High-throughput Detection Method Research Articles

Determining the feasibility of constructing a real-time polymerase chain reaction instrument locally: The cost of intellectual property rights and research and development

BACKGROUND: Real-time polymerase chain reaction (PCR) machines have advanced the field of microbiology by introducing a robust method for high-throughput detection of nucleic acid targets. Unfortunately, these instruments are quite expensive to purchase and maintain, despite containing hardware parts that are relatively inexpensive. AIMS AND OBJECTIVES: We believe that it may be possible to mitigate costs in low- and middleincome countries (LMICs) by building such a PCR instrument from assembled parts. However, the major hindrance is the cost of intellectual property rights (IPRs), associated with research and development (R and D). The aim of this project was to understand the hardware costs, IPR royalties, profit margins, and the cost of R and D associated with PCR instrument manufacturing. MATERIALS AND METHODS: We conducted a review of two PCR machines to examine the differences in their technical and hardware specifications and quantify the cost of assembled parts alone. We also ran a parallel assay using the two machines to understand how the differences in technologies affected assay results. RESULTS AND CONCLUSION: Based on our analysis, we found that assembling a PCR machine using assembled parts can make these instruments more affordable in LMICs. There is a need to have collaboration and agreement between machine licensing, patent, and copyright holders to facilitate this process in LMICs.

Simultaneous enantiomeric determination of multiple triazole fungicides in fruits and vegetables by chiral liquid chromatography/tandem mass spectrometry on a bridged bis(β-cyclodextrin)-bonded chiral stationary phase

A LC-MS/MS method for simultaneous determination of twelve triazole enantiomers (hexaconazole, tebuconazole, triticonazole, flutriafol, diniconazole, paclobutrazol) in six fruits and vegetables was established based on a stable and self-made bridged bis(β-cyclodextrin)-bonded chiral stationary phase. Simultaneous enantio-separation of multiple analytes was achieved with resolution ca. 1.67–2.14. Magnetically assisted QuECHERS was used to simplify and optimize sample pre-treatment. The new method was validated (accuracy, precision, matrix effect, etc.). Good linearity (0.5–20 μg/L, R2 > 0.99) and high recoveries (76.1–103.4%) based on intra- and inter-day relative standard deviation (RSDs) (2.6–11.9%), were obtained. Furthermore, a total of 90 samples were analyzed using this method and enantiomeric fractions (EF) for tebuconazole in strawberry and cucumber (0.63 and 0.43, respectively) were determined as well as 0.57 for flutriafol in tomato. This high-throughput detection method supported a convenient enantiomeric monitoring for chiral pesticides in fruits and vegetables.

Application of Multiplexed Aptasensors in Food Contaminants Detection

The existence of contaminants in food poses a serious threat to human health. In recent years, aptamer sensors (aptasensors) have been developed rapidly for the detection of food contaminants because of their high specificity, design flexibility, and high efficiency. However, the development of high-throughput, highly sensitive, on-site, and cost-effective methods for simultaneous detection of food contaminants is still restricted due to multiple signal overlap or mutual interference and cross-reaction between different analytes with similar molecular structures. To overcome these problems, this Review summarizes some effective strategies from the articles published in recent years about multiplexed aptasensors for the simultaneous detection of food contaminants. This work focuses on the application of multiplexed aptasensors to simultaneously detect antibiotics, pathogens, and mycotoxins in food. These aptasensors mainly contain fluorescent aptasensors, electrochemical aptasensors, surface-enhanced Raman scattering-based aptasensors, microfluidic chip aptasensors, and paper-based multiplexed aptasensors. In addition, this Review also covers the application of nucleic acid cycle amplification and nanomaterial amplification strategies to improve the detection sensitivity. Finally, the limitations and challenges in the design of multiplexed aptasensor are also taken into account.

