bluuebunny/crossref_metadata_2025_split huggingface dataset:
Knotted artifacts in predicted 3D RNA structures
Authors: Gren Bartosz A. , Antczak Maciej , Zok Tomasz , Sulkowska Joanna I. , Szachniuk Marta 
Published: March 2024

AbstractUnlike proteins, RNAs deposited in the Protein Data Bank do not contain topological knots. Recently, admittedly, the first trefoil knot and some lasso-type conformations have been found in experimental RNA structures, but these are still exceptional cases. Meanwhile, algorithms predicting 3D RNA models have happened to form knotted structures not so rarely. Interestingly, machine learning-based predictors seem to be more prone to generate knotted RNA folds than traditional methods. A similar situation is observed for the entanglements of structural elements. In this paper, we analyze all models submitted to the CASP15 competition in the 3D RNA structure prediction category. We show what types of topological knots and structure element entanglements appear in the submitted models and highlight what methods are behind the generation of such conformations. We also study the structural aspect of susceptibility to entanglement. We suggest that predictors take care of an evaluation of RNA models to avoid publishing structures with artifacts, such as unusual entanglements, that result from hallucinations of predictive algorithms.Author summary3D RNA structure prediction contests such as CASP and RNA-Puzzles lack measures for topology-wise evaluation of predicted models. Thus, predictors happen to submit potentially inappropriate conformations, for example, containing entanglements that are prediction artifacts.Automated identification of entanglements in 3D RNA structures is computationally hard. Distinguishing correct from incorrectly entangled conformations is not trivial and often requires expert knowledge.We analyzed 3D RNA models submitted to CASP15 and found that all entanglements in these models are artifacts.Compared to non-ML, machine learning-based methods are more prone to generating entanglements that are not present in natural RNAs.To increase the reliability of 3D RNA structure prediction, it is necessary to reject abnormally entangled structures in the modeling stage.
Spatial visualization of A-to-I Editing in cells using Endonuclease V Immunostaining Assay (EndoVIA)
Authors: Quillin Alexandria L. , Arnould Benoît , Knutson Steve D. , Heemstra Jennifer M. 
Published: March 2024

AbstractAdenosine-to-Inosine (A-to-I) editing is one of the most widespread post-transcriptional RNA modifications and is catalyzed by adenosine deaminases acting on RNA (ADARs). Varying across tissue types, A-to-I editing is essential for numerous biological functions and dysregulation leads to autoimmune and neurological disorders, as well as cancer. Recent evidence has also revealed a link between RNA localization and A-to-I editing, yet understanding of the mechanisms underlying this relationship and its biological impact remains limited. Current methods rely primarily onin vitrocharacterization of extracted RNA that ultimately erases subcellular localization and cell-to-cell heterogeneity. To address these challenges, we have repurposed Endonuclease V (EndoV), a magnesium dependent ribonuclease that cleaves inosine bases in edited RNA, to selectively bind and detect A-to-I edited RNA in cells. The work herein introduces Endonuclease V Immunostaining Assay (EndoVIA), a workflow that provides spatial visualization of edited transcripts, enables rapid quantification of overall inosine abundance, and maps the landscape of A-to-I editing within the transcriptome at the nanoscopic level.
NFixDB (Nitrogen Fixation DataBase) - A Comprehensive Integrated Database for Robust ‘Omics Analysis of Diazotrophs
Authors: Bellanger Madeline , Figueroa Jose L. , Tiemann Lisa , Friesen Maren L. , White Richard Allen 
Published: March 2024

