bluuebunny/crossref_metadata_2025_split huggingface dataset:
Molecular basis of interchain disulfide-bond formation in BMP-9 and BMP-10
Authors: Schwartze Tristin A. , Morosky Stefanie A. , Rosato Teresa L. , Henrickson Amy , Lin Guowu , Hinck Cynthia S. , Taylor Alexander B. , Olsen Shaun K. , Calero Guillermo , Demeler Borries , Roman Beth L. , Hinck Andrew P. 
Published: October 2024

AbstractBMP-9 and BMP-10 are TGF-β family signaling ligands naturally secreted into blood. They act on endothelial cells and are required for proper development and maintenance of the vasculature. In hereditary hemorrhagic telangiectasia, regulation is disrupted due to mutations in the BMP-9/10 pathway, namely in the type I receptor ALK1 or the co-receptor endoglin. It has been demonstrated that BMP-9/10 heterodimers are the most abundant signaling species in the blood, but it is unclear how they form. Unlike other ligands of the TGF-β family, BMP-9 and -10 are secreted as a mixture of monomers and disulfide-linked dimers. Here, we show that the monomers are secreted in a cysteinylated form that crystallizes as a noncovalent dimer. Despite this, monomers do not self-associate at micromolar or lower concentrations and have reduced signaling potency compared to dimers. We further show using protein crystallography that the interchain disulfide of the BMP-9 homodimer adopts a highly strained syn-periplanar conformation. Hence, geometric strain across the interchain disulfide is responsible for the reduced propensity to dimerize, not the cysteinylation. Additionally, we show that the dimerization propensity of BMP-9 is lower than BMP-10 and these propensities can be reversed by swapping residues near the interchain disulfide that form attractive interactions with the opposing monomer. Finally, we discuss the implications of these observations on BMP-9/10 heterodimer formation.
Role of AAA-ATPase Cdc48p in Peroxisomal Quality Control
Authors: Yusuf Ismaila Francis , Girzalsky Wolfgang , Erdmann Ralf 
Published: October 2024

AbstractThe majority of peroxisomal matrix proteins are equipped with a type 1 peroxisomal targeting signal (PTS1), which is recognized in the cytosol by the import receptor Pex5p and targeted to the peroxisomal membrane. After cargo translocation into the peroxisomal lumen, the receptor is monoubiquitinated and recycled to the cytosol in an ATP-dependent manner by the AAA-ATPases Pex1p and Pex6p. Defects in receptor recycling trigger a quality control process by which the receptor is polyubiquitinated, extracted from the membrane and targeted to the proteasome for degradation by the RADAR (Receptor Accumulation and Degradation in the Absence of Recycling)-pathway.Although the RADAR-pathway is conserved among species, it seemed to be missing in baker’s yeast. We present the identification and characterization of the RADAR pathway inS. cerevisiaeand discover that the AAA-ATPases Msp1p and predominantly Cdc48p together with its co-factors Ufd1p/Npl4p are constituents of this pathway. In the RADAR-pathway, Cdc48p cooperates with the heterodimeric Ufd1p/Npl4p cofactor to pull misfolded, polyubiquitinated receptor out of the peroxisomal membrane for its subsequent degradation.
Pep2Vec: An Interpretable Model for Peptide-MHC Presentation Prediction and Contaminant Identification in Ligandome Datasets
Authors: Thrift William John , Broadwell Quade , Perera Jason , Lounsbury Nicolas W. , Chen Jieming , Jhunjhunwala Suchit 
Published: October 2024

AbstractAs personalized cancer vaccines advance, precise modeling of antigen presentation by MHC class I and II is crucial. High-quality training data is essential for clinical models. Existing deep learning models focus on prediction performance but lack interpretability. We introduce Pep2Vec, a modular, transformer-based model trained on MHC I and II ligandome data, transforming input sequences into interpretable vectors. This approach integrates source protein features and elucidates the source of its performance gains, revealing regions that correlate with gene expression and protein-protein interactions. Pep2Vec’s peptide latent space shows relationships between peptides of varying MHC class, allotype, lengths, and submotifs. This enables identifying four major contaminant types, constituting 5.0% of our data. Pep2Vec enhances MHC presentation prediction, achieving higher average precision on our presentation test set and immunogenicity datasets than existing models, and reducing contaminant-like peptide recommendations. Pep2Vec addresses a critical need for the development of more precise and effective applications of peptide MHC models, such as for cancer vaccines and antibody deimmunization.
SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations
Authors: Chen Tony , Zhang Haoyu , Mazumder Rahul , Lin Xihong 
Published: October 2024

