bluuebunny/crossref_metadata_2025_split huggingface dataset:
The histone chaperone NASP maintains H3-H4 reservoirs in the early Drosophila embryo
Authors: Tirgar Reyhaneh , Davies Jonathan P. , Plate Lars , Nordman Jared T. 
Published: September 2022

ABSTRACTHistones are essential for chromatin packaging and histone supply must be tightly regulated as excess histones are toxic. To drive the rapid cell cycles of the early embryo, however, excess histones are maternally deposited. Therefore, soluble histones must be buffered by histone chaperones but the chaperone necessary to stabilize soluble H3-H4 pools in the Drosophila embryo has yet to be identified. Here, we show that CG8223, the Drosophila ortholog of NASP, is a H3-H4-specific chaperone in the early embryo. NASP specifically binds to H3-H4 in the early embryo. We demonstrate that, while a NASP null mutant is viable in Drosophila, NASP is maternal effect lethal gene. Embryos laid by NASP mutant mothers have a reduce rate of hatching and show defects in early embryogenesis. Critically, soluble H3-H4 pools are degraded in embryos laid by NASP mutant mothers. Our work identifies NASP as the critical H3-H4 histone chaperone in the Drosophila embryo.
Quantifying climate change impacts on plant functional composition and soil nitrogen fixation in Mediterranean grasslands
Authors: Bomfim Barbara , Dawson Hilary R. , Reed Paul B. , Shek Katherine L. , Bohannan Brendan J. M. , Bridgham Scott D. , Silva Lucas C. R. 
Published: September 2022

AbstractThe projected increase in warming and drought severity (i.e., hotter and drier summers) in the U.S. Pacific Northwest (PNW) may negatively impact grassland plant composition and ecosystem function, with further implications for sustainable land management in the region. To test the vulnerability of Mediterranean grassland function to climate change, we quantified the response of grassland communities to multiannual warming (+2.5°C) and drought (−40% precipitation) by quantifying plant species diversity, legume cover, and biogeochemical controls on and patterns of soil asymbiotic nitrogen fixation (ANF). We hypothesized that the effects of warming on plant functional diversity would increase soil ANF inputs by decreasing legume cover and soil nitrogen availability. Given that asymbiotic N fixers can increase soil organic carbon (C) and nitrogen (N) availability under drought, we hypothesized that the effect of drought on grassland plant cover correlated with increased soil ANF. We surveyed the vegetation and collected composite soil samples from five co-located plots under control (ambient), drought and warming conditions during the fall and spring seasons. In control and drought plots, we quantified the moderator effect of plant composition by comparing low-diversity (unmanipulated plant composition) and high-diversity (manipulated composition) grassland plots. We used a point intercept technique to survey plot-level plant community composition and calculate Shannon’s diversity index and percent cover of legumes (members of Fabaceae according to the Integrated Taxonomic Information System). We measured ANF by incubating collected soils with N-labeled dinitrogen (15N2), and quantified total soil C, total and available N, available phosphorus (P) and iron (Fe) pools, pH, and soil water holding capacity. Plant species diversity decreased significantly with warming and along the drought severity gradient. ANF response to warming varied by season and site, with rates increasing along the drought severity gradient in the fall but decreasing in the spring. Total soil inorganic N was the strongest predictor of ANF response to warming in the spring but not in the fall. Soil ANF response to drought increased with drought intensity; while soil ANF increased nearly twofold in the southernmost (warm and dry) site, ANF decreased in the northernmost (cool and wet) site. ANF response to drought also varied depending on plant diversity, where low-diversity grasslands had more predictable response to drought than high-diversity grasslands. Soil P availability and pH were the most important variables explaining ANF variability across vegetation types and sites. Our study highlights the importance of using soil-plant-atmosphere interactions to assess grassland ecosystem resilience to drought and warming in the PNW.
Influence of Sodium Salicylate on Adventitious Organogenesis of a Commercial Cucumber Cultivar
Authors: Miguel Jorge Fonseca 
Published: September 2022

