Biomonitoring of lead in blood of children living in a former mining area in Lower Saxony, Germany.

Environmental exposure to lead substantially decreased over the past decades. However, soil of former mining areas still contains high lead levels. We therefore performed a biomonitoring study among children living in two former mining communities in Lower Saxony, Germany. In these communities, soil contains lead levels of 1000 to 30,000 mg/kg. Overall, 75 children (6-10 years of age) attending the two primary schools of the study area took part in the study. Parents completed a short questionnaire on sociodemographics, and children provided capillary whole blood samples. We analysed lead using inductively coupled plasma tandem mass spectrometer. We compared the results to current German (20 µg/l for boys, 15 µg/l for girls) and US (35 µg/l) reference values. Potential associations between questionnaire information and lead results were tested using lead as continuous outcome and using lead dichotomized at the reference values. Finally, we analysed spatial patterns of elevated biomonitoring results. Of all children, 48% exceeded the German reference values for lead (5% expected) and 8% the US reference value (2.5% expected). Children 6-8 years of age were more likely to exceed German reference values (63%) than 9-10 year old children were (32%; pFisher = 0.01). No other questionnaire information was statistically significantly associated with biomonitoring results. Additionally, we did not find any indication of spatial clustering. In conclusion, we observed elevated blood lead levels in primary school children living in a former mining area. In the next step, exposure pathways need to be identified to implement effective public health measures.

Proteomic changes induced by longevity-promoting interventions in mice.

Using mouse models and high-throughput proteomics, we conducted an in-depth analysis of the proteome changes induced in response to seven interventions known to increase mouse lifespan. This included two genetic mutations, a growth hormone receptor knockout (GHRKO mice) and a mutation in the Pit-1 locus (Snell dwarf mice), four drug treatments (rapamycin, acarbose, canagliflozin, and 17α-estradiol), and caloric restriction. Each of the interventions studied induced variable changes in the concentrations of proteins across liver, kidney, and gastrocnemius muscle tissue samples, with the strongest responses in the liver and limited concordance in protein responses across tissues. To the extent that these interventions promote longevity through common biological mechanisms, we anticipated that proteins associated with longevity could be identified by characterizing shared responses across all or multiple interventions. Many of the proteome alterations induced by each intervention were distinct, potentially implicating a variety of biological pathways as being related to lifespan extension. While we found no protein that was affected similarly by every intervention, we identified a set of proteins that responded to multiple interventions. These proteins were functionally diverse but tended to be involved in peroxisomal oxidation and metabolism of fatty acids. These results provide candidate proteins and biological mechanisms related to enhancing longevity that can inform research on therapeutic approaches to promote healthy aging.

The Association of Biomolecular Resource Facilities Proteome Informatics Research Group Study on Metaproteomics (iPRG-2020).

Metaproteomics research using mass spectrometry data has emerged as a powerful strategy to understand the mechanisms underlying microbiome dynamics and the interaction of microbiomes with their immediate environment. Recent advances in sample preparation, data acquisition, and bioinformatics workflows have greatly contributed to progress in this field. In 2020, the Association of Biomolecular Research Facilities Proteome Informatics Research Group launched a collaborative study to assess the bioinformatics options available for metaproteomics research. The study was conducted in 2 phases. In the first phase, participants were provided with mass spectrometry data files and were asked to identify the taxonomic composition and relative taxa abundances in the samples without supplying any protein sequence databases. The most challenging question asked of the participants was to postulate the nature of any biological phenomena that may have taken place in the samples, such as interactions among taxonomic species. In the second phase, participants were provided a protein sequence database composed of the species present in the sample and were asked to answer the same set of questions as for phase 1. In this report, we summarize the data processing methods and tools used by participants, including database searching and software tools used for taxonomic and functional analysis. This study provides insights into the status of metaproteomics bioinformatics in participating laboratories and core facilities.

Structural surfaceomics reveals an AML-specific conformation of integrin ß2 as a CAR T cellular therapy target.

