bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cell type-specific immune regulation under symbiosis in a facultatively symbiotic coral
Authors: Valadez-Ingersoll Maria , Rivera Hanny E. , Da-Anoy JK , Kanke Matthew R. , Gomez-Campo Kelly , Martinez-Rugerio M. Isabel , Kwan Julian , Hekman Ryan , Emili Andrew , Gilmore Thomas D. , Davies Sarah W. 
Published: June 2024

ABSTRACTMany cnidarians host single-celled algae within gastrodermal cells, yielding a mutually beneficial exchange of nutrients between host and symbiont, and dysbiosis can lead to host mortality. Previous research has uncovered symbiosis tradeoffs, including suppression of immune pathways in cnidarians hosting intracellular algae and correlations between symbiotic state and pathogen susceptibility. Here, we used a multiomic approach to characterize symbiotic states of the facultatively symbiotic coralOculina arbusculaby generating genotype-controlled fragments of symbiotic and aposymbiotic tissue. 16S metabarcoding showed no difference in bacterial communities between symbiotic states. Whole-organism proteomics revealed differential abundance of proteins related to immunity, confirming immune suppression during symbiosis. Finally, single-cell RNAseq identified diverse cell clusters within seven cell types across symbiotic states. Specifically, the gastrodermal cell clusters containing algal-hosting cells from symbiotic tissue had higher expression of nitrogen cycling and sugar transport genes than aposymbiotic gastrodermal cells. Furthermore, differential enrichment of immune system gene pathways and lower expression of genes involved in immune regulation were observed in these gastrodermal cells from symbiotic tissue. However, no differences in immune gene expression in the immune cell cluster were observed between symbiotic states. This work reveals a compartmentalization of immune system regulation in specific gastrodermal cells in symbiosis, which may limit symbiosis tradeoffs by simultaneously dampening immunity in algal-hosting cells while maintaining general organismal immunity.
Weakly nonlinear responses at low intrinsic noise levels in two types of electrosensory primary afferents
Authors: Barayeu Alexandra , Schlungbaum Maria , Lindner Benjamin , Benda Jan , Grewe Jan 
Published: June 2024

AbstractNeuronal processing is inherently nonlinear — spiking thresholds or rectification in synapses are central to neuronal computations. Nevertheless, linear response theory has been instrumental in understanding, for example, the impact of noise or synchronous spikes on signal transmission, or the emergence of oscillatory activity. At higher signal-to-noise ratios, however, the third term in the Volterra series becomes relevant. This second-order susceptibility captures nonlinear interactions between pairs of stimulus frequencies. Theoretical results for leaky integrate-and-fire neurons suggest strong responses at the sum of two input frequencies only when these frequencies or their sum match the neuron’s baseline firing rate. We here analyze second-order susceptibilities in two types of primary electroreceptor afferents, P-units of the active and ampullary cells of the passive electrosensory system of the wave-type electric fishApteronotus leptorhynchus. In our combined experimental and modeling approach we find the predicted weakly nonlinear responses in some P-units with very low baseline interspike-interval variability and much stronger in all ampullary cells, which are less noisy than P-units. Such nonlinear responses boost responses to weak sinusoidal stimuli and are therefore of immediate relevance for wave-type electric fish that are exposed to superpositions of many frequencies in social contexts.
TransLeish: Identification of membrane transporters essential for survival of intracellularLeishmaniaparasites in a systematic gene deletion screen
Authors: Albuquerque-Wendt Andreia , McCoy Ciaran , Neish Rachel , Dobramysl Ulrich , Beneke Tom , Cowley Sally A. , Crouch Kathryn , Wheeler Richard J. , Mottram Jeremy C. , Gluenz Eva 
Published: June 2024

