TITLE: No Title
AUTHORS: 

[DESCRIPTION]
<p>For routine protein assays, we recommend that researchers generate their own CB-X™ Tables or standard curves. This is a one time commitment to ensure user specific results and allows single tube assays to be performed each time as opposed to generating new calibration plots for each assay. We recommend using a protein standard similar to you protein of interest or a purified source of your protein.</p>
<p> </p>
<p>The supplied CB-X™ tables may result in some inconsistencies due to the type of cuvettes or microtiter plates used. CB-X™ Table for Spectrophotometer readings were measured with 1cm path length cuvettes against deionized water and CB-X™ Table for Microplate Reader readings were measured using Nunc™ Immuno 96 MicroWell™ Plates (MaxiSorp™ ) [Cat# 442404] against deionized water.</p>

[GUIDELINES]
<p><strong>INTRODUCTION </strong></p>
<p>Protein assays are routinely used in many research fields to estimate proteins in a vast array of buffers and conditions. A major problem for researchers is to select a protein assay from the vast selection on the market that is compatible with their protein sample. CB-X™ Protein Assay eliminates this problem as it is designed to be compatible with all commonly used buffers and conditions in protein isolation, storage and assays.</p>
<p> </p>
<p>For protein samples in simple, uncomplicated aqueous buffers CB-X™ is a highly sensitive, single reagent assay that can be performed in 5 minutes. CB-X™ Protein Assay uses a protein dye that is an improvement on the Bradford Coomassie dye reagent.</p>
<p> </p>
<p>For complicated protein samples CB-X™ Protein Assay is supplied with reagents to clean up the samples and remove all reagents and chemicals that interfere with accurate protein estimation. These reagents include detergents, chaotropes, reducing agents, alkylating agents, sugars, high salt concentrations, buffering agents and chelating agents (Table 1). The clean up stage and subsequent protein assay is performed in a single tube to ensure no protein loss and to maintain the accuracy of the assay.</p>
<p> </p>
<table style="width: 257px;">
<tbody>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;"><strong>DETERGENTS</strong></td>
<td style="width: 10px; height: 40px;"> </td>
<td style="width: 10px; height: 40px;"><strong>REDUCING AGENTS</strong></td>
<td style="width: 10px; height: 40px;"> </td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">Brij* 35</td>
<td style="width: 10px; height: 40px;">2%</td>
<td style="width: 10px; height: 40px;"> 2-mercaptoethanol</td>
<td style="width: 10px; height: 40px;">1M</td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">CHAPS</td>
<td style="width: 10px; height: 40px;">2%</td>
<td style="width: 10px; height: 40px;">DTT </td>
<td style="width: 10px; height: 40px;">1M</td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">CHAPSO </td>
<td style="width: 10px; height: 40px;">2% </td>
<td style="width: 10px; height: 40px;"><strong>CHAOTROPES</strong></td>
<td style="width: 10px; height: 40px;"> </td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">Nonidet* P-40</td>
<td style="width: 10px; height: 40px;">2%  </td>
<td style="width: 10px; height: 40px;">Guanidine.HCl</td>
<td style="width: 10px; height: 40px;">6M </td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">SDS</td>
<td style="width: 10px; height: 40px;">2%  </td>
<td style="width: 10px; height: 40px;">Urea</td>
<td style="width: 10px; height: 40px;">6M </td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">Triton* X-100</td>
<td style="width: 10px; height: 40px;"> 2% </td>
<td style="width: 10px; height: 40px;"><strong>SALTS</strong></td>
<td style="width: 10px; height: 40px;"> </td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">Tween* 20</td>
<td style="width: 10px; height: 40px;"> 2% </td>
<td style="width: 10px; height: 40px;">Ammonium sulfate </td>
<td style="width: 10px; height: 40px;">1M</td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">Deoxycholate</td>
<td style="width: 10px; height: 40px;">0.1%</td>
<td style="width: 10px; height: 40px;"><strong>MISCELLANEOUS</strong></td>
<td style="width: 10px; height: 40px;"> </td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;"><strong>SUGARS</strong> </td>
<td style="width: 10px; height: 40px;"> </td>
<td style="width: 10px; height: 40px;"> EDTA</td>
<td style="width: 10px; height: 40px;">0.1M</td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">Glucose</td>
<td style="width: 10px; height: 40px;">1M</td>
<td style="width: 10px; height: 40px;">HEPES </td>
<td style="width: 10px; height: 40px;">0.1M</td>
</tr>
<tr style="height: 40px;">
<td style="width: 10px; height: 40px;">Sucrose</td>
