Biology subjects

Coudray, N.

Publications and source records attributed to Coudray, N..

At least 19 recordsLinked to original sources

bioRxiv2026

Multicenter self-supervised computational pathology identifies prognostic histomorphological phenotypes in colorectal cancer

H&E whole-slide images capture prognostic information encoded in tumor morphology and the surrounding microenvironment, but these signals remain difficult to extract and interpret at scale. Here, we developed a self-supervised computational pathology framework to predict disease-free survival in colorectal cancer and link model-derived risk to interpretable histomorphology and spatial tumor biology. Using a multicenter developmental cohort spanning colorectal adenomas and invasive colorectal cancer, we trained HPL-PanColon, a self-supervised representation model, to extract tile-level embeddings and identify recurrent histomorphological phenotype clusters across the adenoma-carcinoma spectrum. Compared with general-purpose pathology foundation models, HPL-PanColon yielded representations with reduced institution- and dataset-specific batch effects. We then applied HPL-PanColon to a global survival cohort of 1,024 colorectal cancer patients in a leave-one-institution-out framework, using tile embeddings to train an attention-based survival model and derive the Colon Histomorphology Prognostic Score (CHiPS). CHiPS stratified patients by disease-free survival and provided complementary prognostic information to a UICC TNM-informed clinicopathological model, increasing the c-index from 0.683 to 0.706. Integrating model attention with phenotype assignments traced CHiPS-associated risk to pathologist-recognizable tissue patterns, with high-risk regions enriched for desmoplastic, stromal, and fibroinflammatory morphologies and low-risk regions reflecting tumor-rich epithelial glandular patterns. Spatial transcriptomic analysis further linked high-risk morphologies to fibroblastic, perivascular, myofibroblastic, and immune-reactive tumor microenvironment programs, while low-risk morphologies mapped to epithelial and tumor-enriched regions. These findings establish a scalable framework for interpretable histology-based prognosis and spatial biological discovery in colorectal cancer.

pathology↗

bioRxiv2026

Interactions of outer membrane lipoproteins P. aeruginosa PA3214 and E. coli PqiC with their MCE protein binding partners, PA3213 and PqiB

Members of the Mammalian Cell Entry (MCE) superfamily interact with other proteins to form diverse architectures for the transport of hydrophobic molecules across the cell envelope in Gram-negative bacteria. Some of these trans-envelope MCE protein complexes include a PqiC-like outer membrane (OM) lipoprotein component. The best-studied member of this group of OM lipoproteins is E. coli PqiC, from the PqiABC system, which can form an octameric ring. How PqiC-like lipoproteins interact with their MCE protein binding partners to facilitate transport is not well understood. Here we report the cryo-electron microscopy structures of Pseudomonas aeruginosa PA3214, a homolog of PqiC, in the context of the full MCE transport PA3211-PA3214 system. Our structure provides insight into the biological assembly of the lipoprotein and interactions with its binding partner, MCE protein PA3213. We utilize deep mutational scanning to identify functionally important sites in E. coli PqiC in an unbiased manner. Through phenotypic and biochemical experiments, we characterize the interactions of the lipoproteins PqiC and PA3214 with their associated MCE proteins PqiB and PA3213, thus providing a model for how some MCE proteins employ a C-terminal peptide to mediate key interactions with their cognate lipoproteins at the OM.

microbiology↗

bioRxiv2025

Polar tube firing dynamics and ultrastructure from the shrimp microsporidian Ecytonucleospora hepatopenaei (EHP)