SummaryFor the protozoan parasiteLeishmania, completion of its life cycle requires sequential adaptation of cellular physiology and nutrient scavenging mechanisms to the different environments of a sand fly alimentary tract and the acidic mammalian host cell phagolysosome. Transmembrane transporters are the gatekeepers of intracellular environments, controlling the flux of solutes and ions across membranes. To discover which transporters are vital for survival as intracellular amastigote forms, we carried out a systematic loss-of-function screen of theL. mexicanatransportome. A total of 312 protein components of small molecule carriers, ion channels and pumps were identified and targeted in a CRISPR-Cas9 gene deletion screen in the promastigote form, yielding 188 viable null mutants. Forty transporter deletions caused significant loss of fitness in macrophage and mouse infections. A striking example is the Vacuolar H+ATPase (V-ATPase), which, unexpectedly, was dispensable for promastigote growthin vitrobut essential for survival of the disease-causing amastigotes.
Disordered regions of human eIF4B orchestrate a dynamic self-association landscape
Authors: Swain Bikash Chandra , Sarkis Pascale , Ung Vanessa , Rousseau Sabrina , Fernandez Laurent , Meltonyan Ani , Aho V. Esperance , Mercadante Davide , Mackereth Cameron D. , Aznauryan Mikayel 
Published: June 2024

AbstractEukaryotic translation initiation factor eIF4B is required for efficient cap-dependent translation, it is overexpressed in cancer cells, and may influence stress granule formation. Due to the high degree of intrinsic disorder, eIF4B is rarely observed in cryo-EM structures of translation complexes and only ever by its single structured RNA recognition motif domain, leaving the molecular details of its large intrinsically disordered region (IDR) unknown. By integrating experiments and simulations we demonstrate that eIF4B IDR orchestrates and fine-tunes an intricate transition from monomers to a condensed phase, in which large-size dynamic oligomers form before mesoscopic phase separation. Single-molecule spectroscopy combined with molecular simulations enabled us to characterize the conformational ensembles and underlying intra- and intermolecular dynamics across the oligomerization transition. The observed sensitivity to ionic strength and molecular crowding in the self-association landscape suggests potential regulation of eIF4B nanoscopic and mesoscopic behaviors such as driven by protein modifications, binding partners or changes to the cellular environment.
Spatiotemporal analysis of F-actin polymerization with micropillar arrays reveals synchronization between adhesion sites
Authors: Hollander Sarit , Guo Yuanning , Wolfenson Haguy , Zaritsky Assaf 
Published: June 2024

AbstractWe repurposed micropillar-arrays to quantify spatiotemporal inter-adhesion communication. Following the observation that integrin adhesions formed around pillar tops we relied on the precise repetitive spatial control of the pillars to reliably monitor F-actin dynamics in mouse embryonic fibroblasts as a model for spatiotemporal adhesion-related intracellular signaling. Using correlation-based analyses we revealed localized information-flows propagating between adjacent pillars that were integrated over space and time to synchronize the adhesion dynamics within the entire cell. Probing the mechanical regulation, we discovered that stiffer pillars or partial actomyosin contractility inhibition enhances inter-adhesion F-actin synchronization. Our results suggest that adhesions can communicate and highlight the potential of using micropillar arrays as a tool to measure spatiotemporal intracellular signaling.
Molecular mapping and functional validation of GLP-1R cholesterol binding sites in pancreatic beta cells
Authors: Oqua Affiong I , Chao Kin , El Eid Liliane , Casteller Lisa , Baxter Billy P , Miguéns-Gómez Alba , Barg Sebastian , Jones Ben , Bernadino de la Serna Jorge , Rouse Sarah L , Tomas Alejandra 
Published: June 2024