Safely expanding indications for cellular therapies has been challenging given a lack of highly cancer-specific surface markers. Here we explore the hypothesis that tumor cells express cancer-specific surface protein conformations that are invisible to standard target discovery pipelines evaluating gene or protein expression, and these conformations can be identified and immunotherapeutically targeted. We term this strategy integrating cross-linking mass spectrometry with glycoprotein surface capture 'structural surfaceomics'. As a proof of principle, we apply this technology to acute myeloid leukemia (AML), a hematologic malignancy with dismal outcomes and no known optimal immunotherapy target. We identify the activated conformation of integrin ß2 as a structurally defined, widely expressed AML-specific target. We develop and characterize recombinant antibodies to this protein conformation and show that chimeric antigen receptor T cells eliminate AML cells and patient-derived xenografts without notable toxicity toward normal hematopoietic cells. Our findings validate an AML conformation-specific target antigen and demonstrate a tool kit for applying these strategies more broadly.

A revised concept for deriving reference values for internal exposures to chemical substances and its application to population-representative biomonitoring data in German children and adolescents 2014-2017 (GerES V).

HBM reference values, in contrast to toxicologically derived values, are statistically derived values that provide information on the exposure of the population. The exceedance frequency (if applicable for individual population groups) is often a first assessment standard for the local exposure situation for municipalities. More than 25 years have passed since the German Human Biomonitoring Commission (HBMC) formulated the first recommendations for the derivation of population-based reference values (HBM reference values, RV95) for substance concentrations based on HBM studies. A fundamental revision is timely, for several reasons. There have been considerable advances in relevant statistical methods, which meant that previously time-consuming and inaccessible procedures and calculations are now widely available. Furthermore, not all steps for the derivation of HBM reference values were clearly elaborated in the first recommendations. With this revision we intended to achieve a rigorous standardization of the entire process of deriving HBM reference values, also to realise a higher degree of transparency. In accordance with established international practice, it is recommended to use the 95th percentile of the reference distribution as the HBM reference value. To this end, the empirical 95th percentile of a suitable sample should be rounded, ensuring that the rounded value is within the two-sided 95% confidence interval of the percentile. All estimates should be based on distribution-free methods, and the confidence interval should be estimated using a bootstrap approach, if possible, according to the BCa ("bias-corrected and accelerated bootstrap"). A minimum sample size of 80 observations is considered necessary. The entire procedure ensures that the derived HBM reference value is robust against at least two extreme values and can also be used for underlying mixed distributions. If it is known in advance that certain subgroups (different age groups, smokers, etc.) show differing internal exposures, it is recommended that group-specific HBM reference values should be derived. Especially when the sample sizes for individual subgroups are too small, individual datasets with potential outliers can be excluded in advance to homogenize the reference value population. In the second part, new HBM reference values based on data of the German Environmental Survey for Children and Adolescents (GerES V, 2014-2017) were derived in accordance with the revised recommendations. The GerES V is the most recent population-representative monitoring of human exposure to pollutants in Germany on children and adolescents aged 3-17 years (N = 2294). RV95 for GerES V are reported for four subgroups (males/females and 3-11/12-17 years) for 108 different substances including phthalates and alternative plasticisers, metals, organochlorine pesticides, polychlorinated biphenyls (PCB), per- and polyfluoroalkyl substances (PFAS), parabens, aprotic solvents, chlorophenols, polycyclic aromatic hydrocarbons (PAH) and UV filter, in total 135 biomarkers. Algorithms implemented in R were used for the statistics and the determination of the HBM reference values. To facilitate a quality control of the study data, the corresponding R source code is given, together with graphical representations of results. The HBM reference values listed in this article replace earlier RV95 values derived by the HBMC for children and adolescents from data of precedent GerES studies (e.g. published in Apel et al., 2017).

Lifespan-extending interventions induce consistent patterns of fatty acid oxidation in mouse livers.

Aging manifests as progressive deteriorations in homeostasis, requiring systems-level perspectives to investigate the gradual molecular dysregulation of underlying biological processes. Here, we report systemic changes in the molecular regulation of biological processes under multiple lifespan-extending interventions. Differential Rank Conservation (DIRAC) analyses of mouse liver proteomics and transcriptomics data show that mechanistically distinct lifespan-extending interventions (acarbose, 17α-estradiol, rapamycin, and calorie restriction) generally tighten the regulation of biological modules. These tightening patterns are similar across the interventions, particularly in processes such as fatty acid oxidation, immune response, and stress response. Differences in DIRAC patterns between proteins and transcripts highlight specific modules which may be tightened via augmented cap-independent translation. Moreover, the systemic shifts in fatty acid metabolism are supported through integrated analysis of liver transcriptomics data with a mouse genome-scale metabolic model. Our findings highlight the power of systems-level approaches for identifying and characterizing the biological processes involved in aging and longevity.

Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate Chronic Obstructive Pulmonary Disease.

The integration of transcriptomic and proteomic data from lung tissue with chronic obstructive pulmonary disease (COPD)-associated genetic variants could provide insight into the biological mechanisms of COPD. Here, we assessed associations between lung transcriptomics and proteomics with COPD in 98 subjects from the Lung Tissue Research Consortium. Low correlations between transcriptomics and proteomics were generally observed, but higher correlations were found for COPD-associated proteins. We integrated COPD risk SNPs or SNPs near COPD-associated proteins with lung transcripts and proteins to identify regulatory cis-quantitative trait loci (QTLs). Significant expression QTLs (eQTLs) and protein QTLs (pQTLs) were found regulating multiple COPD-associated biomarkers. We investigated mediated associations from significant pQTLs through transcripts to protein levels of COPD-associated proteins. We also attempted to identify colocalized effects between COPD genome-wide association studies and eQTL and pQTL signals. Evidence was found for colocalization between COPD genome-wide association study signals and a pQTL for RHOB and an eQTL for DSP. We applied weighted gene co-expression network analysis to find consensus COPD-associated network modules. Two network modules generated by consensus weighted gene co-expression network analysis were associated with COPD with a false discovery rate lower than 0.05. One network module is related to the catenin complex, and the other module is related to plasma membrane components. In summary, multiple cis-acting determinants of transcripts and proteins associated with COPD were identified. Colocalization analysis, mediation analysis, and correlation-based network analysis of multiple omics data may identify key genes and proteins that work together to influence COPD pathogenesis.

Trans-Proteomic Pipeline: Robust Mass Spectrometry-Based Proteomics Data Analysis Suite.

The Trans-Proteomic Pipeline (TPP) mass spectrometry data analysis suite has been in continual development and refinement since its first tools, PeptideProphet and ProteinProphet, were published 20 years ago. The current release provides a large complement of tools for spectrum processing, spectrum searching, search validation, abundance computation, protein inference, and more. Many of the tools include machine-learning modeling to extract the most information from data sets and build robust statistical models to compute the probabilities that derived information is correct. Here we present the latest information on the many TPP tools, and how TPP can be deployed on various platforms from personal Windows laptops to Linux clusters and expansive cloud computing environments. We describe tutorials on how to use TPP in a variety of ways and describe synergistic projects that leverage TPP. We conclude with plans for continued development of TPP.

Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline.

Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.

The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data.

The Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database.

Residential proximity to oil and gas production sites and hematologic malignancies: A case-control study.

BACKGROUND: We investigated the association between residential proximity to oil and gas production sites and hematologic malignancies, due to a cancer cluster in the German state of Lower Saxony. METHODS: A registry-based case-control study was conducted including 3978 cases of hematologic malignancies diagnosed within 2013-2016 and 15,912 frequency-matched controls randomly drawn by population registries. Residential proximity to 5333 oil and gas production sites at the time of diagnosis was calculated. Unconditional logistic regression models were used to estimate the association between living within 1 km of any exposure site and developing a hematologic malignancy. Models were adjusted for matching variables sex, age group, district, and year of diagnosis as well as for proximity to main streets and to agricultural land. RESULTS: We found no association between the development of hematologic malignancies and the proximity to all oil and gas production sites (odds ratio: 0.97; 95% confidence interval: 0.85, 1.11). Focusing on gas production sites increased the odds of developing hematologic cancer (odds ratio: 1.19; 95% confidence interval: 0.97, 1.45). In stratified analyses, associations were stronger in women and for acute myeloblastic leukemia. We also found an association in the district where the initial cluster occurred. CONCLUSIONS: Our results suggest that residential proximity to oil and gas production is not a risk factor for all hematologic malignancies in general. Sporadic and past exposures are the most likely scenarios for mechanisms involving oil and gas production, leading to increased risk for certain subtypes of cancer in certain populations.

