Prediction driven functional annotation of hypothetical proteins in the major facilitator superfamily of S. aureus NCTC 8325

Leveraging big data bioinformatics approaches to extract knowledge from Staphylococcus aureus public omics data

Staphylococcus aureus is a notorious pathogen posing challenges in the medical industry due to drug resistance and biofilm formation. The horizon of knowledge on S. aureus pathogenesis has expanded with the advancement of data-driven bioinformatics techniques. Mining information from sequenced genomes and their expression data is an economic approach that alleviates wastage of resources and redundancy in experiments. The current review covers how big data bioinformatics has been used in the analysis of S. aureus from publicly available -omics data to uncover mechanisms of infection and inhibition. Particularly, advances in the past two decades in biomarker discovery, host responses, phenotype identification, consolidation of information, and drug development are discussed highlighting the challenges and shortcomings. Overall, the review summarizes the diverse aspects of scrupulous re-analysis of S. aureus proteomic and transcriptomic expression datasets retrieved from public repositories in terms of the efforts taken, benefits offered, and follow-up actions. The detailed review thus serves as a reference and aid for (i) Computational biologists by briefing the approaches utilized for bacterial omics re-analysis concerning S. aureus and (ii) Experimental biologists by elucidating the potential of bioinformatics in biological research to generate reliable postulates in a prompt and economical manner.

Enhancement of the antibiotic activity by quercetin against Staphylococcus aureus efflux pumps

The objective of this work was to evaluate the inhibitory effect of quercetin on S. aureus Efflux Pumps. The MIC of Quercetin was evaluated through the broth microdilution method, as well as the Efflux Pump inhibition assay through the method of reducing the antibiotic minimum inhibitory concentration as well as that of ethidium bromide. The in silico approach through bioinformatics was performed to demonstrate the molecular mechanism of interaction of the substrate and the binding cavity. The Quercetin inhibition concentration was not clinically relevant. With respect to the reversal of bacterial resistance effect by efflux pump inhibition, this effect was observed with the strains carrying the TetK and NorA pumps. Regarding the interaction between the Quercetin complex and the NorA pump, the extra stability was provided by hydrogen bonds produced by the hydroxyl group.

An Educational Bioinformatics Project to Improve Genome Annotation

Scientific advancement is hindered without proper genome annotation because biologists lack a complete understanding of cellular protein functions. In bacterial cells, hypothetical proteins (HPs) are open reading frames with unknown functions. HPs result from either an outdated database or insufficient experimental evidence (i.e., indeterminate annotation). While automated annotation reviews help keep genome annotation up to date, often manual reviews are needed to verify proper annotation. Students can provide the manual review necessary to improve genome annotation. This paper outlines an innovative classroom project that determines if HPs have outdated or indeterminate annotation. The Hypothetical Protein Characterization Project uses multiple well-documented, freely available, web-based, bioinformatics resources that analyze an amino acid sequence to (1) detect sequence similarities to other proteins, (2) identify domains, (3) predict tertiary structure including active site characterization and potential binding ligands, and (4) determine cellular location. Enough evidence can be generated from these analyses to support re-annotation of HPs or prioritize HPs for experimental examinations such as structural determination via X-ray crystallography. Additionally, this paper details several approaches for selecting HPs to characterize using the Hypothetical Protein Characterization Project. These approaches include student- and instructor-directed random selection, selection using differential gene expression from mRNA expression data, and selection based on phylogenetic relations. This paper also provides additional resources to support instructional use of the Hypothetical Protein Characterization Project, such as example assignment instructions with grading rubrics, links to training videos in YouTube, and several step-by-step example projects to demonstrate and interpret the range of achievable results that students might encounter. Educational use of the Hypothetical Protein Characterization Project provides students with an opportunity to learn and apply knowledge of bioinformatic programs to address scientific questions. The project is highly customizable in that HP selection and analysis can be specifically formulated based on the scope and purpose of each student's investigations. Programs used for HP analysis can be easily adapted to course learning objectives. The project can be used in both online and in-seat instruction for a wide variety of undergraduate and graduate classes as well as undergraduate capstone, honor's, and experiential learning projects.

