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Glioblastoma is the most common malignant primary brain tumor. To date, clinically relevant biomarkers are restricted to isocitrate dehydrogenase (IDH) gene 1 or 2 mutations and O6-methylguanine DNA methyltransferase (MGMT) promoter methylation. Long non-coding RNAs (lncRNAs) have been shown to contribute to glioblastoma pathogenesis and could potentially serve as novel biomarkers. The clinical significance of HOXA Transcript Antisense RNA, Myeloid-Specific 1 (HOTAIRM1) was determined by analyzing HOTAIRM1 in multiple glioblastoma gene expression data sets for associations with prognosis, as well as, IDH mutation and MGMT promoter methylation status. Finally, the role of HOTAIRM1 in glioblastoma biology and radiotherapy resistance was characterized in vitro and in vivo. We identified HOTAIRM1 as a candidate lncRNA whose up-regulation is significantly associated with shorter survival of glioblastoma patients, independent from IDH mutation and MGMT promoter methylation. Glioblastoma cell line models uniformly showed reduced cell viability, decreased invasive growth and diminished colony formation capacity upon HOTAIRM1 down-regulation. Integrated proteogenomic analyses revealed impaired mitochondrial function and determination of reactive oxygen species (ROS) levels confirmed increased ROS levels upon HOTAIRM1 knock-down. HOTAIRM1 knock-down decreased expression of transglutaminase 2 (TGM2), a candidate protein implicated in mitochondrial function, and knock-down of TGM2 mimicked the phenotype of HOTAIRM1 down-regulation in glioblastoma cells. Moreover, HOTAIRM1 modulates radiosensitivity of glioblastoma cells both in vitro and in vivo. Our data support a role for HOTAIRM1 as a driver of biological aggressiveness, radioresistance and poor outcome in glioblastoma. Targeting HOTAIRM1 may be a promising new therapeutic approach.
Top-down and bottom-up approaches are the general methods used to analyse proteomic samples today, however, the bottom-up approach has been dominant in the last decade. Establishing a bottom-up method involves not only the choice of adequate instruments and the optimisation of the experimental parameters, but also choosing the right experimental conditions and sample preparation steps. LC-ESI MS/MS has widely been used in this field due to its advanced automation. The primary objective of the present study was to establish a sensitive high-throughput nLC-MALDI MS/MS method for the identification and characterisation of proteins in biological samples. The method establishment included optimisation and validation of parameters such as the capillaries in the HPLC systems, gradient slopes, column temperature, spotting frequencies or the MS and MS/MS acquisition methods. The optimisation was performed using two HPLC-systems (Agilent 1100 series and Proxeon Easy nLC system), three spotters and the 4800 MALDI-TOF/TOF analyzer. Furthermore, samples preparation protocols were modified to fit to the established nLCMALDI- TOF/TOF-platform. The potentials of this method was demonstrated by the successful analysis of complex protein samples isolated from lipid particles, pre-adipocytes/adipocytes tissues, membrane proteins and proteins pulled-down from protein-proteins interaction studies. Despite the small amount of proteins in the lipid particles or oil bodies, and the challenges encountered in studying such proteins, 41(6 novel + 14 mammal specific + 21 visceral specific) proteins were added to the already existing proteins of the secretome of human subcutaneous (pre)adipocytes and 6 novel proteins localised in the yeast lipid particles. Protein-protein interaction studies present another area of application. Here the analytical challenges are mostly due to the loss of binding partner upon sample clean-up and to differentiate from non-specific background. Novel interaction partners for AF4•MLL and AF4 protein complex were identified. Furthermore, a novel sample protocol for the analysis of membrane proteins, based on the less specific protease, elastase, was established. Compared to trypsin, a higher sequence coverage and higher coverage of the transmembrane domains were achieved. The use of this enzyme in proteomics has been limited because of its non specific cleavage. However, from the results obtained in these studies, elastase was found to cleave preferentially at the C-terminal site of the amino acids AVLIST. The advantage of the established protocol over conventional protocols is that the same enzyme can be used for shaving of the soluble dormains of intact proteins in membranes and the digestion of the hydrophobic domain after solubilisation. Furthermore, the solvents used are compatible with the nLC-MALDI method setup. In addition, it was also shown that for less specific enzymes, a higher mass accuracy is required to reduce the rate of false positive identifications, since current search engines are not perfectly adapted for these types of enzymes. A brief statistical analysis of the MS/MS data obtained from the LC-MALDI TOF/TOF system showed