Sequence-based Search Research Articles

SID-2 is a conserved extracellular vesicle protein that is not associated with environmental RNAi in parasitic nematodes.

In the free-living nematode Caenorhabditis elegans, the transmembrane protein SID-2 imports double-stranded RNA into intestinal cells to trigger systemic RNA interference (RNAi), allowing organisms to sense and respond to environmental cues such as the presence of pathogens. This process, known as environmental RNAi, has not been observed in the most closely related parasites that are also within clade V. Previous sequence-based searches failed to identify sid-2 orthologues in available clade V parasite genomes. In this study, we identified sid-2 orthologues in these parasites using genome synteny and protein structure-based comparison, following identification of a SID-2 orthologue in extracellular vesicles from the murine intestinal parasitic nematode Heligmosomoides bakeri. Expression of GFP-tagged H. bakeri SID-2 in C. elegans showed similar localization to the intestinal apical membrane as seen for GFP-tagged C. elegans SID-2, and further showed mobility in intestinal cells in vesicle-like structures. We tested the capacity of H. bakeri SID-2 to functionally complement environmental RNAi in a C. elegans SID-2 null mutant and show that H. bakeri SID-2 does not rescue the phenotype in this context. Our work identifies SID-2 as a highly abundant EV protein whose ancestral function may be unrelated to environmental RNAi, and rather highlights an association with extracellular vesicles in nematodes.

Almost 40 years of studying homeobox genes in C. elegans.

Homeobox genes are among the most deeply conserved families of transcription factor-encoding genes. Following their discovery in Drosophila, homeobox genes arrived on the Caenorhabditis elegans stage with a vengeance. Between 1988 and 1990, just a few years after their initial discovery in flies and vertebrates, positional cloning and sequence-based searches showed that C. elegans contains HOX cluster genes, an apparent surprise given the simplicity and non-segmented body plan of the nematode, as well as many other non-clustered homeobox genes of all major subfamilies (e.g. LIM, POU, etc.). Not quite 40 years later, we have an exceptionally deep understanding of homeodomain protein expression and function in C. elegans, revealing their prevalent role in nervous system development. In this Spotlight, we provide a historical perspective and a non-comprehensive journey through the C. elegans homeobox field and discuss open questions and future directions.

Semantic search using protein large language models detects class II microcins in bacterial genomes.

Antibiotic resistance is becoming an increasingly serious problem in modern medicine, but the development pipeline for conventional antibiotics is not promising. Therefore, alternative approaches to combat bacterial infections are urgently needed. One such approach may be to employ naturally occurring antibacterial peptides produced by bacteria to kill competing bacteria. A promising class of such peptides are class II microcins. However, only a small number of class II microcins have been discovered to date, and the discovery of further such microcins has been hampered by their high sequence divergence and short length, which can cause sequence-based search methods to fail. Here, we demonstrate that a more robust method for microcin discovery can be built on the basis of a protein large language model, and we use this method to identify several putative novel class II microcins.

Harnessing the 3D-Beacons Network: A Comprehensive Guide to Accessing and Displaying Protein Structure Data.

Recent advancements in protein structure determination and especially in protein structure prediction techniques have led to the availability of vast amounts of macromolecular structures. However, the accessibility and integration of these structures into scientific workflows are hindered by the lack of standardization among publicly available data resources. To address this issue, we introduced the 3D-Beacons Network, a unified platform that aims to establish a standardized framework for accessing and displaying protein structure data. In this article, we highlight the importance of standardized approaches for accessing protein structure data and showcase the capabilities of 3D-Beacons. We describe four protocols for finding and accessing macromolecular structures from various specialist data resources via 3D-Beacons. First, we describe three scenarios for programmatically accessing and retrieving data using the 3D-Beacons API. Next, we show how to perform sequence-based searches to find structures from model providers. Then, we demonstrate how to search for structures and fetch them directly into a workflow using JalView. Finally, we outline the process of facilitating access to data from providers interested in contributing their structures to the 3D-Beacons Network. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Programmatic access to the 3D-Beacons API Basic Protocol 2: Sequence-based search using the 3D-Beacons API Basic Protocol 3: Accessing macromolecules from 3D-Beacons with JalView Basic Protocol 4: Enhancing data accessibility through 3D-Beacons.

