bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanical constraints organize 3D tissues and orchestrate muscle differentiation
Authors: Nagle Irène , van der Spek Lorijn , Gesenhues Paul , Savy Thierry , Réa Laurent , Richert Alain , Receveur Mathieu , Delort Florence , Batonnet-Pichon Sabrina , Wilhelm Claire , Luciani Nathalie , Reffay Myriam 
Published: October 2024

Biological tissues achieve proper shape and ordered structures during development through responses to internal and external signals, with mechanical cues playing a crucial role. These forces guide cellular organization, leading to complex self-organizing structures that are foundational to embryonic patterns. Emerging theories and experiments suggest that “topological morphogens” drive these processes. Despite the predominance of three-dimensional (3D) structures in biology, studying 3D tissues remains challenging due to limited model systems and the complexity of modeling. Here, we address these challenges by using self-organized cellular aggregates, specifically spindle-shaped C2C12 myoblasts, subjected to controlled mechanical stretching. Our findings reveal that these cells form a multilayered, actin-oriented tissue structure, where mechanical forces drive long-range 3D organization and muscle differentiation. Notably, tissue surface emerges as a hotspot for differentiation, correlating with directional order as shown by single molecule fluorescentin situhybridization.Significance StatementWe explore how cells work together to form complex structures, particularly in 3D, using muscle precursors cells (C2C12 myoblasts) as a model. By applying controlled stretching forces, we found that these cells self-organize into layered tissues that guide their transformation into muscle. This research highlights the critical role of physical forces in shaping tissues, suggesting that the way cells are physically arranged and stretched in three dimensions can significantly influence their behavior and function. Our findings offer new insights into how tissues develop and could have implications for tissue engineering, where creating the right 3D environment is key to successful tissue growth and repair.
Glycogen synthase kinase-3 is essential for Tregdevelopment and function
Authors: Kandasamy Matheswaran , Andrew Hana F. , Raza Iwan G. , Mitchell Robert , Borsa Mariana , Attar Moustafa , Clarke Alexander J 
Published: October 2024

AbstractTregsare critical regulators of the immune response, but the cellular signalling pathways that control their development and homeostasis remain to be determined. We found that glycogen synthase kinase-3 (GSK3), a kinase which integrates signals from AKT and mTOR, was essential for Tregdevelopment, restraining fatal autoimmunity. Loss ofGsk3led to metabolic rewiring in Tregs, with disordered nucleotide metabolism and activation of OxPhos. Acute deletion ofGsk3did not affect Tregfrequency or numbers, but induced an effector gene expression program, and led to the formation of populations with pro-inflammatory signatures. The loss ofGsk3in Tregsprofoundly enhanced anti-tumoral immune responses and suppressed tumour growth.
Finding Agreement: fMRI-hyperscanning reveals that dyads explore in mental state space to align opinions
Authors: Speer Sebastian P.H. , Sened Haran , Mwilambwe-Tshilobo Laetitia , Falk Emily B. , Tsoi Lily , Burns Shannon M. , Tamir Diana I. 
Published: October 2024

AbstractMany prize synchrony as the ingredient that turns a conversation from a debate into a delightful duet. Yet, learning from other people’s diverging opinions can also foster understanding and agreement, satisfy curiosity, and spur imagination. Using fMRI hyperscanning and natural language processing we tested how two debaters navigate conflictual conversations to find agreement. Dyads (N=60) discussed pressing societal problems while being instructed to eitherpersuadetheir partner orcompromisewith each other. Our analysis uncovered three key insights: First, individuals instructed to compromise rather than persuade tended to agree more at the end of the session. Second, hyperscanning and linguistic analyses revealed that encouraging compromise resulted in increased exploration during conversations; dyads given compromise instructions traversed more diverse mental states and topics. Third, heightened exploration was linked to greater eventual agreement. Notably, the effect of the compromise instruction on agreement was entirely mediated by the degree of exploration. Together, these results suggest that trying to find agreement may be spurred by exploration, something that happens when people are motivated to compromise but not persuade.
Patient-derived glioblastoma organoids as real-time avatars for assessing responses to clinical CAR-T cell therapy
Authors: Logun Meghan , Wang Xin , Sun Yusha , Bagley Stephen J. , Li Nannan , Desai Arati , Zhang Daniel Y. , Nasrallah MacLean P. , Pai Emily Ling-Lin , Oner Bike Su , Plesa Gabriela , Siegel Donald , Binder Zev A. , Ming Guo-li , Song Hongjun , O’Rourke Donald M. 
Published: October 2024

