bluuebunny/crossref_metadata_2025_split huggingface dataset:
NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity
Authors: Su Kenong , Katebi Ataur , Kohar Vivek , Clauss Benjamin , Gordin Danya , Qin Zhaohui S. , Karuturi R. Krishna M. , Li Sheng , Lu Mingyang 
Published: May 2022

AbstractA major question in systems biology is how to identify the core gene regulatory circuit that governs the decision-making of a biological process. Here, we develop a computational platform, named NetAct, for constructing core transcription-factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers regulators’ activity using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation. Our in-silico benchmark test shows that NetAct outperforms existing algorithms in inferring transcriptional activity and gene networks. We illustrate the application of NetAct to model networks driving TGF-β induced epithelial-mesenchymal transition and macrophage polarization.
Alone in a crowd: Effect of a nonfunctional lateral line on expression of the social hormone parathyroid hormone 2
Authors: Venuto Alexandra , Smith Cameron P. , Cameron-Pack Marybelle , Erickson Timothy 
Published: May 2022

ABSTRACTParathyroid hormone 2 (Pth2) is a vertebrate-specific neuropeptide whose thalamic expression is upregulated by social contact with conspecifics. However, social interactions fail to stimulate pth2 expression in isolated zebrafish whose lateral line hair cells have been chemically ablated. These results suggest that modulation of pth2 by social context is acutely dependent on mechanosensory information from the lateral line. However, it is unclear how a congenital loss of lateral line function influences the ability of zebrafish to interpret their social environment. In this study, we measure pth2 levels in zebrafish mutants lacking hair cell function in either the lateral line only, or in both the inner ear and lateral line. Socially-raised lateral line mutants express lower levels of pth2 relative to wild type siblings, but there is no further reduction when all sensory hair cells are nonfunctional. However, social isolation of hair cell mutants causes a further reduction in pth2 expression, pointing to additional unidentified sensory cues that influence pth2 production. Lastly, we report that social context modulates fluorescent transgenes driven by the pth2 promoter. Altogether, these data suggest that lateral line mutants experience a form of isolation, even when raised in a social environment.SUMMARY STATEMENTExpression of the pro-social neuropeptide pth2 is downregulated in larval zebrafish with a congenital loss of lateral line function. Thus, even in social environments, fish with compromised lateral lines may experience a form of isolation.
Intracortical remodelling increases in highly-loaded bone after exercise cessation
Authors: da Silva Raniere Gaia Costa , Sun Tsim Christopher , Mishra Ambika Prasad , Boyde Alan , Doube Michael , Riggs Christopher Michael 
Published: May 2022

AbstractResorption within cortices of long bones removes excess mass and damaged tissue, and increases during periods of reduced mechanical loading. Returning to high-intensity exercise may place bones at risk of failure due to increased porosity caused by bone resorption. We used microradiographs of bone slices from highly-loaded (metacarpal, tibia) and minimally-loaded (rib) bones from 12 racehorses, 6 that died during a period of high-intensity exercise and 6 that had a period of intense exercise followed by at least 35 days of rest prior to death, and measured intracortical canal cross-sectional area (Ca.Ar) and number (N.Ca) to infer remodelling activity across sites and exercise groups. Large canals that are the consequence of bone resorption (Ca.Ar > 0.04 mm2) were 1.4× to 18.7× greater in number and area in the third metacarpal bone from rested than exercised animals (p = 0.005– 0.008), but were similar in number and area in ribs from rested and exercised animals (p = 0.575–0.688). An intermediate relationship was present in the tibia, and when large canals and smaller canals that result from partial bony infilling (Ca.Ar > 0.002 mm2) were considered together. The mechanostat may override targeted remodelling during periods of high mechanical load by enhancing bone formation, reducing resorption and suppressing turnover. Both systems may work synergistically in rest periods to remove excess and damaged tissue.
Predicting Working Memory performance based on specific individual EEG spatiotemporal features
Authors: Changoluisa Vinicio , Poch Claudia , Campo Pablo , Rodriguez Francisco B. 
Published: May 2022

