scholarly journals Snipe: highly sensitive pathogen detection from metagenomic sequencing data

2021 ◽  
Author(s):  
Lihong Huang ◽  
Bin Hong ◽  
Wenxian Yang ◽  
Liansheng Wang ◽  
Rongshan Yu
Keyword(s):  
Foodborne Pathogens ◽  
Pathogen Detection ◽  
High Sensitivity ◽  
High Specificity ◽  
Correction Method ◽  
Food Samples ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Metagenomics Data ◽  
Species Specific

Abstract Metagenomics data provide rich information for the detection of foodborne pathogens from food and environmental samples that are mixed with complex background bacteria strains. While pathogen detection from metagenomic sequencing data has become an activity of increasing interest, shotgun sequencing of uncultured food samples typically produces data that contain reads from many different organisms, making accurate strain typing a challenging task. Particularly, as many pathogens may contain a common set of genes that are highly similar to those from normal bacteria in food samples, traditional strain-level abundance profiling approaches do not perform well at detecting pathogens of very low abundance levels. To overcome this limitation, we propose an abundance correction method based on species-specific genomic regions to achieve high sensitivity and high specificity in target pathogen detection at low abundance.

scholarly journals Snipe: Highly sensitive pathogen detection from metagenomic sequencing data

2020 ◽  
Author(s):  
Lihong Huang ◽  
Bin Hong ◽  
Wenxian Yang ◽  
Liansheng Wang ◽  
Rongshan Yu
Keyword(s):  
Foodborne Pathogens ◽  
Pathogen Detection ◽  
High Sensitivity ◽  
High Specificity ◽  
Correction Method ◽  
Food Samples ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Metagenomics Data ◽  
Species Specific

Metagenomics data provides rich information for the detection of foodborne pathogens from food and environmental samples that are mixed with complex background bacteria strains. While pathogen detection from metagenomic sequencing data has become an activity of increasing interest, shotgun sequencing of uncultured food samples typically produces data that contains reads from many different organisms, making accurate strain typing a challenging task. Particularly, as many pathogens may contain a common set of genes that are highly similar to those from normal bacteria in food samples, traditional strain-level abundance profiling approaches do not perform well at detecting pathogens of very low abundance levels. To overcome this limitation, we propose an abundance correction method based on species-specific genomic regions to achieve high sensitivity and high specificity in target pathogen detection at low abundance.

Microbiome population dynamics of cold smoked sockeye salmon during refrigerated storage and after culture enrichment

2021 ◽  
Author(s):  
Karen Jarvis ◽  
Chiun-Kang Hsu ◽  
James B. Pettengill ◽  
John Ihrie ◽  
Hiren Karathia ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Foodborne Pathogens ◽  
Sockeye Salmon ◽  
Pathogen Detection ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Smoked Salmon ◽  
Spoilage Bacteria ◽  
Culture Enrichment ◽  
Processing And Storage

Cold smoked salmon is a ready-to-eat seafood product of high commercial importance. The processing and storage steps facilitate the introduction, growth and persistence of foodborne pathogens and spoilage bacteria. The growth of commensal bacteria during storage and once the product is opened also influence the quality and safety of cold smoked salmon. Here we investigated the microbial community through targeted 16s rRNA gene and shotgun metagenomic sequencing, as means to better understand the interactions among bacteria in cold smoked salmon. Cold smoked salmon samples were tested over 30 days of aerobic storage at 4℃ and cultured at each timepoint in buffered Listeria enrichment broth (BLEB) commonly used to detect Listeria in foods. The microbiomes were comprised of Firmicutes and Proteobacteria namely, Carnobacterium , Brochothrix , Pseudomonas , Serratia , and Psychrobacter . Pseudomonas species were the most diverse species with 181 taxa identified. Additionally, we identified potential homologs to 10 classes of bacteriocins in microbiomes of cold smoked salmon stored at 4°C and corresponding BLEB culture enrichments. The findings presented here contribute to our understanding of microbiome population dynamics in cold smoked salmon, including changes in bacterial taxa during aerobic cold storage and after culture enrichment.  This may facilitate improvements to pathogen detection and quality preservation of this food.

scholarly journals A 16S rDNA-based nested PCR protocol to detect Campylobacter gracilis in oral infections

2003 ◽  
Vol 17 (2) ◽  
pp. 142-146 ◽  
Author(s):  
José Freitas Siqueira Júnior ◽  
Isabela das Neves Rôças
Keyword(s):  
16S Rdna ◽  
High Sensitivity ◽  
High Specificity ◽  
Cross Reactivity ◽  
Nested Polymerase Chain Reaction ◽  
Oral Infections ◽  
Root Canals ◽  
Infected Root ◽  
Pcr Products ◽  
Species Specific

