The Art of Assays, Part 1: Insights From Our Lab Into Enzymatic Assay Development
The Art of Assays, Part 1: Insights From Our Lab Into Enzymatic Assay Development
The Art of Assays, Part 1: Insights From Our Lab Into Enzymatic Assay Development
Michelle Vandeloo & Jinel Shah
Michelle Vandeloo & Jinel Shah
July 9, 2024
July 9, 2024
One of the founding principles of Cradle is a commitment to sharing knowledge and resources with the research community. In both our wet labs and AI labs, we do a lot of experimentation to arrive at the best, most efficient, ‘this makes sense’ ways of doing things. Today, we want to share some of our insights into developing biochemical assays to measure enzyme activity and specificity.
Assay Development Should Not Be Intimidating
If you are working on improving enzyme properties or even designing new enzymes entirely, chances are you will need to develop your own enzyme assays to measure your progress. It may seem like an intimidating task, especially if you have not done assay development before or if the enzyme you are working with is ‘tricky’. We want to break the stereotype that you have to be a very specialized and experienced biochemist to develop new enzyme assays. All you need to get started is curiosity and a basic understanding of how enzymes work.
"We want to break the stereotype that you have to be a very specialized and experienced biochemist to develop new enzyme assays. All you need to get started is curiosity and a basic understanding of how enzymes work"
In this two-part series, we want to provide a general framework, along with some tips and pointers, on how to approach the process of developing a new assay yourself, instead of looking for a commercially available (and often expensive) option. Once you understand the logic behind it, you can apply this framework to any assay and scale it up to a 96- or 384-well plate format. A good assay with a well-defined output and a clear signal is going to be robust and scalable.
If you take one thing from this post, we hope it’s the attitude that assay development is not hard but rather fun and creative—like figuring out a puzzle. Let’s dive into it.
Step 1: Getting to Know Your Enzyme
The first step in developing any new enzymatic assay is learning about your enzyme. You could perform a literature search to see if someone has already developed an assay for this or a similar enzyme. If there is a suitable enzyme assay out there—you’ve hit a jackpot! Otherwise, it’s time to do some investigative work.
First, you need to figure out what reaction the enzyme catalyzes. You want to know what its substrate(s) and product(s) are, whether the reaction is reversible or irreversible, and whether it requires any cofactors or specific conditions. In most cases, you can look up this information in databases like the Protein Data Bank (PDB), BRENDA, NCBI, and BioCyc, or do a literature search.
If the enzyme you are interested in is not in databases or is poorly annotated, you may want to look up similar enzymes. These could include phylogenetic variants or structural homologs. Sometimes, you may even need to write out the proposed reaction yourself—especially if you are designing a new-to-nature enzyme.
Step 2: Developing a Scalable Assay
Once you have figured out what the enzyme reaction is, you need to think about how you can measure it, and ideally, do it in a plate-based format. To achieve throughput and reproducibility, we want to develop assays that can be measured using a common lab instrument, such as a UV-Vis spectrophotometer, and can be easily scaled.
Developing your own enzyme assay allows you to select the type of readout that best fits your needs. Common readouts are absorbance, fluorescence, or luminescence. Each type has its pros and cons, and you need to weigh out what is more important to you. For example, do you need precise quantification? Or do you want an assay that is easier to set up and provides faster measurements?
Regardless of what type of readout you pick, make sure you pick an assay that gives you good, consistent results: “A good enzyme assay is universal,” says Jinel. “It will work in any lab: large or small, industrial or academic. A scalable assay can be adapted to different throughputs and is transferable between labs. If the assay is well made, anyone should be able to replicate it and obtain clean, reliable data.”
Types of Assay Readouts
Absorbance
If the substrate, product or one of the cofactors involved in the reaction absorbs light, you can measure the changes in their concentrations over time. This can be done using a spectrophotometer, an instrument that quantitatively measures the absorption or emission of visible and ultraviolet light at specific wavelengths. Absorbance assays are generally easy to set up and provide quick measurements. However, they can be noisy due to the presence of other molecules in the sample that absorb light. If you expect to see dramatic changes and don’t care so much about the noise, absorbance is your best friend.
