Biology subjects

Krouk, G.

Publications and source records attributed to Krouk, G..

12 recordsLinked to original sources

bioRxiv2026

Repurposing PeTriBERT for Protein Protein Interaction Prediction with Sequence Structure Fusion

Recent advances in artificial intelligence have enabled models to capture protein sequence and structural features. We present PeTriPPI2, a hybrid framework for protein--protein interaction (PPI) prediction that combines sequence embeddings from ESM-2 with structural representations from PeTriBERT, an encoder originally designed for inverse folding. We evaluate this sequence--structure approach on the Pinder dataset. On a test set of 2,342 protein pairs, the selected checkpoint achieves 0.898 accuracy, 0.917 precision, 0.876 recall, and 0.896 F1 score for the interacting class (AUROC 0.963). Compared with SpatialPPIv2 on the same test data, PeTriPPI2 has higher precision (0.917 versus 0.886) but lower recall (0.876 versus 0.942) and F1 score (0.896 versus 0.913). Component ablations indicate that both the sequence and structural pathways contribute to this configuration.

bioinformatics↗

bioRxiv2026

Biuret inhibits Arabidopsis root growth through an active, reversible, and genetically tractable developmental response

Biuret, a nitrogen-rich by-product of urea and a common contaminant of urea-based fertilisers, has long been considered a passive phytotoxin, affecting plant performances. Yet its effects on root development and the existence of endogenous mechanisms of perception or tolerance remain largely uncharacterised. Here we combined physiological, developmental, genetic and transcriptomic approaches to investigate the response of Arabidopsis thaliana to biuret. Biuret inhibited primary root growth in a dose-dependent manner by reducing meristematic cell division rather than cell elongation, and concomitantly impaired shoot growth by limiting leaf expansion. This root inhibition was reversible upon biuret removal and was accompanied by increased auxin-responsive (DR5) and decreased cytokinin-responsive (TCS) outputs at the root apex, consistent with a regulated remodelling of meristem activity rather than purely cumulative damage. A forward genetic screen identified the biuret-resistant mutant bir29, which sustained root and inflorescence development under inhibitory concentrations. Using {superscript 1}N-labelled biuret, we showed that resistance occurred without any change in biuret influx or accumulation, uncoupling sensitivity from exposure. Whole-genome transcriptomics revealed that bir29 fails to execute the wild-type response, neither repressing the cell-cycle machinery nor deploying the stress-associated programme induced by biuret. Genetic characterisation linked resistance to multiple genomic loci required for full resistance. Together, the results indicate that biuret triggers an active, reversible and genetically tractable developmental response, suggesting that this xenobiotic compound is integrated into endogenous signalling networks. Significance StatementBiuret, a poorly metabolised contaminant of urea fertilisers, is generally regarded as a passive phytotoxin, yet we show that it inhibits Arabidopsis root growth through a reversible and genetically tractable developmental response, accompanied by reorganised auxin and cytokinin signalling, rather than through cumulative chemical injury. The isolation of the resistant mutant bir29 suggests that plants integrate this xenobiotic molecule into endogenous signalling networks, reframing biuret as an informative probe of root developmental regulation.

Plant Biology↗

bioRxiv2025

Boosting Protein-Protein Interaction Detection with AlphaFold Multimer and Transformers

In 2021, DeepMind released AlphaFold 2, an AI-driven algorithm that revolutionized protein folding predictions by achieving error rates comparable to traditional experimental methods. Its remarkable performance has inspired researchers to extend its applications beyond its original purpose, leveraging AlphaFold 2 and its output features to tackle various unresolved biological challenges. In this paper, we discuss previous works that explored the repurposing of AlphaFold 2 for the detection of peptide- protein interactions (PPI). We propose a novel methodology where the outputs of a lightweight version of AlphaFold 2 Multimer are enhanced by a fine-tuned transformer encoder and benchmarked against classic machine learning algorithms. We study the performance of our approach on a curated version of Propedia, a peptide-protein dataset, and show that the boosting models significantly improve the detection of PPIs. Additionally, we provide HAPI (Hacky API), a freely available Python library designed to facilitate the seamless integration and use of AlphaFold 2 in computational workflows, further empowering the scientific community.

bioinformatics↗

bioRxiv2024

Classification and Regression Trees to predict Transcription Factor Combinatorial Interaction in scRNA-seq data.

