bluuebunny/crossref_metadata_2025_split huggingface dataset:
Highly fucosylated N-glycans at the synaptic vesicle and neuronal plasma membrane
Authors: Bradberry Mazdak M. , Peters-Clarke Trenton M. , Shishkova Evgenia , Chapman Edwin R. , Coon Joshua J. 
Published: July 2022

ABSTRACTAt neuronal synapses, synaptic vesicles (SVs) require glycoproteins for normal trafficking, and N-linked glycosylation is required for delivery of the major SV glycoproteins synaptophysin and SV2A to SVs. The molecular compositions of SV N-glycans, which may drive important neurobiological processes, are largely unknown. In this study, we combined organelle isolation techniques, fluorescence detection of N-glycans, and high-resolution mass spectrometry to characterize N-glycosylation at synapses and SVs from mouse brain. Detecting over 2,500 unique glycopeptides from over 550 glycoproteins, we found that abundant SV proteins harbor N-glycans with fucose on their complex antennae, and we identify a highly fucosylated N-glycan enriched in SVs as compared to synaptosomes. Antennary fucosylation was also characteristic of plasma membrane proteins and cell adhesion molecules with established roles in synaptic function and development. Our results represent the first defined N-glycoproteome of a neuronal organelle and raise new questions in the glycobiology of synaptic pruning and neuroinflammation.
Rho activation drives luminal collapse and eversion in epithelial acini
Authors: Narayanan Vani , Purkayastha Purboja , Yu Bo , Pendyala Kavya , Chukkapalli Sasanka , Cabe Jolene I , Dickinson Richard B. , Conway Daniel E. , Lele Tanmay P 
Published: July 2022

AbstractEpithelial cells lining a gland and cells grown in a soft extracellular matrix polarize with apical proteins exposed to the lumen and basal proteins in contact with the extracellular matrix. Alterations to polarity, including an apical-out polarity, occur in human cancers. While some aberrant polarity states may result from altered protein trafficking, recent observations of an extraordinary tissue-level inside-out unfolding suggest an alternate pathway for altered polarity. Because mechanical alterations are common in human cancer including an upregulation of RhoA mediated actomyosin tension in acinar epithelia, we explored whether perturbing mechanical homeostasis could cause apical-out eversion. Acinar eversion was robustly induced by direct activation of RhoA in normal and tumor epithelial acini, or indirect activation of RhoA through blockage of β1 integrins, disruption of the LINC complex, oncogenic Ras activation, or Rac1 inhibition. Furthermore, laser ablation of a portion of the untreated acinus was sufficient to induce eversion. Analyses of acini revealed high curvature and low phosphorylated myosin in the apical cell surfaces relative to the basal surfaces. A vertex-based mathematical model which balances tension at cell-cell interfaces revealed a five-fold greater basal cell surface tension relative to the apical cell surface tension. The model suggests that the difference in surface energy between the apical and basal surfaces is the driving force for acinar eversion. Our findings raise the possibility that a loss of mechanical homeostasis may cause apical-out polarity states in human cancers.
DeepBend: An Interpretable Model of DNA Bendability
Authors: Khan Samin Rahman , Sakib Sadman , Rahman M. Sohel , Samee Md. Abul Hassan 
Published: July 2022

AbstractThe bendability of genomic DNA impacts chromatin packaging and protein-DNA binding. However, beyond a handful of known sequence motifs, such as certain dinucleotides and poly(A)/poly(T) sequences, we do not have a comprehensive understanding of the motifs influencing DNA bendability. Recent high-throughput technologies like Loop-Seq offer an opportunity to address this gap but the lack of accurate and interpretable machine learning models still poses a significant challenge. Here we introduce DeepBend, a convolutional neural network model built as a visible neural network where we designed the convolutions to directly capture the motifs underlying DNA bendability and how their periodic occurrences or relative arrangements modulate bendability. Through extensive benchmarking on Loop-Seq data, we show that DeepBend consistently performs on par with alternative machine learning and deep learning models while giving an extra edge through mechanistic interpretations. Besides confirming the known motifs of DNA bendability, DeepBend also revealed several novel motifs and showed how the spatial patterns of motif occurrences influence bendability. DeepBend’s genome-wide prediction of bendability further showed how bendability is linked to chromatin conformation and revealed the motifs controlling bendability of topologically associated domains and their boundaries.
Nucleoside-modified mRNA-based influenza vaccines circumvent problems associated with H3N2 vaccine strain egg-adaptation
Authors: Gouma Sigrid , Parkhouse Kaela , Weirick Madison , Muramatsu Hiromi , Pardi Norbert , Fan Steven H.Y. , Weissman Drew , Hensley Scott E. 
Published: July 2022

