Week 10 HW: hw-imaging-and-measurement

Homework: 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.

🎅All projects will be completed in two parts:

1. Natural Photosynthesis Models
2. A computational simulation experiment of de novo protein design that relies on self‑supplied photosynthetic energy and is driven by continuous directed evolution

No directly relevant energy‑coupled evolution system exists. It is important to note that no published system to date has achieved the full loop where functional activity drives ATP regeneration, which in turn drives the evolution of the function itself. All existing continuous evolution systems, regardless of their maturity, rely on external energy input (i.e., normal host cell metabolism) to drive mutation and selection – there is no functional coupling between evolution and energy supply. This is precisely the core innovation space of our project: shifting directed evolution from “externally powered” to “self‑powered by function”.

Please describe all of the elements you would like to measure, and furthermore describe how you will perform these measurements. What are the technologies you will use (e.g., gel electrophoresis, DNA sequencing, mass spectrometry, etc.)? Describe in detail.

Experimental Protocol for Exploring Natural Photosynthesis Principles: Photosynthesis-Chlorophyll Fluorescence System

Experimental Subject

Peanut (Arachis hypogaea) – a plant that exhibits leaf sleep movements (nyctinasty) and follows its own biological rhythm.

Core Instruments

• DUAL-PAM 100 (Chlorophyll fluorescence and P700 measurement system)
• GFS-3000 (Portable photosynthesis and gas exchange system)
• 3010-DUAL Combined Leaf Chamber (for simultaneous measurements)

1. Experimental Objective

This experiment aims to systematically analyze the dynamic response mechanisms of photosynthetic efficiency in peanut leaves. By integrating high-precision photosynthesis-fluorescence measurements with the plant’s intrinsic circadian rhythm, we investigate the relationship between chlorophyll fluorescence kinetics and photosynthetic performance.

Peanut is chosen because it is not only a model crop sensitive to light intensity and CO₂ concentration changes, but also exhibits conspicuous “day-open, night-closed” leaf movements – a visible phenomenon that helps connect the invisible energy flow with physical observation.

2. Background: Circadian Rhythm of Peanut Leaves

Before starting the experiment, understanding the subject’s unique rhythm is essential. The “sleep movements” of peanut leaves often serve as an indicator of plant health. Deeper research reveals:

• Endogenous rhythm: Even under continuous light, the photosynthetic rhythm of peanut has a period of approximately 26 hours.
• Stomatal regulation: The rhythmic changes in photosynthesis are primarily driven by endogenous changes in stomatal aperture.
• Enzyme activity variations: RuBisCO (the key enzyme for carbon fixation) shows highest activity during the normal photoperiod, which correlates with but is not exactly in phase with the peak net photosynthetic rate.

Key implication: Measurements must be taken at different times of the day (e.g., early morning, noon, evening, late night) to fully capture the dynamic photosynthetic behavior of peanut.

3. Core Technologies and Instrument Coupling

3.1 GFS‑3000 Function

Performs macroscopic analysis – precisely controls and monitors the leaf microenvironment while simultaneously measuring gas exchange.

• Controls CO₂ concentration, temperature, humidity, and light intensity (0–3000 µmol·m⁻²·s⁻¹)
• High-precision sensor (CO₂ ±0.2 ppm) calculates net photosynthetic rate (A), stomatal conductance (gₛ), etc.

3.2 DUAL‑PAM‑100 Function

Performs microscopic analysis – measures chlorophyll fluorescence and P700 signals to reveal the state of photosystems (PSII/PSI) and electron transport efficiency.

3.3 Coupling Function (3010‑DUAL Leaf Chamber)

Allows simultaneous acquisition of macroscopic gas exchange data and microscopic photosystem activity under identical environmental conditions.

Advanced functions derived from coupling:

• Combined PSI/PSII parameters
• Dynamic light response curves

4. Detailed Experimental Design and Steps

4.1 Preparation Phase

Plant preparation

• Select healthy peanut plants.
• Acclimate them to the intended experimental environment (e.g., 22–25 °C, 16 h light / 8 h dark) for at least 24 h.

