bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel regulators of islet function identified from genetic variation in mouse islet Ca2+oscillations
Authors: Emfinger Christopher H. , Clark Lauren E. , Yandell Brian , Schueler Kathryn L. , Simonett Shane P. , Stapleton Donnie S. , Mitok Kelly A. , Merrins Matthew J. , Keller Mark P. , Attie Alan D. 
Published: November 2022

ABSTRACTInsufficient insulin secretion to meet metabolic demand results in diabetes. The intracellular flux of Ca2+into β-cells triggers insulin release. Since genetics strongly influences variation in islet secretory responses, we surveyed islet Ca2+dynamics in eight genetically diverse mouse strains. We found high strain variation in response to four conditions: 1) 8 mM glucose; 2) 8 mM glucose plus amino acids; 3) 8 mM glucose, amino acids, plus 10 nM GIP; and 4) 2 mM glucose. These stimuli interrogate β-cell function, α-cell to β-cell signaling, and incretin responses. We then correlated components of the Ca2+waveforms to islet protein abundances in the same strains used for the Ca2+measurements. To focus on proteins relevant to human islet function, we identified human orthologues of correlated mouse proteins that are proximal to glycemic-associated SNPs in human GWAS. Several orthologues have previously been shown to regulate insulin secretion (e.g. ABCC8, PCSK1, and GCK), supporting our mouse-to-human integration as a discovery platform. By integrating these data, we nominated novel regulators of islet Ca2+oscillations and insulin secretion with potential relevance for human islet function. We also provide a resource for identifying appropriate mouse strains in which to study these regulators.
scRNAseq of healthy and irradiated mouse parotid glands highlights crosstalk between immune and secretory cells during chronic injury
Authors: Rheinheimer Brenna A. , Pasquale Mary C. ,   NIDCD/NIDCR Genomics and Computational Biology Core, Limesand Kirsten H. , Hoffman Matthew P. , Chibly Alejandro M 
Published: November 2022

SUMMARYTranslational frameworks to understand the chronic loss of salivary dysfunction that follows after clinical irradiation, and the development of regenerative therapies remain an unmet clinical need. Understanding the transcriptional landscape long after irradiation treatment that results in chronic salivary hypofunction will help identify injury mechanisms and develop regenerative therapies to address this need. Advances in single cell (sc)RNAseq have made it possible to identify previously uncharacterized cell types within tissues and to uncover gene regulatory networks that mediate cell-cell communication and drive specific cell states. scRNAseq studies have been performed for virtually all major tissues including salivary glands; however, there are currently no scRNAseq studies evaluating the long-term chronic effects of irradiation on salivary glands. Here, we present scRNAseq from control and irradiated murine parotid glands collected 10 months post-irradiation. We identify a population of epithelial cells in the gland defined by expression ofEtv1, which may be an acinar cell precursor. These Etv1+ cells also expressNtrk2andErbb3and thus may respond to myoepithelial cell-derived growth factor ligands. Furthermore, our data suggests that CD4+CD8+ T-cells and secretory cells are the most transcriptionally affected during chronic injury with radiation, suggesting active immune involvement during chronic injury post-irradiation. Thus, our study provides a resource to understand the transcriptional landscape in a chronic post-irradiation microenvironment and identifies cell-specific pathways that may be targeted to repair chronic damage.HighlightsWe generated a scRNAseq dataset of chronic irradiation injury in parotid glandsA newly identifiedEtv1+ epithelial population may be acinar precursorsNtrk2 and Erbb3 are highly specific Etv1+ cell receptors that may mediate cell-cell communication with myoepithelial cellsCD8+ T-cells and secretory acinar cells have the greatest transcriptional changes post-IR
Cell type-specific attenuation of brassinosteroid signalling drives stomatal asymmetric cell division
Authors: Kim Eun-Ji , Zhang Cheng , Guo Boyu , Eekhout Thomas , Houbaert Anaxi , Wendrich Jos R. , Vandamme Niels , Tiwari Manish , Simon--Vezo Claire , Vanhoutte Isabelle , Saeys Yvan , Wang Kun , Zhu Yuxian , De Rybel Bert , Russinova Eugenia 
Published: November 2022

