bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coevolution with a seed bank
Authors: Schwartz Daniel A. , Shoemaker William R. , Măgălie Andreea , Weitz Joshua S. , Lennon Jay T. 
Published: February 2023

ABSTRACTDormancy is as an adaptation to living in fluctuating environments. It can also influence species interactions, for example, by providing organisms with a refuge from predators and parasites. Here we test the hypothesis that dormancy generates a seed bank of protected individuals that can modify antagonistic coevolutionary dynamics. We experimentally evolved a spore-forming bacterial host along with a phage parasite that can infect active but not dormant cells. Seed banks buffered population dynamics against phage infection and retained phenotypic diversity that was otherwise lost to directional selection. By storing genetic diversity, seed banks also altered the distribution of host alleles, which contributed to dampened coevolutionary dynamics. Our findings demonstrate that dormancy generates a seed bank that can modify the eco-evolutionary outcomes of host-parasite systems.
Translational control byTrypanosoma bruceiDRBD18 contributes to the maintenance of the procyclic state
Authors: Ciganda Martin , Sotelo-Silveira José , Smith Joseph T. , Shen Shichen , Qu Jun , Smircich Pablo , Read Laurie K. 
Published: February 2023

ABSTRACTTrypanosoma bruceioccupies distinct niches throughout its life cycle, within both the mammalian and tsetse fly hosts. The immunological and biochemical complexity and variability of each of these environments require a reshaping of the protein landscape of the parasite both to evade surveillance and face changing metabolic demands. Whereas most well-studied organisms rely on transcriptional control as the main regulator of gene expression, post-transcriptional control mechanisms are particularly important inT. brucei, and these are often mediated by RNA-binding proteins. DRBD18 is aT. bruceiRNA-binding protein that interacts with ribosomal proteins and translation factors. Here, we tested a role for DRBD18 in translational control. We show that DRBD18 depletion by RNA interference leads to altered polysomal profiles with a specific depletion of heavy polysomes. Ribosome profiling analysis reveals that 101 transcripts change in translational efficiency (TE) upon DRBD18 depletion: 41 exhibit decreased TE and 60 exhibit increased TE. A further 66 transcripts are buffered,i.e. changes in transcript abundance are compensated by changes in TE such that the total translational output is expected not to change. Proteomic analysis validates these data. In DRBD18-depleted cells, a cohort of transcripts that codes for procyclic form-specific proteins is translationally repressed while, conversely, transcripts that code for bloodstream form- and metacyclic form-specific proteins are translationally enhanced. These data suggest that DRBD18 contributes to the maintenance of the procyclic state through both positive and negative translational control of specific mRNAs.
Palmitic acid reduces viability and increases production of reactive oxygen species and respiration in rat tendon-derived cells
Authors: Konar Subhajit , Hedges Christopher P , Callon Karen E , Bolam Scott , Leung Sophia , Cornish Jillian , Naot Dorit , Musson David S 
Published: February 2023

AbstractClinically, there is a positive correlation between BMI and the risk of tendinopathy. However, the underlying mechanisms are not understood. Dyslipidaemia and increased circulating free fatty acids (FFA) are associated with increased BMI. We hypothesised that increased FFA concentrations negatively affect rat tendon-derived cells (rTDCs) through mitochondrial-mediated mechanisms.rTDCs were isolated and treated with oleic acid (OA), stearic acid (SA), and palmitic acid (PA). Cell viability was assessed using AlamarBlue™ assay, and gene expression using real-time PCR. Cell respiration and reactive oxygen species (ROS) production were measured using high-resolution respirometry and MitoSox staining. PA transport into the mitochondria was blocked by pre-treatment with 50µM etomoxir.Treatment with SA and PA at 10 µg/ml decreased rTDC viability by 40% and 60%, respectively. PA decreased the gene expression of the tendon markersScxandTnmd, and increased the expression ofMmp3, Mmp13, andPtgs2(encoding Cox-2). FFA treatment increased the expression ofCpt1andPdk4, indicating an increase in mitochondrial FFA oxidation. PA, at 10 µg/ml, increased cellular respiration and ROS production. Pre-treatment with etomoxir partially inhibited the effects of PA on cell viability,Mmp3gene expression, ROS production, and cell respiration, but did not affect PA-induced inhibition ofScxorTnmdexpression.We found that increased saturated FFA concentrations in the microenvironment reduce cell viability and alter ROS production, respiration, and gene expression. Blocking PA transport into mitochondria partially reversed the negative effects of PA. Overall, an increase in saturated FFA concentrations may contribute to poor tendon health.
Deep learning distinguishes focal epilepsy groups using connectomes: Feasibility and clinical implications
Authors: Maher Christina , Tang Zihao , D’Souza Arkiev , Cabezas Mariano , Cai Weidong , Barnett Michael , Kavehei Omid , Wang Chenyu , Nikpour Armin 
Published: February 2023

