bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determinants of directionality and efficiency of the ATP synthase Fo motor at atomic resolution
Authors: Marciniak Antoni , Chodnicki Pawel , Hossain Kazi A , Slabonska Joanna , Czub Jacek 
Published: September 2021

AbstractFo subcomplex of ATP synthase is an membraneembedded rotary motor that converts proton motive force into mechanical energy. Despite a rapid increase in the number of high-resolution structures, the mechanism of tight coupling between proton transport and motion of the rotary c-ring remains elusive. Here, using extensive all-atom free energy simulations, we show how the motor’s directionality naturally arises from the interplay between intra-protein interactions and energetics of protonation of the c-ring. Notably, our calculations reveal that the strictly conserved arginine in the a-subunit (R176) serves as a jack-of-all-trades: it dictates the direction of rotation, controls the protonation state of the proton-release site and separates the two proton-access half-channels. Therefore, arginine is necessary to avoid slippage between the proton flux and the mechanical output and guarantees highly efficient energy conversion. We also provide mechanistic explanations for the reported defective mutations of R176, reconciling the structural information on the Fo motor with previous functional and single-molecule data.
Synthetic reconstruction of the hunchback promoter specifies the role of Bicoid, Zelda and Hunchback in the dynamics of its transcription
Authors: Fernandes Goncalo , Tran Huy , Andrieu Maxime , Diaw Youssoupha , Romero Carmina Perez , Fradin Cécile , Coppey Mathieu , Walczak Aleksandra M. , Dostatni Nathalie 
Published: September 2021

AbstractFor over 40 years, the Bicoid-hunchback (Bcd-hb) system in the fruit fly embryo has been used as the model to study how positional information in morphogen concentration gradients is robustly translated into step-like responses. A body of quantitative comparisons between theory and experiment have since questioned the initial paradigm that the sharp hb transcription pattern emerges solely from diffusive biochemical interactions between the Bicoid transcription factor and the gene promoter region. Several alternative mechanisms have been proposed, such as additional sources of positional information, positive feedback from Hb proteins or out-of-equilibrium transcription activation.By using the MS2-MCP RNA-tagging system and analysing in real time, the transcription dynamics of synthetic reporters for Bicoid and/or its two partners Zelda and Hunchback, we show that all the hb expression pattern features and temporal dynamics are compatible with an equilibrium model with a short decay length Bicoid activity gradient as a sole source of positional information. Meanwhile, Bicoid’s partners speed-up the process by different means: Zelda lowers the Bicoid concentration threshold required for transcriptional activation while Hunchback reduces burstiness and increases the polymerase firing rate.
Open-Access STRS Database Of Populations From The 1000 Genomes Project Using High Coverage Phase 3 Data
Authors: Frontanilla Tamara Soledad , Valle-Silva Guilherme , Ayala Jesus , Mendes-Junior Celso Teixeira 
Published: September 2021

ABSTRACTAccurate STR genotyping from next-generation sequencing (NGS) data has been challenging. Haplotype inference and phasing for STRs (HipSTR) was specifically developed to deal with genotyping errors and obtain reliable STR genotypes from whole-genome sequencing datasets. The objective of this investigation was to perform a comprehensive genotyping analysis of a set of STRs of broad forensic interest from the 1000 Genomes populations and release a reliable open-access STR database to the forensic genetics community. A set of 22 STR markers were analyzed using the CRAM files of the 1000 Genomes Project Phase 3 high-coverage (30x) dataset generated by the New York Genome Center (NYGC). HipSTR was used to call genotypes from 2,504 samples from 26 populations organized into five groups: African, East Asian, European, South Asian, and admixed American. The D21S11 marker could not be detected in the present study. Moreover, the Hardy-Weinberg equilibrium analysis, coupled with a comprehensive analysis of allele frequencies, revealed that HipSTR could not identify longer Penta E (and Penta D at a lesser extent) alleles. This issue is probably due to the limited length of sequencing reads available for genotype calling, resulting in heterozygote deficiency. Notwithstanding that, AMOVA, a clustering analysis using STRUCTURE, and a Principal Coordinates Analysis revealed a clear-cut separation between the four major ancestries sampled by the 1000 Genomes Consortium (AFR, EUR, EAS, SAS). Meanwhile, the AMOVA results corroborated previous reports that most of the variance is (97.12%) observed within populations. This set of analyses revealed that except for larger Penta D and Penta E alleles, allele frequencies and genotypes defined by HipSTR from the 1000 Genomes Project phase 3 data and offered as an open-access database are consistent and highly reliable.
Selective signatures and high genome-wide diversity in traditional Brazilian manioc (Manihot esculentaCrantz) varieties
Authors: Alves-Pereira Alessandro , Zucchi Maria I. , Clement Charles R. , Viana João P. G. , Pinheiro José B. , Veasey Elizabeth A. , Souza Anete P. 
Published: September 2021

