bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of fire and fire-induced changes in soil properties on post-burn soil respiration
Authors: Johnson Dana B. , Yedinak Kara M. , Sulman Benjamin N. , Berry Timothy D. , Kruger Kelsey , Whitman Thea 
Published: April 2024

AbstractBackgroundBoreal forests cover vast areas of land in the northern hemisphere and store large amounts of carbon (C) both aboveground and belowground. Wildfires, which are a primary ecosystem disturbance of boreal forests, affect soil C via combustion and transformation of organic matter during the fire itself, and via changes in plant growth and microbial activity post-fire. Wildfire regimes in many areas of the boreal forests of North America are shifting towards more frequent and severe fires driven by changing climate. As wildfire regimes shift and the effects of fire on belowground microbial community composition are becoming clearer, there is a need to link fire-induced changes in soil properties to changes in microbial functions such as respiration in order to better predict the impact of future fires on C cycling.ResultsWe used laboratory burns to simulate boreal crown fires on both organic-rich and sandy soil cores collected from Wood Buffalo National Park, Alberta, Canada, to measure the effects of burning on soil properties including pH, total C, and total nitrogen (N). We used 70-day soil incubations and two-pool exponential decay models to characterize the impacts of burning and its resulting changes in soil properties on soil respiration. Laboratory burns successfully captured a range of soil temperatures that were realistic for natural wildfire events. We found that burning increased pH and caused small decreases in C:N in organic soil. Overall, respiration per gram total (post-burn) C in burned soil cores was 16% lower than in corresponding unburned control cores, indicating that soil C lost during a burn may be partially offset by burn-induced decreases in respiration rates. Simultaneously, burning altered how remaining C cycled, causing an increase in the proportion of C represented in the modelled slow-cycling vs. fast-cycling C pool as well as an increase in fast-cycling C decomposition rates.ConclusionsTogether, our findings imply that C storage in boreal forests following wildfires will be driven by the combination of C losses during the fire itself as well as fire-induced changes to the soil C pool that modulate post-fire respiration rates. Moving forward, we will pair these results with soil microbial community data to understand how fire-induced changes in microbial community composition may influence respiration.
RAG suppresses group 2 innate lymphoid cells
Authors: Ver Heul Aaron M. , Mack Madison , Zamidar Lydia , Tamari Masato , Yang Ting-Lin , Trier Anna M. , Kim Do-Hyun , Janzen-Meza Hannah , Van Dyken Steven J. , Hsieh Chyi-Song , Karo Jenny M. , Sun Joseph C. , Kim Brian S. 
Published: April 2024

ABSTRACTAntigen specificity is the central trait distinguishing adaptive from innate immune function. Assembly of antigen-specific T cell and B cell receptors occurs through V(D)J recombination mediated by the Recombinase Activating Gene endonucleases RAG1 and RAG2 (collectively called RAG). In the absence of RAG, mature T and B cells do not develop and thus RAG is critically associated with adaptive immune function. In addition to adaptive T helper 2 (Th2) cells, group 2 innate lymphoid cells (ILC2s) contribute to type 2 immune responses by producing cytokines like Interleukin-5 (IL-5) and IL-13. Although it has been reported that RAG expression modulates the function of innate natural killer (NK) cells, whether other innate immune cells such as ILC2s are affected by RAG remains unclear. We find that in RAG-deficient mice, ILC2 populations expand and produce increased IL-5 and IL-13 at steady state and contribute to increased inflammation in atopic dermatitis (AD)-like disease. Further, we show that RAG modulates ILC2 function in a cell-intrinsic manner independent of the absence or presence of adaptive T and B lymphocytes. Lastly, employing multiomic single cell analyses of RAG1 lineage-traced cells, we identify key transcriptional and epigenomic ILC2 functional programs that are suppressed by a history of RAG expression. Collectively, our data reveal a novel role for RAG in modulating innate type 2 immunity through suppression of ILC2s.
Evaluation of Inducible Gene Expression Systems for Beet Cyst Nematode Infection Assays inArabidopsis thaliana
Authors: Liu Xunliang , Mitchum Melissa G 
Published: April 2024

