bluuebunny/crossref_metadata_2025_split huggingface dataset:
The D614G virus mutation enhances anosmia in COVID-19 patients: Evidence from a systematic review and meta-analysis of studies from South Asia
Authors: von Bartheld Christopher S. , Hagen Molly M. , Butowt Rafal 
Published: August 2021

AbstractThe prevalence of chemosensory dysfunction in patients with COVID-19 varies greatly between populations. It is unclear whether such differences are due to factors at the level of the human host, or at the level of the coronavirus, or both. At the host level, the entry proteins which allow virus binding and entry have variants with distinct properties, and the frequency of such variants differs between ethnicities. At the level of the virus, the D614G mutation enhances virus entry to the host cell. Since the two virus strains (D614 and G614) co-existed in the first six months of the pandemic in most populations, it has been difficult to distinguish between contributions of the virus and contributions of the host for anosmia. To answer this question, we conducted a systematic review and meta-analysis of studies in South Asian populations when either the D614 or the G614 virus was dominant. We show that populations infected predominantly with the G614 virus had a much higher prevalence of anosmia (pooled prevalence of 31.8%) compared with the same ethnic populations infected mostly with the D614 virus strain (pooled anosmia prevalence of 5.3%). We conclude that the D614G mutation is a major contributing factor that increases the prevalence of anosmia in COVID-19, and that this enhanced effect on olfaction constitutes a previously unrecognized phenotype of the D614G mutation. The new virus strains that have additional mutations on the background of the D614G mutation can be expected to cause a similarly increased prevalence of chemosensory dysfunctions.Graphical Abstract
Non-mycorrhizal root associated fungi of a tropical montane forest are relatively robust to the long-term addition of moderate rates of nitrogen and phosphorus
Authors: Dueñas Juan F. , Hempel Stefan , Homeier Jürgen , Suárez Juan Pablo , Rillig Matthias C. , Camenzind Tessa 
Published: August 2021

AbstractAndean forests are biodiversity hotspots and globally important carbon (C) repositories. This status might be at risk due to increasing rates of atmospheric nutrient deposition. As fungal communities are key in the recirculation of soil nutrients, assessing their responses to soil eutrophication can help establish a link between microbial biodiversity and the sustainability of the C sink status of this region. Beyond mycorrhizal fungi, which have been studied more frequently, a wide range of other fungi associate with the fine root fraction of trees. Monitoring these communities can offer insights into how communities composed of both facultative and obligate root associated fungi are responding to soil eutrophication.Here we document the response of non-mycorrhizal root associated fungal (RAF) communities to a long-term nutrient manipulation experiment. The stand level fine root fraction of an old growth tropical montane forest was sampled after seven years of nitrogen (N) and phosphorus (P) additions. RAF communities were characterized by a deep sequencing approach. As per the resource imbalance model, we expected that asymmetries in the availability of C, N and P elicited by fertilization will lead to mean richness reductions and alterations of the community structure.We recovered moderately diverse fungal assemblages composed by sequence variants classified within a wide set of trophic guilds. While mean richness remained stable, community composition shifted, particularly among Ascomycota and after the addition of P. Fertilization factors, however, only accounted for a minor proportion of the variance in community composition. These findings suggest that, unlike mycorrhizal fungi, RAF communities are less sensitive to shifts in soil nutrient availability. A plausible explanation is that non-mycorrhizal RAF have fundamentally different nutrient acquisition and life history traits, thus allowing them greater stoichiometric plasticity and an array of functional acclimation responses that collectively express as subtle shifts in community level attributes.
Invalidity of light sensor data in field studies and a proposal of an algorithmic approach for detection and filtering of non-wear time
Authors: Hunt Larissa C. , Fritz Josef , Herf Michael , Herf Lorna , Vetter Celine 
Published: August 2021

