Biology subjects

Siekmann, I.

Publications and source records attributed to Siekmann, I..

3 recordsLinked to original sources

bioRxiv2026

Dynamic proteomic profiling reveals protein-specific regulation of synthesis rates underpinning the divergent adaptation of human muscle to endurance and resistance training

Endurance (END) or resistance exercise (RE) training results in adaptations that give rise to distinct skeletal muscle phenotypes. Hallmarks of RE include increases in muscle fibre and muscle cross-sectional area and strength, whereas END increases mitochondrial content. Such distinct phenotypes arise from differential metabolic and mechanical signal transduction, transcriptional, and protein translation pathways, culminating in exercise mode-specific adaptations in the muscle proteome. However, little empirical data exist on the protein-specific dynamic responses underlying training-mode-specific adaptations in humans. Using a model of unilateral exercise combined with stable isotope labelling with deuterium oxide, we measured changes in synthesis and abundance from baseline and during early (week 1) and later (week 10) periods of adaptation to END and RE training in young healthy adults (n = 14; 8 female, 6 male; 20 {+/-} 1 y, 70 {+/-} 10 kg). We quantified changes in the abundance (n = 1146 proteins) and synthesis (n = 247 proteins) profiles of skeletal muscle across a 5-day pre-training baseline period and during early and later adaptation to RE and END. Abundance profiling revealed mode-specific proteome remodelling, whereby RE increased ribosomal and contractile protein networks, whereas END increased mitochondrial inner membrane proteins after 10 weeks of training. The protein-specific synthesis rates of 119 proteins showed training-induced differences (P < 0.1 and log2 fold change > 1), including subsets of structural proteins that responded differently to RE and END training modes. Notably, distinct Z-disc proteins, such as XIRP1 (RE-specific) and LDB3 (END-specific), exhibited mode-specific regulation despite sharing a similar subcellular localisation. We report, for the first time, that divergent phenotypic adaptations to RE and END extend beyond changes in bulk fraction-specific synthesis rates and are regulated by training-mode-specific adaptations in distinct protein subsets within similar subcellular protein locations.

physiology↗

bioRxiv2024

Classification of dinosaur footprints using machine learning

Fossilised dinosaur footprints enable us to study the behaviour of individual dinosaurs as well as interactions between dinosaurs of the same or different species. There are two principal groups of three-toed dinosaurs, ornithopods and theropods. Determining if a footprint is from an ornithopod or a theropod is a challenging problem. Based on a data set of over 300 dinosaur footprints we train several machine learning models for classifying footprints as either ornithopods or theropods. The data are provided in the form of 20 landmarks for representing each footprint which are derived from images. Variable selection using logistic forward regression demonstrates that the selected landmarks are at locations that are intuitively expected to be especially informative locations, such as the top or the bottom of a footprint. Most models show good accuracy but the recall of ornithopods, of which fewer samples were contained in the data set, was generally lower than the recall of theropods. The Multi-Layer Perceptron (MLP) stands out as the model which did best at dealing with the class imbalance. Finally, we investigate which footprints were misclassified by the majority of models. We find that some misclassified samples exhibit features that are characteristic of the other class or have a compromised shape, for example, a middle toe that points to the left or the right rather than straight ahead.

paleontology↗

bioRxiv2023

Muscle of obese insulin-resistant humans exhibits losses in proteostasis and attenuated proteome dynamics that are improved by exercise training.

We examined muscle proteostasis in obese insulin-resistant (OIR) individuals to determine whether endurance exercise could positively influence proteome dynamics in this population. Male OIR (n = 3) and lean, healthy controls (LHC; n = 4) were recruited and underwent a 14-d measurement protocol of daily deuterium oxide (D2O) consumption and serial biopsies of vastus lateralis muscle. The OIR group then completed 10-weeks of high-intensity interval training (HIIT), encompassing 3 sessions per week of cycle ergometer exercise with 1 min intervals at 100 % maximum aerobic power (Wmax) interspersed by 1 min recovery periods. The number of intervals per session progressed from 4 to 8, and during weeks 8-10 the 14-d measurement protocol was repeated. The abundance and turnover rates of 880 and 301 proteins, respectively, were measured. OIR and LHC muscle exhibited 352 differences (p < 0.05, false discovery rate (p < 0.05) differences in protein turnover. OIR muscle was enriched with markers of metabolic stress, protein misfolding and components of the ubiquitin-proteasome system, and the turnover rate of many of these proteins was less compared to LHC muscle. HIIT altered the abundance of 53 proteins and increased the turnover rate of 22 proteins (p < 0.05) in OIR muscle and tended to restore proteostasis, evidenced by increasing muscle protein turnover rates and normalizing proteasome composition in OIR participants. In conclusion, obesity and insulin resistance are associated with compromised muscle proteostasis, which can be partially restored by endurance exercise.

physiology↗