Influence of image analysis strategy, cooling rate, and sample volume on apparent protein cloud-point temperature determination

The protein cloud-point temperature (TCloud) is a known representative of protein–protein interaction strength and provides valuable information during the development and characterization of protein-based products, such as biopharmaceutics. A high-throughput low volume TCloud detection method was introduced in preceding work, where it was concluded that the extracted value is an apparent TCloud (TCloud,app). As an understanding of the apparent nature is imperative to facilitate inter-study data comparability, the current work was performed to systematically evaluate the influence of 3 image analysis strategies and 2 experimental parameters (sample volume and cooling rate) on TCloud,app detection of lysozyme. Different image analysis strategies showed that TCloud,app is detectable by means of total pixel intensity difference and the total number of white pixels, but the latter is also able to extract the ice nucleation temperature. Experimental parameter variation showed a TCloud,app depression for increasing cooling rates (0.1–0.5 °C/min), and larger sample volumes (5–24 μL). Exploratory thermographic data indicated this resulted from a temperature discrepancy between the measured temperature by the cryogenic device and the actual sample temperature. Literature validation confirmed that the discrepancy does not affect the relative inter-study comparability of the samples, regardless of the image analysis strategy or experimental parameters. Additionally, high measurement precision was demonstrated, as TCloud,app changes were detectable down to a sample volume of only 5 μL and for 0.1 °C/min cooling rate increments. This work explains the apparent nature of the TCloud detection method, showcases its detection precision, and broadens the applicability of the experimental setup.

High-Throughput Method for Detection of Arbovirus Infection of Saliva in Mosquitoes Aedes aegypti and Ae. albopictus.

Vector competence refers to the ability of a vector to acquire, maintain, and transmit a pathogen. Collecting mosquito saliva in medium-filled capillary tubes has become the standard for approximating arbovirus transmission. However, this method is time-consuming and labor-intensive. Here we compare the capillary tube method to an alternative high-throughput detection method the collection of saliva on paper cards saturated with honey, with (FTA card) and without (filter paper) reagents for the preservation of nucleic acid for Aedes aegypti and Aedes albopictus mosquitoes infected with two emerging genotypes of the chikungunya virus (CHIKV). Model results showed that the Asian genotype CHIKV dissemination in the harvested legs of both Ae. aegypti and Ae. albopictus increased the odds of females having a positive salivary infection and higher salivary viral titers, while for the IOL genotype the same effect was observed only for Ae. aegypti. Of the three tested detection methods, the FTA card was significantly more effective at detecting infected saliva of Ae. aegypti and Ae. albopictus females than the capillary tube and filter paper was as effective as the capillary tube for the Asian genotype. We did not find significant effects of the detection method in detecting higher viral titer for both Asian and IOL genotypes. Our results are discussed in light of the limitations of the different tested detection methods.

Efficient Biosynthesis of (2S)-Eriodictyol from (2S)-Naringenin in Saccharomyces cerevisiae through a Combination of Promoter Adjustment and Directed Evolution.

The compound (2S)-eriodictyol is an important flavonoid that can be derived from (2S)-naringenin through flavonoid 3'-hydroxylase (F3'H) catalyzation. F3'H is a cytochrome P450 enzyme that requires a cytochrome P450 reductase (CPR) to function. However, P450s have limited applications in industrial scale biosynthesis, owing to their low activity. Here, an efficient SmF3'H and a matched SmCPR were identified from Silybum marianum. To improve the efficiency of SmF3'H, we established a high-throughput detection method for (2S)-eriodictyol, in which the promoter combination of SmF3'H and SmCPR were optimized in Saccharomyces cerevisiae. The results revealed that SmF3'H/SmCPR should be expressed by using promoters with similar and strong expression levels. Furthermore, directed evolution was applied to further improve the efficiency of SmF3'H/SmCPR. With the optimized promoter and mutated combinations SmF3'HD285N/SmCPRI453V, the (2S)-eriodictyol titer was improved to 3.3 g/L, the highest titer in currently available reports. These results indicated that S.cerevisiae is an ideal platform for functional expression of flavonoid related P450 enzymes.