AbstractKnowledge about crops’ genetic diversity is essential to promote effective use and conservation of their genetic resources, because genetic diversity enables farmers to adapt their crops to specific needs and is the raw material for breeding efforts. Currently, manioc (Manihot esculentassp.esculenta) is one of the most important food crops in the world and has the potential to help achieve food security in the context of on-going climate changes. In this study we assessed the patterns of genome-wide diversity of traditional Brazilian manioc varieties conserved in the gene bank of the Luiz de Queiroz College of Agriculture, University of São Paulo. We used single nucleotide polymorphisms to evaluate the organization of genetic diversity and to identify selective signatures contrasting varieties from different biomes with samples of manioc’s wild relativeM. esculentassp.flabellifolia. We identified signatures of selection putatively associated with resistance genes, plant development and response to abiotic stresses. This presumed adaptive variation might have been important for the initial domestication and for the crop’s diversification in response to cultivation in different environments. The neutral variation revealed high levels of genetic diversity within groups of varieties from different biomes and low to moderate genetic divergence among biomes. These results reflect the complexity of manioc’s biology and its evolutionary dynamics under traditional cultivation. Our results exemplify how the smallholder practices contribute to the conservation of manioc’s genetic resources, maintaining variation of potential adaptive significance and high levels of neutral genetic diversity.
Protein sequence sampling and prediction from structural data
Authors: Orellana Gabriel A. , Caceres-Delpiano Javier , Ibañez Roberto , Dunne Michael P. , Alvarez Leonardo 
Published: September 2021

AbstractThe increasing integration between protein engineering and machine learning has led to many interesting results. A problem still to solve is to evaluate the likelihood that a sequence will fold into a target structure. This problem can be also viewed as sequence prediction from a known structure.In the current work, we propose improvements in the recent architecture of Geometric Vector Perceptrons [1] in order to optimize the sampling of sequences from a known backbone structure. The proposed model differs from the original in that there is: (i) no updating in the vectorial embedding, only in the scalar one, (ii) only one layer of decoding. The first aspect improves the accuracy of the model and reduces the use of memory, the second allows for training of the model with several tasks without incurring data leakage.We treat the trained classifier as an Energy-Based Model and sample sequences by sampling amino acids in a non-autoreggresive manner in the empty positions of the sequence using energy-guided criteria and followed by random mutation optimization. We improve the median identity of samples from 40.2% to 44.7%.An additional question worth investigating is whether sampled and original sequences fold into similar structures independent of their identity. We chose proteins in our test set whose sampled sequences show low identity (under 30%) but for which our model predicted favorable energies. We used AlphaFold [2, 3] and observed that the predicted structures for sampled sequences highly resemble the predicted structures for original sequences, with an average TM-score of 0.84.
Interpretable and tractable models of transcriptional noise for the rational design of single-molecule quantification experiments
Authors: Gorin Gennady , Vastola John J. , Fang Meichen , Pachter Lior 
Published: September 2021

