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<p>Reliable and repeatable measurement is a key component to all engineering disciplines. The same holds true for synthetic biology, which has also been called engineering biology. However, the ability to repeat measurements in different labs has been | <p>Reliable and repeatable measurement is a key component to all engineering disciplines. The same holds true for synthetic biology, which has also been called engineering biology. However, the ability to repeat measurements in different labs has been | ||
− | difficult. The Measurement Committee, through the InterLab study, has been developing a robust measurement procedure for green fluorescent protein (GFP) over the last several years. GFP was chosen as the measurement marker for this study since it's one of the most used markers in synthetic biology and, as a result, most laboratories are equipped to measure this protein. | + | difficult. The Measurement Committee, through the InterLab study, has been developing a robust measurement procedure for green fluorescent protein (GFP) over the last several years. GFP was chosen as the measurement marker for this study since it's |
+ | one of the most used markers in synthetic biology and, as a result, most laboratories are equipped to measure this protein. | ||
</p> | </p> | ||
− | + | <br> | |
<p>The aim is to improve the measurement tools available to both the iGEM community and the synthetic biology community as a whole. One of the big challenges in synthetic biology measurement has been that fluorescence data usually cannot be compared because | <p>The aim is to improve the measurement tools available to both the iGEM community and the synthetic biology community as a whole. One of the big challenges in synthetic biology measurement has been that fluorescence data usually cannot be compared because | ||
− | it has been reported in different units or because different groups process data in different ways. Many have tried to work around this using “relative expression” comparisons; however, being unable to directly compare measurements makes it harder to debug engineered biological constructs, harder to effectively share constructs between labs, and harder even to just interpret your experimental controls. | + | it has been reported in different units or because different groups process data in different ways. Many have tried to work around this using “relative expression” comparisons; however, being unable to directly compare measurements makes it harder |
+ | to debug engineered biological constructs, harder to effectively share constructs between labs, and harder even to just interpret your experimental controls. | ||
</p> | </p> | ||
− | + | <br> | |
<p>The InterLab protocol aims to address these issues by providing researchers with a detailed protocol and data analysis form that yields absolute units for measurements of GFP in a plate reader.</p> | <p>The InterLab protocol aims to address these issues by providing researchers with a detailed protocol and data analysis form that yields absolute units for measurements of GFP in a plate reader.</p> | ||
− | + | <br> | |
<h2 style="color:#5bc7d8">Goal for the Fifth InterLab</h2> | <h2 style="color:#5bc7d8">Goal for the Fifth InterLab</h2> | ||
+ | <p>The goal of the iGEM InterLab Study is to identify and correct the sources of systematic variability in synthetic biology measurements, so that eventually, measurements that are taken in different labs will be no more variable than measurements taken | ||
+ | within the same lab. Until we reach this point, synthetic biology will not be able to achieve its full potential as an engineering discipline, as labs will not be able to reliably build upon others’ work. </p> | ||
+ | <p>In the previous interlab studies, it was shown that by measuring GFP expression in absolute fluorescence units calibrated against a known concentration of fluorescent molecule can greatly reduce the variability in measurements between labs. However, | ||
+ | when taking bulk measurements of a population of cells (such as with a plate reader), there is still a large source of variability in these measurements: the number of cells in the sample. | ||
+ | </p> | ||
+ | <p>Because the fluorescence value measured by a plate reader is an aggregate measurement of an entire population of cells, we need to divide the total fluorescence by the number of cells in order to determine the mean expression level of GFP per cell. | ||
+ | Usually this is done by measuring the absorbance of light at 600nm, from which the “optical density (OD)” of the sample is computed as an approximation of the number of cells. OD measurements are subject to high variability between labs, however, | ||
+ | and it is unclear how good of an approximation an OD measurement actually is. If a more direct method is used to determine the cell count in each sample, then potentially another source of variability can be removed from the measurements. | ||
+ | </p> | ||
+ | <br> | ||
+ | <p>This year, teams participating in the interlab study helped iGEM to answer the following question: <strong>Can we reduce lab-to-lab variability in fluorescence measurements by normalizing to absolute cell count or colony-forming units (CFUs) instead of OD? </strong></p> | ||
+ | |||
</div> | </div> | ||
Revision as of 21:56, 29 July 2018
iGEM 2018 InterLab Study
Introduction to the InterLab Study
Reliable and repeatable measurement is a key component to all engineering disciplines. The same holds true for synthetic biology, which has also been called engineering biology. However, the ability to repeat measurements in different labs has been difficult. The Measurement Committee, through the InterLab study, has been developing a robust measurement procedure for green fluorescent protein (GFP) over the last several years. GFP was chosen as the measurement marker for this study since it's one of the most used markers in synthetic biology and, as a result, most laboratories are equipped to measure this protein.
The aim is to improve the measurement tools available to both the iGEM community and the synthetic biology community as a whole. One of the big challenges in synthetic biology measurement has been that fluorescence data usually cannot be compared because it has been reported in different units or because different groups process data in different ways. Many have tried to work around this using “relative expression” comparisons; however, being unable to directly compare measurements makes it harder to debug engineered biological constructs, harder to effectively share constructs between labs, and harder even to just interpret your experimental controls.
The InterLab protocol aims to address these issues by providing researchers with a detailed protocol and data analysis form that yields absolute units for measurements of GFP in a plate reader.
Goal for the Fifth InterLab
The goal of the iGEM InterLab Study is to identify and correct the sources of systematic variability in synthetic biology measurements, so that eventually, measurements that are taken in different labs will be no more variable than measurements taken within the same lab. Until we reach this point, synthetic biology will not be able to achieve its full potential as an engineering discipline, as labs will not be able to reliably build upon others’ work.
In the previous interlab studies, it was shown that by measuring GFP expression in absolute fluorescence units calibrated against a known concentration of fluorescent molecule can greatly reduce the variability in measurements between labs. However, when taking bulk measurements of a population of cells (such as with a plate reader), there is still a large source of variability in these measurements: the number of cells in the sample.
Because the fluorescence value measured by a plate reader is an aggregate measurement of an entire population of cells, we need to divide the total fluorescence by the number of cells in order to determine the mean expression level of GFP per cell. Usually this is done by measuring the absorbance of light at 600nm, from which the “optical density (OD)” of the sample is computed as an approximation of the number of cells. OD measurements are subject to high variability between labs, however, and it is unclear how good of an approximation an OD measurement actually is. If a more direct method is used to determine the cell count in each sample, then potentially another source of variability can be removed from the measurements.
This year, teams participating in the interlab study helped iGEM to answer the following question: Can we reduce lab-to-lab variability in fluorescence measurements by normalizing to absolute cell count or colony-forming units (CFUs) instead of OD?