AbstractWorking Memory (WM) is a limited capacity system for storing and processing information, which varies from subject to subject. Several works show the ability to predict the performance of WM with machine learning (ML) methods, and although good prediction results are obtained in these works, ignoring the intersubject variability and the temporal and spatial characterization in a WM task to improve the prediction in each subject. In this paper, we take advantage of the spectral properties of WM to characterize the individual differences in visual WM capacity and predict the subject’s performance. Feature selection was implemented through the selection of electrodes making use of methods to treat unbalanced classes. The results show a correlation between the accuracy achieved with an Regularized Linear Discriminant Analysis (RLDA) classifier using the power spectrum of the EEG signal and the accuracy achieved by each subject in the behavioral experiment response of a WM task with retro-cue. The proposed methodology allows identifying spatial and temporal characteristics in the WM performance in each subject. Our methodology shows that it is possible to predict the WM performance in each subject. Finally, our results showed that by knowing the spatiotemporal characteristics that predict WM performance, it is possible to customize a WM task and optimize the use of electrodes for agile processing adapted to a specific subject. Thus, we pave the way for implementing neurofeedback through a Brain-Computer Interface.
Comparative single-cell transcriptomes of dose and time dependent epithelial-mesenchymal spectrums
Authors: Panchy Nicholas , Watanabe Kazuhide , Takahashi Masataka , Willems Andrew , Hong Tian 
Published: May 2022

AbstractEpithelial-mesenchymal transition (EMT) is a cellular process involved in development and disease progression. Intermediate EMT states were observed in tumors and fibrotic tissues, but previous in vitro studies focused on time-dependent responses with single doses of signals; it was unclear whether single-cell transcriptomes support stable intermediates observed in diseases. Here, we performed single-cell RNA-sequencing with human mammary epithelial cells treated with multiple doses of TGF-β. We found that dose-dependent EMT harbors multiple intermediate states at nearly steady state. Comparisons of dose- and time-dependent EMT transcriptomes revealed that the dose-dependent data enable higher sensitivity to detect genes associated EMT. We identified cell clusters unique to time-dependent EMT, reflecting cells en route to stable states. Combining dose- and time-dependent cell clusters gave rise to accurate prognosis for cancer patients. Our transcriptomic data and analyses uncover a stable EMT continuum at the single-cell resolution, and complementary information of two types of single-cell experiments.
Amplification is the Primary Mode of Gene-by-Sex Interaction in Complex Human Traits
Authors: Zhu Carrie , Ming Matthew J. , Cole Jared M. , Edge Michael D. , Kirkpatrick Mark , Harpak Arbel 
Published: May 2022

SummarySex differences in complex traits are suspected to be in part due to widespread gene-by-sex interactions (GxSex), but empirical evidence has been elusive. Here, we infer the mixture of ways polygenic effects on physiological traits covary between males and females. We find that GxSex is pervasive but acts primarily through systematic sex differences in the magnitude of many genetic effects (“amplification”), rather than in the identity of causal variants. Amplification patterns account for sex differences in trait variance. In some cases, testosterone may mediate amplification. Finally, we develop a population-genetic test linking GxSex to contemporary natural selection and find evidence for sexually antagonistic selection on variants affecting testosterone levels. Taken together, our results suggest that the amplification of polygenic effects is a common mode of GxSex that may contribute to sex differences and fuel their evolution.Abstract Figure
Computational prediction and characterization of cell-type-specific and shared binding sites
Authors: Zhang Qinhu 
Published: May 2022

