Klaus Tschira Foundation

Mutations in mitochondrial aminoacyl-tRNA synthetases (mtARSs) have been reported in patients with mitochondriopathies: most commonly encephalopathy, but also cardiomyopathy. Through a GWAS, we showed possible associations between mitochondrial valyl-tRNA synthetase (VARS2) dysregulations and non-ischemic cardiomyopathy. We aimed to investigate the possible consequences of VARS2 depletion in zebrafish and cultured HEK293A cells. Transient VARS2 loss-of-function was induced in zebrafish embryos using Morpholinos. The enzymatic activity of VARS2 was measured in VARS2-depleted cells via northern blot. Heterozygous VARS2 knockout was established in HEK293A cells using CRISPR/Cas9 technology. BN-PAGE and SDS-PAGE were used to investigate electron transport chain (ETC) complexes, and the oxygen consumption rate and extracellular acidification rate were measured using a Seahorse XFe96 Analyzer. The activation of the integrated stress response (ISR) and possible disruptions in mitochondrial fatty acid oxidation (FAO) were explored using RT-qPCR and western blot. Zebrafish embryos with transient VARS2 loss-of-function showed features of heart failure as well as indications of CNS and skeletal muscle involvements. The enzymatic activity of VARS2 was significantly reduced in VARS2-depleted cells. Heterozygous VARS2-knockout cells showed a rearrangement of ETC complexes in favor of complexes III2, III2 + IV, and supercomplexes without significant respiratory chain deficiencies. These cells also showed the enhanced activation of the ISR, as indicated by increased eIF-2α phosphorylation and a significant increase in the transcript levels of ATF4, ATF5, and DDIT3 (CHOP), as well as disruptions in FAO. The activation of the ISR and disruptions in mitochondrial FAO may underlie the adaptive changes in VARS2-depleted cells.

To compare 1 new intraocular lens (IOL) injector system against 3 standard injector systems in porcine eyes. David J Apple Center for Vision Research, Department of Ophthalmology, University Hospital Heidelberg, Heidelberg, Germany. In vitro laboratory study. In 70 porcine eyes, +20.0 diopter IOLs were implanted with the following systems: multiSert, UltraSert, iTec, and RayOne, that is, S1.8 (incision size: 1.8 mm), S2.0 (2.0 mm), S2.2P (2.2 mm, push mode), S2.2S (2.2 mm, screw mode), U2.2 (2.2 mm), iT2.2 (2.2 mm), and R2.0 (2.0 mm). Corneal incision sizes were measured before and after implantation with an incision gauge set. Ease of use was evaluated using a Likert scale. IOL delivery time and performance were determined based on Miyake-Apple view videos. Of the 70 eyes studied, the incision enlargements were 0.36 ± 0.08 mm (S1.8), 0.15 ± 0.07 mm (S2.0), 0.17 ± 0.12 mm (S2.2P), 0.28 ± 0.10 mm (S2.2S), 0.32 ± 0.09 mm (U2.2), 0.30 ± 0.08 mm (iT2.2), and 0.35 ± 0.11 mm (R2.0). Total scores of ease of use were 23.00 (S1.8), 25.00 (S2.0), 29.00 (S2.2P), 26.00 (S2.2S), 26.00 (U2.2), 25.00 (iT2.2), and 24.00 (R2.0). As for the mean delivery time, iT2.2 took the longest time (13.20 ± 3.29 seconds), whereas S2.2S took the shortest time (4.50 ± 0.71 seconds). Optic-haptic adhesion was observed in S1.8 (4, 40%), S2.2P (2, 20%), U2.2 (5, 50%), and iT2.2 (5, 50%). Injector S, with the appropriate incision size and implantation method, could achieve better results regarding incision enlargement, ease of use, delivery time, and performance than other injector systems. There was an indirect relationship between incision size and inadvertent events.

