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The F region downstream of the mecI gene in the SCCmec element in hospital-associated methicillin-resistant Staphylococcus aureus (HA-MRSA) contains two bidirectionally overlapping open reading frames (ORFs), the fudoh ORF and the psm-mec ORF. The psm-mec ORF encodes a cytolysin, phenol-soluble modulin (PSM)-mec. Transformation of the F region into the Newman strain, which is a methicillin-sensitive S. aureus (MSSA) strain, or into the MW2 (USA400) and FRP3757 (USA300) strains, which are community-acquired MRSA (CA-MRSA) strains that lack the F region, attenuated their virulence in a mouse systemic infection model. Introducing the F region to these strains suppressed colony-spreading activity and PSMα production, and promoted biofilm formation. By producing mutations into the psm-mec ORF, we revealed that (i) both the transcription and translation products of the psm-mec ORF suppressed colony-spreading activity and promoted biofilm formation; and (ii) the transcription product of the psm-mec ORF, but not its translation product, decreased PSMα production. These findings suggest that both the psm-mec transcript, acting as a regulatory RNA, and the PSM-mec protein encoded by the gene on the mobile genetic element SCCmec regulate the virulence of Staphylococcus aureus.

Chlamydomonas reinhardtii is a unicellular eukaryotic alga possessing a single chloroplast that is widely used as a model system for the study of photosynthetic processes. This report analyzes the surprising structural and evolutionary features of the completely sequenced 203,395-bp plastid chromosome. The genome is divided by 21.2-kb inverted repeats into two single-copy regions of ∼80 kb and contains only 99 genes, including a full complement of tRNAs and atypical genes encoding the RNA polymerase. A remarkable feature is that >20% of the genome is repetitive DNA: the majority of intergenic regions consist of numerous classes of short dispersed repeats (SDRs), which may have structural or evolutionary significance. Among other sequenced chlorophyte plastid genomes, only that of the green alga Chlorella vulgaris appears to share this feature. The program MultiPipMaker was used to compare the genic complement of Chlamydomonas with those of other chloroplast genomes and to scan the genomes for sequence similarities and repetitive DNAs. Among the results was evidence that the SDRs were not derived from extant coding sequences, although some SDRs may have arisen from other genomic fragments. Phylogenetic reconstruction of changes in plastid genome content revealed that an accelerated rate of gene loss also characterized the Chlamydomonas/Chlorella lineage, a phenomenon that might be independent of the proliferation of SDRs. Together, our results reveal a dynamic and unusual plastid genome whose existence in a model organism will allow its features to be tested functionally.

Prokaryotes have numerous mobile genetic elements (MGEs) that mediate horizontal gene transfer (HGT) between cells. These elements can be costly, even deadly, and cells use numerous defense systems to filter, control, or inactivate them. Recent studies have shown that prophages, conjugative elements, their parasites (phage satellites and mobilizable elements), and other poorly described MGEs encode defense systems homologous to those of bacteria. These constitute a significant fraction of the repertoire of cellular defense genes. As components of MGEs, these defense systems have presumably evolved to provide them, not the cell, adaptive functions. While the interests of the host and MGEs are aligned when they face a common threat such as an infection by a virulent phage, defensive functions carried by MGEs might also play more selfish roles to fend off other antagonistic MGEs or to ensure their maintenance in the cell. MGEs are eventually lost from the surviving host genomes by mutational processes and their defense systems can be co-opted when they provide an advantage to the cell. The abundance of defense systems in MGEs thus sheds new light on the role, effect, and fate of the so-called “cellular defense systems,” whereby they are not only merely microbial defensive weapons in a 2-partner arms race, but also tools of intragenomic conflict between multiple genetic elements with divergent interests that shape cell fate and gene flow at the population level.