The aim of this study was to describe a 16S rDNA-based nested polymerase chain reaction (nPCR) assay to investigate the occurrence of Campylobacter gracilis in oral infections. Samples were collected from ten infected root canals, ten cases of acute periradicular abscesses and eight cases of adult marginal periodontitis. DNA extracted from the samples was initially amplified using universal 16S rDNA primers. A second round of amplification used the first PCR products to detect C. gracilis using oligonucleotide primers designed from species-specific 16S rDNA signature sequences. The nPCR assay used in this study showed a detection limit of 10 C. gracilis cells and no cross-reactivity was observed with nontarget bacteria. C. gracilis was detected in the three types of oral infections investigated - 4/10 infected root canals; 2/10 acute periradicular abscesses; and 1/8 subgingival specimens from adult periodontitis. The method proposed in this study showed both high sensitivity and high specificity to directly detect C. gracilis in samples from root canal infections, abscesses, and subgingival plaque. Our findings confirmed that C. gracilis may be a member of the microbiota associated with distinct oral infections, and its specific role in such diseases requires further clarification.

scholarly journals DNA Sequence Signatures for Rapid Detection of Six Target Bacterial Pathogens Using PCR Assays

2015 ◽  
Vol 8 ◽  
pp. MBI.S29736 ◽  
Author(s):  
Kenjiro Nagamine ◽  
Guo-Chiuan Hung ◽  
Bingjie Li ◽  
Shyh-Ching Lo
Keyword(s):  
Safety Concern ◽  
Rapid Development ◽  
High Sensitivity ◽  
High Specificity ◽  
Clostridium Tetani ◽  
Specificity And Sensitivity ◽  
Wide Range ◽  
Pcr Assays ◽  
Primer Sets ◽  
Species Specific

Using Streptococcus pyogenes as a model, we previously established a stepwise computational workflow to effectively identify species-specific DNA signatures that could be used as PCR primer sets to detect target bacteria with high specificity and sensitivity. In this study, we extended the workflow for the rapid development of PCR assays targeting Enterococcus faecalis, Enterococcus faecium, Clostridium perfringens, Clostridium difficile, Clostridium tetani, and Staphylococcus aureus, which are of safety concern for human tissue intended for transplantation. Twenty-one primer sets that had sensitivity of detecting 5–50 fg DNA from target bacteria with high specificity were selected. These selected primer sets can be used in a PCR array for detecting target bacteria with high sensitivity and specificity. The workflow could be widely applicable for the rapid development of PCR-based assays for a wide range of target bacteria, including those of biothreat agents.

scholarly journals Challenging a bioinformatic tool’s ability to detect microbial contaminants usingin silicowhole genome sequencing data

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3729 ◽  
Author(s):  
Nathan D. Olson ◽  
Justin M. Zook ◽  
Jayne B. Morrow ◽  
Nancy J. Lin
Keyword(s):  
Binary Mixtures ◽  
Genome Sequencing ◽  
Pathogen Detection ◽  
A Priori ◽  
High Sensitivity ◽  
False Positives ◽  
Sequencing Data ◽  
Materials Used ◽  
The Individual ◽  
Genome Assemblies

High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need fora prioriassumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, withStaphylococcus,Escherichia, andShigellahaving the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in thein-silicodatasets at the equivalent of 1 in 1,000 cells, thoughF. tularensiswas not detected in any of the simulated contaminant mixtures andY. pestiswas only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.

scholarly journals Quantum dot biosensor combined with antibody and aptamer for tracing food-borne pathogens

2021 ◽  
Vol 5 ◽  
Author(s):  
Feifei Sun ◽  
Jing Zhang ◽  
Qingli Yang ◽  
Wei Wu
Keyword(s):  
Quantum Dots ◽  
Pathogen Detection ◽  
High Sensitivity ◽  
High Specificity ◽  
Detection Methods ◽  
Food Borne Pathogens ◽  
Food Borne ◽  
Recognition Elements ◽  
Different Characteristics ◽  
And Control

Abstract Due to the increasing number of food-borne diseases, more attention is being paid to food safety. Food-borne pathogens are the main cause of food-borne diseases, which seriously endanger human health, so it is necessary to detect and control them. Traditional detection methods cannot meet the requirements of rapid detection of food due to many shortcomings, such as being time-consuming, laborious or requiring expensive instrumentation. Quantum dots have become a promising nanotechnology in pathogens tracking and detection because of their excellent optical properties. New biosensor detection methods based on quantum dots are have been gradually developed due to their high sensitivity and high specificity. In this review, we summarize the different characteristics of quantum dots synthesized by carbon, heavy metals and composite materials firstly. Then, attention is paid to the principles, advantages and limitations of the quantum dots biosensor with antibodies and aptamers as recognition elements for recognition and capture of food-borne pathogens. Finally, the great potential of quantum dots in pathogen detection is summarized.

