Biology subjects

Klimm, F.

Publications and source records attributed to Klimm, F..

4 recordsLinked to original sources

bioRxiv2023

Cryptic mitochondrial ageing coincides with mid-late life and is pathophysiologically informative in single cells across tissues and species

Ageing is associated with a range of chronic diseases and has diverse hallmarks. Mitochondrial dysfunction is implicated in ageing, and mouse-models with artificially enhanced mitochondrial DNA (mtDNA) mutation rates show accelerated ageing. A scarcely studied aspect of ageing, because it is invisible in aggregate analyses, is the accumulation of somatic mtDNA mutations which are unique to single cells (cryptic mutations). We find evidence of cryptic mtDNA mutations from diverse single-cell datasets, from three species, and discover: cryptic mutations constitute the vast majority of mtDNA mutations in aged post-mitotic tissues, that they can avoid selection, that their accumulation is consonant with theory, hits high levels coinciding with species specific mid-late life, and that their presence covaries with a majority of the hallmarks of ageing including protein misfolding and ER stress. We identify mechanistic links to ER stress experimentally and further give evidence that aged brain cells with high levels of cryptic mutations show markers of neurodegeneration and that calorie restriction slows the accumulation of cryptic mutations.

bioinformatics↗

bioRxiv2023

Force generation in the coiling tendrils of Passiflora caerulea

Tendrils of climbing plants coil along their length and thus form a striking helical spring and generate tensional forces. We have found that, for tendrils of the passion flower Passiflora caerulea, the generated force lies in the range of 6-140 mN, which is sufficient to lash the plant tightly to its substrate. Further, we revealed that the generated force strongly correlates with the water status of the plant. By combining force measurements with anatomical investigations and dehydration-rehydration experiments on both entire tendril segments and isolated lignified tissues, we are able to propose a two-phasic principle of spring formation: First, during the free coiling phase, the tendril coiling is based on the active contraction of a fiber ribbon in interaction with the surrounding parenchyma as resistance layer. Second, in a stabilization phase, the entire center of the coiled tendril lignifies, stiffening the spring and securing its function independent of hydration status.

plant biology↗

bioRxiv2020

Hypergraphs for predicting essential genes using multiprotein complex data

Protein-protein interactions are crucial in many biological pathways and facilitate cellular function. Investigating these interactions as a graph of pairwise interactions can help to gain a systemic understanding of cellular processes. It is known, however, that proteins interact with each other not exclusively in pairs but also in polyadic interactions and they can form multiprotein complexes, which are stable interactions between multiple proteins. In this manuscript, we use hypergraphs to investigate multiprotein complex data. We investigate two random null models to test which hypergraph properties occur as a consequence of constraints, such as the size and the number of multiprotein complexes. We find that assortativity, the number of connected components, and clustering differ from the data to these null models. Our main finding is that projecting a hypergraph of polyadic interactions onto a graph of pairwise interactions leads to the identification of different proteins as hubs than the hyper-graph. We find in our data set that the hypergraph degree is a more accurate predictor for gene-essentiality than the degree in the pairwise graph. We find that analysing a hypergraph as pairwise graph drastically changes the distribution of the local clustering coefficient. Furthermore, using a pairwise interaction representing multiprotein complex data may lead to a spurious hierarchical structure, which is not observed in the hypergraph. Hence, we illustrate that hypergraphs can be more suitable than pairwise graphs for the analysis of multiprotein complex data.

systems biology↗

bioRxiv2019

Functional module detection through integration of single-cell RNA sequencing data with protein-protein interaction networks

Recent advances in single-cell RNA sequencing (scRNA-seq) have allowed researchers to explore transcriptional function at a cellular level. In this study, we present O_SCPLOWSCC_SCPLOWPPIN, a method for integrating single-cell RNA sequencing data with protein-protein interaction networks (PPINs) that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted PPINs, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As a case study, we investigate RNA-sequencing data from human liver spheroids but the techniques described here are applicable to other organisms and tissues. O_SCPLOWSCC_SCPLOWPPIN allows us to expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the PPIN significantly enriched which represent biological pathways. In these pathways, O_SCPLOWSCC_SCPLOWPPIN also identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differentially expressed gene analysis.

bioinformatics↗