bluuebunny/crossref_metadata_2025_split huggingface dataset:
Site-specific analysis of the SARS-CoV-2 glycan shield
Authors: Watanabe Yasunori , Allen Joel D. , Wrapp Daniel , McLellan Jason S. , Crispin Max 
Published: March 2020

AbstractThe emergence of the betacoronavirus, SARS-CoV-2 that causes COVID-19, represents a significant threat to global human health. Vaccine development is focused on the principal target of the humoral immune response, the spike (S) glycoprotein, that mediates cell entry and membrane fusion. SARS-CoV-2 S gene encodes 22 N-linked glycan sequons per protomer, which likely play a role in immune evasion and occluding immunogenic protein epitopes. Here, using a site-specific mass spectrometric approach, we reveal the glycan structures on a recombinant SARS-CoV-2 S immunogen. This analysis enables mapping of the glycan-processing states across the trimeric viral spike. We show how SARS-CoV-2 S glycans differ from typical host glycan processing, which may have implications in viral pathobiology and vaccine design.
Testing theoretical minimal genomes using whole-cell models
Authors: Rees-Garbutt Joshua , Rightmyer Jake , Chalkley Oliver , Marucci Lucia , Grierson Claire 
Published: March 2020

AbstractThe minimal gene set for life has often been theorised, with at least ten produced forMycoplasma genitalium(M. genitalium). Due to the difficulty of usingM. genitaliumin the lab, combined with its long replication time of 12 - 15 hours, none of these theoretical minimal genomes have been tested, even with modern techniques. The publication of theM. genitaliumwhole-cell model provided the first opportunity to test them, simulating the genome editsin-silico. We simulated eight minimal gene sets from the literature, finding that they producedin-silicocells that did not divide. Using knowledge from previous research, we reintroduced specific essential and low essential genesin-silico; enabling cellular division. This reinforces the need to identify species-specific low essential genes and their interactions. Any genome designs created using the currently incomplete and fragmented gene essentiality information, will very likely requirein-vivoreintroductions to correct issues and produce dividing cells.
A Chlorophyte alga utilizes alternative electron transport for primary photoprotection
Authors: Ware Maxwell A. , Hunstiger Darcy , Cantrell Michael , Peers Graham 
Published: March 2020

AbstractDesmodesmus armatusis an emerging biofuel platform producing high amount of lipids and biomass in mass culture. We observedD. armatusin light-limiting, excess light and sinusoidal light environments to investigate its photoacclimation behaviors and the mechanisms by which it dissipates excess energy. Chlorophylla:bratios and the functional absorption cross section of photosystem II (PSII) suggested a constitutively small light harvesting antenna size relative to other green algae.In situandex situmeasurements of photo-physiology revealed that nonphotochemical quenching (NPQ) is not a significant contributor to photoprotection, but cells do not suffer substantial photoinhibition despite its near absence. We performed membrane inlet mass spectrometry analysis to show thatD. armatushas a very high capacity for alternative electron transport (AET) measured as light dependent oxygen consumption. Up to 90% of electrons generated at PSII can be dissipated by AET in a water-water cycle during growth in rapidly fluctuating light environments like those found in industrial scale photobioreactors. This work highlights the diversity of photoprotective mechanisms shown in algal systems, that NPQ is not necessarily required for effective photoprotection in some algae and suggests that engineering AET may be an attractive target for increasing biomass productivity of some strains.One-sentence summaryConstitutive small antennae, alternative electron transport and an efficient photosystem II turnover capacity enableD. armatusto photosynthesize efficiently.
Analysis of computational codon usage models and their association with translationally slow codons
Authors: Wright Gabriel , Rodriguez Anabel , Li Jun , Clark Patricia L. , Milenković Tijana , Emrich Scott 
Published: March 2020

AbstractImproved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely ongenome-widecodon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only inhighly expressedgenes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments fromS. cerevisiae, because RFP data is often considered as a “ground truth” for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.
Amino acid quality modifies the quantitative availability of protein for reproduction inDrosophila melanogaster
Authors: Ma Carolyn , Mirth Christen K. , Hall Matthew D. , Piper Matthew D.W. 
Published: March 2020