AbstractThe effect of different concentrations of sodium salicylate (NaSA), a phenolic compound, onin vitrocallus and shoot regeneration of cucumber (Cucumis sativusL.) was investigated. Four-day-old cotyledon explants from the Spanish cultivar ‘Marketer’ were employed. MS-derived shoot induction medium containing 0.5 mg L-1 IAA and 2.5 mg L-1 BAP was supplemented with NaSA. Frequency and shoot number were enhanced by 1.5-fold with NaSA at 0.1 μM. Higher salicylate levels led to increased callus formation and decreased shoot regeneration. The application of sodium salicylate at a specific concentration showed a positive trend inin vitroadventitious organogenesis of a commercial cucumber cultivar. Some probable mechanisms that may underlie the beneficial effects of salicylic acid/salicylates onin vitroregeneration were also discussed.
Distributed coding of evidence accumulation across the mouse brain using microcircuits with a diversity of timescales
Authors: Imani Elaheh , Radkani Setayesh , Hashemi Alireza , Harati Ahad , Pourreza Hamidreza , Goudarzi Morteza Moazami 
Published: September 2022

AbstractThe gradual accumulation of noisy evidence for or against options is the main step in the perceptual decision-making process. Using brain-wide electrophysiological recording in mice (Steinmetz et al., 2019), we examined neural correlates of evidence accumulation across brain areas. We demonstrated that the neurons with Drift-Diffusion-Model-like firing rate activity (i.e., evidence-sensitive ramping firing rate) were distributed across the brain. Exploring the underlying neural mechanism of evidence accumulation for the DDM-like neurons revealed different accumulation mechanisms (i.e. single and race) both within and across the brain areas. Our findings support the hypothesis that evidence accumulation is happening through multiple integration mechanisms in the brain. We further explored the timescale of the integration process in the single and race accumulator models. The results demonstrated that the accumulator microcircuits within each brain area had distinct properties in terms of their integration timescale, which were organized hierarchically across the brain. These findings support the existence of evidence accumulation over multiple timescales. Besides the variability of integration timescale across the brain, a heterogeneity of timescales was observed within each brain area as well. We demonstrated that this variability reflected the diversity of microcircuit parameters, such that accumulators with longer integration timescales had higher recurrent excitation strength.
PrePCI: A structure- and chemical similarity-informed database of predicted protein compound interactions
Authors: Trudeau Stephen J. , Hwang Howook , Mathur Deepika , Begum Kamrun , Petrey Donald , Murray Diana , Honig Barry 
Published: September 2022

AbstractWe describe the Predicting Protein Compound Interactions (PrePCI) database which comprises over 5 billion predicted interactions between nearly 7 million chemical compounds and 19,797 human proteins. PrePCI relies on a proteome-wide database of structural models based on both traditional modeling techniques and the AlphaFold Protein Structure Database. Sequence and structural similarity-based metrics are established between template proteins in the Protein Data Bank, T, that bind small molecules, C, and proteins in the models database, Q. When these metrics pass a sequence threshold value, it is assumed that C also binds to Q with a probability derived from machine learning. If the relationship is based on structure, this probability is based on a scoring function that measures the extent to which C is compatible with the binding site of Q as described in the LT-scanner algorithm. For every predicted complex derived in this way, chemical similarity based on the Tanimoto Coefficient identifies other small molecules that may bind to Q. A likelihood ratio for the binding of C to Q is obtained from naïve Bayesian statistics. The PrePCI algorithm performs well under different validations. It can be queried by entering a UniProt ID for a protein and obtaining a list of compounds predicted to bind to it along with associated probabilities. Alternatively, entering an identifier for the compound outputs a list of proteins it is predicted to bind. Specific applications of the database are described and a strategy is introduced to use PrePCI as a first step in a docking screen.
Combinatorial assembly and design of enzymes
Authors: Lipsh-Sokolik Rosalie , Khersonsky Olga , Schröder Sybrin P. , de Boer Casper , Hoch Shlomo-Yakir , Davies Gideon J. , Overkleeft Hermen S. , Fleishman Sarel J. 
Published: September 2022

