bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tailored Graphical Lasso for Data Integration in Gene Network Reconstruction
Authors: Lingjærde Camilla , Lien Tonje G , Borgan Ørnulf , Glad Ingrid K 
Published: December 2020

AbstractBackgroundIdentifying gene interactions is a topic of great importance in genomics, and approaches based on network models provide a powerful tool for studying these. Assuming a Gaussian graphical model, a gene association network may be estimated from multiomic data based on the non-zero entries of the inverse covariance matrix. Inferring such biological networks is challenging because of the high dimensionality of the problem, making traditional estimators unsuitable. The graphical lasso is constructed for the estimation of sparse inverse covariance matrices in Gaussian graphical models in such situations, usingL1-penalization on the matrix entries. An extension of the graphical lasso is the weighted graphical lasso, in which prior biological information from other (data) sources is integrated into the model through the weights. There are however issues with this approach, as it naïvely forces the prior information into the network estimation, even if it is misleading or does not agree with the data at hand. Further, if an associated network based on other data is used as the prior, weighted graphical lasso often fails to utilize the information effectively.ResultsWe propose a novel graphical lasso approach, thetailored graphical lasso, that aims to handle prior information of unknown accuracy more effectively. We provide an R package implementing the method,tailoredGlasso. Applying the method to both simulated and real multiomic data sets, we find that it outperforms the unweighted and weighted graphical lasso in terms of all performance measures we consider. In fact, the graphical lasso and weighted graphical lasso can be considered special cases of the tailored graphical lasso, and a parameter determined by the data measures the usefulness of the prior information. With our method, mRNA data are demonstrated to provide highly useful prior information for protein-protein interaction networks.ConclusionsThe method we introduce utilizes useful prior information more effectively without involving any risk of loss of accuracy should the prior information be misleading.
Analysis of a Mad2 homolog inTrypanosoma bruceiprovides possible hints on the origin of the spindle checkpoint
Authors: Akiyoshi Bungo 
Published: December 2020

AbstractThe spindle checkpoint is a surveillance mechanism that ensures accurate nuclear DNA segregation in eukaryotes. It does so by delaying the onset of anaphase until all kinetochores have established proper attachments to spindle microtubules. The evolutionary origin of the spindle checkpoint remains unclear. The flagellated kinetoplastid parasiteTrypanosoma bruceihas a nucleus that contains the nuclear genome and a kinetoplast that contains the mitochondrial genome. The kinetoplast is physically linked to the basal body of the flagellum and its segregation is driven by the movement of basal bodies. While there is no strong evidence thatT. bruceipossesses a functional spindle checkpoint, it has been suggested that initiation of cytokinesis may be linked to the completion of kinetoplast segregation or basal body separation in this organism. Interestingly, the only identifiable spindle checkpoint component TbMad2 localizes at the basal body area. Here, I report identification of proteins that co-purified with TbMad2. One protein, which I propose to call TbMBP65, localizes at the basal body area and has a putative Mad2-interacting motif. Interestingly, 26S proteasome subunits also co-purified with TbMad2, raising a possibility that TbMad2 might regulate proteasome activity to regulate or monitor the segregation of basal bodies. I speculate that such a function might represent a prototype of the spindle checkpoint. I also show that TbAUK3, one of the three Aurora kinase homologs inT. brucei, localizes at the basal body area from late G1 until the time of kinetoplast separation. Immunoprecipitation of TbAUK3 identified an uncharacterized protein (termed TbABP79) that has a similar localization pattern as TbAUK3. These findings provide a starting point to reveal the function of TbMad2 and TbAUK3 as well as the origin of the spindle checkpoint.
A group refactorization procedure for sleep electroencephalography
Authors: Law Robert G. , Purcell Shaun M. 
Published: December 2020

