Nucleic Acids Res. 2022 May 17:gkac382. doi: 10.1093/nar/gkac382. Online ahead of print.

ABSTRACT

SynergyFinder (https://synergyfinder.fimm.fi) is a free web-application for interactive analysis and visualization of multi-drug combination response data. Since its first release in 2017, SynergyFinder has become a popular tool for multi-dose combination data analytics, partly because the development of its functionality and graphical interface has been driven by a diverse user community, including both chemical biologists and computational scientists. Here, we describe the latest upgrade of this community-effort, SynergyFinder release 3.0, introducing a number of novel features that support interactive multi-sample analysis of combination synergy, a novel consensus synergy score that combines multiple synergy scoring models, and an improved outlier detection functionality that eliminates false positive results, along with many other post-analysis options such as weighting of synergy by drug concentrations and distinguishing between different modes of synergy (potency and efficacy). Based on user requests, several additional improvements were also implemented, including new data visualizations and export options for multi-drug combinations. With these improvements, SynergyFinder 3.0 supports robust identification of consistent combinatorial synergies for multi-drug combinatorial discovery and clinical translation.

PMID:35580060 | DOI:10.1093/nar/gkac382

Nucleic Acids Res. 2022 May 17:gkac371. doi: 10.1093/nar/gkac371. Online ahead of print.

ABSTRACT

For decades, natural products have been used as a primary resource in drug discovery pipelines to find new antibiotics, which are mainly produced as secondary metabolites by bacteria. The biosynthesis of these compounds is encoded in co-localized genes termed biosynthetic gene clusters (BGCs). However, BGCs are often not expressed under laboratory conditions. Several genetic manipulation strategies have been developed in order to activate or overexpress silent BGCs. Significant increases in production levels of secondary metabolites were indeed achieved by modifying the expression of genes encoding regulators and transporters, as well as genes involved in resistance or precursor biosynthesis. However, the abundance of genes encoding such functions within bacterial genomes requires prioritization of the most promising ones for genetic manipulation strategies. Here, we introduce the 'Secondary Metabolite Transcriptomic Pipeline' (SeMa-Trap), a user-friendly web-server, available at https://sema-trap.ziemertlab.com. SeMa-Trap facilitates RNA-Seq based transcriptome analyses, finds co-expression patterns between certain genes and BGCs of interest, and helps optimize the design of comparative transcriptomic analyses. Finally, SeMa-Trap provides interactive result pages for each BGC, allowing the easy exploration and comparison of expression patterns. In summary, SeMa-Trap allows a straightforward prioritization of genes that could be targeted via genetic engineering approaches to (over)express BGCs of interest.

PMID:35580059 | DOI:10.1093/nar/gkac371

Nucleic Acids Res. 2022 May 17:gkac372. doi: 10.1093/nar/gkac372. Online ahead of print.

ABSTRACT

Significant improvements have been made in the efficiency and accuracy of RNA 3D structure prediction methods in recent years; however, many tools developed in the field stay exclusive to only a few bioinformatic groups. To perform a complete RNA 3D structure modeling analysis as proposed by the RNA-Puzzles community, researchers must familiarize themselves with a quite complex set of tools. In order to facilitate the processing of RNA sequences and structures, we previously developed the rna-tools package. However, using rna-tools requires the installation of a mixture of libraries and tools, basic knowledge of the command line and the Python programming language. To provide an opportunity for the broader community of biologists to take advantage of the new developments in RNA structural biology, we developed rna-tools.online. The web server provides a user-friendly platform to perform many standard analyses required for the typical modeling workflow: 3D structure manipulation and editing, structure minimization, structure analysis, quality assessment, and comparison. rna-tools.online supports biologists to start benefiting from the maturing field of RNA 3D structural bioinformatics and can be used for educational purposes. The web server is available at https://rna-tools.online.

PMID:35580057 | DOI:10.1093/nar/gkac372

Nucleic Acids Res. 2022 May 17:gkac370. doi: 10.1093/nar/gkac370. Online ahead of print.

ABSTRACT

Understanding the functions and origins of proteins requires splitting these macromolecules into fragments that could be independent in terms of folding, activity, or evolution. For that purpose, structural domains are the typical level of analysis, but shorter segments, such as subdomains and supersecondary structures, are insightful as well. Here, we propose SWORD2, a web server for exploring how an input protein structure may be decomposed into 'Protein Units' that can be hierarchically assembled to delimit structural domains. For each partitioning solution, the relevance of the identified substructures is estimated through different measures. This multilevel analysis is achieved by integrating our previous work on domain delineation, 'protein peeling' and model quality assessment. We hope that SWORD2 will be useful to biologists searching for key regions in their proteins of interest and to bioinformaticians building datasets of protein structures. The web server is freely available online: https://www.dsimb.inserm.fr/SWORD2.

PMID:35580056 | DOI:10.1093/nar/gkac370

Nucleic Acids Res. 2022 May 17:gkac368. doi: 10.1093/nar/gkac368. Online ahead of print.

ABSTRACT

The development of RNA aptamers/fluorophores system is highly desirable for understanding the dynamic molecular biology of RNAs in vivo. Peppers-based imaging systems have been reported and applied for mRNA imaging in living cells. However, the need to insert corresponding RNA aptamer sequences into target RNAs and relatively low fluorescence signal limit its application in endogenous mRNA imaging. Herein, we remolded the original Pepper aptamer and developed a tandem array of inert Pepper (iPepper) fluorescence turn-on system. iPepper allows for efficient and selective imaging of diverse endogenous mRNA species in live cells with minimal agitation of the target mRNAs. We believe iPepper would significantly expand the applications of the aptamer/fluorophore system in endogenous mRNA imaging, and it has the potential to become a powerful tool for real-time studies in living cells and biological processing.

PMID:35580055 | DOI:10.1093/nar/gkac368

Nucleic Acids Res. 2022 May 17:gkac359. doi: 10.1093/nar/gkac359. Online ahead of print.

ABSTRACT

T-box riboswitches (T-boxes) are essential RNA regulatory elements with a remarkable structural diversity, especially among bacterial pathogens. In staphylococci, all glyS T-boxes synchronize glycine supply during synthesis of nascent polypeptides and cell wall formation and are characterized by a conserved and unique insertion in their antiterminator/terminator domain, termed stem Sa. Interestingly, in Staphylococcus aureus the stem Sa can accommodate binding of specific antibiotics, which in turn induce robust and diverse effects on T-box-mediated transcription. In the present study, domain swap mutagenesis and probing analysis were performed to decipher the role of stem Sa. Deletion of stem Sa significantly reduces both the S. aureus glyS T-box-mediated transcription readthrough levels and the ability to discriminate among tRNAGly isoacceptors, both in vitro and in vivo. Moreover, the deletion inverted the previously reported stimulatory effects of specific antibiotics. Interestingly, stem Sa insertion in the terminator/antiterminator domain of Geobacillus kaustophilus glyS T-box, which lacks this domain, resulted in elevated transcription in the presence of tigecycline and facilitated discrimination among proteinogenic and nonproteinogenic tRNAGly isoacceptors. Overall, stem Sa represents a lineage-specific structural feature required for efficient staphylococcal glyS T-box-mediated transcription and it could serve as a species-selective druggable target through its ability to modulate antibiotic binding.

PMID:35580054 | DOI:10.1093/nar/gkac359

Nucleic Acids Res. 2022 May 17:gkac335. doi: 10.1093/nar/gkac335. Online ahead of print.

ABSTRACT

Biomedical researchers take advantage of high-throughput, high-coverage technologies to routinely generate sets of genes of interest across a wide range of biological conditions. Although these technologies have directly shed light on the molecular underpinnings of various biological processes and diseases, the list of genes from any individual experiment is often noisy and incomplete. Additionally, interpreting these lists of genes can be challenging in terms of how they are related to each other and to other genes in the genome. In this work, we present GenePlexus (https://www.geneplexus.net/), a web-server that allows a researcher to utilize a powerful, network-based machine learning method to gain insights into their gene set of interest and additional functionally similar genes. Once a user uploads their own set of human genes and chooses between a number of different human network representations, GenePlexus provides predictions of how associated every gene in the network is to the input set. The web-server also provides interpretability through network visualization and comparison to other machine learning models trained on thousands of known process/pathway and disease gene sets. GenePlexus is free and open to all users without the need for registration.

