Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Identification of protein-coding and non-coding RNA expression profiles in CD34(+) and in stromal cells in refractory anemia with ringed sideroblasts

Background: Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods: In this study, gene expression profiles of CD34(+) cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results: In CD34(+) cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value <= 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value <= 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions: These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34(+) cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.

Validation of dot blot hybridization and denaturing high performance liquid chromatography as reliable methods for TP53 codon 72 genotyping in molecular epidemiologic studies

Background: Mutations in TP53 are common events during carcinogenesis. In addition to gene mutations, several reports have focused on TP53 polymorphisms as risk factors for malignant disease. Many studies have highlighted that the status of the TP53 codon 72 polymorphism could influence cancer susceptibility. However, the results have been inconsistent and various methodological features can contribute to departures from Hardy-Weinberg equilibrium, a condition that may influence the disease risk estimates. The most widely accepted method of detecting genotyping error is to confirm genotypes by sequencing and/or via a separate method. Results: We developed two new genotyping methods for TP53 codon 72 polymorphism detection: Denaturing High Performance Liquid Chromatography (DHPLC) and Dot Blot hybridization. These methods were compared with Restriction Fragment Length Polymorphism (RFLP) using two different restriction enzymes. We observed high agreement among all methodologies assayed. Dot-blot hybridization and DHPLC results were more highly concordant with each other than when either of these methods was compared with RFLP. Conclusions: Although variations may occur, our results indicate that DHPLC and Dot Blot hybridization can be used as reliable screening methods for TP53 codon 72 polymorphism detection, especially in molecular epidemiologic studies, where high throughput methodologies are required.

GPIomics: global analysis of glycosylphosphatidylinositol-anchored molecules of Trypanosoma cruzi

Glycosylphosphatidylinositol (GPI) anchoring is a common, relevant posttranslational modification of eukaryotic surface proteins. Here, we developed a fast, simple, and highly sensitive (high attomole-low femtomole range) method that uses liquid chromatography-tandem mass spectrometry (LC-MS(n)) for the first large-scale analysis of GPI-anchored molecules (i.e., the GPIome) of a eukaryote, Trypanosoma cruzi, the etiologic agent of Chagas disease. Our genome-wise prediction analysis revealed that approximately 12% of T. cruzi genes possibly encode GPI-anchored proteins. By analyzing the GPIome of T. cruzi insect-dwelling epimastigote stage using LC-MS(n), we identified 90 GPI species, of which 79 were novel. Moreover, we determined that mucins coded by the T. cruzi small mucin-like gene (TcSMUG S) family are the major GPI-anchored proteins expressed on the epimastigote cell surface. TcSMUG S mucin mature sequences are short (56-85 amino acids) and highly O-glycosylated, and contain few proteolytic sites, therefore, less likely susceptible to proteases of the midgut of the insect vector. We propose that our approach could be used for the high throughput GPIomic analysis of other lower and higher eukaryotes. Molecular Systems Biology 7 April 2009; doi:10.1038/msb.2009.13

Downscaling a multicommuted flow injection analysis system for the photometric determination of iodate in table salt

In this work a downscaled multicommuted flow injection analysis setup for photometric determination is described. The setup consists of a flow system module and a LED based photometer, with a total internal volume of about 170 mu L The system was tested by developing an analytical procedure for the photometric determination of iodate in table salt using N,N-diethyl-henylenediamine (DPD) as the chromogenic reagent. Accuracy was accessed by applying the paired r-test between results obtained using the proposed procedure and a reference method, and no significant difference at the 95% confidence level was observed. Other profitable features, such as a low reagent consumption of 7.3 mu g DPD per determination: a linear response ranging from 0.1 up to 3.0 m IO(3)(-), a relative standard deviation of 0.9% (n = 11) for samples containing 0.5 m IO(3)(-), a detection limit of 17 mu g L(-1) IO(3)(-), a sampling throughput of 117 determination per hour, and a waste generation 600 mu L per determination, were also achieved. (C) 2010 Elsevier B.V. All rights reserved.

