Lysosomal membrane integrity is essential for cell survival, but how damage sensing is spatiotemporally coupled to repair remains poorly understood. Recruitment and assembly of endosomal sorting complex required for transport (ESCRT) I-III rapidly counteracts membrane damage, but it is unclear how ESCRT-I recognizes defective lysosomal membranes. Here, leveraging genome-wide CRISPRi screens in a damage-sensitized genetic background, we identified LC3/GABARAP-assisted stimulator for ESCRT recruitment (LASER), a multicomponent protein assembly that forms rapidly upon calcium release from damaged lysosomes and couples sensing of lysosomal membrane damage to ESCRT-dependent repair. At the core of LASER is TFG, an endoplasmic reticulum exit-site-resident protein that translocates to damaged lysosomes by binding to ATG8 family proteins (LC3 and GABARAP) conjugated to lysosomal phospholipids. ATG8-bound TFG forms oligomeric assemblies that directly recruit the essential ESCRT-I subunit TSG101 via conserved motif recognition enhanced by avidity-driven interactions. TFG binding to TSG101 stimulates sequential ESCRT-I-II-III polymerization and promotes membrane repair. TFG mutations that drive hereditary spastic paraplegia disrupt its oligomerization and impair lysosomal ESCRT recruitment and membrane resealing, implicating defective repair as a driver of TFG-associated neurodegeneration. Thus, LASER promotes ESCRT polymerization at damaged lysosomes and couples damage sensing to membrane repair.

HIV-1 diversified for decades within the Democratic Republic of the Congo (DRC) before spreading globally in the early 1980s. Thus, the DRC is home to some of the most ancestral and diverse HIV-1 strains. Recent serosurveys conducted from 2017 to 2019 in Kinshasa, DRC, indicated high prevalence of HIV-1, yet sequence data is lacking from this period. Given the history of circulating rare HIV-1 subtypes in the DRC, a viral whole-genome sequencing study was conducted to determine current diversity in the greater Kinshasa area. Next-generation sequencing (NGS) through metagenomic and target enrichment methods was conducted on 197 specimens collected from 2017 to 2019. A large array of HIV subtypes (A, B, C, D, F1, G, H, J, and K), circulating recombinant forms (CRF01_AE, CRF02_AG, CRF05_DF, CRF11_cpx, CRF13_cpx, CRF25_cpx, CRF 45_cpx, and CRF92_C2U), unique recombinant forms, and unclassifiable sequences were observed, with many branching in basal positions within, or outside of, many subtypes on phylogenetic trees. Incorporating these new sequences into Bayesian inference of phylogeny pushes back the dates of the most recent common ancestors of HIV-1 group M and the rare subtypes G, H, and J by between 3 and 7 years each. The DRC continues to harbor diverse and rare HIV-1 subtypes that could challenge diagnostic tests, treatments, and vaccines. In addition to shifting subtype emergence dates, the sequences from our study are evidence that rare strains continue to circulate and should be regularly monitored.

Recent advances in functional genomics tools have ushered in a new era of genetic editing to identify molecular pathways relevant to developmental and disease biology. However, limited model systems are available that adequately mimic cell states and phenotypes associated with human disease pathways. Here, we quantitatively analyzed the founder population bottleneck effect and demonstrated how the population changes from human induced pluripotent stem cells (hiPSCs) to hematopoietic stem cells and to the final induced macrophage population. We then engineered a key gene encoding an enzyme in the myeloid cell antiviral pathway-SAMHD1-knockout (KO) hiPSCs and characterized the hiPSC line with RNA-Seq and induced macrophages from two distinct protocols with functional analysis. We then generated SAMHD1 KO CRISPR-dCAS9 KRAB hiPSCs through lentiviral transduction aiming to increase the efficiency of lentiviral mediated gene transfer. We demonstrated increased lentiviral transduction efficiency in induced macrophages, as well as microglia induced with two distinct protocols. This model allows for efficient gene knockdown, as well as large-scale functional genomics screens in mature hiPSC-derived macrophages or microglia with applications in innate immunity and chronic inflammatory disease biology. These experiments highlight the broad applicability of this platform for disease-relevant target identification and may improve our ability to run large-scale screens in hiPSC-derived myeloid model systems.