AbstractPolygenic risk scores are widely used in disease risk stratification, but their accuracy varies across diverse populations. Recent methods large-scale leverage multi-ancestry data to improve accuracy in under-represented populations but require labelling individuals by ancestry for prediction. This poses challenges for practical use, as clinical practices are typically not based on ancestry. We propose SPLENDID, a novel penalized regression framework for diverse biobank-scale data. Our method utilizes ancestry principal component interactions to model genetic ancestry as a continuum within a single prediction model for all ancestries, eliminating the need for discrete labels. In extensive simulations and analyses of 9 traits from the All of Us Research Program (N=224,364) and UK Biobank (N=340,140), SPLENDID significantly outperformed existing methods in prediction accuracy and model sparsity. By directly incorporating continuous genetic ancestry in model training, SPLENDID stands as a valuable tool for robust risk prediction across diverse populations and fairer clinical implementation.
Transcriptome Enhanced Rice Grain Metabolic Model Identifies Histidine Level as a Marker for Grain Chalkiness
Authors: Chowdhury Niaz Bahar , Chandran Anil Kumar Nalini , Walia Harkamal , Saha Rajib 
Published: October 2024

ABSTRACTRising temperatures due to global warming can negatively impact rice grain quality and yield. This study investigates the effects of increased warmer night temperatures (WNT), a consequence of global warming, on the quality of rice kernel, particularly grain chalkiness. By integrating computational and experimental approaches, we used a rice grain metabolic network to discover the metabolic factors of chalkiness. For this, we reconstructed the rice grain genome-scale metabolic model (GSM), iOSA3474-G and incorporated transcriptomics data from three different times of the day (dawn, dawn 7h, and dusk) for both control and WNT conditions with iOSA3474-G. Three distinct growth phases: anoxia, normoxia, and hyperoxia, were identified in rice kernels from the GSMs, highlighting the grain-filling pattern under varying oxygen levels. We predicted histidine as a marker of normoxia, during which kernel chalkiness occurs. Moreover, we proposed tyrosine as a marker for the hyperoxic growth phase. We also proposed a potential link between monodehydroascorbate reductase, an enzyme with evolutionary significance dating back to the carboniferous era, in regulating the hyperoxic growth phase. Metabolic bottleneck analysis identified nucleoside diphosphate kinase as a central regulator of metabolic flux under different conditions. These findings provide targeted insights into the complex metabolic network governing rice grain chalkiness under WNT conditions. Integration of GSM and transcriptomics data, enhanced our understanding of the intricate relationship between environmental factors, metabolic processes, and grain quality and also offer markers that can be useful to develop rice with improved resilience.
EGFR and tyrosine kinase inhibitor interactions probed by hydrogen-deuterium exchange and mass spectrometry (HDX-MS)
Authors: Ashtekar Kumar D. , Lemmon Mark A. , Tsutsui Yuko 
Published: October 2024

SummaryEGFR is one of the primary drug targets for treating non-small cell lung cancer (NSCLC) patients carrying EGFR oncogenic mutations in the tyrosine kinase domain (TKD). Such patients typically receive tyrosine kinase inhibitors (TKIs) to inhibit aberrant activation of EGFR; however, together with the appearance of the TKI-resistant mutations, TKIs’ severe side effects often limit their clinical usage. To develop TKIs with the wild-type sparing effect, the wild-type structures bound to various TKIs ought to be characterized, though comparisons of such crystal structures do not show clear differences. To characterize subtle EGFR TKD structural changes upon TKI binding that cannot be gleaned from crystal structure comparisons, we employed HDX-MS. We show inhibitor-dependent EGFR dynamics that are displayed even among the TKD bound to chemically similar inhibitors. Such inhibitor-dependent structural changes appear to underlie TKI side effects and the selectivity of covalent inhibitors.HighlightsEGFR shows TKI-dependent dynamics even if TKIs are structurally similar.The stability of the TKI-encounter complexes correlates with their side effects.Covalent TKIs disrupt the binding pocket of wild-type EGFR.The structure of the osimertinib-L858R/T790M complex is extremely rigid.
Mitomycin C Retains Efficacy after Adaptive Laboratory Evolution ofStaphylococcus aureus
Authors: Petersen Maiken Engelbrecht , Khamas Amanda Batoul , Østergaard Lars Jørgen , Jørgensen Nis Pedersen , Meyer Rikke Louise 
Published: October 2024

