SELPLG Human
Description
Introduction to SELPLG (Human Selectin P Ligand)
SELPLG (Selectin P Ligand), also termed CD162 or PSGL-1 (P-selectin glycoprotein ligand-1), is a gene encoding a dimeric mucin-like glycoprotein critical for leukocyte adhesion and trafficking during inflammation . This transmembrane protein is expressed on white blood cells and serves as the high-affinity ligand for P-selectin, E-selectin, and L-selectin, facilitating immune cell recruitment to sites of injury or infection .
Key Features:
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Protein Structure: Dimeric glycoprotein with extensive O-linked glycosylation and tyrosine sulfation required for selectin binding .
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Post-Translational Modifications:
Functional Roles:
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Leukocyte Rolling: Mediates initial tethering of leukocytes to endothelial cells via selectins, enabling immune cell migration .
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Immune Regulation: Modulates T-cell exhaustion in tumor microenvironments and influences checkpoint inhibitor responses .
Inflammatory Diseases
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Acute Respiratory Distress Syndrome (ARDS):
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SELPLG expression is upregulated in lung tissue during LPS- or ventilator-induced injury. Inhibition with TSGL-Ig (a recombinant PSGL-1 fusion protein) reduces lung injury severity .
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Hypoxia-inducible factors (HIF-1α, HIF-2α) and NRF2 transcriptionally regulate SELPLG promoter activity under ARDS conditions .
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| Study | Key Finding | Source |
|---|---|---|
| Preclinical ARDS | TSGL-Ig reduces SELPLG expression and attenuates lung injury in mice | |
| Genetic Variants | rs2228315 (Met62Ile) linked to ARDS susceptibility |
Cancer Biology
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Tumor Microenvironment:
| Cancer Type | SELPLG Role | Source |
|---|---|---|
| Osteosarcoma | Low SELPLG correlates with metastasis and poor prognosis | |
| Melanoma | PSGL-1 deficiency enhances anti-PD-1 efficacy |
Genetic and Epigenetic Regulation
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Polymorphisms:
| Population | Polymorphism | Effect on SELPLG/SELP Levels | Source |
|---|---|---|---|
| African Americans | SELPLG M62I | ↓ Granulocyte/monocyte SELPLG | |
| Whites | SELP T715P | ↓ Platelet SELP |
Prognostic Utility
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Osteosarcoma: Low SELPLG expression independently predicts poor survival (HR = 0.72, p = 0.014) .
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Immune Infiltration: In osteosarcoma, high SELPLG correlates with increased M1/M2 macrophage infiltration .
Therapeutic Strategies
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Soluble PSGL-1: Recombinant PSGL-Ig inhibits leukocyte recruitment, showing efficacy in ischemia-reperfusion injury and ARDS .
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Checkpoint Inhibition: Anti-PSGL-1 antibodies combined with anti-PD-1 reduce tumor growth in preclinical models .
Data Synthesis and Future Directions
SELPLG’s dual roles in inflammation and immune evasion highlight its therapeutic potential. Current research focuses on:
Product Specs
The SELPLG glycoprotein serves as a high-affinity counter-receptor for selectin molecules (P, E, and L), which are found on stimulated T lymphocytes and myeloid cells. It plays a crucial role in leukocyte trafficking during inflammation by binding leukocytes to activated platelets or endothelia expressing selectins. SELPLG requires two post-translational modifications for high-affinity binding: tyrosine sulfation and the addition of the sialyl Lewis x tetrasaccharide (sLex) to its O-linked glycans. Variations and irregular expression of SELPLG have been associated with abnormalities in the innate and adaptive immune responses. Alternative splicing results in different transcript variants.
Recombinant Human SELPLG, produced in HEK293 cells, is a single, glycosylated polypeptide chain comprising 496 amino acids (42-295 a.a.). It has a molecular weight of 53.4 kDa. The SELPLG is fused to a 239 amino acid hIgG-His-Tag at its C-terminus and is purified using proprietary chromatographic methods.
Sterile filtered, colorless solution.
The SELPLG solution (concentration: 1 mg/ml) is prepared in phosphate-buffered saline (pH 7.4) containing 10% glycerol.
For short-term storage (2-4 weeks), keep at 4°C. For extended periods, store frozen at -20°C. Adding a carrier protein (0.1% HSA or BSA) is recommended for long-term storage. Repeated freezing and thawing should be avoided.
