bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chimeric RNA:DNA Donorguide Improves HDR in vitro and in vivo
Authors: Simone Brandon W. , Lee Han B. , Daby Camden L. , Restrepo-Castillo Santiago , Martínez-Gálvez Gabriel , Ata Hirotaka , Gendron William A.C. , Clark Karl J. , Ekker Stephen C. 
Published: May 2021

AbstractIntroducing small genetic changes to study specific mutations or reverting clinical mutations to wild type has been an area of interest in precision genomics for several years. In fact, it has been found that nearly 90% of all human pathogenic mutations are caused by small genetic variations, and the methods to efficiently and precisely correct these errors are critically important. One common way to make these small DNA changes is to provide a single stranded DNA (ssDNA) donor containing the desired alteration together with a targeted double-strand break (DSB) at the genomic target. The donor is typically flanked by regions of homology that are often ~30-100bp in length to leverage the homology directed repair (HDR) pathway. Coupling a ssDNA donor with a CRISPR-Cas9 to produce a targeted DSB is one of the most streamlined approaches to introduce small changes. However, in many cell types this approach results in a low rate of incorporation of the desired alteration and has undesired imprecise repair at the 5’ or 3’ junction due to artifacts of the DNA repair process. We herein report a technology that couples the spatial temporal localization of an ssDNA repair template and leverages the nucleic acid components of the CRISPR-Cas9 system. We show that by direct fusion of an ssDNA template to the trans activating RNA (tracrRNA) to generate an RNA-DNA chimera, termed Donorguide, we recover precise integration of genetic alterations, with both increased integration rates and decreased imprecision at the 5’ or 3’ junctions relative to an ssODN donor in vitro in HEK293T cells as well as in vivo in zebrafish. Further, we show that this technology can be used to enhance gene conversion with other gene editing tools such as TALENs.
Integration and comparison of multi-omics profiles of NGLY1 deficiency plasma and cellular models to identify clinically relevant molecular phenotypes
Authors: Chen Songjie , Wang Guangwen , Shen Xiaotao , Hornburg Daniel , Rego Shannon , Hoffman Rene , Nevins Stephanie , Cheng Xun , Snyder Michael 
Published: May 2021

AbstractNGLY1 (N-glycanase 1) deficiency is a rare congenital recessive disorder of protein deglycosylation unaddressed by the current standard of care. Using combined metabolomics and proteomics profiling, we show that NGLY1 deficiency activates the immune response and disturbs lipid metabolism, biogenic amine synthesis, and glutathione metabolism. These alterations were also observed in NGLY1 deficient patient-derived induced pluripotent stem cells (iPSCs) and differentiated neural progenitor cells (NPCs), which serve as personalized cellular models of the disease. These findings provide molecular insight into the pathophysiology of NGLY1 deficiency and suggest potential therapeutic strategies.
Seeing beyond the target: Leveraging off-target reads in targeted clinical tumor sequencing to identify prognostic biomarkers
Authors: Mangul Serghei , Brito Jaqueline J , Groha Stefan , Zaitlen Noah , Gusev Alexander 
Published: May 2021

AbstractClinical tumor sequencing is rapidly becoming a standard component of clinical care, providing essential information for selecting amongst treatment options and providing prognostic value. Here we develop a robust and scalable software platform (SBT: Seeing Beyond the Target) that mines discarded components of clinical sequences to produce estimates of a rich set of omics features including rDNA and mtDNA copy number, microbial species abundance, and T and B cell receptor sequences. We validate the accuracy of SBT via comparison to multimodal data from the TCGA and apply SBT to a tumor panel cohort of 2,920 lung adenocarcinomas to identify associations of clinical value. We replicated known associations of somatic events in TP53 with changes in rDNA (p=0.012); as well as diversity of BCR and TCR repertoires with the biopsy site (p=2.5×10−6, p<10−20). We observed striking differences in EGFR mutant lung cancers versus wild-type, including higher rDNA copy number and lower immune repertoire diversity. Integrating clinical outcomes, we identified significant prognostic associations with overall survival, including SBT estimates of 5S rDNA (p=1.9×10−4, hazard ratio = 1.22) and TCR diversity (p=2.7×10−3, hazard ratio=1.77). Both novel survival associations replicated in 1,302 breast carcinoma and 1,651 colorectal cancer tumors. We anticipate that feature estimates derived by SBT will yield novel biomarker hypotheses and open research opportunities in existing and emerging clinical tumor sequencing cohorts.
Structural basis of polyamine transport by human ATP13A2 (PARK9)
Authors: Sim Sue Im , von Bülow Sören , Hummer Gerhard , Park Eunyong 
Published: May 2021