Ecytonucleospora (Enterocytozoon) hepatopenaei or EHP is an obligate intracellular parasite that belongs to phylum Microsporidia. EHP infection in shrimp results in growth retardation and size variation, leading to severe economic loss to shrimp aquaculture worldwide. Similar to other microsporidian species, EHP utilizes a harpoon-like invasion apparatus called the polar tube in order to infect host cells. The polar tube typically coils inside the spore and rapidly transits to a long, extended tube after being activated with proper stimuli. However, the mechanism and physical conditions affecting the polar tube firing in EHP are poorly understood. Here, we screened several germination buffers and found that a buffer containing potassium hydrogen phthalate (KHP) at pH 3.0 yielded the highest germination rate. The optimal temperatures for EHP germination range between 25-28{degrees}C, similar to the shrimps body temperature. The spores require at least 30 seconds to be activated, suggesting that the stimuli could rapidly move across the spore wall. We utilized high-speed live-cell imaging to study the dynamics of the EHP polar tube firing and compared the dynamics when the spores were treated with KHP and a previously reported stimulus, phloxine B. The polar tube firing dynamics between these two conditions are different. The total firing time was [~]100 milliseconds with the maximum velocity of [~]300 m*s-1 in KHP condition. Further investigation on the EHP polar tube ultrastructure using cryo-electron microscopy revealed that the EHP polar tube was composed of a membrane layer with an additional repetitive protein-array on the outermost surface. The distance between each repetitive unit ranges between 52-66 [A]. These repetitive units could possibly be polar tube proteins (PTPs). Altogether, this study provides insights into EHP polar tube firing dynamics and its architecture which are important foundations for understanding the biophysical factors governing EHP pathogenesis and in developing EHP control strategies. Author summaryThe microsporidian Ecytonucleospora hepatopenaei (EHP) poses a significant threat to global shrimp aquaculture, causing substantial economic losses. Many studies on EHP have been focused on development of detection methods, and farm management. Little is known about EHP pathogenesis and how it infects shrimp cells. Here, we identified laboratory conditions to activate the parasites infection process, which occurs on a millisecond timescale. We utilized a high-speed live-cell imaging to further characterize the rapid EHP infection process. The architecture and ultrastructure of EHP invasion organelle were also investigated using cryo-electron microscopy. Our findings provide a better understanding of the EHP infection mechanisms that are crucial for developing effective control strategies.

microbiology↗

bioRxiv2025

LetA defines a structurally distinct transporter family involved in lipid trafficking

Membrane transport proteins translocate diverse cargos, ranging from small sugars to entire proteins, across cellular membranes. A few structurally distinct protein families have been described that account for most of the known membrane transport processes. However, many membrane proteins with predicted transporter functions remain uncharacterized. We determined the structure of E. coli LetAB, a phospholipid transporter involved in outer membrane integrity, and found that LetA adopts a distinct architecture that is structurally and evolutionarily unrelated to known transporter families. LetA functions as a pump at one end of a ~225 [A] long tunnel formed by its binding partner, MCE protein LetB, creating a pathway for lipid transport between the inner and outer membranes. Unexpectedly, the LetA transmembrane domains adopt a fold that is evolutionarily related to the eukaryotic tetraspanin family of membrane proteins, including TARPs and claudins. LetA has no detectable homology to known transport proteins, and defines a new class of membrane transporters. Through a combination of deep mutational scanning, molecular dynamics simulations, AlphaFold-predicted alternative states, and functional studies, we present a model for how the LetA-like family of membrane transporters may use energy from the proton-motive force to drive the transport of lipids across the bacterial cell envelope.

biophysics↗

bioRxiv2024

Bond-centric modular design of protein assemblies

We describe a modular bond-centric approach to protein nanomaterial design inspired by the rich diversity of chemical structures that can be generated from the small number of atomic valencies and bonding interactions. We design protein building blocks with regular coordination geometries and bonding interactions that enable the assembly of a wide variety of closed and opened nanomaterials using simple geometrical principles. Experimental characterization confirms successful formation of more than twenty multi-component polyhedral protein cages, 2D arrays, and 3D protein lattices, with a high (10-50 %) success rate and electron microscopy data closely matching the corresponding design models. Because of the modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable systems.

biochemistry↗

bioRxiv2024

Cryo-ET reveals the in situ architecture of the polar tube invasion apparatus from microsporidian parasites

