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Versatile and precise genome modifications are needed to create a wider range of adoptive cellular therapies 1 – 5 . Here we report two improvements that increase the efficiency of CRISPR–Cas9-based genome editing in clinically relevant primary cell types. Truncated Cas9 target sequences (tCTSs) added at the ends of the homology-directed repair (HDR) template interact with Cas9 ribonucleoproteins (RNPs) to shuttle the template to the nucleus, enhancing HDR efficiency approximately two- to fourfold. Furthermore, stabilizing Cas9 RNPs into nanoparticles with polyglutamic acid further improves editing efficiency by approximately twofold, reduces toxicity, and enables lyophilized storage without loss of activity. Combining the two improvements increases gene targeting efficiency even at reduced HDR template doses, yielding approximately two to six times as many viable edited cells across multiple genomic loci in diverse cell types, such as bulk (CD3 + ) T cells, CD8 + T cells, CD4 + T cells, regulatory T cells (Tregs), γδ T cells, B cells, natural killer cells, and primary and induced pluripotent stem cell-derived 6 hematopoietic stem progenitor cells (HSPCs). Precise genome editing is made more efficient by stabilizing Cas9 and enhancing shuttling to the nucleus.

Runt domain-related (Runx) transcription factors are essential for early T cell development in mice from uncommitted to committed stages. Single and double Runx knockouts via Cas9 show that target genes responding to Runx activity are not solely controlled by the dominant factor, Runx1. Instead, Runx1 and Runx3 are coexpressed in single cells; bind to highly overlapping genomic sites; and have redundant, collaborative functions regulating genes pivotal for T cell development. Despite stable combined expression levels across pro-T cell development, Runx1 and Runx3 preferentially activate and repress genes that change expression dynamically during lineage commitment, mostly activating T-lineage genes and repressing multipotent progenitor genes. Furthermore, most Runx target genes are sensitive to Runx perturbation only at one stage and often respond to Runx more for expression transitions than for maintenance. Contributing to this highly stage-dependent gene regulation function, Runx1 and Runx3 extensively shift their binding sites during commitment. Functionally distinct Runx occupancy sites associated with stage-specific activation or repression are also distinguished by different patterns of partner factor cobinding. Finally, Runx occupancies change coordinately at numerous clustered sites around positively or negatively regulated targets during commitment. This multisite binding behavior may contribute to a developmental “ratchet” mechanism making commitment irreversible.

The authors use tiled CRISPR activation for functional enhancer discovery across two autoimmunity risk loci, CD69 and IL2RA , and identify elements with features of stimulus-responsive enhancers, including an IL2RA enhancer that harbours a fine-mapped autoimmunity risk variant. CRISPRa mapping of enhancer functions Enhancers are gene regulatory elements that shape cell-type-specific transcriptional programs and responses to specific extracellular cues. Mapping enhancer function is challenging because of our limited understanding of the cellular context in which each enhancer contributes to gene regulation. Here, Alexander Marson and colleagues use a tiled CRISPR activation (CRISPRa) approach for functional enhancer discovery across two autoimmunity risk loci: CD69 and IL2RA. They identify several elements with features of stimulus-responsive enhancers, including an IL2RA enhancer that contains an autoimmunity risk variant. This approach should be useful for discovering functional enhancers without prior knowledge of their specific biological context. The majority of genetic variants associated with common human diseases map to enhancers, non-coding elements that shape cell-type-specific transcriptional programs and responses to extracellular cues 1 , 2 , 3 . Systematic mapping of functional enhancers and their biological contexts is required to understand the mechanisms by which variation in non-coding genetic sequences contributes to disease. Functional enhancers can be mapped by genomic sequence disruption 4 , 5 , 6 , but this approach is limited to the subset of enhancers that are necessary in the particular cellular context being studied. We hypothesized that recruitment of a strong transcriptional activator to an enhancer would be sufficient to drive target gene expression, even if that enhancer was not currently active in the assayed cells. Here we describe a discovery platform that can identify stimulus-responsive enhancers for a target gene independent of stimulus exposure. We used tiled CRISPR activation (CRISPRa) 7 to synthetically recruit a transcriptional activator to sites across large genomic regions (more than 100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA . We identified several CRISPRa-responsive elements with chromatin features of stimulus-responsive enhancers, including an IL2RA enhancer that harbours an autoimmunity risk variant. Using engineered mouse models, we found that sequence perturbation of the disease-associated Il2ra enhancer did not entirely block Il2ra expression, but rather delayed the timing of gene activation in response to specific extracellular signals. Enhancer deletion skewed polarization of naive T cells towards a pro-inflammatory T helper (T H 17) cell state and away from a regulatory T cell state. This integrated approach identifies functional enhancers and reveals how non-coding variation associated with human immune dysfunction alters context-specific gene programs.

