Identification of potential substrates of LNX1 in chicken cells

Abstract

Ubiquitination of proteins is involved in numerous life activities. In poultry, several ubiquitin ligases tightly control the innate immune response, imbalance of which may result in autoimmune diseases and seriously impair poultry growth, development, and productivity. LNX1, an E3 ubiquitin ligase, catalyzes the ubiquitination and subsequent degradation of specific substrate proteins. A cell line with stable knockdown of the LNX1 gene was developed using chicken macrophages (HD11) as the model. The relative quantitative values of each protein were analyzed using 4D-FastDIA quantitative proteomics. This identified 319 proteins with up-regulated expression, a majority of which relate to the immune system. Overall, this study uncovered potential substrate proteins targeted by LNX1 and their associated biological pathways. The findings suggest that LNX1 could be implicated in the regulation of the chicken innate immune system by mediating protein ubiquitination.

Introduction

Maintaining internal stability is crucial for poultry health. Ubiquitination and deubiquitination of key proteins are reciprocal reactions catalyzed by ubiquitination-associated enzymes and deubiquitinating enzymes that regulate almost all biological processes (Ebner et al., 2017). As a protein modification, ubiquitination is widespread among eukaryotes (Lechtenberg and Komander, 2024); moreover, the number of enzymes that perform ubiquitination exceeds the number of phosphorylases, highlighting the importance and complexity of this process (Gallo et al., 2017). Indeed, ubiquitination is involved in virtually all life activities, including transcriptional regulation (Conaway et al., 2002; Panahi and Shahi, 2024), cell cycle (Dang et al., 2021), immune response (Hu and Sun, 2016), and energy metabolism (Lavie et al., 2018), due to its centrality in protein homeostasis and localization. As a consequence, dysregulation of ubiquitination can have negative impacts, potentially leading to diseases or life-threatening conditions and certainly affecting the growth, development, and production performance of livestock such as poultry (Li et al., 2020).

The protein LNX1 is reported to serve as an E3 ubiquitin ligase, catalyzing substrate protein ubiquitination and promoting degradation (Nie et al., 2002). LNX1 was initially identified for its role in binding and catalyzing the degradation of NUMB, a determinant of cell fate during development (Dho et al., 1998). Structurally, the LNX1 protein contains a RING domain with E3 ubiquitinase activity, along with four PDZ domains, each of which exhibits distinct substrate-binding preferences, enabling interaction with and modification of various substrate proteins (Nie et al., 2002). In addition to its involvement in neural pathway development (Liu et al., 2018), LNX1 has been implicated in immune evasion by Mycobacterium tuberculosis (Fu et al., 2020). Ubiquitination modifications are known to be crucial for immune responses (Zinngrebe et al., 2014), encompassing immune cell differentiation, defense mechanisms (Bhutda et al., 2022), antigen processing, and inflammation, and a number of ubiquitin ligases have been reported to regulate immune pathways (Ben-Neriah, 2002). The specific role of LNX1 in immunity is yet unknown. Mining additional substrate proteins for LNX1-mediated modifications is essential for elucidating this ubiquitin ligase's regulatory role in immune pathways and responses.

Macrophages are pivotal components of the immune system, defending against pathogens, presenting antigens, and clearing foreign substances (Shojadoost et al., 2019). This study employed chicken monocyte macrophage cells (HD11) as a cell model for the construction of a stable LNX1 knockdown cell line. Protein expression levels in the knockdown line were compared with those of wild-type cells to identify potential substrates for LNX1.

Materials and methods

Cell culture

HEK293T (ATCC CRL-3216) cells were cultured in Dulbecco's Modified Eagle's Medium supplemented with 10 % fetal bovine serum (Gibco) and 1 % penicillin-streptomycin (Gibco). Chicken macrophage cells (HD11 cells, from the cell bank of the Chinese Academy of Sciences) were cultured in RPMI 1640 medium (Gibco) complemented with 10 % FBS (Gibco), 5 % chicken serum (Solarbio), 1 % sodium pyruvate (Gibco), 1 % non-essential amino acids (Gibco), and 0.1 % β-mercaptoethanol (Solarbio). All cells were maintained in a humidified incubator with 5 % CO₂ at 37 °C.

