week 10 imaging-and-measurement

Measurement Plan for Final Project: Piezoelectric Tone Modulation

Project Context

My final project explores a concept called Piezoelectric Tone Modulation, where a biologically produced peptide or protein-based scaffold, called here PiezoTone, could be integrated into a soft robotic wearable system for muscle tone modulation or rehabilitation support. The project combines synthetic biology, biomaterials, and wearable soft robotics.

Because this project includes both a biological production phase and a functional wearable prototype phase, I would measure several aspects at different levels:

1. DNA/plasmid design and verification

2. Protein or peptide expression

3. Protein purification and identity

4. Material integration into a scaffold or film

5. Piezoelectric/mechanical response

6. Muscle-related sensing or tone modulation performance

7. Biocompatibility and safety, if the project advances toward biological or wearable testing

1. DNA / Plasmid Verification

What I would measure

The first element I would measure is whether the designed DNA construct is correct. The plasmid should contain the correct components for expression in E. coli:

• Promoter

• Ribosome binding site

• PiezoTone peptide/protein coding sequence

• His-tag for purification

• Terminator

• Antibiotic resistance marker

• Origin of replication

Why this is important

Before producing the peptide or protein, I need to confirm that the genetic construct is correct. If the sequence has mutations, missing regions, or incorrect orientation, the expression may fail.

Technologies and methods

Agarose Gel Electrophoresis

I would use agarose gel electrophoresis to verify the size of the plasmid or DNA insert after digestion or PCR.

Procedure:

1. Prepare a sample of plasmid DNA.

2. Digest the plasmid with restriction enzymes or amplify the insert by PCR.

3. Load the DNA sample into an agarose gel.

4. Run the gel using an electric field.

5. Compare the DNA bands with a DNA ladder.

6. Confirm whether the band size matches the expected plasmid or insert size.

Expected result:

A DNA band corresponding to the expected size of the PiezoTone insert and/or complete plasmid.

Sanger Sequencing

I would use Sanger sequencing to confirm the exact nucleotide sequence of the PiezoTone coding region.

Procedure:

1. Send the plasmid DNA with specific sequencing primers.

2. Sequence across the promoter, coding sequence, His-tag, and terminator.

3. Compare the sequencing result with the designed sequence in Benchling.

4. Check for mutations, frame shifts, or incorrect orientation.

Expected result:

The sequence should match the designed PiezoTone construct with no unwanted mutations.

2. Protein / Peptide Expression

What I would measure

After confirming the plasmid, I would measure whether the PiezoTone peptide or protein is successfully expressed in E. coli or in a cell-free expression system.

The main measurable elements are:

• Presence or absence of the PiezoTone protein

• Approximate molecular weight

• Expression level

• Solubility of the protein

• Difference between induced and non-induced samples

Why this is important

The project depends on producing the PiezoTone peptide/protein. Measuring expression allows me to know whether the biological system is producing the desired material.

Technologies and methods

SDS-PAGE

I would use SDS-PAGE to separate proteins by molecular weight and verify whether a new band appears at the expected size of the PiezoTone protein.

SDS-PAGE is a standard method used to analyze protein expression and purity. In protein expression workflows, SDS-PAGE is commonly used together with Western blotting to verify whether a recombinant protein has been produced. oai_citation:0‡PMC

Procedure:

1. Grow transformed E. coli cells containing the PiezoTone plasmid.

2. Induce expression, for example with IPTG if using an inducible promoter.

3. Collect samples before and after induction.

4. Lyse the cells.

5. Separate soluble and insoluble fractions.

6. Load samples on an SDS-PAGE gel.

7. Stain the gel with Coomassie Blue.

8. Compare the bands with a protein ladder.

Samples to compare:

• Non-induced cells

• Induced cells

• Soluble fraction

• Insoluble pellet

• Purified protein fraction

Expected result:

A protein band should appear at the expected molecular weight after induction. A stronger band in the induced sample would suggest successful expression.

3. Protein Identity and Purification

What I would measure

After expression, I would measure whether the produced protein is really the PiezoTone protein and whether it can be purified.

