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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.

BackgroundMass distribution of azithromycin to preschool children twice yearly for 2 years has been shown to reduce childhood mortality in sub-Saharan Africa but at the cost of amplifying macrolide resistance. The effects on the gut resistome, a reservoir of antimicrobial resistance genes in the body, of twice-yearly administration of azithromycin for a longer period are unclear.MethodsWe investigated the gut resistome of children after they received twice-yearly distributions of azithromycin for 4 years. In the Niger site of the MORDOR trial, we enrolled 30 villages in a concurrent trial in which they were randomly assigned to receive mass distribution of either azithromycin or placebo, offered to all children 1 to 59 months of age every 6 months for 4 years. Rectal swabs were collected at baseline, 36 months, and 48 months for analysis of the participants' gut resistome. The primary outcome was the ratio of macrolide-resistance determinants in the azithromycin group to those in the placebo group at 48 months.ResultsOver the entire 48-month period, the mean (±SD) coverage was 86.6±12% in the villages that received placebo and 83.2±16.4% in the villages that received azithromycin. A total of 3232 samples were collected during the entire trial period; of the samples obtained at the 48-month monitoring visit, 546 samples from 15 villages that received placebo and 504 from 14 villages that received azithromycin were analyzed. Determinants of macrolide resistance were higher in the azithromycin group than in the placebo group: 7.4 times as high (95% confidence interval [CI], 4.0 to 16.7) at 36 months and 7.5 times as high (95% CI, 3.8 to 23.1) at 48 months. Continued mass azithromycin distributions also selected for determinants of nonmacrolide resistance, including resistance to beta-lactam antibiotics, an antibiotic class prescribed frequently in this region of Africa.ConclusionsAmong villages assigned to receive mass distributions of azithromycin or placebo twice yearly for 4 years, antibiotic resistance was more common in the villages that received azithromycin than in those that received placebo. This trial showed that mass azithromycin distributions may propagate antibiotic resistance. (Funded by the Bill and Melinda Gates Foundation and others; ClinicalTrials.gov number, NCT02047981.).

We developed a metagenomic next-generation sequencing (mNGS) test using cell-free DNA from body fluids to identify pathogens. The performance of mNGS testing of 182 body fluids from 160 patients with acute illness was evaluated using two sequencing platforms in comparison to microbiological testing using culture, 16S bacterial PCR and/or 28S–internal transcribed ribosomal gene spacer (28S–ITS) fungal PCR. Test sensitivity and specificity of detection were 79 and 91% for bacteria and 91 and 89% for fungi, respectively, by Illumina sequencing; and 75 and 81% for bacteria and 91 and 100% for fungi, respectively, by nanopore sequencing. In a case series of 12 patients with culture/PCR-negative body fluids but for whom an infectious diagnosis was ultimately established, seven (58%) were mNGS positive. Real-time computational analysis enabled pathogen identification by nanopore sequencing in a median 50-min sequencing and 6-h sample-to-answer time. Rapid mNGS testing is a promising tool for diagnosis of unknown infections from body fluids. A universal method enables high-specificity, unbiased pathogen detection from diverse body fluids using metagenomic sequencing and may accelerate clinical decisions.

SUMMARYTumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth, expansion to neighboring and distal tissues, and therapeutic resistance. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma which enabled us to track tumor evolution from single transformed cells to metastatic tumors at unprecedented resolution. We found that loss of the initial, stable alveolar-type2-like state was accompanied by transient increase in plasticity. This was followed by adoption of distinct fitness-associated transcriptional programs which enable rapid expansion and ultimately clonal sweep of rare, stable subclones capable of metastasizing to distant sites. Finally, we showed that tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates tumor progression by creating novel evolutionary paths. Overall, our study elucidates the hierarchical nature of tumor evolution, and more broadly enables the in-depth study of tumor progression.

The development of DNA-barcoded antibodies to tag cell surface molecules has enabled the use of droplet-based single-cell sequencing (dsc-seq) to profile protein abundances from thousands of cells simultaneously. As compared to flow and mass cytometry, the high per cell cost of current dsc-seq-based workflows precludes their use in clinical applications and large-scale pooled screens. Here, we introduce SCITO-seq, a workflow that uses splint oligonucleotides (oligos) to enable combinatorially indexed dsc-seq of DNA-barcoded antibodies from over 105 cells per reaction using commercial microfluidics. By encoding sample barcodes into splint oligos, we demonstrate that multiplexed SCITO-seq produces reproducible estimates of cellular composition and surface protein expression comparable to those from mass cytometry. We further demonstrate two modified splint oligo designs that extend SCITO-seq to achieve compatibility with commercial DNA-barcoded antibodies and simultaneous expression profiling of the transcriptome and surface proteins from the same cell. These results demonstrate SCITO-seq as a flexible and ultra-high-throughput platform for sequencing-based single-cell protein and multimodal profiling.

The MORDOR I trial1, conducted in Niger, Malawi and Tanzania, demonstrated that mass azithromycin distribution to preschool children reduced childhood mortality1. However, the large but simple trial design precluded determination of the mechanisms involved. Here we examined the gut microbiome of preschool children from 30 Nigerien communities randomized to either biannual azithromycin or placebo. Gut microbiome γ-diversity was not significantly altered (P = 0.08), but the relative abundances of two Campylobacter species, along with another 33 gut bacteria, were significantly reduced in children treated with azithromycin at the 24-month follow-up. Metagenomic analysis revealed functional differences in gut bacteria between treatment groups. Resistome analysis showed an increase in macrolide resistance gene expression in gut microbiota in communities treated with azithromycin (P = 0.004). These results suggest that prolonged mass azithromycin distribution to reduce childhood mortality reduces certain gut bacteria, including known pathogens, while selecting for antibiotic resistance. Mass antibiotic administration to preschool children in Nigerien communities alters the relative abundances of 35 bacterial species in the gut microbiome, including enteric pathogens, but also increases expression of macrolide resistance genes.

