapie gegeben sind. Da die Vielfalt des chemischen Strukturraums es unmöglich macht diesen experimentell vollständig zu durchmustern, wurden im Rahmen dieser Arbeit auch Naturstoffe als vielversprechende Wirkstoffquelle untersucht. Um zukünftig umfassend bioaktive Substanzen aus diesen hochkomplexen Stoffgemischen experimentell identifizieren zu können, wurde eine Fluoreszenzmikroskopie-basierte Hochdurchsatzanalyse-Plattform am Mainz Screening Center (MSC) etabliert. Damit konnte bereits ein weiterer, bisher unbekannter Exportinhibitor aus Cyphellopsis anomala identifiziert werden. Neben einer Anwendung dieser Substanz als chemisches Werkzeug zur Aufklärung der Regulation von Transportvorgängen, stellt sich auch die evolutionsbiologisch relevante Frage, wie es dem Pilzproduzenten gelingt die Blockierung des eigenen Kernexports zu umgehen. Weiterführende Projekte müssen sich neben der Aufklärung der molekularen Wirkmechanismen der gefundenen Substanzen mit der Identifizierung spezifischer chemischer „Funktionseinheiten“ beschäftigen. Neben einem verbesserten mechanistischen Verständnis von Transportvorgängen stellen die erarbeiteten Transportinhibitoren Vorstufen zur Weiterentwicklung möglicher Wirkstoffe dar. Die im Rahmen dieser Arbeit etablierte Technologie-Plattform und molekularen Werkzeuge stellen darüber hinaus eine wichtige Voraussetzung dar, um eine systematische Suche nach möglichen Wirkstoffen im Forschungsfeld der „Chemischen Biomedizin“ voranzutreiben.

Identification of selective norbornane-type aspartate analogue inhibitors of the glutamate transporter 1 (GLT-1) from the chemical universe generated database (GDB)

A variety of conformationally constrained aspartate and glutamate analogues inhibit the glutamate transporter 1 (GLT-1, also known as EAAT2). To expand the search for such analogues, a virtual library of aliphatic aspartate and glutamate analogues was generated starting from the chemical universe database GDB-11, which contains 26.4 million possible molecules up to 11 atoms of C, N, O, F, resulting in 101026 aspartate analogues and 151285 glutamate analogues. Virtual screening was realized by high-throughput docking to the glutamate binding site of the glutamate transporter homologue from Pyrococcus horikoshii (PDB code: 1XFH ) using Autodock. Norbornane-type aspartate analogues were selected from the top-scoring virtual hits and synthesized. Testing and optimization led to the identification of (1R*,2R*,3S*,4R*,6R*)-2-amino-6-phenethyl-bicyclo[2.2.1]heptane-2,3-dicarboxylic acid as a new inhibitor of GLT-1 with IC(50) = 1.4 ?M against GLT-1 and no inhibition of the related transporter EAAC1. The systematic diversification of known ligands by enumeration with help of GDB followed by virtual screening, synthesis, and testing as exemplified here provides a general strategy for drug discovery.

UPLC-MS-based urine metabolomics reveals indole-3-lactic acid and phenyllactic acid as conserved biomarkers for alcohol-induced liver disease in the Ppara-null mouse model

Since the development and prognosis of alcohol-induced liver disease (ALD) vary significantly with genetic background, identification of a genetic background-independent noninvasive ALD biomarker would significantly improve screening and diagnosis. This study explored the effect of genetic background on the ALD-associated urinary metabolome using the Ppara-null mouse model on two different backgrounds, C57BL/6 (B6) and 129/SvJ (129S), along with their wild-type counterparts. Reversed-phase gradient UPLC-ESI-QTOF-MS analysis revealed that urinary excretion of a number of metabolites, such as ethylsulfate, 4-hydroxyphenylacetic acid, 4-hydroxyphenylacetic acid sulfate, adipic acid, pimelic acid, xanthurenic acid, and taurine, were background-dependent. Elevation of ethyl-β-d-glucuronide and N-acetylglycine was found to be a common signature of the metabolomic response to alcohol exposure in wild-type as well as in Ppara-null mice of both strains. However, increased excretion of indole-3-lactic acid and phenyllactic acid was found to be a conserved feature exclusively associated with the alcohol-treated Ppara-null mouse on both backgrounds that develop liver pathologies similar to the early stages of human ALD. These markers reflected the biochemical events associated with early stages of ALD pathogenesis. The results suggest that indole-3-lactic acid and phenyllactic acid are potential candidates for conserved and pathology-specific high-throughput noninvasive biomarkers for early stages of ALD.

