bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trehalose increases tomato drought tolerance, induces defenses, and increases resistance to bacterial wilt disease
Authors: MacIntyre April M. , Meline Valerian , Gorman Zachary , Augustine Steven P. , Dye Carolyn J. , Hamilton Corri D. , Iyer-Pascuzzi Anjali S. , Kolomiets Michael V. , McCulloh Katherine A. , Allen Caitilyn 
Published: July 2021

AbstractRalstonia solanacearumcauses bacterial wilt disease, leading to severe crop losses. Xylem sap fromR. solanacearum-infected tomato is enriched in the disaccharide trehalose. Water-stressed plants also accumulate trehalose, which increases drought tolerance via abscisic acid (ABA) signaling. BecauseR. solanacearum-infected plants suffer reduced water flow, we hypothesized that bacterial wilt physiologically mimics drought stress, which trehalose could mitigate. We found thatR. solanacearum-infected plants differentially expressed drought-associated genes, including those involved in ABA and trehalose metabolism, and had more ABA in xylem sap. Consistent with this, treating tomato roots with ABA reduced both stomatal conductance and stem colonization byR. solanacearum. Treating roots with trehalose increased xylem sap ABA and reduced plant water use by lowering stomatal conductance and temporarily improving water use efficiency. Trehalose treatment also upregulated expression of salicylic acid (SA)-dependent tomato defense genes; increased xylem sap levels of SA and other antimicrobial compounds; and increased bacterial wilt resistance of SA-insensitiveNahGtomato plants. Additionally, trehalose treatment increased xylem concentrations of jasmonic acid and related oxylipins. Finally, trehalose-treated plants were substantially more resistant to bacterial wilt disease. Together, these data show that exogenous trehalose reduced both water stress and bacterial wilt disease and triggered systemic disease resistance, possibly through a Damage Associated Molecular Pattern (DAMP) response pathway. This suite of responses revealed unexpected linkages between plant responses to biotic and abiotic stress and suggested thatR. solanacearum-infected plants increase trehalose to improve water use efficiency and increase wilt disease resistance. The pathogen may degrade trehalose to counter these efforts. Together, these results suggest that treating tomatoes with exogenous trehalose could be a practical strategy for bacterial wilt management.
Caldendrin represses neurite regeneration via a sex-dependent mechanism in sensory neurons
Authors: Lopez Josue A. , Yamamoto Annamarie , Vecchi Joseph T. , Hagen Jussara , Lee Amy 
Published: July 2021

ABSTRACTCaldendrin is a calmodulin-like Ca2+binding protein that is expressed primarily in neurons and regulates multiple effectors including Cav1 L-type Ca2+channels. Here, we tested the hypothesis that caldendrin regulates Cav1-dependent pathways that repress neurite growth in dorsal root ganglion neurons (DRGNs). By immunofluorescence, caldendrin was localized in medium- and large-diameter DRGNs. Consistent with an inhibitory effect of caldendrin on neurite growth, neurite initiation and growth was enhanced in dissociated DRGNs from caldendrin knockout (KO) mice compared to those from wild type (WT) mice. In anin vitroaxotomy assay, caldendrin KO DRGNs grew longer neurites via a mechanism that was more sensitive to inhibitors of transcription as compared to WT DRGNs. Strong depolarization, which normally represses neurite growth through activation of Cav1 channels, had no effect on neurite growth in DRGN cultures from female caldendrin KO mice. Remarkably, DRGNs from caldendrin KO males were no different from those of WT males in terms of depolarization-dependent neurite growth repression. We conclude that caldendrin opposes neurite regeneration and growth, and this involves coupling of Cav1 channels to growth-inhibitory pathways in DRGNs of females but not males. Our findings suggest that caldendrin KO mice represent an ideal model in which to interrogate the transcriptional pathways controlling neurite regeneration and how these pathways may differ in males and females.
Newly identified parasitic nematode beta-tubulin alleles confer resistance to benzimidazoles
Authors: Dilks Clayton M. , Koury Emily J. , Buchanan Claire M. , Andersen Erik C. 
Published: July 2021

