bluuebunny/crossref_metadata_2025 huggingface dataset:
Testing afterglow models of FRB 200428 with early post-burst observations of SGR 1935 + 2154
Authors: Cooper A J , Rowlinson A , Wijers R A M J , Bassa C , Gourdji K , Hessels J , van der Horst A J , Kondratiev V , Michilli D , Pleunis Z , Shimwell T , ter Veen S
Published: October 2022

We present LOFAR imaging observations from the April/May 2020 active episode of magnetar SGR 1935 + 2154. We place the earliest radio limits on persistent emission following the low-luminosity fast radio burst FRB 200428 from the magnetar. We also perform an image-plane search for transient emission and find no radio flares during our observations. We examine post-FRB radio upper limits in the literature and find that all are consistent with the multiwavelength afterglow predicted by the synchrotron maser shock model interpretation of FRB 200428. However, early optical observations appear to rule out the simple versions of the afterglow model with constant-density circumburst media. We show that these constraints may be mitigated by adapting the model for a wind-like environment, but only for a limited parameter range. In addition, we suggest that late-time non-thermal particle acceleration occurs within the afterglow model when the shock is no longer relativistic, which may prove vital for detecting afterglows from other Galactic FRBs. We also discuss future observing strategies for verifying either magnetospheric or maser shock FRB models via rapid radio observations of Galactic magnetars and nearby FRBs.
Spectral characteristics of the black hole binary 4U 1957+115: a multi mission perspective
Authors: Mudambi S P , Gudennavar S B , Misra R , Bubbly S G
Published: October 2022

We report spectral analysis of the persistent black hole X-ray binary, 4U 1957+115, using AstroSat, Swift, and NuSTAR observations carried out between 2016 and 2019. Modelling with a disc emission, thermal Comptonization, and blurred reflection components revealed that the source was in the high-soft state with the disc flux ∼87 per cent of the total and high-energy photon index ∼2.6. There is an evidence that either the inner disc radius varied by ∼25 per cent or the colour hardening factor changed by ∼12 per cent. The values of the inner disc radius imply that for a non-spinning black hole, the black hole mass is  < 7 M ⊙ and the source is located  > 30 kpc away. On the other hand, a rapidly spinning black hole would be consistent with the more plausible black hole mass of  < 10 M ⊙ and a source distance of ∼10 kpc. Fixing the distance to 10 kpc and using a relativistic accretion disc model, constrained the black hole mass to 6 M⊙ and inclination angle to 72°. A positive correlation is detected between the accretion rate and inner radii or equivalently between the accretion rate and colour factor.
The burst mode of accretion in massive star formation with stellar inertia
Authors: Meyer D M-A , Vorobyov E I , Elbakyan V G , Kraus S , Liu S-Y , Nayakshin S , Sobolev A M
Published: October 2022

The burst mode of accretion in massive star formation is a scenario linking the initial gravitational collapse of parent pre-stellar cores to the properties of their gravitationally unstable discs and of their accretion-driven bursts. In this study, we present a series of high-resolution 3D radiation-hydrodynamics numerical simulations for young massive stars formed out of collapsing $100{\rm M}_{\odot }$ molecular cores, spinning with several values of the ratio of rotational-to-gravitational energies $\beta =5{{-}9\ per cent}$. The models include the indirect gravitational potential caused by disc asymmetries. We find that this modifies the barycentre of the disc, causing significant excursions of the central star position, which we term stellar wobbling. The stellar wobbling slows down and protracts the development of gravitational instability in the disc, reducing the number and magnitude of the accretion-driven bursts undergone by the young massive stars, whose properties are in good agreement with that of the burst monitored from the massive protostar M17 MIR. Including stellar wobbling is therefore important for accurate modelling disc structures. Synthetic alma interferometric images in the millimetre waveband show that the outcomes of efficient gravitational instability such as spiral arms and gaseous clumps can be detected for as long as the disc is old enough and has already entered the burst mode of accretion.
Machine-learning classification of astronomical sources: estimating F1-score in the absence of ground truth
Authors: Humphrey A , Kuberski W , Bialek J , Perrakis N , Cools W , Nuyttens N , Elakhrass H , Cunha P A C
Published: October 2022

Machine-learning based classifiers have become indispensable in the field of astrophysics, allowing separation of astronomical sources into various classes, with computational efficiency suitable for application to the enormous data volumes that wide-area surveys now typically produce. In the standard supervised classification paradigm, a model is typically trained and validated using data from relatively small areas of sky, before being used to classify sources in other areas of the sky. However, population shifts between the training examples and the sources to be classified can lead to ‘silent’ degradation in model performance, which can be challenging to identify when the ground-truth is not available. In this letter, we present a novel methodology using the nannyml Confidence-Based Performance Estimation (CBPE) method to predict classifier F1-score in the presence of population shifts, but without ground-truth labels. We apply CBPE to the selection of quasars with decision-tree ensemble models, using broad-band photometry, and show that the F1-scores are predicted remarkably well (${\rm MAPE} \sim 10{{\ \rm per\ cent}}$; R2 = 0.74–0.92). We discuss potential use-cases in the domain of astronomy, including machine-learning model and/or hyperparameter selection, and evaluation of the suitability of training data sets for a particular classification problem.
The impact of two massive early accretion events in a Milky Way-like galaxy: repercussions for the buildup of the stellar disc and halo
Authors: Orkney Matthew D A , Laporte Chervin F P , Grand Robert J J , Gómez Facundo A , van de Voort Freeke , Marinacci Federico , Fragkoudi Francesca , Pakmor Ruediger , Springel Volker
Published: October 2022

