scholarly journals Antibiotic susceptibility profiles of Pediococcus pentosaceus from various origins and their implications for the safety assessment of strains with food-technology applications

2020 ◽  
Author(s):  
Noam Shani ◽  
Simone Oberhaensli ◽  
Emmanuelle Arias-Roth
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Antibiotic Susceptibility ◽  
False Negative ◽  
Antibiotic Resistance Genes ◽  
Fermented Foods ◽  
Food Technology ◽  
Pediococcus Pentosaceus ◽  
Minimal Inhibitory Concentrations ◽  
Technology Applications

In the fight against the spread of antibiotic resistance (ABR), authorities usually require that strains “intentionally added into the food chain” be tested for their antibiotic susceptibility. This applies to strains used in starter or adjunct cultures for the production of fermented foods, such as many strains of Pediococcus pentosaceus . The European Food Safety Authority (EFSA) recommends testing strains for their antibiotic susceptibility based on both genomic and phenotypic approaches. Furthermore, it proposes a set of antibiotics to assess, as well as a list of microbiological cutoffs (MCs) allowing classifying lactic acid bacteria as susceptible or resistant. Accurate MCs are essential, on the one hand, to avoid false negative strains, which may carry ABR genes and remain unnoticed, and on the other, to avoid false positive strains, which may be discarded while screening potential candidates for food-technology applications. Due to relatively scarce data, MCs have been defined for the whole Pediococcus genus, although differences between different species should be expected. In this study, we investigated the antibiotic susceptibility of thirty-five strains of P. pentosaceus isolated from various matrices in the last seventy years. Minimal inhibitory concentrations (MICs) were determined using a standard protocol, and MIC distributions were established. Phenotypic analyses were complemented with genome sequencing and by seeking known antibiotic resistance genes. The genomes of all the strains were free of known antibiotic resistance genes, but most displayed MICs above the currently defined MCs for chloramphenicol, and all showed excessive MICs for tetracycline. Based on the distributions, we calculated and proposed new MCs for chloramphenicol (16 instead of 4 mg/L) and tetracycline (256 instead of 8 mg/L).

scholarly journals Preliminary Results on the Prevalence of Salmonella Spp. in Marine Animals Stranded in Sicilian Coasts: Antibiotic Susceptibility Profile and ARGs Detection in the Isolated Strains

Pathogens ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 930
Author(s):  
Delia Gambino ◽  
Sonia Sciortino ◽  
Sergio Migliore ◽  
Lucia Galuppo ◽  
Roberto Puleio ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Antibiotic Susceptibility ◽  
Antibiotic Resistance Genes ◽  
Diffusion Method ◽  
Salmonella Spp ◽  
Marine Animals ◽  
Disk Diffusion Method ◽  
Phenotypic Resistance ◽  
Low Prevalence

The presence of Salmonella spp. in marine animals is a consequence of contamination from terrestrial sources (human activities and animals). Bacteria present in marine environments, including Salmonella spp., can be antibiotic resistant or harbor resistance genes. In this study, Salmonella spp. detection was performed on 176 marine animals stranded in the Sicilian coasts (south Italy). Antibiotic susceptibility, by disk diffusion method and MIC determination, and antibiotic resistance genes, by molecular methods (PCR) of the Salmonella spp. strains, were evaluated. We isolated Salmonella spp. in three animals, though no pathological signs were detected. Our results showed a low prevalence of Salmonella spp. (1.7%) and a low incidence of phenotypic resistance in three Salmonella spp. strains isolated. Indeed, of the three strains, only Salmonella subsp. enterica serovar Typhimurium from S. coeruleoalba and M. mobular showed phenotypic resistance: the first to ampicillin, tetracycline, and sulphamethoxazole, while the latter only to sulphamethoxazole. However, all strains harbored resistance genes (blaTEM, blaOXA, tet(A), tet(D), tet(E), sulI, and sulII). Although the low prevalence of Salmonella spp. found in this study does not represent a relevant health issue, our data contribute to the collection of information on the spread of ARGs, elements involved in antibiotic resistance, now considered a zoonosis in a One Health approach.

