Capturing Cardiomyocyte Cell-to-Cell Heterogeneity via Shotgun Single Cell Top-Down Proteomics

This study introduces a shotgun single-cell top-down proteomics strategy that successfully profiles diverse proteoforms in individual mouse cardiomyocytes, revealing substantial cell-to-cell molecular heterogeneity and establishing a powerful tool for understanding cardiac cellular identity and physiology.

The Gist

Imagine your heart is a bustling city made of millions of tiny workers called cardiomyocytes (heart muscle cells). For a long time, scientists thought these workers were all identical clones, like a factory assembly line where every worker wears the exact same uniform and does the exact same job.

However, this new research reveals that the city is actually much more chaotic and interesting than we thought. Even though these cells look the same on the outside, inside, they are all wearing different "outfits" and carrying different "tools."

Here is a breakdown of what the scientists discovered, using simple analogies:

1. The Problem: The "Recipe" vs. The "Dish"

Scientists have been great at reading the cell's instruction manual (DNA/RNA). It's like reading a recipe book. But knowing the recipe doesn't tell you exactly what the final dish tastes like.

• The Reality: The real workers are proteins. And proteins aren't static; they get modified. They might get a "sticker" (a chemical tag) added, a "zipper" (a cut) taken off, or a "paint job" (a chemical change).
• The Challenge: These modified versions are called proteoforms. Previous methods were like taking a whole cake, smashing it into crumbs, and trying to guess the original recipe from the crumbs. You lose the information about how the ingredients were put together.

2. The Solution: The "Whole Cake" Approach

The researchers developed a new super-powerful microscope technique called Shotgun Single Cell Top-Down Proteomics.

• The Analogy: Instead of smashing the cake, they gently lift the entire cake (the intact protein) out of the box and examine it whole.
• The "Shotgun" Part: They don't just look at one cake; they look at individual cells one by one. They took 13 separate heart cells from a mouse, isolated them, and analyzed them without mixing them together.
• The Magic Trick: They used a special "lysis buffer" (a cleaning solution made of strong solvents) that acts like a gentle but effective solvent. It dissolves the cell wall and prepares the proteins for the machine without breaking them apart first. This is crucial because if you break the protein, you lose the evidence of its unique modifications.

3. What They Found: The "Outfit" Diversity

When they looked at these 13 heart cells, they found something surprising:

• The Core Team: All the cells had the same basic "uniforms" (the main proteins). This is the "core proteome."
• The Unique Flair: But the details were totally different. One cell might have a protein with a "trimethyl" sticker, while its neighbor has the same protein with a "phosphorylation" sticker, or maybe a "truncated" version (a protein that got chopped short).
• The Result: They found 165 different versions of proteins across just 13 cells. It's like walking into a room of 13 people wearing the same t-shirt, but realizing that 10 of them have different pins, patches, or rolled-up sleeves, and no two are exactly alike.

4. Specific Discoveries: The "Secret Codes"

The researchers found specific "codes" on heart proteins that might explain how the heart works (or fails):

• The Myosin Light Chain (MLC-2): This is a critical muscle protein. They found it with a "trimethyl" tag and a "phosphorylation" tag at the same time. This is like finding a car that has both a racing stripe and a turbocharger installed simultaneously. This combination might control how hard the heart muscle squeezes.
• The Mitochondrial Workers: They found tags on the proteins that power the cell's engine (mitochondria). For example, they found a "succinylation" tag on a protein called Qcr7. This might be a clue to why heart cells get tired or fail in diseases like heart failure.

5. Why This Matters

Think of the heart as a symphony orchestra.

• Old View: We thought every violinist played the exact same note at the exact same volume.
• New View: This study shows that every violinist is actually playing a slightly different note, with a different vibrato, and a different bow speed.

By understanding these tiny differences (heterogeneity), doctors might one day be able to:

• Diagnose diseases earlier: Spotting a "bad outfit" on a single cell before the whole heart starts failing.
• Create better drugs: Designing medicines that fix specific "outfits" rather than treating the whole heart as a single block.

In a Nutshell

This paper is a breakthrough because it gave scientists a high-resolution camera to look at individual heart cells and see their unique molecular identities. It proves that no two heart cells are exactly the same, and understanding these tiny differences is the key to unlocking the secrets of heart disease and health.

Technical Summary

1. Problem Statement

• Limitation of Current Technologies: While single-cell RNA sequencing (scRNA-seq) effectively reveals transcriptomic variability, it fails to capture the functional state of cells. Proteins, particularly their diverse structural variants known as proteoforms (arising from post-translational modifications [PTMs], sequence variations, and truncations), are the primary functional effectors in cells.
• Shortcomings of Bottom-Up Proteomics: Traditional bottom-up proteomics (digesting proteins into peptides) loses information regarding the co-occurrence of multiple PTMs on the same protein molecule and suffers from the "protein inference problem," making it impossible to fully characterize proteoform diversity.
• Technical Barriers in Single-Cell Top-Down Proteomics (SC-TDP): Analyzing intact proteins from single cells is extremely challenging due to:
  • Extremely low sample input (picogram to femtogram levels).
  • Loss of material during sample handling and transfer.
  • Difficulty in separating and fragmenting intact proteins effectively.
  • Limited throughput and sensitivity of existing methods.