AbstractDesign of structurally diverse enzymes is constrained by long-range interactions that are needed for accurate folding. We introduce an atomistic and machine-learning strategy for Combinatorial Assembly and Design of ENZymes, CADENZ, to design fragments that combine with one another to generate diverse, low-energy structures with stable catalytic constellations. We applied CADENZ to endoxylanases and used activity-based protein profiling to recover thousands of active and structurally diverse enzymes. Functional designs exhibit high active-site preorganization and more stable and compact packing outside the active site. Implementing these lessons into CADENZ led to a tenfold improved hit rate and >10,000 active enzymes. This design-test-learn loop can be applied, in principle, to any modular protein family, yielding huge diversity and general lessons on protein design principles.
Reconstructor: A COBRApy compatible tool for automated genome-scale metabolic network reconstruction with parsimonious flux-based gap-filling
Authors: Jenior Matthew L , Glass Emma M , Papin Jason A 
Published: September 2022

AbstractSummaryGenome-scale metabolic network reconstructions (GENREs) are valuable for understanding cellular metabolism in silico. Several tools exist for automatic GENRE generation. However, these tools frequently (1) do not readily integrate with some of the widely-used suites of packaged methods available for network analysis, (2) lack effective network curation tools, and (3) are not sufficiently user-friendly. Here, we present Reconstructor, a user-friendly COBRApy compatible tool with ModelSEED namespace compatibility and a pFBA-based gap-filling technique. We demonstrate how Reconstructor readily generates high-quality GENRES that are useful for further biological discovery.Availability and ImplementationThe Reconstructor package is freely available for download via pip in the command line (pip install reconstructor). Usage instructions and benchmarking data are available at http://github.com/emmamglass/reconstructor.ContactJason Papin: papin@virginia.edu
CysPresso: A classification model utilizing deep learning protein representations to predict recombinant expression of cysteine-dense peptides
Authors: Ouellet Sébastien , Ferguson Larissa , Lau Angus Z. , Lim Tony K.Y. 
Published: September 2022

AbstractBackground:Cysteine-dense peptides (CDPs) are an attractive pharmaceutical scaffold that display extreme biochemical properties, low immunogenicity, and the ability to bind targets with high affinity and selectivity. While many CDPs have potential and confirmed therapeutic uses, synthesis of CDPs is a challenge. Recent advances have made the recombinant expression of CDPs a viable alternative to chemical synthesis. Moreover, identifying CDPs that can be expressed in mammalian cells is crucial in predicting their compatibility with gene therapy and mRNA therapy. Currently, we lack the ability to identify CDPs that will express recombinantly in mammalian cells without labour intensive experimentation. To address this, we developed CysPresso, a novel machine learning model that predicts recombinant expression of CDPs based on primary sequence.Results:We tested various protein representations generated by deep learning algorithms (SeqVec, proteInfer, AlphaFold2) for their suitability in predicting CDP expression and found that AlphaFold2 representations possessed the best predictive features. We then optimized the model by concatenation of AlphaFold2 representations, time series transformation with random convolutional kernels, and dataset partitioning.Conclusion:Our novel model, CysPresso, is the first to successfully predict recombinant CDP expression in mammalian cells and is particularly well suited for predicting recombinant expression of knottin peptides. When preprocessing the deep learning protein representation for supervised machine learning, we found that random convolutional kernel transformation preserves more pertinent information relevant for predicting expressibility than embedding averaging. Our study showcases the applicability of deep learning-based protein representations, such as those provided by AlphaFold2, in tasks beyond structure prediction.
Environment-dependent epistasis increases phenotypic diversity in gene regulatory networks
Authors: Baier Florian , Gauye Florence , Perez-Carrasco Ruben , Payne Joshua L. , Schaerli Yolanda 
Published: September 2022