PMID:35580053 | DOI:10.1093/nar/gkac335

Nucleic Acids Res. 2022 May 17:gkac378. doi: 10.1093/nar/gkac378. Online ahead of print.

ABSTRACT

The importance of the quantitative description of protein unfolding and aggregation for the rational design of stability or understanding the molecular basis of protein misfolding diseases is well established. Protein thermostability is typically assessed by calorimetric or spectroscopic techniques that monitor different complementary signals during unfolding. The CalFitter webserver has already proved integral to deriving invaluable energy parameters by global data analysis. Here, we introduce CalFitter 2.0, which newly incorporates singular value decomposition (SVD) of multi-wavelength spectral datasets into the global fitting pipeline. Processed time- or temperature-evolved SVD components can now be fitted together with other experimental data types. Moreover, deconvoluted basis spectra provide spectral fingerprints of relevant macrostates populated during unfolding, which greatly enriches the information gains of the CalFitter output. The SVD analysis is fully automated in a highly interactive module, providing access to the results to users without any prior knowledge of the underlying mathematics. Additionally, a novel data uploading wizard has been implemented to facilitate rapid and easy uploading of multiple datasets. Together, the newly introduced changes significantly improve the user experience, making this software a unique, robust, and interactive platform for the analysis of protein thermal denaturation data. The webserver is freely accessible at https://loschmidt.chemi.muni.cz/calfitter.

PMID:35580052 | DOI:10.1093/nar/gkac378

Nucleic Acids Res. 2022 May 17:gkac357. doi: 10.1093/nar/gkac357. Online ahead of print.

ABSTRACT

The assembly of high molecular mass ribonucleoprotein complexes typically relies on the binary interaction of defined RNA sequences or precisely folded RNA motifs with dedicated RNA-binding domains on the protein side. Here we describe a new molecular recognition principle of RNA molecules by a high molecular mass protein complex. By chemically probing the solvent accessibility of mitochondrial pre-mRNAs when bound to the Trypanosoma brucei editosome, we identified multiple similar but non-identical RNA motifs as editosome contact sites. However, by treating the different motifs as mathematical graph objects we demonstrate that they fit a consensus 2D-graph consisting of 4 vertices (V) and 3 edges (E) with a Laplacian eigenvalue of 0.5477 (λ2). We establish that synthetic 4V(3E)-RNAs are sufficient to compete for the editosomal pre-mRNA binding site and that they inhibit RNA editing in vitro. Furthermore, we demonstrate that only two topological indices are necessary to predict the binding of any RNA motif to the editosome with a high level of confidence. Our analysis corroborates that the editosome has adapted to the structural multiplicity of the mitochondrial mRNA folding space by recognizing a fuzzy continuum of RNA folds that fit a consensus graph descriptor.

PMID:35580050 | DOI:10.1093/nar/gkac357

Nucleic Acids Res. 2022 May 17:gkac354. doi: 10.1093/nar/gkac354. Online ahead of print.

ABSTRACT

Chemical synthesis of RNA conjugates has opened new strategies to study enzymatic mechanisms in RNA biology. To gain insights into poorly understood RNA nucleotide methylation processes, we developed a new method to synthesize RNA-conjugates for the study of RNA recognition and methyl-transfer mechanisms of SAM-dependent m6A RNA methyltransferases. These RNA conjugates contain a SAM cofactor analogue connected at the N6-atom of an adenosine within dinucleotides, a trinucleotide or a 13mer RNA. Our chemical route is chemo- and regio-selective and allows flexible modification of the RNA length and sequence. These compounds were used in crystallization assays with RlmJ, a bacterial m6A rRNA methyltransferase. Two crystal structures of RlmJ in complex with RNA-SAM conjugates were solved and revealed the RNA-specific recognition elements used by RlmJ to clamp the RNA substrate in its active site. From these structures, a model of a trinucleotide bound in the RlmJ active site could be built and validated by methyltransferase assays on RlmJ mutants. The methyl transfer by RlmJ could also be deduced. This study therefore shows that RNA-cofactor conjugates are potent molecular tools to explore the active site of RNA modification enzymes.

PMID:35580049 | DOI:10.1093/nar/gkac354

Nucleic Acids Res. 2022 May 17:gkac355. doi: 10.1093/nar/gkac355. Online ahead of print.

ABSTRACT

Generation of haploid gametes depends on a modified version of homologous recombination in meiosis. Meiotic recombination is initiated by single-stranded DNA (ssDNA) ends originating from programmed DNA double-stranded breaks (DSBs) that are generated by the topoisomerase-related SPO11 enzyme. Meiotic recombination involves chromosomal synapsis, which enhances recombination-mediated DSB repair, and thus, crucially contributes to genome maintenance in meiocytes. Synapsis defects induce oocyte apoptosis ostensibly due to unrepaired DSBs that persist in asynaptic chromosomes. In mice, SPO11-deficient oocytes feature asynapsis, apoptosis and, surprisingly, numerous foci of the ssDNA-binding recombinase RAD51, indicative of DSBs of unknown origin. Hence, asynapsis is suggested to trigger apoptosis due to inefficient DSB repair even in mutants that lack programmed DSBs. By directly detecting ssDNAs, we discovered that RAD51 is an unreliable marker for DSBs in oocytes. Further, SPO11-deficient oocytes have fewer persistent ssDNAs than wild-type oocytes. These observations suggest that oocyte quality is safeguarded in mammals by a synapsis surveillance mechanism that can operate without persistent ssDNAs.

PMID:35580048 | DOI:10.1093/nar/gkac355

Nucleic Acids Res. 2022 May 17:gkac384. doi: 10.1093/nar/gkac384. Online ahead of print.

ABSTRACT

Cancer is a heterogeneous disease characterized by unregulated cell growth and promoted by mutations in cancer driver genes some of which encode suitable drug targets. Since the distinct set of cancer driver genes can vary between and within cancer types, evidence-based selection of drugs is crucial for targeted therapy following the precision medicine paradigm. However, many putative cancer driver genes can not be targeted directly, suggesting an indirect approach that considers alternative functionally related targets in the gene interaction network. Once potential drug targets have been identified, it is essential to consider all available drugs. Since tools that offer support for systematic discovery of drug repurposing candidates in oncology are lacking, we developed CADDIE, a web application integrating six human gene-gene and four drug-gene interaction databases, information regarding cancer driver genes, cancer-type specific mutation frequencies, gene expression information, genetically related diseases, and anticancer drugs. CADDIE offers access to various network algorithms for identifying drug targets and drug repurposing candidates. It guides users from the selection of seed genes to the identification of therapeutic targets or drug candidates, making network medicine algorithms accessible for clinical research. CADDIE is available at https://exbio.wzw.tum.de/caddie/ and programmatically via a python package at https://pypi.org/project/caddiepy/.

PMID:35580047 | DOI:10.1093/nar/gkac384

Nucleic Acids Res. 2022 May 17:gkac361. doi: 10.1093/nar/gkac361. Online ahead of print.