that for less specific enzymes, under high-energy collision conditions, approximately 43 % of the fragment ions could not be matched to the known y- b type ions and their resultant internal fragments. This limitation greatly influenced the search results. However, this limitation can be overcome by modifying the N-terminal amino acids with basic moieties such as TMT. The use of elastase as a digestion enzyme in proteomic workflow further increased the complexity of the sample. Therefore, orthogonal multidimensional separation was necessary. Offgel-IEF was used as the separation technique for the first dimension. Here peptides are separated according to the pI. However, the acquired samples could not be loaded to the nLC due to the high viscosity of the concentrated samples when using the standard protocol. In order to achieve compatibility of the Offgel-IEF to the nLC-MALDI-TOF/TOF-platform, the separation protocol of the Offgel-IEF was modified by omitting the glycerol, which was the cause of the viscous solution. The novel glycerol free protocol is advantageous over the conventional method because the samples could directly be picked-up and loaded onto the pre-column without resulting in an increase in back pressure or a subsequent pre-column clogging. The glycerol free protocol was then assessed using purple membrane and membrane fraction of C. glutamicum. The results obtained were comparable to those applied in published reports. Therefore, the absence of glycerol did not affect the separation efficiency of the Offgel-IEF. In addition the applicability of elastase and the glycerol free Offgel-IEF for quantitation of membrane proteins was assessed. Most of the unique peptides identified were in the acidic region and 85 % were focused only into one fraction and approximately 95 % in only two fractions. These results are in accordance with previously published results (Lengqvist et al., 2007). When compared with theoretical digests of the proteins identified in this study, it can be concluded that basic moiety (TMT) on the peptide backbone, did not affect the separation efficiency of the Offgel-IEF. In an applied study, changes in the protein content of yeast strain grown in two different media were relatively quantified. For example, prominent proteins, such as the hexose tranporter proteins responsible for transporting glucose accross the membrane, were successfully quantified. Last but not least, the nLC-MALDI-TOF/TOF platform also served as a basis for the development of a high-throughput method for the identification of protein phosphorylation. The establishment of such a method using MALDI has been challenging due to the lack of sensitive matrices, such as CHCA for non-modified peptides, which exhibit a homogenous crystallisation and thus yield stable signal intensity over a long period of time in an automated setup. The first step of this method was the establishment of a matrix/matrix mixture with better crystal morphology and higher analyte signal intensity than the matrix of choice, i.e. DHB. From MS and MS/MS measurements of standard phosphopeptides, a combination of FCCA and CHAC in a 3:1 ratio and 3 mM NH4H2PO4 facilitated high analyte signal intensities and good fragmentation behaviour. Combining a custom-packed biphasic column for the enrichment of phosphopeptides, the applicability of the matrix mixture was assessed in anautomated phosphopeptide analysis using standard phosphopeptides spiked to a 20-fold excess BSA digest. These analyses showed that this method is reproducibile and both flow throughs can be analysed. Applying the method to the analysis of 2 standard phosphoproteins, alpha/beta-casein, and a leukemia related protein, ENL, 13 phosphopeptides from both alpha/beta-Casein and 13 phosphopeptides with 6 phosphorylation sites from the ENL were identified. As a general conclusion, it can be stated that the nLC-MALDI-TOF/TOF method established here in various modifications for different analytical purposes is a robust platform for proteomic analyses.
In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.
Regulation of protein turnover allows cells to react to their environment and maintain homeostasis. Proteins can show different turnover rates in different tissue, but little is known about protein turnover in different brain cell types. We used dynamic SILAC to determine half-lives of over 5100 proteins in rat primary hippocampal cultures as well as in neuron-enriched and glia-enriched cultures ranging from <1 to >20 days. In contrast to synaptic proteins, membrane proteins were relatively shorter-lived and mitochondrial proteins were longer-lived compared to the population. Half-lives also correlate with protein functions and the dynamics of the complexes they are incorporated in. Proteins in glia possessed shorter half-lives than the same proteins in neurons. The presence of glia sped up or slowed down the turnover of neuronal proteins. Our results demonstrate that both the cell-type of origin as well as the nature of the extracellular environment have potent influences on protein turnover.