The measurable elements are:

• Protein identity

• Protein purity

• Protein yield

• Presence of the His-tag

• Approximate concentration of purified protein

Technologies and methods

His-tag Purification / Nickel Affinity Chromatography

If the PiezoTone construct includes a His-tag, I would purify it using Ni-NTA affinity chromatography. His-tagged proteins can bind to immobilized metal ions such as nickel, cobalt, or copper, which makes the tag useful for purification and detection. oai_citation:1‡thermofisher.com

Procedure:

1. Lyse the transformed E. coli cells.

2. Apply the protein lysate to a Ni-NTA column.

3. Allow the His-tagged PiezoTone protein to bind to the nickel resin.

4. Wash away non-specific proteins.

5. Elute the His-tagged protein using imidazole.

6. Analyze the eluted fractions by SDS-PAGE.

Expected result:

The purified fraction should show a stronger and cleaner band at the expected molecular weight.

Western Blot

I would use Western blotting with an anti-His antibody to confirm that the detected protein contains the His-tag.

Procedure:

1. Run the expressed protein on SDS-PAGE.

2. Transfer the proteins to a membrane.

3. Incubate the membrane with an anti-His antibody.

4. Detect the signal.

5. Confirm whether the band appears at the expected size.

Expected result:

A positive band at the expected molecular weight would confirm the presence of the His-tagged PiezoTone protein.

Protein Concentration Assay

I would measure protein concentration using a Bradford assay, BCA assay, or Nanodrop-based protein measurement.

Procedure:

1. Prepare a standard curve using known protein concentrations.

2. Add the protein sample to the assay reagent.

3. Measure absorbance using a spectrophotometer or plate reader.

4. Calculate the concentration of the purified protein.

Expected result:

A quantitative value in mg/mL or µg/mL, showing how much PiezoTone protein was produced.

Mass Spectrometry

For stronger confirmation, I would use mass spectrometry to verify the molecular mass and identity of the protein. Protein purification facilities often use mass spectrometry to confirm protein identity after purification. oai_citation:2‡embl.org

Procedure:

1. Excise the protein band from an SDS-PAGE gel or prepare the purified protein in solution.

2. Digest the protein into peptides, commonly using trypsin.

3. Analyze the peptides by mass spectrometry.

4. Compare the detected peptide masses with the expected PiezoTone sequence.

Expected result:

The detected peptide fragments should match the designed PiezoTone sequence.

4. Material Integration into a Soft Robotic Scaffold

What I would measure

Once the PiezoTone protein or peptide is produced, I would measure whether it can be integrated into a material system, such as:

• Hydrogel

• Biofilm

• Textile coating

• Flexible polymer scaffold

• Soft robotic actuator layer

The measurable elements are:

• Protein distribution in the material

• Protein retention after washing or deformation

• Film or scaffold thickness

• Surface morphology

• Mechanical stability

• Adhesion to textile or soft substrate

Technologies and methods

Microscopy

I would use optical microscopy or fluorescence microscopy if the protein is labeled.

Purpose:

• Observe whether the material coating is homogeneous.

• Check whether the protein or peptide is distributed across the scaffold.

• Detect cracks, aggregation, or irregular deposition.

SEM: Scanning Electron Microscopy

If available, I would use SEM to observe the microstructure of the scaffold.

Purpose:

• Analyze surface morphology.

• Observe fibers, pores, or crystalline structures.

• Compare untreated and PiezoTone-coated samples.

FTIR Spectroscopy

I would use FTIR spectroscopy to detect chemical bonds and confirm whether the protein or peptide is present in the material.

Purpose:

• Identify characteristic amide peaks from proteins.

• Compare the base material with the PiezoTone-integrated material.

• Verify chemical interaction between protein and scaffold.

Contact Angle Measurement

If the material is intended to interact with skin or biological fluids, I would measure the contact angle.

Purpose:

• Determine whether the surface is hydrophilic or hydrophobic.

• Understand how the material might behave when placed on skin.

• Compare before and after protein coating.

5. Piezoelectric or Electromechanical Response

What I would measure

Because the project is related to piezoelectric tone modulation, I would measure whether the material generates an electrical signal when mechanically deformed.

The measurable elements are:

• Voltage output under pressure or bending

• Current output

• Signal stability over repeated cycles

• Sensitivity to deformation

• Response time

• Durability after repeated mechanical loading

Why this is important

The key functional hypothesis is that the PiezoTone-based material or hybrid scaffold could participate in mechanical-electrical interaction. If the material is compressed, stretched, or bent, it should ideally generate a measurable electrical response or modify the mechanical/electrical behavior of the wearable system.

Technologies and methods

Oscilloscope or Digital Multimeter

I would use an oscilloscope or sensitive digital multimeter to measure voltage output.