Fluorescence
You can use fluorescence to get a more accurate readout in cases when the concentrations of molecules are low or when you want precise quantitation. With fluorescence, the readout molecule is first activated by a specific wavelength of light and then emits a photon of a different wavelength, which can be measured by the instrument. This reaction is very specific and provides accurate measurements that are unaffected by the presence of other molecules in the assay.
Luminescence
Luminescence signal is even more specific than fluorescence and can be used for precise quantification of gene expression, for example. However, it requires first cloning the luminescent reporter genes into your expression system.
Step 3: Understanding the Enzyme Kinetics
The first thing you want to do after you get the assay up and running is to plot the Michaelis-Menten curve using purified enzymes. Analyzing the curve, along with the key enzyme metrics like kcat and Km, is a good starting point for thinking about what specific biochemical properties you want to target in order to improve the enzyme.
This is where the scientist’s expertise comes in: as an enzyme engineer, you will need to decide what aspects of the enzyme you are most interested in improving. For instance, you may want to improve the enzyme’s affinity for the substrate (km) so that it performs better at low substrate concentrations. Or if the substrate is abundant, you may need to work on increasing its catalytic efficiency, kcat, instead.
You may even want to tweak your assay conditions to focus on the target property and precisely measure the improvement in engineered enzyme variants. When you are plotting the Michaelis-Menten curve, it is a good idea to also test different substrates, such as alternative non-native substrates or inhibitors, to better understand the true nature of the enzyme.
Michaelis-Menten Curve
The Michaelis-Menten equation and corresponding plot is the Holy Grail of understanding and engineering enzymes. The Michaelis-Menten curve is a visual representation of the reaction that shows how much product is being made over time at various substrate concentrations.
Vmax is the maximum speed of the reaction at saturating substrate concentration. Vmax depends on the amount of enzyme used: if you double the amount of enzyme in the reaction, the Vmax will double accordingly.
kcat is one of the most important enzyme metrics: its turnover number. In simple terms, it tells you how quickly a substrate comes in, reacts and leaves the enzyme as a product.
Km stands for Michaelis constant. It describes the affinity of the enzyme for a particular substrate. Affinities of enzymes for substrates vary considerably, so knowing km helps understand how well an enzyme is suited for the substrate. A high km value means it takes more substrate to get to vmax. Low km values correspond to high affinity for the substrate.
kcat/Km is another important metric: the catalytic efficiency of the enzyme. A higher ratio represents a higher turnover rate of the enzyme and higher specificity for the substrate.
Understanding the Michaelis-Menten curve can tell you a lot about the enzyme, including metrics such as its efficiency (kcat) and affinity for the substrate (Km). It was named after the German biochemist Leonor Michaelis and Maud Menten, a Canadian biomedical researcher and chemist who was among the first women to earn a medical doctorate in 1916.
Make sure to check whether your enzyme could be inhibited by the substrate, product or any other component of the assay. This is important because if the reaction is inhibited by one of its components you have to think about how to circumvent that. For example, you may utilize a system that produces the substrate at a consistently low concentration or find an alternative enzyme that will avoid product accumulation in the reaction. We will be talking more about creative ways to navigate these potential issues in Part 2 of this series.
Step 4: Customizing Your Assay
Every assay you develop is going to be unique. This is where the scientist’s creativity really shines. For example, you may be interested in improving a specific property of an enzyme, such as its binding affinity. In this case, you will need to think about the best way to measure that property and quantify improvement. Or perhaps you can only look at the reaction at certain time points, instead of monitoring it continuously. The good news is that by developing the assay yourself, you can make it work for you.
For example, one useful way you could customize your assay is by making the reaction irreversible. Most common enzyme-catalyzed reactions are reversible. The direction of the reaction is determined by the concentrations of the substrate and product. Inside living cells, the concentration of a product is often limited because it gets immediately converted into another product or excreted from the cell. This forces the reaction to proceed in one direction.