ABSTRACTCell-type-specific gene expression is maintained in large part by transcription factors (TFs) selectively binding to distinct sets of sites in different cell types. Recent research works have provided evidence that such cell-type-specific binding is determined by TF’s intrinsic sequence preferences, cooperative interactions with cofactors, cell-type-specific chromatin landscapes, and 3D chromatin interactions. However, computational prediction and characterization of cell-type-specific and shared binding sites is rarely studied. In this paper, we propose two computational approaches for predicting and characterizing cell-type-specific and shared binding sites by integrating multiple types of features, in which one is based on XGBoost and another is based on convolutional neural network (CNN). To validate the performance of our proposed approaches, ChIP-seq datasets of 10 binding factors were collected from the GM12878 (lymphoblastoid) and K562 (erythroleukemic) human hematopoietic cell lines, each of which was further categorized into cell-type-specific (GM12878-specific and K562-specific) and shared binding sites. Then, multiple types of features for these binding sites were integrated to train the XGBoost-based and CNN-based models. Experimental results show that our proposed approaches significantly outperform other competing methods on three classification tasks. To explore the contribution of different features, we performed ablation experiments and feature importance analysis. Consistent with previous studies, we find that chromatin features are major contributors in which chromatin accessibility is the best predictor. Moreover, we identified independent feature contribution for cell-type-specific and shared sites through SHAP values, observing that chromatin features play a main role in the cell-type-specific sites while motif features play a main role in the shared sites. Beyond these observations, we explored the ability of the CNN-based model to predict cell-type-specific and shared binding sites by excluding or including DNase signals, showing that chromatin accessibility significantly improves the prediction performance. Besides, we investigated the generalization ability of our proposed approaches to different binding factors in the same cellular environment or to the same binding factors in the different cellular environments.
Microfluidic chemostatic bioreactor for high-throughput screening and sustainable co-harvesting of biomass and biodiesel in microalgae
Authors: Zheng Guoxia , Cui Yutong , Lu Ling , Guo Ming , Hu Xuejun , Wang Lin , Yu Shuping , Sun Shenxia , Li Yuancheng , Zhang Xingcai , Wang Yunhua 
Published: May 2022

ABSTRACTAs a renewable and sustainable source for energy, environment, and biomedical applications, microalgae and microalgal biodiesel have attracted great attention. However, their applications are confined due to the cost-efficiency of microalgal mass production. One-step strategy and continuous culturing systems could be solutions. However, current studies for optimization throughout microalgae-based biofuel production pipelines are generally derived from the batch culture process. Better tools are needed to study algal growth kinetics in continuous systems. A microfluidics chemostatic bioreactor array was presented, providing low-adhesion cultivation for algae in the gas, nutrition, and temperature (GNT) well-controlled environment with high throughput. The chip wasused to mimic the continuous culture environment of bioreactors. It allowed simultaneously studying of 8×8 different chemostatic conditions on algal growth and oil production in parallel on a 7×7 cm2 footprint. On-chip experiments of batch and continuous cultures of Chlorella. sp. were performed to study growth and lipid accumulation under different nitrogen concentrations. The results demonstrated that microalgal cultures can be regulated to grow and accumulate lipids concurrently, thus enhancing lipid productivity in one step. The developed on-chip culturing condition screening, which was more suitable for continuous bioreactor, was achieved at a half shorter time, 64-times higher throughput, and less reagent consumption. It could be used to establish chemostat cultures in continuous bioreactors which can dramatically accelerate the development of renewable and sustainable algal for CO2 fixation and biosynthesis and related systems for advanced sustainable energy, food, pharmacy, and agriculture with enormous social and ecological benefits.TEASERSustainable microfluidic bioreactor for 64 times higher-throughput screening CO2 fixation and biomass and biodiesel production in microalgae.
Temporally integrated transcriptome analysis reveals ASFV pathology and host response dynamics
Authors: Lv Lin , Zhang Tianyun , Zhang Yanyan , Ahsan Asif , Zhao Xiaoyang , Shen Zhiqiang , Chen Teng , Shen Ning 
Published: May 2022

