Bad to the bone? - Genomic analysis of Enterococcus isolates from diverse environments reveals that most are safe and display potential as food fermentation microorganisms

Enterococci comprise a group of lactic acid bacteria (LAB) with considerable potential to serve as food fermentation microorganisms. Unfortunately, enterococci have received a lot of negative attention, due to the occurrence of pathogenic and multidrug resistant strains. In this study, we used genomics to select safe candidates among the forty-four studied enterococcal isolates. The genomes of the forty-four strains were fully sequenced and assessed for presence of virulence and antibiotic resistance genes. Nineteen isolates belonging to the species Enterococcus lactis, Enterococcus faecium, Enterococcus durans, and Enterococcus thailandicus, were deemed safe from the genome analysis. The presence of secondary metabolite gene clusters for bacteriocins was assessed, and twelve candidates were found to secrete antimicrobial compounds effective against Listeria monocytogenes isolated from cheese and Staphylococcus aureus. Physiological characterization revealed nineteen industrial potentials; all strains grew well at 42 °C and acidified 1.5 hours faster than their mesophilic counterpart Lactococcus lactis, with which they share metabolism and flavor forming ability. We conclude that a large fraction of the examined enterococci were safe and could serve as excellent food fermentation microorganisms with inherent bioprotective abilities.

Genomic characterization and assessment of pathogenic potential of Legionella spp. isolates from environmental monitoring

Several species in the genus Legionella are known to cause an acute pneumonia when the aerosols containing the bacteria from man-made water systems are inhaled. The disease is usually caused by Legionella pneumophila, but other species have been implicated in the infection. The disease is frequently manifested as an outbreak, which means several people are affected when exposed to the common source of Legionella contamination. Therefor environmental surveillance which includes isolation and identification of Legionella is performed routinely. However, usually no molecular or genome-based methods are employed in further characterization of the isolates during routine environmental monitoring. During several years of such monitoring, isolates from different geographical locations were collected and 39 of them were sequenced by hybrid de novo approach utilizing short and long sequencing reads. In addition, the isolates were typed by standard culture and MALDI-TOF method. The sequencing reads were assembled and annotated to produce high-quality genomes. By employing discriminatory genome typing, four potential new species in the Legionella genus were identified, which are yet to be biochemically and morphologically characterized. Moreover, functional annotations concerning virulence and antimicrobial resistance were performed on the sequenced genomes. The study contributes to the knowledge on little-known non-pneumophila species present in man-made water systems and establishes support for future genetic relatedness studies as well as understanding of their pathogenic potential.

Modeling of Urinary Microbiota Associated With Cystitis

A decade ago, when the Human Microbiome Project was starting, urinary tract (UT) was not included because the bladder and urine were considered to be sterile. Today, we are presented with evidence that healthy UT possesses native microbiota and any major event disrupting its “equilibrium” can impact the host also. This dysbiosis often leads to cystitis symptoms, which is the most frequent lower UT complaint, especially among women. Cystitis is one of the most common causes of antimicrobial drugs prescriptions in primary and secondary care and an important contributor to the problem of antimicrobial resistance. Despite this fact, we still have trouble distinguishing whether the primary cause of majority of cystitis cases is a single pathogen overgrowth, or a systemic disorder affecting entire UT microbiota. There are relatively few studies monitoring changes and dynamics of UT microbiota in cystitis patients, making this field of research still an unknown. In this study variations to the UT microbiota of cystitis patients were identified and microbial dynamics has been modeled. The microbial genetic profile of urine samples from 28 patients was analyzed by 16S rDNA Illumina sequencing and bioinformatics analysis. One patient with bacterial cystitis symptoms was prescribed therapy based on national guideline recommendations on antibacterial treatment of urinary tract infections (UTI) and UT microbiota change was monitored by 16S rDNA sequencing on 24 h basis during the entire therapy duration. The results of sequencing implied that a particular class of bacteria is associated with majority of cystitis cases in this study. The contributing role of this class of bacteria – Gammaproteobacteria, was further predicted by generalized Lotka-Volterra modeling (gLVM). Longitudinal microbiota insight obtained from a single patient under prescribed antimicrobial therapy revealed rapid and extensive changes in microbial composition and emphasized the need for current guidelines revision in regards to therapy duration. Models based on gLVM indicated protective role of two taxonomic classes of bacteria, Actinobacteria and Bacteroidia class, which appear to actively suppress pathogen overgrowth.