XYZeq is a novel scalable platform that directly encodes spatial location from tissue into single-cell RNA sequencing libraries., Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.

BackgroundSequencing of the SARS-CoV-2 viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities.MethodsSARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during November 22-December 2, 2020 and January 10-29, 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants.ResultsA total of 12,124 tests were performed yielding 1,099 positives. From these, 811 high quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.9% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to “West Coast” variants were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.357 vs 0.294, RR=1.29; 95% CI:1.01-1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.1%).ConclusionsThe increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants; however, additional laboratory and epidemiological studies are required to better understand differences between these variants.SummaryWe observed a growing prevalence and elevated attack rate for “West Coast” SARS-CoV-2 variants in a community testing setting in San Francisco during January 2021, suggesting its modestly higher transmissibility.

Background. Sequencing of the SARS-CoV-2 viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities. Methods. SARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during November 22-December 2, 2020 and January 10-29, 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants. Results. A total of 12,124 tests were performed yielding 1,099 positives. From these, 811 high quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.9% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to “West Coast” variants were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.357 vs 0.294, RR=1.29; 95% CI:1.01-1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.1%). Conclusions. The increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants; however, additional laboratory and epidemiological studies are required to better understand differences between these variants., Summary: We observed a growing prevalence and elevated attack rate for “West Coast” SARS-CoV-2 variants in a community testing setting in San Francisco during January 2021, suggesting its modestly higher transmissibility.

Author(s): Crawford, Emily D; Acosta, Irene; Ahyong, Vida; Anderson, Erika C; Arevalo, Shaun; Asarnow, Daniel; Axelrod, Shannon; Ayscue, Patrick; Azimi, Camillia S; Azumaya, Caleigh M; Bachl, Stefanie; Bachmutsky, Iris; Bhaduri, Aparna; Brown, Jeremy Bancroft; Batson, Joshua; Behnert, Astrid; Boileau, Ryan M; Bollam, Saumya R; Bonny, Alain R; Booth, David; Borja, Michael Jerico B; Brown, David; Buie, Bryan; Burnett, Cassandra E; Byrnes, Lauren E; Cabral, Katelyn A; Cabrera, Joana P; Caldera, Saharai; Canales, Gabriela; Castaneda, Gloria R; Chan, Agnes Protacio; Chang, Christopher R; Charles-Orszag, Arthur; Cheung, Carly; Chio, Unseng; Chow, Eric D; Citron, Y Rose; Cohen, Allison; Cohn, Lillian B; Chiu, Charles; Cole, Mitchel A; Conrad, Daniel N; Constantino, Angela; Cote, Andrew; Crayton-Hall, Tre'Jon; Darmanis, Spyros; Detweiler, Angela M; Dial, Rebekah L; Dong, Shen; Duarte, Elias M; Dynerman, David; Egger, Rebecca; Fanton, Alison; Frumm, Stacey M; Fu, Becky Xu Hua; Garcia, Valentina E; Garcia, Julie; Gladkova, Christina; Goldman, Miriam; Gomez-Sjoberg, Rafael; Gordon, M Grace; Grove, James CR; Gupta, Shweta; Haddjeri-Hopkins, Alexis; Hadley, Pierce; Haliburton, John; Hao, Samantha L; Hartoularos, George; Herrera, Nadia; Hilberg, Melissa; Ho, Kit Ying E; Hoppe, Nicholas; Hosseinzadeh, Shayan; Howard, Conor J; Hussmann, Jeffrey A; Hwang, Elizabeth; Ingebrigtsen, Danielle; Jackson, Julia R; Jowhar, Ziad M; Kain, Danielle; Kim, James YS; Kistler, Amy; Kreutzfeld, Oriana; Kulsuptrakul, Jessie; Kung, Andrew F

Defining the biologically active structures of proteins in their cellular environments remains challenging for proteins with multiple conformations and functions, where only a minor conformer might be associated with a given function. Here, we use deep mutational scanning to probe the structure and dynamics of α-synuclein, a protein known to adopt disordered, helical, and amyloid conformations. We examined the effects of 2,600 single-residue substitutions on the ability of intracellularly expressed α-synuclein to slow the growth of yeast. Computational analysis of the data showed that the conformation responsible for this phenotype is a long, uninterrupted, amphiphilic helix with increasing dynamics toward the C terminus. Deep mutational scanning can therefore determine biologically active conformations in cellular environments, even for a highly dynamic multi-conformational protein.

Protein conformations are shaped by cellular environments, but how environmental changes alter the conformational landscapes of specific proteins in vivo remains largely uncharacterized, in part due to the challenge of probing protein structures in living cells. Here, we use deep mutational scanning to investigate how a toxic conformation of α-synuclein, a dynamic protein linked to Parkinson’s disease, responds to perturbations of cellular proteostasis. In the context of a course for graduate students in the UCSF Integrative Program in Quantitative Biology, we screened a comprehensive library of α-synuclein missense mutants in yeast cells treated with a variety of small molecules that perturb cellular processes linked to α-synuclein biology and pathobiology. We found that the conformation of α-synuclein previously shown to drive yeast toxicity—an extended, membrane-bound helix—is largely unaffected by these chemical perturbations, underscoring the importance of this conformational state as a driver of cellular toxicity. On the other hand, the chemical perturbations have a significant effect on the ability of mutations to suppress α-synuclein toxicity. Moreover, we find that sequence determinants of α-synuclein toxicity are well described by a simple structural model of the membrane-bound helix. This model predicts that α-synuclein penetrates the membrane to constant depth across its length but that membrane affinity decreases toward the C terminus, which is consistent with orthogonal biophysical measurements. Finally, we discuss how parallelized chemical genetics experiments can provide a robust framework for inquiry-based graduate coursework.

