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Sievers BL, Chakraborty S, Xue Y, Gelbart T, Gonzalez JC, Cassidy AG, Golan Y, Prahl M, Gaw SL, Arunachalam PS, Blish CA, Boyd SD, Davis MM, Jagannathan P, Nadeau KC, Pulendran B, Singh U, Scheuermann RH, Frieman MB, Vashee S, Wang TT, Tan GS. Antibodies elicited by SARS-CoV-2 infection or mRNA vaccines have reduced neutralizing activity against Beta and Omicron pseudoviruses. Sci Transl Med 2022; 14:eabn7842. [PMID: 35025672 PMCID: PMC8891085 DOI: 10.1126/scitranslmed.abn7842] [Citation(s) in RCA: 78] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 01/07/2022] [Indexed: 01/29/2023]
Abstract
Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that have mutations associated with increased transmission and antibody escape have arisen over the course of the current pandemic. Although the current vaccines have largely been effective against past variants, the number of mutations found on the Omicron (B.1.1.529) spike protein appear to diminish the protection conferred by preexisting immunity. Using vesicular stomatitis virus (VSV) pseudoparticles expressing the spike protein of several SARS-CoV-2 variants, we evaluated the magnitude and breadth of the neutralizing antibody response over time in individuals after infection and in mRNA-vaccinated individuals. We observed that boosting increases the magnitude of the antibody response to wild-type (D614), Beta, Delta, and Omicron variants; however, the Omicron variant was the most resistant to neutralization. We further observed that vaccinated healthy adults had robust and broad antibody responses, whereas responses may have been reduced in vaccinated pregnant women, underscoring the importance of learning how to maximize mRNA vaccine responses in pregnant populations. Findings from this study show substantial heterogeneity in the magnitude and breadth of responses after infection and mRNA vaccination and may support the addition of more conserved viral antigens to existing SARS-CoV-2 vaccines.
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Abramson BW, Novotny M, Hartwick NT, Colt K, Aevermann BD, Scheuermann RH, Michael TP. The genome and preliminary single-nuclei transcriptome of Lemna minuta reveals mechanisms of invasiveness. PLANT PHYSIOLOGY 2022; 188:879-897. [PMID: 34893913 PMCID: PMC8825320 DOI: 10.1093/plphys/kiab564] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 11/16/2021] [Indexed: 05/13/2023]
Abstract
The ability to trace every cell in some model organisms has led to the fundamental understanding of development and cellular function. However, in plants the complexity of cell number, organ size, and developmental time makes this a challenge even in the diminutive model plant Arabidopsis (Arabidopsis thaliana). Duckweed, basal nongrass aquatic monocots, provide an opportunity to follow every cell of an entire plant due to their small size, reduced body plan, and fast clonal growth habit. Here we present a chromosome-resolved genome for the highly invasive Lesser Duckweed (Lemna minuta) and generate a preliminary cell atlas leveraging low cell coverage single-nuclei sequencing. We resolved the 360 megabase genome into 21 chromosomes, revealing a core nonredundant gene set with only the ancient tau whole-genome duplication shared with all monocots, and paralog expansion as a result of tandem duplications related to phytoremediation. Leveraging SMARTseq2 single-nuclei sequencing, which provided higher gene coverage yet lower cell count, we profiled 269 nuclei covering 36.9% (8,457) of the L. minuta transcriptome. Since molecular validation was not possible in this nonmodel plant, we leveraged gene orthology with model organism single-cell expression datasets, gene ontology, and cell trajectory analysis to define putative cell types. We found that the tissue that we computationally defined as mesophyll expressed high levels of elemental transport genes consistent with this tissue playing a role in L. minuta wastewater detoxification. The L. minuta genome and preliminary cell map provide a paradigm to decipher developmental genes and pathways for an entire plant.
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Pinski AN, Steffen TL, Zulu MZ, George SL, Dickson A, Tifrea D, Maroney KJ, Tedeschi N, Zhang Y, Scheuermann RH, Pinto AK, Brien JD, Messaoudi I. Corticosteroid treatment in COVID-19 modulates host inflammatory responses and transcriptional signatures of immune dysregulation. J Leukoc Biol 2021; 110:1225-1239. [PMID: 34730254 PMCID: PMC8667650 DOI: 10.1002/jlb.4cova0121-084rr] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 09/14/2021] [Accepted: 09/16/2021] [Indexed: 12/15/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-2019 (COVID-19), a respiratory disease that varies in severity from mild to severe/fatal. Several risk factors for severe disease have been identified, notably age, male sex, and pre-existing conditions such as diabetes, obesity, and hypertension. Several advancements in clinical care have been achieved over the past year, including the use of corticosteroids (e.g., corticosteroids) and other immune-modulatory treatments that have now become standard of care for patients with acute severe COVID-19. While the understanding of the mechanisms that underlie increased disease severity with age has improved over the past few months, it remains incomplete. Furthermore, the molecular impact of corticosteroid treatment on host response to acute SARS-CoV-2 infection has not been investigated. In this study, a cross-sectional and longitudinal analysis of Ab, soluble immune mediators, and transcriptional responses in young (65 ≤ years) and aged (≥ 65 years) diabetic males with obesity hospitalized with acute severe COVID-19 was conducted. Additionally, the transcriptional profiles in samples obtained before and after corticosteroids became standard of care were compared. The analysis indicates that severe COVID-19 is characterized by robust Ab responses, heightened systemic inflammation, increased expression of genes related to inflammatory and pro-apoptotic processes, and reduced expression of those important for adaptive immunity regardless of age. In contrast, COVID-19 patients receiving steroids did not show high levels of systemic immune mediators and lacked transcriptional indicators of heightened inflammatory and apoptotic responses. Overall, these data suggest that inflammation and cell death are key drivers of severe COVID-19 pathogenesis in the absence of corticosteroid therapy.
