Genomic Characterization of a New Biofilm-Forming and Adhesive ST398 Human-Adapted MSSA Lineage Causing Septic Knee Arthritis Following Surgical Reconstruction

Methicillin-susceptible (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) is a pathogen commonly found in bone and joint infections, including septic arthritis. S. aureus virulence and the frailty of affected patients can cause several complications; a prompt and specific antibiotic treatment can positively affect the outcome of patients. We carried out an in-depth genomic characterization by Illumina whole genome sequencing and bioinformatics of two biofilm-producing M1 and M2 ST398 MSSA causing septic knee arthritis not-responding to antimicrobial therapy. The strains were characterized for antibiotic resistance, biofilm and adhesive properties as well as genomics, single nucleotide polymorphism phylogeny, resistomics and virulomics. Our results showed that M1 and M2 MSSA were ST398-t1451-agrI-Cap5, susceptible to cefoxitin and resistant to erythromycin and clindamycin, traits consistent with the lack of the SCCmec-locus and the presence of the sole blaZ and ermT. Furthermore, M1 and M2 were biofilm-producing and largely potentially adhesive strains, as indicated by the adhesion gene profile. Our data characterized a new human-adapted ST398 MSSA lineage, representing a "fusion" between the human-animal independent ST398 and the Livestock Associated (LA) ST398 lineages, forming biofilm and genomically predicted high adhesive, characterized by different genomic adaptation conferring a great ability to adhere to the host's extracellular matrix causing septic knee arthritis.

Genomic and Long-Term Transcriptomic Imprints Related to the Daptomycin Mechanism of Action Occurring in Daptomycin- and Methicillin-Resistant Staphylococcus aureus Under Daptomycin Exposure

Daptomycin (DAP) is one of the last-resort treatments for heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) and vancomycin-intermediate S. aureus (VISA) infections. DAP resistance (DAP-R) is multifactorial and mainly related to cell-envelope modifications caused by single-nucleotide polymorphisms and/or modulation mechanisms of transcription emerging as result of a self-defense process in response to DAP exposure. Nevertheless, the role of these adaptations remains unclear. We aim to investigate the comparative genomics and late post-exponential growth-phase transcriptomics of two DAP-resistant/DAP-susceptible (DAP^R/S) methicillin-resistant S. aureus (MRSA) clinical strain pairs to focalize the genomic and long-term transcriptomic fingerprinting and adaptations related to the DAP mechanism of action acquired in vivo under DAP pressure using Illumina whole-genome sequencing (WGS), RNA-seq, bioinformatics, and real-time qPCR validation. Comparative genomics revealed that membrane protein and transcriptional regulator coding genes emerged as shared functional coding-gene clusters harboring mutational events related to the DAP-R onset in a strain-dependent manner. Pairwise transcriptomic enrichment analysis highlighted common and strain pair-dependent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, whereas DAP^R/S double-pair cross-filtering returned 53 differentially expressed genes (DEGs). A multifactorial long-term transcriptomic-network characterized DAP^R MRSA includes alterations in (i) peptidoglycan biosynthesis, cell division, and cell-membrane (CM) organization genes, as well as a cidB/lytS autolysin genes; (ii) ldh2 involved in fermentative metabolism; (iii) CM-potential perturbation genes; and (iv) oxidative and heat/cold stress response-related genes. Moreover, a D-alanyl–D-alanine decrease in cell-wall muropeptide characterized DAP/glycopeptide cross-reduced susceptibility mechanisms in DAP^R MRSA. Our data provide a snapshot of DAP^R MRSA genomic and long-term transcriptome signatures related to the DAP mechanism of action (MOA) evidencing that a complex network of genomic changes and transcriptomic adaptations is required to acquire DAP-R.

COLR Acinetobacter baumannii sRNA Signatures: Computational Comparative Identification and Biological Targets