Procedure:

1. Place electrodes on the PiezoTone-integrated material.

2. Apply controlled pressure, bending, or stretching.

3. Record the voltage response.

4. Repeat the test under different forces and frequencies.

5. Compare the response with a control sample without PiezoTone.

Expected result:

The PiezoTone-integrated material should show a measurable electrical response under mechanical deformation.

Force Sensor + Voltage Measurement

To quantify the relationship between force and voltage, I would combine:

• Force sensor

• Mechanical testing setup

• Oscilloscope or data acquisition board

Procedure:

1. Apply known forces to the sample.

2. Measure the generated voltage.

3. Plot voltage output against applied force.

4. Calculate sensitivity.

Possible output data:

• Voltage-force curve

• Peak voltage

• Signal repeatability

• Response under cyclic loading

Cyclic Mechanical Testing

I would test the material under repeated bending or compression cycles.

Purpose:

• Evaluate durability.

• Measure whether the signal decreases over time.

• Understand whether the material is suitable for wearable use.

6. Muscle Tone / Wearable Performance Measurements

What I would measure

If the project advances into a wearable prototype, I would measure how the system interacts with muscle activity or muscle tone.

The measurable elements could include:

• Muscle activation

• Muscle contraction

• Muscle stiffness or tone

• Movement range

• User comfort

• Pressure applied by the wearable

• Response of the actuator to body movement

Technologies and methods

EMG: Electromyography

I would use surface electromyography to measure electrical activity of muscles.

Purpose:

• Detect muscle activation.

• Compare muscle activity before, during, and after using the wearable.

• Understand whether the system supports or modulates muscle effort.

Procedure:

1. Place surface EMG electrodes on the target muscle.

2. Record baseline muscle activity.

3. Activate or apply the wearable system.

4. Record muscle activity during movement or assisted movement.

5. Compare EMG amplitude and frequency changes.

Expected result:

If the wearable supports movement, the EMG signal may show reduced effort for the same movement task, or a change in activation pattern.

Mechanomyography / Piezoresistive Sensing

Mechanomyography measures mechanical vibrations or movements produced by muscle contraction. Wearable force-sensitive or piezoresistive sensors have been explored as alternatives or complements to EMG for measuring muscle contraction. oai_citation:3‡PMC

Purpose:

• Measure the mechanical behavior of the muscle.

• Detect contraction intensity.

• Compare muscle mechanical response with and without the wearable.

Procedure:

1. Place a piezoresistive or vibration sensor over the target muscle.

2. Ask the participant or test system to perform controlled movements.

3. Record the mechanical signal.

4. Compare the signal to EMG and actuator output.

Ultrasound or Wearable Ultrasonic Sensing

For advanced validation, I could use ultrasound to measure muscle thickness or contraction parameters. Wearable ultrasonic sensors based on PVDF piezoelectric films have been used to measure skeletal muscle contractile parameters. oai_citation:4‡MDPI

Purpose:

• Measure changes in muscle thickness during contraction.

• Observe deeper muscle movement.

• Validate whether the wearable affects muscle contraction.

Procedure:

1. Place the ultrasound sensor over the target muscle.

2. Record muscle thickness during rest and contraction.

3. Compare data before and after wearable assistance.

4. Analyze contraction timing and amplitude.

7. Biocompatibility and Skin Interaction

What I would measure

If the PiezoTone material is intended to be used close to the body or skin, I would measure basic biocompatibility and comfort-related properties.

The measurable elements are:

• Skin irritation potential

• Cytotoxicity

• Surface pH

• Breathability

• Flexibility

• Comfort

• Moisture interaction

Technologies and methods

Cell Viability Assay

For early biocompatibility testing, I would use a cell viability assay such as MTT or Live/Dead staining.

Purpose:

• Test whether the material is toxic to cells.

• Compare cells exposed to the material with control cells.

Expected result:

Cells exposed to the material should maintain high viability compared with controls.

Wearability Observation

For a non-clinical prototype, I would evaluate:

• Comfort

• Flexibility

• Skin contact

• Stability during movement

• Ease of wearing and removing the device

This would be done first with non-invasive user feedback and mechanical testing, not clinical claims.

Summary Table of Measurements

PiezoTone Project — Validation & Characterisation Plan

Final Measurement Strategy

The most important measurements for my final project would be organized in three levels.

Level 1: Biological verification

First, I would confirm that the PiezoTone DNA construct is correct using agarose gel electrophoresis and Sanger sequencing. Then, I would express the protein in E. coli or in a cell-free system and verify expression using SDS-PAGE. If the protein has a His-tag, I would purify it using Ni-NTA chromatography and confirm its identity using Western blot and, ideally, mass spectrometry.