SUMMARYPatient-derived tumor organoids have been leveraged for disease modeling and preclinical studies, but rarely applied in real-time to aid with interpretation of patient treatment responses in clinics. We recently demonstrated early efficacy signals in a first-in-human, phase 1 study of dual-targeting chimeric antigen receptor T cells (EGFR-IL13Rα2 CAR-T cells) in patients with recurrent glioblastoma. Here we analyzed six sets of patient-derived glioblastoma organoids (GBOs) treated concurrently with the same autologous CAR-T cell products as patients in our phase 1 study. We found that CAR-T cell treatment led to target antigen reduction and cytolysis of tumor cells in GBOs, the degree of which correlated with CAR-T cell engraftment detected in patients’ cerebrospinal fluid (CSF). Furthermore, cytokine release patterns in GBOs mirrored patient CSF samples over time. Our findings highlight a unique trial design and GBOs as a valuable platform for real-time assessment of CAR-T cell bioactivity and insights into immunotherapy efficacy.
A new spatial multi-omics approach to deeply characterize human cancer tissue using a single tissue section
Authors: Adimi Yasmine , Levin Clement , Lombardi Emilia Puig , Morin Benjamin , Gervais Claire , Tolou Sandrine , Noirot-Jagu Anne-Claude , Hauret Julie , Thomas Corinne , Tchepikoff Patricia , Grigorev Fedor , Djafri Anya , Longuemaux Sandrine , Caron Anne , Naimi Souad , Cesaroni Matteo , Tartour Eric , Classe Marion , Badoual Cecile 
Published: October 2024

AbstractIn the ever-changing world of digital pathology, being able to extract a maximum amount of information from a patient tissue sample is of paramount importance for better diagnosis, disease characterization, and therapeutic strategies. Recent technologies such as multiplex immunofluorescence imaging and spatial transcriptomic now enable a deep analysis of protein and gene expression while retaining the spatial context of the tissue. Here, we describe an innovative approach combining a 34-protein Phenocycler panel and transcriptome analysis using Visium on a single head and neck squamous cell carcinoma section. While protein analysis reveals the complexity of the immune phenotypes involved in the disease, transcriptome analysis reveals the intricate cellular states of cancer cells that coexist within the patient’s tumor. Finally, integrating both omics modalities, we uncover unique comparison of gene and protein expression of spatially resolved cellular subspaces.
Fixation probability in a diploid sexually reproducing population
Authors: Shi Zhenyu , Marrec Loïc , Richter Xiang-Yi Li 
Published: October 2024

AbstractClassical population genetics models with haploid individuals and cloning reproduction, such as the Moran process, have limited power in predicting the evolutionary fate of mutants in diploid, sexually reproducing populations. In this work, we built a new stochastic population genetics model to fill this outstanding knowledge gap. We showed that sexual reproduction tends to suppress the fixation probability of beneficial mutants than clonal reproduction, except under overdominance. This effect is particularly large in small populations with biased sex ratios. We also found that small populations are prone to the invasion of mildly detrimental alleles when the heterozygotes have a fitness advantage. Our study highlights the pressing need to extend the research of stochastic population dynamics to consider the biology of sexual reproduction, such as allelic interactions and biased sex ratio. Our model extends the frontier of population genetics research into diploid, sexually reproducing populations and sets the foundation to explore the great variety of biological factors and processes, such as sexual selection and sexual conflict, on stochastic evolutionary dynamics. Future research in this direction will help make better predictions of the evolutionary fate of mutants in relevant contexts, including the conservation of endangered species and evolutionary rescue.
Computational design and evaluation of optimal bait sets for scalable proximity proteomics
Authors: Kasmaeifar Vesal , Sedighi Saya , Gingras Anne-Claude , Campbell Kieran R. 
Published: October 2024

