bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developmental disruption of the mitochondrial fission genedrp-1extends the longevity ofdaf-2insulin/IGF-1 receptor mutant
Authors: Traa Annika , Van Raamsdonk Jeremy M. 
Published: February 2024

AbstractThe dynamic nature of the mitochondrial network is regulated by mitochondrial fission and fusion, allowing for re-organization of mitochondria to adapt to the cell’s ever-changing needs. As organisms age, mitochondrial fission and fusion become dysregulated and mitochondrial networks become increasingly fragmented. Modulation of mitochondrial dynamics has been shown to affect longevity in fungi, yeast,DrosophilaandC. elegans. While disruption of the mitochondrial fission genedrp-1only mildly increases wild-type lifespan, it drastically increases the already long lifespan ofdaf-2insulin/IGF-1 signaling (IIS) mutants. In this work, we determined the conditions required fordrp-1disruption to extenddaf-2longevity and explored the molecular mechanisms involved. We found that knockdown ofdrp-1during development is sufficient to extenddaf-2lifespan, while tissue-specific knockdown ofdrp-1in neurons, intestine or muscle failed to increasedaf-2longevity. Disruption of other genes involved in mitochondrial fission also increaseddaf-2lifespan as did treatment with a number of different RNAi clones that decrease mitochondrial fragmentation. In exploring potential mechanisms involved, we found that deletion ofdrp-1increases resistance to chronic stresses and slows physiologic rates indaf-2worms. In addition, we found that disruption ofdrp-1increased mitochondrial and peroxisomal connectedness indaf-2worms, increased oxidative phosphorylation and ATP levels, and increased mitophagy indaf-2worms, but did not affect their ROS levels or mitochondrial membrane potential. Overall, this work defined the conditions under whichdrp-1disruption increasesdaf-2lifespan and has identified multiple changes indaf-2;drp-1mutants that may contribute to their lifespan extension.
Dimensionality reduction distills complex evolutionary relationships in seasonal influenza and SARS-CoV-2
Authors: Nanduri Sravani , Black Allison , Bedford Trevor , Huddleston John 
Published: February 2024

AbstractPublic health researchers and practitioners commonly infer phylogenies from viral genome sequences to understand transmission dynamics and identify clusters of genetically-related samples. However, viruses that reassort or recombine violate phylogenetic assumptions and require more sophisticated methods. Even when phylogenies are appropriate, they can be unnecessary or difficult to interpret without specialty knowledge. For example, pairwise distances between sequences can be enough to identify clusters of related samples or assign new samples to existing phylogenetic clusters. In this work, we tested whether dimensionality reduction methods could capture known genetic groups within two human pathogenic viruses that cause substantial human morbidity and mortality and frequently reassort or recombine, respectively: seasonal influenza A/H3N2 and SARS-CoV-2. We applied principal component analysis (PCA), multidimensional scaling (MDS), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection (UMAP) to sequences with well-defined phylogenetic clades and either reassortment (H3N2) or recombination (SARS-CoV-2). For each low-dimensional embedding of sequences, we calculated the correlation between pairwise genetic and Euclidean distances in the embedding and applied a hierarchical clustering method to identify clusters in the embedding. We measured the accuracy of clusters compared to previously defined phylogenetic clades, reassortment clusters, or recombinant lineages. We found that MDS embeddings accurately represented pairwise genetic distances including the intermediate placement of recombinant SARS-CoV-2 lineages between parental lineages. Clusters from t-SNE embeddings accurately recapitulated known phylogenetic clades, H3N2 reassortment groups, and SARS-CoV-2 recombinant lineages. We show that simple statistical methods without a biological model can accurately represent known genetic relationships for relevant human pathogenic viruses. Our open source implementation of these methods for analysis of viral genome sequences can be easily applied when phylogenetic methods are either unnecessary or inappropriate.
Full 16S and 23S rRNA gene-based,strain-level resolution of the microbiota of a mock bacterial microbiome using ONT nanopore sequencing
Authors: Woodruff Christopher J. , Zhang Zhengming , Speed Terence P. 
Published: February 2024

