bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patterning of membrane adhesion under hydraulic stress
Authors: Dinet Céline , Torres-Sánchez Alejandro , Arroyo Marino , Staykova Margarita 
Published: January 2023

AbstractHydraulic fracturing plays a major role in the formation of biological lumens during embryonic development, when the accumulation of pressurized fluid leads to the formation of microlumens that fracture cell-cell contacts and later evolve to form a single large lumen. However, the physical principles underpinning the formation of a pattern of microlumens from a pristine adhesion and their subsequent coarsening are poorly understood. Here, we use giant unilamellar vesicles adhered to a supported lipid bilayer and subjected to osmotic stress to generate and follow the dynamics of hydraulic fracturing akin to those in cells. Using this simplified system together with theoretical modelling and numerical simulations, we provide a mechanistic understanding of the nucleation of hydraulic cracks, their spatial patterns and their coarsening dynamics. Besides coarsening, we show that microlumens can irreversibly bud out of the membrane, reminiscent of endocytic vesicles in cell-cell adhesion. By establishing the physics of patterning and dynamics of hydraulic cracks, our work unveils the mechanical constraints for the biological regulation of hydraulically-driven adhesion remodeling.
Reconstruction of 3-dimensional tissue organization at the single-cell resolution
Authors: Fu Yuheng , Das Arpan , Wang Dongmei , Braun Rosemary , Yi Rui 
Published: January 2023

AbstractRecent advances in spatial transcriptomics (ST) have allowed for the mapping of tissue heterogeneity, but this technique lacks the resolution to investigate gene expression patterns, cell-cell communications and tissue organization at the single-cell resolution. ST data contains a mixed transcriptome from multiple heterogeneous cells, and current methods predict two-dimensional (2D) coordinates for individual cells within a predetermined space, making it difficult to reconstruct and study three-dimensional (3D) tissue organization. Here we present a new computational method called scHolography that uses deep learning to map single-cell transcriptome data to 3D space. Unlike existing methods, which generate a projection between transcriptome data and 2D spatial coordinates, scHolography uses neural networks to create a high-dimensional transcriptome-to-space map that preserves the distance information between cells, allowing for the construction of a cell-cell proximity matrix beyond the 2D ST scaffold. Furthermore, the neighboring cell profile of a given cell type can be extracted to study spatial cell heterogeneity. We apply scHolography to human skin, human skin cancer and mouse brain datasets, providing new insights into gene expression patterns, cell-cell interactions and spatial microenvironment. Together, scHolography offers a computational solution for digitizing transcriptome and spatial information into high-dimensional data for neural network-based mapping and the reconstruction of 3D tissue organization at the single-cell resolution.
IL-15 enhances functional properties and responses of cytotoxic CD4+CD28−T cells expanded in Systemic lupus erythematosus
Authors: Wang Tingting , Wei Laiyou , Meng Shuihui , Song Wencong , Chen Yulan , Li Heng , Zhao Qianqian , Jiang Zhenyou , Liu Dongzhou , Ren Huan , Hong Xiaoping 
Published: January 2023

AbstractSystemic lupus erythematosus (SLE) is an autoimmune disorder that results in an attack by body’s immune system of its own tissues, causing chronic inflammation and tissue damage. T cells play a key role in the pathogenesis of SLE, as they secrete pro-inflammatory cytokines as well as mediate direct effects on target tissues. Recently, CD4-positive T cells with cytotoxic potential were showed to be involved in autoimmune disease progression and tissue damage. However, whether this cell type expands and plays effector functions in SLE patients remain to be elucidated. Analyzing single-cell RNA sequencing (scRNA-Seq) data and flow cytometry data, we find that cytotoxic CD4+CD28−T cells are present in SLE patients. We also show that these cells expand most prominently in patients affected by lupus nephritis, and they exhibit cytotoxic activity against human renal glomerular endothelial cells in vitro. In addition, our study suggests that Interleukin-15 (IL-15) promotes the expansion, proliferation and cytotoxic function of CD4+CD28−T cells in SLE patients. Tofacitinib, a selective JAK3 inhibitor, inhibits the effect of IL-15 on CD4+CD28−T cells. Together, our study clearly demonstrated that CD4+CD28−T cells characterized by proinflammatory properties and cytolytic function expand in SLE patients. The pathogenic potential of these CD4+CD28−T cells is driven by IL-15/IL-15R/JAK3/STAT5 signaling pathway, which may open new avenues for therapeutic intervention to prevent progression of SLE patients.
Detailedin vivocharacterization of the players and impact of individual loop extrusion trajectories
Authors: Han Ruiqi , Huang Yike , Robers Michelle , Magnitov Mikhail , Vaandrager Iwan , Allahyar Amin , Verstegen Marjon J.A.M. , Zhang Kexin , de Wit Elzo , de Laat Wouter , Krijger Peter H.L. 
Published: January 2023