Multidrug-Resistant (MDR) and Extensively Drug Resistant (XDR) Acinetobacter baumannii (Ab) represent a serious cause of healthcare-associated infections worldwide. Currently, the available treatment options are very restricted and colistin-based therapies are last-line treatments of these infections, even though colistin resistant (COL^R) Ab have rarely been isolated yet. In bacteria, small non-coding RNAs (sRNAs) have been implicated in regulatory pathways of different biological functions, however, no knowledge exists about the sRNA role on the biological adaptation in COL^RAb. Our study investigated two Italian XDR isogenic colistin-susceptible/resistant (COL^S/R) Ab strain-pairs to discover new sRNA signatures. Comparative sRNA transcriptome (sRNAome) analyses were carried out by Illumina RNA-seq using both a Tru-Seq and a Short Insert library, whilst Ab ATCC 17978 and ACICU Reference Genome assembly, mapping, annotation and statistically significant differential expression (q-value ≤ 0.01) of the raw reads were performed by the Rockhopper tool. A computational filtering, sorting only similarly statistically significant differentially expressed (DE) sRNAs mapping on the same gene in both COL^RAb isolates was conducted. COL^R vs. COL^S sRNAome, analyzed integrating the DE sRNAs obtained from the two different libraries, revealed some statistically significant DE sRNAs in COL^RAb. In detail, we found: (i) two different under-expressed cis-acting sRNAs (AbsRNA₁ and AbsRNA₂) mapping in antisense orientation the 16S rRNA gene A1S_r01, (ii) one under-expressed cis-acting sRNA (AbsRNA₃) targeting the A1S_2505 gene (hypothetical protein), (iii) one under-expressed microRNA-size small RNA fragment (AbsRNA₄) and its pre-microAbsRNA₄ targeting the A1S_0501 gene (hypothetical protein), (iv) as well as an over-expressed microRNA-size small RNA fragment (AbsRNA₅) and its pre-microAbsRNA₅ targeting the A1S_3097 gene (signal peptide). Custom TaqMan^® probe-based real-time qPCRs validated the expression pattern of the selected sRNA candidates shown by RNA-seq. Furthermore, analysis on sRNA ΔA1S_r01, ΔA1S_2505 as well as the over-expressed A1S_3097 mutants revealed no effects on colistin resistance. Our study, for the first time, found the sRNAome signatures of clinical COL^RAb with a computational prediction of their targets related to protein synthesis, host-microbe interaction and other different biological functions, including biofilm production, cell-cycle control, virulence, and antibiotic-resistance.

Colistin Resistant A. baumannii: Genomic and Transcriptomic Traits Acquired Under Colistin Therapy

Even though colistin-based treatment represents the antimicrobial-regimen backbone for the management of multidrug-resistant Gram-negative infections, colistin resistance is still rare, at least as a full resistance, in Acinetobacter baumannii (Ab). We investigated the genomics and transcriptomics of two clinical Extensively Drug Resistance (XDR) colistin-susceptible/resistant (COL-S/R) Ab strain-pairs in which COL-resistance was developed after exposure to colistin therapy. The molecular characterization of the strains showed that all strains belonged to PFGE-A, ST-281, OXA-23 producers, Global Clone-II, and were resistant to imipenem, meropenem, ampicillin/sulbactam, ciprofloxacin, gentamicin, amikacin, trimethoprim/sulfamethoxazole, and susceptible to tigecycline, in agreement with NGS-acquired resistome. COL-R vs. COL-S Ab comparative genomics, mapping on Ab ATCC 17978 and Ab ACICU Reference Genomes, revealed a closely related genomic phylogeny, especially between strain-pair isolates, and distinctive common genomic non-synonymous SNPs (nsSNPs) in COL-R Ab strains. Furthermore, pmrB and pmrC nsSNPs were found. Notably we recovered, for the first time, lpxC and lpxD nsSNPs previously described only in "in-vitro" mutants and associated with colistin resistance in a clinical COL-R Ab. COL-R vs. COL-S Ab comparative transcriptomics evidenced a strain-dependent response to the colistin resistance onset highly variable among the single COL-R strains vs. their COL-S parents and merely seven common over-expressed transcripts, i.e. the PgaB lipoprotein for biofilm-matrix production, the diacylglycerol kinase for the lipid recycling in the membrane-derived oligosaccharide cycle, a membrane non-ribosomal peptide synthetase, the Lipid A phosphoethanol aminotransferase PmrC, and three hypothetical proteins. The transcript analysis of the "COL-R related genes" and the RNA-seq data confirmed pmrCAB over-expression responsible for a greater positive net cell-charge, and lpxACD under-expression in COL-R causing a decreased LPS production, as main mechanisms of colistin resistance. Our study reports the COL-R Ab genomic and transcriptomic signatures reflecting the interplay between several direct and indirect potential adaptations to antimicrobial pressure, including the occurrence of SNP accumulation hotspot loci in genes related to intrinsic or adaptive colistin resistance, surface adhesion proteins and porins, and over-expressed genes involved in different pathways, i.e. biofilm production, oxidative stress response, extensive drug and COL resistance.

