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Yu C, Dai S, Li S, Li J, Hu H, Meng J, Wei C, Wu JJ. Nucleic Acid Detection with Ion Concentration Polarization Microfluidic Chip for Reduced Cycle Numbers of Polymerase Chain Reaction. MICROMACHINES 2022; 13:1394. [PMID: 36144017 PMCID: PMC9506297 DOI: 10.3390/mi13091394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/24/2022] [Accepted: 08/24/2022] [Indexed: 06/16/2023]
Abstract
Nucleic acid detection is widely used in disease diagnosis, food safety, environmental monitoring and many other research fields. The continuous development of rapid and sensitive new methods to detective nucleic acid is very important for practical application. In this study, we developed a rapid nucleic-acid detection method using polymerase chain reaction (PCR) combined with electrokinetic preconcentration based on ion concentration polarization (ICP). Using a Nafion film, the proposed ICP microfluidic chip is utilized to enrich the nucleic acid molecules amplified by PCR thermal cycles. To demonstrate the capability of the microfluidic device and the hybrid nucleic-acid detection method, we present an animal-derived component detection experiment for meat product identification applications. With the reduced cycle numbers of 24 cycles, the detection can be completed in about 35 min. The experimental results show that this work can provide a microfluidic device and straightforward method for rapid detection of nucleic acids with reduced cycle numbers.
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Affiliation(s)
- Chengzhuang Yu
- Hebei Key Laboratory of Smart Sensing and Human–Robot Interactions, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Shijie Dai
- Hebei Key Laboratory of Smart Sensing and Human–Robot Interactions, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Shanshan Li
- Hebei Key Laboratory of Smart Sensing and Human–Robot Interactions, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Junwei Li
- Institute of Biophysics, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Hezhi Hu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
- Department of Electronics and Information Engineering, Hebei University of Technology, Langfang 065099, China
| | - Jiyu Meng
- Hebei Key Laboratory of Smart Sensing and Human–Robot Interactions, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Chunyang Wei
- Hebei Key Laboratory of Smart Sensing and Human–Robot Interactions, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Jie Jayne Wu
- Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA
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Detection of Ovine or Bovine Milk Components in Commercial Camel Milk Powder Using a PCR-Based Method. Molecules 2022; 27:molecules27093017. [PMID: 35566364 PMCID: PMC9103995 DOI: 10.3390/molecules27093017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 04/27/2022] [Accepted: 04/29/2022] [Indexed: 12/01/2022] Open
Abstract
Food ingredient adulteration, especially the adulteration of milk and dairy products, is one of the important issues of food safety. The large price difference between camel milk powder, ovine, and bovine milk powder may be an incentive for the incorporation of ovine and bovine derived foods in camel milk products. This study evaluated the use of ordinary PCR and real-time PCR for the detection of camel milk powder adulteration based on the presence of ovine and bovine milk components. DNA was extracted from camel, ovine, and bovine milk powder using a deep-processed product column DNA extraction kit. The quality of the extracted DNA was detected by amplifying the target sequence from the mitochondrial Cytb gene, and the extracted DNA was used for the identification of milk powder based on PCR analysis. In addition, PCR-based methods (both ordinary PCR and real-time PCR) were used to detect laboratory adulteration models of milk powder using primers targeting mitochondrial genes. The results show that the ordinary PCR method had better sensitivity and could qualitatively detect ovine and bovine milk components in the range of 1% to 100% in camel milk powder. The commercial camel milk powder was used to verify the practicability of this method. The real-time PCR normalization system has a good exponential correlation (R2 = 0.9822 and 0.9923) between ovine or bovine content and Ct ratio (specific/internal reference gene) and allows for the quantitative determination of ovine or bovine milk contents in adulterated camel milk powder samples. Accuracy was effectively validated using simulated adulterated samples, with recoveries ranging from 80% to 110% with a coefficient of variation of less than 7%, exhibiting sufficient parameters of trueness. The ordinary PCR qualitative detection and real-time PCR quantitative detection method established in this study proved to be a specific, sensitive, and effective technology, which is expected to be used for market detection.
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Zhang X, Qiao C, Fu S, Jiao Y, Liu Y. DNA-based qualitative and quantitative identification of bovine whey powder in goat dairy products. J Dairy Sci 2022; 105:4749-4759. [PMID: 35450717 DOI: 10.3168/jds.2021-21618] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 02/16/2022] [Indexed: 11/19/2022]
Abstract
As one of the main ingredients in some milk powders, whey powder is sometimes added to pure goat milk products, which causes health risks, economic fraud, and unfair competition of food industries. This study is the first to explore qualitative and quantitative methods to identify adulteration of bovine whey powder in goat dairy products based on DNA. We extracted DNA from whey powder using a modified DNA extraction method; this exhibited good quality and integrity, with purity of 1.53 to 1.75 and concentration of 122 to 179 ng/μL. Conventional PCR and real-time PCR were compared for qualitative detection of bovine whey powder; real-time PCR demonstrated sensitivity of 0.01 ng/μL, which was higher than the 0.05 ng/μL detected by the conventional PCR method. Furthermore, real-time PCR was conducted for DNA quantitative detection, with good linearity (R2 = 0.9858) obtained for bovine whey powder contents from 0.1% to 30%. Relative error decreased with increase of the mixing proportion of whey powder; the coefficient of variation above 0.1% of the mixing ratio was close to or less than 5%; and the relative standard deviation of repeatability results was less than 5%. Considering the economic costs of testing, conventional PCR could be performed first, and samples with obvious intentional adulteration detected can be further accurately quantified by real-time PCR. Overall, this research provides a realistic and effective method for qualitative and quantitative identification of bovine whey powder in goat dairy products, thus laying a good foundation for verification of goat dairy product label claims and industrial control.