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Aevermann BD, Shannon CP, Novotny M, Ben-Othman R, Cai B, Zhang Y, Ye JC, Kobor MS, Gladish N, Lee AHY, Blimkie TM, Hancock RE, Llibre A, Duffy D, Koff WC, Sadarangani M, Tebbutt SJ, Kollmann TR, Scheuermann RH. Machine Learning-Based Single Cell and Integrative Analysis Reveals That Baseline mDC Predisposition Correlates With Hepatitis B Vaccine Antibody Response. Front Immunol 2021; 12:690470. [PMID: 34777332 PMCID: PMC8588842 DOI: 10.3389/fimmu.2021.690470] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 08/25/2021] [Indexed: 01/23/2023] Open
Abstract
Vaccination to prevent infectious disease is one of the most successful public health interventions ever developed. And yet, variability in individual vaccine effectiveness suggests that a better mechanistic understanding of vaccine-induced immune responses could improve vaccine design and efficacy. We have previously shown that protective antibody levels could be elicited in a subset of recipients with only a single dose of the hepatitis B virus (HBV) vaccine and that a wide range of antibody levels were elicited after three doses. The immune mechanisms responsible for this vaccine response variability is unclear. Using single cell RNA sequencing of sorted innate immune cell subsets, we identified two distinct myeloid dendritic cell subsets (NDRG1-expressing mDC2 and CDKN1C-expressing mDC4), the ratio of which at baseline (pre-vaccination) correlated with the immune response to a single dose of HBV vaccine. Our results suggest that the participants in our vaccine study were in one of two different dendritic cell dispositional states at baseline – an NDRG2-mDC2 state in which the vaccine elicited an antibody response after a single immunization or a CDKN1C-mDC4 state in which the vaccine required two or three doses for induction of antibody responses. To explore this correlation further, genes expressed in these mDC subsets were used for feature selection prior to the construction of predictive models using supervised canonical correlation machine learning. The resulting models showed an improved correlation with serum antibody titers in response to full vaccination. Taken together, these results suggest that the propensity of circulating dendritic cells toward either activation or suppression, their “dispositional endotype” at pre-vaccination baseline, could dictate response to vaccination.
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Bakken TE, Jorstad NL, Hu Q, Lake BB, Tian W, Kalmbach BE, Crow M, Hodge RD, Krienen FM, Sorensen SA, Eggermont J, Yao Z, Aevermann BD, Aldridge AI, Bartlett A, Bertagnolli D, Casper T, Castanon RG, Crichton K, Daigle TL, Dalley R, Dee N, Dembrow N, Diep D, Ding SL, Dong W, Fang R, Fischer S, Goldman M, Goldy J, Graybuck LT, Herb BR, Hou X, Kancherla J, Kroll M, Lathia K, van Lew B, Li YE, Liu CS, Liu H, Lucero JD, Mahurkar A, McMillen D, Miller JA, Moussa M, Nery JR, Nicovich PR, Niu SY, Orvis J, Osteen JK, Owen S, Palmer CR, Pham T, Plongthongkum N, Poirion O, Reed NM, Rimorin C, Rivkin A, Romanow WJ, Sedeño-Cortés AE, Siletti K, Somasundaram S, Sulc J, Tieu M, Torkelson A, Tung H, Wang X, Xie F, Yanny AM, Zhang R, Ament SA, Behrens MM, Bravo HC, Chun J, Dobin A, Gillis J, Hertzano R, Hof PR, Höllt T, Horwitz GD, Keene CD, Kharchenko PV, Ko AL, Lelieveldt BP, Luo C, Mukamel EA, Pinto-Duarte A, Preissl S, Regev A, Ren B, Scheuermann RH, Smith K, Spain WJ, White OR, Koch C, Hawrylycz M, Tasic B, Macosko EZ, McCarroll SA, Ting JT, Zeng H, Zhang K, Feng G, Ecker JR, Linnarsson S, Lein ES. Comparative cellular analysis of motor cortex in human, marmoset and mouse. Nature 2021; 598:111-119. [PMID: 34616062 PMCID: PMC8494640 DOI: 10.1038/s41586-021-03465-8] [Citation(s) in RCA: 289] [Impact Index Per Article: 96.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 03/17/2021] [Indexed: 12/11/2022]
Abstract
The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.
