Biology subjects

Auge, G.

Publications and source records attributed to Auge, G..

6 recordsLinked to original sources

bioRxiv2026

usiGrabber: Automating the curation of proteomics spectra data at scale, making large datasets ready for use in machine learning systems

MotivationAn unprecedented amount of mass spectrometry-based proteomics data is publicly available through repositories such as the PRoteomics IDEntifications Database (PRIDE), and the field is increasingly leveraging machine learning approaches. However, the available data is not ready to be reused in a scalable way beyond the original acquisition purpose. Existing machine learning models commonly rely on a few manually curated datasets that require deep domain expertise and tedious technical work to construct. Importantly, these datasets have not been updated in recent years, so that newly published data remains inaccessible. We present usiGrabber, a scalable framework for assembling large proteomic datasets. usiGrabber is designed around portability and extensibility. It extracts spectra identification data from mzIdentML files, stores additional project-level metadata retrieved through the PRIDE API, indexes raw spectra using Universal Spectrum Identifiers (USIs), and offers download utilities to retrieve spectra data at scale. ResultsWithin 49 hours, we parsed over 800 million peptide spectrum matches and corresponding USIs from over 1,200 projects. As a proof of concept, we used usiGrabber to construct a phosphorylation-specific training dataset of nearly 11 million spectra in under two days and used it to retrain a binary phosphorylation classifier based on the AHLF model architecture. With a balanced accuracy of 0.78, our model achieves comparable performance to the original model on an independent test set, showing that automated data extraction is an alternative to manual curation of static datasets. AvailabilityAll code is available at https://github.com/usiGrabber/usiGrabber; the data is available at https://zenodo.org/records/18853258.

bioinformatics↗

bioRxiv2025

A Critical Window of Maternal Temperature Effects on Weedy Rice Seed Dormancy

Seed dormancy is a critical trait for the survival and adaptation of agricultural weeds. The maternal temperature after flowering influences the post-dispersal response of progeny seeds, which adds layers of complexity to weed control management programs. Understanding when the maternal environment exerts its effect on seed dormancy provides valuable insights into plant fitness and weed management. In this study, we investigated weedy rice progeny seed responses to determine the sensitivity window to the maternal temperature effects in controlled and field environments. We observed that the occurrence of hot temperatures during the late reproductive stage affected weedy rice dormancy. For this effect to influence progeny seed germination, mother plants had to experience two weeks of hot treatment, especially on weeks 4 and 5 after flowering, resulting in a delay on dormancy release after seed after-ripening. Early and late transplanting in the field, which exposed mother plants to different environments after flowering, showed delayed release from dormancy consistent with the sensitivity window and responses in controlled conditions. Altogether, our results indicate that the timing and duration of the maternal environment fluctuation may serve as an input to better predict weedy rice seed responses and develop targeted and more precise control programs. HighlightTwo weeks of maternal heat in the late reproductive stage are critical for delaying the release of dormancy in weedy rice seeds, which can affect plant fitness and control strategies.

plant biology↗

bioRxiv2025

What Large Language Models Know About Plant Molecular Biology

Large language models (LLMs) are rapidly permeating scientific research, yet their capabilities in plant molecular biology remain largely uncharacterized. Here, we present MOBIPLANT, the first comprehensive benchmark for evaluating LLMs in this domain, developed by a consortium of 112 plant scientists across 19 countries. MOBIPLANT comprises 565 expert-curated multiple-choice questions and 1,075 synthetically generated questions, spanning core topics from gene regulation to plant-environment interactions. We benchmarked seven leading chat-based LLMs using both automated scoring and human evaluation of open-ended answers. Models performed well on multiple-choice tasks (exceeding 75% accuracy), although most of them exhibited a consistent bias towards option A. In contrast, expert reviews exposed persistent limitations, including factual misalignment, hallucinations, and low self-awareness. Critically, we found that model performance strongly correlated with the citation frequency of source literature, suggesting that LLM knowledge inherits the visibility distribution of the underlying scientific corpus. Consequently, models tend to be more reliable on consolidated topics and less reliable on under-cited or recently emerging ones. We also benchmarked agents equipped with web-search and additional tools in more complex tasks involving DNA sequence analysis. These agents were outperformed by domain specific models in sequence classification and regression tasks, indicating an opportunity for joint agentic systems that combine both the reasoning power of LLMs and the dedicated processing of DNA models. This understanding is key to guiding both the development of next-generation models and the informed use of current tools in the everyday work of plant researchers. MOBIPLANT is publicly available online in this link.

