Browsing by Author "Bräcker, Julia"

Now showing 1 - 4 of 4

Open Access
Flanking sequences influence the activity of TET1 and TET2 methylcytosine dioxygenases and affect genomic 5hmC patterns
(2022) Adam, Sabrina; Bräcker, Julia; Klingel, Viviane; Osteresch, Bernd; Radde, Nicole E.; Brockmeyer, Jens; Bashtrykov, Pavel; Jeltsch, Albert
TET dioxygenases convert 5-methylcytosine (5mC) preferentially in a CpG context into 5-hydroxymethylcytosine (5hmC) and higher oxidized forms, thereby initiating DNA demethylation, but details regarding the effects of the DNA sequences flanking the target 5mC site on TET activity are unknown. We investigated oxidation of libraries of DNA substrates containing one 5mC or 5hmC residue in randomized sequence context using single molecule readout of oxidation activity and sequence and show pronounced 20 and 70-fold flanking sequence effects on the catalytic activities of TET1 and TET2, respectively. Flanking sequence preferences were similar for TET1 and TET2 and also for 5mC and 5hmC substrates. Enhanced flanking sequence preferences were observed at non-CpG sites together with profound effects of flanking sequences on the specificity of TET2. TET flanking sequence preferences are reflected in genome-wide and local patterns of 5hmC and DNA demethylation in human and mouse cells indicating that they influence genomic DNA modification patterns in combination with locus specific targeting of TET enzymes.
Open Access
Identification and characterization of IgE‐reactive proteins and a new allergen (Cic a 1.01) from chickpea (Cicer arietinum)
(2020) Wangorsch, Andrea; Kulkarni, Anuja; Jamin, Annette; Spiric, Jelena; Bräcker, Julia; Brockmeyer, Jens; Mahler, Vera; Blanca‐López, Natalia; Ferrer, Marta; Blanca, Miguel; Torres, Maria; Gomez, Paqui; Bartra, Joan; García‐Moral, Alba; Goikoetxea, María J.; Vieths, Stefan; Toda, Masako; Zoccatelli, Gianni; Scheurer, Stephan
Chickpea (Cicer arietinum) allergy has frequently been reported particularly in Spain and India. Nevertheless, chickpea allergens are poorly characterized. The authors aim to identify and characterize potential allergens from chickpea. Candidate proteins are selected by an in silico approach or immunoglobuline E (IgE)-testing. Potential allergens are prepared as recombinant or natural proteins and characterized for structural integrity by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), circular dichroism (CD)-spectroscopy, and mass spectrometry (MS) analysis. IgE-sensitization pattern of Spanish chickpea allergic and German peanut and birch pollen sensitized patients are investigated using chickpea extracts and purified proteins. Chickpea allergic patients show individual and heterogeneous IgE-sensitization profiles with extracts from raw and boiled chickpeas. Chickpea proteins pathogenesis related protein family 10 (PR-10), a late embryogenesis abundant protein (LEA/DC-8), and a vicilin-containing fraction, but not 2S albumin, shows IgE reactivity with sera from chickpea, birch pollen, and peanut sensitized patients. Remarkably, allergenic vicilin, DC-8, and PR-10 are detected in the extract of boiled chickpeas. Several IgE-reactive chickpea allergens are identified. For the first time a yet not classified DC-8 protein is characterized as minor allergen (Cic a 1). Finally, the data suggest a potential risk for peanut allergic patients by IgE cross-reactivity with homologous chickpea proteins.
Open Access
Protecting sensitive data in the information age : state of the art and future prospects
(2022) Stach, Christoph; Gritti, Clémentine; Bräcker, Julia; Behringer, Michael; Mitschang, Bernhard
The present information age is characterized by an ever-increasing digitalization. Smart devices quantify our entire lives. These collected data provide the foundation for data-driven services called smart services. They are able to adapt to a given context and thus tailor their functionalities to the user’s needs. It is therefore not surprising that their main resource, namely data, is nowadays a valuable commodity that can also be traded. However, this trend does not only have positive sides, as the gathered data reveal a lot of information about various data subjects. To prevent uncontrolled insights into private or confidential matters, data protection laws restrict the processing of sensitive data. One key factor in this regard is user-friendly privacy mechanisms. In this paper, we therefore assess current state-of-the-art privacy mechanisms. To this end, we initially identify forms of data processing applied by smart services. We then discuss privacy mechanisms suited for these use cases. Our findings reveal that current state-of-the-art privacy mechanisms provide good protection in principle, but there is no compelling one-size-fits-all privacy approach. This leads to further questions regarding the practicality of these mechanisms, which we present in the form of seven thought-provoking propositions.
Open Access
SMARTEN : a sample-based approach towards privacy-friendly data refinement
(2022) Stach, Christoph; Behringer, Michael; Bräcker, Julia; Gritti, Clémentine; Mitschang, Bernhard
Two factors are crucial for the effective operation of modern-day smart services: Initially, IoT-enabled technologies have to capture and combine huge amounts of data on data subjects. Then, all these data have to be processed exhaustively by means of techniques from the area of big data analytics. With regard to the latter, thorough data refinement in terms of data cleansing and data transformation is the decisive cornerstone. Studies show that data refinement reaches its full potential only by involving domain experts in the process. However, this means that these experts need full insight into the data in order to be able to identify and resolve any issues therein, e.g., by correcting or removing inaccurate, incorrect, or irrelevant data records. In particular for sensitive data (e.g., private data or confidential data), this poses a problem, since these data are thereby disclosed to third parties such as domain experts. To this end, we introduce SMARTEN, a sample-based approach towards privacy-friendly data refinement to smarten up big data analytics and smart services. SMARTEN applies a revised data refinement process that fully involves domain experts in data pre-processing but does not expose any sensitive data to them or any other third-party. To achieve this, domain experts obtain a representative sample of the entire data set that meets all privacy policies and confidentiality guidelines. Based on this sample, domain experts define data cleaning and transformation steps. Subsequently, these steps are converted into executable data refinement rules and applied to the entire data set. Domain experts can request further samples and define further rules until the data quality required for the intended use case is reached. Evaluation results confirm that our approach is effective in terms of both data quality and data privacy.