bluuebunny/crossref_metadata_2025_split huggingface dataset:
New design strategies for ultra-specific CRISPR-Cas13a-based RNA-diagnostic tools with single-nucleotide mismatch sensitivity
Authors: Vargas Adrian M. Molina , Osborn Raven , Sinha Souvik , Arantes Pablo R. , Patel Amun , Dewhurst Stephen , Palermo Giulia , O’Connell Mitchell R. 
Published: July 2023

ABSTRACTThe pressing need for clinical diagnostics has required the development of novel nucleic acid-based detection technologies that are sensitive, fast, and inexpensive, and that can be deployed at point-of-care. Recently, the RNA-guided ribonuclease CRISPR-Cas13 has been successfully harnessed for such purposes. However, developing assays for detection of genetic variability, for example single-nucleotide polymorphisms, is still challenging and previously described design strategies are not always generalizable. Here, we expanded our characterization of LbuCas13a RNA-detection specificity by performing a combination of experimental RNA mismatch tolerance profiling, molecular dynamics simulations, protein, and crRNA engineering. We found certain positions in the crRNA-target-RNA duplex that are particularly sensitive to mismatches and establish the effect of RNA concentration in mismatch tolerance. Additionally, we determined that shortening the crRNA spacer or modifying the direct repeat of the crRNA leads to stricter specificities. Furthermore, we harnessed our understanding of LbuCas13a allosteric activation pathways through molecular dynamics and structure-guided engineering to develop novel Cas13a variants that display increased sensitivities to single-nucleotide mismatches. We deployed these Cas13a variants and crRNA design strategies to achieve superior discrimination of SARS-CoV-2 strains compared to wild-type LbuCas13a. Together, our work provides new design criteria and new Cas13a variants for easier-to-implement Cas13-based diagnostics.KEY POINTSCertain positions in the Cas13a crRNA-target-RNA duplex are particularly sensitive to mismatches.Understanding Cas13a’s allosteric activation pathway allowed us to develop novel high-fidelity Cas13a variants.These Cas13a variants and crRNA design strategies achieve superior discrimination of SARS-CoV-2 strains.GRAPHICAL ABSTRACTNew strategies to improve Cas13a RNA-detection specificity developed via mismatch tolerance profiling, uncovering features that modulate specificity, and structure-guided engineering of LbuCas13a.
Interpreting roles of mutations associated with the emergence ofS. aureusUSA300 strains using transcriptional regulatory network reconstruction
Authors: Poudel Saugat , Hyun Jason , Hefner Ying , Monk Jon , Nizet Victor , Palsson Bernhard O. 
Published: July 2023

AbstractTheStaphylococcus aureusclonal complex 8 (CC8) is made up of several subtypes with varying levels of clinical burden; from community-associated methicillin resistantS. aureus(CA-MRSA) USA300 strains to hospital-associated (HA-MRSA) USA500 strains and ancestral methicillin susceptible (MSSA) strains. This phenotypic distribution within a single clonal complex makes CC8 an ideal clade to study the emergence of mutations important for antibiotic resistance and community spread. Gene level analysis comparing USA300 against MSSA and HA-MRSA strains have revealed key horizontally acquired genes important for its rapid spread in the community. However, efforts to define the contributions of point mutations and indels have been confounded by strong linkage disequilibrium resulting from clonal propagation. To break down this confounding effect, we combined genetic association testing with a model of the transcriptional regulatory network (TRN) to find candidate mutations that may have led to changes in gene regulation. First, we used a De Bruijn graph genome-wide association study (DBGWAS) to enrich mutations unique to the USA300 lineages within CC8. Next, we reconstructed the TRN by using Independent Component Analysis on 670 RNA sequencing samples from USA300 and non-USA300 CC8 strains which predicted several genes with strain-specific altered expression patterns. Examination of the regulatory region of one of the genes enriched by both approaches,isdH,revealed a 38 base pair deletion containing a Fur binding site and a conserved Single Nucleotide Polymorphism (SNP) which likely led to the altered expression levels in USA300 strains. Taken together, our results demonstrate the utility of reconstructed TRNs to address the limits of genetic approaches when studying emerging pathogenic strains.
Restriction site associated DNA sequencing for tumour mutation burden estimation and mutation signature analysis
Authors: McGuinness Conor F , Black Michael A , Dunbier Anita K 
Published: July 2023

