bluuebunny/crossref_metadata_2025_split huggingface dataset:
CASowary: CRISPR-Cas13 guide RNA predictor for transcript depletion
Authors: Krohannon Alexander , Srivastava Mansi , Rauch Simone , Srivastava Rajneesh , Dickinson Bryan C. , Janga Sarath Chandra 
Published: July 2021

AbstractRecent discovery of the gene editing system -CRISPR (Clustered Regularly Interspersed Short Palindromic Repeats) associated proteins (Cas), has resulted in its widespread use for improved understanding of a variety of biological systems. Cas13, a lesser studied Cas protein, has been repurposed to allow for efficient and precise editing of RNA molecules. The Cas13 system utilizes base complementarity between a crRNA/sgRNA (crispr RNA or single guide RNA) and a target RNA transcript, to preferentially bind to only the target transcript. Unlike targeting the upstream regulatory regions of protein coding genes on the genome, the transcriptome is significantly more redundant, leading to many transcripts having wide stretches of identical nucleotide sequences. Transcripts also exhibit complex three-dimensional structures and interact with an array of RBPs (RNA Binding Proteins), both of which further limit the scope of effective target sequences. As a result, there currently exists no method to predict whether a specific sgRNA will effectively knockdown a transcript. Here we present a novel machine learning and computational tool, CASowary, to predict the efficacy of a sgRNA. We used publicly available RNA knockdown data from Cas13 characterization experiments for 555 sgRNAs targeting the transcriptome in HEK293 cells, in conjunction with transcriptome-wide protein occupancy information on RNA. Our model utilizes a Decision Tree architecture with a set of 112 sequence and target availability features, to classify sgRNA efficacy into one of four classes, based upon expected level of target transcript knockdown. After accounting for noise in the training data set, the noise-normalized accuracy exceeds 70%. Additionally, highly effective sgRNA predictions have been experimentally validated using an independent RNA targeting Cas system -CIRTS, confirming the robustness and reproducibility of our model’s sgRNA predictions. Utilizing transcriptome wide protein occupancy map generated using POP-seq in Hela cells against publicly available protein-RNA interaction map in Hek293 cells, we show that CASowary can predict high quality guides for numerous transcripts in a cell line specific manner. Application of CASowary to whole transcriptomes should enable rapid deployment of CRISPR/Cas13 systems, facilitating the development of therapeutic interventions linked with aberrations in RNA regulatory processes.
Immunization with synthetic SARS-CoV-2 S glycoprotein virus-like particles protects Macaques from infection
Authors: Sulbaran Guidenn , Maisonnasse Pauline , Amen Axelle , Guilligay Delphine , Dereuddre-Bosquet Nathalie , Burger Judith A. , Poniman Meliawati , Buisson Marlyse , Dergan Dylon Sebastian , Naninck Thibaut , Lemaître Julien , Gros Wesley , Gallouët Anne-Sophie , Marlin Romain , Bouillier Camille , Contreras Vanessa , Relouzat Francis , Fenel Daphna , Thepaut Michel , Bally Isabelle , Thielens Nicole , Fieschi Franck , Schoehn Guy , van der Werf Sylvie , van Gils Marit J. , Sanders Rogier W. , Poignard Pascal , Le Grand Roger , Weissenhorn Winfried 
Published: July 2021

AbstractThe SARS-CoV-2 pandemic causes an ongoing global health crisis, which requires efficient and safe vaccination programs. Here, we present synthetic SARS-CoV2 S glycoprotein-coated liposomes that resemble in size and surface structure virus-like particles. Soluble S glycoprotein trimers were stabilized by formaldehyde cross-linking and coated onto lipid vesicles (S-VLP). Immunization of cynomolgus macaques with S-VLPs induced high antibody titers and TH1 CD4+ biased T cell responses. Although antibody responses were initially dominated by RBD specificity, the third immunization boosted non-RBD antibody titers. Antibodies showed potent neutralization against the vaccine strain and the Alpha variant after two immunizations and robust neutralization of Beta and Gamma strains. Challenge of animals with SARS-CoV-2 protected all vaccinated animals by sterilizing immunity. Thus, the S-VLP approach is an efficient and safe vaccine candidate based on a proven classical approach for further development and clinical testing.
AMaLa: Analysis of Directed Evolution Experiments via Annealed Mutational approximated Landscape
Authors: Sesta Luca , Uguzzoni Guido , Diaz Jorge Fernandez-de-Cossio , Pagnani Andrea 
Published: July 2021