Discovery and Visualization of Uncharacterized Drug-Protein Adducts Using Mass Spectrometry.

Drugs are often metabolized to reactive intermediates that form protein adducts. Adducts can inhibit protein activity, elicit immune responses, and cause life-threatening adverse drug reactions. The masses of reactive metabolites are frequently unknown, rendering traditional mass spectrometry-based proteomics approaches incapable of adduct identification. Here, we present Magnum, an open-mass search algorithm optimized for adduct identification, and Limelight, a web-based data processing package for analysis and visualization of data from all existing algorithms. Limelight incorporates tools for sample comparisons and xenobiotic-adduct discovery. We validate our tools with three drug/protein combinations and apply our label-free workflow to identify novel xenobiotic-protein adducts in CYP3A4. Our new methods and software enable accurate identification of xenobiotic-protein adducts with no prior knowledge of adduct masses or protein targets. Magnum outperforms existing label-free tools in xenobiotic-protein adduct discovery, while Limelight fulfills a major need in the rapidly developing field of open-mass searching, which until now lacked comprehensive data visualization tools.

Plasmodium falciparum Calcium-Dependent Protein Kinase 4 is Critical for Male Gametogenesis and Transmission to the Mosquito Vector.

Gametocytes of the malaria parasite Plasmodium are taken up by the mosquito vector with an infectious blood meal, representing a critical stage for parasite transmission. Calcium-independent protein kinases (CDPKs) play key roles in calcium-mediated signaling across the complex life cycle of the parasite. We sought to understand their role in human parasite transmission from the host to the mosquito vector and thus investigated the role of the human-infective parasite Plasmodium falciparum CDPK4 in the parasite life cycle. P. falciparum cdpk4- parasites created by targeted gene deletion showed no effect in blood stage development or gametocyte development. However, cdpk4- parasites showed a severe defect in male gametogenesis and the emergence of flagellated male gametes. To understand the molecular underpinnings of this defect, we performed mass spectrometry-based phosphoproteomic analyses of wild-type and Plasmodium falciparum cdpk4- late gametocyte stages to identify key CDPK4-mediated phosphorylation events that may be important for the regulation of male gametogenesis. We further employed in vitro assays to identify these putative substrates of Plasmodium falciparum CDPK4. This indicated that CDPK4 regulates male gametogenesis by directly or indirectly controlling key essential events, such as DNA replication, mRNA translation, and cell motility. Taken together, our work demonstrates that PfCDPK4 is a central kinase that regulates exflagellation and thereby is critical for parasite transmission to the mosquito vector. IMPORTANCE Transmission of the malaria parasite to the mosquito vector is critical for the completion of the sexual stage of the parasite life cycle and is dependent on the release of male gametes from the gametocyte body inside the mosquito midgut. In the present study, we demonstrate that PfCDPK4 is critical for male gametogenesis and is involved in phosphorylation of proteins essential for male gamete emergence. Targeting PfCDPK4 and its substrates may provide insights into achieving effective malaria transmission-blocking strategies.

Hallstatt miners consumed blue cheese and beer during the Iron Age and retained a non-Westernized gut microbiome until the Baroque period.

We subjected human paleofeces dating from the Bronze Age to the Baroque period (18th century AD) to in-depth microscopic, metagenomic, and proteomic analyses. The paleofeces were preserved in the underground salt mines of the UNESCO World Heritage site of Hallstatt in Austria. This allowed us to reconstruct the diet of the former population and gain insights into their ancient gut microbiome composition. Our dietary survey identified bran and glumes of different cereals as some of the most prevalent plant fragments. This highly fibrous, carbohydrate-rich diet was supplemented with proteins from broad beans and occasionally with fruits, nuts, or animal food products. Due to these traditional dietary habits, all ancient miners up to the Baroque period have gut microbiome structures akin to modern non-Westernized individuals whose diets are also mainly composed of unprocessed foods and fresh fruits and vegetables. This may indicate a shift in the gut community composition of modern Westernized populations due to quite recent dietary and lifestyle changes. When we extended our microbial survey to fungi present in the paleofeces, in one of the Iron Age samples, we observed a high abundance of Penicillium roqueforti and Saccharomyces cerevisiae DNA. Genome-wide analysis indicates that both fungi were involved in food fermentation and provides the first molecular evidence for blue cheese and beer consumption in Iron Age Europe.