However, in a test tube or 96-well assay plate, the concentrations of substrates and products are very different. As the product concentration increases, it can push the reaction in the reverse direction until it reaches an equilibrium. A reversible reaction makes it difficult to measure the important enzyme metrics that you want to capture, like reaction rates, and catalytic constants.
You can overcome this problem by making the reaction unidirectional. For example, you can add a dye that precipitates the product or a second enzyme that converts it into something your primary enzyme cannot utilize. Essentially, by taking away the reaction product, you are converting a reversible reaction into an irreversible one. This allows you to measure and evaluate all the aspects of the Michaelis-Menten equation.
This is just one way you can customize your assay. In Part 2 we provide more examples of how you can get around experimental constraints and take your assay game to the next level.
Step 5: Quality Control Process
Before you deploy the newly developed assay on a high-throughput scale, you need to ensure that the assay is set up properly. This includes introducing metrics and statistical procedures to evaluate the assay readout quality, as well as setting up the positive and negative controls.
For a positive control, you can often use a commercially available enzyme. Otherwise, you can use an in-house purified enzyme sample that has been tested by other methods, such as mass spectrometry or liquid chromatography. For a negative control, you can simply use another, unrelated enzyme that is not supposed to act on your substrate. If that enzyme still gives you a signal, that means something is wrong with the way the assay was set up.
Controls give you a quick ‘yes’ or ‘no’ answer to whether your assay is functional but consistent performance over time is what makes a robust assay. This is where you will need to use statistics. You can look at some quick statistical readouts, such as the standard deviation, assay to signal ratio, assay to noise ratio and Z' factor, to check the robustness of the assay. A good rule of thumb is: tighter the assay window and Z' values, the more robust the assay. For a more detailed analysis, however, it is good to introduce specialized statistical tools into your workflows.
Statistics are also important for assessing the improvement in the performance of the enzyme variants you are screening. To set up a statistical threshold, you can try adding different concentrations of your enzyme to mimic what a good hit would look like and whether your assay can detect these improvements.
As you are developing your assays, always keep in mind that enzyme engineering and assay development go hand-in-hand. It’s an iterative process that is full of surprises and opportunities to be creative. This is why we love it so much.
If you follow these five basic steps, you can start developing your own enzyme assays, with confidence. For pro-level tips and tricks on how to make your enzyme assays stand out, check out Part 2 of this series!
One of the founding principles of Cradle is a commitment to sharing knowledge and resources with the research community. In both our wet labs and AI labs, we do a lot of experimentation to arrive at the best, most efficient, ‘this makes sense’ ways of doing things. Today, we want to share some of our insights into developing biochemical assays to measure enzyme activity and specificity.
Assay Development Should Not Be Intimidating
If you are working on improving enzyme properties or even designing new enzymes entirely, chances are you will need to develop your own enzyme assays to measure your progress. It may seem like an intimidating task, especially if you have not done assay development before or if the enzyme you are working with is ‘tricky’. We want to break the stereotype that you have to be a very specialized and experienced biochemist to develop new enzyme assays. All you need to get started is curiosity and a basic understanding of how enzymes work.
"We want to break the stereotype that you have to be a very specialized and experienced biochemist to develop new enzyme assays. All you need to get started is curiosity and a basic understanding of how enzymes work"
In this two-part series, we want to provide a general framework, along with some tips and pointers, on how to approach the process of developing a new assay yourself, instead of looking for a commercially available (and often expensive) option. Once you understand the logic behind it, you can apply this framework to any assay and scale it up to a 96- or 384-well plate format. A good assay with a well-defined output and a clear signal is going to be robust and scalable.
If you take one thing from this post, we hope it’s the attitude that assay development is not hard but rather fun and creative—like figuring out a puzzle. Let’s dive into it.
Step 1: Getting to Know Your Enzyme
The first step in developing any new enzymatic assay is learning about your enzyme. You could perform a literature search to see if someone has already developed an assay for this or a similar enzyme. If there is a suitable enzyme assay out there—you’ve hit a jackpot! Otherwise, it’s time to do some investigative work.
