bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unique structure and positive selection promote the rapid divergence of Drosophila Y chromosomes
Authors: Chang Ching-Ho , Gregory Lauren E. , Gordon Kathleen E. , Meiklejohn Colin D. , Larracuente Amanda M. 
Published: August 2021

AbstractY chromosomes across diverse species convergently evolve a gene-poor, heterochromatic organization enriched for duplicated genes, LTR retrotransposable elements, and satellite DNA. Sexual antagonism and a loss of recombination play major roles in the degeneration of young Y chromosomes. However, the processes shaping the evolution of mature, already degenerated Y chromosomes are less well-understood. Because Y chromosomes evolve rapidly, comparisons between closely related species are particularly useful. We generated de novo long read assemblies complemented with cytological validation to reveal Y chromosome organization in three closely related species of the Drosophila simulans complex, which diverged only 250,000 years ago and share >98% sequence identity. We find these Y chromosomes are divergent in their organization and repetitive DNA composition and discover new Y-linked gene families whose evolution is driven by both positive selection and gene conversion. These Y chromosomes are also enriched for large deletions, suggesting that the repair of double-strand breaks on Y chromosomes may be biased toward microhomology-mediated end joining over canonical non-homologous end-joining. We propose that this repair mechanism generally contributes to the convergent evolution of Y chromosome organization.
On the nature of the earliest known lifeforms
Authors: Kanaparthi Dheeraj , Westall Frances , Lampe Marko , Zhu Baoli , Boesen Thomas , Scheu Bettina , Klingl Andreas , Schwille Petra , Lueders Tillmann 
Published: August 2021

AbstractMicrofossils from the Paleoarchean Eon are the oldest known evidence of life. Despite their significance in understanding the history of life on Earth, any interpretation of the nature of these microfossils has been a point of contention among researchers. Decades of back-and-forth arguments led to the consensus that reconstructing the lifecycles of Archaean Eon organisms is the most promising way of understanding the nature of these microfossils. Here, we transformed a Gram-positive bacterium into a primitive lipid vesicle-like state and studied it under environmental conditions prevalent on early Earth. Using this approach, we successfully reconstructed morphologies and life cycles of Archaean microfossils. In addition to reproducing microfossil morphologies, we conducted experiments that spanned years to understand the process of cell degradation and how Archaean cells could have undergone encrustation minerals (in this case, salt), leading to their preservation as fossilized organic carbon in the rock record. These degradation products strongly resemble fossiliferous features from Archaean rock formations. Our observations suggest that microfossils aged between 3.8 to 2.5Ga most likely were liposome-like protocells that have evolved physiological pathways of energy conservation but not the mechanisms to regulate their morphology. Based on these observations, we propose that morphology is not a reliable indicator of taxonomy in these microfossils.
Spatial analysis for highly multiplexed imaging data to identify tissue microenvironments
Authors: Patrick Ellis , Canete Nicolas P. , Iyengar Sourish S. , Harman Andrew N. , Sutherland Greg T. , Yang Pengyi 
Published: August 2021

AbstractHighly multiplexedin situimaging cytometry assays have made it possible to study the spatial organisation of numerous cell types simultaneously. We have addressed the challenge of quantifying complex multi-cellular relationships by proposing a statistical method which clusters local indicators of spatial association. Our approach successfully identifies distinct tissue architectures in datasets generated from three state-of-the-art high-parameter assays demonstrating its value in summarising the information-rich data generated from these technologies.
Particle Uptake Driven Phagocytosis in Macrophages and Neutrophils Enhances Bacterial Clearance
Authors: Sharma Preeti , Vijaykumar Anjali , Raghavan Jayashree Vijaya , Rananaware Supriya Rajendra , Alakesh Alakesh , Bodele Janhavi , Rehman Junaid Ur , Shukla Shivani , Wagde Virta , Nadig Savitha , Chakrabarti Sveta , Visweswariah Sandhya S. , Nandi Dipankar , Gopal Balasubramanian , Jhunjhunwala Siddharth 
Published: August 2021

