Pseudomonas aeruginosa is a highly versatile, antibiotic-resistant Gram-negative bacterium known for causing opportunistic infections and contamination of industrial products. Despite extensive genomic analysis of clinical P. aeruginosa strains, no genomes exist for preservative-tolerant industrial strains. A unique collection of 69 industrial isolates was assembled and compared to clinical and environmental strains; 16 genetically distinct industrial strains were subjected to array tube genotyping, multilocus sequence typing and whole-genome sequencing. The industrial strains possessed high preservative tolerance and were dispersed widely across P. aeruginosa as a species, but recurrence of strains from the same lineage within specific industrial products and locations was identified. The industrial P. aeruginosa genomes (mean=7.0 Mb) were significantly larger than those of previously sequenced environmental (mean=6.5 Mb; n=19) and clinical (mean=6.6 Mb; n=66) strains. Complete sequencing of the P. aeruginosa industrial strain RW109, which encoded the largest genome (7.75 Mb), revealed a multireplicon structure including a megaplasmid (555 265 bp) and large plasmid (151 612 bp). The RW109 megaplasmid represented an emerging plasmid family conserved in seven industrial and two clinical P. aeruginosa strains, and associated with extremely stress-resilient phenotypes, including antimicrobial resistance and solvent tolerance. Here, by defining the detailed phylogenomics of P. aeruginosa industrial strains, we show that they uniquely possess multireplicon, megaplasmid-bearing genomes, and significantly greater genomic content worthy of further study.

Bacterial endophytes are found in the internal tissues of plants and have intimate associations with their host. However, little is known about the diversity of medicinal plant endophytes (ME) or their capability to produce specialised metabolites that may contribute to therapeutic properties. We isolated 75 bacterial ME from 24 plant species of the Western Ghats, India. Molecular identification by 16S rRNA gene sequencing grouped MEs into 13 bacterial genera, with members of Gammaproteobacteria and Firmicutes being the most abundant. To improve taxonomic identification, 26 selected MEs were genome sequenced and average nucleotide identity (ANI) used to identify them to the species-level. This identified multiple species in the most common genus as Bacillus. Similarly, identity of the Enterobacterales was also distinguished within Enterobacter and Serratia by ANI and core-gene analysis. AntiSMASH identified non-ribosomal peptide synthase, lantipeptide and bacteriocin biosynthetic gene clusters (BGC) as the most common BGCs found in the ME genomes. A total of five of the ME isolates belonging to Bacillus, Serratia and Enterobacter showed antimicrobial activity against the plant pathogen Pectobacterium carotovorum. Using molecular and genomic approaches we have characterised a unique collection of endophytic bacteria from medicinal plants. Their genomes encode multiple specialised metabolite gene clusters and the collection can now be screened for novel bioactive and medicinal metabolites.

Preventing microbial contamination of non-food products is a major area of industrial microbiology where preservatives are used to stop microbial growth. However, microorganisms occasionally overcome product preservation, causing recalls and the implementation of multiple procedures to prevent further contamination. Correct reporting of microbial contamination in non-food industrial products is vital, especially if spoilage organisms are antimicrobial resistant and pose a health threat. Gram-negative bacteria such as Pseudomonas, Burkholderia and Enterobacteriaceae are frequently reported as non-food product contaminants, including species that overlap current antimicrobial resistance priorities. Historical analysis of recall databases highlighted that for greater than 15% of contamination incidents, the causative microbial agents are reported as unidentified. Here we review the current antimicrobial resistant bacterial species associated with non-food product contamination and evaluate recall reporting in Europe from 2005 to 2018. Our review shows that 49% of microbial contaminants are reported as unidentified despite frequent detection of antimicrobial resistant pathogens; in contrast, 98% of food-related microbial contaminants are classified. Recommendations to fill this microbial identification gap in non-food product recalls are made. Overall, reporting standards for microbial contamination in non-food products must be improved to enable surveillance and for understanding the risks associated with antimicrobial resistant microorganisms

Pseudomonas baetica strain a390T is the type strain of this recently described species and here we present its high-contiguity draft genome. To celebrate the 16th International Conference on Pseudomonas, the genome of P. baetica strain a390T was sequenced using a unique combination of Ion Torrent semiconductor and Oxford Nanopore methods as part of a collaborative community-led project. The use of high-quality Ion Torrent sequences with long Nanopore reads gave rapid, high-contiguity and -quality, 16-contig genome sequence. Whole genome phylogenetic analysis places P. baetica within the P. koreensis clade of the P. fluorescens group. Comparison of the main genomic features of P. baetica with a variety of other Pseudomonas spp. suggests that it is a highly adaptable organism, typical of the genus. This strain was originally isolated from the liver of a diseased wedge sole fish, and genotypic and phenotypic analyses show that it is tolerant to osmotic stress and to oxytetracycline.

Infections caused by methicillin-sensitive (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) are prevalent. MRSA infections are difficult to treat and there are no new classes of antibiotics produced to the market to treat infections caused by the resistant bacteria. Therefore, using antibiotic enhancers to rescue existing classes of antibiotics is an attractive strategy. Nordihydroguaiaretic acid (NDGA) is an antioxidant compound found in extracts from plant Larrea Tridentata. It exhibits antimicrobial activity and may target bacterial cell membrane. Combination efficacies of NDGA with many classes of antibiotics were examined by chequerboard method against 200 clinical isolates of MRSA and MSSA. NDGA in combination with gentamicin, neomycin and tobramycin was examined by time-kill assays. The synergistic combinations of NDGA and aminoglycosides were tested in vivo using a murine skin infection model. Calculations of the fractional inhibitory concentration index (FICI) showed that NDGA when combined with gentamicin, neomycin or tobramycin displayed synergistic activities in more than 97% of MSSA and MRSA, respectively. Time kill analysis demonstrated that NDGA significantly augmented the activities of these aminoglycosides against MRSA and MSSA in vitro and in murine skin infection model. The enhanced activity of NDGA resides on its ability to damage bacterial cell membrane leading to accumulation of the antibiotics inside bacterial cells. We demonstrated that NDGA strongly revived the therapeutic potencies of aminoglycosides in vitro and in vivo. This combinational strategy could contribute major clinical implications to treat antibiotic resistant bacterial infections.

The immunogenicity and effectiveness of oral rotavirus vaccines (ORVs) against severe rotavirus-associated gastroenteritis are impaired in low- and middle-income countries (LMICs) where the burden of disease is highest. Determining risk factors for impaired ORV response may help identify strategies to enhance vaccine effectiveness. In this study, we use metagenomic sequencing to provide a high-resolution taxonomic analysis of stool samples collected at 6 weeks of age (coinciding with the first ORV dose) during a prospective study of ORV immunogenicity in India and Malawi. We then analyse the functional capacity of the developing microbiome in these cohorts. Microbiome composition differed significantly between countries, although functional capacity was more similar than taxonomic composition. Our results confirm previously reported findings that the developing microbiome is more diverse in taxonomic composition in ORV non-seroconverters compared with seroconverters, and we additionally demonstrate a similar pattern in functional capacity. Although taxonomic or functional feature abundances are poor predictors of ORV response, we show that skews in the direction of associations within these microbiome data can be used to identify consistent markers of ORV response across LMIC infant cohorts. We also highlight the systemic under-representation of reference genes from LMICs that limit functional annotation in our study (7% and 13% annotation at pathway and enzyme commission level, respectively). Overall, higher microbiome diversity in early life may act as marker for impaired ORV response in India and Malawi, whilst a holistic perspective of functional capacity may be hidden in the “dark matter” of the microbiome.