AbstractThe cohesin complex shapes chromosomes by DNA loop extrusion, but individual extrusion trajectories were so far unappreciablein vivo. Here, we developed and validated TArgeted Cohesin Loader (TACL), a system enabling the strong activation of anchored loop extrusion from dozens of defined genomic sites in living cells. Studying their individual loop extrusion trajectories revealed that extruding cohesinSTAG2stops not only at domain boundaries but at all flanking CTCF sites, engaging them in a complex transient looping network that supports intradomain contacts. CohesinSTAG1cannot associate with weak CTCF binding sites and fails to similarly support intradomain interactions. NIPBL-MAU2 remains associated with cohesin when stalled at looping CTCF sites, suggesting these factors may also be required for loop stabilization. TACL induces cohesin traffic jams and illegal loops with divergent CTCF sites, demonstrating that stalled cohesin can block extruding cohesinin vivo. Genes exposed to TACL-induced loop extrusion were collectively hindered in transcription and the underlying chromatin altered its accessibility and reduced its H3K27ac marks. Thus, by enabling the study of individual loop extrusion trajectoriesin vivo,we could assign new functions to players, identify new looping networks and uncover an interplay between loop extrusion, gene transcription and chromatin composition.
Unravelling cell type specific response to Parkinson’s Disease at single cell resolution
Authors: Martirosyan Araks , Pestana Francisco , Hebestreit Katja , Gasparyan Hayk , Aleksanyan Razmik , Poovathingal Suresh , Marneffe Catherine , Thal Dietmar R. , Kottick Andrew , Hanson-Smith Victor , Guelfi Sebastian , Metzakopian Emmanouil , Belgard T. Grant 
Published: January 2023

AbstractParkinson’s Disease (PD) is the second most common neurodegenerative disorder and is generally characterized by impaired motor functions. It currently affects 6.3 million people aged 60 years and more, worldwide. The pathological hallmarks of PD are Lewy bodies (abnormal aggregation of α-synuclein inside cells), which are observed primarily in the substantia nigra (SN) region of the midbrain. It is yet not known how different cell types in SN respond during PD and what are the molecular mechanisms underlying neurodegeneration. To address this question, we generated a large-scale single cell transcriptomics dataset from human post-mortem SN tissue of 29 donors including 15 sporadic cases and 14 controls. We obtained data for a total of ∼80K nuclei, representing major cell types of the brain (including neurons, astrocytes, microglia and oligodendrocytes). Pathway and differential gene expression analysis revealed multicellular character of PD pathology involving major cellular response from neuronal and glial cells.
MuLan-Methyl - Multiple Transformer-based Language Models for Accurate DNA Methylation Prediction
Authors: Zeng Wenhuan , Gautam Anupam , Huson Daniel H. 
Published: January 2023

AbstractTransformer-based language models are successfully used to address massive text-related tasks. DNA methylation is an important epigenetic mechanism and its analysis provides valuable insights into gene regulation and biomarker identification. Several deep learning-based methods have been proposed to identify DNA methylation and each seeks to strike a balance between computational effort and accuracy. Here, we introduce MuLan-Methyl, a deep-learning framework for predicting DNA methylation sites, which is based on five popular transformer-based language models. The framework identifies methylation sites for three different types of DNA methylation, namely N6-adenine, N4-cytosine, and 5-hydroxymethylcytosine. Each of the employed language models is adapted to the task using the “pre-train and fine-tune” paradigm. Pre-training is performed on a custom corpus of DNA fragments and taxonomy lineages using self-supervised learning. Fine-tuning aims at predicting the DNA-methylation status of each type. The five models are used to collectively predict the DNA methylation status. We report excellent performance of MuLan-Methyl on a benchmark dataset. Moreover, we argue that the model captures characteristic differences between different species that are relevant for methylation. This work demonstrates that language models can be successfully adapted to applications in biological sequence analysis and that joint utilization of different language models improves model performance. Mulan-Methyl is open source and we provide a web server that implements the approach.Key pointsMuLan-Methyl aims at identifying three types of DNA-methylation sites.It uses an ensemble of five transformer-based language models, which were pre-trained and fine-tuned on a custom corpus.The self-attention mechanism of transformers give rise to importance scores, which can be used to extract motifs.The method performs favorably in comparison to existing methods.The implementation can be applied to chromosomal sequences to predict methylation sites.
A model forcis-regulation of transcriptional condensates and gene expression by proximal lncRNAs
Authors: Natarajan Pradeep , Shrinivas Krishna , Chakraborty Arup K. 
Published: January 2023