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation–enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

The antiSMASH database version 4: additional genomes and BGCs, new sequence-based searchesand more.

Many microorganisms produce natural products that are frequently used in the development of medicines and crop protection agents. Genome mining has evolved into a prominent method to access this potential. antiSMASH is the most popular tool for this task. Here we present version 4 of the antiSMASH database, providing biosynthetic gene clusters detected by antiSMASH 7.1 in publicly available, dereplicated, high-quality microbial genomes via an interactive graphical user interface. In version 4, the database contains 231534 high quality BGC regions from 592 archaeal, 35726 bacterialand 236 fungal genomes and is available at https://antismash-db.secondarymetabolites.org/.

An archaeal lid-containing feruloyl esterase degrades polyethylene terephthalate

Polyethylene terephthalate (PET) is a commodity polymer known to globally contaminate marine and terrestrial environments. Today, around 80 bacterial and fungal PET-active enzymes (PETases) are known, originating from four bacterial and two fungal phyla. In contrast, no archaeal enzyme had been identified to degrade PET. Here we report on the structural and biochemical characterization of PET46 (RLI42440.1), an archaeal promiscuous feruloyl esterase exhibiting degradation activity on semi-crystalline PET powder comparable to IsPETase and LCC (wildtypes), and higher activity on bis-, and mono-(2-hydroxyethyl) terephthalate (BHET and MHET). The enzyme, found by a sequence-based metagenome search, is derived from a non-cultivated, deep-sea Candidatus Bathyarchaeota archaeon. Biochemical characterization demonstrated that PET46 is a promiscuous, heat-adapted hydrolase. Its crystal structure was solved at a resolution of 1.71 Å. It shares the core alpha/beta-hydrolase fold with bacterial PETases, but contains a unique lid common in feruloyl esterases, which is involved in substrate binding. Thus, our study widens the currently known diversity of PET-hydrolyzing enzymes, by demonstrating PET depolymerization by a plant cell wall-degrading esterase.

Comparison, Analysis, and Molecular Dynamics Simulations of Structures of a Viral Protein Modeled Using Various Computational Tools.

The structural analysis of proteins is a major domain of biomedical research. Such analysis requires resolved three-dimensional structures of proteins. Advancements in computer technology have led to progress in biomedical research. In silico prediction and modeling approaches have facilitated the construction of protein structures, with or without structural templates. In this study, we used three neural network-based de novo modeling approaches-AlphaFold2 (AF2), Robetta-RoseTTAFold (Robetta), and transform-restrained Rosetta (trRosetta)-and two template-based tools-the Molecular Operating Environment (MOE) and iterative threading assembly refinement (I-TASSER)-to construct the structure of a viral capsid protein, hepatitis C virus core protein (HCVcp), whose structure have not been fully resolved by laboratory techniques. Templates with sufficient sequence identity for the homology modeling of complete HCVcp are currently unavailable. Therefore, we performed domain-based homology modeling for MOE simulations. The templates for each domain were obtained through sequence-based searches on NCBI and the Protein Data Bank. Then, the modeled domains were assembled to construct the complete structure of HCVcp. The full-length structure and two truncated forms modeled using various computational tools were compared. Molecular dynamics (MD) simulations were performed to refine the structures. The root mean square deviation of backbone atoms, root mean square fluctuation of Cα atoms, and radius of gyration were calculated to monitor structural changes and convergence in the simulations. The model quality was evaluated through ERRAT and phi-psi plot analysis. In terms of the initial prediction for protein modeling, Robetta and trRosetta outperformed AF2. Regarding template-based tools, MOE outperformed I-TASSER. MD simulations resulted in compactly folded protein structures, which were of good quality and theoretically accurate. Thus, the predicted structures of certain proteins must be refined to obtain reliable structural models. MD simulation is a promising tool for this purpose.

