bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influenza virus replication in cardiomyocytes drives heart dysfunction and fibrosis
Authors: Kenney Adam D. , Aron Stephanie L. , Gilbert Clara , Kumar Naresh , Chen Peng , Eddy Adrian , Zhang Lizhi , Zani Ashley , Vargas-Maldonado Nahara , Speaks Samuel , Kawahara Jeffrey , Denz Parker J. , Dorn Lisa , Accornero Federica , Ma Jianjie , Zhu Hua , Rajaram Murugesan V.S. , Cai Chuanxi , Langlois Ryan A. , Yount Jacob S. 
Published: October 2021

AbstractCardiac dysfunction is a common extrapulmonary complication of severe influenza virus infection. Prevailing models propose that influenza-associated heart dysfunction is indirectly triggered by cytokine mediated cardiotoxicity downstream of the inflamed lung, rather than by direct infection of cardiac tissue. To test the etiology of cardiac dysfunction resulting from influenza virus infection, we generated a novel recombinant H1N1 influenza A virus that was attenuated in cardiomyocytes by incorporation of target sequences for miRNAs expressed specifically in that cell type (miR133b and miR206). Compared with control virus, mice infected with the miR-targeted virus had significantly reduced heart viral titers, confirming cardiac attenuation of viral replication. The miR-targeted virus, however, was fully replicative and inflammatory in lungs when compared to control virus, and induced similar systemic weight loss. The miR-targeted virus induced considerably lower levels of cardiac arrhythmia, fibrosis, and inflammation, compared with control virus, in mice lacking interferon induced transmembrane protein 3 (IFITM3), which serve as the only available model for severe influenza-associated cardiac pathology. We conclude that robust replication of virus in the heart is required for pathology even when lung inflammation is severe. Indeed, we show that human stem cell-derived cardiomyocytes are susceptible to influenza virus infection. This work establishes a fundamental new paradigm in which influenza virus damages the heart through direct infection of cardiomyocytes.
Selfing-outcrossing as a gradient, not a dichotomy: propensity for selfing varies within a population of hermaphroditic animals
Authors: Felmy Anja , Streiff Alena B. , Jokela Jukka 
Published: October 2021

AbstractFor mating-system evolution, individual-level variation is essential. In self-compatible hermaphrodites, individuals may vary in their lifetime propensity for selfing, which consists of individual and environmental components. According to the reproductive assurance hypothesis explaining partial selfing, a key environmental factor is mate availability, which fluctuates with population density.We quantified individual variation in selfing propensity in a hermaphroditic snail by manipulating mate availability, recording mating behaviour, estimating selfing rates from progeny arrays, and measuring female lifetime fitness. We found substantial among-individual variation in selfing propensity, including pure outcrossers, pure selfers, and two types of plastic individuals. This variation only manifested in the laboratory; for the highly dense field population, data suggest full outcrossing. Meanwhile, experimental levels of mate availability (lowversusmoderate) neither significantly affected selfing propensities nor selfing rates.Instead, selfing propensities had an individual, environment-independent component. Our results imply that selfing propensities are partially heritable and, when selected on, cause mean selfing rates to evolve. We propose that genetic variation in selfing propensities offers a reconciliation between the reproductive assurance hypothesis and its limited empirical support in animals: distributions of selfing propensities vary temporally and spatially, thus obscuring the relationship between population density and realised selfing rates.
Widespread redundancy in -omics profiles of cancer mutation states
Authors: Crawford Jake , Christensen Brock C. , Chikina Maria , Greene Casey S. 
Published: October 2021

AbstractIn studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal may be unclear. In this study, we consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem. Since functional signatures of cancer mutation have been identified across many data types, this problem presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. The TCGA Pan-Cancer Atlas contains genetic alteration data including somatic mutations and copy number variants (CNVs), as well as several -omics data types. From TCGA, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts.Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. Surprisingly, we found that for many of the genes we considered, one or more other data types are approximately equally effective predictors. Performance was more variable between mutations than it was between data types for the same mutation, and there was often little difference between the top data types. We also found that combining data types into a single multi-omics model provided little or no improvement in predictive ability over the best individual data type. Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.
Single-molecule imaging suggests compact and spliceosome dependent organization of long introns
Authors: Adivarahan Srivathsan , Kalhara Abeykoon A.M.S. , Zenklusen Daniel 
Published: October 2021