AbstractPurposeThe feasibility of achieving near-strain taxonomic resolution and reliable microbiota strain-level abundance estimation using amplicon-based nanopore sequencing was investigated.MethodsDenoising was applied to separate 16S and 23S genes extracted from a metagenomic dataset generated by Sereika et al. [9] using nanopore sequencing. Denoising used Kumar et al.’s [8] Robust Amplicon Denoising (RAD) and generated amplicon sequence variants (ASVs). The Sereika et al. data set was generated from the Zymo [10] D6322 7-bacterial species mock microbiome. A sub-sampling procedure generated additional datasets that allowed sensitivity assessment over multiple orders of relative abundance. Alignment to bespoke 16S and 23S rRNA gene databases, provided both identification and abundance information data for sub-species analyses.ResultsSub-species identification was clearly achieved, both with the “even” D6322 dataset, and with the 4 sub-sampled datasets in which 3-orders of magnitude relative abundances were present. Multiple ASVs of length approximately 2500 bases were generated which gave perfect alignments to reference 23S rRNA genes. Similarly for the approximately 1500 base long 16S rRNA genes. Despite strain ambiguity for some species, the strain of each species known to be present was identified in all but 1 (of 70) cases examined for all species. A process to merge the 16S and 23S rRNA genes results reduced ambiguity, allowing better sub-species resolution, and better species, and sub-species, relative cellular abundance estimates.ConclusionPrincipled methods for dealing with strain-level ambiguity in microbiota analysis have been developed that are generally applicable. Their application to nanopore sequencing with the current state of Oxford Nanopore Technology, together with state-of-the-art denoising, allows near strain resolution of bacterial microbiota identity, and improved estimates of species, and sub-species, relative abundances.
Predicting COVID-19 booster immunogenicity against future SARS-CoV-2 variants and the benefits of vaccine updates
Authors: Cromer Deborah , Reynaldi Arnold , Hie Ainslie , Schlub Timothy E. , Juno Jennifer A. , Wheatley Adam K. , Kent Stephen J. , Khoury David S. , Davenport Miles P. 
Published: February 2024

AbstractThe ongoing evolution of the SARS-CoV-2 virus has led to a move to update vaccine antigens in 2022 and 2023. These updated antigens were chosen and approved based on in vitro neutralisation titres against recent SARS-CoV-2 variants. However, unavoidable delays in viral manufacture and distribution meant that the updated booster vaccine was no longer well matched to the circulating SARS-CoV-2 variant by the time of its deployment. Understanding whether the updating of booster vaccine antigens improves immune responses to subsequent SARS-CoV-2 circulating variants is a major priority in justifying future vaccine updates. Here we analyse all available data on the immunogenicity of variant containing SARS-CoV-2 vaccines and their ability to neutralise later circulating SARS-CoV-2 variants. We find that updated booster antigens give a 1.4-fold [95%CI 1.07-1.82] greater increase in neutralising antibody levels when compared with a historical vaccine immunogen. We then use this to predict the relative protection that can be expected from an updated vaccine even when the circulating variant has evolved away from the updated vaccine immunogen. These findings help inform the roll out of future booster vaccination programs.
Couple-Centered HIV Prevention and Care: Endorsement, Practice and Uncertainty among US Healthcare Providers in Western-Central Upstate New York
Authors: Leblanc Natalie M. , Muheriwa-Matemba Sadandaula R. , Vil Noelle St. , Alcena-Stiner Danielle , Bond Keosha T. , Glazier Alexander , Rosario-McCabe Luis , Lambert Faith , Smith Martez 
Published: February 2024