The development of DNA-barcoded antibodies to tag cell-surface molecules has enabled the use of droplet-based single cell sequencing (dsc-seq) to profile the surface proteomes of cells. Compared to flow and mass cytometry, the major limitation of current dsc-seq-based workflows is the high cost associated with profiling each cell, thus precluding its use in applications where millions of cells are required. Here, we introduce SCITO-seq, a new workflow that combines combinatorial indexing and commercially available dsc-seq to enable cost-effective cell surface proteomic sequencing of greater than 105 cells per microfluidic reaction. We demonstrate SCITO-seq’s feasibility and scalability by profiling mixed species cell lines and mixed human T and B lymphocytes. To further demonstrate its applicability, we show comparable cellular composition estimates in peripheral blood mononuclear cells obtained with SCITO-seq and mass cytometry. SCITO-seq can be extended to include simultaneous profiling of additional modalities such as transcripts and accessible chromatin or tracking of experimental perturbations such as genome edits or extracellular stimuli.

Spatial transcriptomics seeks to integrate single cell transcriptomic data within the three-dimensional space of multicellular biology. Current methods to correlate a cell’s position with its transcriptome in living tissues have various limitations. We developed an approach, called ‘ZipSeq’, that uses patterned illumination and photocaged oligonucleotides to serially print barcodes (‘zipcodes’) onto live cells in intact tissues, in real time and with an on-the-fly selection of patterns. Using ZipSeq, we mapped gene expression in three settings: in vitro wound healing, live lymph node sections and a live tumor microenvironment. In all cases, we discovered new gene expression patterns associated with histological structures. In the tumor microenvironment, this demonstrated a trajectory of myeloid and T cell differentiation from the periphery inward. A combinatorial variation of ZipSeq efficiently scales in the number of regions defined, providing a pathway for complete mapping of live tissues, subsequent to real-time imaging or perturbation. ZipSeq uses patterned illumination and photocaged oligonucleotides to serially print barcodes onto live, intact tissues for spatially mapping single cell transcriptomes.

Spatial transcriptomics seeks to integrate single cell transcriptomic data within the three-dimensional space of multicellular biology. Current methods to correlate a cell's position with its transcriptome in living tissues have various limitations. We developed an approach, called 'ZipSeq', that uses patterned illumination and photocaged oligonucleotides to serially print barcodes ('zipcodes') onto live cells in intact tissues, in real time and with an on-the-fly selection of patterns. Using ZipSeq, we mapped gene expression in three settings: in vitro wound healing, live lymph node sections and a live tumor microenvironment. In all cases, we discovered new gene expression patterns associated with histological structures. In the tumor microenvironment, this demonstrated a trajectory of myeloid and T cell differentiation from the periphery inward. A combinatorial variation of ZipSeq efficiently scales in the number of regions defined, providing a pathway for complete mapping of live tissues, subsequent to real-time imaging or perturbation.

Although DNA methylation is a key regulator of gene expression, the comprehensive methylation landscape of metastatic cancer has never been defined. Through whole-genome bisulfite sequencing paired with deep whole-genome and transcriptome sequencing of 100 castration-resistant prostate metastases, we discovered alterations affecting driver genes that were detectable only with integrated whole-genome approaches. Notably, we observed that 22% of tumors exhibited a novel epigenomic subtype associated with hypermethylation and somatic mutations in TET2, DNMT3B, IDH1 and BRAF. We also identified intergenic regions where methylation is associated with RNA expression of the oncogenic driver genes AR, MYC and ERG. Finally, we showed that differential methylation during progression preferentially occurs at somatic mutational hotspots and putative regulatory regions. This study is a large integrated study of whole-genome, whole-methylome and whole-transcriptome sequencing in metastatic cancer that provides a comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer.

Paraneoplastic neurological disorders are immune-mediated diseases understood to manifest as part of a misdirected anti-tumor immune response. Paraneoplastic neurological disorder-associated autoantibodies can assist with diagnosis and enhance our understanding of tumor-associated immune processes. We designed a comprehensive library of 49-amino-acid overlapping peptides spanning the entire human proteome, including all splicing isoforms and computationally predicted coding regions. Using this library, we optimized a phage immunoprecipitation and sequencing protocol with multiple rounds of enrichment to create high-resolution epitope profiles in serum and cerebrospinal fluid (CSF) samples from patients suffering from two common paraneoplastic neurological disorders, the anti-Yo (n = 36 patients) and anti-Hu (n = 44 patients) syndromes. All (100%) anti-Yo patient samples yielded enrichment of peptides from the canonical anti-Yo (CDR2 and CDR2L) antigens, while 38% of anti-Hu patients enriched peptides deriving from the nELAVL (neuronal embryonic lethal abnormal vision like) family of proteins, the anti-Hu autoantigenic target. Among the anti-Hu patient samples that were positive for nELAVL, we noted a restricted region of immunoreactivity. To achieve single amino acid resolution, we designed a novel deep mutational scanning phage library encoding all possible single-point mutants targeting the reactive nELAVL region. This analysis revealed a distinct preference for the degenerate motif, RLDxLL, shared by ELAVL2, 3 and 4. Lastly, phage immunoprecipitation sequencing identified several known autoantigens in these same patient samples, including peptides deriving from the cancer-associated antigens ZIC and SOX families of transcription factors. Overall, this optimized phage immunoprecipitation sequencing library and protocol yielded the high-resolution epitope mapping of the autoantigens targeted in anti-Yo and anti-Hu encephalitis patients to date. The results presented here further demonstrate the utility and high-resolution capability of phage immunoprecipitation sequencing for both basic science and clinical applications and for better understanding the antigenic targets and triggers of paraneoplastic neurological disorders., Phage display and immunoprecipitation sequencing was used to screen the peptide-binding affinities of 80 patients suffering from anti-Hu or anti-Yo paraneoplastic disease. Patient-binding signatures implicate CDR2L as the primary antigen in anti-Yo paraneoplastic disease and suggest that rare exons/isoforms play a role in the anti-Hu oncoimmune response., Graphical Abstract Graphical Abstract

