Daucke, R. | bioRxiv Science

bioRxiv2025

The tryptophan-binding pockets of Arabidopsis AGO1 facilitate amplified RNA interference via SGS3

ARGONAUTE (AGO) proteins associate with small RNAs to form RNA-induced silencing complexes (RISCs). Arabidopsis AGO1 effects post-transcriptional silencing by microRNAs (miRNAs) and small interfering RNAs (siRNAs) and is necessary for siRNA amplification through conversion of RISC target RNAs into double-stranded RNA by the RNA-dependent RNA Polymerase RDR6 and its mandatory cofactors SGS3 and SDE5. Many AGO proteins harbor hydrophobic pockets that interact with tryptophan residues, often surrounded by glycine (GW/WG), in intrinsically disordered regions (IDRs) of RISC cofactors. Here, we show that GW/WG dipeptides in the IDR of SGS3 and the hydrophobic pockets in AGO1 are required for fully functional RDR6-dependent siRNA amplification. We also show that this mechanism requires AGO1-specific structural elements, including positively charged residues surrounding the binding pockets, and a conserved, negatively charged patch in the IDR of SGS3. Thus, the same, conserved protein-protein interaction site is used for different purposes in distinct eukaryotic AGO proteins: the GW/WG-mediated TNRC6-Ago2 interaction is crucial for miRNA-guided silencing in metazoans whereas the GW/WG-mediated SGS3-AGO1 interaction facilitates siRNA amplification via RDR6 in plants.

molecular biology↗

bioRxiv2024

Refining Spatial Proteomics by Mass Spectrometry: An Efficient Workflow Tailored for Archival Tissue

BackgroundFormalin-fixed, paraffin-embedded (FFPE) tissue remains the gold standard for extensively archiving biological specimens, providing biobanks with large repositories of retrospective potential. However, while formalin crosslinking is effective at preserving tissue, it poses significant challenges for extracting molecular information, including the proteome. Traditionally, this process required high levels of input material, which, in turn, limited the ability to preserve cell-type heterogeneity and spatial information. To address these limitations, we developed an easily adaptable and highly efficient workflow for extracting deep proteomes from low-input materials, such as biopsies used in routine histopathological diagnostics. MethodsWe compared the extraction efficiency of pancreatic acinar cells identified in FFPE tissue samples stained with conventional hematoxylin-eosin (H&E) against that of cells isolated from tissue samples immunostained for the epithelial cell adhesion molecule (EpCAM) across material inputs ranging from 1,166 to 800,000 {micro}m2 (estimated to 2 to 1,310 cells in volume). Cells were isolated using laser capture microdissection and subsequently analyzed using Liquid Chromatography-Tandem Mass Spectrometry. ResultsSimilar yields for both methods were observed, with EpCAM-positive cells yielding slightly higher results--approximately 1,200 unique protein groups at the lowest input and up to 5,900 at the highest. In cells isolated from H&E-stained tissue, [~]900 to [~]5,200 protein groups were identified. We decided that the optimal balance for our workflow, ensuring maximum protein identification while minimizing input material, lies within the range of approximately 50,000 to 100,000 {micro}m2. With these results, we tested spatial capabilities and biological relevance by isolating cancer cells from biopsies of pancreatic cancer, lung cancer, or glioblastoma, with the first two being stained with EpCAM and the latter being stained against the tumor-suppressor protein p53. We successfully identified tissue-specific protein expressions and observed prominent clustering of all cell populations. DiscussionOur results highlight the feasibility of performing spatial proteomics on FFPE tissue using minimal input material. This adaptable methodology opens up possibilities for investigating cell-type-specific biology while preserving spatial and histological information.

bioengineering↗