First, you need to figure out what reaction the enzyme catalyzes. You want to know what its substrate(s) and product(s) are, whether the reaction is reversible or irreversible, and whether it requires any cofactors or specific conditions. In most cases, you can look up this information in databases like the Protein Data Bank (PDB), BRENDA, NCBI, and BioCyc, or do a literature search.
If the enzyme you are interested in is not in databases or is poorly annotated, you may want to look up similar enzymes. These could include phylogenetic variants or structural homologs. Sometimes, you may even need to write out the proposed reaction yourself—especially if you are designing a new-to-nature enzyme.
Step 2: Developing a Scalable Assay
Once you have figured out what the enzyme reaction is, you need to think about how you can measure it, and ideally, do it in a plate-based format. To achieve throughput and reproducibility, we want to develop assays that can be measured using a common lab instrument, such as a UV-Vis spectrophotometer, and can be easily scaled.
Developing your own enzyme assay allows you to select the type of readout that best fits your needs. Common readouts are absorbance, fluorescence, or luminescence. Each type has its pros and cons, and you need to weigh out what is more important to you. For example, do you need precise quantification? Or do you want an assay that is easier to set up and provides faster measurements?
Regardless of what type of readout you pick, make sure you pick an assay that gives you good, consistent results: “A good enzyme assay is universal,” says Jinel. “It will work in any lab: large or small, industrial or academic. A scalable assay can be adapted to different throughputs and is transferable between labs. If the assay is well made, anyone should be able to replicate it and obtain clean, reliable data.”
Types of Assay Readouts
Absorbance
If the substrate, product or one of the cofactors involved in the reaction absorbs light, you can measure the changes in their concentrations over time. This can be done using a spectrophotometer, an instrument that quantitatively measures the absorption or emission of visible and ultraviolet light at specific wavelengths. Absorbance assays are generally easy to set up and provide quick measurements. However, they can be noisy due to the presence of other molecules in the sample that absorb light. If you expect to see dramatic changes and don’t care so much about the noise, absorbance is your best friend.
Fluorescence
You can use fluorescence to get a more accurate readout in cases when the concentrations of molecules are low or when you want precise quantitation. With fluorescence, the readout molecule is first activated by a specific wavelength of light and then emits a photon of a different wavelength, which can be measured by the instrument. This reaction is very specific and provides accurate measurements that are unaffected by the presence of other molecules in the assay.
Luminescence
Luminescence signal is even more specific than fluorescence and can be used for precise quantification of gene expression, for example. However, it requires first cloning the luminescent reporter genes into your expression system.
Step 3: Understanding the Enzyme Kinetics
The first thing you want to do after you get the assay up and running is to plot the Michaelis-Menten curve using purified enzymes. Analyzing the curve, along with the key enzyme metrics like kcat and Km, is a good starting point for thinking about what specific biochemical properties you want to target in order to improve the enzyme.
This is where the scientist’s expertise comes in: as an enzyme engineer, you will need to decide what aspects of the enzyme you are most interested in improving. For instance, you may want to improve the enzyme’s affinity for the substrate (km) so that it performs better at low substrate concentrations. Or if the substrate is abundant, you may need to work on increasing its catalytic efficiency, kcat, instead.
You may even want to tweak your assay conditions to focus on the target property and precisely measure the improvement in engineered enzyme variants. When you are plotting the Michaelis-Menten curve, it is a good idea to also test different substrates, such as alternative non-native substrates or inhibitors, to better understand the true nature of the enzyme.
Michaelis-Menten Curve
The Michaelis-Menten equation and corresponding plot is the Holy Grail of understanding and engineering enzymes. The Michaelis-Menten curve is a visual representation of the reaction that shows how much product is being made over time at various substrate concentrations.
Vmax is the maximum speed of the reaction at saturating substrate concentration. Vmax depends on the amount of enzyme used: if you double the amount of enzyme in the reaction, the Vmax will double accordingly.
kcat is one of the most important enzyme metrics: its turnover number. In simple terms, it tells you how quickly a substrate comes in, reacts and leaves the enzyme as a product.