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 550 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved a savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Paraneoplastic neurological disorders (PNDs) are immune-mediated diseases of the nervous system understood to manifest as part of a misdirected anti-tumor immune response. Identifying PND-associated autoantibodies and their cognate antigens can assist with proper diagnosis and treatment while also enhancing our understanding of tumor-associated immune processes, triggers for autoimmune disease, and the functional significance of onconeuronal proteins. Here, we employed an enhanced version of phage display immunoprecipitation and sequencing (PhIP-Seq) leveraging a library of over 731,000 unique phage clones tiling across the entire human proteome to detect autoantibodies and create high-resolution epitope profiles in serum and CSF samples from patients suffering from two common PNDs, the anti-Yo (n = 36 patients) and anti-Hu syndromes (n = 44 patients). All patient samples positive for anti-Yo antibody by a validated clinical assay yielded polyspecific enrichment of phage presenting peptides from the canonical anti-Yo (CDR2 and CDR2L) antigens, while 38% of anti-Hu patients (17/44) had a serum and/or CSF sample that significantly enriched peptides deriving from the ELAVL family of proteins, the anti-Hu autoantigenic target. The anti-Hu antibodies showed a remarkably convergent antigenic signature across 15/17 patients corresponding to residues surrounding and including the degenerate motif, RLDxLL, shared by ELAVL2, 3 and 4. Lastly, PhIP-Seq identified several known and novel autoantigens in these same patient samples, representing potential biomarkers that could aid in the diagnosis and prognosis of PND and cancer.

Summary Responses to anti-PD-1 immunotherapy occur but are infrequent in bladder cancer. The specific T cells that mediate tumor rejection are unknown. T cells from human bladder tumors and non-malignant tissue were assessed with single-cell RNA and paired T cell receptor (TCR) sequencing of 30,604 T cells from 7 patients. We find that the states and repertoires of CD8+ T cells are not distinct in tumors compared with non-malignant tissues. In contrast, single-cell analysis of CD4+ T cells demonstrates several tumor-specific states, including multiple distinct states of regulatory T cells. Surprisingly, we also find multiple cytotoxic CD4+ T cell states that are clonally expanded. These CD4+ T cells can kill autologous tumors in an MHC class II-dependent fashion and are suppressed by regulatory T cells. Further, a gene signature of cytotoxic CD4+ T cells in tumors predicts a clinical response in 244 metastatic bladder cancer patients treated with anti-PD-L1., Graphical Abstract, Highlights • Human bladder tumors contain multiple clonally expanded cytotoxic CD4+ T cell states • Cytotoxic CD4+ T cells can kill autologous tumors in an MHC class II-dependent fashion • Autologous regulatory T cells can inhibit the activity of cytotoxic CD4+ T cells • A cytotoxic CD4+ gene signature predicts response to anti-PD-L1 in bladder cancer, Single-cell RNA and paired T cell receptor sequencing highlights enrichment of cytotoxic CD4+ T cells rather than CD8+ T cells in human bladder cancer. These CD4+ T cells are capable of killing autologous tumor cells and are subjected to inhibition by Tregs.

Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86–1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63–0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75–1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved a savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved cost savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved a savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library. After library preparation, the next step before putting samples on the sequencer is to pool samples to be able to multiplex sequencing. Final concentrations of each sample will vary from sample to sample depending on various things like RNA input, library prep, and PCR cycles among other factors. It is difficult tomanually quantify and pool uniformly 384 samples, so that is why we employ robots. To quickly and accurately pool hundreds of samples at a time, we employed a two-step method. Using the Labcyte Echo, equal volumes of each library are pooled together and sequenced on the Illumina iSeq or MiSeq sequencing platforms to determine the representation of each library in the total pool.Using this information, libraries were pooled using the Echo into a normalized pool for downstream sequencing on the Illumina NovaSeq.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved a savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved a savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library. This automated, miniaturized protocol for bead cleaning can be used with theHigh-Throughput Echo Library Prep Protocol for processing up to 384 samples simultaneously. To facilitate the miniaturized columes required by this protocol, we have included the .STL file for our 3D-printed adaptor, which, when placed on the magnet, raises the height of the PCR plate, thereby lowering the beads inside of the well and allowing for elutions in as low as 6uL.

Sample multiplexing facilitates scRNA-seq by reducing costs and artifacts such as cell doublets. However, universal and scalable sample barcoding strategies have not been described. We therefore developed MULTI-seq: multiplexing using lipid-tagged indices for single-cell and single-nucleus RNA sequencing. MULTI-seq reagents can barcode any cell type or nucleus from any species with an accessible plasma membrane. The method involves minimal sample processing, thereby preserving cell viability and endogenous gene expression patterns. MULTI-seq enables doublet identification, which improves data quality and increases cell throughput by minimizing the negative consequences of Poisson droplet loading. MULTI-seq sample classifications additionally identify cells with low RNA content that would otherwise be discarded by standard quality-control workflows. We use MULTI-seq to track the dynamics of T-cell activation, perform a 96-plex perturbation experiment with primary human mammary epithelial cells, and multiplex cryopreserved tumors and metastatic sites isolated from a patient-derived xenograft mouse model of triple-negative breast cancer.

Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.