SummaryIntron removal from pre-mRNAs is a critical step in the processing of RNA polymerase II transcripts, required to create translation competent mRNAs. In humans, introns account for large portions of the pre-mRNA, with intronic sequences representing about 95% of most pre-mRNA. Intron length varies considerably; introns can be as short as a few to hundreds of thousands of nucleotides in length. How nascent long intronic RNA is organized during transcription to facilitate the communication between 5’ and 3’ splice-sites required for spliceosome assembly however is still poorly understood. Here, we use single-molecule fluorescent RNA in situ hybridization (smFISH) to investigate the spatial organization of co- and post-transcriptional long introns in cells. Using two long introns within the POLA1 pre-mRNA as a model, we show that introns are packaged into compact assemblies, and when fully transcribed, are organized in a looped conformation with their ends in proximity. This organization is observed for nascent and nucleoplasmic pre-mRNAs and requires spliceosome assembly, as disruption of U2 snRNP binding results in introns with separated 5’ and 3’ ends. Moreover, interrogating the spatial organization of partially transcribed co-transcriptional POLA1 intron 35 indicates that the 5’ splice site is maintained proximal to the 3’ splice site during transcription, supporting a model that 5’ splice site tethering to the elongating polymerase might contribute to spliceosome assembly at long introns. Together, our study reveals details of intron and pre-mRNA organization in cells and provides a tool to investigate mechanisms of splicing for long introns.
Telescoping bimodal latent Dirichlet allocation to identify expression QTLs across tissues
Authors: Gewirtz Ariel DH , Townes F William , Engelhardt Barbara E 
Published: October 2021

AbstractExpression quantitative trait loci (eQTLs), or single nucleotide polymorphisms (SNPs) that affect average gene expression levels, provide important insights into context-specific gene regulation. Classic eQTL analyses use one-to-one association tests, which test gene-variant pairs individually and ignore correlations induced by gene regulatory networks and linkage disequilibrium. Probabilistic topic models, such as latent Dirichlet allocation, estimate latent topics for a collection of count observations. Prior multi-modal frameworks that bridge genotype and expression data assume matched sample numbers between modalities. However, many data sets have a nested structure where one individual has several associated gene expression samples and a single germline genotype vector. Here, we build a telescoping bimodal latent Dirichlet allocation (TBLDA) framework to learn shared topics across gene expression and genotype data that allows multiple RNA-sequencing samples to correspond to a single individual’s genotype. By using raw count data, our model avoids possible adulteration via normalization procedures. Ancestral structure is captured in a genotype-specific latent space, effectively removing it from shared components. Using GTEx v8 expression data across ten tissues and genotype data, we show that the estimated topics capture meaningful and robust biological signal in both modalities, and identify associations within and across tissue types. We identify 53,358 cis-eQTLs and 1,173 trans-eQTLs by conducting eQTL mapping between the most informative features in each topic. Our TBLDA model is able to identify associations using raw sequencing count data when the samples in two separate data modalities are matched one-to-many, as is often the case in biological data.
Whole-genome sequence and methylome profiling of the almond (Prunus dulcis [Mill.] D.A.Webb) cultivar ‘Nonpareil’
Authors: D’Amico-Willman Katherine M. , Ouma Wilberforce Z. , Meulia Tea , Sideli Gina M. , Gradziel Thomas M. , Fresnedo-Ramírez Jonathan 
Published: October 2021

AbstractAlmond (Prunus dulcis [Mill.] D.A. Webb) is an economically important, specialty nut crop grown almost exclusively in the United States. Breeding and improvement efforts worldwide have led to the development of key, productive cultivars, including ‘Nonpareil,’ which is the most widely grown almond cultivar. Thus far, genomic resources for this species have been limited, and a whole-genome assembly for ‘Nonpareil’ is not currently available despite its economic importance and use in almond breeding worldwide. We generated a 615.89X coverage genome sequence using Illumina, PacBio, and optical mapping technologies. Gene prediction revealed 27,487 genes using MinION Oxford nanopore and Illumina RNA sequencing, and genome annotation found that 68% of predicted models are associated with at least one biological function. Further, epigenetic signatures of almond, namely DNA cytosine methylation, have been implicated in a variety of phenotypes including self-compatibility, bud dormancy, and development of non-infectious bud failure. In addition to the genome sequence and annotation, this report also provides the complete methylome of several key almond tissues, including leaf, flower, endocarp, mesocarp, fruit skin, and seed coat. Comparisons between methylation profiles in these tissues revealed differences in genome-wide weighted percent methylation and chromosome-level methylation enrichment. The raw sequencing data are available on NCBI Sequence Read Archive, and the complete genome sequence and annotation files are available on NCBI Genbank. All data can be used without restriction.
Jaagsiekte sheep retrovirus infection induces changes in microRNA expression in the ovine lung
Authors: Garcia Maria Contreras , Karagianni Anna E. , Vasoya Deepali , Jayaraman Siddharth , Lin Yao-Tang , Wood Ann R. , Dagleish Mark P. , Cousens Chris , Watson Mick , Grey Finn E. , Griffiths David J. 
Published: October 2021