Antibiotic susceptibility profiles and frequency of resistance genes in clinical Shiga toxin-producing Escherichia coli isolates from Michigan over a 14-year period

2021 ◽  
Author(s):  
Sanjana Mukherjee ◽  
Heather M. Blankenship ◽  
Jose A. Rodrigues ◽  
Rebekah E. Mosci ◽  
James T. Rudrik ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Shiga Toxin ◽  
Antibiotic Susceptibility ◽  
Genetic Relatedness ◽  
Antibiotic Resistance Genes ◽  
Genomic Analysis ◽  
Mechanisms Of Resistance ◽  
Susceptibility Profiles

Background: Shiga toxin-producing Escherichia coli (STEC) is an important foodborne pathogen that contributes to over 250,000 infections in the US each year. Because antibiotics are not recommended for STEC infections, resistance in STEC has not been widely researched despite an increased likelihood for the transfer of resistance gene from STEC to opportunistic pathogens residing within the same microbial community. Methods: Between 2001 and 2014, 969 STEC isolates were collected from Michigan patients. Serotyping and antibiotic susceptibility profiles to clinically relevant antibiotics were determined using disc diffusion, while epidemiological data was used to identify factors associated with resistance. Whole genome sequencing was used to examine genetic relatedness and identify genetic determinants and mechanisms of resistance in the non-O157 isolates. Results: Increasing frequencies of resistance to at least one antibiotic was observed over the 14 years (p=0.01). While the non-O157 serogroups were more commonly resistant than O157 (Odds Ratio: 2.4; 95% Confidence Interval:1.43-4.05), the frequency of ampicillin resistance among O157 isolates was significantly higher in Michigan compared to the national average (p=0.03). Genomic analysis of 321 non-O157 isolates uncovered 32 distinct antibiotic resistance genes (ARGs). Although mutations in genes encoding resistance to ciprofloxacin and ampicillin were detected in four isolates, most of the horizontally acquired ARGs conferred resistance to aminoglycosides, β-lactams, sulfonamides and/or tetracycline. Conclusions: This study provides insight into the mechanisms of resistance in a large collection of clinical non-O157 STEC isolates and demonstrates that antibiotic resistance among all STEC serogroups has increased over time, prompting the need for enhanced surveillance.

scholarly journals Investigation of Some Antibiotic Resistance Genes of Indigenous Lactobacilli Isolated From Traditional Yogurt In Zanjan Province of Iran

2021 ◽  
Author(s):  
Bahare Moghimi ◽  
Maryam Ghobadi Dana ◽  
Reza Shapouri
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Food Chain ◽  
Starter Culture ◽  
Antibiotic Resistance Genes ◽  
Molecular Methods ◽  
Diffusion Method ◽  
Resistant Bacteria ◽  
Fermented Foods ◽  
Antibiotic Resistant

Abstract Purpose: Given the increasing use of antibiotics on humans and livestock for treatment or as a growth stimulant, antibiotic resistance has become a general concern. The food chain and specially fermented foods could be a source of antibiotic-resistant bacteria and resistance genes. Lactic Acid Bacteria (LAB) and Lactobacilli are considered safe to use as starter culture or probiotic strains. Recently, however, antibiotic-resistant genes isolated from LABs showed the necessity of setting international regulations to reduce the risk of antibiotic resistance genes transmission via the food chain. The current study aimed to investigate the antibiotic resistance of Lactobacilli isolated from traditional yogurt samples from Zanjan province in Iran.Methods: Lactobacilli characterization and identification were carried out through biochemical and molecular methods. The disk diffusion method was applied to determine phenotype resistance using 13 antibiotic disks resistance genes presence were investigated in the isolates to determine transferability risk, respectively.Results: Based on biochemical and molecular methods, 24 isolates have been identified as Lactobacilli with multiple antibiotic-resistant phenotypes. Vancomycin resistance was a typical phenotype and genotype among isolates. On investigated Lactobacilli chromosome, Tetracycline resistance genes Chloramphenicol (cat), beta-lactam, aminoglycosides (aph (3’)-III), and aadA resistance genes have been detected. While the examined resistance genes have not been detected on the plasmids, they were all on the bacterial chromosome.Conclusion: The results showed that the investigated isolates did not carry the resistance genes on their plasmids. It, therefore, would be a good point since they probably do not transfer resistance genes to other bacteria, and they would be proper candidates to do more investigation for introducing new safe starter culture or probiotic strain to food industries.

scholarly journals DeepARG: A deep learning approach for predicting antibiotic resistance genes from metagenomic data