AbstractDiet composition, especially the relative abundance of key macronutrients, is well known to affect animal wellbeing by changing reproductive output, metabolism and length of life. However, less attention has been paid to the ways the quality of these nutrients modify these macronutrient interactions. Nutritional Geometry can be used to model the effects of multiple dietary components on life-history traits and to compare these responses when diet quality is varied. Previous studies have shown that dietary protein quality can be increased for egg production inDrosophila melanogasterby matching the dietary amino acid proportions to the balance of amino acids used by the sum of proteins in the fly’sin silicotranslated exome. Here, we show that dietary protein quality dramatically alters the effect of protein quantity on female reproduction across a broad range of diets varying in both protein and carbohydrate concentrations. These data show that when sources of ingredients vary, their relative value to the consumer can vastly differ and yield very different physiological outcomes. Such variations could be particularly important for meta analyses that look to draw generalisable conclusions from diverse studies.
A global Ramachandran score identifies protein structures with unlikely stereochemistry
Authors: Sobolev Oleg V. , Afonine Pavel V. , Moriarty Nigel W. , Hekkelman Maarten L. , Joosten Robbie P. , Perrakis Anastassis , Adams Paul D. 
Published: March 2020

SummaryRamachandran plots report the distribution of the (φ, Ψ) torsion angles of the protein backbone and are one of the best quality metrics of experimental structure models. Typically, validation software reports the number of residues belonging to “outlier”, “allowed” and “favored” regions. While “zero unexplained outliers” can be considered the current “gold standard”, this can be misleading if deviations from expected distributions, even within the favored region, are not considered. We therefore revisited the Ramachandran Z-score (Rama-Z), a quality metric introduced more than two decades ago, but underutilized. We describe a re-implementation of the Rama-Z score in the Computational Crystallography Toolbox along with a new algorithm to estimate its uncertainty for individual models; final implementations are available both in Phenix and in PDB-REDO. We discuss the interpretation of the Rama-Z score and advocate including it in the validation reports provided by the Protein Data Bank. We also advocate reporting it alongside the outlier/allowed/favored counts in structural publications.
Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce
Authors: Zhou Linghua , Chen Zhiqiang , Olsson Lars , Grahn Thomas , Karlsson Bo , Wu Harry X. , Lundqvist Sven-Olof , García-Gil María Rosario 
Published: March 2020

AbstractGenomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce(Picea abies(L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. GS predictive abilities were comparable with those based on pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Use of different statistical methods had no significant impact on the estimated PAs. We also compared the abilities to predict density, MFA and MOE of 19 year old trees with models trained on data from coring at different ages and to different depths into the stem. 78-95% of the maximal PAs obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12, thereby shortening the cycle and reducing the impact on the tree.
The Nucleocapsid Protein of SARS-CoV-2 Abolished Pluripotency in Human Induced Pluripotent Stem Cells
Authors: Lin Zebin , Wu Zhiming , Mai Jinlian , Zhou Lishi , Qian Yu , Cai Tian , Chen Zhenhua , Wang Ping , Lin Bin 
Published: March 2020

AbstractThe COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is raging across the world, leading to a global mortality rate of 3.4% (estimated by World Health Organization in March 2020). As a potential vaccine and therapeutic target, the nucleocapsid protein of SARS-CoV-2 (nCoVN) functions in packaging the viral genome and viral self-assembly. To investigate the biological effects of nCoVN to human stem cells, genetically engineered human induced pluripotent stem cells (iPSC) expressing nCoVN (iPSC-nCoVN) were generated by lentiviral expression systems, in which the expression of nCoVN could be induced by the doxycycline. The proliferation rate of iPSC-nCoVN was decreased. Unexpectedly, the morphology of iPSC started to change after nCoVN expression for 7 days. The pluripotency marker TRA-1-81 were not detectable in iPSC-nCoVN after a four-day induction. Meanwhile, iPSC-nCoVN lost the ability for differentiation into cardiomyocytes with a routine differentiation protocol. The RNA-seq data of iPSC-nCoVN (induction for 30 days) and immunofluorescence assays illustrated that iPSC-nCoVN were turning to fibroblast-like cells. Our data suggested that nCoVN disrupted the pluripotent properties of iPSC and turned them into other types of cells, which provided a new insight to the pathogenic mechanism of SARS-CoV-2.
Comparative effects of oncogenic mutations G12C, G12V, G13D, and Q61H on local conformations and dynamics of K-Ras
Authors: Vatansever Sezen , Erman Burak , Gümüş Zeynep H. 
Published: March 2020