Abstract[WORKING DRAFT] In order to relate health and disease to brain state, patterns of activity in the brain must be phenotyped. In this regard, polysomnography datasets present both an opportunity and a challenge, as although sleep data are extensive and multidimensional, features of the sleep EEG are known to correlate with clinical outcomes. Machine learning methods for rank reduction are attractive means for bringing the phenotyping problem to a manageable size. The whole-night power spectrogram is nonnegative, and so applying nonnegative matrix factorization (NMF) to separate spectrograms into time and frequency factors is a natural choice for dimension reduction. However, NMF converges differently depending on initial conditions, and there is no guarantee that factors obtained from one individual will be comparable with those from another, hampering inter-individual analysis.We therefore reseed time-frequency NMF with group frequency factors obtained from the entire sample. This “refactorization” extends classical frequency bands to frequency factors. The group reseeding procedure coerces factors into equivalence classes, making them comparable across individuals. By comparing frequency factor properties, we illustrate age-related effects on the sleep EEG. The procedure can presumably be adapted to higher resolutions, e.g. to local field potential datasets, for characterizing individual time-frequency events.
Genomic islands of heterozygosity maintained across caribou populations despite inbreeding
Authors: Solmundson Kirsten , Bowman Jeff , Wilson Paul J. , Taylor Rebecca S. , Horn Rebekah L. , Keobouasone Sonesinh , Manseau Micheline 
Published: December 2020

AbstractSmall, isolated populations are prone to inbreeding, increasing the proportion of homozygous sites across the genome that can be quantified as runs of homozygosity (ROH). Caribou (Rangifer tarandus) are declining across their range in Canada; thus, understanding the effects of inbreeding on genetic potential is pertinent for conserving small, isolated populations. We quantified ROH in high-coverage whole genomes of boreal caribou from small, isolated populations in southern Ontario, Canada, in comparison to caribou from the continuous range of Ontario, other caribou ecotypes in Canada, and western Greenland. Sampled populations presented divergent evolutionary histories, differing population sizes, and extents of isolation. We conducted BLAST searches across regions of elevated heterozygosity to identify genes that have maintained variation despite inbreeding. We found caribou from recently isolated populations in Ontario had a large proportion of their genome in long ROH. We observed even larger proportions but shorter ROH in western Greenland, indicating that inbreeding has occurred over a longer period in comparison to other populations. We observed the least inbreeding in barren-ground and eastern migratory caribou, which occur in larger population sizes than boreal caribou. Despite vastly different inbreeding extents, we found regions of high heterozygosity maintained across all populations. Within these islands of heterozygosity, we identified genes associated with immunity, signaling regulation, nucleotide binding, toxin elimination, and feeding behaviour regulation. In this study, we confirm inbreeding in isolated populations of a species at risk, but also uncover high variation in some genes maintained across divergent populations despite inbreeding, suggesting strong balancing selection.
ESR1mutant breast cancers show elevated basal cytokeratins and immune activation
Authors: Li Zheqi , Wu Yang , Bahreini Amir , Priedigkeit Nolan M. , Ding Kai , Sartorius Carol A. , Miller Lori , Rosenzweig Margaret , Wagle Nikhil , Richer Jennifer K. , Muller William J. , Buluwela Laki , Ali Simak , Fang Yusi , Zhu Li , Tseng George C. , Gertz Jason , Atkinson Jennifer M. , Lee Adrian V. , Oesterreich Steffi 
Published: December 2020

AbstractEstrogen receptor alpha (ER/ESR1) is mutated in 30-40% of endocrine resistant ER-positive (ER+) breast cancer.ESR1mutations cause ligand-independent growth and increased metastasisin vivoandin vitro. Despite the distinct clinical features and changes in therapeutic response associated withESR1mutations, there are no data about their potential role in intrinsic subtype switching. Applying four luminal and basal gene set pairs,ESR1mutant cell models and clinical samples showed a significant enrichment of basal subtype markers. Among them, the six basal cytokeratins (BCKs) were the most enriched genes. Induction of BCKs was independent of ER binding and instead associated with chromatin reprogramming centered around a progesterone receptor-orchestrated topological associated domain at theKRT14/16/17genomic region. Unexpectedly, highBCKexpression in ER+ primary breast cancer is associated with good prognosis, and these tumors show enriched activation of a number of immune pathways, a distinctive feature shared withESR1mutant tumors. S100A8 and S100A9 were among the most highly induced immune mediators shared between high-BCKs ER+ andESR1mutant tumors, and single-cell RNA-seq analysis inferred their involvement in paracrine crosstalk between epithelial and stromal cells. Collectively, these observations demonstrate thatESR1mutant tumors gain basal features with induction of basal cytokeratins via epigenetic mechanisms in rare subpopulation of cells. This is associated with increased immune activation, encouraging additional studies of immune therapeutic vulnerabilities inESR1mutant tumors.
Engineering, production and characterization of Spike and Nucleocapsid structural proteins of SARS–CoV-2 inNicotiana benthamianaas vaccine candidates against COVID-19
Authors: Mamedov Tarlan , Yuksel Damla , Ilgın Merve , Gürbüzaslan İrem , Gulec Burcu , Mammadova Gulshan , Say Deniz , Hasanova Gulnara 
Published: December 2020