The high-throughput antibiotic resistance gene (ARG) qPCR array, initially published in 2012, is increasingly used to quantify resistance and mobile determinants in environmental matrices. Continued utility of the array; however, necessitates improvements such as removing or redesigning questionable primer sets, updating targeted genes and coverage of available sequences. Towards this goal, a new primer design tool (EcoFunPrimer) was used to aid in identification of conserved regions of diverse genes. The total number of assays used for diverse genes was reduced from 91 old primer sets to 52 new primer sets, with only a 10% loss in sequence coverage. While the old and new array both contain 384 primer sets, a reduction in old primer sets permitted 147 additional ARGs and mobile genetic elements to be targeted. Results of validating the updated array with a mock community of strains resulted in over 98% of tested instances incurring true positive/negative calls. Common queries related to sensitivity, quantification and conventional data analysis (e.g. Ct cutoff value, and estimated genomic copies without standard curves) were also explored. A combined list of new and previously used primer sets is provided with a recommended set based on redesign of primer sets and results of validation.

The spread of antibiotic resistance is a growing public health concern. While numerous studies have highlighted the importance of environmental sources and pathways of the spread of antibiotic resistance, a systematic means of comparing and prioritizing risks represented by various environmental compartments is lacking. Here, we introduce MetaCompare, a publicly available tool for ranking 'resistome risk', which we define as the potential for antibiotic resistance genes (ARGs) to be associated with mobile genetic elements (MGEs) and mobilize to pathogens based on metagenomic data. A computational pipeline was developed in which each ARG is evaluated based on relative abundance, mobility, and presence within a pathogen. This is determined through the assembly of shotgun sequencing data and analysis of contigs containing ARGs to determine if they contain sequence similarity to MGEs or human pathogens. Based on the assembled metagenomes, samples are projected into a 3-dimensionalhazard space and assigned resistome risk scores. To validate, we tested previously published metagenomic data derived from distinct aquatic environments. Based on unsupervised machine learning, the test samples clustered in the hazard space in a manner consistent with their origin. The derived scores produced a well-resolved ascending resistome risk ranking of: wastewater treatment plant effluent, dairy lagoon, and hospital sewage.

Antibiotic resistance is one of the major problems facing medical practice in the 21st century. Historical approaches to managing antibiotic resistance have often focused on individual patients, specific pathogens and particular resistance phenotypes. However, it is increasingly recognized that antibiotic resistance is a complex ecological and evolutionary problem. As such, understanding the dynamics of antibiotic resistance requires integration of data on the diverse mobile genetic elements often associated with antibiotic resistance genes, and their dissemination by various mechanisms of horizontal gene transfer between bacterial cells and environments. Most important is understanding the fate and effects of antibiotics at sub-inhibitory concentrations, and co-selection. This opinion paper identifies key knowledge gaps in our understanding of resistance phenomena, and outlines research needs that should be addressed to help us manage resistance into the future.

Key Points The antibiotic resistome is the collection of all the antibiotic resistance genes, including those usually associated with pathogenic bacteria isolated in the clinics, non-pathogenic antibiotic producing bacteria and all other resistance genes. Many bacterial genomes contain cryptic resistance genes that can confer resistance, but do not seem to have been selected in response to recent exposure to antibiotics. These represent a large reservoir of antibiotic resistance genes. The antibiotic resistance genes in environmental and other non-pathogenic bacteria share amino-acid sequence similarities and biochemical mechanisms with resistance elements in clinical isolates. Structural biology and protein biochemistry has revealed that antibiotic resistance has evolved from precursor proteins with other metabolic functions. The powerful selection pressure produced by the use of cytotoxic antimicrobial agents spurs the selection of resistance mechanisms from these precursors. Antibiotics are ancient, dating back hundreds of millions of years. Resistance is therefore equally ancient, and the number of genes in the resistome is a reflection of the continuous co-evolution of small molecules in natural environments and microbial genomes. Resistance to antibiotics in microorganisms predates the use of these drugs. This Review examines why antibiotic resistance is inevitable and where it originates from. Over the millennia, microorganisms have evolved evasion strategies to overcome a myriad of chemical and environmental challenges, including antimicrobial drugs. Even before the first clinical use of antibiotics more than 60 years ago, resistant organisms had been isolated. Moreover, the potential problem of the widespread distribution of antibiotic resistant bacteria was recognized by scientists and healthcare specialists from the initial use of these drugs. Why is resistance inevitable and where does it come from? Understanding the molecular diversity that underlies resistance will inform our use of these drugs and guide efforts to develop new efficacious antibiotics.