We identify and characterize a Milky Way-like realization from the Auriga simulations with two consecutive massive mergers $\sim 2$ Gyr apart at high redshift, comparable to the reported Kraken and Gaia-Sausage-Enceladus. The Kraken-like merger (z = 1.6, $M_{\rm Tot}=8\times 10^{10}\, \rm {M_{\odot }}$) is gas-rich, deposits most of its mass in the inner $10\,$ kpc, and is largely isotropic. The Sausage-like merger (z = 1.14, $M_{\rm Tot}=1\times 10^{11}\, \rm {M_{\odot }}$) leaves a more extended mass distribution at higher energies, and has a radially anisotropic distribution. For the higher-redshift merger, the stellar mass ratio of the satellite to host galaxy is high (1:3). As a result, the chemistry of the remnant is indistinguishable from contemporaneous in situ populations, making it challenging to identify through chemical abundances. This naturally explains why all abundance patterns attributed so far to Kraken are in fact fully consistent with the metal-poor in situ so-called Aurora population and thick disc. However, our model makes a falsifiable prediction: if the Milky Way underwent a gas-rich double merger at high redshift, then this should be imprinted on its star formation history with bursts about $\sim 2\,$ s apart. This may offer constraining power on the highest-redshift massive mergers.
DRESIS: the first comprehensive landscape of drug resistance information
Authors: Sun Xiuna , Zhang Yintao , Li Hanyang , Zhou Ying , Shi Shuiyang , Chen Zhen , He Xin , Zhang Hanyu , Li Fengcheng , Yin Jiayi , Mou Minjie , Wang Yunzhu , Qiu Yunqing , Zhu Feng
Published: October 2022

Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named ‘DRESIS’ was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/
DrugMAP: molecular atlas and pharma-information of all drugs
Authors: Li Fengcheng , Yin Jiayi , Lu Mingkun , Mou Minjie , Li Zhaorong , Zeng Zhenyu , Tan Ying , Wang Shanshan , Chu Xinyi , Dai Haibin , Hou Tingjun , Zeng Su , Chen Yuzong , Zhu Feng
Published: October 2022

The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studied drugs. However, our understanding of such information is neither comprehensive nor precise, which necessitates the construction of a new database providing a network containing a large number of drugs and their interacting molecules. Here, a new database describing the molecular atlas and pharma-information of drugs (DrugMAP) was therefore constructed. It provides a comprehensive list of interacting molecules for >30 000 drugs/drug candidates, gives the differential expression patterns for >5000 interacting molecules among different disease sites, ADME (absorption, distribution, metabolism and excretion)-relevant organs and physiological tissues, and weaves a comprehensive and precise network containing >200 000 interactions among drugs and molecules. With the great efforts made to clarify the complex mechanism underlying drug pharmacokinetics and pharmacodynamics and rapidly emerging interests in artificial intelligence (AI)-based network analyses, DrugMAP is expected to become an indispensable supplement to existing databases to facilitate drug discovery. It is now fully and freely accessible at: https://idrblab.org/drugmap/
TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies
Authors: Lu Mingming , Zhang Yadong , Yang Fengchun , Mai Jialin , Gao Qianwen , Xu Xiaowei , Kang Hongyu , Hou Li , Shang Yunfei , Qain Qiheng , Liu Jie , Jiang Meiye , Zhang Hao , Bu Congfan , Wang Jinyue , Zhang Zhewen , Zhang Zaichao , Zeng Jingyao , Li Jiao , Xiao Jingfa
Published: October 2022

Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits. Despite the ever-increasing TWAS outputs, there is still a lack of databases curating massive public TWAS information and knowledge. To fill this gap, here we present TWAS Atlas (https://ngdc.cncb.ac.cn/twas/), an integrated knowledgebase of TWAS findings manually curated from extensive literature. In the current implementation, TWAS Atlas collects 401,266 high-quality human gene–trait associations from 200 publications, covering 22,247 genes and 257 traits across 135 tissue types. In particular, an interactive knowledge graph of the collected gene–trait associations is constructed together with single nucleotide polymorphism (SNP)–gene associations to build up comprehensive regulatory networks at multi-omics levels. In addition, TWAS Atlas, as a user-friendly web interface, efficiently enables users to browse, search and download all association information, relevant research metadata and annotation information of interest. Taken together, TWAS Atlas is of great value for promoting the utility and availability of TWAS results in explaining the complex genetic basis as well as providing new insights for human health and disease research.
USP15 promotes cGAS activation through deubiquitylation and liquid condensation
Authors: Shi Chengrui , Yang Xikang , Hou Yanfei , Jin Xue , Guo Lerui , Zhou Yi , Zhang Conggang , Yin Hang
Published: October 2022