AbstractInArabidopsis thaliana, the negative brassinosteroid (BR) signalling regulator, BR INSENSITIVE2 (BIN2) promotes and restricts stomatal asymmetric cell division (ACD) depending on its subcellular localization, which is regulated by the stomatal lineage-specific scaffolding protein POLAR. BRs inactivate BIN2, but how they govern stomatal development remains unclear. Mapping the single-cell transcriptome of stomatal lineages with either exogenous BRs or the specific BIN2 inhibitor revealed that the two modes of BR activation triggered spatiotemporally distinct transcriptional responses. We established that when in a complex with POLAR and its closest homolog POLAR-LIKE1, BIN2 is insulated from BR-mediated inactivation, nevertheless, it remains sensitive to the inhibitor. Subsequently, BR signalling is attenuated in ACD precursors, whereas it remains active in epidermal cells that would undergo differentiation. Our study demonstrates how scaffold proteins contribute to cellular signal specificity of hormonal responses in plants.
Upstream of N-Ras C-terminal cold shock domains mediate poly(A) specificity in a novel RNA recognition mode and bind poly(A) binding protein during translation regulation
Authors: Hollmann Nele Merret , Ankush Jagtap Pravin Kumar , Linse Johanna-Barbara , Ullmann Philip , Payr Marco , Murciano Brice , Simon Bernd , Hub Jochen S. , Hennig Janosch 
Published: November 2022

ABSTRACTRNA binding proteins (RBPs) often engage multiple RNA binding domains (RBDs) to increase target specificity and affinity. However, the complexity of target recognition of multiple RBDs remains largely unexplored. Here we use Upstream of N-Ras (Unr), a multidomain RBP, to demonstrate how multiple RBDs orchestrate target specificity. A crystal structure of the three C-terminal RNA binding cold-shock domains (CSD) of Unr bound to a poly(A) sequence exemplifies how recognition goes beyond the classical π-π-stacking in CSDs. Further structural studies reveal several interaction surfaces between the N-terminal and C-terminal part of Unr with the poly(A)-binding protein (pAbp). This provides first atomistic details towards understanding regulation of translation initiation that is mediated by the interplay of these two proteins with each other and RNA.
Inhibitory effect of lactobacilli supernatants on biofilm and filamentation ofC. albicans, C. tropicalis, andC. parapsilosis
Authors: Poon Yeuklan , Hui Mamie 
Published: November 2022

AbstractProbioticLactobacillusstrains had been investigated for the potential to protect against infection caused by the major fungal pathogen of human,Candida albicans. Besides antifungal activity, lactobacilli demonstrated a promising inhibitory effect on biofilm formation and filamentation ofC. albicans. On the other hand, two commonly isolated non-albicansCandidaspecies,C. tropicalisandC. parapsilosis, have similar characteristics in filamentation and biofilm formation withC. albicans. However, there is scant information of the effect of lactobacilli on the two species. In this study, biofilm inhibitory effects ofL. rhamnosusATCC 53103,L. plantarumATCC 8014, andL. acidophilusATCC 4356 were tested on the reference strainC. albicansSC5314 and six bloodstream isolated clinical strains, two each ofC. albicans, C. tropicalis, andC. parapsilosis. Cell-free culture supernatants (CFSs) ofL. rhamnosusandL. plantarumsignificantly inhibitedin vitrobiofilm growth ofC. albicansandC. tropicalis. L. acidophilus, conversely, had little effect onC. albicansandC. tropicalisbut was more effective on inhibitingC. parapsilosisbiofilms. NeutralizedL. rhamnosusCFS at pH 7 retained the inhibitory effect, suggesting that exometabolites other than lactic acid produced by theLactobacillusstrain might be accounted for the effect. Furthermore, we evaluated the inhibitory effects ofL. rhamnosusandL. plantarumCFSs on the filamentation ofC. albicansandC. tropicalisstrains. Significantly lessCandidafilaments were observed after co-incubating with CFSs under hyphae-inducing conditions. Expressions of six biofilm-related genes (ALS1, ALS3, BCR1, EFG1, TEC1, andUME6inC. albicansand corresponding orthologs inC. tropicalis) in biofilms co-incubated with CFSs were analyzed using quantitative real-time PCR. When compared to untreated control, the expressions ofALS1, ALS3, EFG1, andTEC1genes were downregulated inC. albicansbiofilm. InC. tropicalisbiofilms,ALS3andUME6were downregulated whileTEC1was upregulated. Taken together, theL. rhamnosusandL. plantarumstrains demonstrated an inhibitory effect, which is likely mediated by the metabolites secreted into culture medium, on filamentation and biofilm formation ofC. albicansandC. tropicalis. Our finding suggested an alternative to antifungals for controllingCandidabiofilm.
Transcriptional analysis in multiple barley varieties identifies signatures of waterlogging response
Authors: Miricescu Alexandra , Brazel Ailbhe Jane , Beegan Joseph , Wellmer Frank , Graciet Emmanuelle 
Published: November 2022