ABSTRACTLong non-coding RNAs (lncRNAs) perform several important functions in cells including cis-regulation of transcription. Barring a few specific cases, the mechanisms underlying transcriptional regulation by lncRNAs remain poorly understood. Transcriptional proteins can form condensates via phase separation at protein-binding loci (BL) on the genome (e.g., enhancers and promoters). lncRNA-coding genes are present at loci in close genomic proximity of these BL and these RNAs can interact with transcriptional proteins via attractive heterotypic interactions mediated by their net charge. Motivated by these observations, we propose that lncRNAs can dynamically regulate transcription in cis via charge-based heterotypic interactions with transcriptional proteins in condensates. To study the consequences of this mechanism, we developed and studied a dynamical phase-field model. We find that proximal lncRNAs can promote condensate formation at the BL. Vicinally localized lncRNA can migrate to the BL to attract more protein because of favorable interaction free energies. However, increasing the distance beyond a threshold leads to a sharp decrease in protein recruitment to the BL. This finding could potentially explain why genomic distances between lncRNA-coding genes and protein-coding genes are conserved across metazoans. Finally, our model predicts that lncRNA transcription can fine-tune transcription from neighboring condensate-controlled genes, repressing transcription from highly expressed genes and enhancing transcription of genes expressed at a low level. This non-equilibrium effect can reconcile conflicting reports that lncRNAs can enhance or repress transcription from proximal genes.SIGNIFICANCELong non-coding RNAs (lncRNAs) form a significant part of the human genome but do not code for any proteins. They have many hypothesized functions in the cell, including the regulation of transcription. Transcriptional condensates are assemblies of transcriptional proteins that concentrate at specific genomic sites through phase separation and can regulate transcription. In this study, we propose that lncRNAs can regulate transcription by interacting with proteins in transcriptional condensates to modulate condensate formation. We find that this model can explain some puzzling observations such as conflicting reports of gene activation and repression by lncRNAs, and conservation of genomic distances between lncRNA-coding genes relative to protein-coding genes in metazoans. Experimentally testable predictions that can further explore our model are discussed.
Organometallic Pillarplexes that bind DNA 4-way Holliday Junctions and Forks
Authors: Craig James S. , Melidis Larry , Williams Hugo D. , Dettmer Samuel J. , Heidecker Alexandra A. , Altmann Philipp J. , Guan Shengyang , Campbell Callum , Browning Douglas F. , Sigel Roland K.O. , Johannsen Silke , Egan Ross T. , Aikman Brech , Casini Angela , Pöthig Alexander , Hannon Michael J. 
Published: January 2023

ABSTRACTHolliday 4-way junctions are key to important biological DNA processes (insertion, recombination and repair) and are dynamic structures which adopt either open or closed conformations, with the open conformation being the biologically active form. Tetracationic metallo-supramolecular pillarplexes display aryl faces about a cylindrical core giving them an ideal structure to interact with the central cavities of open DNA junctions. Combining experimental studies and MD simulations we show that an Au pillarplex can bind DNA 4-way junctions (Holliday junctions) in their open form, a binding mode not accessed by synthetic agents before. The Au pillarplexes can bind designed 3-way junctions too but their large size leads them to open up and expand that junction, disrupting the base pairing which manifests in an increase in hydrodynamic size and a lower junction thermal stability. At high loading they re-arrange both 4-way and 3-way junctions into Y-shaped DNA forks to increase the available junction-like binding sites. The structurally related Ag pillarplexes show similar DNA junction binding behaviour, but a lower solution stability. This pillarplex binding contrasts with (but complements) that of the metallo-supramolecular cylinders, which prefer 3-way junctions and we show can rearrange 4-way junctions into 3-way junction structures. The pillarplexes’ ability to bind open 4-way junctions creates exciting possibilities to modulate and switch such structures in biology, as well as in synthetic nucleic acid nanostructures where they are key interconnecting components. Studies in human cells, confirm that the pillarplexes do reach the nucleus, with antiproliferative activity at levels similar to those of cisplatin. The findings provide a new roadmap for targeting higher order junction structures using a metallo-supramolecular approach, as well as expanding the toolbox available to design bioactive junction-binders into organometallic chemistry.Abstract Figure
Integrative proteogenomics using ProteomeGenerator2
Authors: Kwok Nathaniel , Aretz Zita , Takao Sumiko , Ser Zheng , Cifani Paolo , Kentsis Alex 
Published: January 2023

AbstractRecent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and proteins sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as non-canonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source fromhttps://github.com/kentsisresearchgroup/ProteomeGenerator2.
ElasticBLAST: Accelerating Sequence Search via Cloud Computing
Authors: Camacho Christiam , Boratyn Grzegorz M. , Joukov Victor , Alvarez Roberto Vera , Madden Thomas L. 
Published: January 2023