AbstractThe spatial organization of proteins in eukaryotic cells can be explored by identifying nearby proteins using proximity-dependent biotinylation approaches like BioID. BioID defines the localization of thousands of endogenous proteins in human cells when used on hundreds of bait proteins. However, this high bait number restricts the approach’s usage and gives these datasets limited scalability for context-dependent spatial profiling. To make subcellular proteome mapping across different cell types and conditions more practical and cost-effective, we developed a comprehensive benchmarking platform and multiple metrics to assess how well a given bait subset can reproduce an original BioID dataset. We also introduce GENBAIT, which uses a genetic algorithm to optimize bait subset selection, to derive bait subsets predicted to retain the structure and coverage of two large BioID datasets using less than a third of the original baits. This flexible solution is poised to improve the intelligent selection of baits for contextual studies.
Deep Learning-Based Motif Discovery in Major Histocompatibility Complex: A Primer
Authors: Alvarez Bruno , Nielsen Morten 
Published: October 2024

AbstractIn this work, we present a deep learning-based approach for motif discovery in the Major Histo-compatibility Complex (MHC) system, which plays a key role in the immune response. We explore the use of convolutional neural networks (CNNs) to identify peptide binding motifs for different MHC alleles. By training models on data from specific MHC Class I and II molecules, we demonstrate how 1-dimensional convolutional filters can effectively capture motifs and binding preferences. Our study introduces a method for extracting motif logos directly from the trained models, providing insights into how internal neural network representations align with known biological motifs. The results show significant alignment with experimental binding motifs, underscoring the utility of deep learning in immunological research and the potential for improving vaccine design and immunotherapy.
Quantitative proteomic mass spectrometry of protein kinases to determine dynamic heterogeneity of the human kinome
Authors: East Michael P. , Sprung Robert W. , Okumu Denis O. , Olivares-Quintero J. Felix , Joisa Chinmaya U. , Chen Xin , Zhang Qiang , Erdmann-Gilmore Petra , Mi Yiling , Sciaky Noah , Malone James P. , Bhatia Sonam , McCabe Ian C. , Xu Yi , Sutcliffe Matthew D. , Luo Jingqin , Spears Patricia A. , Perou Charles M. , Earp H. Shelton , Carey Lisa A. , Yeh Jen Jen , Spector David L. , Gomez Shawn M. , Spanheimer Philip M. , Townsend R. Reid , Johnson Gary L. 
Published: October 2024

AbstractThe kinome is a dynamic system of kinases regulating signaling networks in cells and dysfunction of protein kinases contributes to many diseases. Regulation of the protein expression of kinases alters cellular responses to environmental changes and perturbations. We configured a library of 672 proteotypic peptides to quantify >300 kinases in a single LC-MS experiment using ten micrograms protein from human tissues including biopsies. This enables absolute quantitation of kinase protein abundance at attomole-femtomole expression levels, requiring no kinase enrichment and less than ten micrograms of starting protein from flash-frozen and formalin fixed paraffin embedded tissues. Breast cancer biopsies, organoids, and cell lines were analyzed using the SureQuant method, demonstrating the heterogeneity of kinase protein expression across and within breast cancer clinical subtypes. Kinome quantitation was coupled with nanoscale phosphoproteomics, providing a feasible method for novel clinical diagnosis and understanding of patient kinome responses to treatment.
H+drives ultra-fast root-to-root responses to wounding
Authors: Ducla Julie , Di Fino Luciano , Mentzelopoulou Andriani , Talide Loïc , Besten Maarten , Bernacka-Wojcik Iwona , Sjöström Theresia Arbring , Zahid Nageena , Jämtgård Sandra , Stavrinidou Eleni , Niittylä Totte , Sprakel Joris , Marhavý Peter 
Published: October 2024

