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Viral whole-genome sequencing (WGS) provides critical insight into the transmission and evolution of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Long-read sequencing devices from Oxford Nanopore Technologies (ONT) promise significant improvements in turnaround time, portability and cost, compared to established short-read sequencing platforms for viral WGS (e.g., Illumina). However, adoption of ONT sequencing for SARS-CoV-2 surveillance has been limited due to common concerns around sequencing accuracy. To address this, here we perform viral WGS with ONT and Illumina platforms on 157 matched SARS-CoV-2-positive patient specimens and synthetic RNA controls, enabling rigorous evaluation of analytical performance. We report that, despite the elevated error rates observed in ONT sequencing reads, highly accurate consensus-level sequence determination was achieved, with single nucleotide variants (SNVs) detected at >99% sensitivity and >99% precision above a minimum ~60-fold coverage depth, thereby ensuring suitability for SARS-CoV-2 genome analysis. ONT sequencing also identified a surprising diversity of structural variation within SARS-CoV-2 specimens that were supported by evidence from short-read sequencing on matched samples. However, ONT sequencing failed to accurately detect short indels and variants at low read-count frequencies. This systematic evaluation of analytical performance for SARS-CoV-2 WGS will facilitate widespread adoption of ONT sequencing within local, national and international COVID-19 public health initiatives. Nanopore sequencing (ONT) has been used in SARS-CoV-2 studies, however adoption of ONT for SARS-CoV-2 surveillance has been limited due to common concerns around sequencing accuracy. Here, the authors perform a comprehensive evaluation of ONT analytical performance on 157 matched SARS-CoV-2-positive patient specimens and synthetic RNA controls.

High-throughput single-cell RNA sequencing is a powerful technique but only generates short reads from one end of a cDNA template, limiting the reconstruction of highly diverse sequences such as antigen receptors. To overcome this limitation, we combined targeted capture and long-read sequencing of T-cell-receptor (TCR) and B-cell-receptor (BCR) mRNA transcripts with short-read transcriptome profiling of barcoded single-cell libraries generated by droplet-based partitioning. We show that Repertoire and Gene Expression by Sequencing (RAGE-Seq) can generate accurate full-length antigen receptor sequences at nucleotide resolution, infer B-cell clonal evolution and identify alternatively spliced BCR transcripts. We apply RAGE-Seq to 7138 cells sampled from the primary tumor and draining lymph node of a breast cancer patient to track transcriptome profiles of expanded lymphocyte clones across tissues. Our results demonstrate that RAGE-Seq is a powerful method for tracking the clonal evolution from large numbers of lymphocytes applicable to the study of immunity, autoimmunity and cancer. Single cell RNA sequencing generates short reads from one end of a template, providing incomplete transcript coverage and limiting identification of diverse sequences such as antigen receptors. Here the authors combine long read nanopore sequencing with short read profiling of barcoded libraries to generate full-length antigen receptor sequences.

Background GemSIM, or General Error-Model based SIMulator, is a next-generation sequencing simulator capable of generating single or paired-end reads for any sequencing technology compatible with the generic formats SAM and FASTQ (including Illumina and Roche/454). GemSIM creates and uses empirically derived, sequence-context based error models to realistically emulate individual sequencing runs and/or technologies. Empirical fragment length and quality score distributions are also used. Reads may be drawn from one or more genomes or haplotype sets, facilitating simulation of deep sequencing, metagenomic, and resequencing projects. Results We demonstrate GemSIM's value by deriving error models from two different Illumina sequencing runs and one Roche/454 run, and comparing and contrasting the resulting error profiles of each run. Overall error rates varied dramatically, both between individual Illumina runs, between the first and second reads in each pair, and between datasets from Illumina and Roche/454 technologies. Indels were markedly more frequent in Roche/454 than Illumina and both technologies suffered from an increase in error rates near the end of each read. The effects of these different profiles on low-frequency SNP-calling accuracy were investigated by analysing simulated sequencing data for a mixture of bacterial haplotypes. In general, SNP-calling using VarScan was only accurate for SNPs with frequency > 3%, independent of which error model was used to simulate the data. Variation between error profiles interacted strongly with VarScan's 'minumum average quality' parameter, resulting in different optimal settings for different sequencing runs. Conclusions Next-generation sequencing has unprecedented potential for assessing genetic diversity, however analysis is complicated as error profiles can vary noticeably even between different runs of the same technology. Simulation with GemSIM can help overcome this problem, by providing insights into the error profiles of individual sequencing runs and allowing researchers to assess the effects of these errors on downstream data analysis.