2017 ◽  
Author(s):  
G. A. Arango-Argoty ◽  
E. Garner ◽  
A. Pruden ◽  
L. S. Heath ◽  
P. Vikesland ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Deep Learning ◽  
Resistance Genes ◽  
Agricultural Waste ◽  
Antibiotic Resistance Gene ◽  
False Negative ◽  
Antibiotic Resistance Genes ◽  
Direct Access ◽  
Metagenomic Data ◽  
Community Research

ABSTRACTGrowing concerns regarding increasing rates of antibiotic resistance call for global monitoring efforts. Monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is of particular interest as these media can serve as sources of potential novel antibiotic resistance genes (ARGs), as hot spots for ARG exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequence-based monitoring has recently enabled direct access and profiling of the total metagenomic DNA pool, where ARGs are identified or predicted based on the “best hits” of homology searches against existing databases. Unfortunately, this approach tends to produce high rates of false negatives. To address such limitations, we propose here a deep leaning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two models, deepARG-SS and deepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Performance evaluation of the deep learning models over 30 classes of antibiotics demonstrates that the deepARG models can predict ARGs with both high precision (>0.97) and recall (>0.90) for most of the antibiotic resistance categories. The models show advantage over the traditional best hit approach by having consistently much lower false negative rates and thus higher overall recall (>0.9). As more data become available for under-represented antibiotic resistance categories, the deepARG models’ performance can be expected to be further enhanced due to the nature of the underlying neural networks. The deepARG models are available both in command line version and via a Web server at http://bench.cs.vt.edu/deeparg. Our newly developed ARG database, deepARG-DB, containing predicted ARGs with high confidence and high degree of manual curation, greatly expands the current ARG repository. DeepARG-DB can be downloaded freely to benefit community research and future development of antibiotic resistance-related resources.AbbreviationsARGantibiotic resistance gene

scholarly journals Identification of Antibiotic-Resistance Genes from Lactic Acid Bacteria in Indonesian Fermented Foods

2014 ◽  
Vol 21 (3) ◽  
pp. 144-150 ◽  
Author(s):  
LINDA SUKMARINI ◽  
APON ZAENAL MUSTOPA ◽  
MARIDHA NORMAWATI ◽  
IKRIMAH MUZDALIFAH
Keyword(s):  
Antibiotic Resistance ◽  
Lactic Acid ◽  
Lactic Acid Bacteria ◽  
Resistance Genes ◽  
Antibiotic Resistance Genes ◽  
Fermented Foods

Quintuplex PCR to Detect Antibiotic Resistance Genes in Streptococcus pneumoniae

2016 ◽  
Vol 1 (2) ◽  
pp. 22 ◽  
Author(s):  
Navindra Kumari Palanisamy ◽  
Parasakthi Navaratnam ◽  
Shamala Devi Sekaran
Keyword(s):  
Antibiotic Resistance ◽  
Streptococcus Pneumoniae ◽  
Resistance Genes ◽  
Bacterial Pathogen ◽  
Antibiotic Resistance Genes ◽  
Pcr Amplification ◽  
Penicillin Resistance ◽  
Penicillin Binding Proteins ◽  
Efflux Mechanism ◽  
Mic Value

Introduction: Streptococcus pneumoniae is an important bacterial pathogen, causing respiratory infection. Penicillin resistance in S. pneumoniae is associated with alterations in the penicillin binding proteins, while resistance to macrolides is conferred either by the modification of the ribosomal target site or efflux mechanism. This study aimed to characterize S. pneumoniae and its antibiotic resistance genes using 2 sets of multiplex PCRs. Methods: A quintuplex and triplex PCR was used to characterize the pbp1A, ermB, gyrA, ply, and the mefE genes. Fifty-eight penicillin sensitive strains (PSSP), 36 penicillin intermediate strains (PISP) and 26 penicillin resistance strains (PRSP) were used. Results: Alteration in pbp1A was only observed in PISP and PRSP strains, while PCR amplification of the ermB or mefE was observed only in strains with reduced susceptibility to erythromycin. The assay was found to be sensitive as simulated blood cultures showed the lowest level of detection to be 10cfu. Conclusions: As predicted, the assay was able to differentiate penicillin susceptible from the non-susceptible strains based on the detection of the pbp1A gene, which correlated with the MIC value of the strains.

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