Level 2: Material and electromechanical characterization

Second, I would integrate the purified PiezoTone protein or peptide into a soft scaffold, hydrogel, coating, or textile-based material. I would measure its distribution using microscopy, its chemical presence using FTIR, and its morphology using SEM. Then, I would test whether the material produces an electrical response under mechanical deformation using an oscilloscope, force sensor, and cyclic bending or compression setup.

Level 3: Wearable and muscle-related validation

Finally, I would evaluate the wearable system as a soft robotic interface for muscle tone modulation. I would use EMG to measure muscle activation and mechanomyography or piezoresistive sensing to measure mechanical contraction. In a more advanced stage, ultrasound could be used to measure changes in muscle thickness and contraction dynamics. These measurements would help determine whether the PiezoTone-based soft wearable system can interact with muscle movement and support rehabilitation-oriented applications.

Overall, these measurements would allow me to evaluate the project from DNA design to protein production, from biomaterial integration to electromechanical response, and finally from wearable prototype to possible muscle tone modulation performance.

Correction about the expression system

Initially, I considered expressing the PiezoTone peptide/protein in E. coli. However, after reviewing the biological requirements of the target protein, I realized that E. coli may not be the most appropriate system if the protein requires a correct quaternary structure, complex folding, or post-translational modifications.

Because E. coli is a prokaryotic system, it is very useful for producing simple recombinant proteins, peptides, and bacterial proteins. However, it has limitations when expressing complex eukaryotic proteins, especially proteins that need:

• Correct folding into multi-subunit or quaternary structures
• Disulfide bond formation
• Glycosylation or other post-translational modifications
• Mammalian-like cellular processing
• Membrane localization or complex protein assembly

For this reason, if the PiezoTone concept requires a protein that functions through a complex quaternary structure or needs mammalian post-translational modifications, a mammalian cell expression system may be more suitable than E. coli.

Possible mammalian expression systems include:

• HEK293 cells
• CHO cells
• COS-7 cells

These systems would allow better protein folding, mammalian post-translational modifications, and more realistic functional behavior for proteins related to mechanosensing, ion channels, or cellular tone modulation.

Therefore, the expression strategy should be adjusted as follows:

1. Use E. coli only for early-stage plasmid amplification, cloning, and possibly simple peptide expression.
2. Use a mammalian expression system if the target protein requires complex folding, quaternary structure, or mammalian post-translational modifications.
3. Validate the expression using SDS-PAGE, Western blot, immunofluorescence, and possibly functional assays depending on the target protein.

Although I initially considered expressing the PiezoTone construct in E. coli, this may not be suitable if the protein requires a correct quaternary structure, complex folding, or mammalian post-translational modifications. In that case, a mammalian cell expression system such as HEK293 or CHO cells would be more appropriate.

You can find more information under imaging and measurement documentation here: Imaging and Measurement section.

eGFP Intact Mass Analysis

Waters Xevo G3 QTof MS — Native & Denatured States

Question 1: Theoretical Molecular Weight

Using the ExPASy ProtParam tool with the given sequence, the average molecular weight from sequence alone ≈ 27,837 Da.

However, eGFP undergoes autocatalytic chromophore maturation — a post-translational modification involving the tripeptide Thr65–Tyr66–Gly67:

$$M_{\text{eGFP (calc)}} \approx 27{,}837 - 20 = \mathbf{27{,}817 \ \text{Da}}$$

Note: The His₆-tag + LE linker (LEHHHHHH) are included in the ExPASy calculation since they are part of the input sequence.

eGFP Sequence Used

MVSKGEELFTG VVPILVELDG DVNGHKFSVS GEGEGDATYG KLTLKFICTT GKLPVPWPTL
VTTLTYGVQC FSRYPDHMKQ HDFFKSAMPE GYVQERTIFF KDDGNYKTRA EVKFEGDTLV
NRIELKGIDF KEDGNILGHK LEYNYNSHNV YIMADKQKNG IKVNFKIRHN IEDGSVQLAD
HYQQNTPIGD GPVLLPDNHY LSTQSALSKD PNEKRDHMVL LEFVTAAGIT LGMDELYKLE
HHHHHH

The predicted molecular weight of the provided eGFP construct, including the LE linker and C-terminal 6×His purification tag, is approximately 28,006.6 Da for the unmodified polypeptide. However, mature eGFP undergoes chromophore formation, which involves dehydration and oxidation, resulting in a mass loss of approximately 20 Da. Therefore, the expected molecular weight of mature eGFP is approximately 27,986.6 Da.

