bluuebunny/crossref_metadata_2025_split huggingface dataset:
A FRET biosensor, SMART, monitors necroptosis in renal tubular epithelial cells in a cisplatin-induced kidney injury model
Authors: Murai Shin , Takakura Kanako , Sumiyama Kenta , Moriwaki Kenta , Terai Kenta , Komazawa-Sakon Sachiko , Yamaguchi Yoshifumi , Mikami Tetuo , Araki Kimi , Ohmuraya Masaki , Matsuda Michiyuki , Nakano Hiroyasu 
Published: June 2022

AbstractNecroptosis is a regulated form of cell death involved in various pathological conditions, including ischemic reperfusion injuries, virus infections, and drug-induced tissue injuries. However, it is not fully understood when and where necroptosis occursin vivo. We previously generated a Forster resonance energy transfer (FRET) biosensor, termed SMART (the sensor for MLKL activation based on FRET), which specifically monitored necroptosis in human and murine cell linesin vitro. Here, we generated transgenic (Tg) mice that expressed the SMART biosensor in various tissues. SMART monitored necroptosis, but not apoptosis or pyroptosis, in primary cells, including peritoneal macrophages and embryonic fibroblasts. Moreover, the FRET signal was elevated in renal tubular cells of cisplatin-treated SMART Tg mice compared to untreated SMART Tg mice. Together, SMART Tg mice may provide a valuable tool for monitoring necroptosis in different types of cellsin vitroandin vivo.
Alterations of auditory sensory gating in mice with noise-induced tinnitus treated with nicotine and cannabis extract
Authors: Ciralli Barbara , Malfatti Thawann , Lima Thiago Z. , Silva Sérgio Ruschi B. , Cederroth Christopher R. , Leao Katarina E. 
Published: June 2022

AbstractTinnitus is a phantom sound perception affecting both auditory and limbic structures. The mechanisms of tinnitus remain unclear and it is debatable whether tinnitus alters attention to sound and the ability to inhibit repetitive sounds, a phenomenon also known as auditory gating. Here we investigate if noise exposure interferes with auditory gating and whether natural extracts of cannabis or nicotine could improve auditory pre-attentional processing in noise-exposed mice. We used 22 male C57BL/6J mice divided into noise-exposed (exposed to a 9-11 kHz narrow band noise for 1 hour) and sham (no sound during noise exposure) groups. Hearing thresholds were measured using auditory brainstem responses, and tinnitus-like behavior was assessed using Gap prepulse inhibition of acoustic startle. After noise exposure, mice were implanted with multi-electrodes in the dorsal hippocampus to assess auditory event-related potentials in response to paired clicks. The results showed that mice with tinnitus-like behavior displayed auditory gating of repetitive clicks, but with larger amplitudes and longer latencies of the N40 component of the aERP waveform. The combination of cannabis extract and nicotine improved auditory gating ratio in noise-exposed mice without permanent hearing threshold shifts. Lastly, the longer latency of the N40 component appears due to an increased sensitivity to cannabis extract in noise-exposed mice compared to sham mice. The study suggests that the altered central plasticity in tinnitus is more sensitive to the combined actions on the cholinergic and the endocannabinoid systems. Overall, the findings contribute to a better understanding of pharmacological modulation of auditory sensory gating.
PI3P dependent regulation of cell size and autophagy by phosphatidylinositol 5-phosphate 4-kinase
Authors: Ghosh Avishek , Venugopal Aishwarya , Shinde Dhananjay , Sharma Sanjeev , Krishnan Meera , Mathre Swarna , Krishnan Harini , Raghu Padinjat 
Published: June 2022

