bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeted engineering of the phase separating PARCL protein
Authors: Veevers Ruth , Ostendorp Steffen , Ostendorp Anna , Kehr Julia , Morris Richard J. 
Published: June 2024

AbstractPARCL is a plant-specific RNA-binding protein (RBP) that exhibits chaperone activity, is abundant in the phloem, intrinsically disordered, and contains a prion-like domain (PLD). PARCL proteins have been observed to form large biomolecular condensatesin vivoandin vitro. Biomolecular condensates are membraneless compartments, wherein biomolecules become partitioned from their surrounding liquid environment into liquid droplets with their own composition, dynamics, and function. Which molecular properties drive phase separation is of great interest for targeted engineering efforts. Here, we present results on residue interactions derived from simulations of PARCL using course-grained molecular dynamics with the HPS-Urry model. We adjust the parameters of the simulations to allow the inclusion of folded eYFP tags, since fluorescent tags are often used in phase separation experiments for visualising droplets, yet have not been included in simulations to date. While still simulating phase separation, these trajectories suggest minor changes to droplet and network structure when proteins contain eYFP. By analysing the residues of the PARCL molecules that come within contact distance in the simulations, we identify which individual residues drive phase separation. To experimentally validate these findings, we introduced mutations of the most contacted residues and could indeed confirm that these mutations prevent the formation of condensate droplets. To investigate the RNA-binding of PARCL, we added microRNA to the simulation and find a short region of PARCL consistently making contact with the miRNA, which is also in agreement with predictions and experiments. We discuss the implications of our findings in terms of model-guided engineering of biomolecular condensates.
MetaKSSD: Boosting the Scalability of Reference Taxonomic Marker Database and the Performance of Metagenomic Profiling Using Sketch Operations
Authors: Yi Huiguang , Lu Xiaoxin , Chang Qing 
Published: June 2024

AbstractThe rapid increase in genomes and metagenomic data presents major scalability and efficiency challenges for current metagenomic profilers. In response, we introduce MetaKSSD, which redefines reference taxonomic marker database (MarkerDB) construction and metagenomic profiling using sketch operations, offering efficiency improvements by orders of magnitude. MetaKSSD encompasses 85,202 species in its MarkerDB using just 0.17GB of storage and profiles 10GB of data within seconds, utilizing only 0.5GB of memory. Extensive benchmarking experiments demonstrated that MetaKSSD is among the top-performing profilers across various metrics. In a microbiome-phenotype association study, MetaKSSD identified significantly more effective associations than MetaPhlAn4. We profiled 382,016 metagenomic runs using MetaKSSD, conducted extensive sample clustering analyses, and suggested potential yet-to-be-discovered niches. Additionally, we developed functionality in MetaKSSD for instantaneous searching among large-scale profiles. The client-server architecture of MetaKSSD allows the swift transmission of metagenome sketches over the network and enables real-time online metagenomic analysis, facilitating use by non-expert users.
Molecular Architecture of Monkeypox Mature Virus
Authors: Hong Ye , Huang Baoying , Zhang Junxia , Peng Cheng , Kong Weizheng , Tan Wenjie , Li Sai 
Published: June 2024

AbstractSince the 2022 mpox outbreak, MPXV has caused ∼100,000 infected cases with ∼200 deaths across 117 countries. and was declared a public health emergency of international concern by the WHO. The causative pathogen, monkeypox virus (MPXV), is a zoonotic double-stranded DNA orthopoxvirus. To investigate the structures and replication mechanism of MPXV, the MPXV recombinant proteins and vaccinia virus (VACV) particles have been studied by cryo-EM, however,in situstructural insights into major structural proteins and assembly of the authentic MPXV particles are missing. In this work, we isolated two MPXV strains from the first imported mpox case and the first local mpox case in mainland China. From the two strains, we propagated and purified mature viruses, and applied cryo-electron tomography (cryo-ET) and sub-tomogram averaging (STA) to unveil the architecture of intact MPXV virus. Interestingly, we also discovered irregularly-shaped mature virions with distorted core walls. To our knowledge, these in situ structural insights in MPXV have not been reported before.
Disruption of liquid/liquid phase separation in asymmetric GUVs prepared by hemifusion
Authors: Kennison-Cook Kristen B. , Heberle Frederick A. 
Published: June 2024