In LC-MS analysis, the protein is expected to appear as a multiply charged ion series. Under denaturing LC-MS conditions, eGFP will unfold and typically show a broader distribution of higher charge states compared with native MS conditions, where the folded protein usually presents fewer and lower charge states.

Question 2: Adjacent Charge State Approach

Background

In electrospray ionization (ESI), a protein acquires multiple protons, producing a charge state envelope — a series of peaks at different m/z values corresponding to different numbers of charges z. The adjacent charge state method uses two neighboring peaks to simultaneously solve for z and the molecular weight M.

2.1 Determine z for each adjacent pair of peaks (n, n + 1)

Charge state determination (in short)

For each adjacent pair of peaks, corresponding to charge states (z_n) and (z_{n+1}), the charge state can be estimated using:

[ z = \frac{m/z_{n+1}}{(m/z_n) - (m/z_{n+1})} ]

where:

• (m/z_n) is the mass-to-charge ratio of one peak
• (m/z_{n+1}) is the mass-to-charge ratio of the adjacent peak at the next higher charge state
• (z) is the charge state of the peak at (m/z_n)
• z = (m/z of lower-mass adjacent peak) / [(m/z of higher-mass peak) - (m/z of lower-mass adjacent peak)] Then the neutral molecular weight can be estimated with: M = z × (m/z - proton mass) where the proton mass is approximately: 1.0073 Da

For peak $n$ carrying charge $z$, and peak $n+1$ carrying charge $z + 1$ (at lower m/z), the observed m/z values are (ignoring the small proton mass as an approximation):

$$\frac{m}{z_n} \approx \frac{M}{z} \qquad \frac{m}{z_{n+1}} \approx \frac{M}{z+1}$$

Setting $M$ equal in both expressions:

$$z \cdot \frac{m}{z_n} = (z+1) \cdot \frac{m}{z_{n+1}}$$

$$z \cdot \frac{m}{z_n} = z \cdot \frac{m}{z_{n+1}} + \frac{m}{z_{n+1}}$$

$$z \left( \frac{m}{z_n} - \frac{m}{z_{n+1}} \right) = \frac{m}{z_{n+1}}$$

$$\boxed{z = \frac{\dfrac{m}{z_{n+1}}}{\dfrac{m}{z_n} - \dfrac{m}{z_{n+1}}}}$$

z is the charge state of peak n (the higher m/z peak of the pair). Peak n+1 has charge $z + 1$.
Round the result to the nearest integer — charge states must be whole numbers.

2.2 Calculate M from z

Once z is known (rounded), recover the molecular weight using either peak:

From peak n: $$M = z \cdot \frac{m}{z_n} - z \cdot 1.00728$$

From peak n+1 (cross-check): $$M = (z+1) \cdot \frac{m}{z_{n+1}} - (z+1) \cdot 1.00728$$

Both should give the same M. Small differences reflect reading uncertainty from the spectrum.

2.3 Step-by-Step Procedure

For each adjacent pair selected from the LC-MS spectrum (Figure 1):

1. Read off $\left(\frac{m}{z}\right)n$ and $\left(\frac{m}{z}\right){n+1}$ from the spectrum
2. Plug into the formula to calculate z
3. Round z to the nearest integer
4. Calculate M using the rounded z
5. Repeat for a second adjacent pair
6. Average the M values → report as experimental MW
7. Compare to the theoretical value from Question 1

2.4 Worksheet Template

2.5 Interpreting the Charge State Distribution

Key concept: In the native state, the compact folded structure shields many basic residues from protonation. In the denatured state, the fully unfolded chain exposes all basic sites. Despite different charge envelopes, both states yield the same molecular weight M.

3. Calculate the measurement accuracy / relative error

Using the labelled adjacent charge-state peaks in the intact eGFP LC-MS spectrum, the charge states were assigned from approximately 33+ to 28+. The molecular weight was calculated using the relationship:

[ MW = z \times (m/z - H) ]

where (H = 1.0073) Da. Across the selected charge states, the calculated molecular weights were highly consistent, giving an average experimental molecular weight of approximately 27,983.2 Da.

