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Song Z, Ge Y, Yu X, Liu R, Liu C, Cheng K, Guo L, Yao S. Development of a single nucleotide polymorphism-based strain-identified method for Streptococcus thermophilus CICC 6038 and Lactobacillus delbrueckii ssp. bulgaricus CICC 6047 using pan-genomics analysis. J Dairy Sci 2024; 107:4248-4258. [PMID: 38246550 DOI: 10.3168/jds.2023-23655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
The health benefits conferred by probiotics is specific to individual probiotic strains, highlighting the importance of identifying specific strains for research and production purposes. Streptococcus thermophilus CICC 6038 and Lactobacillus delbrueckii ssp. bulgaricus CICC 6047 are exceedingly valuable for commercial use with an excellent mixed-culture fermentation. To differentiate these 2 strains from other S. thermophilus and L. delbrueckii ssp. bulgaricus, a specific, sensitive, accurate, rapid, convenient, and cost-effective method is required. In this study, we conducted a pan-genome analysis of S. thermophilus and L. delbrueckii ssp. bulgaricus to identify species-specific core genes, along with strain-specific SNPs. These genes were used to develop suitable PCR primers, and the conformity of sequence length and unique SNPs was confirmed by sequencing for qualitative identification at the strain level. The results demonstrated that SNPs analysis of PCR products derived from these primers could distinguish CICC 6038 and CICC 6047 accurately and reproducibly from the other strains of S. thermophilus and L. delbrueckii ssp. bulgaricus, respectively. The strain-specific PCR method based on SNPs herein is universally applicable for probiotics identification. It offers valuable insights into identifying probiotics at the strain level that is fit-for-purpose in quality control and compliance assessment of commercial dairy products.
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Affiliation(s)
- Zhiquan Song
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China
| | - Yuanyuan Ge
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China; Beijing Forestry University, College of Biological Sciences and Biotechnology, Beijing, 100083, China
| | - Xuejian Yu
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China
| | - Rui Liu
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China
| | - Chong Liu
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China
| | - Kun Cheng
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China
| | - Lizheng Guo
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China
| | - Su Yao
- China National Research Institute of Food and Fermentation Industries Co. Ltd., China Center of Industrial Culture Collection, Beijing, 100015, China.
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Mafizur RM, Sangjin L, Chul PY. Prevalence of Salmonella spp. and Escherichia coli in the feces of free-roaming wildlife throughout South Korea. PLoS One 2024; 19:e0281006. [PMID: 38358989 PMCID: PMC10868816 DOI: 10.1371/journal.pone.0281006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 01/08/2023] [Indexed: 02/17/2024] Open
Abstract
Wildlife can carry pathogenic organisms, including viruses, bacteria, parasites, and fungi, which can spread to humans and cause mild to serious illnesses and even death. Spreading through animal feces, these pathogens significantly contributes to the global burden of human diseases. Therefore, the present study investigated the prevalence of zoonotic bacterial pathogens, such as Salmonella spp., Escherichia coli, and Shiga toxin-producing E. coli (STEC), in animal feces. Between September 2015 and August 2017, 699 wildlife fecal samples were collected from various agricultural production regions and mountainous areas in South Korea. Fecal samples were collected from wild mammals (85.26%, 596/699) and birds (14.73%, 103/699). Salmonella spp. and E. coli were present in 3% (21/699) and 45.63% (319/699) of the samples, respectively. Moreover, virulence genes stx1 and both stx1 and stx2 were detected in 13.30% (93/699) and 0.72% (5/699) of the samples, respectively. The 21 Salmonella spp. were detected in badgers (n = 5), leopard cats (n = 7), wild boars (n = 2), and magpies (n = 7); STEC was detected in roe deer, water deer, mice, and wild boars. Through phylogenetic and gene-network analyses, the Salmonella spp. isolates (n = 21 laboratory isolates, at least one isolate from each Salmonella-positive animal fecal sample, and n = 6 widely prevalent reference Salmonella serovars) were grouped into two major lineages: S. enterica subsp. enterica and S. enterica subsp. diarizonae. Similarly, 93 E. coli isolates belonged to stx1, including three major lineages (groups 1-3), and stx1 and stx2 detected groups. To the best of our knowledge, this is the first report of a wild leopard cat serving as a reservoir for Salmonella spp. in South Korea. The research findings can help manage the potential risk of wildlife contamination and improve precautionary measures to protect public health.