Whole-genome sequence analyses of Glaesserella parasuis isolates reveals extensive genomic variation and diverse antibiotic resistance determinants

Background

Glaesserella parasuis (G. parasuis) is a respiratory pathogen of swine and the etiological agent of Glässer’s disease. The structural organization of genetic information, antibiotic resistance genes, potential pathogenicity, and evolutionary relationships among global G. parasuis strains remain unclear. The aim of this study was to better understand patterns of genetic variation, antibiotic resistance factors, and virulence mechanisms of this pathogen.

Methods

The whole-genome sequence of a ST328 isolate from diseased swine in China was determined using Pacbio RS II and Illumina MiSeq platforms and compared with 54 isolates from China sequenced in this study and 39 strains from China and eigtht other countries sequenced by previously. Patterns of genetic variation, antibiotic resistance, and virulence mechanisms were investigated in relation to the phylogeny of the isolates. Electrotransformation experiments were performed to confirm the ability of pYL1—a plasmid observed in ST328—to confer antibiotic resistance.

Results

The ST328 genome contained a novel Tn6678 transposon harbouring a unique resistance determinant. It also contained a small broad-host-range plasmid pYL1 carrying aac(6’)-Ie-aph(2”)-Ia and bla_ROB-1; when transferred to Staphylococcus aureus RN4220 by electroporation, this plasmid was highly stable under kanamycin selection. Most (85.13–91.74%) of the genetic variation between G. parasuis isolates was observed in the accessory genomes. Phylogenetic analysis revealed two major subgroups distinguished by country of origin, serotype, and multilocus sequence type (MLST). Novel virulence factors (gigP, malQ, and gmhA) and drug resistance genes (norA, bacA, ksgA, and bcr) in G. parasuis were identified. Resistance determinants (sul2, aph(3”)-Ib, norA, bacA, ksgA, and bcr) were widespread across isolates, regardless of serovar, isolation source, or geographical location.

Conclusions

Our comparative genomic analysis of worldwide G. parasuis isolates provides valuable insight into the emergence and transmission of G. parasuis in the swine industry. The result suggests the importance of transposon-related and/or plasmid-related gene variations in the evolution of G. parasuis.

Comparative genomics of Staphylococcus aureus associated with subclinical and clinical bovine mastitis

Many efforts have been made to understand the pathogenesis of bovine mastitis to reduce losses and promote animal welfare. Staphylococcus aureus may cause bovine clinical mastitis, but it is mainly associated with subclinical infection, which is usually persistent and can easily reoccur. Here, we conducted a comparative genomic analysis between strains of S. aureus causing subclinical infection (Sau170, 302, 1269, 1364), previously sequenced by our group, and two well-characterized strains causing clinical mastitis (N305 and RF122) to find differences that could be linked to mastitis outcome. A total of 146 virulence-associated genes were compared and no appreciable differences were found between the bacteria. However, several nonsynonymous single nucleotide polymorphisms (SNPs) were identified in genes present in the subclinical strains when compared to RF122 and N305, especially in genes encoding host immune evasion and surface proteins. The secreted and surface proteins predicted by in silico tools were compared through multidimensional scaling analysis (MDS), revealing a high degree of similarity among the strains. The comparison of orthologous genes by OrthoMCL identified a membrane transporter and a lipoprotein as exclusive of bacteria belonging to the subclinical and clinical groups, respectively. No hit was found in RF122 and N305 for the membrane transporter using BLAST algorithm. For the lipoprotein, sequences of Sau170, 302, 1269, and 1364 with identities between 68–73% were found in the MDS dataset. A conserved region found only in the lipoprotein genes of RF122 and N305 was used for primer design. Although the polymerase chain reaction (PCR) on field isolates of S. aureus did not validate the findings for the transporter, the lipoprotein was able to separate the clinical from the subclinical isolates. These results show that sequence variation among bovine S. aureus, and not only the presence/absence of virulence factors, is an important aspect to consider when comparing isolates causing different mastitis outcomes.