We present Annealed Mutational approximated landscape (AMaLa), a new method to infer fitness landscapes from Directed Evolution experiment sequencing data. Directed Evolution experiments typically start from a single wild-type sequence, which undergoes Darwinian in vitro evolution acted via multiple rounds of mutation and selection with respect to a target phenotype. In the last years, Directed Evolution is emerging as a powerful instrument to probe fitness landscapes under controlled experimental condition and, thanks to the use of high-throughput sequencing of the different rounds, as a relevant testing ground to develop accurate statistical models and inference algorithms.Fitness landscape modeling strategies, either use as input data the enrichment of variants abundances and hence require observing the same variants at different rounds, or they simply assume that the variants at the last sequenced round are the results of a sampling process at equilibrium. AMaLa aims at leveraging effectively the information encoded in the time evolution of all sequenced rounds. To do so, on the one hand we assume statistical sampling independence between sequenced rounds, and on the other we gauge all possible trajectories in sequence space with a time-dependent statistical weight consisting of two contributions: (i) a statistical energy term accounting for the selection process, (ii) a simple generalized Jukes-Cantor model to describe the purely mutational step.This simple scheme allows us to accurately describe the Directed Evolution dynamics in a concrete experimental setup and to infer a fitness landscape that reproduces correctly the measures of the phenotype under selection (e.g. antibiotic drug resistance), notably outperforming widely used inference strategies. We assess the reliability of AMaLa by showing how the inferred statistical model could be used to predict relevant structural properties of the wild-type sequence, and to reproduce the mutational effects of large scale functional screening not used to train the model.
Uncoupling of the Diurnal Growth Program by Artificial Genome Relaxation in Synechocystis sp. PCC 6803
Authors: Behle Anna , Dietsch Maximilian , Goldschmidt Louis , Murugathas Wandana , Brandt David , Busche Tobias , Kalinowski Jörn , Ebenhöh Oliver , Axmann Ilka M. , Machné Rainer 
Published: July 2021

AbstractIn cyanobacteria DNA supercoiling varies over the diurnal light/dark cycle and is integrated with temporal programs of transcription and replication. We manipulated DNA supercoiling in Synechocystis sp. PCC 6803 by CRISPRi-based knock-down of gyrase subunits and overexpression of topoisomerase I (TopoI), and characterized the phenotypes. Cell division was blocked, most likely due to inhibition of genomic but not plasmid DNA replication. Cell growth continued to 4-5x of the wildtype cell volume, and metabolic flux was redirected towards glycogen in the TopoI overexpression strain. TopoI induction initially lead to down-regulation of GC-rich and up-regulation of AT-rich genes. The response quickly bifurcated and four diurnal co-expression cohorts (dawn, noon, dusk and night) all responded differently, in part with a circadian (≈ 24 h) pattern. A GC-rich region − 50 bp of transcription start sites is differentially enriched in these four cohorts. We suggest a model where energy- and gyrase-gated transcription of growth genes at the dark/light transition (dawn) generates DNA supercoiling which then facilitates DNA replication and initiates the diurnal transcriptome program.
Characterizing enterotypes in human metagenomics: a viral perspective
Authors: Song Li , Zhang Lu , Fang Xiaodong 
Published: July 2021

