bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shared neurophysiological resources between exogenous and endogenous visuospatial attentional processes
Authors: Landry Mathieu , Da Silva Castanheira Jason , Baillet Sylvain , Sackur Jérôme , Raz Amir 
Published: April 2022

AbstractPrevailing accounts of visuospatial attention differentiate exogenous (involuntary shifts) from endogenous (voluntary control) orienting of attention. While these two forms of attentional processes are functionally separable, their interactions have been at the center of ongoing debates for more than two decades. One hypothesis is that exogenous and endogenous attention interfere because they share processing resources. Here, we confirm that endogenous attention alters exogenous attention processing, and examine the role of alpha-band neurophysiological activity in such interference events. We contrast the effects of exogenous attention across two experimental conditions: a single-cueing condition where exogenous attention is engaged alone, and a double-cueing condition where exogenous attention is concurrently engaged with endogenous attention. Our results show that the engagement of endogenous attention alters the emergence of exogenous attention across cue-related and target-related brain processes. Importantly, we also report that classifiers trained to decode exogenous attention from the power and phase of alpha-band brain activity in the single-cueing condition fail to do so in the doublecueing condition, where endogenous attention is also engaged. Taken together, our observations challenge the idea that exogenous attention operates independently from top-down processes and demonstrate that both forms of attention orienting engage shared brain processes, which constrain their interactions.Significance StatementVisuospatial attention is often dichotomized into top-down and bottom-up components: Top-down attention reflects slow voluntary shifts of attention orienting, while bottom-up attention is recruited by emerging demands from the environment. A large body of previous findings support the view that these two forms of attention orienting are functionally separable, with some interactions. The current study examines such interactions between top-down and bottom-up attention. Using electroencephalography (EEG) and multivariate pattern classification techniques, the researchers show that top-down attention interferes with the brain activity patterns of bottom-up attention. Moreover, machine learning classifiers trained to detect bottom-up attention based on brain activity in the alpha band (8-12 Hz), a marker of visuospatial attention, fail systematically when top-down attention is also engaged. The authors therefore conclude that both forms of visuospatial orienting are supported by overlapping processes that share brain resources.
Genome-scale metabolic modelling enables deciphering ethanol metabolism via the acrylate pathway in the propionate-producer Anaerotignum neopropionicum
Authors: Benito-Vaquerizo Sara , Olm Ivette Parera , de Vroet Thijs , Schaap Peter J. , Sousa Diana Z , Martins dos Santos Vitor A.P. , Suarez-Diez Maria 
Published: April 2022

AbstractBackgroundMicrobial production of propionate from diluted streams of ethanol (e.g., deriving from syngas fermentation) is a sustainable alternative to the petrochemical production route. Yet, few ethanol-fermenting propionigenic bacteria are known, and understanding of their metabolism is limited. Anaerotignum neopropionicum is a propionate-producing bacterium that uses the acrylate pathway to ferment ethanol and CO2 to propionate and acetate. In this work, we used computational and experimental methods to study the metabolism of A. neopropionicum and, in particular, the pathway for conversion of ethanol into propionate.ResultsOur work describes iANEO_SB607, the first genome-scale metabolic model (GEM) of A. neopropionicum. The model was built combining the use of automatic tools with an extensive manual curation process, and it was validated with experimental data from this and published studies. The model predicted growth of A. neopropionicum on ethanol, lactate, sugars and amino acids, matching observed phenotypes. In addition, the model was used to implement a dynamic flux balance analysis (dFBA) approach that accurately predicted the fermentation profile of A. neopropionicum during batch growth on ethanol. A systematic analysis of the metabolism of A. neopropionicum combined with model simulations shed light into the mechanism of ethanol fermentation via the acrylate pathway, and revealed the presence of the electron-transferring complexes NADH-dependent reduced ferredoxin:NADP+ oxidoreductase (Nfn) and acryloyl-CoA reductase-EtfAB, identified for the first time in this bacterium.ConclusionsThe realisation of the GEM iANEO_SB607 is a stepping stone towards the understanding of the metabolism of the propionate-producer A. neopropionicum. With it, we have gained insight into the functioning of the acrylate pathway and energetic aspects of the cell, with focus on the fermentation of ethanol. Overall, this study provides a basis to further exploit the potential of propionigenic bacteria as microbial cell factories.
A population of gray matter oligodendrocytes directly associates with the vasculature
Authors: Palhol Justine S. C. , Balia Maddalena , Terán Fernando Sánchez-Román , Labarchède Mélody , Gontier Etienne , Battefeld Arne 
Published: April 2022

