FCM Data Management and Analysis in ImmPort
Richard H. Scheuermann, Ph.D.
Department of Pathology and Division of Biomedical Informatics
U.T. Southwestern Medical Center, Dallas, TX
Outline
• The Immunology Database and Analysis Portal – ImmPort
• Data management challenges– Support for large projects using diverse experiment
methodologies
– Extensive clinical data
• Automated FCM data analysis challenges– Cross-sample comparison
• Linkage of automated FCM analysis results with knowledge about cell types– Use of the Cell Ontology
ImmPort Purpose and History
• NIH/NIAID/DAIT would like to:– maximize the return on the public investment in basic, translational and clinical
research
– allow investigators to more effectively extract meaningful information from the vast amounts of data generated from advanced research technologies
– => data sharing policy
• Bioinformatics Integration Support Contract (BISC) to support data sharing for all DAIT-funded programs - basic, translational and clinical research
• Immunology Database and Analysis Portal (ImmPort) - www.ImmPort.org – Archive and manage basic and clinical research data
– Integrate these research data with extensive biological knowledge
– Support analysis of these integrated data
Home page
www.immport.org
• Support for many large projects that use a variety of different experiment methodologies, including FCM
Challenge 1
Immune Function and Biodefense in Children, Elderly, and Immunocompromised Populations Program
Population Genetics Analysis Program: Immunity to Vaccines/Infections Program
HLA Region Genetics in Immune-Mediated Diseases Program
Other Consortium Projects
Immune Modeling Centers
ImmPort Research Data | My Work Bench
Browse Data/ ImmPort Research Data/ ImmPort Supported Programs
Grants/Contracts/Projects:
Immune Function and Biodefense in Children, Elderly, and Immunocompromised Populations Program
Project Title InstitutionPrinciple
Investigator ObjectiveNumber of
Subjects Mechanistic Assays
An Improved Influenza A Vaccine for Rapid Protection of the Elderly
The Wistar InstituteHildegund C. J. Ertl, M.D.
To conduct pre-clinical studies needed to develop a vaccine for the elderly that would provide protection in the event of a bioterror attack with influenza A virus.
600ELISA, ELISPOT, Flow Cytometry
Protective Immunity in Transplant Recipients Emory Transplant CenterLarsen, Christian, Ph.D.
To determine the effects of chronic immunosuppressive therapies on adaptive, innate and specific immunity
90ELISA, ELISPOT, Microarry, RT - PCR
Kinetic analysis of immunologic repletion and influenza vaccine responsiveness
Children´s Hospital of Philadelphia
Sullivan, Kathleen, Ph.D.
To propose a comprehensive analysis of the immunologic response to killed trivalent influenza vaccine in different immunocompromised populations in order to understand how to improve vaccine responses
54ELISPOT, Sequencing, Flow Cytometry
Immune Function and Biodefense in Children, Elderly, and Immunocompromised Populations: TLRs in Innate Immunity and the Induction of Adaptive Immunity in the Neonate and Infant
University of WashingtonWilson, Christopher, M.D.
To define comprehensively and in molecular and cellular detail differences in recognition and response to microbe-derived danger signals between adults, neonates and infants, and how these, in turn, contribute to differences in innate immunity and the induction of antigen-specific (adaptive) immunity
17 adults, 17 neonates
RT-PCR, ELISA, Flow Cytometry, Microarray
Responses to Influenza Vaccination in Systemic Lupus
Oklahoma Medical Research Foundation (OMRF)
Thompson, Linda, Ph.D.
To understand why many patients with systemic lupus erythematosus (SLE) fail to make adequate responses to immunization with the influenza vaccine.
60ELISPOT, ELISA, multiplex RT-PCR
Immune function and Biodefense in Children, Elderly and Immunocompromised Populations
Oregon Health and Science University
Nikolich-Zugich, Janko, M.D., Ph.D.
To characterize immune markers and mechanisms in the elderly that determine their vulnerability to infectious and bioterrorism agents in categories A-C.
130Flow Cytometry, ELISA, RT-PCR, Gene expression,
Immune Response to Virus Infection During Pregnancy
Mt. Sinai School of Medicine
Moran, Thomas, Ph.D.