AbstractBiological nitrogen fixation is a fundamental biogeochemical process that transforms that provides fixed biologically available nitrogen by diazotrophic microbes. Diazotrophs anaerobically fix nitrogen using the nitrogenase enzyme which has three different gene clusters: 1) molybdenum nitrogenase (nifDHK) is the most abundant, followed by it’s alternatives 2) vanadium nitrogenase (vnfDHK), and 3) iron nitrogenase (anfDHK). Multiple databases have been constructed as resources for diazotrophic ‘omics analysis; however, an integrated database based on whole genome references does not exist. Here, we present NFixDB (NitrogenFixationDataBase), a comprehensive integrated whole genome based database for diazotrophs, which includes all nitrogenases (nifDHK,vnfDHK,anfDHK) and nitrogenase-like enzymes (e.g.,nflDH) linked to ribosomal operons (16S-5.8S-23S). NFixDB was computed using Hidden Markov Models (HMMs) against the entire whole genome based Genome Taxonomy Database (GTDB R214), providing searchable reference HMMs for all nitrogenase and nitrogenase-like genes, complete ribosomal operons, both GTDB and NCBI/RefSeq taxonomy, and an SQL database for querying matches. We compared NFixDB tonifHdatabases from Buckley, Zehr, Mise, and FunGene finding extensive evidence ofnifH, in addition tovnfHandnflH. NFixDB contains more than 4,000 verifiednifHDKsequences contained on 50 unique phyla of bacteria and archaea. NFixDB offers the first comprehensive nitrogenase database available to researchers.
Large-scale single-cell profiling of stem cells uncovers redundant regulators of shoot development and yield trait variation
Authors: Xu Xiaosa , Passalacqua Michael , Rice Brian , Demesa-Arevalo Edgar , Kojima Mikiko , Takebayashi Yumiko , Harris Benjamin , Sakakibara Hitoshi , Gallavotti Andrea , Gillis Jesse , Jackson David 
Published: March 2024

SUMMARYStem cells in plant shoots are a rare population of cells that produce leaves, fruits and seeds, vital sources for food and bioethanol. Uncovering regulators expressed in these stem cells will inform crop engineering to boost productivity. Single-cell analysis is a powerful tool for identifying regulators expressed in specific groups of cells. However, accessing plant shoot stem cells is challenging. Recent single-cell analyses of plant shoots have not captured these cells, and failed to detect stem cell regulators likeCLAVATA3andWUSCHEL. In this study, we finely dissected stem cell-enriched shoot tissues from both maize and arabidopsis for single-cell RNA-seq profiling. We optimized protocols to efficiently recover thousands ofCLAVATA3andWUSCHELexpressed cells. A cross-species comparison identified conserved stem cell regulators between maize and arabidopsis. We also performed single-cell RNA-seq on maize stem cell overproliferation mutants to find additional candidate regulators. Expression of candidate stem cell genes was validated using spatial transcriptomics, and we functionally confirmed roles in shoot development. These candidates include a family of ribosome-associated RNA-binding proteins, and two families of sugar kinase genes related to hypoxia signaling and cytokinin hormone homeostasis. These large-scale single-cell profiling of stem cells provide a resource for mining stem cell regulators, which show significant association with yield traits. Overall, our discoveries advance the understanding of shoot development and open avenues for manipulating diverse crops to enhance food and energy security.
Targeting dermatophyte Cdc42 and Rac GTPase signaling to hinder hyphal elongation and virulence
Authors: Ishii Masaki , Matsumoto Yasuhiko , Yamada Tsuyoshi , Uga Hideko , Katada Toshiaki , Ohata Shinya 
Published: March 2024

SummaryThe identification of novel molecular targets for antifungal drugs is critical due to limited treatment options and drug-resistance threats. We screened inhibitors of small GTPases, molecular switches in signal transduction, inTrichophyton rubrum, the primary cause of dermatophytosis. Our study found that chemical and genetic inhibition of Cdc42 and Rac GTPases, which are involved in cellular morphological changes, significantly impair hyphal formation, and are crucial for pathogenic fungal growth and virulence. Genetic repression of Cdc24, a guanine nucleotide exchange factor of Cdc42 and Rac, led to hyphal growth defects, abnormal cell morphology, and cell death. Chemical screening identified EHop-016 as an inhibitor of Cdc24 activity, which improved outcomes inin vitronail infection and invertible infection models ofT. rubrum. Our results suggest the Cdc24-Cdc42/Rac pathway as a promising therapeutic target for antifungal agent development, with EHop-016 as a potential lead compound.
Dissecting the contribution of common variants to risk of rare neurodevelopmental conditions
Authors: Huang Qin Qin , Wigdor Emilie M , Campbell Patrick , Malawsky Daniel S , Samocha Kaitlin E , Chundru V Kartik , Danecek Petr , Lindsay Sarah , Marchant Thomas , Musa Mahmoud Koko , Amanat Sana , Bonifanti Davide , Sheridan Eamonn , Radford Elizabeth J , Barrett Jeffrey C , Wright Caroline F , Firth Helen V , Warrier Varun , Young Alexander Strudwick , Hurles Matthew E , Martin Hilary C 
Published: March 2024