A knowledge base for Vitis vinifera functional analysis

Background

Vitis vinifera (Grapevine) is the most important fruit species in the modern world. Wine and table grapes sales contribute significantly to the economy of major wine producing countries. The most relevant goals in wine production concern quality and safety. In order to significantly improve the achievement of these objectives and to gain biological knowledge about cultivars, a genomic approach is the most reliable strategy. The recent grapevine genome sequencing offers the opportunity to study the potential roles of genes and microRNAs in fruit maturation and other physiological and pathological processes. Although several systems allowing the analysis of plant genomes have been reported, none of them has been designed specifically for the functional analysis of grapevine genomes of cultivars under environmental stress in connection with microRNA data.

Description

Here we introduce a novel knowledge base, called BIOWINE, designed for the functional analysis of Vitis vinifera genomes of cultivars present in Sicily. The system allows the analysis of RNA-seq experiments of two different cultivars, namely Nero d'Avola and Nerello Mascalese. Samples were taken under different climatic conditions of phenological phases, diseases, and geographic locations. The BIOWINE web interface is equipped with data analysis modules for grapevine genomes. In particular users may analyze the current genome assembly together with the RNA-seq data through a customized version of GBrowse. The web interface allows users to perform gene set enrichment by exploiting third-party databases.

Conclusions

BIOWINE is a knowledge base implementing a set of bioinformatics tools for the analysis of grapevine genomes. The system aims to increase our understanding of the grapevine varieties and species of Sicilian products focusing on adaptability to different climatic conditions, phenological phases, diseases, and geographic locations.

MIDClass: microarray data classification by association rules and gene expression intervals

We present a new classification method for expression profiling data, called MIDClass (Microarray Interval Discriminant CLASSifier), based on association rules. It classifies expressions profiles exploiting the idea that the transcript expression intervals better discriminate subtypes in the same class. A wide experimental analysis shows the effectiveness of MIDClass compared to the most prominent classification approaches.

Sequence similarity is more relevant than species specificity in probabilistic backtranslation

BACKGROUND

Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module. The degeneracy of the genetic code makes backtranslation potentially ambiguous since most amino acids are encoded by multiple codons. The common approach to overcome this difficulty is based on imitation of codon usage within the target species.

RESULTS

This paper describes EasyBack, a new parameter-free, fully-automated software for backtranslation using Hidden Markov Models. EasyBack is not based on imitation of codon usage within the target species, but instead uses a sequence-similarity criterion. The model is trained with a set of proteins with known cDNA coding sequences, constructed from the input protein by querying the NCBI databases with BLAST. Unlike existing software, the proposed method allows the quality of prediction to be estimated. When tested on a group of proteins that show different degrees of sequence conservation, EasyBack outperforms other published methods in terms of precision.

CONCLUSION

The prediction quality of a protein backtranslation methis markedly increased by replacing the criterion of most used codon in the same species with a Hidden Markov Model trained with a set of most similar sequences from all species. Moreover, the proposed method allows the quality of prediction to be estimated probabilistically.

NetMatch: a Cytoscape plugin for searching biological networks

NetMatch is a Cytoscape plugin which allows searching biological networks for subcomponents matching a given query. Queries may be approximate in the sense that certain parts of the subgraph-query may be left unspecified. To make the query creation process easy, a drawing tool is provided. Cytoscape is a bioinformatics software platform for the visualization and analysis of biological networks.

AVAILABILITY

The full package, a tutorial and associated examples are available at the following web sites: http://alpha.dmi.unict.it/~ctnyu/netmatch.html, http://baderlab.org/Software/NetMatch.

AntiClustal: Multiple Sequence Alignment by antipole clustering and linear approximate 1-median computation

In this paper we present a new Multiple Sequence Alignment (MSA) algorithm called AntiClusAl. The method makes use of the commonly use idea of aligning homologous sequences belonging to classes generated by some clustering algorithm, and then continue the alignment process ina bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of the progressive alignment with the 1-median (center) of the cluster. The 1-median of set S of sequences is the element of S which minimizes the average distance from any other sequence in S. Its exact computation requires quadratic time. The basic idea of our proposed algorithm is to make use of a simple and natural algorithmic technique based on randomized tournaments which has been successfully applied to large size search problems in general metric spaces. In particular a clustering algorithm called Antipole tree and an approximate linear 1-median computation are used. Our algorithm compared with Clustal W, a widely used tool to MSA, shows a better running time results with fully comparable alignment quality. A successful biological application showing high aminoacid conservation during evolution of Xenopus laevis SOD2 is also cited.