Km stands for Michaelis constant. It describes the affinity of the enzyme for a particular substrate. Affinities of enzymes for substrates vary considerably, so knowing km helps understand how well an enzyme is suited for the substrate. A high km value means it takes more substrate to get to vmax. Low km values correspond to high affinity for the substrate.
kcat/Km is another important metric: the catalytic efficiency of the enzyme. A higher ratio represents a higher turnover rate of the enzyme and higher specificity for the substrate.
Understanding the Michaelis-Menten curve can tell you a lot about the enzyme, including metrics such as its efficiency (kcat) and affinity for the substrate (Km). It was named after the German biochemist Leonor Michaelis and Maud Menten, a Canadian biomedical researcher and chemist who was among the first women to earn a medical doctorate in 1916.
Make sure to check whether your enzyme could be inhibited by the substrate, product or any other component of the assay. This is important because if the reaction is inhibited by one of its components you have to think about how to circumvent that. For example, you may utilize a system that produces the substrate at a consistently low concentration or find an alternative enzyme that will avoid product accumulation in the reaction. We will be talking more about creative ways to navigate these potential issues in Part 2 of this series.
Step 4: Customizing Your Assay
Every assay you develop is going to be unique. This is where the scientist’s creativity really shines. For example, you may be interested in improving a specific property of an enzyme, such as its binding affinity. In this case, you will need to think about the best way to measure that property and quantify improvement. Or perhaps you can only look at the reaction at certain time points, instead of monitoring it continuously. The good news is that by developing the assay yourself, you can make it work for you.
For example, one useful way you could customize your assay is by making the reaction irreversible. Most common enzyme-catalyzed reactions are reversible. The direction of the reaction is determined by the concentrations of the substrate and product. Inside living cells, the concentration of a product is often limited because it gets immediately converted into another product or excreted from the cell. This forces the reaction to proceed in one direction.
However, in a test tube or 96-well assay plate, the concentrations of substrates and products are very different. As the product concentration increases, it can push the reaction in the reverse direction until it reaches an equilibrium. A reversible reaction makes it difficult to measure the important enzyme metrics that you want to capture, like reaction rates, and catalytic constants.
You can overcome this problem by making the reaction unidirectional. For example, you can add a dye that precipitates the product or a second enzyme that converts it into something your primary enzyme cannot utilize. Essentially, by taking away the reaction product, you are converting a reversible reaction into an irreversible one. This allows you to measure and evaluate all the aspects of the Michaelis-Menten equation.
This is just one way you can customize your assay. In Part 2 we provide more examples of how you can get around experimental constraints and take your assay game to the next level.
Step 5: Quality Control Process
Before you deploy the newly developed assay on a high-throughput scale, you need to ensure that the assay is set up properly. This includes introducing metrics and statistical procedures to evaluate the assay readout quality, as well as setting up the positive and negative controls.
For a positive control, you can often use a commercially available enzyme. Otherwise, you can use an in-house purified enzyme sample that has been tested by other methods, such as mass spectrometry or liquid chromatography. For a negative control, you can simply use another, unrelated enzyme that is not supposed to act on your substrate. If that enzyme still gives you a signal, that means something is wrong with the way the assay was set up.
Controls give you a quick ‘yes’ or ‘no’ answer to whether your assay is functional but consistent performance over time is what makes a robust assay. This is where you will need to use statistics. You can look at some quick statistical readouts, such as the standard deviation, assay to signal ratio, assay to noise ratio and Z' factor, to check the robustness of the assay. A good rule of thumb is: tighter the assay window and Z' values, the more robust the assay. For a more detailed analysis, however, it is good to introduce specialized statistical tools into your workflows.
Statistics are also important for assessing the improvement in the performance of the enzyme variants you are screening. To set up a statistical threshold, you can try adding different concentrations of your enzyme to mimic what a good hit would look like and whether your assay can detect these improvements.
As you are developing your assays, always keep in mind that enzyme engineering and assay development go hand-in-hand. It’s an iterative process that is full of surprises and opportunities to be creative. This is why we love it so much.
If you follow these five basic steps, you can start developing your own enzyme assays, with confidence. For pro-level tips and tricks on how to make your enzyme assays stand out, check out Part 2 of this series!
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