bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lost in translation: the pitfalls of Ensembl Gene annotations between human genome assemblies and their impact on diagnostics
Authors: Abdallah Mohammed O.E , Koko Mahmoud , Ramesar Raj 
Published: November 2020

AbstractBackgroundThe GRCh37 human genome assembly is still widely used in genomics despite the fact an updated human genome assembly (GRCh38) has been available for many years. A particular issue with relevant ramifications for clinical genetics currently is the case of the GRCh37 Ensembl gene annotations which has been archived, and thus not updated, since 2013. These Ensembl GRCh37 gene annotations are just as ubiquitous as the former assembly and are the default gene models used and preferred by the majority of genomic projects internationally. In this study, we highlight the issue of genes with discrepant annotations, that have been recognized as protein coding in the new but not the old assembly. These genes are ignored by all genomic resources that still rely on the archived and outdated gene annotations. Moreover, the majority if not all of these discrepant genes (DGs) are automatically discarded and ignored by all variant prioritization tools that rely on the GRCh37 Ensembl gene annotations.MethodsWe performed bioinformatics analysis identifying Ensembl genes with discrepant annotations between the two most recent human genome assemblies, hg37, hg38, respectively. Clinical and phenotype gene curations have been obtained and compared for this gene set. Furthermore, matching RefSeq transcripts have also been collated and analyzed.ResultsWe found hundreds of genes (N=267) that were reclassified as “protein-coding” in the new hg38 assembly. Notably, 169 of these genes also had a discrepant HGNC gene symbol between the two assemblies. Most genes had RefSeq matches (N=199/267) including all the genes with defined phenotypes in Ensembl genes GRCh38 assembly (N=10). However, many protein-coding genes remain missing from the current known RefSeq gene models (N=68)ConclusionWe found many clinically relevant genes in this group of neglected genes and we anticipate that many more will be found relevant in the future. For these genes, the inaccurate label of “non-protein-coding” hinders the possibility of identifying any causal sequence variants that overlap them. In addition, Important additional annotations such as evolutionary constraint metrics are also not calculated for these genes for the same reason, further relegating them into oblivion.
Beating your Neighbor to the Berry Patch
Authors: Rogers Alan R. 
Published: November 2020

AbstractForagers often compete for resources that ripen (or otherwise improve) gradually. What strategy is optimal in this situation? It turns out that there is no optimal strategy. There is no evolutionarily stable strategy (ESS), and the only Nash equilibrium (NE) is unstable: strategies similar to the NE can always invade. But in spite of this instability, the NE is predictive. If harvesting attempts are costly or there are many competitors, the process tends to remain near the unstable NE. In this case, the resource often goes unharvested. Harvesting attempts—when they happen at all—usually occur when the resource is barely ripe enough to offset costs. The more foragers there are, the lower the chance that the resource will be harvested and the greater its mean value when harvested. This counterintuitive behavior is exhibited not only by theoretical models and computer simulations, but also by human subjects in an experimental game.
StrongestPath: a Cytoscape application for protein-protein interaction analysis
Authors: Mousavian Zaynab , Khodabandeh Mehran , Sharifi-Zarchi Ali , Nadafian Alireza , Mahmoudi Alireza 
Published: November 2020

ABSTRACTBackgroundStrongestPath is a Cytoscape 3 application that enables to look for one or more cascades of interactions connecting two single or groups of proteins in a collection of protein-protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, it is able to process them and identify the cascade of interactions having the highest total confidence score. Given a set of proteins, StrongestPath can extract and show the network of interactions among them from the given databases, and expand the network by adding new proteins having the most interactions with highest total confidence to the current proteins. The application can also identify any activation or inhibition regulatory paths between two distinct sets of transcription factors and target genes. This application can be either used with a set of built-in human and mouse PPI or signaling databases, or any user-provided database for some organism.ResultsOur results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in the middle of the pathway by finding the strongest path(s) in the PPI or signaling network.ConclusionEasy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform and providing a user-friendly graphical interface make the StrongestPath easy to use.
Accumbens D2-MSN hyperactivity drives behavioral supersensitivity
Authors: Kruyer Anna , Parilla-Carerro Jeffrey , Powell Courtney , Brandt Lasse , Gutwinski Stefan , Angelis Ariana , Chalhoub Reda , Amato Davide 
Published: November 2020

