Biochemical and in silico structural characterization of a cold-active arginase from the psychrophilic yeast, Glaciozyma antarctica PI12.

Glaciozyma antarctica PI12 is a psychrophilic yeast isolated from Antarctica. In this work, we describe the heterologous production, biochemical properties and in silico structure analysis of an arginase from this yeast (GaArg). GaArg is a metalloenzyme that catalyses the hydrolysis of L-arginine to L-ornithine and urea. The cDNA of GaArg was reversed transcribed, cloned, expressed and purified as a recombinant protein in Escherichia coli. The purified protein was active against L-arginine as its substrate in a reaction at 20 °C, pH 9. At 10-35 °C and pH 7-9, the catalytic activity of the protein was still present around 50%. Mn2+, Ni2+, Co2+ and K+ were able to enhance the enzyme activity more than two-fold, while GaArg is most sensitive to SDS, EDTA and DTT. The predicted structure model of GaArg showed a very similar overall fold with other known arginases. GaArg possesses predominantly smaller and uncharged amino acids, fewer salt bridges, hydrogen bonds and hydrophobic interactions compared to the other counterparts. GaArg is the first reported arginase that is cold-active, facilitated by unique structural characteristics for its adaptation of catalytic functions at low-temperature environments. The structure and function of cold-active GaArg provide insights into the potentiality of new applications in various biotechnology and pharmaceutical industries.

GrAfSS: a webserver for substructure similarity searching and comparisons in the structures of proteins and RNA.

The GrAfSS (Graph theoretical Applications for Substructure Searching) webserver is a platform to search for three-dimensional substructures of: (i) amino acid side chains in protein structures; and (ii) base arrangements in RNA structures. The webserver interfaces the functions of five different graph theoretical algorithms - ASSAM, SPRITE, IMAAAGINE, NASSAM and COGNAC - into a single substructure searching suite. Users will be able to identify whether a three-dimensional (3D) arrangement of interest, such as a ligand binding site or 3D motif, observed in a protein or RNA structure can be found in other structures available in the Protein Data Bank (PDB). The webserver also allows users to determine whether a protein or RNA structure of interest contains substructural arrangements that are similar to known motifs or 3D arrangements. These capabilities allow for the functional annotation of new structures that were either experimentally determined or computationally generated (such as the coordinates generated by AlphaFold2) and can provide further insights into the diversity or conservation of functional mechanisms of structures in the PDB. The computed substructural superpositions are visualized using integrated NGL viewers. The GrAfSS server is available at http://mfrlab.org/grafss/.

Dissecting the Biology of Rafflesia Species: Current Progress and Future Directions Made Possible with High-Throughput Sequencing Data.

The angiosperm Rafflesia exhibits a unique biology, including a growth strategy that involves endophytic parasitism of a specific host, with only the gigantic flower externally visible. The Rafflesia possesses many unique evolutionary, developmental and morphological features that are rooted in yet-to-be-explained physiological processes. Although studies on the molecular biology of Rafflesia are limited by sampling difficulties due to its rarity in the wild and the short life span of its flower, current advances in high-throughput sequencing technology have allowed for the genome- and transcriptome-level dissection of the molecular mechanisms behind the unique characteristics of this parasitic plant. In this review, we summarize major findings on the cryptic biology of Rafflesia and provide insights into future research directions. The wealth of data obtained can improve our understanding of Rafflesia species and contribute toward the conservation strategy of this endangered plant.

Regulation of Glycine Cleavage and Detoxification by a Highly Conserved Glycine Riboswitch in Burkholderia spp.

The glycine riboswitch is a known regulatory element that is unique in having two aptamers that are joined by a linker region. In this study, we investigated a glycine riboswitch located in the 5' untranslated region of a glycine cleavage system homolog (gcvTHP) in Burkholderia spp. Structure prediction using the sequence generated a model with a glycine binding pocket composed of base-triple interactions (G62-A64-A86 and G65-U84-C85) that are supported by A/G minor interactions (A17-C60-G88 and G16-C61-G87, respectively) and two ribose-zipper motifs (C11-G12 interacting with A248-A247 and C153-U154 interacting with A79-A78) which had not been previously reported. The capacity of the riboswitch to bind to glycine was experimentally validated by native gel assays and the crucial role of interactions that make up the glycine binding pocket were proven by mutations of A17U and G16C which resulted in conformational differences that may lead to dysfunction. Using glycine supplemented minimal media, we were able to prove that the expression of the gcvTHP genes found downstream of the riboswitch responded to the glycine concentrations introduced thus confirming the role of this highly conserved Burkholderia riboswitch and its associated genes as a putative glycine detoxification system in Burkholderia spp.

