Journal: International Journal of Molecular Sciences

Article Title: The Hidden Power of the Secretome: Therapeutic Potential on Wound Healing and Cell-Free Regenerative Medicine—A Systematic Review

doi: 10.3390/ijms26051926

Figure Lengend Snippet: Biogenesis of secretome.

Article Snippet: S.Biomedics , Seoul, Seongdong-gu, Republic of Korea , CF-FECS-DF , Secretome from human dermal fibroblasts spheroids , Damaged skin , [ ] .

Techniques:

Journal: International Journal of Molecular Sciences

Article Title: The Hidden Power of the Secretome: Therapeutic Potential on Wound Healing and Cell-Free Regenerative Medicine—A Systematic Review

doi: 10.3390/ijms26051926

Figure Lengend Snippet: Main features of the selected articles. Trend of secretome studies from different mesenchymal stem cells (MSC) sources ( A ), and geographical distribution of research on using MSCs secretome in wound healing ( B ).

Article Snippet: S.Biomedics , Seoul, Seongdong-gu, Republic of Korea , CF-FECS-DF , Secretome from human dermal fibroblasts spheroids , Damaged skin , [ ] .

Techniques:

Journal: International Journal of Molecular Sciences

Article Title: The Hidden Power of the Secretome: Therapeutic Potential on Wound Healing and Cell-Free Regenerative Medicine—A Systematic Review

doi: 10.3390/ijms26051926

Figure Lengend Snippet: Xeno-free chemically defined media used for obtaining secretome.

Article Snippet: S.Biomedics , Seoul, Seongdong-gu, Republic of Korea , CF-FECS-DF , Secretome from human dermal fibroblasts spheroids , Damaged skin , [ ] .

Techniques: Recombinant

Journal: International Journal of Molecular Sciences

Article Title: The Hidden Power of the Secretome: Therapeutic Potential on Wound Healing and Cell-Free Regenerative Medicine—A Systematic Review

doi: 10.3390/ijms26051926

Figure Lengend Snippet: Current state of secretome use in practical applications (in vivo).

Article Snippet: S.Biomedics , Seoul, Seongdong-gu, Republic of Korea , CF-FECS-DF , Secretome from human dermal fibroblasts spheroids , Damaged skin , [ ] .

Techniques: In Vivo, Immunofluorescence, Injection, Migration, Transfection, Expressing, Enzyme-linked Immunosorbent Assay, TUNEL Assay, Staining, Immunohistochemistry, Control, Activation Assay

Journal: International Journal of Molecular Sciences

Article Title: The Hidden Power of the Secretome: Therapeutic Potential on Wound Healing and Cell-Free Regenerative Medicine—A Systematic Review

doi: 10.3390/ijms26051926

Figure Lengend Snippet: Secretome products available on the market for skin conditions.

Article Snippet: S.Biomedics , Seoul, Seongdong-gu, Republic of Korea , CF-FECS-DF , Secretome from human dermal fibroblasts spheroids , Damaged skin , [ ] .

Techniques:

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: Concept of secretome-based screening—the combination of a secretome library and a cell-based assay with a disease-relevant readout results in the identification of novel targets and elucidation of signal transduction pathways. ( A ) Different responses can be measured in a secretome-based assay. (1) A secreted ligand (triangle) induces an agonist response that results in an increase in the signal of the phenotypic readout. (2) A secreted ligand functions as an antagonist and reduces the signal of the phenotypic readout. (3) A secreted ligand or ECD function as a decoy factor. (4) A secreted ligand is an enzyme, which produces a metabolite that affects the phenotypic readout. The arrows illustrate that both agonist (gray) and antagonist (black) readouts can be measured. ( B ) Novel biology and putative targets can be discovered at different stages of the secretome-based workflow.

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Cell Based Assay, Transduction

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: The secretome library—the constituents, how to produce it, information flow, and sample management. ( A ) Annotation of the KTH secretome library comprising more than 1500 produced secreted proteins and ECDs. Secreted proteins can be divided into different subcategories based on Uniprot keywords for molecular function and/or biological process. The circle diagram shows the division into subfamilies as indicated. ( B ) Overview of protein production. (1) Bioinformatics to design constructs for all human secreted proteins and selected ECDs of one-pass TM proteins. (2) Gene synthesis and custom cloning of the constructs followed by sequence verification. (3) Plasmid preparation and additional sequence verification before entering the protein production. (4) Protein expression using the episomal QMCF vector in CHO cells. (5) Protein purification using the C-terminal HPC4 tag. (6) Protein quality check. ( C ) Overview of the information flow and sample management process. (1) Purified proteins in 2D barcoded vials. (2) Protein batches were thawed once and dispensed into subaliquots (15–20 µL) that were snap-frozen in liquid nitrogen. (3) Aliquots were stored at −80 °C until tested in the cell-based screens. (4) Proteins were dispensed and diluted in 384-well plates before addition to cell-based assays. (5) Data information handling. The library is registered in AstraZeneca compound management databases to allow for the integration between compound handling, assay screening, and data analysis.

