bluuebunny/crossref_metadata_2025_split huggingface dataset:
SIRT5variants from patients with mitochondrial disease are associated with reduced SIRT5 stability and activity, but not with neuropathology
Authors: Yuan Taolin , Kumar Surinder , Skinner Mary , Victor-Joseph Ryan , Abuaita Majd , Keijer Jaap , Zhang Jessica , Kunkel Thaddeus J. , Liu Yanghan , Petrunak Elyse M. , Saunders Thomas L. , Lieberman Andrew P. , Stuckey Jeanne A. , Neamati Nouri , Al-Murshedi Fathiya , Alfadhel Majid , Spelbrink Johannes N. , Rodenburg Richard , de Boer Vincent C. J. , Lombard David B. 
Published: December 2023

SummarySIRT5 is a sirtuin deacylase that represents the major activity responsible for removal of negatively-charged lysine modifications, in the mitochondrial matrix and elsewhere in the cell. In benign cells and mouse models, under basal non-stressed conditions, the phenotypes of SIRT5 deficiency are generally quite subtle. Here, we identify two homozygousSIRT5variants in human patients suffering from severe mitochondrial disease. Both variants, P114T and L128V, are associated with reduced SIRT5 protein stability and impaired biochemical activity, with no evidence of neomorphic or dominant negative properties. The crystal structure of the P114T enzyme was solved and shows only subtle deviations from wild-type. Via CRISPR-Cas9, we generate a mouse model that recapitulates the human P114T mutation; homozygotes show reduced SIRT5 levels and activity, but no obvious metabolic abnormalities, neuropathology or other gross evidence of severe disease. We conclude that these humanSIRT5variants most likely represent severe hypomorphs, and are likely not the primary pathogenic cause of the neuropathology observed in the patients.
Trade-off between light deprivation and desiccation in intertidal seagrasses due to periodic tidal inundation and exposure: insights from a data-calibrated model
Authors: Wang Xinyan , Adams Matthew P. , Shao Dongdong 
Published: December 2023

AbstractMany seagrass species thrive in shallow intertidal zones globally, adapting to periodic tidal inundation and exposure with distinctive physiological traits and offering crucial ecosystem services. However, predicting the responses of intertidal seagrasses to external stressors is hampered by the complexity of the dynamic and harsh environments they occupy. Consequently, intertidal seagrass growth models, especially those incorporating dynamic physiological responses, are scarce in the literature. Our study comprehensively collated relevant data from the literature to parameterize the relationship between air exposure, seagrass leaf water content and photosynthetic efficiency to inform new growth rate functions for generalisable intertidal seagrass growth models. We tested the applicability of these model formulations for scenarios with varying physiological process assumptions, seagrass species, tidal conditions, meadow elevations and water turbidity. We found that neglecting air-exposed physiological responses (i.e., leaf water content loss and reduced photosynthetic efficiency) can substantially overestimate seagrass growth rates. We also observed a trade-off between light deprivation and desiccation on intertidal seagrass growth under specific tidal ranges and turbidity conditions. This can yield an “optimal” elevation where combined stressors of desiccation (increasing with meadow elevation) and light deprivation (decreasing with meadow elevation) are minimized. The predicted optimal elevation, i.e., the most suitable habitat for intertidal seagrass, moves upward as water turbidity increases. Our study provides both conceptual and quantitative guidance for ecological modellers to include air exposure responses of intertidal seagrasses in coastal ecosystem models. The model also helps to evaluate the viability of intertidal seagrass habitats and inform site selection for seagrass restoration.
A 3-component module maintains sepal flatness in Arabidopsis
Authors: Xu Shouling , He Xi , Trinh Duy-Chi , Zhang Xinyu , Wu Xiaojiang , Qiu Dengying , Zhou Ming , Xiang Dan , Roeder Adrienne H. K. , Hamant Olivier , Hong Lilan 
Published: December 2023