AbstractThe COVID-19 pandemic, which is caused by SARS-CoV-2 has rapidly spread to more than 216 countries and has put global public health at high risk. The world urgently needs a cost-effective and safe SARS-CoV-2 coronavirus vaccine, antiviral and therapeutic drugs to control the COVID-19 pandemic. In this study, we engineered the Nucleocapsid (N) and Spike protein (S) variants (Receptor binding domain, RBD and S1 domain) of SARS-CoV-2 genes and produced inNicotiana benthamianaplant. The purification yields were at least 20 mg of pure protein/kg of plant biomass for each target protein. The S protein variants of SARS-CoV-2 showed specific binding to angiotensin converting enzyme 2 (ACE2), the SARS-CoV-2 receptor. The purified plant produced N and S variants were recognized by N and S protein specific monoclonal and polyclonal antibodies demonstrating specific reactivity of mAb to plant produced N and S protein variants. In addition, IgG responses of plant produced N and S antigens elicited significantly high titers of antibody in mice. This is the first report demonstrating production of functional active S1 domain and Nucleocapsid protein of SARC-CoV-2 in plants. In addition, in this study, for the first time, we report the co-expression of RBD with N protein to produce a cocktail antigen of SARS-CoV-2, which elicited high-titer antibodies compared to RBD or N proteins. Thus, obtained data support that plant produced N and S antigens, developed in this study, are promising vaccine candidates against COVID-19.
Gait-level analysis of mouse open field behavior using deep learning-based pose estimation
Authors: Sheppard Keith , Gardin Justin , Sabnis Gautam S , Peer Asaf , Darrell Megan , Deats Sean , Geuther Brian , Lutz Cathleen M. , Kumar Vivek 
Published: December 2020

1AbstractGait and whole body posture are sensitive measures of the proper functioning of numerous neural circuits, and are often perturbed in many neurological, neuromuscular, and neuropsychiatric illnesses. Rodents provide a tractable model for elucidating disease mechanisms and interventions, however, studying gait and whole body posture in rodent models requires specialized methods and remains challenging. Here, we develop a simple assay that allows adoption of the commonly used open field apparatus for gait and whole body posture analysis. We leverage modern neural networks to abstract a mouse into keypoints and extract gait and whole body coordination metrics of the animal. Gait-level analysis allows us to detect every step of the animal’s movement and provides high resolution information about the animal’s behavior. We quantitate gait and whole body posture with high precision and accuracy across 62 highly visually diverse strains of mice. We apply our approach to characterize four genetic mutants with known gait deficits. In extended analysis, we demonstrate that multiple autism spectrum disorder (ASD) models show gait and posture deficits, implying this is a general feature of ASD. We conduct a large strain survey of 1898 mice, and find that gait and whole body posture measures are highly heritable in the laboratory mouse, and fall into three classes. Furthermore, the reference mouse strain, C57BL/6J, has a distinctly different gait and posture compared to other standard laboratory and wild-derived strains. We conduct a genome wide association study (GWAS) to define the genetic architecture of mouse movement in the open field. In sum, we describe a simple, sensitive, accurate, scalable, and ethologically relevant method of mouse gait and whole body posture analysis for behavioral neurogenetics. These results provide one of the largest laboratory mouse gait-level data resources for the research community and show the utility of automated machine learning approaches for deriving biological insights.
Dopamine receptors in obesity: a meta-analysis
Authors: Pak Kyoungjune , Lee Myung Jun , Kim Keunyoung , Kim In Joo 
Published: December 2020