Microsporidia are divergent fungal pathogens that employ a harpoon-like apparatus called the polar tube (PT) to invade host cells. The PT architecture and its association with neighboring organelles remain poorly understood. Here, we use cryo-electron tomography to investigate the structural cell biology of the PT in dormant spores from the human-infecting microsporidian species, Encephalitozoon intestinalis. Segmentation and subtomogram averaging of the PT reveal at least four layers: two protein-based layers surrounded by a membrane, and filled with a dense core. Regularly spaced protein filaments form the structural skeleton of the PT. Combining cryo-electron tomography with cellular modeling, we propose a model for the 3-dimensional organization of the polaroplast, an organelle that is continuous with the membrane layer that envelops the PT. Our results reveal the ultrastructure of the microsporidian invasion apparatus in situ, laying the foundation for understanding infection mechanisms.

microbiology↗

bioRxiv2024

Self-Supervised Learning Reveals Clinically Relevant Histomorphological Patterns for Therapeutic Strategies in Colon Cancer

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-and-eosin-stained whole-slide images (WSIs). We trained an SSL Barlow Twins-encoder on 435 TCGA colon adenocarcinoma WSIs to extract features from small image patches. Leiden community detection then grouped tiles into histomorphological phenotype clusters (HPCs). HPC reproducibility and predictive ability for overall survival was confirmed in an independent clinical trial cohort (N=1213 WSIs). This unbiased atlas resulted in 47 HPCs displaying unique and sharing clinically significant histomorphological traits, highlighting tissue type, quantity, and architecture, especially in the context of tumor stroma. Through in-depth analysis of these HPCs, including immune landscape and gene set enrichment analysis, and association to clinical outcomes, we shed light on the factors influencing survival and responses to treatments like standard adjuvant chemotherapy and experimental therapies. Further exploration of HPCs may unveil new insights and aid decision-making and personalized treatments for colon cancer patients.

bioinformatics↗

bioRxiv2023

Conformational states of the microtubule nucleator, the γ-tubulin ring complex

Microtubules (MTs) perform essential functions in the cell, and it is critical that they are made at the correct cellular location and cell cycle stage. This nucleation process is catalyzed by the {gamma}-tubulin ring complex ({gamma}-TuRC), a cone-shaped protein complex composed of over 30 subunits. Despite recent insight into the structure of vertebrate {gamma}-TuRC, which shows that its diameter is wider than that of a MT, and that it exhibits little of the symmetry expected for an ideal MT template, the question of how {gamma}-TuRC achieves MT nucleation remains open. Here, we utilized single particle cryo-EM to identify two conformations of {gamma}-TuRC. The helix composed of 14 {gamma}-tubulins at the top of the {gamma}-TuRC cone undergoes substantial deformation, which is predominantly driven by bending of the hinge between the GRIP1 and GRIP2 domains of the {gamma}-tubulin complex proteins. However, surprisingly, this deformation does not remove the inherent asymmetry of {gamma}-TuRC. To further investigate the role of {gamma}-TuRC conformational change, we used cryo electron-tomography (cryo-ET) to obtain a 3D reconstruction of {gamma}-TuRC bound to a nucleated MT, providing insight into the post-nucleation state. Rigid-body fitting of our cryo-EM structures into this reconstruction suggests that the MT lattice is nucleated by spokes 2 through 14 of the {gamma}-tubulin helix, which entails spokes 13 and 14 becoming more structured than what is observed in apo {gamma}-TuRC. Together, our results allow us to propose a model for conformational changes in {gamma}-TuRC and how these may facilitate MT formation in a cell.

molecular biology↗

bioRxiv2023

MetFinder: a neural network-based tool for automated quantitation of metastatic burden in histological sections from animal models

Diagnosis of most diseases relies on expert histopathological evaluation of tissue sections by an experienced pathologist. By using standardized staining techniques and an expanding repertoire of markers, a trained eye is able to recognize disease-specific patterns with high accuracy and determine a diagnosis. As efforts to study mechanisms of metastasis and novel therapeutic approaches multiply, researchers need accurate, high-throughput methods to evaluate effects on tumor burden resulting from specific interventions. However, current methods of quantifying tumor burden are low in either resolution or throughput. Artificial neural networks, which can perform in-depth image analyses of tissue sections, provide an opportunity for automated recognition of consistent histopathological patterns. In order to increase the outflow of data collection from preclinical studies, we trained a deep neural network for quantitative analysis of melanoma tumor content on histopathological sections of murine models. This AI-based algorithm, made freely available to academic labs through a web-interface called MetFinder, promises to become an asset for researchers and pathologists interested in accurate, quantitative assessment of metastasis burden.