Double-stranded DNA (dsDNA) is recognized as a danger signal by cyclic GMP-AMP synthase (cGAS), which triggers innate immune responses. cGAS activity must be properly regulated to maintain immune homeostasis. However, the mechanism by which cGAS activation is controlled remains to be better understood. In this study, we identified USP15 as a cGAS-interacting partner. USP15 promoted DNA-induced cGAS activation and downstream innate immune responses through a positive feedback mechanism. Specifically, USP15 deubiquitylated cGAS and promoted its activation. In the absence of DNA, USP15 drove cGAS dimerization and liquid condensation through the USP15 intrinsic disordered region (IDR), which prepared cGAS for a rapid response to DNA. Upon DNA stimulation, USP15 was induced to express and boost cGAS activation, functioning as an efficient amplifier in innate immune signal transduction. In summary, the positive role played by USP15-mediated cGAS activation may be a novel regulatory mechanism in the fine-tuning of innate immunity.
RABC: Rheumatoid Arthritis Bioinformatics Center
Authors: Chen Haiyan , Xu Jing , Wei Siyu , Jia Zhe , Sun Chen , Kang Jingxuan , Guo Xuying , Zhang Nan , Tao Junxian , Dong Yu , Zhang Chen , Ma Yingnan , Lv Wenhua , Tian Hongsheng , Bi Shuo , Lv Hongchao , Huang Chen , Kong Fanwu , Tang Guoping , Jiang Yongshuai , Zhang Mingming
Published: October 2022

Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.
Nature-inspired engineering of an artificial ligase enzyme by domain fusion
Authors: Tong Cher Ling , Kanwar Nisha , Morrone Dana J , Seelig Burckhard
Published: October 2022

The function of most proteins is accomplished through the interplay of two or more protein domains and fine-tuned by natural evolution. In contrast, artificial enzymes have often been engineered from a single domain scaffold and frequently have lower catalytic activity than natural enzymes. We previously generated an artificial enzyme that catalyzed an RNA ligation by >2 million-fold but was likely limited in its activity by low substrate affinity. Inspired by nature's concept of domain fusion, we fused the artificial enzyme to a series of protein domains known to bind nucleic acids with the goal of improving its catalytic activity. The effect of the fused domains on catalytic activity varied greatly, yielding severalfold increases but also reductions caused by domains that previously enhanced nucleic acid binding in other protein engineering projects. The combination of the two better performing binding domains improved the activity of the parental ligase by more than an order of magnitude. These results demonstrate for the first time that nature's successful evolutionary mechanism of domain fusion can also improve an unevolved primordial-like protein whose structure and function had just been created in the test tube. The generation of multi-domain proteins might therefore be an ancient evolutionary process.
MeDBA: the Metalloenzyme Data Bank and Analysis platform
Authors: Yu Jun-Lin , Wu Song , Zhou Cong , Dai Qing-Qing , Schofield Christopher J , Li Guo-Bo
Published: October 2022

Metalloenzymes are attractive research targets in fields of chemistry, biology, and medicine. Given that metalloenzymes can manifest conservation of metal-coordination and ligand binding modes, the excavation and expansion of metalloenzyme-specific knowledge is of interest in bridging metalloenzyme-related fields. Building on our previous metalloenzyme-ligand association database, MeLAD, we have expanded the scope of metalloenzyme-specific knowledge and services, by forming a versatile platform, termed the Metalloenzyme Data Bank and Analysis (MeDBA). The MeDBA provides: (i) manual curation of metalloenzymes into different categories, that this M-I, M-II and M-III; (ii) comprehensive information on metalloenzyme activities, expression profiles, family and disease links; (iii) structural information on metalloenzymes, in particular metal binding modes; (iv) metalloenzyme substrates and bioactive molecules acting on metalloenzymes; (v) excavated metal-binding pharmacophores and (vi) analysis tools for structure/metal active site comparison and metalloenzyme profiling. The MeDBA is freely available at https://medba.ddtmlab.org.
Catastrophic chromosome fragmentation probes the nucleoid structure and dynamics in Escherichia coli
Authors: Mahaseth Tulip , Kuzminov Andrei
Published: October 2022