Heterologous Expression and Partial Characterization of a Putative Opine Dehydrogenase from a Metagenomic Sequence of Desulfohalobium retbaense.

The aim of this research was to prove the function of the putative opine dehydrogenase from Desulfohalobium retbaense and to characterize the enzyme in terms of functional and kinetic parameters. A putative opine dehydrogenase was identified from a metagenomic library by a sequence-based technique search of the metagenomic library, and afterward was successfully heterologously produced in Escherichia coli. In order to examine its potential for applications in the synthesis of secondary amines, first the substrate specificity of the enzyme towards different amino donors and amino acceptors was determined. The highest affinity was observed towards small amino acids, preferentially L-alanine, and when it comes to α-keto acids, pyruvate proved to be a preferential amino acceptor. The highest activity was observed at pH 6.5 in the absence of salts. The enzyme showed remarkable stability in a wide range of experimental conditions, such as broad pH stability (from 6.0-11.0 after 30 min incubation in buffers at a certain pH), stability in the presence of NaCl up to 3.0 M for 24 h, it retained 80 % of the initial activity after 1 h incubation at 45 °C, and 65 % of the initial activity after 24 h incubation in 30 % dimethyl sulfoxide.

The metagenome-derived esterase PET40 is highly promiscuous and hydrolyses polyethylene terephthalate (PET).

Polyethylene terephthalate (PET) is a widely used synthetic polymer and known to contaminate marine and terrestrial ecosystems. Only few PET-active microorganisms and enzymes (PETases) are currently known, and it is debated whether degradation activity for PET originates from promiscuous enzymes with broad substrate spectra that primarily act on natural polymers or other bulky substrates, or whether microorganisms evolved their genetic makeup to accepting PET as a carbon source. Here, we present a predicted diene lactone hydrolase designated PET40, which acts on a broad spectrum of substrates, including PET. It is the first esterase with activity on PET from a GC-rich Gram-positive Amycolatopsis species belonging to the Pseudonocardiaceae (Actinobacteria). It is highly conserved within the genera Amycolatopsis and Streptomyces. PET40 was identified by sequence-based metagenome search using a PETase-specific hidden Markov model. Besides acting on PET, PET40 has a versatile substrate spectrum, hydrolyzing δ-lactones, β-lactam antibiotics, the polyester-polyurethane Impranil® DLN, and various para-nitrophenyl ester substrates. Molecular docking suggests that the PET degradative activity is likely a result of the promiscuity of PET40, as potential binding modes were found for substrates encompassing mono(2-hydroxyethyl) terephthalate, bis(2-hydroxyethyl) terephthalate, and a PET trimer. We also solved the crystal structure of the inactive PET40 variant S178A to 1.60 Å resolution. PET40 is active throughout a wide pH (pH 4-10) and temperature range (4-65 °C) and remarkably stable in the presence of 5% SDS, making it a promising enzyme as a starting point for further investigations and optimization approaches.

A bioinformatic analysis of zinc transporters in intestinal Lactobacillaceae.

As the second most abundant transition element and a crucial cofactor for many proteins, zinc is essential for the survival of all living organisms. To maintain required zinc levels and prevent toxic overload, cells and organisms have a collection of metal transport proteins for uptake and efflux of zinc. In bacteria, metal transport proteins are well defined for model organisms and many pathogens, but fewer studies have explored metal transport proteins, including those for zinc, in commensal bacteria from the gut microbiota. The healthy human gut microbiota comprises hundreds of species and among these, bacteria from the Lactobacillaceae family are well documented to have various beneficial effects on health. Furthermore, changes in dietary metal intake, such as for zinc and iron, are frequently correlated with changes in abundance of Lactobacillaceae. Few studies have explored zinc requirements and zinc homeostasis mechanisms in Lactobacillaceae, however. Here we applied a bioinformatics approach to identify and compare predicted zinc uptake and efflux proteins in several Lactobacillaceae genera of intestinal relevance. Few Lactobacillaceae had zinc transporters currently annotated in proteomes retrieved from the UniProt database, but protein sequence-based homology searches revealed that high-affinity ABC transporter genes are likely common, albeit with genus-specific domain features. P-type ATPase transporters are probably also common and some Lactobacillaceae genera code for predicted zinc efflux cation diffusion facilitators. This analysis confirms that Lactobacillaceae harbor genes for various zinc transporter homologs, and provides a foundation for systematic experimental studies to elucidate zinc homeostasis mechanisms in these bacteria.