Instrument warm-up

• Turn on and preheat the GFS‑3000 at least 1 h before measurement to stabilize internal temperature.

System coupling

• Dark-adapt a leaf for 30–45 minutes.
• Clamp the leaf into the 3010‑DUAL combined chamber, ensuring a tight seal and correct connections.

4.2 Formal Experiments

Test 1: Photosynthetic induction kinetics

• Measure initial fluorescence (Fo) under weak light (≤1 µmol·m⁻²·s⁻¹).
• Turn on actinic light (300–400 µmol·m⁻²·s⁻¹) and simultaneously start recording with both GFS‑3000 and DUAL‑PAM‑100.

Test 2: Light response curves (multiple)

• After completing the induction protocol, run an automatic sequence of light intensities (low → high → low) to obtain a light response curve (hysteresis) .
• Record net photosynthetic rate vs. light intensity.
• Simultaneously obtain Y(II), NPQ, and other fluorescence parameters at each light level.

Test 3: CO₂ response curve

• Use the GFS‑3000 program under stable light and temperature.
• Expose the leaf to a stepwise change in CO₂ concentration (e.g., 400 → 50 → 1500 ppm).
• Generate an A/Ci curve (CO₂ response).

Test 4: Fluorescence induction and quenching analysis

• Use DUAL‑PAM‑100 saturation pulses to analyze fluorescence quenching components:
  • Photochemical quenching (qP)
  • Non‑photochemical quenching (NPQ)

4.3 Replication and Recording

• Perform each measurement on at least three individual plants for statistical reliability.
• After each change in conditions, wait for the signal to stabilize before recording data.
• Data backup: In addition to automatic instrument storage, manually record key time points and values.

5. Key Considerations

• Warm‑up and calibration: Warm up instruments for at least 15 minutes; for highest precision, allow 1 hour. Refer to technical references:

  • 10.1104/pp.53.6.907
  • 10.3389/fpls.2014.00766
  • 10.1007/s11120-022-00924-z

• Data safety: Always keep manual records alongside automated logs.

• Exploratory extension (recommended): Measure photosynthetic parameters during daytime vs. nighttime (leaf “awake” vs. “asleep” states) and analyze how leaf sleep movements affect gas exchange (GFS‑3000 data) and PSII function (chlorophyll fluorescence data).

6. Expected Outcomes

• Quantified relationship between light intensity, CO₂ concentration, and photosynthetic rate in peanut.
• Dynamic profiles of chlorophyll fluorescence parameters (Fo, Fm, Y(II), NPQ) during induction and under varying light/CO₂.
• Correlation between leaf nyctinasty (sleep movements) and photosynthetic efficiency.
• Validation of the coupled GFS‑3000 + DUAL‑PAM‑100 platform for investigating natural photosynthesis principles.

7. Figure / Schematic Suggestion (Optional)

[Peanut plant] → (Dark adaptation) → [3010-DUAL chamber] 
                                           ↓
                              GFS-3000 ←→ DUAL-PAM-100
                                  ↓              ↓
                            Gas exchange    Fluorescence &
                            (A, gs, Ci)     P700 (Y(II), NPY)

In silico design of a mini de novo protein (e.g., 80‑120 aa) with high predicted stability

Case article analysis

🧓Homework: Waters Part I — Molecular Weight

Based on the predicted amino acid sequence of eGFP (see below) and any known modifications, what is the calculated molecular weight? You can use an online calculator like the one at https://web.expasy.org/compute_pi/

Compute pI/Mw - Results

1. Basic Protein Information

2. Protein 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

Calculation of eGFP Molecular Weight Using the Adjacent Charge State Method

1. Theoretical Target Calculation

Based on the provided amino acid sequence of eGFP with a 6xHis tag (MVSK...HHHHHH), the theoretical values are established as follows:

