ABSTRACT
Introduction: The antimicrobial resistance (AMR) mobilome plays a key role in the dissemination of resistance genes encoded by mobile genetics elements (MGEs) including plasmids, transposons (Tns), and insertion sequences (ISs). These MGEs contribute to the dissemination of multidrug resistance (MDR) in enteric bacterial pathogens which have been considered as a global public health risk. Methods: To further understand the diversity and distribution of AMR genes and MGEs across different plasmid types, we utilized multiple sequence-based computational approaches to evaluate AMR-associated plasmid genetics. A collection of 1,309 complete plasmid sequences from Gammaproteobacterial species, including 100 plasmids from each of the following 14 incompatibility (Inc) types: A/C, BO, FIA, FIB, FIC, FIIA, HI1, HI2, I1, K, M, N, P except W, where only 9 sequences were available, was extracted from the National Center for Biotechnology Information (NCBI) GenBank database using BLAST tools. The extracted FASTA files were analyzed using the AMRFinderPlus web-based tools to detect antimicrobial, disinfectant, biocide, and heavy metal resistance genes and ISFinder to identify IS/Tn MGEs within the plasmid sequences. Results and Discussion: In silico prediction based on plasmid replicon types showed that the resistance genes were diverse among plasmids, yet multiple genes were widely distributed across the plasmids from enteric bacterial species. These findings provide insights into the diversity of resistance genes and that MGEs mediate potential transmission of these genes across multiple plasmid replicon types. This notion was supported by the observation that many IS/Tn MGEs and resistance genes known to be associated with them were common across multiple different plasmid types. Our results provide critical insights about how the diverse population of resistance genes that are carried by the different plasmid types can allow for the dissemination of AMR across enteric bacteria. The results also highlight the value of computational-based approaches and in silico analyses for the assessment of AMR and MGEs, which are important elements of molecular epidemiology and public health outcomes.
ABSTRACT
To understand the genetic diversity of porcine deltacoronavirus(PDCo V) in Guangxi Province, clinical diarrhea samples were collected from suspected piglets in Guangxi Province from2017 to 2019, detected by RT-PCR for PDCoV, and the positive samples were used for amplification and sequence of S, M, N genes. Finally, 16 S, M and N gene sequences of PDCoV were obtained. Homology analysis showed that the S, M, N gene nucleotide identity among Guangxi strains were 95.8% -99.9%, 95.9%-100% and 97.9%-99.9%, respectively. The nucleotide identity of S, M and N genes among Guangxi strains and other reference strains were 95.1%-100%, 95.0%-100%and 96.3%-99.9%, respectively. Sequence alignment showed that S1 protein existed amino acid mutations and insertions, and there were some variations among different epidemic strains. Phylogenetic trees based on S, M and N genes obtained similar topological diagram and all strains could be divided into Group I, Group II and GroupIII, of which Group I came from USA, Japan and Korea, Group II came from China, and Group III came from China, Vietnam, Laos and Thailand. Most strains from Guangxi Province distributed in Group II, individual strain distributed in Group III and some strains formed a single small branch. The evolutionary rates of S, M and N genes of Guangxi strains and other reference strains were 2.57 x 10-4, 2.07 x 10-4, 1.70 x 10-4 substitutions/site/year, respectively, showing that the evolutionary rate of S gene was the fastest. The results indicated that the S, M, N genes of PDCo V strains from Guangxi Province had some variations and existed genetic diversity.
ABSTRACT
Antimicrobial resistance (AMR) is a growing public health threat. Improved surveillance of AMR's genetic indicators in environmental reservoirs should lead to a more comprehensive understanding of the problem at a global scale, as with SARS-CoV-2 monitoring in sewage. However, the "best" monitoring approach is unclear. Some scientific works have emphasized monitoring for the abundance of already-known antimicrobial resistance genes (ARGs);others have emphasized monitoring for the potential of new ARGs to arise. The goal of this study was to examine which methods were employed by highly-cited papers studying AMR in environmental engineering and agricultural systems, thus providing insight into current and future methodological trends for monitoring ARGs. We searched recent (2018-2020) literature documenting AMR in five environmental matrices: wastewater, surface water, drinking water, stormwater, and livestock manure. We selected the most highly-cited papers across these matrices (89 papers from 17 809 initial results) and categorized them as using targeted methods (e.g., qPCR), non-targeted methods (e.g., shotgun metagenomics), or both. More than 80% of papers employed targeted methods. Only 33% employed non-targeted methods, and the use of targeted versus non-targeted methods varied by environmental matrix. We posit that improving AMR surveillance in environmental reservoirs requires assessing risk, and that different monitoring approaches imply different objectives for risk assessment. Targeted methods are appropriate for quantifying known threats, particularly in environmental matrices where direct human exposure is likely (e.g., drinking water). However, long-term studies employing non-targeted methods are needed to provide an understanding of how frequently new threats (i.e., novel ARGs) arise.