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Aevermann B, Zhang Y, Novotny M, Keshk M, Bakken T, Miller J, Hodge R, Lelieveldt B, Lein E, Scheuermann RH. A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing. Genome Res 2021; 31:1767-1780. [PMID: 34088715 PMCID: PMC8494219 DOI: 10.1101/gr.275569.121] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 05/24/2021] [Indexed: 11/24/2022]
Abstract
Single-cell genomics is rapidly advancing our knowledge of the diversity of cell phenotypes, including both cell types and cell states. Driven by single-cell/-nucleus RNA sequencing (scRNA-seq), comprehensive cell atlas projects characterizing a wide range of organisms and tissues are currently underway. As a result, it is critical that the transcriptional phenotypes discovered are defined and disseminated in a consistent and concise manner. Molecular biomarkers have historically played an important role in biological research, from defining immune cell types by surface protein expression to defining diseases by their molecular drivers. Here, we describe a machine learning-based marker gene selection algorithm, NS-Forest version 2.0, which leverages the nonlinear attributes of random forest feature selection and a binary expression scoring approach to discover the minimal marker gene expression combinations that optimally capture the cell type identity represented in complete scRNA-seq transcriptional profiles. The marker genes selected provide an expression barcode that serves as both a useful tool for downstream biological investigation and the necessary and sufficient characteristics for semantic cell type definition. The use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and noncoding RNAs in neuronal cell type identity.
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Zhang Y, Aevermann BD, Bakken TE, Miller JA, Hodge RD, Lein ES, Scheuermann RH. FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test. Brief Bioinform 2021; 22:bbaa339. [PMID: 33249453 PMCID: PMC8294536 DOI: 10.1093/bib/bbaa339] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 10/26/2020] [Accepted: 10/27/2020] [Indexed: 12/22/2022] Open
Abstract
Single cell/nucleus RNA sequencing (scRNAseq) is emerging as an essential tool to unravel the phenotypic heterogeneity of cells in complex biological systems. While computational methods for scRNAseq cell type clustering have advanced, the ability to integrate datasets to identify common and novel cell types across experiments remains a challenge. Here, we introduce a cluster-to-cluster cell type matching method-FR-Match-that utilizes supervised feature selection for dimensionality reduction and incorporates shared information among cells to determine whether two cell type clusters share the same underlying multivariate gene expression distribution. FR-Match is benchmarked with existing cell-to-cell and cell-to-cluster cell type matching methods using both simulated and real scRNAseq data. FR-Match proved to be a stringent method that produced fewer erroneous matches of distinct cell subtypes and had the unique ability to identify novel cell phenotypes in new datasets. In silico validation demonstrated that the proposed workflow is the only self-contained algorithm that was robust to increasing numbers of true negatives (i.e. non-represented cell types). FR-Match was applied to two human brain scRNAseq datasets sampled from cortical layer 1 and full thickness middle temporal gyrus. When mapping cell types identified in specimens isolated from these overlapping human brain regions, FR-Match precisely recapitulated the laminar characteristics of matched cell type clusters, reflecting their distinct neuroanatomical distributions. An R package and Shiny application are provided at https://github.com/JCVenterInstitute/FRmatch for users to interactively explore and match scRNAseq cell type clusters with complementary visualization tools.
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Tarke A, Sidney J, Methot N, Yu ED, Zhang Y, Dan JM, Goodwin B, Rubiro P, Sutherland A, Wang E, Frazier A, Ramirez SI, Rawlings SA, Smith DM, da Silva Antunes R, Peters B, Scheuermann RH, Weiskopf D, Crotty S, Grifoni A, Sette A. Impact of SARS-CoV-2 variants on the total CD4 + and CD8 + T cell reactivity in infected or vaccinated individuals. Cell Rep Med 2021; 2:100355. [PMID: 34230917 PMCID: PMC8249675 DOI: 10.1016/j.xcrm.2021.100355] [Citation(s) in RCA: 396] [Impact Index Per Article: 132.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 06/07/2021] [Accepted: 06/24/2021] [Indexed: 01/19/2023]
Abstract
The emergence of SARS-CoV-2 variants with evidence of antibody escape highlight the importance of addressing whether the total CD4+ and CD8+ T cell recognition is also affected. Here, we compare SARS-CoV-2-specific CD4+ and CD8+ T cells against the B.1.1.7, B.1.351, P.1, and CAL.20C lineages in COVID-19 convalescents and in recipients of the Moderna (mRNA-1273) or Pfizer/BioNTech (BNT162b2) COVID-19 vaccines. The total reactivity against SARS-CoV-2 variants is similar in terms of magnitude and frequency of response, with decreases in the 10%-22% range observed in some assay/VOC combinations. A total of 7% and 3% of previously identified CD4+ and CD8+ T cell epitopes, respectively, are affected by mutations in the various VOCs. Thus, the SARS-CoV-2 variants analyzed here do not significantly disrupt the total SARS-CoV-2 T cell reactivity; however, the decreases observed highlight the importance for active monitoring of T cell reactivity in the context of SARS-CoV-2 evolution.