To determine whether the different trimesters of pregnancy, characterized by unique hormonal environments, are associated with (a) identifiable, discrete changes in maternal systemic immunity and/or (b) recognizable alterations in susceptibility to select bio-defense pathogens and/or (c) differential responses to influenza vaccination
75Flow Cytometry, multiplex ELISA, RT-PCR
Rochester Biodefense University of Rochester Sanz, Ignacio, M.D.To identify the specific immune defects that make immunocomprised populations specially susceptible at bioterrorists attack.
280 Flow Cytometry
Innate Immune Responsiveness in the Elderly and the Immunosuppressed
Yale School of Medicine Fikrig, Erol, M.D.
This proposal will explore the hypothesis that altered innate immune responsiveness in the elderly and the immunosuppressed contributes to vaccine unresponsiveness or disease susceptibility.
1160SNP genotyping, Flow Cytometry, ELISA
ImmPort Research Data | My Work Bench
Browse Data/ ImmPort Research Data/ ImmPort Supported Programs
• Extensive clinical data for correlative analysis
Challenge 2
AUTOMATED FCM ANALYSIS
Challenge 3
• Identification of same cell populations in multiple samples
Challenge 4
• Linkage of automated results with knowledge about known cell types
N1-3
UM1-2
UM3-4PB GSM
GNSM
DNM
CD27
IgD
B220
CD24
CD38
IgG
A
17 B Cell Populations in Blood
Population characteristics
Populationa Colorb CD27c IgDc IgGc CD38c CD24c B220c Proportiond Putative cell typea
N1 Gray - + - + int + 48.94% naïve (CD38+)[Bm2?]N2 Magenta - + - - + + 4.69% naïve (CD38-)N3 Purple - + - + + low 4.41% naïve (CD38+B220low)
UM1 Darkred + + - + + + 1.55% unswitched memory (CD38+)UM2 Salmon + + - - + + 0.94% unswitched memory (CD38-)[Bm1?]UM3 Darkblue + int - + + low 6.16% IgDlow unswitched memory (CD38+)UM4 Green + int - - + low 11.50% IgDlow unswitched memory (CD38-)
GSM1 Grayishgreen + + + + + + 0.36% switching memory (IgD+IgG+CD38+)GSM2 Yellow + - + + + low 4.05% switched memory (CD38+)[early Bm5?]GSM3 Blue + - + - + low 4.40% switched memory (CD38-)[late Bm5?]
GNSM1 Cyan + - - + + low 4.84% IgD-IgG- memoryGNSM2 Darkgreen + - - - + low 3.84% IgD-IgG- memoryGNSM3 Teal + - - + + + 1.30% IgD-IgG- memoryGNSM4 Orange + - - - - low 0.51% IgD-IgG- memory
DNSM1 Pink - - + - - + 0.85% double negative memory (IgG+)DNSM2 Darkgray - - - - - + 0.91% double negative memory (IgG-)
PB Red high - - high - low 0.75% plasmablasts
Summary Statistics
B cell component of the Cell Ontology
http://www.obofoundry.org/
FCM Data Challenges
• Data management challenges– Support for large projects using diverse experiment
methodologies
– Extensive clinical data for correlative analysis
• Automated FCM data analysis challenges– Cross-sample comparison
• Linkage of automated FCM analysis results with knowledge about cell types– Use of the Cell Ontology
UT SouthwesternYu (Max) QianDavid DougallMegan KongJamie LeeJennifer CaiJie HuangNishanth MarthandanDiane XiangYoung Bun KimPaula GuidryEva Sadat
Ignacio Sanz (Rochester)Chungwen Wei (Rochester)Tim Mosmann (Rochester)Adam Seegmiller (UTSW)Nitin Karandikar (UTSW)Christine Martens (Emory)Chris Ding (UTA)
Alex Diehl (Jackson Labs)Terry Meehan (Jackson Labs)Martin Zand (Rochester)
Supported by NIH N01AI40076 and N01AI40041
Northrop GrummanJohn CampbellCarl DahlkeYue LiuLiz ThompsonJeff WiserMike Attasi
Immune Tolerance NetworkDave ParrishKeith BoyceTom CasaleJeff Bluestone
Acknowledgments