ABSTRACT
The wide spread of viral infections and the ease of overcoming the species-specific barriers require the identification of critical stages in the virus interaction with multicellular organisms of mammals and the analysis of key molecular genetic systems involved. To date, a large amount of data has already been accumulated on the diversity and complexity of such systems, as well as the involvement in them the wide range of metabolic pathways. In this regard, attempts to identify some common elements that are implemented in different infectious processes are of particular relevance. This paper is such attempt made on the example of the analysis of the main events of cattle infection by bovine leukemia virus (BLV). Systems involved in the entry of BLV genetic material into the cytoplasm of host cells, the suppression of innate and adaptive immunity, as well as interactions between the genomes of the BLV provirus and the host genome are the identified critical stages. The direct participants in the reception of viral proteins are parts of some host tansmembrane systems (G.Yu. Kosovsky et al., 2017;V.I. Glazko et al., 2018;L. Bai et al., 2019;H. Sato et al., 2020). During virus reproduction in host cells, host enzymes modify virus envelope proteins by (A. De Brogniez et al., 2016;W. Assi et al., 2020). Importantly, modifications of SARS-CoV-2 spike proteins, as well as BLV envelope proteins, have a significant impact on their pathogenicity (M. Hoffmann et al., 2020). Pathogenicity and depressing effect of both BLV and SARS-CoV-2 on innate and adaptive immunity is realized in part through the activation of T regulatory cells and an increase in the expression of the growth transforming factor TGF-b (L.Y. Chang et al., 2015;G.Yu. Kosovsky et al., 2017;W. Chen et al., 2020). Intracellular mechanisms of protection against retrotranspositions, recombinations between viruses and host retrotransposons, the formation of new elements of host regulatory networks such as microRNAs, and the integration of proviral DNA into the host genome are closely related and controlled by interfering RNA (RNAi) systems with the key gene dicer1 (P.V. Maillard et al., 2019;E.Z. Poirier et al., 2021;G.Y. Kosovsky et al., 2020). These systems can provide a certain left-pointing-double-angle resistance right-pointing-double-angle of the host genome both to the integration of exogenous genetic material and to transpositions of own mobile genetic elements. Apparently, it is the polygenicity of the control of these critical stages of viral infection that leads to difficulties in predicting their development and developing methods for their prevention.
ABSTRACT
As the COVID-19 pandemic spread globally, the consumption of antibiotics increased. However, no studies exist evaluating the effect of antibiotics use on the antibiotic resistance of intestinal flora in COVID-19 patients during the pandemic. To explore this issue, we collected 15 metagenomic data of fecal samples from healthy controls (HCs) with no use history of antibiotics, 23 metagenomic data of fecal samples from COVID-19 patients who received empirical antibiotics [COVID-19 (abx+)], 18 metagenomic data of fecal samples from antibiotics-naïve COVID-19 patients [COVID-19 (abx-)], and six metagenomic data of fecal samples from patients with community-acquired pneumonia [PC (abx+)] from the Sequence Read Archive database. A total of 513 antibiotic-resistant gene (ARG) subtypes of 18 ARG types were found. Antibiotic treatment resulted in a signiï¬cant increase in the abundance of ARGs in intestinal flora of COVID-19 patients and markedly altered the composition of ARG proï¬les. Grouped comparisons of pairs of Bray-Curtis dissimilarity values demonstrated that the dissimilarity of the HC versus the COVID-19 (abx+) group was signiï¬cantly higher than the dissimilarity of the HC versus the COVID-19 (abx-) group. The mexF, mexD, OXA_209, major facilitator superfamily transporter, and EmrB_QacA family major facilitator transporter genes were the discriminative ARG subtypes for the COVID-19 (abx+) group. IS621, qacEdelta, transposase, and ISCR were significantly increased in COVID-19 (abx+) group; they greatly contributed toward explaining variation in the relative abundance of ARG types. Overall, our data provide important insights into the effect of antibiotics use on the antibiotic resistance of COVID-19 patients during the COVID-19 epidemic.