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Produced, Construct, Cloning, Sequencing, Plasmid Preparation, Expressing, Protein Purification, Purification

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: The secretome-based workflow from initial screen to confirmed active. ( A ) Schematic flow diagram showing the different steps in a typical secretome-based screen using purified proteins. (1) Usually the full library is tested at three concentrations in duplicate. A small volume of secretome protein (typically 1 µL) is added to each well (typically 40–50 µL). This results in a top concentration of 200 nM protein for a majority of samples tested. Occasionally, another dose of protein is added to the cells during incubation if the assay is running for a long period of time (>3 days). (2) Actives from the primary screen are confirmed in dose response in the primary assay. (3) A list of confirmed active proteins will be annotated in silico. This involves, for example, literature searches, expression data, disease relevance, and human target validation. (4) Additional protein will be produced so that the secretome library is not depleted. (5) Annotated actives will be tested in additional biologic effect assays (BEAs) before initiating any mechanistic studies (6). ( B ) An illustrative example of one assay where two markers are measured simultaneously. , As a result, four types of actives are identified that affect the markers differently (see main text).

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Purification, Concentration Assay, Incubation, In Silico, Expressing, Biomarker Discovery, Produced

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: A summary of different steps needed to identify a receptor and signaling pathway induced by a secreted ligand. When an active has been identified from a secretome-based screen, the next step is to identify the cognate receptor and/or enzymatic activity that is needed to transduce the signal into the cells. There are several methods available to establish the identity of the receptor as described in the main text. Also, gene expression analysis can be utilized to profile the transcriptional events that are induced by the active secretome proteins. Finally, this can be confirmed by siRNA or precise genome editing (PGE). See text for more details.

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Activity Assay, Transduction, Gene Expression

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: Examples of targets discovered by secretome-based screening. , , ( A ) A secretome-based screen to identify targets that affect the viability of monocytes. IL-34 was discovered in the primary screen using primary human monocytes. The methodology used was CellTiter-Glo. The activity of IL-34 was confirmed in human bone marrow cultures (BMCs), in which IL-34 promoted the formation of macrophage progenitor cells. The receptor of IL-34 was discovered by preincubating the protein with ECDs in the secretome library and measuring cell viability. Preincubation with macrophage CSF-1R-ECD resulted in an inhibition of the effect compared with other IL-34-ECD samples. ( B ) Identification of the NKp44-PDGF-DD receptor pair. A NKp44-GFP reporter cell line was used to identify the ligand of NKp44 as PDGF-D. The activity of purified PDGF-DD was confirmed using human NK cells from donors, by measuring phosphorylation of downstream substrates Akt and Erk and by measuring proinflammatory cytokine release (interferon-γ and tumor necrosis factor). ( C ) Identification of FGF16 as a specific inducer of human CPC proliferation. The ability of secretome proteins to induce iPSC-CPC proliferation was measured by nuclear count. All actives were counterscreened in a CF proliferation assay. The interaction of FGF9 and FGF16 with CPCs and CFs was quantified using biosensor analysis. Conditioned medium libraries were used in A and B , whereas a purified protein library was used in C .

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Activity Assay, Inhibition, Purification, Phospho-proteomics, Proliferation Assay

Journal: Aging (Albany NY)

Article Title: Systemic factors in young human serum influence in vitro responses of human skin and bone marrow-derived blood cells in a microphysiological co-culture system

doi: 10.18632/aging.206288

Figure Lengend Snippet: The BM model secretes age-associated proteins. The BM model was statically cultured for five weeks. After two weeks, the BM cells were treated with either young or old human serum. On culture day 35, the BM cells were harvested, and the washed cell pellet analyzed using tandem LC-IMS-MS/MS proteomics. ( A ) Log2FC and −log2( p -value) of all significantly ( p < 0.05) up (orange) or downregulated (turquoise) proteins in the BM with old serum compared to young serum. Proteins regulated in the same direction in at least 4 of 5 samples are depicted as well as either upregulated (red) or downregulated (blue). ( B ) Comparison of all regulated proteins to 2772 potentially secreted proteins according to the human protein atlas, creating an overlap of 233 proteins. ( C ) Go-Term analysis of down- (left) and up- (right) regulated overlapped proteins shown in ( B ). ( D ) Heatmap showing the log2FC of the overlapped 55 proteins in ( E ) depicting upregulated (red) and downregulated (blue) proteins with old serum. ( E ) Venn diagram showing the overlap of regulated proteins that belong to the human secretome (left) and secreted proteins that significantly change upon aging (right), resulting in 55 proteins shared between the two categories. ( F ) STRING protein network of the down- (left) and up- (right) regulated proteins from the 55 overlap proteins shown in ( E ). Expression by different BM cell types is highlighted with yellow circles (granulocytes), blue circles (progenitor cells) or violet circles (monocytes). Data were obtained from one experiment with 5 replicates.

Article Snippet: According to the Human Protein Atlas list “human secretome” (proteinatlas.org) [ ], none of these proteins are known to be secreted to potentially impact other tissues.

Techniques: Cell Culture, Tandem Mass Spectroscopy, Comparison, Expressing