ABSTRACTWearable light sensors are increasingly used in intervention and population-based studies investigating the consequences of environmental light exposure on human physiology. An important step in such analyses is the reliable detection of non-wear time. We observed in light data that days with less wear-time also have lower variability in the light signal, and we sought to test if the standard deviation of the change between subsequent samples can detect this condition. In this study, we propose and validate an easy-to-implement algorithm designed to discriminate between days with a non-wear time >4h (“invalid days”) vs. ≤4h (“valid days”) and investigate to which extent values of commonly used physiologically meaningful light variables differ between invalid days, valid days, and algorithm-selected non-wear days. We used 83 days of light data from a field study with high participant compliance, complemented by 47 days of light data where free-living individuals were instructed not to wear the sensor for varying amounts of time. Light data were recorded every two minutes using the pendant-worn f.luxometer light sensor; validity was derived from daily logs where participants recorded all non-wear time. The algorithm-derived score discriminated well between valid and invalid days (area under the curve (AUC): 0.77, 95% CI: 0.67-0.87). The best cut-off value (i.e., highest Youden index) correctly recognized valid days with a probability of 87% (“sensitivity”), and invalid days with a probability of 63% (“specificity”). Values of various light variables derived from algorithm-selected days only (median: 264.3 (Q1: 153.6, Q3: 420.0) for 24h light intensity (in lux); 496.0 (404.0, 582.0) for time spent above 50-lux) gave values close to those derived from self-reported valid days only. However, these values did not significantly differ when derived across all days compared to self-reported valid days. Our results suggest that our proposed algorithm discriminates well between valid and invalid days. However, in high compliance cohorts, distortions in aggregated light measures of individual-level environmental light recordings across days appear to be small, making the application of our algorithm optional, but not necessary.
Whole genome analysis for 163 guide RNAs in Cas9 edited mice reveals minimal off-target activity
Authors: Peterson Kevin A. , Khalouei Sam , Wood Joshua A. , Lanza Denise G. , Lintott Lauri G. , Willis Brandon J. , Seavitt John R. , Hanafi Nour , Braun Robert E. , Dickinson Mary E. , White Jacqueline K. , Lloyd K.C. Kent , Heaney Jason D. , Murray Stephen A. , Ramani Arun , Nutter Lauryl M.J. 
Published: August 2021

Introductory ParagraphThe Knockout Mouse Phenotyping Program (KOMP2) uses CRISRPR/Cas9 for high-throughput mouse line production to generate null alleles in the inbred C57BL/6N strain for broad-based in vivo phenotyping. In order to assess the risk of spurious S. pyogenes Cas9-induced off-target mutagenesis, we applied whole genome sequencing to compare the genomes of 50 Cas9-derived founder mice representing 163 different gRNAs to 28 untreated inbred control mice. Our analysis pipeline detected 28 off-target sequence variants associated with 21 guides. These potential off-targets were identified in 18/50 (36%) founders with 9/28 (32%) independently validated corresponding to 8 founder animals. In total, only 4.9% (8/163) of all guides exhibited off-target activity resulting in a rate of 0.16 Cas9 off-target mutations per founder analyzed. In comparison, we observed ~1225 unique variants in each mouse regardless of whether or not it was exposed to Cas9. These findings indicate that Cas9-mediated off-target mutagenesis is rare in founder knockout mice generated using guide RNAs designed to minimize off-target risk. Overall, bona fide off-target variants comprise a small fraction of the genetic heterogeneity found in carefully maintained colonies of inbred strains.
Site Pattern Probabilities Under the Multispecies Coalescent and a Relaxed Molecular Clock: Theory and Applications
Authors: Richards A. , Kubatko L. 
Published: August 2021

1AbstractThe first step in statistical inference of the evolutionary histories of species is developing a probability model that describes the mutation process as accurately and realistically as possible. A major complication of this inference is that different loci on the genome can have histories that diverge from the common species history and each other. The multispecies coalescent process is commonly used to model one source of this divergence, incomplete lineage sorting, or ILS. Chifman and Kubatko (2015) computed the site pattern probabilities for four taxa under a full probability model based on the Jukes-Cantor substitution model when the molecular clock holds. This paper generalizes that work to a relaxed clock model, allowing for mutation rates to differ among species. This will enable better phylogentic inference in cases where the molecular clock does not hold.
Cross-sectional genomic perspective of epidemic waves of SARS-CoV-2: a pan India study
Authors: Kumar Sanjeet , Bansal Kanika 
Published: August 2021