AbstractAntibiotic resistance is one of the greatest threats against human health and the misuse and overuse of antibiotics is a key factor driving resistance development. During prolonged antibiotic treatment of chronic infections, the antimicrobial pressure facilitates selection of antibiotic resistance mutations. It has been suggested that using antibiotics in combinations may reduce the emergence of resistance. Furthermore, antibiotic tolerant persister cells may be a reservoir for resistance development, so targeting persister cells with anti-persister drugs could also reduce the emergence of resistance.In this study, we conducted a 42-day adaptive laboratory evolution experiment usingStaphylococcus aureusexposed to common antibiotics and the anti-persister drug mitomycin C, either alone or in combination. We monitored susceptibility daily and assessed phenotypic changes in growth and biofilm formation in evolved strains. Whole-genome sequencing revealed mutations linked to antibiotic resistance and phenotypic shifts.Resistance developed rapidly against rifampicin, while ciprofloxacin and daptomycin showed slower resistance emergence. Treatments with vancomycin or mitomycin C resulted in minimal changes in susceptibility. Combination therapies generally delayed resistance, though resistance was not fully prevented. Notably, mitomycin C combined with rifampicin effectively suppressed rifampicin resistance. Sub-inhibitory antibiotic concentrations were associated with both known and novel mutations, including in the nucleotide excision repair system and azoreductase, following mitomycin C treatment—mutations not previously reported.While combination therapy delayed resistance, mitomycin C’s efficacy and ability to prevent rifampicin resistance highlights its potential in combating antibiotic resistance. Further investigation is needed to evaluate the broader application of anti-persister drugs in resistance prevention.
Cis-regulatory mutations co-opting circadian clock regulation underlie naturally selected extreme trait inArabidopsis halleri
Authors: Castanedo Leonardo , Cebula Justyna , Nouet Cécile , Spielmann Julien , Hanikenne Marc , Krämer Ute 
Published: October 2024

AbstractHEAVY METAL ATPase 4(HMA4) is required for the naturally selected traits of zinc/cadmium hyperaccumulation and hypertolerance of inArabidopsis halleri.Cis-regulatory alterations and tandem triplication ofAhHMA4result in substantially elevated transcript levels compared to the closely related non-tolerant non-hyperaccumulatorArabidopsis thaliana. Here we identifycis-regulatory Metal Hyperaccumulation Elements (MHEs) necessary forAhHMA4promoter activity, employing sequence comparisons and motif elicitation analyses combined with progressive deletions and site-directed mutagenesis of promoter-reporter constructs. We report that the promoters of allAhHMA4gene copies share a distal MHE1 (consensus TGTAAC), and a proximal pair of MHE2s identical or highly similar to the Evening Element (AAAATATCT). Evening elements are known binding sites of Arabidopsis CIRCADIAN CLOCK-ASSOCIATED 1 (CCA1), a phytochrome-regulated transcription factor in the core circadian clock. We show that the promoter of eachAhHMA4gene copy, but not ofAtHMA4, mediates enhanced transcript levels of the reporter and their diel rhythmicity. These functional characteristics areCCA1-dependent and recapitulated by a synthetic reporter construct placing the MHE2 pair into theAtHMA4-promoter sequence context, according to the example of theAhHMA4-1promoter. Consistent with our observations in transgenic reporter lines,AhHMA4transcript levels follow a diel rhythm in wild-typeA. halleriplants. Different fromA. halleri, we identify complex repressive functionalities co-localizing with an upstream lncRNA and an intron in the 5’ untranslated region ofA. thaliana HMA4. In summary, our work exemplifies howcis-regulatory mutations contributed to the evolution of extreme physiological traits through the co-option of the circadian clock regulatory network.
Female Specific Restrictive Cardiomyopathy and Metabolic Dysregulation in transgenic mice expressing a Peptide of the Amino-Terminus of GRK2
Authors: Bledzka Kamila M. , Manaserh Iyad H. , Ifft Amanda D. , Rennison Julie H. , Bohacek Madison , Vasiliauskas Katie M. , Grondolsky Jessica , Ampong Isaac , Van Wagoner David R. , Schumacher Sarah M. 
Published: October 2024