ABSTRACTAntipsychotic-induced behavioral supersensitivity is a problematic consequence of long-term treatment with antipsychotic drugs and is characterized by emergence of refractory symptoms and dyskinesias. The underlying mechanisms are unknown, and no rational approaches exist to prevent or reverse antipsychotic-induced supersensitivity. Here we describe major adaptations impacting populations of striatal medium spiny neurons (MSNs) during the development of behavioral supersensitivity and reveal a prominent role played by D2 receptor expressing MSNs. We show that enhanced D2-MSN activity underlies several symptoms spanning from psychostimulant sensitization, to antipsychotic treatment resistance and drug addiction. Our data warn against severe adverse events following antipsychotic treatment discontinuation and offer insight that may inform therapeutic approaches to overcome antipsychotic-induced supersensitivity.
Developmental Single-cell transcriptomics in theLytechinus variegatusSea Urchin Embryo
Authors: Massri Abdull J. , Greenstreet Laura , Afanassiev Anton , Escobar Alejandro Berrio , Wray Gregory M. , Schiebinger Geoffrey , McClay David R. 
Published: November 2020

AbstractHere we employed scRNA-seq coupled with computational approaches to examine molecular changes in cells during specification and differentiation. We examined the first 24 hours of development of the sea urchinLytechinus variegatus(Lv) with 18 time points during which the embryo develops to the larval stage. Using Waddington-OT, the time points were computationally “stitched” together to calculate developmental trajectories. Skeletogenic cells displayed the expected immediate early divergence while other lineages diverged asynchronously, with many cells retaining an intermediate specification status until late in gastrulation. TheLv-scRNA-seq dataset was compared to the developmental Gene Regulatory Network (dGRN) model of specification inStrongylocentrotus purpuratus(Sp). 79 of 80 genes (98%) in that dGRN are present in theLv-scRNA-seq dataset, and expressed in the correct lineages in which the dGRN circuits operate. Surprisingly, however, many heterochronies in timing of first expression of dGRN genes have evolved between the two species. Replotting the two dGRNs with precise attention to time of expression revealed a number of feedback inputs that likely buffer the dGRNs, allowing them to maintain function in the face of accumulating heterochronies.Summary statementThe early development of the sea urchin embryo was followed using scRNA-seq plus computational methods to trace lineage diversifications. These were matched to gene regulatory network changes over time.
The Tec kinase ITK differentially optimizes NFAT, NF-κB, and MAPK signaling during early T cell activation to regulate graded gene induction
Authors: Gallagher Michael P. , Conley James M. , Vangala Pranitha , Reboldi Andrea , Garber Manuel , Berg Leslie J. 
Published: November 2020

ABSTRACTThe strength of peptide:MHC interactions with the T cell receptor (TCR) is correlated with the time to first cell division, the relative scale of the effector cell response, and the graded expression of activation-associated proteins like IRF4. To regulate T cell activation programming, the TCR and the TCR proximal kinase ITK simultaneously trigger many biochemically separate TCR signaling cascades. T cells lacking ITK exhibit selective impairments in effector T cell responses after activation, but under the strongest signaling conditions ITK activity is dispensable. To gain insight into whether TCR signal strength and ITK activity tune observed graded gene expression through unequal activation of disparate signaling pathways, we examined Erk1/2 activation and NFAT, NF-κB translocation in naive OT-I CD8+cell nuclei. We observed consistent digital activation of NFAT1 and Erk-MAPK, but NF-κB displayed dynamic, graded activation in response to variation in TCR signal strength and was tunable by treatment with an ITK inhibitor. Inhibitor-treated cells showed dampened induction of AP-1 factorsFosandFosb, NF-κB response gene transcripts, and survival factorIl2transcripts. ATAC-seq analysis also revealed genomic regions most sensitive to ITK inhibition were enriched for NF-κB and AP-1 motifs. Specific inhibition of NF-κB during peptide stimulation tuned expression of early gene products like c-Fos. Together, these data indicate a key role for ITK in orchestrating optimal activation of separate TCR downstream pathways, specifically aiding NF-κB activation. More broadly, we revealed a mechanism by which variation in TCR signal strength can produce patterns of graded gene expression in activated T cells.
Quantification ofBrucella abortuspopulation structure in a natural host
Authors: Fiebig Aretha , Vrentas Catherine E. , Le Thien , Huebner Marianne , Boggiatto Paola M. , Olsen Steven C. , Crosson Sean 
Published: November 2020