Escherichia coli cells treated with a combination of cyanide (CN) and hydrogen peroxide (HP) succumb to catastrophic chromosome fragmentation (CCF), detectable in pulsed-field gels as >100 double-strand breaks per genome equivalent. Here we show that CN + HP-induced double-strand breaks are independent of replication and occur uniformly over the chromosome,—therefore we used CCF to probe the nucleoid structure by measuring DNA release from precipitated nucleoids. CCF releases surprisingly little chromosomal DNA from the nucleoid suggesting that: (i) the nucleoid is a single DNA-protein complex with only limited stretches of protein-free DNA and (ii) CN + HP-induced breaks happen within these unsecured DNA stretches, rather than at DNA attachments to the central scaffold. Mutants lacking individual nucleoid-associated proteins (NAPs) release more DNA during CCF, consistent with NAPs anchoring chromosome to the central scaffold (Dps also reduces the number of double-strand breaks directly). Finally, significantly more broken DNA is released once ATP production is restored, with about two-thirds of this ATP-dependent DNA release being due to transcription, suggesting that transcription complexes act as pulleys to move DNA loops. In addition to NAPs, recombinational repair of double-strand breaks also inhibits DNA release by CCF, contributing to a dynamic and complex nucleoid structure.
A sePARate phase? Poly(ADP-ribose) versus RNA in the organization of biomolecular condensates
Authors: Alemasova Elizaveta E , Lavrik Olga I
Published: October 2022

Condensates are biomolecular assemblies that concentrate biomolecules without the help of membranes. They are morphologically highly versatile and may emerge via distinct mechanisms. Nucleic acids–DNA, RNA and poly(ADP-ribose) (PAR) play special roles in the process of condensate organization. These polymeric scaffolds provide multiple specific and nonspecific interactions during nucleation and ‘development’ of macromolecular assemblages. In this review, we focus on condensates formed with PAR. We discuss to what extent the literature supports the phase separation origin of these structures. Special attention is paid to similarities and differences between PAR and RNA in the process of dynamic restructuring of condensates during their functioning.
G-quadruplex-guided RNA engineering to modulate CRISPR-based genomic regulation
Authors: Liu Xingyu , Cui Shuangyu , Qi Qianqian , Lei Huajun , Zhang Yutong , Shen Wei , Fu Fang , Tian Tian , Zhou Xiang
Published: October 2022

It is important to develop small moelcule-based methods to modulate gene editing and expression in human cells. The roles of the G-quadruplex (G4) in biological systems have been widely studied. Here, G4-guided RNA engineering is performed to generate guide RNA with G4-forming units (G4-gRNA). We further demonstrate that chemical targeting of G4-gRNAs holds promise as a general approach for modulating gene editing and expression in human cells. The rich structural diversity of RNAs offers a reservoir of targets for small molecules to bind, thus creating the potential to modulate RNA biology.
PertOrg 1.0: a comprehensive resource of multilevel alterations induced in model organisms by in vivo genetic perturbation
Authors: Zhai Zhaoyu , Zhang Xuelu , Zhou Lu , Lin Zhewei , Kuang Ni , Li Qiang , Ma Qinfeng , Tao Haodong , Gao Jieya , Ma Shiyong , Pan Jianbo
Published: October 2022

Genetically modified organisms (GMOs) can be generated to model human genetic disease or plant disease resistance, and they have contributed to the exploration and understanding of gene function, physiology, disease onset and drug target discovery. Here, PertOrg (http://www.inbirg.com/pertorg/) was introduced to provide multilevel alterations in GMOs. Raw data of 58 707 transcriptome profiles and associated information, such as phenotypic alterations, were collected and curated from studies involving in vivo genetic perturbation (e.g. knockdown, knockout and overexpression) in eight model organisms, including mouse, rat and zebrafish. The transcriptome profiles from before and after perturbation were organized into 10 116 comparison datasets, including 122 single-cell RNA-seq datasets. The raw data were checked and analysed using widely accepted and standardized pipelines to identify differentially expressed genes (DEGs) in perturbed organisms. As a result, 8 644 148 DEGs were identified and deposited as signatures of gene perturbations. Downstream functional enrichment analysis, cell type analysis and phenotypic alterations were also provided when available. Multiple search methods and analytical tools were created and implemented. Furthermore, case studies were presented to demonstrate how users can utilize the database. PertOrg 1.0 will be a valuable resource aiding in the exploration of gene functions, biological processes and disease models.
HProteome-BSite: predicted binding sites and ligands in human 3D proteome
Authors: Sim Jiho , Kwon Sohee , Seok Chaok
Published: October 2022

Atomic-level knowledge of protein-ligand interactions allows a detailed understanding of protein functions and provides critical clues to discovering molecules regulating the functions. While recent innovative deep learning methods for protein structure prediction dramatically increased the structural coverage of the human proteome, molecular interactions remain largely unknown. A new database, HProteome-BSite, provides predictions of binding sites and ligands in the enlarged 3D human proteome. The model structures for human proteins from the AlphaFold Protein Structure Database were processed to structural domains of high confidence to maximize the coverage and reliability of interaction prediction. For ligand binding site prediction, an updated version of a template-based method GalaxySite was used. A high-level performance of the updated GalaxySite was confirmed. HProteome-BSite covers 80.74% of the UniProt entries in the AlphaFold human 3D proteome. Predicted binding sites and binding poses of potential ligands are provided for effective applications to further functional studies and drug discovery. The HProteome-BSite database is available at https://galaxy.seoklab.org/hproteome-bsite/database and is free and open to all users.
Aquila: a spatial omics database and analysis platform
Authors: Zheng Yimin , Chen Yitian , Ding Xianting , Wong Koon Ho , Cheung Edwin
Published: October 2022