AbstractAs in origami, morphogenesis in living systems heavily relies on tissue curving and folding, through the interplay between biochemical and biomechanical cues. In contrast, certain organs maintain their flat posture over several days. Here we identified a pathway, which is required for the maintenance of organ flatness, taking the sepal, the outermost floral organ, in Arabidopsis as a model system. Through genetic, cellular and mechanical approaches, our results demonstrate that global gene expression regulator VERNALIZATION INDEPENDENCE 4 (VIP4) fine-tunes the mechanical properties of sepal cell walls and maintains balanced growth on both sides of the sepals, mainly by orchestrating the distribution pattern of AUXIN RESPONSE FACTOR 3 (ARF3).vip4mutation results in softer cell walls and faster cell growth on the adaxial sepal side, which eventually cause sepals to bend outward. Downstream of VIP4, ARF3 works through modulating auxin signaling to down-regulate pectin methylesterase VANGUARD1, resulting in decreased cell wall stiffness. Our work unravels a 3-component module, which relates hormonal patterns to organ curvature, and actively maintains sepal flatness during its growth.
A maternal-to-zygotic-transition gene block on the zebrafish sex chromosome
Authors: Wilson Catherine A. , Postlethwait John H. 
Published: December 2023

ABSTRACTWild zebrafish (Danio rerio) have a ZZ/ZW chromosomal sex determination system with the major sex locus on the right arm of chromosome-4 (Chr4R) near the largest heterochromatic block in the genome, suggesting the hypothesis that the Chr4R transcriptome might be different from the rest of the genome. We conducted an RNA-seq analysis of adult ZW ovaries and ZZ testes and identified four regions of Chr4 with different gene expression profiles. Unique in the genome, protein-coding genes in a 41.7 Mb section (Region-2) were expressed in testis but silent in ovary. The AB lab strain, which lacks sex chromosomes, verified this result, showing that testis-biased gene expression in Region-2 depends on gonad biology, not on sex-determining mechanism. RNA-seq analyses in female and male brain and liver validated few transcripts from Region-2 in somatic cells, but without sex-specificity. Region-2 corresponds to the heterochromatic portion of Chr4R and its content of genes and repetitive elements distinguishes it from the rest of the genome. In Region-2, protein-coding genes lack human orthologs; it has zinc finger genes expressed early in zygotic genome activation; it has maternal 5S rRNA genes, maternal spliceosome genes, a concentration of tRNA genes, and an distinct set of repetitive elements. The colocalization of 1) genes silenced in ovaries but not in testes that are 2) expressed in embryos briefly at the onset of zygotic genome activation; 3) maternal-specific genes for translation machinery; 4) maternal-specific spliceosome components; and 4) adjacent genes encoding miR-430, which mediates maternal transcript degradation, suggest that this is a Maternal-to-Zygotic-Transition Gene Regulatory Block.ARTICLE SUMMARYThe wild zebrafish sex chromosome has a region, unique in the genome, that contains protein-coding genes silenced in ovaries but expressed in testes and transiently in the embryo as it begins to express its own genes. This region also contains maternal-specific genes encoding the protein-synthesis machinery used specifically by developing embryos, and molecules that target for degradation messenger RNAs that the mother stored in her eggs. This region defines a distinct maternal-to-zygotic-transition gene block.
Bioluminescence-Based Determination of Cytosolic Accumulation of Antibiotics inEscherichia coli
Authors: Dash Rachita , Holsinger Kadie A. , Chordia Mahendra D. , Sharifian Gh. Mohammad , Pires Marcos M. 
Published: December 2023

AbstractAntibiotic resistance is an alarming public health concern that affects millions of individuals across the globe each year. A major challenge in the development of effective antibiotics lies in their limited ability to permeate into cells, noting that numerous susceptible antibiotic targets reside within the bacterial cytosol. Consequently, improving cellular permeability is often a key consideration during antibiotic development, underscoring the need for reliable methods to assess the permeability of molecules across cellular membranes. Currently, methods used to measure permeability often fail to discriminate between arrival within the cytoplasm and the overall association of molecules with the cell. Additionally, these techniques typically possess throughput limitations. In this work, we describe a luciferase-based assay designed for assessing the permeability of molecules into the cytosolic compartment of Gram-negative bacteria. Our findings demonstrate a robust system that can elucidate the kinetics of intracellular antibiotics accumulation in live bacterial cells in real time.
Mutational signature decomposition with deep neural networks reveals origins of clock-like processes and hypoxia dependencies
Authors: Serrano Colome Claudia , Canal Anton Oleguer , Seplyarskiy Vladimir , Weghorn Donate 
Published: December 2023