The question of how cell-to-cell differences in transcription rate affect RNA count distributions is fundamental for understanding biological processes underlying transcription. We argue that answering this question requires quantitative models that are both interpretable (describing concrete biophysical phenomena) and tractable (amenable to mathematical analysis). This enables the identification of experiments which best discriminate between competing hypotheses. As a proof of principle, we introduce a simple but flexible class of models involving a stochastic transcription rate coupled to a discrete stochastic RNA transcription and splicing process, and compare and contrast two biologically plausible hypotheses about transcription rate variation. One assumes variation is due to DNA experiencing mechanical strain, while the other assumes it is due to regulator number fluctuations. Although biophysically distinct, these models are mathematically similar, and we show they are hard to distinguish without comparing whole predicted probability distributions. Our work illustrates the importance of theory-guided data collection, and introduces a general framework for constructing and solving mathematically nontrivial continuous–discrete stochastic models.Significance StatementThe interpretation of transcriptomic observations requires detailed models of biophysical noise that can be compared and fit to experimental data. Models of intrinsic noise, describing stochasticity in molecular reactions, and extrinsic noise, describing cell-to-cell variation, are particularly common. However, integrating and solving them is challenging, and previous results are largely limited to summary statistics. We examine two mechanistically grounded stochastic models of transcriptional variation and demonstrate that (1) well-known regimes naturally emerge in limiting cases, and (2) the choice of noise model significantly affects the RNA distributions, but not the lower moments, offering a route to model identification and inference. This approach provides a simple and biophysically interpretable means to construct and unify models of transcriptional variation.
Ascertaining cells’ synaptic connections and RNA expression simultaneously with massively barcoded rabies virus libraries
Authors: Saunders Arpiar , Huang Kee Wui , Vondrak Cassandra , Hughes Christina , Smolyar Karina , Sen Harsha , Philson Adrienne C. , Nemesh James , Wysoker Alec , Kashin Seva , Sabatini Bernardo L. , McCarroll Steven A. 
Published: September 2021

ABSTRACTBrain function depends on forming and maintaining connections between neurons of specific types, ensuring neural function while allowing the plasticity necessary for cellular and behavioral dynamics. However, systematic descriptions of how brain cell types organize into synaptic networks and which molecules instruct these relationships are not readily available. Here, we introduce SBARRO (Synaptic Barcode Analysis by Retrograde Rabies ReadOut), a method that uses single-cell RNA sequencing to reveal directional, monosynaptic relationships based on the paths of a barcoded rabies virus from its “starter” postsynaptic cell to that cell’s presynaptic partners1. Thousands of these partner relationships can be ascertained in a single experiment, alongside genome-wide RNA profiles – and thus cell identities and molecular states – of each host cell. We used SBARRO to describe synaptic networks formed by diverse mouse brain cell types in vitro, leveraging a system similar to those used to identify synaptogenic molecules. We found that the molecular identity (cell type/subtype) of the starter cell predicted the number and types of cells that had synapsed onto it. Rabies transmission tended to occur into cells with RNA-expression signatures related to developmental maturation and synaptic transmission. The estimated size of a cell’s presynaptic network, relative to that of other cells of the same type, associated with increased expression of Arpp21 and Cdh13. By tracking individual virions and their clonal progeny as they travel among host cells, single-cell, single-virion genomic technologies offer new opportunities to map the synaptic organization of neural circuits in health and disease.
High-throughput small molecule screen identifies inhibitors of microsporidia invasion and proliferation in C. elegans
Authors: Murareanu Brandon M. , Antao Noelle V. , Zhao Winnie , Dubuffet Aurore , El Alaoui Hicham , Knox Jessica , Ekiert Damian C. , Bhabha Gira , Roy Peter J. , Reinke Aaron W. 
Published: September 2021

