1
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Chen X, Wang Y, Cappuccio A, Cheng WS, Zamojski FR, Nair VD, Miller CM, Rubenstein AB, Nudelman G, Tadych A, Theesfeld CL, Vornholt A, George MC, Ruffin F, Dagher M, Chawla DG, Soares-Schanoski A, Spurbeck RR, Ndhlovu LC, Sebra R, Kleinstein SH, Letizia AG, Ramos I, Fowler VG, Woods CW, Zaslavsky E, Troyanskaya OG, Sealfon SC. Author Correction: Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data. Nat Comput Sci 2023; 3:805. [PMID: 38177788 PMCID: PMC10766523 DOI: 10.1038/s43588-023-00523-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Affiliation(s)
- Xi Chen
- Center for Computational Biology, Flatiron Institute, New York, NY, USA
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Yuan Wang
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Antonio Cappuccio
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wan-Sze Cheng
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Venugopalan D Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Clare M Miller
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aliza B Rubenstein
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - German Nudelman
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alicja Tadych
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Chandra L Theesfeld
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Alexandria Vornholt
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Felicia Ruffin
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Michael Dagher
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Daniel G Chawla
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | | | | | - Lishomwa C Ndhlovu
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Robert Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven H Kleinstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Pathology and Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | | | - Irene Ramos
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vance G Fowler
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Christopher W Woods
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Olga G Troyanskaya
- Center for Computational Biology, Flatiron Institute, New York, NY, USA.
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA.
- Department of Computer Science, Princeton University, Princeton, NJ, USA.
| | - Stuart C Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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2
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Chen X, Wang Y, Cappuccio A, Cheng WS, Zamojski FR, Nair VD, Miller CM, Rubenstein AB, Nudelman G, Tadych A, Theesfeld CL, Vornholt A, George MC, Ruffin F, Dagher M, Chawla DG, Soares-Schanoski A, Spurbeck RR, Ndhlovu LC, Sebra R, Kleinstein SH, Letizia AG, Ramos I, Fowler VG, Woods CW, Zaslavsky E, Troyanskaya OG, Sealfon SC. Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data. Nat Comput Sci 2023; 3:644-657. [PMID: 37974651 PMCID: PMC10653299 DOI: 10.1038/s43588-023-00476-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 06/06/2023] [Indexed: 11/19/2023]
Abstract
Resolving chromatin-remodeling-linked gene expression changes at cell-type resolution is important for understanding disease states. Here we describe MAGICAL (Multiome Accessibility Gene Integration Calling and Looping), a hierarchical Bayesian approach that leverages paired single-cell RNA sequencing and single-cell transposase-accessible chromatin sequencing from different conditions to map disease-associated transcription factors, chromatin sites, and genes as regulatory circuits. By simultaneously modeling signal variation across cells and conditions in both omics data types, MAGICAL achieved high accuracy on circuit inference. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single-cell data that we generated from subjects with bloodstream infection and uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be activated by bacterial sepsis. We addressed the challenging problem of distinguishing host regulatory circuit responses to methicillin-resistant and methicillin-susceptible S. aureus infections. Although differential expression analysis failed to show predictive value, MAGICAL identified epigenetic circuit biomarkers that distinguished methicillin-resistant from methicillin-susceptible S. aureus infections.
