Evaluation and application of a next generation sequencing approach for meat species identification

Food Control ◽  
2020 ◽  
Vol 110 ◽  
pp. 107003 ◽  
Author(s):  
Geoffrey Cottenet ◽  
Carine Blancpain ◽  
Poh Fong Chuah ◽  
Christophe Cavin
Food Control ◽  
2021 ◽  
pp. 108590
Author(s):  
Roberta Piredda ◽  
Anna Mottola ◽  
Giulia Cipriano ◽  
Roberto Carlucci ◽  
Giuseppina Ciccarese ◽  
...  

Planta Medica ◽  
2017 ◽  
Vol 84 (06/07) ◽  
pp. 428-433 ◽  
Author(s):  
Corinna Schmiderer ◽  
Brigitte Lukas ◽  
Joana Ruzicka ◽  
Johannes Novak

AbstractQuality control of drugs consists of identifying the raw material to avoid unwanted admixtures or exchange of material as well as looking for abiotic and biotic contaminations. So far, identity and microbial contamination are analyzed by separate processes and separate methods. Species identification by their DNA (“DNA barcoding”) has the potential to supplement existing methods of identification. The introduction of next-generation sequencing methods offers completely new approaches like the identification of whole communities in one analysis, termed “DNA metabarcoding”. Here we present a next-generation sequencing assessment to identify plants and fungi of two commercial sage samples (Salvia officinalis) using the standard DNA barcoding region “internal transcribed spacer” consisting of internal transcribed spacer 1 and internal transcribed spacer 2, respectively. The main species in both samples was identified as S. officinalis. The spectrum of accompanying plant and fungal species, however, was completely different between the samples. Additionally, the composition between internal transcribed spacer 1 and internal transcribed spacer 2 within the samples was different and demonstrated the influence of primer selection and therefore the need for harmonization. This next-generation sequencing approach does not result in quantitative species composition but gives deeper insight into the composition of additional species. Therefore, it would allow for a better knowledge-based risk assessment than any other method available. However, the method is only economically feasible in routine analysis if a high sample throughput can be guaranteed.


2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Xinmei Liu ◽  
Zhiyang Liu ◽  
Yiyu Cheng ◽  
Haijing Wu ◽  
Wei Shen ◽  
...  

Polymerase chain reaction (PCR) detection is a commonly used method for species identification of meat products. However, this method is not suitable for the analysis of meat products containing multiple mixtures. This study aimed to test whether next-generation sequencing (NGS) technology could be used as a method for the certification of mixed meat products. In this study, five kinds of common meat (pigs, cattle, sheep, chickens, and ducks) were mixed as samples with different proportions. The primers designed from mitochondrial 16S rRNA and nuclear genome gene (growth hormone receptor, GHR), respectively, were used to detect these meats. The sequencing results of NGS were analyzed using a self-designed bioinformatics program. The fragments with similar sequences were classified and compared with the database to determine their species. The results showed that all five kinds of meat components could be correctly identified using these two primers. The meat composition could be detected as low as 0.5% in the mixed samples using the NGS technology targeting GHR gene fragments, which was superior to those targeting mitochondrial 16S rRNA. However, the quantitative detection of species in the mixture was not likely to be quite accurate due to the amplification bias of PCR amplification. These results showed that the NGS technology could be applied to identify meat species in mixtures.


Author(s):  
Maja Kosecka-Strojek ◽  
Artur J. Sabat ◽  
Viktoria Akkerboom ◽  
Anna M. D. Kooistra-Smid ◽  
Jacek Miedzobrodzki ◽  
...  

Abstract Background Many members of Streptococcus and Enterococcus genera are clinically relevant opportunistic pathogens warranting accurate and rapid identification for targeted therapy. Currently, the developed method based on next generation sequencing (NGS) of the 16S–23S rRNA region proved to be a rapid, reliable and precise approach for species identification directly from polymicrobial and challenging clinical samples. The introduction of this new method to routine diagnostics is hindered by a lack of the reference sequences for the 16S–23S rRNA region for many bacterial species. The aim of this study was to develop a careful assignment for streptococcal and enterococcal species based on NGS of the 16S–23S rRNA region. Methods Thirty two strains recovered from clinical samples and 19 reference strains representing 42 streptococcal species and nine enterococcal species were subjected to bacterial identification by four Sanger-based sequencing methods targeting the genes encoding (i) 16S rRNA, (ii) sodA, (iii) tuf and (iv) rpoB; and NGS of the 16S–23S rRNA region. Results This study allowed obtainment and deposition of reference sequences of the 16S–23S rRNA region for 15 streptococcal and 3 enterococcal species followed by enrichment for 27 and 6 species, respectively, for which reference sequences were available in the databases. For Streptococcus, NGS of the 16S–23S rRNA region was as discriminative as Sanger sequencing of the tuf and rpoB genes allowing for an unambiguous identification of 93% of analyzed species. For Enterococcus, sodA, tuf and rpoB genes sequencing allowed for identification of all species, while the NGS-based method did not allow for identification of only one enterococcal species. For both genera, the sequence analysis of the 16S rRNA gene was endowed with a low identification potential and was inferior to that of other tested identification methods. Moreover, in case of phylogenetically related species the sequence analysis of only the intergenic spacer region was not sufficient enough to precisely identify Streptococcus strains at the species level. Conclusions Based on the developed reference dataset, clinically relevant streptococcal and enterococcal species can now be reliably identified by 16S–23S rRNA sequences in samples. This study will be useful for introduction of a novel diagnostic tool, NGS of the 16S–23S rRNA region, which undoubtedly is an improvement for reliable culture-independent species identification directly from polymicrobially constituted clinical samples.


2017 ◽  
Vol 234 ◽  
pp. 212-219 ◽  
Author(s):  
Kristina Kappel ◽  
Ilka Haase ◽  
Christine Käppel ◽  
Carmen G. Sotelo ◽  
Ute Schröder

Sign in / Sign up

Export Citation Format

Share Document