ABSTRACT

DDX58 encodes RIG-I, a cytosolic RNA sensor that ensures immune surveillance of nonself RNAs. Individuals with RIG-IE510V and RIG-IQ517H mutations have increased susceptibility to Singleton-Merten syndrome (SMS) defects, resulting in tissue-specific (mild) and classic (severe) phenotypes. The coupling between RNA recognition and conformational changes is central to RIG-I RNA proofreading, but the molecular determinants leading to dissociated disease phenotypes remain unknown. Herein, we employed hydrogen/deuterium exchange mass spectrometry (HDX-MS) and single molecule magnetic tweezers (MT) to precisely examine how subtle conformational changes in the helicase insertion domain (HEL2i) promote impaired ATPase and erroneous RNA proofreading activities. We showed that the mutations cause a loosened latch-gate engagement in apo RIG-I, which in turn gradually dampens its self RNA (Cap2 moiety:m7G cap and N1-2-2'-O-methylation RNA) proofreading ability, leading to increased immunopathy. These results reveal HEL2i as a unique checkpoint directing two specialized functions, i.e. stabilizing the CARD2-HEL2i interface and gating the helicase from incoming self RNAs; thus, these findings add new insights into the role of HEL2i in the control of antiviral innate immunity and autoimmunity diseases.

PMID:35580046 | DOI:10.1093/nar/gkac361

Nucleic Acids Res. 2022 May 17:gkac375. doi: 10.1093/nar/gkac375. Online ahead of print.

ABSTRACT

Non-homologous end joining (NHEJ) is the major pathway that mediates the repair of DNA double-strand breaks (DSBs) generated by ionizing radiation (IR). Previously, the DNA helicase RECQL4 was implicated in promoting NHEJ, but its role in the pathway remains unresolved. In this study, we report that RECQL4 stabilizes the NHEJ machinery at DSBs to promote repair. Specifically, we find that RECQL4 interacts with the NHEJ core factor DNA-PKcs and the interaction is increased following IR. RECQL4 promotes DNA end bridging mediated by DNA-PKcs and Ku70/80 in vitro and the accumulation/retention of NHEJ factors at DSBs in vivo. Moreover, interaction between DNA-PKcs and the other core NHEJ proteins following IR treatment is attenuated in the absence of RECQL4. These data indicate that RECQL4 promotes the stabilization of the NHEJ factors at DSBs to support formation of the NHEJ long-range synaptic complex. In addition, we observed that the kinase activity of DNA-PKcs is required for accumulation of RECQL4 to DSBs and that DNA-PKcs phosphorylates RECQL4 at six serine/threonine residues. Blocking phosphorylation at these sites reduced the recruitment of RECQL4 to DSBs, attenuated the interaction between RECQL4 and NHEJ factors, destabilized interactions between the NHEJ machinery, and resulted in decreased NHEJ. Collectively, these data illustrate reciprocal regulation between RECQL4 and DNA-PKcs in NHEJ.

PMID:35580045 | DOI:10.1093/nar/gkac375

Nucleic Acids Res. 2022 May 17:gkac373. doi: 10.1093/nar/gkac373. Online ahead of print.

ABSTRACT

The visualization of biological sequences with various functional elements is fundamental for the publication of scientific achievements in the field of molecular and cellular biology. However, due to the limitations of the currently used applications, there are still considerable challenges in the preparation of biological schematic diagrams. Here, we present a professional tool called IBS 2.0 for illustrating the organization of both protein and nucleotide sequences. With the abundant graphical elements provided in IBS 2.0, biological sequences can be easily represented in a concise and clear way. Moreover, we implemented a database visualization module in IBS 2.0, enabling batch visualization of biological sequences from the UniProt and the NCBI RefSeq databases. Furthermore, to increase the design efficiency, a resource platform that allows uploading, retrieval, and browsing of existing biological sequence diagrams has been integrated into IBS 2.0. In addition, a lightweight JS library was developed in IBS 2.0 to assist the visualization of biological sequences in customized web services. To obtain the latest version of IBS 2.0, please visit https://ibs.renlab.org.

PMID:35580044 | DOI:10.1093/nar/gkac373

Nucleic Acids Res. 2022 May 12:gkac358. doi: 10.1093/nar/gkac358. Online ahead of print.

ABSTRACT

During fasting, hepatocytes produce glucose in response to hormonal signals. Glucagon and glucocorticoids are principal fasting hormones that cooperate in regulating glucose production via gluconeogenesis. However, how these hormone signals are integrated and interpreted to a biological output is unknown. Here, we use genome-wide profiling of gene expression, enhancer dynamics and transcription factor (TF) binding in primary mouse hepatocytes to uncover the mode of cooperation between glucagon and glucocorticoids. We found that compared to a single treatment with each hormone, a dual treatment directs hepatocytes to a pro-gluconeogenic gene program by synergistically inducing gluconeogenic genes. The cooperative mechanism driving synergistic gene expression is based on 'assisted loading' whereby a glucagon-activated TF (cAMP responsive element binding protein; CREB) leads to enhancer activation which facilitates binding of the glucocorticoid receptor (GR) upon glucocorticoid stimulation. Glucagon does not only activate single enhancers but also activates enhancer clusters, thereby assisting the loading of GR also across enhancer units within the cluster. In summary, we show that cells integrate extracellular signals by an enhancer-specific mechanism: one hormone-activated TF activates enhancers, thereby assisting the loading of a TF stimulated by a second hormone, leading to synergistic gene induction and a tailored transcriptional response to fasting.

PMID:35556130 | DOI:10.1093/nar/gkac358

Nucleic Acids Res. 2022 May 12:gkac363. doi: 10.1093/nar/gkac363. Online ahead of print.

ABSTRACT

The NCBI Sequence Read Archive currently hosts microRNA sequencing data for over 800 different species, evidencing the existence of a broad taxonomic distribution in the field of small RNA research. Simultaneously, the number of samples per miRNA-seq study continues to increase resulting in a vast amount of data that requires accurate, fast and user-friendly analysis methods. Since the previous release of sRNAtoolbox in 2019, 55 000 sRNAbench jobs have been submitted which has motivated many improvements in its usability and the scope of the underlying annotation database. With this update, users can upload an unlimited number of samples or import them from Google Drive, Dropbox or URLs. Micro- and small RNA profiling can now be carried out using high-confidence Metazoan and plant specific databases, MirGeneDB and PmiREN respectively, together with genome assemblies and libraries from 441 Ensembl species. The new results page includes straightforward sample annotation to allow downstream differential expression analysis with sRNAde. Unassigned reads can also be explored by means of a new tool that performs mapping to microbial references, which can reveal contamination events or biologically meaningful findings as we describe in the example. sRNAtoolbox is available at: https://arn.ugr.es/srnatoolbox/.

PMID:35556129 | DOI:10.1093/nar/gkac363

Nucleic Acids Res. 2022 May 12:gkac337. doi: 10.1093/nar/gkac337. Online ahead of print.

ABSTRACT

Axonally synthesized proteins support nerve regeneration through retrograde signaling and local growth mechanisms. RNA binding proteins (RBP) are needed for this and other aspects of post-transcriptional regulation of neuronal mRNAs, but only a limited number of axonal RBPs are known. We used targeted proteomics to profile RBPs in peripheral nerve axons. We detected 76 proteins with reported RNA binding activity in axoplasm, and levels of several change with axon injury and regeneration. RBPs with altered levels include KHSRP that decreases neurite outgrowth in developing CNS neurons. Axonal KHSRP levels rapidly increase after injury remaining elevated up to 28 days post axotomy. Khsrp mRNA localizes into axons and the rapid increase in axonal KHSRP is through local translation of Khsrp mRNA in axons. KHSRP can bind to mRNAs with 3'UTR AU-rich elements and targets those transcripts to the cytoplasmic exosome for degradation. KHSRP knockout mice show increased axonal levels of KHSRP target mRNAs, Gap43, Snap25, and Fubp1, following sciatic nerve injury and these mice show accelerated nerve regeneration in vivo. Together, our data indicate that axonal translation of the RNA binding protein Khsrp mRNA following nerve injury serves to promote decay of other axonal mRNAs and slow axon regeneration.

PMID:35556128 | DOI:10.1093/nar/gkac337

Nucleic Acids Res. 2022 May 12:gkac374. doi: 10.1093/nar/gkac374. Online ahead of print.

