HIV-1 Nef Interacts with LMP7 To Attenuate Immunoproteasome Formation and Major Histocompatibility Complex Class I Antigen Presentation

Mass Spectrometry-Based Proteomic Analysis of Potential Host Proteins Interacting with GP5 in PRRSV-Infected PAMs

Porcine reproductive and respiratory syndrome virus (PRRSV) is a typical immunosuppressive virus causing a large economic impact on the swine industry. The structural protein GP5 of PRRSV plays a pivotal role in its pathogenicity and immune evasion. Virus-host interactions play a crucial part in viral replication and immune escape. Therefore, understanding the interactions between GP5 and host proteins are significant for porcine reproductive and respiratory syndrome (PRRS) control. However, the interaction network between GP5 and host proteins in primary porcine alveolar macrophages (PAMs) has not been reported. In this study, 709 GP5-interacting host proteins were identified in primary PAMs by immunoprecipitation coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Bioinformatics analysis revealed that these proteins were involved in multiple cellular processes, such as translation, protein transport, and protein stabilization. Subsequently, immunoprecipitation and immunofluorescence assay confirmed that GP5 could interact with antigen processing and presentation pathways related proteins. Finally, we found that GP5 may be a key protein that inhibits the antigen processing and presentation pathway during PRRSV infection. The novel host proteins identified in this study will be the candidates for studying the biological functions of GP5, which will provide new insights into PRRS prevention and vaccine development.

Antagonizing pathological α-synuclein-mediated neurodegeneration by J24335 via the activation of immunoproteasome

The aggregation of misfolded proteins, such as α-synuclein in Parkinson's disease (PD), occurs intracellularly or extracellularly in the majority of neurodegenerative diseases. The immunoproteasome has more potent chymotrypsin-like activity than normal proteasome. Thus, degradation of α-synuclein aggregation via immunoproteasome is an attractive approach for PD drug development. Herein, we aimed to determine if novel compound, 11-Hydroxy-1-(8-methoxy-5-(trifluoromethyl)quinolin-2-yl)undecan-1-one oxime (named as J24335), is a promising candidate for disease-modifying therapy to prevent the pathological progression of neurodegenerative diseases, such as PD. The effects of J24335 on inducible PC12/A53T-α-syn cell viability and cytotoxicity were evaluated by MTT assay and LDH assay, respectively. Evaluation of various proteasome activities was done by measuring the luminescence of enzymatic activity after the addition of different amounts of aminoluciferin. Immunoblotting and real-time PCR were employed to detect the expression of various proteins and genes, respectively. We also used a transgenic mouse model for behavioral testing and immunochemical analysis, to assess the neuroprotective effects of J24335. J24335 inhibited wild-type and mutant α-synuclein aggregation without affecting the growth or death of neuronal cells. The inhibition of α-synuclein aggregation by J24335 was caused by activation of immunoproteasome, as mediated by upregulation of LMP7, and increased cellular chymotrypsin-like activity in 20S proteasome. J24335-enhanced immunoproteasome activity was mediated by PKA/Akt/mTOR pathway activation. Moreover, animal studies revealed that J24335 treatment markedly mitigated both the loss of tyrosine hydroxylase-positive (TH-) neurons and impaired motor skill development. This is the first report to use J24335 as an immunoproteasome enhancing agent to antagonize pathological α-synuclein-mediated neurodegeneration.

In Memory of the Virologist Jianguo Wu, 1957-2022

It is with deep sorrow that we mourn the passing of the virologist Professor Jianguo Wu [...].

A Tribute to Professor Jianguo Wu

It has been a couple of months since Professor Jianguo Wu left us [...].

Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer

BACKGROUND

According to the guidelines, PD-L1 expression is a critical indicator for guiding immunotherapy application. According to certain studies, regardless of PD-L1 expression, immunotherapy could be advantageous for individuals with gastric cancer. Therefore, new scoring systems or biomarkers are required to enhance treatment strategies.

METHODS

Mass spectrometry and machine learning were used to search for strongly related PD-L1 genes, and the NMF approach was then used to separate gastric cancer patients into two categories. Differentially expressed genes (DEGs) between the two subtypes identified in this investigation were utilized to develop the UBscore predictive model, which was verified by the Gene Expression Omnibus (GEO) database. Coimmunoprecipitation, protein expression, and natural killing (NK) cell coculture experiments were conducted to validate the findings.

RESULTS

A total of 123 proteins were identified as PD-L1 interactors that are substantially enriched in the proteasome complex at the mRNA level. Using random forest, 30 UPS genes were discovered in the GSE66229 cohort, and ANAPC7 was experimentally verified as one of 123 PD-L1 interactors. Depending on the expression of PD-L1 and ANAPC7, patients were separated into two subgroups with vastly distinct immune infiltration. Low UBscore was related to increased tumor mutation burden (TMB) and microsatellite instability-high (MSI-H). In addition, chemotherapy medications were more effective in individuals with a low UBscore. Finally, we discovered that ANAPC7 might lead to the incidence of immunological escape when cocultured with NK-92 cells.