ABSTRACTMost human influenza vaccine antigens are produced in fertilized chicken eggs. Recent H3N2 egg-based vaccine antigens have limited effectiveness, partially due to egg-adaptive substitutions that alter the antigenicity of the hemagglutinin (HA) protein. The nucleoside-modified messenger RNA encapsulated in lipid nanoparticle (mRNA-LNP) vaccine platform is a promising alternative for egg-based influenza vaccines because mRNA-LNP-derived antigens are not subject to adaptive pressures that arise during the production of antigens in chicken eggs. Here, we compared H3N2-specific antibody responses in mice vaccinated with either 3c.2A H3-encoded mRNA-LNP or a conventional egg-based Fluzone vaccine (which included an egg-adapted 3c.2A antigen) supplemented with an MF59-like adjuvant. We tested mRNA-LNP encoding wild-type and egg-adapted 3c.2A H3 antigens. We found that mRNA-LNP encoding wild-type 3c.2A H3 elicited antibodies that neutralized the wild-type 3c.2A H3N2 virus more effectively relative to antibodies elicited by mRNA-LNP encoding egg-adapted 3c2.A H3 or the egg-based Fluzone vaccine. mRNA-LNP expressing either wild-type or egg-adapted 3c2.A H3 protected mice against infection with the wild-type 3c2.A H3N2, whereas the egg-based Fluzone vaccine did not. We found that both mRNA-LNP vaccines elicited high levels of group 2 HA stalk-reactive antibodies that likely contributed to protection in vivo. Our studies indicate that nucleoside-modified mRNA-LNP-based vaccines can circumvent problems associated with egg-adaptations with recent 3c2.A H3N2 viruses.SummaryThis study shows that the nucleoside-modified messenger RNA encapsulated in lipid nanoparticle (mRNA-LNP) vaccine platform is a promising alternative for egg-based influenza vaccines. We show that mRNA-LNP expressing H3 antigens elicit high levels of antibodies in mice and protect against H3N2 influenza virus infection.
The associations of chronotype and shift work with rheumatoid arthritis
Authors: Butler TD , Maidstone RJ , Rutter MK , McLaughlin J , Ray DW , Gibbs JE 
Published: July 2022

ABSTRACTIntroductionThe circadian clock regulates multiple aspects of human physiology including immunity. People have a circadian preference termed chronotype. Those with an evening preference may be better suited to shift work, but also carry higher risk of adverse health. Shift work leads to misalignment of circadian rhythms and is associated with increased risk of inflammatory disease such as asthma and cancer. Here, we investigate the association between chronotype, shift work and rheumatoid arthritis (RA).MethodsThe associations between exposures of shift work and chronotype on risk of RA were studied in up to 444,210 UK Biobank participants. Multivariate logistic regression models were adjusted for covariates including age, sex, alcohol intake, smoking history and BMI.ResultsAfter adjusting for covariates, individuals with a morning chronotype had lower odds of having RA (OR 0.93, 95% CI 0.88 to 0.99) when compared to intermediate chronotypes. The association between morning chronotype and lower odds of RA persisted with a more stringent RA case definition (Covariate-adjusted OR 0.89, 95% CI 0.81 to 0.97). Shift workers had a higher odds of RA (OR 1.22, 95% CI 1.1 – 1.36), that attenuated to the null after covariate adjustment.ConclusionsThese data implicate circadian rhythms in RA pathogenesis. Further studies are required to determine the mechanisms underlying this association and understand the potential impact of shift work on chronic inflammatory disease and its mediating factors.KEY MESSAGESWhat is already known about this subject?Chronotype impacts a person’s ability to adapt to shift work, which contributes to circadian misalignment and is associated with adverse health outcomes including asthma, diabetes and cancerWhat does this study add?People with morning chronotype have a lower likelihood of RA, compared to intermediate chronotypesShift workers have higher likelihood of RA, compared to day workers, but this relationship may be mediated or confounded by factors such as smoking and BMIHow might this impact on clinical practice or future developments?Chronotype is easy to assess and could be combined with other factors to determine an individual’s risk of developing RA and influence decisions about undertaking shift workGrowing evidence that common chronic inflammatory disorders are affected by circadian misalignment generates further need to investigate the impact of chronotype and shift work on immune function
Racial Disparities in Hesitancy and Utilization of Monoclonal Antibody Infusion Treatment of COVID-19
Authors: Shaikh Yahya , Gupta Ishaan , Purekal Sophia , Vaeth Mary Jane E. , Foyez Maisha , Callahan Charles D. , Elhabashy Maryam , Ficke James R. , Wu Albert W. , Auwaerter Paul G. , Kantsiper Melinda E. , Siddiqui Zishan K. 
Published: July 2022