Next POI Recommendation with Dynamic Graph and Explicit Dependency

Next Point-Of-Interest (POI) recommendation plays an important role in various location-based services. Its main objective is to predict the user's next interested POI based on her previous check-in information. Most existing methods directly use users' historical check-in trajectories to construct various graphs to assist sequential models to complete this task. However, as users' check-in data is extremely sparse, it is difficult to capture the potential relations between POIs by directly using these check-in data. To this end, we propose the Sequence-based Neighbour search and Prediction Model (SNPM) for next POI recommendation. In SNPM, the RotatE knowledge graph embedding and Eigenmap methods are used to extract POI relationships implied in check-in data, and build the POI similarity graph. Then, we enhance the model's generalized representations of POIs' general features by aggregating similar POIs. As the context is typically rich and valuable when making Next POI predictions, the sequence model selects which POIs to aggregate not only depends on the current state, but also needs to consider the previous POI sequence. Therefore, we construct a Sequence-based, Dynamic Neighbor Graph (SDNG) to find the similarity neighbourhood and develop a Multi-Step Dependency Prediction model (MSDP) inspired by RotatE, which explicitly leverage information from previous states. We evaluate the proposed model on two real-world datasets, and the experimental results show that the proposed method significantly outperforms existing state-of-the-art POI recommendation methods.

Betacoronaviral lectins: Identification through a genomic search—A structural and evolutionary biology perspective

Carbohydrate-binding proteins known as “Lectins” play a crucial role in host-pathogen interactions. Most of the viral surface proteins have lectin activity. In fact, they make the first line of communication with the host cells. Recent reports indicating the haemagglutination property and structural evidences of coronaviral protein bound with Sialic acid (Sia) draw our attention to exploring the presence of lectins in the Betacoronavirus genus from reference genomes. We have considered the seventeen reference genomes of different species and subspecies under the Betacoronavirus genus to identify lectin fold/domain(s) types. We have employed three strategies for characterizing lectin fold/domain(s). The strategies include the sequence-based search against the conserved domain database (CDD) and profile HMMER and Structure-based search against Protein Data Bank (PDB) and unified platform of lectins UniLectin3D database. Interestingly, both the identified proteins, namely Hemagglutinin-esterase (HE) and Spike (S) protein, were localized on viral membranes and played a pivotal role in host-pathogen interactions. These protein structures are fabricated by most pliable β-strands forming varied architectures and topologies, such as β-sandwich, jelly-roll fold, β-barrel, β-prism, β-trefoil, β-propeller and β-hairpins. The identified lectin fold/domain(s) were compared with the characterized ones and were docked with Sia using HADDOCK, and the binding affinity was calculated using the PRODIGY server. Molecular docking studies reveal that all the identified lectin fold/domains agree with the Canyon hypothesis. Furthermore, it could be observed that coronaviruses are constantly evolving by shedding their extra baggage. The latter variants were found to have only the lectin domain but not the esterase domain.

A computational approach for the identification of distant homologs of bacterial riboswitches based on inverse RNA folding.