ABSTRACTBackgroundBiomedical researchers use alignments produced by BLAST (Basic Local Alignment Search Tool) to categorize their query sequences. Producing such alignments is an essential bioinformatics task that is well suited for the cloud. The cloud can perform many calculations quickly as well as store and access large volumes of data. Bioinformaticians can also use it to collaborate with other researchers, sharing their results, datasets and even their pipelines on a common platform.ResultsWe present ElasticBLAST, a cloud native application to perform BLAST alignments in the cloud. ElasticBLAST can handle anywhere from a few to many thousands of queries and run the searches on thousands of virtual CPUs (if desired), deleting resources when it is done. It uses cloud native tools for orchestration and can request discounted instances, lowering cloud costs for users. It is supported on Amazon Web Services and Google Cloud Platform. It can search BLAST databases that are user provided or from the National Center for Biotechnology Information.ConclusionWe show that ElasticBLAST is a useful application that can efficiently perform BLAST searches for the user in the cloud, demonstrating that with two examples. At the same time, it hides much of the complexity of working in the cloud, lowering the threshold to move work to the cloud.
Coordinated electrical and chemical signaling between two neurons orchestrates switching of motor states
Authors: Bach Maximilian , Bergs Amelie , Mulcahy Ben , Zhen Mei , Gottschalk Alexander 
Published: January 2023

SummaryTo survive in a complex environment, animals must respond to external cues, e.g., to escape threats or to navigate towards favorable locations. Navigating requires transition between motor states, e.g. switching from forward to backward movement. Here, we investigated how two classes of interneurons, RIS and RIM, fine-tune this transition in the nematodeC. elegans. By Ca2+imaging in freely moving animals, we found that RIS gets active slightly before RIM and likely biases decision-making towards a reversal. In animals lacking RIS, we observed lowered Ca2+-levels in RIM prior to a reversal. Combined photo-stimulation and voltage imaging revealed that FLP-11, a neuropeptide released by RIS, has an excitatory effect on RIM, while tyramine, released from RIM, inhibits RIS. Voltage imaging of intrinsic activity provided evidence for tight electrical coupling between RIS and RIM via gap junctions harboring UNC-7 innexins. Asymmetric junctional current flow was observed from RIS to RIM, and vice versa. We propose that the interplay of RIS and RIM is based on concerted electrical and chemical signaling, with a fast junctional current exchange early during the transition from forward to backward movement, followed by chemical signaling, likely during reversal execution.
Reciprocating RNA Polymerase batters through roadblocks
Authors: Qian Jin , Cartee Allison , Xu Wenxuan , Yan Yan , Wang Bing , Artsimovitch Irina , Dunlap David , Finzi Laura 
Published: January 2023

AbstractRNA polymerases (RNAPs) must transit through protein roadblocks to produce full-length RNAs. Here we report real-time measurements ofEscherichia coli(E. coli) RNAP passage through different barriers. As intuitively expected, assisting forces facilitated, and opposing forces hindered, RNAP passage through LacI bound to natural operator sites. Force-dependent differences were significant at magnitudes as low as 0.2 pN and were abolished in the presence of GreA, which rescues backtracked RNAP. In stark contrast, opposing forces promoted passage when the rate of backtracking was comparable to, or faster than the rate of dissociation of the roadblock, particularly in the presence of GreA. Our experiments and simulations indicate that RNAP may transit after roadblocks dissociate, or undergo cycles of backtracking, recovery, and ramming into roadblocks to pass through. We propose that such reciprocating motion also enables RNAP to break protein-DNA contacts holding RNAP back during promoter escape and RNA chain elongation, facilitating productive transcriptionin vivo.
Poor neutralizing antibody responses against SARS-CoV-2 Omicron BQ.1.1 and XBB in Norway in October 2022
Authors: Vikse Elisabeth Lea , Fossum Even , Erdal Magnhild Sekse , Hungnes Olav , Bragstad Karoline 
Published: January 2023

AbstractNew sub-lineages of the SARS-CoV-2 omicron variants with enhanced ability to evade existing antibody responses continue to evolve. A better understanding how susceptible emerging virus variants are to immunity induced by vaccination or infection could help predict which strains will become dominant going forward. Here we evaluate neutralizing antibodies against several clinical isolates of omicron variants including BQ.1.1 and XBB in sera from 3x mRNA vaccinated individuals and individuals with breakthrough infections with early (BA.1 or 2) or late (BA.5) omicron variants. In addition, we evaluate neutralizing antibodies in serum samples harvested from 32 individuals from the middle of October 2022, to provide a more recent estimate of immunity. As expected, serum samples harvested after breakthrough infections were more efficient at neutralizing all the omicron variants, compared to sera from non-infected individuals. While neutralization remained high against variants such as BA.2.75.2, BR.1 and BF.7, there was a marked reduction in neutralizing titers against BQ.1.1 and XBB. Similarly, most serum samples harvested in October 2022 had very low neutralizing antibodies against BQ.1.1 and XBB, suggesting that these variants and their descendants will dominate infection waves in Norway this winter season.