2. Methodology

The authors developed a robust Shotgun Single-Cell Top-Down Proteomics (SC-TDP) workflow specifically optimized for mouse cardiomyocytes.

• Sample Preparation & Lysis:

  • Isolation: Individual cardiomyocytes were isolated from mouse hearts and sorted into a 384-well plate using a CellenONE X1 device.
  • Direct Lysis: To minimize sample loss, cells were lysed directly in the well.
  • Optimized Buffer: A specialized lysis buffer containing Trifluoroethanol (TFE) and Dimethyl Sulfoxide (DMSO) in 5% formic acid was used. This mixture solubilizes proteins, induces denaturation, and preserves proteoform integrity while enhancing MS sensitivity.
  • Workflow: The workflow eliminated sample transfer steps, moving directly from the 384-well plate to the LC-MS system.

• Chromatography & Mass Spectrometry:

  • LC: Separation was performed on a nanocapillary column packed with 2.7 µm C4 reversed-phase resin to enhance separation efficiency for small sample volumes.
  • MS Instrument: An Orbitrap Fusion Lumos mass spectrometer was used.
  • Fragmentation Strategy: A hybrid fragmentation approach was employed within the same scan:
    • EThcD (Electron-Transfer/Higher-Energy Collision Dissociation): Provided superior backbone fragmentation and PTM localization.
    • HCD (Higher-Energy Collision Dissociation): Used to mitigate the long duty cycle of EThcD, ensuring faster acquisition.
  • Data Acquisition: Data-dependent acquisition (DDA) with dynamic exclusion. The method utilized high-resolution MS/MS (15k–60k resolving power) and averaged multiple microscans to improve signal-to-noise ratios.

• Data Analysis:

  • Raw data was processed using ProSight PD 4.5 software.
  • A three-node search strategy was used against a Mus musculus database:
    1. Wide mass tolerance (200 Da) for unknown modifications.
    2. Narrow mass tolerance (2.2 Da) for known proteoforms.
    3. Specific search for truncated proteoforms.
  • False Discovery Rate (FDR) was controlled at 1% for both protein and proteoform levels.

3. Key Contributions

• Novel SC-TDP Platform: Established a high-throughput, ultrasensitive, and robust platform capable of profiling intact proteoforms from single cardiomyocytes without prior purification.
• Hybrid Fragmentation Optimization: Demonstrated that combining EThcD and HCD in a single scan significantly improves proteoform coverage and backbone fragmentation efficiency compared to using either method alone.
• Chemical Optimization: Validated the use of TFE/DMSO-based lysis buffers for single-cell top-down analysis, ensuring protein solubility and preventing precipitation in low-volume samples.
• First Evidence of Specific Modifications: Provided the first identification of several specific proteoforms in single cardiomyocytes, including:
  • MLC-2 (Myosin Light Chain 2): Concurrent N-terminal trimethylation (A1) and T51 phosphorylation on the same backbone.
  • MYL3: N-terminal trimethylation.
  • Qcr7: Lysine-11 succinylation.
  • COX6c: N-terminal acetylation.

4. Results

• Scale of Analysis: The study analyzed 13 individual cardiomyocytes (sized 61.04–67.92 µm) and a bulk tissue control.
• Proteoform Identification:
  • Total: Identified 57 proteins represented by 165 distinct proteoforms across the single cells.
  • Bulk Control: The bulk sample yielded 41 proteins and 83 proteoforms, validating the workflow's consistency.
  • Mass Range: Detected biomolecules ranged from ~2 to 22 kDa.
• Heterogeneity Findings:
  • Protein Level: High overlap in protein identity across cells (conserved core proteome).
  • Proteoform Level: Significant cell-to-cell heterogeneity. While core proteins were shared, the specific proteoform composition varied substantially between individual cells.
  • Quantitative Variation: The number of detected proteoforms varied by cell size/quality (e.g., 70 proteoforms in the largest cell vs. 18 in a smaller cell), but even cells of similar size showed unique proteoform signatures.
• Specific Biological Insights:
  • MLC-2: Confirmed trimethylation at A1 (distinguishing it from acetylation via mass shift and diagnostic ions) and its co-occurrence with phosphorylation at T51. This suggests complex combinatorial regulation of contractile function.
  • Mitochondrial Proteins: Identified succinylation on Qcr7 and acetylation on COX6c, linking proteoform diversity to mitochondrial function and potential metabolic dysregulation in heart failure.

5. Significance

• Unprecedented Molecular Resolution: This study moves beyond protein abundance to define the functional landscape of single cells. It reveals that cellular identity and physiology are dictated not just by which proteins are present, but by the specific proteoform mix (PTMs, truncations) within each cell.
• Cardiac Biology: The findings highlight that cardiomyocytes are not uniform; they exist in distinct molecular configurations. This heterogeneity may underlie specialized roles in cardiac physiology and the progression of diseases like heart failure.
• Biomarker Potential: The identified proteoforms (e.g., specific phosphorylation or succinylation states) serve as potential early biomarkers for cardiac dysfunction, detectable before overt cell damage occurs.
• Future Impact: The developed SC-TDP strategy provides a transformative tool for investigating intercellular variability, disease mechanisms, and therapeutic targets in the heart and other tissues, paving the way for precision medicine based on proteoform signatures.