The predicted molecular weight of mature eGFP containing the LE linker and C-terminal 6×His tag is approximately 27,986.6 Da. Therefore, the relative error of the measurement is:

[ \frac{|27983.2 - 27986.6|}{27986.6} \times 100 = 0.012% ]

This indicates that the LC-MS measurement agrees very closely with the predicted molecular weight of the protein.

eGFP Intact MS — Questions 2.2, 3, and Charge State Observation

Q2.2 — Determine MW from Adjacent Charge State Pairs

Using labeled peaks from the denatured-state envelope in Figure 1 and the formula:

$$z = \frac{\dfrac{m}{z_{n+1}}}{\dfrac{m}{z_n} - \dfrac{m}{z_{n+1}}} \qquad M = z \cdot \frac{m}{z_n} - z \cdot 1.00728$$

Pair 1 worked example:

$$z = \frac{848.9756}{875.4421 - 848.9756} = \frac{848.9756}{26.4665} = 32.08 \rightarrow z = 32$$

$$M = 32 \times 875.4421 - 32 \times 1.00728 = 28{,}014.15 - 32.23 = \mathbf{27{,}981.9 \ \text{Da}}$$

Pair 2 worked example:

$$z = \frac{875.4421}{903.7148 - 875.4421} = \frac{875.4421}{28.2727} = 30.96 \rightarrow z = 31$$

$$M = 31 \times 903.7148 - 31 \times 1.00728 = 28{,}015.16 - 31.23 = \mathbf{27{,}983.9 \ \text{Da}}$$

$$\overline{M}_\text{experiment} = \frac{27{,}981.9 + 27{,}983.9}{2} = \mathbf{27{,}982.9 \ \text{Da}}$$

Q3 — Accuracy of the Measurement

$$\text{Accuracy} = \frac{|MW_\text{experiment} - MW_\text{theory}|}{MW_\text{theory}} = \frac{|27{,}982.9 - 27{,}987|}{27{,}987} = \frac{3.7}{27{,}987} \approx \mathbf{0.013%}$$

This is excellent mass accuracy. The small residual error arises from reading peak positions off a printed figure; the Xevo G3 QTof achieves < 5 ppm under calibrated conditions with lockspray.

eGFP Intact MS — Questions 2.2, 3, and Charge State Observation

Q2.2 — Determine MW from Adjacent Charge State Pairs

Using labeled peaks from the denatured-state envelope in Figure 1 and the formula:

$$z = \frac{\dfrac{m}{z_{n+1}}}{\dfrac{m}{z_n} - \dfrac{m}{z_{n+1}}} \qquad M = z \cdot \frac{m}{z_n} - z \cdot 1.00728$$

Pair 1 worked example:

$$z = \frac{848.9756}{875.4421 - 848.9756} = \frac{848.9756}{26.4665} = 32.08 \rightarrow z = 32$$

$$M = 32 \times 875.4421 - 32 \times 1.00728 = 28{,}014.15 - 32.23 = \mathbf{27{,}981.9 \ \text{Da}}$$

Pair 2 worked example:

$$z = \frac{875.4421}{903.7148 - 875.4421} = \frac{875.4421}{28.2727} = 30.96 \rightarrow z = 31$$

$$M = 31 \times 903.7148 - 31 \times 1.00728 = 28{,}015.16 - 31.23 = \mathbf{27{,}983.9 \ \text{Da}}$$

$$\overline{M}_\text{experiment} = \frac{27{,}981.9 + 27{,}983.9}{2} = \mathbf{27{,}982.9 \ \text{Da}}$$

Q3 — Accuracy of the Measurement

$$\text{Accuracy} = \frac{|MW_\text{experiment} - MW_\text{theory}|}{MW_\text{theory}} = \frac{|27{,}982.9 - 27{,}987|}{27{,}987} = \frac{3.7}{27{,}987} \approx \mathbf{0.013%}$$

This is excellent mass accuracy. The small residual error arises from reading peak positions off a printed figure; the Xevo G3 QTof achieves < 5 ppm under calibrated conditions with lockspray.

Q — Can You Observe the Charge State from the Zoomed-In Peak?

Yes — the charge state is z = 19.