AbstractPhosphatidylinositol 3-phosphate (PI3P) and Phosphatidylinositol 5-phosphate (PI5P) are low abundant phosphoinositides crucial for key cellular events such as endosomal trafficking and autophagy. Phosphatidylinositol 5-phosphate 4-kinase (PIP4K) is an enzyme that regulates PI5P in vivo but can act on both PI5P and PI3P, in vitro. In this study, we report a novel role for PIP4K in regulating PI3P levels in Drosophila tissues. Loss-of-function mutants of the only PIP4K gene in Drosophila (dPIP4K29) show reduced cell size in larval salivary glands. We find that PI3P levels are elevated in dPIP4K29 tissues and that reverting PI3P levels back towards wild type, without changes in PI5P levels, can also rescue the reduced cell size phenotype. dPIP4K29 mutants also show an upregulation in autophagy and the reduced cell size can be reverted by decreasing Atg8a, that is required for autophagosome maturation. Lastly, increasing PI3P levels in wild type salivary glands can phenocopy the reduction in cell size and associated upregulation of autophagy seen in dPIP4K29. Thus, our study reports for the first time, a role for a PIP4K-regulated PI3P pool in the control of autophagy and cell size regulation that may explain the reported role of PIP4K in regulating neurodegeneration and tumour growth.
Antisense oligonucleotide therapy rescues disturbed brain rhythms and sleep in juvenile and adult mouse models of Angelman syndrome
Authors: Lee Dongwon , Chen Wu , Kaku Heet Naresh , Zhuo Xinming , Chao Eugene S. , Soriano Armand , Kuncheria Allen , Flores Stephanie , Kim Joo Hyun , Rigo Frank , Jafar-nejad Paymaan , Beaudet Arthur L. , Caudill Matthew S. , Xue Mingshan 
Published: June 2022

AbstractUBE3A encodes ubiquitin protein ligase E3A, and in neurons its expression from the paternal allele is repressed by the UBE3A antisense transcript (UBE3A-ATS). This leaves neurons susceptible to loss-of-function of maternal UBE3A. Indeed, Angelman syndrome, a severe neurodevelopmental disorder, is caused by maternal UBE3A deficiency. A promising therapeutic approach to treating Angelman syndrome is to reactivate the intact paternal UBE3A by suppressing UBE3A-ATS. Prior studies show that many neurological phenotypes of maternal Ube3a knockout mice can only be rescued by reinstating Ube3a expression in early development, indicating a restricted therapeutic window for Angelman syndrome. Here we report that reducing Ube3a-ATS by antisense oligonucleotides in juvenile or adult maternal Ube3a knockout mice rescues the abnormal electroencephalogram rhythms and sleep disturbance, two prominent clinical features of Angelman syndrome. Importantly, the degree of phenotypic improvement correlates with the increase of Ube3a protein levels. These results indicate that the therapeutic window of genetic therapies for Angelman syndrome is broader than previously thought, and electroencephalogram power spectrum and sleep architecture should be used to evaluate the clinical efficacy of therapies.
Pumping the brakes on RNA velocity – understanding and interpreting RNA velocity estimates
Authors: Zheng Shijie C. , Stein-O’Brien Genevieve , Boukas Leandros , Goff Loyal A. , Hansen Kasper D. 
Published: June 2022

ABSTRACTRNA velocity analysis of single cells promises to predict temporal dynamics from gene expression. Indeed, in many systems, it has been observed that RNA velocity produces a vector field that qualitatively reflects known features of the system. Despite this observation, the limitations of RNA velocity estimates are poorly understood. Using real data and simulations, we dissect the impact of different steps in the RNA velocity workflow on the estimated vector field. We find that the process of mapping RNA velocity estimates into a low-dimensional representation, such as those produced by UMAP, has a large impact on the result. The RNA velocity vector field strongly depends on the k-NN graph of the data. This dependence leads to significant estimator errors when the k-NN graph is not a faithful representation of the true data structure, a feature that cannot be known for most real datasets. Finally, we establish that RNA velocity estimates expression speed neither at the gene nor cellular level. We propose that RNA velocity is best considered a smoothed interpolation of the observed k-NN structure, as opposed to an extrapolation of future cellular states, and that the use of RNA velocity as a validation of latent space embedding structures is circular.
Strong pathogen competition in neonatal gut colonisation
Authors: Mäklin Tommi , Thorpe Harry A. , Pöntinen Anna K. , Gladstone Rebecca A. , Shao Yan , Pesonen Maiju , McNally Alan , Johnsen Pål J. , Samuelsen Ørjan , Lawley Trevor D. , Honkela Antti , Corander Jukka 
Published: June 2022