Purity is determined to be greater than 90.0% using SDS-PAGE analysis.
Cutaneous Lymphocyte-Associated Associated Antigen, Selectin P Ligand, PSGL-1, CD162 Antigen, P-Selectin Glycoprotein Ligand 1, CLA.
HEK293 Cells.
DGSQATEYEY LDYDFLPETE PPEMLRNSTD TTPLTGPGTP ESTTVEPAAR RSTGLDAGGA VTELTTELAN MGNLSTDSAA MEIQTTQPAA TEAQTTPLAA TEAQTTRLTA TEAQTTPLAA TEAQTTPPAA TEAQTTQPTG LEAQTTAPAA MEAQTTAPAA MEAQTTPPAA MEAQTTQTTA MEAQTTAPEA TEAQTTQPTA TEAQTTPLAA MEALSTEPSA TEALSMEPTT KRGLFIPFSV SSVTHKGIPM AASNLSVLEP KSCDKTHTCP PCPAPELLGG PSVFLFPPKP KDTLMISRTP EVTCVVVDVS HEDPEVKFNW YVDGVEVHNA KTKPREEQYN STYRVVSVLT VLHQDWLNGK EYKCKVSNKA LPAPIEKTIS KAKGQPREPQ VYTLPPSRDE LTKNQVSLTC LVKGFYPSDI AVEWESNGQP ENNYKTTPPV LDSDGSFFLY SKLTVDKSRW QQGNVFSCSV MHEALHNHYT QKSLSLSPGK HHHHHH
Q&A
What is the SELPLG gene and what protein does it encode?
SELPLG is a human gene that codes for P-selectin glycoprotein ligand-1 (PSGL-1), a dimeric mucin-like glycoprotein found primarily on the surface of white blood cells. PSGL-1 functions as a high-affinity counter-receptor for P-selectin on myeloid cells and stimulated T lymphocytes. While it can bind to all three selectins (P, E, and L), it has the highest affinity for P-selectin .
The gene and structure of human PSGL-1 was first reported in 1993. Most of the binding activity was later localized within its N-terminal 19 amino acids, including the sulfotyrosines at positions 5, 7, and 10, and a critical O-linked glycan attached to threonine at position 16 of the mature protein. The co-crystal structure of human PSGL-1 bound to human P-selectin was published in 2000 .
How is the SELPLG gene organized and regulated?
The organization of the SELPLG gene closely resembles that of CD43 and human platelet glycoprotein GpIb-alpha. It features an intron in the 5'-noncoding region, a long second exon containing the complete coding region, and TATA-less promoters .
SELPLG promoter activity is regulated by multiple transcription factors, including:
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Hypoxia-inducible transcription factors (HIF-1α and HIF-2α)
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Other inflammatory and epigenetic factors
The promoter contains specific regions that respond to different stimuli:
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Two significant LPS response regions have been identified in the SELPLG promoter
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A promoter inhibitory/repressor binding region (-2000 to -800 bp)
What techniques are commonly used to measure SELPLG promoter activity?
Researchers investigating SELPLG promoter activity typically employ several methodological approaches:
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Dual luciferase reporter gene assays: These involve cotransfection of cells with SELPLG promoter plasmid constructs containing firefly luciferase reporter and TK renilla vector. After exposure to stimuli, luciferase activity is measured and normalized as the ratio of firefly to renilla luciferase activities .
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Serial deletion analysis: This technique uses a series of nested deletion vectors of the SELPLG promoter to identify critical regulatory regions. For example, researchers have created eight serial deletion vectors of the SELPLG promoter to map regions responsive to LPS .
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Exposure paradigms: Common experimental conditions include:
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Transfection approaches: Transfection reagents like Fugene HD are used to introduce reporter constructs into cells such as human pulmonary artery endothelial cells .
How does SELPLG contribute to acute respiratory distress syndrome (ARDS) pathophysiology?
SELPLG plays a significant role in ARDS pathophysiology through several mechanisms:
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Increased expression in lung injury: SELPLG lung tissue expression is markedly elevated in murine models of lipopolysaccharide (LPS) and ventilator-induced lung injury (VILI) .
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Genetic susceptibility: Single nucleotide polymorphisms (SNPs) in SELPLG, particularly the Met62Ile variant, are significantly linked to ARDS risk and severity .
