Name: construction of models for nondestructive prediction of ingredient contents in blueberries by near-infrared spectroscopy based on hplc measurements
Uploaded: 2016-06-28T14:00:00
Description: Watch this Scientific Journal Video about Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements at JoVE.co

This work was partially supported by the project "A Scheme to Revitalize Agriculture and Fisheries in Disaster Area through Deploying Highly Advanced Technology" of Ministry of Agriculture, Forestry and Fisheries, Japan.

1. Collection of Samples
<ol>
	<li>Decide which cultivars will be included in the target of the calibration model.</li>
	<li>Collect sufficient number and various types of sample blueberries of the target cultivars.
	<ol>
		<li>Collect preferably 100 blueberries for the construction of the calibration model, and at least 10 for the validation of the constructed model. In order to construct robust models, collect samples of various types, i.e. with various colors, sizes, and at various ripening conditions.</li>...

<ol>
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Some additional comments on the protocol are described here. Firstly, in step 1.1, it is mentioned to decide the cultivars included in the target. Although it is possible to construct models covering blueberries from many cultivars or without specifying cultivars, the prediction accuracies with the models are sometimes much lower than those with the models for a single cultivar and for limited cultivars. It should also be noted that the calibration models should be constructed for blueberries from each production site to...

Near-infrared (NIR) spectroscopy is widely applied as a nondestructive technique to analyze contents of fruits and vegetables of various kinds.1,2 Nondestructive analyses by NIR spectroscopy enable the shipping of only delicious fruits and vegetables with guaranteed qualities. NIR spectroscopy has already been applied to orange, apple, melon, cherry, kiwi fruit, mango, papaya, peach and so on to know their Brix that corresponds to the total sugar content, acidity, TSC (total solids contents), and so on. Recently, we have reported the application of NIR spectroscopy to the quality evaluation of blueberries.3 We measured not only the total sugar content and the total organic acid content corresponding to acidity, but also the total anthocyanin content. Anthocyanin is a bioactive component which is believed to improve human health. It is convenient for consumers if they can buy delicious blueberries with an assurance of their sugar content, acidity, and anthocyanin content.
In NIR absorption spectra of fruits and vegetables, only broad absorption bands are observed. They are mainly the bands due to fiber and moisture. Although many weak bands due to various ingredients of the non-destructed target are observed simultaneously, the observed bands cannot be assigned to specific vibrational modes of specific components of the target in most cases. Therefore, the traditional technique to determine the content of a specific component using the Lambert-Beer&#39;s law is not effective for NIR spectra. Instead, calibration models to predict the contents of the target components from the observed spectra are constructed using chemometrics by examining the correlation between the observed spectra and the ingredient contents corresponding to the spectra.4,5 Here, a protocol to construct and validate the models for prediction of total sugar content, total organic acid content corresponding to acidity, and total anthocyanin content of blueberries from NIR spectra is presented.
Figure 1 shows the general flow chart to construct reliable and robust calibration models. Samples of sufficient number are collected. Some of them are used for the construction of models while the others are used for the validation of the constructed models. For each of collected samples, an NIR spectrum is measured, and then the target components are analyzed quantitatively with traditional destructive chemical analysis methods. Here, high-performance liquid chromatography (HPLC) is used for the chemical analyses of sugars, organic acids, and anthocyanins. Partial least squares (PLS) regression is used for the construction of calibration models where the correlation between the observed spectra and the ingredient contents determined by chemical analyses is examined. In order to construct robust models with the best prediction ability, the pretreatments of observed spectra and the wavelength regions used for the prediction are also examined. Finally, the constructed models are validated to confirm their sufficient prediction ability. In the validation, the contents predicted from the observed spectrum by the constructed model (predicted values) are compared with the contents determined by the chemical analyses (observed values). If the sufficient correlation cannot be found between the predicted and observed values, the calibration model should be re-constructed until the sufficient correlation is obtained. Although it is preferable to use different groups of samples for the construction and validation of a model as shown in this figure (external validation), samples in a same group are used both for the construction and the validation (cross validation) when the number of samples is not large enough.
<img alt="Figure 1" src="/files/ftp_upload/53981/53981fig1.jpg" /> 
Figure 1. Flow chart for the construction and validation of the calibration model. The procedures surrounded by blue and green lines correspond, respectively, to the construction of a calibration model and its validation. <a href="https://www.jove.com/files/ftp_upload/53981/53981fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="0" cellpadding="0" cellspacing="0" width="1315">
	<tbody>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">FT-NIR spectrophotometer</td>
			<td style="width:320px;">Bruker Optics GmbH</td>
			<td style="width:355px;">MPA&#160;</td>
			<td style="width:320px;"></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">High-Performance Liquid Chromatography</td>
			<td style="width:320px;">Shimadzu Corporation</td>
			<td>228-45041-91, 228-45000-31, 228-45018-31,</td>
			<td>For sugar analysis</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>223-04500-31, 228-45010-31, 228-45095-31</td>