Green Chemistry-Sensitive Analytical Procedure for Photometric Determination of Orthophosphate in River and Tap Water by Use of a Simple LED-Based Photometer

In the current work a Green Analytical Chemistry (GAC) procedure for photometric determination of orthophosphate in river water at mu g L-1 concentration level is described. The flow system module and the LED-based photometer were assembled together to constitute a compact unit in order to allow that a flow cell with optical path-length of 100mm was coupled to them. The photometric procedure based on the molybdenum blue method was implemented employing the multicommuted flow injection analysis approach, which provided facilities to allow reduction of reagent consumption and as well as waste generation. Aiming to prove the usefulness of the system, orthophosphate in river and tap waters was determined. Accuracy was ascertained by spiking samples with orthophosphate solution yielding recoveries ranging from 96% up to 107%. Other profitable features such as a wide linear response range between 10 to 800 mu g L-1 [image omitted]; a detection limit (3 sigma criterion) of 2.4 mu g L-1 [image omitted]; a relative standard deviation (n=7) of 2% using a typical water sample with concentration of 120 mu g L-1 [image omitted]; reagent consumption of 3.0mg ammonium molybdate, 0.3mg hydrazine sulfate, and 0.03mg stannous chloride per determination; a waste generation of 2.4mL per determination; and a sampling throughput of 20 determination per hours were also achieved.

Exploiting Mn(III)/EDTA complex in a flow system with solenoid micro-pumps coupled to long pathlength spectrophotometry for fast manganese determination

The formation of the Mn(III)/EDTA complex in a flow system with solenoid micro-pumps was exploited for fast manganese determination in freshwater. Manganese(II) was oxidized in a solid-phase reactor containing lead dioxide immobilized on polyester. Long pathlength spectrophotometry was exploited to increase sensitivity, aiming to reach the threshold limit established by environmental legislation. A linear response was observed from 25 to 1500 mu g L(-1), with a detection limit of 6 mu g L(-1) (99.7% confidence level). Sample throughput and coefficient of variation were 36 samples/h and 2.6% (n = 10), respectively. EDTA consumption and waste generation were estimated as 500 mu g and 3 mL per determination, respectively. The amount of Pb in the residue corresponds to 250 mu g per determination and a solid-phase reactor could be used for up to 1600 determinations. Adsorption in active charcoal avoided interferences caused by organic matter and the developed procedure was successfully applied for determination of manganese in freshwater samples. Results were in agreement with those attained by GFAAS at the 95% confidence level. (C) 2010 Elsevier B.V. All rights reserved.

An expert flow system involving in-line prior assay for turbidimetric determination of chloride and sulphate in natural waters

A multi-pumping flow system exploiting prior assay is proposed for sequential turbidimetric determination of sulphate and chloride in natural waters. Both methods are implemented in the same manifold that provides facilities for: in-line sample clean-up with a Bio-Rex 70 mini-column with fluidized beads: addition of low amounts of sulphate or chloride ions to the reaction medium for improving supersaturation; analyte precipitation with Ba(2+) or Ag(+); real-time decision on the need for next assay. The sample is initially run for chloride determination, and the analytical signal is compared with a preset value. If higher, the sample is run again, now for sulphate determination. The strategy may lead to all increased sample throughput. The proposed system is computer-controlled and presents enhanced figures of merit. About 10 samples are run per hour (about 60 measurements) and results are reproducible and Unaffected by the presence of potential interfering ions at concentration levels usually found in natural waters. Accuracy was assessed against ion chromatography. (C) 2008 Elsevier B.V. All rights reserved.

Estudo de variabilidade e otimização do circuito de moagem SAG da Usina do Sossego

Sossego was the first Vale SAG mill operation to process copper-gold ore. It is located in the State of Para, southeastern Amazon region of Brazil. In the first three years of continuous operation, Vale investigated different alternatives for improving the circuit`s performance by investigating operating conditions, mainly focusing on the SAG mill. It was decided to further assess the performance of the comminution circuit as a function of ore characteristics. A comprehensive ore characterization program was then conducted, together with the calibration of mathematical models on the basis of surveys carried out at the industrial circuit. The simulator was then used to predict the throughput associated to each ore type, as well as to establish the optimized circuit configuration and tailored operating conditions. This paper describes in detail the main aspects of optimizing the industrial circuit performance, as well as the successful method for predicting the production as a function of ore characteristics and circuit configuration.

Evaluation of GFP Tag as a Screening Reporter in Directed Evolution of a Hyperthermophilic beta-Glucosidase

By applying a directed evolution methodology specific enzymatic characteristics can be enhanced, but to select mutants of interest from a large mutant bank, this approach requires high throughput screening and facile selection. To facilitate such primary screening of enhanced clones, an expression system was tested that uses a green fluorescent protein (GFP) tag from Aequorea victoria linked to the enzyme of interest. As GFP`s fluorescence is readily measured, and as there is a 1:1 molar correlation between the target protein and GFP, the concept proposed was to determine whether GFP could facilitate primary screening of error-prone PCR (EPP) clones. For this purpose a thermostable beta-glucosidase (BglA) from Fervidobacterium sp. was used as a model enzyme. A vector expressing the chimeric protein BglA-GFP-6XHis was constructed and the fusion protein purified and characterized. When compared to the native proteins, the components of the fusion displayed modified characteristics, such as enhanced GFP thermostability and a higher BglA optimum temperature. Clones carrying mutant BglA proteins obtained by EPP, were screened based on the BglA/GFP activity ratio. Purified tagged enzymes from selected clones resulted in modified substrate specificity.