Drug ReposER: a web server for predicting similar amino acid arrangements to known drug binding interfaces for potential drug repositioning.

A common drug repositioning strategy is the re-application of an existing drug to address alternative targets. A crucial aspect to enable such repurposing is that the drug's binding site on the original target is similar to that on the alternative target. Based on the assumption that proteins with similar binding sites may bind to similar drugs, the 3D substructure similarity data can be used to identify similar sites in other proteins that are not known targets. The Drug ReposER (DRug REPOSitioning Exploration Resource) web server is designed to identify potential targets for drug repurposing based on sub-structural similarity to the binding interfaces of known drug binding sites. The application has pre-computed amino acid arrangements from protein structures in the Protein Data Bank that are similar to the 3D arrangements of known drug binding sites thus allowing users to explore them as alternative targets. Users can annotate new structures for sites that are similarly arranged to the residues found in known drug binding interfaces. The search results are presented as mappings of matched sidechain superpositions. The results of the searches can be visualized using an integrated NGL viewer. The Drug ReposER server has no access restrictions and is available at http://mfrlab.org/drugreposer/.

Graph Theoretical Methods and Workflows for Searching and Annotation of RNA Tertiary Base Motifs and Substructures.

The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when searching for tertiary base motifs and substructures. Such base arrangements and motifs have diverse roles that range from contributions to structural stability to more direct involvement in the molecule's functions, such as the sites for ligand binding and catalytic activity. We review the utility of computational approaches in annotating RNA tertiary base motifs in a dataset of PDB structures, particularly the use of graph theoretical algorithms that can search for such base motifs and annotate them or find and annotate clusters of hydrogen-bond-connected bases. We also demonstrate how such graph theoretical algorithms can be integrated into a workflow that allows for functional analysis and comparisons of base arrangements and sub-structures, such as those involved in ligand binding. The capacity to carry out such automatic curations has led to the discovery of novel motifs and can give new context to known motifs as well as enable the rapid compilation of RNA 3D motifs into a database.

Computational discovery and annotation of conserved small open reading frames in fungal genomes.

BACKGROUND: Small open reading frames (smORF/sORFs) that encode short protein sequences are often overlooked during the standard gene prediction process thus leading to many sORFs being left undiscovered and/or misannotated. For many genomes, a second round of sORF targeted gene prediction can complement the existing annotation. In this study, we specifically targeted the identification of ORFs encoding for 80 amino acid residues or less from 31 fungal genomes. We then compared the predicted sORFs and analysed those that are highly conserved among the genomes. RESULTS: A first set of sORFs was identified from existing annotations that fitted the maximum of 80 residues criterion. A second set was predicted using parameters that specifically searched for ORF candidates of 80 codons or less in the exonic, intronic and intergenic sequences of the subject genomes. A total of 1986 conserved sORFs were predicted and characterized. CONCLUSIONS: It is evident that numerous open reading frames that could potentially encode for polypeptides consisting of 80 amino acid residues or less are overlooked during standard gene prediction and annotation. From our results, additional targeted reannotation of genomes is clearly able to complement standard genome annotation to identify sORFs. Due to the lack of, and limitations with experimental validation, we propose that a simple conservation analysis can provide an acceptable means of ensuring that the predicted sORFs are sufficiently clear of gene prediction artefacts.

InterRNA: a database of base interactions in RNA structures.

A major component of RNA structure stabilization are the hydrogen bonded interactions between the base residues. The importance and biological relevance for large clusters of base interactions can be much more easily investigated when their occurrences have been systematically detected, catalogued and compared. In this paper, we describe the database InterRNA (INTERactions in RNA structures database-http://mfrlab.org/interrna/) that contains records of known RNA 3D motifs as well as records for clusters of bases that are interconnected by hydrogen bonds. The contents of the database were compiled from RNA structural annotations carried out by the NASSAM (http://mfrlab.org/grafss/nassam) and COGNAC (http://mfrlab.org/grafss/cognac) computer programs. An analysis of the database content and comparisons with the existing corpus of knowledge regarding RNA 3D motifs clearly show that InterRNA is able to provide an extension of the annotations for known motifs as well as able to provide novel interactions for further investigations.

Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data.

BACKGROUND: Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion. RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure). CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.

An analysis of simple computational strategies to facilitate the design of functional molecular information processors.

