bluuebunny/crossref_metadata_2025_split huggingface dataset:
scAAVengr: Single-cell transcriptome-based quantification of engineered AAVs in non-human primate retina
Authors: Öztürk Bilge E. , Johnson Molly E. , Kleyman Michael , Turunç Serhan , He Jing , Jabalameli Sara , Xi Zhouhuan , Visel Meike , Dufour Valérie L. , Iwabe Simone , Marinho Felipe Pompeo , Aguirre Gustavo D. , Sahel José-Alain , Schaffer David V. , Pfenning Andreas R. , Flannery John G. , Beltran William A. , Stauffer William R. , Byrne Leah C. 
Published: October 2020

AbstractAdeno-associated virus (AAV)-mediated gene therapies are rapidly advancing to the clinic, and AAV engineering has resulted in vectors with increased ability to deliver therapeutic genes. Although the choice of vector is critical, quantitative comparison of AAVs, especially in large animals, remains challenging. Here, we developed an efficient single-cell AAV engineering pipeline (scAAVengr) to quantify efficiency of AAV-mediated gene expression across all cell types. scAAVengr allows for definitive, head-to-head comparison of vectors in the same animal. To demonstrate proof-of-concept for the scAAVengr workflow, we quantified – with cell-type resolution – the abilities of naturally occurring and newly engineered AAVs to mediate gene expression in primate retina following intravitreal injection. A top performing variant, K912, was used to deliver SaCas9 and edit the rhodopsin gene in macaque retina, resulting in editing efficiency similar to infection rates detected by the scAAVengr workflow. These results validate scAAVengr as a powerful method for development of AAV vectors.
Museum genomics illuminate the high specificity of a bioluminescent symbiosis across a genus of reef fish
Authors: Gould Alison L. , Fritts-Penniman Allison , Gaisiner Ana 
Published: October 2020

AbstractSymbiotic relationships between bioluminescent bacteria and fishes have evolved multiple times across hundreds of fish taxa, but relatively little is known about the specificity of these associations and how conserved they have been through time. This study describes the degree of specificity of a bioluminescent symbiosis between cardinalfishes in the genus Siphamia and luminous bacteria in the Vibrio family. Primarily using museum specimens, we investigate the co-divergence of host and symbiont and test for patterns of divergence that correlate with both biogeography and time. Contrary to expectations, we determined that the light organ symbionts of all 14 Siphamia species examined belong to one genetic clade of Photobacterium mandapamensis (Clade II), indicating that the association is highly specific and conserved across the host genus. Thus, we did not find evidence of codivergence among hosts and symbionts. We did observe that symbionts hosted by individuals sampled from colder water regions were more divergent, containing more than three times as many single nucleotide polymorphisms than the rest of the symbionts examined. Overall our findings indicate that the symbiosis between Siphamia fishes and P. mandapamensis Clade II has been highly conserved across a broad geographic range and through time despite the facultative nature of the bacterial symbiont. These results suggest that this bioluminescent symbiosis could have played a key role in the evolution of the host genus and that there are conserved mechanisms regulating its specificity that have yet to be defined.
Potent mouse monoclonal antibodies that block SARS-CoV-2 infection
Authors: Guo Youjia , Kawaguchi Atsushi , Takeshita Masaru , Sekiya Takeshi , Hirohama Mikako , Yamashita Akio ,   the Keio Donner Project, Siomi Haruhiko , Murano Kensaku 
Published: October 2020

AbstractCoronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has developed into a global pandemic since its first outbreak in the winter of 2019. An extensive investigation of SARS-CoV-2 is critical for disease control. Various recombinant monoclonal antibodies of human origin that neutralize SARS-CoV-2 infection have been isolated from convalescent patients and will be applied as therapies and prophylaxis. However, the need for dedicated monoclonal antibodies in molecular pathology research is not fully addressed. Here, we produced mouse anti-SARS-CoV-2 spike monoclonal antibodies that exhibit not only robust performance in immunoassays including western blotting, ELISA, immunofluorescence, and immunoprecipitation, but also neutralizing activity against SARS-CoV-2 infectionin vitro. Our monoclonal antibodies are of mouse origin, making them compatible with the experimental immunoassay setups commonly used in basic molecular biology research laboratories, and large-scale production and easy distribution are guaranteed by conventional mouse hybridoma technology.
Assessingin vivomutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
Authors: Tisthammer Kaho H. , Solis Caroline , Oracles Faye , Nzerem Madu , Winstead Ryan , Dong Weiyan , Joy Jeffrey B. , Pennings Pleuni S. 
Published: October 2020