AbstractMicrosporidia are a diverse group of fungal-related obligate intracellular parasites that infect most animal phyla. Despite the emerging threat that microsporidia have become to humans and agricultural animals, few reliable treatment options exist. To identify novel chemical inhibitors of microsporidia infection, we developed a high-throughput screening method using Caenorhabditis elegans and the microsporidia species Nematocida parisii. We screened the Spectrum Collection of 2,560 FDA-approved compounds and natural products to identify compounds that prevent C. elegans progeny inhibition caused by N. parisii infection. We developed a semi-automated method for quantifying C. elegans progeny number in liquid culture, confirming 11 candidate microsporidia inhibitors. We show that five compounds prevent microsporidia infection by inhibiting spore firing, and demonstrate that one compound, dexrazoxane, slows infection progression. We also show that these compounds have activity against several other microsporidia species, including those which infect humans. Together, our results demonstrate the effectiveness of C. elegans as a model host for drug discovery against intracellular pathogens and provide a scalable high-throughput system for the identification and characterization of additional microsporidia inhibitors.
Both Simulation and Sequencing Data Reveal Multiple SARS-CoV-2 Variants Coinfection in COVID-19 Pandemic
Authors: Li Yinhu , Jiang Yiqi , Li Zhengtu , Yu Yonghan , Chen Jiaxing , Jia Wenlong , Ng Yen Kaow , Ye Feng , Shen Bairong , Li Shuai Cheng 
Published: September 2021

AbstractSARS-CoV-2 is a single-stranded RNA betacoronavirus with a high mutation rate. The rapidly emerged SARS-CoV-2 variants could increase the transmissibility, aggravate the severity, and even fade the vaccine protection. Although the coinfections of SARS-CoV-2 with other respiratory pathogens have been reported, whether multiple SARS-CoV-2 variants coinfection exists remains controversial. This study collected 12,986 and 4,113 SARS-CoV-2 genomes from the GISAID database on May 11, 2020 (GISAID20May11) and April 1, 2021 (GISAID21Apr1), respectively. With the single-nucleotide variants (SNV) and network clique analysis, we constructed the single-nucleotide polymorphism (SNP) coexistence networks and noted the SNP number of the maximal clique as the coinfection index. The coinfection indices of GISAID20May11 and GISAID21Apr1 datasets were 16 and 34, respectively. Simulating the transmission routes and the mutation accumulations, we discovered the linear relationship between the coinfection index and the coinfected variant number. Based on the linear relationship, we deduced that the COVID-19 cases in the GISAID20May11 and GISAID21Apr1 datasets were coinfected with 2.20 and 3.42 SARS-CoV-2 variants on average. Additionally, we performed Nanopore sequencing on 42 COVID-19 patients to explore the virus mutational characteristics. We found the heterozygous SNPs in 41 COVID-19 cases, which support the coinfection of SARS-CoV-2 variants and challenge the accuracy of phylogenetic analysis. In conclusion, our findings reported the coinfection of SARS-CoV-2 variants in COVID-19 patients, demonstrated the increased coinfected variants number in the epidemic, and provided clues for the prolonged viral shedding and severe symptoms in some cases.
The vaccinia-based Sementis Copenhagen Vector COVID-19 vaccine induces broad and durable cellular and humoral immune responses
Authors: Eldi Preethi , Cooper Tamara H. , Prow Natalie A. , Liu Liang , Heinemann Gary K. , Zhang Voueleng J. , Trinidad Abigail D. , Guzman-Genuino Ruth Marian , Wulff Peter , Hobbs Leanne M. , Diener Kerrilyn R. , Hayball John D. 
Published: September 2021

AbstractThe ongoing COVID-19 pandemic perpetuated by SARS-CoV-2 variants, has highlighted the continued need for broadly protective vaccines that elicit robust and durable protection. Here, the vaccinia virus-based, replication-defective Sementis Copenhagen Vector (SCV) was used to develop a first-generation COVID-19 vaccine encoding the spike glycoprotein (SCV-S).Vaccination of mice rapidly induced polyfunctional CD8 T cells with cytotoxic activity and robust Th1-biased, spike-specific neutralizing antibodies, which are significantly increased following a second vaccination, and contained neutralizing activity against the alpha and beta variants of concern. Longitudinal studies indicated neutralizing antibody activity was maintained up to 9 months post-vaccination in both young and aging mice, with durable immune memory evident even in the presence of pre-existing vector immunity. This immunogenicity profile suggests a potential to expand protection generated by current vaccines in a heterologous boost format, and presents a solid basis for second-generation SCV-based COVID-19 vaccine candidates incorporating additional SARS-CoV-2 immunogens.
Greater Neural Pattern Dissimilarity and Higher Meaningfulness in the Retrieval Stage are Enhanced by Spaced Learning
Authors: Yaowen Liang 
Published: September 2021