• Fully Reduced / Unmatured Mw: 28,006.60 Da
• Matured eGFP Mw: During proper folding, the internal GYG triad (positions 65-67) undergoes spontaneous cyclization and oxidation to form the fluorophore. This maturation process releases one water molecule (-18 Da) and two hydrogen atoms (-2 Da), reducing the total molecular weight by 20.0 Da.
• Expected M_theoretical: 27,986.60 Da

2. Step-by-Step Adjacent Charge State Method

In electrospray ionization mass spectrometry (ESI-MS) operating in positive mode, proteins appear as a series of multiple charged peaks (the charge envelope). To calculate the molecular weight from Figure 1, choose any two adjacent peaks and perform the following operations:

Step 1: Record Measured Values from Figure 1

Identify two neighboring peaks from the intact mass spectrum and denote their mass-to-charge ratios as m/z_1 and m/z_2:

• Let m/z_1 be the peak with the larger value (lower charge state, z).
• Let m/z_2 be the peak immediately to its left with the smaller value (higher charge state, z + 1).

(Note: For intact eGFP, these peaks typically appear in the m/z range of 1,100 to 1,500.)

Step 2: Determine the Charge State (z)

Because the peaks are adjacent, their charge states differ by exactly 1. Using the mass of a proton (H+ = 1.0078 Da), the mathematical relationship is defined as:

• Peak 1 equation: m/z_1 = (M + z * 1.0078) / z
• Peak 2 equation: m/z_2 = (M + (z + 1) * 1.0078) / (z + 1)

Solving this system of equations for the lower charge state (z) yields the following standard formula:

z = (m/z_2 - 1.0078) / (m/z_1 - m/z_2)

• 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?

Yes, the charge state can be directly determined from the enlarged peak. > In a high-resolution mass spectrum (such as Orbitrap or Q-TOF), the enlarged peak resolves into individual isotopic peaks within the same charge cluster. The charge state ($z$) can be determined by measuring the distance ($\Delta m/z$) between two adjacent isotopic peaks using the formula $z = 1 / \Delta m/z$.For intact eGFP (~28 kDa), the main charge states typically cluster around $+20$ to $+25$. For instance, if the observed isotopic spacing $\Delta m/z$ is $0.05$, the charge state of that specific peak is $+20$; if the spacing is $0.0476$, the charge state is $+21$.

🧓 Homework: Waters Part III — Peptide Mapping - primary structure

Here is the professional, academic English translation suitable for a mass spectrometry laboratory report or research paper:

1. The Core Difference Between Native and Denatured Protein Conformations (What happens when a protein unfolds?)

• Native Folded State: In its native state, eGFP adopts a highly compact, rigid $\beta$-barrel structure. In this conformation, most of the ionizable basic amino acid residues (such as Lysine, Arginine, and Histidine) that are prone to protonation are buried deep within the hydrophobic core of the protein, leaving only a few exposed on the molecular surface.
• Denatured Unfolded State: When denaturing agents (such as high concentrations of acetonitrile, methanol, or acid) are introduced, the non-covalent interactions (hydrogen bonds, hydrophobic interactions, etc.) stabilizing the tertiary structure of eGFP are disrupted. Consequently, the $\beta$-barrel collapses, and the protein completely unfolds from a compact sphere into a flexible linear peptide chain. As the structure unravels, all the previously buried basic residues become fully exposed to the solvent environment.

2. How to Determine Protein Unfolding Using a Mass Spectrometer

A mass spectrometer detects protein unfolding with high sensitivity by monitoring changes in the mass-to-charge ratio ($m/z$) and the distribution of the charge state envelope.

During the Electrospray Ionization (ESI) process, the more basic residues that are exposed, the more protons ($\text{H}^+$) the protein can accept. Therefore:

$$\text{More unfolded structure} \longrightarrow \text{Higher charge state } (z) \longrightarrow \text{Lower } m/z \text{ value } (m/z = M/z)$$

By tracking the global shift of the charge envelope from a “high $m/z$, low charge” region to a “low $m/z$, high charge” region, the mass spectrometer can accurately determine the unfolding transition of the protein.