High throughput detection and characterization of red blood cells deformability by combining optical tweezers with microfluidic technique

A high throughput measurement method of human red blood cells (RBCs) deformability combined with optical tweezers technology and the microfluidic chip was proposed to accurately characterize the deformability of RBCs statistically. Firstly, the effective stretching deformation of RBCs was realized by the interaction of photo-trapping force and fluid viscous resistance. Secondly, the characteristic parameters before and after the deformation of the single cell were extracted through the image processing method to obtain the deformation index of area and circumference. Finally, statistical analysis was performed, and the average deformation index parameters (, ) were used to characterize the deformability of RBCs. A high-throughput detection system was built, and the optimal experimental conditions were obtained through a large number of experiments. Three groups of samples with different deformability were used for statistical verification. The results showed that the smallest cell component was 9.71%, and the detection flux of 8-channel structure was about 370 cells/min. High-throughput detection and characterization methods can effectively distinguish different deformed RBCs statistically, which provides a solution for high-throughput deformation analysis of other types of samples.

Image-Based High-Throughput Detection and Phenotype Evaluation Method for Multiple Lettuce Varieties.

The yield and quality of fresh lettuce can be determined from the growth rate and color of individual plants. Manual assessment and phenotyping for hundreds of varieties of lettuce is very time consuming and labor intensive. In this study, we utilized a “Sensor-to-Plant” greenhouse phenotyping platform to periodically capture top-view images of lettuce, and datasets of over 2000 plants from 500 lettuce varieties were thus captured at eight time points during vegetative growth. Here, we present a novel object detection–semantic segmentation–phenotyping method based on convolutional neural networks (CNNs) to conduct non-invasive and high-throughput phenotyping of the growth and development status of multiple lettuce varieties. Multistage CNN models for object detection and semantic segmentation were integrated to bridge the gap between image capture and plant phenotyping. An object detection model was used to detect and identify each pot from the sequence of images with 99.82% accuracy, semantic segmentation model was utilized to segment and identify each lettuce plant with a 97.65% F1 score, and a phenotyping pipeline was utilized to extract a total of 15 static traits (related to geometry and color) of each lettuce plant. Furthermore, the dynamic traits (growth and accumulation rates) were calculated based on the changing curves of static traits at eight growth points. The correlation and descriptive ability of these static and dynamic traits were carefully evaluated for the interpretability of traits related to digital biomass and quality of lettuce, and the observed accumulation rates of static straits more accurately reflected the growth status of lettuce plants. Finally, we validated the application of image-based high-throughput phenotyping through geometric measurement and color grading for a wide range of lettuce varieties. The proposed method can be extended to crops such as maize, wheat, and soybean as a non-invasive means of phenotype evaluation and identification.

Advances in biological functions of RNA chemical modification m<sup>6</sup>A

N 6-methyladenine (m6A) is the most abundant internal chemical modification in eukaryotic messenger RNAs (mRNAs). The discovery of m6A dynamic reversible regulatory mechanism has greatly promoted the development of epitranscriptomics. Our understanding of the m6A distribution and regulation is deepened by a variety of m6A high-throughput sequencing technologies or detection methods. In mammals and plants, m6A can be deposited, removed and interpreted by an arsenal of methyltransferases, demethylases and binding proteins. m6A can regulate various biological activities by affecting the function of RNA. In this review, we summarize the research progress of m6A detection methods, m6A function in mammals and plants in the past decade and provide an outlook on the m6A related fields.

On-Site and Quantitative Detection of Trace Methamphetamine in Urine/Serum Samples with a Surface-Enhanced Raman Scattering-Active Microcavity and Rapid Pretreatment Device.

Here, it reports a high-throughput detection method for reliably quantitative analysis of illegal drugs in complex biological samples by means of a surface-enhanced Raman scattering (SERS) active microcavity and rapid pretreatment device. Based on the well-made hemispherical microcavities that regularly distributed on a glass array, the quality-controllable microcavity device is fabricated by the compact self-assembly of core-shell nanopeanuts (CSNPs) onto the inside surface. Both the CSNPs with a quantifiable internal standard signal of crystal violet acetate anchored inside their gap and the well-made microcavity referred to the physical amplification of the microscale groove surface will do well in trace analysis, which will allow us to realize the accurately quantitative SERS analysis of targeted analytes spread on the bottom area of the microcavity array. As an example, 0.8 nM malachite green and 160 ppb methamphetamine (MATM) have been successively detected in a wide range as standard, while even 0.01 ppm MATM mixed in the urine/serum samples has been efficiently tested by the microcavity device equipped with a rapid pretreatment device (manual monolithic column syringe needle). All of the above suggest that the SERS-active microcavity equipped with a rapid pretreatment device has potential in the on-site quick test of trace amounts of illegal drugs in bodily fluid samples or other field analysis of food sanitation, environmental safety, and public health.