AbstractHumans are exposed to numerous synthetic foreign particulates in the form of environmental pollutants and diagnostic or therapeutic agents. Specialized immune cells (phagocytes) clear these particulates by phagocytosing and attempting to degrade them. The process of recognition and internalization of the particulates may trigger changes in the function of phagocytes. Some of these changes, especially the ability of a particle-loaded phagocyte to take up and neutralize pathogens, remains poorly studied. Herein, we demonstrate that the uptake of non-stimulatory cargo-free particles enhances the phagocytic ability of monocytes, macrophages and neutrophils. The enhancement in phagocytic ability was independent of particle properties, such as size or the base material constituting the particle. Additionally, we show that the increased phagocytosis was not a result of cellular activation or cellular heterogeneity but was driven by changes in cell membrane fluidity and cellular compliance. A consequence of the enhanced phagocytic activity was that particulate-laden immune cells neutralize E. coli faster in culture. Moreover, when administered in mice as a prophylactic, particulates enable faster clearance of E. coli and S. epidermidis. Together, we demonstrate that the process of uptake induces cellular changes that favor additional phagocytic events. This study provides insights into using non-stimulatory cargo-free particles to engineer immune cell functions for applications involving faster clearance of phagocytosable particulates.
Endothelial cell polarity and extracellular matrix production rely on functional ATP6AP2 during developmental and pathological angiogenesis
Authors: Patel NR , Blanks A , Li Y , Prieto MC , Meadows SM 
Published: August 2021

AbstractThe (Pro)renin receptor ((P)RR), also known as ATP6AP2, is a single-transmembrane protein that is implicated in a multitude of biological processes. However, the exact role of ATP6AP2 during blood vessel development remains largely undefined. Here, we use an inducible endothelial cell (EC)-specificAtp6ap2knockout mouse model to investigate the role of ATP6AP2 during both physiological and pathological angiogenesisin vivo. We observed that postnatal deletion ofAtp6ap2in ECs results in cell migration defects, loss of tip cell polarity and subsequent impairment of retinal angiogenesis.In vitro, Atp6ap2deficient ECs similarly displayed reduced cell migration, impaired sprouting, and defective cell polarity. Transcriptional profiling of ECs isolated fromAtp6ap2mutant mice further indicated regulatory roles in angiogenesis, cell migration and extracellular matrix composition. Mechanistically, we showed that expression of various extracellular matrix components is controlled by ATP6AP2 via the extracellular-signal-regulated kinase (ERK) pathway. Furthermore,Atp6ap2deficient retinas exhibited reduced revascularization in an oxygen induced retinopathy model. Collectively, our results demonstrated a critical role of ATP6AP2 as a regulator of developmental and pathological angiogenesis.
A Novel Model for Encephalomyosynangiosis Surgery after Middle Cerebral Artery Occlusion-Induced Stroke in Mice
Authors: Paro Mitch , Turro Daylin Gamiotea , Blumenfeld Leslie , Bulsara Ketan R. , Verma Rajkumar 
Published: August 2021

AbstractBackground and PurposeNo effective treatment is available for most patients who suffer ischemic stroke. Development of novel treatment options is imperative. The brain attempts to self-heal after ischemic stroke via various mechanism mediated by restored blood circulation in affected region of brain but this process is limited by inadequate angiogenesis or neoangiogenesis. Encephalomyosynangiosis (EMS) is a neurosurgical procedure that achieves angiogenesis with low morbidity in patients with moyamoya disease, reducing risk of stroke. However, EMS, surgery has never been studied as an therapeutic option after ischemic stroke. Here we described a novel procedure and feasibility data for EMS after ischemic stroke in mice.MethodsA 60 mins of middle cerebral artery occlusion (MCAo) was used to induce ischemic stroke in mice. After 3-4 hours of MCAo onset/sham, EMS was performed. Mortality of EMS, MCAo and. MCAo+EMS mice was recorded up to 21 days after surgery. Graft tissue viability was measured using a nicotinamide adenine dinucleotide reduced tetrazolium reductase assay.ResultsEMS surgery after ischemic stroke does not increase mortality compared to stroke alone. Graft muscle tissue remained viable 21 days after surgery.ConclusionsThis novel protocol is effective and well-tolerated, may serve as novel platform for new angiogenesis and thus recovery after ischemic stroke. If successful in mice, EMS can a very feasible and novel treatment option for ischemic stroke in humans.
Understanding the microbial biogeography of ancient human dentitions to guide study design and interpretation
Authors: Fagernäs Zandra , Salazar-García Domingo C. , Avilés Azucena , Haber María , Henry Amanda , Maurandi Joaquín Lomba , Ozga Andrew , Velsko Irina M , Warinner Christina 
Published: August 2021