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Vita R, Zheng J, Jackson R, Dooley D, Overton JA, Miller MA, Berrios DC, Scheuermann RH, He Y, McGinty HK, Brochhausen M, Lin AY, Jain SB, Chibucos MC, Judkins J, Giglio MG, Feng IY, Burns G, Brush MH, Peters B, Stoeckert CJ. Standardization of assay representation in the Ontology for Biomedical Investigations. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2021; 2021:6318069. [PMID: 34244718 PMCID: PMC8271124 DOI: 10.1093/database/baab040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 05/24/2021] [Accepted: 06/15/2021] [Indexed: 11/24/2022]
Abstract
The Ontology for Biomedical Investigations (OBI) underwent a focused review of assay term annotations, logic and hierarchy with a goal to improve and standardize these terms. As a result, inconsistencies in W3C Web Ontology Language (OWL) expressions were identified and corrected, and additionally, standardized design patterns and a formalized template to maintain them were developed. We describe here this informative and productive process to describe the specific benefits and obstacles for OBI and the universal lessons for similar projects.
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Huang N, Pérez P, Kato T, Mikami Y, Okuda K, Gilmore RC, Conde CD, Gasmi B, Stein S, Beach M, Pelayo E, Maldonado JO, Lafont BA, Jang SI, Nasir N, Padilla RJ, Murrah VA, Maile R, Lovell W, Wallet SM, Bowman NM, Meinig SL, Wolfgang MC, Choudhury SN, Novotny M, Aevermann BD, Scheuermann RH, Cannon G, Anderson CW, Lee RE, Marchesan JT, Bush M, Freire M, Kimple AJ, Herr DL, Rabin J, Grazioli A, Das S, French BN, Pranzatelli T, Chiorini JA, Kleiner DE, Pittaluga S, Hewitt SM, Burbelo PD, Chertow D, Frank K, Lee J, Boucher RC, Teichmann SA, Warner BM, Byrd KM. SARS-CoV-2 infection of the oral cavity and saliva. Nat Med 2021; 27:892-903. [PMID: 33767405 PMCID: PMC8240394 DOI: 10.1038/s41591-021-01296-8] [Citation(s) in RCA: 433] [Impact Index Per Article: 144.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 02/26/2021] [Indexed: 02/01/2023]
Abstract
Despite signs of infection-including taste loss, dry mouth and mucosal lesions such as ulcerations, enanthema and macules-the involvement of the oral cavity in coronavirus disease 2019 (COVID-19) is poorly understood. To address this, we generated and analyzed two single-cell RNA sequencing datasets of the human minor salivary glands and gingiva (9 samples, 13,824 cells), identifying 50 cell clusters. Using integrated cell normalization and annotation, we classified 34 unique cell subpopulations between glands and gingiva. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral entry factors such as ACE2 and TMPRSS members were broadly enriched in epithelial cells of the glands and oral mucosae. Using orthogonal RNA and protein expression assessments, we confirmed SARS-CoV-2 infection in the glands and mucosae. Saliva from SARS-CoV-2-infected individuals harbored epithelial cells exhibiting ACE2 and TMPRSS expression and sustained SARS-CoV-2 infection. Acellular and cellular salivary fractions from asymptomatic individuals were found to transmit SARS-CoV-2 ex vivo. Matched nasopharyngeal and saliva samples displayed distinct viral shedding dynamics, and salivary viral burden correlated with COVID-19 symptoms, including taste loss. Upon recovery, this asymptomatic cohort exhibited sustained salivary IgG antibodies against SARS-CoV-2. Collectively, these data show that the oral cavity is an important site for SARS-CoV-2 infection and implicate saliva as a potential route of SARS-CoV-2 transmission.
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da Silva Antunes R, Soldevila F, Pomaznoy M, Babor M, Bennett J, Tian Y, Khalil N, Qian Y, Mandava A, Scheuermann RH, Cortese M, Pulendran B, Petro CD, Gilkes AP, Purcell LA, Sette A, Peters B. A system-view of Bordetella pertussis booster vaccine responses in adults primed with whole-cell versus acellular vaccine in infancy. JCI Insight 2021; 6:141023. [PMID: 33690224 PMCID: PMC8119213 DOI: 10.1172/jci.insight.141023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 03/03/2021] [Indexed: 01/26/2023] Open
Abstract
The increased incidence of whooping cough worldwide suggests that current vaccination against Bordetella pertussis infection has limitations in quality and duration of protection. The resurgence of infection has been linked to the introduction of acellular vaccines (aP), which have an improved safety profile compared with the previously used whole-cell (wP) vaccines. To determine immunological differences between aP and wP priming in infancy, we performed a systems approach of the immune response to booster vaccination. Transcriptomic, proteomic, cytometric, and serologic profiling revealed multiple shared immune responses with different kinetics across cohorts, including an increase of blood monocyte frequencies and strong antigen-specific IgG responses. Additionally, we found a prominent subset of aP-primed individuals (30%) with a strong differential signature, including higher levels of expression for CCL3, NFKBIA, and ICAM1. Contrary to the wP individuals, this subset displayed increased PT-specific IgE responses after boost and higher antigen-specific IgG4 and IgG3 antibodies against FHA and FIM2/3 at baseline and after boost. Overall, the results show that, while broad immune response patterns to Tdap boost overlap between aP- and wP-primed individuals, a subset of aP-primed individuals present a divergent response. These findings provide candidate targets to study the causes and correlates of waning immunity after aP vaccination.