AbstractDNA mutational processes generate patterns of somatic and germline mutations. A multitude of such mutational processes has been identified and linked to biochemical mechanisms of DNA damage and repair. Cancer genomics relies on these so-called mutational signatures to classify tumours into subtypes, navigate treatment, determine exposure to mutagens, and characterise the origin of individual mutations. Yet, state-of-the-art methods to quantify the contributions of different mutational signatures to a tumour sample frequently fail to detect certain mutational signatures, work well only for a relatively high number of mutations, and do not provide comprehensive error estimates of signature contributions. Here, we present a novel approach to signature decomposition using artificial neural networks that addresses these problems. We show that our approach, SigNet, outperforms existing methods by learning the prior frequencies of signatures and their correlations present in real data. Unlike any other method we tested, SigNet achieves high prediction accuracy even with few mutations. We used this to generate estimates of signature weights for more than 7500 tumours for which only whole-exome sequencing data are available. We then identified systematic differences in signature activity both as a function of epigenetic covariates and over the course of tumour evolution. This allowed us to decipher the origins of signatures SBS3, SBS5 and SBS40. We further discovered novel associations of mutational signatures with hypoxia, including strong positive correlations with the activities of clock-like and defective DNA repair mutational processes. These results provide new insights into the interplay between tumour biology and mutational processes and demonstrate the utility of our novel approach to mutational signature decomposition, a crucial part of cancer genomics studies.
ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers
Authors: Notin Pascal , Weitzman Ruben , Marks Debora S. , Gal Yarin 
Published: December 2023

AbstractProtein design holds immense potential for optimizing naturally occurring proteins, with broad applications in drug discovery, material design, and sustainability. How-ever, computational methods for protein engineering are confronted with significant challenges, such as an expansive design space, sparse functional regions, and a scarcity of available labels. These issues are further exacerbated in practice by the fact most real-life design scenarios necessitate the simultaneous optimization of multiple properties. In this work, we introduce ProteinNPT, a non-parametric trans-former variant tailored to protein sequences and particularly suited to label-scarce and multi-task learning settings. We first focus on the supervised fitness prediction setting and develop several cross-validation schemes which support robust perfor-mance assessment. We subsequently reimplement prior top-performing baselines, introduce several extensions of these baselines by integrating diverse branches of the protein engineering literature, and demonstrate that ProteinNPT consistently outperforms all of them across a diverse set of protein property prediction tasks. Finally, we demonstrate the value of our approach for iterative protein design across extensive in silico Bayesian optimization and conditional sampling experiments.
Selective lipid recruitment by an archaeal DPANN symbiont from its host
Authors: Ding Su , Hamm Joshua N. , Bale Nicole J. , Sinninghe Damsté Jaap S. , Spang Anja 
Published: December 2023

AbstractThe symbiontCa.Nanohaloarchaeum antarcticus is obligately dependent on its hostHalorubrum lacusprofundifor lipids and other metabolites due to its lack of certain biosynthetic genes. However, it remains unclear which specific lipids or metabolites are acquired from its host, and how the host responds to infection. Here, we explored the lipidome dynamics of theCa.Nha. antarcticus –Hrr. lacusprofundisymbiotic relationship during co-cultivation. By using a comprehensive untargeted lipidomic methodology, our study reveals thatCa.Nha. antarcticus selectively recruits 110 lipid species from its host, i.e. nearly two-thirds of the total number of host lipids. Lipid profiles of co-cultures displayed shifts in abundances of bacterioruberins and menaquinones and changes in degree of bilayer-forming glycerolipid unsaturation. This likely results in increased membrane fluidity and improved resistance to membrane disruptions, consistent with compensation for higher metabolic load and mechanical stress on host membranes when in contact withCa.Nha. antarcticus cells. Notably, our findings differ from previous observations of other DPANN symbiont-host systems, where no differences in lipidome composition were reported. Altogether, our work emphasizes the strength of employing untargeted lipidomics approaches to provide details into the dynamics underlying a DPANN symbiont-host system.
CRISPR-HOLMES-based NAD+detection
Authors: Zhuang Songkuan , Hu Tianshuai , Zhou Hongzhong , He Shiping , Li Jie , Zhang Yuehui , Gu Dayong , Xu Yong , Chen Yijian , Wang Jin 
Published: December 2023