Numerous studies have shown that viral variants that elude the host immune response may incur a fitness expense, diminishing the survival of the viral strain within the host, and the capacity of the variant to survive future transmission events. This definition can be divided into intrinsic fitness—fitness without immune pressure—and effective fitness, which includes immune influence. Co-occurring mutations outside immune-targeted epitope regions may also affect variant survival (epistasis). Analysis of viral fitness and epistasis over the non-structural protein regions is lacking for hepatitis C virus (HCV). Using a rare cohort of subjects recently infected with HCV, we build on prior work by integrating mathematical modeling and experimental data to examine the interplay between transmitted/founder (T/F) viruses, immune responses, fitness, and co-occurring mutations. We show that viral fitness declines during the first 90 days post-infection (DPI), associated with the magnitude of CD8 +T cell responses and early diversification. Fitness then rebounds in a complex pattern marked by co-occurring mutations. Finally, we demonstrate that an early, strong CD8 +T cell response in the absence of neutralizing antibodies (nAbs) exerts strong selective pressure, allowing escape and chronic infection. These insights support HCV vaccine strategies that elicit broad T and B cell immunity.

Severe influenza A virus (IAV) infection is associated with immune dysfunction. Here, we show circulating CD8 + T-cell profiles from patients hospitalized with avian H7N9, seasonal IAV, and influenza vaccinees. Patient survival reflects an early, transient prevalence of highly activated CD38 + HLA-DR + PD-1 + CD8 + T cells, whereas the prolonged persistence of this set is found in ultimately fatal cases. Single-cell T cell receptor (TCR)-αβ analyses of activated CD38 + HLA-DR + CD8 + T cells show similar TCRαβ diversity but differential clonal expansion kinetics in surviving and fatal H7N9 patients. Delayed clonal expansion associated with an early dichotomy at a transcriptome level (as detected by single-cell RNAseq) is found in CD38 + HLA-DR + CD8 + T cells from patients who succumbed to the disease, suggesting a divergent differentiation pathway of CD38 + HLA-DR + CD8 + T cells from the outset during fatal disease. Our study proposes that effective expansion of cross-reactive influenza-specific TCRαβ clonotypes with appropriate transcriptome signatures is needed for early protection against severe influenza disease. Virus-specific CD8 + T cells are crucial during H7N9 influenza infection, but CD8 + T cell dysfunction is associated with poor prognosis. Here, the authors use molecular and phenotypic analysis to establish persistence of clonally diverse CD8 + T cell populations during fatal infection.

Chimeric antigen receptor (CAR) T cell therapy is effective in treating B cell malignancies, but factors influencing the persistence of functional CAR + T cells, such as product composition, patients’ lymphodepletion, and immune reconstitution, are not well understood. To shed light on this issue, here we conduct a single-cell multi-omics analysis of transcriptional, clonal, and phenotypic profiles from pre- to 1-month post-infusion of CAR + and CAR − T cells from patients from a CARTELL study (ACTRN12617001579381) who received a donor-derived 4-1BB CAR product targeting CD19. Following infusion, CAR + T cells and CAR − T cells shows similar differentiation profiles with clonally expanded populations across heterogeneous phenotypes, demonstrating clonal lineages and phenotypic plasticity. We validate these findings in 31 patients with large B cell lymphoma treated with CD19 CAR T therapy. For these patients, we identify using longitudinal mass-cytometry data an association between NK-like subsets and clinical outcomes at 6 months with both CAR + and CAR − T cells. These results suggest that non-CAR-derived signals can provide information about patients’ immune recovery and be used as correlate of clinically relevant parameters. Phenotype of cells in the infusion product as well at specific post-infusion time points has been associated with clinical response to CD19 CAR T cells. Here the authors present a single-cell multi-omics analysis of pre- and post-infusion CAR+ and CAR- T cells from patients with relapsed or refractory B-ALL or LBCL who received CD19 CAR T therapy.