Progranulin deficiency is associated with neurodegeneration in humans and in mice. The mechanisms likely involve progranulin-promoted removal of protein waste via autophagy. We performed a deep proteomic screen of the pre-frontal cortex in aged (13–15 months) female progranulin-deficient mice (GRN−/−) and mice with inducible neuron-specific overexpression of progranulin (SLICK-GRN-OE) versus the respective control mice. Proteins were extracted and analyzed per liquid chromatography/mass spectrometry (LC/MS) on a Thermo Scientific™ Q Exactive Plus equipped with an ultra-high performance liquid chromatography unit and a Nanospray Flex Ion-Source. Full Scan MS-data were acquired using Xcalibur and raw files were analyzed using the proteomics software Max Quant. The mouse reference proteome set from uniprot (June 2015) was used to identify peptides and proteins. The DiB data file is a reduced MaxQuant output and includes peptide and protein identification, accession numbers, protein and gene names, sequence coverage and label free quantification (LFQ) values of each sample. Differences in protein expression in genotypes are presented in "Progranulin overexpression in sensory neurons attenuates neuropathic pain in mice: Role of autophagy" (C. Altmann, S. Hardt, C. Fischer, J. Heidler, H.Y. Lim, A. Haussler, B. Albuquerque, B. Zimmer, C. Moser, C. Behrends, F. Koentgen, I. Wittig, M.H. Schmidt, A.M. Clement, T. Deller, I. Tegeder, 2016) [1].
The measurement of protein dynamics by proteomics to study cell remodeling has seen increased attention over the last years. This development is largely driven by a number of technological advances in proteomics methods. Pulsed stable isotope labeling in cell culture (SILAC) combined with tandem mass tag (TMT) labeling has evolved as a gold standard for profiling protein synthesis and degradation. While the experimental setup is similar to typical proteomics experiments, the data analysis proves more difficult: After peptide identification through search engines, data extraction requires either custom scripted pipelines or tedious manual table manipulations to extract the TMT-labeled heavy and light peaks of interest. To overcome this limitation, which deters researchers from using protein dynamic proteomics, we developed a user-friendly, browser-based application that allows easy and reproducible data analysis without the need for scripting experience. In addition, we provide a python package that can be implemented in established data analysis pipelines. We anticipate that this tool will ease data analysis and spark further research aimed at monitoring protein translation and degradation by proteomics.
H2S is an important signalling molecule involved in diverse biological processes. It mediates the formation of cysteine persulfides (R-S-SH), which affect the activity of target proteins. Like thiols, persulfides show reactivity towards electrophiles and behave similarly to other cysteine modifications in a biotin switch assay. In this manuscript, we report on qPerS-SID a mass spectrometry-based method allowing the isolation of persulfide containing peptides in the mammalian proteome. With this method, we demonstrated that H2S donors differ in their efficacy to induce persulfides in HEK293 cells. Furthermore, data analysis revealed that persulfide formation affects all subcellular compartments and various cellular processes. Negatively charged amino acids appeared more frequently adjacent to cysteines forming persulfides. We confirmed our proteomic data using pyruvate kinase M2 as a model protein and showed that several cysteine residues are prone to persulfide formation finally leading to its inactivation. Taken together, the site-specific identification of persulfides on a proteome scale can help to identify target proteins involved in H2S signalling and enlightens the biology of H2S and its releasing agents.
The ancestral SARS-CoV-2 strain that initiated the Covid-19 pandemic at the end of 2019 has rapidly mutated into multiple variants of concern with variable pathogenicity and increasing immune escape strategies. However, differences in host cellular antiviral responses upon infection with SARS-CoV-2 variants remain elusive. Leveraging whole-cell proteomics, we determined host signaling pathways that are differentially modulated upon infection with the clinical isolates of the ancestral SARS-CoV-2 B.1 and the variants of concern Delta and Omicron BA.1. Our findings illustrate alterations in the global host proteome landscape upon infection with SARS-CoV-2 variants and the resulting host immune responses. Additionally, viral proteome kinetics reveal declining levels of viral protein expression during Omicron BA.1 infection when compared to ancestral B.1 and Delta variants, consistent with its reduced replication rates. Moreover, molecular assays reveal deferral activation of specific host antiviral signaling upon Omicron BA.1 and BA.2 infections. Our study provides an overview of host proteome profile of multiple SARS-CoV-2 variants and brings forth a better understanding of the instigation of key immune signaling pathways causative for the differential pathogenicity of SARS-CoV-2 variants.