AbstractGiven the influence of provider perspective and practice in the uptake of HIV/STI prevention and care strategies, this qualitative description design study sought to illuminate perspectives of couples HIV testing and counseling (CHTC), and describe couple/partner-based practices among health providers in New York State. We utilized a purposive sampling strategy to recruit health providers (N = 27). Semi-structured in-depth interviews were conducted from Sept. 2019 to Feb. 2021. Four themes emerged: perspectives on engaging partners and couples-centered sexual health promotion; providers’ experiences with patients and partners in HIV prevention and care; provider endorsement of CHTC; and perceived CHTC implementation determinants. CHTC endorsement was prominently due to the perception of CHTC as a facilitator to enhance patient-provider engagement in HIV/STI treatment and care, especially in the communication and dissemination of information among partners. Providers reported that health literacy needs regarding HIV/STI testing and diagnosis, but primarily STIs treatment regimens warranted a joint approach. CHTC endorsement entailed the strategy’s perceived ability to enhance sexual health literacy among patients and patient’s partners. Lastly, CHTC endorsements entailed provider beliefs that it ensured knowledge equity and joint literacy in the communication of health information among health consumers. Determinants of CHTC implementation were factors that providers perceived to have a bearing on the facilitation or posed as barriers to jointly engaging partners in HIV/STI prevention and care and was subsequently a source of provider uncertainty. These determinants ranged from provider-level factors to organizational capacity issues that could impact CHTC implementation. Recommendations for CHTC are discussed.
STREAMLINED PROTEOME-WIDE IDENTIFICATION OF DRUG TARGETS INDICATES ORGAN-SPECIFIC ENGAGEMENT
Authors: Batth Tanveer Singh , Locard-Paulet Marie , Doncheva Nadezhda T. , Mendez Blanca Lopez , Jensen Lars Juhl , Olsen Jesper Velgaard 
Published: February 2024

ABSTRACTProteins are the primary targets of almost all small molecule drugs. However, even the most selectively designed drugs can potentially target several unknown proteins. Identification of potential drug targets can facilitate design of new drugs and repurposing of existing ones. Current state-of-the-art proteomics methodologies enable screening of thousands of proteins against a limited number of drug molecules. Here we report the development of a label-free quantitative proteomics approach that enables proteome-wide screening of small organic molecules in a scalable, reproducible, and rapid manner by streamlining the proteome integral solubility alteration (PISA) assay. We used rat organsex-vivoto determine organ specific targets of medical drugs and enzyme inhibitors to identify novel drug targets for common drugs such as Ibuprofen. Finally, global drug profiling revealed overarching trends of how small molecules affect the proteome through either direct or indirect protein interactions.
Systematic benchmarking of deep-learning methods for tertiary RNA structure prediction
Authors: Bahai Akash , Kwoh Chee Keong , Mu Yuguang , Li Yinghui 
Published: February 2024

AbstractThe 3D structure of RNA critically influences its functionality, and understanding this structure is vital for deciphering RNA biology. Experimental methods for determining RNA structures are labour-intensive, expensive, and time-consuming. Computational approaches have emerged as valuable tools, leveraging physics-based-principles and machine learning to predict RNA structures rapidly. Despite advancements, the accuracy of computational methods remains modest, especially when compared to protein structure prediction. Deep learning methods, while successful in protein structure prediction, have shown some promise for RNA structure prediction as well but face unique challenges. This study systematically benchmarks state-of-the-art deep learning methods for RNA structure prediction across diverse datasets. Our aim is to identify factors influencing performance variation, such as RNA family diversity, sequence length, RNA type, multiple sequence alignment (MSA) quality, and deep learning model architecture. We show that generally ML-based methods perform much better than non-ML methods on most RNA targets, although the performance difference isn’t substantial when working with unseen novel or synthetic RNAs. The quality of the MSA and secondary structure prediction both play an important role and most methods aren’t able to predict non-Watson-Crick pairs in the RNAs. Overall, DeepFoldRNA has the best prediction followed by DRFold as the second best method. Finally, we also suggest possible mitigations to improve the quality of the prediction for future method development.
Microglia-astrocyte crosstalk regulates synapse remodeling via Wnt signaling
Authors: Faust Travis E. , Lee Yi-Han , O’Connor Ciara D. , Boyle Margaret A. , Gunner Georgia , Badimon Ana , Ayata Pinar , Schaefer Anne , Schafer Dorothy P. 
Published: February 2024

