Mouse genome rewriting and tailoring of three important disease loci.

Genetically engineered mouse models (GEMMs) help us to understand human pathologies and develop new therapies, yet faithfully recapitulating human diseases in mice is challenging. Advances in genomics have highlighted the importance of non-coding regulatory genome sequences, which control spatiotemporal gene expression patterns and splicing in many human diseases1,2. Including regulatory extensive genomic regions, which requires large-scale genome engineering, should enhance the quality of disease modelling. Existing methods set limits on the size and efficiency of DNA delivery, hampering the routine creation of highly informative models that we call genomically rewritten and tailored GEMMs (GREAT-GEMMs). Here we describe 'mammalian switching antibiotic resistance markers progressively for integration' (mSwAP-In), a method for efficient genome rewriting in mouse embryonic stem cells. We demonstrate the use of mSwAP-In for iterative genome rewriting of up to 115 kb of a tailored Trp53 locus, as well as for humanization of mice using 116 kb and 180 kb human ACE2 loci. The ACE2 model recapitulated human ACE2 expression patterns and splicing, and notably, presented milder symptoms when challenged with SARS-CoV-2 compared with the existing K18-hACE2 model, thus representing a more human-like model of infection. Finally, we demonstrated serial genome writing by humanizing mouse Tmprss2 biallelically in the ACE2 GREAT-GEMM, highlighting the versatility of mSwAP-In in genome writing.

Helminth resistance is mediated by differential activation of recruited monocyte-derived alveolar macrophages and arginine depletion.

Macrophages are known to mediate anti-helminth responses, but it remains uncertain which subsets are involved or how macrophages actually kill helminths. Here, we show rapid monocyte recruitment to the lung after infection with the nematode parasite Nippostrongylus brasiliensis. In this inflamed tissue microenvironment, these monocytes differentiate into an alveolar macrophage (AM)-like phenotype, expressing both SiglecF and CD11c, surround invading parasitic larvae, and preferentially kill parasites in vitro. Monocyte-derived AMs (Mo-AMs) express type 2-associated markers and show a distinct remodeling of the chromatin landscape relative to tissue-derived AMs (TD-AMs). In particular, they express high amounts of arginase-1 (Arg1), which we demonstrate mediates helminth killing through L-arginine depletion. These studies indicate that recruited monocytes are selectively programmed in the pulmonary environment to express AM markers and an anti-helminth phenotype.

SARS-CoV-2 exacerbates proinflammatory responses in myeloid cells through C-type lectin receptors and Tweety family member 2.

Despite mounting evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) engagement with immune cells, most express little, if any, of the canonical receptor of SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2). Here, using a myeloid cell receptor-focused ectopic expression screen, we identified several C-type lectins (DC-SIGN, L-SIGN, LSECtin, ASGR1, and CLEC10A) and Tweety family member 2 (TTYH2) as glycan-dependent binding partners of the SARS-CoV-2 spike. Except for TTYH2, these molecules primarily interacted with spike via regions outside of the receptor-binding domain. Single-cell RNA sequencing analysis of pulmonary cells from individuals with coronavirus disease 2019 (COVID-19) indicated predominant expression of these molecules on myeloid cells. Although these receptors do not support active replication of SARS-CoV-2, their engagement with the virus induced robust proinflammatory responses in myeloid cells that correlated with COVID-19 severity. We also generated a bispecific anti-spike nanobody that not only blocked ACE2-mediated infection but also the myeloid receptor-mediated proinflammatory responses. Our findings suggest that SARS-CoV-2-myeloid receptor interactions promote immune hyperactivation, which represents potential targets for COVID-19 therapy.

Gene characterization and expression of the γδ T cell co-receptor WC1 in sheep.

Sheep are known to express the hybrid co-receptor/pattern recognition receptor WC1 on their γδ T cells but details of the ovine WC1 multigenic array and gene expression were unknown. Annotation of the sheep genome assembly (Oar_rambouillet_v1.0) yielded 15 complete and 42 partial WC1 genes predicted to code for six different protein structures. RT-PCR amplification of the most distal scavenger receptor cysteine rich (SRCR) domain known as a1, which serves as the gene signature, from genomic and cDNA templates verified the majority of annotated genes. As for cattle and goats, sheep a1 domain sequences included WC1.1 and WC1.2 types. A unique ovine gene, WC1-16, had multiple SRCR a-pattern domains in tandem similar to one found in goats. Intracytoplasmic domains of WC1 transcripts had splice variants that may affect signal transduction. The larger number of WC1 genes in sheep and differences in structures and splice variants relative to cattle could have implications in expression patterns and engagement of γδ T cells by pathogens or vaccine constructs.

Variegated Transcription of the WC1 Hybrid PRR/Co-Receptor Genes by Individual γδ T Cells and Correlation With Pathogen Responsiveness.

γδ T cells have broad reactivity and actively participate in protective immunity against tumors and infectious disease-causing organisms. In γδ-high species such as ruminants and other artiodactyls many γδ T cells bear the lineage-specific markers known as WC1. WC1 molecules are scavenger receptors coded for by a multigenic array and are closely related to SCART found on murine γδ T cells and CD163 found on a variety of cells. We have previously shown that WC1 molecules are hybrid pattern recognition receptors thereby binding pathogens as well as signaling co-receptors for the γδ T cell receptor. WC1+ γδ T cells can be divided into two major subpopulations differentiated by the WC1 genes they express and the pathogens to which they respond. Therefore, we hypothesize that optimal γδ T cell responses are contingent on pathogen binding to WC1 molecules, especially since we have shown that silencing WC1 results in an inability of γδ T cells from primed animals to respond to the pathogen Leptospira, a model system we have employed extensively. Despite this knowledge about the crucial role WC1 plays in γδ T cell biology, the pattern of WC1 gene expression by individual γδ T cells was not known but is critical to devise methods to engage γδ T cells for responses to specific pathogens. To address this gap, we generated 78 γδ T cell clones. qRT-PCR evaluation showed that approximately 75% of the clones had one to three WC1 genes transcribed but up to six per cell occurred. The co-transcription of WC1 genes by clones showed many combinations and some WC1 genes were transcribed by both subpopulations although there were differences in the overall pattern of WC1 genes transcription. Despite this overlap, Leptospira-responsive WC1+ memory γδ T cell clones were shown to have a significantly higher propensity to express WC1 molecules that are known to bind to the pathogen.