AbstractCOVID-19 has posed unforeseen circumstances and throttled major economies worldwide. India has witnessed two waves affecting around 31 million people representing 16% of the cases globally. To date, the epidemic waves have not been comprehensively investigated to understand pandemic progress in India. In the present study, we aim for a cross-sectional analysis since its first incidence up to 26th July 2021. We have performed the pan Indian evolutionary study using 20,086 high-quality complete genomes of SARS-CoV-2. Based on the number of cases reported and mutation rates, we could divide the Indian epidemic into seven different phases. First, three phases constituting the pre-first wave had a very less average mutation rate (<11), which increased in the first wave to 17 and then doubled in the second wave (~34). In accordance with the mutation rate, variants of concern (alpha, beta, gamma and delta) and interest (eta and kappa) also started appearing in the first wave (1.5% of the genomes), which dominated the second (~96% of genomes) and post-second wave (100% of genomes) phases. Whole genome-based phylogeny could demarcate the post-first wave isolates from previous ones by the point of diversification leading to incidences of VOCs and VOIs in India. Nation-wide mutational analysis depicted more than 0.5 million events with four major mutations in ~97% of the total 20,086 genomes in the study. These included two mutations in coding (spike (D614G) and NSP 12b (P314L) of RNA dependent RNA polymerase), one silent mutation (NSP3 F106F) and one extragenic mutation (5’ UTR 241). Large scale genome-wide mutational analysis is crucial in expanding knowledge on evolution of deadly variants of SARS-CoV-2 and timely management of the pandemic.
Investigate Inhibitory Effects of Ginger polyphenols compare to Simvastatin towards HMG-CoA reductase: An Integrated Molecular Docking and Molecular dynamic simulation
Authors: Belachew Aweke Mulu , Feyisa Asheber , Ufgaa Mulugeta Gajaa , Yesuf Teslim Yimama 
Published: August 2021

AbstractDiabetes is an increasing problem in Ethiopia, affecting up to 6.5% of Ethiopian adults. There are serious complications associated with diabetes including macrovascular and microvascular. Controlling Lipid profiles and blood glucose significantly reduces the risk of complications. Statins are the only current treatment for both type 1 diabetes and Type 2 diabetes dyslipidemia. HMG-CoA reductase plays a central role in the production of cholesterol which, associated with cardiovascular disease (CVD). Statins have been found to reduce cardiovascular disease and mortality in those who are at high risk. Nonetheless, it has adverse effect, such as drug-related hypoglycemia and high cost. These situations lead to develop suitable phytotherapeutic agents with less frequent side effects. Ginger (Zingiber officinale) is widely consumed as a spice, and numerous studies suggest that ginger may have beneficial effects for diabetes and dyslipidemia. But, further studies are needed to investigate effects of binding affinity and binding site residues for major ginger extract polyphenols towards target HMG-CoA reductase. In this study, ADMET web server, Auto-Dock 5.4 and Gromacs 2020 were used. Out of eleven major gingers polyphenols screened three selected based on docking energy compare to Simvastatin for MD simulation. The predicted binding affinity for 6-paradol, 6-shogaol and gingerdione were −8.51, −6.93, −9.24 kcal/mol, respectively. The results of molecular dynamic simulation are consistence with docking. The predicted ligand binding site residues are Arg641, Gly808, Arg641, Met781, Ser794 and Arg595. In conclusion, 6-paradol, 6-shogaol and gingerdione could be possible therapy because, of interactions with target HMG-CoA reductase. Therefore, further wet lab study will be needed, for the better understanding of the mechanism of action of ginger extract by which it modulates liver and kidney vivo condition.
Reference genome and resequencing of 305 accessions provide insights into spinach evolution, domestication and genetic basis of agronomic traits
Authors: Cai Xiaofeng , Sun Xuepeng , Xu Chenxi , Sun Honghe , Wang Xiaoli , Ge Chenhui , Zhang Zhonghua , Wang Quanxi , Fei Zhangjun , Jiao Chen , Wang Quanhua 
Published: August 2021