Background Mass distributions of oral azithromycin have long been used to eliminate trachoma, and they are now being proposed to reduce childhood mortality. The observed benefit appears to be augmented with each additional treatment, suggesting a possible community-level effect. Here, we assess whether 2 biannual mass treatments of preschool children affect the community’s gut microbiome at 6 months after the last distribution. Methods In this cluster-randomized controlled trial, children aged 1–60 months in the Dossa region of Niger were randomized at the village level to receive a single dose of azithromycin or placebo every 6 months. Fecal samples were collected 6 months after the second treatment for metagenomic deep sequencing. The prespecified primary outcome was the Euclidean PERMANOVA of the gut microbiome, or effectively the distance between the genus-level centroid at the community level, with the secondary outcome being the Simpson’s α diversity. Results In the azithromycin arm, the gut microbial structures were significantly different than in the placebo arm (Euclidean PERMANOVA, P < .001). Further, the diversity of the gut microbiome in the azithromycin arm was significantly lower than in the placebo arm (inverse Simpson’s index, P = .005). Conclusions Two mass azithromycin administrations, 6 months apart, in preschool children led to long-term alterations of the gut microbiome structure and community diversity. Here, long-term microbial alterations in the community did not imply disease but were associated with an improvement in childhood mortality. Clinical Trials Registration NCT02048007.

Although the primary protein sequence of ubiquitin (Ub) is extremely stable over evolutionary time, it is highly tolerant to mutation during selection experiments performed in the laboratory. We have proposed that this discrepancy results from the difference between fitness under laboratory culture conditions and the selective pressures in changing environments over evolutionary timescales. Building on our previous work (Mavor et al., 2016), we used deep mutational scanning to determine how twelve new chemicals (3-Amino-1,2,4-triazole, 5-fluorocytosine, Amphotericin B, CaCl2, Cerulenin, Cobalt Acetate, Menadione, Nickel Chloride, p-Fluorophenylalanine, Rapamycin, Tamoxifen, and Tunicamycin) reveal novel mutational sensitivities of ubiquitin residues. Collectively, our experiments have identified eight new sensitizing conditions for Lys63 and uncovered a sensitizing condition for every position in Ub except Ser57 and Gln62. By determining the ubiquitin fitness landscape under different chemical constraints, our work helps to resolve the inconsistencies between deep mutational scanning experiments and sequence conservation over evolutionary timescales., Summary: We organized a project-based course that used deep mutational scanning of ubiquitin to resolve the inconsistencies between tolerance to mutations in laboratory conditions and sequence conservation over evolutionary timescales.

Summary The splicing of pre-mRNAs into mature transcripts is remarkable for its precision, but the mechanisms by which the cellular machinery achieves such specificity are incompletely understood. Here, we describe a deep neural network that accurately predicts splice junctions from an arbitrary pre-mRNA transcript sequence, enabling precise prediction of noncoding genetic variants that cause cryptic splicing. Synonymous and intronic mutations with predicted splice-altering consequence validate at a high rate on RNA-seq and are strongly deleterious in the human population. De novo mutations with predicted splice-altering consequence are significantly enriched in patients with autism and intellectual disability compared to healthy controls and validate against RNA-seq in 21 out of 28 of these patients. We estimate that 9%–11% of pathogenic mutations in patients with rare genetic disorders are caused by this previously underappreciated class of disease variation.

Author(s): Zinter, Matt S; Dvorak, Christopher C; Mayday, Madeline Y; Iwanaga, Kensho; Ly, Ngoc P; McGarry, Meghan E; Church, Gwynne D; Faricy, Lauren E; Rowan, Courtney M; Hume, Janet R; Steiner, Marie E; Crawford, Emily D; Langelier, Charles; Kalantar, Katrina; Chow, Eric D; Miller, Steve; Shimano, Kristen; Melton, Alexis; Yanik, Gregory A; Sapru, Anil; DeRisi, Joseph L | Abstract: BackgroundDespite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. Therefore, we aimed to develop a highly sensitive metagenomic next-generation sequencing (mNGS) assay capable of evaluating the pulmonary microbiome and identifying diverse pathogens in the lungs of immunocompromised children.MethodsWe collected 41 lower respiratory specimens from 34 immunocompromised children undergoing evaluation for pulmonary disease at 3 children's hospitals from 2014-2016. Samples underwent mechanical homogenization, parallel RNA/DNA extraction, and metagenomic sequencing. Sequencing reads were aligned to the National Center for Biotechnology Information nucleotide reference database to determine taxonomic identities. Statistical outliers were determined based on abundance within each sample and relative to other samples in the cohort.ResultsWe identified a rich cross-domain pulmonary microbiome that contained bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Samples with bacterial outliers had significantly depressed alpha-diversity (median, 0.61; interquartile range [IQR], 0.33-0.72 vs median, 0.96; IQR, 0.94-0.96; P l .001). Potential pathogens were detected in half of samples previously negative by clinical diagnostics, demonstrating increased sensitivity for missed pulmonary pathogens (P l .001).ConclusionsAn optimized mNGS assay for pulmonary microbes demonstrates significant inoculation of the lower airways of immunocompromised children with diverse bacteria, fungi, and viruses. Potential pathogens can be identified based on absolute and relative abundance. Ongoing investigation is needed to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised children with pulmonary disease.