AbstractMutations to gene regulatory networks can be maladaptive or a source of evolutionary novelty. Epistasis confounds our understanding of how mutations impact the expression patterns of gene regulatory networks, because such nonlinearities make it difficult to predict the combined phenotypic effects of mutations based on knowledge of the mutations’ individual effects. This challenge is exacerbated by the dependence of epistasis on the environment, which is particularly germane to gene regulatory networks that interpret signals in space or time. To help fill this knowledge gap, we used the toolkit of synthetic biology to systematically assay the effects of pairwise and triplet combinations of mutant genotypes on the expression pattern of a gene regulatory network expressed in Escherichia coli that interprets an inducer gradient across a spatial domain. We uncovered a preponderance of epistasis in both pairwise and triplet combinations that can switch in magnitude and sign across the inducer gradient to produce a greater diversity of expression pattern phenotypes than would be possible in the absence of such environment-dependent epistasis. We discuss our findings in the context of the evolution of hybrid incompatibilities and evolutionary novelties, arguing that environment-dependent epistasis is likely an important cause of both phenomena in gene regulatory networks.
Phospholipase B is critical for Cryptococcus neoformans survival in the central nervous system
Authors: Hamed Mohamed F. , de Sousa Araújo Glauber Ribeiro , Munzen Melissa E. , Reguera-Gomez Marta , Epstein Carly , Lee Hiu Ham , Frases Susana , Martinez Luis R. 
Published: September 2022

ABSTRACTCryptococcus neoformans (Cn) is an opportunistic, encapsulated, yeast-like fungus that causes severe meningoencephalitis, especially in countries with high HIV prevalence. In addition to its well-known polysaccharide capsule, Cn has other virulence factors such as phospholipases, a heterogeneous group of enzymes that hydrolyze ester linkages in glycerophospholipids. Phospholipase B (PLB1) has been demonstrated to play a key role in Cn pathogenicity. In this study, we used a PLB1 mutant (plb1) and its reconstituted strain (Rec1) to assess the importance of this enzyme on Cn brain infection in vivo and in vitro. Mice infected with plb1 strain survive significantly longer, have lower central nervous system (CNS) fungal load, and fewer and smaller cryptococcomas or biofilm-like brain lesions compared to H99- and Rec1-infected animals. plb1 cryptococci are significantly more phagocytosed and killed by NR-9460 microglia-like cells. plb1 cells have altered capsular polysaccharide biophysical properties that impair their ability to stimulate glia cell responses or morphological changes. We provide significant evidence demonstrating that Cn phospholipase is an important virulence factor for fungal colonization of and survival in the CNS as well as in the progression of cryptococcal meningitis. These findings may potentially help fill in a gap of knowledge in our understanding of cerebral cryptococcosis and may provide novel research avenues in Cn pathogenesis.IMPORTANCECryptococcal meningoencephalitis is a serious disease caused by infection of the neurotropic fungal pathogen Cryptococcus neoformans (Cn). Due to the increasing number of cases in HIV-infected individuals, as well as the limited therapies available, investigation into potential targets for new therapeutics has become critical. Phospholipase B (PLB1) is an enzyme synthesized by Cn that confers virulence to the fungus through capsular enlargement, immunomodulation, and intracellular replication. In this study, we examined the properties of PLB1 by comparing infection of Cn PLB1 mutant strain with both the wild-type and a PLB1 reconstituted strain. We show that PLB1 augments the survival and proliferation of the fungus in the CNS and strengthens virulence through modulation of the immune response and enhancement of specific biophysical properties of the fungus. The implications of PLB1 inhibition reveal its involvement in Cn infection and suggest that it may be a possible molecular target in the development of antifungal therapies. The results of this study support additional investigation into the mechanism of PLB1 to further understand the intricacies of Cn infection.
A deep learning workflow for quantification of Micronuclei in DNA damage studies in cultured cancer cell lines: a proof of principle investigation
Authors: Panchbhai Anand , Ishanzadeh Munuse Ceyda , Pankanti Smarana , Sidali Ahmed , Solaiman Nadeeen , Kanagaraj Radhakrishnan , Murphy John J , Surendranath Kalpana 
Published: September 2022

AbstractThe cytokinesis block micronucleus assay is widely used for measuring/scoring/counting micronuclei, a marker of genome instability in cultured and primary cells. Though a gold standard method, this is a laborious and time-consuming process with person-to-person variation observed in quantification of micronuclei. We report in this study the utilisation of a new deep learning workflow for detection of micronuclei in DAPI stained nuclear images. The proposed deep learning framework achieved an average precision of >90% in detection of micronuclei. This proof of principle investigation in a DNA damage studies laboratory supports the idea of deploying AI powered tools in a cost-effective manner for repetitive and laborious tasks with relevant computational expertise. These systems will also help improving the quality of data and wellbeing of researchers.Simple SummaryThis study aims to test a suitable deep learning method for micronucleus detection in images acquired for cytokinesis block micronucleus assay. This study has reached a mean average precision of >90%.
Cholinergic boutons are distributed along the dendrites and somata of VIP neurons in the inferior colliculus
Authors: Kwapiszewski Julia T. , Rivera-Perez Luis M. , Roberts Michael T. 
Published: September 2022