AbstractThe plant-to-plant communication of damage is vital for plants to mount pre-emptive defensive responses in the face of threats. A variety of threats to the well-being of plants are found below ground; yet how plant roots activate inter-plant communication is largely unclear. Here we demonstrate that a wounded root rapidly releases protons (H+), that travel faster than any other “known” soluble biochemical signal due to a specialised diffusion mechanism. Within seconds after damage, cells in neighbouring unwounded roots sense the acidification and activate tissue-specific Ca2+damage signalling. In turn, this triggers a differential growth response allowing the unwounded root to avoid the site of a potential threat. Our results reveal a non-canonical rapid response mechanism for inter-plant communication based on ultrafast proton diffusion.
Impact of JN.1 booster vaccination on neutralisation of SARS-CoV-2 variants KP.3.1.1 and XEC
Authors: Arora Prerna , Happle Christine , Kempf Amy , Nehlmeier Inga , Stankov Metodi V. , Dopfer-Jablonka Alexandra , Behrens Georg M. N. , Pöhlmann Stefan , Hoffmann Markus 
Published: October 2024

AbstractThe SARS-CoV-2 KP.3.1.1 lineage is currently the dominating lineage on several continents. In parallel, the XEC lineage, a recombinant of KS.1.1 and KP.3.3, is on track of becoming the next dominant lineage in Europe and North America. Here we performed a rapid virological characterisation of the XEC lineage and studied the impact of JN.1 mRNA booster vaccination on KP.3.1.1 and XEC neutralisation.
ExEnDiff: An Experiment-guided Diffusion model for protein conformational Ensemble generation
Authors: Liu Yikai , Yu Zongxin , Lindsay Richard J. , Lin Guang , Chen Ming , Sahoo Abhilash , Hanson Sonya M. 
Published: October 2024

AbstractUnderstanding protein conformation is key to understanding their function. Importantly, most proteins adopt multiple conformations with non-trivial ensemble distributions that change depending on their environment to perform functions like catalysis, signaling, and transport. Recently, machine learning techniques, especially deep generative models, have been employed to develop protein conformation generators. These models, known as unified protein ensemble samplers, are trained on the PDB dataset and can generate diverse protein conformation ensembles given a protein sequence. However, their reliance solely on structural data from the PDB, which primarily captures folded protein states, restricts the diversity of the generated ensembles and can result in physically unrealistic conformations. In this paper, we overcome these challenges by introducing ExEnDiff, an experiment-guided diffusion model for protein conformation generation. ExEnDiff integrates experimental measurements as a physical prior, enabling the generation of protein conformations with desired properties. Our experiments on a variety of fast-folding and intrinsically disordered proteins demonstrate that ExEnDiff significantly advances the capabilities of current unified protein ensemble samplers. With little computational cost, ExEnDiff can capture important proteins’ configuration properties and the underlying Boltzmann distribution, paving the way for a next-generation molecular dynamics engine. We further demonstrate the effectiveness of ExEnDiff to capture conformational changes in the presence of mutations and as an efficient tool for determining a reasonable CV space for protein ensembles. With these results, ExEnDiff is well-poised to push the study of protein ensembles into a data-rich regime currently available to few problems in biology.
Design of bacterial DNT sensors based on computational models
Authors: Bahiri Elitzur Shir , Shpigel Etai , Katzir Itai , Alon Uri , Belkin Shimshon , Tuller Tamir 
Published: October 2024

AbstractDetecting explosive compounds such as 2,4,6-trinitrotoluene (TNT) and its volatile byproduct 2,4-dinitrotoluene (DNT) is paramount for public health and environmental safety. In this study, we present the successful application of diverse computational and data analysis models toward developing a bacterial biosensor engineered to detect DNT with high sensitivity and specificity. TheEscherichia coli-based biosensor harbors a plasmid-based fusion of a gene promoter acting as the sensing element to a microbial bioluminescence gene cassette as the reporter. By analyzing endogenous and heterologous promoter data under conditions of DNT exposure, a total of 367 novel variants were generated. The biosensors engineered with these modifications demonstrated a remarkable amplification of up to 4-fold change in signal intensity upon exposure to 2,4-dinitrotoluene compared to non-modified biosensors, accompanied by a decrease in the detection threshold. Our analysis suggests that the sequence features with the highest contribution to biosensor performances are DNA folding patterns and nucleotide motifs associated with DNT sensing. These computational insights guided the rational design of the biosensor, leading to significantly improved DNT detection capabilities compared to the previous biosensor strain.Our results demonstrate the effectiveness of integrating computational modeling with synthetic biology techniques to develop advanced biosensors tailored for environmental monitoring applications. A similar approach may be applied to a wide array of ecological, industrial, and medical sensing endeavors.
ATAD2 drives HIRA/histone H3.3-dependent chromatin dynamics
Authors: Liakopoulou Ariadni , Boussouar Fayçal , Perazza Daniel , Barral Sophie , Lambert Emeline , Wang Tao , Chuffart Florent , Bourova-Flin Ekaterina , Gard Charlyne , Puthier Denis , Rousseaux Sophie , Arnoult Christophe , Verdel André , Khochbin Saadi 
Published: October 2024