Lower respiratory tract infections (LRTI) lead to more deaths each year than any other infectious disease category(1). Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests(2). In critically ill patients, non-infectious inflammatory syndromes resembling LRTI further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the lung microbiome and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed rules-based and logistic regression models (RBM, LRM) in a derivation cohort of 20 patients with LRTI or non-infectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with non-infectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an AUC of 0.96 (95% CI = 0.86 - 1.00), the diversity metric with an AUC of 0.80 (95% CI = 0.63 – 0.98), and the host transcriptional classifier with an AUC of 0.91 (95% CI = 0.80 – 1.00). Combining all three achieved an AUC of 0.99 (95% CI = 0.97 – 1.00) and negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome and host transcriptome may hold promise as a novel tool for LRTI diagnosis.SIGNIFICANCE STATEMENTLower respiratory tract infections (LRTI) are the leading cause of infectious disease-related death worldwide yet remain challenging to diagnose because of limitations in existing microbiologic tests. In critically ill patients, non-infectious respiratory syndromes that resemble LRTI further complicate diagnosis and confound targeted treatment. To address this, we developed a novel metagenomic sequencing-based approach that simultaneously interrogates three core elements of acute airway infections: the pathogen, lung microbiome and host response. We studied this approach in a prospective cohort of critically ill patients with acute respiratory failure and found that combining pathogen, microbiome and host gene expression metrics achieved accurate LRTI diagnosis and identified etiologic pathogens in patients with clinically identified infections but otherwise negative testing.FundingNHLBI K12HL119997 (Langelier C), NHLBI K23HL123778 (Christensen S), NIAID P01AI091575 and the Chan Zuckerberg Biohub (DeRisi JL), NHLBI K23 HL136844 (Moazed F), NHLBI R01HL110969, K24HL133390, R35HL140026 (Calfee C), Gladstone Institutes (Pollard KS).

Although the primary protein sequence of ubiquitin (Ub) is extremely stable over evolutionary time, it is highly tolerant to mutation during selection experiments performed in the laboratory. We have proposed that this discrepancy results from the difference between fitness under laboratory culture conditions and the selective pressures in changing environments over evolutionary time scales. Building on our previous work (Mavor et al 2016), we used deep mutational scanning to determine how twelve new chemicals (3-Amino-1,2,4-triazole, 5-fluorocytosine, Amphotericin B, CaCl2, Cerulenin, Cobalt Acetate, Menadione, Nickel Chloride, p-fluorophenylalanine, Rapamycin, Tamoxifen, and Tunicamycin) reveal novel mutational sensitivities of ubiquitin residues. We found sensitization of Lys63 in eight new conditions. In total, our experiments have uncovered a sensitizing condition for every position in Ub except Ser57 and Gln62. By determining the Ubiquitin fitness landscape under different chemical constraints, our work helps to resolve the inconsistencies between deep mutational scanning experiments and sequence conservation over evolutionary timescales.Builds onMavor D, Barlow KA, Thompson S, Barad BA, Bonny AR, Cario CL, Gaskins G, Liu Z, Deming L, Axen SD, Caceres E, Chen W, Cuesta A, Gate R, Green EM, Hulce KR, Ji W, Kenner LR, Mensa B, Morinishi LS, Moss SM, Mravic M, Muir RK, Niekamp S, Nnadi CI, Palovcak E, Poss EM, Ross TD, Salcedo E, See S, Subramaniam M, Wong AW, Li J, Thorn KS, Conchúir SÓ, Roscoe BP, Chow ED, DeRisi JL, Kortemme T, Bolon DN, Fraser JS. Determination of Ubiquitin Fitness Landscapes Under Different Chemical Stresses in a Classroom Setting. eLife. 2016.Impact StatementWe organized a project-based course that used deep mutational scanning in multiple chemical conditions to resolve the inconsistencies between tolerance to mutations in laboratory conditions and sequence conservation over evolutionary timescales.

Doan et al. Genome Medicine (2016) 8:123 DOI 10.1186/s13073-016-0377-x ERRATUM Open Access Erratum to: Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens Thuy Doan 1,2† , Michael R. Wilson 3,4† , Emily D. Crawford 3,5 , Eric D. Chow 3 , Lillian M. Khan 3 , Kristeene A. Knopp 3 , Brian D. O’Donovan 3 , Dongxiang Xia 6 , Jill K. Hacker 6 , Jay M. Stewart 2 , John A. Gonzales 1,2 , Nisha R. Acharya 1,2 and Joseph L. DeRisi 3* Erratum It has come to our attention that there is an error in Fig. 3a for this article [1]. The correct version of Fig. 3a can be found below. The red markers now reflect the se- quence differences. The text is correct. There was also a row omitted in Additional file 1: Table S1. The revised version can be found below. Additional file Additional file 1: Table S1. List of nucleotide substitutions identified in subject 6’s RV genome. The patient’s RV genome was aligned with the Stuttgart strain (GenBank DQ388280.1). A nucleotide change was considered a substitution only if the change was present in ≥ 4 reads or in 80% of the total reads at that nucleotide position. (PDF 120 kb) Author details Francis I. Proctor Foundation, University of California San Francisco, San Francisco, CA, USA. 2 Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA. 3 Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA. Department of Neurology, University of California San Francisco, San Francisco, CA, USA. 5 Howard Hughes Medical Institute, Chevy Chase, MD, USA. 6 California Department of Public Health, Richmond, CA, USA. Received: 7 November 2016 Accepted: 7 November 2016 Reference 1. Doan T, Wilson MR, Crawford ED, Chow ED, Khan LM, Knopp KA, O’Donovan BD, Xia D, Hacker JK, Stewart JM, Gonzales JA, Archarya NR, DeRisi JL. Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens. Genome Med. 2016;8:106. * Correspondence: joe@derisilab.ucsf.edu Equal contributors Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA © The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

A molecular understanding of drug resistance mechanisms enables surveillance of the effectiveness of new antimicrobial therapies during development and deployment in the field. We used conventional drug resistance selection as well as a regime of limiting dilution at early stages of drug treatment to probe two antimalarial imidazolopiperazines, KAF156 and GNF179. The latter approach permits the isolation of low-fitness mutants that might otherwise be out-competed during selection. Whole-genome sequencing of 24 independently derived resistant Plasmodium falciparum clones revealed four parasites with mutations in the known cyclic amine resistance locus (pfcarl) and a further 20 with mutations in two previously unreported P. falciparum drug resistance genes, an acetyl-CoA transporter (pfact) and a UDP-galactose transporter (pfugt). Mutations were validated both in vitro by CRISPR editing in P. falciparum and in vivo by evolution of resistant Plasmodium berghei mutants. Both PfACT and PfUGT were localized to the endoplasmic reticulum by fluorescence microscopy. As mutations in pfact and pfugt conveyed resistance against additional unrelated chemical scaffolds, these genes are probably involved in broad mechanisms of antimalarial drug resistance.

