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. 2022 Sep 2;21(9):2237-2245.
doi: 10.1021/acs.jproteome.2c00409. Epub 2022 Aug 2.

In-Depth Mass Spectrometry-Based Proteomics of Formalin-Fixed, Paraffin-Embedded Tissues with a Spatial Resolution of 50-200 μm

Affiliations

In-Depth Mass Spectrometry-Based Proteomics of Formalin-Fixed, Paraffin-Embedded Tissues with a Spatial Resolution of 50-200 μm

Andikan J Nwosu et al. J Proteome Res. .

Abstract

Formalin-fixed, paraffin-embedded (FFPE) tissues are banked in large repositories to cost-effectively preserve valuable specimens for later study. With the rapid growth of spatial proteomics, FFPE tissues can serve as a more accessible alternative to more commonly used frozen tissues. However, extracting proteins from FFPE tissues is challenging due to cross-links formed between proteins and formaldehyde. Here, we have adapted the nanoPOTS sample processing workflow, which was previously applied to single cells and fresh-frozen tissues, to profile protein expression from FFPE tissues. Following the optimization of extraction solvents, times, and temperatures, we identified an average of 1312 and 3184 high-confidence master proteins from 10 μm thick FFPE-preserved mouse liver tissue squares having lateral dimensions of 50 and 200 μm, respectively. The observed proteome coverage for FFPE tissues was on average 88% of that achieved for similar fresh-frozen tissues. We also characterized the performance of our fully automated sample preparation and analysis workflow, termed autoPOTS, for FFPE spatial proteomics. This modified nanodroplet processing in one pot for trace samples (nanoPOTS) and fully automated processing in one pot for trace sample (autoPOTS) workflows provides the greatest coverage reported to date for high-resolution spatial proteomics applied to FFPE tissues. Data are available via ProteomeXchange with identifier PXD029729.

Keywords: FFPE; LCM; autoPOTS; mass spectrometry; nanodroplet; spatial proteomics.

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Conflict of interest statement

The authors declare the following competing financial interest(s): RTK has a financial interest in MicrOmics Technologies, which provided nanoelectrospray emitters for this study.

Figures

Figure 1.
Figure 1.
Overview depicting the processing and analysis of microdissected FFPE tissues using either the nanoPOTS (blue arrows) or autoPOTS (red arrows) workflows. For autoPOTS, samples are transferred to a 384-well plate, prepared in an automated fashion using the Opentrons OT-2 liquid handler and analyzed by LC-MS using a commercial autosampler. For nanoPOTS, the excised tissue samples are transferred to custom nanowell chips, prepared using an in-house-developed robotic platform and manually injected for LC-MS analysis.
Figure 2.
Figure 2.
Peptide groups (left) and master proteins (right) identified from 200 μm × 200 μm tissue samples. Specific extraction conditions are shown in Figure 1. N = 4 for each condition.
Figure 3.
Figure 3.
Comparison between frozen and FFPE mouse liver tissues obtained from the same mouse. (Left) Pearson correlation plot between fresh-frozen and FFPE tissue types. (Right) Venn diagram showing the overlap of high-confidence master proteins between fresh-frozen and FFPE tissues. Only proteins identified in all four replicates, including those identified with MBR, are included.
Figure 4.
Figure 4.
Number of identified peptide groups (Left) and high-confidence master proteins (Right) for the nanoPOTS analysis of frozen and FFPE-preserved mouse liver tissue squares having lateral dimensions of 50–200 μm, as well as autoPOTS analysis of the FFPE tissue sections of the same dimensions. The lighter shading in each bar indicates additional identifications made using MBR. Standard deviations for each condition (N = 4) are provided in Table S1.

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