AbstractAlthough rare neurodevelopmental conditions have a large Mendelian component, common genetic variants also contribute to risk. However, little is known about how this polygenic risk is distributed among patients with these conditions and their parents, its interplay with rare variants, and whether parents’ polygenic background contributes to their children’s risk beyond the direct effect of variants transmitted to the child (i.e. via indirect genetic effects potentially mediated through the prenatal environment or ‘genetic nurture’). Here, we addressed these questions using genetic data from 11,573 patients with rare neurodevelopmental conditions, 9,128 of their parents and 26,869 controls. Common variants explained ∼10% of variance in overall risk. Patients with a monogenic diagnosis had significantly less polygenic risk than those without, supporting a liability threshold model, while both genetically undiagnosed patients and diagnosed patients with affected parents had significantly more risk than controls. In a trio-based model, using a polygenic score for neurodevelopmental conditions, the transmitted but not the non-transmitted parental alleles were associated with risk, indicating a direct genetic effect. In contrast, we observed no direct genetic effect of polygenic scores for educational attainment and cognitive performance, but saw a significant correlation between the child’s risk and non-transmitted alleles in the parents, potentially due to indirect genetic effects and/or parental assortment for these traits. Indeed, as expected under parental assortment, we show that common variant predisposition for neurodevelopmental conditions is correlated with the rare variant component of risk. Our findings thus suggest that future studies should investigate the possible role and nature of indirect genetic effects on rare neurodevelopmental conditions, and consider the contribution of common and rare variants simultaneously when studying cognition-related phenotypes.
Cause-Specific Excess Mortality in the US During the COVID-19 Pandemic
Authors: Degtiareva Ekaterina , Tilstra Andrea M. , Schöley Jonas , Kashyap Ridhi , Dowd Jennifer B. 
Published: March 2024

ABSTRACTThe COVID-19 pandemic was a significant shock to United States mortality, and it is important to understand how the pandemic impacted other causes of death. We estimated monthly excess mortality in the US by cause of death, age, and sex, for official deaths at ages 15 and older. Data come from the CDC Wonder Multiple Cause of Death database. We used a compositionally robust Generalized Additive Model (GAM) to estimate expected mortality counts in March 2020-December 2022 for eight causes of death: accidents, cardiovascular diseases, cancer, diabetes, influenza and pneumonia, substance-related (drugs and alcohol), suicide, and residual (including COVID-19 related deaths). Analyses were stratified by sex and 15-year age groups from 15-29 to 75+. Excess mortality was calculated as observed deaths minus expected deaths. From March 2020 to December 2022, we estimated 1 298 763 total excess deaths (95% CI: 1 226 542 to 1 370 804). While there were fewer deaths than expected due to some causes like flu/pneumonia and suicide, the largest number of excess deaths, excluding COVID-19, were attributed to cardiovascular diseases (115 765 deaths, 95% CI: 98 697 to 133 783) and substance use (86 637 deaths, 95% CI: 79 273 to 93 690). Percent excess substance-related mortality was high across all ages, while percent excess from cardiovascular diseases was highest at midlife ages. Some of these excess cardiovascular deaths were likely due to undercounted COVID-19 deaths, but others may reflect indirect impacts of the pandemic on healthcare utilization or longer-term effects of COVID-19 infections.SIGNIFICANCE STATEMENTThe COVID-19 pandemic increased mortality directly due to COVID-19 deaths, but also changed the pattern of deaths due to other causes in the United States. We estimated excess cause-specific mortality in the US and present several findings. We estimated nearly 1.3 million total excess deaths in the US from March 2020 to December 2022. Deaths from suicide and influenza and pneumonia were lower than expected based on previous trends, but deaths due to cardiovascular diseases, diabetes, accidents, and substance-related causes (drug and alcohol) were higher. Cancer deaths were generally unchanged. By quantifying both the direct and indirect effects of the COVID-19 pandemic on US mortality, we highlight areas of on-going vulnerability in the US.
The emerging H3K9me3 chromatin landscape during zebrafish embryogenesis
Authors: Duval Katherine L. , Artis Ashley R. , Goll Mary G. 
Published: March 2024