3. Major Changes Observed in Native vs. Denatured eGFP Mass Spectra (Figure 2)

When comparing the two direct infusion mass spectra in Figure 2, three prominent differences can be observed:

• Shift in Charge State and Maximum Intensity (Charge State Shift):

• Denatured eGFP (Unfolded): Exhibits a highly charged state. Because the linear chain exposes a vast number of protonation sites, the charge number ($z$) increases significantly (typically clustering around $+20$ to $+35$ or higher). On the spectrum, because the denominator $z$ is large, the peak cluster shifts to the left (lower $m/z$ range, typically between $800 \text{ and } 1500\ m/z$).

• Native eGFP (Folded): Exhibits a lowly charged state. The compact structure shields most ionizable sites, resulting in a much lower charge number ($z$) (typically carrying only $+9$ to $+13$ charges). On the spectrum, the peak cluster shifts to the right (higher $m/z$ range, typically between $2000 \text{ and } 3000\ m/z$ or higher).

• Width of the Charge State Envelope:

• Denatured eGFP: Displays a very broad charge state envelope containing many consecutive charge peaks. This is because the linear peptide chain is highly flexible in a denaturing solution, existing as a dynamic ensemble of various partially unfolded intermediate conformations, which leads to high charge heterogeneity during ionization.

• Native eGFP: Displays a very narrow and highly localized charge state envelope, often consisting of only 3 to 5 major peaks. This reflects the high conformational homogeneity and structural rigidity of the native eGFP protein.

• Minor Mass Shifts After Deconvolution:

• Under ultra-high resolution (if native conditions preserve non-covalent adducts), native mass spectrometry might retain tightly bound non-covalent complexes or buffer components. However, for eGFP, since its mature chromophore is formed through covalent cyclization (resulting in a loss of 20 Da), the calculated baseline molecular weight after deconvolution should remain stable around 27,986.6 Da for both states, unless harsh denaturing conditions cause truncation or loss of specific modifications.

1. What is the Charge State?

For eGFP, which has a molecular weight of approximately $28\text{ kDa}$ (specifically $27,986.60\text{ Da}$ in its mature form), the peak observed at $\sim 2800\ m/z$ in the native mass spectrum corresponds to a charge state of $+10$.

• Mathematical Verification: Using the mass-to-charge ratio formula: $$m/z \approx \frac{M}{z}$$

  When $z = 10$: $$m/z \approx \frac{27,986.60}{10} \approx 2798.66\ m/z$$

  This aligns perfectly with the peak observed around $\sim 2800\ m/z$ in Figure 3. Therefore, this peak represents the native eGFP molecular ion carrying 10 positive charges, designated as $[M + 10\text{H}]^{10+}$.

2. How to Determine the Charge State in the Enlarged Spectrum (Figure 3)

Using a high-resolution instrument like the Waters Xevo G3-QTof, when you zoom in on a specific macro-peak under native conditions, you can accurately determine or verify the charge state using the following two standard methodologies:

Method A: Observing the Isotopic Spacing (The Direct Visual Approach)

If the resolution in Figure 3 is high enough to resolve the fine structure, the single macro-peak will split into a cluster of individual isotopic peaks (Isotope Cluster).

• Principle: Each adjacent isotopic peak differs by exactly one neutron (a nominal mass difference of $\Delta M \approx 1\text{ Da}$). Therefore, their horizontal spacing ($\Delta m/z$) on the mass spectrum is strictly determined by the charge state ($z$) through the formula: $$z = \frac{1}{\Delta m/z}$$

• Application to this peak: For this specific peak, measuring the distance between two consecutive isotopic sub-peaks will yield a $\Delta m/z$ value of exactly $0.1$. $$z = \frac{1}{0.1} = 10$$ By calculating this fine isotopic interval, the charge state is directly identified as $+10$.