AbstractLike many viruses, Hepatitis C Virus (HCV) has a high nutation rate, which helps the virus adapt quickly, but mutations come with fitness costs. Fitness costs can be studied by different approaches, such as experimental or frequency-based approaches. The frequency-based approach is particularly useful to estimatein vivofitness costs, but this approach works best with deep sequencing data from many hosts, are. In this study, we applied the frequency-based approach to a large dataset of 195 patients and estimated the fitness costs of mutations at 7957 sites along the HCV genome. We used beta regression and random forest models to better understand how different factors influenced fitness costs. Our results revealed that costs of nonsynonymous mutations were three times higher than those of synonymous mutations, and mutations at nucleotides A or T had higher costs than those at C or G. Genome location had a modest effect, with lower costs for mutations in HVR1 and higher costs for mutations in Core and NS5B. Resistance mutations were, on average, costlier than other mutations. Our results show thatin vivofitness costs of mutations can be virus specific, reinforcing the utility of constructingin vivofitness cost maps of viral genomes.Author SummaryUnderstanding how viruses evolve within patients is important for combatting viral diseases, yet studying viruses within patients is difficult. Laboratory experiments are often used to understand the evolution of viruses, in place of assessing the evolution in natural populations (patients), but the dynamics will be different. In this study, we aimed to understand the within-patient evolution of Hepatitis C virus, which is an RNA virus that replicates and mutates extremely quickly, by taking advantage of high-throughput next generation sequencing. Here, we describe the evolutionary patterns of Hepatitis C virus from 195 patients: We analyzed mutation frequencies and estimated how costly each mutation was. We also assessed what factors made a mutation more costly, including the costs associated with drug resistance mutations. We were able to create a genome-wide fitness map of within-patient mutations in Hepatitis C virus which proves that, with technological advances, we can deepen our understanding of within-patient viral evolution, which can contribute to develop better treatments and vaccines.
Detecting cryptic clinically-relevant structural variation in exome sequencing data increases diagnostic yield for developmental disorders
Authors: Gardner Eugene J. , Sifrim Alejandro , Lindsay Sarah J. , Prigmore Elena , Rajan Diana , Danecek Petr , Gallone Giuseppe , Eberhardt Ruth Y. , Martin Hilary C. , Wright Caroline F. , FitzPatrick David R. , Firth Helen V. , Hurles Matthew E. 
Published: October 2020

SummaryStructural Variation (SV) describes a broad class of genetic variation greater than 50bps in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DD). Patients presenting with DD are often referred for diagnostic testing with chromosomal microarrays (CMA) to identify large copy-number variants (CNVs) and/or with single gene, gene-panel, or exome sequencing (ES) to identify single nucleotide variants, small insertions/deletions, and CNVs. However, patients with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the novel tool ‘InDelible’, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DD recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 64 rare, damaging variants in genes previously associated with DD missed by standard SNV, InDel or CNV discovery approaches. Clinical review of these 64 variants determined that about half (30/64) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21-500 bps in size, and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.3%. Of particular interest were seven confirmed de novo variants in MECP2 which represent 35.0% of all de novo protein truncating variants in MECP2 among DDD patients. InDelible provides a framework for the discovery of pathogenic SVs that are likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases.
Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer
Authors: Ponzi Erica , Thoresen Magne , Nøst Therese Haugdahl , Møllersen Kajsa 
Published: October 2020

AbstractBackgroundCancer genomic studies often include data collected from several omics platforms. Each omics data source contributes to the understanding of the underlying biological process via source specific (“individual”) patterns of variability. At the same time, statistical associations and potential interactions among the different data sources can reveal signals from common biological processes that might not be identified by single source analyses. These common patterns of variability are referred to as “shared” or “joint”. In this work, we show how the use of joint and individual components can lead to better predictive models, and to a deeper understanding of the biological process at hand. We identify joint and individual contributions of DNA methylation, miRNA and mRNA expression collected from blood samples in a lung cancer case-control study nested within the Norwegian Women and Cancer (NOWAC) cohort study, and we use such components to build prediction models for case-control and metastatic status. To assess the quality of predictions, we compare models based on simultaneous, integrative analysis of multi-source omics data to a standard non-integrative analysis of each single omics dataset, and to penalized regression models. Additionally, we apply the proposed approach to a breast cancer dataset from The Cancer Genome Atlas.ResultsOur results show how an integrative analysis that preserves both components of variation is more appropriate than standard multi-omics analyses that are not based on such a distinction. Both joint and individual components are shown to contribute to a better quality of model predictions, and facilitate the interpretation of the underlying biological processes in lung cancer development.ConclusionIn the presence of multiple omics data sources, we recommend the use of data integration techniques that preserve the joint and individual components across the omics sources. We show how the inclusion of such components increases the quality of model predictions of clinical outcomes.
Inorganic and black carbon hotspots constrain blue carbon mitigation services across tropical seagrass and temperate tidal marshes
Authors: Gallagher John Barry , Prahalad Vishnu , Aalders John 
Published: October 2020