AbstractGenome-wide measures of genetic disruption such as tumour mutation burden (TMB) and mutation signatures are emerging as useful biomarkers to stratify patients for treatment. Clinicians commonly use cancer gene panels for tumour mutation burden estimation, and whole genome sequencing is the gold standard for mutation signature analysis. However, the accuracy and cost associated with these assays limits their utility at scale. Usingin silicolibrary simulations we demonstrate that restriction enzyme associated DNA sequencing (RADseq) may be a cost-effective solution to improve accuracy of TMB estimation and derivation of mutation profiles when compared to a derived FDA approved cancer gene panel TMB score. Using simulated immune checkpoint blockade (ICB) trials, we show that inaccurate tumour mutation burden estimation leads to a reduction in power for deriving an optimal TMB cutoff to stratify patients for immune checkpoint blockade treatment. Additionally, prioritisation of APOBEC hypermutated tumours in these trials optimises TMB cutoff determination for breast cancer. Finally, the utility of RADseq in an experimental setting is also demonstrated, based on characterisation of an APOBEC mutation signature in anAPOBEC3Atransfected mouse cell line. In conclusion, our work demonstrates that RADseq has the potential to be used as a cost-effective, accurate solution for TMB estimation and mutation signature analysis by both clinicians and basic researchers.
Multiscale modelling of chromatin 4D organization in SARS-CoV-2 infected cells
Authors: Chiariello Andrea M. , Abraham Alex , Bianco Simona , Esposito Andrea , Vercellone Francesca , Conte Mattia , Fontana Andrea , Nicodemi Mario 
Published: July 2023

AbstractSARS-CoV-2 is able to re-structure chromatin organization and alters the epigenomic landscape of the host genome, though the mechanisms that produce such changes are still poorly understood. Here, we investigate with polymer physics chromatin re-organization of the host genome, in space and time upon SARS-CoV-2 viral infection. We show that re-structuring of A/B compartments is well explained by a re-modulation of intra-compartment homotypic affinities, which leads to the weakening of A-A interactions and enhances A-B mixing. At TAD level, re-arrangements are physically described by a general reduction of the loop extrusion activity coupled with an alteration of chromatin phase-separation properties, resulting in more intermingling between different TADs and spread in space of TADs themselves. In addition, the architecture of loci relevant to the antiviral interferon (IFN) response, such as DDX58 or IFIT, results more variable within the 3D single-molecule population of the infected model, suggesting that viral infection leads to a loss of chromatin structural specificity. Analysis of time trajectories of pairwise gene-enhancer and higher-order contacts reveals that such variability derives from a more fluctuating dynamics in infected case, suggesting that SARS-CoV-2 alters gene regulation by impacting the stability of the contact network in time.Overall, our study provides the first polymer-physics based 4D reconstruction of SARS-CoV-2 infected genome with mechanistic insights on the consequent gene mis-regulation.
Hypoxia-sensing by the Histone Demethylase UTX (KDM6A) Controls Colitogenic CD4+T cell Fate and Mucosal Inflammation
Authors: Cheng Mandy I. , Hong Lee , Chen Bryan , Chin Scott , Luthers Christopher R. , Bustillos Christian , Sheikh Shehzad Z. , Su Maureen A. 
Published: July 2023