Spatial omics is a rapidly evolving approach for exploring tissue microenvironment and cellular networks by integrating spatial knowledge with transcript or protein expression information. However, there is a lack of databases for users to access and analyze spatial omics data. To address this limitation, we developed Aquila, a comprehensive platform for managing and analyzing spatial omics data. Aquila contains 107 datasets from 30 diseases, including 6500+ regions of interest, and 15.7 million cells. The database covers studies from spatial transcriptome and proteome analyses, 2D and 3D experiments, and different technologies. Aquila provides visualization of spatial omics data in multiple formats such as spatial cell distribution, spatial expression and co-localization of markers. Aquila also lets users perform many basic and advanced spatial analyses on any dataset. In addition, users can submit their own spatial omics data for visualization and analysis in a safe and secure environment. Finally, Aquila can be installed as an individual app on a desktop and offers the RESTful API service for power users to access the database. Overall, Aquila provides a detailed insight into transcript and protein expression in tissues from a spatial perspective. Aquila is available at https://aquila.cheunglab.org.
PAT: a comprehensive database of prokaryotic antimicrobial toxins
Authors: Liu Ya , Liu Sheng , Pan Zhuo , Ren Yu , Jiang Yiru , Wang Feng , Li Dan-dan , Li Yue-zhong , Zhang Zheng
Published: October 2022

Antimicrobial toxins help prokaryotes win competitive advantages in intraspecific or interspecific conflicts and are also a critical factor affecting the pathogenicity of many pathogens that threaten human health. Although many studies have revealed that antagonism based on antimicrobial toxins plays a central role in prokaryotic life, a database on antimicrobial toxins remains lacking. Here, we present the prokaryotic antimicrobial toxin database (PAT, http://bioinfo.qd.sdu.edu.cn/PAT/), a comprehensive data resource collection on experimentally validated antimicrobial toxins. PAT has organized information, derived from the reported literature, on antimicrobial toxins, as well as the corresponding immunity proteins, delivery mechanisms, toxin activities, structural characteristics, sequences, etc. Moreover, we also predict potential antimicrobial toxins in prokaryotic reference genomes and show the taxonomic information and environmental distribution of typical antimicrobial toxins. These details have been fully incorporated into the PAT database, where users can browse, search, download, analyse and view informative statistics and detailed information. PAT resources have already been used in our prediction and identification of prokaryotic antimicrobial toxins and may contribute to promoting the efficient investigation of antimicrobial toxin functions, the discovery of novel antimicrobial toxins, and an improved understanding of the biological roles and significance of these toxins.
Molecular basis of dual anti-CRISPR and auto-regulatory functions of AcrIF24
Authors: Kim Gi Eob , Lee So Yeon , Birkholz Nils , Kamata Kotaro , Jeong Jae-Hee , Kim Yeon-Gil , Fineran Peter C , Park Hyun Ho
Published: October 2022

CRISPR-Cas systems are adaptive immune systems in bacteria and archaea that provide resistance against phages and other mobile genetic elements. To fight against CRISPR-Cas systems, phages and archaeal viruses encode anti-CRISPR (Acr) proteins that inhibit CRISPR-Cas systems. The expression of acr genes is controlled by anti-CRISPR-associated (Aca) proteins encoded within acr-aca operons. AcrIF24 is a recently identified Acr that inhibits the type I-F CRISPR-Cas system. Interestingly, AcrIF24 was predicted to be a dual-function Acr and Aca. Here, we elucidated the crystal structure of AcrIF24 from Pseudomonas aeruginosa and identified its operator sequence within the regulated acr-aca operon promoter. The structure of AcrIF24 has a novel domain composition, with wing, head and body domains. The body domain is responsible for recognition of promoter DNA for Aca regulatory activity. We also revealed that AcrIF24 directly bound to type I-F Cascade, specifically to Cas7 via its head domain as part of its Acr mechanism. Our results provide new molecular insights into the mechanism of a dual functional Acr-Aca protein.
Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers
Authors: Tao Yifeng , Ma Xiaojun , Palmer Drake , Schwartz Russell , Lu Xinghua , Osmanbeyoglu Hatice Ulku
Published: October 2022