AbstractPolyamines are small, organic polycations that are ubiquitous and essential to all forms of life. Currently, how polyamines are transported across membranes is not understood. Recent studies have suggested that ATP13A2 and its close homologs, collectively known as P5B-ATPases, are polyamine transporters at endo-/lysosomes. Loss-of-function mutations of ATP13A2 in humans cause hereditary early-onset Parkinson’s disease. To understand the polyamine transport mechanism of ATP13A2, we determined high-resolution cryo-EM structures of human ATP13A2 in five distinct conformational intermediates, which together represent a near-complete transport cycle of ATP13A2. The structural basis of the polyamine specificity was revealed by an endogenous polyamine molecule bound to a narrow, elongated cavity within the transmembrane domain. The structures show an atypical transport path for a water-soluble substrate, where polyamines may exit within the cytosolic leaflet of the membrane. Our study provides important mechanistic insights into polyamine transport and a framework to understand functions and mechanisms of P5B-ATPases.HighlightsCryo-EM structures of human ATP13A2 in five distinct conformations at 2.5–3.7 Å resolutions.Unique features of ATP13A2 in comparison to other P-type ATPases.Structure of the substrate-binding pocket of ATP13A2 and the molecular basis of polyamine binding.Conformational changes along the transport cycle and proposed model for polyamine transport.
A Role for Synaptonemal Complex in Meiotic Mismatch Repair
Authors: Voelkel-Meiman Karen , Oke Ashwini , Feil Arden , Shames Alexander , Fung Jennifer , MacQueen Amy 
Published: May 2021

AbstractDuring meiosis a large subset of interhomolog recombination repair intermediates form within the physical context of the synaptonemal complex (SC), a protein-rich structure assembled at the interface of aligned homologous chromosomes. However, the functional relationship between SC structure and homologous recombination remains poorly defined. In prior work we determined that tripartite SC is dispensable for recombination in S. cerevisiae; SC central element proteins Ecm11 and Gmc2 instead limit the number of recombination events. Here we report that while dispensable for recombination per se, SC central element proteins influence the processing of interhomolog recombination intermediates in a manner that minimizes errors in mismatch correction. Failure to correct mis-paired bases within heteroduplex at meiotic recombination sites leads to genotypically sectored colonies (post meiotic segregation events) arising from mitotic proliferation of mismatch-containing spores. We discovered an increase in post-meiotic segregation at the THR1 locus in cells lacking Ecm11 or Gmc2, or in the SC-deficient but crossover recombination-proficient zip1[Δ21-163] mutant. High-throughput sequencing of octad meiotic products revealed a genome-wide increase in recombination events with uncorrected mismatches in ecm11 mutants relative to wild type. Meiotic cells missing Ecm11 also display longer gene conversion tracts, but tract length alone does not account for the higher frequency of uncorrected mismatches. Interestingly, the per-nucleotide mismatch frequency is elevated in ecm11 mutants when analyzing all gene conversion tracts, but is similar between wild type and ecm11 if one considers only those events with uncorrected mismatches. Our data suggest that a subset of recombination events is similarly susceptible to mismatch repair errors in both wild type and ecm11 strains, but in ecm11 mutants many more recombination events fall into this inefficient repair category. Finally, we observe elevated post-meiotic segregation at THR1 in mutants with a dual deficiency in MutSγ-mediated crossover recombination and SC assembly, but not in the mlh3 mutant, which lacks MutSγ crossovers but has abundant SC. We propose that SC structure promotes efficient mismatch repair of joint molecule recombination intermediates resolved via both MutSγ-associated and MutSγ-independent pathways, and is the molecular basis for elevated post-meiotic segregation in both MutSγ crossover-proficient (ecm11, gmc2) and MutSγ crossover-deficient (msh4, zip3) strains.
A Longitudinal Study of Antimicrobial Resistance inEnterococcusspp. Isolated from a Beef Processing Plant and Retail Ground Beef
Authors: Holman Devin B. , Klima Cassidy L. , Gzyl Katherine E. , Zaheer Rahat , Service Cara , Jones Tineke H. , McAllister Tim A. 
Published: May 2021