AbstractOligodendrocyte lineage cells interact with the vasculature in the gray matter. Physical and functional interactions between blood vessels and oligodendrocyte precursor cells play an essential role in both the developing and adult brain. Oligodendrocyte precursor cells have been shown to migrate along the vasculature and subsequently detach from it during their differentiation to oligodendrocytes. However, the association of mature oligodendrocytes with blood vessels has been noted since the discovery of this glial cell type almost a century ago and this interaction remains poorly explored. Here, we systematically investigated the extent of mature oligodendrocyte interaction with the vasculature in mouse. We found that ~17% of oligodendrocytes were in contact with blood vessels in cortex, hippocampus and cerebellum. Contacts were made mainly with capillaries and sparsely with larger arterioles or venules. By combining light and serial electron microscopy, we demonstrated that oligodendrocytes are in direct contact with the vascular basement membrane, raising the possibility of direct signaling pathways and metabolite exchange with endothelial cells. During experimental remyelination in the adult, oligodendrocytes were regenerated and associated with blood vessels in the same proportion compared to control cortex, suggesting a homeostatic regulation of the vasculature-associated oligodendrocyte population. Based on the frequent and close association with blood vessels, we propose that vasculature-associated oligodendrocytes should be considered as an integral part of the vasculature microenvironment. This particular location could underlie specific functions of vasculature-associated oligodendrocytes, while contributing to the vulnerability of mature oligodendrocytes in neurological diseases.
Receptor binding domain of SARS-CoV-2 is a functional αv-integrin agonist
Authors: Norris Emma G. , Pan Xuan Sabrina , Hocking Denise C. 
Published: April 2022

ABSTRACTAmong the novel mutations distinguishing SARS-CoV-2 from similar respiratory coronaviruses is a K403R substitution in the receptor-binding domain (RBD) of the viral spike (S) protein within its S1 region. This amino acid substitution occurs near the angiotensin-converting enzyme 2 (ACE2)-binding interface and gives rise to a canonical RGD adhesion motif that is often found in native extracellular matrix proteins, including fibronectin. In the present study, the ability of recombinant S1-RBD to bind to cell surface integrins and trigger downstream signaling pathways was assessed and compared to RGD-containing, integrin-binding fragments of fibronectin. S1-RBD supported adhesion of both fibronectin-null mouse embryonic fibroblasts as well as primary human small airway epithelial cells. Cell adhesion to S1-RBD was cation- and RGD-dependent, and was inhibited by blocking antibodies against αvand β3, but not α5or β1, integrins. Similarly, direct binding of S1-RBD to recombinant human αvβ3and αvβ6integrins, but not α5β1integrins, was observed by surface plasmon resonance. Adhesion to S1-RBD initiated cell spreading, focal adhesion formation, and actin stress fiber organization to a similar extent as fibronectin. Moreover, S1-RBD stimulated tyrosine phosphorylation of the adhesion mediators FAK, Src, and paxillin, Akt activation, and supported cell proliferation. Together, these data demonstrate that the RGD sequence within S1-RBD can function as an αv-selective integrin agonist. This study provides evidence that cell surface αv-containing integrins can respond functionally to spike protein and raise the possibility that S1-mediated dysregulation of ECM dynamics may contribute to the pathogenesis and/or post-acute sequelae of SARS-CoV-2 infection.
Endogenous viral elements reveal associations between a non-retroviral RNA virus and symbiotic dinoflagellate genomes
Authors: Veglia Alex J. , Bistolas Kalia S.I. , Voolstra Christian R. , Hume Benjamin C. C. , Planes Serge , Allemand Denis , Boissin Emilie , Wincker Patrick , Poulain Julie , Moulin Clémentine , Bourdin Guillaume , Iwankow Guillaume , Romac Sarah , Agostini Sylvain , Banaigs Bernard , Boss Emmanuel , Bowler Chris , de Vargas Colomban , Douville Eric , Flores Michel , Forcioli Didier , Furla Paola , Galand Pierre , Gilson Eric , Lombard Fabien , Pesant Stéphane , Reynaud Stéphanie , Sunagawa Shinichi , Thomas Olivier , Troublé Romain , Zoccola Didier , Correa Adrienne M.S. , Vega Thurber Rebecca L. 
Published: April 2022