Antibodies

Chicken LNX1 Rabbit Polyclonal Antibody is customized and produced by Hangzhou HuaAn Biotech.

GAPDH Mouse Monoclonal Antibody (AC002) is purchased from ABclonal.

Short hairpin RNA interference plasmids

Duplexed short hairpin RNA (shRNA) was synthesized by Beijing Tsingke Biotech with the following sequence and ligated into the pLV3ltr-ZsGreen-Puro-U6 plasmid for expression.

LNX1 shRNA for chicken, 5′- AGUAUCAUGUCUCCAGGCAGC -3′.

Lentivirus production

T-75 flasks (Corning) of rapidly dividing HEK293T cells (ATCC; Manassas, VA, USA) were transfected with lentivirus production helper plasmids pMD2.G and psPAX2 in combination with modified pLV3ltr-ZsGreen-Puro-U6. Transfection was facilitated by Lipofectamine 3000 (Invitrogen) according to the manufacturer's protocol. After 48 h, the supernatant was collected, centrifuged at 500 g for 5 minutes to remove cellular debris, and filtered through a 0.45-µm filter. Filtered supernatant was concentrated using the PEG-it Virus Precipitation Solution (System Biosciences) according to the manufacturer's directions. The resulting pellet was resuspended in Opti-MEM (Gibco) using 1 % of the original medium volume, then flash-frozen and stored at −80°C until needed.

Lentiviral infections and flow cytometric sorting

Healthy HD11 cells were seeded into T-25 flasks. Upon reaching 60-70 % confluence, the medium was supplemented with Polybrene (MedChemExpress) to a final concentration of 8 µg/ml and incubated for four to six hours. Previously prepared lentivirus was then added to the culture medium, and infection allowed to proceed for 48 h. Subsequently, the medium was removed and the cells were collected in phosphate-buffered saline (Hyclone) with 2 % FBS, then transferred to a flow cytometry tube. Flow cytometry was used to sort the cells based on GFP fluorescence, isolating stably transfected positive cells.

Protein extraction

The sample was ground with liquid nitrogen into cell powder and then transferred to a centrifuge tube. Next, four volumes of lysis buffer (1 % SDS, 1 % protease inhibitor cocktail [Roche]) was added to the cell powder, followed by sonication for three minutes on ice using a high intensity ultrasonic processor (Scientz). The remaining debris was removed by centrifugation at 12,000 g at 4°C for 10 min. Finally, the supernatant was collected and the protein concentration was determined with a BCA (Vazyme) kit according to the manufacturer's instructions.

Trypsin digestion

The protein sample was added with one volume of pre-cooled acetone, vortexed to mix, and then added with four volumes of pre-cooled acetone and allowed to precipitate at -20 °C for 2 h. Afterwards, the precipitate was washed 2-3 times with further pre-cooled acetone. The protein sample was then redissolved in 200 mM TEAB and ultrasonically dispersed. Trypsin was added at a 1:50 trypsin-to-protein mass ratio for the first digestion, performed overnight. The next day, the sample was reduced with 5 mM dithiothreitol for 30 min at 56 °C, then alkylated with 11 mM iodoacetamide for 15 min at room temperature in darkness. Finally, the peptides were desalted using a Strata X SPE column.