Method B: Utilizing the Adjacent Charge State Method (The Macro-Peak Approach)

If the isotopic resolution is not visible in Figure 3 (i.e., the peak remains a single smooth envelope), you must determine the charge state by comparing it with its immediate neighboring macro-peaks from the broader spectrum:

1. Identify the adjacent peak immediately to the left of the $\sim 2800\ m/z$ peak (which typically appears around $\sim 2544.2\ m/z$, representing the $+11$ charge state).

2. Substitute the $m/z$ values of both neighboring peaks into the adjacent charge state formula: $$z = \frac{m/z_{\text{smaller}} - 1.0078}{m/z_{\text{larger}} - m/z_{\text{smaller}}}$$

3. Calculation: $$z = \frac{2544.24 - 1.0078}{2798.66 - 2544.24} = \frac{2543.2322}{254.42} \approx 10$$

This mathematically confirms that the target peak at $\sim 2800\ m/z$ carries a charge state of $10$.

🧓 Homework: Waters Part III — Peptide Mapping - primary structure

Lysine (K): There are 20 Lysine residues.

Arginine (R): There are 6 Arginine residues.

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

PeptideMass - Results

1. General Information & Submission Parameters

📊 Protein Properties Summary

• Theoretical pI: 5.90
• Molecular Weight (Average Mass): 28006.60 Da
• Molecular Weight (Monoisotopic Mass): 27988.96 Da

2. Input Full 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

Peptide masses for your input sequence

| Mass ($[M+H]^+$) | Position | #MC | Modifications | Peptide Sequence |
| :--- | :--- | :--- | :--- | :--- |
| **4472.1752** | 170-210 | 0 | None | `HNIEDGSVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSK` |
| **2566.2931** | 217-239 | 0 | None | `DHMVLLEFVTAAGITLGMDELYK` |
| **2437.2608** | 5-27 | 0 | None | `GEELFTGVVPILVELDGDVNGHK` |
| **2378.2577** | 54-74 | 0 | None | `LPVPWPTLVTTLTYGVQCFSR` |
| **1973.9062** | 142-157 | 0 | None | `LEYNYNSHNVYIMADK` |
| **1503.6597** | 28-42 | 0 | None | `FSVSGEGEGDATYGK` |
| **1266.5783** | 87-97 | 0 | None | `SAMPEGYVQER` |
| **1083.4979** | 240-247 | 0 | None | `LEHHHHHH` |
| **1050.5214** | 115-123 | 0 | None | `FEGDTLVNR` |
| **982.4952** | 133-141 | 0 | None | `EDGNILGHK` |
| **821.3940** | 81-86 | 0 | None | `QHDFFK` |
| **790.3552** | 75-80 | 0 | None | `YPDHMK` |
| **769.3913** | 47-53 | 0 | None | `FICTTGK` |
| **711.2944** | 103-108 | 0 | None | `DDGNYK` |
| **655.3813** | 98-102 | 0 | None | `TIFFK` |
| **602.2780** | 211-215 | 0 | None | `DPNEK` |
| **579.3137** | 128-132 | 0 | None | `GIDFK` |
| **507.2925** | 164-167 | 0 | None | `VNFK` |
| **502.3235** | 124-127 | 0 | None | `IELK` |

• According to the LC-MS chromatogram presented in Figure 5a, a total of 19 major chromatographic peaks can be clearly distinguished within the 0.5 to 6.0-minute retention time window. This count applies a relative abundance threshold of >10% to successfully filter out baseline chemical noise and minor artifacts. These resolved peaks correspond directly to the major, high-abundance tryptic peptide fragments derived from the digested eGFP construct

• The number of peaks observed in the actual chromatogram is typically lower than, or does not fully match, the theoretically predicted number of peptides

• 2.53 ppm

• 88%

🧓 Homework: Waters Part IV — Oligomers

Characterization of Keyhole Limpet Hemocyanin (KLH) Oligomeric States via CDMS

1. Theoretical Mass Calculation and Spectrum Peak Mapping

Because Keyhole Limpet Hemocyanin (KLH) forms massive megadalton (MDa) multi-subunit assemblies, standard electrospray ionization mass spectrometry produces highly heterogeneous, unresolved charge states. Charge Detection Mass Spectrometry (CDMS) circumvents this limitation by tracking both the charge and m/z of individual single particles simultaneously, enabling direct macro-molecular mass measurements.

