Mar 25, 2026
Phospho-α-Synuclein Staining
- Le Zhang1,
- Pallavi Gopal1
- 1Yale University
Protocol Citation: Le Zhang, Pallavi Gopal 2026. Phospho-α-Synuclein Staining. protocols.io https://dx.doi.org/10.17504/protocols.io.rm7vzeq44vx1/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: February 27, 2026
Last Modified: March 25, 2026
Protocol Integer ID: 244198
Keywords: ASAPCRN, synuclein staining phospho, synuclein, phospho
Funders Acknowledgements:
ASAP
Grant ID: ASAP-000529
Abstract
Phospho-α-Synuclein Staining
Guidelines
1. Subset all neuron cells from the dataset (excitatory and inhibitory).
2. For each gene, sum up all the counts in excitatory/inhibitory neurons in each individual - 3e Dimension: (#gene, 2 * 12).
3. For each individual, the total counts across all genes (summing up both cell types) is calculated as the individual-wise library size.
4. Divide each entry of the matrix from step 2 by the corresponding sample library size from step 3.
5. To calculate the normalized gene expression, utilize the library size normalized counts.
Detailed normalization steps:
- Subset all the neuron cells from the dataset, including excitatory neurons and inhibitory neurons.
- For each gene, sum up all the counts in excitatory and inhibitory neurons within each individual to get the cell-type specific pseudobulk data.
- The individual-wise library size was calculated by summing up the counts among all genes for both neuron types.
- Divide each entry of the pseudobulk data by the sample library size to get the normalized gene expression matrix.
Troubleshooting
Before start
Immunocytochemistry and histopathology were performed on the prefrontal cortex obtained from the same cohort of brains as single nucleus transcriptomics and proteomics. Slabs of frozen prefrontal cortex that remained after sequencing were fixed in 10% neutral buffered formalin overnight at room temperature and then processed into paraffin blocks at the Yale Pathology Tissue Services Histology Core.
Phospho-α-synuclein Staining
Immunocytochemistry and histopathology were performed on the prefrontal cortex obtained from the same cohort of brains as single nucleus transcriptomics and proteomics. Slabs of frozen prefrontal cortex that remained after sequencing were fixed in 10% neutral buffered formalin overnight at room temperature and then processed into paraffin blocks at the Yale Pathology Tissue Services Histology Core.
Hematoxylin and Eosin (H 26E) staining and immunohistochemical staining for phospho-serine-129 (pS129) α-Synuclein (Abcam; ab51253) were performed according to manufacturer’s protocol / product datasheet, and with appropriate controls.
Quantitative scoring of synuclein pathology was performed in a blinded manner. Lewy neurite (LN) score was defined as the average number of pS129 positive Lewy neurites counted in 10 consecutive high-power fields (400x magnification). Similarly, the Lewy body score was defined as the average number of pS129 positive Lewy bodies counted in 10 consecutive high power fields.
The combined quantitative Lewy pathology score was defined as the sum of the LN score and Lewy body score weighted by a factor of 10 (LN+10* Lewy body) in the prefrontal cortex. LN scores in the prefrontal cortex were also subdivided into semiquantitative scoring categories, as follows: “None” was defined LN score of zero; “Mild (+)” was defined as LN score 3e 0 to 2; “Moderate (++)” was defined as LN score 3e 2 to 5; and “Severe (+++)” was defined as LN score 3e 5.
We calculated the Pearson correlation score for all genes expressed in ExN and the top 10% of the genes with positive correlation ( 3e0.795) were analyzed. This unbiased GO analysis identified the top GO term to be highly synapse-specific, including neuron to neuron synapse (q = 0.0005), ion-channel complex (q = 0.0005) and postsynapse organization (q = 0.0009). This enrichment of synapse-related genes with a high pathology correlation suggests that the observed synaptic alterations (Fig. 1G) may contribute spread of pathology.
Subset all neuron cells from the dataset (excitatory and inhibitory).
For each gene, sum up all the counts in excitatory/inhibitory neurons in each individual -> Dimension: (#gene, 2 * 12).
For each individual, the total counts across all genes (summing up both cell types) is calculated as the individual-wise library size.
Divide each entry of the matrix from step 2 by the corresponding sample library size from step 3.
To calculate the normalized gene expression, utilize the library size normalized counts.
Subset all the neuron cells from the dataset, including excitatory neurons and inhibitory neurons.
For each gene, sum up all the counts in excitatory and inhibitory neurons within each individual to get the cell-type specific pseudobulk data.
The individual-wise library size was calculated by summing up the counts among all genes for both neuron types.
Divide each entry of the pseudobulk data by the sample library size to get the normalized gene expression matrix.