AbstractThe oral cavity is a heterogeneous environment, varying in factors such as pH, oxygen levels, and salivary flow. These factors affect the microbial community composition and distribution of species in dental plaque, but it is not known how well these patterns are reflected in archaeological dental calculus. In most archaeological studies, a single sample of dental calculus is studied per individual and is assumed to represent the entire oral cavity. However, it is not known if this sampling strategy introduces biases into studies of the ancient oral microbiome. Here, we present the results of a shotgun metagenomic study of a dense sampling of dental calculus from four Chalcolithic individuals from the southeast Iberian peninsula (ca. 4500-5000 BP). Inter-individual differences in microbial composition are found to be much larger than intra-individual differences, indicating that a single sample can indeed represent an individual in most cases. However, there are minor spatial patterns in species distribution within the oral cavity that should be taken into account when designing a study or interpreting results. Finally, we show that plant DNA identified in the samples may be of environmental origin, showing the importance of including environmental controls or several lines of biomolecular evidence.
Generation of nanobodies targeting the human, transcobalamin-mediated vitamin B12 uptake route
Authors: Bloch Joël S. , Sequeira Jeffrey M. , Ramírez Ana S. , Quadros Edward V. , Locher Kaspar P. 
Published: August 2021

AbstractCellular uptake of vitamin B12 in humans is mediated by the endocytosis of the B12 carrier protein transcobalamin (TC) via its cognate cell surface receptor TCblR (or CD320), encoded by the CD320 gene(1). Because CD320 expression is associated with the cell cycle and upregulated in highly proliferating cells such as cancer cells(2–4), this uptake route is a potential target for cancer therapy(5). We developed and characterized four camelid nanobodies that bind TC or the interface of the TC:TCblR complex with nanomolar affinities. We determined X-ray crystal structures of all four nanobodies in complex with TC:TCblR, which enabled us to map their binding sites. When conjugated to a toxin, three of these nanobodies are capable of inhibiting the growth of HEK293T cells and therefore have the potential to inhibit the growth of human cancer cells. We visualized the cellular binding and endocytic uptake of the most potent nanobody (TCNB4) using fluorescent light microscopy. The co-crystal structures of TC:TCblR with another nanobody (TCNB34) revealed novel features of the interface of TC and the LDLR-A1 domain of TCblR. Our findings rationalize the structural basis for a decrease in affinity of TC-B12 binding caused by the TCblR-Glu88 deletion mutant.
A deep learning-based approach to model anomalous diffusion of membrane proteins: The case of the nicotinic acetylcholine receptor
Authors: Buena Maizón Héctor , Barrantes Francisco J. 
Published: August 2021

AbstractWe present a concatenated deep-learning multiple neural network system for the analysis of single-molecule trajectories. We apply this machine learning-based analysis to characterize the translational diffusion of the nicotinic acetylcholine receptor at the plasma membrane, experimentally interrogated using superresolution optical microscopy. The receptor protein displays a heterogeneous diffusion behavior that goes beyond the ensemble level, with individual trajectories exhibiting more than one diffusive state, requiring the optimization of the neural networks through a hyperparameter analysis for different numbers of steps and durations, especially for short trajectories (<50 steps) where the accuracy of the models is most sensitive to localization errors. We next use the statistical models to test for Brownian, continuous-time random walk, and fractional Brownian motion, and introduce and implement an additional, two-state model combining Brownian walks and obstructed diffusion mechanisms, enabling us to partition the two-state trajectories into segments, each of which is independently subjected to multiple analysis. The concatenated multi-network system evaluates and selects those physical models that most accurately describe the receptor’s translational diffusion. We show that the two-state Brownian-obstructed diffusion model can account for the experimentally observed anomalous diffusion (mostly subdiffusive) of the population and the heterogeneous single-molecule behavior, accurately describing the majority (72.5% to 88.7% for α-bungarotoxin-labeled receptor and between 73.5% and 90.3% for antibody-labeled molecules) of the experimentally observed trajectories, with only ∼15% of the trajectories fitting to the fractional Brownian motion model.
2020 BioImage Analysis Survey: Community experiences and needs for the future
Authors: Jamali Nasim , Dobson Ellen TA , Eliceiri Kevin W. , Carpenter Anne E. , Cimini Beth A. 
Published: August 2021