Time course proteomic profiling of human myocardial infarction plasma samples: An approach to new biomarker discovery

Background: The aim of this study was to identify novel candidate biomarker proteins differentially expressed in the plasma of patients with early stage acute myocardial infarction (AMI) using SELDI-TOF-MS as a high throughput screening technology. Methods: Ten individuals with recent acute ischemic-type chest pain (< 12 h duration) and ST-segment elevation AMI (1STEMI) and after a second AMI (2STEMI) were selected. Blood samples were drawn at six times after STEMI diagnosis. The first stage (T(0)) was in Emergency Unit before receiving any medication, the second was just after primary angioplasty (T(2)), and the next four stages occurred at 12 h intervals after T(0). Individuals (n = 7) with similar risk factors for cardiovascular disease and normal ergometric test were selected as a control group (CG). Plasma proteomic profiling analysis was performed using the top-down (i.e. intact proteins) SELDI-TOF-MS, after processing in a Multiple Affinity Removal Spin Cartridge System (Agilent). Results: Compared with the CG, the 1STEMI group exhibited 510 differentially expressed protein peaks in the first 48 h after the AMI (p < 0.05). The 2STEMI group, had similar to 85% fewer differently expressed protein peaks than those without previous history of AMI (76, p < 0.05). Among the 16 differentially-regulated protein peaks common to both STEMI cohorts (compared with the CG at T(0)), 6 peaks were persistently down-regulated at more than one time-stage, and also were inversed correlated with serum protein markers (cTnI, CK and CKMB) during 48 h-period after IAM. Conclusions: Proteomic analysis by SELDI-TOF-MS technology combined with bioinformatics tools demonstrated differential expression during a 48 h time course suggests a potential role of some of these proteins as biomarkers for the very early stages of AMI, as well as for monitoring early cardiac ischemic recovery. (C) 2011 Elsevier B.V. All rights reserved.

HPLC-UV determination of metformin in human plasma for application in pharmacokinetics and bioequivalence studies

In this study, a simple, rapid and sensitive HPLC method with UV detection is described for determination of metformin in plasma samples from bioequivalence assays. Sample preparation was accomplished through protein precipitation with acetonitrile and chromatographic separation was performed on a reversed-phase phenyl column at 40 degrees C. Mobile phase consisted of a mixture of phosphate buffer and acetonitrile at flow rate of 1.0 ml/min. Wavelength was set at 236 nm. The method was applied to a bioequivalence study of two drug products containing metformin, and allowed determination of metformin at low concentrations with a higher throughput than previously described methods. (c) 2007 Elsevier B.V. All rights reserved.

A fast sample preparation procedure for mercury speciation in hair samples by high-performance liquid chromatography coupled to ICP-MS

A simple method for mercury speciation in hair samples with a fast sample preparation procedure using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry is proposed. Prior to analysis, 50 mg of hair samples were accurately weighed into 15 mL conical tubes. Then, an extractant solution containing mercaptoethanol, L-cysteine and HCl was added to the samples following sonication for 10 min. Quantitative mercury extraction was achieved with the proposed procedure. Separation of inorganic mercury (Ino-Hg), methylmercury (Met-Hg) and ethylmercury (Et-Hg) was accomplished in less than 8 min on a C18 reverse phase column with a mobile phase containing 0.05% v/v mercaptoethanol, 0.4% m/v L-cysteine, 0.06 mol L(-1) ammonium acetate and 5% v/v methanol. The method detection limits were found to be 15 ng g(-1), 10 ng g(-1) and 38 ng g(-1), for inorganic mercury, methylmercury and ethylmercury, respectively. Sample throughput is 4 samples h(-1) (duplicate). A considerable improvement in the time of analysis was achieved when compared to other published methods. Method accuracy is traceable to Certified Reference Materials (CRMs) 85 and 86 human hair from the International Atomic Energy Agency (IAEA). Finally, the proposed method was successfully applied to the speciation of mercury in hair samples collected from fish-eating communities of the Brazilian Amazon.