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ABID
(2022)
In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
IsoCor
(2022)
Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.
MALDI-TOF-MS-based identification of monoclonal murine anti-SARS-CoV-2 antibodies within one hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used thirty-five monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied onto the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 45 minutes and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 °C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0 (https://gets.shinyapps.io/ABID/). This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
Molekülmassenspektrometrie entwickelt sich weg von klassischer Target- hin zu Nontarget-Analytik. Elementmassenspektrometrie liefert hohe Ortsauflösung beim Element-Imaging und analysiert einzelne Zellen. Aufgrund der Fortschritte bei den Geräten für Timeof-Flight-Massenspektrometrie mit induktiv gekoppeltem Plasma (ICPToF-MS) lässt sich das gesamte Periodensystem der Elemente in kurzen transienten Signalen quasi-simultan massenspektrometrisch erfassen.
T cells need to adapt their cellular metabolism for effector cell differentiation. This relies on alterations in mitochondrial physiology. Which signals and molecules regulate those alterations remains unclear. We recently reported, that the mitochondrial protein TCAIM inhibits activation-induced changes in mitochondrial morphology and function and thus, CD effector T cell formation. Using conditional TCAIM knock-in (KI) and knockout (KO) mice, w now show that it also applies to CD8+ T cells and more importantly, delineate the molecular processes in mitochondria by which TCAIM controls effector cell differentiation. TCAIM KI resulted in reduced activation-induced HIF1α protein expression. Metabolomics and transcriptional data in combination with mathematical flux modeling revealed an impaired induction of anabolic pathways, especially of the mevalonate pathway and cholesterol biosynthesis in TCAIM KI CD8+ T cells. Addition of cholesterol completely rescued HIF1α protein expression, activation and proliferation of TCAIM KI CD8+ T cells. At the molecular level, TCAIM delayed activation-induced mitochondria-ER contact (MERC) formation by binding to MERC promoting proteins such as RMD3 and VDAC2. In summary, we demonstrate that TCAIM suppresses effector cell differentiation by inhibiting MERC formation, which induce HIF1α-mediated increase in cellular metabolism and cholesterol biosynthesis.
Multiple works have studied possible associations between human leukocyte antigen (HLA) alleles and end stage renal disease (ESRD). However, there are several contradictions in these previous works and no consistent HLA associations with ESRD itself have been identified. Most of these works have several limitations, for instance, the population size was too small, or only limited HLA loci were studied. The presented work aims to revisit the association between ESRD and HLA antigens while taking in to account the previously overlooked limitations. Here, we compared the HLA polymorphism (at HLA-A, -B, -C, -DRB1, -DQB1 and DQA1 loci) in ESRD patients (n=497) and controls (n=672). Our data identified several HLA alleles that displayed a significant positive or negative association with ESRD. We also determined whether heterozygosity or homozygosity of the ESRD-associated HLA alleles at different loci could modify the prevalence of the disease. Few HLA allele combinations displayed significant associations with ESRD among which HLA-A*3 –HLA-A*26 combination showed the highest strength of association (OR= 4.488, P≤ 0.05) with ESRD. However, the age of ESRD onset was not affected by HLA allele combinations at different loci. Most of the previous works have studied the association of HLA with ESRD in homogeneous ethnic groups and have interpreted their data accordingly. Here, we also performed an extensive literature analysis to determine whether the association of HLA to ESRD can be similar across different ethnic groups. This analysis showed that at least for certain alleles, the association of HLA to ESRD can be similar in different ethnic groups. For instance, HLA-A*11, HLA-DRB1*11, and HLA-DRB1*4 all showed significant positive associations with ESRD in different ethnic groups. The findings of our study will help in determining possible protective or susceptible roles of various HLA alleles in ESRD.