AbstractWaterlogging leads to major crop losses globally, particularly for waterlogging sensitive crops such as barley. Waterlogging reduces oxygen availability and results in additional stresses, leading to the activation of hypoxia and stress response pathways that promote plant survival. Although certain barley varieties have been shown to be more tolerant to waterlogging than others and some tolerance-related QTLs have been identified, the molecular mechanisms underlying this trait are mostly unknown. Transcriptomics approaches can provide very valuable information for our understanding of waterlogging tolerance. Here, we surveyed 21 barley varieties for the differential transcriptional activation of conserved hypoxia-response genes under waterlogging, and selected five varieties with different levels of induction of core hypoxia-response genes. We further characterized their phenotypic response to waterlogging in terms of shoot and root traits. RNA-sequencing to evaluate the genome-wide transcriptional responses to waterlogging of these selected varieties led to the identification of a set of 98 waterlogging-response genes common to the different datasets. Many of these genes are orthologs of the so-called ‘core hypoxia response genes’, thus highlighting the conservation of plant responses to waterlogging. Hierarchical clustering analysis also identified groups of genes with intrinsic differential expression between varieties prior to waterlogging stress. These genes could constitute interesting candidates to study ‘predisposition’ to waterlogging tolerance or sensitivity in barley.
Evaluating restriction enzyme selection for genome reduction in conservation genomics
Authors: López Ainhoa , Carreras Carlos , Pascual Marta , Pegueroles Cinta 
Published: November 2022

AbstractConservation genomic studies in non-model organisms generally rely on genome reduction techniques based on restriction enzymes to identify population structure as well as candidate loci for local adaptation. These reduced libraries ensure a high density of SNP loci and high coverage for accurate genotyping. Despite the fraction of the genome that is sequenced is expected to be randomly located, the reduction of the genome might depend on the recognition site of the restriction enzyme used. Here, we evaluate the distribution and functional composition of loci obtained after Genotyping-by-sequencing (GBS) genome reduction with two widely used restriction enzymes (EcoT22I and ApeKI). To do so, we compared data from two endemic fish species (Symphodus ocellatusandSymphodus tinca, EcoT22I enzyme) and two ecosystem engineer sea urchins (Paracentrotus lividusandArbacia lixula, ApeKI enzyme). In brief, we mapped the sequenced loci to the phylogenetically closest reference genome available (Labrus bergyltafor fish andStrongylocentrotus purpuratusfor sea urchins), classified them as exonic, intronic, and intergenic, and studied their functionality by using GO terms. We detected an enrichment towards exonic or intergenic regions depending on the restriction enzyme used, and we did not detect differences between total loci and candidate loci for adaptation. Despite most GO terms being shared between species, the analysis of their abundance showed differences between taxonomic groups, which may be attributed to differences of the targeted loci. Our results highlight the importance of restriction enzyme selection and the need for high-quality annotated genomes in conservation genomic studies.
The virome of the invasive Asian bush mosquitoAedes japonicusin Europe
Authors: Abbo Sandra R. , de Almeida João P. P. , Olmo Roenick P. , Balvers Carlijn , Griep Jet S. , Linthout Charlotte , Koenraadt Constantianus J. M. , Silva Bruno M. , Fros Jelke J. , Aguiar Eric R. G. R. , Marois Eric , Pijlman Gorben P. , Marques João T. 
Published: November 2022