AbstractCardiovascular disease and heart failure are a major health challenge, with sex differences in pathophysiology and treatment responses critically influencing patient outcomes. G protein-coupled receptor (GPCR) kinase 2 (GRK2) is a pivotal regulator of cellular signaling whose elevation is a hallmark of heart failure progression. Its complex network of protein interactions impact a wide range of physiological and pathophysiological processes including cardiac function. In this study, we examined the effects of cardiac-restricted expression of an amino-terminal peptide of GRK2 (βARKnt) in female mice subjected to acute and chronic pressure overload. Our findings reveal that that βARKnt affects hypertrophy development and cardiac function differently in female mice than in males, leading to a transition to heart failure not observed in control females or βARKnt males. Notably, the βARKnt female mice exhibited baseline hypertrophy with distinct left atrial morphology, increased fibrosis, and immune cell infiltration compared to the controls, which progressed under chronic stress, indicating adverse cardiac remodeling. Furthermore, βARKnt female mice, unlike males, exhibit impaired tissue respiration following acute pressure overload and altered glucose sensitivity and insulin tolerance, highlighting significant remodeling of cardiac and systemic metabolism.
Evaluating Plant-Microbe Associations in Response to Environmental Stressors to Enhance Salt Marsh Restoration
Authors: Davis Kai A. , McKinney Mary-Margaret S. , Gittman Rachel K. , Peralta Ariane L. 
Published: October 2024

ABSTRACTMicroorganisms can enhance nutrient acquisition or suppress diseases from pathogens, while plants can provide carbon resources and oxygen to root-associated microbes. However, human activities have altered nutrient cycles and disrupted such mutualisms. Therefore, we need to understand how to promote positive plant-microbe associations to aid in restoring coastal wetland ecosystems where human stressors and climate change (e.g., hurricanes, sea-level rise) challenge restoration outcomes. This study examined how salinity stressors influence plant-microbe relationships, where we hypothesize that the presence of microbes will buffer stressor effects. We used a whole sediment inocula approach and exposed marsh cordgrass (Sporobolus alterniflorus) plugs to a replicated factorial experiment with three levels of microbiome addition (microbial inocula, autoclaved microbial inocula, no microbe control) and two levels of salinity (<0.5 psu, 20 psu), replicated ten times. We added microbial inocula from the marsh site with autoclaved soilless media and exposed half the plugs to saltwater (20 psu) and half to freshwater (<0.5 psu). Results revealed that marsh microbial inocula additions during early plant development may ameliorate salinity stressors and could be critical for future restoration efforts. The addition of marsh microbial inocula provided a rescue effect from salinity stress, observed in plant height over time. Aboveground and belowground biomass, bacterial diversity H’, and bacterial evenness J’ were similar across microbial and water treatments; however, water and microbial treatments significantly influenced the bacterial community composition. This work provides evidence that microbiome stewardship buffers against environmental stressors and could promote plant establishment for coastal wetland restoration.
Context-based protein function prediction in bacterial genomes
Authors: Toibazar Daulet , Kulmanov Maxat , Hoehndorf Robert 
Published: October 2024