AbstractCattle are natural hosts of the intracellular pathogen,Brucella abortus, which inflicts a significant burden on the health and reproduction of these important livestock. The primary routes of infection in field settings have been described, but it is not known how the bovine host shapes the structure ofB. abortuspopulations during infection. We utilized a library of approximately 106uniquely barcodedB. abortusstrains to temporally and spatially quantify population structure at the strain level during colonization of cattle through a natural route of infection. Introducing 108bacteria from this barcoded library to the conjunctival mucosa resulted in expected levels of local lymph node colonization at a one-week timepoint. We leveraged variance in strain abundance in the library to demonstrate that only 1 in 10,000 brucellae introduced at the site of infection reached the parotid lymph nodes. Thus, cattle restrict the overwhelming majority ofB. abortusintroduced via the ocular conjunctiva at this dose. Individual strains were spatially restricted within the host tissue, and the totalB. abortuscensus was dominated by a small number of distinct strains in each lymph node. These results define a bottleneck thatB. abortusmust traverse to colonize local lymph nodes from the conjunctival mucosa. The data further support a model in which a small number of spatially isolated granulomas founded by unique strains are present one-week post infection. These experiments demonstrate the power of barcoded transposon tools to quantify infection bottlenecks and to define pathogen population structure in host tissues.Significance statementUnderstanding microbial population dynamics during infection has important implications for disease management, transmission and pathogen evolution. A quantitative analysis of microbial population structure requires the ability to track individual strains. We used a pool of individually barcoded strains to measure changes inBrucella abortuspopulation structure during infection of bovine hosts via the ocular conjunctiva, a natural route of entry. Cattle exert a severe bottleneck on the bacterial population entering through the conjunctival mucosa such that individual cells have a 0.0001 probability of colonizing a local draining lymph node. The populations in lymph nodes, even on different sides of the same animal, are distinct and dominated by a small number of highly abundant, spatially distinct clones.
SeqPIP-2020: Sequence based Protein Interaction Prediction Contest
Authors: Halder Anup Kumar , Mollah Ayatullah Faruk , Chatterjee Piyali , Kole Dipak Kumar , Basu Subhadip , Plewczyński Dariusz 
Published: November 2020

AbstractComputational protein-protein interaction (PPI) prediction techniques can contribute greatly in reducing time, cost and false-positive interactions compared to experimental approaches. Sequence is one of the key and primary information of proteins that plays a crucial role in PPI prediction. Several machine learning approaches have been applied to exploit the characteristics of PPI datasets. However, these datasets greatly influence the performance of predicting models. So, care should be taken on both dataset curation as well as design of predictive models. Here, we summarize the results of the SeqPIP competition whose objective was to develop comprehensive PPI predictive models from sequence information with high-quality bias-free interaction datasets. A training set of 2000 positive and 2000 negative interactions with sequences was given to each contestant. The methods were evaluated with three independent high-quality interaction test datasets.
MUNIn (Multiple sample UNifying long-range chromatin Interaction detector): a statistical framework for identifying long-range chromatin interactions from multiple samples
Authors: Liu Weifang , Abnousi Armen , Zhang Qian , Kubo Naoki , Martin Beem Joshua S. , Li Yun , Hu Ming , Yang Yuchen 
Published: November 2020