AbstractThe structural organization of eukaryotic genomes is contingent upon the fractionation of DNA into transcriptionally permissive euchromatin and repressive heterochromatin. However, we have a limited understanding of how these distinct states are first established during animal embryogenesis. Histone 3 lysine 9 trimethylation (H3K9me3) is critical to heterochromatin formation and bulk establishment of this mark is thought to help drive large-scale remodeling of an initially naive chromatin state during animal embryogenesis. However, a detailed understanding of this process is lacking. Here, we leverage CUT&RUN to define the emerging H3K9me3 landscape of the zebrafish embryo with high sensitivity and temporal resolution. Despite the prevalence of DNA transposons in the zebrafish genome, we found that LTR transposons are preferentially targeted for embryonic H3K9me3 deposition, with different families exhibiting distinct establishment timelines. High signal-to-noise ratios afforded by CUT&RUN revealed new, emerging sites of low-amplitude H3K9me3 that initiated before the major wave of zygotic genome activation (ZGA). Early sites of establishment predominated at specific subsets of transposons and were particularly enriched for transposon sequences with maternal piRNAs and pericentromeric localization. Notably, the number of H3K9me3 enriched sites increased linearly across blastula development, while quantitative comparison revealed a >10-fold genome-wide increase in H3K9me3 signal at established sites over just 30 minutes at the onset of ZGA. Continued maturation of the H3K9me3 landscape was observed beyond the initial wave of bulk establishment.Article SummaryEukaryotic genomes are organized into transcriptionally permissive euchromatin and repressive heterochromatin. However, we have a limited understanding of how these distinct states are first established during animal embryogenesis. Here, we define the emerging landscape of the heterochromatic histone tail modification H3K9me3 across zebrafish embryogenesis. Our results uncover distinct kinetics of H3K9me3 establishment and growth, define unique characteristics associated with initial sites of H3K9me3, and demonstrate additional maturation of the H3K9me3 landscape beyond the window of bulk H3K9me3 deposition.
Picoplankton nitrogen guilds in the tropical and subtropical oceans: from the surface to the deep
Authors: Rivas-Santisteban Juan , Fernández-González Nuria , Laso-Pérez Rafael , Tamames Javier , Pedrós-Alió Carlos 
Published: March 2024

AbstractEcological guilds quantify the incidence and extent of resource transformation functions, irrespective of the species involved. Therefore, tackling the microbial nitrogen guilds is key to our understanding of the oceanic nitrogen cycle, but quantitative estimates of guild contribution across varying depths and under specific environmental conditions have yet to be accomplished. In this study, we examine the main picoplankton guilds participating in nitrogen cycling within the low and mid-latitude ocean ecosystems, from the surface down to 4000 m, using data obtained from 75 samples belonging to 11 stations in the Malaspina (MP) dataset. In particular, we used a quantitative approach to investigate the stability of nitrogen acquisition and nitrogen-redox guilds separately. Our results showed that nitrogen acquisition guilds are more stable and redundant than nitrogen-redox guilds across depths and site specific conditions. For example, differential conditions such as nitrogen depletion and oxygen availability affected the two groups of guilds in different ways. These findings have implications for the understanding of global nitrogen fluxes and the biosphere’s functional diversification.
The latent stage ofToxoplasma gondiiis targeted by the immune response and host protective
Authors: Shallberg Lindsey A. , Eberhard Julia N. , Winn Aaron , Chandrasekaran Sambamurthy , Giuliano Christopher J. , Merritt Emily F. , Willis Elinor , Christian David A. , Aldridge Daniel L. , Bunkofske Molly , Jacquet Maxime , Dzierszinski Florence , Katifori Eleni , Lourido Sebastian , Koshy Anita A. , Hunter Christopher A. 
Published: March 2024

AbstractLatency is a microbial strategy for persistence. ForToxoplasma gondiithe ability of the bradyzoite stage to form long-lived cysts is critical for transmission, while their presence in neurons is considered important for immune evasion. Development of a mathematical model highlighted that immune pressure on bradyzoites should contribute to dynamics of cyst formation and reactivation. Experimental data demonstrated that a cyst-derived antigen was recognized by CD8+T cells and that IFN-γ signaling in neurons contributes to cyst control. In addition, modeling and the use of a parasite strain unable to form bradyzoites revealed that this stage was not required for long-term persistence, but the absence of cyst formation resulted in increased tachyzoite replication in the CNS with associated tissue damage and mortality. Thus, the latent form ofT. gondiiis under immune pressure, mitigates infection-induced damage, and promotes survival of host and parasite.
Bacteroidesvesicles promote functional alterations in gut microbiota composition
Authors: Shagaleeva Olga Yu. , Kashatnikova Daria A. , Kardonsky Dmitry A. , Efimov Boris A. , Ivanov Viktor A. , Evsiev Suleiman S. , Zubkov Eugene A. , Abramova Olga V. , Zorkina Yana A. , Morozova Anna Y. , Vorobeva Elizaveta A. , Silantiev Artemiy S. , Kolesnikova Irina V. , Markelova Maria I. , Olekhnovich Evgenii I. , Morozov Maxim D. , Zoruk Polina Y. , Boldyreva Daria I. , Vanyushkina Anna A. , Chaplin Andrei V. , Grigoryeva Tatiana V. , Zakharzhevskaya Natalya B. 
Published: March 2024