AbstractBacterial pathogen species and their strains that colonise the human gut are generally understood to compete against both each other and the commensal species colonising this ecosystem. However, currently we are lacking a population-wide quantification of strain-level colonisation dynamics for many common bacterial pathogens and the relationship of colonisation potential to prevalence in disease is unknown. In addition, it is unclear how ecological factors might be modulating the dynamics. Here, using a combination of latest high-resolution metagenomics and strain-level genomic epidemiology methods leveraging large genomic reference libraries of key pathogens, we performed a characterisation of the competition (co-exclusion and co-presence) and colonisation dynamics for a longitudinal cohort of neonatal gut microbiomes. We found a strong inter- and intra-species competition dynamic in the gut colonisation process, but also a number of synergistic relationships among several species belonging to genusKlebsiella, which includes the prominent human pathogenKlebsiella pneumoniae. Additionally, we find no evidence of preferential colonisation by hospital-adapted pathogen lineages in either vaginal or caesarean section birth groups. Our analysis also enables the first unbiased assessment of the strain-level colonisation potential of extra-intestinal pathogenicEscherichia coli(ExPEC) in comparison with their potential to cause bloodstream infections. We determined that the established common ExPEC clones ST73 and ST95 are overall significantly more pathogenic than the more recent, globally circulating multi-drug resistant clone ST131, where only a single subclone (ST131-C2) exhibited excess pathogenic potential. Our study highlights the importance of systematic surveillance of bacterial gut pathogens, not only from disease but also from carriage state, to better inform therapies and preventive medicine in the future.
Dynein dysfunction prevents maintenance of high concentrations of slow axonal transport cargos at the axon terminal: a computational study
Authors: Kuznetsov Ivan A. , Kuznetsov Andrey V. 
Published: June 2022

AbstractHere we report computational studies of bidirectional transport in an axon, specifically focusing on predictions when the retrograde motor becomes dysfunctional. We are motivated by reports that mutations in dynein-encoding genes can cause diseases associated with peripheral motor and sensory neurons, such as type 2O Charcot-Marie-Tooth disease. We use two different models to simulate bidirectional transport in an axon: an anterograde-retrograde model, which neglects passive transport by diffusion in the cytosol, and a full slow transport model, which includes passive transport by diffusion in the cytosol. As dynein is a retrograde motor, dysfunction should not directly influence anterograde transport. However, our modeling results unexpectedly predict that slow axonal transport fails to transport cargos against their concentration gradient without dynein. The reason is the lack of a physical mechanism for the reverse information flow from the axon terminal, which is required so that the cargo concentration at the terminal could influence the cargo concentration distribution in the axon. Mathematically speaking, to achieve a prescribed concentration at the terminal, equations governing cargo transport must allow for the imposition of a boundary condition postulating the cargo concentration at the terminal. Perturbation analysis for the case when the retrograde motor velocity becomes close to zero predicts uniform cargo distributions along the axon. The obtained results explain why slow axonal transport must be bidirectional to allow for the maintenance of concentration gradients along the axon length. Our result is limited to small cargo diffusivity, which is a reasonable assumption for many slow axonal transport cargos (such as cytosolic and cytoskeletal proteins, neurofilaments, actin, and microtubules) which are transported as large multiprotein complexes or polymers.
Flexible and efficient handling of nanopore sequencing signal data with slow5tools
Authors: Samarakoon Hiruna , Ferguson James M. , Jenner Sasha P. , Amos Timothy G. , Parameswaran Sri , Gamaarachchi Hasindu , Deveson Ira W. 
Published: June 2022

ABSTRACTBackgroundNanopore sequencing is an emerging technology that is being rapidly adopted in research and clinical genomics. We recently developed SLOW5, a new file format for storage and analysis of raw data from nanopore sequencing experiments. SLOW5 is a community-centric, open source format that offers considerable performance benefits over the existing nanopore data format, known as FAST5. Here we introduce slow5tools, a simple, intuitive toolkit for handling nanopore raw signal data in SLOW5 format.ResultsSlow5tools enables lossless FAST5-to-SLOW5 and SLOW5-to-FAST5 data conversion, and a range of tools for structuring, indexing, viewing and querying SLOW5 files. Slow5tools uses multi-threading, multi-processing and other engineering strategies to achieve fast data conversion and manipulation, including live FAST5-to-SLOW5 conversion during sequencing. We outline a series of examples and benchmarking experiments to illustrate slow5tools usage, and describe the engineering principles underpinning its high performance.ConclusionSlow5tools is an essential toolkit for handling nanopore signal data, which was developed to support adoption of SLOW5 by the nanopore community. Slow5tools is written in C/C++ with minimal dependencies and is freely available as an open-source program under an MIT licence: https://github.com/hasindu2008/slow5tools.
Prediction of inter-chain distance maps of protein complexes with 2D attention-based deep neural networks
Authors: Guo Zhiye , Liu Jian , Skolnick Jeffrey , Cheng Jianlin 
Published: June 2022

