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Burdukiewicz, M.

Publications and source records attributed to Burdukiewicz, M..

3 recordsLinked to original sources

Functional amyloids in the microbiomes of a rat Parkinson's disease model and wild-type rats

Cross-seeding between amyloidogenic proteins in the gut is receiving increasing attention as a possible mechanism for initiation or acceleration of amyloid formation by aggregation-prone proteins such as SN, which is central in the development of Parkinsons disease. This is particularly pertinent in view of the growing number of functional (i.e. benign and useful) amyloid proteins discovered in bacteria. Here we identify two functional amyloid proteins, Pr12 and Pr17, in fecal matter from Parkinsons disease transgenic rats and their wild type counterparts, based on their stability against dissolution by formic acid. Both proteins show robust aggregation into ThT-positive aggregates that contain higher-order {beta}-sheets and have a fibrillar morphology, indicative of amyloid proteins. In addition, Pr17 aggregates formed in vitro showed significant resistance against formic acid, suggesting an ability to form highly stable amyloid. Treatment with proteinase K revealed a protected core of approx. 9 kDa. Neither Pr12 nor Pr17, however, affected SN aggregation in vitro. Thus, amyloidogenicity does not per se lead to an ability to cross-seed fibrillation of SN. Our results support the use of proteomics and formic acid to identify amyloid protein in complex mixtures and indicates the existence of numerous functional amyloid proteins in microbiomes. IMPORTANCEThe bacterial microbiome in the gastrointestinal tract is increasingly seen as important for human health and disease. One area of particular interest is that of neurodegenerative diseases such as Parkinsons which involve pathological aggregation into amyloid of human proteins such as - synuclein (SN). Bacteria are known to form benign or functional amyloid, some of which may initiate unwanted aggregation of e.g. SN in the enteric nervous system through cross-seeding via contact with the microbiome. Here we show that the rat microbiome contains several proteins which form this type of amyloid aggregate both in vivo and in vitro. Although the two proteins we investigate in depth do not directly promote SN aggregation, our work shows that the microbiome potentially harbors a significant number of bacterial amyloid which could play a role in human physiology at various levels.

biophysics↗

PCRedux: A Data Mining and Machine Learning Toolkit for qPCR Experiments

MotivationQuantitative Real-time PCR (qPCR) is a widely used -omics method for the precise quantification of nucleic acids, in which the result is associated with the presence/absence or quantity of a specific nucleic acid sequence. As the amount of qPCR data increases worldwide, the manual assessment of results becomes challenging and difficult to reproduce. To overcome this, some automatable characteristics of amplification curves have been described in the literature, often with an appropriate "rule of thumb". ResultsWe developed PCRedux to analyze and calculate 90 numerical qPCR amplification curve descriptors ( features") from large datasets of qPCR amplification curves that are aimed for interpretable machine learning and development of decision support systems. In a case study of a diverse dataset with 3181 positive, negative and ambiguous amplification curves, as assessed by three human raters, we demonstrate a sensitivity >99 % and specificity >97 % in detecting positive and negative amplification. PCRedux is unique as it goes beyond traditional qPCR analysis to capture curvature properties that improve the characterization and classification of amplification curves. The calculation of the features is reproducible and objective, since R is used as a controllable working environment. PCRedux is not a black box, but open source software following on the principle of mathematically interpretable features. These can be combined with user-defined labels for automatic multi-category classification and regression in machine learning. Availabilityhttps://cran.r-project.org/package=PCRedux. Web server: http://shtest.evrogen.net/PCRedux-app/. Documentation: https://PCRuniversum.github.io/PCRedux/.

bioinformatics↗

MegaGO: a fast yet powerful approach to assess functional similarity across meta-omics data sets

The study of microbiomes has gained in importance over the past few years, and has led to the fields of metagenomics, metatranscriptomics and metaproteomics. While initially focused on the study of biodiversity within these communities the emphasis has increasingly shifted to the study of (changes in) the complete set of functions available in these communities. A key tool to study this functional complement of a microbiome is Gene Ontology (GO) term analysis. However, comparing large sets of GO terms is not an easy task due to the deeply branched nature of GO, which limits the utility of exact term matching. To solve this problem, we here present MegaGO, a user-friendly tool that relies on semantic similarity between GO terms to compute functional similarity between two data sets. MegaGO is highly performant: each set can contain thousands of GO terms, and results are calculated in a matter of seconds. MegaGO is available as a web application at https://megago.ugent.be and installable via pip as a standalone command line tool and reusable software library. All code is open source under the MIT license, and is available at https://github.com/MEGA-GO/.

bioinformatics↗