AbstractEndogenous viral elements (EVEs) offer insight into the evolutionary histories and hosts of contemporary viruses. This study leveraged DNA metagenomics and genomics to detect and infer the host of a non-retroviral dinoflagellate-infecting +ssRNA virus (dinoRNAV) common in coral reefs. As part of the Tara Pacific Expedition, this study surveyed 269 newly sequenced cnidarians and their resident symbiotic dinoflagellates (Symbiodiniaceae), associated metabarcodes, and publicly available metagenomes, revealing 178 dinoRNAV EVEs, predominantly among hydrocoral-dinoflagellate metagenomes. Putative associations between Symbiodiniaceae and dinoRNAV EVEs were corroborated by the characterization of dinoRNAV-like sequences in 17 of 18 scaffold-scale and one chromosome-scale dinoflagellate genome assembly, flanked by characteristically cellular sequences and in proximity to retroelements, suggesting potential mechanisms of integration. EVEs were not detected in dinoflagellate-free (aposymbiotic) cnidarian genome assemblies, including stony corals, hydrocorals, jellyfish, or seawater. The pervasive nature of dinoRNAV EVEs within dinoflagellate genomes (especially Symbiodinium), as well as their inconsistent within-genome distribution and fragmented nature, suggest ancestral or recurrent integration of this virus with variable conservation. Broadly, these findings illustrate how +ssRNA viruses may obscure their genomes as members of nested symbioses, with implications for host evolution, exaptation, and immunity in the context of reef health and disease.
Analysis of community connectivity in spatial transcriptomics data
Authors: Allen Carter , Jung Kyeong Joo , Chang Yuzhou , Ma Qin , Chung Dongjun 
Published: April 2022

AbstractThe advent of high throughput spatial transcriptomics (HST) has allowed for unprecedented characterization of spatially distinct cell communities within a tissue sample. While a wide range of computational tools exist for detecting cell communities in HST data, none allow for characterization of community connectivity, i.e., the relative similarity of cells within and between found communities – an analysis task that can elucidate cellular dynamics in important settings such as the tumor microenvironment. To address this gap, we introduce the concept of analysis of community connectivity (ACC), which entails not only labeling distinct cell communities within a tissue sample, but understanding the relative similarity of cells within and between communities. We develop a Bayesian multi-layer network model called BANYAN for integration of spatial and gene expression information to achieve ACC. We use BANYAN to implement ACC in invasive ductal carcinoma, and uncover distinct community structure relevant to the interaction of cell types within the tumor microenvironment. Next, we show how ACC can help clarify ambiguous annotations in a human white adipose tissue sample. Finally, we demonstrate BANYAN’s ability to recover community connectivity structure via a simulation study based on real sagittal mouse brain HST data.AvailabilityAn R package banyan is available at https://github.com/carter-allen/banyan.Contactchung.911@osu.eduSupplementary informationSupplementary data are available online.Author SummaryThe proliferation of spatial transcriptomics technologies have prompted the development of numerous statistical models for characterizing the makeup of a tissue sample in terms of distinct cell sub-populations. However, existing methods regard inferred sub-populations as static entities and do not offer any ability to discover the relative similarity of cells within and between communities, thereby obfuscating the true interactive nature of cells in a tissue sample. We develop BANYAN: a statistical model for implementing analysis of community connectivity (ACC), i.e., the process of inferring the similarity of cells within and between cell sub-populations. We demonstrate the utility of ACC through the analysis of a publicly available breast cancer data set, which revealed distinct community structure between tumor suppressive and invasive cancer cell sub-populations. We then showed how ACC may help elucidate ambiguous sub-population annotations in a publicly available human white adipose tissue data set. Finally, we implement a simulation study to validate BANYAN’s ability to recover true community connectivity structure in HST data.
Extracellular vesicles secreted byBrugia malayimicrofilariae modulate the melanization pathway in the mosquito host
Authors: Loghry Hannah J. , Kwon Hyeogsun , Smith Ryan C , Sondjaja Noelle A , Minkler Sarah J , Young Sophie , Wheeler Nicolas J , Zamanian Mostafa , Bartholomay Lyric C , Kimber Michael J 
Published: April 2022