ABSTRACTAntimicrobial use in food-producing animals has come under increasing scrutiny due to its potential association with antimicrobial resistance (AMR). Monitoring of AMR in indicator microorganisms such asEnterococcusspp. in meat production facilities and retail meat products can provide important information on the dynamics and prevalence of AMR in these environments. In this study, swabs or samples were obtained from various locations in a commercial beef packing operation (n = 600 total) and from retail ground beef (n = 60) over a 19-month period. All samples/swabs were enriched forEnterococcusspp. and suspected enterococci isolates were identified using species-specific PCR primers.Enterococcus faecaliswas the most frequently isolated species followed byEnterococcus hirae,which was found mostly on hides and ground beef.Enterococcus faecium(n = 9) andE.faecalis(n = 120) isolates were further characterized for antimicrobial resistance and resistant genes due to the clinical significance of these species. Twenty-one unique AMR profiles were identified, with 90% of isolates resistant to at least two antimicrobials, and two that were resistant to nine antimicrobials. Tetracycline resistance was observed most often inE.faecalis(28.8%) and was likely mediated bytet(M). Genomic analysis of selectedE.faecalisandE.faeciumisolates revealed that many of the isolates in this study clustered with other publicly available genomes from ground beef, suggesting that these strains are well adapted to the beef packaging environment.IMPORTANCEAntimicrobial resistance (AMR) is a serious challenge facing the agricultural industry. Understanding the flow of antimicrobial resistant-bacteria through the beef fabrication process and into ground beef is an important step in identifying intervention points for reducing AMR. In this study we used enterococci as indicator bacteria for monitoring AMR in a commercial beef packaging facility and in retail ground beef over a 19-month period. Although washing of carcasses post-hide removal reduced the isolation frequency ofEnterococcusspp., a number of antimicrobial resistant-Enterococcus faecalisisolates were recovered from ground beef produced in the packaging plant. Genome analysis showed that severalE.faecalisisolates were genetically similar to publicly available isolates recovered from retail ground beef in the United States.
Structural basis for recognition of anti-migraine drug lasmiditan by the serotonin receptor 5-HT1F–G protein complex
Authors: Huang Sijie , Xu Peiyu , Tan Yangxia , You Chongzhao , Zhang Yumu , Jiang Yi , Xu H. Eric 
Published: May 2021

AbstractMigraine headache has become global pandemics and is the number one reason of work day loss. The most common drugs for anti-migraine are the triptan class of drugs that are agonists for serotonin receptors 5-HT1B and 5-HT1D. However, these drugs have side effects related to vasoconstriction that could have fatal consequences of ischemic heart disease and myocardial infarction. Lasmiditan is a new generation of anti-migraine drug that selectively binds to the serotonin receptor 5-HT1F due to its advantage over the tripan class of anti-migraine drugs. Here we report the cryo-EM structure of the 5-HT1F in complex with Lasmiditan and the inhibitory G protein heterotrimer. The structure reveals the mechanism of 5-HT1F-selective activation by Lasmiditan and provides a template for rational design of anti-migraine drugs.
Genome of the giant panda roundworm illuminates its host shift and parasitic adaptation
Authors: Xie Yue , Wang Sen , Wu Shuangyang , Gao Shenghan , Meng Qingshu , Wang Chengdong , Lan Jingchao , Luo Li , Zhou Xuan , Xu Jing , Gu Xiaobin , He Ran , Yang Zijiang , Peng Xuerong , Hu Songnian , Yang Guangyou 
Published: May 2021