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Response to inflammatory stimuli: SELPLG promoter activity increases significantly in response to:
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Therapeutic targeting potential: A recombinant tandem PSGL1 immunoglobulin fusion molecule (TSGL-Ig) that competitively inhibits PSGL1/P-selectin interactions has shown significant protection against LPS- and VILI-induced lung injury. This molecule carries four P-selectin binding sites per molecule, enhancing its selectin-binding properties .
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Two-hit model relevance: The LPS/VILI two-hit model simulates the clinical scenario of ARDS subjects with severe sepsis progressing to respiratory failure and mechanical ventilation with susceptibility to VILI .
What is the relationship between SELPLG expression and cancer progression?
Research has revealed important connections between SELPLG expression and cancer progression, particularly in osteosarcoma (OS):
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Expression patterns in metastasis: Significantly lower SELPLG expression is observed in metastatic OS samples compared with non-metastatic OS samples, consistently demonstrated in both TARGET and GSE21257 datasets .
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Prognostic value: Low SELPLG expression functions as an independent unfavorable prognostic factor for OS patients, confirmed in both TARGET and GEO datasets .
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Molecular mechanisms: Analysis identified 62 differentially expressed gene (DEG) overlaps between high vs. low SELPLG expression and non-metastatic vs. metastatic OS samples. These genes appear to affect metastases and thereby influence prognosis .
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Pathway involvement: The 62 overlapping genes were significantly enriched in 40 GO terms and six KEGG pathways, suggesting specific molecular mechanisms by which SELPLG affects cancer progression .
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Immune microenvironment impact: Five types of immune cells showed significantly different infiltration patterns between high and low SELPLG expression OS patients, indicating SELPLG may influence the tumor immune microenvironment .
How do inflammatory stimuli and mechanical stress regulate SELPLG expression?
The regulation of SELPLG expression by inflammatory stimuli and mechanical stress involves complex mechanisms:
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Promoter response elements: Analysis of the SELPLG promoter has identified:
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Dose-dependent responses:
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Transcription factor involvement: SELPLG promoter activity is strongly regulated by:
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Epigenetic regulation: DNA methylation influences SELPLG expression in endothelial cells, with demethylation reagents like 5'-Aza affecting promoter activity .
What methods are effective for studying SELPLG in leukocyte-endothelial interactions?
To study SELPLG in leukocyte-endothelial interactions, researchers employ several methodological approaches:
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In vitro models:
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Transgenic approaches:
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Inhibitory strategies:
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Preclinical models:
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Statistical analysis:
How can SELPLG be targeted therapeutically in inflammatory conditions?
Several approaches have shown promise for targeting SELPLG therapeutically in inflammatory conditions:
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Competitive inhibition: The novel recombinant tandem PSGL1 immunoglobulin fusion molecule (TSGL-Ig) competitively inhibits PSGL1/P-selectin interactions. This molecule:
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Promoter modulation: Understanding the regulatory mechanisms of SELPLG promoter activity enables targeted interventions:
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Precision targeting: The identification of specific SELPLG SNPs linked to disease risk (e.g., Met62Ile in ARDS) provides potential for personalized therapeutic approaches .
What is the potential role of SELPLG in biomarker development for inflammatory diseases?
SELPLG shows promise as a biomarker in several inflammatory conditions:
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ARDS risk stratification: SELPLG SNPs, particularly Met62Ile, are significantly linked to ARDS risk and severity, offering potential for genetic risk assessment .
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Cancer prognosis: In osteosarcoma, SELPLG expression levels correlate with metastatic potential and patient outcomes, suggesting utility as a prognostic biomarker .
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Inflammatory profiling: Combined analysis of SELPLG with diacylglycerols (DG) and lysophosphatidic acid (LPA) might provide a comprehensive inflammatory profile, as individuals with high lipoprotein(a) [Lp(a)] levels show alterations in both lipid profiles and inflammatory markers .
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Immune cell infiltration: SELPLG expression correlates with specific patterns of immune cell infiltration in tumors, potentially serving as a marker for immune microenvironment status .
What statistical approaches are most appropriate for analyzing SELPLG experimental data?