AbstractModel asymmetric bilayers are useful for studying the coupling between lateral and transverse lipid organization. Here, we used calcium-induced hemifusion to create asymmetric giant unilamellar vesicles (aGUVs) for exploring the phase behavior of 16:0-PC/16:1-PC/Cholesterol, a simplified model for the mammalian plasma membrane. Symmetric GUVs (sGUVs) were first prepared using a composition that produced coexisting liquid-disordered and liquid-ordered phases visible by confocal fluorescence microscopy. The sGUVs were then hemifused to a supported lipid bilayer (SLB) composed of uniformly mixed 16:1-PC/Cholesterol. The extent of outer leaflet exchange was quantified in aGUVs in two ways: (1) from the reduction in fluorescence intensity of a lipid probe initially in the sGUV (“probe exit”); or (2) from the gain in intensity of a probe initially in the SLB (“probe entry”). These measurements revealed a large variability in the extent of outer leaflet exchange in aGUVs within a given preparation, and two populations with respect to their phase behavior: a subset of vesicles that remained phase separated, and a second subset that appeared uniformly mixed. Moreover, a correlation between phase behavior and extent of asymmetry was observed, with more strongly asymmetric vesicles having a greater probability of being uniformly mixed. We also observed substantial overlap between these populations, an indication that the uncertainty in measured exchange fraction is high. We developed models to determine the position of the phase boundary (i.e., the fraction of outer leaflet exchange above which domain formation is suppressed) and found that the phase boundaries determined separately from probe-entry and probe-exit data are in good agreement. Our models also provide improved estimates of the compositional uncertainty of individual aGUVs. We discuss several potential sources of uncertainty in the determination of lipid exchange from fluorescence measurements.Statement of SignificanceWe used calcium-induced hemifusion to create an asymmetric lipid distribution in giant unilamellar vesicles that are models for the mammalian plasma membrane. Confocal fluorescence micrographs of asymmetric vesicles showed that coexisting liquid-ordered and liquid-disordered domains initially present in symmetric vesicles were disrupted after 75% of the saturated lipid in their outer leaflets was replaced with unsaturated lipid. We developed quantitative models for extracting valuable information from the data, including the location of the phase boundary and the compositional uncertainty of individual asymmetric vesicles. The methodology we describe can help reveal the molecular determinants of interleaflet coupling of phase behavior and thus contribute to a better understanding of lipid raft phenomena.
GeneSpectra: a method for context-aware comparison of cell type gene expression across species
Authors: Song Yuyao , Papatheodorou Irene , Brazma Alvis 
Published: June 2024

AbstractComputational comparison of single cell expression profiles cross-species uncovers functional similarities and differences between cell types. Importantly, it offers the potential to refine evolutionary relationships based on gene expression. Current analysis strategies are limited by the strong hypothesis of ortholog conjecture, which implies that orthologs have similar cell type expression patterns. They also lose expression information from non-orthologs, making them inapplicable in practice for large evolutionary distances. To address these limitations, we devised a novel analytical framework, GeneSpectra, to robustly classify genes by their expression specificity and distribution across cell types. This framework allows for the generalization of the ortholog conjecture by evaluating the degree of ortholog class conservation. We utilise different gene classes to decode species effects on cross-species transcriptomics space and compare sequence conservation with expression specificity similarity across different types of orthologs. We develop contextualised cell type similarity measurements while considering species-unique genes and non-one-to-one orthologs. Finally, we consolidate gene classification results into a knowledge graph, GeneSpectraKG, allowing a hierarchical depiction of cell types and orthologous groups, while continuously integrating new data.
Multisensory Integration of Naturalistic Speech and Gestures in Autistic Adults
Authors: Matyjek Magdalena , Kita Sotaro , Torralba Cuello Mireia , Soto Faraco Salvador 
Published: June 2024