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Affiliation(s)
- Rahman M. Mafizur
- Division of Forest Science, Kangwon National University, Chuncheon, Republic of Korea
- Department of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh
| | - Lim Sangjin
- Division of Forest Science, Kangwon National University, Chuncheon, Republic of Korea
- Institute of Forest Science, Kangwon National University, Chuncheon, Republic of Korea
| | - Park Y. Chul
- Division of Forest Science, Kangwon National University, Chuncheon, Republic of Korea
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Hoon KS, Holt DC, Auburn S, Shaw P, Giffard PM. minSNPs: an R package for the derivation of resolution-optimised SNP sets from microbial genomic data. PeerJ 2023; 11:e15339. [PMID: 37250706 PMCID: PMC10224671 DOI: 10.7717/peerj.15339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 04/12/2023] [Indexed: 05/31/2023] Open
Abstract
Here, we present the R package, minSNPs. This is a re-development of a previously described Java application named Minimum SNPs. MinSNPs assembles resolution-optimised sets of single nucleotide polymorphisms (SNPs) from sequence alignments such as genome-wide orthologous SNP matrices. MinSNPs can derive sets of SNPs optimised for discriminating any user-defined combination of sequences from all others. Alternatively, SNP sets may be optimised to determine all sequences from all other sequences, i.e., to maximise diversity. MinSNPs encompasses functions that facilitate rapid and flexible SNP mining, and clear and comprehensive presentation of the results. The minSNPs' running time scales in a linear fashion with input data volume and the numbers of SNPs and SNPs sets specified in the output. MinSNPs was tested using a previously reported orthologous SNP matrix of Staphylococcus aureus and an orthologous SNP matrix of 3,279 genomes with 164,335 SNPs assembled from four S. aureus short read genomic data sets. MinSNPs was shown to be effective for deriving discriminatory SNP sets for potential surveillance targets and in identifying SNP sets optimised to discriminate isolates from different clonal complexes. MinSNPs was also tested with a large Plasmodium vivax orthologous SNP matrix. A set of five SNPs was derived that reliably indicated the country of origin within three south-east Asian countries. In summary, we report the capacity to assemble comprehensive SNP matrices that effectively capture microbial genomic diversity, and to rapidly and flexibly mine these entities for optimised marker sets.
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Affiliation(s)
- Kian Soon Hoon
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia
| | - Deborah C. Holt
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia
- CDU Menzies School of Medicine, Faculty of Health, Charles Darwin University, Darwin, Northern Territory, Australia
| | - Sarah Auburn
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia
- Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom
| | - Peter Shaw
- Oujian Laboratory, Wenzhou, Zhejiang, China
| | - Philip M. Giffard
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia
- CDU Menzies School of Medicine, Faculty of Health, Charles Darwin University, Darwin, Northern Territory, Australia
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Parihar A, Yadav S, Sadique MA, Ranjan P, Kumar N, Singhal A, Khare V, Khan R, Natarajan S, Srivastava AK. Internet‐of‐medical‐things integrated point‐of‐care biosensing devices for infectious diseases: Toward better preparedness for futuristic pandemics. Bioeng Transl Med 2023; 8:e10481. [DOI: 10.1002/btm2.10481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 12/15/2022] [Accepted: 12/19/2022] [Indexed: 01/04/2023] Open
Affiliation(s)
- Arpana Parihar
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
| | - Shalu Yadav
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
| | - Mohd Abubakar Sadique
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
| | - Pushpesh Ranjan
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
| | - Neeraj Kumar
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
| | - Ayushi Singhal
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
| | - Vedika Khare
- School of Nanotechnology, UTD, RGPV Campus Bhopal Madhya Pradesh India
| | - Raju Khan
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
| | - Sathish Natarajan
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
| | - Avanish K. Srivastava
- Industrial Waste Utilization, Nano and Biomaterials, CSIR‐Advanced Materials and Processes Research Institute (AMPRI) Bhopal Madhya Pradesh India
- Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India
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Genome-Wide Searching Single Nucleotide-Polymorphisms (SNPs) and SNPs-Targeting a Multiplex Primer for Identification of Common Salmonella Serotypes. Pathogens 2022; 11:pathogens11101075. [PMID: 36297133 PMCID: PMC9611365 DOI: 10.3390/pathogens11101075] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 12/04/2022] Open
Abstract
A rapid and high-quality single-nucleotide polymorphisms (SNPs)-based method was developed to improve detection and reduce salmonellosis burden. In this study, whole-genome sequence (WGS) was used to investigate SNPs, the most common genetic marker for identifying bacteria. SNP-sites encompassing 15 sets of primers (666–863 bp) were selected and used to amplify the target Salmonella serovar strains, and the amplified products were sequenced. The prevalent Salmonella enterica subspecies enterica serovars, including Typhimurium; Enteritidis, Agona, enterica, Typhi, and Abony, were amplified and sequenced. The amplified sequences of six Salmonella serovars with 15 sets of SNP-sites encompassing primers were aligned, explored SNPs, and SNPs-carrying primers (23 sets) were designed to develop a multiplex PCR marker (m-PCR). Each primer exists in at least two SNPs bases at the 3′ end of each primer, such as one was wild, and another was a mismatched base by transition or transversion mutation. Thus, twenty-three sets of SNP primers (242–670 bp), including 13 genes (SBG, dedA, yacG, mrcB, mesJ, metN, rihA/B, modA, hutG, yehX, ybiY, moeB, and sopA), were developed for PCR confirmation of target Salmonella serovar strains. Finally, the SNPs in four genes, including fliA gene (S. Enteritidis), modA (S. Agona and S. enterica), sopA (S. Abony), and mrcB (S. Typhimurium and S. Typhi), were used for detection markers of six target Salmonella serotypes. We developed an m-PCR primer set in which Salmonella serovars were detected in a single reaction. Nevertheless, m-PCR was validated with 21 Salmonella isolates (at least one isolate was taken from one positive animal fecal, and n = 6 reference Salmonella strains) and non-Salmonella bacteria isolates. The SNP-based m-PCR method would identify prevalent Salmonella serotypes, minimize the infection, and control outbreaks.
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