BACKGROUND: Biological macromolecules (DNA, RNA and proteins) are capable of processing physical or chemical inputs to generate outputs that parallel conventional Boolean logical operators. However, the design of functional modules that will enable these macromolecules to operate as synthetic molecular computing devices is challenging. RESULTS: Using three simple heuristics, we designed RNA sensors that can mimic the function of a seven-segment display (SSD). Ten independent and orthogonal sensors representing the numerals 0 to 9 are designed and constructed. Each sensor has its own unique oligonucleotide binding site region that is activated uniquely by a specific input. Each operator was subjected to a stringent in silico filtering. Random sensors were selected and functionally validated via ribozyme self cleavage assays that were visualized via electrophoresis. CONCLUSIONS: By utilising simple permutation and randomisation in the sequence design phase, we have developed functional RNA sensors thus demonstrating that even the simplest of computational methods can greatly aid the design phase for constructing functional molecular devices.

COGNAC: a web server for searching and annotating hydrogen-bonded base interactions in RNA three-dimensional structures.

Hydrogen bonds are crucial factors that stabilize a complex ribonucleic acid (RNA) molecule's three-dimensional (3D) structure. Minute conformational changes can result in variations in the hydrogen bond interactions in a particular structure. Furthermore, networks of hydrogen bonds, especially those found in tight clusters, may be important elements in structure stabilization or function and can therefore be regarded as potential tertiary motifs. In this paper, we describe a graph theoretical algorithm implemented as a web server that is able to search for unbroken networks of hydrogen-bonded base interactions and thus provide an accounting of such interactions in RNA 3D structures. This server, COGNAC (COnnection tables Graphs for Nucleic ACids), is also able to compare the hydrogen bond networks between two structures and from such annotations enable the mapping of atomic level differences that may have resulted from conformational changes due to mutations or binding events. The COGNAC server can be accessed at http://mfrlab.org/grafss/cognac.

Characterization of Burkholderia pseudomallei protein BPSL1375 validates the Putative hemolytic activity of the COG3176 N-Acyltransferase family.

BACKGROUND: There are still numerous protein subfamilies within families and superfamilies that do not yet have conclusive empirical experimental evidence providing a specific function. These proteins persist in databases with the annotation of a specific 'putative' function made by association with discernible features in the protein sequence. RESULTS: Here, we report the characterization of one such protein produced by the pathogenic soil bacterium Burkholderia pseudomallei, BPSL1375, which provided evidence for putative hemolysins in the COG3176 family to have experimentally validated hemolytic activity. BPSL1375 can be classified into the N-acyltransferase superfamily, specifically to members of the COG3176 family. Sequence alignments identified seven highly conserved residues (Arg54, Phe58, Asp75, Asp78, Arg99, Glu132 and Arg135), of which several have been implicated with N-acyltransferase activity in previously characterized examples. Using the 3D model of an N-acyltransferase example as a reference, an acyl homoserine lactone synthase, we generated 3D structure models for mutants of six of the seven N-acyltransferase conserved residues (R54, D75, D78, R99, E132 and R135). Both the R99 and R135 mutants resulted in a loss of hemolytic activity while mutations at the other five positions resulted in either reduction or increment in hemolytic activity. CONCLUSIONS: The implication of residues previously characterized to be important for N-acyltransferase activity to hemolytic activity for the COG3176 family members of the N-acyltransferase provides validation of the correct placement of the hemolytic capability annotation within the N-acyltransferase superfamily.

IMAAAGINE: a webserver for searching hypothetical 3D amino acid side chain arrangements in the Protein Data Bank.

We describe a server that allows the interrogation of the Protein Data Bank for hypothetical 3D side chain patterns that are not limited to known patterns from existing 3D structures. A minimal side chain description allows a variety of side chain orientations to exist within the pattern, and generic side chain types such as acid, base and hydroxyl-containing can be additionally deployed in the search query. Moreover, only a subset of distances between the side chains need be specified. We illustrate these capabilities in case studies involving arginine stacks, serine-acid group arrangements and multiple catalytic triad-like configurations. The IMAAAGINE server can be accessed at http://mfrlab.org/grafss/imaaagine/.

The genome of the Tiger Milk mushroom, Lignosus rhinocerotis, provides insights into the genetic basis of its medicinal properties.

