@article{BrunkSputhDooseetal.2018, author = {Brunk, Michael and Sputh, Sebastian and Doose, S{\"o}ren and van de Linde, Sebastian and Terpitz, Ulrich}, title = {HyphaTracker: An ImageJ toolbox for time-resolved analysis of spore germination in filamentous fungi}, series = {Scientific Reports}, volume = {8}, journal = {Scientific Reports}, doi = {10.1038/s41598-017-19103-1}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-221691}, year = {2018}, abstract = {The dynamics of early fungal development and its interference with physiological signals and environmental factors is yet poorly understood. Especially computational analysis tools for the evaluation of the process of early spore germination and germ tube formation are still lacking. For the time-resolved analysis of conidia germination of the filamentous ascomycete Fusarium fujikuroi we developed a straightforward toolbox implemented in ImageJ. It allows for processing of microscopic acquisitions (movies) of conidial germination starting with drift correction and data reduction prior to germling analysis. From the image time series germling related region of interests (ROIs) are extracted, which are analysed for their area, circularity, and timing. ROIs originating from germlings crossing other hyphae or the image boundaries are omitted during analysis. Each conidium/hypha is identified and related to its origin, thus allowing subsequent categorization. The efficiency of HyphaTracker was proofed and the accuracy was tested on simulated germlings at different signal-to-noise ratios. Bright-field microscopic images of conidial germination of rhodopsin-deficient F. fujikuroi mutants and their respective control strains were analysed with HyphaTracker. Consistent with our observation in earlier studies the CarO deficient mutant germinated earlier and grew faster than other, CarO expressing strains.}, language = {en} } @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{CaliskanCrouchGiddinsetal.2022, author = {Caliskan, Aylin and Crouch, Samantha A. W. and Giddins, Sara and Dandekar, Thomas and Dangwal, Seema}, title = {Progeria and aging — Omics based comparative analysis}, series = {Biomedicines}, volume = {10}, journal = {Biomedicines}, number = {10}, issn = {2227-9059}, doi = {10.3390/biomedicines10102440}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-289868}, year = {2022}, abstract = {Since ancient times aging has also been regarded as a disease, and humankind has always strived to extend the natural lifespan. Analyzing the genes involved in aging and disease allows for finding important indicators and biological markers for pathologies and possible therapeutic targets. An example of the use of omics technologies is the research regarding aging and the rare and fatal premature aging syndrome progeria (Hutchinson-Gilford progeria syndrome, HGPS). In our study, we focused on the in silico analysis of differentially expressed genes (DEGs) in progeria and aging, using a publicly available RNA-Seq dataset (GEO dataset GSE113957) and a variety of bioinformatics tools. Despite the GSE113957 RNA-Seq dataset being well-known and frequently analyzed, the RNA-Seq data shared by Fleischer et al. is far from exhausted and reusing and repurposing the data still reveals new insights. By analyzing the literature citing the use of the dataset and subsequently conducting a comparative analysis comparing the RNA-Seq data analyses of different subsets of the dataset (healthy children, nonagenarians and progeria patients), we identified several genes involved in both natural aging and progeria (KRT8, KRT18, ACKR4, CCL2, UCP2, ADAMTS15, ACTN4P1, WNT16, IGFBP2). Further analyzing these genes and the pathways involved indicated their possible roles in aging, suggesting the need for further in vitro and in vivo research. In this paper, we (1) compare "normal aging" (nonagenarians vs. healthy children) and progeria (HGPS patients vs. healthy children), (2) enlist genes possibly involved in both the natural aging process and progeria, including the first mention of IGFBP2 in progeria, (3) predict miRNAs and interactomes for WNT16 (hsa-mir-181a-5p), UCP2 (hsa-mir-26a-5p and hsa-mir-124-3p), and IGFBP2 (hsa-mir-124-3p, hsa-mir-126-3p, and hsa-mir-27b-3p), (4) demonstrate the compatibility of well-established R packages for RNA-Seq analysis for researchers interested but not yet familiar with this kind of analysis, and (5) present comparative proteomics analyses to show an association between our RNA-Seq data analyses and corresponding changes in protein expression.}, language = {en} } @article{KunzGoettlichWallesetal.2017, author = {Kunz, Meik and G{\"o}ttlich, Claudia and Walles, Thorsten and Nietzer, Sarah and Dandekar, Gudrun and Dandekar, Thomas}, title = {MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact}, series = {Tumor Biology}, volume = {39}, journal = {Tumor Biology}, number = {7}, doi = {10.1177/1010428317706430}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-158399}, year = {2017}, abstract = {MicroRNAs are well-known strong RNA regulators modulating whole functional units in complex signaling networks. Regarding clinical application, they have potential as biomarkers for prognosis, diagnosis, and therapy. In this review, we focus on two microRNAs centrally involved in lung cancer progression. MicroRNA-21 promotes and microRNA-34 inhibits cancer progression. We elucidate here involved pathways and imbed these antagonistic microRNAs in a network of interactions, stressing their cancer microRNA biology, followed by experimental and bioinformatics analysis of such microRNAs and their targets. This background is then illuminated from a clinical perspective on microRNA-21 and microRNA-34 as general examples for the complex microRNA biology in lung cancer and its diagnostic value. Moreover, we discuss the immense potential that microRNAs such as microRNA-21 and microRNA-34 imply by their broad regulatory effects. These should be explored for novel therapeutic strategies in the clinic.}, language = {en} } @article{KunzWolfSchulzeetal.2016, author = {Kunz, Meik and Wolf, Beat and Schulze, Harald and Atlan, David and Walles, Thorsten and Walles, Heike and Dandekar, Thomas}, title = {Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools}, series = {Genes}, volume = {8}, journal = {Genes}, number = {1}, doi = {10.3390/genes8010008}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147990}, pages = {8}, year = {2016}, abstract = {Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs.}, language = {en} }