Identification and prioritization of macrolideresistance genes with hypothetical annotation inStreptococcus pneumoniae

Macrolide resistant Streptococcus pneumoniae infections have limited treatment options. While some resistance mechanisms are well established, ample understanding is limited by incomplete genome annotation (hypothetical genes). Some hypothetical genes encode a domain of unknown function (DUF), a conserved protein domain with uncharacterized function. Here, we identify and confirm macrolide resistance genes. We further explore DUFs from macrolide resistance hypothetical genes to prioritize them for experimental characterization. We found gene similarities between two macrolide resistance gene signatures from untreated and either erythromycin- or spiramycin-treated resistant Streptococcus pneumoniae. We confirmed the association of these gene sets with macrolide resistance through comparison to gene signatures from (i) second erythromycin resistant Streptococcus pneumoniae strain, and (ii) erythromycin-treated sensitive Streptococcus pneumoniae strain, both from non-overlapping datasets. Examination into which cellular processes these macrolide resistance genes belong found connections to known resistance mechanisms such as increased amino acid biosynthesis and efflux genes, and decreased ribonucleotide biosynthesis genes, highlighting the predictive ability of the method used. 22 genes had hypothetical annotation with 10 DUFs associated with macrolide resistance. DUF characterization could uncover novel co-therapies that restore macrolide efficacy across multiple macrolide resistant species. Application of the methods to other antibiotic resistances could revolutionize treatment of resistant infections

Functional annotation of operome from Methanothermobacter thermautotrophicus ΔH: An insight to metabolic gap filling

Methanothermobacter thermautotrophicus ΔH (MTH) is a potential methanogen known to reduce CO₂ with H₂ for producing methane biofuel in thermophilic digesters. The genome of this organism contains ~50.5% conserved hypothetical proteins (HPs; operome) whose function is still not determined precisely. Here, we employed a combined bioinformatics approach to annotate a precise function to HPs and categorize them as enzymes, binding proteins, and transport proteins. Results of our study show that 315 (35.6%) HPs have exhibited well-defined functions contributing imperative roles in diverse cellular metabolism. Some of them are responsible for stress-response mechanisms and cell cycle, membrane transport, and regulatory processes. The genome-neighborhood analysis found five important gene clusters (dsr, ehb, kaiC, cmr, and gas) involving in the energetic metabolism and defense systems. MTH operome contains 223 enzymes with 15 metabolic subsystems, 15 cell cycle proteins, 17 transcriptional regulators and 33 binding proteins. Functional annotation of its operome is thus more fundamental to a profound understanding of the molecular and cellular machinery at systems-level.

In silico Prediction, Characterization, Molecular Docking, and Dynamic Studies on Fungal SDRs as Novel Targets for Searching Potential Fungicides Against Fusarium Wilt in Tomato

Vascular wilt of tomato caused by Fusarium oxysporum f.sp. lycopersici (FOL) is one of the most devastating diseases, that delimits the tomato production worldwide. Fungal short-chain dehydrogenases/reductases (SDRs) are NADP(H) dependent oxidoreductases, having shared motifs and common functional mechanism, have been demonstrated as biochemical targets for commercial fungicides. The 1,3,6,8 tetra hydroxynaphthalene reductase (T4HNR) protein, a member of SDRs family, catalyzes the naphthol reduction reaction in fungal melanin biosynthesis. We retrieved an orthologous member of T4HNR, (complexed with NADP(H) and pyroquilon from Magnaporthe grisea) in the FOL (namely; FOXG_04696) based on homology search, percent identity and sequence similarity (93% query cover; 49% identity). The hypothetical protein FOXG_04696 (T4HNR like) had conserved T-G-X-X-X-G-X-G motif (cofactor binding site) at N-terminus, similar to M. grisea (1JA9) and Y-X-X-X-K motif, as a part of the active site, bearing homologies with two fungal keto reductases T4HNR (M. grisea) and 17-β-hydroxysteroid dehydrogenase from Curvularia lunata (teleomorph: Cochliobolus lunatus PDB ID: 3IS3). The catalytic tetrad of T4HNR was replaced with ASN¹¹⁵, SER¹⁴¹, TYR¹⁵⁴, and LYS¹⁵⁸ in the FOXG_04696. The structural alignment and superposition of FOXG_04696 over the template proteins (3IS3 and 1JA9) revealed minimum RMSD deviations of the C alpha atomic coordinates, and therefore, had structural conservation. The best protein model (FOXG_04696) was docked with 37 fungicides, to evaluate their binding affinities. The Glide XP and YASARA docked complexes showed discrepancies in results, for scoring and ranking the binding affinities of fungicides. The docked complexes were further refined and rescored from their docked poses through 50 ns long MD simulations, and binding free energies (ΔG_bind) calculations, using MM/GBSA analysis, revealed Oxathiapiprolin and Famoxadone as better fungicides among the selected one. However, Famoxadone had better interaction of the docked residues, with best protein ligand contacts, minimum RMSD (high accuracy of the docking pose) and RMSF (structural integrity and conformational flexibility of docking) at the specified docking site. The Famoxadone was found to be acceptable based on in silico toxicity and in vitro growth inhibition assessment. We conclude that the FOXG_04696, could be employed as a novel candidate protein, for structure-based design, and screening of target fungicides against the FOL pathogen.

