Global Discovery and Temporal Changes of Human Albumin Modifications by Pan-Protein Adductomics: Initial Application to Air Pollution Exposure

Assessing personal exposure to environmental toxicants is a critical challenge for predicting disease risk. Previously, using human serum albumin (HSA)-based biomonitoring, we reported dosimetric relationships between adducts at HSA Cys34 and ambient air pollutant levels (Smith et al., Chem. Res. Toxicol. 2021, 34, 1183). These results provided the foundation to explore modifications at other sites in HSA to reveal novel adducts of complex exposures. Thus, the Pan-Protein Adductomics (PPA) technology reported here is the next step toward an unbiased, comprehensive characterization of the HSA adductome. The PPA workflow requires <2 μL serum/plasma and uses nanoflow-liquid chromatography, gas-phase fractionation, and overlapping-window data-independent acquisition high-resolution tandem mass spectrometry. PPA analysis of albumin from nonsmoking women exposed to high levels of air pollution uncovered 68 unique location-specific modifications (LSMs) across 21 HSA residues. While nearly half were located at Cys34 (33 LSMs), 35 were detected on other residues, including Lys, His, Tyr, Ser, Met, and Arg. HSA adduct relative abundances spanned a ∼400 000-fold range and included putative products of exogenous (SO2, benzene, phycoerythrobilin) and endogenous (oxidation, lipid peroxidation, glycation, carbamylation) origin, as well as 24 modifications without annotations. PPA quantification revealed statistically significant changes in LSM levels across the 84 days of monitoring (∼3 HSA lifetimes) in the following putative adducts: Cys34 trioxidation, β-methylthiolation, benzaldehyde, and benzene diol epoxide; Met329 oxidation; Arg145 dioxidation; and unannotated Cys34 and His146 adducts. Notably, the PPA workflow can be extended to any protein. Pan-Protein Adductomics is a novel and powerful strategy for untargeted global exploration of protein modifications

Relation between Plasma <i>R249S-</i>mutated <i>DNA</i> and HBs-antigen (HBsAg) and HCV-antibody (HCV-ab).

<p><i>X₂</i> test when compared to cholangiocarcinoma, chronic liver disease and reference group all together (*: p value <0.05; ***: p value <0.001; NA: Not Available; ns: non significant).</p

School register for Children and Youth Center in České Budějovice

The goal of my bachelor{\crq}s thesis is to introduce the reader into the subject of administration of a school register for Children and Youth Centres as well as for other organizations providing extra-curricular education. The thesis includes a summary of the respective legal regulations, the analysis of requirements specific for educational facilities, a draft and the implementation of the SW application called the School Register (Skolni matrika). This application will enable on-line administration of the school register depending on the needs of the Children and Youth Centres

Relation between Plasma <i>R249S-mutated DNA</i> and AFP.

*<p><i>X₂</i> test comparing individuals with <i>R249S</i> > = 150 copies/mL against individuals with <i>R249S</i> <150 copies/mL.</p

Geographic distribution of liver cancer cases.

<p>Dots represent the distribution by province. Pie charts describe the distribution of HCC/no cirrhosis (lines), HCC/cirrhosis (full black) and CC (small dots) among the Northwest, Northeast and Central-south parts of the country.</p

Sociodemographic characteristics of study participants.

<p>Sociodemographic characteristics of study participants.</p

Box and whisker distributions of <i>TP53 R249S</i>-<i>mutated DNA plasma concentrations</i> (≥150 copies/mL) for the different groups.

<p>Boxes extend from 25^th to 75^th percentiles and are divided by a solid line representing the median of each centre. The median levels for the different groups are: 328 in HCC/no cirrhosis, 273 in HCC/cirrhosis, 252 in CC, 256 in CLD and 202 in R.</p

Statistical Inference from Multiple iTRAQ Experiments without Using Common Reference Standards

Isobaric tags for relative and absolute quantitation (iTRAQ) is a prominent mass spectrometry technology for protein identification and quantification that is capable of analyzing multiple samples in a single experiment. Frequently, iTRAQ experiments are carried out using an aliquot from a pool of all samples, or “masterpool”, in one of the channels as a reference sample standard to estimate protein relative abundances in the biological samples and to combine abundance estimates from multiple experiments. In this manuscript, we show that using a masterpool is counterproductive. We obtain more precise estimates of protein relative abundance by using the available biological data instead of the masterpool and do not need to occupy a channel that could otherwise be used for another biological sample. In addition, we introduce a simple statistical method to associate proteomic data from multiple iTRAQ experiments with a numeric response and show that this approach is more powerful than the conventionally employed masterpool-based approach. We illustrate our methods using data from four replicate iTRAQ experiments on aliquots of the same pool of plasma samples and from a 406-sample project designed to identify plasma proteins that covary with nutrient concentrations in chronically undernourished children from South Asia

Flow-chart of recruitment.

<p>Numbers of households or participants at each stage of recruitment, for each department and for the final sample.</p

Adjusted geometric means of serum aflatoxin-albumin adducts by sociodemographic characteristics of study participants.

<p>Adjusted geometric means of serum aflatoxin-albumin adducts by sociodemographic characteristics of study participants.</p