plant biology↗

bioRxiv2022

Hybrid-derived weedy rice maintains adaptive combinations of alleles associated with seed dormancy

Hybridization is a widespread phenomenon in plants and is a pathway for the evolution of adaptive traits. However, this process may also affect the persistence of combinations of adaptive alleles evolved through natural selection when hybridization occurs between adapted and non-adapted populations. Hybridization between weedy and cultivated rice has been confirmed with an adaptive introgression of deep seed dormancy alleles from cultivated rice. In this study, we explored the influence of hybridization on the conservation of combinations of adaptive alleles by evaluating the natural variation in and the genetic structure of genomic regions associated with seed dormancy. Based on sequence variation in the genomic regions associated with seed dormancy, we revealed that hybrid-derived weedy rice strains maintained most of the adaptive combinations for this trait that were observed in the parental weedy rice, despite equal representation of the parental weedy and cultivated rice in the whole genome sequence. Moreover, the hybrid-derived weedy rice strains had deeper seed dormancy than their parental weedy rice strains. This study suggests that hybridization between weedy rice (having adaptive allelic combinations for seed dormancy) and cultivated rice (having non-adaptive combinations) generates weedy rice strains that express deep seed dormancy caused by genome stabilization through the removal of alleles derived from cultivated rice, in addition to the adaptive introgression of deep seed dormancy alleles derived from cultivated rice. Thus, hybridization between adapted and non-adapted populations seems to be reinforcing the trajectory towards the evolution of adaptive traits.

evolutionary biology↗

bioRxiv2021

SLP2/prohibitins aggregates and instability of the PHB complex are key elements in CHCHD10S59L-related disease

CHCHD10 is an ALS/FTD gene, also involved in a large clinical spectrum, that encodes a protein whose precise function within mitochondria is unclear. Here we show that CHCHD10 interacts with the Stomatin-Like Protein 2 (SLP2) to control the stability of the Prohibitin (PHB) complex in the inner mitochondrial membrane. In affected tissues, SLP2 forms aggregates with prohibitins and the instability of the PHB complex results in activation of OMA1 and accelerated OPA1 proteolysis leading to mitochondrial fragmentation, loss of mitochondrial cristae and apoptosis. Abnormal cristae morphogenesis depends on both the PHB complex destabilization leading to MICOS complex instability, via disruption of OPA1/Mitofilin interaction, and the activation of PINK1-mediated pathways. We also show that the increase of mitophagy found in both heart and hippocampus of Chchd10S59L/+ mito-QC mice is PINK1/Parkin-dependent. Thus, SLP2/PHBs aggregates and destabilization of the PHB complex with PINK1 activation are critical in the sequence of events leading to CHCHD10S59L-related disease.

pathology↗

bioRxiv2020

Structural and Functional Comparison of SARS-CoV-2-Spike Receptor Binding Domain Produced in Pichia pastoris and Mammalian Cells

The yeast Pichia pastoris is a cost-effective and easily scalable system for recombinant protein production. In this work we compared the conformation of the receptor binding domain (RBD) from SARS-CoV-2 Spike protein expressed in P. pastoris and in the well established HEK-293T mammalian cell system. RBD obtained from both yeast and mammalian cells was properly folded, as indicated by UV-absorption, circular dichroism and tryptophan fluorescence. They also had similar stability, as indicated by temperature-induced unfolding (observed Tm were 50 {degrees}C and 52 {degrees}C for RBD produced in P. pastoris and HEK-293T cells, respectively). Moreover, the stability of both variants was similarly reduced when the ionic strength was increased, in agreement with a computational analysis predicting that a set of ionic interactions may stabilize RBD structure. Further characterization by HPLC, size-exclusion chromatography and mass spectrometry revealed a higher heterogeneity of RBD expressed in P. pastoris relative to that produced in HEK-293T cells, which disappeared after enzymatic removal of glycans. The production of RBD in P. pastoris was scaled-up in a bioreactor, with yields above 45 mg/L of 90% pure protein, thus potentially allowing large scale immunizations to produce neutralizing antibodies, as well as the large scale production of serological tests for SARS-CoV-2.

biochemistry↗