AbstractSeeing the speaker facilitates auditory speech comprehension through audio-visual integration. This is especially the case in challenging listening conditions, such as in real-life social environments. Autism has been associated with atypicalities in integrating audio-visual information, potentially underlying social difficulties in this population. The present study investigated multisensory integration (MSI) in speech processing among autistic (N=35) and neurotypical (N=35) adults. Participants performed a speech-in-noise task in a realistic multispeaker social scenario with audio-visual, auditory, or visual trials while their brain activity was recorded using EEG. The neurotypical group demonstrated a non-linear audio-visual interaction in alpha suppression, whereas the autistic group showed merely additive processing of these same inputs. Despite these differences in neural correlates, both groups achieved similar behavioural audio-visual facilitation outcomes. These findings suggest that although autistic and neurotypical brains might process multisensory cues differently, they achieve comparable benefits from audio-visual speech. These results contribute to the growing body of literature on MSI atypicalities in autism.
Decoupling individual host response and immune cell engager cytotoxic potency
Authors: Gonzalez Gutierrez Cristina , Aimard Adrien , Biarnes-Pélicot Martine , Kerfelec Brigitte , Puech Pierre-Henri , Robert Philippe , Piazza Francesco , Chames Patrick , Limozin Laurent 
Published: June 2024

AbstractImmune cell engagers are molecular agents, usually antibody-based constructs, engineered to recruit immune cells against cancer cells and kill them. They represent a versatile and powerful tool for cancer immunotherapy. Despite the multiplication of new engagers tested and accepted in the clinics, how molecular and cellular parameters influence their action is poorly understood. In particular, disentangling the respective role of host immune cells and engager biophysical characteristics is needed to improve their design and efficiency. Focusing here on harnessing antibody dependent Natural Killer cell cytotoxicity, we measure the efficiency of 6 original bispecific antibodies (bsAb), associating an anti-HER2 nanobody and an anti-CD16 nanobody.In vitrocytotoxicity data using primary human NK cells on different target cell lines exposing different antigen densities were collected, exhibiting a wide range of bsAb dose response. In order to rationalize our observations, we introduce a simple multiscale model, postulating that the density of bsAb bridging the two cells is the main parameter triggering the cytotoxic response. We introduce two new microscopic parameters: the surface cooperativity describing bsAb affinity at the bridging step and the threshold of bridge density determining the donor-dependent response. Both parameters permit to rank Abs and donors and to predict bsAb potency as a function of antibodies bulk affinities and receptor surface densities on cells. Our approach thus provides a general way to decouple donor response from immune engagers characteristics, rationalizing the landscape of molecule design.
ACE-2 Blockade & TMPRSS2 Inhibition Mitigate SARS-CoV-2 Severity Following Cigarette Smoke Exposure in Airway Epithelial Cells In Vitro
Authors: Hussain Shah S , Libby Emily Falk , Lever Jacelyn E Peabody , Tipper Jennifer L , Phillips Scott E , Mazur Marina , Li Qian , Campos-Gómez Javier , Harrod Kevin S , Rowe Steven M 
Published: June 2024