The ability to identify gene functions and interactions in specific cellular contexts has been greatly enabled by functional genomics technologies. CRISPR-based genetic screens have proven invaluable in elucidating gene function in mammalian cells. Single-cell functional genomics methods, such as Perturb-seq and Spear-ATAC, have made it possible to achieve high-throughput mapping of the functional effects of gene perturbations by profiling transcriptomes and DNA accessibility, respectively. Combining single-cell chromatin accessibility and transcriptomic data via multiomic approaches has facilitated the discovery of novel cis and gene regulatory interactions. However, pseudobulk readouts from cell populations can often cloud the interpretation of results due to a heterogeneous response from cells receiving the same genetic perturbation, which could be mitigated by using transcriptional profiles of single cells to subset the ATAC-seq data. Existing methods to capture CRISPR guide RNAs to simultaneously assess the impact of genetic perturbations on RNA and ATAC profiles require either cloning of gRNA libraries in specialized vectors or implementing complex protocols with multiple rounds of barcoding. Here, we introduce CAT-ATAC, a technique that adds CRISPR gRNA capture to the existing 10X Genomics Multiome assay, generating paired transcriptome, chromatin accessibility and perturbation identity data from the same individual cells. We demonstrate up to 77% guide capture efficiency for both arrayed and pooled delivery of lentiviral gRNAs in induced pluripotent stem cells (iPSCs) and cancer cell lines. This capability allows us to construct gene regulatory networks (GRNs) in cells under drug and genetic perturbations. By applying CAT-ATAC, we were able to identify a GRN associated with dasatinib resistance, indirectly activated by the HIC2 gene. Using loss of function experiments, we further validated that the gene, ZFPM2, a component of the predicted GRN, also contributes to dasatinib resistance. CAT-ATAC can thus be used to generate high-content multidimensional genotype-phenotype maps to reveal novel gene and cellular interactions and functions. ### Competing Interest Statement Y.A.Y, V.S, J.P, R.E, G.A and S.S are employees of GSK. E.D.C. is a co-founder of Survey Genomics.

Recent advances in functional genomics tools have ushered in a new era of genetic editing to identify molecular pathways relevant to developmental and disease biology. However, limited model systems are available that adequately mimic cell states and phenotypes associated with human disease pathways. Here, we quantitatively analyzed the founder population bottleneck effect and demonstrated how the population changes from induced pluripotent stem cells (iPSCs) to hematopoietic stem cells and to the final induced macrophage population. We then engineered SAMHD1 knockout (KO) iPSC and characterized the iPSC line with RNA Seq, and induced macrophages from two distinct protocols with functional analysis. We then generated SAMHD1 KO CRISPR-dCAS9 KRAB iPSC through lenti-viral transduction aiming to increase the efficiency of lentiviral mediated gene transfer. We demonstrated increased lenti-viral transduction efficiency in induced macrophage, as well as microglia induced with two distinct protocols. This model allows for efficient gene knock down, as well as large-scale functional genomics screens in mature iPSC-derived macrophages or microglia with applications in innate immunity and chronic inflammatory disease biology. These experiments highlight the broad applicability of this platform for disease-relevant target identification and may improve our ability to run large-scale screens in iPSC-derived myeloid model systems. ### Competing Interest Statement MA, YAY, RE and SS are employees of GSK.

Here, we introduce CRISPR and transcriptomics-assay for transposase-accessible chromatin (CAT-ATAC), a technique that adds CRISPR guide RNA (gRNA) capture to the existing 10× Genomics Multiome assay, generating linked transcriptome, chromatin accessibility, and perturbation identity data from the same individual cells. We demonstrate up to 77% capture rate for both arrayed and pooled delivery of lentiviral gRNAs in induced pluripotent stem cells (iPSCs) and cancer cell lines. This capability allows us to construct gene regulatory networks (GRNs) in cells under drug and genetic perturbations. By applying CAT-ATAC, we identified a GRN associated with dasatinib resistance, indirectly activated by the HIC2 gene. Using loss-of-function experiments, we further validated that ZFPM2, a component of the predicted GRN, also contributes to dasatinib resistance. CAT-ATAC can thus be used to generate high-content multidimensional genotype-phenotype maps to reveal gene and cellular interactions and functions.

CRISPR genome editing approaches theoretically enable researchers to define the function of each human gene in specific cell types, but challenges remain to efficiently perform genetic perturbations in relevant models. In this work, we develop a library cloning protocol that increases sgRNA uniformity and greatly reduces bias in existing genome-wide libraries. We demonstrate that our libraries can achieve equivalent or better statistical power compared to previously reported screens using an order of magnitude fewer cells. This improved cloning protocol enables genome-scale CRISPR screens in technically challenging cell models and screen formats.