Human Immunodeficiency Virus (HIV) relies on host molecular machinery for replication. Systematic attempts to genetically or biochemically define these host factors have yielded hundreds of candidates, but few have been functionally validated in primary cells. Here, we target 426 genes previously implicated in the HIV lifecycle through protein interaction studies for CRISPR-Cas9-mediated knock-out in primary human CD4+ T cells in order to systematically assess their functional roles in HIV replication. We achieve efficient knockout (>50% of alleles) in 364 of the targeted genes and identify 86 candidate host factors that alter HIV infection. 47 of these factors validate by multiplex gene editing in independent donors, including 23 factors with restrictive activity. Both gene editing efficiencies and HIV-1 phenotypes are highly concordant among independent donors. Importantly, over half of these factors have not been previously described to play a functional role in HIV replication, providing numerous novel avenues for understanding HIV biology. These data further suggest that host-pathogen protein-protein interaction datasets offer an enriched source of candidates for functional host factor discovery and provide an improved understanding of the mechanics of HIV replication in primary T cells. Here, Hiatt et al. report the knock-out of over 400 genes in primary CD4+ T cells to assess their functional role in HIV replication, finding 86 initial candidates of which 47 are validated as HIV host factors, including 23 with restrictive activity.

Abstract Context Recent studies using skin biopsy suggest presence of small-fiber neuropathy in subclinical hypothyroidism. This study uses two noninvasive methods—the laser Doppler imager flare technique (LDIFLARE) and corneal confocal microscopy (CCM)—to assess small-fiber function (SFF) and small-fiber structure (SFS), respectively, in newly diagnosed hypothyroidism (HT) before and after adequate treatment. Design and Setting Single-center, prospective, intervention-based cohort study. Patients and Participants Twenty patients with newly diagnosed HT (15 with primary HT and 5 with post-radioiodine HT) along with 20 age-matched healthy controls (HCs). Interventions Patients with HT and HCs were assessed neurologically at diagnosis and baseline, respectively. The HT group was reassessed after optimal replacement (defined as TSH level of 0.27 to 4.20 mIU/L) with levothyroxine (LT4) and HCs were reviewed after 1 year. Main Outcome Measures Neurologic assessment for small fibers was performed by using LDIFLARE for SFF and CCM for SFS; large fibers were studied by sural nerve conduction velocity (SNCV) and sural nerve amplitude (SNAP). Results At baseline, both LDIFLARE (mean ± SD) (6.74 ± 1.20 vs 8.90 ± 1.75 cm2; P = 0.0002) and CCM nerve fiber density (CNFD) (expressed as number of fibers per mm2: 50.77 ± 6.54 vs 58.32 ± 6.54; P = 0.002) were significantly reduced in the HT group compared with HCs whereas neither SNCV nor SNAP was different (P ≥ 0.05). After optimal LT4 treatment, both LDIFLARE (7.72 ± 1.12 vs 6.74 ± 1.20 cm2; P ≤ 0.0001) and CNFD (54.43 ± 5.70 vs 50.77 ± 6.54 no./mm2; P = 0.02) improved significantly but remained significantly reduced compared to HCs (P = 0.008 and P = 0.01, respectively) despite normalization of TSH. Conclusions This study demonstrates that dysfunction of small fibers precedes large neural fiber abnormalities in early HT. This can be reversed by replacement therapy to achieve a biochemically euthyroid state, but small-fiber neural outcomes continued to remain low compared with values in HCs. Neurologic dysfunction in untreated HT is more sensitively detected by using methods of small-fiber function and structure than using methods for large-fiber neuropathy.

The laser Doppler imaging (LDI) FLARE and corneal confocal microscopy (CCM) are reliable markers of small fibre function (SFF) and structure (SFS), respectively, but the impact of potential confounding variables needs to be defined. The objective of this study was to determine the influence of age, anthropometric and biochemical variables on LDI and CCM. 80 healthy volunteers (43 males) (age: 39.7±15.2 yrs.) underwent LDIFLARE and CCM assessment and the effect of age, anthropometric and biochemical variables was determined using multivariate analysis. There was an age-related decline in LDIFLARE (0.07cm2/yr; R2 = 0.669; p = <0.0001) and CCM parameters (CNFD: 0.05 fibres/mm2 /yr; R2 = 0.590; p = <0.0001, CNBD: 0.06 branches/mm2/yr; R2 = 0.549; p = 0.001and CNFL 0.07 mm/mm2/yr; R2 = 0.369; p = 0.009). BMI did not influence SFF (p = 0.08) but had a significant independent association with CNFD (p = 0.01). Fasting triglycerides (TG) independently influenced the LDIFLARE (βc:-0.204; p = 0.008) and all CCM indices (βc:-0.191 to -0.243; p = <0.05). HbA1c was significantly associated with CNFD only (p = 0.001) but not with LDIFLARE, CNBD or CNFL (p = ≥0.05). Blood pressure and total cholesterol were not associated with LDIFLARE or any CCM parameters. There was a significant correlation between LDIFLARE and all CCM parameters (p = ≤0.01). This study shows that in healthy controls, both SFF measured by LDIFLARE and SFS assessed by CCM showed a significant inverse correlation with age and triglycerides, perhaps suggesting the use of age-specific normative values when interpreting these outcomes. Furthermore, this study shows that in healthy controls, despite measuring different neural parameters, both methods correlated significantly with each other.