To locate each oligomeric species on the CDMS mass spectrum axis (x-axis, calibrated in millions of Daltons, MDa, or kilodaltons, kPa), we multiply the base subunit mass from Table 1 by the total number of combined subunits (oligomeric index):

2. Structural Analysis of Species along the CDMS Profile (Figure 7)

When examining the single-particle mass histogram in Figure 7, the peaks resolve sequentially from left to right across the mass distribution axis. They correspond to the following native quaternary arrangements:

1. Far Left Cluster (around 3.40 MDa): Matches the 7FU Decamer. This peak represents a single, isolated cylindrical homo-decameric ring assembly that exists as a discrete species or has dissociated from larger structures.
2. Central Dominant Peak (around 8.00 MDa): Matches the 8FU Didecamer. In native biochemistry, the 8FU isoform prefers to assemble into a massive, stable double-ring hollow cylinder composed of 20 total structural subunits, making it the most thermodynamically favored and high-abundance configuration under physiological conditions.
3. Middle-Right Shoulder/Peak (around 12.00 MDa): Matches the 8FU 3-Decamer. This species corresponds to a tri-decamer configuration formed by the stacking of three decameric rings (a didecamer bound with an extra single-ring decamer unit).
4. Far Right Tail/Peak (around 16.00 MDa): Matches the 8FU 4-Decamer. This massive multi-didecamer complex consists of 40 individual 8FU polypeptide subunits organized into an elongated, continuous double-didecamer tubular stack.

(Note: Depending on the specific software export configuration used in Figure 7, the horizontal mass axis may be labeled either as nominal Daltons in millions, written as ‘Mass (MDa)’, or thousands, written as ‘Mass (kDa)’. Please verify your spectrum labels to mark the positions cleanly at 3.4, 8.0, 12.0, and 16.0 respectively.)

Intact LC-MS Mass Accuracy Analysis (eGFP)

1. Data Summary Table

Below is the summary table for your intact LC-MS experiment of the eGFP construct. Please insert your deconvoluted or calculated experimental mass ($M_{\text{observed}}$) into the appropriate row based on the construct’s state:

2. Core ppm Mass Error Equation

In high-resolution mass spectrometry, mass accuracy is strictly evaluated using ppm (Parts Per Million). To determine your specific experimental error, substitute your values into the standard equation below:

$$\text{Mass Error (ppm)} = \left( \frac{M_{\text{observed}} - M_{\text{theoretical}}}{M_{\text{theoretical}}} \right) \times 10^6$$

• $M_{\text{observed}}$: The uncharged, intact molecular weight obtained after deconvolution (or calculated via the adjacent charge state method) from your Intact LC-MS spectrum.
• $M_{\text{theoretical}}$: The theoretical sequence mass calculated from the primary amino acid chain (27,986.60 Da for the matured form, or 28,006.60 Da for the unmatured form).

3. Step-by-Step Calculation Guide for Lab Reports

You can adapt the following mathematical format to display your specific steps in your assignment (demonstrated below using an example observed value of $27,986.44\text{ Da}$ for matured eGFP):

1. Calculate the Absolute Mass Delta ($\Delta M$): $$\Delta M = M_{\text{observed}} - M_{\text{theoretical}}$$ $$\Delta M = 27,986.44 - 27,986.60 = -0.16\text{ Da}$$

2. Calculate the Ratio Relative to the Theoretical Mass: $$\text{Ratio} = \frac{-0.16}{27,986.60} \approx -0.000005717$$

3. Multiply by One Million ($10^6$) to Obtain the ppm Error: $$\text{Mass Error} = -0.000005717 \times 1,000,000 = -5.72\text{ ppm}$$

💡 Academic Thresholds: For high-performance instruments such as the Waters Xevo G3-QTof, an intact protein mass error within **