AbstractBaylisascaris schroederi, a bamboo-feeding giant panda (Ailuropoda melanoleuca)-specific roundworm (ascaridoid) parasite, is the causative agent of baylisascariasis, which represents a leading reason for the mortality of wild giant panda populations and therefore poses a significant threat to giant panda conservation. Here we present a 293-Mb chromosome-level genome assembly ofB. schroederito inform its biology, including host adaptations. Comparative genomics revealed an evolutionary trajectory accompanied by host-shift events in ascaridoid parasite lineages after host separations, suggesting their potential transmissions and fast adaptations to hosts. Genomic and anatomical lines of evidence, including expansion and positive selection of genes related to cuticle and basal metabolisms, indicates thatB. schroederiundergoes specific adaptations to survive in the sharp-edged bamboo enriched gut of giant panda by structurally increasing its cuticle thickness and efficiently utilizing host nutrients during gut parasitism. Also, we characterized the secretome and predicted potential drug and vaccine targets for new interventions. Overall, this genome resource provides new insights into the host adaptation ofB. schroederito giant panda as well as the host-shift events in ascaridoid parasite lineages. These findings also add to our knowledge on the unique biology of the giant panda roundworm and aid the development of much-needed novel strategies for the control of baylisascariasis and thus the protection of giant panda populations.
Refining conformational ensembles of flexible proteins against small-angle X-ray scattering data
Authors: Pesce Francesco , Lindorff-Larsen Kresten 
Published: May 2021

ABSTRACTIntrinsically disordered proteins and flexible regions in multi-domain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modelling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model, i.e. an algorithm to calculate experimental observables from individual conformations or ensembles. In many cases, this involve one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle X-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data, but across the entire ensemble. Here, we present a protocol to dissect the effect of free-parameters on the calculated SAXS intensities, and to identify a reliable set of values. We have implemented this procedure in our Bayesian/Maximum Entropy framework for ensemble refinement, and demonstrate the results on four intrinsically disordered proteins and a three-domain protein connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects, and suggests that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins.SIGNIFICANCEThe flexibility of a protein is often key to its biological function, yet understanding and characterizing its conformational heterogeneity is difficult. We here describe a robust protocol for combining small-angle X-ray scattering experiments with computational modelling to obtain a conformational ensemble. In particular, we focus on the contribution of protein hydration to the experiments and how this is included in modelling the data. Our resulting algorithm and software should make modelling intrinsically disordered proteins and multi-domain proteins more robust, thus aiding in understanding the relationship between protein dynamics and biological function.
Are plants in sown flower strips suitable for communities of wild bees? Pollination network approach in conservation biology
Authors: Hadrava Jiří , Talašová Anna , Straka Jakub , Benda Daniel , Kazda Jan , Klečka Jan 
Published: May 2021

AbstractDrastic reductions of insect diversity and abundance are observed in the highly fragmented agricultural landscapes of central Europe. Declines of pollinators may have detrimental effects on the reproduction of wild insect-pollinated plants as well as the yield of crops. In order to mitigate such impacts, sown flower strips on arable land within Agri-Environment Climate Schemes (AECS) are supported across EU countries. However, it is not clear whether sown flower strips provide equivalent benefits to wild flower-visiting insects as semi-natural habitats.Here, we apply plant-pollinator network approach to evaluate the function of sown flower strips for the communities of wild bees. We compared the structural characteristics and the robustness of plant-pollinator networks in sown flower strips and nearby semi-natural habitats. We also quantified the importance of individual plant species for bees based on simulations of plant-pollinator extinction cascades.We found that assemblages of plants and pollinators were less diverse in sown flower strips than in semi-natural habitats, more generalized, and more nested. However, we did not find any significant differences in network robustness to plant-pollinator coextinctions. Further, simulations revealed a large variation in the functional importance among plant species from both habitats.We conclude that although the analysis of network robustness suggested that plants in the sown flower strips and semi-natural habitats were functionally equivalent, this masked important differences among the two habitats. From the conservation point of view, semi-natural habitats were superior in supporting a more diverse community of solitary bees and bumblebees.
Automated segmentation of insect anatomy from micro-CT images using deep learning
Authors: Toulkeridou Evropi , Gutierrez Carlos Enrique , Baum Daniel , Doya Kenji , Economo Evan P. 
Published: May 2021