AbstractSpinach is a nutritious leafy vegetable belonging to the family Chenopodiaceae. Here we report a chromosome-scale reference genome assembly of spinach, which has a total size of 894.3 Mb and an N50 contig size of 23.8 Mb, with 98.3% anchored and ordered on the six chromosomes. Reconstruction of ancestral Chenopodiaceae karyotype indicates substantial genome rearrangements in spinach after its divergence from ancestral Chenopodiaceae, coinciding with high repeat content in the spinach genome. Resequencing the genomes of 305 cultivated and wild spinach accessions provides insights into spinach genetic diversity and population differentiation. Genome-wide association studies of 20 agronomical traits identify numerous significantly associated regions and candidate genes for these traits. Domestication sweeps in the spinach genome are identified, some of which are associated with important traits (e.g., leaf phenotype, bolting and flowering), demonstrating the role of artificial selection in shaping spinach phenotypic evolution. This study provides not only insights into the spinach evolution and domestication but also valuable resources for facilitating spinach breeding.
The Proteomic Architecture of Schizophrenia Cerebral Organoids Reveals Alterations in GWAS and Neuronal Development Factors
Authors: Notaras Michael , Lodhi Aiman , Fang Haoyun , Greening David , Colak Dilek 
Published: August 2021

ABSTRACTSchizophrenia (Scz) is a brain disorder that has a typical onset in early adulthood but otherwise maintains unknown disease origins. Unfortunately, little progress has been made in understanding the molecular mechanisms underlying neurodevelopment of Scz due to ethical and technical limitations in accessing developing human brain tissue. To overcome this challenge, we have previously utilized patient-derived Induced Pluripotent Stem Cells (iPSCs) to generate self-developing, self-maturating, and self-organizing 3D brain-like tissue known as cerebral organoids. As a continuation of this prior work [1], here we provide a molecular architectural map of the developing Scz organoid proteome. Utilizing iPSCs fromn= 25 human donors (n= 8 healthy Ctrl donors, andn= 17 Scz patients), we generated 3D human cerebral organoids, employed 16-plex isobaric sample-barcoding chemistry, and simultaneously subjected samples to comprehensive high-throughput liquid-chromatography/mass-spectrometry (LC/MS) quantitative proteomics. Of 3,705 proteins identified by high-throughput proteomic profiling, we identified that just ~2.62% of the organoid global proteomic landscape was differentially regulated in Scz organoids. In sum, just 43 proteins were up-regulated and 54 were down-regulated in Scz patient-derived organoids. Notably, a range of neuronal factors were depleted in Scz organoids (e.g., MAP2, TUBB3, SV2A, GAP43, CRABP1, NCAM1 etc.). Based on global enrichment analysis, alterations in key pathways that regulate nervous system development (e.g., axonogenesis, axon development, axon guidance, morphogenesis pathways regulating neuronal differentiation, as well as substantia nigra development) were perturbed in Scz patient-derived organoids. We also identified prominent alterations in two novel GWAS factors, Pleiotrophin (PTN) and Podocalyxin (PODXL), in Scz organoids. In sum, this work serves as both a report and a resource whereby researchers can leverage human-derived neurodevelopmental data from Scz patients, which can be used to mine, compare, contrast, or orthogonally validate novel factors and pathways related to Scz risk identified in datasets from observational clinical studies and other model systems.
CsrA-controlled proteins reveal new dimensions of Acinetobacter baumannii desiccation tolerance
Authors: Oda Yasuhiro , Shapiro Madelyn M. , Lewis Nathan M. , Zhong Xuefei , Huse Holly K. , Zhong Weizhi , Bruce James E. , Manoil Colin , Harwood Caroline S. 
Published: August 2021

