Antibiotic resistance reservoirs within food-producing animals are thought to be a risk to animal and human health. This study describes the minimum natural resistome of pig faeces as the bacteria are under no direct antibiotic selective pressure. The faecal resistome of 257 different genes comprised 56 core and 201 accessory resistance genes. The genes present at the highest relative abundances across all samples were tetW , tetQ , tet44 , tet37 , tet40 , mefA , aadE , ant(9)−1 , ermB and cfxA2 . This study characterized the baseline resistome, the microbiome composition and the metabolic components described by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in healthy pig faeces, without antibiotic selective pressures. The microbiome hierarchical analysis resulted in a cluster tree with a highly similar pattern to that of the accessory resistome cluster tree. Functional capacity profiling identified genes associated with horizontal gene transfer. We identified a statistically significant positive correlation between the total antibiotic resistome and suggested indicator genes, which agree with using these genes as indicators of the total resistomes. The correlation between total resistome and total microbiome in this study was positive and statistically significant. Therefore, the microbiome composition influenced the resistome composition. This study identified a core and accessory resistome present in a cohort of healthy pigs, in the same conditions without antibiotics. It highlights the presence of antibiotic resistance in the absence of antibiotic selective pressure and the variability between animals even under the same housing, food and living conditions. Antibiotic resistance will remain in the healthy pig gut even when antibiotics are not used. Therefore, the risk of antibiotic resistance transfer from animal faeces to human pathogens or the environment will remain in the absence of antibiotics.
Gliotoxin is produced by non-ribosomal peptide synthesis and secreted from certain fungi, including Aspergillus fumigatus. It is an epipolythiodioxopiperazine that contains an intact disulphide bridge and is the focus of intense research as a consequence of its negative immunomodulatory properties. Gliotoxin detection is generally enabled by reversed-phase-high-performance liquid chromatography (RP-HPLC), with absorbance detection (220-280 nm), or liquid chromatography-mass spectrometry, yet detection is not readily achievable by matrix-assisted laser desorption ionisation-time-of-flight mass spectrometry (MALDI-ToF MS). We have developed a single-pot derivatisation strategy which uses sodium borohydride-mediated reduction of gliotoxin followed by immediate alkylation of exposed thiols by 5′-iodoacetamidofluorescein to yield a stable product, diacetamidofluorescein-gliotoxin (GT-(AF) 2 ), of molecular mass 1103.931 Da ((M+H)+). This product is readily detectable by RP-HPLC and exhibits a 6.8-fold increase in molar absorptivity compared with gliotoxin, which results in a higher sensitivity of detection (40 ng; 125 pmoL). GT-(AF) 2 also fluoresces (excitation/emission, 492:518 nm). Unlike free gliotoxin, the product (>800 fmol) is detectable by MALDI-ToF MS. Sporidesmin A can also be detected by RP-HPLC and MALDI-ToF MS (>530 fmol) using this strategy. We also demonstrate that the strategy facilitates detection of gliotoxin (mean± SD = 3.55 ± 0.07 μg 100 μL −1 ; n = 2) produced by A. fumigatus, without the requirement for organic extraction of culture supernatants and associated solvent removal. GT-(AF) 2 is also detectable (150 ng; 460 pmol) by thinlayer chromatography.
Within the past decade, microbiologists have moved from detecting single antibiotic resistance genes (ARGs) to detecting all known resistance genes within a sample due to advances in next generation sequencing. This has provided a wealth of data on the variation and relative abundances of ARGs present in a total bacterial population. However, to use these data in terms of therapy or risk to patients, they must be analyzed in the context of the background microbiome. Using a quantitative PCR ARG chip and 16S rRNA amplicon sequencing, we have sought to identify the ARGs and bacteria present in a fecal sample of a healthy adult using genomic tools. Of the 42 ARGs detected, 12 fitted into the ResCon1 category of ARGs: cfxA, cphA, bacA, sul3, aadE, bla, aphA1, aphA3, aph(2')-Id, aacA/aphd, catA1, and vanC. Therefore, we describe these 12 genes as the core resistome of this person's fecal microbiome and the remaining 30 ARGs as descriptors of the microbial population within the fecal microbiome. The dominant phyla and genera agree with those previously detected in the greatest abundances in fecal samples of healthy humans. The majority of the ARGs detected were associated with the presence of specific bacterial taxa, which were confirmed using microbiome analysis. We acknowledge the limitations of the data in the context of the limited sample set. However, the principle of combining qPCR and microbiome analysis was shown to be helpful to identify the association of the ARGs with specific taxa.
It has been well documented that antibiotic resistance (AR) is a clinical concern that affects both human and animal health but AR in the environment and food-chain is not as well understood. AR bacteria can occur naturally in soil, water and organic fertilizers used in agriculture so there is a risk that AR can pass to humans via the food-chain. This study focuses on lettuce cultivation undergoing four treatments (Normal irrigation water+normal soil, normal irrigation water+manure, UV irrigation water+normal soil, UV irrigation water+manure)to determine the mechanisms by which the AR is transferred to the plants over the growth period of the lettuce (7 time-points – week 0 to week 6). Plasmids (n=318) have been isolated from irrigation water (n=36), soil (n=45) and lettuce (n=42) samples using the exogenous isolation method for week 0 and week 6 initially. Antibiotic susceptibility testingto amikacin, cefotaxime, ciprofloxacin, imipenem, kanamycin, tetracycline has been carried out. Multi-drug resistance profiles were established for soil taken at timepoint 0 and lettuce taken at timepoint 6. Extracted plasmid DNA was sent for metagenomic analysis to determine which genes are involved in the transfer of AR at the interfaces. The results of the sequencing showed that there are multiple AR genespresent, including Tet, Sme, Cmy, Oxa and ANT(4’)-Ib, that confer resistance to bacteria. The identification of multi-drug resistance in soil and lettuce samples is concerning and highlights the need to determine the mechanisms leading to antibiotic resistance in food.
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