Serodiagnosis of Echinococcus spp. infection: explorative selection of diagnostic antigens by peptide microarray

BACKGROUND: Production of native antigens for serodiagnosis of helminthic infections is laborious and hampered by batch-to-batch variation. For serodiagnosis of echinococcosis, especially cystic disease, most screening tests rely on crude or purified Echinococcus granulosus hydatid cyst fluid. To resolve limitations associated with native antigens in serological tests, the use of standardized and highly pure antigens produced by chemical synthesis offers considerable advantages, provided appropriate diagnostic sensitivity and specificity is achieved. METHODOLOGY/PRINCIPAL FINDINGS: Making use of the growing collection of genomic and proteomic data, we applied a set of bioinformatic selection criteria to a collection of protein sequences including conceptually translated nucleotide sequence data of two related tapeworms, Echinococcus multilocularis and Echinococcus granulosus. Our approach targeted alpha-helical coiled-coils and intrinsically unstructured regions of parasite proteins potentially exposed to the host immune system. From 6 proteins of E. multilocularis and 5 proteins of E. granulosus, 45 peptides between 24 and 30 amino acids in length were designed. These peptides were chemically synthesized, spotted on microarrays and screened for reactivity with sera from infected humans. Peptides reacting above the cut-off were validated in enzyme-linked immunosorbent assays (ELISA). Peptides identified failed to differentiate between E. multilocularis and E. granulosus infection. The peptide performing best reached 57% sensitivity and 94% specificity. This candidate derived from Echinococcus multilocularis antigen B8/1 and showed strong reactivity to sera from patients infected either with E. multilocularis or E. granulosus. CONCLUSIONS/SIGNIFICANCE: This study provides proof of principle for the discovery of diagnostically relevant peptides by bioinformatic selection complemented with screening on a high-throughput microarray platform. Our data showed that a single peptide cannot provide sufficient diagnostic sensitivity whereas pooling several peptide antigens improved sensitivity; thus combinations of several peptides may lead the way to new diagnostic tests that replace, or at least complement conventional immunodiagnosis of echinococcosis. Our strategy could prove useful for diagnostic developments in other pathogens.

Data Quality Assessment of Ungated Flow Cytometry Data in High

Background: The recent development of semi-automated techniques for staining and analyzing flow cytometry samples has presented new challenges. Quality control and quality assessment are critical when developing new high throughput technologies and their associated information services. Our experience suggests that significant bottlenecks remain in the development of high throughput flow cytometry methods for data analysis and display. Especially, data quality control and quality assessment are crucial steps in processing and analyzing high throughput flow cytometry data. Methods: We propose a variety of graphical exploratory data analytic tools for exploring ungated flow cytometry data. We have implemented a number of specialized functions and methods in the Bioconductor package rflowcyt. We demonstrate the use of these approaches by investigating two independent sets of high throughput flow cytometry data. Results: We found that graphical representations can reveal substantial non-biological differences in samples. Empirical Cumulative Distribution Function and summary scatterplots were especially useful in the rapid identification of problems not identified by manual review. Conclusions: Graphical exploratory data analytic tools are quick and useful means of assessing data quality. We propose that the described visualizations should be used as quality assessment tools and where possible, be used for quality control.

EXPLORATION, NORMALIZATION, AND GENOTYPE CALLS OF HIGH DENSITY OLIGONUCLEOTIDE SNP ARRAY DATA

In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of gene expression measurements, relative to ad-hoc procedures introduced by designers and manufacturers of the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular we describe methodology useful for preprocessing Affymetrix SNP chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from three relatively large studies including one in which large number independent calls are available. Software implementing these ideas are avialble from the Bioconductor oligo package.

How reliable and robust are current biomarkers for copper status?

Cu is an essential nutrient for man, but can be toxic if intakes are too high. In sensitive populations, marginal over- or under-exposure can have detrimental effects. Malnourished children, the elderly, and pregnant or lactating females may be susceptible for Cu deficiency. Cu status and exposure in the population can currently not be easily measured, as neither plasma Cu nor plasma cuproenzymes reflect Cu status precisely. Some blood markers (such as ceruloplasmin) indicate severe Cu depletion, but do not inversely respond to Cu excess, and are not suitable to indicate marginal states. A biomarker of Cu is needed that is sensitive to small changes in Cu status, and that responds to Cu excess as well as deficiency. Such a marker will aid in monitoring Cu status in large populations, and will help to avoid chronic health effects (for example, liver damage in chronic toxicity, osteoporosis, loss of collagen stability, or increased susceptibility to infections in deficiency). The advent of high-throughput technologies has enabled us to screen for potential biomarkers in the whole proteome of a cell, not excluding markers that have no direct link to Cu. Further, this screening allows us to search for a whole group of proteins that, in combination, reflect Cu status. The present review emphasises the need to find sensitive biomarkers for Cu, examines potential markers of Cu status already available, and discusses methods to identify a novel suite of biomarkers.

HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.