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Tarke A, Sidney J, Methot N, Zhang Y, Dan JM, Goodwin B, Rubiro P, Sutherland A, da Silva Antunes R, Frazier A, Rawlings SA, Smith DM, Peters B, Scheuermann RH, Weiskopf D, Crotty S, Grifoni A, Sette A. Negligible impact of SARS-CoV-2 variants on CD4 + and CD8 + T cell reactivity in COVID-19 exposed donors and vaccinees. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.02.27.433180. [PMID: 33688655 PMCID: PMC7941626 DOI: 10.1101/2021.02.27.433180] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The emergence of SARS-CoV-2 variants highlighted the need to better understand adaptive immune responses to this virus. It is important to address whether also CD4+ and CD8+ T cell responses are affected, because of the role they play in disease resolution and modulation of COVID-19 disease severity. Here we performed a comprehensive analysis of SARS-CoV-2-specific CD4+ and CD8+ T cell responses from COVID-19 convalescent subjects recognizing the ancestral strain, compared to variant lineages B.1.1.7, B.1.351, P.1, and CAL.20C as well as recipients of the Moderna (mRNA-1273) or Pfizer/BioNTech (BNT162b2) COVID-19 vaccines. Similarly, we demonstrate that the sequences of the vast majority of SARS-CoV-2 T cell epitopes are not affected by the mutations found in the variants analyzed. Overall, the results demonstrate that CD4+ and CD8+ T cell responses in convalescent COVID-19 subjects or COVID-19 mRNA vaccinees are not substantially affected by mutations found in the SARS-CoV-2 variants.
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Yuste R, Hawrylycz M, Aalling N, Aguilar-Valles A, Arendt D, Armañanzas R, Ascoli GA, Bielza C, Bokharaie V, Bergmann TB, Bystron I, Capogna M, Chang Y, Clemens A, de Kock CPJ, DeFelipe J, Dos Santos SE, Dunville K, Feldmeyer D, Fiáth R, Fishell GJ, Foggetti A, Gao X, Ghaderi P, Goriounova NA, Güntürkün O, Hagihara K, Hall VJ, Helmstaedter M, Herculano-Houzel S, Hilscher MM, Hirase H, Hjerling-Leffler J, Hodge R, Huang J, Huda R, Khodosevich K, Kiehn O, Koch H, Kuebler ES, Kühnemund M, Larrañaga P, Lelieveldt B, Louth EL, Lui JH, Mansvelder HD, Marin O, Martinez-Trujillo J, Chameh HM, Mohapatra AN, Munguba H, Nedergaard M, Němec P, Ofer N, Pfisterer UG, Pontes S, Redmond W, Rossier J, Sanes JR, Scheuermann RH, Serrano-Saiz E, Staiger JF, Somogyi P, Tamás G, Tolias AS, Tosches MA, García MT, Wozny C, Wuttke TV, Liu Y, Yuan J, Zeng H, Lein E. A community-based transcriptomics classification and nomenclature of neocortical cell types. Nat Neurosci 2021; 23:1456-1468. [PMID: 32839617 PMCID: PMC7683348 DOI: 10.1038/s41593-020-0685-8] [Citation(s) in RCA: 144] [Impact Index Per Article: 48.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.
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Phadke S, Macherla S, Scheuermann RH. Database and Analytical Resources for Viral Research Community. ENCYCLOPEDIA OF VIROLOGY 2021. [PMCID: PMC7173540 DOI: 10.1016/b978-0-12-809633-8.20995-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Many public databases and analytical resources are available to facilitate virology research. The Virus Pathogen Database and Analysis Resource (ViPR, see “Relevant Websites section”) and Influenza Research Database (IRD, see “Relevant Websites section”) are comprehensive and highly curated repositories of genome and protein sequence records and annotations, protein structures, immune epitopes, and epidemiological and surveillance data about human and related viral pathogens. These data are acquired from public repositories, direct submissions and in-house bioinformatics analyses. The resources offer seamless integration of data, analytics and visualization, and are freely available without cost or restriction to facilitate diagnostics and therapeutics development for priority pathogens.
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Shannon CP, Blimkie TM, Ben-Othman R, Gladish N, Amenyogbe N, Drissler S, Edgar RD, Chan Q, Krajden M, Foster LJ, Kobor MS, Mohn WW, Brinkman RR, Le Cao KA, Scheuermann RH, Tebbutt SJ, Hancock RE, Koff WC, Kollmann TR, Sadarangani M, Lee AHY. Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small Cohort. Front Immunol 2020; 11:578801. [PMID: 33329547 PMCID: PMC7734088 DOI: 10.3389/fimmu.2020.578801] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 10/15/2020] [Indexed: 12/11/2022] Open
Abstract
Background Vaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts. Methods We applied cutting edge multi-omics approaches to extensively characterize temporal molecular responses following vaccination with hepatitis B virus (HBV) vaccine. Data were integrated across cellular, epigenomic, transcriptomic, proteomic, and fecal microbiome profiles, and correlated to final HBV antibody titres. Results Using both an unsupervised molecular-interaction network integration method (NetworkAnalyst) and a data-driven integration approach (DIABLO), we uncovered baseline molecular patterns and pathways associated with more effective vaccine responses to HBV. Biological associations were unravelled, with signalling pathways such as JAK-STAT and interleukin signalling, Toll-like receptor cascades, interferon signalling, and Th17 cell differentiation emerging as important pre-vaccination modulators of response. Conclusion This study provides further evidence that baseline cellular and molecular characteristics of an individual's immune system influence vaccine responses, and highlights the utility of integrating information across many parallel molecular datasets.