ABSTRACT

Immune checkpoint blockade (ICB) therapy has been successfully applied to clinically therapeutics in multiple cancers, but its efficacy varies greatly among different patients and cancer types. Therefore, the construction of gene signatures to identify patients who could benefit from ICB therapy is particularly important for precision cancer treatment. However, due to the lack of a user-friendly platform, the construction of such gene signatures is a great challenge for clinical investigators who have limited programming skills. In light of this challenge, we developed a web server called Tumor Immunotherapy Response Signature Finder(TIRSF) for the construction of gene signatures to predict ICB therapy response in cancer patients. TIRSF consists of three functional modules. The first module is the Signature Discovery module which provides signature construction and performance evaluation functionalities. The second is a module for response prediction based on the TIRSF signatures, which enables response prediction and prognostic analysis of immunotherapy samples. The last is a module for response prediction based on existing signatures. This module currently integrates 24 published signatures for ICB therapy response prediction. Together, all of above features can be freely accessed at http://tirsf.renlab.org/.

PMID:35554556 | DOI:10.1093/nar/gkac374

Nucleic Acids Res. 2022 May 12:gkac365. doi: 10.1093/nar/gkac365. Online ahead of print.

ABSTRACT

Residue interaction networks (RINs) are used to represent residue contacts in protein structures. Thanks to the advances in network theory, RINs have been proved effective as an alternative to coordinate data in the analysis of complex systems. The RING server calculates high quality and reliable non-covalent molecular interactions based on geometrical parameters. Here, we present the new RING 3.0 version extending the previous functionality in several ways. The underlying software library has been re-engineered to improve speed by an order of magnitude. RING now also supports the mmCIF format and provides typed interactions for the entire PDB chemical component dictionary, including nucleic acids. Moreover, RING now employs probabilistic graphs, where multiple conformations (e.g. NMR or molecular dynamics ensembles) are mapped as weighted edges, opening up new ways to analyze structural data. The web interface has been expanded to include a simultaneous view of the RIN alongside a structure viewer, with both synchronized and clickable. Contact evolution across models (or time) is displayed as a heatmap and can help in the discovery of correlating interaction patterns. The web server, together with an extensive help and tutorial, is available from URL: https://ring.biocomputingup.it/.

PMID:35554554 | DOI:10.1093/nar/gkac365

Nucleic Acids Res. 2022 May 12:gkac342. doi: 10.1093/nar/gkac342. Online ahead of print.

ABSTRACT

Biomolecular associations forged by specific interaction among structural scaffolds are fundamental to the control and regulation of cell processes. One such structural architecture, characterized by HEAT repeats, is involved in a multitude of cellular processes, including intracellular transport, signaling, and protein synthesis. Here, we review the multitude and versatility of HEAT domains in the regulation of mRNA translation initiation. Structural and cellular biology approaches, as well as several biophysical studies, have revealed that a number of HEAT domain-mediated interactions with a host of protein factors and RNAs coordinate translation initiation. We describe the basic structural architecture of HEAT domains and briefly introduce examples of the cellular processes they dictate, including nuclear transport by importin and RNA degradation. We then focus on proteins in the translation initiation system featuring HEAT domains, specifically the HEAT domains of eIF4G, DAP5, eIF5, and eIF2Bϵ. Comparative analysis of their remarkably versatile interactions, including protein-protein and protein-RNA recognition, reveal the functional importance of flexible regions within these HEAT domains. Here we outline how HEAT domains orchestrate fundamental aspects of translation initiation and highlight open mechanistic questions in the area.

PMID:35552740 | DOI:10.1093/nar/gkac342

Nucleic Acids Res. 2022 May 12:gkac330. doi: 10.1093/nar/gkac330. Online ahead of print.

ABSTRACT

The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.

PMID:35552456 | DOI:10.1093/nar/gkac330

Nucleic Acids Res. 2022 May 12:gkac332. doi: 10.1093/nar/gkac332. Online ahead of print.

ABSTRACT

Quick growth restart after upon encountering favourable environmental conditions is a major fitness contributor in natural environment. It is widely assumed that the time required to restart growth after nutritional upshift is determined by how long it takes for cells to synthesize enough ribosomes to produce the proteins required to reinitiate growth. Here we show that a reduction in the capacity to synthesize ribosomes by reducing number of ribosomal RNA (rRNA) operons (rrn) causes a longer transition from stationary phase to growth of Escherichia coli primarily due to high mortality rates. Cell death results from DNA replication blockage and massive DNA breakage at the sites of the remaining rrn operons that become overloaded with RNA polymerases (RNAPs). Mortality rates and growth restart duration can be reduced by preventing R-loop formation and improving DNA repair capacity. The same molecular mechanisms determine the duration of the recovery phase after ribosome-damaging stresses, such as antibiotics, exposure to bile salts or high temperature. Our study therefore suggests that a major function of rrn operon multiplicity is to ensure that individual rrn operons are not saturated by RNAPs, which can result in catastrophic chromosome replication failure and cell death during adaptation to environmental fluctuations.

PMID:35552441 | DOI:10.1093/nar/gkac332

Nucleic Acids Res. 2022 May 12:gkac369. doi: 10.1093/nar/gkac369. Online ahead of print.

ABSTRACT

Deep learning has been applied for solving many biological problems, and it has shown outstanding performance. Applying deep learning in research requires knowledge of deep learning theories and programming skills, but researchers have developed diverse deep learning platforms to allow users to build deep learning models without programming. Despite these efforts, it is still difficult for biologists to use deep learning because of limitations of the existing platforms. Therefore, a new platform is necessary that can solve these challenges for biologists. To alleviate this situation, we developed a user-friendly and easy-to-use web application called DLEB (Deep Learning Editor for Biologists) that allows for building deep learning models specialized for biologists. DLEB helps researchers (i) design deep learning models easily and (ii) generate corresponding Python code to run directly in their machines. DLEB provides other useful features for biologists, such as recommending deep learning models for specific learning tasks and data, pre-processing of input biological data, and availability of various template models and example biological datasets for model training. DLEB can serve as a highly valuable platform for easily applying deep learning to solve many important biological problems. DLEB is freely available at http://dleb.konkuk.ac.kr/.

PMID:35552439 | DOI:10.1093/nar/gkac369

Nucleic Acids Res. 2022 May 20;50(9):5384-5399. doi: 10.1093/nar/gkac353.

ABSTRACT

Establishing saturated mutagenesis in a specific gene through gene editing is an efficient approach for identifying the relationships between mutations and the corresponding phenotypes. CRISPR/Cas9-based sgRNA library screening often creates indel mutations with multiple nucleotides. Single base editors and dual deaminase-mediated base editors can achieve only one and two types of base substitutions, respectively. A new glycosylase base editor (CGBE) system, in which the uracil glycosylase inhibitor (UGI) is replaced with uracil-DNA glycosylase (UNG), was recently reported to efficiently induce multiple base conversions, including C-to-G, C-to-T and C-to-A. In this study, we fused a CGBE with ABE to develop a new type of dual deaminase-mediated base editing system, the AGBE system, that can simultaneously introduce 4 types of base conversions (C-to-G, C-to-T, C-to-A and A-to-G) as well as indels with a single sgRNA in mammalian cells. AGBEs can be used to establish saturated mutant populations for verification of the functions and consequences of multiple gene mutation patterns, including single-nucleotide variants (SNVs) and indels, through high-throughput screening.

PMID:35544322 | PMC:PMC9122597 | DOI:10.1093/nar/gkac353

Nucleic Acids Res. 2022 May 11:gkac350. doi: 10.1093/nar/gkac350. Online ahead of print.

ABSTRACT

In the last decade, significant advances have been made towards the rational design of proteins, DNA, and other organic nanostructures. The emerging possibility to precisely engineer molecular structures resulted in a wide range of new applications in fields such as biotechnology or medicine. The complexity and size of the artificial molecular systems as well as the number of interactions are greatly increasing and are manifesting the need for computational design support. In addition, a new generation of AI-based structure prediction tools provides researchers with completely new possibilities to generate recombinant proteins and functionalized DNA nanostructures. In this study, we present Catana, a web-based modelling environment suited for proteins and DNA nanostructures. User-friendly features were developed to create and modify recombinant fusion proteins, predict protein structures based on the amino acid sequence, and manipulate DNA origami structures. Moreover, Catana was jointly developed with the novel Unified Nanotechnology Format (UNF). Therefore, it employs a state-of-the-art coarse-grained data model, that is compatible with other established and upcoming applications. A particular focus was put on an effortless data export to allow even inexperienced users to perform in silico evaluations of their designs by means of molecular dynamics simulations. Catana is freely available at http://catana.ait.ac.at/.