AbstractMotivationThe rapid growth of sequencing data from high-throughput technologies has emphasized the need to uncover the functions of unannotated genes. Recent advancements in deep learning algorithms have enabled researchers to utilize various features to predict protein functions. Traditionally, these algorithms treat proteins as independent functional units or consider interactions only at the protein level. However, prokaryotes often preserve specific genomic neighborhoods over evolutionary time, providing valuable context for predicting protein functions. This context can arise from genes near the gene of interest or synteny regions, where the conserved order of genes on chromosomes results from common ancestry.ResultsWe developed a transformer-based model to pre-train representations of proteins based on their genomic context, and use this model for predicting protein functions. Our results show that context-based protein representations capture context-specific functional semantics and can effectively predict protein functions. We use our model to investigate the influence of phylogenetic distance and homology on the performance of context-dependent function prediction, and find that synteny affects the prediction performance substantially, except for some functions where the function is determined by the genomic context. Our experiments allow us to gain insights into the factors affecting the performance and applicability of context-based function prediction methods across diverse prokaryotic genomes and meta-genomes.Availability and implementationThe generated model, including all training code and generated data, is freely available athttps://github.com/bio-ontology-research-group/Genomic_context.Contactrobert.hoehndorf@kaust.edu.sa
Aerotolerant methanogens use seaweed and seagrass metabolites to drive marine methane emissions
Authors: Hall N. , Wong W. W. , Lappan R. , Ricci F. , Glud R. N. , Kawaichi S. , Rotaru A-E. , Greening C. , Cook P. L. M. 
Published: October 2024

AbstractMethanogenesis is classically thought to be limited to strictly anoxic environments. While oxygenated oceans are a known methane source, it is argued that methanogenesis is driven by methylphosphonate-degrading bacteria or potentially is associated to zooplankton gut microbiomes rather than by methanogenic archaea. Here we show throughin situmonitoring andex situmanipulations that methane is rapidly produced by archaea in frequently oxygenated sandy sediments. By combining biogeochemical, metagenomic, and culture-based experiments, we show this activity is driven by aerotolerant methylotrophic methanogens (Methanococcoidesspp.) broadly distributed in surface layers of sandy sediments, providing evidence of a hidden process contributing to marine methane emissions. Moreover, we show that methane emissions are driven by methylated seaweed and seagrass metabolites, revealing an unexpected feedback loop between eutrophication-driven algal blooms and greenhouse gas emissions.
Less Haste, More Speed: Does delayed blood culture loading lead to adverse incubation time or yield?
Authors: Deas Gavin , Hamilton Fergus , Williams Philip 
Published: October 2024

AbstractBackgroundBlood culture remains a vital diagnostic tool in the acutely unwell patient. The UK Standards for Microbiology Investigations (SMI) stipulate pre-analytical requirements that are aimed at increasing yield and reducing turnaround time. The requirement to load blood cultures onto incubators within 4 hours has shown to reduce turnaround time but limited evidence exists as to whether it improves yield.MethodsWe extracted blood culture results including organism growth, time to detection (TTD), location and time of sample collection from 4 hospitals in Southwest England. We then used mixed effects, Bayesian linear and logistic regression models to examine the effect of predictor variables like time to loading (TTL) on the response variable of growth or TTD. We used generalised additive models to explore non-linearity.Results449,191 culture sets were analysed, 398,077 of which had enough data to include in the final analysis. 37,255 sets flagged positive (9.36%) of which 21,330 were considered pathogens. Our primary analysis identified a small decrease in yield with each hour delay in loading, OR 0.997 (95% credible interval, CrI 0.994 - 1.001). This effect was largest inStreptococcus pneumoniae, agalactiaeandpyogenes. In our analysis on TTD, culture sets spend 10.98 (95% CrI 7.8 – 13.2) minutes less incubating for each hour delay. There was no convincing non-linearity in either of these effects.ConclusionThere is a marginal loss of growth for every hour a blood culture is left unincubated, with the loss of recovery ofStreptococcus pyogenesand other streptococci most common. There was no evidence of a reduction in Gram-negatives, anaerobes, or yeasts. There was a small decrease in TTD for delayed sets. This analysis suggests there is only marginal benefit in reducing time to load blood cultures on incubators.HighlightsThe UK SMI stipulates blood cultures be loaded within 4 hours of being takenThe effect on yield has not been determined for delayed loadingWe found overall that there was a marginal 0.3% loss of yield per hour delayThere was a significant loss ofStreptococcus pyogenesat 3.2% per hour delay