AbstractStudies have indicated that intracellular nicotinamide adenine dinucleotide (NAD+) level is associated with the occurrence and development of many diseases. While traditional NAD+detection techniques are time-consuming and may require large and expensive instruments. We recently found that the CRISPR-Cas12a protein can be inactivated by AcrVA5-mediated acetylation and reactivated by CobB, using NAD+as the co-factor. Therefore, here in this study, we created a CRISPR-Cas12a-based one-step HOLMES(NAD) system for rapid and convenient NAD+detection with the employment of both acetylated Cas12a and CobB. In HOLMES(NAD), acetylated Cas12a losses itstrans-cleavage activates and can be reactivated by CobB at the presence of NAD+, cutting ssDNA reporters to generate fluorescence signals. HOLMES(NAD) shows both sensitivity and specificity in NAD+detection and can be used for quantitative determination of intracellular NAD+concentrations. Therefore, HOLMES(NAD) not only provides a convenient and rapid approach for target NAD+quantitation but also expands the application scenarios of HOLMES to non-nucleic acid detection.
Metabolomics of Mouse Embryonic CSF Following Maternal Immune Activation
Authors: Petrova Boryana , Lacey Tiara E , Culhane Andrew J , Cui Jin , Raskin Alexander , Misra Aditya , Lehtinen Maria K , Kanarek Naama 
Published: December 2023

AbstractThe cerebrospinal fluid (CSF) serves various roles in the developing central nervous system (CNS), from neurogenesis to lifelong cognitive functions. Changes in CSF composition due to inflammation can impact brain function. We recently identified an abnormal cytokine signature in embryonic CSF (eCSF) following maternal immune activation (MIA), a mouse model of autism spectrum disorder (ASD). We hypothesized that MIA leads to other alterations in eCSF composition and employed untargeted metabolomics to profile changes in the eCSF metabolome in mice after inducing MIA with polyI:C. We report these data here as a resource, include a comprehensive MS1and MS2reference dataset, and present additional datasets comparing two mouse strains (CD-1 and C57Bl/6) and two developmental time points (E12.5 and E14.5). Targeted metabolomics further validated changes upon MIA. We show a significant elevation of glucocorticoids and kynurenine pathway related metabolites. Both pathways are relevant for suppressing inflammation or could be informative as disease biomarkers. Our resource should inform future mechanistic studies regarding the etiology of MIA neuropathology and roles and contributions of eCSF metabolites to brain development.
scDiffEq: drift-diffusion modeling of single-cell dynamics with neural stochastic differential equations
Authors: Vinyard Michael E. , Rasmussen Anders W. , Li Ruitong , Klein Allon M. , Getz Gad , Pinello Luca 
Published: December 2023

AbstractSingle-cell sequencing measurements facilitate the reconstruction of dynamic biology by capturing snapshot molecular profiles of individual cells. Cell fate decisions in development and disease are orchestrated through an intricate balance of deterministic and stochastic regulatory events. Drift-diffusion equations are effective in modeling single-cell dynamics from high-dimensional single-cell measurements. While existing solutions describe the deterministic dynamics associated with the drift term of these equations at the level of cell state, diffusion is modeled as a constant across cell states. To fully understand the dynamic regulatory logic in development and disease, models explicitly attuned to the balance between deterministic and stochastic biology are required. To address these limitations, we introduce scDiffEq, a generative framework for learning neural stochastic differential equations that approximate biology’s deterministic and stochastic dynamics. Using lineage-traced single-cell data, we demonstrate that scDiffEq offers an improved reconstruction of cell trajectories and prediction of cell fate from multipotent progenitors during hematopoiesis. By impartingin silicoperturbations to multipotent progenitor cells, we find that scDiffEq accurately recapitulates the dynamics of CRISPR-perturbed hematopoiesis. We generalize this approach beyond lineage-traced or multi-time point datasets to model the dynamics of single-cell data from a single time point. Using scDiffEq, we simulate high-resolution developmental cell trajectories, which can model their drift and diffusion, enabling us to study their time-dependent gene-level dynamics.
Reward circuit function and treatment outcome following vALIC deep brain stimulation in treatment-resistant depression
Authors: Runia N. , van de Mortel L.A. , Smith C. L. C. , Bergfeld I.O. , de Kwaasteniet B.P. , Luigjes J. , van Laarhoven J. , Notten P. , Beute G. , van den Munckhof P. , Schuurman P.R. , Denys D.A.J.P. , van Wingen G.A. 
Published: December 2023