AbstractG protein-coupled receptors (GPCRs) are integral membrane proteins which closely interact with their plasma membrane lipid microenvironment. Cholesterol is a lipid enriched at the plasma membrane with pivotal roles in the control of membrane fluidity and maintenance of membrane microarchitecture, directly impacting on GPCR stability, dynamics and function. Cholesterol extraction from pancreatic beta cells has previously been shown to disrupt the internalisation, clustering and cAMP responses of the glucagon-like peptide-1 receptor (GLP-1R), a class B1 GPCR with key roles in the control of blood glucose levels via the potentiation of insulin secretion in beta cells and weight reduction via the modulation of brain appetite control centres. Here, we unveil the detrimental effect of a high cholesterol diet on GLP-1R-dependent glucoregulationin vivo, and the improvement in GLP-1R function that a reduction in cholesterol synthesis using simvastatin exerts in pancreatic islets. We next identify and map sites of cholesterol high occupancy and residence time on activeversusinactive GLP-1Rs using coarse-grained molecular dynamics (cgMD) simulations, followed by a screen of key residues selected from these sites and detailed analyses of the effects of mutating one of these residues, Val229, to alanine on GLP-1R interactions with cholesterol, plasma membrane behaviours, clustering, trafficking and signalling in pancreatic beta cells and primary islets, unveiling an improved insulin secretion profile for the V229A mutant receptor. This study 1) highlights the role of cholesterol in regulating GLP-1R responsesin vivo; 2) provides a detailed map of GLP-1R - cholesterol binding sites in model membranes; 3) validates their functional relevance in beta cells; and 4) highlights their potential as locations for the rational design of novel allosteric modulators with the capacity to fine-tune GLP-1R responses.
Point set registration for combining fluorescence microscopy methods
Authors: Severins Ivo , Joo Chirlmin , van Noort John 
Published: June 2024

SUMMARYImplementation of combined microscopy methods provides valuable information across various scientific applications. However, aligning the datasets and finding the correct point correspondence poses a challenge, especially for large, randomly distributed point sets that are subject to positional errors and missing points. Here, we provide a three-step procedure to perform point set registration, which can be applied to datasets with millions of points and stays robust even when only 10% of the points correspond. In the first global step, the scaling and rotation parameters for the imaging systems are determined once on a smaller calibration dataset using a geometric hashing algorithm. When the global transformation is known, full experimental datasets can be registered by performing step two: a course registration using cross-correlation, and step three: a precise registration to fine-tune the transformation. After these three steps, point correspondence is determined by setting a distance threshold based on a statistical model of random point sets that additionally provides the matching error. We have demonstrated its successful implementation in coupling fluorescence and sequencing methodologies. To enable wide application of these point set registration and correspondence algorithms we provide a python library called MatchPoint.
Exosomes Released from Senescent Cells and Circulatory Exosomes Isolated from Human Plasma Reveal Aging-associated Proteomic and Lipid Signatures
Authors: Patel Sandip Kumar , Bons Joanna , Rose Jacob P. , Chappel Jessie R. , Beres Rebecca L. , Watson Mark A. , Webster Corey , Burton Jordan B. , Bruderer Roland , Desprez Pierre-Yves , Reiter Lukas , Campisi Judith , Baker Erin S. , Schilling Birgit 
Published: June 2024

AbstractSenescence emerged as a significant mechanism of aging and age-related diseases, offering an attractive target for clinical interventions. Senescent cells release a senescence-associated secretory phenotype (SASP), including exosomes that may act as signal transducers between distal tissues, propagating secondary or bystander senescence and signaling throughout the body. However, the composition of exosome SASP remains underexplored, presenting an opportunity for novel unbiased discovery. Here, we present a detailed proteomic and lipidomic analysis of exosome SASP using mass spectrometry from human plasma from young and older individuals and from tissue culture of senescent primary human lung fibroblasts. We identified ~1,300 exosome proteins released by senescent fibroblasts induced by three different senescence inducers causing most exosome proteins to be differentially regulated with senescence. In parallel, a human plasma cohort from young and old individuals revealed over 1,350 exosome proteins and 171 plasma exosome proteins were regulated when comparing old vs young individuals. Of the age-regulated plasma exosome proteins, we observed 52 exosome SASP factors that were also regulated in exosomes from the senescent fibroblasts, including serine protease inhibitors (SERPINs), Prothrombin, Coagulation factor V, Plasminogen, and Reelin. In addition, 247 lipids were identified with high confidence in all exosome samples. Following the senescence inducers, a majority of the identified phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin species increased significantly indicating cellular membrane changes. The most notable categories of significantly changed proteins were related to extracellular matrix remodeling and inflammation, both potentially detrimental pathways that can damage surrounding tissues and even induce secondary or bystander senescence. Our findings reveal mechanistic insights and potential senescence biomarkers, enabling a better approach to surveilling the senescence burden in the aging population and offering promising therapeutic targets for interventions.
Engineered yeast multicellularity via synthetic cell-cell adhesion and direct-contact signalling
Authors: Meng Fankang , Shaw William M. , Kam Yui Kei Keith , Ellis Tom 
Published: June 2024