AbstractHypoxia is a feature of inflammatory conditions [e.g., inflammatory bowel disease (IBD)] and can exacerbate tissue damage in these diseases. To counteract hypoxia’s deleterious effects, adaptive responses have evolved which protect against hypoxia-associated tissue injury. To date, much attention has focused on hypoxia-activated HIF (hypoxia-inducible factor) transcription factors in these responses. However, recent work has identified epigenetic regulators that are also oxygen-sensitive, but their role in adaptation to hypoxic inflammation is currently unclear. Here, we show that the oxygen-sensing epigenetic regulator UTX is a critical modulator of colitis severity. Unlike HIF transcription factors that act on gut epithelial cells, UTX functions in colitis through its effects on immune cells. Hypoxia results in decreased CD4+T cell IFN-γ production and increased CD4+regulatory T cells, and these findings are recapitulated by T cell-specific UTX deficiency. Hypoxia impairs the histone demethylase activity of UTX, and loss of UTX function leads to accumulation of repressive H3K27me3 epigenetic marks at IL12/STAT4 pathway genes (Il12rb2, Tbx21,andIfng). In a colitis mouse model, T cell-specific UTX deletion ameliorates colonic inflammation, protects against weight loss, and increases survival. Together these findings implicate UTX’s oxygen-sensitive histone demethylase activity in mediating protective, hypoxia-induced pathways in colitis.
Splam: a deep-learning-based splice site predictor that improves spliced alignments
Authors: Chao Kuan-Hao , Mao Alan , Salzberg Steven L , Pertea Mihaela 
Published: July 2023

AbstractThe process of splicing messenger RNA to remove introns plays a central role in creating genes and gene variants. Here we describe Splam, a novel method for predicting splice junctions in DNA based on deep residual convolutional neural networks. Unlike some previous models, Splam looks at a relatively limited window of 400 base pairs flanking each splice site, motivated by the observation that the biological process of splicing relies primarily on signals within this window. Additionally, Splam introduces the idea of training the network on donor and acceptor pairs together, based on the principle that the splicing machinery recognizes both ends of each intron at once. We compare Splam’s accuracy to recent state-of-the-art splice site prediction methods, particularly SpliceAI, another method that uses deep neural networks. Our results show that Splam is consistently more accurate than SpliceAI, with an overall accuracy of 96% at predicting human splice junctions. Splam generalizes even to non-human species, including distant ones like the flowering plantArabidopsis thaliana. Finally, we demonstrate the use of Splam on a novel application: processing the spliced alignments of RNA-seq data to identify and eliminate errors. We show that when used in this manner, Splam yields substantial improvements in the accuracy of downstream transcriptome analysis of both poly(A) and ribo-depleted RNA-seq libraries. Overall, Splam offers a faster and more accurate approach to detecting splice junctions, while also providing a reliable and efficient solution for cleaning up erroneous spliced alignments.
Use of linear features by red-legged partridges in an intensive agricultural landscape: implications for landscape management in farmland
Authors: Perrot Charlotte , Séranne Léo , Berceaux Antoine , Noel Mathias , Arroyo Beatriz , Bacon Léo 
Published: July 2023

AbstractCurrent agricultural practices and change are the major cause of biodiversity loss. An important change associated with the intensification of agriculture in the last 50 years is the spatial homogenization of the landscape with substantial loss of such biodiversity-rich elements as seminatural linear features (hedgerows, field margins, grassy strips, etc.). In Europe, some management prescriptions serve to increase heterogeneity by the creation of these seminatural linear features which are not being used primarily for agricultural production. However, these elements are not equal in their support for biodiversity according to their structure and composition. The aim of this study is to determine the importance of landscape heterogeneity and specifically linear features on the spatial distribution of red-legged partridges, a small game species in decline in Europe. Through GPS-monitoring of adult birds, we first assess home range size throughout the year and during the breeding season, in relation to breeding status and to linear features (seminatural linear vegetation and tracks-roads for human traffic) density. Then, we focus on habitat selection during the breeding period in relation to linear features. We found that linear elements shape the use of space by red-legged partridges according to their reproductive status. Traffic routes and seminatural features structured by both herbaceous and woody cover, negatively influenced home range size. Further, breeding birds select linear elements with herbaceous cover while non-breeders select linear elements with woody cover, underlining the different needs of birds according to their breeding status. All birds selected areas near tracks, but non-breeders seemed to avoid roads. This study shows the importance for this species of the linear components that structure the agricultural landscape. We propose recommendations to promote the presence of the red-legged partridge in this agricultural environment but also of the biodiversity in general.
Context-Dependent Design of Induced-fit Enzymes using Deep Learning Generates Well Expressed, Thermally Stable and Active Enzymes
Authors: Zimmerman Lior , Alon Noga , Levin Itay , Koganitsky Anna , Shpigel Nufar , Brestel Chen , Lapidoth Gideon D. 
Published: July 2023