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Affiliation(s)
- Xi Chen
- Center for Computational Biology, Flatiron Institute, New York, NY, USA
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Yuan Wang
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Antonio Cappuccio
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wan-Sze Cheng
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Venugopalan D. Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Clare M. Miller
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aliza B. Rubenstein
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - German Nudelman
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alicja Tadych
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Chandra L. Theesfeld
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Alexandria Vornholt
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Felicia Ruffin
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Michael Dagher
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Daniel G. Chawla
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | | | | | - Lishomwa C. Ndhlovu
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Robert Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven H. Kleinstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Pathology and Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | | | - Irene Ramos
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vance G. Fowler
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Christopher W. Woods
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- These authors jointly supervised this work: Elena Zaslavsky, Olga G. Troyanskaya, Stuart C. Sealfon
| | - Olga G. Troyanskaya
- Center for Computational Biology, Flatiron Institute, New York, NY, USA
- Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, NJ, USA
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- These authors jointly supervised this work: Elena Zaslavsky, Olga G. Troyanskaya, Stuart C. Sealfon
| | - Stuart C. Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- These authors jointly supervised this work: Elena Zaslavsky, Olga G. Troyanskaya, Stuart C. Sealfon
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3
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Sparks R, Rachmaninoff N, Hirsch DC, Bansal N, Lau WW, Martins AJ, Chen J, Liu CC, Cheung F, Failla LE, Biancotto A, Fantoni G, Sellers BA, Chawla DG, Howe KN, Mostaghimi D, Farmer R, Kotliarov Y, Calvo KR, Palmer C, Daub J, Foruraghi L, Kreuzburg S, Treat J, Urban AK, Jones A, Romeo T, Deuitch NT, Moura NS, Weinstein B, Moir S, Ferrucci L, Barron KS, Aksentijevich I, Kleinstein SH, Townsley DM, Young NS, Frischmeyer-Guerrerio PA, Uzel G, Pinto-Patarroyo GP, Cudrici CD, Hoffmann P, Stone DL, Ombrello AK, Freeman AF, Zerbe CS, Kastner DL, Holland SM, Tsang JS. Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health. Res Sq 2023:rs.3.rs-2070975. [PMID: 36993430 PMCID: PMC10055521 DOI: 10.21203/rs.3.rs-2070975/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health.
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Affiliation(s)
- Rachel Sparks
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Nicholas Rachmaninoff
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
- Graduate Program in Biological Sciences, University of Maryland, College Park, MD 20742, USA
| | - Dylan C. Hirsch
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Neha Bansal
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - William W. Lau
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
- Office of Intramural Research, CIT, NIH, Bethesda, MD 20892, USA
| | - Andrew J. Martins
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Jinguo Chen
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Candace C. Liu
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Foo Cheung
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Laura E. Failla
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | | | - Giovanna Fantoni
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Brian A. Sellers
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Daniel G. Chawla
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Katherine N. Howe
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Darius Mostaghimi
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Rohit Farmer
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Yuri Kotliarov
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Katherine R. Calvo
- Hematology Section, Department of Laboratory Medicine, NIH Clinical Center, Bethesda, MD 20892, USA
| | - Cindy Palmer
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Janine Daub
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Ladan Foruraghi
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Samantha Kreuzburg
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Jennifer Treat
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Amanda K. Urban
- Clinical Research Directorate, Frederick National Laboratory for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701, USA
| | - Anne Jones
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Tina Romeo
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Natalie T. Deuitch
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Natalia Sampaio Moura
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Barbara Weinstein
- Hematology Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Susan Moir
- Laboratory of Immunoregulation, NIAID, NIH, Bethesda, MD 20892, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD 21224, USA
| | - Karyl S. Barron
- Divison of Intramural Research, NIAID, NIH, Bethesda, MD 20892, USA