Background Ocular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~50 % of presumed infectious uveitis cases. The objective of this study is to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis. Methods This is a proof-of-concept study, in which intraocular fluid samples were obtained from five subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology. Samples were subjected to MDS, and results were compared with those from conventional diagnostic tests. Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from MDS. Results Unbiased MDS of intraocular fluid produced results concordant with known diagnoses in subjects with (n = 4) and without (n = 1) uveitis. Samples positive for Cryptococcus neoformans, Toxoplasma gondii, and herpes simplex virus 1 as tested by a Clinical Laboratory Improvement Amendments-certified laboratory were correctly identified with MDS. Rubella virus was identified in one case of chronic bilateral idiopathic uveitis. The subject’s strain was most closely related to a German rubella virus strain isolated in 1992, one year before he developed a fever and rash while living in Germany. The pattern and the number of viral identified mutations present in the patient’s strain were consistent with long-term viral replication in the eye. Conclusions MDS can identify fungi, parasites, and DNA and RNA viruses in minute volumes of intraocular fluid samples. The identification of chronic intraocular rubella virus infection highlights the eye’s role as a long-term pathogen reservoir, which has implications for virus eradication and emerging global epidemics. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0344-6) contains supplementary material, which is available to authorized users.

SUMMARYBackgroundOcular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~ 50% of presumed infectious uveitis cases.1,2 We aimed to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis.MethodsThis is a proof-of-concept study, in which intraocular fluid samples were obtained from 5 subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology. Samples were subjected to MDS, and results were compared with conventional diagnostic tests. Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from MDS.FindingsUnbiased MDS of intraocular fluid produced results concordant with known diagnoses in subjects with (n=4) and without (n=1) uveitis. Rubella virus (RV) was identified in one case of chronic bilateral idiopathic uveitis. The subject’s strain was most closely related to a German RV strain isolated in 1992, one year before he developed a fever and rash while living in Germany.InterpretationMDS can identify fungi, parasites, and DNA and RNA viruses in minute volumes of intraocular fluid samples. The identification of chronic intraocular RV infection highlights the eye’s role as a long-term pathogen reservoir, which has implications for virus eradication and emerging global epidemics.

Ubiquitin is essential for eukaryotic life and varies in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies indicate that ubiquitin is highly tolerant to single mutations. We hypothesized that this tolerance would be reduced by chemically induced physiologic perturbations. To test this hypothesis, a class of first year UCSF graduate students employed deep mutational scanning to determine the fitness landscape of all possible single residue mutations in the presence of five different small molecule perturbations. These perturbations uncover 'shared sensitized positions' localized to areas around the hydrophobic patch and the C-terminus. In addition, we identified perturbation specific effects such as a sensitization of His68 in HU and a tolerance to mutation at Lys63 in DTT. Our data show how chemical stresses can reduce buffering effects in the ubiquitin proteasome system. Finally, this study demonstrates the potential of lab-based interdisciplinary graduate curriculum. DOI: http://dx.doi.org/10.7554/eLife.15802.001, eLife digest The ability of an organism to grow and reproduce, that is, it’s “fitness”, is determined by how its genes interact with the environment. Yeast is a model organism in which researchers can control the exact mutations present in the yeast’s genes (its genotype) and the conditions in which the yeast cells live (their environment). This allows researchers to measure how a yeast cell’s genotype and environment affect its fitness. Ubiquitin is a protein that many organisms depend on to manage cell stress by acting as a tag that targets other proteins for degradation. Essential proteins such as ubiquitin often remain unchanged by mutation over long periods of time. As a result, these proteins evolve very slowly. Like all proteins, ubiquitin is built from a chain of amino acid molecules linked together, and the ubiquitin proteins of yeast and humans are made of almost identical sequences of amino acids. Although ubiquitin has barely changed its sequence over evolution, previous studies have shown that – under normal growth conditions in the laboratory – most amino acids in ubiquitin can be mutated without any loss of cell fitness. This led Mavor et al. to hypothesize that treating the yeast cells with chemicals that cause cell stress might lead to amino acids in ubiquitin becoming more sensitive to mutation. To test this idea, a class of graduate students at the University of California, San Francisco grew yeast cells with different ubiquitin mutations together, and with different chemicals that induce cell stress, and measured their growth rates. Sequencing the ubiquitin gene in the thousands of tested yeast cells revealed that three of the chemicals cause a shared set of amino acids in ubiquitin to become more sensitive to mutation. This result suggests that these amino acids are important for the stress response, possibly by altering the ability of yeast cells to target certain proteins for degradation. Conversely, another chemical causes yeast to become more tolerant to changes in the ubiquitin sequence. The experiments also link changes in particular amino acids in ubiquitin to specific stress responses. Mavor et al. show that many of ubquitin’s amino acids are sensitive to mutation under different stress conditions, while others can be mutated to form different amino acids without effecting fitness. By testing the effects of other chemicals, future experiments could further characterize how the yeast’s genotype and environment interact. DOI: http://dx.doi.org/10.7554/eLife.15802.002

Background: With widespread adoption of next-generation sequencing (NGS) technologies, the need has arisen for a broadly applicable method to remove unwanted high-abundance species prior to sequencing. We introduce DASH (Depletion of Abundant Sequences by Hybridization), a facile technique for targeted depletion of undesired sequences. Results: Sequencing libraries are DASHed with recombinant Cas9 protein complexed with a library of single guide RNAs (sgRNAs) programmed to target unwanted species for cleavage, thus preventing them from consuming sequencing space. We demonstrate up to 99% reduction of mitochondrial ribosomal RNA (rRNA) in HeLa cells, and enrichment of pathogen sequences up to 4-fold in metagenomic samples from patients with infectious diseases. Similarly, we demonstrate the utility of DASH in the context of cancer diagnostics by significantly increasing the detectable fraction of KRAS mutant sequences over the predominant wild-type allele. Conclusion: This simple single-tube method is reprogrammable for virtually any sample type to increase sequencing yield without additional cost. [Note: Wei Gu and Emily Crawford contributed equally to this work.]