AbstractInflammatory bowel diseases are characterized by chronic intestinal inflammation and alterations of gut microbiota composition.Bacteroides fragilis, which secretes outer membrane vesicles (OMVs) with polysaccharide A (PSA), can moderate inflammatory response and possibly alter microbiota composition. In this research, we created a murine model of chronic DSS- induced intestinal colitis and treated it withBacteroides fragilisOMVs. We monitored the efficiency of OMVs therapy by determining the disease activity index (DAI) and histological examination (HE) of the intestine before and after vesicles exposure. We also analyzed the microbiota composition using 16S rRNA gene sequencing. Finally, we evaluated the volatile compounds composition in animals’ stools by HS-GC/MS to assess the functional activity of the microbiota. As a result, we observed a more effective intestine repair after OMVs treatment according to DAI and HE. The metabolomic study also indicated the microbiota functional activity change, showing a predominance of phenol and pentanoic acid in the control group compared to the group treated with DSS (DSS) and the group treated with OMVs (DSS OMV). We also observed a positive correlation of these metabolites withSaccharibacteriaandHungatei Clostridiumin the control group, whereas in the DSS group there was a negative correlation of phenol and pentanoic acid withLactococcusandRomboutsia. According to metabolome and sequencing data, the microbiota composition of the DSS OMV group was intermediate between the control and DSS groups. It can be concluded that OMVs not only have an anti-inflammatory effect, but also contribute to the recovery of the microbiota composition.
High-Throughput Phenotyping of Seed Quality Traits Using Imaging and Deep Learning in Dry Pea
Authors: Morales Mario Andres , Worral Hannah , Piche Lisa , Adeniyi Atanda Sikiru , Dariva Francoise , Ramos Catalina , Hoang Khang , Yan Changhui , Flores Paulo , Bandillo Nonoy 
Published: March 2024

AbstractSeed traits, such as seed color and seed size, directly impact seed quality, affecting the marketability and value of dry peas [1]. Assessing seed quality is integral to a plant breeding programs to ensure optimal seed standards. This research introduced a phenotyping tool to assess seed quality traits specifically tailored for pulse crops, which integrates image processing with cutting-edge deep learning models. The proposed method is designed for automation, seamlessly processing a sequence of images while minimizing human intervention. The pipeline standardized red-green-blue (RGB) images captured from a color light box and used deep learning models to segment and detect seed features. Our method extracted up to 86 distinct seed characteristics, ranging from basic size metrics to intricate texture details and color nuances. Compared to traditional methods, our pipeline demonstrated a 95 percent similarity in seed quality assessment and increased time efficiency (from 2 weeks to 30 minutes for processing time). Specifically, we observed an improvement in the accuracy of seed trait identification by simply using an RGB value instead of a categorical, non-standard description, which allowed for an increase in the range of detectable seed quality characteristics. By integrating conventional image processing techniques with foundational deep learning models, this approach emerges as a pivotal instrument in pulse breeding programs, guaranteeing the maintenance of superior seed quality standards.
P
-wave states
Tbb−
from diquarks
Authors: Lin Zu-Hang , An Chun-Sheng , Deng Cheng-Rong 
Published: March 2024

We investigate the P-wave states Tbb− in the isospin singlet and three excited modes [excitation occurring in the diquark [bb]c1s1 (ρ-mode), antidiquark [u¯d¯]c2s2 (r-mode), or between them (λ-mode)] from diquarks in a quark model. We analyze the dynamical behaviors of the diquark [bb]c1s1, antidiquark [u¯d¯]c2s2, and their correlations in the states Tbb− by decomposing the interactions from various sources in the model. The absolute dominant color-spin configuration, more than 99%, in the ρ-mode with 1P11 is [bb]3¯0[u¯d¯]30. Its energy is lower by about 18 MeV than the threshold B¯B¯ so that it can establish a compact bound state. The chromomagnetic and meson-exchange interactions in the antidiquark [u¯d¯]30 are responsible for its binding mechanism. Two other excited modes are higher than their respective threshold. The color configuration 6⊗6¯ need to be handled discreetly in the tetraquark states.

Published by the American Physical Society
2024