| | - Ivona Aksentijevich
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Steven H. Kleinstein
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06510, USA
- Department of Pathology, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Danielle M. Townsley
- Hematology Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Neal S. Young
- Hematology Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA
| | | | - Gulbu Uzel
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | | | - Cornelia D. Cudrici
- National Institute of Arthritis and Musculoskeletal and Skin Diseases, NIH, Bethesda MD 20892, USA
| | - Patrycja Hoffmann
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Deborah L. Stone
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Amanda K. Ombrello
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Alexandra F. Freeman
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Christa S. Zerbe
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Daniel L. Kastner
- Inflammatory Diseases Section, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Steven M. Holland
- Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD 20892, USA
| | - John S. Tsang
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
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4
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Konstorum A, Mohanty S, Zhao Y, Melillo A, Vander Wyk B, Nelson A, Tsang S, Blevins TP, Belshe R, Chawla DG, Rondina MT, Gill TM, Montgomery RR, Allore HG, Kleinstein SH, Shaw AC. Platelet response to influenza vaccination reflects effects of aging. Aging Cell 2023; 22:e13749. [PMID: 36656789 PMCID: PMC9924941 DOI: 10.1111/acel.13749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 10/21/2022] [Accepted: 11/15/2022] [Indexed: 01/20/2023] Open
Abstract
Platelets are uniquely positioned as mediators of not only hemostasis but also innate immunity. However, how age and geriatric conditions such as frailty influence platelet function during an immune response remains unclear. We assessed the platelet transcriptome at baseline and following influenza vaccination in Younger (age 21-35) and Older (age ≥65) adults (including community-dwelling individuals who were largely non-frail and skilled nursing facility (SNF)-resident adults who nearly all met criteria for frailty). Prior to vaccination, we observed an age-associated increase in the expression of platelet activation and mitochondrial RNAs and decrease in RNAs encoding proteins mediating translation. Age-associated differences were also identified in post-vaccination response trajectories over 28 days. Using tensor decomposition analysis, we found increasing RNA expression of genes in platelet activation pathways in young participants, but decreasing levels in (SNF)-resident adults. Translation RNA trajectories were inversely correlated with these activation pathways. Enhanced platelet activation was found in community-dwelling older adults at the protein level, compared to young individuals both prior to and post-vaccination; whereas SNF residents showed decreased platelet activation compared to community-dwelling older adults that could reflect the influence of decreased translation RNA expression. Our results reveal alterations in the platelet transcriptome and activation responses that may contribute to age-associated chronic inflammation and the increased incidence of thrombotic and pro-inflammatory diseases in older adults.
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Affiliation(s)
- Anna Konstorum
- Department of PathologyYale School of MedicineNew HavenConnecticutUSA
| | - Subhasis Mohanty
- Department of Internal Medicine, Section of Infectious DiseasesYale School of MedicineNew HavenConnecticutUSA
| | - Yujiao Zhao
- Section of Rheumatology, Department of Internal MedicineYale School of MedicineNew HavenConnecticutUSA
| | - Anthony Melillo
- Department of PathologyYale School of MedicineNew HavenConnecticutUSA
| | - Brent Vander Wyk
- Department of Internal Medicine, Section of Geriatrics and Program on AgingYale School of MedicineNew HavenConnecticutUSA
| | - Allison Nelson
- Department of Internal Medicine, Section of Infectious DiseasesYale School of MedicineNew HavenConnecticutUSA
| | - Sui Tsang
- Department of Internal Medicine, Section of Geriatrics and Program on AgingYale School of MedicineNew HavenConnecticutUSA
| | - Tamara P. Blevins
- Division of Infectious Diseases, Department of MedicineSaint Louis University School of MedicineSt. LouisMissouriUSA
| | - Robert B. Belshe
- Division of Infectious Diseases, Department of MedicineSaint Louis University School of MedicineSt. LouisMissouriUSA
| | - Daniel G. Chawla
- Program in Computational Biology and BioinformaticsYale UniversityNew HavenConnecticutUSA
| | - Matthew T. Rondina
- Departments of Internal Medicine and Pathology, and the Molecular Medicine ProgramUniversity of Utah HealthSalt Lake CityUtahUSA
- Department of Medicine and the GRECCGeorge E. Wahlen VAMCSalt Lake CityUtahUSA
| | - Thomas M. Gill
- Department of Internal Medicine, Section of Geriatrics and Program on AgingYale School of MedicineNew HavenConnecticutUSA
| | - Ruth R. Montgomery
- Section of Rheumatology, Department of Internal MedicineYale School of MedicineNew HavenConnecticutUSA
| | - Heather G. Allore
- Department of Internal Medicine, Section of Geriatrics and Program on AgingYale School of MedicineNew HavenConnecticutUSA
| | - Steven H. Kleinstein
- Department of PathologyYale School of MedicineNew HavenConnecticutUSA
- Program in Computational Biology and BioinformaticsYale UniversityNew HavenConnecticutUSA
| | - Albert C. Shaw