AbstractInfections by parasitic nematodes cause large health and economic burdens worldwide. We use anthelmintic drugs to reduce these infections. However, resistance to anthelmintic drugs is extremely common and increasing worldwide. It is essential to understand the mechanisms of resistance to slow its spread. Recently, four new parasitic nematode beta-tubulin alleles have been identified in benzimidazole (BZ) resistant parasite populations: E198I, E198K, E198T, and E198stop. These alleles have not been tested for the ability to confer resistance or for any effects that they might have on organismal fitness. We introduced these four new alleles into the sensitive C. elegans laboratory-adapted N2 strain and exposed these genome-edited strains to both albendazole and fenbendazole. We found that all four alleles conferred resistance to both BZ drugs. Additionally, we tested for fitness consequences in both control and albendazole conditions over seven generations in competitive fitness assays. We found that none of the edited alleles had deleterious effects on fitness in control conditions and that all four alleles conferred strong and equivalent fitness benefits in BZ drug conditions. Because it is unknown if previously validated alleles confer a dominant or recessive BZ resistance phenotype, we tested the phenotypes caused by five of these alleles and found that none of them conferred a dominant BZ resistance phenotype. Accurate measurements of resistance, fitness effects, and dominance caused by the resistance alleles allow for the generation of better models of population dynamics and facilitate control practices that maximize the efficacy of this critical anthelmintic drug class.HighlightsFour newly identified parasitic nematode beta-tubulin alleles confer benzimidazole resistanceThe four newly identified alleles do not confer deleterious fitness consequencesFive beta-tubulin alleles confer recessive benzimidazole resistanceGraphical abstract
Selective ancestral sorting and de novo evolution in the agricultural invasion of Amaranthus tuberculatus
Authors: Kreiner J.M. , Caballero Amalia , Wright S.I. , Stinchcombe J.R. 
Published: July 2021

AbstractThe relative role of hybridization, de novo evolution, and standing variation in weed adaptation to agricultural environments is largely unknown. In Amaranthus tuberculatus, a widespread North American agricultural weed, adaptation is likely influenced by recent secondary contact and admixture of two previously isolated subspecies. We characterized the extent of adaptation and phenotypic differentiation accompanying the spread of A. tuberculatus into agricultural environments and the contribution of subspecies divergence. We generated phenotypic and whole-genome sequence data from a manipulative common garden experiment, using paired samples from natural and agricultural populations. We found strong latitudinal, longitudinal, and sex differentiation in phenotypes, and subtle differences among agricultural and natural environments that were further resolved with ancestry inference. The transition into agricultural environments has favoured southwestern var. rudis ancestry that leads to higher biomass and environment-specific phenotypes: increased biomass and earlier flowering under reduced water availability, and reduced plasticity in fitness-related traits. We also detected de novo adaptation to agricultural habitats independent of ancestry effects, including marginally higher biomass and later flowering in agricultural populations, and a time to germination home advantage. Therefore, the invasion of A. tuberculatus into agricultural environments has drawn on adaptive variation across multiple timescales—through both preadaptation via the preferential sorting of var. rudis ancestry and de novo local adaptation.
A single exposure to altered auditory feedback causes observable sensorimotor adaptation in speech
Authors: Hantzsch Lana , Parrell Benjamin , Niziolek Caroline A. 
Published: July 2021