AbstractCyst nematodes co-opt plant developmental programs for the establishment of a permanent feeding site called a syncytium in plant roots. In recent years, the role of plant developmental genes in syncytium formation has gained much attention. One main obstacle in studying the function of development-related genes in syncytium formation is that mutation or ectopic expression of such genes can cause pleiotropic phenotypes making it difficult to interpret nematode-related phenotypes, or in some cases, impossible to carry out infection assays due to aberrant root development. Here, we tested three commonly used inducible gene expression systems for their application in beet cyst nematode infection assays of the model plantArabidopsis thaliana. We found that even a low amount of ethanol diminished nematode development, deeming the ethanol-based system unsuitable for use in cyst nematode infection assays; whereas treatment with estradiol or dexamethasone did not negatively affect cyst nematode viability. Dose and time course responses showed that in both systems, a relatively low dose of inducer (1 μM) is sufficient to induce high transgene expression within 24 hours of treatment. Transgene expression peaked at 3-5 days post induction and began to decline thereafter, providing a perfect window for inducible transgenes to interfere with syncytium establishment while minimizing any adverse effects on root development. These results indicate that both estradiol- and dexamethasone-based inducible gene expression systems are suitable for cyst nematode infection assays. The employment of such systems provides a powerful tool to investigate the function of development essential plant genes in syncytium formation.
Tree Surface Area Allometry
Authors: Shenkin Alexander , Wilkes Phil , Enquist Brian , Sarmiento Alvaro , Burt Andy , Calders Kim , Raumonen Pasi , Patrick Bentley Lisa , Disney Mat , Malhi Yadvinder 
Published: April 2024

AbstractUtilizing terrestrial laser scanning (TLS) and three-dimensional modeling, this study quantitatively assessed the woody surface areas of 2161 trees across ecosystems encompassing both tropical and temperate forests. TLS enables precise measurement of tree structures at unprecedented scales. This research builds on theoretical scaling relationships with empirical data, significantly refining our understanding of tree woody surface area. Key findings indicate that direct measurements diverge from theoretical predictions, particularly in the finer branch structures, suggesting modifications to existing allometric models might be necessary. This integration of direct measurements with TLS not only challenges established theories but also enhances our capability to accurately model tree surface area, which is key for understanding forest carbon dynamics and metabolic scaling in ecological systems.
Generation of a zebrafish neurofibromatosis model via inducible knockout ofnf2
Authors: Desingu Rajan Ayyappa Raja , Huang Yuanyun , Stundl Jan , Chu Katelyn , Irodi Anushka , Yang Zihan , Applegate Brian E. , Bronner Marianne E. 
Published: April 2024

SummaryNeurofibromatosis Type 2 (NF-2) is a dominantly inherited genetic disorder that results from mutations in the tumor suppressor gene, neurofibromin 2 (NF2) gene. Here, we report the generation of a conditional zebrafish model of neurofibromatosis established by an inducible genetic knockout ofnf2a/b, the zebrafish homolog of human NF2. Analysis ofnf2aandnf2bexpression reveals ubiquitous expression ofnf2bin the early embryo, with overlapping expression in the neural crest and its derivatives and in the cranial mesenchyme. In contrast,nf2adisplays lower expression levels. Induction ofnf2a/bknockout at early stages increases the proliferation of larval Schwann cells and meningeal fibroblasts. Subsequently, in adult zebrafish,nf2a/bknockout triggers the development of a spectrum of tumors, including vestibular schwannomas, spinal schwannomas, meningiomas, and retinal hamartomas, mirroring the tumor manifestations observed in patients with NF-2. Collectively, these findings highlight the generation of a novel zebrafish model that mimics the complexities of the human NF-2 disorder. Consequently, this model holds significant potential for facilitating therapeutic screening and elucidating key driver genes implicated in NF-2 onset.
Engineering Memory T Cells as a platform for Long-Term Enzyme Replacement Therapy in Lysosomal Storage Disorders
Authors: Laoharawee Kanut , Kleinboehl Evan W , Jensen Jacob D , Peterson Joseph J , Slipek Nicholas J , Wick Bryce J , Johnson Matthew J , Webber Beau R , Moriarity Branden S 
Published: April 2024