ABSTRACTOvine pulmonary adenocarcinoma (OPA) is an infectious neoplastic lung disease of sheep caused by jaagsiekte sheep retrovirus. OPA is an important veterinary problem and is also a valuable large animal model for human lung adenocarcinoma. JSRV infects type 2 alveolar epithelial cells in the lung and induces the growth of tumors, but little is known about the molecular events that lead to the activation of oncogenic pathways in infected cells. MicroRNAs (miRNAs) are small RNA molecules of approximately 22 nucleotides with important roles in regulating gene expression in eukaryotes and with well-established roles in cancer. Here we used small-RNA sequencing to investigate the changes in miRNA expression that occur in JSRV-infected ovine lung. After filtering out low abundance miRNAs, we identified expression of 405 miRNAs, 32 of which were differentially expressed in JSRV-infected lung compared to mock-inoculated control lung. Highly upregulated miRNAs included miR-182, miR-183, miR-96 and miR-135b, which have also been associated with oncogenic changes in human lung cancer. Network analysis of genes potentially targeted by the deregulated miRNAs identified their involvement in pathways known to be dysregulated in OPA. We found no evidence to support the existence of miRNAs encoded by JSRV. This study provides the first information on miRNA expression in OPA and identifies a number of targets for future studies into the role of these molecules in the pathogenesis of this unique veterinary model for human lung adenocarcinoma.IMPORTANCEOvine pulmonary adenocarcinoma is a neoplastic lung disease of sheep caused by jaagsiekte sheep retrovirus (JSRV). OPA is a significant welfare and economic concern for sheep producers and is a valuable large animal model for human lung adenocarcinoma. MicroRNAs are small RNA molecules of approximately 22 nucleotides with important functions in regulating gene expression in eukaryotes and with well-established roles in cancer. In this study, we examined the changes in microRNA expression that occur in the lung in response to JSRV infection. We identified differential expression of a number of host-encoded microRNAs in infected tissue, including microRNAs with roles in human cancer. We found no evidence that JSRV encodes a microRNA. This study provides new insights on the cellular response to JSRV infection in the ovine lung, which will inform future studies into the pathogenesis of OPA in sheep and its use as a model for human lung adenocarcinoma.
Selective inhibition of PfATP6 by artemisinins and identification of new classes of inhibitors after expression in yeast
Authors: Moore Catherine M. , Wang Jigang , Lin Qingsong , Ferreira Pedro , Avery Mitchell A. , Elokely Khaled , Staines Henry M. , Krishna Sanjeev 
Published: October 2021

AbstractTreatment failures with artemisinin combination therapies (ACTs) threaten global efforts to eradicate malaria. They highlight the importance of identifying drug targets and new inhibitors and of studying how existing antimalarial classes work.Herein we report the successful development of an heterologous expression-based compound screening tool. Validated drug target P. falciparum calcium ATPase6 (PfATP6) and a mammalian ortholog (SERCA1a) were functionally expressed in yeast providing a robust, sensitive, and specific screening tool. Whole-cell and in vitro assays consistently demonstrated inhibition and labelling of PfATP6 by artemisinins. Mutations in PfATP6 resulted in fitness costs that were ameliorated in the presence of artemisinin derivatives when studied in the yeast model.As previously hypothesised, PfATP6 is a target of artemisinins. Mammalian SERCA1a can be mutated to become more susceptible to artemisinins. The inexpensive, low technology yeast screening platform has identified unrelated classes of druggable PfATP6 inhibitors. Resistance to artemisinins may depend on mechanisms that can concomitantly address multi-targeting by artemisinins and fitness costs of mutations that reduce artemisinin susceptibility.
WGS analysis ofListeria monocytogenesfrom rural, urban, and farm environments in Norway: Genetic diversity, persistence, and relation to clinical and food isolates
Authors: Fagerlund Annette , Idland Lene , Heir Even , Møretrø Trond , Aspholm Marina , Lindbäck Toril , Langsrud Solveig 
Published: October 2021