PMID:35544315 | DOI:10.1093/nar/gkac350

Nucleic Acids Res. 2022 May 20;50(9):5400. doi: 10.1093/nar/gkac390.

NO ABSTRACT

PMID:35544313 | PMC:PMC9122582 | DOI:10.1093/nar/gkac390

Nucleic Acids Res. 2022 May 11:gkac341. doi: 10.1093/nar/gkac341. Online ahead of print.

ABSTRACT

Genome binning has been essential for characterization of bacteria, archaea, and even eukaryotes from metagenomes. Yet, few approaches exist for viruses. We developed vRhyme, a fast and precise software for construction of viral metagenome-assembled genomes (vMAGs). vRhyme utilizes single- or multi-sample coverage effect size comparisons between scaffolds and employs supervised machine learning to identify nucleotide feature similarities, which are compiled into iterations of weighted networks and refined bins. To refine bins, vRhyme utilizes unique features of viral genomes, namely a protein redundancy scoring mechanism based on the observation that viruses seldom encode redundant genes. Using simulated viromes, we displayed superior performance of vRhyme compared to available binning tools in constructing more complete and uncontaminated vMAGs. When applied to 10,601 viral scaffolds from human skin, vRhyme advanced our understanding of resident viruses, highlighted by identification of a Herelleviridae vMAG comprised of 22 scaffolds, and another vMAG encoding a nitrate reductase metabolic gene, representing near-complete genomes post-binning. vRhyme will enable a convention of binning uncultivated viral genomes and has the potential to transform metagenome-based viral ecology.

PMID:35544285 | DOI:10.1093/nar/gkac341

Nucleic Acids Res. 2022 May 20;50(9):5080-5094. doi: 10.1093/nar/gkac344.

ABSTRACT

The Dlk1-Dio3 imprinted domain is controlled by an imprinting control region (ICR) called IG-DMR that is hypomethylated on the maternal allele and hypermethylated on the paternal allele. Although several genetic mutation experiments have shown that IG-DMR is essential for imprinting control of the domain, how DNA methylation itself functions has not been elucidated. Here, we performed both gain and loss of DNA methylation experiments targeting IG-DMR by transiently introducing CRISPR/Cas9 based-targeted DNA methylation editing tools along with one guide RNA into mouse ES cells. Altered DNA methylation, particularly at IG-DMR-Rep, which is a tandem repeat containing ZFP57 methylated DNA-binding protein binding motifs, affected the imprinting state of the whole domain, including DNA methylation, imprinted gene expression, and histone modifications. Moreover, the altered imprinting states were persistent through neuronal differentiation. Our results suggest that the DNA methylation state at IG-DMR-Rep, but not other sites in IG-DMR, is a master element to determine whether the allele behaves as the intrinsic maternal or paternal allele. Meanwhile, this study provides a robust strategy and methodology to study core DNA methylation in cis-regulatory elements, such as ICRs and enhancers.

PMID:35544282 | PMC:PMC9122602 | DOI:10.1093/nar/gkac344

Nucleic Acids Res. 2022 May 20;50(9):5095-5110. doi: 10.1093/nar/gkac346.

ABSTRACT

Promoters and enhancers are sites of transcription initiation (TSSs) and carry specific histone modifications, including H3K4me1, H3K4me3, and H3K27ac. Yet, the principles governing the boundaries of such regulatory elements are still poorly characterized. Alu elements are good candidates for a boundary function, being highly abundant in gene-rich regions, while essentially excluded from regulatory elements. Here, we show that the interval ranging from TSS to first upstream Alu, accommodates all H3K4me3 and most H3K27ac marks, while excluding DNA methylation. Remarkably, the average length of these intervals greatly varies in-between tissues, being longer in stem- and shorter in immune-cells. The very shortest TSS-to-first-Alu intervals were observed at promoters active in T-cells, particularly at immune genes, where first-Alus were traversed by RNA polymerase II transcription, while accumulating H3K4me1 signal. Finally, DNA methylation at first-Alus was found to evolve with age, regressing from young to middle-aged, then recovering later in life. Thus, the first-Alus upstream of TSSs appear as dynamic boundaries marking the transition from DNA methylation to active histone modifications at regulatory elements, while also participating in the recording of immune gene transcriptional events by positioning H3K4me1-modified nucleosomes.

PMID:35544277 | PMC:PMC9122584 | DOI:10.1093/nar/gkac346

Nucleic Acids Res. 2022 May 20;50(9):5313-5334. doi: 10.1093/nar/gkac327.

ABSTRACT

Alternative splicing is critical for development; however, its role in the specification of the three embryonic germ layers is poorly understood. By performing RNA-Seq on human embryonic stem cells (hESCs) and derived definitive endoderm, cardiac mesoderm, and ectoderm cell lineages, we detect distinct alternative splicing programs associated with each lineage. The most prominent splicing program differences are observed between definitive endoderm and cardiac mesoderm. Integrative multi-omics analyses link each program with lineage-enriched RNA binding protein regulators, and further suggest a widespread role for Quaking (QKI) in the specification of cardiac mesoderm. Remarkably, knockout of QKI disrupts the cardiac mesoderm-associated alternative splicing program and formation of myocytes. These changes arise in part through reduced expression of BIN1 splice variants linked to cardiac development. Mechanistically, we find that QKI represses inclusion of exon 7 in BIN1 pre-mRNA via an exonic ACUAA motif, and this is concomitant with intron removal and cleavage from chromatin. Collectively, our results uncover alternative splicing programs associated with the three germ lineages and demonstrate an important role for QKI in the formation of cardiac mesoderm.

PMID:35544276 | PMC:PMC9122611 | DOI:10.1093/nar/gkac327

Nucleic Acids Res. 2022 May 11:gkac312. doi: 10.1093/nar/gkac312. Online ahead of print.

ABSTRACT

RSAT (Regulatory Sequence Analysis Tools) enables the detection and the analysis of cis-regulatory elements in genomic sequences. This software suite performs (i) de novo motif discovery (including from genome-wide datasets like ChIP-seq/ATAC-seq) (ii) genomic sequences scanning with known motifs, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations and (v) comparative genomics. RSAT comprises 50 tools. Six public Web servers (including a teaching server) are offered to meet the needs of different biological communities. RSAT philosophy and originality are: (i) a multi-modal access depending on the user needs, through web forms, command-line for local installation and programmatic web services, (ii) a support for virtually any genome (animals, bacteria, plants, totalizing over 10 000 genomes directly accessible). Since the 2018 NAR Web Software Issue, we have developed a large REST API, extended the support for additional genomes and external motif collections, enhanced some tools and Web forms, and developed a novel tool that builds or refine gene regulatory networks using motif scanning (network-interactions). The RSAT website provides extensive documentation, tutorials and published protocols. RSAT code is under open-source license and now hosted in GitHub. RSAT is available at http://www.rsat.eu/.

PMID:35544234 | DOI:10.1093/nar/gkac312

Nucleic Acids Res. 2022 May 11:gkac324. doi: 10.1093/nar/gkac324. Online ahead of print.

