Biosurfactants are unique secondary metabolites, synthesised non-ribosomally by certain bacteria, fungi and yeast, with their most promising applications as antimicrobial agents and surfactants in the medical and food industries. Naturally produced glycolipids and lipopeptides are found as a mixture of congeners, which increases their antimicrobial potency. Sensitive analysis techniques, such as liquid chromatography coupled to mass spectrometry, enable the fingerprinting of different biosurfactant congeners within a naturally produced crude extract. Bacillus amyloliquefaciens ST34 and Pseudomonas aeruginosa ST5, isolated from wastewater, were screened for biosurfactant production. Biosurfactant compounds were solvent extracted and characterised using ultra-performance liquid chromatography (UPLC) coupled to electrospray ionisation mass spectrometry (ESI–MS). Results indicated that B. amyloliquefaciens ST34 produced C13–16 surfactin analogues and their identity were confirmed by high resolution ESI–MS and UPLC–MS. In the crude extract obtained from P. aeruginosa ST5, high resolution ESI–MS linked to UPLC–MS confirmed the presence of di- and monorhamnolipid congeners, specifically Rha–Rha–C10–C10 and Rha–C10–C10, Rha–Rha–C8–C10/Rha–Rha–C10–C8 and Rha–C8–C10/Rha–C10–C8, as well as Rha–Rha–C12–C10/Rha–Rha–C10–C12 and Rha–C12–C10/Rha–C10–C12. The crude surfactin and rhamnolipid extracts also retained pronounced antimicrobial activity against a broad spectrum of opportunistic and pathogenic microorganisms, including antibiotic resistant Staphylococcus aureus and Escherichia coli strains and the pathogenic yeast Candida albicans. In addition, the rapid solvent extraction combined with UPLC–MS of the crude samples is a simple and powerful technique to provide fast, sensitive and highly specific data on the characterisation of biosurfactant compounds.Electronic supplementary materialThe online version of this article (doi:10.1186/s13568-017-0363-8) contains supplementary material, which is available to authorized users.

The genome of the severe acute respiratory syndrome coronavirus encodes for eight accessory viral proteins with no known homologues in other coronaviruses. One of these is the 3b protein, which is encoded by the second open reading frame in subgenomic RNA 3 and contains 154 amino acids. Here, a detailed time-course study was performed to compare the apoptosis and necrosis profiles induced by full-length 3b, a 3b mutant that was deleted by 30 amino acids from the C terminus (3b∆124-154) and the classical apoptosis inducer, Bax. Our results showed that Vero E6 cells transfected with a construct for expressing 3b underwent necrosis as early as 6 h after transfection and underwent simultaneous necrosis and apoptosis at later time-points. At all the time-points analysed, the apoptosis induced by the expression of 3b was less than the level induced by Bax but the level of necrosis was comparable. The 3b∆124-154 mutant behaves in a similar manner indicating that the localization of the 3b protein does not seems to be important for the cell-death pathways since full-length 3b is localized predominantly to the nucleolus, while the mutant is found to be concentrated in the peri-nuclear regions. To our knowledge, this is the first report of the induction of necrosis by a SARS-CoV protein.

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Severe acute respiratory syndrome coronavirus (SARS-CoV) 7a is an accessory protein with no known homologues. In this study, we report the interaction of a SARS-CoV 7a and small glutamine-rich tetratricopeptide repeat-containing protein (SGT). SARS-CoV 7a and human SGT interaction was identified using a two-hybrid system screen and confirmed with interaction screens in cell culture and cellular co-localization studies. The SGT domain of interaction was mapped by deletion mutant analysis and results indicated that tetratricopeptide repeat 2 (aa 125-158) was essential for interaction. We also showed that 7a interacted with SARS-CoV structural proteins M (membrane) and E (envelope), which have been shown to be essential for virus-like particle formation. Taken together, our results coupled with data from studies of the interaction between SGT and HIV-1 vpu indicated that SGT could be involved in the life-cycle, possibly assembly of SARS-CoV.Coronaviruses are members of the Coronaviridae family in the order Nidovirales. This family of viruses contains genomes of ~30 kb that include non-structural (pp1ab) and structural proteins (spike [S], envelope [E], membrane [M], and nucleocapsid [N]), making them the largest known RNA viruses. Interspersed among the structural proteins are group-specific proteins that differ in location and composition between the three coronavirus groups. The group-specific genes are not well characterized and the vast majority has, as yet, no known function. Initial research into the functions of these genes has shown that they are non-essential and dispensable for virus growth in cell culture [1]. However, more recent studies have shown that the accessory genes are required for in vivo infection in the natural host [2-4].Severe acute respiratory syndrome virus (SARS-CoV) encodes for eight potential open reading frames (ORFs), i.e., ORF 3a, 3b,6, 7a, 7b, 8a, 8b, and 9b,. Of these, SARS 3a, 3b, 6, 7a, and 9b have been detected in SARS-CoV infected cells, as well as in clinical samples [8], indicating possible in vivo functions. SARSCoV 7a (previously designated U122 in [9] and X4 in [10]) is the first ORF of subgenomic RNA 7 [6] and has been shown to be expressed inSARS-CoV infected Vero E6 cells [9,11]. It has been shown to localize to the Golgi apparatus and the endoplasmic reticulum (ER) and is recycled between the ER and Golgi complex via the intermediate