ABSTRACTHospital environments are excellent reservoirs for the opportunistic pathogen Acinetobacter baumannii in part because it is exceptionally tolerant to desiccation. We found that relative to other A. baumannii strains, the virulent strain AB5075 was strikingly desiccation resistant at 2% relative humidity (RH), suggesting that it’s a good model for studies of the functional basis of this trait. Consistent with results from other A. baumannii strains at 30% RH, we found the global post-transcriptional regulator CsrA to be critically important for desiccation tolerance of AB5075 at 2% RH. To identify CsrA-controlled proteins that may contribute to desiccation tolerance we used proteomics to identify proteins that were differentially present in wild type and csrA mutant cells. Subsequent mutant analysis revealed nine genes that were required for wild type levels of desiccation tolerance, five of which had modest phenotypes. Catalase and a universal stress protein gene were moderately important for desiccation tolerance and two genes of unknown function had very strong desiccation phenotypes. The predicted amino acid sequence of one of these genes predicts an intrinsically disordered protein. This category of proteins is widespread in eukaryotes but less so in prokaryotes. Our results suggest there may be mechanisms responsible for desiccation tolerance that have not previously been explored in bacteria.IMPORTANCEAcinetobacter baumannii is commonly found in terrestrial environments but can cause nosocomial infections in very sick patients. A factor that contributes to the prevalence of A. baumannii in hospital settings is that it is intrinsically resistant to dry conditions. Here, we established the virulent strain A. baumannii AB5075 as a model for studies of desiccation tolerance at very low relative humidity. Our results show that this trait depends on two proteins of unknown function, one of which is predicted to be an intrinsically disordered protein. This category of protein is critical for the small animals named tardigrades to survive desiccation. Our results suggest that A. baumannii may have novel strategies to survive desiccation that have not previously been seen in bacteria.
Refining Bulk Segregant Analyses: Ontology-Mediated Discovery of Flowering Time Genes in Brassica oleracea
Authors: Vos Rutger A. , van der Veen-van Wijk Catharina A. M. , Schranz M. Eric , Vrieling Klaas , Klinkhamer Peter G. L. , Lens Frederic 
Published: August 2021

AbstractBackgroundBulk segregant analysis (BSA) can help identify quantitative trait loci (QTLs), but this may result in substantial bycatch of functionally irrelevant genes. Here we develop a Gene Ontology-mediated approach to zoom in on specific markers implicated in flowering time from among QTLs identified by BSA of the giant woody Jersey kale phenotyped in four bulks of flowering onset.ResultsOur BSA yielded tens of thousands of candidate genes. We reduced this by two orders of magnitude by focusing on genes annotated with terms contained within relevant subgraphs of the Gene Ontology. A further enrichment test led to the pathway for circadian rhythm in plants. The genes that enriched this pathway are attested from previous research as regulating flowering time. Some of these genes were also identified as having functionally significant variation compared to ArabidopsisConclusionsWe validated and confirmed our ontology-mediated results through a more targeted, homology-based approach. However, our ontology-mediated approach produced additional genes of putative importance, showing that the approach aids in exploration and discovery. We view our method as potentially applicable to the study of other complex traits and therefore make our workflows available as open-source code and a reusable Docker container.
Looking at the BiG picture: Incorporating bipartite graphs in drug response prediction
Authors: Hostallero David Earl , Li Yihui , Emad Amin 
Published: August 2021

ABSTRACTMotivationThe increasing number of publicly available databases containing drugs’ chemical structures, their response in cell lines, and molecular profiles of the cell lines has garnered attention to the problem of drug response prediction. However, many existing methods do not fully leverage the information that is shared among cell lines and drugs with similar structure. As such, drug similarities in terms of cell line responses and chemical structures could prove to be useful in forming drug representations to improve drug response prediction accuracy.ResultsWe present two deep learning approaches, BiG-DRP and BiG-DRP+, for drug response prediction. Our models take advantage of the drugs’ chemical structure and the underlying relationships of drugs and cell lines through a bipartite graph and a heterogenous graph convolutional network that incorporate sensitive and resistant cell line information in forming drug representations. Evaluation of our methods and other state-of-the-art models in different scenarios shows that incorporating this bipartite graph significantly improves the prediction performance. Additionally, genes that contribute significantly to the performance of our models also point to important biological processes and signaling pathways. Analysis of predicted drug response of patients’ tumors using our model revealed important associations between mutations and drug sensitivity, illustrating the utility of our model in pharmacogenomics studies.Availability and ImplementationAn implementation of the algorithms in Python is provided in github.com/ddhostallero/BiG-DRP.Contactamin.emad@mcgill.caSupplementary InformationOnline-only supplementary data is available at the journal’s website.