ABSTRACT

Phylogenomics data have grown exponentially over the last decades. It is currently common for genome-wide projects to generate hundreds or even thousands of phylogenetic trees and multiple sequence alignments, which may also be very large in size. However, the analysis and interpretation of such data still depends on custom bioinformatic and visualisation workflows that are largely unattainable for non-expert users. Here, we present PhyloCloud, an online platform aimed at hosting, indexing and exploring large phylogenetic tree collections, providing also seamless access to common analyses and operations, such as node annotation, searching, topology editing, automatic tree rooting, orthology detection and more. In addition, PhyloCloud provides quick access to tools that allow users to build their own phylogenies using fast predefined workflows, graphically compare tree topologies, or query taxonomic databases such as NBCI or GTDB. Finally, PhyloCloud offers a novel tree visualisation system based on ETE Toolkit v4.0, which can be used to explore very large trees and enhance them with custom annotations and multiple sequence alignments. The platform allows for sharing tree collections and specific tree views via private links, or make them fully public, serving also as a repository of phylogenomic data. PhyloCloud is available at https://phylocloud.cgmlab.org.

PMID:35544233 | DOI:10.1093/nar/gkac324

Nucleic Acids Res. 2022 May 11:gkac345. doi: 10.1093/nar/gkac345. Online ahead of print.

ABSTRACT

Circular dichroism (CD) spectroscopy is widely used to characterize the secondary structure composition of proteins. To derive accurate and detailed structural information from the CD spectra, we have developed the Beta Structure Selection (BeStSel) method (PNAS, 112, E3095), which can handle the spectral diversity of β-structured proteins. The BeStSel webserver provides this method with useful accessories to the community with the main goal to analyze single or multiple protein CD spectra. Uniquely, BeStSel provides information on eight secondary structure components including parallel β-structure and antiparallel β-sheets with three different groups of twist. It overperforms any available method in accuracy and information content, moreover, it is capable of predicting the protein fold down to the topology/homology level of the CATH classification. A new module of the webserver helps to distinguish intrinsically disordered proteins by their CD spectrum. Secondary structure calculation for uploaded PDB files will help the experimental verification of protein MD and in silico modelling using CD spectroscopy. The server also calculates extinction coefficients from the primary sequence for CD users to determine the accurate protein concentrations which is a prerequisite for reliable secondary structure determination. The BeStSel server can be freely accessed at https://bestsel.elte.hu.

PMID:35544232 | DOI:10.1093/nar/gkac345

Nucleic Acids Res. 2022 May 20;50(9):5191-5207. doi: 10.1093/nar/gkac334.

ABSTRACT

Bacteria are under constant assault by bacteriophages and other mobile genetic elements. As a result, bacteria have evolved a multitude of systems that protect from attack. Genes encoding bacterial defence mechanisms can be clustered into 'defence islands', providing a potentially synergistic level of protection against a wider range of assailants. However, there is a comparative paucity of information on how expression of these defence systems is controlled. Here, we functionally characterize a transcriptional regulator, BrxR, encoded within a recently described phage defence island from a multidrug resistant plasmid of the emerging pathogen Escherichia fergusonii. Using a combination of reporters and electrophoretic mobility shift assays, we discovered that BrxR acts as a repressor. We present the structure of BrxR to 2.15 Å, the first structure of this family of transcription factors, and pinpoint a likely binding site for ligands within the WYL-domain. Bioinformatic analyses demonstrated that BrxR-family homologues are widespread amongst bacteria. About half (48%) of identified BrxR homologues were co-localized with a diverse array of known phage defence systems, either alone or clustered into defence islands. BrxR is a novel regulator that reveals a common mechanism for controlling the expression of the bacterial phage defence arsenal.

PMID:35544231 | PMC:PMC9122601 | DOI:10.1093/nar/gkac334

Nucleic Acids Res. 2022 May 20;50(9):5335-5348. doi: 10.1093/nar/gkac292.

ABSTRACT

Eukaryotic uL11 contains a conserved MPPKFDP motif at the N-terminus that is not found in archaeal and bacterial homologs. Here, we determined the solution structure of human uL11 by NMR spectroscopy and characterized its backbone dynamics by 15N-1H relaxation experiments. We showed that these N-terminal residues are unstructured and flexible. Structural comparison with ribosome-bound uL11 suggests that the linker region between the N-terminal domain and C-terminal domain of human uL11 is intrinsically disordered and only becomes structured when bound to the ribosomes. Mutagenesis studies show that the N-terminal conserved MPPKFDP motif is involved in interacting with the P-complex and its extended protuberant domain of uL10 in vitro. Truncation of the MPPKFDP motif also reduced the poly-phenylalanine synthesis in both hybrid ribosome and yeast mutagenesis studies. In addition, G→A/P substitutions to the conserved GPLG motif of helix-1 reduced poly-phenylalanine synthesis to 9-32% in yeast ribosomes. We propose that the flexible N-terminal residues of uL11, which could extend up to ∼25 Å from the N-terminal domain of uL11, can form transient interactions with the uL10 that help to fetch and fix it into a position ready for recruiting the incoming translation factors and facilitate protein synthesis.

PMID:35544198 | PMC:PMC9122527 | DOI:10.1093/nar/gkac292

Nucleic Acids Res. 2022 May 10:gkac349. doi: 10.1093/nar/gkac349. Online ahead of print.

ABSTRACT

Proteins with similar phylogenetic patterns of conservation or loss across evolutionary taxa are strong candidates to work in the same cellular pathways or engage in physical or functional interactions. Our previously published tools implemented our method of normalized phylogenetic sequence profiling to detect functional associations between non-homologous proteins. However, many proteins consist of multiple protein domains subjected to different selective pressures, so using protein domain as the unit of analysis improves the detection of similar phylogenetic patterns. Here we analyze sequence conservation patterns across the whole tree of life for every protein domain from a set of widely studied organisms. The resulting new interactive webserver, DEPCOD (DEtection of Phylogenetically COrrelated Domains), performs searches with either a selected pre-defined protein domain or a user-supplied sequence as a query to detect other domains from the same organism that have similar conservation patterns. Top similarities on two evolutionary scales (the whole tree of life or eukaryotic genomes) are displayed along with known protein interactions and shared complexes, pathway enrichment among the hits, and detailed visualization of sources of detected similarities. DEPCOD reveals functional relationships between often non-homologous domains that could not be detected using whole-protein sequences. The web server is accessible at http://genetics.mgh.harvard.edu/DEPCOD.

PMID:35536332 | DOI:10.1093/nar/gkac349

Nucleic Acids Res. 2022 May 20;50(9):4900-4916. doi: 10.1093/nar/gkac347.

ABSTRACT

RNA can be extensively modified post-transcriptionally with >170 covalent modifications, expanding its functional and structural repertoire. Pseudouridine (Ψ), the most abundant modified nucleoside in rRNA and tRNA, has recently been found within mRNA molecules. It remains unclear whether pseudouridylation of mRNA can be snoRNA-guided, bearing important implications for understanding the physiological target spectrum of snoRNAs and for their potential therapeutic exploitation in genetic diseases. Here, using a massively parallel reporter based strategy we simultaneously interrogate Ψ levels across hundreds of synthetic constructs with predesigned complementarity against endogenous snoRNAs. Our results demonstrate that snoRNA-mediated pseudouridylation can occur on mRNA targets. However, this is typically achieved at relatively low efficiencies, and is constrained by mRNA localization, snoRNA expression levels and the length of the snoRNA:mRNA complementarity stretches. We exploited these insights for the design of snoRNAs targeting pseudouridylation at premature termination codons, which was previously shown to suppress translational termination. However, in this and follow-up experiments in human cells we observe no evidence for significant levels of readthrough of pseudouridylated stop codons. Our study enhances our understanding of the scope, 'design rules', constraints and consequences of snoRNA-mediated pseudouridylation.

PMID:35536311 | PMC:PMC9122591 | DOI:10.1093/nar/gkac347

Nucleic Acids Res. 2022 May 10:gkac294. doi: 10.1093/nar/gkac294. Online ahead of print.