AbstractBackground and MethodsWe conducted a single center cross-sectional study to investigate racial disparities in the hesitancy and utilization of monoclonal antibody (mAb) treatment of COVID-19 among treatment eligible patients who were referred to the infusion center between January 4, 2021 and May 14, 2021.ResultsAmong the 2,406 eligible participants, African Americans were significantly more likely to underutilize mAb treatment (OR 1.8; 95% CI 1.5-2.1) and miss treatment opportunities due to monoclonal hesitancy (OR 1.7, 95% CI 1.3-2.1).ConclusionAddressing racial disparities in mAb delivery is an opportunity to bridge the racial inequities in COVID-19 care.
Ecological models predict narrow potential distribution for Trioza erytreae, vector of the citrus greening disease
Authors: Godefroid Martin 
Published: July 2022

AbstractThe African citrus psyllid, Trioza erytreae (Hemiptera: Triozidae), is a vector of citrus greening disease (Huanglonbing - HLB) caused by the bacterium Candidatus liberibacter. Native from Africa, T. erytreae was detected in northwestern Spain in 2014, and since then it has established along Atlantic coastal areas of the Iberian Peninsula. Given the severe bio-economic impact of HLB, an accurate assessment of the risk of potential spread of African citrus psyllid to citrus-growing regions of the Mediterranean area and the rest of the world, is urgently needed to design effective control strategies and anticipate economic losses. Therefore, I calibrated species distribution models to understand the bioclimatic characteristics that shape the distribution of T. erytreae and to assess the climatic suitability of the world’s major citrus-growing regions for this species under current and future climate conditions. The models identify mild summer and winter temperatures and high levels of precipitation as optimal conditions for long-term psyllid establishment. It is noteworthy that the models trained without the available occurrences in continental Europe, predict only the Atlantic coastal regions of the Iberian Peninsula as highly climatically suitable in Europe, which corresponds perfectly with the area currently invaded by the psyllid. This striking predictive accuracy lends great credibility to the model predictions. Most economically important citrus production areas in the world are predicted to be of low or moderate climatic suitability for T. erytreae. This research is crucial for assessing the global risk of HLB and is particularly timely for Europe where the African citrus psyllid has recently been detected.
svCapture: Efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing
Authors: Wilson Thomas E. , Ahmed Samreen , Higgins Jake , Salk Jesse J. , Glover Thomas W. 
Published: July 2022

ABSTRACTError-corrected sequencing of genomic targets enriched by probe-based capture has become a standard approach for detecting single-nucleotide variants (SNVs) and small insertion/deletions (indels) present at very low variant allele frequencies. Less attention has been given to strategies for comparable detection of rare structural variant (SV) junctions, where different error mechanisms must be addressed. Working from cell samples with known SV properties, we demonstrate that Duplex Sequencing (DuplexSeq), which demands confirmation of variants on both strands of a source DNA molecule, eliminates false SV junctions arising from chimeric PCR. DuplexSeq could not address frequent intermolecular ligation artifacts that arise during Y-adapter addition prior to strand denaturation without requiring multiple source molecules. In contrast, tagmentation libraries coupled with data filtering based on strand family size greatly reduced both artifact classes and enabled efficient and specific detection of even single-molecule SV junctions. The throughput of SV capture sequencing (svCapture) and the high base-level accuracy of DuplexSeq provided detailed views of the microhomology profile and limited occurrence of de novo SNVs near the junctions of hundreds of sub-clonal and newly created SVs, suggesting end joining as a predominant formation mechanism. The open source svCapture pipeline enables rare SV detection as a routine addition to SNVs/indels in properly prepared capture sequencing libraries.
Drivers of polar bear behavior, and the possible effects of prey availability on foraging strategy
Authors: Togunov Ron R. , Derocher Andrew E. , Lunn Nicholas J. , Auger-Méthé Marie 
Published: July 2022

1AbstractChange in behavior is one of the earliest measurable responses to variation in habitat suitability, making the study of factors that promote behaviors particularly important in areas undergoing environmental change. We applied hidden Markov models to movement data of 14 polar bears, Ursus maritimus, from Western Hudson Bay, Canada between 2011 and 2021 during the foraging season (January–June) when bears inhabit the sea ice. The model incorporated bear movement and orientation relative to wind to classify three behaviors (stationary/drifting, area-restricted search, and olfactory search), and investigated 11 factors to identify conditions that may promote these behaviors. In contrast to other polar bear populations, we found high levels of evening activity, with active behaviors peaking around 20:00. We identified an increase in activity as the ice-covered season progressed. This apparent shift in foraging strategy from still-hunting to active search corresponds to a shift in prey availability (i.e., increase in haul-out behavior during winter to the spring pupping and molting seasons). Last, we described spatial patterns of distribution with respect to season and ice concentration that may be indicative of variation in habitat quality and segregation by bear age that may reflect competitive exclusion. Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings compared to other populations could be explained by variation in regional or temporal variation in resource abundance or distribution. Our findings and novel methodology can help identify periods, locations, and environmental conditions representing critical habitat.
Deep proteomic analysis of microglia reveals fundamental biological differences between model systems
Authors: Lloyd Amy F , Martinez-Muriana Anna , Davis Emma , Daniels Michael JD , Hou Pengfei , Mancuso Renzo , Brenes Alejandro J , Geric Ivana , Snellinx An , Craessaerts Katleen , Theys Tom , Fiers Mark , De Strooper Bart , Howden Andrew JM 
Published: July 2022

AbstractUsing high resolution quantitative mass spectrometry, we have generated the most comprehensive human and mouse microglia proteomic datasets to date, consisting of over 11,000 proteins across all six microglia groups. Microglia from different sources share a core protein signature of over 5600 proteins, yet fundamental differences are observed between species and culture conditions, indicating limitations for human disease modelling in mouse or inin vitrocultures of microglia. Mouseex vivomicroglia show important differences at the proteome level such as differential expression of inflammation and Alzheimer’s Disease associated proteins. We identify a tenfold difference in the protein content ofex vivoandin vitrocells and significant proteome differences associated with protein synthesis, metabolism, microglia marker expression and environmental sensors. Culturing microglia induces rapidly increased growth, protein content and inflammatory protein expression. These changes can be restored by engraftingin vitrocells into the brain, with xenografted hESC-derived microglia closely resembling microglia from human brain. This data provides an important resource for the field and highlights important considerations needed when using model systems to study human physiology and pathology of microglia.
Uncovering gene-family founder events during major evolutionary transitions in animals, plants and fungi using GenEra
Authors: Barrera-Redondo Josué , Lotharukpong Jaruwatana Sodai , Drost Hajk-Georg , Coelho Susana M. 
Published: July 2022

AbstractThe emergence of new genes is an important driver of evolutionary novelty. Yet, we lack a conceptual and computational approach that accurately traces gene-family founder events and effectively associates them with trait innovation and major radiation events. Here, we present GenEra, a DIAMOND-fuelled gene-family founder inference framework that addresses previously raised limitations and biases of founder gene detection in genomic phylostratigraphy by accounting for homology detection failure (HDF). We demonstrate how GenEra can accelerate gene-family founder computations from several months to a few days for any query genome of interest. We analyzed 30 genomes to explore the emergence of new gene families during the major evolutionary transitions in plants, animals and fungi. The detection of highly conserved protein domains in these gene families indicates that neofunctionalization of preexisting protein domains is a richer source of gene-family founder events compared withde novogene birth. We report vastly different patterns of gene-family founder events in animal and fungi before and after accounting for HDF. Only plants exhibit a consistent pattern of founder gene emergence after accounting for HDF, suggesting they are more likely to evolve novelty through the emergence of new genes compared to opisthokonts. Finally, we show that gene-family founder bursts are associated with the transition to multicellularity in streptophytes, the terrestrialization of land plants and the origin of angiosperms, as well as with the evolution of bilateral symmetry in animals.
Annexin A2 modulates phospholipid membrane composition upstream of Arp2 to control angiogenic sprout initiation
Authors: Sveeggen Timothy M. , Abbey Colette A. , Smith Rebecca L. , Bayless Kayla J. 
Published: July 2022

AbstractThe intersection of protein and lipid biology is of growing importance for understanding how cells address structural challenges during adhesion and migration. While protein complexes engaged with the cytoskeleton play a vital role, support from the phospholipid membrane is crucial for directing localization and assembly of key protein complexes. During angiogenesis, it is well observed that dramatic cellular remodeling is necessary for endothelial cells to shift from a stable monolayer to invasive structures. However, the molecular dynamics between lipids and proteins during endothelial invasion are not defined. Here, we utilized cell culture, immunofluorescence, and lipidomic analyses to identify a novel role for the membrane binding protein Annexin A2 (ANXA2) in modulating the composition of specific membrane lipids necessary for cortical F-actin organization and adherens junction stabilization. In the absence of ANXA2, there is disorganized cortical F-actin, reduced junctional Arp2, excess sprout initiation, and ultimately failed sprout maturation. Further, we observed reduced filipin III labeling of membrane cholesterol in cells with reduced ANXA2, suggesting there is an alteration in phospholipid membrane dynamics. Lipidomic analyses reveal that 42 lipid species are altered with loss of ANXA2, including an accumulation of phosphatidylcholine (16:0_16:0). We find that supplementation of phosphatidylcholine (16:0_16:0) in wild-type endothelial cells mimics the ANXA2 knock-down phenotype, indicating that ANXA2 regulates the phospholipid membrane upstream of Arp2 recruitment and organization of cortical F-actin. Altogether these data indicate a novel role for ANXA2, and show that proper lipid modulation is a critical component of endothelial sprouting.Summary StatementAnnexin A2 modulates composition of select phospholipid species in endothelial cells needed for F-actin organization and Arp2 recruitment to endothelial adherens junctions. These events simultaneously temper sprout initiation and support sprout maturation to maintain the integrity of sprouting structures during angiogenesis
Multimodal Prediction of Breast Cancer Recurrence Assays and Risk of Recurrence
Authors: Howard Frederick M. , Dolezal James , Kochanny Sara , Khramtsova Galina , Vickery Jasmine , Srisuwananukorn Andrew , Woodard Anna , Chen Nan , Nanda Rita , Perou Charles M. , Olopade Olufunmilayo I. , Huo Dezheng , Pearson Alexander T. 
Published: July 2022

AbstractGene expression-based recurrence assays are strongly recommended to guide the use of chemotherapy in hormone receptor-positive, HER2-negative breast cancer, but such testing is expensive, can contribute to delays in care, and may not be available in low-resource settings. Here, we describe the training and independent validation of a deep learning model that predicts recurrence assay result and risk of recurrence using both digital histology and clinical risk factors. We demonstrate that this approach outperforms an established clinical nomogram (area under the receiver operating characteristic curve of 0.833 versus 0.765 in an external validation cohort, p = 0.003), and can identify a subset of patients with excellent prognoses who may not need further genomic testing.