Cancer is a disease of gene dysregulation, where cells acquire somatic and epigenetic alterations that drive aberrant cellular signaling. These alterations adversely impact transcriptional programs and cause profound changes in gene expression. Interpreting somatic alterations within context-specific transcriptional programs will facilitate personalized therapeutic decisions but is a monumental task. Toward this goal, we develop a partially interpretable neural network model called Chromatin-informed Inference of Transcriptional Regulators Using Self-attention mechanism (CITRUS). CITRUS models the impact of somatic alterations on transcription factors and downstream transcriptional programs. Our approach employs a self-attention mechanism to model the contextual impact of somatic alterations. Furthermore, CITRUS uses a layer of hidden nodes to explicitly represent the state of transcription factors (TFs) to learn the relationships between TFs and their target genes based on TF binding motifs in the open chromatin regions of tumor samples. We apply CITRUS to genomic, transcriptomic, and epigenomic data from 17 cancer types profiled by The Cancer Genome Atlas. CITRUS predicts patient-specific TF activities and reveals transcriptional program variations between and within tumor types. We show that CITRUS yields biological insights into delineating TFs associated with somatic alterations in individual tumors. Thus, CITRUS is a promising tool for precision oncology.
AmyloGraph: a comprehensive database of amyloid–amyloid interactions
Authors: Burdukiewicz Michał , Rafacz Dominik , Barbach Agnieszka , Hubicka Katarzyna , Bąkała Laura , Lassota Anna , Stecko Jakub , Szymańska Natalia , Wojciechowski Jakub W , Kozakiewicz Dominika , Szulc Natalia , Chilimoniuk Jarosław , Jęśkowiak Izabela , Gąsior-Głogowska Marlena , Kotulska Małgorzata
Published: October 2022

Information about the impact of interactions between amyloid proteins on their fibrillization propensity is scattered among many experimental articles and presented in unstructured form. We manually curated information located in almost 200 publications (selected out of 562 initially considered), obtaining details of 883 experimentally studied interactions between 46 amyloid proteins or peptides. We also proposed a novel standardized terminology for the description of amyloid–amyloid interactions, which is included in our database, covering all currently known types of such a cross-talk, including inhibition of fibrillization, cross-seeding and other phenomena. The new approach allows for more specific studies on amyloids and their interactions, by providing very well-defined data. AmyloGraph, an online database presenting information on amyloid–amyloid interactions, is available at (http://AmyloGraph.com/). Its functionalities are also accessible as the R package (https://github.com/KotulskaLab/AmyloGraph). AmyloGraph is the only publicly available repository for experimentally determined amyloid–amyloid interactions.
SIGNOR 3.0, the SIGnaling network open resource 3.0: 2022 update
Authors: Lo Surdo Prisca , Iannuccelli Marta , Contino Silvia , Castagnoli Luisa , Licata Luana , Cesareni Gianni , Perfetto Livia
Published: October 2022

The SIGnaling Network Open Resource (SIGNOR 3.0, https://signor.uniroma2.it) is a public repository that captures causal information and represents it according to an ‘activity-flow’ model. SIGNOR provides freely-accessible static maps of causal interactions that can be tailored, pruned and refined to build dynamic and predictive models. Each signaling relationship is annotated with an effect (up/down-regulation) and with the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the regulation of the target entity. Since its latest release, SIGNOR has undergone a significant upgrade including: (i) a new website that offers an improved user experience and novel advanced search and graph tools; (ii) a significant content growth adding up to a total of approx. 33,000 manually-annotated causal relationships between more than 8900 biological entities; (iii) an increase in the number of manually annotated pathways, currently including pathways deregulated by SARS-CoV-2 infection or involved in neurodevelopment synaptic transmission and metabolism, among others; (iv) additional features such as new model to represent metabolic reactions and a new confidence score assigned to each interaction.
isomiRdb: microRNA expression at isoform resolution
Authors: Aparicio-Puerta Ernesto , Hirsch Pascal , Schmartz Georges P , Fehlmann Tobias , Keller Verena , Engel Annika , Kern Fabian , Hackenberg Michael , Keller Andreas
Published: October 2022

A significant fraction of mature miRNA transcripts carries sequence and/or length variations, termed isomiRs. IsomiRs are differentially abundant in cell types, tissues, body fluids or patients’ samples. Not surprisingly, multiple studies describe a physiological and pathophysiological role. Despite their importance, systematically collected and annotated isomiR information available in databases remains limited. We thus developed isomiRdb, a comprehensive resource that compiles miRNA expression data at isomiR resolution from various sources. We processed 42 499 human miRNA-seq datasets (5.9 × 1011 sequencing reads) and consistently analyzed them using miRMaster and sRNAbench. Our database provides online access to the 90 483 most abundant isomiRs (>1 RPM in at least 1% of the samples) from 52 tissues and 188 cell types. Additionally, the full set of over 3 million detected isomiRs is available for download. Our resource can be queried at the sample, miRNA or isomiR level so users can quickly answer common questions about the presence/absence of a particular miRNA/isomiR in tissues of interest. Further, the database facilitates to identify whether a potentially interesting new isoform has been detected before and its frequency. In addition to expression tables, isomiRdb can generate multiple interactive visualisations including violin plots and heatmaps. isomiRdb is free to use and publicly available at: https://www.ccb.uni-saarland.de/isomirdb.
Integrated multi-omics approach revealed cellular senescence landscape
Authors: Song Qiao , Hou Yuli , Zhang Yiyin , Liu Jing , Wang Yaqi , Fu Jingxuan , Zhang Chi , Cao Min , Cui Yuting , Zhang Xiaomin , Wang Xiaoling , Zhang Jingjing , Liu Congcong , Zhang Yingzhen , Wang Peichang
Published: October 2022