LC–MS/MS analysis

The mobile phase for LC-MS/MS consisted of solvent A (0.1 % formic acid, 2 % acetonitrile/in water) and solvent B (0.1 % formic acid in acetonitrile). The tryptic peptides were dissolved in solvent A, directly loaded onto a home-made reversed-phase analytical column (25-cm length, 100 μm i.d.). Peptides were separated with the following gradient: 0-14 min, 6 %-24 % B; 14-16 min, 24 %-35 % B; 16-18 min, 35 %-80 % B; and 18-20 min, 80 % B; all steps utilized a constant flow rate of 500 nl/min on a NanoElute UHPLC system (Bruker Daltonics). After separation on the column, peptides were subjected to capillary source followed by timsTOF Pro mass spectrometry. The electrospray voltage applied was 1.75 kV. Precursors and fragments were analyzed at the TOF detector. The timsTOF Pro was operated in data independent parallel accumulation serial fragmentation (dia-PASEF) mode. The full MS scan was set as 300-1500 (MS/MS scan range), and 20 PASEF (MS/MS mode)-MS/MS scans were acquired per cycle. The MS/MS scan range was set as 400-850 and the isolation window as 7 m/z.

MS data analysis

The DIA data were processed using the DIA-NN search engine (v.1.8). Tandem mass spectra were searched against Gallus_gallus_9031_PR_20231010.fasta (43711 entries) concatenated with a reverse decoy database. Trypsin/P was specified as the cleavage enzyme, and up to 1 missing cleavage was allowed. Excision on N-term Met and carbamidomethyl on Cys were specified as fixed modifications. The FDR was adjusted to < 1 %.

Functional enrichment

Fisher's exact test was used to analyze the significance of functional enrichments identified among differentially expressed proteins (using all identified proteins as the background). Functional terms with fold enrichment >1.5 and P value <0.05 were considered significant. A heatmap and bubble plots were generated by www.bioinformatics.com.cn (last accessed on 10 Nov 2023), an online platform for data analysis and visualization.

Real-time PCR

Total cellular RNA was extracted by TRIzol (Invitrogen) according to the manufacturer's instructions. Next, cDNA was generated from 1 μg of RNA using the PrimeScript RT reagent kit with gDNA Eraser (Takara). Target mRNAs were quantified by real-time PCR using SYBR Green master mix (Applied Biosystems). Data were normalized to the expression of the housekeeping gene β-actin. The sequences of the PCR primers used to amplify target chicken genes are listed below:

β-actin: sense 5′-GAGAAATTGTGCGTGACATCA-3′, antisense 5′-CCTGAACCTCTCATTGCCA-3′.

LNX1: sense 5′- CCCATGAGAACCTGGCCATT -3′, antisense 5′- CTCCAGGCAGCAATCTTCCA -3′.

Western blotting

Cells were lysed in RIPA buffer (50 mM Tris-HCl, pH 7.4, 150 mM NaCl, 0.25 % deoxycholic acid, 1 % NP-40, and 0.5 % SDS, supplemented with protease inhibitor [Roche]) and centrifuged at 12,000 g at 4 °C for 10 min. Cell lysates were separated by electrophoresis on SDS-PAGE gels and then transferred onto polyvinylidene fluoride membranes (Millipore). The membranes were first blocked with 5 % (w/v) fat-free milk in TBST, then incubated with the corresponding primary antibodies diluted in 5 % (w/v) fat-free milk in TBST. After washing with TBST, the membranes were incubated with the appropriate secondary antibodies diluted in 5 % (w/v) fat-free milk in TBST. The protein bands were visualized using Immobilon Western Chemiluminescent HRP Substrate (Millipore) in accordance with the manufacturer's instructions.