De novo assembly and comparative transcriptome analysis of Monilinia fructicola, Monilinia laxa and Monilinia fructigena, the causal agents of brown rot on stone fruits

BACKGROUND

Brown rots are important fungal diseases of stone and pome fruits. They are caused by several Monilinia species but M. fructicola, M. laxa and M. fructigena are the most common all over the world. Although they have been intensively studied, the availability of genomic and transcriptomic data in public databases is still scant. We sequenced, assembled and annotated the transcriptomes of the three pathogens using mRNA from germinating conidia and actively growing mycelia of two isolates of opposite mating types per each species for comparative transcriptome analyses.

RESULTS

Illumina sequencing was used to generate about 70 million of paired-end reads per species, that were de novo assembled in 33,861 contigs for M. fructicola, 31,103 for M. laxa and 28,890 for M. fructigena. Approximately, 50% of the assembled contigs had significant hits when blasted against the NCBI non-redundant protein database and top-hits results were represented by Botrytis cinerea, Sclerotinia sclerotiorum and Sclerotinia borealis proteins. More than 90% of the obtained sequences were complete, the percentage of duplications was always less than 14% and fragmented and missing transcripts less than 5%. Orthologous transcripts were identified by tBLASTn analysis using the B. cinerea proteome as reference. Comparative transcriptome analyses revealed 65 transcripts over-expressed (FC ≥ 8 and FDR ≤ 0.05) or unique in M. fructicola, 30 in M. laxa and 31 in M. fructigena. Transcripts were involved in processes affecting fungal development, diversity and host-pathogen interactions, such as plant cell wall-degrading and detoxifying enzymes, zinc finger transcription factors, MFS transporters, cell surface proteins, key enzymes in biosynthesis and metabolism of antibiotics and toxins, and transposable elements.

CONCLUSIONS

This is the first large-scale reconstruction and annotation of the complete transcriptomes of M. fructicola, M. laxa and M. fructigena and the first comparative transcriptome analysis among the three pathogens revealing differentially expressed genes with potential important roles in metabolic and physiological processes related to fungal morphogenesis and development, diversity and pathogenesis which need further investigations. We believe that the data obtained represent a cornerstone for research aimed at improving knowledge on the population biology, physiology and plant-pathogen interactions of these important phytopathogenic fungi.

Improved Annotations of 23 Differentially Expressed Hypothetical Proteins in Methicillin Resistant S.aureus

Antibiotic resistant Staphylococcus aureus is a major public health concern effecting millions of people annually. Medical science has documented completely untreatable S. aureus infections. These strains are appearing in the community with increasing frequency. New diagnostic and therapeutic options are needed to combat this deadly infection. Interestingly, around 50% of the proteins in S. aureus are annotated as hypothetical. Methods to select hypothetical proteins related to antibiotic resistance have been inadequate. This study uses differential gene expression to identify hypothetical proteins related to antibiotic resistant phenotype strain variations. We apply computational tools to predict physiochemical properties, cellular location, sequence-based homologs, domains, 3D modeling, active site features, and binding partners. Nine of 23 hypothetical proteins were <100 residues, unlikely to be functional proteins based on size. Of the 14 differentially expressed hypothetical proteins examined, confident predictions on function could not be made. Most identified domains had unknown functions. Six hypothetical protein models had >50% confidence over >20% residues. These findings indicate the method of hypothetical protein identification is sufficient; however, current scientific knowledge is inadequate to properly annotate these proteins. This process should be repeated regularly until entire genomes are clearly and accurately annotated.