The Colorimetric Isothermal Multiple-Self-Matching-Initiated Amplification Using Cresol Red for Rapid and Sensitive Detection of Porcine Circovirus 3.

In 2016, a novel porcine circovirus (PCV), PCV3, was identified in USA. Subsequently, it was proved to be also epidemic in China, Poland, and Korea. To analyze and control the epidemic situation of PCV3, it is necessary to establish accurate and high-throughput detection methods. In this study, the colorimetric isothermal multiple-self-matching-initiated amplification (IMSA) using cresol red was developed to detect PCV3 for the first time. The reaction can be easily performed by incubating the tube at 63°C for 60 min. By the addition of pH-sensitive indicator dye cresol red, the initial color of the reaction mixture is red. When PCV3 capsid gene DNA was positive in the sample, the color of the reaction mixture changed from red to yellow after the isothermal incubation at 63°C, while the negative control maintained the red color. The colorimetric IMSA displayed good specificity in detecting PCV3, PCV2, and PCV1 and 4 porcine DNA pathogens. Moreover, it has a low and repeatable detection limit of 10 copies, which is consistent with TaqMan-based qPCR, but 10 times more sensitive than PCR. In diagnosing 128 clinical specimens, it not only showed 100% agreement with qPCR but also detected 15 positive results more than PCR. The colorimetric IMSA we offered might be a good choice for PCV3 epidemiological investigation and point-of-care testing.

A high-throughput detection method for the clonality of Human T-cell leukemia virus type-1-infected cells in vivo.

Approximately 10-20million of Human T-cell leukemia virus type-1 (HTLV-1)-infected carriers have been previously reported, and approximately 5% of these carriers develop adult T-cell leukemia/lymphoma (ATL) with a characteristic poor prognosis. In Japan, Southern blotting has long been routinely performed for detection of clonally expanded ATL cells in vivo, and as a confirmatory diagnostic test for ATL. However, alternative methods to Southern blotting, such as sensitive, quantitative, and rapid analytical methods, are currently required in clinical practice. In this study, we developed a high-throughput method called rapid amplification of integration site (RAIS) that could amplify HTLV-1-integrated fragments within 4h and detect the integration sites in > 0.16% of infected cells. Furthermore, we established a novel quantification method for HTLV-1 clonality using Sanger sequencing with RAIS products, and the validity of the quantification method was confirmed by comparing it with next-generation sequencing in terms of the clonality. Thus, we believe that RAIS has a high potential for use as an alternative routine molecular confirmatory test for the clonality analysis of HTLV-1-infected cells.

Rapid and efficient detection methods of pathogenic swine enteric coronaviruses.

Porcine enteric coronaviruses (CoVs) cause highly contagious enteric diarrhea in suckling piglets. These COV infections are characterized by clinical signs of vomiting, watery diarrhea, dehydration, and high morbidity and mortality, resulting in significant economic losses and tremendous threats to the pig farming industry worldwide. Because the clinical manifestations of pigs infected by different CoVs are similar, it is difficult to differentiate between the specific pathogens. Effective high-throughput detection methods are powerful tools used in the prevention and control of diseases. The immune system of piglets is not well developed, so serological methods to detect antibodies against these viruses are not suitable for rapid and early detection. This paper reviews various PCR-based methods used for the rapid and efficient detection of these pathogenic CoVs in swine intestines.Key points Swine enteric coronaviruses (CoVs) emerged and reemerged in past years.Enteric CoVs infect pigs at all ages with high mortality rate in suckling pigs.Rapid and efficient detection methods are needed and critical for diagnosis.