Riboswitches are conserved structural ribonucleic acid (RNA) sensors that are mainly found to regulate a large number of genes/operons in bacteria. Presently, >50 bacterial riboswitch classes have been discovered, but only the thiamine pyrophosphate riboswitch class is detected in a few eukaryotes like fungi, plants and algae. One of the most important challenges in riboswitch research is to discover existing riboswitch classes in eukaryotes and to understand the evolution of bacterial riboswitches. However, traditional search methods for riboswitch detection have failed to detect eukaryotic riboswitches besides just one class and any distant structural homologs of riboswitches. We developed a novel approach based on inverse RNA folding that attempts to find sequences that match the shape of the target structure with minimal sequence conservation based on key nucleotides that interact directly with the ligand. Then, to support our matched candidates, we expanded the results into a covariance model representing similar sequences preserving the structure. Our method transforms a structure-based search into a sequence-based search that considers the conservation of secondary structure shape and ligand-binding residues. This method enables us to identify a potential structural candidate in fungi that could be the distant homolog of bacterial purine riboswitches. Further, phylogenomic analysis and evolutionary distribution of this structural candidate indicate that the most likely point of origin of this structural candidate in these organisms is associated with the loss of traditional purine riboswitches. The computational approach could be applicable to other domains and problems in RNA research.

BASISMAP: sequence-based similarity search for geomagnetic positioning

Indoor localization has become a popular topic with the development of location-based services (LBS) and indoor navigation systems. Beside these circumstances indoor positioning has been the focus of attention for researchers as the most important component of these applications. Many signals are used as distinguishable features for indoor positioning. RF-based Wi-Fi and BLE systems are the most popular ones and these have been preferred because of their high distinguishable feature. The use of geomagnetism, a natural signal found all over the world, has also been of interest to many researchers. Geomagnetic signals being distorted in the indoor area due to the effect of the structure by using that information takes opportunity to determine the relevant location. In this study, a new method is proposed to convert these unknown signals into location data using a magnetic fingerprint database. The sequential data collected using a dynamic comparison buffer in motion is evaluated with the help of the similarity search method called matrix profile, and position is obtained. The study was compared with other methods in the literature and its prominent and weak points were shared. The performance of the study was evaluated using site-survey by collecting data in an office environment. It has been concluded that the cumulative error is below 2.2 m in the normal operating phase of the system on a 100-m-long path. Compared to the literature, a low complexity and efficient solution is proposed. Furthermore, matrix-profile-based path matching method was used for the first time in magnetic sequence-based localization.

Bioassay-Guided Fractionation Leads to the Detection of Cholic Acid Generated by the Rare Thalassomonas sp.

Bacterial symbionts of marine invertebrates are rich sources of novel, pharmaceutically relevant natural products that could become leads in combatting multidrug-resistant pathogens and treating disease. In this study, the bioactive potential of the marine invertebrate symbiont Thalassomonas actiniarum was investigated. Bioactivity screening of the strain revealed Gram-positive specific antibacterial activity as well as cytotoxic activity against a human melanoma cell line (A2058). The dereplication of the active fraction using HPLC-MS led to the isolation and structural elucidation of cholic acid and 3-oxo cholic acid. T. actiniarum is one of three type species belonging to the genus Thalassomonas. The ability to generate cholic acid was assessed for all three species using thin-layer chromatography and was confirmed by LC-MS. The re-sequencing of all three Thalassomonas type species using long-read Oxford Nanopore Technology (ONT) and Illumina data produced complete genomes, enabling the bioinformatic assessment of the ability of the strains to produce cholic acid. Although a complete biosynthetic pathway for cholic acid synthesis in this genus could not be determined based on sequence-based homology searches, the identification of putative penicillin or homoserine lactone acylases in all three species suggests a mechanism for the hydrolysis of conjugated bile acids present in the growth medium, resulting in the generation of cholic acid and 3-oxo cholic acid. With little known currently about the bioactivities of this genus, this study serves as the foundation for future investigations into their bioactive potential as well as the potential ecological role of bile acid transformation, sterol modification and quorum quenching by Thalassomonas sp. in the marine environment.

