Biology subjects

Pavelka, J.

Publications and source records attributed to Pavelka, J..

5 recordsLinked to original sources

bioRxiv2025

SALVE: prediction of interorgan communication with transcriptome latent space representation

Massive transcriptomics data allow gene relationships to be discovered from their correlated expression. We describe SALVE, a method to infer the associations between secretome-encoding transcripts and gene modules in a distal organ from RNA sequencing data. This method builds upon similar bioinformatics approaches by introducing transcriptome latent space representations and transfer learning to simultaneously increase discovery power and predict downstream functional associations. Applied to GTEx v8 data, we show the method readily recapitulates canonical endocrine relationships, including insulin and adiponectin signaling, while inferring new candidate organokines and their signaling modality. We also explore its utility for generating new hypotheses on cardiokine candidates and finding distal factors that may affect cardiac protein synthesis and metabolism. The predictions suggest a potential role of circulating galectin-3 (LGALS3) in regulating cardiac protein synthesis and homeostasis, which can be recapitulated in part in human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes. This method may aid in ongoing efforts to delineate interorgan communications and endocrine networks in various areas of study. New & NoteworthyWe describe a bioinformatics strategy to find associations between the secretome-coding genes and functional pathways of two organs. This approach may be used to find crosstalk signals between the heart, adipose, liver, and other tissues. Applied to GTEx data, it suggests a potential role of circulating galectin-3 in regulating cardiac protein synthesis and homeostasis pathways.

bioinformatics↗

bioRxiv2025

Directed Evolution of a Pantoea Strain for Antibiotic Production via Interspecies Competition: A Reproducible Experimental Approach

A novel methodology for evolving antibiotic-producing bacterial strains is presented, based on interspecies competition and environmental pressure. Using a previously undescribed strain of the genus Pantoea, we established a breeding protocol in which gradual exposure to different bacterial pathogens at increasing temperatures resulted in the selective emergence of antibiotic-producing variants. The target pathogens included Staphylococcus aureus, Acinetobacter baumannii, Streptococcus agalactiae, Escherichia coli, and Pseudomonas aeruginosa. The competitive passages were performed over a range of temperatures, gradually selecting for strains capable of inhibiting these species. Antibiotic activity was confirmed via disk diffusion assays. Although the chemical identity of the active compounds remains to be determined, their biological effects are reproducible and strain-specific. The approach provides a low-cost, scalable method for the generation of new antibiotic-producing bacterial strains.

microbiology↗

bioRxiv2025

Deuterium labeling enables proteome wide turnover kinetics analysis in cell culture

The half-life of proteins is tightly regulated and underlies many cellular processes. It remains unclear the extent to which proteins are dynamically synthesized and degraded in different cell types and cell states. We introduce an improved D2O labeling workflow and apply it to examine the landscape of protein turnover in pluripotent and differentiating human induced pluripotent stem cells (hiPSC). The majority of hiPSC proteins show minimal turnover beyond cell doubling rates, but we also identify over 100 new fast-turnover proteins not previously described as short-lived. These include proteins that function in cell division and cell cycle checkpoints, that are enriched in APC/C and SPOP degrons, and that are depleted upon pluripotency exit. Differentiation rapidly shifts the set of fast-turnover proteins toward including RNA binding and splicing proteins. The ability to identify fast-turnover proteins in different cell cultures also facilitates secretome analysis, as exemplified by studies of hiPSC-derived cardiac myocytes and primary human cardiac fibroblasts. The presented workflow is broadly applicable to protein turnover studies in diverse primary, pluripotent, and transformed cells.

biochemistry↗

bioRxiv2024

Improved determination of protein turnover rate with heavy water labeling by mass isotopomer ratio selection

The synthesis and degradation rates of proteins form an essential component of gene expression control. Heavy water labeling has been used in conjunction with mass spectrometry to measure protein turnover rates, but the optimal analytical approaches to derive turnover rates from the isotopomer patterns of deuterium labeled peptides continue to be a subject of research. Here we describe a method, which comprises a reverse lookup of numerically approximated peptide isotope envelopes, coupled to the selection of optimal isotopomer pairs based on peptide sequence, to calculate the molar fraction of new peptide synthesis in heavy water labeling mass spectrometry experiments. We validated this approach using an experimental calibration curve comprising mixtures of fully unlabeled and fully labeled proteomes. We then re-analyzed 17 proteome-wide turnover experiments from four mouse organs, and showed that the method increases the coverage of well-fitted peptides in protein turnover experiments by 25-82%. The method is implemented in the Riana software tool for protein turnover analysis, and may avail ongoing efforts to study the synthesis and degradation kinetics of proteins in animals on a proteome-wide scale. Whats newWe describe a reverse lookup method to calculate the molar fraction of new synthesis from numerically approximated peptide isotopomer profiles in heavy water labeling mass spectrometry experiments. Using an experimental calibration curve comprising mixtures of fully unlabeled and fully labeled proteomes at various proportions, we show that this method provides a straightforward way to calculate the proportion of new proteins in a protein pool from arbitrarily chosen isotopomer ratios. We next analyzed which of the isotopomer pairs within the peptide isotope envelope yielded isotopomer time courses that fit most closely to kinetic models, and found that the identity of the isotopomer pair depends partially on the number of deuterium accessible labeling sites of the peptide. We next derived a strategy to automatically select the isotopomer pairs to calculate turnover rates based on peptide sequence, and showed that this increases the coverage of existing proteome-wide turnover experiments in multiple data sets of the mouse heart, liver, kidney, and skeletal muscle by up to 25-82%.

biochemistry↗

bioRxiv2017

An epigenetic change in a moth is generated by temperature and transmitted to many subsequent generations mediated by RNA

Based on the presented results, the epigenetic phenomenon (paramutation) found in the short antennae (sa) mutation of the flour moth (Ephestia kuehniella) is probably determined by a small RNA (maybe piRNA) and transmitted in this way to subsequent generations through the male and female gametes. It is triggered by a change in the ambient environment; it persists for many generations (20 so far); during the epigenetic effect the original wild type appeared again. The epigenetic effect of the flour moth is induced by changes in ontogenetic development, such as increased temperature on pupae development, little nutritious food, different salts in food of certain chemicals into eggs. We found this mechanism may explain the intermittent clearance of this effect at some individuals and/or progeny of a pair in the generation chain in which the effect transfers. As the nature of the observed phenomenon could related to sirtuin genes, we hypothesize an association of these genes and non-coding small Piwi-interacting RNAs (piRNAs). The key is that the survival of RNA over many generations carries a number of practical implications. It is evident that the reaction to environmental change can manifest through RNA. It follows that there may be evolutionary significance in the long-term transmission of traits to future generations.

genetics↗