AbstractThe application of deep learning models to evaluate connectome data is gaining interest in epilepsy research. Deep learning may be a useful initial tool to partition connectome data into network subsets for further analysis. Few prior works have used deep learning to examine structural connectomes from patients with focal epilepsy. We evaluated whether a deep learning model applied to whole-brain connectomes could classify 28 participants with focal epilepsy from 20 controls and identify nodal importance for each group. Participants with epilepsy were further grouped based on whether they had focal seizures that evolved into bilateral tonic-clonic seizures (17 with, 11 without). The trained neural network classified patients from controls with an accuracy of 72.92%, while the seizure subtype groups achieved a classification accuracy of 67.86%. In the patient subgroups, the nodes and edges deemed important for accurate classification were also clinically relevant, indicating the model’s interpretability. The current work expands the evidence for the potential of deep learning to extract relevant markers from clinical datasets. Our findings offer a rationale for further research interrogating structural connectomes to obtain features that can be biomarkers and aid the diagnosis of seizure subtypes.
Epigenome-wide association study using peripheral blood leukocytes identifies genomic regions associated with periodontal disease and edentulism in the Atherosclerosis Risk in Communities Study
Authors: Zhao Naisi , Teles Flavia , Lu Jiayun , Koestler Devin C. , Beck James , Boerwinkle Eric , Bressler Jan , Kelsey Karl T. , Platz Elizabeth A. , Michaud Dominique S. 
Published: February 2023

ABSTRACTAimOur goal was to investigate individual susceptibility to periodontitis by conducting an epigenome-wide association study using peripheral blood.Materials and MethodsFor this analysis, we included 1077 African American and 457 European American participants of the Atherosclerosis Risk in Communities (ARIC) study who had completed a dental examination or reported being edentulous at visit 4 and had available data on DNA methylation. DNA methylation levels were compared by periodontal disease severity and edentulism to identify differentially methylated regions (DMRs) and evaluate the CpGs belonging to those DMRs using multinominal logistic regression.ResultsWe identified a region in geneZFP57(6p22.1) that was significantly hypomethylated in severe periodontal disease compared to no/mild periodontal disease in European American participants. A separate region in an unknown gene (located in Chr10: 743,992-744,958) demonstrated significant positive association with edentulism compared to no/mild periodontal disease in African American participants. Four CpGs in a region located withinHOXA4were significantly hypermethylated in severe periodontal disease compared to no/mild periodontal disease in African American participants.ConclusionsOur study highlights epigenetic variations inZPF57andHOXA4that were significantly and reproducibly associated with periodontitis. Future studies should evaluate gene regulatory mechanisms in the candidate regions of these loci.CLINICAL RELEVANCEScientific Rationale for StudyWithout altering the DNA sequence, epigenetic effects (e.g., DNA methylation changes) can alter gene activity and influence host response to periodontal infections. Our well-powered study investigates individual susceptibility to periodontitis by conducting a thorough assessment of periodontitis-related DNA methylation levels in blood.Principal FindingsWe identified two gene regions,ZPF57andHOXA4, that are differentially methylated in individuals with compared to those without periodontitis.Practical implicationsStudying differential leukocyte DNA methylation patterns may point to candidate regions and underlying gene regulatory mechanisms that play a key role in the progression and/or susceptibility to periodontitis.
An algorithm that combines machine learning ensemble modeling and network analysis to predict self-tolerant tumor-associated antigens for anti-cancer immunotherapy
Authors: Lischer Christopher , Eberhardt Martin , Weich Adrian , Vera Julio 
Published: February 2023