Why the charge state is readable here

At 30,000 resolution, the instrument just resolves individual isotope peaks within the native-state charge state envelope. Since consecutive isotopes differ by exactly 1 Da in mass, their spacing in m/z is:

$$\Delta\left(\frac{m}{z}\right)_\text{isotope} = \frac{1 \ \text{Da}}{z}$$

Inverting this gives the charge state directly:

$$z = \frac{1}{\Delta(m/z)_\text{isotope}}$$

Reading z from the inset

Adjacent isotope peaks in the zoom (e.g. 1473.0884 and 1473.1428) are separated by:

$$\Delta\left(\frac{m}{z}\right) = 1473.1428 - 1473.0884 = 0.0544$$

$$z = \frac{1}{0.0544} = 18.4 \approx \mathbf{19}$$

Cross-check with MW

Using the experimental MW from Q2.2:

$$\frac{m}{z_{19}} = \frac{27{,}982.9 + 19 \times 1.007}{19} = \frac{28{,}002.0}{19} = \mathbf{1473.8} \ \checkmark$$

This matches the most abundant labeled peak at 1473.7859 in the inset exactly.

Why resolution matters

Resolving isotope peaks at m/z ≈ 1474 with z = 19 requires a minimum resolving power of:

$$R_\text{min} = \frac{m/z}{\Delta(m/z)_\text{isotope}} = \frac{1474}{1/19} = 1474 \times 19 = \mathbf{28{,}006}$$

The Xevo G3 at 30,000 resolution just clears this threshold. On a lower-resolution instrument (e.g. a single quadrupole or low-res QTof), the isotope peaks would merge into a single unresolved hump and the charge state could not be read this way — you would only see a broad peak and would need to use the adjacent charge state formula instead.

Summary table

Q — Can You Observe the Charge State from the Zoomed-In Peak?

Yes — the charge state is z = 19.

Why the charge state is readable here

At 30,000 resolution, the instrument just resolves individual isotope peaks within the native-state charge state envelope. Since consecutive isotopes differ by exactly 1 Da in mass, their spacing in m/z is:

$$\Delta\left(\frac{m}{z}\right)_\text{isotope} = \frac{1 \ \text{Da}}{z}$$

Inverting this gives the charge state directly:

$$z = \frac{1}{\Delta(m/z)_\text{isotope}}$$

Reading z from the inset

Adjacent isotope peaks in the zoom (e.g. 1473.0884 and 1473.1428) are separated by:

$$\Delta\left(\frac{m}{z}\right) = 1473.1428 - 1473.0884 = 0.0544$$

$$z = \frac{1}{0.0544} = 18.4 \approx \mathbf{19}$$

Cross-check with MW

Using the experimental MW from Q2.2:

$$\frac{m}{z_{19}} = \frac{27{,}982.9 + 19 \times 1.007}{19} = \frac{28{,}002.0}{19} = \mathbf{1473.8} \ \checkmark$$

This matches the most abundant labeled peak at 1473.7859 in the inset exactly.

Why resolution matters

Resolving isotope peaks at m/z ≈ 1474 with z = 19 requires a minimum resolving power of:

$$R_\text{min} = \frac{m/z}{\Delta(m/z)_\text{isotope}} = \frac{1474}{1/19} = 1474 \times 19 = \mathbf{28{,}006}$$

The Xevo G3 at 30,000 resolution just clears this threshold. On a lower-resolution instrument (e.g. a single quadrupole or low-res QTof), the isotope peaks would merge into a single unresolved hump and the charge state could not be read this way — you would only see a broad peak and would need to use the adjacent charge state formula instead.

Summary table

eGFP Tryptic Digest — Peptide Map Prediction

Question 1: Lysines (K) and Arginines (R) in eGFP

Annotated Sequence

Trypsin cleavage sites marked with |. K = Lysine (bold), R = Arginine (italic).

MVSK|GEELFTGVVPILVELDGDVNGHK|FSVSGEGEGDATYGK|LTLK|FICTTGK|
  K              K                  K          K      K

LPVPWPTLVTTLTYGVQCFSR|YPDHMK|QHDFFK|SAMPEGYVQER|TIFFK|
                    R       K      K           R     K

DDGNYK|TR|AEVK|FEGDTLVNR|IELK|GIDFK|EDGNILGHK|
      K   R    K        R    K     K          K

LEYNYNSHNVYIMADK|QK|NGIK|VNFK|IR|
                K   K    K    K  R

HNIEDGSVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSK|DPNEK|R|
                                          K      K  R

DHMVLLEFVTAAGITLGMDELYK|LEHHHHHH
                       K

Note: There are no KP or RP motifs in this sequence, so trypsin cleaves at all 26 K and R residues without exception.

Question 2: Number of Tryptic Peptides

With 26 cleavage sites and 0 missed cleavages:

$$\text{Number of peptides} = \text{cleavage sites} + 1 = 26 + 1 = \mathbf{27 \ \text{peptides}}$$

Full Peptide List (0 Missed Cleavages)

MW calculated as average isotope masses (Da), including water (+18.02 Da).