- Department of Internal Medicine, Section of Infectious DiseasesYale School of MedicineNew HavenConnecticutUSA
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5
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Chawla DG, Cappuccio A, Tamminga A, Sealfon SC, Zaslavsky E, Kleinstein SH. Benchmarking transcriptional host response signatures for infection diagnosis. Cell Syst 2022; 13:974-988.e7. [PMID: 36549274 PMCID: PMC9768893 DOI: 10.1016/j.cels.2022.11.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 08/04/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022]
Abstract
Identification of host transcriptional response signatures has emerged as a new paradigm for infection diagnosis. For clinical applications, signatures must robustly detect the pathogen of interest without cross-reacting with unintended conditions. To evaluate the performance of infectious disease signatures, we developed a framework that includes a compendium of 17,105 transcriptional profiles capturing infectious and non-infectious conditions and a standardized methodology to assess robustness and cross-reactivity. Applied to 30 published signatures of infection, the analysis showed that signatures were generally robust in detecting viral and bacterial infections in independent data. Asymptomatic and chronic infections were also detectable, albeit with decreased performance. However, many signatures were cross-reactive with unintended infections and aging. In general, we found robustness and cross-reactivity to be conflicting objectives, and we identified signature properties associated with this trade-off. The data compendium and evaluation framework developed here provide a foundation for the development of signatures for clinical application. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Daniel G Chawla
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Antonio Cappuccio
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Andrea Tamminga
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Stuart C Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Steven H Kleinstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA; Department of Pathology and Department of Immunobiology, Yale School of Medicine, New Haven, CT 06511, USA.
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6
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Fourati S, Tomalin LE, Mulè MP, Chawla DG, Gerritsen B, Rychkov D, Henrich E, Miller HER, Hagan T, Diray-Arce J, Dunn P, Levy O, Gottardo R, Sarwal MM, Tsang JS, Suárez-Fariñas M, Pulendran B, Kleinstein SH, Sékaly RP. Pan-vaccine analysis reveals innate immune endotypes predictive of antibody responses to vaccination. Nat Immunol 2022; 23:1777-1787. [PMID: 36316476 PMCID: PMC9747610 DOI: 10.1038/s41590-022-01329-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 09/12/2022] [Indexed: 11/05/2022]
Abstract
Several studies have shown that the pre-vaccination immune state is associated with the antibody response to vaccination. However, the generalizability and mechanisms that underlie this association remain poorly defined. Here, we sought to identify a common pre-vaccination signature and mechanisms that could predict the immune response across 13 different vaccines. Analysis of blood transcriptional profiles across studies revealed three distinct pre-vaccination endotypes, characterized by the differential expression of genes associated with a pro-inflammatory response, cell proliferation, and metabolism alterations. Importantly, individuals whose pre-vaccination endotype was enriched in pro-inflammatory response genes known to be downstream of nuclear factor-kappa B showed significantly higher serum antibody responses 1 month after vaccination. This pro-inflammatory pre-vaccination endotype showed gene expression characteristic of the innate activation state triggered by Toll-like receptor ligands or adjuvants. These results demonstrate that wide variations in the transcriptional state of the immune system in humans can be a key determinant of responsiveness to vaccination.
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Affiliation(s)
- Slim Fourati
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA
| | - Lewis E Tomalin
- Center for Biostatistics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matthew P Mulè
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID and Center for Human Immunology (CHI), NIH, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program, Cambridge University, Cambridge, UK
| | | | | | - Dmitry Rychkov
- Division of Transplant Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Evan Henrich
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Thomas Hagan
- Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Joann Diray-Arce
- Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Patrick Dunn
- ImmPort Curation Team, NG Health Solutions, Rockville, MD, USA
| | - Ofer Levy
- Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Raphael Gottardo
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Biomedical Data Science Center, University of Lausanne and Lausanne University Hospital, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Minnie M Sarwal
- Division of Transplant Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - John S Tsang
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID and Center for Human Immunology (CHI), NIH, Bethesda, MD, USA
| | - Mayte Suárez-Fariñas
- Center for Biostatistics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bali Pulendran
- Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Rafick-Pierre Sékaly
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA.