AbstractTumor-associated antigens (TAAs) and their derived peptides constitute the chance to design off-the-shelf mainline or adjuvant anti-cancer immunotherapies for a broad array of patients. Here, we present a computational pipeline that selects and ranks candidate antigens in a multi-pronged approach and applied it to the case of uveal melanoma. In addition to antigen expression in the tumor target and in healthy tissues, we incorporated a network analysis-derived antigen indispensability index motivated by computational modeling results, and candidate immunogenicity predictions from a machine learning ensemble model on peptide physicochemical characteristics.
Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth
Authors: Bagautdinova Joëlle , Bourque Josiane , Sydnor Valerie J , Cieslak Matt , Alexander-Bloch Aaron F , Bertolero Max A , Cook Phil A , Gur Raquel C , Gur Ruben E , Larsen Bart , Moore Tyler M , Radhakrishnan Hamsi , Roalf David R , Shinohara Russel T , Tapera Tinashe M , Zhao Chenying , Sotiras Aristeidis , Davatzikos Christos , Satterthwaite Theodore D 
Published: February 2023

ABSTRACTThe white matter architecture of the human brain undergoes substantial development throughout childhood and adolescence, allowing for more efficient signaling between brain regions that support executive function. Increasingly, the field understands grey matter development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. While white matter development also appears asynchronous, previous studies have largely relied on anatomical atlases to characterize white matter tracts, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Here, we leveraged advances in diffusion modeling and unsupervised machine learning to delineate white matter fiber covariance networks comprised of structurally similar areas of white matter in a cross-sectional sample of 939 youth aged 8-22 years. We then evaluated associations between fiber covariance network structural properties with both age and executive function using generalized additive models. The identified fiber covariance networks aligned with the known architecture of white matter while simultaneously capturing novel spatial patterns of coordinated maturation. Fiber covariance networks showed heterochronous increases in fiber density and cross section that generally followed hierarchically organized temporal patterns of cortical development, with the greatest increases in unimodal sensorimotor networks and the most prolonged increases in superior and anterior transmodal networks. Notably, we found that executive function was associated with structural features of limbic and association networks. Taken together, this study delineates data-driven patterns of white matter network development that support cognition and align with major axes of brain maturation.
A versatile CRISPR-based system for lineage tracing in living plants
Authors: Donà Mattia , Bradamante Gabriele , Bogojevic Zorana , Gutzat Ruben , Streubel Susanna , Mosiolek Magdalena , Dolan Liam , Scheid Ortrun Mittelsten 
Published: February 2023

SUMMARYIndividual cells give rise to diverse cell lineages during the development of multicellular organisms. Understanding the contribution of these lineages to mature organisms is a central question of developmental biology. Several techniques to document cell lineages have been used, from marking single cells with mutations that express a visible marker to generating molecular bar codes by CRISPR-induced mutations and subsequent single-cell analysis. Here, we exploit the mutagenic activity of CRISPR to allow lineage tracing within living plants. Cas9-induced mutations are directed to correct a frameshift mutation that restores expression of a nuclear fluorescent protein, labelling the initial cell and all progenitor cells with a strong signal without modifying other phenotypes of the plants. Spatial and temporal control of Cas9 activity can be achieved using tissue-specific and/or inducible promoters. We provide proof of principle for the function of lineage tracing in two model plants. The conserved features of the components and the versatile cloning system, allowing for easy exchange of promoters, are expected to make the system widely applicable.SIGNIFICANCE STATEMENTBy targeting Cas9 in a tissue- and time-specific way to correct a frameshift mutation, resulting in fluorescence labelling of nuclei, we generated a method forin vivovisual lineage tracing in two model plants. The versatile cloning system makes the system widely applicable in other plants.
Metaphor - A workflow for streamlined assembly and binning of metagenomes
Authors: Salazar Vinícius W. , Shaban Babak , del Mar Quiroga Maria , Turnbull Robert , Tescari Edoardo , Marcelino Vanessa Rossetto , Verbruggen Heroen , Lê Cao Kim-Anh 
Published: February 2023

