Integrated aquaculture contributes to the transfer of mcr-1 between animals and humans via the aquaculture supply chain

Background Since its discovery in 2015, the mobile colistin resistance gene mcr-1 has been reported in bacteria from > 50 countries. Although aquaculture-associated bacteria may act as a significant reservoir for colistin resistance, systematic investigations of mcr-1 in the aquaculture supply chain are scarce. Objectives We investigated the presence of colistin resistance determinants in the aquaculture supply chain in south China and determined their characteristics and relationships. Methods A total of 250 samples were collected from a duck-fish integrated fishery, slaughter house, and market in Guangdong Province, China, in July 2017. Colistin-resistant bacteria were isolated on colistin-supplemented CHROMagar Orientation plates, and the species were identified by matrix-assisted laser desorption/ionization time-of-flight assay. The presence of mcr genes was confirmed by polymerase chain reaction analysis. We examined the minimum inhibitory concentrations (MICs) of 16 antimicrobial agents against the isolates using agar diffusion and broth microdilution methods. Whole-genome sequencing (WGS) was used to explore the molecular characteristics and relationships of mcr-1-positive Escherichia coli (MCRPEC). Results Overall, 143 (57.2%) colistin-resistant bacteria were isolated, of which, 56 (22.4%, including 54 Escherichia coli and two Klebsiella pneumoniae) and four Aeromonas species were positive for mcr-1 and mcr-3, respectively. The animal-derived MCRPEC were significantly more prevalent in integrated fishery samples (40.0%) than those in market (4.8%, P 90%) but were susceptible to carbapenems and tigecycline. WGS analysis suggested that mcr-1 was mainly contained on plasmids, including IncHI2 (29.6%), IncI2 (27.8%), IncX4 (14.8%), and IncP (11.1%). Genomic analysis suggested mcr-1 transmission via the aquatic food chain. Conclusions MCRPEC were highly prevalent in the aquaculture supply chain, with the isolates showing resistance to most antibiotics. The data suggested mcr-1 could be transferred to humans via the aquatic food chain. Taking the “One Health” perspective, aquaculture should be incorporated into systematic surveillance programs with animal, human, and environmental monitoring

Comparative analysis of genomics and proteomics in Bacillus thuringiensis 4.0718.

Bacillus thuringiensis is a widely used biopesticide that produced various insecticidal active substances during its life cycle. Separation and purification of numerous insecticide active substances have been difficult because of the relatively short half-life of such substances. On the other hand, substances can be synthetized at different times during development, so samples at different stages have to be studied, further complicating the analysis. A dual genomic and proteomic approach would enhance our ability to identify such substances, and particularily using mass spectrometry-based proteomic methods. The comparative analysis for genomic and proteomic data have showed that not all of the products deduced from the annotated genome could be identified among the proteomic data. For instance, genome annotation results showed that 39 coding sequences in the whole genome were related to insect pathogenicity, including five cry genes. However, Cry2Ab, Cry1Ia, Cytotoxin K, Bacteriocin, Exoenzyme C3 and Alveolysin could not be detected in the proteomic data obtained. The sporulation-related proteins were also compared analysis, results showed that the great majority sporulation-related proteins can be detected by mass spectrometry. This analysis revealed Spo0A~P, SigF, SigE(+), SigK(+) and SigG(+), all known to play an important role in the process of spore formation regulatory network, also were displayed in the proteomic data. Through the comparison of the two data sets, it was possible to infer that some genes were silenced or were expressed at very low levels. For instance, found that cry2Ab seems to lack a functional promoter while cry1Ia may not be expressed due to the presence of transposons. With this comparative study a relatively complete database can be constructed and used to transform hereditary material, thereby prompting the high expression of toxic proteins. A theoretical basis is provided for constructing highly virulent engineered bacteria and for promoting the application of proteogenomics in the life sciences

The results of the Mass spectrometry-based proteomic data compare with genome annotation data.

<p>A, not found.</p><p>B, not match.</p><p>The results of the Mass spectrometry-based proteomic data compare with genome annotation data.</p

The comparative analysis of insecticidal activity substances in <i>B</i>.<i>thuringiensis</i> 4.0718 in genomics and proteomics.

<p>+, The insecticidal activity substance genes or proteins can be searched.</p><p>-, The insecticidal activity substance genes or proteins can not be searched.</p><p>The comparative analysis of insecticidal activity substances in <i>B</i>.<i>thuringiensis</i> 4.0718 in genomics and proteomics.</p

Complete circuit diagram of key regulatory genes in sporulation.

<p>Spo0A is a key protein that directs the transcriptional regulation of downstream gene, including asymmetric division and the expression of SigF and SigE, which are special transcription factors of pre-spore and mother cell, respectively. The two transcription factors decide the regulation of the development of spore. Red line, inhibition; Orange line, activation; Green, translation.</p

Analysis of insecticidal Cry protein regulation network.

<p>The figure exhibits that the insecticidal Cry protein interacts with beta-lactamase type II. Beta-lactamase type II is also regulated by LysR family transcriptional regulator.</p

The statistics of not found proteins for the result of genome annotation with comparison the result of the LC-MS/MS searched.

<p>The statistics of not found proteins for the result of genome annotation with comparison the result of the LC-MS/MS searched.</p

The results of ncRNA prediction.

<p>The prediction of ncRNA by using WebMGA and tRNAscan-SE-1.3.1 software.</p><p>The results of ncRNA prediction.</p

Analysis of start codon and initiator methionine for acetate CoA-transferase, alpha subunit.

<p>Red arrow, initiator methionine, as identified by Prodigal.v2_60 software. Green arrow, initiator methionine of the protein identified by LC-MS/MS through received uniprot blast. These initiator methionines were determined from <i>B</i>. <i>thuringiensis subsp</i>. <i>konkukian</i> (strain 97–27) and <i>B</i>. <i>thuringiensis serovar kurstaki</i> strain T03a001, respectively.</p