cancer biology↗

bioRxiv2023

Blueprinting expandable nanomaterials with standardized protein building blocks

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies in comparison has been much more complex, largely due to the irregular shapes of protein structures1. Here we describe extendable linear, curved, and angled protein building blocks, as well as inter-block interactions that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight "train track" assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence-structure relationships, it has not been previously possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank 3D canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to "back of an envelope" architectural blueprints.

biochemistry↗

bioRxiv2022

Protein-protein interactions in the Mla lipid transport system probed by computational structure prediction and deep mutational scanning

The outer membrane (OM) of Gram-negative bacteria is an asymmetric bilayer that protects the cell from various external stressors, such as antibiotics. The Mla transport system is implicated in the Maintenance of outer membrane Lipid Asymmetry and is thought to mediate retrograde phospholipid transport across the cell envelope. This system uses a shuttle-like mechanism to move lipids between the MlaFEDB inner membrane complex and the MlaA-OmpF/C OM complex, via a periplasmic lipid-binding protein, MlaC. MlaC binds to MlaD and MlaA, but the underlying protein-protein interactions that facilitate lipid transfer are not well understood. Here, we take an unbiased deep mutational scanning approach to map the fitness landscape of MlaC, which provides insights into important functional sites. Combining this analysis with AlphaFold2 structure predictions and binding experiments, we map the MlaC-MlaA and MlaC-MlaD protein-protein interfaces. Our results suggest that the MlaD and MlaA binding surfaces on MlaC overlap to a large extent, leading to a model in which MlaC can only bind one of these proteins at a time. Low-resolution cryo-electron microscopy (cryo-EM) maps of MlaC bound to MlaFEDB suggest that at least two MlaC molecules can bind to MlaD at once, in a conformation consistent with AlphaFold2 predictions. These data lead us to a model for MlaC interaction with its binding partners and insights into lipid transfer steps that underlie phospholipid transport between the inner and outer membranes.

biophysics↗

bioRxiv2022

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma

Early-stage lung adenocarcinoma is typically treated by surgical resection of the tumor. While in the majority of cases surgery can lead to cure, approximately 30% of patients progress. Despite intense efforts to map the genetic landscape of early-stage lung tumors, there has been limited success in discovering accurate biomarkers that can predict clinical outcomes. Meanwhile, the role of the tumor-adjacent tissue in cancer progression has been largely ignored. To test whether tumor-adjacent tissue can be informative of progression-free survival and to probe the underlying molecular pathways involved, we designed a multi-omic study in both tumor and matched tumor-adjacent histologically normal lung tissue from the same patient. Our study includes 143 treatment naive stage I cases with long-term patient follow-up and is, to our knowledge, the largest such study with the longest follow-up. We performed a comprehensive histologic characterization of all tumors, mapped the mutational landscape and probed the transcriptome of both tumor and adjacent normal tissue. We evaluated the predictive power of each data modality and showed that the transcriptome of tumor-adjacent histologically normal lung tissue is the only reliable predictor of clinical outcome. Unbiased discovery of co-expressed gene modules revealed that inflammatory pathways are upregulated in the tumor-adjacent tissue of patients at high risk for disease progression. Furthermore, single-cell transcriptome analysis in the tumor-adjacent lung demonstrated that progression-associated inflammatory signatures were broadly expressed by both immune and non-immune cells including mesothelial cells, alveolar type 2 cells and fibroblasts, CD1 dendritic cells and MAST cells. Collectively, our studies suggest that molecular profiling of tumor-adjacent tissue can identify patients that are at high risk for disease progression.