Cellular senescence is a complex multifactorial biological phenomenon that plays essential roles in aging, and aging-related diseases. During this process, the senescent cells undergo gene expression altering and chromatin structure remodeling. However, studies on the epigenetic landscape of senescence using integrated multi-omics approaches are limited. In this research, we performed ATAC-seq, RNA-seq and ChIP-seq on different senescent types to reveal the landscape of senescence and identify the prime regulatory elements. We also obtained 34 key genes and deduced that NAT1, PBX1 and RRM2, which interacted with each other, could be the potential markers of aging and aging-related diseases. In summary, our work provides the landscape to study accessibility dynamics and transcriptional regulations in cellular senescence. The application of this technique in different types of senescence allows us to identify the regulatory elements responsible for the substantial regulation of transcription, providing the insights into molecular mechanisms of senescence.
CRISPR/Cas9-induced structural variations expand in T lymphocytes in vivo
Authors: Wu Jinchun , Zou Ziye , Liu Yang , Liu Xuhao , Zhangding Zhengrong , Xu Mo , Hu Jiazhi
Published: October 2022

CRISPR/Cas9 has been adapted to disrupt endogenous genes in adoptive T-lymphocyte therapy to prevent graft-versus-host disease. However, genome editing also generates prevalent deleterious structural variations (SVs), including chromosomal translocations and large deletions, raising safety concerns about reinfused T cells. Here, we dynamically monitored the progression of SVs in a mouse model of T-cell receptor (TCR)-transgenic T-cell adoptive transfer, mimicking TCR T therapeutics. Remarkably, CRISPR/Cas9-induced SVs persist and undergo clonal expansion in vivo after three weeks or even two months, evidenced by high enrichment and low junctional diversity of identified SVs post infusion. Specifically, we detected 128 expanded translocations, with 20 615 as the highest number of amplicons. The identified SVs are stochastically selected among different individuals and show an inconspicuous locus preference. Similar to SVs, viral DNA integrations are routinely detected in edited T cells and also undergo clonal expansion. The persistent SVs and viral DNA integrations in the infused T cells may constantly threaten genome integrity, drawing immediate attention to the safety of CRISPR/Cas9-engineered T cells mediated immunotherapy.
Genenames.org: the HGNC resources in 2023
Authors: Seal Ruth L , Braschi Bryony , Gray Kristian , Jones Tamsin E M , Tweedie Susan , Haim-Vilmovsky Liora , Bruford Elspeth A
Published: October 2022

The HUGO Gene Nomenclature Committee (HGNC) assigns unique symbols and names to human genes. The HGNC database (www.genenames.org) currently contains over 43 000 approved gene symbols, over 19 200 of which are assigned to protein-coding genes, 14 000 to pseudogenes and nearly 9000 to non-coding RNA genes. The public website, www.genenames.org, displays all approved nomenclature within Symbol Reports that contain data curated by HGNC nomenclature advisors and links to related genomic, clinical, and proteomic information. Here, we describe updates to our resource, including improvements to our search facility and new download features.
SPASCER: spatial transcriptomics annotation at single-cell resolution
Authors: Fan Zhiwei , Luo Yangyang , Lu Huifen , Wang Tiangang , Feng YuZhou , Zhao Weiling , Kim Pora , Zhou Xiaobo
Published: October 2022

In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location and provides novel insights into diverse spatially related biological contexts. Even though two spatial transcriptomics databases exist, they provide limited analytical information. Information such as spatial heterogeneity of genes and cells, cell-cell communication activities in space, and the cell type compositions in the microenvironment are critical clues to unveil the mechanism of tumorigenesis and embryo differentiation. Therefore, we constructed a new spatial transcriptomics database, named SPASCER (https://ccsm.uth.edu/SPASCER), designed to help understand the heterogeneity of tissue organizations, region-specific microenvironment, and intercellular interactions across tissue architectures at multiple levels. SPASCER contains datasets from 43 studies, including 1082 sub-datasets from 16 organ types across four species. scRNA-seq was integrated to deconvolve/map spatial transcriptomics, and processed with spatial cell-cell interaction, gene pattern and pathway enrichment analysis. Cell–cell interactions and gene regulation network of scRNA-seq from matched spatial transcriptomics were performed as well. The application of SPASCER will provide new insights into tissue architecture and a solid foundation for the mechanistic understanding of many biological processes in healthy and diseased tissues.
KRCC1, a modulator of the DNA damage response
Authors: Neizer-Ashun Fiifi , Dwivedi Shailendra Kumar Dhar , Dey Anindya , Thavathiru Elangovan , Berry William L , Lees-Miller Susan Patricia , Mukherjee Priyabrata , Bhattacharya Resham
Published: October 2022