AbstractCoordination of behaviour in multicellular systems is one the main ways that nature increases the complexity of biological function in organisms and communities. WhileSaccharomyces cerevisiaeyeast is used extensively in research and biotechnology, it is a unicellular organism capable of only limited multicellular states. Here we expand the possibilities for engineering multicellular behaviours in yeast by developing modular toolkits for two key mechanisms seen in multicellularity, contact-dependent signalling and specific cell-to-cell adhesion. MARS (Mating-peptideAnchoredResponseSystem) is a toolkit based on surface-displayed fungal mating peptides and G protein-coupled receptor (GPCR) signalling which can mimic juxtacrine signalling between yeasts. SATURN (SaccharomycesAdhesionToolkit for multicellUlar patteRNing) surface displays adhesion-proteins pairs on yeasts and facilitates the creation of cell aggregation patterns. Together they can be used to create multicellular logic circuits, equivalent to developmental programs that lead to cell differentiation based on the local population. Using MARS and SATURN, we further developed JUPITER (JUxtacrine sensor forProtein-protein InTERaction), a genetic sensor for assaying protein-protein interactions in culture, demonstrating this as a tool to select for high affinity binders among a population of mutated nanobodies. Collectively, MARS, SATURN, and JUPITER present valuable tools that facilitate the engineering of complex multicellularity with yeast and expand the scope of its biotechnological applications.
The structural, functional, and neurophysiological connectome of mild traumatic brain injury: a DTI, fMRI and MEG multimodal clustering and data fusion study
Authors: Zhang Jing , Solar Kevin , Safar Kristina , Zamyadi Rouzbeh , Vandewouw Marlee M. , Da Costa Leodante , Rhind Shawn G. , Jetly Rakesh , Dunkley Benjamin T. 
Published: June 2024

AbstractThe clinical presentation and neurobiology of mild traumatic brain injury (mTBI) - also referred to as concussion - are complex and multifaceted, and interrelationships between neurobiological measures derived from neuroimaging are poorly understood. This study applied machine learning (ML) to multimodal whole-brain functional connectomes from magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and structural connectomes from diffusion tensor imaging (DTI) in a test of discriminative accuracy in cases of mTBI. Resting state MEG (amplitude envelope correlations), fMRI (BOLD correlations), and DTI (fractional anisotropy, FA; streamline count, SC) connectome data was acquired in 26 controls without mTBI (all male; 27.6 ± 4.7 years) and 24 participants with mTBI (all male; 29.7 ± 6.7 years) in the acute-subacute phase of injury. ML with data fusion was used to optimally identify modalities and brain features for discriminating individuals with mTBI from those without. Univariate group differences were only found for MEG functional connectivity, while no differences were found for fMRI or DTI. Functional connectivity (fMRI and MEG) showed robust unimodal classification accuracy for mTBI, followed by structural connectivity (DTI), where FA showed marginally better classification performance than SC, but SC outperformed FA in data interpretation and fusion. Perfect, unsupervised separation of participants with and without mTBI was achieved through participant fusion maps featuring all three data modalities. Finally, the MEG-only full feature fusion map showed group differences, and this effect was eliminated upon integrating DTI and fMRI datasets. The markers identified here align well with prior multimodal findings in concussion and highlight modality-specific considerations for their use in understanding network abnormalities of mTBI.
NeoGx: Machine-Recommended Rapid Genome Sequencing for Neonates
Authors: Antoniou Austin A. , McGinley Regan , Metzler Marina , Chaudhari Bimal P. 
Published: June 2024