Cancer cell lipid class homeostasis is altered under nutrient-deprivation but stable under hypoxia
(2018)
Under oxygen/nutrient deprivation cancer cells modify the Balance between fatty acid (FA) synthesis and uptake, which alters the levels of individual triglyceride or phospholipid sub-species. These modifications may affect survival and drug-uptake in cancer cells. Here, we aimed to attain a more holistic overview of the lipidomic profiles of cancer cells under stress and assess the changes in Major lipid-classes. First, expressions of markers of FA synthesis/uptake in cancer cells were assessed and found to be differentially regulated under metabolic stress. Next, we performed a broad lipidomics assay, comprising 244 lipids from six major classes, which allowed us to investigate robust stress induced changes in median levels of different lipid classes -additionally stratified by fatty acid side chain saturation status. The lipidomic profiles of cancer cells were predominantly affected by nutrient-deprivation. Neutral lipid compositions were markedly modified under serum-deprivation and, strikingly, the cellular level of triglyceride subspecies decreased with increasing number of double bonds in their fatty acyl chains. In contrast, cancer cells maintained lipid class homeostasis under hypoxic stress. We conclude that although the levels of individual lipid moieties alter under hypoxia, the robust averages of broader lipid class remain unchanged.
MYCN is a transcription factor that is aberrantly expressed in many tumor types and is often correlated with poor patient prognosis. Recently, several lines of evidence pointed to the fact that oncogenic activation of MYC family proteins is concomitant with reprogramming of tumor cells to cope with an enhanced need for metabolites during cell growth. These adaptions are driven by the ability of MYC proteins to act as transcriptional amplifiers in a tissue-of-origin specific manner. Here, we describe the effects of MYCN overexpression on metabolic reprogramming in neuroblastoma cells. Ectopic expression of MYCN induced a glycolytic switch that was concomitant with enhanced sensitivity towards 2-deoxyglucose, an inhibitor of glycolysis. Moreover, global metabolic profiling revealed extensive alterations in the cellular metabolome resulting from overexpression of MYCN. Limited supply with either of the two main carbon sources, glucose or glutamine, resulted in distinct shifts in steady-state metabolite levels and significant changes in glutathione metabolism. Interestingly, interference with glutamine-glutamate conversion preferentially blocked proliferation of MYCN overexpressing cells, when glutamine levels were reduced. Thus, our study uncovered MYCN induction and nutrient levels as important metabolic master switches in neuroblastoma cells and identified critical nodes that restrict tumor cell proliferation.
Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.
Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.
Gas chromatography using atmospheric pressure chemical ionization coupled to mass spectrometry (GC/APCI-MS) is an emerging metabolomics platform, providing much-enhanced capabilities for structural mass spectrometry as compared to traditional electron ionization (EI)-based techniques. To exploit the potential of GC/APCI-MS for more comprehensive metabolite annotation, a major bottleneck in metabolomics, we here present the novel R-based tool InterpretMSSpectrum assisting in the common task of annotating and evaluating in-source mass spectra as obtained from typical full-scan experiments. After passing a list of mass-intensity pairs, InterpretMSSpectrum locates the molecular ion (M0), fragment, and adduct peaks, calculates their most likely sum formula combination, and graphically summarizes results as an annotated mass spectrum. Using (modifiable) filter rules for the commonly used methoximated-trimethylsilylated (MeOx-TMS) derivatives, covering elemental composition, typical substructures, neutral losses, and adducts, InterpretMSSpectrum significantly reduces the number of sum formula candidates, minimizing manual effort for postprocessing candidate lists. We demonstrate the utility of InterpretMSSpectrum for 86 in-source spectra of derivatized standard compounds, in which rank-1 sum formula assignments were achieved in 84% of the cases, compared to only 63% when using mass and isotope information on the M0 alone. We further use, for the first time, automated annotation to evaluate the purity of pseudospectra generated by different metabolomics preprocessing tools, showing that automated annotation can serve as an integrative quality measure for peak picking/deconvolution methods. As an R package, InterpretMSSpectrum integrates flexibly into existing metabolomics pipelines and is freely available from CRAN (https://cran.r-project.org/).
Data file (RData) containing measurement data recorded during the production process of the Certified Reference Material BAM-A001 containing Polycyclic Aromatic Hydrocarbons (PAH) in olive oil. The data can be most conveniently openend using the Shiny-App eCerto which is accessible at https://www.bam.de/eCerto.
Metabolomics
(2024)