ABSTRACTBackgroundThe Asian bush mosquitoAedes japonicusis rapidly invading North America and Europe. Due to its potential to transmit multiple pathogenic arthropod-borne (arbo)viruses including Zika virus, West Nile virus and chikungunya virus, it is important to understand the biology of this vector mosquito in more detail. In addition to arboviruses, mosquitoes can also carry insect-specific viruses that receive increasing attention due to their potential effects on host physiology and arbovirus transmission. In this study, we characterized the collection of viruses, referred to as the virome, circulating inAe. japonicuspopulations in the Netherlands and France.ResultsApplying a small RNA-based metagenomic approach toAe. japonicus, we uncovered a distinct group of viruses present in samples from both the Netherlands and France. These included one known virus,Ae. japonicusnarnavirus 1 (AejapNV1), and three new virus species that we namedAe. japonicustotivirus 1 (AejapTV1),Ae. japonicusanphevirus 1 (AejapAV1) andAe. japonicusbunyavirus 1 (AejapBV1). We also discovered sequences that were presumably derived from two additional novel viruses:Ae. japonicusbunyavirus 2 (AejapBV2) andAe. japonicusrhabdovirus 1 (AejapRV1). All six viruses induced strong RNA interference responses, including the production of 21 nucleotide sized small interfering RNAs, a signature of active replication in the host. Notably, AejapBV1 and AejapBV2 belong to different viral families, however, no RNA-dependent RNA polymerase sequence has been found for AejapBV2. Intriguingly, our small RNA-based approach identified a ∼1 kb long ambigrammatic RNA that is associated with AejapNV1 as a secondary segment but showed no similarity to any sequence in public databases. We confirmed the presence of AejapNV1 primary and secondary segments, AejapTV1, AejapAV1 and AejapBV1 by reverse-transcriptase PCR in wild-caughtAe. japonicusmosquitoes. AejapNV1 and AejapTV1 were found at high prevalence (87-100%) in adult females, adult males and larvae.ConclusionsUsing a small RNA-based, sequence-independent metagenomic strategy, we uncovered a conserved and prevalent virome amongAe. japonicusmosquito populations. The high prevalence of AejapNV1 and AejapTV1 across all tested mosquito life stages suggests that these viruses are intimately associated withAe. japonicusand may affect different aspects of the physiology of this vector mosquito.
Thermodynamic Architecture and Conformational Plasticity of GPCRs
Authors: Anantakrishnan Sathvik , Naganathan Athi N. 
Published: November 2022

ABSTRACTG-protein-coupled receptors (GPCRs) are ubiquitous integral membrane proteins involved in diverse cellular signaling processes and consequently serve as crucial drug targets. Here, we carry out the first large-scale ensemble thermodynamic study of 45 different ligand-free GPCRs employing a structure-based statistical mechanical framework and identify extensive conformational plasticity encompassing the seven transmembrane (TM) helices. Multiple partially structured states or intermediates co-exist in equilibrium in the native ensemble, with the TM helices 1, 6 and 7 displaying varied degrees of structure, and TM3 exhibiting the maximal stability. Active state GPCRs are characterized by reduced conformational heterogeneity with altered coupling-patterns distributed not just locally but throughout the structural scaffold. Strongly coupled residues are distributed across the structure in an anisotropic manner accounting for only 13% of the residues, highlighting that a large number of residues in GPCRs are inherently dynamic to enable structural motions critical for function. Our work thus uncovers the thermodynamic hallmarks of GPCR structure and activation, and how differences quantifiable only via higher-order coupling free energies provide insights into their exquisite structural specialization and the fluid nature of the intramolecular interaction network. The intricate landscapes and perturbation methodologies presented here lay the foundation for understanding allosteric mechanisms in GPCRs, location of structural-functional hot-spots, and effects of disease-causing mutations.
Deep Learning for Predicting 16S rRNA Gene Copy Number
Authors: Miao Jiazheng , Chen Tianlai , Misir Mustafa , Lin Yajuan 
Published: November 2022

ABSTRACTBackgroundCulture-independent 16S rRNA gene metabarcoding is a commonly used method in microbiome profiling. However, this approach can only reflect the proportion of sequencing reads, rather than the actual cell fraction. To achieve more quantitative cell fraction estimates, we need to resolve the 16S gene copy numbers (GCN) for different community members. Currently, there are several bioinformatic tools available to estimate 16S GCN, either based on taxonomy assignment or phylogeny.MethodHere we develop a novel algorithm, Stacked Ensemble Model (SEM), that estimates 16S GCN directly from the 16S rRNA gene sequence strings, without resolving taxonomy or phylogeny. For accessibility, we developed a public, end-to-end, web-based tool based on the SEM model, named Artificial Neural Network Approximator for 16S rRNA Gene Copy Number (ANNA16).ResultsBased on 27,579 16S rRNA gene sequence data (rrnDB database), we show that ANNA16 outperforms the most commonly used 16S GCN prediction algorithms. The prediction error range in the 5-fold cross validation of SEM is completely lower than all other algorithms for the 16S full-length sequence and partially lower at 16S subregions. The final test and a mock community test indicate ANNA16 is more accurate than all currently available tools (i.e., rrnDB, CopyRighter, PICRUSt2, & PAPRICA). SHAP value analysis indicates ANNA16 mainly learns information from rare insertions.ConclusionANNA16 represents a deep learning based 16S GCN prediction tool. Compared to the traditional GCN prediction tools, ANNA16 has a simple structure, faster inference speed without precomputing, and higher accuracy. With increased 16S GCN data in the database, future studies could improve the prediction errors for rare, high-GCN taxa due to current under sampling.
Functional diversification despite structural congruence in the HipBST toxin-antitoxin system ofLegionella pneumophila
Authors: Lin Jordan D. , Stogios Peter J. , Abe Kento T. , Wang Avril , MacPherson John , Skarina Tatiana , Gingras Anne-Claude , Savchenko Alexei , Ensminger Alexander W. 
Published: November 2022