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Brown DM, Zhang Y, Scheuermann RH. Epidemiology and Sequence-Based Evolutionary Analysis of Circulating Non-Polio Enteroviruses. Microorganisms 2020; 8:microorganisms8121856. [PMID: 33255654 PMCID: PMC7759938 DOI: 10.3390/microorganisms8121856] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 11/13/2020] [Accepted: 11/17/2020] [Indexed: 02/07/2023] Open
Abstract
Enteroviruses (EVs) are positive-sense RNA viruses, with over 50,000 nucleotide sequences publicly available. While most human infections are typically associated with mild respiratory symptoms, several different EV types have also been associated with severe human disease, especially acute flaccid paralysis (AFP), particularly with endemic members of the EV-B species and two pandemic types—EV-A71 and EV-D68—that appear to be responsible for recent widespread outbreaks. Here we review the recent literature on the prevalence, characteristics, and circulation dynamics of different enterovirus types and combine this with an analysis of the sequence coverage of different EV types in public databases (e.g., the Virus Pathogen Resource). This evaluation reveals temporal and geographic differences in EV circulation and sequence distribution, highlighting recent EV outbreaks and revealing gaps in sequence coverage. Phylogenetic analysis of the EV genus shows the relatedness of different EV types. Recombination analysis of the EV-A species provides evidence for recombination as a mechanism of genomic diversification. The absence of broadly protective vaccines and effective antivirals makes human enteroviruses important pathogens of public health concern.
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Ben-Othman R, Cai B, Liu AC, Varankovich N, He D, Blimkie TM, Lee AH, Gill EE, Novotny M, Aevermann B, Drissler S, Shannon CP, McCann S, Marty K, Bjornson G, Edgar RD, Lin DTS, Gladish N, Maclsaac J, Amenyogbe N, Chan Q, Llibre A, Collin J, Landais E, Le K, Reiss SM, Koff WC, Havenar-Daughton C, Heran M, Sangha B, Walt D, Krajden M, Crotty S, Sok D, Briney B, Burton DR, Duffy D, Foster LJ, Mohn WW, Kobor MS, Tebbutt SJ, Brinkman RR, Scheuermann RH, Hancock REW, Kollmann TR, Sadarangani M. Systems Biology Methods Applied to Blood and Tissue for a Comprehensive Analysis of Immune Response to Hepatitis B Vaccine in Adults. Front Immunol 2020; 11:580373. [PMID: 33250895 PMCID: PMC7672042 DOI: 10.3389/fimmu.2020.580373] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Accepted: 09/24/2020] [Indexed: 12/26/2022] Open
Abstract
Conventional vaccine design has been based on trial-and-error approaches, which have been generally successful. However, there have been some major failures in vaccine development and we still do not have highly effective licensed vaccines for tuberculosis, HIV, respiratory syncytial virus, and other major infections of global significance. Approaches at rational vaccine design have been limited by our understanding of the immune response to vaccination at the molecular level. Tools now exist to undertake in-depth analysis using systems biology approaches, but to be fully realized, studies are required in humans with intensive blood and tissue sampling. Methods that support this intensive sampling need to be developed and validated as feasible. To this end, we describe here a detailed approach that was applied in a study of 15 healthy adults, who were immunized with hepatitis B vaccine. Sampling included ~350 mL of blood, 12 microbiome samples, and lymph node fine needle aspirates obtained over a ~7-month period, enabling comprehensive analysis of the immune response at the molecular level, including single cell and tissue sample analysis. Samples were collected for analysis of immune phenotyping, whole blood and single cell gene expression, proteomics, lipidomics, epigenetics, whole blood response to key immune stimuli, cytokine responses, in vitro T cell responses, antibody repertoire analysis and the microbiome. Data integration was undertaken using different approaches-NetworkAnalyst and DIABLO. Our results demonstrate that such intensive sampling studies are feasible in healthy adults, and data integration tools exist to analyze the vast amount of data generated from a multi-omics systems biology approach. This will provide the basis for a better understanding of vaccine-induced immunity and accelerate future rational vaccine design.
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Mavian C, Pond SK, Marini S, Magalis BR, Vandamme AM, Dellicour S, Scarpino SV, Houldcroft C, Villabona-Arenas J, Paisie TK, Trovão NS, Boucher C, Zhang Y, Scheuermann RH, Gascuel O, Lam TTY, Suchard MA, Abecasis A, Wilkinson E, de Oliveira T, Bento AI, Schmidt HA, Martin D, Hadfield J, Faria N, Grubaugh ND, Neher RA, Baele G, Lemey P, Stadler T, Albert J, Crandall KA, Leitner T, Stamatakis A, Prosperi M, Salemi M. Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable. Proc Natl Acad Sci U S A 2020; 117:12522-12523. [PMID: 32381734 PMCID: PMC7293693 DOI: 10.1073/pnas.2007295117] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
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Qian Y, Nguyen QV, Putzel P, Bevins N, Bui JD, Wang HY, Smyth P, Scheuermann RH. Novel computational analytics of clinical flow cytometry data identifies difficult-to-resolve leukemia cells for precision diagnosis. THE JOURNAL OF IMMUNOLOGY 2020. [DOI: 10.4049/jimmunol.204.supp.86.12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Abstract
Motivation
Diagnosis of leukemia relies on accurate identification of leukemic cell populations. Flow cytometry (FCM) is a primary diagnostic assay routinely used in clinical practice. The assay workflows consist of multiple manual gating steps performed by technicians, followed by interpretation by hematopathologists. Challenges to this process include technical variability in manual gating, difficulty in identification of the atypical leukemic cells, and the growing number of antigens used for diagnosis.
