Week 10 HW: Advanced Imaging & Measurement Technology

Final Project

Please identify at least one (ideally many) aspect(s) of your project that you will measure. It could be the mass or sequence of a protein, the presence, absence, or quantity of a biomarker, etc.

1. molecular validation (to confirm whether the Twist plasmids are correct and transformed properly) through the presence of the sender and receiver plasmid, correct insert size and sequence identity, then successful bacterial transformation
2. functional signalling validation / AHL sensing ability through receiver activation threshold, GFP expression strength, dose-response curve, signal saturation
3. spatial pattern formation to measure whether LuxI actually produces AHL through sender-generated AHL activity, effective AHL equivalent concentration, and hopefully signalling consistency between cultures
4. ML/CAD dataset features through OT-2 plate maps, fluorescence reads and metadata logs

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

The project will measure genetic construct integrity, quorum-sensing response strength, sender-derived signalling output, and spatial cellular automata pattern formation

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

1. Plasmid integrity will be measured using agarose gel electrophoresis to confirm the expected insert sizes of the LuxI sender and LuxR-sfGFP receiver constructs.

2. Functional LuxR receiver performance will be quantified by exposing transformed receiver E. coli to a defined dilution series of 3-oxo-C6-HSL and measuring GFP fluorescence over time using a handmade(! to plan) fluorescence plate reader

3. LuxI sender activity will be measured indirectly by collecting cell-free sender supernatant and applying it to the receiver strain, using the previously generated AHL-GFP calibration curve to understand the effective signalling molecule concentration.

4. Spatial pattern formation relevant to biological cellular automata will be measured using Opentrons (OT-2) automated plate layouts combined with fluorescence time-lapse imaging. Metrics including activation radius, neighbourhood response, and endpoint fluorescence distribution will then be extracted and used as training data for ML-enhanced CAD prediction in Aim 2.

Waters Part I — Molecular Weight

1. Calculated molecular weight

Compute pI/Mw - Results Theoretical pI/Mw (average)

Sequence: 10 20 30 40 50 60 MVSKGEELFT GVVPILVELD GDVNGHKFSV SGEGEGDATY GKLTLKFICT TGKLPVPWPT

    70         80         90        100        110        120 

LVTTLTYGVQ CFSRYPDHMK QHDFFKSAMP EGYVQERTIF FKDDGNYKTR AEVKFEGDTL

   130        140        150        160        170        180 

VNRIELKGID FKEDGNILGH KLEYNYNSHN VYIMADKQKN GIKVNFKIRH NIEDGSVQLA

   190        200        210        220        230        240 

DHYQQNTPIG DGPVLLPDNH YLSTQSALSK DPNEKRDHMV LLEFVTAAGI TLGMDELYKL

EHHHHHH

Theoretical pI/Mw: 5.90 / 28006.60

2. Calculated molecular weight of the eGFP using the adjacent charge state approach described in the recitation

For my data I chose peaks at $m/z = 933.8044$ and $m/z = 966.0037$

For $n$ and $n-1$:

$z = 30$ and $z = 29$:

$m/z = 933.8044$ is $z = 30$

$m/z = 966.0037$ is $z = 29$

MW ($z = 30$):

Super close to the theoretical MW of $28,006.60\ \text{Da}$ from the first step

3. accuracy of the measurement using the deconvoluted MW from 2.2 and the predicted weight of the protein from 2.1

3. Can you observe the charge state for the zoomed-in peak in the mass spectrum for the intact eGFP? If yes, what is it? If no, why not?

No, as the protein is in its denatured state at a high charge state (32+)

Waters Part III — Peptide Mapping - primary structure

1. Lysines (K) and Arginines (R) are in eGFP

K R

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

K=20 R=6

2. Peptides generated from tryptic digestion of eGFP?

Theoretical pI: 5.90
Mw (average mass): 28006.60
Mw (monoisotopic mass): 27988.96

Predicted peptides = 19

3. Based on the LC-MS data for the Peptide Map data generated in lab (please use Figure 5a as a reference) how many chromatographic peaks do you see in the eGFP peptide map between 0.5 and 6 minutes? You may count all peaks that are >10% relative abundance.

-5.

4. Assuming all the peaks are peptides, does the number of peaks match the number of peptides predicted from question 2 above? Are there more peaks in the chromatogram or fewer?

Observed LC peaks = ~19

Observed peaks are about the same as predicted

5. Identify the mass-to-charge of the peptide shown in Figure 5b. What is the charge of the most abundant charge state of the peptide (use the separation of the isotopes to determine the charge state). Calculate the mass of the singly charged form of the peptide based on its m/z and z

Main peptide peak = 525.76712

Spacing = 0.5 m/z, => most abundant charge state is 2+. The singly charged mass is 1050.52 Da

Charge = +2 [ M + H ] + [M+H] + = 1050.52145 Da [ M + H ] + [M+H] + = 1050.52438 Da

Identified peptide: FEGDTLVNR

the error is about 2.8 ppm

6. Identify the peptide from PeptideMass

FEGDTLVNR has a theoretical monoisotopic mass of 1050.52143 Da

7. 88 is the percentage of the sequence that is confirmed by peptide mapping

Waters Part IV — Oligomers

7FU Decamer = 3.40 MDa

8FU Didecamer = 8 MDa

8FU 3-Decamer = 12 MDa

8FU 4-Decamer = 16 MDa

Waters Part V — Did I make GFP?

Yes!