CONCLUSION

According to our analysis of the PD-L1-related signature in GC, the UBscore played a crucial role in prognosis and had a strong relationship with TMB, MSI, and chemotherapeutic drug sensitivity. This research lays the groundwork for improving GC patient prognosis and treatment response.

Comparative Immunoreactivity Analyses of Hantaan Virus Glycoprotein-Derived MHC-I Epitopes in Vaccination

MHC-I antigen processes and presentation trigger host-specific anti-viral cellular responses during infection, in which epitope-recognizing cytotoxic T lymphocytes eliminate infected cells and contribute to viral clearance through a cytolytic killing effect. In this study, Hantaan virus (HTNV) GP-derived 9-mer dominant epitopes were obtained with high affinity to major HLA-I and H-2 superfamilies. Further immunogenicity and conservation analyses selected 11 promising candidates, and molecule docking (MD) was then simulated with the corresponding MHC-I alleles. Two-way hierarchical clustering revealed the interactions between GP peptides and MHC-I haplotypes. Briefly, epitope hotspots sharing good affinity to a wide spectrum of MHC-I molecules highlighted the biomedical practice for vaccination, and haplotype clusters represented the similarities among individuals during T-cell response establishment. Cross-validation proved the patterns observed through both MD simulation and public data integration. Lastly, 148 HTNV variants yielded six types of major amino acid residue replacements involving four in nine hotspots, which minimally influenced the general potential of MHC-I superfamily presentation. Altogether, our work comprehensively evaluates the pan-MHC-I immunoreactivity of HTNV GP through a state-of-the-art workflow in light of comparative immunology, acknowledges present discoveries, and offers guidance for ongoing HTNV vaccine pursuit.

New Approaches to Dendritic Cell-Based Therapeutic Vaccines Against HIV-1 Infection

Due to the success of combined antiretroviral therapy (cART) in recent years, the pathological outcome of Human Immunodeficiency Virus type 1 (HIV-1) infection has improved substantially, achieving undetectable viral loads in most cases. Nevertheless, the presence of a viral reservoir formed by latently infected cells results in patients having to maintain treatment for life. In the absence of effective eradication strategies against HIV-1, research efforts are focused on obtaining a cure. One of these approaches is the creation of therapeutic vaccines. In this sense, the most promising one up to now is based on the establishing of the immunological synapse between dendritic cells (DCs) and T lymphocytes (TL). DCs are one of the first cells of the immune system to encounter HIV-1 by acting as antigen presenting cells, bringing about the interaction between innate and adaptive immune responses mediated by TL. Furthermore, TL are the end effector, and their response capacity is essential in the adaptive elimination of cells infected by pathogens. In this review, we summarize the knowledge of the interaction between DCs with TL, as well as the characterization of the specific T-cell response against HIV-1 infection. The use of nanotechnology in the design and improvement of vaccines based on DCs has been researched and presented here with a special emphasis.

Machine Learning in Discovery of New Antivirals and Optimization of Viral Infections Therapy

Nowadays, computational approaches play an important role in the design of new drug-like compounds and optimization of pharmacotherapeutic treatment of diseases. The emerging growth of viral infections, including those caused by the Human Immunodeficiency Virus (HIV), Ebola virus, recently detected coronavirus, and some others, leads to many newly infected people with a high risk of death or severe complications. A huge amount of chemical, biological, clinical data is at the disposal of the researchers. Therefore, there are many opportunities to find the relationships between the particular features of chemical data and the antiviral activity of biologically active compounds based on machine learning approaches. Biological and clinical data can also be used for building models to predict relationships between viral genotype and drug resistance, which might help determine the clinical outcome of treatment. In the current study, we consider machine-learning approaches in the antiviral research carried out during the past decade. We overview in detail the application of machine-learning methods for the design of new potential antiviral agents and vaccines, drug resistance prediction, and analysis of virus-host interactions. Our review also covers the perspectives of using the machine-learning approaches for antiviral research, including Dengue, Ebola viruses, Influenza A, Human Immunodeficiency Virus, coronaviruses, and some others.

Role of immunoproteasomes and thymoproteasomes in health and disease

The proteasome is a multisubunit protease that degrades intracellular proteins into small peptides. Besides playing a pivotal role in many cellular processes indispensable for survival, it is involved in the production of peptides presented by major histocompatibility complex class I molecules. In addition to the standard proteasome shared in all eukaryotes, jawed vertebrates have two specialized forms of proteasome known as immunoproteasomes and thymoproteasomes. The immunoproteasome, which contains cytokine-inducible catalytic subunits with distinct cleavage specificities, produces peptides presented by class I molecules more efficiently than the standard proteasome. The thymoproteasome, which contains a unique catalytic subunit β5t, is a tissue-specific proteasome expressed exclusively in cortical thymic epithelial cells. It plays a critical role in CD8⁺ cytotoxic T cell development via positive selection. This review provides a brief overview on the structure and function of these specialized forms of proteasome and their involvement in human disease.