Lung proteomic biomarkers associated with chronic obstructive pulmonary disease.

Identifying protein biomarkers for chronic obstructive pulmonary disease (COPD) has been challenging. Most previous studies have used individual proteins or preselected protein panels measured in blood samples. Mass spectrometry proteomic studies of lung tissue have been based on small sample sizes. We used mass spectrometry proteomic approaches to discover protein biomarkers from 150 lung tissue samples representing COPD cases and controls. Top COPD-associated proteins were identified based on multiple linear regression analysis with false discovery rate (FDR) < 0.05. Correlations between pairs of COPD-associated proteins were examined. Machine learning models were also evaluated to identify potential combinations of protein biomarkers related to COPD. We identified 4,407 proteins passing quality controls. Twenty-five proteins were significantly associated with COPD at FDR < 0.05, including interleukin 33, ferritin (light chain and heavy chain), and two proteins related to caveolae (CAV1 and CAVIN1). Multiple previously reported plasma protein biomarkers for COPD were not significantly associated with proteomic analysis of COPD in lung tissue, although RAGE was borderline significant. Eleven pairs of top significant proteins were highly correlated (r > 0.8), including several strongly correlated with RAGE (EHD2 and CAVIN1). Machine learning models using Random Forests with the top 5% of protein biomarkers demonstrated reasonable accuracy (0.707) and area under the curve (0.714) for COPD prediction. Mass spectrometry-based proteomic analysis of lung tissue is a promising approach for the identification of biomarkers for COPD.

A redox-active crosslinker reveals an essential and inhibitable oxidative folding network in the endoplasmic reticulum of malaria parasites.

Malaria remains a major global health problem, creating a constant need for research to identify druggable weaknesses in P. falciparum biology. As important components of cellular redox biology, members of the Thioredoxin (Trx) superfamily of proteins have received interest as potential drug targets in Apicomplexans. However, the function and essentiality of endoplasmic reticulum (ER)-localized Trx-domain proteins within P. falciparum has not been investigated. We generated conditional mutants of the protein PfJ2-an ER chaperone and member of the Trx superfamily-and show that it is essential for asexual parasite survival. Using a crosslinker specific for redox-active cysteines, we identified PfJ2 substrates as PfPDI8 and PfPDI11, both members of the Trx superfamily as well, which suggests a redox-regulatory role for PfJ2. Knockdown of these PDIs in PfJ2 conditional mutants show that PfPDI11 may not be essential. However, PfPDI8 is required for asexual growth and our data suggest it may work in a complex with PfJ2 and other ER chaperones. Finally, we show that the redox interactions between these Trx-domain proteins in the parasite ER and their substrates are sensitive to small molecule inhibition. Together these data build a model for how Trx-domain proteins in the P. falciparum ER work together to assist protein folding and demonstrate the suitability of ER-localized Trx-domain proteins for antimalarial drug development.

SPACEPro: A Software Tool for Analysis of Protein Sample Cleavage for Tandem Mass Spectrometry.

The efficiency of shotgun proteomic analysis is dependent on the reproducibility of the peptide cleavage process during sample preparation. To generate rapid and useful metrics for peptide cleavage efficiency, as in enzymatic or chemical cleavage, SPACEPro was developed to evaluate efficiency and reproducibility of protein cleavage in peptide samples following data-dependent analysis by mass spectrometry. SPACEPro analyzes samples at the peptide-spectrum match (PSM), peptide, and protein levels to provide a comprehensive representation of the overall sample processing to peptides. All output is provided in human-readable text and JSON files that can be further processed to assess the cleavage efficiency on proteins within the sample. SPACEPro provides a snapshot of the protein cleavage efficiency through very minimal effort so that the user is informed of the quality of the sample processing efficiency and can accordingly develop protocols to improve the initial sample preparation for subsequent analyses.