PurposeTo compare the performance of unbiased high-throughput sequencing with pathogen directed PCR using DNA isolated from archived ocular fluid, approaches that are compatible with the current sample handling practice of ophthalmologists.DesignRetrospective molecular study of banked vitreous samples.MethodsWe evaluated a metagenomic DNA sequencing-based approach (DNA-seq) using archived positive (n= 31) and negative (n=36) vitreous specimens as determined by reference pathogen-specific PCR assays (herpes simplex virus 1 and 2, cytomegalovirus, varicella-zoster virus, andToxoplasma gondii). Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from DNA-seq. Clinical samples were de-identified and laboratory personnel handling the samples and interpreting the data were masked.ResultsMetagenomic DNA sequencing detected 87% of positive reference samples. In the presumed negative reference samples, DNA-seq detected an additional 6 different pathogens in 8 samples (22% of negative samples) that were either not detected or not targeted with pathogen-specific PCR assays. Infectious agents identified only with DNA-seq wereCandida dubliniensis,Klebsiella pneumoniae, human herpesvirus 6 (HHV-6), and human T-cell leukemia virus type 1 (HTLV-1). Discordant samples were independently verified in CLIA-certified laboratories. CMV sequences were compared against the antiviral mutation database and 3 of the samples were found to have mutations conferring ganciclovir resistance.ConclusionsMetagenomic DNA sequencing was highly concordant with pathogen-directed PCRs. The unbiased nature of metagenomics DNA sequencing allowed an expanded scope of pathogen detection, including bacteria, fungal species, and viruses, resolving 22% of cases that had previously escaped detection by routine pathogen-specific PCRs. The detection of drug resistance mutations highlights the potential for unbiased sequencing to provide clinically actionable information beyond pathogen species detection.

Importance Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. Objective To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious. Design, Setting, and Participants In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based onzscores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weightedzscore was used to filter out environmental contaminants and facilitate efficient data triage and analysis. Main Outcomes and Measures Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. Results The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans,Aspergillus oryzae,Histoplasma capsulatum, andCandida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weightedzscore–based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm. Conclusions and Relevance Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused byAspergillus oryzae, and the fourth reported case ofC dubliniensismeningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.

Bladder cancer can be responsive to immunotherapies such as anti-PD-1 and anti-PD-L1 checkpoint inhibitors, but overall response rates are low. Tumor-resident T cells demonstrate considerable heterogeneity as far as antigenic repertoire and phenotype. Whether the bladder tumor environment is enriched for specific types of T cells with a particular functional profile and antigenic specificity, and whether these tumor-specific populations are associated with treatment or response to immunotherapy, remains unclear. We performed single-cell RNA sequencing of CD4+ and CD8+ T cells from localized human bladder tumors and paired adjacent non-malignant bladder. We also assessed resected bladder tumors treated with neoadjuvant chemotherapy or atezolizumab (anti-PD-L1) as part of an ongoing phase II trial. We find both known and unexpected CD4+ T cell functional populations that are specific to the tumor microenvironment, including regulatory T cells and a novel population of cytotoxic CD4+ T cells. Furthermore, by combining whole-transcriptome data with paired T cell receptor identification on single cells, we find that tumor-specific CD4+ populations are clonally expanded and utilize an antigenic repertoire which is distinct from uninvolved bladder. These findings provide evidence for specialization of both phenotype and antigenic specificity of CD4+ T cells in the bladder tumor environment, and indicate that a limited number of tumor-specific antigens may drive in situ expansion and differentiation of specialized CD4+ subsets whose function may be critical to tumor control. Citation Format: David Yoonsuk Oh, Serena S. Kwek, Serghei Mangul, Siddharth S. Raju, Sasha Targ, Arun Burra, Eric Chow, Dvir Aran, Sima Porten, Maxwell V. Meng, Terence W. Friedlander, Chun Jimmie Ye, Lawrence Fong. Single-cell discrimination of altered human T cell states in the bladder tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4688.

The infectivity and persistence of Mycobacterium tuberculosis requires the utilization of host cell cholesterol. We have examined the specific role of cytochrome P450 CYP125A1 in the cholesterol degradation pathway using genetic, biochemical and high-resolution mass spectrometric approaches. The analysis of lipid profiles from cells grown on cholesterol revealed that CYP125A1 is required to incorporate the cholesterol side-chain carbon atoms into cellular lipids, as evidenced by an increase in the mass of the methyl-branched phthiocerol dimycocerosates. We observed that cholesterol-exposed cells lacking CYP125A1 accumulate cholest-4-en-3-one, suggesting that this is a physiological substrate for this enzyme. Reconstitution of enzymatic activity with spinach ferredoxin and ferredoxin reductase revealed that recombinant CYP125A1 indeed binds both cholest-4-en-3-one and cholesterol, efficiently hydroxylates both of them at C-27, and then further oxidizes 27-hydroxycholest-4-en-3-one to cholest-4-en-3-one-27-oic acid. We determined the X-ray structure of cholest-4-en-3-one-bound CYP125A1 at a resolution of 1.58 A. CYP125A1 is essential for growth of CDC1551 in media containing cholesterol or cholest-4-en-3-one. In its absence, the latter compound is toxic for both CDC1551 and H37Rv when added with glycerol as a second carbon source. CYP125A1 is a key enzyme in cholesterol metabolism and plays a crucial role in circumventing the deleterious effect of cholest-4-en-3-one.