BACKGROUND: The sclerotium of Lignosus rhinocerotis (Cooke) Ryvarden or Tiger milk mushroom (Polyporales, Basidiomycota) is a valuable folk medicine for indigenous peoples in Southeast Asia. Despite the increasing interest in this ethnobotanical mushroom, very little is known about the molecular and genetic basis of its medicinal and nutraceutical properties. RESULTS: The de novo assembled 34.3 Mb L. rhinocerotis genome encodes 10,742 putative genes with 84.30% of them having detectable sequence similarities to others available in public databases. Phylogenetic analysis revealed a close evolutionary relationship of L. rhinocerotis to Ganoderma lucidum, Dichomitus squalens, and Trametes versicolor in the core polyporoid clade. The L. rhinocerotis genome encodes a repertoire of enzymes engaged in carbohydrate and glycoconjugate metabolism, along with cytochrome P450s, putative bioactive proteins (lectins and fungal immunomodulatory proteins) and laccases. Other genes annotated include those encoding key enzymes for secondary metabolite biosynthesis, including those from polyketide, nonribosomal peptide, and triterpenoid pathways. Among them, the L. rhinocerotis genome is particularly enriched with sesquiterpenoid biosynthesis genes. CONCLUSIONS: The genome content of L. rhinocerotis provides insights into the genetic basis of its reported medicinal properties as well as serving as a platform to further characterize putative bioactive proteins and secondary metabolite pathway enzymes and as a reference for comparative genomics of polyporoid fungi.

NASSAM: a server to search for and annotate tertiary interactions and motifs in three-dimensional structures of complex RNA molecules.

Similarities in the 3D patterns of RNA base interactions or arrangements can provide insights into their functions and roles in stabilization of the RNA 3D structure. Nucleic Acids Search for Substructures and Motifs (NASSAM) is a graph theoretical program that can search for 3D patterns of base arrangements by representing the bases as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. The input files for NASSAM are PDB formatted 3D coordinates. This web server can be used to identify matches of base arrangement patterns in a query structure to annotated patterns that have been reported in the literature or that have possible functional and structural stabilization implications. The NASSAM program is freely accessible without any login requirement at http://mfrlab.org/grafss/nassam/.

SPRITE and ASSAM: web servers for side chain 3D-motif searching in protein structures.

Similarities in the 3D patterns of amino acid side chains can provide insights into their function despite the absence of any detectable sequence or fold similarities. Search for protein sites (SPRITE) and amino acid pattern search for substructures and motifs (ASSAM) are graph theoretical programs that can search for 3D amino side chain matches in protein structures, by representing the amino acid side chains as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. Both programs require the input file to be in the PDB format. The objective of using SPRITE is to identify matches of side chains in a query structure to patterns with characterized function. In contrast, a 3D pattern of interest can be searched for existing occurrences in available PDB structures using ASSAM. Both programs are freely accessible without any login requirement. SPRITE is available at http://mfrlab.org/grafss/sprite/ while ASSAM can be accessed at http://mfrlab.org/grafss/assam/.

Structural dissection of two redox proteins from the shipworm symbiont Teredinibacter turnerae.

The discovery of lytic polysaccharide monooxygenases (LPMOs), a family of copper-dependent enzymes that play a major role in polysaccharide degradation, has revealed the importance of oxidoreductases in the biological utilization of biomass. In fungi, a range of redox proteins have been implicated as working in harness with LPMOs to bring about polysaccharide oxidation. In bacteria, less is known about the interplay between redox proteins and LPMOs, or how the interaction between the two contributes to polysaccharide degradation. We therefore set out to characterize two previously unstudied proteins from the shipworm symbiont Teredinibacter turnerae that were initially identified by the presence of carbohydrate binding domains appended to uncharacterized domains with probable redox functions. Here, X-ray crystal structures of several domains from these proteins are presented together with initial efforts to characterize their functions. The analysis suggests that the target proteins are unlikely to function as LPMO electron donors, raising new questions as to the potential redox functions that these large extracellular multi-haem-containing c-type cytochromes may perform in these bacteria.

Biofilm Signaling, Composition and Regulation in Burkholderia pseudomallei.

The incidence of melioidosis cases caused by the gram-negative pathogen Burkholderia pseudomallei (BP) is seeing an increasing trend that has spread beyond its previously known endemic regions. Biofilms produced by BP have been associated with antimicrobial therapy limitation and relapse melioidosis, thus making it urgently necessary to understand the mechanisms of biofilm formation and their role in BP biology. Microbial cells aggregate and enclose within a self-produced matrix of extracellular polymeric substances (EPSs) to form biofilm. The transition mechanism of bacterial cells from planktonic state to initiate biofilm formation, which involves the formation of surface attachment microcolonies and the maturation of the biofilm matrix, is a dynamic and complex process. Despite the emerging findings on the biofilm formation process, systemic knowledge on the molecular mechanisms of biofilm formation in BP remains fractured. This review provides insights into the signaling systems, matrix composition, and the biosynthesis regulation of EPSs (exopolysaccharide, eDNA and proteins) that facilitate the formation of biofilms in order to present an overview of our current knowledge and the questions that remain regarding BP biofilms.