AbstractChromatin spatial organization (interactome) plays a critical role in genome function. Deep understanding of chromatin interactome can shed insights into transcriptional regulation mechanisms and human disease pathology. One essential task in the analysis of chromatin interactomic data is to identify long-range chromatin interactions. Existing approaches, such as HiCCUPS, FitHiC/FitHiC2 and FastHiC, are all designed for analyzing individual cell types or samples. None of them accounts for unbalanced sequencing depths and heterogeneity among multiple cell types or samples in a unified statistical framework. To fill in the gap, we have developed a novel statistical framework MUNIn (Multiple sampleUNifying long-range chromatinInteraction detector) for identifying long-range chromatin interactions from multiple samples. MUNIn adopts a hierarchical hidden Markov random field (H-HMRF) model, in which the status (peak or background) of each interacting chromatin loci pair depends not only on the status of loci pairs in its neighborhood region, but also on the status of the same loci pair in other samples. To benchmark the performance of MUNIn, we performed comprehensive simulation studies and real data analysis, and showed that MUNIn can achieve much lower false positive rates for detecting sample-specific interactions (33.1 - 36.2%), and much enhanced statistical power for detecting shared peaks (up to 74.3%), compared to uni-sample analysis. Our data demonstrated that MUNIn is a useful tool for the integrative analysis of interactomic data from multiple samples.
An evolutionary analysis of the SARS-CoV-2 genomes from the countries in the same meridian
Authors: Mastriani Emilio , Rakov Alexey V. , Liu Shu-Lin 
Published: November 2020

AbstractIn the current study we analyzed the genomes of SARS-CoV-2 strains isolated from Italy, Sweden, Congo (countries in the same meridian) and Brazil, as outgroup country. Evolutionary analysis revealed codon 9628 under episodic selective pressure for all four countries, suggesting it as a key site for the virus evolution. Belonging to the P0DTD3 (Y14_SARS2) uncharacterized protein 14, further investigation has been conducted showing the codon mutation as responsible for the helical modification in the secondary structure. According to the predictions done, the codon is placed into the more ordered region of the gene (41-59) and close the area acting as transmembrane (54-67), suggesting its involvement into the attachment phase of the virus. The predicted structures of P0DTD3 mutated and not confirmed the importance of the codon to define the protein structure and the ontological analysis of the protein emphasized that the mutation enhances the binding probability.
Characterization and significance of extracellular polymeric substances, reactive oxygen species, and extracellular electron transfer in methanogenic biocathode
Authors: Zakaria Basem S. , Dhar Bipro Ranjan 
Published: November 2020

AbstractThe microbial electrolysis cell assisted anaerobic digestion (MEC-AD) holds great promises over conventional anaerobic digestion. This article reports an experimental investigation of extracellular polymeric substances (EPS), reactive oxygen species (ROS), and the expression of genes associated with extracellular electron transfer (EET) in methanogenic biocathodes. The MEC-AD systems were examined using two cathode materials: carbon fibers and stainless-steel mesh. A higher abundance of hydrogenotrophicMethanobacteriumsp. and homoacetogenicAcetobacteriumsp. appeared to play a major role in superior methanogenesis from stainless steel biocathode than carbon fibers. Moreover, the higher secretion of EPS accompanied by the lower ROS level in stainless steel biocathode indicated that higher EPS perhaps protected cells from harsh metabolic conditions (possibly unfavorable local pH) induced by faster catalysis of hydrogen evolution reaction. In contrast, EET-associated gene expression patterns were comparable in both biocathodes. Thus, these results indicated hydrogenotrophic methanogenesis is the key mechanism, while cathodic EET has a trivial role in distinguishing performances between two cathode electrodes. These results provide new insights into the efficient methanogenic biocathode development.
Deep Semi-Supervised Learning Improves Universal Peptide Identification of Shotgun Proteomics Data
Authors: Halloran John T. , Urban Gregor , Rocke David , Baldi Pierre 
Published: November 2020