ABSTRACTToxin-antitoxin (TA) systems are abundant genetic modules in bacterial chromosomes and on mobile elements. They are often patchily distributed and their physiological functions remain poorly understood. Here, we characterize a TA system inLegionella pneumophilathat is highly conserved acrossLegionellaspecies. This system is distantly related toEscherichia coliHipBST and we demonstrate that it is a functional tripartite TA system (denoted HipBSTLp). We identify HipBSTLphomologs in diverse taxa, yet in the Gammaproteobacteria these are almost exclusively found inLegionellaspecies. Notably, the toxin HipTLpwas previously reported to be a pathogenic effector protein that is translocated byL. pneumophilainto its eukaryotic hosts. Contrary to this, we find no signal of HipTLptranslocation beyond untranslocated control levels and make several observations consistent with a canonical role as a bacterial toxin. We present structural and biochemical insights into the regulation and neutralization of HipBSTLp, and identify key variations between this system and HipBSTEc. Finally, we show that the target of HipTLpis likely not conserved with any characterized HipA or HipT toxin. This work serves as a unique comparison of a TA system across bacterial species and illustrates the molecular diversity that exists within a single TA family.
Multi-environment analysis enhances genomic prediction accuracy of agronomic traits in sesame
Authors: Sabag Idan , Bi Ye , Peleg Zvi , Morota Gota 
Published: November 2022

AbstractSesame is an ancient oilseed crop containing many valuable nutritional components. Recently, the demand for sesame seeds and their products has increased worldwide, making it necessary to enhance the development of high-yielding cultivars. One approach to enhance genetic gain in breeding programs is genomic selection. However, studies on genomic selection and genomic prediction in sesame are limited. In this study, we performed genomic prediction for agronomic traits using the phenotypes and genotypes of a sesame diversity panel grown under Mediterranean climatic conditions over two growing seasons. We aimed to assess the accuracy of prediction for nine important agronomic traits in sesame using single- and multi-environment analyses. In single-environment analysis, genomic best linear unbiased prediction, BayesB, BayesC, and reproducing kernel Hilbert spaces models showed no substantial differences. The average prediction accuracy of the nine traits across these models ranged from 0.39–0.79 for both growing seasons. In the multi-environment analysis, the marker-by-environment interaction model, which decomposed the marker effects into components shared across environments and environment-specific deviations, improved the prediction accuracies for all traits by 15%–58% compared to the single-environment model, particularly when borrowing information from other environments was made possible. Our results showed that single-environment analysis produced moderate-to-high genomic prediction accuracy for agronomic traits in sesame. The multi-environment analysis further enhanced this accuracy by exploiting marker-by-environment interaction. We concluded that genomic prediction using multi-environmental trial data could improve efforts for breeding cultivars adapted to the semi-arid Mediterranean climate.
Environmental microbes promote phenotypic plasticity inDrosophilareproduction and sleep behavior
Authors: Téfit Mélisandre A. , Budiman Tifanny , Dupriest Adrianna , Yew Joanne Y. 
Published: November 2022

AbstractThe microbiome has been hypothesized as a driving force of phenotypic variation in host organisms that is capable of extending metabolic processes, altering development, and in some cases, conferring novel functions that are critical for survival (1-5). Only a few studies have directly shown a causal role for the environmental microbiome in altering host phenotypic features. To directly assess the extent to which environmental microbes induce variation in host life history traits and behavior, we inoculated axenicDrosophilawith microbes isolated from two different field sites and generated two populations with distinct bacterial and fungal profiles. We show that microbes isolated from environmental sites with modest abiotic differences induce large variation in host reproduction, fatty acid levels, stress tolerance, and sleep behavior. Importantly, clearing microbes from each experimental population removed the phenotypic differences. The results support the causal role of environmental microbes as drivers of host phenotypic variation and potentially, rapid adaptation and evolution.