AbstractSensory errors caused by perturbations to movement-related feedback induce two types of behavioral changes that oppose the perturbation: rapid compensation within a movement, as well as longer-term adaptation of subsequent movements. Although adaptation is hypothesized to occur whenever a sensory error is perceived (including after a single exposure to altered feedback), adaptation of articulatory movements in speech has only been observed after repetitive exposure to auditory perturbations, questioning both current theories of speech sensorimotor adaptation as well as the universality of more general theories of adaptation. Thus, positive evidence for the hypothesized single-exposure or “one-shot” learning would provide critical support for current theories of speech sensorimotor learning and control and align adaptation in speech more closely with other motor domains. We measured one-shot learning in a large dataset in which participants were exposed to intermittent, unpredictable auditory perturbations to their vowel formants (the resonant frequencies of the vocal tract that distinguish between different vowels). On each trial, participants spoke a word out loud while their first formant was shifted up, shifted down, or remained unshifted. We examined whether the perturbation on a given trial affected speech on the subsequent, unperturbed trial. We found that participants adjusted their first formant in the opposite direction of the preceding shift, demonstrating that learning occurs even after a single auditory perturbation as predicted by current theories of sensorimotor adaptation. While adaptation and the preceding compensation responses were correlated, this was largely due to differences across individuals rather than within-participant variation from trial to trial. These findings are more consistent with theories that hypothesize adaptation is driven directly by updates to internal control models than those that suggest adaptation results from incorporation of feedback responses from previous productions.
TCF12 controls oligodendroglial cell proliferation and regulates signaling pathways conserved in gliomas
Authors: Archontidi Sofia , Marie Corentine , Gyorgy Beata , Guegan Justine , Sanson Marc , Parras Carlos , Huillard Emmanuelle 
Published: July 2021

AbstractDiffuse gliomas are primary brain tumors originating from the transformation of glial cells. In particular, oligodendrocyte precursor cells constitute the major tumor-amplifying population in the gliomagenic process. We previously identified the TCF12 gene, encoding a transcription factor of the E protein family, as being recurrently mutated in oligodendrogliomas. In this study, we sought to understand the function of TCF12 in oligodendroglial cells, the glioma lineage of origin. We first describe TCF12 mRNA and protein expression pattern in oligodendroglial development in the mouse brain. Second, by TCF12 genome wide chromatin profiling in oligodendroglial cells, we show that TCF12 binds active promoters of genes involved in proliferation, translation/ribosomes, and pathways involved in oligodendrocyte development and cancer. Finally, we perform OPC-specific Tcf12 inactivation in vivo and demonstrate by immunofluorescence and transcriptomic analyses that TCF12 is transiently required for OPC proliferation but dispensable for oligodendrocyte differentiation. We further show that Tcf12 inactivation results in deregulation of biological processes that are also altered in oligodendrogliomas. Together, our data suggest that TCF12 directly regulates transcriptional programs in oligodendroglia development that are relevant in a glioma context.
Longitudinal single-cell chemical imaging of engineered strains reveals heterogeneity in fatty acid production
Authors: Tague Nathan , Lin Haonan , Lugagne Jean-Baptiste , O’Connor Owen M. , Burman Deeya , Wong Wilson W. , Cheng Ji-Xin , Dunlop Mary J. 
Published: July 2021

AbstractUnderstanding metabolic heterogeneity is critical for optimizing microbial production of valuable chemicals, but requires tools that can quantify metabolites at the single-cell level over time. Here, we develop longitudinal hyperspectral stimulated Raman scattering (SRS) chemical imaging to directly visualize free fatty acids in engineered Escherichia coli over many cell cycles. We also develop compositional analysis to determine the chain length and unsaturation of the fatty acids in living cells. Our method reveals substantial heterogeneity in fatty acid production among and within colonies that emerges over the course of many generations. Interestingly, the strains display distinct types of production heterogeneity in an enzyme-dependent manner. By pairing time-lapse and SRS imaging, we examine the relationship between growth and production at the single-cell level. Single-cell quantification does not show a significant growth-production tradeoff in a strain that exhibits high production heterogeneity. Our results demonstrate that cell-to-cell production heterogeneity is pervasive and provide a means to link single-cell and population-level production.
Cognitive process modeling addresses context independence violations in the ABCD Study stop-signal task
Authors: Weigard Alexander , Matzke Dora , Tanis Charlotte , Heathcote Andrew 
Published: July 2021