Animal feed is increasingly being supplemented with antibiotics to decrease the risk of epidemics in animal husbandry. This practice could lead to the selection for antibiotic resistant micro-organisms. The aim of this study was to determine the level of antibiotic resistant bacteria present on retail and abattoir chicken. Staphylococci, Enterobacteriaceae, Salmonella and isolates from total aerobic plate count were tested for resistance to vancomycin, streptomycin, methicillin, tetracycline and gentamicin using the disc diffusion susceptibility test; resistance to penicillin was determined using oxacillin. Results from the antibiotic code profile indicated that many of the bacterial strains were displaying multiple antibiotic resistance (MAR). A larger proportion of resistance to most antibiotics, except for vancomycin, was displayed by the abattoir samples, therefore suggesting that the incidence of MAR pathogenic bacteria was also higher in the abattoir samples. This resistance spectrum of abattoir samples is a result of farmers adding low doses of antibiotics to livestock feed to improve feeding efficiency so that the animals need less food to reach marketable weight. The lower incidence of MAR pathogenic bacteria in the retail samples is a result of resistance genes being lost due to lack of selective pressure, or to the fact that the resistant flora are being replaced by more sensitive flora during processing. The use of subtherapeutic levels of antibiotics for prophylaxis and as growth promoters remains a concern as the laws of evolution dictate that microbes will eventually develop resistance to practically any antibiotic. Selective pressure exerted by widespread antimicrobial use is therefore the driving force in the development of antibiotic resistance. This study indicated that a large proportion of the bacterial flora on fresh chicken is resistant to a variety of antibiotics, and that resultant food-related infections will be more difficult to treat.

Ethidium monoazide (EMA) quantitative polymerase chain reaction (qPCR), propidium monoazide (PMA)-qPCR and DNase treatment in combination with qPCR were compared for the determination of microbial cell viability. Additionally, varying EMA and PMA concentrations were analysed to determine which dye and concentration allowed for the optimal identification of viable cells. Viable, heat treated (70 °C for 15 min) and autoclaved cultures of Legionella pneumophila, Pseudomonas aeruginosa, Salmonella typhimurium, Staphylococcus aureus and Enterococcus faecalis were utilised in the respective viability assays. Analysis of the viable and heat-treated samples indicated that variable log reductions were recorded for both EMA [log reductions ranging from 0.01 to 2.71 (viable) and 0.27 to 2.85 (heat treated)], PMA [log reductions ranging from 0.06 to 1.02 (viable) and 0.62 to 2.46 (heat treated)] and DNase treatment [log reductions ranging from 0.06 to 0.82 (viable) and 0.70 to 2.91 (heat treated)], in comparison to the no viability treatment controls. Based on the results obtained, 6 μM EMA and 50 μM PMA were identified as the optimal dye concentrations as low log reductions were recorded (viable and heat-treated samples) in comparison to the no viability treatment control. In addition, the results recorded for the 6 μM EMA concentration were comparable to the results obtained for both the 50 μM PMA and the DNase treatment. The use of EMA-qPCR (6 μM) may therefore allow for the rapid identification and quantification of multiple intact opportunistic pathogens in water sources, which would benefit routine water quality monitoring following disinfection treatment.

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