AbstractThe question of whether repeated studies bring more variability or less to our brain is a critical problem before scientist continue their further study about memory. In the past ten years, a series of neural pattern representation studies have found that under the condition of spaced learning, the neural pattern similarity(NPS) between two encoding stages increases, and the researchers claimed that these results support the idea that repeated studies bring more similarity along with repetition in our brain, which is conflicted with the encoding variability theory(Feng et al., 2019; Y. Lu et al., 2015; Xue et al., 2010, 2011a). However, we doubt this viewpoint because we think the difference between encoding processing cannot be used to represent the difference between memory states. In current experiments, we used a new experimental paradigm with a longer lag and elaboration learning task to test the encoding variability theory. By comparing the difference between neural pattern dissimilarity(NPDS1)(spaced learning - one-time learning) and NPDS2(massed learning - one-time learning) in the final test (retrieval) stage, we get the result that the NPDS1 was significantly greater than NPDS2 in the parietal lobe of 400ms and the right frontal lobe of 600ms, which is more fitting to the encoding variability mechanism. However, we believe that there is no contradiction between these two experimental evidences. On the contrary, we think they reflect different aspects of the process of spaced learning. We propose that the deficient processing in encoding stage exactly lead to less encoding variability in our memory. More importantly, this result gives us reason to double the paper published ten years ago in Science, which claimed repetition brings greater neural pattern similarity.
Dissecting the roles of Haspin and VRK1 in Histone H3 threonine-3 phosphorylation during mitosis
Authors: Cartwright Tyrell N. , Harris Rebecca J. , Meyer Stephanie K. , Watson Nikolaus A. , Tan Cheryl , Wang Fangwei , Higgins Jonathan M.G. 
Published: September 2021

AbstractProtein kinases that phosphorylate histones are ideally-placed to influence the behavior of chromosomes during cell division. Indeed, a number of conserved histone phosphorylation events occur prominently during mitosis and meiosis in most eukaryotes, including on histone H3 at threonine-3 (H3T3ph). At least two kinases, Haspin and VRK1 (NHK-1/ballchen in Drosophila), have been proposed to carry out this modification. Phosphorylation of H3 by Haspin has defined roles in mitosis, but the significance of VRK1 activity towards histones in dividing cells has been unclear. Here, using in vitro kinase assays, KiPIK screening, RNA interference, and CRISPR/Cas9 approaches, we were unable to substantiate a direct role for VRK1, or its homologue VRK2, in the phosphorylation of threonine-3 or serine-10 of Histone H3 in mitosis, although loss of VRK1 did slow cell proliferation. We conclude that the role of VRK1, and its more recently identified association with neuromuscular disease in humans, is unlikely to involve mitotic histone kinase activity. In contrast, Haspin is required to generate H3T3ph during mitosis.
Reframing educator preparation to collaboratively prepare teachers and administrators: challenges and advantages
Authors: Rhodes Ginger , Robinson Kerry K. , Kubasko Dennis S. , Ryder Andrew J. , Hooker Steven D. , Reid-Griffin Angelia , Sterrett William L. 
Published: September 2021

Purpose
This study examines reframing an organization that permitted three typically siloed university programs to collaborate around a shared experience focused on teaching, leadership, evaluation, and applied learning.

Design
Participants were seven faculty members who designed and implemented the shared experience. Data sources included participants’ responses to a feedback survey, meeting notes, and project documents. The data were coded and grouped based on themes.

Findings
Themes revealed challenges and advantages faculty experienced during the project. Challenges included creating shared expectations, technology, and continuity with student evaluators. Advantages included reflecting on teaching practices, frameworks, instructional strategies, and professional goals.

Originality
Despite the difficulty and rarity of cross-program collaborations, this study demonstrates how such efforts may incorporate best practices in preparing educators.