AbstractThe diversity and high genomic mutation rates of viral species hinder our understanding of viruses and their contributions to human health. Here we investigated the human fecal virome using previously published sequencing data of 2,690 metagenomes from seven countries. We found that the virome was dominated by double-stranded DNA viruses, and young children and adults showed dramatic differences in their fecal enterovirus composition. Beta diversity showed there were significantly higher distances to centroids in individuals with severe phenotypes, such as cirrhosis. In contrast, there were no significant differences in lengths to centroids or viral components between patients with mild phenotypes, such as hypertension. Enterotypes showed the same specific viruses and enrichment direction after independent determination of enterotypes in various projects. Confounding factors, such as different sequencing platforms and library construction, did not result in a batch effect to confuse enterotype assignment. The gut virome composition pattern could be described by two viral enterotypes, which supported a discrete, rather than a gradient, distribution. Compared with enterotype 2, enterotype 1 had a higher viral count and Shannon index, but a lower beta diversity, indicating more resistance to the external environment’s harmful effects. Disease was usually accompanied by a viral enterotype disorder. However, a sample outside of the enterotyping mathematical space of enterotype database did not necessarily indicate sickness. Therefore, the background context must be carefully considered when using a viral enterotype as a biomarker for disease prediction. The disease, second only to the enterotype, explains significant variation in viral community composition, implying that double-stranded DNA is relevant to human health. Our results of investigating a baseline viral database highlight important insights into the virome composition of human ecosystems, and provide an alternate biomarker for early disease screening.
Effect of stimulation time on the expression of human macrophage polarization markers
Authors: Purcu Duygu Unuvar , Korkmaz Asli , Gunalp Sinem , Helvaci Derya Goksu , Erdal Yonca , Dogan Yavuz , Suner Asli , Wingender Gerhard , Sag Duygu 
Published: July 2021

AbstractMacrophages are highly plastic cells that can polarize into functionally distinct subsetsin vivoandin vitroin response to environmental signals. The development of protocols to model macrophage polarizationin vitrogreatly contributes to our understanding of macrophage biology. Macrophages are divided into two main groups: Pro-inflammatory M1 macrophages (classically activated) and anti-inflammatory M2 macrophages (alternatively activated), based on several key surface markers and the production of inflammatory mediators. However, the expression of these common macrophage polarization markers is greatly affected by the stimulation time used. Unfortunately, there is no consensus yet regarding the optimal stimulation times for particular macrophage polarization markers inin vitroexperiments. This situation is problematic, (i) as analysing a particular marker at a suboptimal time point can lead to false-negative results, and (ii) as it clearly impedes the comparison of different studies. Using human monocyte-derived macrophages (MDMs)in vitro, we analysed how the expression of the main polarization markers for M1 (CD64, CD86, CXCL9, CXCL10, HLA-DR, IDO1, IL1β, IL12, TNF), M2a (CD200R, CD206, CCL17, CCL22, IL-10, TGM2), and M2c (CD163, IL-10, TGFβ) macrophages changes over time at mRNA and protein levels. Our data establish the most appropriate stimulation time for the analysis of the expression of human macrophage polarization markersin vitro. Providing such a reference guide will likely facilitate the investigation of macrophage polarization and its reproducibility.
Temporal Dynamics of HCMV Gene Expression in Lytic and Latent Infections
Authors: Rozman Batsheva , Nachshon Aharon , Samia Roi Levi , Lavi Michael , Schwartz Michal , Stern-Ginossar Noam 
Published: July 2021

AbstractPrimary infection with Human cytomegalovirus (HCMV) results in a persistent lifelong infection due to its ability to establish latent infection. During productive HCMV infection, viral genes are expressed in a coordinated cascade that is characteristic of all herpesviruses and traditionally relies on the dependencies of viral genes on protein synthesis and viral DNA replication. In contrast, the transcriptional landscape associated with HCMV latency is still disputed and poorly understood. Here, we examine viral transcriptomic dynamics during the establishment of both productive and latent HCMV infections. Our temporal measurements reveal that viral gene expression dynamics along productive infection and their dependencies on protein synthesis and viral DNA replication, do not fully align. This illustrates that the regulation of herpesvirus genes does not represent a simple sequential transcriptional cascade, and surprisingly, many viral genes are regulated by multiple independent modules. Using our improved classification of viral gene expression kinetics in conjunction with transcriptome-wide measurements of the effects of a wide array of chromatin modifiers, we unbiasedly show that a defining characteristic of latent cells is the unique repression of immediate early (IE) genes. Altogether, our findings provide an elaborate definition of HCMV gene expression patterns and reveal novel principles that govern viral gene expression in lytic and latent infection states.
NMR spectroscopy of a single mammalian embryo
Authors: Sivelli Giulia , Conley Gaurasundar M. , Herrera Carolina , Marable Kathryn , Rodriguez Kyle J. , Bollwein Heinrich , Sudano Mateus J. , Brugger Jürgen , Simpson Andre J. , Boero Giovanni , Grisi Marco 
Published: July 2021