AbstractCigarette smoking is associated with COVID-19 prevalence and severity, but the mechanistic basis for how smoking alters SARS-CoV-2 pathogenesis is unknown. A potential explanation is that smoking alters the expression of the SARS-CoV-2 cellular receptor and point of entry, angiotensin converting enzyme-2 (ACE-2), and its cofactors including transmembrane protease serine 2 (TMPRSS2). We investigated the impact of cigarette smoking on the expression of ACE-2, TMPRSS2, and other known cofactors of SARS-CoV-2 infection and the resultant effects on infection severity in vitro. Cigarette smoke extract (CSE) exposure increased ACE-2 and TMPRSS2 mRNA expression compared to air control in ferret airway cells, Calu-3 cells, and primary human bronchial epithelial (HBE) cells derived from normal and COPD donors. CSE-exposed ferret airway cells inoculated with SARS-CoV-2 had a significantly higher intracellular viral load versus vehicle-exposed cells. Likewise, CSE-exposure increased both SARS-CoV-2 intracellular viral load and viral replication in both normal and COPD HBE cells over vehicle control. Apoptosis was increased in CSE-exposed, SARS-CoV-2-infected HBE cells. Knockdown of ACE-2 via an antisense oligonucleotide (ASO) reduced SARS-CoV-2 viral load and infection in CSE-exposed ferret airway cells that was augmented by co-administration of camostat mesylate to block TMPRSS2 activity. Smoking increases SARS-CoV-2 infection via upregulation of ACE2 and TMPRSS2.
Using Photoswitching FRET to Define the Interaction Boundaries between the Rab1b GTPase and Secretory Cargo
Authors: Malis Yehonathan , Hirschberg Guy M. , Patterson George H. , Hirschberg Koret 
Published: June 2024

AbstractFRET is a powerful tool to simultaneously establish and localize interactions between fluorescently tagged proteins with high spatial resolution. Rainey K.H. and Patterson G.H. introduced Photoswitching FRET (psFRET) using the Dronpa Photoswitching fluorescent protein. We present a straightforward detailed method, and a powerful software tool that allows adaptation of psFRET to diverse experimental setups. Image stacks, recording the decay of the Dronpa donor, serve as input to the software utility that includes effective preprocessing options preceding the calculation FRET efficiency at the single pixel level. We applied psFRET to generate interaction maps analyzing diverse interactions between cargo proteins, the GTPase Rab1b, and GRASP65 during ER to Golgi trafficking. Cargo-Rab1b interactions were restricted to the transit period from ER to Golgi. These data lend support to a mechanism whereby cargo sensing may regulate the level of downstream effectors recruitment to secretory membranes by Rab1.
SWEET family transporters act as water conducting carrier proteins in plants
Authors: Selvam Balaji , Paul Arnav , Yu Ya-Chi , Chen Li-Qing , Shukla Diwakar 
Published: June 2024

AbstractDedicated water channels are involved in the facilitated diffusion of water molecules across the cell membrane in plants. Transporter proteins are also known to transport water molecules along with substrates, however the molecular mechanism of water permeation is not well understood in plant transporters. Here, we show plant sugar transporters from the SWEET (SugarWillEventually beExportedTransporter) family act as water-conducting carrier proteins via a variety of passive and active mechanisms that allow diffusion of water molecules from one side of the membrane to the other. This study provides a molecular perspective on how plant membrane transporters act as water carrier proteins, a topic that has not been extensively explored in literature. Water permeation in membrane transporters could occur via four distinct mechanisms which form our hypothesis for water transport in SWEETs. These hypothesis are tested using molecular dynamics simulations of the outward-facing, occluded, and inward-facing state of AtSWEET1 to identify the water permeation pathways and the flux associated with them. The hydrophobic gates at the center of the transport tunnel act as a barrier that restricts water permeation. We have performedin silicosingle and double mutations of the hydrophobic gate residues to examine the changes in the water conductivity. Surprisingly, the double mutant allows the water permeation to the intracellular half of the membrane and forms a continuous water channel. These computational results are validated by experimentally examining the transport of hydrogen peroxide molecules by the AtSWEET family of transporters. We have also shown that the transport of hydrogen peroxide follows the similar mechanism as water transport in AtSWEET1. Finally, we conclude that similar water-conduction states are also present in other SWEET transporters due to the high sequence and structure conservation exhibited by this transporter family.
Cortical Lesion Expansion in Chronic Traumatic Brain Injury
Authors: Freeman Holly J. , Atalay Alexander S. , Li Jian , Sobczak Evie , Gilmore Natalie , Snider Samuel B. , Healy Brian C , Carrington Holly , Selmanovic Enna , Pruyser Ariel , Bura Lisa , Sheppard David , Hunt David , Seifert Alan C. , Bodien Yelena G. , Hoffman Jeanne M. , Mac Donald Christine L. , Dams-O’Connor Kristen , Edlow Brian L. 
Published: June 2024