AbstractEnzymopathy disorders are the result of missing or defective enzymes. Amongst these enzymopathies, mucopolysaccharidosis type I, is a rare genetic lysosomal storage disorder caused by mutations in the gene encoding alpha-L-iduronidase (IDUA), ultimately causes toxic build-up of glycosaminoglycans (GAGs). There is currently no cure and standard treatments provide insufficient relief to the skeletal structure and central nervous system (CNS). Human memory T cells (Tm) migrate throughout the body’s tissues and can persist for years, making them an attractive approach for cellular-based, systemic enzyme replacement therapy. Here, we tested genetically engineered, IDUA-expressing Tm as a cellular therapy in an immunodeficient mouse model of MPS I. Our results demonstrate that a single dose of engineered Tm leads to detectable IDUA enzyme levels in the blood for up to 22 weeks and reduced urinary GAG excretion. Furthermore, engineered Tm take up residence in nearly all tested tissues, producing IDUA and leading to metabolic correction of GAG levels in the heart, lung, liver, spleen, kidney, bone marrow, and the CNS. Our study indicates that genetically engineered Tm holds great promise as a platform for cellular-based enzyme replacement therapy for the treatment of mucopolysaccharidosis type I and potentially many other enzymopathies and protein deficiencies.
Exploration of the genetic landscape of bacterial dsDNA viruses reveals an ANI gap amidst extensive mosaicism
Authors: Ndovie Wanangwa , Havránek Jan , Leconte Jade , Koszucki Janusz , Chindelevitch Leonid , Adriaenssens Evelien M. , Mostowy Rafal J. 
Published: April 2024

AbstractAverage Nucleotide Identity (ANI) is a widely used metric to estimate genetic relatedness, especially in microbial species delineation. While ANI calculation has been well optimised for bacteria and closely related viral genomes, accurate estimation of ANI below 80%, particularly in large reference datasets, has been challenging due to a lack of accurate and scalable methods. To bridge this gap, here we introduce MANIAC, an efficient computational pipeline optimised for estimating ANI and alignment fraction (AF) in viral genomes with divergence around ANI of 70%. Using a rigorous simulation framework, we demonstrate MANIAC’s accuracy and scalability compared to existing approaches, even to datasets of hundreds-of-thousands of viral genomes. Applying MANIAC to a curated dataset of complete bacterial dsDNA viruses revealed a multimodal ANI distribution, with a distinct gap around 80%, akin to the bacterial ANI gap (∼90%) but shifted, likely due to viral-specific evolutionary processes such as recombination dynamics and mosaicism. We then evaluated ANI and AF as predictors of genus-level taxonomy using a logistic regression model. We found that this model has strong predictive power (PR-AUC=0.981), but that it works much better for virulent (PR-AUC=0.997) than temperate (PR-AUC=0.847) bacterial viruses. This highlights the complexity of taxonomic classification in temperate phages, known for their extensive mosaicism, and cautions against over-reliance on ANI in such cases. MANIAC can be accessed underhttps://github.com/bioinf-mcb/MANIAC.ImportanceWe introduce a novel computational pipeline called MANIAC, designed to accurately assess Average Nucleotide Identity (ANI) and alignment fraction (AF) between diverse viral genomes, scalable to datasets of over 100k genomes. Through the use of computer simulations and real data analyses, we show that MANIAC could ac- curately estimate genetic relatedness between pairs of viral genomes around 60-70% ANI. We applied MANIAC to investigate the question of ANI discontinuity in bacterial dsDNA viruses, finding evidence for an ANI gap, akin to the one seen in bacteria but around ANI of 80%. We then assessed the ability of ANI and AF to predict taxonomic genus boundaries, finding its strong predictive power in virulent, but not in temperate phages. Our results suggest that bacterial dsDNA viruses may exhibit an ANI threshold (on average around 80%) above which recombination helps maintain population cohesiveness, as previously argued in bacteria.
Immune perturbations in human pancreas lymphatic tissues prior to and after type 1 diabetes onset
Authors: Golden Gregory J. , Wu Vincent H. , Hamilton Jacob T. , Amses Kevin R. , Shapiro Melanie R. , Japp Alberto Sada , Liu Chengyang , Pampena Maria Betina , Kuri-Cervantes Leticia , Knox James J. , Gardner Jay S. ,   HPAP Consortium, Atkinson Mark A. , Brusko Todd M. , Prak Eline T. Luning , Kaestner Klaus H. , Naji Ali , Betts Michael R. 
Published: April 2024