AbstractResidue-residue distance information is useful for predicting the tertiary structures of protein monomers or the quaternary structures of protein complexes. Many deep learning methods have been developed to predict intra-chain residue-residue distances of monomers accurately, but very few methods can accurately predict inter-chain residue-residue distances of protein complexes. We develop a new deep learning method CDPred (i.e., Complex Distance Prediction) based on the 2D attention-powered residual network architecture to address the gap. CDPred predicts the inter-chain distance maps of dimers (homodimers or heterodimers) from the features extracted from multiple sequence alignments (MSAs) and the intra-chain distance maps of predicted tertiary structures of monomers. Tested on two homodimer test datasets, CDPred achieves the precision of 61.56% and 43.26% for top L/5 inter-chain contact predictions (L: length of the monomer in homodimer), respectively, which is substantially higher than DeepHomo’s 37.40% and 23.08% and GLINTER’s 48.09% and 36.74%. And tested on the two heterodimer test datasets, the top L/5 inter-chain contact prediction precision (L: length of the shorter monomer in heterodimer) of CDPred is 47.59% and 22.87% respectively, which surpasses GLINTER’s 23.24% and 13.49%. Moreover, we demonstrate that the residue-residue co-evolutionary features calculated from multiple sequence alignments by a deep learning language model are more informative for the inter-chain contact prediction than the traditional statistical optimization approach of maximizing direct co-evolutionary signals, and large intra-chain distances in the intra-chain distance maps of monomers are more useful for the inter-chain distance prediction than small intra-chain distances.
One model fits all: combining inference and simulation of gene regulatory networks
Authors: Ventre Elias , Herbach Ulysse , Espinasse Thibault , Benoit Gérard , Gandrillon Olivier 
Published: June 2022

AbstractThe rise of single-cell data highlights the need for a nondeterministic view of gene expression, while offering new opportunities regarding gene regulatory network inference. We recently introduced two strategies that specifically exploit time-course data, where single-cell profiling is performed after a stimulus: HARISSA, a mechanistic network model with a highly efficient simulation procedure, and CARDAMOM, a scalable inference method seen as model calibration. Here, we combine the two approaches and show that the same model driven by transcriptional bursting can be used simultaneously as an inference tool, to reconstruct biologically relevant networks, and as a simulation tool, to generate realistic transcriptional profiles emerging from gene interactions. We verify that CARDAMOM quantitatively reconstructs causal links when the data is simulated from HARISSA, and demonstrate its performance on experimental data collected onin vitrodifferentiating mouse embryonic stem cells. Overall, this integrated strategy largely overcomes the limitations of disconnected inference and simulation.Author summaryGene regulatory network (GRN) inference is an old problem, to which single-cell data has recently offered new challenges and breakthrough potential. Many GRN inference methods based on single-cell transcriptomic data have been developed over the last few years, while GRN simulation tools have also been proposed for generating synthetic datasets with realistic features. However, except for benchmarking purposes, these two fields remain largely disconnected. In this work, building on a combination of two methods we recently described, we show that a particular GRN model can be used simultaneously as an inference tool, to reconstruct a biologically relevant network from time-course single-cell gene expression data, and as a simulation tool, to generate realistic transcriptional profiles in a non-trivial way through gene interactions. This integrated strategy demonstrates the benefits of using the same executable model for both simulation and inference.
Molecular interactions underlying the phase separation of HP1α: Role of phosphorylation, ligand and nucleic acid binding
Authors: Her Cheenou , Phan Tien M. , Jovic Nina , Kapoor Utkarsh , Ackermann Bryce E. , Rizuan Azamat , Kim Young , Mittal Jeetain , Debelouchina Galia T. 
Published: June 2022