ABSTRACTThe brain plays a major role in controlling the desire to eat. This meta-analysis aimed to assess the association between dopamine receptor (DR) availability, measured using positron emission tomography, and obesity. We performed a systematic search of MEDLINE (from inception to June 2019) and EMBASE (from inception to June 2019) for articles published in English using the keywords “dopamine receptor,” “obesity,” and “neuroimaging.” Fitting a locally weighted estimated scatterplot smoothing curve for binding potential (BPND) of the ventral striatum measured by11C-raclopride was performed. Five studies involving 119 subjects were included in this analysis.11C-raclopride was used in four studies, regardless of the ROIs included. The curve of BPNDof the ventral striatum went up and down at BMI of 20–30 kg/m2and became flat after a BMI of >40 kg/m2. Linear regression analysis was performed with BPNDof the striatum from two studies (n = 20). The BPNDof the striatum was negatively associated with BMI. In conclusion, dopamine plays a major role in the reward system with regard to obesity. Compared to normal-weight subjects, overweight and obese subjects had decreased DR availability. However, this tendency should be interpreted carefully with regard to radiopharmaceuticals and ROIs.
Human blood contains circulating cell-free mitochondria, but are they really functional?
Authors: Stier Antoine 
Published: December 2020

AbstractDache et al. (2020,FASEB J.15, e2002338–15) recently reported the presence ofrespiratory-competentcell-free mitochondria in human blood (up to 3.7 × 106per mL of blood), providing exciting perspectives on the potential role of these extra-cellular mitochondria. While their evidence for the presence of cell-free mitochondria in human blood is compelling, their conclusion that these cell-free mitochondria are respiratory-competent or functional has to be re-evaluated. To this end, we evaluated the functionality of cell-free mitochondria in human blood using high-resolution respirometry and mitochondria extracted from platelets of the same blood samples as positive controls. While cell-free mitochondria were present in human plasma (i.e. significant MitoTracker Green Fluorescence and complex IV activity), there was no evidence suggesting that their mitochondrial electron transport system (ETS) was functional (i.e. respiration rate not significantly different from 0; no significant responses to ADP, uncoupler or mitochondrial inhibitors oligomycin and antimycin A). Yet,in vitrocomplex IV activity was detectable and even slightly higher than levels found in mitochondria extracted from platelets, suggesting that cell-free mitochondria in human blood are likely to only retain a non-functional part of the electron transport system. Despite being unlikely to be fully functional in the narrow-sense (i.e. capable of oxidative phosphorylation), circulating cell-free mitochondria may have significant physiological roles that remain to be elucidated.
Chromatin Interaction Neural Network (ChINN): A machine learning-based method for predicting chromatin interactions from DNA sequences
Authors: Cao Fan , Zhang Yu , Cai Yichao , Animesh Sambhavi , Zhang Ying , Akincilar Semih , Loh Yan Ping , Chng Wee Joo , Tergaonkar Vinay , Kwoh Chee Keong , Fullwood Melissa J. 
Published: December 2020

AbstractChromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limited. Various computational methods have been developed to predict chromatin interactions. Most of these methods rely on large collections of ChIP-Seq/RNA-Seq/DNase-Seq datasets and predict only enhancer-promoter interactions. Some of the ‘state-of-the-art’ methods have poor experimental designs, leading to over-exaggerated performances and misleading conclusions. Here we developed a computational method, Chromatin Interaction Neural Network (ChINN), to predict chromatin interactions between open chromatin regions by using only DNA sequences of the interacting open chromatin regions. ChINN is able to predict CTCF-, RNA polymerase II- and HiC-associated chromatin interactions between open chromatin regions. ChINN also shows good across-sample performances and captures various sequence features that are predictive of chromatin interactions. To apply our results to clinical patient data, we applied CHINN to predict chromatin interactions in 6 chronic lymphocytic leukemia (CLL) patient samples and a cohort of open chromatin data from 84 CLL samples that was previously published. Our results demonstrated extensive heterogeneity in chromatin interactions in patient samples, and one of the sources of this heterogeneity were the different subtypes of CLL.
Asciminib mitigates DNA damage stress signalling induced by cyclophosphamide in the ovary
Authors: Mattiello Luca , Pucci Giulia , Marchetti Francesco , Diederich Marc , Gonfloni Stefania 
Published: December 2020

