Biology subjects

Druart, K.

Publications and source records attributed to Druart, K..

6 recordsLinked to original sources

bioRxiv2026

Targeting Sec61 to Silence Pathogenic Light-Chain Production in AL Amyloidosis

Unstable immunoglobulin light chains (LCs) secreted by clonal plasma cells drive organ damage in AL amyloidosis, yet no therapy exist to directly suppress their biosynthesis. Here, we targeted the Sec61 translocon to block LC biogenesis. In patient-derived plasma cells, the Sec61 blocker mycolactone redirected nascent LCs to proteasomal degradation, inducing proteotoxic stress that synergized with bortezomib. In vivo, this combination reduced plasma-cell engraftment and LC secretion but caused toxicity, underscoring the need for Sec61 client selectivity. Proteomic profiling of a model patient-derived plasma cell line treated with the synthetic Sec61 inhibitors A317 and A347 revealed intermediate- and narrow-spectrum client selectivity, respectively, while retaining activity against the LC. However, unlike A317, the more selective A347 failed to inhibit diverse amyloidogenic LCs in a signal-peptide reporter assay. In primary plasma cells from an AL cohort, A317 consistently reduced pathogenic LC production while sparing matched non-malignant bone marrow cells. Together, these findings establish Sec61 as a therapeutic target in AL amyloidosis and identify the need to balance client selectivity with coverage of diverse amyloidogenic LC signal peptides.

cell biology↗

bioRxiv2026

High-quality proteins and RNAs extracted from exact same samples for proteomics and RNA-Seq analyses

Back to the 1990 the single step method developed by Chomczynski and Sacchi for RNA isolation was extended for sequential isolation of RNA, DNA and proteins from a same sample. Although the quality of the extracted RNA turned compatible with RNA-Seq analyses, the extraction of the protein fraction from the same sample was time-consuming and resulting in low yield and quality of proteins not compatible with LC-MS proteomic analyses. Here we report a novel procedure by isolating in parallel the protein fraction and the RNA fraction from the same exact minute mosquito samples. We provide evidence that each cognate fractions are compatible with LC-MS proteomic analysis on the one hand and RNA-Seq analysis on the other hand. This protocol is simple, time efficient and adequate for studies involving limited sample size and could be applied easily to a broad range of animal and human samples.

molecular biology↗

bioRxiv2025

Mapping regulatory networks underlying Leishmania stage differentiation reveals an essential role for protein degradation in parasite development

Vector-borne, protist parasites have evolved complex developmental programs to adapt to very distinct host environments. How these important pathogens transition between insect and mammalian stages is only poorly understood. Here we investigate stage differentiation in the trypanosomatid parasite Leishmania that shows constitutive gene transcription, thus providing a unique model system to assess how development is governed by post-transcriptional mechanisms. Using a five-layer integrative systems analysis (from genome to metabolome), we examined hamster-isolated Leishmania donovani amastigotes and culture-derived, insect-stage promastigotes. This approach enabled us to rule out genomic adaptation as a key driver of parasite stage differentiation, while confirming the pivotal role of differential mRNA turnover in stage-specific gene expression. Assessing transcriptomic against proteomic expression changes uncovered an unexpectedly broad dynamic range of stage-regulated changes in protein abundance that only poorly correlated with mRNA levels. This discrepancy correlated with (i) alterations in snoRNA expression and changes in rRNA modification they guide suggesting stage-specific adaptation of the protein translation apparatus that can uncouple mRNA from protein abundancies, and (ii) differential protein degradation as revealed by quantitative proteomics of parasites treated with the proteasomal inhibitor lactacystin. Lactacystin treatment stalled the transition of spleen-derived amastigotes into promastigotes in culture, further underscoring the role of proteasomal activity in stage differentiation. Integration of our five-layer systems analysis established the first link between Leishmania development and the expression of co-regulated genetic networks encompassing mRNA turnover, protein translation, phosphorylation, and degradation. Our findings provide a powerful new resource for research programs that aim to dissect the emergent properties of regulatory networks and feedback loops underlying Leishmania stage differentiation, serving as a blueprint for other vector-borne pathogens that rely on disease-associated developmental transitions.

systems biology↗

bioRxiv2022

A multi-parameter optimization in middle-down analysis of monoclonal antibodies by LC-MS/MS

In antibody-based drug research, regulatory agencies request a complete characterization of antibody proteoforms covering both the amino acid sequence and all post-translational modifications. The usual mass spectrometry-based approach to achieve this goal is bottom-up proteomics, which relies on the digestion of antibodies, but does not allow the diversity of proteoforms to be assessed. Middle-down and top-down approaches have recently emerged as attractive alternatives but are not yet mastered and thus used in routine by many analytical chemistry laboratories. The work described here aims at providing guidelines to achieve the best sequence coverage for the fragmentation of intact light and heavy chains generated from a simple reduction of intact antibodies using Orbitrap mass spectrometry. Three parameters were found crucial to this aim: the use of an electron-based activation technique, the multiplex selection of precursor ions of different charge states and the combination of replicates.

biochemistry↗

bioRxiv2021

InDeep : 3D fully convolutional neural networks to assist in silico drug design on protein-protein interactions

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSProtein-protein interactions (PPIs) are key elements in numerous biological pathways and the subject of a growing number of drug discovery projects including against infectious diseases. Designing drugs on PPI targets remains a difficult task and requires extensive efforts to qualify a given interaction as an eligible target. To this end, besides the evident need to determine the role of PPIs in disease-associated pathways and their experimental characterization as therapeutics targets, prediction of their capacity to be bound by other protein partners or modulated by future drugs is of primary importance. ResultsWe present InDeep, a tool for predicting functional binding sites within proteins that could either host protein epitopes or future drugs. Leveraging deep learning on a curated data set of PPIs, this tool can proceed to enhanced functional binding site predictions either on experimental structures or along molecular dynamics trajectories. The benchmark of InDeep demonstrates that our tool outperforms state of the art ligandable binding sites predictors when assessing PPI targets but also conventional targets. This offers new opportunities to assist drug design projects on PPIs by identifying pertinent binding pockets at or in the vicinity of PPI interfaces. AvailabilityThe tool is available on GitHub3 along with a PyMol plugin for visualization. Predictions of InDeep can be consulted at iPPI-DB4

bioinformatics↗

bioRxiv2020

Proteus software for physics-based protein design

We describe methods and software for physics-based protein design. The folded state energy combines molecular mechanics with Generalized Born solvent. Sequence and conformation space are sampled with Replica Exchange Monte Carlo, assuming one or a few fixed protein backbone structures and discrete side chain rotamers. Whole protein design and enzyme design are presented as illustrations. Full redesign of three PDZ domains was done using a simple, empirical, unfolded state model. Designed sequences were very similar to natural ones. Enzyme redesign exploited a powerful, adaptive, importance sampling approach that allows the design to directly target substrate binding, reaction rate, catalytic efficiency, or the specificity of these properties. Redesign of tyrosyl-tRNA synthetase stereospecificity is reported as an example.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