@article{StojanovićFuchsFiedleretal.2020,
  author    = {Stojanović, Stevan D. and Fuchs, Maximilian and Fiedler, Jan and Xiao, Ke and Meinecke, Anna and Just, Annette and Pich, Andreas and Thum, Thomas and Kunz, Meik},
  title     = {Comprehensive bioinformatics identifies key microRNA players in ATG7-deficient lung fibroblasts},
  series = {International Journal of Molecular Sciences},
  volume    = {21},
  journal   = {International Journal of Molecular Sciences},
  number    = {11},
  issn      = {1422-0067},
  doi       = {10.3390/ijms21114126},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285181},
  year      = {2020},
  abstract  = {Background: Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. Method: We have generated ATG7-knockout MRC-5 fibroblasts and performed mass spectrometry to generate a large-scale proteomics dataset. We further quantified the interactions between various proteins combining bioinformatics molecular network reconstruction and functional enrichment analysis. The predicted key regulatory miRs were validated via quantitative polymerase chain reaction. Results: The functional enrichment analysis of the 26 deregulated proteins showed decreased cellular trafficking, increased mitophagy and senescence as the major overarching processes in ATG7-deficient lung fibroblasts. The 26 proteins reconstitute a protein interactome of 46 nodes and miR-regulated interactome of 834 nodes. The miR network shows three functional cluster modules around miR-16-5p, miR-17-5p and let-7a-5p related to multiple deregulated proteins. Confirming these results in a biological setting, serially passaged wild-type and autophagy-deficient fibroblasts displayed senescence-dependent expression profiles of miR-16-5p and miR-17-5p. Conclusions: We have developed a bioinformatics proteome profiling approach that successfully identifies biologically relevant miR regulators from a proteomics dataset of the ATG-7-deficient milieu in lung fibroblasts, and thus may be used to elucidate key molecular players in complex fibrotic pathological processes. The approach is not limited to a specific cell-type and disease, thus highlighting its high relevance in proteome and non-coding RNA research.},
  language  = {en}
}
@article{KannKunzHansenetal.2020,
  author    = {Kann, Simone and Kunz, Meik and Hansen, Jessica and Sievertsen, J{\"u}rgen and Crespo, Jose J. and Loperena, Aristides and Arriens, Sandra and Dandekar, Thomas},
  title     = {Chagas disease: detection of Trypanosoma cruzi by a new, high-specific real time PCR},
  series = {Journal of Clinical Medicine},
  volume    = {9},
  journal   = {Journal of Clinical Medicine},
  number    = {5},
  issn      = {2077-0383},
  doi       = {10.3390/jcm9051517},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-205746},
  year      = {2020},
  abstract  = {Background: Chagas disease (CD) is a major burden in Latin America, expanding also to non-endemic countries. A gold standard to detect the CD causing pathogen Trypanosoma cruzi is currently not available. Existing real time polymerase chain reactions (RT-PCRs) lack sensitivity and/or specificity. We present a new, highly specific RT-PCR for the diagnosis and monitoring of CD. Material and Methods: We analyzed 352 serum samples from Indigenous people living in high endemic CD areas of Colombia using three leading RT-PCRs (k-DNA-, TCZ-, 18S rRNA-PCR), the newly developed one (NDO-PCR), a Rapid Test/enzyme-linked immuno sorbent assay (ELISA), and immunofluorescence. Eighty-seven PCR-products were verified by sequence analysis after plasmid vector preparation. Results: The NDO-PCR showed the highest sensitivity (92.3\%), specificity (100\%), and accuracy (94.3\%) for T. cruzi detection in the 87 sequenced samples. Sensitivities and specificities of the kDNA-PCR were 89.2\%/22.7\%, 20.5\%/100\% for TCZ-PCR, and 1.5\%/100\% for the 18S rRNA-PCR. The kDNA-PCR revealed a 77.3\% false positive rate, mostly due to cross-reactions with T. rangeli (NDO-PCR 0\%). TCZ- and 18S rRNA-PCR showed a false negative rate of 79.5\% and 98.5\% (NDO-PCR 7.7\%), respectively. Conclusions: The NDO-PCR demonstrated the highest specificity, sensitivity, and accuracy compared to leading PCRs. Together with serologic tests, it can be considered as a reliable tool for CD detection and can improve CD management significantly.},
  language  = {en}
}
@article{VeyKapsnerFuchsetal.2019,
  author    = {Vey, Johannes and Kapsner, Lorenz A. and Fuchs, Maximilian and Unberath, Philipp and Veronesi, Giulia and Kunz, Meik},
  title     = {A toolbox for functional analysis and the systematic identification of diagnostic and prognostic gene expression signatures combining meta-analysis and machine learning},
  series = {Cancers},
  volume    = {11},
  journal   = {Cancers},
  number    = {10},
  issn      = {2072-6694},
  doi       = {10.3390/cancers11101606},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193240},
  year      = {2019},
  abstract  = {The identification of biomarker signatures is important for cancer diagnosis and prognosis. However, the detection of clinical reliable signatures is influenced by limited data availability, which may restrict statistical power. Moreover, methods for integration of large sample cohorts and signature identification are limited. We present a step-by-step computational protocol for functional gene expression analysis and the identification of diagnostic and prognostic signatures by combining meta-analysis with machine learning and survival analysis. The novelty of the toolbox lies in its all-in-one functionality, generic design, and modularity. It is exemplified for lung cancer, including a comprehensive evaluation using different validation strategies. However, the protocol is not restricted to specific disease types and can therefore be used by a broad community. The accompanying R package vignette runs in ~1 h and describes the workflow in detail for use by researchers with limited bioinformatics training.},
  language  = {en}
}