AbstractCancer treatments often have adverse effects on the quality of life for young women. One of the most relevant negative impacts is the loss of fertility. Cyclophosphamide is one of the most detrimental chemotherapeutic drugs for the ovary. Cyclophosphamide may induce the destruction of dormant follicles while promoting follicle activation and growth. Herein, we demonstrate thein vivoprotective effect of the allosteric Bcr-Abl tyrosine kinase inhibitor Asciminib on signalling pathways activated by cyclophosphamide in mouse ovaries. Besides, we provide evidence that Asciminib did not interfere with the cytotoxic effect of cyclophosphamide in MCF7 breast cancer cells. Our data indicate that concomitant administration of Asciminib mitigates the cyclophosphamide-induced ovarian reserve loss without preventing the anticancer potential of cyclophosphamide. Altogether these observations are relevant for the development of effective ferto-protective adjuvants to preserve the ovarian reserve from the damaging effect of cancer therapies.
Process Development and Scale-up Optimization of the SARS-CoV-2 Receptor Binding Domain-Based Vaccine Candidate, RBD219-N1C1
Authors: Lee Jungsoon , Liu Zhuyun , Chen Wen-Hsiang , Wei Junfei , Kundu Rakhi , Adhikari Rakesh , Rivera Joanne Altieri , Gillespie Portia M. , Strych Ulrich , Zhan Bin , Hotez Peter J. , Bottazzi Maria Elena 
Published: December 2020

AbstractA SARS-CoV-2 RBD219-N1C1 (RBD219-N1C1) recombinant protein antigen formulated on Alhydrogel®has recently been shown to elicit a robust neutralizing antibody response against SARS-CoV-2 pseudovirus in mice. The antigen has been produced under current good manufacturing practices (cGMP) and is now in clinical testing. Here, we report on process development and scale-up optimization for upstream fermentation and downstream purification of the antigen. This includes production at the 1 and 5 L scale in the yeast,Pichia pastoris,and the comparison of three different chromatographic purification methods. This culminated in the selection of a process to produce RBD219-N1C1 with a yield of >400 mg per liter of fermentation with >92% purity and >39% target product recovery after purification. In addition, we show the results from analytical studies, including SEC-HPLC, DLS, and an ACE2 receptor binding assay that were performed to characterize the purified proteins to select the best purification process. Finally, we propose an optimized upstream fermentation and downstream purification process that generates quality RBD219-N1C1 protein antigen and is fully scalable at a low cost.
Spatio-Temporal Coordination of Transcription Preinitiation Complex Assembly in Live Cells
Authors: Nguyen Vu Q. , Ranjan Anand , Liu Sheng , Tang Xiaona , Ling Yick Hin , Wisniewski Jan , Mizuguchi Gaku , Li Kai Yu , Jou Vivian , Zheng Qinsi , Lavis Luke D. , Lionnet Timothée , Wu Carl 
Published: December 2020

SUMMARYTranscription initiation by RNA polymerase II (Pol II) requirespreinitiationcomplex (PIC) assembly at gene promoters. In the dynamic nucleus where thousands of promoters are broadly distributed in chromatin, it is unclear how ten individual components converge on any target to establish the PIC. Here, we use live-cell, single-molecule tracking inS. cerevisiaeto document subdiffusive, constrained exploration of the nucleoplasm by PIC components and Mediator’s key functions in guiding this process. On chromatin, TBP, Mediator, and Pol II instruct assembly of a short-lived PIC, which occurs infrequently but efficiently at an average promoter where initiation-coupled disassembly may occur within a few seconds. Moreover, PIC exclusion by nucleosome encroachment underscores regulated promoter accessibility by chromatin remodeling. Thus, coordinated nuclear exploration and recruitment to accessible targets underlies dynamic PIC establishment in yeast. Collectively, our study provides a global spatio-temporal model for transcription initiation in live cells.
scMomentum: Inference of Cell-Type-Specific Regulatory Networks and Energy Landscapes
Authors: Soto Larisa M. , Bernal-Tamayo Juan P. , Lehmann Robert , Balsamy Subash , Martinez-de-Morentin Xabier , Vilas-Zornoza Amaia , San-Martin Patxi , Prosper Felipe , Gomez-Cabrero David , Kiani Narsis A. , Tegner Jesper 
Published: December 2020

AbstractRecent progress in single-cell genomics has generated multiple tools for cell clustering, annotation, and trajectory inference; yet, inferring their associated regulatory mechanisms is unresolved. Here we present scMomentum, a model-based data-driven formulation to predict gene regulatory networks and energy landscapes from single-cell transcriptomic data without requiring temporal or perturbation experiments. scMomentum provides significant advantages over existing methods with respect to computational efficiency, scalability, network structure, and biological application.AvailabilityscMomentum is available as a Python package athttps://github.com/larisa-msoto/scMomentum.git