			<td>Refractive Index Detector</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">High-Performance Liquid Chromatography</td>
			<td style="width:320px;">Shimadzu Corporation</td>
			<td>228-45041-91, 228-45003-31, 228-45000-31,</td>
			<td>For organic acid analysis</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>228-45018-31, 228-45010-31, 223-04500-31</td>
			<td>Ultraviolet-Visible Detector</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">High-Performance Liquid Chromatography</td>
			<td style="width:320px;">Shimadzu Corporation</td>
			<td>228-45041-91, 228-45018-31, 228-45000-31,</td>
			<td style="width:320px;">For anthocyanin analysis</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>228-45012-31, 228-45119-31, 228-45005-31,</td>
			<td style="width:320px;">Photodiode Array Detector</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>228-45009-31</td>
			<td style="width:320px;"></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">pH meter</td>
			<td style="width:320px;">Mettler-Toledo</td>
			<td>30019028</td>
			<td style="width:320px;">S220, Automatic temperature compensation</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Ultra-pure water treatment equipment</td>
			<td style="width:320px;">ORGANO Corporation</td>
			<td style="width:355px;">ORG-ULXXXM1; PRA-0015-0V0</td>
			<td style="width:320px;">PURELAB ultra; PURELITE</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Biomedical Freezers&#160;</td>
			<td style="width:320px;">SANYO</td>
			<td style="width:355px;">2-6780-01</td>
			<td style="width:320px;">MDF-U338</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Ultra-Low Temperature Freezer</td>
			<td style="width:320px;">Panasonic healthcare Co.,Ltd.</td>
			<td style="width:355px;">KM-DU73Y1</td>
			<td style="width:320px;">-80&#176;C</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Vacuum lyophilizer</td>
			<td style="width:320px;">IWAKI GLASS Co.,Ltd</td>
			<td>119770</td>
			<td style="width:320px;">DRC-3L;FRD-82M</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Homoginizer</td>
			<td style="width:320px;">Microtec Co., Ltd.&#160;</td>
			<td>Physcotron</td>
			<td style="width:320px;"></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Ultracentrifuge</td>
			<td style="width:320px;">Hitachi Koki Co.,Ltd</td>
			<td style="width:355px;">S204567</td>
			<td>CF15RXII</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Mini-centrifuge</td>
			<td style="width:320px;">LMS CO.,LTD.</td>
			<td>KN3136572</td>
			<td>MCF-2360</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Centrifuge</td>
			<td style="width:320px;">Kokusan Co.,Ltd</td>
			<td style="width:355px;">2-5534-01</td>
			<td>H-103N</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Filter Paper&#160;</td>
			<td style="width:320px;">Advantec</td>
			<td style="width:355px;">1521070</td>
			<td>5B, Eqivalent to Whatman 40</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sep-Pak C18 column</td>
			<td style="width:320px;">Waters Corporation Milford</td>
			<td style="width:355px;">WAT020515</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sep-Pak CM column</td>
			<td style="width:320px;">Waters Corporation Milford</td>
			<td style="width:355px;">WAT020550</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sep-Pak QMA column</td>
			<td style="width:320px;">Waters Corporation Milford</td>
			<td style="width:355px;">WAT020545</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Centrifugal Filter Unit</td>
			<td style="width:320px;">Merck Millipore Corporation</td>
			<td style="width:355px;">R2SA18503</td>
			<td>PVDF, 0.45 &#956;m</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Microtube</td>
			<td style="width:320px;">As One Corporation</td>
			<td style="width:355px;">1-1600-02</td>
			<td>PP, 2 mL</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Syringe Filter</td>
			<td style="width:320px;">GE Healthcare CO.,LTD.</td>
			<td style="width:355px;">6788-1304</td>
			<td>PP, 0.45 &#956;m</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sucrose</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">194-00011</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Glucose</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">049-31165</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Fructose</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">123-02762</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Citric acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">036-05522</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Malic acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">355-17971</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Succinic acid&#160;</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">190-04332</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Quinic acid</td>
			<td style="width:320px;">Alfa Aesar, A Johnson Matthey Company</td>
			<td style="width:355px;">10176328</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;">Phosphoric acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">162-20492</td>
			<td>HPLC-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Trifluoroacetic acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">208-02746</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Methanol</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">131-01826</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Acetonitrile</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">015-08633</td>
			<td>HPLC-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Grade cyanidin-3-O-glucoside chloride</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">306-37661</td>
			<td>HPLC-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Software for analyses</td>
			<td style="width:320px;">Bruker Optics GmbH</td>
			<td style="width:355px;">OPUS ver. 6.5</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Softoware for preprocessing</td>
			<td style="width:320px;">Microsoft</td>
			<td style="width:355px;">Excel powered by Visual Basic for Applications</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Software for construction of models</td>
			<td style="width:320px;"></td>
			<td style="width:355px;">Freemat 4.0</td>
			<td>http://freemat.sourceforge.net/</td>
		</tr>
	</tbody>
</table>