Understanding the regulatory mechanisms that govern gene expression is crucial for deciphering cellular functions. Transcription factors (TFs) play a key role in regulating gene expression. In particular TF combinatorial interactions (TFCI) are now thought to largely shape genomic transcriptional responses, but predicting TFCI per se is still a difficult task. Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool providing a whole new readout of gene regulatory effects. In this study, we propose a machine learning approach utilizing Classification and Regression Trees (CART) for predicting TFCI in >110k scRNA-seq data points yielded from Arabidopsis thaliana root. The proposed methodology provides a valuable tool for pointing to new TFCI mechanisms and could advance our understanding of Gene Regulatory Networks functioning.

bioinformatics↗

bioRxiv2022

PeTriBERT : Augmenting BERT withtridimensional encoding for inverse protein foldingand design

Protein is biology workhorse. Since the recent break-through of novel folding methods, the amount of available structural data is increasing, closing the gap between data-driven sequence-based and structure-based methods. In this work, we focus on the inverse folding problem that consists in predicting an amino-acid primary sequence from protein 3D structure. For this purpose, we introduce a simple Transformer model from Natural Language Processing augmented 3D-structural data. We call the resulting model PeTriBERT: Proteins embedded in tridimensional representation in a BERT model. We train this small 40-million parameters model on more than 350 000 proteins sequences retrieved from the newly available AlphaFoldDB database. Using PetriBert, we are able to in silico generate totally new proteins with a GFP-like structure. These 9 of 10 of these GFP structural homologues have no ressemblance when blasted on the whole entry proteome database. This shows that PetriBert indeed capture protein folding rules and become a valuable tool for de novo protein design.

bioinformatics↗

bioRxiv2022

Full epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction

The first Genome Wide Association Studies (GWAS) shed light on the concept of missing heritability. It constitutes a mystery with transcending consequences from plant to human genetics. This mystery lies in the fact that a large proportion of phenotypes are not explained by unique or simple genomic modifications. One has to invoke genetic interactions among different loci, also known as epistasis, to partly account for it. However, current GWAS statistical models are moderately scalable, very sensitive to False Discovery Rate (FDR) corrections and, even combined with High Performance Computing (HPC), they can take years to evaluate for a full combinatorial epistatic space for a single phenotype. Here we propose a modeling approach, named Next-Gen GWAS (NGG) that evaluates, within hours, >60 billions of single nucleotide polymorphism (SNP) combinatorial first-order interactions, on a reasonable computer power. We first benchmark NGG on state of the art GWAS model results, and applied this to Arabidopsis thaliana providing 2D epistatic maps at gene resolution. We demonstrate on several phenotypes that a large proportion of the missing heritability can i) be retrieved with this modeling approach, ii) indeed lies in epistatic interactions and iii) can be used to improve phenotype prediction.

genetics↗

bioRxiv2021

Root membrane ubiquitinome under short-term osmotic stress

Osmotic stress can be detrimental to plants, whose survival relies heavily on proteomic plasticity. Protein ubiquitination is a central post-translational modification in osmotic mediated stress. Plants use the ubiquitin (Ub) proteasome system to modulate protein content, and a role for Ub in mediating endocytosis and trafficking plant plasma membrane proteins has recently emerged. In this study, we used the K-{varepsilon}-GG antibody enrichment method integrated with high-resolution mass spectrometry to compile a list of 719 ubiquitinated lysine (K-Ub) residues from 450 Arabidopsis root membrane proteins (58% of which are transmembrane proteins), thereby adding to the database of ubiquitinated substrates in plants. Although no Ub motifs could be identified, the presence of acidic residues close to K-Ub was revealed. Our ubiquitinome analysis pointed to a broad role of ubiquitination in the internalization and sorting of cargo proteins. Moreover, the simultaneous proteome and ubiquitinome quantification showed that ubiquitination is mostly not involved in membrane protein degradation in response to short osmotic treatment, but putatively in protein internalization as described for the aquaporin PIP2;1. Our in silico analysis of ubiquitinated proteins shows that two E2 Ub ligases, UBC32 and UBC34, putatively target membrane proteins under osmotic stress. Finally, we revealed a positive role for UBC32 and UBC34 in primary root growth under osmotic stress.

plant biology↗

bioRxiv2021

Nitrate-regulated growth processes involve activation of gibberellin pathway

Nitrate, one of the main nitrogen (N) sources for crops, acts as a nutrient and key signaling molecule coordinating gene expression, metabolism and various growth processes throughout the plant life cycle. It is widely accepted that nitrate-triggered developmental programs cooperate with hormone synthesis and transport, to finely adapt plant architecture to N availability. Here, we report that nitrate, acting through its signaling pathway, promotes growth in Arabidopsis and wheat, in part by modulating the accumulation of gibberellin (GA)-regulated DELLA growth repressors. We show that nitrate reduces the abundance of DELLAs by increasing GA contents through activation of GA metabolism gene expression. Consistently, the growth restraint conferred by nitrate deficiency is partially rescued in global-DELLA mutant that lacks all DELLAs. At the cellular level, we show that nitrate enhances both cell proliferation and elongation in a DELLA-dependent and -independent manner, respectively. Our findings establish a connection between nitrate and GA signaling pathways that allow plants to adapt their growth to nitrate availability.

plant biology↗

bioRxiv2018

HNI9 and HY5 maintain ROS homeostasis under high nitrogen provision in Arabidopsis