AbstractVector-borne, filarial nematode diseases represent a significant and affecting disease burden in humans, domestic animals, and livestock worldwide. Parasitic filarial nematodes require both an intermediate (vector) host and a definitive (mammalian) host during the course of their life cycle. In either host, the nematode must evade the host elicited immune response in order to develop and establish infection. There is direct evidence of parasite-derived immunomodulation in mammals, however, there is less evidence of parasite immunomodulation of the vector host. We have previously reported that all life stages ofBrugia malayi, a causative agent of lymphatic filariasis, secrete extracellular vesicles (EVs). Here we investigate the immunomodulatory effects of microfilariae derived EVs on the vector hostAedes aegypti.RNA-seq analysis of anA. aegypticell line treated withB. malayimicrofilariae EVs showed differential expression of both mRNAs and miRNAs, some with roles in immune regulation. One downregulated gene, AAEL002590, identified as a serine protease, was shown to have direct involvement in the phenoloxidase (PO) cascade through analysis of PO activity. Similarly, injection of adult female mosquitoes withB. malayimicrofilariae EVs validated these resultsin vivo, eliciting a downregulation of the AAEL002590 transcript and a significant reduction in PO activity. Our data indicates that parasite-derived EVs are capable of interfering with critical immune responses in the vector host, particularly immune responses such as melanization that target extracellular parasites. In addition, this data provides novel targets for transmission control strategies for LF and other parasitic diseases.Author SummaryVector-borne, filarial nematode diseases represent a significant and affecting disease burden in humans, domestic animals and livestock worldwide. Parasitic nematodes must evade the elicited immune response of their hosts in order to develop and establish infection. While there is evidence for immunomodulation of the mammalian host, the mechanism of this immunomodulation is not fully clear and there is limited evidence for immunomodulation of the vector host. Here we have shown that parasite-derived extracellular vesicles are effector structures for immunomodulation of the vector host. In particular, we have identified that parasite-derived extracellular vesicles can interfere with critical mosquito immune responses against parasites. This data provides insight into parasite biology and novel targets for transmission control strategies for parasitic diseases.
Beyond bold versus shy: Zebrafish exploratory behavior falls into several behavioral clusters and is influenced by strain and sex
Authors: Rajput Neha , Parikh Kush , Kenney Justin W. 
Published: April 2022

AbstractConsistent individual differences in exploratory behavior have been found across a range of taxa, including zebrafish, and are thought to contribute to evolutionary fitness. Animals that explore more of a novel environment, and visit areas of high predation risk, are considered bold, whereas animals with the opposite pattern of behavior are considered shy. Here, we examined whether this bimodal characterization of bold versus shy adequately captures the breadth of exploratory behavior exhibited by zebrafish or if, instead, behavior falls into multiple distinct behavioral subtypes. To identify the presence of behavioral subtypes, we applied unsupervised machine learning to behaviors extracted from three-dimensional swim traces from over 400 adult zebrafish across four strains (AB, TL, TU, and WIK) and both sexes. We found that behavior stratified into four distinct clusters. These included previously described bold and shy behavior as well as two new behavioral types: wall-huggers and active explorers. Consistent with prior work that found individual differences to be stable across time and influenced by biological factors like genetics and sex, the behavioral subtypes we identified were stable for up to 10 weeks and were influenced by the strain and sex of the animals. Taken together, our work suggests that individual differences in zebrafish exploratory behavior goes beyond bold versus shy and exhibits greater complexity than is typically assumed.
On the interaction between Janzen-Connell effects and habitat partitioning in spatially structured environments
Authors: Smith Daniel J. B. 
Published: April 2022