AbstractListeria monocytogenesis a ubiquitous environmental bacterium associated with a wide variety of natural and man-made environments, such as soil, vegetation, livestock, food processing environments, and urban areas. It is also among the deadliest foodborne pathogens, and knowledge about its presence and diversity in potential sources is crucial to effectively track and control it in the food chain. Isolation ofL. monocytogenesfrom various rural and urban environments showed higher prevalence in agricultural and urban developments than in forest or mountain areas, and that detection was positively associated with rainfall. Whole genome sequencing (WGS) was performed for the collected isolates and forL. monocytogenesfrom Norwegian dairy farms and slugs, in total 218 isolates. The data was compared with available datasets from clinical and food associated sources in Norway collected within the last decade. Multiple examples of clusters of isolates with 0-8 wgMLST allelic differences were collected over time in the same location, demonstrating persistence ofL. monocytogenesin natural, urban and farm environments. Furthermore, several clusters with 6-20 wgMLST allelic differences containing isolates collected across different locations, times and habitats were identified, including nine clusters harbouring clinical isolates. The most ubiquitous clones found in soil and other natural and animal ecosystems (CC91, CC11, and CC37) were distinct from clones predominating among both clinical (CC7, CC121, CC1) and food (CC9, CC121, CC7, CC8) isolates. The analyses indicated that ST91 was more prevalent in Norway than other countries and revealed a high proportion of the hypovirulent ST121 among Norwegian clinical cases.ImportanceListeria monocytogenesis a deadly foodborne pathogen that is widespread in the environment. For effective management, both public health authorities and food producers need reliable tools for source tracking, surveillance, and risk assessment. For this, whole genome sequencing (WGS) is regarded as the present and future gold standard. In the current study, we use WGS to show thatL. monocytogenescan persist for months and years in natural, urban and dairy farm environments. Notably, clusters of almost identical isolates, with genetic distances within the thresholds often suggested for defining an outbreak cluster, can be collected from geographically and temporally unrelated sources. The work highlights the need for a greater knowledge of the genetic relationships between clinical isolates and isolates ofL. monocytogenesfrom a wide range of environments, including natural, urban, agricultural, livestock, food production, and food processing environments, in order to correctly interpret and use results from WGS analyses.
Genomic diversity of hospital-acquired infections revealed through prospective whole genome sequencing-based surveillance
Authors: Mustapha Mustapha M. , Srinivasa Vatsala R. , Griffith Marissa P. , Cho Shu-Ting , Evans Daniel R. , Waggle Kady , Ezeonwuka Chinelo , Snyder Daniel J. , Marsh Jane W. , Harrison Lee H. , Cooper Vaughn S. , Van Tyne Daria 
Published: October 2021

AbstractHealthcare-associated infections (HAIs) cause mortality, morbidity, and waste of healthcare resources. HAIs are also an important driver of antimicrobial resistance, which is increasing around the world. Beginning in November 2016, we instituted an initiative to detect outbreaks of HAI using prospective whole genome sequencing-based surveillance of bacterial pathogens collected from hospitalized patients. Here we describe the biodiversity of bacteria sampled from hospitalized patients at a single center, as revealed through systematic analysis of their genomes. We sequenced the genomes of 3,004 bacterial isolates from hospitalized patients collected over a 25-month period. We identified bacteria belonging to 97 distinct species, which were distributed among 14 species groups. Within these groups, isolates could be distinguished from one another by both average nucleotide identity (ANI) and principal component analysis of accessory genes (PCA-A). Genetic distances between isolates and rates of evolution varied between different species, which has implications for the selection of distance cut-offs for outbreak analysis. Antimicrobial resistance genes and the sharing of mobile genetic elements between different species were frequently observed. Overall, this study describes the population structure of pathogens circulating in a single healthcare setting, and shows how investigating microbial population dynamics can inform genomic epidemiology studies.ImportanceHospitalized patients are at increased risk of becoming infected with antibiotic-resistant organisms. We used whole-genome sequencing to survey and compare over 3,000 bacterial isolates collected from hospitalized patients at a large medical center over a two-year period. We identified nearly 100 different bacterial species, suggesting that patients can be infected with a wide variety of different organisms. When we examined how genetic relatedness differed between species, we found that different species are likely evolving at different rates within our hospital. This is significant because the identification of bacterial outbreaks in the hospital currently relies on genetic similarity cut-offs, which are often applied uniformly across organisms. Finally, we found that antibiotic resistance genes and mobile genetic elements were abundant among the bacterial isolates we sampled. Overall, this study provides an in-depth view of the genomic diversity and evolution of bacteria sampled from hospitalized patients, as well as genetic similarity estimates that can inform hospital outbreak detection and prevention efforts.