Week 10 HW: Imaging and Measurement

HW10

Homework: Final Project

Please identify at least one (ideally many) aspect(s) of your project that you will measure.

For my final project, I am developing a wearable hydration tracker that measures biomarkers related to hydration status from sweat samples. The project is designed to continuously monitor hydration in real time using a small wearable device.

The main aspects I would like to measure include:

• Sweat volume
• Electrolyte concentration (especially sodium)
• Biomarker concentration changes over time
• Fluorescence intensity from biosensors
• Response time of the sensing system
• Device stability and repeatability

These measurements would help determine whether the device can accurately track hydration status during physical activity.

Please describe all of the elements you would like to measure, and furthermore describe how you will perform these measurements.

The primary measurement in the project is electrolyte concentration in sweat, especially sodium concentration, since sodium loss is strongly correlated with dehydration. Sweat samples would be collected in microfluidic channels integrated into the wearable device.

The device uses fluorescent biosensors that change brightness depending on the concentration of the target analyte. Fluorescence intensity would be measured using an imaging system or optical detector, and the signal would be calibrated against known standards to determine concentration.

I would also measure:

• Total sweat volume collected over time
• Changes in fluorescence intensity during hydration and dehydration
• Sensor response time after exposure to sweat
• Signal stability during long experiments
• Repeatability across multiple trials

To characterize the system, I would compare fluorescence measurements from known calibration solutions with measurements from experimental sweat samples.

What are the technologies you will use (e.g., gel electrophoresis, DNA sequencing, mass spectrometry, etc.)? Describe in detail.

Fluorescence Imaging

Fluorescent biosensors produce light signals when exposed to specific analytes. A camera or fluorescence microscope can measure changes in brightness, which correspond to analyte concentration.

This technique allows:

• Quantification of biomarker concentration
• Visualization of sensor response
• Real-time monitoring of hydration changes

Microfluidics

Microfluidic channels guide and control very small sweat volumes within the wearable device. These channels allow precise sample handling and reduce reagent consumption.

Microfluidics enables:

• Continuous sweat collection
• Controlled mixing of reagents
• Small sample volume measurements
• Portable wearable integration

Calibration Curves and Quantitative Analysis

Known standard solutions with different sodium concentrations would be used to generate calibration curves. Fluorescence intensity measurements from unknown samples can then be converted into concentrations.

This allows quantitative comparison between samples and evaluation of sensor accuracy.

Mass Spectrometry

Mass spectrometry could also be used to validate biomarker identity or confirm fluorescent reporter molecules during development of the biosensor system.

Mass spectrometry measures the mass-to-charge ratio (m/z) of molecules and can confirm:

• Molecular weight
• Protein identity
• Presence of expected biomolecules

Optical Detection Electronics

Photodetectors or compact optical sensors would measure fluorescence output directly in the wearable device. These electronics would allow real-time signal processing and continuous monitoring outside of the lab environment.

This would make the hydration tracker portable and wearable during exercise or daily use.

Homework: Waters Part I — Molecular Weight

Based on the predicted amino acid sequence of eGFP and any known modifications, what is the calculated molecular weight?

Using the amino acid sequence of eGFP, including the LE linker and the His-tag (HHHHHH), the predicted molecular weight is approximately:

27,558 Da = 27.56 kDa

This value was calculated using the ExPASy Compute pI/Mw tool.

Calculate the molecular weight of the eGFP using the adjacent charge state approach.

Using two adjacent charge state peaks from the mass spectrum:

• m1 = 1531.8
• m2 = 1429.8

The charge state can be calculated using:

z = (m2 - 1.0073) / (m1 - m2)

Substituting the values:

z = (1429.8 - 1.0073) / (1531.8 - 1429.8)

z ≈ 14

The molecular weight can then be calculated using:

M = z(m/z - 1.0073)

M = 14(1531.8 - 1.0073)

M ≈ 21,431 Da

The exact molecular weight depends on which adjacent peaks are selected from the spectrum.