AbstractAfrican swine fever virus (ASFV) causes a lethal swine hemorrhagic disease and is currently responsible for widespread damage to the pig industry. The molecular mechanisms of ASFV pathogenicity and its interaction with host responses remain poorly understood. In this study, we profiled the temporal viral and host transcriptomes in porcine alveolar macrophages (PAMs) infected at 6, 12, 24 and 48 hours with highly virulent (SY18) and low virulent (HuB20) ASFV strains. We first identified profound differences in the virus expression programs between SY18 and HuB20, while the transcriptome dynamics in host cells were dominated by infection time. Through integrated computational analysis and experimental validation, we identified differentially expressed genes and related biological processes, and elaborated differential usage of the NF-kappaB related pathways by the two virus strains. In addition, we observed that compared to the highly virulent SY18 strain, HuB20 infection quickly activates expression of receptors, sensors, regulators, as well as downstream effectors, including cGAS, STAT1/2, IRF9, MX1/2, suggesting rapid induction of a strong immune response. Lastly, we constructed a host-virus coexpression network, which shed light on pathogenic functions of several ASFV genes. Taken together, these results will provide a basis for further mechanistic studies on the functions of both viral and cellular genes that are involved in different responses.Author SummarySince it was first described in Kenya in 1921, ASF has spread across sub-Saharan Africa, the Caribbean, the Western Europe, the Trans-Caucasus region, and the Russian Federation. Recent outbreaks have also been reported in Asia, which has devastated the pig industry, resulting in an approximately 40% reduction in pork worldwide. In the absence of effective vaccine or treatment, the mortality for infections with highly virulent strains approaches 100%, while low virulent strains causing less mortality spreads fast recently. Nevertheless, the mechanisms of ASFV pathogenicity, especially the differences between highly and low virulent strains remain poorly understood. Here, we used RNA-seq to analyze the viral and host transcriptome changes in PAMs infected with a virulent strain (SY18) or an attenuated strain (HuB20) at different stages. We found that the presence of ASFV significantly affected the cellular transcriptome profile. In addition, we did temporal and described the dynamic expression programs induced in the host cells by ASFV infection of different virulence strains. In particular, we identified differential gene expression patterns in host innate immune responses and expressed cytokines and chemokines between ASFV strains of different virulence. Our study provides new insights into ASFV pathogenicity research and novel drug or vaccine targets.
Conservation of energetic pathways for electroautotrophy in the uncultivated candidate order Tenderiales
Authors: Eddie Brian J. , Bird Lina J. , Pelikan Claus , Mussmann Marc , Martinez-Perez Clara , Pinamang Princess , Malanoski Anthony P. , Glaven Sarah M. 
Published: May 2022

AbstractElectromicrobiology can be used to understand extracellular electron uptake in previously undescribed chemolithotrophs. Enrichment and characterization of the uncultivated electroautotroph “Candidatus Tenderia electrophaga” using electromicrobiology led to the designation of the order Tenderiales. Representative Tenderiales metagenome assembled genomes (MAGs) have been identified in a number of environmental surveys, yet a comprehensive characterization of conserved genes for extracellular electron uptake has thus far not been conducted. Using comparative genomics we identified conserved orthologous genes within the Tenderiales and nearest neighbor orders important for extracellular electron uptake based on a previously proposed pathway from “Ca. Tenderia electrophaga”. The Tenderiales contained a conserved cluster we designated uetABCDEFGHIJ, which encodes proteins containing features that would enable transport of extracellular electrons to cytoplasmic membrane bound energy transducing complexes such as two conserved cytochrome cbb3 oxidases. For example, UetJ is predicted to be an extracellular undecaheme c-type cytochrome that forms a heme wire. We also identified clusters of genes predicted to facilitate assembly and maturation of electron transport proteins, as well as cellular attachment to surfaces. Autotrophy among the Tenderiales is supported by the presence of carbon fixation and stress response pathways that could allow cellular growth by extracellular electron uptake. Key differences between the Tenderiales and other known neutrophilic iron oxidizers were revealed, including very few Cyc2 genes in the Tenderiales. Our results reveal a possible conserved pathway for extracellular electron uptake and suggests the Tenderiales have an distribution unlimited ecological role coupling metal or mineral redox chemistry and the carbon cycle in marine and brackish sediments.ImportanceElectromicrobiology enables enrichment and identification of chemolithotrophic bacteria capable of extracellular electron uptake to drive energy metabolism and CO2 fixation. The recently described order Tenderiales contains the uncultivated electroautotroph “Candidatus Tenderia electrophaga”. The “Ca. Tenderia electrophaga” genome contains genes proposed to make up a previously undescribed extracellular electron uptake pathway. Here we use comparative genomics to show that this pathway is well conserved among Tenderiales spp. recovered by metagenome assembled genomes. This conservation extends to near neighbors of the Tenderiales, but not to other well-studied chemolithotrophs including iron and sulfur oxidizers. Our findings suggest that extracellular electron uptake may be pervasive among the Tenderiales and the geographic location from which metagenome assembled genomes were recovered offers clues to their natural ecological niche.
MAGNETO: an automated workflow for genome-resolved metagenomics
Authors: Churcheward Benjamin , Millet Maxime , Bihouée Audrey , Fertin Guillaume , Chaffron Samuel 
Published: May 2022