Modeling and computational characterization of a Xanthomonas sp. Hypothetical protein identifies a remote ortholog of Burkholderia lethal factor 1.

Burkholderia Lethal Factor 1 (BLF1) is a deamidase first characterized in Burkholderia pseudomallei. This enzyme inhibits cellular protein synthesis by deamidating a glutamine residue to a glutamic acid in its target protein, the eukaryotic translation initiation factor 4 A (eIF4A). In this work, we present the characterization of a hypothetical protein from Xanthomonas sp. Leaf131 as the first report of a BLF1 family ortholog outside of the Burkholderia genus. Although standard sequence similarity searches such as BLAST were not able to detect the homology between the Xanthomonas sp. Leaf131 hypothetical protein sequence and BLF1, our computed structure model for the Xanthomonas sp. hypothetical protein revealed structural similarities with an RMSD of 2.7 Å/164 Cα atoms and a TM-score of 0.72 when superposed. Structural comparisons of the Xanthomonas model structure against BLF1 and Escherichia coli cytotoxic necrotizing factor 1 (CNF1) revealed that the conserved signature LXGC motif and putative catalytic residues are structurally aligned thus signifying a level of functional or mechanistic similarity. Protein-protein docking analysis and molecular dynamics simulations also demonstrated that eIF4A could still be a possible target substrate for deamidation by XLF1 as it is for BLF1. We therefore propose that this Xanthomonas hypothetical protein be renamed as Xanthomonas Lethal Factor 1 (XLF1). Our work also provides further evidence of the utility of programs such as AlphaFold in bridging the computational function annotation transfer gap despite very low sequence identities of under 20%.Communicated by Ramaswamy H. Sarma.

Transitioning from Soil to Host: Comparative Transcriptome Analysis Reveals the Burkholderia pseudomallei Response to Different Niches.

Burkholderia pseudomallei, a soil and water saprophyte, is responsible for the tropical human disease melioidosis. A hundred years since its discovery, there is still much to learn about B. pseudomallei proteins that are essential for the bacterium's survival in and interaction with the infected host, as well as their roles within the bacterium's natural soil habitat. To address this gap, bacteria grown under conditions mimicking the soil environment were subjected to transcriptome sequencing (RNA-seq) analysis. A dual RNA-seq approach was used on total RNA from spleens isolated from a B. pseudomallei mouse infection model at 5 days postinfection. Under these conditions, a total of 1,434 bacterial genes were induced, with 959 induced in the soil environment and 475 induced in bacteria residing within the host. Genes encoding metabolism and transporter proteins were induced when the bacteria were present in soil, while virulence factors, metabolism, and bacterial defense mechanisms were upregulated during active infection of mice. On the other hand, capsular polysaccharide and quorum-sensing pathways were inhibited during infection. In addition to virulence factors, reactive oxygen species, heat shock proteins, siderophores, and secondary metabolites were also induced to assist bacterial adaptation and survival in the host. Overall, this study provides crucial insights into the transcriptome-level adaptations which facilitate infection by soil-dwelling B. pseudomallei. Targeting novel therapeutics toward B. pseudomallei proteins required for adaptation provides an alternative treatment strategy given its intrinsic antimicrobial resistance and the absence of a vaccine. IMPORTANCE Burkholderia pseudomallei, a soil-dwelling bacterium, is the causative agent of melioidosis, a fatal infectious disease of humans and animals. The bacterium has a large genome consisting of two chromosomes carrying genes that encode proteins with important roles for survival in diverse environments as well as in the infected host. While a general mechanism of pathogenesis has been proposed, it is not clear which proteins have major roles when the bacteria are in the soil and whether the same proteins are key to successful infection and spread. To address this question, we grew the bacteria in soil medium and then in infected mice. At 5 days postinfection, bacteria were recovered from infected mouse organs and their gene expression was compared against that of bacteria grown in soil medium. The analysis revealed a list of genes expressed under soil growth conditions and a different set of genes encoding proteins which may be important for survival, replication, and dissemination in an infected host. These proteins are a potential resource for understanding the full adaptation mechanism of this pathogen. In the absence of a vaccine for melioidosis and with treatment being reliant on combinatorial antibiotic therapy, these proteins may be ideal targets for designing antimicrobials to treat melioidosis.