SeqCP: A sequence-based algorithm for searching circularly permuted proteins

Circular permutation (CP) is a protein sequence rearrangement in which the amino- and carboxyl-termini of a protein can be created in different positions along the imaginary circularized sequence. Circularly permutated proteins usually exhibit conserved three-dimensional structures and functions. By comparing the structures of circular permutants (CPMs), protein research and bioengineering applications can be approached in ways that are difficult to achieve by traditional mutagenesis. Most current CP detection algorithms depend on structural information. Because there is a vast number of proteins with unknown structures, many CP pairs may remain unidentified. An efficient sequence-based CP detector will help identify more CP pairs and advance many protein studies. For instance, some hypothetical proteins may have CPMs with known functions and structures that are informative for functional annotation, but existing structure-based CP search methods cannot be applied when those hypothetical proteins lack structural information. Despite the considerable potential for applications, sequence-based CP search methods have not been well developed. We present a sequence-based method, SeqCP, which analyzes normal and duplicated sequence alignments to identify CPMs and determine candidate CP sites for proteins. SeqCP was trained by data obtained from the Circular Permutation Database and tested with nonredundant datasets from the Protein Data Bank. It shows high reliability in CP identification and achieves an AUC of 0.9. SeqCP has been implemented into a web server available at: http://pcnas.life.nthu.edu.tw/SeqCP/.

Folding and Evolution of a Repeat Protein on the Ribosome

Life on earth is the result of the work of proteins, the cellular nanomachines that fold into elaborated 3D structures to perform their functions. The ribosome synthesizes all the proteins of the biosphere, and many of them begin to fold during translation in a process known as cotranslational folding. In this work we discuss current advances of this field and provide computational and experimental data that highlight the role of ribosome in the evolution of protein structures. First, we used the sequence of the Ankyrin domain from the Drosophila Notch receptor to launch a deep sequence-based search. With this strategy, we found a conserved 33-residue motif shared by different protein folds. Then, to see how the vectorial addition of the motif would generate a full structure we measured the folding on the ribosome of the Ankyrin repeat protein. Not only the on-ribosome folding data is in full agreement with classical in vitro biophysical measurements but also it provides experimental evidence on how folded proteins could have evolved by duplication and fusion of smaller fragments in the RNA world. Overall, we discuss how the ribosomal exit tunnel could be conceptualized as an active site that is under evolutionary pressure to influence protein folding.

3DLigandSite: structure-based prediction of protein-ligand binding sites.

3DLigandSite is a web tool for the prediction of ligand-binding sites in proteins. Here, we report a significant update since the first release of 3DLigandSite in 2010. The overall methodology remains the same, with candidate binding sites in proteins inferred using known binding sites in related protein structures as templates. However, the initial structural modelling step now uses the newly available structures from the AlphaFold database or alternatively Phyre2 when AlphaFold structures are not available. Further, a sequence-based search using HHSearch has been introduced to identify template structures with bound ligands that are used to infer the ligand-binding residues in the query protein. Finally, we introduced a machine learning element as the final prediction step, which improves the accuracy of predictions and provides a confidence score for each residue predicted to be part of a binding site. Validation of 3DLigandSite on a set of 6416 binding sites obtained 92% recall at 75% precision for non-metal binding sites and 52% recall at 75% precision for metal binding sites. 3DLigandSite is available at https://www.wass-michaelislab.org/3dligandsite. Users submit either a protein sequence or structure. Results are displayed in multiple formats including an interactive Mol* molecular visualization of the protein and the predicted binding sites.

Sequence-Based Searching for SynBioHub Using VSEARCH

The ability to search for a part by its sequence is crucial for a large repository of parts. Prior to this work, however, this was not possible on SynBioHub. Sequence-based search is now integrated into SynBioHub, allowing users to find a part by a sequence provided in plain text or a supported file format. This sequence-based search feature is accessible to users via SynBioHub's web interface, or programmatically through its API. The core implementation of the tool uses VSEARCH, an open source, global alignment search tool, and it is integrated into SBOLExplorer, an open source distributed search engine used by SynBioHub. We present a new approach to scoring part similarity using SBOLExplorer, which takes into account both the popularity and percentage match of parts.