AbstractATAD2, expressed predominantly in embryonic stem cells as well as in spermatogenic cells emerges as a pivotal regulator of chromatin dynamics by mediating chromatin-bound histone chaperone turnover. Here, investigating the role of ATAD2 in spermatogenesis, we show that through its preponderant expression in haploid male germ cells, ATAD2 modulates the HIRA-dependent H3.3 genome localization and H3.3-dependent gene transcriptional regulation. Furthermore, by influencing histone eviction and the assembly of protamines, it ensures proper chromatin condensation and genome packaging in mature spermatozoa. The disruption ofAtad2results in aberrant mature spermatozoa genome organization, impacting male fertility. Collectively, these findings confirm the occurrence of an overlooked chromatin dynamic regulatory level controlling histone deposition-removal balance, depending on an ATAD2-controlled histone chaperone – chromatin interaction.
Biotin-IndependentSaccharomyces cerevisiaewith Enhanced Growth: Engineering an Acetyl-CoA Carboxylase Bypass
Authors: Slanska Michaela , Haider Sumbul A. , Kardashliev Tsvetan , Huck Dhanu , Liu Chang C. , Ward Thomas R. 
Published: October 2024

AbstractThroughout evolution, mostSaccharomyces cerevisiaestrains have lost their ability to synthesize biotin, an essential cofactor of several carboxylating enzymes. As a result, the essential vitamin or its precursors must be uptaken from the environment and frequently supplemented in fermentations to achieve high cell densities. Engineering of a biotin-independentS. cerevisiaestrain is of interest to eliminate the need for the external biotin supply. Herein, we describe the construction of a biotin-independent yeast strain by engineering a bypass of acetyl-CoA carboxylase, an essential biotin-dependent enzyme in the synthesis of fatty acids. Besides complete rescue of growth in biotin-free media, the resultingS. cerevisiaestrains showed significantly improved growth on malonate compared to biotin. Beyond their industrial relevance, the yeast strains reported here can be valuable in areas of fundamental research, e.g., for developing a new selection marker or increasing the versatility of biotin-streptavidin technologies in living systems.
Elastic analysis of structural ensemble reveals the energetic basis of hand-over-hand in a AAA+ motor
Authors: Mello Victor Hugo , Wald Jiri , Marlovits Thomas C , Sartori Pablo 
Published: October 2024

AbstractProteins carry out cellular functions by changing their structure among a few conformations, each characterized by a different energy level. Therefore, structural changes, energy transformations, and protein function are intimately related. Despite its central importance, this relationship remains elusive. For example, while many AAA+ assemblies are known to function using a hand-over-hand alternation of subunits, how energy transduction throughout the assembly structure drives hand-over-hand is not known. In this work, we unravel the energetic basis of hand-over-hand in a model AAA+ motor, RuvB. To do so, we develop a general method to compute the residue scale elastic energy due to structure changes and apply it to RuvB structures, recently resolved through cryo-EM. This allows us to quantify how progression through RuvB’s mechanochemical cycle translates into residue scale energy transduction. In particular, we find that DNA binding is associated with overcoming a high energy barrier. This is possible through inter-subunit transmission of energy, and ultimately driven by binding of ATP. Furthermore, we show how this structure-inferred energetic quantification can be integrated into a non-equilibrium model of AAA+ assembly dynamics, consistent with single-molecule biophysics measurements. Overall, our work elucidates the energetic basis for the hand-over-hand mechanism in RuvB’s cycle. Furthermore, it presents a generally applicable methodology for studying the energetics of conformational cycles in other proteins, allowing to quantitatively bridge data from structural biology and single-molecule biophysics.PACS numbers: