bluuebunny/crossref_metadata_2025_split huggingface dataset:
CD4+T cell lymphopenia and dysfunction in severe COVID-19 disease is autocrine TNF-α/TNFRI-dependent
Authors: Popescu Iulia , Snyder Mark E. , Iasella Carlo J. , Hannan Stefanie J. , Koshy Ritchie , Burke Robin , Das Antu , Brown Mark J. , Lyons Emily J. , Lieber Sophia C. , Chen Xiaoping , Sembrat John C. , An Xiaojing , Linstrum Kelsey , Kitsios Georgios , Konstantinidis Ioannis , Saul Melissa , Kass Daniel J. , Alder Jonathan K. , Chen Bill B. , Lendermon Elizabeth A. , Kilaru Silpa , Johnson Bruce , Morrell Matthew R. , Pilewski Joseph M. , Kiss Joseph E. , Wells Alan H. , Morris Alison , McVerry Bryan J. , McMahon Deborah K. , Triulzi Darrell J. , Chen Kong , Sanchez Pablo G. , McDyer John F. 
Published: June 2021

AbstractLymphopenia is common in severe COVID-19 disease, yet the mechanisms are poorly understood. In 148 patients with severe COVID-19, we found lymphopenia was associated with worse survival. CD4+lymphopenia predominated, with lower CD4+/CD8+ratios in severe COVID-19 compared to recovered, mild disease (p<0.0001). In severe disease, immunodominant CD4+T cell responses to Spike-1(S1) produced increasedin vitroTNF-α, but impaired proliferation and increased susceptibility to activation-induced cell death (AICD). CD4+TNF-α+T cell responses inversely correlated with absolute CD4+counts from severe COVID-19 patients (n=76; R=-0.744, P<0.0001). TNF-α blockade including infliximab or anti-TNFRI antibodies strikingly rescued S1-specific CD4+proliferation and abrogated S1-AICD in severe COVID-19 patients (P<0.001). Single-cell RNAseq demonstrated downregulation of Type-1 cytokines and NFκB signaling in S1-stimulated CD4+cells with infliximab treatment. Lung CD4+T cells in severe COVID-19 were reduced and produced higher TNF-α versus PBMC. Together, our findings show COVID-19-associated CD4+lymphopenia and dysfunction is autocrine TNF-α/TNFRI-dependent and therapies targeting TNF-α may be beneficial in severe COVID-19.One Sentence SummaryAutocrine TNF-α/TNFRI regulates CD4+T cell lymphopenia and dysfunction in severe COVID-19 disease.
Single cell clonal analysis identifies an AID-dependent pathway of plasma cell differentiation
Authors: Gómez-Escolar Carmen , Serrano-Navarro Alvaro , Benguria Alberto , Dopazo Ana , Sánchez-Cabo Fátima , Ramiro Almudena R 
Published: June 2021

ABSTRACTGerminal centers (GC) are microstructures where B cells that have been activated by antigen can improve the affinity of their B cell receptors and differentiate into memory B cells (MBCs) or antibody secreting plasma cells. Activation Induced Deaminase (AID) initiates antibody diversification in GCs by somatic hypermutation and class switch recombination. Here we have addressed the role of AID in the terminal differentiation of GC B cells by combining single cell transcriptome and immunoglobulin clonal analysis in a mouse model that traces AID-experienced cells. We identified 8 transcriptional clusters that include dark zone and light zone GC subsets, plasmablasts/plasma cells (PB), 4 subsets of MBCs and a novel prePB subset, which shares the strongest clonal relationships with PBs. Mice lacking AID have various alterations in the size and expression profiles of these transcriptional clusters. We find that AID deficiency leads to a reduced proportion of prePB cells and severely impairs transitions between the prePB and the PB subsets. Thus, AID shapes the differentiation fate of GC B cells by enabling PB generation from a prePB state.
The Foundational data initiative for Parkinson’s disease (FOUNDIN-PD): enabling efficient translation from genetic maps to mechanism
Authors: Bressan Elisangela , Reed Xylena , Bansal Vikas , Hutchins Elizabeth , Cobb Melanie M. , Webb Michelle G , Alsop Eric , Grenn Francis P. , Illarionova Anastasia , Savytska Natalia , Violich Ivo , Broeer Stefanie , Fernandes Noémia , Sivakumar Ramiyapriya , Beilina Alexandra , Billingsley Kimberley , Berghausen Joos , Pantazis Caroline B. , Pitz Vanessa , Patel Dhairya , Daida Kensuke , Meechoovet Bessie , Reiman Rebecca , Courtright-Lim Amanda , Logemann Amber , Antone Jerry , Barch Mariya , Kitchen Robert , Li Yan , Dalgard Clifton L. ,   The American Genome Center, Rizzu Patrizia , Hernandez Dena G , Hjelm Brooke E. , Nalls Mike , Gibbs J. Raphael , Finkbeiner Steven , Cookson Mark R , Van Keuren-Jensen Kendall , Craig David W , Singleton Andrew B , Heutink Peter , Blauwendraat Cornelis 
Published: June 2021

AbstractThe FOUNdational Data INitiative for Parkinson’s Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinson’s disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinson’s Progression Markers Initiative study including participants with PD carrying monogenic PD (SNCA) variants, variants with intermediate effects and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modelling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser (https://www.foundinpd.org) as a resource for understanding the molecular pathogenesis of PD.
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models
Authors: Jensen Kristopher T. , Kao Ta-Chu , Stone Jasmine T. , Hennequin Guillaume 
Published: June 2021

AbstractLatent variable models are ubiquitous in the exploratory analysis of neural population recordings, where they allow researchers to summarize the activity of large populations of neurons in lower dimensional ‘latent’ spaces. Existing methods can generally be categorized into (i) Bayesian methods that facilitate flexible incorporation of prior knowledge and uncertainty estimation, but which typically do not scale to large datasets; and (ii) highly parameterized methods without explicit priors that scale better but often struggle in the low-data regime. Here, we bridge this gap by developing a fully Bayesian yet scalable version of Gaussian process factor analysis (bGPFA), which models neural data as arising from a set of inferred latent processes with a prior that encourages smoothness over time. Additionally, bGPFA uses automatic relevance determination to infer the dimensionality of neural activity directly from the training data during optimization. To enable the analysis of continuous recordings without trial structure, we introduce a novel variational inference strategy that scales near-linearly in time and also allows for non-Gaussian noise models appropriate for electrophysiological recordings. We apply bGPFA to continuous recordings spanning 30 minutes with over 14 million data points from primate motor and somatosensory cortices during a self-paced reaching task. We show that neural activity progresses from an initial state at target onset to a reach-specific preparatory state well before movement onset. The distance between these initial and preparatory latent states is predictive of reaction times across reaches, suggesting that such preparatory dynamics have behavioral relevance despite the lack of externally imposed delay periods. Additionally, bGPFA discovers latent processes that evolve over slow timescales on the order of several seconds and contain complementary information about reaction time. These timescales are longer than those revealed by methods which focus on individual movement epochs and may reflect fluctuations in e.g. task engagement.
Novel temporal and spatial patterns of metastatic colonization from rapid-autopsy tumor biopsies
Authors: Huang Xiaomeng , Qiao Yi , Brady Samuel W. , Factor Rachel E. , Downs-Kelly Erinn , Farrell Andrew , McQuerry Jasmine A. , Shrestha Gajendra , Jenkins David , Johnson W. Evan , Cohen Adam L. , Bild Andrea H. , Marth Gabor T. 
Published: June 2021

AbstractBackgroundMetastatic breast cancer is a deadly disease with a low 5-year survival rate. Tracking metastatic spread in living patients is difficult, and thus poorly understood.ResultsVia rapid autopsy, we have collected 30 tumor samples over 3 timepoints and across 8 organs from a triple-negative metastatic breast cancer patient. The large number of sites sampled, together with deep whole genome sequencing and advanced computational analysis, allowed us to comprehensively reconstruct the tumor’s evolution at subclonal resolution. The most unique, previously not reported aspect of the tumor’s evolution we observed in this patient was the presence of “subclone incubators”, i.e. already metastatic sites where substantial tumor evolution occurred before colonization of additional sites and organs by subclones that evolved at the incubator site. Overall, we identified four discrete waves of metastatic expansions, each of which resulted in a number of new, genetically similar metastasis sites that also enriched for particular organs (e.g. abdominal vs bone and brain). The lung played a critical role in facilitating metastatic spread in this patient: the lung was the first site of metastatic escape from the primary breast lesion; subclones at this site were the source of all four subsequent metastatic waves; and multiple sites in the lung acted as subclone incubators. Finally, functional annotation revealed that many known driver or metastasis-promoting tumor mutations in this patient were shared by some, but not all metastatic sites, highlighting the need for more comprehensive surveys of a patient’s metastases for effective clinical intervention.ConclusionsOur analysis revealed the presence of substantial tumor evolution at metastatic incubator sites, with potentially important clinical implications. Our study demonstrated that sampling of a large number of metastatic sites affords unprecedented detail for studying metastatic evolution.
Bifidobacterium castoris strains isolated from wild mice show evidence of frequent host switching and diverse carbohydrate metabolism potential
Authors: Kujawska Magdalena , Raulo Aura , Baltrūnaitė Laima , Knowles Sarah CL , Hall Lindsay J 
Published: June 2021

AbstractMembers of the gut microbiota genus Bifidobacterium are widely distributed human and animal symbionts believed to exert beneficial effects on their hosts. However, in-depth genomic analyses of animal-associated species and strains are somewhat lacking, particularly in wild animal populations. Here, to examine patterns of host specificity and carbohydrate metabolism capacity, we sequenced whole genomes of Bifidobacterium isolated from wild-caught small mammals from two European countries (UK and Lithuania). Members of B. castoris, B. animalis and B. pseudolongum were detected in wild mice (Apodemus sylvaticus, A. agrarius and A. flavicollis), but not voles or shrews. B. castoris constituted the most commonly recovered Bifidobacterium (78% of all isolates), with the majority of strains only detected in a single population, although populations frequently harboured multiple co-circulating strains. Phylogenetic analysis revealed that the mouse-associated B. castoris clades were not specific to a particular location or host species, and their distribution across the host phylogeny was consistent with regular host shifts rather than host-microbe codiversification. Functional analysis suggested that mouse-derived B. castoris strains encoded an extensive arsenal of carbohydrate-active enzymes, including putative novel glycosyl hydrolases such as chitosanases that may act on chitin-derived substrates such as mushrooms or insects, along with genes encoding putative exopolysaccharides, some of which may have been acquired via horizontal gene transfer. Overall, these results provide a rare genome-level analysis of host specificity and genomic capacity among important gut symbionts of wild animals, and reveal that Bifidobacterium has a labile relationship with its host over evolutionary time scale.
Deep Learning Approach to Genomic Breakage Study from Primary Sequence
Authors: Kim Pora , Tan Hua , Liu Jiajia , Yang Mengyuan , Zhou Xiaobo 
Published: June 2021

SUMMARYIdentifying the molecular mechanisms related to genomic breakage is an important goal of cancer mechanism studies. Among the diverse location of the breakpoints of structural variants, the fusion genes, which have the breakpoints in the gene bodies and typically identified from RNA-seq data, can provide a highlighted structural variant resource for studying the genomic breakages with expression and potential pathogenic impacts. In this study, we developed FusionAI which utilizes deep learning to predict gene fusion breakpoints based on primary sequences and let us identify fusion breakage code and genomic context. FusionAI leverages the known fusion breakpoints to provide a prediction model of the fusion genes from the primary genomic sequences via deep learning, thereby helping researchers a more accurate selection of fusion genes and better understand genomic breakage.HighlightsFusionAI, a 9-layer deep neural network, predicts fusion gene breakpoints from a DNA sequenceFusonAI reduce the cost and effort for validating fusion genes by decreasing specificityHigh feature importance scored regions were apart 100nt on average from the exon junction breakpointsHigh feature importance scored regions overlapped with 44 different human genomic featuresTranscription factor fusion genes are targeted by the GC-rich motif TFsFusionAI gives less scores to the non-disease derived breakpoints
Adult fibroblasts retain organ-specific transcriptomic identity
Authors: Forte Elvira , Ramialison Mirana , Nim Hieu T. , Mara Madison , Cohn Rachel , Daigle Sandra L. , Boyd Sarah , Hinson J. Travis , Costa Mauro W. , Rosenthal Nadia A. , Furtado Milena B. 
Published: June 2021

AbstractOrgan fibroblasts are essential components of homeostatic and diseased tissues. They participate in sculpting the extracellular matrix, sensing the microenvironment and communicating with other resident cells. Recent studies have revealed transcriptomic heterogeneity among fibroblasts within and between organs. To dissect the basis of inter-organ heterogeneity, we compare the gene expression of fibroblasts from different tissues (tail, skin, lung, liver, heart, kidney, gonads) and show that they display distinct positional and organ-specific transcriptome signatures that reflect their embryonic origins. We demonstrate that fibroblasts’ expression of genes typically attributed to the surrounding parenchyma is established in embryonic development and largely maintained in culture, bioengineered tissues, and ectopic transplants. Targeted knockdown of key organ-specific transcription factors affects fibroblasts functions, with modulation of genes related to fibrosis and inflammation. Our data open novel opportunities for the treatment of fibrotic diseases in a more precise, organ-specific manner.
Molecular mechanism of quorum sensing inhibition in Streptococcus by the phage protein paratox
Authors: Rutbeek Nicole R. , Rezasoltani Hanieh , Patel Trushar R. , Khajehpour Mazdak , Prehna Gerd 
Published: June 2021

ABSTRACTStreptococcus pyogenes, or Group A Streptococcus, is a Gram-positive bacterium that can be both a human commensal and pathogen. Central to this dichotomy are temperate bacteriophages that incorporate into the bacterial genome as a prophage. These genetic elements encode both the phage proteins as well as toxins harmful to the human host. One such conserved phage protein paratox (Prx) is always found encoded adjacent to the toxin genes and this linkage is preserved during transduction. Within Streptococcus pyogenes, Prx functions to inhibit the quorum-sensing ComRS receptor-signal pair that is the master regulator of natural competence, or the ability to uptake endogenous DNA. Specifically, Prx directly binds and inhibits the receptor ComR by unknown mechanism. To understand how Prx inhibits ComR at the molecular level we pursued an X-ray crystal structure of Prx bound to ComR. The structural data supported by solution X-ray scattering data demonstrate that Prx induces a conformational change in ComR to directly access the DNA binding domain. Furthermore, electromobility shift assays and competition binding assays reveal that Prx effectively uncouples the inter-domain conformational change that is required for activation of ComR by the signaling molecule XIP. Although to our knowledge the molecular mechanism of quorum-sensing inhibition by Prx is unique, it is analogous to the mechanism employed by the phage protein Aqs1 in Pseudomonas aeruginosa. Together, this demonstrates an example of convergent evolution between Gram-positive and Gram-negative phages to inhibit quorum-sensing, and highlights the versatility of small phage proteins.
Reverse-Complement Equivariant Networks for DNA Sequences
Authors: Mallet Vincent , Vert Jean-Philippe 
Published: June 2021

AbstractAs DNA sequencing technologies keep improving in scale and cost, there is a growing need to develop machine learning models to analyze DNA sequences, e.g., to decipher regulatory signals from DNA fragments bound by a particular protein of interest. As a double helix made of two complementary strands, a DNA fragment can be sequenced as two equivalent, so-called Reverse Complement (RC) sequences of nucleotides. To take into account this inherent symmetry of the data in machine learning models can facilitate learning. In this sense, several authors have recently proposed particular RC-equivariant convolutional neural networks (CNNs). However, it remains unknown whether other RC-equivariant architectures exist, which could potentially increase the set of basic models adapted to DNA sequences for practitioners. Here, we close this gap by characterizing the set of all linear RC-equivariant layers, and show in particular that new architectures exist beyond the ones already explored. We further discuss RC-equivariant pointwise nonlinearities adapted to different architectures, as well as RC-equivariant embeddings of k-mers as an alternative to one-hot encoding of nucleotides. We show experimentally that the new architectures can outperform existing ones.
Nitrogen fixation in mesoscale eddies of the North Pacific Subtropical Gyre: patterns and mechanisms
Authors: Dugenne Mathilde , Gradoville Mary R. , Church Matthew J. , Barone Benedetto , Wilson Samuel T. , Sheyn Uri , Harke Matthew J. , Björkman Karin M. , Hawco Nicholas J. , Hynes Annette M. , Ribalet François , Karl David M. , Delong Edward F. , Dyhrman Sonya T. , Armbrust E. Virginia , John Seth , Eppley John M. , Harding Katie , Stewart Brittany , Cabello Ana M. , Turk-Kubo Kendra A. , Caffin Mathieu , White Angelicque E. , Zehr Jonathan P. 
Published: June 2021

