Ferric Reducing Antioxidant Power and Square Wave Voltammetry for Assay of Low Molecular Weight Antioxidants in Blood Plasma: Performance and Comparison of Methods

The purpose of the present study was to employ two methods—square wave voltammetry (SWV) performed on screen printed sensors and ferric reducing antioxidant power (FRAP)—as suitable tools for the assay of low-molecular-weight antioxidants (LMWAs). LMWAs were assayed by both methods and the resulting data were statistically compared. Plasma samples from five Cinereous vultures accidentally intoxicated with lead were used to represent real biological matrices with different levels of LMWAs. Blood was collected from the birds prior to and one month after treatment with Ca-EDTA. SWV resulted in two peaks. The first peak, with the potential value of 466 ± 15 mV, was recognized as ascorbic and uric acids, while the second one (743 ± 30 mV) represented glutathione, tocopherol, ascorbic acid and in a minor effect by uric acid, too. Contribution of individual antioxidants was recognized by separate assays of LMWA standards. Correlation between peaks 1 and 2 as well as the sum of the two peaks and FRAP was analysed. While peak 1 and the sum of peaks were in close correlation to FRAP results (correlation coefficient of 0.97), the relation between peak 2 and FRAP may be expressed using a correlation coefficient of 0.64. The determination of thiols by the Ellman assay confirmed the accuracy of SWV. Levels of glutathione and other similar structures were stable in the chosen model and it may be concluded that SWV is appropriate for assay of LMWAs in plasma samples. The methods employed in the study were advantageous in minimal sample volume consumption and fast acquisition of results

Rab-dependent vesicular traffic affects female gametophyte development in Arabidopsis

Eukaryotic cells rely on the accuracy and efficiency of vesicular traffic. In plants, disturbances in vesicular trafficking are well studied in quickly dividing root meristem cells or polar growing root hairs and pollen tubes. The development of the female gametophyte, a unique haploid reproductive structure located in the ovule, has received far less attention in studies of vesicular transport. Key molecules providing the specificity of vesicle formation and its subsequent recognition and fusion with the acceptor membrane are Rab proteins. Rabs are anchored to membranes by covalently linked geranylgeranyl group(s) that are added by the Rab geranylgeranyl transferase (RGT) enzyme. Here we show that Arabidopsis plants carrying mutations in the gene encoding the β-subunit of RGT (rgtb1) exhibit severely disrupted female gametogenesis and this effect is of sporophytic origin. Mutations in rgtb1 lead to internalization of the PIN1 and PIN3 proteins from the basal membranes to vesicles in provascular cells of the funiculus. Decreased transport of auxin out of the ovule is accompanied by auxin accumulation in tissue surrounding the growing gametophyte. In addition, female gametophyte development arrests at the uni- or binuclear stage in a significant portion of the rgtb1 ovules. These observations suggest that communication between the sporophyte and the developing female gametophyte relies on Rab-dependent vesicular traffic of the PIN1 and PIN3 transporters and auxin efflux out of the ovule

A mitogen-activated protein kinase kinase kinase mediates reactive oxygen species homeostasis in Arabidopsis

No abstract availabl

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes

<div><p>Background</p><p>Carriers of mutations in hereditary cancer predisposition genes represent a small but clinically important subgroup of oncology patients. The identification of causal germline mutations determines follow-up management, treatment options and genetic counselling in patients’ families. Targeted next-generation sequencing-based analyses using cancer-specific panels in high-risk individuals have been rapidly adopted by diagnostic laboratories. While the use of diagnosis-specific panels is straightforward in typical cases, individuals with unusual phenotypes from families with overlapping criteria require multiple panel testing. Moreover, narrow gene panels are limited by our currently incomplete knowledge about possible genetic dispositions.</p><p>Methods</p><p>We have designed a multi-gene panel called CZECANCA (CZEch CAncer paNel for Clinical Application) for a sequencing analysis of 219 cancer-susceptibility and candidate predisposition genes associated with frequent hereditary cancers.</p><p>Results</p><p>The bioanalytical and bioinformatics pipeline was validated on a set of internal and commercially available DNA controls showing high coverage uniformity, sensitivity, specificity and accuracy. The panel demonstrates a reliable detection of both single nucleotide and copy number variants. Inter-laboratory, intra- and inter-run replicates confirmed the robustness of our approach.</p><p>Conclusion</p><p>The objective of CZECANCA is a nationwide consolidation of cancer-predisposition genetic testing across various clinical indications with savings in costs, human labor and turnaround time. Moreover, the unified diagnostics will enable the integration and analysis of genotypes with associated phenotypes in a national database improving the clinical interpretation of variants.</p></div