SummaryAstrocytes and microglia are emerging key regulators of activity-dependent synapse remodeling that engulf and remove synapses in response to changes in neural activity. Yet, the degree to which these cells communicate to coordinate this process remains an open question. Here, we use whisker removal in postnatal mice to induce activity-dependent synapse removal in the barrel cortex. We show that astrocytes do not engulf synapses in this paradigm. Instead, astrocytes reduce their contact with synapses prior to microglia-mediated synapse engulfment. We further show that reduced astrocyte-contact with synapses is dependent on microglial CX3CL1-CX3CR1 signaling and release of Wnts from microglia following whisker removal. These results demonstrate an activity-dependent mechanism by which microglia instruct astrocyte-synapse interactions, which then provides a permissive environment for microglia to remove synapses. We further show that this mechanism is critical to remodel synapses in a changing sensory environment and this signaling is upregulated in several disease contexts.
Development of an improved blood-stage malaria vaccine targeting the essential RH5-CyRPA-RIPR invasion complex
Authors: Williams Barnabas G. , King Lloyd D. W. , Pulido David , Quinkert Doris , Lias Amelia M. , Silk Sarah E. , Ragotte Robert J. , Davies Hannah , Barrett Jordan R. , McHugh Kirsty , Rigby Cassandra A. , Alanine Daniel G. W. , Barfod Lea , Shea Michael W. , Cowley Li An , Dabbs Rebecca A. , Pattinson David J. , Douglas Alexander D. , Lyth Oliver R. , Illingworth Joseph J. , Jin Jing , Carnrot Cecilia , Kotraiah Vinayaka , Christen Jayne M. , Noe Amy R. , MacGill Randall S. , King C. Richter , Birkett Ashley J. , Soisson Lorraine A. , Skinner Katherine , Miura Kazutoyo , Long Carole A. , Higgins Matthew K. , Draper Simon J. 
Published: February 2024

ABSTRACTIn recent years, reticulocyte-binding protein homologue 5 (RH5) has emerged as a leading blood-stagePlasmodium falciparummalaria vaccine antigen. The most advanced blood-stage vaccine candidate in a Phase 2b clinical trial, RH5.1/Matrix-M™, is based on a full-length soluble protein-with-adjuvant formulation. RH5 interacts with cysteine-rich protective antigen (CyRPA) and RH5- interacting protein (RIPR) to form an essential heterotrimeric “RCR-complex”. Here, we investigated whether a vaccine candidate based on the ternary RCR-complex could substantially improve upon the leading clinical candidate RH5.1/Matrix-M™ in preclinical studies. Using a panel of monoclonal antibodies (mAbs) we confirm that parasite growth-inhibitory epitopes on each antigen are exposed on the surface of the RCR-complex and that mAb pairs binding to different antigens can function additively or synergistically to mediate parasite growth inhibition activity (GIA)in vitro. However, immunisation of rats with the RCR-complex consistently fails to outperform RH5.1 alone. We show this is due to immuno-dominance of RIPR coupled with the inferior potency of anti-full length RIPR polyclonal IgG antibodies as compared to the anti-RH5 and anti-CyRPA response. To address this, we identified the growth-inhibitory antibody epitopes of RIPR are clustered within C-terminal EGF-like domains of RIPR. A fusion of these EGF domains to CyRPA, called “R78C”, combined with RH5.1, provided a new vaccination strategy that improves upon the levels ofin vitroGIA seen with RH5.1 alone. Superiority of the combination antigen vaccine candidate was achieved by the induction of a quantitatively higher, but qualitatively similar, polyclonal antibody response that demonstrated additive GIA across the three antigen targets. These preclinical data justified the advancement of the RH5.1+R78C/Matrix-M™ combination vaccine to a Phase 1 clinical trial.
Microbial Electrosynthesis from CO2reaches Productivity of Syngas and Chain Elongation Fermentations
Authors: Cabau-Peinado Oriol , Winkelhorst Marijn , Stroek Rozanne , de Kat Angelino Roderick , Straathof Adrie J.J. , Masania Kunal , Daran Jean Marc , Jourdin Ludovic 
Published: February 2024