AbstractIn this paper, we summarize a global survey of 484 participants of the imaging community, conducted in 2020 through the NIH Center for Open BioImage Analysis (COBA). This 23-question survey covered experience with image analysis, scientific background and demographics, and views and requests from different members of the imaging community. Through open-ended questions we asked the community to provide feedback for the open-source tool developers and tool user groups. The community’s requests for tool developers include general improvement of tool documentation and easy-to-follow tutorials. Respondents encourage tool users to follow the best practices guidelines for imaging and ask their image analysis questions on the Scientific Community Image forum (forum.image.sc). We analyzed the community’s preferred method of learning, based on level of computational proficiency and work description. In general, written step-by-step and video tutorials are preferred methods of learning by the community, followed by interactive webinars and office hours with an expert. There is also enthusiasm for a centralized location online for existing educational resources. The survey results will help the community, especially developers, trainers, and organizations like COBA, decide how to structure and prioritize their efforts.Impact statementThe Bioimage analysis community consists of software developers, imaging experts, and users, all with different expertise, scientific background, and computational skill levels. The NIH funded Center for Open Bioimage Analysis (COBA) was launched in 2020 to serve the cell biology community’s growing need for sophisticated open-source software and workflows for light microscopy image analysis. This paper shares the result of a COBA survey to assess the most urgent ongoing needs for software and training in the community and provide a helpful resource for software developers working in this domain. Here, we describe the state of open-source bioimage analysis, developers’ and users’ requests from the community, and our resulting view of common goals that would serve and strengthen the community to advance imaging science.
SeqDistK: a Novel Tool for Alignment-free Phylogenetic Analysis
Authors: Liu Xuemei , Li Wen , Huang Guanda , Huang Tianlai , Xiong Qingang , Chen Wen , Xia Li C. 
Published: August 2021

AbstractAlgorithms for constructing phylogenetic trees are fundamental to study the evolution of viruses, bacteria, and other microbes. Established multiple alignment-based algorithms are inefficient for large scale metagenomic sequence data because of their high requirement of inter-sequence correlation and high computational complexity. In this paper, we present SeqDistK, a novel tool for alignment-free phylogenetic analysis. SeqDistK computes the dissimilarity matrix for phylogenetic analysis, incorporating seven k-mer based dissimilarity measures, namely d2, d2S, d2star, Euclidean, Manhattan, CVTree, and Chebyshev. Based on these dissimilarities, SeqDistK constructs phylogenetic tree using the Unweighted Pair Group Method with Arithmetic Mean algorithm. Using a golden standard dataset of 16S rRNA and its associated phylogenetic tree, we compared SeqDistK to Muscle – a multi sequence aligner. We found SeqDistK was not only 38 times faster than Muscle in computational efficiency but also more accurate. SeqDistK achieved the smallest symmetric difference between the inferred and ground truth trees with a range between 13 to 18, while that of Muscle was 62. When measures d2, d2star, d2S, Euclidean, and k-mer size k=5 were used, SeqDistK consistently inferred phylogenetic tree almost identical to the ground truth tree. We also performed clustering of 16S rRNA sequences using SeqDistK and found the clustering was highly consistent with known biological taxonomy. Among all the measures, d2S (k=5, M=2) showed the best accuracy as it correctly clustered and classified all sample sequences. In summary, SeqDistK is a novel, fast and accurate alignment-free tool for large-scale phylogenetic analysis. SeqDistK software is freely available athttps://github.com/htczero/SeqDistK.
Revisiting a classic hybrid zone: rapid movement of the northern flicker hybrid zone in contemporary times
Authors: Aguillon Stepfanie M. , Rohwer Vanya G. 
Published: August 2021