AbstractRecent advances in bioinformatics and high-throughput sequencing have enabled the large-scale recovery of genomes from metagenomes. This has the potential to bring important insights as researchers can bypass cultivation and analyse genomes sourced directly from environmental samples. There are, however, technical challenges associated with this process, most notably the complexity of computational workflows required to process metagenomic data, which include dozens of bioinformatics software tools, each with their own set of customisable parameters that affect the final output of the workflow. At the core of these workflows are the processes of assembly - combining the short input reads into longer, contiguous fragments (contigs), and binning - clustering these contigs into individual genome bins. Both processes can be done for each sample separately or by pooling together multiple samples to leverage information from a combination of samples. Here we present Metaphor, a fully-automated workflow for genome-resolved metagenomics (GRM). Metaphor differs from existing GRM workflows by offering flexible approaches for the assembly and binning of the input data, and by combining multiple binning algorithms with a bin refinement step to achieve high quality genome bins. Moreover, Metaphor generates reports to evaluate the performance of the workflow. We showcase the functionality of Metaphor on different synthetic datasets, and the impact of available assembly and binning strategies on the final results. The workflow is freely available athttps://github.com/vinisalazar/metaphor.Author summaryWe present Metaphor, a user-friendly, automated workflow for the recovery of genomes from metagenomes. Our tool offers flexible options for assembling and binning metagenomic contigs, that may be adjusted according to the characteristics of the input data and available computational resources, and a combination of binning algorithms, which improves the quantity and quality of resulting genome bins. We showcase the performance of Metaphor on synthetic benchmarking datasets and discuss the implication of methodological decisions regarding the strategy for assembling and binning metagenomic contigs.
Seroprevalence of IgG Antibody against SARS-CoV-2 Nucleocapsid protein and Associated Risk Factors
Authors: Chowdhury Yeamin Farabi , Hossen Faruk , Islam S. M. Rashadul , Hossain Md. Saddam , Mahtab-Ul-Islam Kazi , Chowdhury Sumaiya Islam , Hasan Md. Rakibul , Tasnim Nishat , Sultana Sharmin , Shaikh Md. Aftab Ali , Karim Md. Rezaul 
Published: February 2023

AbstractEstimation of antibody development against SARS-CoV-2 is essential means for understanding the immune response against the virus. We reported IgG antibody development status against Nucleocapsid protein of the virus and compared with lifestyle (health and food habits), co-existing diseases, vaccination and COVID-19 infection status. ELISA (Enzyme Linked Immunosorbent Assay) was performed to assess IgG antibodies targeted against the Nucleocapsid protein of SARS-CoV-2 in participants (n=500). In this seroprevalence study, serological data were estimated for a period of 10 months in the participants who were aged 10 years and above. Sociodemographic and risk factors related data were collected through a written questionnaire and chi-square test was performed to determine the association with seropositivity. The overall seroprevalence of anti-SARS-CoV-2 antibodies among the study subjects was 47.8%. Estimates were highest among the participants of 21-40 years old (55.1%), and lowest in older aged (>60 years) participants (39.5%). Among the Sinopharm vaccinated individuals 81.8% had developed anti-Nucleocapsid antibody. Physical exercise and existence of comorbidities like hypertension and diabetes were the distinguishing factors between seropositive and seronegative individuals. Seropositivity rate largely varied among symptomatic (67%) and asymptomatic (33.1%) COVID-19 infected participants. The findings suggest that residents of Dhaka city had a higher prevalence of anti-nucleocapsid antibody in the second year of the pandemic. This indicates the improvement of immunological status among the population. Finally, the study emphasizes on maintaining active and healthy lifestyle to improve immunity. However, the absence of IgG antibodies in many cases of COVID-19 infected individuals suggests that antibodies wane with time.Key messagesThe overall seroprevalence of anti-Nucleocapsid IgG among the study subjects was determined to be 47.8%.Age, regular physical exercise, existence of comorbidities were the identified parameters associated with seroprevalence.This study observed lower prevalence of Anti-Nucleocapsid antibody among asymptomatic cases of COVID-19 infected individuals compared to symptomatic cases.
Unipept Desktop 2.0: construction of targeted reference protein databases for proteogenomics analyses
Authors: Verschaffelt Pieter , Tanca Alessandro , Abbondio Marcello , Van Den Bossche Tim , Vande Moortele Tibo , Dawyndt Peter , Martens Lennart , Mesuere Bart 
Published: February 2023