Janzen-Connell Effects and Habitat Partitioning have both been proposed as potential stabilizing mechanisms in species-rich forest communities. Janzen-Connell Effects describe the process in which specialized predators are attracted to adult trees, which reduce the survivorship of nearby conspecific juveniles. This is thought to generate stabilizing negative frequency dependence. Habitation Partitioning describes when species exhibit different fitness responses to spatially heterogeneous environmental factors, typically causing species to aggregate into favorable habitat types. Despite substantial empirical evidence that both processes occur simultaneously in empirical systems, the theoretical implications of how their interactions shape species diversity remain underdeveloped. In this study, I examine a spatially explicit model that incorporates both processes. I show that Janzen-Connell Effects and Habitat Partitioning can act synergistically to promote coexistence such that their contribution to species coexistence is greater than the sum of their parts when environmental spatial heterogeneity is positively autocorrelated. The results of this study highlight the need to explicitly model the interaction between co-occurring spatially dependent coexistence mechanisms to understand the role they play in the maintenance of species diversity.Significance StatementA primary goal of ecology is to explain the maintenance of species diversity. However, the mechanisms that underlie the coexistence of highly diverse tropical rainforests remain contentious. Two leading hypotheses are Janzen-Connell Effects and Habitat Partitioning. Both hypotheses are based on space. Janzen-Connell Effects are based on the observation that natural enemies attracted to adult trees reduce the survival of their nearby seeds and seedlings. In contrast, Habitation Partitioning states that diversity can be maintained when species exhibit different responses to spatially varying environmental conditions such that species congregate into their preferred habitat types. In this paper, I demonstrate that these mechanisms can interact synergistiacally to promote high species diversity.
Multi-trait genomic prediction improves selection accuracy for enhancing seed mineral concentrations in pea (Pisum sativum L.)
Authors: Atanda Sikiru Adeniyi , Steffes Jenna , Lan Yang , Al Bari Md Abdullah , Kim Jeonghwa , Morales Mario , Johnson Josephine , Saludares Rica Amor , Worral Hannah , Piche Lisa , Ross Andrew , Grusak Michael A , Coyne Clarice J. , McGee Rebecca J. , Rao Jiajia , Bandillo Nonoy 
Published: April 2022

AbstractThe superiority of multi-trait genomic selection (MT-GS) over univariate genomic selection (UNI-GS) can be improved by redesigning the phenotyping strategy. In this study, we used about 300 advanced breeding lines from North Dakota State University (NDSU) pulse breeding program and about 200 USDA accessions evaluated for ten nutritional traits to assess the efficiency of sparse testing in MT-GS. Our results showed that sparse phenotyping using MT-GS consistently outperformed UNI-GS when compared to partially balanced phenotyping using MT-GS. This strategy can be further extended to multi-environment multi-trait GS to improve prediction performance and reduce the cost of phenotyping and time-consuming data collection process. Given that MT-GS relies on borrowing information from genetically correlated traits and relatives, consideration should be given to trait combinations in the training and prediction sets to improve model parameters estimate and ultimately prediction performance. Our results point to heritability and genetic correlation between traits as possible parameters to achieve this objective.
Reducing peptide sequence bias in quantitative mass spectrometry data with machine learning
Authors: Dincer Ayse , Lu Yang , Schweppe Devin , Oh Sewoong , Noble William Stafford 
Published: April 2022

AbstractQuantitative mass spectrometry measurements of peptides necessarily incorporate sequence-specific biases that reflect the behavior of the peptide during enzymatic digestion, liquid chromatography, and in the mass spectrometer. These sequence-specific effects impair quantification accuracy, yielding peptide quantities that are systematically under- or over-estimated. We provide empirical evidence for the existence of such biases, and we use a deep neural network, called Pepper, to automatically identify and reduce these biases. The model generalizes to new proteins and new runs within a related set of MS/MS experiments, and the learned coefficients themselves reflect expected physicochemical properties of the corresponding peptide sequences. The resulting adjusted abundance measurements are more correlated with mRNA-based gene expression measurements than the unadjusted measurements. Pepper is suitable for data generated on a variety of mass spectrometry instruments, and can be used with labeled or label-free approaches, and with data-independent or data-dependent acquisition.