Methods
Instead of conducting ad hoc analysis of individual samples, our proposed computational approach leverages preexisting clinical FCM data to improve robustness of the computational identification of leukemic cells. Instead of separating cell population identification and sample classification into two steps, our machine learning classification method optimizes them simultaneously, producing gating locations that are recognizable to hematopathologists.
Results
Our study consists of 10-color FCM data from blood or bone marrow samples of 129 random subjects for chronic lymphocytic leukemia (CLL) diagnosis. Our initial automated gating analysis rendered an accuracy of 89% matched the diagnosis of the hematopathologist. In the remaining cases with discrepant results, the misclassified CLL cells had atypical molecular phenotypes, making them difficult to identify. In our improved pipeline, we demonstrate that these atypical types of CLL cells can be clearly captured using a non-linear embedding dimensionality reduction step.
Conclusion
The results demonstrate the power of a novel computational analysis pipeline for improving the identification of aberrant leukemia cells for precision diagnosis.
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Grifoni A, Sidney J, Zhang Y, Scheuermann RH, Peters B, Sette A. A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2. Cell Host Microbe 2020; 27:671-680.e2. [PMID: 32183941 PMCID: PMC7142693 DOI: 10.1016/j.chom.2020.03.002] [Citation(s) in RCA: 685] [Impact Index Per Article: 171.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 02/26/2020] [Accepted: 03/05/2020] [Indexed: 10/26/2022]
Abstract
Effective countermeasures against the recent emergence and rapid expansion of the 2019 novel coronavirus (SARS-CoV-2) require the development of data and tools to understand and monitor its spread and immune responses to it. However, little information is available about the targets of immune responses to SARS-CoV-2. We used the Immune Epitope Database and Analysis Resource (IEDB) to catalog available data related to other coronaviruses. This includes SARS-CoV, which has high sequence similarity to SARS-CoV-2 and is the best-characterized coronavirus in terms of epitope responses. We identified multiple specific regions in SARS-CoV-2 that have high homology to the SARS-CoV virus. Parallel bioinformatic predictions identified a priori potential B and T cell epitopes for SARS-CoV-2. The independent identification of the same regions using two approaches reflects the high probability that these regions are promising targets for immune recognition of SARS-CoV-2. These predictions can facilitate effective vaccine design against this virus of high priority.
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Hodge RD, Miller JA, Novotny M, Kalmbach BE, Ting JT, Bakken TE, Aevermann BD, Barkan ER, Berkowitz-Cerasano ML, Cobbs C, Diez-Fuertes F, Ding SL, McCorrison J, Schork NJ, Shehata SI, Smith KA, Sunkin SM, Tran DN, Venepally P, Yanny AM, Steemers FJ, Phillips JW, Bernard A, Koch C, Lasken RS, Scheuermann RH, Lein ES. Transcriptomic evidence that von Economo neurons are regionally specialized extratelencephalic-projecting excitatory neurons. Nat Commun 2020; 11:1172. [PMID: 32127543 PMCID: PMC7054400 DOI: 10.1038/s41467-020-14952-3] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 01/31/2020] [Indexed: 12/12/2022] Open
Abstract
von Economo neurons (VENs) are bipolar, spindle-shaped neurons restricted to layer 5 of human frontoinsula and anterior cingulate cortex that appear to be selectively vulnerable to neuropsychiatric and neurodegenerative diseases, although little is known about other VEN cellular phenotypes. Single nucleus RNA-sequencing of frontoinsula layer 5 identifies a transcriptomically-defined cell cluster that contained VENs, but also fork cells and a subset of pyramidal neurons. Cross-species alignment of this cell cluster with a well-annotated mouse classification shows strong homology to extratelencephalic (ET) excitatory neurons that project to subcerebral targets. This cluster also shows strong homology to a putative ET cluster in human temporal cortex, but with a strikingly specific regional signature. Together these results suggest that VENs are a regionally distinctive type of ET neuron. Additionally, we describe the first patch clamp recordings of VENs from neurosurgically-resected tissue that show distinctive intrinsic membrane properties relative to neighboring pyramidal neurons.
