Biology subjects

Guerin, N.

Publications and source records attributed to Guerin, N..

5 recordsLinked to original sources

bioRxiv2024

Nitrogen metabolism in the picoalgae Pelagomonas calceolata: disentangling cyanate lyase function under different nutrient conditions.

Cyanate (OCN-) is potentially an important organic nitrogen source in aquatic environments given the prevalence and activity of cyanate lyase genes in microalgae. However, the conditions under which these genes are expressed and the actual capacity of microalgae to assimilate cyanate remain underexplored. Here, we studied the nitrogen metabolism of the cosmopolitan picoalga Pelagomonas calceolata (Pelagophyceae, Stramenopiles) in environmental metatranscriptomes and transcriptomes from culture experiments under different nitrogen sources and concentrations. We observed that cyanate lyase is over-expressed in nitrate-poor oceanic regions, suggesting that cyanate is an important molecule contributing to the persistence of P. calceolata in oligotrophic environments. In the laboratory, we confirmed that this gene is over-expressed in low-nitrate medium together with several genes involved in nitrate recycling from endogenous molecules. Non-axenic cultures of P. calceolata were capable of growing on various nitrogen sources, including nitrate, urea and cyanate, but not ammonium. RNA sequencing of these cultures revealed that cyanate lyase was under-expressed in the presence of cyanate, indicating that this gene in not involved in the catabolism of extracellular cyanate to ammonia. Conversely, axenic P. calceolata cultures were not able to grow on cyanate, suggesting that the bacterial community consumes cyanate and provides an available form of nitrogen for growth of the alga. Based on environmental datasets and laboratory experiments, we propose that cyanate lyase is important in nitrate-poor environments to reduce the toxicity of intracellular cyanate produced by endogenous nitrogenous compound recycling, rather than being used to metabolise imported extracellular cyanate as an alternative nitrogen source.

genomics↗

bioRxiv2024

DexDesign: A new OSPREY-based algorithm for designing de novo D-peptide inhibitors

With over 270 unique occurrences in the human genome, peptide-recognizing PDZ domains play a central role in modulating polarization, signaling, and trafficking pathways. Mutations in PDZ domains lead to diseases such as cancer and cystic fibrosis, making PDZ domains attractive targets for therapeutic intervention. D-peptide inhibitors offer unique advantages as therapeutics, including increased metabolic stability and low immunogenicity. Here, we introduce DexDesign, a novel OSPREY-based algorithm for computationally designing de novo D-peptide inhibitors. DexDesign leverages three novel techniques that are broadly applicable to computational protein design: the Minimum Flexible Set, K*-based Mutational Scan, and Inverse Alanine Scan, which enable exponential reductions in the size of the peptide sequence search space. We apply these techniques and DexDesign to generate novel D-peptide inhibitors of two biomedically important PDZ domain targets: CAL and MAST2. We introduce a new framework for analyzing de novo peptides--evaluation along a replication/restitution axis--and apply it to the DexDesign-generated D-peptides. Notably, the peptides we generated are predicted to bind their targets tighter than their targets endogenous ligands, validating the peptides potential as lead therapeutic candidates. We provide an implementation of DexDesign in the free and open source computational protein design software OSPREY.

bioinformatics↗

bioRxiv2022

DISRUPTOR: Computational identification of oncogenic mutants disrupting protein interactions

We report an Osprey-based computational protocol to prospectively identify oncogenic mutations that act via disruption of molecular interactions. It is applicable to analyze both protein-protein and protein-DNA interfaces and has been validated on a dataset of clinically relevant mutations. In addition, it was used to predict previously uncharacterized patient mutations in CDK6 and p16 genes, which were experimentally confirmed to impair complex formation.

cancer biology↗

bioRxiv2022

Resistor: an algorithm for predicting resistance mutations using Pareto optimization over multistate protein design and mutational signatures

Resistance to pharmacological treatments is a major public health challenge. Here we report RO_SCPLOWESISTORC_SCPLOW--a novel structure- and sequence-based algorithm for drug design providing prospective prediction of resistance mutations. RO_SCPLOWESISTORC_SCPLOW computes the Pareto frontier of four resistance-causing criteria: the change in binding affinity ({Delta}Ka) of the (1) drug and (2) endogenous ligand upon a proteins mutation; (3) the probability a mutation will occur based on empirically derived mutational signatures; and (4) the cardinality of mutations comprising a hotspot. To validate RO_SCPLOWESISTORC_SCPLOW, we applied it to kinase inhibitors targeting EGFR and BRAF in lung adenocarcinoma and melanoma. RO_SCPLOWESISTORC_SCPLOW correctly identified eight clinically significant EGFR resistance mutations, including the "gatekeeper" T790M mutation to erlotinib and gefitinib and five known resistance mutations to osimertinib. Furthermore, RO_SCPLOWESISTORC_SCPLOW predictions are consistent with sensitivity data on BRAF inhibitors from both retrospective and prospective experiments using the KinCon biosensor technology. RO_SCPLOWESISTORC_SCPLOW is available in the open-source protein design software OSPREY.

bioinformatics↗

bioRxiv2021

Genomic adaptation of the picoeukaryote Pelagomonas calceolata to temperate iron-poor oceans revealed by a chromosome-scale genome sequence.

The smallest phytoplankton species are key actors in oceans biogeochemical cycling and their abundance and distribution are affected with global environmental changes. Picoalgae (cells <2{micro}m) of the Pelagophyceae class encompass coastal species causative of harmful algal blooms while others are cosmopolitan and abundant in open ocean ecosystems. Despite the ecological importance of Pelagophytes, only a few genomic references exist limiting our capacity to identify them and study their adaptation mechanisms in a changing environment. Here, we report the complete chromosome-scale assembled genome sequence of Pelagomonas calceolata. We identified unusual large low-GC and gene-rich regions potentially representing centromeres. These particular genomic structures could be explained by the absence of genes from a recombination pathway involving double Holiday Junctions. We identified a large repertoire of genes involved in inorganic nitrogen sensing and uptake and several genes replacing iron-requiring proteins potentially explaining P. calceolata ecological success in oligotrophic waters. Finally, based on this high-quality assembly, we evaluated P. calceolata relative abundance in all oceans using environmental Tara Oceans datasets. Our results suggest that P. calceolata is one of the most abundant eukaryotic species in the oceans with a relative abundance favoured by high temperature and iron-poor conditions. Climate change projections based on its relative abundance suggest an extension of the P. calceolata habitat toward the poles at the end of this century. Collectively, these findings reveal the ecological importance of P. calceolata and lay the foundation for a global scale analysis of the adaptation and acclimation strategies of picoalgae in a changing environment.

genomics↗