Biology subjects

Endres, L.

Publications and source records attributed to Endres, L..

4 recordsLinked to original sources

bioRxiv2026

Oncogenes have the most distinct codon biases in the genome and codon signatures that oppose tumor suppressor genes

Oncogenes and tumor-suppressor genes play opposing roles in cancer biology to promote and restrict growth, respectively. Codon usage patterns interface with tRNA modifications to control translation, leading to gene-specific codon signatures with regulatory potential. As such, codon-biased translational regulation has been identified as a driver of proliferation and drug resistance in multiple cancers. We used advanced codon analytics methods to characterize and compare codon usage bias in oncogenes and tumor suppressor genes (TSGs) from humans and mice at group and gene-specific levels. We demonstrate that human oncogenes exhibit a distinct and opposing codon usage pattern to TSGs. This phenomenon is also present in mice but with less distinct oncogene bias relative to humans. Further comparison to 447 gene ontology groups demonstrated that human oncogenes have the most distinct codon usage patterns in the genome, while also highlighting that codon bias can separate functionally related genes and pathways from other biological processes. Using gene-specific codon analytics, we determined that human oncogenes have two types of extreme codon bias: a large group (N = 43) over-using G/C ending (GC3) codons and a smaller group (N = 12) over-using A/U (AU3) ending codons. While GC3 bias has been linked to increased translation in general, the AU3 finding suggests that genetic, environmental, or stress-related signals could drive the translation of this small group of oncogenes. The less extreme bias observed in mouse oncogenes and tumor suppressors likely underscores species-specific differences in oncogenic translation programs. Together, our findings highlight codon usage bias as a potential determinant of oncogene expression, provide a framework for ontology-based codon analysis, and uncover on species-specific differences in oncogene translation and codon usage biases.

cancer biology↗

bioRxiv2022

Refining Embedding-Based Binding Predictions by Leveraging AlphaFold2 Structures

BackgroundIdentifying residues in a protein involved in ligand binding is important for understanding its function. bindEmbed21DL is a Machine Learning method which predicts protein-ligand binding on a per-residue level using embeddings derived from the protein Language Model (pLM) ProtT5. This method relies solely on sequences, making it easily applicable to all proteins. However, highly reliable protein structures are now accessible through the AlphaFold Protein Structure Database or can be predicted using AlphaFold2 and ColabFold, allowing the incorporation of structural information into such sequence-based predictors. ResultsHere, we propose bindAdjust which leverages predicted distance maps to adjust the binding probabilities of bindEmbed21DL to subsequently boost performance. bindAdjust raises the recall of bindEmbed21DL from 47{+/-}2% to 53{+/-}2% at a precision of 50% for small molecule binding. For binding to metal ions and nucleic acids, bindAdjust serves as a filter to identify good predictions focusing on the binding site rather than isolated residues. Further investigation of two examples shows that bindAdjust is in fact able to add binding predictions which are not close in sequence but close in structure, extending the binding residue predictions of bindEmbed21DL to larger binding stretches or binding sites. ConclusionDue to its simplicity and speed, the algorithm of bindAdjust can easily refine binding predictions also from other tools than bindEmbed21DL and, in fact, could be applied to any protein prediction task.

bioinformatics↗

bioRxiv2019

Epitranscriptomic regulation of the response to the air pollutant naphthalene in mouse lungs: from the perspectives of specialized translation and tolerance linked to the writer ALKBH8

BackgroundThe epitranscriptomic writer Alkylation Repair Homolog 8 (ALKBH8) is a tRNA methyltransferase that modifies the wobble uridine of selenocysteine tRNA to promote the specialized translation, via stop codon recoding, of proteins that contain selenocysteine. Corresponding selenoproteins play critical roles in protecting against reactive oxygen species and environmental stress. Using a novel animal model deficient in Alkbh8, we have investigated the importance of epitranscriptomic systems in the response to naphthalene (NA), an abundant polycyclic aromatic hydrocarbon, glutathione depleter and lung toxicant found in tobacco smoke, gasoline and mothballs.\n\nObjectivesOur goal was to define the molecular reprogramming of Alkbh8 deficient (Alkbh8def) mice and evaluate the roles that the epitranscriptomic writer ALKBH8 and selenoproteins play in mitigating NA-induced toxicity and lung dysfunction.\n\nMethodsWe performed basal lung analysis and NA exposure studies using WT, Alkbh8def and Cyp2abfgs-null mice, the latter of which lack the cytochrome P450 enzymes required for NA bioactivation. We characterized gene expression, molecular markers of damage, viability and tolerance to NA.\n\nResultsUnder basal conditions, lungs from Alkbh8def mice have increased oxidation-reduction potential (ORP) and 8-isoprostane levels, and have reprogrammed at the molecular level to display increased stress response transcripts. In addition, the ALKBH8 writer deficient lungs have a decreased GSH/GSSG ratio. Alkbh8def mice are more sensitive to NA than WT, showing higher susceptibility to lung damage both at the cellular and molecular levels. WT mice develop a tolerance to NA after 3 days, defined as resistance to a high challenging dose after repeated exposures, which is absent in Alkbh8def mice, with writer deficient not surviving NA exposure.\n\nDiscussionWe conclude that the epitranscriptomic writer ALKBH8 plays a protective role against NA-induced lung dysfunction and promotes NA tolerance. Our work provides an early example of how epitranscriptomic systems can regulate the response to environmental stress in vivo.

molecular biology↗

bioRxiv2018

Salinity shock in Jatropha curcas leaves is more pronounced during recovery than during stress time

To verify the possible morphological and ultrastructural differences in the Jatropha curcas leaves, in response to high-intensity salt stress, three genotypes were evaluated (CNPAE183, JCAL171 and CNPAE218). In all the genotypes, 750mM NaCl, added to the nutrient solution, was applied to test its salt tolerance. For the analysis, the leaves were collected at three time points: (i) before stress (time 0 hour); (ii) during stress time (time 50 hours); and (iii) in the recovery period (time 914 hours) when the stressed plants recovered and demonstrated measurements of net photosynthetic with values similar to those demonstrated by the control plants. We showed that regardless of the genotype, saline shock caused an increase in the thickness of the mesophyll, and after the removal of NaCl, the thicker mesophyll remained in the JCAL171 and CNPAE218 genotypes, while the values observed in the CNPAE183 genotype were similar to those before stress. Scanning electron microscopy indicated that the stomata of CNPAE183 are smaller and have a stomatal index higher than the values demonstrated in JCAL171 and CNPAE218. Therefore, among the genotypes analysed, CNPAE183 demonstrates that it could be considered a promising genotype for future studies of genetic improvement that seek elite genotypes tolerant to salinity.\n\nHighlightsThis manuscript present the following highlights:\n\nThe mesophyll thickness contributes to provide a smaller path for the CO2 to Rubisco J. curcas may reduce mesophyll air spaces as a strategy to mitigate low gas exchange Leaves modulate the expansion of stomata differently than other epidermal cells Smaller stomata with greater pore aperture are more abundant on the abaxial surface CNPAE183 is a candidate for studies in search of elite genotypes tolerant to salinity

plant biology↗