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Affiliation(s)
- Xueru Zhang
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an 710062, Shaanxi, China
| | - Chunyan Qiao
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an 710062, Shaanxi, China
| | - Shangchen Fu
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an 710062, Shaanxi, China
| | - Yang Jiao
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an 710062, Shaanxi, China
| | - Yongfeng Liu
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an 710062, Shaanxi, China.
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Mafra I, Honrado M, Amaral JS. Animal Species Authentication in Dairy Products. Foods 2022; 11:foods11081124. [PMID: 35454711 PMCID: PMC9027536 DOI: 10.3390/foods11081124] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/06/2022] [Accepted: 04/11/2022] [Indexed: 02/01/2023] Open
Abstract
Milk is one of the most important nutritious foods, widely consumed worldwide, either in its natural form or via dairy products. Currently, several economic, health and ethical issues emphasize the need for a more frequent and rigorous quality control of dairy products and the importance of detecting adulterations in these products. For this reason, several conventional and advanced techniques have been proposed, aiming at detecting and quantifying eventual adulterations, preferentially in a rapid, cost-effective, easy to implement, sensitive and specific way. They have relied mostly on electrophoretic, chromatographic and immunoenzymatic techniques. More recently, mass spectrometry, spectroscopic methods (near infrared (NIR), mid infrared (MIR), nuclear magnetic resonance (NMR) and front face fluorescence coupled to chemometrics), DNA analysis (real-time PCR, high-resolution melting analysis, next generation sequencing and droplet digital PCR) and biosensors have been advanced as innovative tools for dairy product authentication. Milk substitution from high-valued species with lower-cost bovine milk is one of the most frequent adulteration practices. Therefore, this review intends to describe the most relevant developments regarding the current and advanced analytical methodologies applied to species authentication of milk and dairy products.
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Affiliation(s)
- Isabel Mafra
- REQUIMTE-LAQV, Faculdade de Farmácia, Universidade do Porto, 4050-313 Porto, Portugal
- Correspondence: (I.M.); (J.S.A.)
| | - Mónica Honrado
- CIMO, Instituto Politécnico de Bragança, 5300-253 Bragança, Portugal;
| | - Joana S. Amaral
- CIMO, Instituto Politécnico de Bragança, 5300-253 Bragança, Portugal;
- Correspondence: (I.M.); (J.S.A.)
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Bwambok DK, Siraj N, Macchi S, Larm NE, Baker GA, Pérez RL, Ayala CE, Walgama C, Pollard D, Rodriguez JD, Banerjee S, Elzey B, Warner IM, Fakayode SO. QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6982. [PMID: 33297345 PMCID: PMC7730680 DOI: 10.3390/s20236982] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/01/2020] [Accepted: 12/03/2020] [Indexed: 12/23/2022]
Abstract
Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.
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Affiliation(s)
- David K. Bwambok
- Chemistry and Biochemistry, California State University San Marcos, 333 S. Twin Oaks Valley Rd, San Marcos, CA 92096, USA;
| | - Noureen Siraj
- Department of Chemistry, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR 72204, USA; (N.S.); (S.M.)
| | - Samantha Macchi
- Department of Chemistry, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR 72204, USA; (N.S.); (S.M.)
| | - Nathaniel E. Larm
- Department of Chemistry, University of Missouri, 601 S. College Avenue, Columbia, MO 65211, USA; (N.E.L.); (G.A.B.)
| | - Gary A. Baker
- Department of Chemistry, University of Missouri, 601 S. College Avenue, Columbia, MO 65211, USA; (N.E.L.); (G.A.B.)
| | - Rocío L. Pérez
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Caitlan E. Ayala
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Charuksha Walgama
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
| | - David Pollard
- Department of Chemistry, Winston-Salem State University, 601 S. Martin Luther King Jr Dr, Winston-Salem, NC 27013, USA;
| | - Jason D. Rodriguez
- Division of Complex Drug Analysis, Center for Drug Evaluation and Research, US Food and Drug Administration, 645 S. Newstead Ave., St. Louis, MO 63110, USA;
| | - Souvik Banerjee
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
| | - Brianda Elzey
- Science, Engineering, and Technology Department, Howard Community College, 10901 Little Patuxent Pkwy, Columbia, MD 21044, USA;
| | - Isiah M. Warner
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Sayo O. Fakayode
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
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Quantitative determination of mutton adulteration with single-copy nuclear genes by real-time PCR. Food Chem 2020; 344:128622. [PMID: 33221099 DOI: 10.1016/j.foodchem.2020.128622] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 11/07/2020] [Accepted: 11/08/2020] [Indexed: 12/17/2022]
Abstract
Mitochondrial genes were generally adopted for PCR-based meat adulteration authentication due to their excellent specificity to species and numerous copies in one cell. However, the number of mitochondrial gene copies varies according to cells and tissues, which leads to quantification errors for meat adulteration. To address this problem, single-copy nuclear genes were selected to develop a quantitative method for identifying mutton adulteration in this study. Both single-copy genes specific to sheep species and single-copy reference genes show good linearity between Ct values and series diluted DNA concentrations, with the correlation coefficients of 0.9999 and 0.9993, respectively. Meanwhile, a constant (correction factor) was introduced to transform DNA concentrations into mutton proportions in adulterated meat. With this method, simulated mutton-pork, mutton-chicken and mutton-duck adulteration samples could be accurately quantified with the recovery rates of 89.56%, 107.13% and 95.20%, respectively.
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