1.AbstractMesoscale eddies have been shown to support elevated dinitrogen (N2) fixation rates (NFRs) and abundances of N2-fixing microorganisms (diazotrophs), but the mechanisms underlying these observations are not well understood. We explored relationships among NFRs and cyanobacterial diazotroph abundances in eddy pairs of opposite polarity sampled in the North Pacific Subtropical Gyre and compared our observations to seasonal trends from the Hawaii Ocean Time-series (HOT) program. Consistent with previous reports, we found that NFRs were anomalously high for this region (up to 3.7-fold above previous monthly HOT observations) in the centers of the sampled anticyclones, coinciding with elevated abundances ofCrocosphaerain the summertime. We then coupled our field-based observations, together with transcriptomic analyses of nutrient stress marker genes and ecological models, to evaluate potential mechanisms controlling diazotroph abundance and activity at the mesoscale. Specifically, we evaluated the role of biological (via estimates of growth and grazing rates) and physical controls on populations ofCrocosphaera,Trichodesmium,and diatom symbionts. Our results suggest that increasedCrocosphaeraabundances associated with summertime anticyclones resulted from the alleviation of phosphate limitation, allowing cells to grow at rates exceeding grazing losses. In contrast, distributions of larger, buoyant taxa (Trichodesmiumand diatom symbionts) appeared less affected by eddy-driven biological controls. Instead, they appeared driven by physical dynamics along frontal boundaries that separate cyclonic and anticyclonic eddies. Together, the interplay of eddy-specific changes in bottom-up control, top-down control, and the physical accumulation of cells likely explains the elevated diazotroph abundances and NFRs associated with anticyclones and eddy fronts.
Control over sampling boosts numerical evidence processing in human decisions from experience
Authors: Appelhoff Stefan , Hertwig Ralph , Spitzer Bernhard 
Published: June 2021

AbstractWhen acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does control over sampling affect the quality of experience-based decisions? Here, combining variants of a numerical sampling task with neural recordings, we show that control over when to stop sampling can enhance (i) behavioral choice accuracy, (ii) the build-up of parietal decision signals, and (iii) the encoding of numerical sample information in multivariate electroencephalogram (EEG) patterns. None of these effects were observed when participants could only control which alternatives to sample, but not when to stop sampling. Furthermore, levels of control had no effect on early sensory signals or on the extent to which sample information leaked from memory. The results indicate that freedom to stop sampling can amplify decisional evidence processing from the outset of information acquisition and lead to more accurate choices.
Identification of a motif in Trm732 required for 2’-O-methylation of the tRNA anticodon loop by Trm7
Authors: Funk Holly M. , DiVita Daisy J. , Sizemore Hannah E. , Wehrle Kendal , Weiner Catherine L. , Guy Adrian R. , Phizicky Eric M. , Guy Michael P. 
Published: June 2021

AbstractPosttranscriptional tRNA modifications are essential for proper gene expression, and defects in the enzymes that perform tRNA modifications are associated with numerous human disorders. Throughout eukaryotes, 2’-O-methylation of residues 32 and 34 of the anticodon loop of tRNA is important for proper translation, and in humans, lack of these modifications results in non-syndromic X-linked intellectual disability. In yeast, the methyltransferase Trm7 forms a complex with Trm732 to 2’-O-methylate tRNA residue 32 and with Trm734 to 2’-O-methylate tRNA residue 34. Trm732 and Trm734 are required for the methylation activity of Trm7, but the role of these auxiliary proteins is not clear. Additionally, Trm732 and Trm734 homologs are implicated in biological processes not directly related to translation, suggesting that these proteins may have additional cellular functions. To identify critical amino acids in Trm732, we generated variants and tested their ability to function in yeast cells. We identified a conserved RRSAGLP motif in the conserved DUF2428 domain of Trm732 that is required for tRNA modification activity by both yeast Trm732 and its human homolog THADA. The identification of Trm732 variants that lack tRNA modification activity will help to determine if other biological functions ascribed to Trm732 and THADA are directly due to tRNA modification, or to secondary effects due to other functions of these proteins.