High-throughput method for detection and quantification of lesions on leaf scale based on trypan blue staining and digital image analysis

BackgroundField-grown leafy vegetables can be damaged by biotic and abiotic factors, or mechanically damaged by farming practices. Available methods to evaluate leaf tissue damage mainly rely on colour differentiation between healthy and damaged tissues. Alternatively, sophisticated equipment such as microscopy and hyperspectral cameras can be employed. Depending on the causal factor, colour change in the wounded area is not always induced and, by the time symptoms become visible, a plant can already be severely affected. To accurately detect and quantify damage on leaf scale, including microlesions, reliable differentiation between healthy and damaged tissue is essential. We stained whole leaves with trypan blue dye, which traverses compromised cell membranes but is not absorbed in viable cells, followed by automated quantification of damage on leaf scale.ResultsWe present a robust, fast and sensitive method for leaf-scale visualisation, accurate automated extraction and measurement of damaged area on leaves of leafy vegetables. The image analysis pipeline we developed automatically identifies leaf area and individual stained (lesion) areas down to cell level. As proof of principle, we tested the methodology for damage detection and quantification on two field-grown leafy vegetable species, spinach and Swiss chard.ConclusionsOur novel lesion quantification method can be used for detection of large (macro) or single-cell (micro) lesions on leaf scale, enabling quantification of lesions at any stage and without requiring symptoms to be in the visible spectrum. Quantifying the wounded area on leaf scale is necessary for generating prediction models for economic losses and produce shelf-life. In addition, risk assessments are based on accurate prediction of the relationship between leaf damage and infection rates by opportunistic pathogens and our method helps determine the severity of leaf damage at fine resolution.

Progress of epigenetics of lymphoma

Followed by increasing accumulation in knowledge of tumor pathogenesis, it is now realized that in addition to chromosome number abnormality, gene translocation and mutation, the important role of epigenetics has become increasingly prominent. Based on the emergence of high-throughput detection methods such as next-generation sequencing technology, the epigenetic (DNA, histone, microRNA, etc.) modification abnormalities in lymphoma can be more comprehensively detected and studied. Those findings show that epigenetic modification has widely affected the pathogenesis, recurrence, progress and drug resistance of lymphoma, which also provide new sights and targets for lymphoma treatment. Based on the relevant abstracts reported on the 61st American Society of Hematology (ASH) Annual Meeting, this article reviews the new progress in epigenetics of lymphoma. Key words: Lymphoma; Epigenetics; High-throughput sequencing; Targeted therapy

A rapid and inexpensive RNA-extraction method for high-throughput virus detection in grapevine

The extraction of RNA from grapevine tissue is a crucial step for virus diagnostics via multiplex reverse transcription-polymerase chain reaction (mRT-PCR). Conventional methods are either time-consuming or expensive when convenient extraction kits are used. Here we present an easy, but reliable extraction method that fulfills the requirements of epidemiological research (high sample throughput with maximum accuracy). A further advantage of the protocol beside the low costs is the absence of harmful chemicals like phenol or chloroform and the possibility to manage 'high-throughput' extractions and analyses.

A novel quantitative technique in detecting stacked genetically modified plants by fluorescent-immunohistochemistry

Stacked genetically modified organisms (GMOs) are gaining popularity for their ability to enhance production efficiency and improve functional properties. Due to different labeling requirements across many countries, the detection and quantification of stacked GMO content is an important concern. Although existing methods can detect pure stacked GMOs, they are considerably less efficient at identifying material that contains the stacked GMO and its single-trait “parent” GM lines. Immunohistochemistry possesses superior specificity and sensitivity in detecting the target, especially proteins. As a result, a novel quantitative technique to detect stacked GMO was developed. Two fluorescent antibodies hybridized with two specific proteins, which were expressed by the single-trait “parents” separately, were employed. By observing whether both of the two fluorescent signals existed in the same cell, the stacked GMO could be easily detected. By calculating the fluorescent signals, quantification could be determined. This method reduces errors and the non-specificity caused by PCR-based methods, and is widely applicable in the quantitative and qualitative detection of stacked GMOs. In sum, it represents a new method for high throughput detection.