In this Letter, analysis of steady-state regulatory T (Treg) cell percentages from Il2ra enhancer deletion (EDEL) and wild-type (WT) mice revealed no differences between them (Extended Data Fig. 9d). This analysis included two mice whose genotypes were incorrectly assigned. Even after correction of the genotypes, no significant differences in Treg cell percentages were seen when data across experimental cohorts were averaged (as was done in Extended Data Fig. 9d). However, if we normalize the corrected data to account for variation among experimental cohorts, a subtle decrease in EDEL Treg cell percentages is revealed and, using the corrected and normalized data, we have redrawn Extended Data Fig. 9d in Supplementary Fig. 1. The Supplementary Information to this Amendment contains the corrected and reanalysed Extended Data Fig. 9d. The sentence “This enhancer deletion (EDEL) strain also had no obvious T cell phenotypes at steady state (Extended Data Fig. 9).” should read: “This enhancer deletion (EDEL) strain had a small decrease in the percentage of Treg cells (Extended Data Fig. 9).”. This error does not affect any of the main figures in the Letter or the data from mice with the human autoimmune-associated single nucleotide polymorphism (SNP) knocked in or with a 12-base-pair deletion at the site (12DEL). In addition, we stated in the Methods that we observed consistent immunophenotypes of EDEL mice across three founders, but in fact, we observed consistent phenotypes in mice from two founders. This does not change any of our conclusions and the original Letter has not been corrected.

Decades of work have aimed to genetically reprogram T cells for therapeutic purposes 1 , 2 using recombinant viral vectors, which do not target transgenes to specific genomic sites 3 , 4 . The need for viral vectors has slowed down research and clinical use as their manufacturing and testing is lengthy and expensive. Genome editing brought the promise of specific and efficient insertion of large transgenes into target cells using homology-directed repair 5 , 6 . Here we developed a CRISPR–Cas9 genome-targeting system that does not require viral vectors, allowing rapid and efficient insertion of large DNA sequences (greater than one kilobase) at specific sites in the genomes of primary human T cells, while preserving cell viability and function. This permits individual or multiplexed modification of endogenous genes. First, we applied this strategy to correct a pathogenic IL2RA mutation in cells from patients with monogenic autoimmune disease, and demonstrate improved signalling function. Second, we replaced the endogenous T cell receptor ( TCR ) locus with a new TCR that redirected T cells to a cancer antigen. The resulting TCR-engineered T cells specifically recognized tumour antigens and mounted productive anti-tumour cell responses in vitro and in vivo. Together, these studies provide preclinical evidence that non-viral genome targeting can enable rapid and flexible experimental manipulation and therapeutic engineering of primary human immune cells. A non-viral strategy to introduce large DNA sequences into T cells enables the correction of a pathogenic mutation that causes autoimmunity, and the replacement of an endogenous T-cell receptor with an engineered receptor that can recognize cancer antigens.

The laser Doppler imaging (LDI) .sub.FLARE and corneal confocal microscopy (CCM) are reliable markers of small fibre function (SFF) and structure (SFS), respectively, but the impact of potential confounding variables needs to be defined. The objective of this study was to determine the influence of age, anthropometric and biochemical variables on LDI and CCM. 80 healthy volunteers (43 males) (age: 39.7±15.2 yrs.) underwent LDI.sub.FLARE and CCM assessment and the effect of age, anthropometric and biochemical variables was determined using multivariate analysis. There was an age-related decline in LDI.sub.FLARE (0.07cm.sup.2 /yr; R.sup.2 = 0.669; p = <0.0001) and CCM parameters (CNFD: 0.05 fibres/mm.sup.2 /yr; R.sup.2 = 0.590; p = <0.0001, CNBD: 0.06 branches/mm.sup.2 /yr; R.sup.2 = 0.549; p = 0.001and CNFL 0.07 mm/mm.sup.2 /yr; R.sup.2 = 0.369; p = 0.009). BMI did not influence SFF (p = 0.08) but had a significant independent association with CNFD (p = 0.01). Fasting triglycerides (TG) independently influenced the LDI.sub.FLARE ([beta].sub.c :-0.204; p = 0.008) and all CCM indices ([beta].sub.c :-0.191 to -0.243; p = <0.05). HbA.sub.1c was significantly associated with CNFD only (p = 0.001) but not with LDI.sub.FLARE, CNBD or CNFL (p = [greater than or equal to]0.05). Blood pressure and total cholesterol were not associated with LDI.sub.FLARE or any CCM parameters. There was a significant correlation between LDI.sub.FLARE and all CCM parameters (p = [less than or equal to]0.01). This study shows that in healthy controls, both SFF measured by LDI.sub.FLARE and SFS assessed by CCM showed a significant inverse correlation with age and triglycerides, perhaps suggesting the use of age-specific normative values when interpreting these outcomes. Furthermore, this study shows that in healthy controls, despite measuring different neural parameters, both methods correlated significantly with each other.