construction of models for nondestructive prediction of ingredient contents in blueberries by near-infrared spectroscopy based on hplc measurements

Nondestructive prediction of ingredient contents of farm products is useful to ship and sell the products with guaranteed qualities. Here, near-infrared spectroscopy is used to predict nondestructively total sugar, total organic acid, and total anthocyanin content in each blueberry. The technique is expected to enable the selection of only delicious blueberries from all harvested ones. The near-infrared absorption spectra of blueberries are measured with the diffuse reflectance mode at the positions not on the calyx. The ingredient contents of a blueberry determined by high-performance liquid chromatography are used to construct models to predict the ingredient contents from observed spectra. Partial least squares regression is used for the construction of the models. It is necessary to properly select the pretreatments for the observed spectra and the wavelength regions of the spectra used for analyses. Validations are necessary for the constructed models to confirm that the ingredient contents are predicted with practical accuracies. Here we present a protocol to construct and validate the models for nondestructive prediction of ingredient contents in blueberries by near-infrared spectroscopy.

Figure 2 shows as an example a set of NIR absorption spectra of blueberries where spectra of 70 blueberries are shown simultaneously. Since the bands definitely assignable to sugars, organic acids, or anthocyanins are not observed in the NIR spectra, traditional Lambert-Beer&#39;s law is not applicable to quantify the ingredient contents. Therefore, the construction of models for the prediction of ingredient contents is necessary.
<p class="jove_content" fo:keep-toget...

Watch this Scientific Journal Video about Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements at JoVE.co

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

We present here a protocol to construct and validate models for nondestructive prediction of total sugar, total organic acid, and total anthocyanin content in individual blueberries by near-infrared spectroscopy.

Nondestructive prediction of ingredient contents of farm products is useful to ship and sell the products with guaranteed qualities. Here, near-infrared ...