ABSTRACTBackgroundGenetic disease is common in the Level IV Neonatal Intensive Care Unit (NICU), but neonatology providers are not always able to identify the need for genetic evaluation. We trained a machine learning (ML) algorithm to predict the need for genetic testing within the first 18 months of life using health record phenotypes.MethodsFor a decade of NICU patients, we extracted Human Phenotype Ontology (HPO) terms from clinical text with Natural Language Processing tools. Considering multiple feature sets, classifier architectures, and hyperparameters, we selected a classifier and made predictions on a validation cohort of 2,241 Level IV NICU admits born 2020-2021.ResultsOur classifier had ROC AUC of 0.87 and PR AUC of 0.73 when making predictions during the first week in the Level IV NICU. We simulated testing policies under which subjects begin testing at the time of first ML prediction, estimating diagnostic odyssey length both with and without the additional benefit of pursuing rGS at this time. Just by using ML to accelerate initial genetic testing (without changing the tests ordered), the median time to first genetic test dropped from 10 days to 1 day, and the number of diagnostic odysseys resolved within 14 days of NICU admission increased by a factor of 1.8. By additionally requiring rGS at the time of positive ML prediction, the number of diagnostic odysseys resolved within 14 days was 3.8 times higher than the baseline.ConclusionsML predictions of genetic testing need, together with the application of the right rapid testing modality, can help providers accelerate genetics evaluation and bring about earlier and better outcomes for patients.
Structural basis for the transport and regulation mechanism of the Multidrug resistance-associated protein 2
Authors: Koide Eriko , Pietz Harlan L. , Beltran Jean , Chen Jue 
Published: June 2024

AbstractMultidrug resistance-associated protein 2 (MRP2) is an ATP-powered exporter important for maintaining liver homeostasis and a potential contributor to chemotherapeutic resistance. Deficiencies in MRP2 function are associated with Dubin-Johnson Syndrome and increased vulnerability to liver injury from cytotoxic drugs. Using cryogenic electron microscopy (cryo-EM), we determined the structures of human MRP2 in three conformational states: an autoinhibited state, a substrate-bound pre-translocation state, and an ATP-bound post-translocation state. These structures show that MRP2 functions through the classic alternating access model, driven by ATP binding and hydrolysis. Its cytosolic regulatory (R) domain serves as a selectivity gauge, wherein only sufficiently high concentrations of substrates can effectively compete with and disengage the R domain to initiate transport. Comparative structural analyses of MRP2 in complex with different substrates reveal how the transporter recognizes a diverse array of compounds, highlighting the transporter’s role in multidrug resistance.
Comparative Approaches for Quantification of Product Yield in a Model Recombinant Green Fluorescent Protein Expressed inE. coli
Authors: Rusch Gabrielle , Wang Junhyeong , Breau Keith , Kilgour Katie , Gilleskie Gary , Keele Jeff , Selle Kurt , Magness Scott T. , Menegatti Stefano , Daniele Michael 
Published: June 2024

AbstractProcess Analytical Technologies (PAT) used to monitor and control manufacturing processes are crucial for efficient and automated bioprocessing, which is in congruence with lights-off-manufacturing and Industry 4.0 initiatives. As biomanufacturing seeks to realize more high-throughput and automated operation, an increasing need for multimodal analysis of process metrics becomes essential. Herein, we detail a series of methods for analyzing product yield from a bioreactor and how to conduct cross-method comparisons. We employ a model system ofEscherichia coli(E. coli) expression of green fluorescent protein (GFP), which is a simple, cost effective model for students and educators to replicate at different scales. GFP is an ideal analytical marker as it is easy to visualize due to its fluorescence which indicates cellular protein expression, cell localization and physiological changes of the cell population. In this study, samples from a 300 L bioreactor with GFP-expressingE. coliare analyzed to improve product yield and bioprocessing efficiency. Utilizing a fed-batch process for enhanced cell density and product titer, this bioreactor runs on a 24-hour schedule from inoculation to GFP induction and final harvest. To reliably quantify relative GFP expression andE. coliproliferation, we provide simple protocols and example results for comparing three different analytical methods: (1) in-line bioreactor measurements, (2) plate reader assays, and (3) microscopy. The GFP and cell density results follow similar trends based on the various inline and offline analytical methods and show a peak of GFP expression and cell density between 12.5 and 18 hours post inoculation.