AbstractThe resolving power, chemical sensitivity and non-invasive nature of NMR has made it an established technique for in vivo studies of large organisms both for research and clinical applications. These features would clearly be beneficial at the nanoliter scale (nL), typical of early development of mammalian embryos, microtissues and organoids, the scale where the building blocks of complex organisms could be observed. However, the handling of such small samples (about 100 micrometers) and sensitivity issues have prevented the widespread adoption of NMR. Recently we have shown how these limitations can be overcome with ultra-compact single-chip probes. In this article we show that such probes have sufficient sensitivity to detect and resolve NMR signals from individual bovine pre-implantation embryos. In less than 1 hour these spherical samples of just 130-190 micrometers produce distinct spectral peaks, largely originating from lipids contained inside them. We further observe how the spectral features, namely the peak intensities, vary from one sample to another despite their optical and morphological similarities.
SIRV: Spatial inference of RNA velocity at the single-cell resolution
Authors: Abdelaal Tamim , Grossouw Laurens M. , Pasterkamp R. Jeroen , Lelieveldt Boudewijn P.F. , Reinders Marcel J.T. , Mahfouz Ahmed 
Published: July 2021

AbstractRNA Velocity allows the inference of cellular differentiation trajectories from single-cell RNA sequencing (scRNA-seq) data. It would be highly interesting to study these differentiation dynamics in the spatial context of tissues. Estimating spatial RNA velocities is, however, limited by the inability to spatially capture spliced and unspliced mRNA molecules in high-resolution spatial transcriptomics. We present SIRV, a method to spatially infer RNA velocities at the single-cell resolution by enriching spatial transcriptomics data with the expression of spliced and unspliced mRNA from reference scRNA-seq data. We used SIRV to infer spatial differentiation trajectories in the developing mouse brain, including the differentiation of midbrain-hindbrain boundary cells and marking the forebrain origin of the cortical hem and diencephalon cells. Our results show that SIRV reveals spatial differentiation patterns not identifiable with scRNA-seq data alone. Additionally, we applied SIRV to mouse organogenesis data and obtained robust spatial differentiation trajectories. Finally, we verified the spatial RNA velocities obtained by SIRV using 10x Visium data of the developing chicken heart and MERFISH data from human osteosarcoma cells. Altogether, SIRV allows the inference of spatial RNA velocities at the single-cell resolution to facilitate studying tissue development.
Model predicts the impact of root system architecture on soil water infiltration
Authors: Mair Andrew , Dupuy Lionel X , Ptashnyk Mariya 
Published: July 2021

AbstractThere is strong experimental evidence that root systems substantially change the saturated hydraulic conductivity of soil. However, the mechanisms by which roots affect soil hydraulic properties remain largely unknown. In this work, we made the hypothesis that preferential soil moisture transport occurs along the axes of roots, and that this is what changes a soil’s saturated hydraulic conductivity. We modified Richards’ equation to incorporate the preferential flow of soil moisture along the axes of roots. Using the finite element method and Bayesian optimisation, we developed a pipeline to calibrate our model with respect to a given root system. When applied to simulated root systems, the pipeline successfully predicted the pore-water pressure profiles corresponding to saturated hydraulic conductivity values, observed by Leung et al. (2018), for soils vegetated with willow and grass. Prediction accuracy improved for root systems with more realistic architectures, therefore suggesting that changes in saturated hydraulic conductivity are a result of roots enabling preferential soil moisture transport along their axes. The model proposed in this work improves our ability to predict moisture transport through vegetated soil and could help optimise irrigation, forecast flood events and plan landslide prevention strategies.
Regulatory start-stop elements in 5’ untranslated regions pervasively modulate translation
Authors: Rendleman Justin , Haizel Solomon , Wu Shaohuan , Liu Junjie , Ge Xinyi , Zou Huijing , Mohammad Mahabub Pasha , Pressler Matthew , Maity Shuvadeep , Hronová Vladislava , Gao Zhaofeng , Herrmannová Anna , Lei Amy , Allgoewer Kristina , Sultanov Daniel , Hinckley Will Edward , Cheng Ziyue , Shelby Lauren , Szkop Krzysztof J. , Topisirovic Ivan , Larsson Ola , Hatzoglou Maria , Valášek Leoš Shivaya , Vogel Christine 
Published: July 2021