SummaryMicrobial electrosynthesis allows the electrochemical upgrading of CO2. However, higher productivities and energy efficiencies are needed to reach a viability that can make the technology transformative. Here we show how a biofilm-based microbial porous cathode in a directed flow-through electrochemical system can continuously reduce CO2to even-chain C2-C6 carboxylic acids during 248 days. We demonstrate a 3-fold higher biofilm concentration, volumetric current density, and productivity than the state of the art, up to a new record of -35 kA m-3cathodeand 69 kgCm-3cathodeday-1, at 60-97% and 30-35% faradaic and energy efficiencies, respectively. Most notably, the volumetric productivity resembles those achieved in lab-scale and industrial syngas (CO-H2-CO2) fermentation and chain elongation fermentation. This work highlights key design parameters for efficient electricity-driven microbial CO2reduction. There is need and room to improve the rates of electrode colonization and microbe-specific kinetics to scale-up the technology.Graphical abstract
Systematic annotation ofHelitron-like elements in eukaryote genomes using HELIANO
Authors: Li Zhen , Gilbert Clément , Peng Haoran , Pollet Nicolas 
Published: February 2024

AbstractHelitron-like elements (HLEs) are widespread eukaryotic DNA transposons employing a rolling-circle transposition mechanism. Despite their prevalence in fungi, animals, and plant genomes, identifyingHelitronsremains challenging. We introduce HELIANO, a software for annotating and classifying autonomous and non-autonomousHelitronandHelentronsequences from whole genomes. HELIANO outperforms existing tools in speed and accuracy, demonstrated through benchmarking and its application to complex genomes (Xenopus tropicalis, Xenopus laevis, Oryza sativa), revealing numerous newly identifiedHelitronsandHelentrons.In a comprehensive analysis of 404 eukaryote genomes, we found HLEs widely distributed across phyla, with exceptions in specific taxa.Helentronswere identified in numerous land plant species, and 20 protein domains were discovered integrated within specific autonomous HLE families. A global phylogenetic analysis confirmed the classification into main cladesHelentronandHelitron, revealing nine subgroups, some enriched in particular taxa. The future use of HELIANO will contribute to the global analysis of TEs across genomes and enhance our understanding of this transposon superfamily.
Mapping Serotonergic Dynamics using Drug-Modulated Molecular Connectivity
Authors: Ionescu TM , Amend M , Hafiz R , Maurer A , Biswal BB , Wehrl HF , Herfert K 
Published: February 2024

AbstractUnderstanding the complex workings of the brain is one of the most significant challenges in neuroscience, providing insights into normal brain function, neurological diseases, and the effects of potential therapeutics. A major challenge in this field lies in the limitations of traditional brain imaging techniques, which often capture only fragments of the complex puzzle of brain function. Our research employs a novel approach termed “molecular connectivity” (MC), which combines the strengths of various imaging methods to provide a comprehensive view of how specific molecules, such as the serotonin transporter, interact across different brain regions and influence brain function.This innovative technique bridges the gap between functional magnetic resonance imaging (fMRI), known for its ability to monitor brain activity by tracking blood flow, and positron emission tomography (PET), which visualizes specific molecular changes. By integrating these methods, we can better understand how drugs influence brain function. Our study focuses on the application of dynamic [11C]DASB PET scans to map the distribution of serotonin transporters, key players in regulating mood and emotions and examines how these transporters are altered following exposure to methylenedioxymethamphetamine (MDMA), which is commonly known as ecstasy.Through a detailed comparison of MCs with traditional measures of brain connectivity, we reveal significant patterns that closely align with physiological changes. Our results revealed clear changes in molecular connectivity after a single dose of MDMA, establishing a direct link between the effects of drugs on serotonin transporter occupancy and changes in the functional brain network.This work offers a novel methodology for the in-depth study of brain function at the molecular level and opens new pathways for understanding how drugs modulate brain activity.