Proper statistical analysis of SELPLG experimental data requires careful consideration of data characteristics:
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For continuous data:
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Nonparametric methods when normal distribution cannot be assumed
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Standard one-way analysis of variance (ANOVA) followed by Newman-Keuls test for group comparisons
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Two-way ANOVA for comparing means from multiple experimental groups
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Post-hoc least significant differences test when ANOVA indicates significance (p < 0.05)
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For expression data:
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For genomic analyses:
How can researchers optimize experimental design for studying SELPLG in complex disease models?
To optimize experimental design for studying SELPLG in complex disease models, researchers should consider:
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Multi-hit approaches: The LPS/VILI two-hit model simulates clinical ARDS more effectively than single-stimulus models, capturing the progression from sepsis to respiratory failure and mechanical ventilation .
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Combinatorial stimuli: Testing SELPLG responses to combined stimuli (e.g., LPS plus mechanical stress) reveals synergistic effects that might be missed with single-factor studies .
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Promoter dissection: Creating serial deletion vectors of the SELPLG promoter helps identify specific regulatory regions responsive to different stimuli .
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Translational relevance: Integrating findings from multiple datasets (e.g., TARGET and GEO for cancer studies) strengthens the robustness and clinical relevance of results .
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Comprehensive endpoint assessment: Measuring both molecular changes (e.g., promoter activity) and functional outcomes (e.g., protection from lung injury) provides a more complete understanding of SELPLG's role .
What emerging technologies could advance SELPLG research?
Several emerging technologies hold promise for advancing SELPLG research:
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CRISPR/Cas9 genome editing: Precise modification of SELPLG or its regulatory elements to study structure-function relationships.
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Single-cell RNA sequencing: Analysis of SELPLG expression patterns at the single-cell level to identify cell-specific regulation and function.
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Spatial transcriptomics: Mapping SELPLG expression within tissue architecture to understand microenvironmental influences.
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Advanced computational modeling: Predicting SELPLG-selectin interactions based on structural data to design more effective inhibitors.
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Organ-on-chip technology: Creating microfluidic devices that mimic specific tissue microenvironments to test SELPLG-targeting approaches in physiologically relevant contexts.
What are the unresolved questions in SELPLG biology that warrant further investigation?
Several important questions remain unresolved in SELPLG biology:
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Cell-specific regulation: How does SELPLG expression and function differ across various leukocyte subsets and under different inflammatory conditions?
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Signaling mechanisms: What intracellular signaling pathways are activated by SELPLG engagement, and how do these contribute to leukocyte function?
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Genetic variants: Beyond Met62Ile, what other SELPLG genetic variants influence disease susceptibility, and what are their functional consequences?
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Cancer biology: What mechanisms explain the correlation between low SELPLG expression and increased metastatic potential in osteosarcoma?
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Cross-talk with other pathways: How does SELPLG interact with other adhesion molecules and signaling systems during inflammation and immune responses?
Product Science Overview
PSGL-1 is expressed on the surface of various hematopoietic cells, including neutrophils, eosinophils, lymphocytes, and monocytes . It plays a crucial role in mediating the tethering and adhesion of these cells to the endothelium, facilitating their migration to sites of inflammation or injury .
The interaction between PSGL-1 and P-selectin is highly specific and involves several structural features:
- Glycosylation: PSGL-1 is heavily glycosylated, with a core 2 O-glycan expressing the unique tetrasaccharide sialyl-Lewis x (sLe X), which is essential for high-affinity binding to P-selectin .
- Tyrosine Sulfation: The presence of tyrosine sulfate residues at positions 46, 48, and 51 significantly enhances the binding affinity of PSGL-1 to P-selectin .
- Fucose and Sialic Acid: These sugar residues also contribute to the high-affinity interaction between PSGL-1 and P-selectin .
While PSGL-1 is essential for normal immune function, its interaction with P-selectin can also contribute to various pathological conditions:
- Thromboinflammation: The P-selectin/PSGL-1 pathway is implicated in thromboinflammatory processes, where both inflammatory and thrombotic pathways are activated simultaneously, contributing to diseases such as atherosclerosis, thrombosis, and metabolic syndrome .
- Cardiovascular Diseases: Sustained expression of P-selectin and its interaction with PSGL-1 can lead to cardiovascular diseases, including stroke and heart attacks .
- Autoimmune Diseases and Cancer: Dysregulation of the P-selectin/PSGL-1 pathway is also associated with autoimmune diseases and cancer .