Results

Multiple proteins exhibited altered expression levels following stable knockdown of LNX1 gene expression

LNX1 gene knockdown was validated by real-time PCR and Western blot, which revealed significant (P <0.01) reductions in both mRNA (Fig. 1.a) and protein levels (Fig. 1.b). To pinpoint proteins targeted by LNX1 for ubiquitination, we performed 4D-FastDIA quantitative proteomic analysis of HD11 cells, comparing those with stable shRNA-mediated LNX1 knockdown to wild-type. We identified 65,541 peptides corresponding to 7,650 proteins. Following raw data filtration with 1 % precursor and protein FDR thresholds, 7,616 proteins were deemed quantitatively comparable. Principal component analysis was conducted using the relative protein abundance values from both groups (Fig. 1.c). Applying threshold criteria of P value less than 0.05 and |Log2FC|>0.585 for difference analysis, we identified 448 differentially expressed proteins, of which 319 were up-regulated and 129 were down-regulated (Fig. 1.d). Volcano plots (Fig. 1.e) and radar plots (Fig. 1.f) were employed to visualize protein expression differences; the proteins that showed marked up-regulation included C7 and ERP29. Furthermore, to validate the results of the data analysis, we selected three proteins from the upregulated proteins and co-transfected with LNX1 in HD11 cells. Western blotting results indicated that overexpression of LNX1 led to downregulation of CD36 (Fig. 2.a), CHIA (Fig. 2.b), and SQSTM1 (Fig. 2.c) protein levels. Among these, CD36 is a critical pattern recognition receptor in the innate immune system. In macrophages, CD36 plays a role in the internalization of apoptotic cells and certain bacterial and fungal pathogens. Since LNX1 is a known E3 ubiquitin ligase, we hypothesize that LNX1 regulates the ubiquitination of CD36, thereby influencing its protein expression levels and affecting innate immune responses.

Fig. 1.

a, b, Experimental validation of LNX1 expression in LNX1 knockdown (SH) and control HD11 cells using real‐time PCR (a) and western blot (b). c, PCA plot showing significant differences between the two groups. d, Counts of up- and down-regulated differentially expressed proteins. e, Volcano plots showing proteins differentially expressed in cells. f, Radar plot showing the top 25 differentially expressed proteins.

Fig. 2.

a, b, c, Co-transfected FLAG empty vector and LNX1, respectively, with MYC-CD36 (a), MYC-CHIA (b), and MYC-SQSTM1 (c) into HD11 cells to assess protein expression levels.

Subcellular localization and functional annotation of differentially expressed proteins

Categorization of the differentially expressed proteins based on subcellular localization revealed them to be distributed across multiple cellular compartments (Fig. 3.a). Functional annotation using KEGG and GO classifications shows that differentially expressed proteins are mainly involved in Global and overview maps, transport and catabolism, signal transduction, and the immune system (Fig. 3, Fig. 3). The Global and overview maps pathway offers a comprehensive depiction of metabolic pathways and functions in biological systems. Because it does not focus on the specific details of any single biochemical process, it highlights the interconnections between major metabolic pathways and the overall structure of the cellular metabolic network, which is why this pathway involves the largest number of proteins.

Fig. 3.

a, Rose plots showing the counts of up- and down-regulated differential proteins in different cellular substructures. b, Distribution of differentially expressed proteins among KEGG functional classifications. c, Distribution of differentially expressed proteins among GO functional classifications. Pink indicates up-regulation, while blue indicates down-regulation.

Enrichment analysis indicates that LNX1 potentially modulates multiple biological pathways

The differentially expressed proteins were examined for enrichment of structural domains, which highlighted the phosphatidylethanolamine binding site, immunoglobulin-like domain, and Kringle domain, among others (Fig. 4.a). GO analysis of differentially expressed proteins showed enrichment of biological process terms like estrogen secretion and positive regulation and mast cell differentiation, and more (Fig. 4.b), alongside enrichment of molecular function terms linked to signal transduction and reception, cytokine receptor interaction and binding, serine-type endopeptidase activity, and oxidative metabolism (Fig. 4.c). KEGG pathway analysis identified associations with processes like the complement and coagulation cascades, and interactions with viral proteins, cytokines, and cytokine receptor complexes (Fig. 4.d). Finally, the Mfuzz algorithm was used to cluster the differentially expressed proteins, producing eight clusters. Relative protein expression levels were quantified for each cluster, and corresponding KEGG-enriched pathways were annotated. This analysis indicated significant differences between the SH and control groups, with five clusters up-regulated and three clusters down-regulated, suggestive of alterations in various metabolic pathways (Fig. 4.e). Collectively, these analyses indicate that stable LNX1 gene knockdown impacts multiple metabolic pathways, underscoring its regulatory role in diverse biological processes.