AbstractHeterochromatin protein 1α (HP1α) is a crucial component for the proper maintenance of chromatin structure and function. It has been proposed that HP1α functions through liquid-liquid phase separation (LLPS), which allows it to sequester and compact chromatin into transcriptionally repressed heterochromatin regions. In vitro, HP1α can form phase separated liquid droplets upon phosphorylation of its N-terminus extension (NTE) and/or through interactions with DNA and chromatin. While it is known that LLPS requires homodimerization of HP1α and that it involves interactions between the positively charged hinge region of HP1α and the negatively charged phosphorylated NTE or nucleic acid, the precise molecular details of this process and its regulation are still unclear. Here, we combine computational modeling and experimental approaches to elucidate the phase separation properties of HP1α under phosphorylation-driven and DNA-driven LLPS conditions. We also tune these properties using peptides from four HP1α binding partners (Sgo1, CAF-1, LBR, and H3). In phosphorylation-driven LLPS, HP1α can exchange intradimer hinge-NTE interactions with interdimer contacts, which also leads to a structural change from a compacted to an extended HP1α dimer conformation. This process can be enhanced by the presence of positively charged peptide ligands such as Sgo1 and H3 and disrupted by the addition of negatively charged or neutral peptides such as LBR and CAF-1. In DNA-driven LLPS, both positively and negatively charged peptide ligands can perturb phase separation. Our findings demonstrate the importance of electrostatic interactions in the LLPS of HP1α where binding partners can modulate the overall charge of the droplets and screen or enhance hinge region interactions through specific and non-specific effects. Our study illuminates the complex molecular framework that can fine tune the properties of HP1α and that can contribute to heterochromatin regulation and function.
Components of TOR and MAP kinase signaling control chemotropism and pathogenicity in the fungal pathogen Verticillium dahliae
Authors: Vangalis Vasileios , Markakis Emmanouil A. , Knop Michael , Pietro Antonio Di , Typas Milton A. , Papaioannou Ioannis A. 
Published: June 2022

ABSTRACTFilamentous fungi can sense useful resources and hazards in their environment and direct growth of their hyphae accordingly. Chemotropism ensures access to nutrients, contact with other individuals (e.g., for mating), and interaction with hosts in the case of pathogens. Previous studies have revealed a complex chemotropic sensing landscape during host-pathogen interactions, but the underlying molecular machinery remains poorly characterized. Here we studied mechanisms controlling directed hyphal growth of the important plant-pathogenic fungus Verticillium dahliae towards different chemoattractants. We found that the homologs of the Rag GTPase Gtr1 and the GTPase-activating protein Tsc2, an activator and a repressor of the TOR kinase respectively, play important roles in hyphal chemotropism towards nutrients, plant-derived signals, and heterologous α-pheromone of Fusarium oxysporum. Furthermore, important roles of these regulators were identified in fungal development and pathogenicity. We also found that the mitogen-activated protein kinase (MAPK) Fus3 is required for chemotropism towards nutrients, while the G protein-coupled receptor (GPCR) Ste2 and the MAPK Slt2 control chemosensing of plant-derived signals and α-pheromone. Our study establishes V. dahliae as a suitable model for the analysis of fungal chemotropism and discovers new components of chemotropic signaling, during growth and host-pathogen interactions of V. dahliae.
Precise Transcript Targeting by CRISPR-Csm Complexes
Authors: Colognori David , Trinidad Marena , Doudna Jennifer A. 
Published: June 2022

ABSTRACTRobust and precise transcript targeting in mammalian cells remains a difficult challenge using existing approaches due to inefficiency, imprecision, and subcellular compartmentalization. Here, we show that the CRISPR-Csm complex, a multi-protein effector from type III CRISPR immune systems in prokaryotes, provides surgical RNA ablation of both nuclear and cytoplasmic transcripts. As part of the most widely occurring CRISPR adaptive immunity pathway, CRISPR-Csm uses a programmable RNA-guided mechanism to find and degrade target RNA molecules without inducing indiscriminate trans-cleavage of cellular RNAs, giving it an important advantage over the CRISPR-Cas13-family enzymes. Using single-vector delivery of the S. thermophilus Csm complex, we observe high-efficiency RNA knockdown (90-99%) and minimal off-target effects in human cells, outperforming existing technologies including shRNA- and Cas13-mediated knockdown. We also find that catalytically inactivated Csm achieves specific and durable RNA binding, a property we harness for live-cell RNA imaging. These results establish the feasibility and efficacy of multi-protein CRISPR-Cas effector complexes as RNA-targeting tools in eukaryotes.