The overall goal of this procedure is to construct and validate models for nondestructive prediction of total sugar, total organic acid, and total anti-cyanine content in individual blueberries by near-infrared spectroscopy. This method will answer key problems in the field of evaluation of farm products, such as fruits and vegetables. To me, an advantage of this technique is that plenty of our products can be checked nondestructively by spectroscopy.And the models constructed through the procedure shown here. Near-infrared spectroscopy is a powerful tool for the nondestructive evaluation of farm products. Prediction models are constructed by examining the correlation between the spectrum and the contents determined by chemical analysis of each target.Demonstrating the procedure will be Yusuke Kimura, a graduated student from my laboratory and Jingai Che, from university and one of the authors of this protocol. Collect a sufficient number and various types of sample blueberries from the target cultivars. Collect preferably 100 blueberries for the construction of the calibration model.And at least 10 for the validation of the constructed model. To construct robust models, collect samples of various types, such as with various colors, sizes, and at various ripening conditions. Weigh each blueberry.The weights measured are used later for the calculation of content percent of ingredients of each blueberry. Next put a blueberry sample in the center of the window of the near-infrared spectrophotomoter for diffuse reflectance measurements. By using the sample single channel command, measure the spectra of each blueberry.Preferably at several points in the fruit. Keep the blueberries in a freezer, below minus 30 degrees celsius if they are not to be analyzed just after the spectrum measurements. To begin the pre-treatment, cut a blueberry into several pieces so it can be easily homogenized.Cutting the blueberry without defrosting when it is frozen. Put the pieces into a 50 milliliter beaker. Add approximately 10 milliliters of ultra pure water to the beaker.Heat the cut blueberry in ultra pure water in a microwave oven for 20 seconds to deactivate the enzymes that might decompose sugars during the analyses. Add approximately 10 milliliters of ultra pure water to the beaker. Homogenize the mixture for five minutes at 12, 000 RPM with a homogenizer equipped with a standard shaft and generator.Centrifuge the homogenized mixture for 10 minutes at 3, 000 RPM. Next collect the filtrate by vacuum filtration of the centrifuged sample using a five B paper filter. After repeating the homogenization steps twice, measure the pH of the filtrate and adjust it to seven with dilute hydrochloric acid and dilute aqueous solutions of sodium hydroxide.Dilute the filtrate to 50 milliliters with ultra pure water. Divide the sample into two. One for the analysis of sugars and the other for the analysis of organic acids.Pass the first sample solution through the columns connected in series to exclude pigments, cations, and anions. Throw away the first one milliliter of the sample solution from the columns. Then use the sample solution from the columns for the analysis of sugars by high performance liquid chromotography or HPLC.Centrifuge the solution at 6, 600 RPM for 10 minutes in a microtube equipped with a 0.445 micron filter with a mini-centrifuge before the analysis by HPLC. Arrange the HPLC system using a gel permeation column in the column oven at 40 degrees celsius. Use de-gassed ultra pure water with a flow rate of 0.1 milliliters per minute as the eluent.Also use a refractive index detector. Measure the HPLC spectrograms of standard solutions by injecting a 20 microliter aliquot for each measurement. Here packed solution software is used for the measurement.Get the area intensity of the band of sugar on the chromatogram of each standard solution by clicking re-analysis with the right button of the mouse. Then plug the area intensities against the corresponding concentrations to get the working curve for each sugar by linear regression. From the curve, the equation representing the relationship between the area intensity and the concentration is obtained for each sugar.After obtaining the standard curve, measure the HPLC spectrograms of sample solutions by injecting a 20 microliter aliquot for each measurement. Get the area intensities of the bands of sugars on the chromatogram of each sample solution as before. Refer to the text protocol for steps on performing HPLC measurements of organic acids.Keep the blueberries in a freezer below minus 80 degrees celsius if they are not to be analyzed for anthocyanins just after the spectrum measurements. To perform pre-treatment for HPLC measurements of anthocyanins, dry each frozen fruit with a vacuum lyophalyzer for 12 hours. Extract anthocyanin from the dried blueberry in a one percent methanol solution of trifluruocetic acid by leaving the mixture in a refrigerator at four degrees celsius for 12 hours.Centrifuge the extract for 15 minutes in a two milliliter microtube using an ultra-centrifuge at minus eight degrees celsius and 15, 000 RPM. Then filter the extract through 0.45 micron filter to get the sample for HPLC measurements. Arrange the HPLC system using a C18 reverse phase column in a column oven at 40 degrees celsius.Apply the gradient method using a 0.1 percent aqueous trifluroacetic acid as LUNA. And 0.5 percent trifluroacetic acid in acetonitrile as LUNB. Use a flow rate of 0.1 milliliters per minute where the ratio of LUNB increases from eight percent to 15%during zero to 50 minutes after the injection.And from 15%to 75%during 50 to 60 minutes after the injection. Use a photo diode array detector monitoring at 520 nanometers. Measure the HPLC spectrograms of standard solutions by injecting a 10 microliter aliquot through the auto-sampler for each measurement.Use the LC solution software for the measurement. Finally measure the HPLC spectrograms of sample solutions by injecting a 10 microliter aliquot through the auto-sampler for each measurement. At this point, the construction of calibration models for prediction of ingredient contents, followed by the validation of these constructed models, is performed as described in the text protocol.Prediction models are constructed using the observed spectra and the ingredient contents determined through the procedure shown here. An example of the result of cross validation of the model constructed for the prediction of total sugar content is shown here. The correlation between the values predicted by near-infrared spectroscopy and those determined by HPLC is satisfactory.A similar result is observed for the cross validation of the model for total anthocyanin content. Again the correlation between the predicted values and the observed ones is satisfactory. After watching this video, you should have a good understanding of how to get previous values of content of blueberries with HPLC.Different evaluation is possible only by using the models constructed properly based on the preset content measured by destructive chemical analysis. It means that previous chemical analysis of a target is mystery to construct high performance prediction models. Please refer to the text protocol for the procedure of the construction of prediction models that are not shown in this video.Once constructed properly, the models for prediction are applicable for the prediction of sugar, organic acids, and any contents of blueberries. Near-infrared spectroscopy, as shown here, is expected to be applicable for the correlation of many kinds of farm products. Don't forget that it is necessary to get preset barriers of content through chemical analysis for the construction of a good model when applying near-infrared spectroscopy to evaluation of any farm product.