ABSTRACTMetagenome-Assembled Genomes (MAGs) represent individual genomes recovered from metagenomic data. MAGs are extremely useful to analyse uncultured microbial genomic diversity, as well as to characterize associated functional and metabolic potential in natural environments. Recent computational developments have considerably improved MAGs reconstruction but also emphasized several limitations, such as the non-binning of sequence regions with repetitions or distinct nucleotidic composition. Different assembly and binning strategies are often used, however, it still remains unclear which assembly strategy in combination with which binning approach, offers the best performance for MAGs recovery. Several workflows have been proposed in order to reconstruct MAGs, but users are usually limited to single-metagenome assembly or need to manually define sets of metagenomes to co-assemble prior to genome binning. Here, we present MAGNETO, an automated workflow dedicated to MAGs reconstruction, which includes a fully-automated co-assembly step informed by optimal clustering of metagenomic distances, and implements complementary genome binning strategies, for improving MAGs recovery. MAGNETO is implemented as a Snakemake workflow and is available at: https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto.IMPORTANCEGenome-resolved metagenomics has led to the discovery of previously untapped biodiversity within the microbial world. As the development of computational methods for the recovery of genomes from metagenomes continues, existing strategies need to be evaluated and compared to eventually lead to standardized computational workflows. In this study, we compared commonly used assembly and binning strategies and assessed their performance using both simulated and real metagenomic datasets. We propose a novel approach to automate co-assembly, avoiding the requirement for a priori knowledge to combine metagenomic information. The comparison against a previous co-assembly approach demonstrates a strong impact of this step on genome binning results, but also the benefits of informing co-assembly for improving the quality of recovered genomes. MAGNETO integrates complementary assembly-binning strategies to optimize genome reconstruction and provides a complete reads-to-genomes workflow for the growing microbiome research community.
Inferring selection effects in SARS-CoV-2 with Bayesian Viral Allele Selection
Authors: Jankowiak Martin , Obermeyer Fritz H. , Lemieux Jacob E. 
Published: May 2022

AbstractThe global effort to sequence millions of SARS-CoV-2 genomes has provided an unprecedented view of viral evolution. Characterizing how selection acts on SARS-CoV-2 is critical to developing effective, long-lasting vaccines and other treatments, but the scale and complexity of genomic surveillance data make rigorous analysis challenging. To meet this challenge, we develop Bayesian Viral Allele Selection (BVAS), a principled and scalable probabilistic method for inferring the genetic determinants of differential viral fitness and the relative growth rates of viral lineages, including newly emergent lineages. After demonstrating the accuracy and efficacy of our method through simulation, we apply BVAS to 6.9 million SARS-CoV-2 genomes. We identify numerous mutations that increase fitness, including previously identified mutations in the SARS-CoV-2 Spike and Nucleocapsid proteins, as well as mutations in non-structural proteins whose contribution to fitness is less well characterized. In addition, we extend our baseline model to identify mutations whose fitness exhibits strong dependence on vaccination status as well as pairwise interaction effects, i.e. epistasis. Strikingly, both these analyses point to the pivotal role played by the N501 residue in the Spike protein. Our method, which couples Bayesian variable selection with a diffusion approximation in allele frequency space, lays a foundation for identifying fitness-associated mutations under the assumption that most alleles are neutral.