AbstractThree-dimensional (3D) imaging, such as micro-computed tomography (micro-CT), is increasingly being used by organismal biologists for precise and comprehensive anatomical characterization. However, the segmentation of anatomical structures remains a bottleneck in research, often requiring tedious manual work. Here, we propose a pipeline for the fully-automated segmentation of anatomical structures in micro-CT images utilizing state-of-the-art deep learning methods, selecting the ant brain as a test case. We implemented the U-Net architecture for 2D image segmentation for our convolutional neural network (CNN), combined with pixel-island detection. For training and validation of the network, we assembled a dataset of semi-manually segmented brain images of 94 ant species. The trained network predicted the brain area in ant images fast and accurately; its performance tested on validation sets showed good agreement between the prediction and the target, scoring 80% Intersection over Union (IoU) and 90% Dice Coefficient (F1) accuracy. While manual segmentation usually takes many hours for each brain, the trained network takes only a few minutes. Furthermore, our network is generalizable for segmenting the whole neural system in full-body scans, and works in tests on distantly related and morphologically divergent insects (e.g., fruit flies). The latter suggest that methods like the one presented here generally apply across diverse taxa. Our method makes the construction of segmented maps and the morphological quantification of different species more efficient and scalable to large datasets, a step toward a big data approach to organismal anatomy.
Interpretable Deep Learning for Breast Cancer Cell Phenotyping Using Diffraction Images from Lens-Free Digital In-Line Holography
Authors: Song Tzu-Hsi , Cao Mengzhi , Min Jouha , Im Hyungsoon , Lee Hakho , Lee Kwonmoo 
Published: May 2021

AbstractLens-free digital in-line holography (LDIH) offers a wide field of view at micrometer-scale resolution, surpassing the capabilities of lens-based microscopes, making it a promising diagnostic tool for high-throughput cellular analysis. However, the complex nature of holograms renders them challenging for human interpretation, necessitating time- consuming computational processing to reconstruct object images. To address this, we present HoloNet, a novel deep learning architecture specifically designed for direct analysis of holographic images from LDIH in cellular phenotyping. HoloNet extracts both global features from diffraction patterns and local features from convolutional layers, achieving superior performance and interpretability compared to other deep learning methods. By leveraging raw holograms of breast cancer cells stained with well-known markers ER/PR and HER2, HoloNet demonstrates its effectiveness in classifying breast cancer cell types and quantifying molecular marker intensities. Furthermore, we introduce the feature-fusion HoloNet model, which extracts diffraction features associated with breast cancer cell types and their marker intensities. This hologram embedding approach allows for the identification of previously unknown subtypes of breast cancer cells, facilitating a comprehensive analysis of cell phenotype heterogeneity, leading to precise breast cancer diagnosis.
The satiating power of sustainability: the effect of package sustainability on perceived satiation of healthy food
Authors: Donato Carmela , Barone Ada Maria , Romani Simona 
Published: May 2021

PurposeThis research investigates the influence of package sustainability on food satiation perception.Design/methodology/approachResearch hypotheses were tested through three experimental studies.FindingsThree experimental studies show that food quality is associated to higher perceived food satiation (preliminary study); that a food packaged in a sustainable package is perceived as more satiating than the same food packaged in a non-sustainable package and that this effect is explained by the higher perceived quality triggered by the presence of a sustainable package (Study 1); and that the positive relationship between higher perceived quality and perceived satiation is verified only for healthy but not for unhealthy foods (Study 2).Originality/valueThe present research advances knowledge on the highly debated issue of sustainable food packages. By proposing that consumers might perceive a healthy food presented in a sustainable package as more satiating, the authors show another extrinsic packaging cue modifying consumers' perception, namely package sustainability.