AbstractThe Adolescent Brain Cognitive Development (ABCD) Study is a longitudinal neuroimaging study of unprecedented scale that is in the process of following over 11,000 youth from middle childhood though age 20. However, a design feature of the study’s stop-signal task violates “context independence”, an assumption critical to current non-parametric methods for estimating stop-signal reaction time (SSRT), a key measure of inhibitory ability in the study. This has led some experts to call for the task to be changed and for previously collected data to be used with caution. We present a formal cognitive process model, the BEESTS-ABCD model, that provides a mechanistic explanation for the impact of this design feature, describes key behavioral trends in the ABCD data, and allows biases in SSRT estimates resulting from context independence violations to be quantified. We use the model to demonstrate that, although non-parametric SSRT estimates generally preserve the rank ordering of participants’ SSRT values, failing to account for context independence violations can lead to erroneous inferences in several realistic scenarios. Nonetheless, as the BEESTS-ABCD model can be used to accurately recover estimates of SSRT and other mechanistic parameters of interest from ABCD data, the impact of such violations can be effectively mitigated.
Elucidation of SARS-Cov-2 Budding Mechanisms Through Molecular Dynamics Simulations of M and E Protein Complexes
Authors: Collins Logan Thrasher , Elkholy Tamer , Mubin Shafat , Hill David , Williams Ricky , Ezike Kayode , Singhal Ankush 
Published: July 2021

AbstractSARS-CoV-2 and other coronaviruses pose major threats to global health, yet computational efforts to understand them have largely overlooked the process of budding, a key part of the coronavirus life cycle. When expressed together, coronavirus M and E proteins are sufficient to facilitate budding into the ER-Golgi intermediate compartment (ERGIC). To help elucidate budding, we ran atomistic molecular dynamics (MD) simulations using the Feig laboratory’s refined structural models of the SARS-CoV-2 M protein dimer and E protein pentamer. Our MD simulations consisted of M protein dimers and E protein pentamers in patches of membrane. By examining where these proteins induced membrane curvature in silico, we obtained insights around how the budding process may occur. Multiple M protein dimers acted together to induce global membrane curvature through protein-lipid interactions while E protein pentamers kept the membrane planar. These results could eventually help guide development of antiviral therapeutics which inhibit coronavirus budding.
Molecular mechanism of the anti-lung cancer effect of Jin Ning Fang based on network pharmacology and experimental verification
Authors: Wu Chunxiao , Yu Qiquan , Shou Weizhen , Zhang Kun , Li Yang , Guo Wentao , Bao Qi 
Published: July 2021

AbstractBackgroundJin Ning Fang (JNF) is widely used as an adjuvant therapy for lung cancer. However, its molecular mechanism against lung cancer is still unclear.MethodsThe chemical compounds JNF were screened from the TCMSP database and its target proteins were then predicted. The genes related to lung cancer were collected from the CTD and DisGeNET databases. Next, targets were integrated with disease-related genes to obtain candidate genes. Functional enrichment and protein-protein interaction (PPI) analysis were also performed, followed by construction of pharmacological network. Meanwhile, Autodock was used to assess the affinity between targets and compound. Finally, the anti-cancer effect of JNF on lung cancer cells was detected and some predicted key genes was validated by using real-time PCR.ResultsTwenty-five overlapping targets were obtained, and pathway analysis showed that JNF might exert its anti-cancer function by regulating some biological pathways, such as apoptosis pathway. PPI and pharmacological network revealed several core targets (such as AKT1, AR, and ESR1) and three compounds (quercetin, calcium carbonate, and beta-sitosterol). Then, beta-sitosterol had a high affinity with AKT1, AR, and ESR1. Further in vitro experiments confirmed that JNF could inhibit proliferation and promote apoptosis of A549 cells. The expression of FDPS, PIM1, VCAM1, SLC29A1, NQO1, and ESR1 were significantly decreased, while mRNA level of AR and ANPEP were markedly increased after JNF treatment.ConclusionJNF may exert anti-lung cancer effect through multiple targets and pathways, and identified genes may be used as potential biomarkers for diagnosis and treatment of lung cancer.
Deep Learning Image Classification of Red Blood Cell Deformability
Authors: Lamoureux Erik S. , Islamzada Emel , Wiens Matthew V. J. , Matthews Kerryn , Duffy Simon P. , Ma Hongshen 
Published: July 2021