AbstractSemi-supervised machine learning post-processors critically improve peptide identification of shot-gun proteomics data. Such post-processors accept the peptide-spectrum matches (PSMs) and feature vectors resulting from a database search, train a machine learning classifier, and recalibrate PSMs using the trained parameters, often yielding significantly more identified peptides acrossq-value thresholds. However, current state-of-the-art post-processors rely on shallow machine learning methods, such as support vector machines. In contrast, the powerful training capabilities of deep learning models have displayed superior performance to shallow models in an ever-growing number of other fields. In this work, we show that deep models significantly improve the recalibration of PSMs compared to the most accurate and widely-used post-processors, such as Percolator and PeptideProphet. Furthermore, we show that deep learning is able to adaptively analyze complex datasets and features for more accurate universal post-processing, leading to both improved Prosit analysis and markedly better recalibration of recently developed database-search functions.
The Preclinical Inhibitor GS441524 in Combination with GC376 Efficaciously Inhibited the Proliferation of SARS-CoV-2 in the Mouse Respiratory Tract
Authors: Shi Yuejun , Shuai Lei , Wen Zhiyuan , Wang Chong , Yan Yuanyuan , Jiao Zhe , Guo Fenglin , Fu Zhen F. , Chen Huanchun , Bu Zhigao , Peng Guiqing 
Published: November 2020

AbstractThe unprecedented coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a serious threat to global public health. Development of effective therapies against SARS-CoV-2 is urgently needed. Here, we evaluated the antiviral activity of a remdesivir parent nucleotide analog, GS441524, which targets the coronavirus RNA-dependent RNA polymerase enzyme, and a feline coronavirus prodrug, GC376, which targets its main protease, using a mouse-adapted SARS-CoV-2 infected mouse model. Our results showed that GS441524 effectively blocked the proliferation of SARS-CoV-2 in the mouse upper and lower respiratory tracts via combined intranasal (i.n.) and intramuscular (i.m.) treatment. However, the ability of high-dose GC376 (i.m. or i.n. and i.m.) was weaker than GS441524. Notably, low-dose combined application of GS441524 with GC376 could effectively protect mice against SARS-CoV-2 infection via i.n. or i.n. and i.m. treatment. Moreover, we found that the pharmacokinetic properties of GS441524 is better than GC376, and combined application of GC376 and GS441524 had a synergistic effect. Our findings support the further evaluation of the combined application of GC376 and GS441524 in future clinical studies.ImportanceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), which has seriously threatened global public health and economic development. Currently, effective therapies to treat COVID-19 are urgently needed. In this study, we assessed the efficacy of the preclinical inhibitors GC376 and GS441524 using a mouse-adapted SARS-CoV-2 infected mouse model for the first time. Our results showed that low-dose combined application of GC376 and GS441524 could effectively protect mice from HRB26M infection in the upper and lower respiratory tracts. Hence, the combined application should be developed and considered for future clinic practice.
SARS-CoV-2 IgG antibody responses in rt-PCR positive cases: first report from India
Authors: Dash Girish Chandra , Parai Debaprasad , Choudhary Hari Ram , Peter Annalisha , Rout Usha Kiran , Nanda Rashmi Ranjan , Kshatri Jaya Singh , Kanungo Srikanta , Palo Subrata Kumar , Pati Sanghamitra , Bhattacharya Debdutta 
Published: November 2020

AbstractThe SARS-CoV-2 antibody responses remain poorly understood and the clinical utility of serological testing is still unclear. As it is thought to confer some degree of immunity, this study is carried out to know the relationship between demographics and ct value of confirmed rt-PCR patients. A total of 384 serum samples were collected between 4-6 weeks after confirmed SARS-CoV-2 infection. IgG positivity was found to be 80.2% (95% CI, 76.2 – 84.2). The IgG positivity increased with the decrease in the ct value, with highest of 87.6% positivity in individuals with <20 ct value. The mean (± SD) ct value of IgG positives and og IgG negatives was 23.34 (± 6.09) and 26.72 (± 7.031) respectively. There was no significant difference found between the demographic characteristics such as age, sex, symptoms and antibody response. The current study is first of its kind wherein we have assessed the correlation of ct of RT-PCR with development of IgG against SARS-CoV-2. Our study showed that although Ct value might not have any relation with severity of the diseases but is associated with the antibody response among the SARS-CoV-2 infected individual.