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7
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Hagan T, Gerritsen B, Tomalin LE, Fourati S, Mulè MP, Chawla DG, Rychkov D, Henrich E, Miller HER, Diray-Arce J, Dunn P, Lee A, Levy O, Gottardo R, Sarwal MM, Tsang JS, Suárez-Fariñas M, Sékaly RP, Kleinstein SH, Pulendran B. Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses. Nat Immunol 2022; 23:1788-1798. [PMID: 36316475 PMCID: PMC9869360 DOI: 10.1038/s41590-022-01328-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 09/12/2022] [Indexed: 11/27/2022]
Abstract
Systems vaccinology has defined molecular signatures and mechanisms of immunity to vaccination. However, comparative analysis of immunity to different vaccines is lacking. We integrated transcriptional data of over 3,000 samples, from 820 adults across 28 studies of 13 vaccines and analyzed vaccination-induced signatures of antibody responses. Most vaccines induced signatures of innate immunity and plasmablasts at days 1 and 7, respectively, after vaccination. However, the yellow fever vaccine induced an early transient signature of T and B cell activation at day 1, followed by delayed antiviral/interferon and plasmablast signatures that peaked at days 7 and 14-21, respectively. Thus, there was no evidence for a 'universal signature' that predicted antibody response to all vaccines. However, accounting for the asynchronous nature of responses, we defined a time-adjusted signature that predicted antibody responses across vaccines. These results provide a transcriptional atlas of immunity to vaccination and define a common, time-adjusted signature of antibody responses.
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Affiliation(s)
- Thomas Hagan
- Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Bram Gerritsen
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Lewis E Tomalin
- Center for Biostatistics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Slim Fourati
- Emory University School of Medicine, Atlanta, GA, USA
| | - Matthew P Mulè
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID and Center for Human Immunology (CHI), NIH, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program, Cambridge University, Cambridge, UK
| | - Daniel G Chawla
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Dmitri Rychkov
- Division of Transplant Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Evan Henrich
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Joann Diray-Arce
- Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Patrick Dunn
- ImmPort Curation Team, NG Health Solutions, Rockville, MD, USA
| | - Audrey Lee
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Ofer Levy
- Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Raphael Gottardo
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Lausanne and Lausanne University Hospital, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Minne M Sarwal
- Division of Transplant Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - John S Tsang
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID and Center for Human Immunology (CHI), NIH, Bethesda, MD, USA
| | - Mayte Suárez-Fariñas
- Center for Biostatistics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | | | - Bali Pulendran
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.
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8
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Diray-Arce J, Miller HER, Henrich E, Gerritsen B, Mulè MP, Fourati S, Gygi J, Hagan T, Tomalin L, Rychkov D, Kazmin D, Chawla DG, Meng H, Dunn P, Campbell J, Sarwal M, Tsang JS, Levy O, Pulendran B, Sekaly R, Floratos A, Gottardo R, Kleinstein SH, Suárez-Fariñas M. The Immune Signatures data resource, a compendium of systems vaccinology datasets. Sci Data 2022; 9:635. [PMID: 36266291 PMCID: PMC9584267 DOI: 10.1038/s41597-022-01714-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 09/22/2022] [Indexed: 01/04/2023] Open
Abstract
Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern 'omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines. However, comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.