AbstractNatural hybrid zones have provided important insights into the evolutionary process, and their geographic stability/instability over time can help to disentangle the underlying biological processes that maintain them. Here, we leverage replicated sampling of an identical transect across the hybrid zone between yellow-shafted and red-shafted flickers in the Great Plains to assess its stability over ∼60 years (1955-1957 to 2016-2018). We identify a ∼73 km westward shift in the hybrid zone center towards the range of the red-shafted flicker, but find no associated changes in width over our sampling period. In fact, the hybrid zone remains remarkably narrow, suggesting some kind of selective pressure maintains the zone. By comparing to previous work in the same geographic region, it appears likely that the movement in the hybrid zone has occurred rapidly in the years since the early 1980s. This recent, rapid movement may be related to changes in climate or land management practices that have allowed asymmetric westward movement of yellow-shafted flickers into the Great Plains.
The Molecular Basis of FimT-mediated DNA Uptake during Bacterial Natural Transformation
Authors: Braus Sebastian A.G. , Short Francesca L. , Holz Stefanie , Stedman Matthew J.M. , Gossert Alvar D. , Hospenthal Manuela K. 
Published: August 2021

AbstractNaturally competent bacteria encode sophisticated protein machineries for the uptake and translocation of exogenous DNA into the cell. If this DNA is integrated into the bacterial genome, the bacterium is said to be naturally transformed. Most competent bacterial species utilise type IV pili for the initial DNA uptake step. These proteinaceous cell-surface structures are composed of thousands of pilus subunits (pilins), designated as major or minor according to their relative abundance in the pilus. In this study, we show that the minor pilin FimT plays an important role in the natural transformation ofLegionella pneumophila. We used NMR spectroscopy,in vitroDNA binding assays andin vivotransformation assays to understand the molecular basis of FimT’s role in this process. FimT directly interacts with DNAviaan electropositive patch, rich in arginines, several of which are well-conserved and located in FimT’s conformationally flexible C-terminal tail. We also show that FimT orthologues from other γ-Proteobacteria share the ability to bind to DNA. Our functional characterisation and comprehensive bioinformatic analysis of FimT, suggest that it plays an important role for DNA uptake in a wide range of competent species.
Deep Learning Features Encode Interpretable Morphologies within Histological Images
Authors: Pour Ali Foroughi , White Brian , Park Jonghanne , Sheridan Todd B. , Chuang Jeffrey H. 
Published: August 2021

ABSTRACTConvolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains difficult. Most studies have considered interpretability in a post hoc fashion, e.g. by presenting example regions with strongly predicted class labels. However, such an approach does not explain the biological features that contribute to correct predictions. To address this problem, here we investigate the interpretability of H&E-derived CNN features (the feature weights in the final layer of a transfer-learning-based architecture), which we show can be construed as abstract morphological genes (“mones”) with strong independent associations to biological phenotypes. We observe that many mones are specific to individual cancer types, while others are found in multiple cancers especially from related tissue types. We also observe that mone-mone correlations are strong and robustly preserved across related cancers. Importantly, linear mone-based classifiers can very accurately separate 38 distinct classes (19 tumor types and their adjacent normals, AUC=97.1% ± 2.8% for each class prediction), and linear classifiers are also highly effective for universal tumor detection (AUC=99.2% ± 0.12%). This linearity provides evidence that individual mones or correlated mone clusters may be associated with interpretable histopathological features or other patient characteristics. In particular, the statistical similarity of mones to gene expression values allows integrative mone analysis via expression-based bioinformatics approaches. We observe strong correlations between individual mones and individual gene expression values, notably mones associated with collagen gene expression in ovarian cancer. Mone-expression comparisons also indicate that immunoglobulin expression can be identified using mones in colon adenocarcinoma and that immune activity can be identified across multiple cancer types, and we verify these findings by expert histopathological review. Our work demonstrates that mones provide a morphological H&E decomposition that can be effectively associated with diverse phenotypes, analogous to the interpretability of transcription via gene expression values.