AbstractSequence elements within the 5’ untranslated region (UTR) of eukaryotic genes, e.g. upstream open reading frames (uORFs), control translation of eukaryotic genes. We describe an element consisting of a start codon immediately followed by a stop codon which is distinct from uORFs in the lack of an elongation step. Start-stops have been described for specific cases, but their widespread impact has been overlooked. Start-stop elements occur in the 5’UTR of 1, 417 human genes and are more often occupied with a ribosome than canonical uORFs or control sequences. Start-stops efficiently halt ribosomes without evidence for accelerated RNA turnover, therefore acting as a barrier for the scanning of the small ribosomal subunit and repressing downstream translation. Our results suggest a model by which the ribosome undergoes repeated cycles of termination and partial ribosomal recycling, during which the large subunit detaches, but the 40S subunit with the Met-tRNAiMetremains associated with the mRNA to be rejoined by the 60S subunit. Start-stop elements occur in many transcription factors and signaling genes, and affect cellular fate via different routes. We investigate the start-stop element in several genes, i.e.MORF4L1,SLC39A1, andPSPC1, and in more detail inATF4.
Emergence of a novel mobile RND-type efflux pump gene cluster,tmexC3D2-toprJ1b, inPseudomonasspecies
Authors: Maehana Shotaro , Eda Ryotaro , Niida Nagi , Hirabayashi Aki , Sakai Kouji , Furukawa Takashi , Sei Kazunari , Kitasato Hidero , Suzuki Masato 
Published: July 2021

AbstractTigecycline exhibits promising activity against multidrug-resistant Gram-negative bacteria (MDR-GNB), whose infections are difficult to treat with antimicrobials. However, mobile tigecycline resistance genes, such astmexCD-toprJ, have emerged in Enterobacterales isolated in China, Vietnam, and possibly other countries in the world. In this study, we investigated tigecycline-nonsusceptible GNB in Japan. Eight tigecycline- and carbapenem-nonsusceptible isolates ofPseudomonas alcaligeneswere obtained from sewage water from a medical institution in Japan in 2020. Whole genome analysis of allP. alcaligenesisolates was performed using short-read sequencing, and the isolate KAM426 was further analyzed using long-read sequencing. For important antimicrobial resistance genes, analysis of surrounding structures and comparison with similar sequences in the public genome database were performed. We identified a novel hybrid type oftmexCD-toprJgene cluster,tmexC3D2-toprJ1bconsisting oftmexC3,tmexC2, andtoprJ1b, in phylogenetically clonal isolates ofP. alcaligenes. The complete genome sequence of KAM426 revealed that this isolate co-harborstmexC3D2-toprJ1band two copies of the carbapenemase geneblaIMP-1on the chromosome.tmexC3D2-toprJ1bin KAM426 was flanked by the IS5/IS1182family transposase gene, suggesting that the gene cluster was acquired by horizontal gene transfer (HGT).tmexC3D2-toprJ1bseemed to have spread to otherPseudomonasspecies such asPseudomonas aeruginosavia HGT mediated by mobile gene elements such as a plasmid. This study identifiedtmexCD-toprJ-like tigecycline resistance genes in Japan for the first time and suggests that diversetmexCD-toprJ-like gene clusters, includingtmexC3D2-toprJ1b, have spread among MDR-GNB worldwide. Further epidemiological genomic studies in clinical and environmental settings are needed.