AbstractThe potential of engineered enzymes in practical applications is often constrained by limitations in their expression levels, thermal stability, and the diversity and magnitude of catalytic activities.De-novoenzyme design, though exciting, is challenged by the complex nature of enzymatic catalysis. An alternative promising approach involves expanding the capabilities of existing natural enzymes to enable functionality across new substrates and operational parameters. To this end we introduce CoSaNN (Conformation Sampling using Neural Network), a novel strategy for enzyme design that utilizes advances in deep learning for structure prediction and sequence optimization. By controlling enzyme conformations, we can expand the chemical space beyond the reach of simple mutagenesis. CoSaNN uses a context-dependent approach that accurately generates novel enzyme designs by considering non-linear relationships in both sequence and structure space. Additionally, we have further developed SolvIT, a graph neural network trained to predict protein solubility inE.Coli, as an additional optimization layer for producing highly expressed enzymes. Through this approach, we have engineered novel enzymes exhibiting superior expression levels, with 54% of our designs expressed in E.Coli, and increased thermal stability with more than 30% of our designs having a higher Tm than the template enzyme. Furthermore, our research underscores the transformative potential of AI in protein design, adeptly capturing high order interactions and preserving allosteric mechanisms in extensively modified enzymes. These advancements pave the way for the creation of diverse, functional, and robust enzymes, thereby opening new avenues for targeted biotechnological applications.
Structural mapping of patient-associatedKCNMA1gene variants
Authors: Moldenhauer Hans J. , Tammen Kelly , Meredith Andrea L. 
Published: July 2023

AbstractKCNMA1-linked channelopathy is a neurological disorder characterized by seizures, motor abnormalities, and neurodevelopmental disabilities. The disease mechanisms are predicted to result from alterations inKCNMA1-encoded BK K+channel activity; however, only a subset of the patient-associated variants have been functionally studied. The localization of these variants within the tertiary structure or evaluation by pathogenicity algorithms has not been systematically assessed. In this study, 82 nonsynonymous patient-associatedKCNMA1variants were mapped within the BK channel protein. Fifty-three variants localized within cryo-EM resolved structures, including 21 classified as either gain-of-function (GOF) or loss-of-function (LOF) in BK channel activity. Clusters of LOF variants were identified in the pore, the AC region (RCK1), and near the Ca2+bowl (RCK2), overlapping with sites of pharmacological or endogenous modulation. However, no clustering was found for GOF variants. To further understand variants of uncertain significance (VUS), assessments by multiple standard pathogenicity algorithms were compared, and new thresholds for sensitivity and specificity were established from confirmed GOF and LOF variants. An ensemble algorithm was constructed (KCNMA1 Meta Score), consisting of a weighted summation of this trained dataset combined with a structural component derived from the Ca2+bound and unbound BK channels. KMS assessment differed from the highest performing individual algorithm (REVEL) at 10 VUS residues, and a subset were studied further by electrophysiology in HEK293 cells. M578T, E656A, and D965V (KMS+;REVEL-) were confirmed to alter BK channel properties in voltage-clamp recordings, and D800Y (KMS-;REVEL+) was assessed as benign under the test conditions. However, KMS failed to accurately assess K457E. These combined results reveal the distribution of potentially disease-causingKCNMA1variants within BK channel functional domains and pathogenicity evaluation for VUS, suggesting strategies for improving channel-level predictions in future studies by building on ensemble algorithms such as KMS.
TGF-β broadly modifies rather than specifically suppresses reactivated memory CD8 T cells in a dose-dependent manner
Authors: Taber Alexis , Konecny Andrew , Scott-Browne James , Prlic Martin 
Published: July 2023