bioinformatics↗

bioRxiv2021

Role of Ring6 in the function of the E. coli MCE protein LetB

LetB is a tunnel-forming protein found in the cell envelope of some double-membraned bacteria, and is thought to be important for the transport of lipids between the inner and outer membranes. In Escherichia coli the LetB tunnel is formed from a stack of seven rings (Ring1 - Ring7), in which each ring is composed of a homo-hexameric assembly of MCE domains. The primary sequence of each MCE domain of the LetB protein is substantially divergent from the others, making each MCE ring unique in nature. The role of each MCE domain and how it contributes to the function of LetB is not well understood. Here we probed the importance of each MCE ring for the function of LetB, using a combination of bacterial growth assays and cryo-EM. Surprisingly, we find that {Delta}Ring3 and {Delta}Ring6 mutants, in which Ring3 and Ring6 have been deleted, confer increased resistance to membrane perturbing agents. Specific mutations in the pore-lining loops of Ring6 similarly confer increased resistance. A cryo-EM structure of the {Delta}Ring6 mutant shows that despite the absence of Ring6, which leads to a shorter assembly, the overall architecture is maintained, highlighting the modular nature of MCE proteins. Previous work has shown that Ring6 is dynamic and in its closed state, may restrict the passage of substrate through the tunnel. Our work suggests that removal of Ring6 may relieve this restriction. The deletion of Ring6 combined with mutations in the pore-lining loops leads to a model for the tunnel gating mechanism of LetB. Together, these results provide insight into the functional roles of individual MCE domains and pore-lining loops in the LetB protein. HighlightsO_LIDeleting MCE domains 3 or 6 from LetB confers increased resistance to membrane-perturbing agents C_LIO_LICryo-EM structure of {Delta}Ring6 LetB mutant highlights the modular nature of MCE domains C_LIO_LIMutations along LetB pore-lining loops modulate detergent resistance C_LI

biochemistry↗

bioRxiv2020

Targeting Allostery in the Dynein Motor Domain with Small Molecule Inhibitors

Cytoplasmic dyneins are AAA (ATPase associated with diverse cellular activities) motor proteins responsible for microtubule minus-end-directed intracellular transport. Dyneins unusually large size, four distinct nucleotide-binding sites, and the existence of closely-related isoforms with different functions, pose challenges for the design of potent and selective chemical inhibitors. Here we use structural approaches to develop a model for the inhibition of a well-characterized S. cerevisiae dynein construct by pyrazolo-pyrimidinone-based compounds. These data, along with single molecule experiments and mutagenesis studies, indicate that the compounds likely inhibit dynein by engaging the regulatory ATPase sites in the AAA3 and AAA4 domains, and not by interacting with dyneins main catalytic site in the AAA1 domain. A double Walker B mutant in AAA3 and AAA4 is an inactive enzyme, suggesting that inhibiting these regulatory sites can have a similar effect to inhibiting AAA1. Our findings reveal how chemical inhibitors can be designed to disrupt allosteric communication across dyneins AAA domains.

biochemistry↗

bioRxiv2020

Structure of MlaFEDB lipid transporter reveals an ABC exporter fold and two bound phospholipids

In double-membraned bacteria, phospholipids must be transported across the cell envelope to maintain the outer membrane barrier, which plays a key role in antibiotic resistance and pathogen virulence. The Mla system has been implicated in phospholipid trafficking and outer membrane integrity, and includes an ABC transporter complex, MlaFEDB. The transmembrane subunit, MlaE, has minimal sequence similarity to other ABC transporters, and the structure of the entire inner membrane MlaFEDB complex remains unknown. Here we report the cryo-EM structure of the MlaFEDB complex at 3.05 [A] resolution. Our structure reveals that while MlaE has many distinct features, it is distantly related to the LPS and MacAB transporters, as well as the eukaryotic ABCA/ABCG families. MlaE adopts an outward-open conformation, resulting in a continuous pathway for phospholipid transport from the MlaE substrate-binding site to the pore formed by the ring of MlaD. Unexpectedly, two phospholipids are bound in the substrate-binding pocket of MlaFEDB, raising the possibility that multiple lipid substrates may be translocated each transport cycle. Site-specific crosslinking confirms that lipids bind in this pocket in vivo. Our structure provides mechanistic insight into substrate recognition and transport by the MlaFEDB complex.