Binding Inhibition Assay Using Fiber-Optic Based Biosensor for the Detection of Foodborne Pathogens

2006 ◽  
Vol 321-323 ◽  
pp. 1145-1150 ◽  
Author(s):  
Mark T. Morgan ◽  
Gi Young Kim ◽  
Daniel Ess ◽  
Aparna Kothapalli ◽  
Byoung Kwon Hahm ◽  
...  
Keyword(s):  
Foodborne Pathogens ◽  
Salmonella Enteritidis ◽  
Pathogen Detection ◽  
Fiber Optic ◽  
Fiber Surface ◽  
Food Samples ◽  
Fluorescent Light ◽  
Inhibition Assay ◽  
Binding Inhibition ◽  
Binding Inhibition Assay

Frequent outbreaks of foodborne illness have been increasing the need for simple, rapid and sensitive methods to detect foodborne pathogens. Conventional methods for pathogen detection and identification are labor-intensive and take days to complete. Some immunological rapid assays are developed, but these assays still require prolonged enrichment steps. Biosensors have shown great potential for the rapid detection of foodborne pathogens. Among the biosensors, fiber-optic methods have much potential because they can be very sensitive and simple to operate. Fiber-optic biosensors typically use a light transmittable, tapered fiber to send excitation laser light to the detection surface and receive emitted fluorescent light. The fluorescent light excited by an evanescent wave generated by the laser is quantitatively related to fluorophor-labeled biomolecules immobilized on the fiber surface. A portable and automated fiber-optic biosensor, RAPTOR (Research International, Monroe, WA), was used to detect Salmonella enteritidis in food samples. A binding inhibition assay based on the biosensor was developed to detect the bacteria in hot dog samples. The biosensor and the binding inhibition assay could detect 104 cfu/ml of bacteria in less than 10 min of assay time.

scholarly journals Biosensor for detection of bacteria with probiotic potential and food pathogens

2020 ◽  
Vol 9 (1) ◽  
pp. 800-807
Keyword(s):  
Foodborne Pathogens ◽  
Pathogen Detection ◽  
Food Contamination ◽  
High Specificity ◽  
Nanostructured Material ◽  
Probiotic Bacteria ◽  
Food Contaminants ◽  
Probiotic Potential ◽  
Detection Technology ◽  
Wide Range

The exploration for novel nano-sensors has enhanced significantly representing an incredible alternative for the development, speedy, and inexpensive bio-sensing strategy. Due to their low detection volumes, reduction of detection time, high specificity and user- friendly applicability, nano-bio sensors have raised the interest of the scientific community. Nanomaterials are now being used to develop biosensors thatexhibit superior sensitivity and uniqueness with applicability in research investigations, food contamination detection, detection of potential probiotic bacteria, etc. Detection of food contamination is of major significance and concern in areas like healthcare, agriculture, beverage, and fermentation industries. Distinctive biosensing technologies have already been developed for instant monitoring of microbes, food contaminants depending upon the application of nanomaterial. A wide range of nanomaterials, for example, gold nanostructured materials, carbon Copper and silicon nanotubes, GeO2/SiO2 matrix, nanoparticles, nanowires, TiO2 nanowire, nano-electrode, and nanostructured material arrays are performing an essential role in the bio-sensing application in food pathogen detection and probiotic bacteria detection.Nanosensors merges the principles of information technology and molecular biology proves essential in facilitating immediate detection of foodborne pathogens, contaminants, hence reducing the health risk and medical costs related to foodborne illness.This chapter aims to encompass the types of emerging nanosensors based on different detection technology, their commercial applications, recent advancement in food contamination detection and their future prospects.

scholarly journals Efficient and Specific Detection ofSalmonellain Food Samples Using astn-Based Loop-Mediated Isothermal Amplification Method

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Mevaree Srisawat ◽  
Watanalai Panbangred
Keyword(s):  
Lamp Assay ◽  
High Sensitivity ◽  
High Specificity ◽  
Culture Method ◽  
Food Samples ◽  
Isothermal Amplification ◽  
Lamp Method ◽  
Loop Mediated Isothermal Amplification ◽  
Amplification Method ◽  
Pure Cultures

TheSalmonellaenterotoxin (stn) gene exhibits high homology amongS. entericaserovars andS. bongori. A set of 6 specific primers targeting thestngene were designed for detection ofSalmonellaspp. using the loop-mediated isothermal amplification (LAMP) method. The primers amplified target sequences in all 102 strains of 87 serovars ofSalmonellatested and no products were detected in 57 non-Salmonellastrains. The detection limit in pure cultures was 5 fg DNA/reaction when amplified at 65°C for 25 min. The LAMP assay could detectSalmonellain artificially contaminated food samples as low as 220 cells/g of food without a preenrichment step. However, the sensitivity was increased 100-fold (~2 cells/g) following 5 hr preenrichment at 35°C. The LAMP technique, with a preenrichment step for 5 and 16 hr, was shown to give 100% specificity with food samples compared to the reference culture method in which 67 out of 90 food samples gave positive results. Different food matrixes did not interfere with LAMP detection which employed a simple boiling method for DNA template preparation. The results indicate that the LAMP method, targeting thestngene, has great potential for detection ofSalmonellain food samples with both high specificity and high sensitivity.

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