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Research

JoVE Journal

Chemistry

Profiling the Triacylglyceride Contents in Bat Integumentary Lipids by Preparative Thin Layer Chromatography and MALDI-TOF Mass Spectrometry

The mammalian integument includes sebaceous glands that secrete an oily material onto the skin surface. Sebum production is part of the innate immune system that is protective against pathogenic microbes. Abnormal sebum production and chemical composition are also a clinical symptom of specific skin diseases. Sebum contains a complex mixture of lipids, including triacylglycerides, which is species-specific. The broad chemical properties exhibited by diverse lipid classes hinder the specific determination of sebum composition. Analytical techniques for lipids typically require chemical derivatizations that are labor-intensive and increase sample preparation costs. This paper describes how to extract lipids from mammalian integument, separate broad lipid classes by thin-layer chromatography, and profile the triacylglyceride contents using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. This robust method enables a direct determination of the triacylglyceride profiles among species and individuals, and it can be readily applied to any taxonomic group of mammals.

Mammalian integument contains solvent-extractable lipids that can provide chemical compositions characteristic of individual species. This paper presents a routine method for separating broad lipid classes isolated from integumentary tissues using thin layer chromatography and determining the triacylglyceride profile by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

The mammalian integument includes sebaceous glands that secrete an oily material onto the skin surface. Sebum production is part of the innate immune ...

Dissolution Dynamic Nuclear Polarization Instrumentation for Real-time Enzymatic Reaction Rate Measurements by NMR

The main limitation of NMR-based investigations is low sensitivity. This prompts for long acquisition times, thus preventing real-time NMR measurements of metabolic transformations. Hyperpolarization via dissolution DNP circumvents part of the sensitivity issues thanks to the large out-of-equilibrium nuclear magnetization stemming from the electron-to-nucleus spin polarization transfer. The high NMR signal obtained can be used to monitor chemical reactions in real time. The downside of hyperpolarized NMR resides in the limited time window available for signal acquisition, which is usually on the order of the nuclear spin longitudinal relaxation time constant, T1, or, in favorable cases, on the order of the relaxation time constant associated with the singlet-state of coupled nuclei, TLLS. Cellular uptake of endogenous molecules and metabolic rates can provide essential information on tumor development and drug response. Numerous previous hyperpolarized NMR studies have demonstrated the relevancy of pyruvate as a metabolic substrate for monitoring enzymatic activity in vivo. This work provides a detailed description of the experimental setup and methods required for the study of enzymatic reactions, in particular the pyruvate-to-lactate conversion rate in presence of lactate dehydrogenase (LDH), by hyperpolarized NMR.

The sensitivity enhancement provided by dissolution dynamic nuclear polarization (DNP) enables following metabolic processes in real time by NMR and MRI. The characteristics and performances of a dedicated dissolution DNP setup designed for study enzymatic reactions are discussed.

The main limitation of NMR-based investigations is low sensitivity. This prompts for long acquisition times, thus preventing real-time NMR measurements of ...

HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells

This method describes a sensitive, specific, reliable and reproducible reverse phase high-performance liquid chromatography (RP-HPLC) assay developed and validated for the quantification of extracellular purine nucleotides and nucleosides produced by purified chronic lymphocytic leukemia (CLL) cells under different culture conditions. The chromatographic separation of adenosine 5&#39;-monophosphate (AMP), adenosine (ADO) and inosine (INO) is performed at RT on a silica-based, reversed-phase column that is used for polar compound retention. The method includes a binary mobile phase, which consists of 7 mM ammonium acetate and acetonitrile with a flow rate of 1.00 ml/min. The eluates are monitored using a Photodiode Array UV detector set at 260 nm. A standard calibration curve is generated to calculate the equation for the analytical quantification of each purine compound. System control, data acquisition and analysis are then performed. Applying this protocol, AMP, INO and ADO elute at 7, 11 and 11.9 min, respectively, and the total run time for each sample is 20 min. This protocol may be applied to different cell types and cell lines (both suspension and adherent), using culture media as matrix. The advantages are easy and fast sample preparation and the requirement of a small amount of supernatant for analysis. Furthermore, the use of a serum-free medium allows skipping the protein precipitation step with acetonitrile that impacts the final concentration of purine compounds. One of the limitations of the method is the requirement of the equilibration column run before each single sample run, making the total run time of the experiment longer and preventing high throughput screening applications.

The protocol described here represents an easy and reproducible method that employs reverse phase high-performance liquid chromatography (RP-HPLC) to measure purine metabolism on chronic lymphocytic leukemia (CLL) cells cultured under different conditions.

This method describes a sensitive, specific, reliable and reproducible reverse phase high-performance liquid chromatography (RP-HPLC) assay developed and ...

Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

The precise details of the interaction of intense X-ray pulses with matter are a topic of intense interest to researchers attempting to interpret the results of femtosecond X-ray free electron laser (XFEL) experiments. An increasing number of experimental observations have shown that although nuclear motion can be negligible, given a short enough incident pulse duration, electronic motion cannot be ignored. The current and widely accepted models assume that although electrons undergo dynamics driven by interaction with the pulse, their motion could largely be considered &#39;random&#39;. This would then allow the supposedly incoherent contribution from the electronic motion to be treated as a continuous background signal and thus ignored. The original aim of our experiment was to precisely measure the change in intensity of individual Bragg peaks, due to X-ray induced electronic damage in a model system, crystalline C60. Contrary to this expectation, we observed that at the highest X-ray intensities, the electron dynamics in C60 were in fact highly correlated, and over sufficiently long distances that the positions of the Bragg reflections are significantly altered. This paper describes in detail the methods and protocols used for these experiments, which were conducted both at the Linac Coherent Light Source (LCLS) and the Australian Synchrotron (AS) as well as the crystallographic approaches used to analyse the data.

We describe an experiment designed to probe the electronic damage induced in nanocrystals of Buckminsterfullerene (C60) by intense, femtosecond pulses of X-rays. The experiment found that, surprisingly, rather than being stochastic, the X-ray induced electron dynamics in C60 are highly correlated, extending over hundreds of unit cells within the crystals1.

The precise details of the interaction of intense X-ray pulses with matter are a topic of intense interest to researchers attempting to interpret the ...

Detection and Quantification of Plasmodium falciparum in Aqueous Red Blood Cells by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis

We demonstrate a method of quantification and detection of parasites in aqueous red blood cells (RBCs) by using a simple benchtop Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectrometer in conjunction with Multivariate Data Analysis (MVDA). 3D7 P. falciparum were cultured to 10% parasitemia ring stage parasites and used to spike fresh donor isolated RBCs to create a dilution series between 0&#8211;1%. 10 &#181;L of each sample were placed onto the center of the ATR diamond window to acquire the spectrum. The sample data was treated to improve the signal to noise ratio and to remove the contribution of water, and then the second derivative was applied to resolve spectral features. The data were then analyzed using two types of MVDA: first Principal Component Analysis (PCA) to determine any outliers and then Partial Least Squares Regression (PLS-R) to build the quantification model.

Detection and Quantification of Plasmodium falciparum in Aqueous Red Blood Cells by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis

Here, we present a protocol for the detection and quantification of Plasmodium falciparum in infected aqueous red blood cells using an attenuated total reflection infrared spectrometer and multivariate data analysis.

We demonstrate a method of quantification and detection of parasites in aqueous red blood cells (RBCs) by using a simple benchtop Attenuated Total ...