Notes on specific peptides

Peptide 23 (HNIEDGSVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSK, 41 residues, 4473.84 Da) is unusually long because R(169) and K(210) are separated by a stretch containing no K or R — these large peptides can be difficult to detect by LC-MS due to poor chromatographic retention.

Peptides 12, 19, 22, 25 (TR, QK, IR, R) are very small (1–2 residues) and will likely not be retained on a reversed-phase LC column — they are typically not observed in a standard bottom-up peptide mapping experiment.

Peptide 6 (LPVPWPTLVTTLTYGVQCFSR) contains multiple prolines and W, making it hydrophobic and challenging to detect; however, it contains a Cys residue (from C49 of the full protein), which is typically alkylated (+57 Da, carbamidomethylation) prior to digestion.

Molecular Weight Calculation Using ExPASy PeptideMass

The theoretical molecular weight of the eGFP construct was calculated using the ExPASy PeptideMass tool. The input sequence included the full eGFP sequence, the LE linker, and the C-terminal 6×His purification tag.

The result showed a theoretical pI of 5.90, an average molecular weight of 28,006.60 Da, and a monoisotopic molecular weight of 27,988.96 Da.

eGFP Peptide Map — Questions 4 & 5

Question 4 — Does the Chromatogram Peak Count Match the Prediction?

From the tryptic digest prediction (Question 2): 27 peptides predicted with 0 missed cleavages.

The chromatogram shows fewer peaks than predicted because:

→ Fewer peaks are observed in the chromatogram than the 27 peptides predicted.

Question 5 — Peptide at 2.78 min (Figure 5b)

Step 1 — Most Abundant m/z

$$\frac{m}{z} = \mathbf{525.767}$$

Step 2 — Determine Charge State z from Isotope Spacing (Inset)

Since consecutive isotopes differ by 1 Da in mass:

$$z = \frac{1 \ \text{Da}}{\Delta(m/z)_\text{isotope}} = \frac{1}{0.492} = 2.03 \xrightarrow{\text{round}} \mathbf{z = 2}$$

Step 3 — Calculate [M+H]⁺

First, recover the neutral mass M:

$$M = z \times \frac{m}{z} - z \times 1.00728 = 2 \times 525.767 - 2 \times 1.00728 = 1051.534 - 2.015 = 1049.520 \ \text{Da}$$

Then add one proton for the singly charged form:

$$\boxed{[M+H]^+ = M + 1.00728 = \mathbf{1050.527 \ \text{Da}}}$$

Verification

The main spectrum shows a singly charged peak ($z = 1$) at 1050.524 — matching the calculated value with a difference of only 0.003 Da (~2.8 ppm), confirming $z = 2$ is correct.

eGFP Peptide Map — Questions 6 & 7

Question 6 — Peptide Identification and Mass Accuracy

Peptide Identity

From Question 5, the peptide at 2.78 min has $[M+H]^+ = 1050.527$ Da. Comparing to the predicted tryptic peptide list, this matches:

$$\textbf{FEGDTLVNR} \quad \text{(residues 115–123)}$$

Confirmation from Fragmentation Spectrum (Figure 5c)

The fragmentation spectrum produces a y-ion series that matches FEGDTLVNR exactly:

Mass Accuracy Calculation

$$[M+H]^+_\text{theory} \ (\text{monoisotopic}) = 1050.522 \ \text{Da}$$

$$[M+H]^+_\text{observed} = 1050.524 \ \text{Da}$$

$$\text{Accuracy (ppm)} = \frac{|MW_\text{experiment} - MW_\text{theory}|}{MW_\text{theory}} \times 10^{6 = \frac{|1050.524 - 1050.522|}{1050.522} \times 10}6 = \mathbf{2.3 \ \text{ppm}}$$

This is excellent mass accuracy, consistent with the Waters BioAccord QTof performance specification of < 5 ppm.

Question 7 — Sequence Coverage Confirmed by Peptide Mapping

From Figure 6 (Amino Acid Coverage Map):

$$\boxed{\textbf{88% sequence coverage}}$$

The blue highlighted regions in Figure 6 show the residues confirmed by detected and identified tryptic peptides. The ~12% not covered corresponds to residues in peptides that were either:

• Too small to be retained on the reversed-phase column (e.g. TR, QK, R, IR)
• Not detected above the signal threshold
• Present as missed cleavage products outside the search window