Strongylid nematodes in large terrestrial herbivores such as great apes, equids, elephants, and humans tend to occur in complex communities. However, identification of all species within strongylid communities using traditional methods based on coproscopy or single nematode amplification and sequencing is virtually impossible. High-throughput sequencing (HTS) technologies provide opportunities to generate large amounts of sequence data and enable analyses of samples containing a mixture of DNA from multiple species/genotypes. We designed and tested an HTS approach for strain-level identification of gastrointestinal strongylids using ITS-2 metabarcoding at the MiSeq Illumina platform in samples from two free-ranging non-human primate species inhabiting the same environment, but differing significantly in their host traits and ecology. Although we observed overlapping of particular haplotypes, overall the studied primate species differed in their strongylid nematode community composition. Using HTS, we revealed hidden diversity in the strongylid nematode communities in non-human primates, more than one haplotype was found in more than 90% of samples and coinfections of more than one putative species occurred in 80% of samples. In conclusion, the HTS approach on strongylid nematodes, preferably using fecal samples, represents a time and cost-efficient way of studying strongylid communities and provides a resolution superior to traditional approaches.

Repetitive elements (REs) comprise 40-60% of the mammalian genome and have been shown to epigenetically influence the expression of genes through the formation of fusion transcript (FTs). We previously showed that an intracisternal A particle forms an FT with the agouti gene in mice, causing obesity/type 2 diabetes. To determine the frequency of FTs genome-wide, we developed a TopHat-Fusion-based analytical pipeline to identify FTs with high specificity. We applied it to an RNA-seq dataset from the nucleus accumbens (NAc) of mice repeatedly exposed to cocaine. Cocaine was previously shown to increase the expression of certain REs in this brain region. Using this pipeline that can be applied to single- or paired-end reads, we identified 438 genes expressing 813 different FTs in the NAc. Although all types of studied repeats were present in FTs, simple sequence repeats were underrepresented. Most importantly, reverse-transcription and quantitative PCR validated the expression of selected FTs in an independent cohort of animals, which also revealed that some FTs are the prominent isoforms expressed in the NAc by some genes. In other RNA-seq datasets, developmental expression as well as tissue specificity of some FTs differed from their corresponding non-fusion counterparts. Finally, in silico analysis predicted changes in the structure of proteins encoded by some FTs, potentially resulting in gain or loss of function. Collectively, these results indicate the robustness of our pipeline in detecting these new isoforms of genes, which we believe provides a valuable tool to aid in better understanding the broad role of REs in mammalian cellular biology.

Escherichia coli strains were isolated from a single dairy farm as a sentinel organism for the persistence of antibiotic resistance genes in the farm environment. Selective microbiological media were used to obtain 126 E. coli isolates from slurry and faeces samples from different farm areas. Antibiotic resistance profiling for 17 antibiotics (seven antibiotic classes) showed 57.9% of the isolates were resistant to between 3 and 15 antibiotics. The highest frequency of resistance was to ampicillin (56.3%), and the lowest to imipenem (1.6%), which appeared to be an unstable phenotype and was subsequently lost. Extended spectrum β-lactamase (ESBL) resistance was detected in 53 isolates and bla CTX-M, bla TEM and bla OXA genes were detected by PCR in 12, 4 and 2 strains, respectively. Phenotypically most isolates showing resistance to cephalosporins were AmpC rather than ESBL, a number of isolates having both activities. Phenotypic resistance patterns suggested co-acquisition of some resistance genes within subsets of the isolates. Genotyping using ERIC-PCR demonstrated these were not clonal, and therefore co-resistance may be associated with mobile genetic elements. These data show a snapshot of diverse resistance genes present in the E. coli population reservoir, including resistance to historically used antibiotics as well as cephalosporins in contemporary use. Multidrug resistant E. coli were isolated from a dairy farm at high frequency. Graphical Abstract Figure. Multidrug resistant E. coli were isolated from a dairy farm at high frequency.