Pretargeted Radioimmunotherapy Based on the Inverse Electron Demand Diels-Alder Reaction

While radioimmunotherapy (RIT) is a promising approach for the treatment of cancer, the long pharmacokinetic half-life of radiolabeled antibodies can result in high radiation doses to healthy tissues. Perhaps not surprisingly, several different strategies have been developed to circumvent this troubling limitation. One of the most promising of these approaches is pretargeted radioimmunotherapy (PRIT). PRIT is predicated on decoupling the radionuclide from the immunoglobulin, injecting them separately, and then allowing them to combine in vivo at the target tissue. This approach harnesses the exceptional tumor-targeting properties of antibodies while skirting their pharmacokinetic drawbacks, thereby lowering radiation doses to non-target tissues and facilitating the use of radionuclides with half-lives that are considered too short for use in traditional radioimmunoconjugates. Over the last five years, our laboratory and others have developed an approach to in vivo pretargeting based on the inverse electron-demand Diels-Alder (IEDDA) reaction between trans-cyclooctene (TCO) and tetrazine (Tz). This strategy has been successfully applied to pretargeted positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging with a variety of antibody-antigen systems. In a pair of recent publications, we have demonstrated the efficacy of IEDDA-based PRIT in murine models of pancreatic ductal adenocarcinoma and colorectal carcinoma. In this protocol, we describe protocols for PRIT using a 177Lu-DOTA-labeled tetrazine radioligand ([177Lu]Lu-DOTA-PEG7-Tz) and a TCO-modified variant of the colorectal cancer targeting huA33 antibody (huA33-TCO). More specifically, we will describe the construction of huA33-TCO, the synthesis and radiolabeling of [177Lu]Lu-DOTA-PEG7-Tz, and the performance of in vivo biodistribution and longitudinal therapy studies in murine models of colorectal carcinoma.

This protocol describes the synthesis and characterization of a trans-cyclooctene (TCO)-modified antibody and a 177Lu-labeled tetrazine (Tz) radioligand for pretargeted radioimmunotherapy (PRIT). In addition, it details the use of these two constructs for in vivo biodistribution and longitudinal therapy studies in a murine model of colorectal cancer.

While radioimmunotherapy (RIT) is a promising approach for the treatment of cancer, the long pharmacokinetic half-life of radiolabeled antibodies can ...

Performing Spectroscopy on Plasmonic Nanoparticles with Transmission-Based Nomarski-Type Differential Interference Contrast Microscopy

Differential interference contrast (DIC) microscopy is a powerful imaging tool that is most commonly employed for imaging microscale objects using visible-range light. The purpose of this protocol is to detail a proven method for preparing plasmonic nanoparticle samples and performing single particle spectroscopy on them with DIC microscopy. Several important steps must be followed carefully in order to perform repeatable spectroscopy experiments. First, landmarks can be etched into the sample substrate, which aids in locating the sample surface and in tracking the region of interest during experiments. Next, the substrate must be properly cleaned of debris and contaminants that can otherwise hinder or obscure examination of the sample. Once a sample is properly prepared, the optical path of the microscope must be aligned, using Kohler Illumination. With a standard Nomarski style DIC microscope, rotation of the sample may be necessary, particularly when the plasmonic nanoparticles exhibit orientation-dependent optical properties. Because DIC microscopy has two inherent orthogonal polarization fields, the wavelength-dependent DIC contrast pattern reveals the orientation of rod-shaped plasmonic nanoparticles. Finally, data acquisition and data analyses must be carefully performed. It is common to represent DIC-based spectroscopy data as a contrast value, but it is also possible to present it as intensity data. In this demonstration of DIC for single particle spectroscopy, the focus is on spherical and rod-shaped gold nanoparticles.

The goal of this protocol is to detail a proven approach for the preparation of plasmonic nanoparticle samples and for performing single particle spectroscopy on them with differential interference contrast (DIC) microscopy.

Differential interference contrast (DIC) microscopy is a powerful imaging tool that is most commonly employed for imaging microscale objects using ...

Covalent Attachment of Single Molecules for AFM-based Force Spectroscopy

Atomic force microscopy (AFM)-based single molecule force spectroscopy is an ideal tool for investigating the interactions between a single polymer and surfaces. For a true single molecule experiment, covalent attachment of the probe molecule is essential because only then can hundreds of force-extension traces with one and the same single molecule be obtained. Many traces are in turn necessary to prove that a single molecule alone is probed. Additionally, passivation is crucial for preventing unwanted interactions between the single probe molecule and the AFM cantilever tip as well as between the AFM cantilever tip and the underlying surface. The functionalization protocol presented here is reliable and can easily be applied to a variety of polymers. Characteristic single molecule events (i.e., stretches and plateaus) are detected in the force-extension traces. From these events, physical parameters such as stretching force, desorption force and desorption length can be obtained. This is particularly important for the precise investigation of stimuli-responsive systems at the single molecule level. As exemplary systems poly(ethylene glycol) (PEG), poly(N-isopropylacrylamide) (PNiPAM) and polystyrene (PS) are stretched and desorbed from SiOx (for PEG and PNiPAM) and from hydrophobic self-assembled monolayer surfaces (for PS) in aqueous environment.