AbstractAutoimmune destruction of pancreatic β cells results in type 1 diabetes (T1D), with pancreatic immune infiltrate representing a key feature in this process. Studies of human T1D immunobiology have predominantly focused on circulating immune cells in the blood, while mouse models suggest diabetogenic lymphocytes primarily reside in pancreas-draining lymph nodes (pLN). A comprehensive study of immune cells in human T1D was conducted using pancreas draining lymphatic tissues, including pLN and mesenteric lymph nodes, and the spleen from non-diabetic control, β cell autoantibody positive non-diabetic (AAb+), and T1D organ donors using complementary approaches of high parameter flow cytometry and CITEseq. Immune perturbations suggestive of a proinflammatory environment were specific for T1D pLN and AAb+ pLN. In addition, certain immune populations correlated with high T1D genetic risk independent of disease state. These datasets form an extensive resource for profiling human lymphatic tissue immune cells in the context of autoimmunity and T1D.
Genotype Representation Graphs: Enabling Efficient Analysis of Biobank-Scale Data
Authors: DeHaas Drew , Pan Ziqing , Wei Xinzhu 
Published: April 2024

AbstractComputational analysis of a large number of genomes requires a data structure that can represent the dataset compactly while also enabling efficient operations on variants and samples. Current practice is to store large-scale genetic polymorphism data using tabular data structures and file formats, where rows and columns represent samples and genetic variants. However, encoding genetic data in such formats has become unsustainable. For example, the UK Biobank polymorphism data of 200,000 phased whole genomes has exceeded 350 terabytes (TB) in Variant Call Format (VCF), cumbersome and inefficient to work with. To mitigate the computational burden, we introduce the Genotype Representation Graph (GRG), an extremely compact data structure to losslessly present phased whole-genome polymorphisms. A GRG is a fully connected hierarchical graph that exploits variant-sharing across samples, leveraging ideas inspired by Ancestral Recombination Graphs. Capturing variant-sharing in a multitree structure compresses biobank-scale human data to the point where it can fit in a typical server’s RAM (5-26 gigabytes (GB) per chromosome), and enables graph-traversal algorithms to trivially reuse computed values, both of which can significantly reduce computation time. We have developed a command-line tool and a library usable via both C++ and Python for constructing and processing GRG files which scales to a million whole genomes. It takes 160GB disk space to encode the information in 200,000 UK Biobank phased whole genomes as a GRG, more than 13 times smaller than the size of compressed VCF. We show that summaries of genetic variants such as allele frequency and association effect can be computed on GRG via graph traversal that runs significantly faster than all tested alternatives, includingvcf.gz, PLINK BED, tree sequence, XSI, and Savvy. Furthermore, GRG is particularly suitable for doing repeated calculations and interactive data analysis. We anticipate that GRG-based algorithms will improve the scalability of various types of computation and generally lower the cost of analyzing large genomic datasets.
A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia
Authors: Blair David Sutherland , Miller Robyn L. , Calhoun Vincent D. 
Published: April 2024