AbstractTraumatic brain injury (TBI) is a risk factor for neurodegeneration and cognitive decline, yet the underlying pathophysiologic mechanisms are incompletely understood. This gap in knowledge is in part related to a lack of reliable and efficient methods for measuring cortical lesions in neuroimaging studies. The objective of this study was to develop a semi-automated lesion detection tool and apply it to an investigation of longitudinal changes in brain structure among individuals with chronic TBI. We identified 24 individuals with chronic moderate-to-severe TBI enrolled in the Late Effects of TBI (LETBI) study who had cortical lesions detected by T1-weighted MRI and underwent two MRI scans at least two years apart. Initial MRI scans were performed more than one year post-injury, and follow-up scans were performed 3.1 (IQR=1.7) years later. We leveraged FreeSurfer parcellations of T1-weighted MRI volumes and a recently developed super-resolution technique, SynthSR, to automate the identification of cortical lesions in this longitudinal dataset. Trained raters received the data in a randomized order and manually edited the automated lesion segmentations, yielding a final semi-automated lesion mask for each scan at each time point. Inter-rater variability was assessed in an independent cohort of 10 additional LETBI subjects with cortical lesions. The semi-automated lesion segmentations showed a high level of accuracy compared to “ground truth” lesion segmentations performed via manual segmentation by a separate blinded rater. In a longitudinal analysis of the semi-automated segmentations, lesion volume increased between the two time points with a median volume change of 4.91 (IQR=12.95) mL (p<0.0001). Lesion volume significantly expanded in 40 of 61 measured lesions (65.6%), as defined by a longitudinal volume increase that exceeded inter-rater variability. Longitudinal analyses showed similar changes in lesion volume using the ground-truth lesion segmentations. Inter-scan duration was not associated with the magnitude of lesion growth. Reliable and efficient semi-automated lesion segmentation is feasible in studies of chronic TBI, creating opportunities to elucidate mechanisms of post-traumatic neurodegeneration.
Development and Validation of a Machine Learning Model Integrated with the Clinical Workflow for Inpatient Discharge Date Prediction
Authors: Mahyoub Mohammed A. , Doughetry Kacie , Yadav Ravi , Berio-Dorta Raul , Shukla Ajit 
Published: June 2024

AbstractBackgroundDischarge date prediction plays a crucial role in healthcare management, enabling efficient resource allocation and patient care planning. Accurate estimation of the discharge date can optimize hospital operations and facilitate better patient outcomes.Materials and MethodsIn this study, we employed a systematic approach to develop a discharge date prediction model. We collaborated closely with clinical experts to identify relevant data elements that contribute to the prediction accuracy. Feature engineering was used to extract predictive features from both structured and unstructured data sources. XGBoost, a powerful machine learning algorithm, was employed for the prediction task. Furthermore, the developed model was seamlessly integrated into a widely used Electronic Medical Record (EMR) system, ensuring practical usability.ResultsThe model achieved a performance surpassing baseline estimates by up to 35.68% in the F1-score. Post-deployment, the model demonstrated operational value by aligning with MS GMLOS and contributing to an 18.96% reduction in excess hospital days.ConclusionsOur findings highlight the effectiveness and potential value of the developed discharge date prediction model in clinical practice. By improving the accuracy of discharge date estimations, the model has the potential to enhance healthcare resource management and patient care planning. Additional research endeavors should prioritize the evaluation of the model’s long-term applicability across diverse scenarios and the comprehensive analysis of its influence on patient outcomes.