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Affiliation(s)
- Joann Diray-Arce
- Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Helen E R Miller
- Harvard Medical School, Boston, MA, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Evan Henrich
- Harvard Medical School, Boston, MA, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Matthew P Mulè
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID NIH Center for Human Immunology, NIH, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program, Department of Medicine, Cambridge University, Atlanta, GA, USA
| | - Slim Fourati
- Emory University School of Medicine, Atlanta, GA, USA
| | - Jeremy Gygi
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Thomas Hagan
- Stanford University School of Medicine, Stanford University, Stanford, CA, USA
- Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Lewis Tomalin
- Department of Population Health Sciences and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Dmitry Rychkov
- University of California, San Francisco, San Francisco, CA, USA
| | - Dmitri Kazmin
- The Jackson Laboratory for Genomic Medicine, Farmington CT, Rockville, MD, USA
| | - Daniel G Chawla
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | | | - Patrick Dunn
- ImmPort Curation Team, NG Health Solutions, Rockville, MD, USA
| | - John Campbell
- ImmPort Curation Team, NG Health Solutions, Rockville, MD, USA
| | - Minnie Sarwal
- University of California, San Francisco, San Francisco, CA, USA
| | - John S Tsang
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID NIH Center for Human Immunology, NIH, Bethesda, MD, USA
| | - Ofer Levy
- Precision Vaccines Program, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
| | - Bali Pulendran
- Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Rafick Sekaly
- Emory University School of Medicine, Atlanta, GA, USA
| | - Aris Floratos
- Columbia University Medical Center, New York, NY, USA
| | - Raphael Gottardo
- Harvard Medical School, Boston, MA, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Lausanne and University Hospital of Lausanne, Lausanne, Switzerland
| | | | - Mayte Suárez-Fariñas
- Department of Population Health Sciences and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
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9
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Cui A, Chawla DG, Kleinstein SH. Sex-Biased Aging Effects on Ig Somatic Hypermutation Targeting. J Immunol 2021; 206:101-108. [PMID: 33288546 PMCID: PMC8582005 DOI: 10.4049/jimmunol.2000576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 10/25/2020] [Indexed: 11/19/2022]
Abstract
Aged individuals, particularly males, display an impaired level of Ab response compared with their younger counterparts, yet the molecular mechanisms responsible for the discrepancy are not well understood. We hypothesize that some of this difference may be linked to B cell somatic hypermutation (SHM) targeting, including error-prone DNA repair activities that are crucial to Ab diversification. To examine the effects of aging on SHM targeting, we analyzed B cell Ig repertoire sequences from 27 healthy male and female human subjects aged 20-89. By studying mutation patterns based on 985,069 mutations obtained from 123,415 sequences, we found that the SHM mutability hierarchies on microsequence motifs (i.e., SHM hot/cold spots) are mostly consistent between different age and sex groups. However, we observed a lower frequency in mutations involving Phase II SHM DNA repair activities in older males, but not in females. We also observed, from a separate study, a decreased expression level of DNA mismatch repair genes involved in SHM in older individuals compared with younger individuals, with larger fold changes in males than in females. Finally, we showed that the balance between Phase I versus Phase II SHM activities impacts the resulting Ig phenotypes. Our results showed that the SHM process is altered in some older individuals, providing insights into observed clinical differences in immunologic responses between different age and sex groups.