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 7

<p><b>Comparison of variant detection (shown as values of variant allelic fraction; AF) in DNA reference standards</b> (NA12878, NA24149, NA24385, NA24631 and NA24143) obtained from CZECANCA analysis (x-axis) and AF from VCF files for these standards downloaded from <a href="http://jimb.stanford.edu/giab/" target="_blank">http://jimb.stanford.edu/giab/</a> (y-axis). The graph shows all variants with GATK quality >100 reached in CZECANCA analysis (including FP variants) and undetected (FN) variants. Heterozygote variants clustered in the center, while homozygote variants in right upper corner. Variant distribution was partially influenced by the differences in mean sequencing coverage targeting 100X and 300X in CZECANCA and DNA reference standards VCFs, respectively. The number of TP, TN, FP, FN, and total number of variant (= CZECANCA target) was used to calculate of sensitivity, specificity, and accuracy of CZECANCA analysis.</p

Identification of c.661_662delinsTA double substitution (p.Val221*) in <i>PALB2</i> (NM_024675).

<p>The BAM file displayed in IGV shows the <i>cis</i>-position of both substitutions in approximately 50% of forward (pink bars) and reverse (blue bars) reads, respectively.</p

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 4

<p><b>Analysis of intra-run (A), inter-run (B), and inter-laboratory (C) replicates.</b> The panels show sequencing coverages (y-axis) of the identified variants arranged according to chromosomal localizations (x-axis). We used moving average curves (average of 3 values) to compare trends in coverages. Panel (A) describes the results of an analysis of three independently processed intra-run replicates from an identical DNA sample pooled in 33 ng (considered as 100%), 24.75 ng (75%), and 16.5 ng (50%), respectively. Panel (B) demonstrates variant coverages identified in two independent inter-run (run 8 and 14) replicates. All coverage values of sample #3647 in run 14 were corrected by a factor of 1.3880 to normalize coverages between samples (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.s004" target="_blank">S4 Table</a>). Panel (C) shows coverages of variants identified in an inter-laboratory control sequenced in four laboratories (Lab) participating in panel validation (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.s005" target="_blank">S5 Table</a>). The coverages of variants identified in Lab 2, 3, and 4 were normalized to the average coverage of Lab 1 for better comparisons of coverages.</p

Coverage (y-axis) of coding sequences (x-axis) of 219 CZECANCA target genes from a routine, randomly selected run targeting 100X coverage.

<p>Note: Fully covered genes are depicted in green letters, genes with coverage <20X in a single exon are in orange letters, and genes with uncovered regions exceeding single exon or >10% of coding sequence are in red letters. Green horizontal bars (below individual graphs constructed using “Boudalyzer” script) indicate coverage ≥ 20X; red horizontal bars indicate regions covered <20X and uncovered regions.</p

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 3

<p><b>Coverage of selected genes from the CZECANCA (A-E) and TruSight Cancer sequencing (F) panels.</b> The pictures show coverage (at y-axis) alongside the coding sequences of <i>BRCA1</i> (NM_007294), <i>BRCA2</i> (NM_000059), <i>PALB2</i> (NM_024675), and <i>TP53</i> (NM_000546), the vertical lines represent exon boundaries. Panels A–D show results obtained from a CZECANCA NGS analysis of various samples performed in four participating laboratories using the ultrasound (A, B) or enzymatic (C, D) DNA fragmentation protocol. Examples of the identified CNV aberrations in the depicted genes (deletions in <i>BRCA1</i>, <i>BRCA2</i> and <i>TP53</i> and duplication in <i>PALB2</i>) are shown in panel E. For comparison, panel F demonstrates the uneven coverage of the depicted genes by sequencing using the TruSight Cancer panel (Illumina).</p

CNV detection is influenced by a DNA preparation method.

<p>Panels show analyses of remaining ACMG genes (not shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.g005" target="_blank">Fig 5B and 5C</a>) from four runs performed in laboratory 1 (116 DNA samples fragmented by ultrasound) and laboratory 3 (125 DNA samples fragmented enzymatically). The numbers in parentheses express number of samples with possible CNVs from all analyzed samples in contributing laboratories. *indicate samples analyzed by MLPA negatively (FP–black) or positively (TP–red). Bin set covering exon 1 in <i>RET</i> was excluded from the analysis due to the large coverage variability.</p