A high-throughput chemotaxis detection method for CCR4+ T cell migration inhibition using image cytometry

Chemotaxis is an important aspect of immune cell behavior within the tumor microenvironment (TME). One prominent example of chemotaxis within the TME is the migration of regulatory T cells (Tregs) in response to the chemokine ligands CCL17 and CCL22. Tregs within the TME cause the suppression of anti-tumor immunity and inhibition of the effect of immunotherapeutic treatments. Therefore, the ability to screen for therapeutic antibodies that can inhibit or stimulate the chemotaxis of various immune cell types is crucial. Traditionally, chemotaxis is studied by determining the number of cells in the bottom reservoir of a Transwell microplate using flow cytometry; however, this method is time-consuming and thus not appropriate for high-throughput screening purposes. The Celigo Image Cytometer has been employed to perform high-throughput cell-based assays and was used to develop a new detection method for chemotaxis measurement. The image-based detection method was developed using chemokine ligands CCL17 and CCL22 to induce the migration of CCR4+ T cells and directly count them on the bottom of the Transwell plates. Finally, the method was applied to measure the inhibitory effects of commercially available anti-CCL17 and anti-CCL22 antibodies, which caused a dose-dependent decrease in the number of migrated T cells. The proposed image cytometry method allowed screening of multiple antibodies at various concentrations, simultaneously, which can improve the efficiency for discovering potential antibody candidates that can induce or inhibit recruitment of immune cells to the tumor microenvironment.

Comparative study of ultra-high-performance supercritical fluid chromatography and ultra-high-performance liquid chromatography to simultaneous determination of ten components in Radix hedysari

Background: In China, dried root of Hedysarum polybotrys Hand-Mazz, known as Hong Qi (Radix hedysari [RH]), is one of the important traditional Chinese medicines (TCMs). The long analysis time was a major limitation when high-throughput techniques are required for research or quality control purposes. Materials and Methods: It is necessary to develop a high?throughput method for the determination of multiple components of TCMs by investigating the separation characteristics of the target with ultra-high-performance liquid chromatography (UHPLC) and ultra-high-performance supercritical fluid chromatography (UHPSFC). Objective: This study intends to establish a high-throughput method for simultaneous determination of ten compounds in RH by UHPSFC and to develop a standardized method to comprehensively evaluate the quality of RH samples. In addition, this study was based on UHPLC and UHPSFC systems to understand and compare the effects of different separation parameters on ten target compounds in RH. A high-throughput and reliable solid-phase extraction method for simultaneous detection of ten target compounds in RH was established and validated. Results: The optimal analysis method was achieved using HSS C18SB column, gradient elution, flow rate of 1.5 mL/min, diode array detection at 270 nm, and back pressure at 12.41 Mpa. The separation method was validated sufficiently by examining the precision, recoveries, linearity, range, limit of detection, and limit of quantification and was successfully applied to quantify the 25 RH samples. In addition, the comparative study also demonstrated the complementary nature of the two separation modes. Conclusion: This is the first study that ten compounds in RH were separated and analyzed simultaneously with UHPSFC-diode array detector. In addition, under the separation conditions of UHPSFC and UHPLC, the comparison of chromatographic parameters shows that a combination of these two separation techniques efficiently separates the ten target compounds in RH. The results obtained in this study are useful for future TCM quality control and high-throughput analysis.

Apparent protein cloud point temperature determination using a low volume high-throughput cryogenic device in combination with automated imaging.

Short-term parameters correlating to long-term protein stability, such as the protein cloud point temperature (Tcloud), are of interest to improve efficiency during protein product development. Such efficiency is reached if short-term parameters are obtained in a low volume and high-throughput (HT) manner. This study presents a low volume HT detection method for (sub-zero) Tcloud determination of lysozyme, as such an experimental method is not available yet. The setup consists of a cryogenic device with an automated imaging system. Measurement reproducibility (median absolute deviation of 0.2°C) and literature-based parameter validation (Pearson correlation coefficient of 0.996) were shown by a robustness and validation study. The subsequent case study demonstrated a partial correlation between the obtained apparent Tcloud parameter and long-term protein stability as a function of lysozyme concentration, ion type, ionic strength, and freeze/thaw stress. The presented experimental setup demonstrates its ability to advance short-term strategies for efficient protein formulation development.