AbstractTotal organic carbon (TOC) sediment stocks as a CO2mitigation service requires exclusion of allochthonous black (BC) and particulate inorganic carbon corrected for water– atmospheric equilibrium (PICeq). For the first time, we address this bias for a temperate salt marsh and a coastal tropical seagrass in BC hotspots. Seagrass TOC stocks were similar to the salt marshes with soil depths < 1 m (59.3 ± 11.3 and 74.9 ± 18.9 MgC ha-1, CI 95% respectively) and sequestration rates of 1.134 MgC ha-1yr-1. Both ecosystems showed larger BC constraints than their pristine counterparts. However, the seagrass meadows’ mitigation services were largely constrained by both higher BC/TOC and PICeq/TOC fractions (38.0% ± 6.6% and 43.4% ± 5.9%, CI 95%) and salt marshes around a third (22% ± 10.2% and 6.0% ± 3.1% CI 95%). The results demonstrate a need to account for both BC and PIC within blue carbon mitigation assessments.
Development and characterization of nanobodies specifically targeting the oncogenic Phosphatase of Regenerating Liver-3 (PRL-3)
Authors: Smith Caroline N. , Kihn Kyle , Williamson Zachary A. , Chow K. Martin , Hersh Louis B. , Korotkov Konstantin V. , Deredge Daniel , Blackburn Jessica S. 
Published: October 2020

AbstractPhosphatase of Regenerating Liver-3 (PRL-3) is associated with cancer progression and metastasis in various solid tumors and leukemias. The mechanisms that drive PRL-3’s oncogenic functions are not well understood, in part due to a lack of research tools available to study this protein. In particular, small molecules do not exhibit binding specificity for PRL-3 over highly homologous family members PRL-1 and PRL-2, and antibodies directed against PRL-3 are limited by assay type. We have begun to address these issues by developing alpaca-derived single domain antibodies, or nanobodies, targeting PRL-3 with a KDof 30-300 nM and no activity towards PRL-1 and PRL-2. Hydrogen deuterium exchange mass spectrometry (HDX-MS) and co-immunoprecipitation with a known PRL-3 substrate showed the nanobodies bind PRL-3 outside of the active site, meaning they can be used to study PRL-3 interaction with binding partners. The nanobodies were also specific to PRL-3 over other PRLs in immunoprecipitation and immunofluorescence experiments in human cancer cells that overexpressed the PRL family. We found that N-terminal tags on PRL-3, such as GFP and FLAG, changed PRL-3 localization compared to untagged protein, indicating that the nanobodies may provide new insights into PRL-3 trafficking and function. The anti-PRL-3 nanobodies represent an important expansion of the research tools available to study PRL-3 function and can be used to define the role of PRL-3 in cancer progression.
Bacterial surface properties influence the activity of the TAT-RasGAP317-326 antimicrobial peptide
Authors: Georgieva Maria , Heinonen Tytti , Vitale Alessandra , Hargraves Simone , Causevic Senka , Pillonel Trestan , Eberl Leo , Widmann Christian , Jacquier Nicolas 
Published: October 2020

AbstractAntibiotic resistance is an increasing threat for public health, underscoring the need for new antibacterial agents. Antimicrobial peptides (AMPs) represent an alternative to classical antibiotics. TAT-RasGAP317-326 is a recently described AMP effective against a broad range of bacteria, but little is known about the conditions that may influence its activity. Using RNA-sequencing and screening of mutant libraries, we show that Escherichia coli and Pseudomonas aeruginosa respond to TAT-RasGAP317-326 by regulating metabolic and stress response pathways, possibly implicating two-component systems. Our results also indicate that bacterial surface properties, in particular integrity of the lipopolysaccharide layer, influence peptide binding and entry. Finally, we found differences between bacterial species with respect to their rate of resistance emergence against this peptide. Our findings provide the basis for future investigation on the mode of action of this peptide and its potential clinical use as an antibacterial agent.
Transposable element expression at unique loci in single cells with CELLO-seq
Authors: Berrens Rebecca V , Yang Andrian , Laumer Christopher E , Lun Aaron TL , Bieberich Florian , Law Cheuk-Ting , Lan Guocheng , Imaz Maria , Gaffney Daniel , Marioni John C 
Published: October 2020