One sentence summaryExcessive N nutrition leads to ROS accumulation, and requires the function of major transcriptional regulators to maintain plants under physiological conditions.\n\nAuthor contributionsAn.M. and A.G. conceived research plans and supervised the experiments; F.B, Am.M., J.B., L.L., L.B. and An.M performed most of the experiments; F.B, Am.M., J.B., G.K., L.L., L.B. and An.M analyzed the data; An.M. wrote the article with contributions of all the authors.\n\nCompeting interestsThe authors declare no competing financial interests.\n\nSummaryReactive Oxygen Species (ROS) can accumulate in cells at excessive levels, leading to unbalanced redox status and to a potential oxidative stress, which can have damaging effects to the molecular components of plant cells. Several environmental conditions have been described as causing an elevation of ROS production in plants. Consequently, this requires the expression of detoxification responses in order to maintain ROS homeostasis at physiological levels. In case of mis-regulation of the detoxification systems, oxidative stress can lead ultimately to growth retardation and developmental defects. Here, we demonstrate that Arabidopsis plants growing under high nitrogen environment have to express a set of genes involved in detoxification of ROS in order to maintain ROS at physiological levels. We show that the chromatin factor HNI9 is an important actor of this response, required for the expression of these detoxification genes. Mutation in HNI9 leads to elevated ROS levels, and to ROS-dependent phenotypic defects under high but not low N provision. In addition, we identify HY5 as one of the major transcription factors also required for the expression of this detoxification program under high N condition. Our results demonstrate the requirement of a balance between N nutrition and ROS production, and identified the first major regulators required to control ROS homeostasis under excessive N nutrition.

plant biology↗

bioRxiv2018

Revisiting the functional properties of NPF6.3/NRT1.1/CHL1 in xenopus oocytes

Within the Arabidopsis NPF proteins, most of the characterized nitrate transporters are low-affinity transporters, whereas the functional characterization of NPF6.3/NRT1.1 has revealed interesting transport properties: the transport of nitrate and auxin, the eletrogenicity of the nitrate transport and a dual-affinity transport behavior for nitrate depending on external nitrate concentration. However, some of these properties remained controversial and were challenged here. We functionally express WT NPF6.3/NRT1.1 and some of its mutant in Xenopus oocytes and used a combination of uptake experiments using 15N-labelled nitrate and two-electrode voltage-clamp. In our experimental conditions in xenopus oocytes, in the presence or in the absence of external chloride, NPF6.3/NRT1.1 behaves as a non-electrogenic and pure low-affinity transporter. Moreover, further functional characterization of a NPF6.3/NRT1.1 point mutant, P492L, allowed us to hypothesize that NPF6.3/NRT1.1 is regulated by internal nitrate concentration and that the internal perception site involves the P492 residue.

plant biology↗

bioRxiv2018

HRS1/HHOs GARP transcription factors and reactive oxygen species are regulators of Arabidopsis nitrogen starvation response.

Plants need to cope with strong variations in the nitrogen content of the soil solution. Although many molecular actors are being discovered concerning how plants perceive NO3- provision, it is less clear how plants recognize a lack of Nitrogen. Indeed, following N removal plants activate their Nitrogen Starvation Response (NSR) being characterized in particular by the activation of very high affinity nitrate transport systems (NRT2.4, NRT2.5) and other sentinel genes such as GDH3. Here we show using a combination of functional genomics (via TF perturbation) and molecular physiology studies, that the GARP Transcription Factors (TFs) belonging the HHO sub-family are important regulators of the NSR through two potential mechanisms. First, HHOs directly repress NRT2.4 and NRT2.5 high-affinity nitrate transporters. Genotypes affected in HHO genes (mutants and overexpressors) display modified high-affinity nitrate transport activities opening interesting perspectives in biotechnology applications. Second, we show that Reactive Oxygen Species (ROS) are important to control NSR in wild type plants and that HRS1 and HHO1 overexpressors are affected in their ROS content, defining a potential feedforward branch of the signaling pathway. Taken together our results define two new classes of molecular actors in the control of NSR including ROS and the first transcription factors to date. This work (i) opens perspectives on a poorly understood nutrient related signaling pathway, and (ii) defines targets for molecular breeding of plants with enhanced NO3- uptake.

plant biology↗

bioRxiv2018

Root Responses to Heterogeneous Nitrate Availability are Mediated by trans-Zeatin in Arabidopsis Shoots

Plants are subjected to variable nitrogen (N) availability including frequent spatial nitrate (NO3-) heterogeneity in soil. Thus, plants constantly adapt their genome expression and root physiology in order to optimize N acquisition from this heterogeneous source. These adaptations rely on a complex and long-distance root-shoot-root signaling network that is still largely unknown. Here, we used a combination of reverse genetics, transcriptomic analysis, NO3- uptake experiments and hormone profiling under conditions of homogeneous or heterogeneous NO3- availability to characterize the systemic signaling involved. We demonstrate the important role of the trans-zeatin form of cytokinin (CK) in shoots, in particular using a mutant altered for ABCG14-mediated trans-zeatin-translocation from the root to the shoot, in mediating: (i) rapid long distance N-demand signaling and (ii) long term functional adaptations to heterogeneous NO3- supply, including changes in NO3- transport capacity and root growth modifications. We also provide insights into the potential CK-dependent and independent shoot-to-root signals involved in root adaptation to heterogeneous N availability.

plant biology↗