AbstractCholinergic signaling shapes sound processing and plasticity in the inferior colliculus (IC), the midbrain hub of the central auditory system, but how cholinergic terminals contact and influence individual neuron types in the IC remains largely unknown. Using pharmacology and electrophysiology, we recently found that acetylcholine strongly excites VIP neurons, a class of glutamatergic principal neurons in the IC, by activating α3β4* nicotinic acetylcholine receptors (nAChRs). Here, we confirm and extend these results using tissue from mice of both sexes. First, we show that mRNA encoding α3and β4nAChR subunits is expressed in many neurons throughout the IC, including most VIP neurons, suggesting that these subunits, which are rare in the brain, are important mediators of cholinergic signaling in the IC.Next, by combining fluorescent labeling of VIP neurons and immunofluorescence against the vesicular acetylcholine transporter (VAChT), we show that individual VIP neurons in the central nucleus of the IC (ICc) are contacted by a large number of cholinergic boutons. Cholinergic boutons were distributed adjacent to the somata and along the full length of the dendritic arbors of VIP neurons, positioning cholinergic signaling to affect synaptic computations arising throughout the somatodendritic compartments of VIP neurons. In addition, cholinergic boutons were observed in close apposition to dendritic spines on VIP neurons, raising the possibility that cholinergic signaling also modulates presynaptic release onto VIP neurons. Together, these results strengthen evidence that cholinergic signaling exerts widespread influence on auditory computations performed by VIP neurons and other neurons in the IC.
Transient Polycomb activity represses developmental genes in growing oocytes
Authors: Jarred Ellen G. , Qu Zhipeng , Tsai Tesha , Oberin Ruby , Petautschnig Sigrid , Bildsoe Heidi , Pederson Stephen , Zhang Qing-hua , Stringer Jessica M. , Carroll John , Gardner David K. , van den Buuse Maarten , Sims Natalie A. , Gibson William T. , Adelson David L. , Western Patrick S. 
Published: September 2022

AbstractBackgroundNon-genetic disease inheritance and offspring phenotype is substantially influenced by germline epigenetic programming, including genomic imprinting. Loss of Polycomb Repressive Complex 2 (PRC2) function in oocytes causes non-genetically inherited effects on offspring, including embryonic growth restriction followed by post-natal offspring overgrowth. While PRC2 dependent non-canonical imprinting is likely to contribute, less is known about germline epigenetic programming of non-imprinted genes during oocyte growth. In addition, de novo germline mutations in genes encoding PRC2 lead to overgrowth syndromes in human patients, but the extent to which PRC2 activity is conserved in human oocytes is poorly understood.ResultsIn this study we identify a discrete period of early oocyte growth during which PRC2 is expressed in mouse growing oocytes. Deletion of Eed during this window led to the de-repression of 343 genes. A high proportion of these were developmental regulators, and the vast majority were not imprinted genes. Many of the de-repressed genes were also marked by the PRC2-dependent epigenetic modification histone 3 lysine 27 trimethylation (H3K27me3) in primary-secondary mouse oocytes, at a time concurrent with PRC2 expression. In addition, we found H3K27me3 was also enriched on many of these genes by the germinal vesicle (GV) stage in human oocytes, strongly indicating that this PRC2 function is conserved in the human germline. However, while the 343 genes were de-repressed in mouse oocytes lacking EED, they were not de-repressed in pre-implantation embryos and lost H3K27me3 during pre-implantation development. This implies that H3K27me3 is a transient feature that represses a wide range of genes in oocytes.ConclusionsTogether, these data indicate that EED has spatially and temporally distinct functions in the female germline to repress a wide range of developmentally important genes, and that this activity is conserved in the mouse and human germlines.