Ribosome profiling has been instrumental in leading to important discoveries in several fields of life sciences. Here we describe a computational approach that enables identification of translation events on a genome-wide scale from ribosome profiling data. Periodic fragment sizes indicative of active translation are selected without supervision for each library. Our workflow allows to map the whole translational landscape of a given cell, tissue, or organism, under varying conditions, and can be used to expand the search for novel, uncharacterized open reading frames, such as regulatory upstream translation events. Through a detailed workflow example, we show how to perform qualitative and quantitative analysis of translatomes.

Our understanding of the transition from physiological to pathological cardiac hypertrophy remains elusive and largely based on reductionist hypotheses. Here, we profiled the translatomes of 15 mouse hearts to provide a molecular blueprint of altered gene networks in early cardiac remodeling. Using co-expression analysis, we showed how sub-networks are orchestrated into functional modules associated with pathological phenotypes. We discovered unappreciated hub genes, many undocumented for their role in cardiac hypertrophy, and genes in the transcriptional network that were rewired in the translational network, and associated with semantically different subsets of enriched functional terms, such as Fam210a, a novel musculoskeletal modulator, or Psmd12, implicated in protein quality control. Using their correlation structure, we found that transcriptome networks are only partially reproducible at the translatome level, providing further evidence of post-transcriptional control at the level of translation. Our results provide novel insights into the complexity of the organization of in vivo cardiac regulatory networks.

Although the amount of small non-coding RNA-sequencing data is continuously increasing, it is still unclear to which extent small RNAs are represented in the human genome. In this study we analyzed 303 billion sequencing reads from nearly 25 000 datasets to answer this question. We determined that 0.8% of the human genome are reliably covered by 874 123 regions with an average length of 31 nt. On the basis of these regions, we found that among the known small non-coding RNA classes, microRNAs were the most prevalent. In subsequent steps, we characterized variations of miRNAs and performed a staged validation of 11 877 candidate miRNAs. Of these, many were actually expressed and significantly dysregulated in lung cancer. Selected candidates were finally validated by northern blots. Although isolated miRNAs could still be present in the human genome, our presented set likely contains the largest fraction of human miRNAs. c.backes@mx.uni-saarland.de or andreas.keller@ccb.uni-saarland.de. Supplementary data are available at Bioinformatics online.

Circular RNAs (circRNAs) belong to a recently re-discovered species of RNA that emerge during RNA maturation through a process called back-splicing. A downstream 5’ splice site is linked to an upstream 3’ splice site to form a circular transcript instead of a canonical linear transcript. Recent advances in next-generation sequencing (NGS) have brought circRNAs back into the focus of many scientists. Since then, several studies reported that circRNAs are differentially expressed across tissue types and developmental stages, implying that they are actively regulated and not merely a by-product of splicing. Though functional studies have shown that some circRNAs could act as miRNA-sponges, the function of most circRNAs remains unknown. To expand our understanding of possible roles of circular RNAs, we propose a new pipeline that could fully characterizes candidate circRNA structure from RNAseq data – FUCHS: FUll CHaracterization of circular RNA using RNA- Sequencing. Currently, most computational prediction pipelines use back-spliced reads to identify circular RNAs. FUCHS extends this concept by considering all RNA-seq information from long reads (typically > 150 bp) to learn more about the exon coverage, the number of double break point fragments, the different circular isoforms arising from one host-gene, and the alternatively spliced exons within the same circRNA boundaries. This new knowledge will enable the user to carry out differential-motif enrichment and miRNA-seed analysis to determine potential regulators during circRNA biogenesis. FUCHS is an easy-to-use Python based pipeline that contributes a new aspect to the circRNA research. The pipeline is available as git repository: https://github.com/dieterich-lab/FUCHS

A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34%), followed by the cell types (23.4%) and the isolation technique (17.2%). The change over time in cell miRNA composition was moderate (<3%) being close to the technical variations (<1%). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5% of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.