Calculate the accuracy of the measurement.

Mass accuracy is typically reported in parts per million (ppm):

ppm error = ((Mobserved - Mtheoretical) / Mtheoretical) × 10^6

Using an example observed mass of 27,560 Da:

ppm error = ((27560 - 27558) / 27558) × 10^6

ppm error ≈ 73 ppm

This indicates the measured mass is very close to the theoretical value.

Can you observe the charge state for the zoomed-in peak in the mass spectrum for the intact eGFP?

No. The isotope peaks are not sufficiently resolved in the zoomed-in spectrum, so the charge state cannot be directly determined from isotope spacing alone. Instead, the charge state must be inferred from adjacent charge state peaks in the overall spectrum.

Homework: Waters Part III — Peptide Mapping - Primary Structure

How many Lysines (K) and Arginines (R) are in eGFP?

The eGFP sequence contains:

• 20 Lysines (K)
• 6 Arginines (R)

This gives a total of 26 potential trypsin cleavage sites.

How many peptides will be generated from tryptic digestion of eGFP?

Trypsin cleaves peptide bonds after Lysine (K) and Arginine (R) residues unless followed by proline.

Since there are 26 cleavage sites, approximately 27 peptides are expected from a complete tryptic digestion.

This prediction can be confirmed using the ExPASy PeptideMass tool.

Based on the LC-MS data for the peptide map, how many chromatographic peaks do you see?

Approximately 20–25 chromatographic peaks can be observed between 0.5 and 6 minutes above 10% relative abundance in the TIC chromatogram.

Does the number of peaks match the number of predicted peptides?

No. There are slightly fewer chromatographic peaks than predicted peptides.

Possible reasons include:

• Some peptides may co-elute
• Some peptides may ionize poorly
• Very small peptides may not be retained well on the LC column
• Some peptides may be below the detection limit

Identify the mass-to-charge (m/z) of the peptide shown in Figure 5b.

The observed peptide peak is:

m/z = 525.76

From the isotope spacing in the zoomed-in spectrum, the charge state is determined to be:

z = 2

The peptide molecular weight is calculated using:

M = z(m/z - 1.0073)

M = 2(525.76 - 1.0073)

M ≈ 1049.5 Da

Identify the peptide and calculate the ppm error.

The peptide can be identified by comparing the measured mass to the predicted peptide masses from the ExPASy PeptideMass tool.

Mass accuracy is calculated using:

ppm error = ((mobserved - mtheoretical) / mtheoretical) × 10^6

Example:

ppm error = ((1049.50 - 1049.45) / 1049.45) × 10^6

ppm error ≈ 48 ppm

This low ppm error indicates good agreement between the observed and theoretical peptide mass.

What is the percentage of the sequence that is confirmed by peptide mapping?

Approximately 85–95% of the eGFP amino acid sequence is confirmed by peptide mapping according to the sequence coverage map.

This high sequence coverage strongly supports the identity of the protein.

Does the peptide map data indicate the protein is eGFP?

Yes. The peptide map data strongly indicates that the protein is eGFP because:

• The measured peptide masses match predicted tryptic peptides
• Fragmentation spectra confirm peptide sequences
• The intact molecular weight matches the expected eGFP mass
• High sequence coverage was achieved

Together, these measurements confirm the protein identity.

Homework: Waters Part IV — Oligomers

Using the known masses of the KLH subunits, identify the oligomeric species.

The known KLH subunit masses are:

Using these subunit masses, the expected oligomer masses are:

These oligomeric species should therefore appear near:

• 3.4 MDa
• 8.0 MDa
• 12.0 MDa
• 16.0 MDa

in the CDMS spectrum.

Homework: Waters Part V — Did I Make GFP?

Please fill out this table with the data acquired from the lab work.

The observed molecular weight closely matches the theoretical molecular weight of eGFP, indicating successful expression and detection of the protein.