AbstractThe role of Transposable Elements (TEs) in regulating diverse biological processes, from early development to cancer, is becoming increasing appreciated. However, unlike other biological processes, next generation single-cell sequencing technologies are ill-suited for assaying TE expression: in particular, their highly repetitive nature means that short cDNA reads cannot be unambiguously mapped to a specific locus. Consequently, it is extremely challenging to understand the mechanisms by which TE expression is regulated and how they might themselves regulate other protein coding genes. To resolve this, we introduce CELLO-seq, a novel method and computational framework for performing long-read RNA sequencing at single cell resolution. CELLO-seq allows for full-length RNA sequencing and enables measurement of allelic, isoform and TE expression at unique loci. We use CELLO-seq to assess the widespread expression of TEs in 2-cell mouse blastomeres as well as human induced pluripotent stem cells (hiPSCs). Across both species, old and young TEs showed evidence of locus-specific expression, with simulations demonstrating that only a small number of very young elements in the mouse could not be mapped back to with high confidence. Exploring the relationship between the expression of individual elements and putative regulators revealed surprising heterogeneity, with TEs within a class showing different patterns of correlation, suggesting distinct regulatory mechanisms.
Two independent approaches converge to the cloning of a newLeptosphaeria maculansavirulence effector gene,AvrLmS-Lep2
Authors: Neik Ting Xiang , Ghanbarnia Kaveh , Ollivier Bénédicte , Scheben Armin , Severn-Ellis Anita , Larkan Nicholas J. , Haddadi Parham , Fernando W.G. Dilantha , Rouxel Thierry , Batley Jacqueline , Borhan Hossein M. , Balesdent Marie-Hélène 
Published: October 2020

SummaryLeptosphaeria maculans, the causal agent of blackleg disease, interacts withBrassica napus(oilseed rape, canola) in a gene-for-gene manner. The avirulence genesAvrLmS and AvrLep2were described to be perceived by the resistance genesRlmSandLepR2, respectively, present in the cultivar Surpass 400. Here we report cloning ofAvrLmSandAvrLep2using two independent methods.AvrLmSwas cloned using combinedin vitrocrossing between avirulent and virulent isolates with sequencing of DNA bulks from avirulent or virulent progeny (Bulked-Segregant-Sequencing) to rapidly identify one candidate avirulence gene present in the effector repertoire ofL. maculans. AvrLep2was cloned using a bi-parental cross of avirulent and virulentL. maculansisolates and a classical map-based cloning approach. Taking these two approaches independently, we found thatAvrLmSandAvrLep2are the same gene. Complementation of virulent isolates with this gene confirmed its role in inducing resistance on Surpass 400 and Topas-LepR2. The gene renamedAvrLmS-Lep2encodes for a small cysteine-rich protein of unknown function with an N-terminal secretory signal peptide, which are common features of the majority of effectors from extracellular fungal plant pathogens. TheAvrLmS-Lep2/LepR2interaction phenotype was found to vary from a typical hypersensitive response to intermediate resistance sometimes at the edge of, or evolving toward, susceptibility depending on the inoculation conditions.AvrLmS-Lep2was nevertheless sufficient to significantly reduce the stem lesion size on plant genotypes withLepR2, indicating the potential efficiency of this resistance to control the disease in the field.
Leveraging high-throughput screening data and conditional generative adversarial networks to advance predictive toxicology
Authors: Green Adrian J. , Mohlenkamp Martin J. , Das Jhuma , Chaudhari Meenal , Truong Lisa , Tanguay Robyn L. , Reif David M. 
Published: October 2020

AbstractThere are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) methods are vital. As part of one such HTS effort, embryonic zebrafish were used to examine a suite of morphological and mortality endpoints at six concentrations from over 1,000 unique chemicals found in the ToxCast library (phase 1 and 2). We hypothesized that by using a conditional Generative Adversarial Network (cGAN) and leveraging this large set of toxicity data, plus chemical structure information, we could efficiently predict toxic outcomes of untested chemicals. CAS numbers for each chemical were used to generate textual files containing three-dimensional structural information for each chemical. Utilizing a novel method in this space, we converted the 3D structural information into a weighted set of points while retaining all information about the structure.In vivotoxicity and chemical data were used to train two neural network generators. The first used regression (Go-ZT) while the second utilized cGAN architecture (GAN-ZT) to train a generator to produce toxicity data. Our results showed that both Go-ZT and GAN-ZT models produce similar results, but the cGAN achieved a higher sensitivity (SE) value of 85.7% vs 71.4%. Conversely, Go-ZT attained higher specificity (SP), positive predictive value (PPV), and Kappa results of 67.3%, 23.4%, and 0.21 compared to 24.5%, 14.0%, and 0.03 for the cGAN, respectively. By combining both Go-ZT and GAN-ZT, our consensus model improved the SP, PPV, and Kappa, to 75.5%, 25.0%, and 0.211, respectively, resulting in an area under the receiver operating characteristic (AUROC) of 0.663. Considering their potential use as prescreening tools, these models could providein vivotoxicity predictions and insight into untested areas of the chemical space to prioritize compounds for HT testing.SummaryA conditional Generative Adversarial Network (cGAN) can leverage a large chemical set of experimental toxicity data plus chemical structure information to predict the toxicity of untested compounds.