Cytotoxic CD8 + T cells are key for immune protection against viral infections. The breadth and cross-reactivity of these responses are important against rapidly mutating RNA viruses, such as dengue (DENV), yet how viral diversity affect T cell responses and their cross-reactivity against multiple variants of the virus remains poorly defined. In this study, an integrated analysis was performed to map experimentally validated CD8 + T cell epitopes onto the distribution of DENV genome sequences across the 4 serotypes worldwide. Despite the higher viral diversity observed within HLA-I restricted epitopes, mapping of 609 experimentally validated epitopes sequences on 3985 full-length viral genomes revealed 19 highly conserved epitopes across the four serotypes within the immunogenic regions of NS3, NS4B and NS5. These conserved epitopes were associated with a higher magnitude of IFN-γ response when compared to non-conserved epitopes and were restricted to 13 HLA class I genotypes, hence providing high coverage among human populations. Phylogeographic analyses showed that these epitopes are largely conserved in most of the endemic regions of the world, and with only some of these epitopes presenting distinct mutated variants circulating in South America and Asia.This study provides evidence for the existence of highly immunogenic and conserved epitopes across serotypes, which may impact design of new universal T-cell-inducing vaccine candidates that minimise detrimental effects of viral diversification and at the same time induce responses to a broad human population.

Vaccine-induced immunity depends on the generation of memory B cells (MBC). However, where and how MBCs are reactivated to make neutralising antibodies remain unknown. Here we show that MBCs are prepositioned in a subcapsular niche in lymph nodes where, upon reactivation by antigen, they rapidly proliferate and differentiate into antibody-secreting plasma cells in the subcapsular proliferative foci (SPF). This novel structure is enriched for signals provided by T follicular helper cells and antigen-presenting subcapsular sinus macrophages. Compared with contemporaneous secondary germinal centres, SPF have distinct single-cell molecular signature, cell migration pattern and plasma cell output. Moreover, SPF are found both in human and mouse lymph nodes, suggesting that they are conserved throughout mammalian evolution. Our data thus reveal that SPF is a seat of immunological memory that may be exploited to rapidly mobilise secondary antibody responses and improve vaccine efficacy. Memory B cells need to be reactivated to produce high affinity antibody responses on subsequent antigen encounters. Here the authors show that memory B cells localise to lymph node subcapsular proliferative foci (SPF), which have distinct properties from the germinal centre, for rapid expansion and the induction of B memory responses.

Background Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information. Results We developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8 + T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians. Conclusions VDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview .

Cytotoxic T lymphocytes (CTLs) are thought to arrive at target sites either via random search or following signals by other leukocytes. Here, we reveal independent emergent behaviour in CTL populations attacking tumour masses. Primary murine CTLs coordinate their migration in a process reminiscent of the swarming observed in neutrophils. CTLs engaging cognate targets accelerate the recruitment of distant T cells through long-range homotypic signalling, in part mediated via the diffusion of chemokines CCL3 and CCL4. Newly arriving CTLs augment the chemotactic signal, further accelerating mass recruitment in a positive feedback loop. Activated effector human T cells and chimeric antigen receptor (CAR) T cells similarly employ intra-population signalling to drive rapid convergence. Thus, CTLs recognising a cognate target can induce a localised mass response by amplifying the direct recruitment of additional T cells independently of other leukocytes. Immune cells known as cytotoxic T lymphocytes, or CTLs for short, move around the body searching for infected or damaged cells that may cause harm. Once these specialised killer cells identify a target, they launch an attack, removing the harmful cell from the body. CTLs can also recognise and eliminate cancer cells, and can be infused into cancer patients as a form of treatment called adoptive cell transfer immunotherapy. Unfortunately, this kind of treatment does not yet work well on solid tumours because the immune cells often do not infiltrate them sufficiently. It is thought that CTLs arrive at their targets either by randomly searching or by following chemicals secreted by other immune cells. However, the methods used to map the movement of these killer cells have made it difficult to determine how populations of CTLs coordinate their behaviour independently of other cells in the immune system. To overcome this barrier, Galeano Niño, Pageon, Tay et al. employed a three-dimensional model known as a tumouroid embedded in a matrix of proteins, which mimics the tissue environment of a real tumour in the laboratory. These models were used to track the movement of CTLs extracted from mice and humans, as well as human T cells engineered to recognise cancer cells. The experiments showed that when a CTL identifies a tumour cell, it releases chemical signals known as chemokines, which attract other CTLs and recruit them to the target site. Further experiments and computer simulations revealed that as the number of CTLs arriving at the target site increases, this amplifies the chemokine signal being secreted, resulting in more and more CTLs being attracted to the tumour. Other human T cells that had been engineered to recognize cancer cells were also found to employ this method of mass recruitment, and collectively ‘swarm’ towards targeted tumours. These findings shed new light on how CTLs work together to attack a target. It is possible that exploiting the mechanism used by CTLs could help improve the efficiency of tumour-targeting immunotherapies. However, further studies are needed to determine whether these findings can be applied to solid tumours in cancer patients.