ABSTRACTK-Ras is the most frequently mutated protein in human cancers. However, until very recently, its oncogenic mutants were viewed as undruggable. To develop inhibitors that directly target oncogenic K-Ras mutants, we need to understand both their mutant-specific and pan-mutant dynamics and conformations. Recently, we have investigated how the most frequently observed K-Ras mutation in cancer patients, G12D, changes its local dynamics and conformations1. Here, we extend our analysis to study and compare the local effects of other frequently observed oncogenic mutations, G12C, G12V, G13D and Q61H. For this purpose, we have performed Molecular Dynamics (MD) simulations of each mutant when active (GTP-bound) and inactive (GDP-bound), analyzed their trajectories, and compared how each mutant changes local residue conformations, inter-protein distance distributions, local flexibility and residue pair correlated motions. Our results reveal that in the four active oncogenic mutants we have studied, the α2 helix moves closer to the C-terminal of the α3 helix. However, P-loop mutations cause α3 helix to move away from Loop7, and only G12 mutations change the local conformational state populations of the protein. Furthermore, the motions of coupled residues are mutant-specific: G12 mutations lead to new negative correlations between residue motions, while Q61H destroys them. Overall, our findings on the local conformational states and protein dynamics of oncogenic K-Ras mutants can provide insights for both mutant-selective and pan-mutant targeted inhibition efforts.
A Reference Feature based method for Quantification and Identification of LC-MS based untargeted metabolomics
Authors: Luan Enhui , Cheng Ken , Long Qiaoyun , Li Dehua , Li Zhenyu , Liu Binghang , Wang Yalan , Li Wei , Guo Baosen , Tan Fengji , Yi Xiaoyi , Feng Lei , Song Jiaping , Zheng Hancheng 
Published: March 2020

AbstractBatch inconsistency is a major problem when applying LC-MS based untargeted metabolomics in real-time analysis situation such as clinical diagnosis or health monitoring. And inefficiency of collecting MS2 is a major problem for metabolite identification. Here, we developed a reference-feature based quantification and identification strategy (RFQI). In RFQI, samples are individually profiled using a pre-fixed reference feature table. Quantification results show that RFQI improves features’ overlap rate and reduce variance across batches significantly in real-time-analysis mode, and can find more than 4-fold numbers of features. Besides, RFQI collects MS2 from consecutive increasing samples for metabolite identification of pre-fixed features, thus it can effectively compensate for the poor efficiency of MS2 collection in data-dependent acquisition mode. In summary, RFQI can make full advantage of consecutive increasing samples in real-time analysis situation, both for quantification and identification.
Identification and Expression Analysis of Heat Shock Proteins in Wheat Infected with Powdery Mildew and Stripe Rust
Authors: Zhang Hong , Guo Huan , Wang Guanghao , Wang Changyou , Wang Yajuan , Liu Xinlun , Ji Wanquan 
Published: March 2020

AbstractHeat shock proteins (HSPs), which are encoded by conserved gene families in plants, are crucial for development and responses to diverse stresses. However, the wheat (Triticum aestivum) HSPs have not been systematically classified, especially those involved in protecting plants from disease. Here, we classified 119 DnaJ (Hsp40) proteins (TaDnaJs; encoded by 313 genes) and 41 Hsp70 proteins (TaHsp70s; encoded by 95 genes) into six and four groups, respectively, via a phylogenetic analysis. An examination of protein structures and a multiple sequence alignment revealed diversity in the TaDnaJ structural organization, but a highly conserved J-domain, which was usually characterized by an HPD motif followed by DRD or DED motifs. The expression profiles of these HSP-encoding homologous genes varied in response toBlumeria graminisf. sp.triticiandPuccinia striiformisf. sp.tritici. A quantitative real-time PCR analysis indicated a lack of similarity in the expression ofDnaJ70b, Hsp70-30b, andHsp90-4bin wheat infected byB. graminisf. sp.tritici, although the expression levels of these genes were abnormal in the infected resistant and susceptible lines. Furthermore, a direct interaction between DnaJ70 and TaHsp70-30 was not detected in a yeast two-hybrid assay. This study revealed the structure and expression profiles of the HSP-encoding genes in wheat. The resulting data may be useful for future functional analyses and for further elucidating the roles of wheat HSPs during responses to fungal infections.
Pseudomonas aeruginosaenhances the efficacy of norfloxacin againstStaphylococcus aureusbiofilms
Authors: Orazi Giulia , Jean-Pierre Fabrice , O’Toole George A. 
Published: March 2020