SummaryTransforming growth factor β (TGF-β) directly acts on naïve, effector and memory T cells to control cell fate decisions, which was shown using genetic abrogation of TGF-β signaling. TGF-β availability is altered by infections and cancer, however the dose-dependent effects of TGF-β on memory CD8 T cell (Tmem) reactivation are still poorly defined. We examined how activation and TGF-β signals interact to shape the functional outcome of Tmemreactivation. We found that TGF-β could suppress cytotoxicity in a manner that was inversely proportional to the strength of the activating TCR or pro-inflammatory signals. In contrast, even high doses of TGF-β had a comparatively modest effect on IFN-γ expression in the context of weak and strong reactivation signals. Since CD8 Tmemmay not always receive TGF-β signals concurrently with reactivation, we also explored whether the temporal order of reactivation versus TGF-β signals is of importance. We found that exposure to TGF-β prior to as well as after an activation event were both sufficient to reduce cytotoxic effector function. Concurrent ATAC-seq and RNA-seq analysis revealed that TGF-β altered ∼10% of the regulatory elements induced by reactivation and also elicited transcriptional changes indicative of broadly modulated functional properties. We confirmed some changes on the protein level and found that TGF-β-induced expression of CCR8 was inversely proportional to the strength of the reactivating TCR signal. Together, our data suggest that TGF-β is not simply suppressing CD8 Tmem, but modifies functional and chemotactic properties in context of their reactivation signals and in a dose-dependent manner.
Chemogenetic manipulation of endogenous proteins in fission yeast using a self-localizing ligand-induced protein translocation (SLIPT) system
Authors: Nakamura Akinobu , Goto Yuhei , Sugiyama Hironori , Tsukiji Shinya , Aoki Kazuhiro 
Published: July 2023

AbstractCells sense extracellular stimuli through membrane receptors and process the information through an intracellular signaling network. Protein translocation triggers intracellular signaling, and techniques such as chemically induced dimerization (CID) have been used to manipulate signaling pathways by altering the subcellular localization of signaling molecules. However, in the fission yeastSchizosaccharomyces pombe, the commonly used FKBP-FRB system has technical limitations, and therefore perturbation tools with low cytotoxicity and high temporal resolution are needed. We here applied our recently developed self-localizing ligand-induced protein translocation (SLIPT) system toS. pombeand successfully perturbed several cell cycle-related proteins. The SLIPT system utilizes self-localizing ligands to recruit binding partners to specific subcellular compartments, such as the plasma membrane or nucleus. We optimzed the self-localizing ligands to maintain long-term recruitment of target molecules to the plasma membrane. By knocking in genes encoding the binding partners for self-localizing ligands, we observed changes in the localization of several endogenous molecules and found perturbations in the cell cycle and associated phenotypes. This study demonstrates the effectiveness of the SLIPT system as a chemogenetic tool for rapid perturbation of endogenous molecules inS. pombe, providing a valuable approach for studying intracellular signaling and cell cycle regulation with improved temporal resolution.
Inhibition of the YAP-MMB interaction and targeting NEK2 as potential therapeutic strategies for YAP-driven cancers
Authors: Jessen Marco , Gertzmann Dörthe , Liss Franziska , Zenk Franziska , Bähner Laura , Schöffler Victoria , Ade Carsten P. , von Eyss Björn , Gaubatz Stefan 
Published: July 2023

ABSTRACTYAP activation in cancer is linked to poor outcomes, making it an attractive therapeutic target. Previous research focused on blocking the interaction of YAP with TEAD transcription factors. Here, we took a different approach by disrupting YAP’s binding to the transcription factor B-MYB using MY-COMP, a fragment of B-MYB containing the YAP binding domain fused to a nuclear localization signal. MY-COMP induced cell cycle defects, nuclear abnormalities, and polyploidization. In an AKT and YAP-driven liver cancer model, MY-COMP significantly reduced liver tumorigenesis, highlighting the importance of the YAP-B-MYB interaction in tumor development. MY-COMP also perturbed the cell cycle progression of YAP-dependent uveal melanoma cells but not of YAP-independent cutaneous melanoma cell lines. It counteracted YAP-dependent expression of MMB-regulated cell cycle genes, explaining the observed effects. We also identified NIMA-related kinase (NEK2) as a downstream target of YAP and B-MYB, promoting YAP-driven transformation by facilitating centrosome clustering and inhibiting multipolar mitosis.