ABSTRACTOver the past decade and a half, dynamic functional imaging has revolutionized the neuroimaging field. Since 2009, it has revealed low dimensional brain connectivity measures, has identified potential common human spatial connectivity states, has tracked the transition patterns of these states, and has demonstrated meaningful alterations in these transition and spatial patterns in neurological disorders, psychiatric disorders, and over the course of development. More recently, researchers have begun to analyze this data from the perspective of dynamic system and information theory in the hopes of understanding the constraints within which these dynamics occur and how they may support less easily quantified processes, such as information processing, cortical hierarchy, and consciousness. Progress has begun to accelerate in this area, particularly around consciousness, which appears to be strongly linked to entropy production in the brain. Outside of disorders of consciousness, however, little attention has been paid to the effects of psychiatric disease on entropy production in the human brain. Even disorders characterized by substantial changes in conscious experience have not been widely analyzed from this perspective.Here, we begin to rectify this gap by examining the complexity of subject trajectories in this state space through the lens of information theory. Specifically, we identify a basis for the dynamic functional connectivity state space and track subject trajectories through this state space over the course of the scan. The dynamic complexity of these trajectories is estimated using a Kozachenko-Leonenko entropy estimator, which assesses the rate of Shannon entropy production along each dimension of the proposed basis space. Using these estimates, we demonstrate that schizophrenia patients display substantially simpler trajectories than demographically matched healthy controls, and that this drop in complexity concentrates along specific dimensions of projected basis space. We also demonstrate that entropy generation in at least one of these dimensions is linked to cognitive performance. Overall, results suggest great value in applying dynamic systems theory to problems of neuroimaging and reveal a substantial drop in the complexity of schizophrenia patients’ brain function.
Fairy: fast approximate coverage for multi-sample metagenomic binning
Authors: Shaw Jim , Yu Yun William 
Published: April 2024

AbstractBackgroundMetagenomic binning, the clustering of assembled contigs that belong to the same genome, is a crucial step for recovering metagenomeassembled genomes (MAGs). Contigs are linked by exploiting consistent read coverage patterns across a genome. Using coverage from multiple samples leads to higher-quality MAGs; however, standard pipelines require all-to-all read alignments for multiple samples to compute coverage, becoming a key computational bottleneck.ResultsWe present fairy (https://github.com/bluenote-1577/fairy), anapproximatecoverage calculation method for metagenomic binning. Fairy is a fast k-mer-based alignment-free method. For multi-sample binning, fairy can be>250×faster than read alignment and accurate enough for binning. Fairy is compatible with several existing binners on host and non-host-associated datasets. Using MetaBAT2, fairy recovers98.5%of MAGs with>50%completeness and<5%incompleteness relative to alignment with BWA. Notably, multi-sample binning with fairy isalwaysbetter than single-sample binning using BWA (>1.5×more>50%complete MAGs on average) while still being faster. For a public sediment metagenome project, we demonstrate that multisample binning recovers higher quality Asgard archaea MAGs than single-sample binning and that fairy’s results are indistinguishable from read alignment.ConclusionsFairy is a new tool for approximately and quickly calculating multi-sample coverage for binning, resolving a longstanding computational bottleneck for metagenomics.
Multi-spectral photoacoustic imaging combined with acoustic radiation force impulse imaging for applications in tissue engineering
Authors: Nguyen Christopher D. , Chen Ying , Kaplan David L. , Mallidi Srivalleesha 
Published: April 2024

AbstractTissue engineering is a dynamic field focusing on the creation of advanced scaffolds for tissue and organ regeneration. These scaffolds are customized to their specific applications and are often designed to be complex, large structures to mimic tissues and organs. This study addresses the critical challenge of effectively characterizing these thick, optically opaque scaffolds that traditional imaging methods fail to fully image due to their optical limitations. We introduce a novel multi-modal imaging approach combining ultrasound, photoacoustic, and acoustic radiation force impulse imaging. This combination leverages its acoustic-based detection to overcome the limitations posed by optical imaging techniques. Ultrasound imaging is employed to monitor the scaffold structure, photoacoustic imaging is employed to monitor cell proliferation, and acoustic radiation force impulse imaging is employed to evaluate the homogeneity of scaffold stiffness. We applied this integrated imaging system to analyze melanoma cell growth within silk fibroin protein scaffolds with varying pore sizes and therefore stiffness over different cell incubation periods. Among various materials, silk fibroin was chosen for its unique combination of features including biocompatibility, tunable mechanical properties, and structural porosity which supports extensive cell proliferation. The results provide a detailed mesoscale view of the scaffolds’ internal structure, including cell penetration depth and biomechanical properties. Our findings demonstrate that the developed multimodal imaging technique offers comprehensive insights into the physical and biological dynamics of tissue-engineered scaffolds. As the field of tissue engineering continues to advance, the importance of non-ionizing and non-invasive imaging systems becomes increasingly evident, and by facilitating a deeper understanding and better characterization of scaffold architectures, such imaging systems are pivotal in driving the success of future tissue-engineering solutions.