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Ji D, Putzel P, Qian Y, Chang I, Mandava A, Scheuermann RH, Bui JD, Wang H, Smyth P. Machine Learning of Discriminative Gate Locations for Clinical Diagnosis. Cytometry A 2020; 97:296-307. [PMID: 31691488 PMCID: PMC7079150 DOI: 10.1002/cyto.a.23906] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Revised: 08/22/2019] [Accepted: 09/18/2019] [Indexed: 01/03/2023]
Abstract
High-throughput single-cell cytometry technologies have significantly improved our understanding of cellular phenotypes to support translational research and the clinical diagnosis of hematological and immunological diseases. However, subjective and ad hoc manual gating analysis does not adequately handle the increasing volume and heterogeneity of cytometry data for optimal diagnosis. Prior work has shown that machine learning can be applied to classify cytometry samples effectively. However, many of the machine learning classification results are either difficult to interpret without using characteristics of cell populations to make the classification, or suboptimal due to the use of inaccurate cell population characteristics derived from gating boundaries. To date, little has been done to optimize both the gating boundaries and the diagnostic accuracy simultaneously. In this work, we describe a fully discriminative machine learning approach that can simultaneously learn feature representations (e.g., combinations of coordinates of gating boundaries) and classifier parameters for optimizing clinical diagnosis from cytometry measurements. The approach starts from an initial gating position and then refines the position of the gating boundaries by gradient descent until a set of globally-optimized gates across different samples are achieved. The learning procedure is constrained by regularization terms encoding domain knowledge that encourage the algorithm to seek interpretable results. We evaluate the proposed approach using both simulated and real data, producing classification results on par with those generated via human expertise, in terms of both the positions of the gating boundaries and the diagnostic accuracy. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.
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Grifoni A, Sidney J, Zhang Y, Scheuermann RH, Peters B, Sette A. Candidate Targets for Immune Responses to 2019-Novel Coronavirus (nCoV): Sequence Homology- and Bioinformatic-Based Predictions. ACTA ACUST UNITED AC 2020:3541361. [PMID: 32714104 PMCID: PMC7366807 DOI: 10.2139/ssrn.3541361] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 02/25/2020] [Indexed: 11/15/2022]
Abstract
Effective countermeasures against the recent emergence and rapid expansion of the 2019-Novel Coronavirus (2019-nCoV) require the development of data and tools to understand and monitor viral spread and immune responses. However, little information about the targets of immune responses to 2019-nCoV is available. We used the Immune Epitope Database and Analysis Resource (IEDB) resource to catalog available data related to other coronaviruses, including SARS-CoV, which has high sequence similarity to 2019-nCoV, and is the best-characterized coronavirus in terms of epitope responses. We identified multiple specific regions in 2019-nCoV that have high homology to SARS virus. Parallel bionformatic predictions identified a priori potential B and T cell epitopes for 2019-nCoV. The independent identification of the same regions using two approaches reflects the high probability that these regions are targets for immune recognition of 2019-nCoV.
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Hodge RD, Bakken TE, Miller JA, Smith KA, Barkan ER, Graybuck LT, Close JL, Long B, Johansen N, Penn O, Yao Z, Eggermont J, Höllt T, Levi BP, Shehata SI, Aevermann B, Beller A, Bertagnolli D, Brouner K, Casper T, Cobbs C, Dalley R, Dee N, Ding SL, Ellenbogen RG, Fong O, Garren E, Goldy J, Gwinn RP, Hirschstein D, Keene CD, Keshk M, Ko AL, Lathia K, Mahfouz A, Maltzer Z, McGraw M, Nguyen TN, Nyhus J, Ojemann JG, Oldre A, Parry S, Reynolds S, Rimorin C, Shapovalova NV, Somasundaram S, Szafer A, Thomsen ER, Tieu M, Quon G, Scheuermann RH, Yuste R, Sunkin SM, Lelieveldt B, Feng D, Ng L, Bernard A, Hawrylycz M, Phillips JW, Tasic B, Zeng H, Jones AR, Koch C, Lein ES. Conserved cell types with divergent features in human versus mouse cortex. Nature 2019; 573:61-68. [PMID: 31435019 PMCID: PMC6919571 DOI: 10.1038/s41586-019-1506-7] [Citation(s) in RCA: 897] [Impact Index Per Article: 179.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2018] [Accepted: 07/17/2019] [Indexed: 12/11/2022]
Abstract
Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.
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Grifoni A, Mahajan S, Sidney J, Martini S, Scheuermann RH, Peters B, Sette A. A survey of known immune epitopes in the enteroviruses strains associated with acute flaccid myelitis. Hum Immunol 2019; 80:923-929. [PMID: 31451291 DOI: 10.1016/j.humimm.2019.08.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 08/08/2019] [Accepted: 08/16/2019] [Indexed: 12/14/2022]
Abstract
Enteroviruses are potentially linked to the emergence of Acute Flaccid Myelitis (AFM), a rare but very serious condition that affects the nervous system. AFM has been associated with coxsackievirus A16, enterovirus A71 (EVA71) and enterovirus D68 (EVD68). Little is known about host-pathogen interactions for these viruses, and whether immune responses may have a protective or immunopathological role in disease presentations. Towards addressing this issue, we used the Immune Epitope Database to assess the known inventory of B and T cell epitopes from enteroviruses, focusing on data related to human hosts. The extent of conservation in areas that are targets of B and T cell immune responses were examined. This analysis sheds light on regions of the enterovirus polypeptide that can be probed to induce a specific or cross-reactive B or T cell the immune response to enteroviruses, with a particular focus on coxsackievirus A16, EVA71 and EVD68. In addition, these analyses reveal the current gap-of-knowledge in the T and B cell immune responses that future studies should aim to address.
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