Covalent attachment of probe molecules to atomic force microscopy (AFM) cantilever tips is an essential technique for the investigation of their physical properties. This allows us to determine the stretching force, desorption force and length of polymers via AFM-based single molecule force spectroscopy with high reproducibility.

Atomic force microscopy (AFM)-based single molecule force spectroscopy is an ideal tool for investigating the interactions between a single polymer and ...

Crystallization of Proteins on Chip by Microdialysis for In Situ X-ray Diffraction Studies

This protocol describes the manufacturing of reproducible and inexpensive microfluidic devices covering the whole pipeline for crystallizing proteins on-chip with the dialysis method and allowing in situ single-crystal or serial crystallography experiments at room temperature. The protocol details the fabrication process of the microchips, the manipulation of the on-chip crystallization experiments and the treatment of the in situ collected X-ray diffraction data for the structural elucidation of the protein sample. The main feature of this microfabrication procedure lies on the integration of a commercially available, semipermeable regenerated cellulose dialysis membrane in between two layers of the chip. The molecular weight cut-off of the embedded membrane varies depending on the molecular weight of the macromolecule and the precipitants. The device exploits the advantages of microfluidic technology, such as the use of minute volumes of samples (&#60;1 &#181;L) and fine tuning over transport phenomena. The chip coupled them with the dialysis method, providing precise and reversible control over the crystallization process and can be used for investigating phase diagrams of proteins at the microliter scale. The device is patterned using a photocurable thiolene-based resin with soft imprint lithography on an optically transparent polymeric substrate. Moreover, the background scattering of the materials composing the microchips and generating background noise was evaluated rendering the chip compatible for in situ X-ray diffraction experiments. Once protein crystals are grown on-chip up to an adequate size and population uniformity, the microchips can be directly mounted in front of the X-ray beam with the aid of a 3D printed holder. This approach addresses the challenges rising from the use of cryoprotectants and manual harvesting in conventional protein crystallography experiments through an easy and inexpensive manner. Complete X-ray diffraction data sets from multiple, isomorphous lysozyme crystals grown on-chip were collected at room temperature for structure determination.

Crystallization of Proteins on Chip by Microdialysis for In Situ X-ray Diffraction Studies

This paper details the fabrication protocol of microfluidic chips developed for on-chip protein crystallization with the dialysis method and in situ X-ray diffraction experiments. The microfabrication process makes it possible to integrate a semipermeable regenerated cellulose dialysis membrane with any molecular weight cut-off, between two layers of the chip.

This protocol describes the manufacturing of reproducible and inexpensive microfluidic devices covering the whole pipeline for crystallizing proteins ...

Construction of Cyclic Cell-Penetrating Peptides for Enhanced Penetration of Biological Barriers

Cancer has been a grand challenge in global health. However, the complex tumor microenvironment generally limits the access of therapeutics to deeper tumor cells, leading to tumor recurrence. To conquer the limited penetration of biological barriers, cell-penetrating peptides (CPPs) have been discovered with excellent membrane translocation ability and have emerged as useful molecular transporters for delivering various cargoes into cells. However, conventional linear CPPs generally show compromised proteolytic stability, which limits their permeability across biological barriers. Thus, the development of novel molecular transporters that can penetrate biological barriers and exhibit enhanced proteolytic stability is highly desired to promote drug delivery efficiency in biomedical applications. We have previously synthesized a panel of short cyclic CPPs with aromatic crosslinks, which exhibited superior permeability in cancer cells and tissues compared to their linear counterparts. Here, a concise protocol is described for the synthesis of the fluorescently labeled cyclic polyarginine R8 peptide and its linear counterpart, as well as key steps for investigating their cell permeability.

This protocol describes the synthesis of cyclic cell-penetrating peptides with aromatic cross-links and the evaluation of their permeability across biological barriers.

Cancer has been a grand challenge in global health. However, the complex tumor microenvironment generally limits the access of therapeutics to deeper ...