Comparative Secretomics Gives Access to High Confident Secretome Data: Evaluation of Different Methods for the Determination of Bona Fide Secreted Proteins

Identification of LMAN1- and SURF4-Dependent Secretory Cargoes

Most proteins secreted into the extracellular space are first recruited from the endoplasmic reticulum into coat protein complex II (COPII)-coated vesicles or tubules that facilitate their transport to the Golgi apparatus. Although several secreted proteins have been shown to be actively recruited into COPII vesicles and tubules by the cargo receptors LMAN1 and SURF4, the full cargo repertoire of these receptors is unknown. We now report mass spectrometry analysis of conditioned media and cell lysates from HuH7 cells CRISPR targeted to inactivate the LMAN1 or SURF4 gene. We found that LMAN1 has limited clients in HuH7 cells, whereas SURF4 traffics a broad range of cargoes. Analysis of putative SURF4 cargoes suggests that cargo recognition is governed by complex mechanisms rather than interaction with a universal binding motif..

Identification of LMAN1 and SURF4 dependent secretory cargoes

Most proteins secreted into the extracellular space are first recruited from the endoplasmic reticulum into coat protein complex II (COPII)-coated vesicles or tubules that facilitate their transport to the Golgi apparatus. Although several secreted proteins have been shown to be actively recruited into COPII vesicles/tubules by the cargo receptors LMAN1 and SURF4, the full cargo repertoire of these receptors is unknown. We now report mass spectrometry analysis of conditioned media and cell lysates from HuH7 cells CRISPR targeted to inactivate the LMAN1 or SURF4 gene. We found that LMAN1 has limited clients in HuH7 cells whereas SURF4 traffics a broad range of cargoes. Analysis of putative SURF4 cargoes suggests that cargo recognition is governed by complex mechanisms rather than interaction with a universal binding motif.

PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping

Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances' mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptomics, while proteomics is not yet routinely applied in toxicology despite the large number of datasets available in public repositories. Exploiting the full potential of these datasets is hampered by differences in measurement procedures and follow-up data processing. Here we present the tool PROTEOMAS, which allows meta-analysis of proteomic data from public origin. The workflow was designed for analyzing proteomic studies in a harmonized way and to ensure transparency in the analysis of proteomic data for regulatory purposes. It agrees with the Omics Reporting Framework guidelines of the OECD with the intention to integrate proteomics to other omic methods in regulatory toxicology. The overarching aim is to contribute to the development of AOPs and to understand the mode of action of substances. To demonstrate the robustness and reliability of our workflow we compared our results to those of the original studies. As a case study, we performed a meta-analysis of 25 proteomic datasets to investigate the toxicological effects of nanomaterials at the lung level. PROTEOMAS is an important contribution to the development of alternative test strategies enabling robust meta-analysis of proteomic data. This workflow commits to the FAIR principles (Findable, Accessible, Interoperable and Reusable) of computational protocols.

Identification of secreted proteins by comparison of protein abundance in conditioned media and cell lysates

Analysis of the full spectrum of secreted proteins in cell culture is complicated by leakage of intracellular proteins from damaged cells. To address this issue, we compared the abundance of individual proteins between the cell lysate and the conditioned medium, reasoning that secreted proteins should be relatively more abundant in the conditioned medium. Marked enrichment for signal-peptide-bearing proteins with increasing conditioned media to cell lysate ratio, as well loss of this signal following brefeldin A treatment, confirmed the sensitivity and specificity of this approach. The subset of proteins demonstrating increased conditioned media to cell lysate ratio in the presence of Brefeldin A identified candidates for unconventional secretion via a pathway independent of ER to Golgi trafficking.

Secretomics—A Key to a Comprehensive Picture of Unconventional Protein Secretion

For a long time, leaderless secreted proteins (LLSP) were neglected as artifacts derived from dying cells. It is now generally accepted that secretion of LLSP–as a part of the collective term unconventional protein secretion (UPS) - is an evolutionarily conserved process and that these LLSP are actively and selectively secreted from living cells bypassing the classical endoplasmic reticulum-Golgi pathway. However, the mechanism of UPS pathways, as well as the number of LLSP and which part of a protein is involved in the selection of LLSPs for secretion, are still enigmatic and await clarification. Secretomics-a proteomics-based approach to identify and quantify all proteins secreted by a cell-is inherently unbiased toward a particular secretion pathway and offers the opportunity to shed light on the UPS. Here, we will evaluate and present recent results of proteomic workflows allowing to obtain high-confident secretome data. Additionally, we address that cell culture conditions largely affect the composition of the secretome. This has to be kept in mind to control cell culture induced artifacts and adaptation stress in serum free conditions. Evaluation of click chemistry for secretome analysis of cells under serum-containing conditions showed a significant change in the cellular proteome with longer incubation time upon treatment with non-canonical amino acid azidohomoalanine. Finally, we showed that the number of LLSP far exceeds the number of secreted proteins annotated in Uniprot and ProteinAtlas. Thus, secretomics in combination with sophisticated microbioanalytical and sample preparation methods is well suited to provide a comprehensive picture of UPS.