Fig. 4.

a, The top 20 domains most significantly enriched among differentially expressed proteins. b, c, The top 20 enriched GO biological processes (b) and molecular functions (c). d, The top 10 enriched KEGG pathways and their associated differentially expressed proteins. e, Clustering of proteomic data using the mfuzz algorithm; violin plots and heatmaps illustrate the differential expression of proteins within each cluster, accompanied by GO annotations.

LNX1 modulates protein expression levels to influence immune responses

We identified multiple differentially expressed proteins that serve as key components in the immune system, specifically functioning as complement or receptor proteins (Fig. 5.a). Structural domain enrichment analysis also revealed the differentially expressed proteins to be notably associated with immunoglobulin domains, driven by proteins such as VSIG4, OPCML, and CNTN1. GO enrichment analysis linked the differentially expressed proteins to serine metabolic processes, as with PLG and C1S (Fig. 5.b). Meanwhile, KEGG enrichment analysis highlighted complement and coagulation cascade pathways by way of proteins such as C7, PLG, F5, ITGAD, F13A1, and C1QC. Finally, notable differences in protein levels were observed for cytokines, including CCR5-L, IL6ST, IL16, and IL18R1, and for the chemokine receptors CXCR4 and CMKLR1 (Fig. 5.c).

Fig. 5.

a, Selected proteins differentially expressed in control and SH cells that are associated with the immune system. b, Differentially expressed proteins associated with serine metabolism. c, KEGG pathway enrichments of up- and down-regulated proteins associated with the immune system. d, Proteins within the ECM receptor-interacting signaling pathway significantly impacted by LNX1 knockdown.

The differentially expressed proteins were also observed to be enriched in the ECM receptor-interacting signaling pathway; moreover, the associated proteins each play significant roles within this pathway. There are several stages in ECM receptor-interacting signaling, such as ECM component recognition, signal transduction, and cellular responses. LNX1 gene disruption led to altered expression of various ECM ligand proteins, including collagen, laminin, and THBS. These findings imply a regulatory role for LNX1 in the ECM receptor interaction signaling pathway, potentially influencing numerous physiological processes including antigen recognition, immune signaling, and macrophage migration and differentiation (Fig. 5.d).

Discussion

Chicken innate immune system which includes cellular mediators, cytokine and chemokine repertoires and molecules involved in antigen detection, develops early in life (Alkie et al., 2019). Unraveling the regulation of innate immunity in chickens should focus on the significant pathways in these areas and leverage the modification regulatory mechanisms of the key proteins involved.

LNX1, as an E3 ubiquitin ligase, regulates various signaling pathways through its interactions with multiple substrate proteins. Studies have shown that LNX1 binds to and catalyzes the degradation of NUMB proteins, which are crucial for determining cell fate in development (Nie et al., 2002). Additionally, LNX1 is implicated in neural pathway formation, Mycobacterium tuberculosis immune evasion, and various other biological processes; however, its role in regulating poultry innate immune responses remains unexplored.

Macrophages, as the first line of defense in innate immunity, protect against infections through pathogen recognition, phagocytosis, and degradation (Shojadoost et al., 2019). They also contribute to adaptive immunity and regulate inflammation. The present work involved constructing a chicken monocyte macrophage cell line with stable LNX1 knockdown for investigating the expression of other proteins downstream. Comparing protein expression levels with wild-type cells and performing enrichment analyses of differentially expressed proteins revealed potential LNX1 substrates. We also hypothesized LNX1 potential regulatory interactions within its associated biological pathways. Given its function as an E3 ubiquitin ligase, reduced expression of LNX1 could diminish its ubiquitination activity, resulting in lower ubiquitin modification levels of its substrates. Consequently, protein stability might be enhanced, resulting in up-regulated protein expression.