biochemistry↗

bioRxiv2020

Structure of MlaFB uncovers novel mechanisms of ABC transporter regulation

ABC transporters facilitate the movement of a diverse array of molecules across cellular membranes, using power from ATP hydrolysis. While the overall mechanism of the transport cycle has been characterized in detail for several important members of this transporter family, it is less well understood how the activity of ABC transporters is regulated in the cell post-translationally. Here we report the X-ray crystal structure of MlaFB from E. coli, an ABC nucleotide binding domain (MlaF) in complex with its putative regulatory subunit (MlaB). MlaFB constitutes the cytoplasmic portion of the larger MlaFEDB ABC transporter complex, which drives phospholipid transport across the bacterial envelope and is important for maintaining the integrity of the outer membrane barrier. Our data show that the regulatory subunit MlaB, a STAS domain protein, binds to the nucleotide binding domain and is required for its stability. Our structure also implicates a unique C-terminal tail of the ABC subunit, MlaF, in self-dimerization. Both the C-terminal tail of MlaF and the interaction with MlaB are required for the proper assembly of the MlaFEDB complex and its function in cells. This work leads to a new model for how the activity of an important bacterial lipid transporter may be regulated by small binding proteins, and raises the possibility that similar regulatory mechanisms may exist more broadly across the ABC transporter family, from bacteria to humans.

microbiology↗

bioRxiv2019

Structure of LetB reveals a tunnel for lipid transport across the bacterial envelope

Gram-negative bacteria are surrounded by an outer membrane composed of phospholipids and lipopolysaccharide (LPS), which acts as a barrier to the environment and contributes to antibiotic resistance. While mechanisms of LPS transport have been well characterised, systems that translocate phospholipids across the periplasm, such as MCE (Mammalian Cell Entry) transport systems, are less well understood. Here we show that E. coli MCE protein LetB (formerly YebT), forms a [~]0.6 megadalton complex in the periplasm. Our cryo-EM structure reveals that LetB consists of a stack of seven modular rings, creating a long hydrophobic tunnel through the centre of the complex. LetB is sufficiently large to span the gap between the inner and outer membranes, and mutations that shorten the tunnel abolish function. Lipids bind inside the tunnel, suggesting that it functions as a pathway for lipid transport. Cryo-EM structures in the open and closed states reveal a dynamic tunnel lining, with implications for gating or substrate translocation. Together, our results support a model in which LetB establishes a physical link between the bacterial inner and outer membranes, and creates a hydrophobic pathway for the translocation of lipids across the periplasm, to maintain the integrity of the outer membrane permeability barrier.

biochemistry↗

bioRxiv2019

Efficient pan-cancer whole-slide image classification and outlier detection using convolutional neural networks

Visual analysis of solid tissue mounted on glass slides is currently the primary method used by pathologists for determining the stage, type and subtypes of cancer. Although whole slide images are usually large (10s to 100s thousands pixels wide), an exhaustive though time-consuming assessment is necessary to reduce the risk of misdiagnosis. In an effort to address the many diagnostic challenges faced by trained experts, recent research has been focused on developing automatic prediction systems for this multi-class classification problem. Typically, complex convolutional neural network (CNN) architectures, such as Googles Inception, are used to tackle this problem. Here, we introduce a greatly simplified CNN architecture, PathCNN, which allows for more efficient use of computational resources and better classification performance. Using this improved architecture, we trained simultaneously on whole-slide images from multiple tumor sites and corresponding non-neoplastic tissue. Dimensionality reduction analysis of the weights of the last layer of the network capture groups of images that faithfully represent the different types of cancer, highlighting at the same time differences in staining and capturing outliers, artifacts and misclassification errors. Our code is available online at: https://github.com/sedab/PathCNN.

pathology↗