Kidney disease is highly heritable; however, the causal genetic variants, the cell types in which these variants function, and the molecular mechanisms underlying kidney disease remain largely unknown. To identify genetic loci affecting kidney function, we performed a GWAS using multiple kidney function biomarkers and identified 462 loci. To begin to investigate how these loci affect kidney function, we generated single-cell chromatin accessibility (scATAC-seq) maps of the human kidney and identified candidate cis-regulatory elements (cCREs) for kidney podocytes, tubule epithelial cells, and kidney endothelial, stromal, and immune cells. Kidney tubule epithelial cCREs explained 58% of kidney function SNP-heritability and kidney podocyte cCREs explained an additional 6.5% of SNP-heritability. In contrast, little kidney function heritability was explained by kidney endothelial, stromal, or immune cell-specific cCREs. Through functionally informed fine-mapping, we identified putative causal kidney function variants and their corresponding cCREs. Using kidney scATAC-seq data, we created a deep learning model (which we named ChromKid) to predict kidney cell type-specific chromatin accessibility from sequence. ChromKid and allele specific kidney scATAC-seq revealed that many fine-mapped kidney function variants locally change chromatin accessibility in tubule epithelial cells. Enhancer assays confirmed that fine-mapped kidney function variants alter tubule epithelial regulatory element function. To map the genes which these regulatory elements control, we used CRISPR interference (CRISPRi) to target these regulatory elements in tubule epithelial cells and assessed changes in gene expression. CRISPRi of enhancers harboring kidney function variants regulated NDRG1 and RBPMS expression. Thus, inherited differences in tubule epithelial NDRG1 and RBPMS expression may predispose to kidney disease in humans. We conclude that genetic variants affecting tubule epithelial regulatory element function account for most SNP-heritability of human kidney function. This work provides an experimental approach to identify the variants, regulatory elements, and genes involved in polygenic disease.

Background/Aim: Plasma Epstein-Barr virus (EBV) viral load measurement is prognostic in nasopharyngeal carcinoma (NPC) disease monitoring; however, a consensus measurement approach does not exist. This study characterized the clinical performance of metagenomic next-generation sequencing (mNGS), an unbiased sequencing-based assay distinct from polymerase chain reaction (PCR) or targeted sequencing approaches, in 73 peripheral blood specimens from 32 patients diagnosed with NPC. Patients and Methods: Samples were analyzed for plasma EBV viral load either by mNGS profiling or PCR-based assays (either LMP2 or BAMHI-W PCR) and compared to tumor presence by clinical assessment. Plasma mNGS-based EBV detection was quantified as reads per million (RPM). Results: Plasma mNGS displayed similar overall performance (100% sensitivity, 86% specificity, 92% accuracy) to BAMHI-W PCR (100% sensitivity, 86% specificity, 94% accuracy) and superior performance to the LMP2 PCR assay (36% sensitivity, 56% specificity, 45% accuracy). In a subset of 13 patients who underwent longitudinal analysis, plasma mNGS EBV RPM correlated with cancer recurrence (95%CI PreCRT=232.10 +/- 214; 95%CI Post-CRT=0.34 +/- 0.32; 95%CI difference=-231.70 +/- 214; *p=0.03, paired t-test), suggesting

The human gut virome and its early life development are poorly understood. Prior studies have captured sin-gle-point assessments with the evolution of the infant virome remaining largely unexplored. We performed viral metagenomic sequencing on stool samples collected longitudinally from a cohort of 53 infants from age 2 weeks to 3 years (80.7 billion reads), and from their mothers (9.8 billion reads) to examine and compare viromes. The asymptomatic infant virome consisted of bacteriophages, nonhuman dietary/environmental vi-ruses, and human-host viruses, predominantly picornaviruses. In contrast, human-host viruses were largely absent from the maternal virome. Previously undescribed, sequence-divergent vertebrate viruses were de-tected in the maternal but not infant virome. As infants aged, the phage component evolved to resemble the maternal virome, but by age 3, the human-host component remained dissimilar from the maternal virome. Thus, early life virome development is determined predominantly by dietary, infectious, and environmental factors rather than direct maternal acquisition.

Metagenomic next-generation sequencing (mNGS) has enabled the high-throughput multiplexed identification of sequences from microbes of potential medical relevance. This approach has become indispensable for viral pathogen discovery and broad-based surveillance of emerging or re-emerging pathogens. From 2015 to 2019, plasma was collected from 9586 individuals in Cameroon and the Democratic Republic of the Congo enrolled in a combined hepatitis virus and retrovirus surveillance program. A subset (n = 726) of the patient specimens was analyzed by mNGS to identify viral co-infections. While co-infections from known blood-borne viruses were detected, divergent sequences from nine poorly characterized or previously uncharacterized viruses were also identified in two individuals. These were assigned to the following groups by genomic and phylogenetic analyses: densovirus, nodavirus, jingmenvirus, bastrovirus, dicistrovirus, picornavirus, and cyclovirus. Although of unclear pathogenicity, these viruses were found circulating at high enough concentrations in plasma for genomes to be assembled and were most closely related to those previously associated with bird or bat excrement. Phylogenetic analyses and in silico host predictions suggested that these are invertebrate viruses likely transmitted through feces containing consumed insects or through contaminated shellfish. This study highlights the power of metagenomics and in silico host prediction in characterizing novel viral infections in susceptible individuals, including those who are immunocompromised from hepatitis viruses and retroviruses, or potentially exposed to zoonotic viruses from animal reservoir species.