ABSTRACTRed blood cells (RBCs) must be highly deformable to transit through the microvasculature to deliver oxygen to tissues. The loss of RBC deformability resulting from pathology, natural aging, or storage in blood bags can impede the proper function of these cells. A variety of methods have been developed to measure RBC deformability, but these methods require specialized equipment, long measurement time, and highly skilled personnel. To address this challenge, we investigated whether a machine learning approach could be applied to determine donor RBC deformability using single cell microscope images. We used the microfluidic ratchet device to sort RBCs based on deformability. Sorted cells are then imaged and used to train a deep learning model to classify RBCs based on deformability. This model correctly predicted deformability of individual RBCs with 84 ± 11% accuracy averaged across ten donors. Using this model to score the deformability of RBC samples were accurate to within 4.4 ± 2.5% of the value obtained using the microfluidic ratchet device. While machine learning methods are frequently developed to automate human image analysis, our study is remarkable in showing that deep learning of single cell microscopy images could be used to measure RBC deformability, a property not normally measurable by imaging. Measuring RBC deformability by imaging is also desirable because it can be performed rapidly using a standard microscopy system, potentially enabling RBC deformability studies to be performed as part of routine clinical assessments.
Genetic loci of theR. anatipestiferserotype discovered by Pan-GWAS and its application for the development of a multiplex PCR serotyping method
Authors: Yang Zhishuang , Yang Xueqin , Wang Mingshu , Jia Renyong , Chen Shun , Liu Mafeng , Zhao Xinxin , Yang Qiao , Wu Ying , Zhang Shaqiu , Huang Juan , Ou Xumin , Mao Sai , Gao Qun , Sun Di , Tian Bin , Zhu Dekang , Cheng Anchun 
Published: July 2021

AbstractThe disease caused byRiemerella anatipestifer(R. anatipestifer) causes large economic losses to the global duck industry every year. Serotype-related genomic variation (such as in O-antigen and capsular polysaccharide gene clusters) has been widely used for the serotyping in many gram-negative bacteria. To date, there have been few studies focused on genetic basis of serotypes inR. anatipestifer. Here, we used pan-genome-wide association studies (Pan-GWAS) to identify the serotype-specific genetic loci of 38R. anatipestifersstrain. Analyses of the loci of 11 serotypes showed that the loci could be well mapped with the serotypes of the corresponding strains. We constructed the knockout strain for thewzygene at the locus, and the results showed that the mutant lost the agglutination characteristics to positive antisera. Based on the of Pan-GWAS results, we developed a multiple PCR method to identify serotypes 1, 2, and 11 ofR. anatipestifer. Our study provides a precedent for systematically analysing the genetic basis of theR anatipestiferserotypes and establishing a complete serotyping system in the future.HighlightsR. anatipestiferserotype-specific locus was identified by Pan-GWAS for the first time.Molecular serotyping multiplex PCR was developed based on O-antigen biosynthesis gene clusters
Engineering Viral Vectors for Acoustically Targeted Gene Delivery
Authors: Li Hongyi , Heath John E. , Trippett James S. , Shapiro Mikhail G. , Szablowski Jerzy O. 
Published: July 2021

ABSTRACTTargeted gene delivery to the brain is a critical tool for neuroscience research and has significant potential to treat human disease. However, the site-specific delivery of common gene vectors such as adeno-associated viruses (AAVs) is typically performed via invasive injections, limiting their scope of research and clinical applications. Alternatively, focused ultrasound blood-brain-barrier opening (FUS-BBBO), performed noninvasively, enables the site-specific entry of AAVs into the brain from systemic circulation. However, when used in conjunction with natural AAV serotypes, this approach has limited transduction efficiency, requires ultrasound parameters close to tissue damage limits, and results in undesirable transduction of peripheral organs. Here, we use high throughput in vivo selection to engineer new AAV vectors specifically designed for local neuronal transduction at the site of FUS-BBBO. The resulting vectors substantially enhance ultrasound-targeted gene delivery and neuronal tropism while reducing peripheral transduction, providing a more than ten-fold improvement in targeting specificity. In addition to enhancing the only known approach to noninvasively target gene delivery to specific brain regions, these results establish the ability of AAV vectors to be evolved for specific physical delivery mechanisms.