Regulatory required, classical toxicity studies for environmental hazard assessment are costly, time consuming, and often lack mechanistic insights about the toxic mode of action induced through a compound. In addition, classical toxicological non-human animal tests raise serious ethical concerns and are not well suited for high throughput screening approaches. Molecular biomarker-based screenings could be a suitable alternative for identifying particular hazardous effects (e.g. endocrine disruption, developmental neurotoxicity) in non-target organisms at the molecular level. This, however, requires a better mechanistic understanding of different toxic modes of action (MoA) to describe characteristic molecular key events and respective markers.
Ecotoxicgenomics, which uses modern day omic technologies and systems biology approaches to study toxicological responses at the molecular level, are a promising new way for elucidating
the processes through which chemicals cause adverse effects in environmental organisms. In this context, this PhD study was designated to investigate and describe MoA-characteristic
ecotoxicogenomic signatures in three ecotoxicologically important aquatic model organisms of different trophic levels (Danio rerio, Daphnia magna and Lemna minor).
Applying non-target transcriptomic and proteomic methodologies post chemical exposure, the aim was to identify robust functional profiles and reliable biomarker candidates with potential
predictive properties to allow for a differentiation among different MoA in these organisms. For the sublethal exposure studies in the zebrafish embryo model (96 hpf), the acute fish embryo toxicity test guideline (OECD 236) was used as conceptual framework. As different test compounds with known MoA, the thyroid hormone 3,3′,5-triiodothyronine (T3) and the thyrostatic 6-propyl-2-thiouracil (6-PTU), as well as six nerve- and muscle-targeting insecticides (abamectin, carbaryl, chlorpyrifos, fipronil, imidacloprid and methoxychlor) were evaluated. Furthermore, a novel sublethal immune challenge assay in early zebrafish embryos (48 hpf) was evaluated for its potential to assess immuno-suppressive effects at the gene expression level. Therefore, toxicogenomic profiles after an immune response inducing stimulus with and without prior clobetasol propionate (CP) treatment were compared. For the aquatic invertebrate D. magna, the study was performed with previously determined low effect concentrations (EC5 & EC20) of fipronil and imidacloprid according to the acute immobilization test in water flea (OECD 202). The aim was to compare toxicogenomic signatures of the GABA-gated chloride channel blocker (fipronil) and the nAChR agonist (imidacloprid). With similar low effect concentrations, a shortened 3 day version of the growth inhibition test with L. minor (OECD 221) was conducted to find molecular profiles differentiating between photosynthesis and HMG-CoA reductase inhibitory effects. Here, the biological interpretation of the molecular stress response profiles in L. minor due to the lack of functional annotation of the reference genome was particularly challenging. Therefore, an annotation workflow was developed based on protein sequence homology predicted from the genomic reference sequences.
With this PhD work, it was shown how transcriptomic, proteomic and computational systems biology approaches can be coupled with aquatic toxicological tests, to gain important mechanistic insights into adverse effects at the molecular level. In general, for the different investigated adverse effects for the different organisms, biomarker candidates were identified, which describe a potential functional link between impaired gene expressions and previously reported apical effects. For the assessed chemicals in the zebrafish embryo model, biomarker candidates for thyroid disruption as well as developmental toxicity targeting the heart and central nervous system were described. The biomarkers derived from nerve- and muscletargeting insecticides were associated with three major affected processes: (1) cardiac muscle cell development and functioning, (2) oxygen transport and hypoxic stress and (3) neuronal development and plasticity. To our knowledge, this is the first study linking neurotoxic insecticide exposure and affected expression of important regulatory genes for heart muscle (tcap, actc2) and forebrain (npas4a) development in a vertebrate model. The proposed immunosuppression assay found CP to affect innate immune induction by attenuating the response of genes involved in antigen processing, TLR signalling, NF-КB signalling, and complement activation ...
In recent decades, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review actual strategies and problems of the methods for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.