The lysine-rich coiled-coil 1 (KRCC1) protein is overexpressed in multiple malignancies, including ovarian cancer, and overexpression correlates with poor overall survival. Despite a potential role in cancer progression, the biology of KRCC1 remains elusive. Here, we characterize the biology of KRCC1 and define its role in the DNA damage response and in cell cycle progression. We demonstrate that KRCC1 associates with the checkpoint kinase 1 (CHK1) upon DNA damage and regulates the CHK1-mediated checkpoint. KRCC1 facilitates RAD51 recombinase foci formation and augments homologous recombination repair. Furthermore, KRCC1 is required for proper S-phase progression and subsequent mitotic entry. Our findings uncover a novel component of the DNA damage response and a potential link between cell cycle, associated damage response and DNA repair.
CellTracer: a comprehensive database to dissect the causative multilevel interplay contributing to cell development trajectories
Authors: Guo Qiuyan , Wang Peng , Liu Qian , Hao Yangyang , Gao Yue , Qi Yue , Xu Rongji , Chen Hongyan , Xin Mengyu , Wu Xiaoting , Sun Rui , Zhi Hui , Zhang Yunpeng , Ning Shangwei , Li Xia
Published: October 2022

During the complex process of tumour development, the unique destiny of cells is driven by the fine-tuning of multilevel features such as gene expression, network regulation and pathway activation. The dynamic formation of the tumour microenvironment influences the therapeutic response and clinical outcome. Thus, characterizing the developmental landscape and identifying driver features at multiple levels will help us understand the pathological development of disease in individual cell populations and further contribute to precision medicine. Here, we describe a database, CellTracer (http://bio-bigdata.hrbmu.edu.cn/CellTracer), which aims to dissect the causative multilevel interplay contributing to cell development trajectories. CellTracer consists of the gene expression profiles of 1 941 552 cells from 222 single-cell datasets and provides the development trajectories of different cell populations exhibiting diverse behaviours. By using CellTracer, users can explore the significant alterations in molecular events and causative multilevel crosstalk among genes, biological contexts, cell characteristics and clinical treatments along distinct cell development trajectories. CellTracer also provides 12 flexible tools to retrieve and analyse gene expression, cell cluster distribution, cell development trajectories, cell-state variations and their relationship under different conditions. Collectively, CellTracer will provide comprehensive insights for investigating the causative multilevel interplay contributing to cell development trajectories and serve as a foundational resource for biomarker discovery and therapeutic exploration within the tumour microenvironment.
ChromLoops: a comprehensive database for specific protein-mediated chromatin loops in diverse organisms
Authors: Zhou Qiangwei , Cheng Sheng , Zheng Shanshan , Wang Zhenji , Guan Pengpeng , Zhu Zhixian , Huang Xingyu , Zhou Cong , Li Guoliang
Published: October 2022

Chromatin loops (or chromatin interactions) are important elements of chromatin structures. Disruption of chromatin loops is associated with many diseases, such as cancer and polydactyly. A few methods, including ChIA-PET, HiChIP and PLAC-Seq, have been proposed to detect high-resolution, specific protein-mediated chromatin loops. With rapid progress in 3D genomic research, ChIA-PET, HiChIP and PLAC-Seq datasets continue to accumulate, and effective collection and processing for these datasets are urgently needed. Here, we developed a comprehensive, multispecies and specific protein-mediated chromatin loop database (ChromLoops, https://3dgenomics.hzau.edu.cn/chromloops), which integrated 1030 ChIA-PET, HiChIP and PLAC-Seq datasets from 13 species, and documented 1 491 416 813 high-quality chromatin loops. We annotated genes and regions overlapping with chromatin loop anchors with rich functional annotations, such as regulatory elements (enhancers, super-enhancers and silencers), variations (common SNPs, somatic SNPs and eQTLs), and transcription factor binding sites. Moreover, we identified genes with high-frequency chromatin interactions in the collected species. In particular, we identified genes with high-frequency interactions in cancer samples. We hope that ChromLoops will provide a new platform for studying chromatin interaction regulation in relation to biological processes and disease.
Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits
Authors: Pan Siyu , Kang Hongen , Liu Xinxuan , Lin Shiqi , Yuan Na , Zhang Zhang , Bao Yiming , Jia Peilin
Published: October 2022

A broad range of complex phenotypes are related to dysfunctions in brain (hereafter referred to as brain-related traits), including various mental and behavioral disorders and diseases of the nervous system. These traits in general share overlapping symptoms, pathogenesis, and genetic components. Here, we present Brain Catalog (https://ngdc.cncb.ac.cn/braincatalog), a comprehensive database aiming to delineate the genetic components of more than 500 GWAS summary statistics datasets for brain-related traits from multiple aspects. First, Brain Catalog provides results of candidate causal variants, causal genes, and functional tissues and cell types for each trait identified by multiple methods using comprehensive annotation datasets (58 QTL datasets spanning 6 types of QTLs). Second, Brain Catalog estimates the SNP-based heritability, the partitioning heritability based on functional annotations, and genetic correlations among traits. Finally, through bidirectional Mendelian randomization analyses, Brain Catalog presents inference of risk factors that are likely causal to each trait. In conclusion, Brain Catalog presents a one-stop shop for the genetic components of brain-related traits, potentially serving as a valuable resource for worldwide researchers to advance the understanding of how GWAS signals may contribute to the biological etiology of brain-related traits.