AbstractDepression is associated with abnormal functioning of the reward circuit. Several deep brain stimulation (DBS) targets for treatment-resistant depression (TRD) directly modulate white matter bundles of the reward circuit. Here we investigated whether baseline reward processing in the brain is associated with ventral anterior limb of the internal capsule (vALIC) DBS outcome and whether vALIC DBS changes neural activity in the reward circuit.We studied fifteen patients with TRD who performed a monetary reward task during functional magnetic resonance imaging (fMRI) before vALIC DBS surgery, after DBS parameter optimization, and during a sham-controlled crossover phase. DBS devices were switched off during scanning for MRI safety reasons. Additionally, fifteen matched healthy controls were investigated twice to account for test-retest effects. We investigated brain responses to reward anticipation, loss anticipation, reward feedback and loss feedback.Results showed that lower baseline nucleus accumbens activation during loss anticipation and higher baseline caudate nucleus and midcingulate cortex activation during reward feedback processing were associated with worse DBS outcome. No significant changes in reward processing were observed following vALIC DBS in comparison to healthy controls or after active compared to sham stimulation. Instead, increased middle frontal gyrus responses following DBS to loss feedback was associated with better DBS outcome.These results suggest that DBS efficacy in TRD is related to individual differences in reward circuit functioning at baseline and to changes in middle frontal gyrus responses following DBS.
What factors predict ambulance pre-alerts to the emergency department? Analysis of routine data from 3 UK ambulance services
Authors: Sampson Fiona , Pilbery Richard , Herbert Esther , Goodacre Steve , Bell Fiona , Spaight Rob , Rosser Andy , Webster Peter , Millins Mark , Pountney Andy , Coster Joanne , Long Jaqui , O’Hara Rachel , Foster Alexis , Miles Jamie , Turner Janette , Boyd Aimee 
Published: December 2023

AbstractObjectiveAmbulance clinicians use pre-alert calls to advise emergency departments (EDs) of the arrival of patients requiring immediate review or intervention. Consistency of pre-alert practice is important in ensuring appropriate EDs response. We used routine data to describe pre-alert practice and explore factors affecting variation in practice.MethodsWe undertook an observational study using a linked dataset incorporating 12 months’ ambulance patient records, ambulance clinician data and emergency call data for three UK ambulance services. We used LASSO regression to identify candidate variables for multivariate logistic regression models to predict variation in pre-alert use, analysing clinician factors (role, experience, qualification, time of pre-alert during shift), patient factors (NEWS2 score, clinical working impression, age, sex) and hospital factors (receiving ED, ED handover delay status).ResultsFrom the dataset of 1,363,274 patients conveyed to ED, 142,795 (10.5%) were pre-alerted, of whom only a third were for conditions with clear pre-alert pathways (e.g. sepsis, STEMI, major trauma). Casemix (illness acuity score, clinical diagnostic impression) was the strongest predictor of pre-alert use but male patient gender, clinician role, receiving hospital, and hospital turnaround delay at receiving hospitals were also statistically significant predictors, after adjusting for casemix. There was no evidence of higher pre-alert rates in the final hour of shift.ConclusionsPre-alert decisions are determined by factors other than illness acuity and clinical diagnostic impression. Research is required to determine whether our findings are reproducible elsewhere and why non-clinical factors (e.g. patient gender) may influence pre-alert practice.