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Affiliation(s)
- Ang Cui
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA 02139;
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Daniel G Chawla
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511
| | - Steven H Kleinstein
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511;
- Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06520; and
- Department of Pathology and Department of Immunobiology, Yale School of Medicine, New Haven, CT 06510
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10
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Avey S, Mohanty S, Chawla DG, Meng H, Bandaranayake T, Ueda I, Zapata HJ, Park K, Blevins TP, Tsang S, Belshe RB, Kaech SM, Shaw AC, Kleinstein SH. Seasonal Variability and Shared Molecular Signatures of Inactivated Influenza Vaccination in Young and Older Adults. J Immunol 2020; 204:1661-1673. [PMID: 32060136 DOI: 10.4049/jimmunol.1900922] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 01/08/2020] [Indexed: 01/01/2023]
Abstract
The seasonal influenza vaccine is an important public health tool but is only effective in a subset of individuals. The identification of molecular signatures provides a mechanism to understand the drivers of vaccine-induced immunity. Most previously reported molecular signatures of human influenza vaccination were derived from a single age group or season, ignoring the effects of immunosenescence or vaccine composition. Thus, it remains unclear how immune signatures of vaccine response change with age across multiple seasons. In this study we profile the transcriptional landscape of young and older adults over five consecutive vaccination seasons to identify shared signatures of vaccine response as well as marked seasonal differences. Along with substantial variability in vaccine-induced signatures across seasons, we uncovered a common transcriptional signature 28 days postvaccination in both young and older adults. However, gene expression patterns associated with vaccine-induced Ab responses were distinct in young and older adults; for example, increased expression of killer cell lectin-like receptor B1 (KLRB1; CD161) 28 days postvaccination positively and negatively predicted vaccine-induced Ab responses in young and older adults, respectively. These findings contribute new insights for developing more effective influenza vaccines, particularly in older adults.
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Affiliation(s)
- Stefan Avey
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511
| | - Subhasis Mohanty
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520
| | - Daniel G Chawla
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511
| | - Hailong Meng
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520
| | - Thilinie Bandaranayake
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520
| | - Ikuyo Ueda
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520
| | - Heidi J Zapata
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520
| | - Koonam Park
- Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520; and
| | - Tamara P Blevins
- Division of Infectious Diseases, Department of Medicine, Saint Louis University School of Medicine, St. Louis, MO 63104
| | - Sui Tsang
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520
| | - Robert B Belshe
- Division of Infectious Diseases, Department of Medicine, Saint Louis University School of Medicine, St. Louis, MO 63104
| | - Susan M Kaech
- Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520; and
| | - Albert C Shaw
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520;
| | - Steven H Kleinstein
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511; .,Department of Pathology, Yale School of Medicine, New Haven, CT 06520.,Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520; and
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11
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Chawla DG, Shah RV, Barth ZK, Lee JD, Badecker KE, Naik A, Brewster MM, Salmon TP, Peel N. Caenorhabditis elegans glutamylating enzymes function redundantly in male mating. Biol Open 2016; 5:1290-8. [PMID: 27635036 PMCID: PMC5051658 DOI: 10.1242/bio.017442] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Microtubule glutamylation is an important modulator of microtubule function and has been implicated in the regulation of centriole stability, neuronal outgrowth and cilia motility. Glutamylation of the microtubules is catalyzed by a family of tubulin tyrosine ligase-like (TTLL) enzymes. Analysis of individual TTLL enzymes has led to an understanding of their specific functions, but how activities of the TTLL enzymes are coordinated to spatially and temporally regulate glutamylation remains relatively unexplored. We have undertaken an analysis of the glutamylating TTLL enzymes in C. elegans. We find that although all five TTLL enzymes are expressed in the embryo and adult worm, loss of individual enzymes does not perturb microtubule function in embryonic cell divisions. Moreover, normal dye-filling, osmotic avoidance and male mating behavior indicate the presence of functional amphid cilia and male-specific neurons. A ttll-4(tm3310); ttll-11(tm4059); ttll-5(tm3360) triple mutant, however, shows reduced male mating efficiency due to a defect in the response step, suggesting that these three enzymes function redundantly, and that glutamylation is required for proper function of the male-specific neurons. Summary: Although mutations in individual microtubule glutamylating enzymes do not disrupt essential microtubule functions in C. elegans, combining mutations in three enzymes uncovers a redundant function for glutamylation in male mating.
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Affiliation(s)
- Daniel G Chawla
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
| | - Ruchi V Shah
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
| | - Zachary K Barth
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
| | - Jessica D Lee
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
| | | | - Anar Naik
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
| | - Megan M Brewster
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
| | - Timothy P Salmon
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
| | - Nina Peel
- Department of Biology, The College of New Jersey, Ewing, NJ 08618, USA
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