AbstractThe thick mucus within the airways of individuals with cystic fibrosis (CF) promotes frequent respiratory infections that are often polymicrobial.Pseudomonas aeruginosaandStaphylococcus aureusare two of the most prevalent pathogens that cause CF pulmonary infections, and both have been associated with worse lung function. Furthermore, the ability ofP. aeruginosaandS. aureusto form biofilms promotes the establishment of chronic infections that are often difficult to eradicate using antimicrobial agents. In this study, we found that multiple LasR-regulated exoproducts ofP. aeruginosa, including HQNO, siderophores, phenazines, and rhamnolipids, likely contribute to the ability ofP. aeruginosato shiftS. aureusnorfloxacin susceptibility profiles. Here, we observe that exposure toP. aeruginosaexoproducts leads to an increase in intracellular norfloxacin accumulation byS. aureus. We previously showed thatP. aeruginosasupernatant dissipatesS. aureusmembrane potential, and furthermore, depletion of theS. aureusproton-motive force recapitulates the effect ofP. aeruginosasupernatant on shifting norfloxacin sensitivity profiles of biofilm-grownS. aureus. From these results, we hypothesize that exposure toP. aeruginosaexoproducts leads to increased uptake of the drug and/or an impaired ability ofS. aureusto efflux norfloxacin. Our results illustrate that microbially-derived products can greatly alter the ability of antimicrobial agents to kill bacterial biofilms.ImportancePseudomonas aeruginosaandStaphylococcus aureusare frequently co-isolated from multiple infection sites, including the lungs of individuals with cystic fibrosis (CF) and non-healing diabetic foot ulcers. Co-infection withP. aeruginosaandS. aureushas been shown to produce worse outcomes compared to infection with one organism alone. Furthermore, the ability of these pathogens to form biofilms enables them to cause persistent infection and withstand antimicrobial therapy. In this study, we found thatP. aeruginosa-secreted products dramatically increase the ability of the antibiotic norfloxacin to killS. aureusbiofilms. Understanding how interspecies interactions alter the antibiotic susceptibility of bacterial biofilms may inform treatment decisions and inspire the development of new therapeutic strategies.
Sterol-response pathways mediate alkaline survival in diverse fungi
Authors: Brown Hannah E. , Telzrow Calla L. , Saelens Joseph W. , Fernandes Larissa , Alspaugh J. Andrew 
Published: March 2020

AbstractThe ability for cells to maintain homeostasis in the presence of extracellular stress is essential for their survival. Stress adaptations are especially important for microbial pathogens to respond to rapidly changing conditions, such as those encountered during the transition from the environment to the infected host. Many fungal pathogens have acquired the ability to quickly adapt to changes in extracellular pH to promote their survival in the various micro-environments encountered during a host infection. For example, the fungal-specific Rim/Pal alkaline response pathway has been well characterized in many fungal pathogens, includingCryptococcus neoformans. However, alternative mechanisms for sensing and responding to host pH have yet to be extensively studied. Recent observations from a genetic screen suggest that theC. neoformanssterol homeostasis pathway is required for growth at elevated pH. This work explores interactions among mechanisms of membrane homeostasis, alkaline pH tolerance, and Rim pathway activation. We find that the sterol homeostasis pathway is necessary for growth in an alkaline environment, and that an elevated pH is sufficient to induce Sre1 activation. This pH-mediated activation of the Sre1 transcription factor is linked to the biosynthesis of ergosterol, but is not dependent on Rim pathway signaling, suggesting that these two pathways are responding to alkaline pH independently. Furthermore, we discover thatC. neoformansis more susceptible to membrane-targeting antifungals in alkaline conditions highlighting the impact of micro-environmental pH on the treatment of invasive fungal infections. Together, these findings further connect membrane integrity and composition with the fungal pH response and pathogenesis.
SARS-CoV-2 proteome microarray for mapping COVID-19 antibody interactions at amino acid resolution
Authors: Wang Hongye , Hou Xin , Wu Xian , Liang Te , Zhang Xiaomei , Wang Dan , Teng Fei , Dai Jiayu , Duan Hu , Guo Shubin , Li Yongzhe , Yu Xiaobo 
Published: March 2020

AbstractCOVID-19 has quickly become a worldwide pandemic, which has significantly impacted the economy, education, and social interactions. Understanding the humoral antibody response to SARS-CoV-2 proteins may help identify biomarkers that can be used to detect and treat COVID-19 infection. However, no immuno-proteomics platform exists that can perform such proteome-wide analysis. To address this need, we created a SARS-CoV-2 proteome microarray to analyze antibody interactions at amino acid resolution by spotting peptides 15 amino acids long with 5-amino acid offsets representing full-length SARS-CoV-2 proteins. Moreover, the array processing time is short (1.5 hours), the dynamic range is ~2 orders of magnitude, and the lowest limit of detection is 94 pg/mL. Here, the SARS-CoV-2 proteome array reveals that antibodies commercially available for SARS-CoV-1 proteins can also target SARS-CoV-2 proteins. These readily available reagents could be used immediately in COVID-19 research. Second, IgM and IgG immunogenic epitopes of SARS-CoV-2 proteins were profiled in the serum of ten COVID-19 patients. Such epitope biomarkers provide insight into the immune response to COVID-19 and are potential targets for COVID-19 diagnosis and vaccine development. Finally, serological antibodies that may neutralize viral entry into host cells via the ACE2 receptor were identified. Further investigation into whether these antibodies can inhibit the propagation of SARS-CoV-2 is warranted. Antibody and epitope profiling in response to COVID-19 is possible with our peptide-based SARS-COV-2 proteome microarray. The data gleaned from the array could provide invaluable information to the scientific community to understand, detect, and treat COVID-19.