<td style="width: 10px; height: 40px;">25% </td>
<td style="width: 10px; height: 40px;">MES</td>
<td style="width: 10px; height: 40px;">0.1M </td>
</tr>
</tbody>
</table>
<p>Table 1: CB-X™ Protein Assay is compatible with many interfering agents</p>
<p> </p>
<p>Figure 1 demonstrates the efficiency of the CB-X™ Protein Assay. If interfering agents are present, such as detergents, or if an artifact results are produced then the protein samples are treated with the clean up reagents and the protein is then assayed generating a linear response.</p>
<p><img 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" width="435" height="281" /></p>
<p><strong>Figure 1: CB-X™ Protein Assay.</strong> Inhibitory effects of detergents on protein assays are abolished with CB-X™ . Protein solutions containing 1% Triton® X-100 or 1% SDS were assayed using a standard Coomassie dye protein assay. The same protein samples with 1% Triton® X- 100 or 1% SDS were assayed using CB-X™ protein assay. A linear response to increasing protein concentration was visualized, indicating no interference by the detergents.</p>
<p> </p>
<p>CB-X™ Protein Assay is supplied with a lot specific CB-X™ Tables. These allow researchers to perform single protein clean ups, subsequent assays and then look up their absorbance in the CB-X™ Table to find the protein concentration. The CB-X™ Table eliminates the need for multiple protein standards and saves considerable time and effort. The CB-X™ Table is prepared with a complex protein mixture that compares well with proteins from mammalian, plant, bacteria and yeast sources. An optional set of bovine serum albumin standards or non-animal protein standards are supplied with Cat. # 786-12X or 786-894 respectively for generating curves when using CB-X™ Assay Dye alone or for researcher’s who prefer to generate their own standard curve or to generate their own CB-X™ Table for their specific conditions.</p>
<p> </p>
<p>The CB-X™ Protein Assay is reliable over the range of 0.5-50µg per assay. The regular size kit contains enough CB-X™ Assay Dye for 500 protein assays and enough clean up reagents for 250 clean ups. <em>(Patents Pending)</em></p>
<p> </p>
<p><strong>ITEM(S) SUPPLIED</strong></p>
<table>
<tbody>
<tr>
<td><strong>Description</strong></td>
<td><strong>Cat. # 786-11X</strong></td>
<td><strong>Cat. # 786-12X</strong></td>
<td><strong>Cat. # 786-894</strong></td>
<td><strong>Cat. # 786-12XT</strong></td>
</tr>
<tr>
<td>CB-X™</td>
<td>2 x 125ml</td>
<td>2 x 125ml</td>
<td>2 x 125ml</td>
<td>10ml</td>
</tr>
<tr>
<td>CB-X™ Assay Dye</td>
<td>2 x 250ml</td>
<td>2 x 250ml</td>
<td>2 x 250ml</td>
<td>10ml</td>
</tr>
<tr>
<td>CB-X™ Solubilization Buffer-I</td>
<td>15ml</td>
<td>15ml</td>
<td>15ml</td>
<td>1ml</td>
</tr>
<tr>
<td>CB-X™ Solubilization Buffer-II</td>
<td>15ml</td>
<td>15ml</td>
<td>15ml</td>
<td>1ml</td>
</tr>
<tr>
<td>CB-X™ Protein Standard [2mg/ml]</td>
<td>-</td>
<td>5ml</td>
<td> </td>
<td>-</td>
</tr>
<tr>
<td>Non-Animal Protein Standard [2mg/ml]</td>
<td>-</td>
<td>-</td>
<td>5ml</td>
<td>-</td>
</tr>
<tr>
<td>CB-X™ Table: Lot Specific</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td> 1</td>
</tr>
</tbody>
</table>
<p> </p>
<p> </p>
<p><strong>STORAGE CONDITION</strong></p>
<p>The kit is shipped at ambient temperature. Upon arrival, store CB-X™ Assay Dye and protein standard at 4°C and other kit components at room temperature. The CB-X™ reagent must be chilled to -20°C for optimal efficiency, for additional convenience the CB-X™ reagent can be stored at -20°C. When stored and used properly this kit is good for 12 months.</p>
<p> </p>
<p><strong>ITEMS NEEDED AND NOT SUPPLIED WITH THIS KIT</strong></p>
<p>• Centrifuge</p>
<p>• Assay tubes (G-Biosciences Cat # 786-008)</p>
<p>• Disposable polystyrène cuvettes (G-Biosciences Cat # 786-009)</p>
<p> </p>
<p><strong>PROTOCOL OPTIMIZATION</strong></p>
<p>For routine protein assays, we recommend that researchers generate their own CB-X™ Tables or standard curves. This is a one time commitment to ensure user specific results and allows single tube assays to be performed each time as opposed to generating new calibration plots for each assay. We recommend using a protein standard similar to you protein of interest or a purified source of your protein.</p>
<p> </p>
<p>The supplied CB-X™ tables may result in some inconsistencies due to the type of cuvettes or microtiter plates used. CB-X™ Table for Spectrophotometer readings were measured with 1cm path length cuvettes against deionized water and CB-X™ Table for Microplate Reader readings were measured using Nunc™ Immuno 96 MicroWell™ Plates (MaxiSorp™ ) [Cat# 442404] against deionized water.</p>
<p> </p>

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