Pathogens carried by insects, such as bunyaviruses, are frequently transmitted into human populations and cause diseases. Knowing which spillover events represent a public health threat remains a challenge. Metagenomic next-generation sequencing (mNGS) can support infectious disease diagnostics by enabling the detection of any pathogen from clinical specimens. mNGS was performed on blood samples to identify potential viral coinfections in human immunodeficiency virus (HIV)-positive individuals from Kinshasa, the Democratic Republic of the Congo (DRC), participating in an HIV diversity cohort study. Time-resolved phylogenetics and molecular assay development assisted in viral characterization. The nearly complete genome of a novel orthobunyavirus related to Nyangole virus, a virus previously identified in neighboring Uganda, was assembled from a hepatitis B virus-positive patient. A quantitative polymerase chain reaction assay was designed and used to screen >2,500 plasma samples from Cameroon, the DRC, and Uganda, failing to identify any additional cases. The recent sequencing of a US Center for Disease Control Arbovirus Reference Collection revealed that this same virus, now named Bangui virus, was first isolated in 1970 from an individual in the Central African Republic. Time-scaled phylogenetic analyses of Bangui with the related Anopheles and Tanga serogroup complexes indicate that this virus emerged nearly 10,000 years ago. Pervasive and episodic models further suggest that this virus is under purifying selection and that only distant common ancestors were subject to positive selection events. This study represents only the second identification of a Bangui virus infection in over 50 years. The presumed rarity of Bangui virus infections in humans can be explained by its constraint to an avian host and insect vector, precluding efficient transmission into the human population. Our results demonstrate that molecular phylogenetic analyses can provide insights into the threat posed by novel or re-emergent viruses identified by mNGS.

ABSTRACT The development of CRISPR genetic screening tools has improved functional genomics, as these tools enable precise genomic editing, provide broad access to genomic regions beyond protein-coding genes, and have fewer off-target effects than other functional genomics modalities, allowing for novel applications with smaller library sizes compared to prior technologies. Pooled functional genomics screens require high cellular coverage per perturbation to accurately quantify phenotypes and average out phenotype-independent variability across the population. While more compact libraries have decreased the number of cells needed for a given screen, the cell coverage required for large-scale CRISPR screens still poses technical hurdles to screen in more challenging systems, such as iPSC-derived and primary cells. A major factor that influences cell coverage is screening library uniformity, as larger variation in individual guide RNA abundance requires higher cell coverage to reliably measure low-abundance guides. In this work, we have systematically optimized guide RNA cloning procedures to decrease bias. We implement these protocols to demonstrate that CRISPRi screens using 10-fold fewer cells than the current standard provides equivalent statistically significant hit-calling results to screens run at higher coverage, opening the possibility of conducting genome-wide and other large-scale CRISPR screens in technically challenging models.

We identified a novel SARS-CoV-2 variant by viral whole-genome sequencing of 2,172 nasal/nasopharyngeal swab samples from 44 counties in California. Named B.1.427/B.1.429 to denote its 2 lineages, the variant emerged around May 2020 and increased from 0% to >50% of sequenced cases from September 1, 2020 to January 29, 2021, exhibiting an 18.6-24% increase in transmissibility relative to wild-type circulating strains. The variant carries 3 mutations in the spike protein, including an L452R substitution. Our analyses revealed 2-fold increased B.1.427/B.1.429 viral shedding in vivo and increased L452R pseudovirus infection of cell cultures and lung organoids, albeit decreased relative to pseudoviruses carrying the N501Y mutation found in the B.1.1.7, B.1.351, and P.1 variants. Antibody neutralization assays showed 4.0 to 6.7-fold and 2.0-fold decreases in neutralizing titers from convalescent patients and vaccine recipients, respectively. The increased prevalence of a more transmissible variant in California associated with decreased antibody neutralization warrants further investigation.