AbstractUnipept Desktop 2.0 is the most recent iteration of the Unipept Desktop tool that adds support for the analysis of proteogenomics datasets. Unipept Desktop now supports the automatic construction of targeted protein reference databases that only contain proteins associated with a predetermined list of taxa. This improves both the taxonomic and functional resolution of a metaproteomic analysis and yields several technical advantages. By limiting the proteins present in a reference database, it is now also possible to perform (meta)proteogenomics analyses. Since the protein reference database now lives on the user’s local machine, they have complete control over the database used during an analysis. Data does no longer need to be transmitted over the internet, decreasing the time required for an analysis and better safeguarding privacy sensitive data. As a proof of concept, we present a case study in which a human gut metaproteome dataset is analyzed with Unipept Desktop 2.0 using different targeted databases based on matched 16S rRNA gene sequencing data.
ImmuneMirror: a Machine Learning-based Integrative Pipeline and Web Server for Neoantigen Prediction
Authors: Chuwdhury Gulam Sarwar , Guo Yunshan , Chiang Chi-Leung , Lam Ka-On , Kam Ngar-Woon , Liu Zhonghua , Dai Wei 
Published: February 2023

ABSTRACTNeoantigens are derived from tumors but are absent in normal tissues. Emerging evidence suggests that neoantigens can stimulate tumor-specific T-cell-mediated antitumor immune responses, and neoantigens are potential immunotherapy targets. We developed ImmuneMirror as a stand-alone open-source pipeline (https://github.com/weidai2/ImmuneMirror/) and a web server (http://immunemirror.hku.hk/App/) incorporating a balanced random forest model for neoantigen prediction and prioritization; the model was trained and tested using known immunogenic neopeptides collected from 19 published studies. The area under the curve (AUC) of our model was 0.87. We utilized ImmuneMirror in gastrointestinal tract cancers and discovered a subgroup of microsatellite instability-high (MSI-H) colorectal cancer (CRC) patients with a low neoantigen load but a high tumor mutation burden (TMB>10 mutations per Mbp). Although the efficacy of PD-1 blockade has been demonstrated in advanced MSI-H patients, almost half of such patients do not respond well. Our study may identify MSI-H patients who do not benefit from this treatment. Additionally, the neopeptide YMCNSSCMGV-TP53G245V, derived from a hotspot mutation restricted by HLA-A02, was identified as an actionable target in esophageal squamous cell carcinoma (ESCC). This is the largest study to comprehensively evaluate neoantigen prediction models using experimentally validated neopeptides. Our results demonstrate the reliability and effectiveness of ImmuneMirror for neoantigen prediction.
An RNA to rule them all: Critical steps in Lassa virus ribonucleoparticle assembly and recruitment
Authors: Sänger Lennart , Williams Harry M. , Yu Dingquan , Vogel Dominik , Kosinski Jan , Rosenthal Maria , Uetrecht Charlotte 
Published: February 2023

AbstractLassa virus is a negative-strand RNA virus with only four structural proteins that causes periodic outbreaks in West Africa. The nucleoprotein (NP) encapsidates the viral genome, forming the ribonucleoprotein complexes (RNPs) together with the viral RNA and the L protein. RNPs have to be continuously restructured during viral genome replication and transcription. The Z protein is important for membrane recruitment of RNPs, viral particle assembly and budding, and has also been shown to interact with the L protein. However, the interaction of NP, viral RNA and Z is poorly understood. Here, we characterize the interactions between Lassa virus NP, Z and RNA using structural mass spectrometry. We identify the presence of RNA as the driver for disassembly of ring-like NP trimers, a storage form, into monomers to subsequently form higher order RNA-bound NP assemblies. We locate the interaction site of Z and NP and demonstrate that while NP binds Z independently of the presence of RNA, this interaction is pH-dependent. These data improve our understanding of RNP assembly, recruitment and release in Lassa virus.