ABSTRACT

As of today, the majority of environmental microorganisms remain uncultured and is therefore referred to as 'microbial dark matter' (MDM). Hence, genomic insights into these organisms are limited to cultivation-independent approaches such as single-cell- and metagenomics. However, without access to cultured representatives for verifying correct taxon-assignments, MDM genomes may cause potentially misleading conclusions based on misclassified or contaminant contigs, thereby obfuscating our view on the uncultured microbial majority. Moreover, gradual database contaminations by past genome submissions can cause error propagations which affect present as well as future comparative genome analyses. Consequently, strict contamination detection and filtering need to be applied, especially in the case of uncultured MDM genomes. Current genome reporting standards, however, emphasize completeness over purity and the de facto gold standard genome assessment tool, checkM, discriminates against uncultured taxa and fragmented genomes. To tackle these issues, we present a novel contig classification, screening, and filtering workflow and corresponding open-source python implementation called MDMcleaner, which was tested and compared to other tools on mock and real datasets. MDMcleaner revealed substantial contaminations overlooked by current screening approaches and sensitively detects misattributed contigs in both novel genomes and the underlying reference databases, thereby greatly improving our view on 'microbial dark matter'.

PMID:35536293 | DOI:10.1093/nar/gkac294

Nucleic Acids Res. 2022 May 10:gkac336. doi: 10.1093/nar/gkac336. Online ahead of print.

ABSTRACT

Cells contain intracellular compartments, including membrane-bound organelles and the nucleus, and are surrounded by a plasma membrane. Proteins are localised to one or more of these cellular compartments; the correct localisation of proteins is crucial for their correct processing and function. Moreover, proteins and the cellular processes they partake in are regulated by relocalisation in response to various cellular stimuli. High-throughput 'omics experiments result in a list of proteins or genes of interest; one way in which their functional role can be understood is through the knowledge of their subcellular localisation, as deduced through statistical enrichment for Gene Ontology Cellular Component (GOCC) annotations or similar. We have designed a bioinformatics tool, named SubcellulaRVis, that compellingly visualises the results of GOCC enrichment for quick interpretation of the localisation of a group of proteins (rather than single proteins). We demonstrate that SubcellulaRVis precisely describes the subcellular localisation of gene lists whose locations have been previously ascertained. SubcellulaRVis can be accessed via the web (http://phenome.manchester.ac.uk/subcellular/) or as a stand-alone app (https://github.com/JoWatson2011/subcellularvis). SubcellulaRVis will be useful for experimental biologists with limited bioinformatics expertise who want to analyse data related to protein (re)localisation and location-specific modules within the intracellular protein network.

PMID:35536291 | DOI:10.1093/nar/gkac336

Nucleic Acids Res. 2022 May 10:gkac310. doi: 10.1093/nar/gkac310. Online ahead of print.

ABSTRACT

With the proliferation of genomic sequence data for biomedical research, the exploration of human genetic information by domain experts requires a comprehensive interrogation of large numbers of scientific publications in PubMed. However, a query in PubMed essentially provides search results sorted only by the date of publication. A search engine for retrieving and interpreting complex relations between biomedical concepts in scientific publications remains lacking. Here, we present pubmedKB, a web server designed to extract and visualize semantic relationships between four biomedical entity types: variants, genes, diseases, and chemicals. pubmedKB uses state-of-the-art natural language processing techniques to extract semantic relations from the large number of PubMed abstracts. Currently, over 2 million semantic relations between biomedical entity pairs are extracted from over 33 million PubMed abstracts in pubmedKB. pubmedKB has a user-friendly interface with an interactive semantic graph, enabling the user to easily query entities and explore entity relations. Supporting sentences with the highlighted snippets allow to easily navigate the publications. Combined with a new explorative approach to literature mining and an interactive interface for researchers, pubmedKB thus enables rapid, intelligent searching of the large biomedical literature to provide useful knowledge and insights. pubmedKB is available at https://www.pubmedkb.cc/.

PMID:35536289 | DOI:10.1093/nar/gkac310

Nucleic Acids Res. 2022 May 10:gkac320. doi: 10.1093/nar/gkac320. Online ahead of print.

ABSTRACT

Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited in their ability to separate transcriptionally similar cell types and can suffer further difficulties identifying cell types in slide regions where transcript capture is low. Here, we describe a conceptually novel methodology that can computationally integrate spatial transcriptomics data with cell-type-informative paired tissue images, obtained from, for example, the reverse side of the same tissue section, to improve inferences of tissue cell type composition in spatial transcriptomics data. The underlying statistical approach is generalizable to any spatial transcriptomics protocol where informative paired tissue images can be obtained. We demonstrate a use case leveraging cell-type-specific immunofluorescence markers obtained on mouse brain tissue sections and a use case for leveraging the output of AI annotated H&E tissue images, which we used to markedly improve the identification of clinically relevant immune cell infiltration in breast cancer tissue. Thus, combining spatial transcriptomics data with paired tissue images has the potential to improve the identification of cell types and hence to improve the applications of spatial transcriptomics that rely on accurate cell type identification.

PMID:35536287 | DOI:10.1093/nar/gkac320

Nucleic Acids Res. 2022 May 10:gkac322. doi: 10.1093/nar/gkac322. Online ahead of print.

ABSTRACT

Here we present ICARUS, a web server to enable users without experience in R to undertake single cell RNA-seq analysis. The focal point of ICARUS is its intuitive tutorial-style user interface, designed to guide logical navigation through the multitude of pre-processing, analysis and visualization steps. ICARUS is easily accessible through a dedicated web server (https://launch.icarus-scrnaseq.cloud.edu.au/) and avoids installation of software on the user's computer. Notable features include the facility to apply quality control thresholds and adjust dimensionality reduction and cell clustering parameters. Data is visualized through 2D/3D UMAP and t-SNE plots and may be curated to remove potential confounders such as cell cycle heterogeneity. ICARUS offers flexible differential expression analysis with user-defined cell groups and gene set enrichment analysis to identify likely affected biological pathways. Eleven organisms including human, dog, mouse, rat, zebrafish, fruit fly, nematode, yeast, cattle, chicken and pig are currently supported. Visualization of multimodal data including those generated by CITE-seq and the 10X Genomics Multiome kit is included. ICARUS incorporates a function to save the current state of analysis avoiding computationally intensive steps during repeat analysis. The complete analysis of a typical single cell RNA-seq dataset by inexperienced users may be achieved in 1-2 h.

PMID:35536286 | DOI:10.1093/nar/gkac322

Nucleic Acids Res. 2022 May 10:gkac340. doi: 10.1093/nar/gkac340. Online ahead of print.

ABSTRACT

Most proteins in nature contain multiple folding units (or domains). The revolutionary success of AlphaFold2 in single-domain structure prediction showed potential to extend deep-learning techniques for multi-domain structure modeling. This work presents a significantly improved method, DEMO2, which integrates analogous template structural alignments with deep-learning techniques for high-accuracy domain structure assembly. Starting from individual domain models, inter-domain spatial restraints are first predicted with deep residual convolutional networks, where full-length structure models are assembled using L-BFGS simulations under the guidance of a hybrid energy function combining deep-learning restraints and analogous multi-domain template alignments searched from the PDB. The output of DEMO2 contains deep-learning inter-domain restraints, top-ranked multi-domain structure templates, and up to five full-length structure models. DEMO2 was tested on a large-scale benchmark and the blind CASP14 experiment, where DEMO2 was shown to significantly outperform its predecessor and the state-of-the-art protein structure prediction methods. By integrating with new deep-learning techniques, DEMO2 should help fill the rapidly increasing gap between the improved ability of tertiary structure determination and the high demand for the high-quality multi-domain protein structures. The DEMO2 server is available at https://zhanggroup.org/DEMO/.

PMID:35536281 | DOI:10.1093/nar/gkac340

Nucleic Acids Res. 2022 May 20;50(9):5239-5250. doi: 10.1093/nar/gkac343.

ABSTRACT

Bacteria use diverse immune systems to defend themselves from ubiquitous viruses termed bacteriophages (phages). Many anti-phage systems function by abortive infection to kill a phage-infected cell, raising the question of how they are regulated to avoid cell killing outside the context of infection. Here, we identify a transcription factor associated with the widespread CBASS bacterial immune system, that we term CapW. CapW forms a homodimer and binds a palindromic DNA sequence in the CBASS promoter region. Two crystal structures of CapW suggest that the protein switches from an unliganded, DNA binding-competent state to a ligand-bound state unable to bind DNA. We show that CapW strongly represses CBASS gene expression in uninfected cells, and that phage infection causes increased CBASS expression in a CapW-dependent manner. Unexpectedly, this CapW-dependent increase in CBASS expression is not required for robust anti-phage activity, suggesting that CapW may mediate CBASS activation and cell death in response to a signal other than phage infection. Our results parallel concurrent reports on the structure and activity of BrxR, a transcription factor associated with the BREX anti-phage system, suggesting that CapW and BrxR are members of a family of universal defense signaling proteins.

PMID:35536256 | PMC:PMC9122588 | DOI:10.1093/nar/gkac343

Nucleic Acids Res. 2022 May 10:gkac333. doi: 10.1093/nar/gkac333. Online ahead of print.

ABSTRACT

Cell-cell interactions are the fundamental building blocks of tissue organization and multicellular life. We developed Neighbor-seq, a method to identify and annotate the architecture of direct cell-cell interactions and relevant ligand-receptor signaling from the undissociated cell fractions in massively parallel single cell sequencing data. Neighbor-seq accurately identifies microanatomical features of diverse tissue types such as the small intestinal epithelium, terminal respiratory tract, and splenic white pulp. It also captures the differing topologies of cancer-immune-stromal cell communications in pancreatic and skin tumors, which are consistent with the patterns observed in spatial transcriptomic data. Neighbor-seq is fast and scalable. It draws inferences from routine single-cell data and does not require prior knowledge about sample cell-types or multiplets. Neighbor-seq provides a framework to study the organ-level cellular interactome in health and disease, bridging the gap between single-cell and spatial transcriptomics.

PMID:35536255 | DOI:10.1093/nar/gkac333

Nucleic Acids Res. 2022 May 20;50(9):4860-4876. doi: 10.1093/nar/gkac339.

ABSTRACT

The expansion of d(CGG) trinucleotide repeats (TRs) lies behind several important neurodegenerative diseases. Atypical DNA secondary structures have been shown to trigger TR expansion: their characterization is important for a molecular understanding of TR disease. CD spectroscopy experiments in the last decade have unequivocally demonstrated that CGG runs adopt a left-handed Z-DNA conformation, whose features remain uncertain because it entails accommodating GG mismatches. In order to find this missing motif, we have carried out molecular dynamics (MD) simulations to explore all the possible Z-DNA helices that potentially form after the transition from B- to Z-DNA. Such helices combine either CpG or GpC Watson-Crick steps in Z-DNA form with GG-mismatch conformations set as either intrahelical or extrahelical; and participating in BZ or ZZ junctions or in alternately extruded conformations. Characterization of the stability and structural features (especially overall left-handedness, higher-temperature and steered MD simulations) identified two novel Z-DNA helices: the most stable one displays alternately extruded Gs, and is followed by a helix with symmetrically extruded ZZ junctions. The G-extrusion favors a seamless stacking of the Watson-Crick base pairs; extruded Gs favor syn conformations and display hydrogen-bonding and stacking interactions. Such conformations could have the potential to hijack the MMR complex, thus triggering further expansion.

PMID:35536254 | PMC:PMC9122592 | DOI:10.1093/nar/gkac339

Nucleic Acids Res. 2022 May 10:gkac286. doi: 10.1093/nar/gkac286. Online ahead of print.

ABSTRACT

BioUML (https://www.biouml.org)-is a web-based integrated platform for systems biology and data analysis. It supports visual modelling and construction of hierarchical biological models that allow us to construct the most complex modular models of blood pressure regulation, skeletal muscle metabolism, COVID-19 epidemiology. BioUML has been integrated with git repositories where users can store their models and other data. We have also expanded the capabilities of BioUML for data analysis and visualization of biomedical data: (i) any programs and Jupyter kernels can be plugged into the BioUML platform using Docker technology; (ii) BioUML is integrated with the Galaxy and Galaxy Tool Shed; (iii) BioUML provides two-way integration with R and Python (Jupyter notebooks): scripts can be executed on the BioUML web pages, and BioUML functions can be called from scripts; (iv) using plug-in architecture, specialized viewers and editors can be added. For example, powerful genome browsers as well as viewers for molecular 3D structure are integrated in this way; (v) BioUML supports data analyses using workflows (own format, Galaxy, CWL, BPMN, nextFlow). Using these capabilities, we have initiated a new branch of the BioUML development-u-science-a universal scientific platform that can be configured for specific research requirements.

PMID:35536253 | DOI:10.1093/nar/gkac286

Nucleic Acids Res. 2022 May 10:gkac313. doi: 10.1093/nar/gkac313. Online ahead of print.

ABSTRACT

BioTransformer 3.0 (https://biotransformer.ca) is a freely available web server that supports accurate, rapid and comprehensive in silico metabolism prediction. It combines machine learning approaches with a rule-based system to predict small-molecule metabolism in human tissues, the human gut as well as the external environment (soil and water microbiota). Simply stated, BioTransformer takes a molecular structure as input (SMILES or SDF) and outputs an interactively sortable table of the predicted metabolites or transformation products (SMILES, PNG images) along with the enzymes that are predicted to be responsible for those reactions and richly annotated downloadable files (CSV and JSON). The entire process typically takes less than a minute. Previous versions of BioTransformer focused exclusively on predicting the metabolism of xenobiotics (such as plant natural products, drugs, cosmetics and other synthetic compounds) using a limited number of pre-defined steps and somewhat limited rule-based methods. BioTransformer 3.0 uses much more sophisticated methods and incorporates new databases, new constraints and new prediction modules to not only more accurately predict the metabolic transformation products of exogenous xenobiotics but also the transformation products of endogenous metabolites, such as amino acids, peptides, carbohydrates, organic acids, and lipids. BioTransformer 3.0 can also support customized sequential combinations of these transformations along with multiple iterations to simulate multi-step human biotransformation events. Performance tests indicate that BioTransformer 3.0 is 40-50% more accurate, far less prone to combinatorial 'explosions' and much more comprehensive in terms of metabolite coverage/capabilities than previous versions of BioTransformer.

PMID:35536252 | DOI:10.1093/nar/gkac313

Nucleic Acids Res. 2022 May 10:gkac326. doi: 10.1093/nar/gkac326. Online ahead of print.

ABSTRACT

Interpretation of non-coding genome remains an unsolved challenge in human genetics due to impracticality of exhaustively annotating biochemically active elements in all conditions. Deep learning based computational approaches emerge recently to help interpret non-coding regions. Here, we present LOGO (Language of Genome), a self-attention based contextualized pre-trained language model containing only two self-attention layers with 1 million parameters as a substantially light architecture that applies self-supervision techniques to learn bidirectional representations of the unlabelled human reference genome. LOGO is then fine-tuned for sequence labelling task, and further extended to variant prioritization task via a special input encoding scheme of alternative alleles followed by adding a convolutional module. Experiments show that LOGO achieves 15% absolute improvement for promoter identification and up to 4.5% absolute improvement for enhancer-promoter interaction prediction. LOGO exhibits state-of-the-art multi-task predictive power on thousands of chromatin features with only 3% parameterization benchmarking against the fully supervised model, DeepSEA and 1% parameterization against a recent BERT-based DNA language model. For allelic-effect prediction, locality introduced by one dimensional convolution shows improved sensitivity and specificity for prioritizing non-coding variants associated with human diseases. In addition, we apply LOGO to interpret type 2 diabetes (T2D) GWAS signals and infer underlying regulatory mechanisms. We make a conceptual analogy between natural language and human genome and demonstrate LOGO is an accurate, fast, scalable, and robust framework to interpret non-coding regions for global sequence labeling as well as for variant prioritization at base-resolution.

PMID:35536244 | DOI:10.1093/nar/gkac326