This dataset contains the following: genome fasta files from viral whole-genome sequencing of SARS-CoV-2 positive nasal/nasopharyngeal swabs codes used to analyze epidemiologic data (i.e. logistic growth curves, transmission rate, doubling time) and generate plots and figures codes used to perform statistical analysis and visualization of viral loads phylogenetic analyses description, trees, and logs supplementary tables with relevant sample information

We combined viral genome sequencing with contact tracing to investigate introduction and evolution of severe acute respiratory syndrome coronavirus 2 lineages in Santa Clara County, California, from 27 January to 21 March 2020. From 558 persons with coronavirus disease 2019, 101 genomes from 143 available clinical samples comprised 17 lineages, including SCC1 (n = 41), WA1 (n = 9; including the first 2 reported deaths in the United States, with postmortem diagnosis), D614G (n = 4), ancestral Wuhan Hu-1 (n = 21), and 13 others (n = 26). Public health intervention may have curtailed the persistence of lineages that appeared transiently during February and March. By August, only D614G lineages introduced after 21 March were circulating in Santa Clara County.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease-19 (COVID-19), has emerged as the cause of a global pandemic. We used RNA sequencing to analyze 286 nasopharyngeal (NP) swab and 53 whole-blood (WB) samples from 333 patients with COVID-19 and controls. Overall, a muted immune response was observed in COVID-19 relative to other infections (influenza, other seasonal coronaviruses, and bacterial sepsis), with paradoxical down-regulation of several key differentially expressed genes. Hospitalized patients and outpatients exhibited up-regulation of interferon-associated pathways, although heightened and more robust inflammatory responses were observed in hospitalized patients with more clinically severe illness. Two-layer machine learning-based host classifiers consisting of complete (>1000 genes), medium (<100), and small (<20) gene biomarker panels identified COVID-19 disease with 85.1-86.5% accuracy when benchmarked using an independent test set. SARS-CoV-2 infection has a distinct biosignature that differs between NP swabs and WB and can be leveraged for COVID-19 diagnosis.

Importance:Cerebrospinal fluid (CSF) cytologic testing and flow cytometry are insensitive for diagnosing neoplasms of the central nervous system (CNS). Such clinical phenotypes can mimic infectious and autoimmune causes of meningoencephalitis.Objective:To ascertain whether CSF metagenomic next-generation sequencing (mNGS) can identify aneuploidy, a hallmark of malignant neoplasms, in difficult-to-diagnose cases of CNS malignant neoplasm.Design, Setting, and Participants:Two case-control studies were performed at the University of California, San Francisco (UCSF). The first study used CSF specimens collected at the UCSF Clinical Laboratories between July 1, 2017, and December 31, 2019, and evaluated test performance in specimens from patients with a CNS malignant neoplasm (positive controls) or without (negative controls). The results were compared with those from CSF cytologic testing and/or flow cytometry. The second study evaluated patients who were enrolled in an ongoing prospective study between April 1, 2014, and July 31, 2019, with presentations that were suggestive of neuroinflammatory disease but who were ultimately diagnosed with a CNS malignant neoplasm. Cases of individuals whose tumors could have been detected earlier without additional invasive testing are discussed.Main Outcomes and Measures:The primary outcome measures were the sensitivity and specificity of aneuploidy detection by CSF mNGS. Secondary subset analyses included a comparison of CSF and tumor tissue chromosomal abnormalities and the identification of neuroimaging characteristics that were associated with test performance.Results:Across both studies, 130 participants were included (median [interquartile range] age, 57.5 [43.3-68.0] years; 72 men [55.4%]). The test performance study used 125 residual laboratory CSF specimens from 47 patients with a CNS malignant neoplasm and 56 patients with other neurological diseases. The neuroinflammatory disease study enrolled 12 patients and 17 matched control participants. The sensitivity of the CSF mNGS assay was 75% (95% CI, 63%-85%), and the specificity was 100% (95% CI, 96%-100%). Aneuploidy was detected in 64% (95% CI, 41%-83%) of the patients in the test performance study with nondiagnostic cytologic testing and/or flow cytometry, and in 55% (95% CI, 23%-83%) of patients in the neuroinflammatory disease study who were ultimately diagnosed with a CNS malignant neoplasm. Of the patients in whom aneuploidy was detected, 38 (90.5%) had multiple copy number variations with tumor fractions ranging from 31% to 49%.Conclusions and Relevance:This case-control study showed that CSF mNGS, which has low specimen volume requirements, does not require the preservation of cell integrity, and was orginally developed to diagnose neurologic infections, can also detect genetic evidence of a CNS malignant neoplasm in patients in whom CSF cytologic testing and/or flow cytometry yielded negative results with a low risk of false-positive results.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.