Our study identified numerous differentially expressed proteins with roles in complement activation and receptor-mediated immunity. The up-regulation of VSIG4, a cell surface member of the immunoglobulin superfamily, is particularly noteworthy. VSIG4 serves as a complement receptor and plays a critical role in innate immunity (Ebstein et al., 2023). Specifically, it binds to complement proteins, including C3b and iC3b, thereby modulating macrophage activation, implementing regulation that aids in controlling the severity of the inflammatory response and maintaining immune homeostasis (Helmy et al., 2006; Zeng et al., 2016). Additionally, VSIG4 is a potent negative regulator of murine and human T cell proliferation and IL-2 production (Vogt et al., 2006), and it suppresses Th-type cytokine production (Jung et al., 2012). Tissue-resident macrophages play a central role in tissue immune surveillance and infection response, partly mediated through VSIG4-dependent phagocytosis (Helmy et al., 2006). VSIG4 is reported to act as a pattern recognition receptor for a pathogen-associated molecular pattern (PAMP) on the surface of gram-positive bacteria, promoting bacterial clearance in vivo (Zeng et al., 2016). More importantly, research reports suggest that enhanced VSIG4 expression inhibits M1 polarization of macrophages by blocking TLR4/NF-κB activation (Wang et al., 2022).

Upon pathway enrichment analysis of differentially expressed proteins, we found significant enrichment of proteins involved in ECM-receptor interaction signaling, including numerous proteins implicated as critical surface receptors. Our research underscores the significance of CD36, a key pattern recognition receptor in the innate immune system. CD36 recognizes pathogen-associated molecular patterns (PAMPs), triggering innate immune responses and modulating inflammation (Febbraio et al., 2001). It plays a critical role in immune cell differentiation and activation, ultimately influencing cell fate (Chen et al., 2022; Zhang et al., 2024). In macrophages, CD36 functions as a scavenger receptor, facilitating the internalization of apoptotic cells as well as certain bacterial and fungal pathogens by recognizing specific oxidized phospholipids and lipoproteins (Silverstein and Febbraio, 2009). It also acts as a shared receptor for the TLR4-TLR6 heterodimer, with its activity regulated by signals from the scavenger receptor (Stewart et al., 2010). Moreover, some TLR2 ligands are dependent on CD36, highlighting its broader role in immune signaling (Hoebe et al., 2005). Our findings suggest that LNX1 may influence macrophage function by modulating CD36 ubiquitination levels, thereby affecting immune defense. Specifically, we observed that overexpression of LNX1 is associated with downregulation of CD36 protein expression. This indicates a potential regulatory role for LNX1 in macrophage activity through its effects on CD36.

Further research is needed to fully elucidate the mechanisms underlying this regulatory interaction and its implications for immune defense.

Supplementary files

Table S1. 4D-FastDIA quantitative proteomic raw data of control and SH cell samples.

Table S2. Information of differentially expressed proteins between control and SH cells.

Funding

This work was supported by Biological Breeding-National Science and Technology Major Project (2023ZD0405302 to QL), Innovation Program of Chinese Academy of Agricultural Sciences (CAAS-CSAB-202401 to QL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

CRediT authorship contribution statement

Yuhong Liu: Conceptualization, Methodology, Visualization, Writing – original draft, Writing – review & editing. Qianmei Gao: Conceptualization, Investigation, Visualization. Qi Zhang: Investigation. Chen Li: Investigation. Sha Liu: Investigation. Meng Su: Investigation. Danli Song: Investigation. Guiping Zhao: Supervision. Qinghe Li: Conceptualization, Methodology, Supervision.

Declaration of competing interest

The authors have declared that no competing interests exist.