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  1. Objective

    Cutaneous inflammation can signal disease in juvenile dermatomyositis (DM) and childhood‐onset systemic lupus erythematosus (cSLE), but we do not fully understand cellular mechanisms of cutaneous inflammation. In this study, we used imaging mass cytometry to characterize cutaneous inflammatory cell populations and cell–cell interactions in juvenile DM as compared to cSLE.

    Methods

    We performed imaging mass cytometry analysis on skin biopsy samples from juvenile DM patients (n = 6) and cSLE patients (n = 4). Tissue slides were processed and incubated with metal‐tagged antibodies for CD14, CD15, CD16, CD56, CD68, CD11c, HLA–DR, blood dendritic cell antigen 2, CD20, CD27, CD138, CD4, CD8, E‐cadherin, CD31, pan‐keratin, and type I collagen. Stained tissue was ablated, and raw data were acquired using the Hyperion imaging system. We utilized the Phenograph unsupervised clustering algorithm to determine cell marker expression and permutation test by histoCAT to perform neighborhood analysis.

    Results

    We identified 14 cell populations in juvenile DM and cSLE skin, including CD14+ and CD68+ macrophages, myeloid and plasmacytoid dendritic cells (pDCs), CD4+ and CD8+ T cells, and B cells. Overall, cSLE skin had a higher inflammatory cell infiltrate, with increased CD14+ macrophages, pDCs, and CD8+ T cells and immune cell–immune cell interactions. Juvenile DM skin displayed a stronger innate immune signature, with a higher overall percentage of CD14+ macrophages and prominent endothelial cell–immune cell interaction.

    Conclusion

    Our findings identify immune cell population differences, including CD14+ macrophages, pDCs, and CD8+ T cells, in juvenile DM skin compared to cSLE skin, and highlight a predominant innate immune signature and endothelial cell–immune cell interaction in juvenile DM, providing insight into candidate cell populations and interactions to better understand disease‐specific pathophysiology.

     
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  2. Abstract

    Despite promising developments in computational tools, peptide‐class II MHC (MHCII) binding predictors continue to lag behind their peptide‐class I MHC counterparts. Consequently, peptide–MHCII binding is often evaluated experimentally using competitive binding assays, which tend to sacrifice throughput for quantitative binding detail. Here, we developed a high‐throughput semiquantitative peptide–MHCII screening strategy termed microsphere‐assisted peptide screening (MAPS) that aims to balance the accuracy of competitive binding assays with the throughput of computational tools. Using MAPS, we screened a peptide library from Zika virus envelope (E) protein for binding to four common MHCII alleles (DR1, DR4, DR7, DR15). Interestingly, MAPS revealed a significant overlap between peptides that promiscuously bind multiple MHCII alleles and antibody neutralization sites. This overlap was also observed for rotavirus outer capsid glycoprotein VP7, suggesting a deeper relationship between B cell and CD4+T cell specificity which can facilitate the design of broadly protective vaccines to Zika and other viruses.

     
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  3. Virus-like particles (VLPs) have been proposed as an attractive tool in SARS-CoV-2 vaccine development, both as (1) a vaccine candidate with high immunogenicity and low reactogenicity and (2) a substitute for live virus in functional and neutralization assays. Though multiple SARS-CoV-2 VLP designs have already been explored in Sf9 insect cells, a key parameter ensuring VLPs are a viable platform is the VLP spike yield (i.e., spike protein content in VLP), which has largely been unreported. In this study, we show that the common strategy of producing SARS-CoV-2 VLPs by expressing spike protein in combination with the native coronavirus membrane and/or envelope protein forms VLPs, but at a critically low spike yield (~0.04–0.08 mg/L). In contrast, fusing the spike ectodomain to the influenza HA transmembrane domain and cytoplasmic tail and co-expressing M1 increased VLP spike yield to ~0.4 mg/L. More importantly, this increased yield translated to a greater VLP spike antigen density (~96 spike monomers/VLP) that more closely resembles that of native SARS-CoV-2 virus (~72–144 Spike monomers/virion). Pseudotyping further allowed for production of functional alpha (B.1.1.7), beta (B.1.351), delta (B.1.617.2), and omicron (B.1.1.529) SARS-CoV-2 VLPs that bound to the target ACE2 receptor. Finally, we demonstrated the utility of pseudotyped VLPs to test neutralizing antibody activity using a simple, acellular ELISA-based assay performed at biosafety level 1 (BSL-1). Taken together, this study highlights the advantage of pseudotyping over native SARS-CoV-2 VLP designs in achieving higher VLP spike yield and demonstrates the usefulness of pseudotyped VLPs as a surrogate for live virus in vaccine and therapeutic development against SARS-CoV-2 variants.

     
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  4. Comprehending cutaneous lupus Cutaneous lupus erythematosus (CLE) is a disfiguring skin condition that affects most patients with systemic lupus erythematosus (SLE) and can be resistant to treatment even when systemic disease is responsive. Billi et al. analyzed CLE lesions and paired normal-appearing skin biopsies, as well as circulating immune cell subsets, to better understand changes in the skin that drive CLE pathogenesis. Using single-cell RNA sequencing and spatial RNA sequencing, they identified a type I IFN–rich signature in prelesional, normal-looking skin that influenced transcription and cell-cell communication for all major skin cell types. CD16 + dendritic cells, which are associated with SLE, were also shaped by the type I IFN environment, and cells in these sites shifted toward a proinflammatory phenotype. Together, these data provide insights into transcriptional changes in the skin that contribute to CLE pathogenesis. 
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  5. Cutaneous lupus erythematosus (CLE) is a chronic inflammatory skin disease characterized by a diverse cadre of clinical presentations. CLE commonly occurs in patients with systemic lupus erythematosus (SLE), and CLE can also develop in the absence of systemic disease. Although CLE is a complex and heterogeneous disease, several studies have identified common signaling pathways, including those of type I interferons (IFNs), that play a key role in driving cutaneous inflammation across all CLE subsets. However, discriminating factors that drive different phenotypes of skin lesions remain to be determined. Thus, we sought to understand the skin-associated cellular and transcriptional differences in CLE subsets and how the different types of cutaneous inflammation relate to the presence of systemic lupus disease. In this study, we utilized two distinct cohorts comprising a total of 150 CLE lesional biopsies to compare discoid lupus erythematosus (DLE), subacute cutaneous lupus erythematosus (SCLE), and acute cutaneous lupus erythematosus (ACLE) in patients with and without associated SLE. Using an unbiased approach, we demonstrated a CLE subtype-dependent gradient of B cell enrichment in the skin, with DLE lesions harboring a more dominant skin B cell transcriptional signature and enrichment of B cells on immunostaining compared to ACLE and SCLE. Additionally, we observed a significant increase in B cell signatures in the lesional skin from patients with isolated CLE compared with similar lesions from patients with systemic lupus. This trend was driven primarily by differences in the DLE subgroup. Our work thus shows that skin-associated B cell responses distinguish CLE subtypes in patients with and without associated SLE, suggesting that B cell function in skin may be an important link between cutaneous lupus and systemic disease activity. 
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