Integrating Cytomics with Proteomics

J. Paul RobinsonProfessor of Immunopharmacology

Professor of Biomedical Engineering

Harvard UniversityNovember, 2004

Purdue University Cytometry Laboratories

Cytome - Cytomics• Cytomes can be defined as cellular systems and subsystems

and functional components of the body.

• Cytomics is the study of the heterogeneity of cytomes or more precisely the study of molecular single cell phenotypes resulting from genotype and exposure in combination with exhaustive bioinformatics knowledge extraction.

• The word Cytomics was first used in 2001 by:Davies E, Stankovic B, Azama K, Shibata K, Abe S.“Novel components of the plant cytoskeleton: A beginning to plant "cytomics"

Plant Science, Invited Review, Plant Science (160)2 (2001) pp. 185-196.

Cytomics links technology to biology – it relates measurement and detection to structure and function. It Integrates flow and image cytometry with proteomics.

Courtesy of Gunter Valet

Environment – Cytome (cell) – GenomeA web of interactions

Instead of concentrating on molecular targets within the relatively infinite network of highly redundant molecular pathways of cells, one could focus on the end result, represented by molecular phenotypes of cells as a consequence of both genotype

and environment.

Environment From Gene to ProteinGenome - Proteome

CellCytome

Exploring the Human CytomeTechnology

• Advanced microscopy techniques:– LM, EM, Confocal and laser scanning microscopy, spectral

imaging, FRET, SEM, TEM, digital microscopy, …

• High Content Screening:– High speed and large volume screening, …

• Flow Cytometry– Fast imaging in flow, …

• Biomolecular analysis techniques:– Single-cell polymerase chain reaction (PCR), labeling of

biomolecules by quantum dots, protein identification, etc

• Bioinformatics:– Data exploration, statistics and data management, …

Predictive Medicine by Cytomics(= therapy-dependent individualized disease

course prediction)

• Diseases represent molecular changes in cellular systems of organisms (cytomes)

• Cytomics: study of molecular cell phenotypes in combination with exhaustive bioinformatic knowledge extraction

• Cell phenotypes result from genotype and exposure

• Goal: individualized predictions >95% correct

Genomics

Cytomics

Proteomics

Genome Proteome

Cytome

A Human Cytome Project

Small working group having a number of roundtable discussions

From Valet, Tarnok, Murphy, Kriete, & Robinson

A Human Cytome Project ?

Systems Integration• Analytical Cytology

– Flow cytometry– Single cell analysis systems– Tissue analysis– High Content Analysis (screening)

• Image Analysis – Single cells– Tissues and sections– Cell culture systems

• Proteomics

Study approaches• Study 1: Cell growth in 3D matrix

• Study 2: 3D matrix isolation and characterization

• Study 3: Standard cell line characterization

(Study 4: toxins of phenotypically separated Listeriamonocytogenes)

Cellular heterogeneity

Cellular Heterogeneity• Identification and characterization of cellular systems is

advanced• We can separate and very highly define cellular systems

by with multivariate analysis

High-resolution cytology segmentation

ConventionalRGB Image

Spectrallysegmented Image

Wavelength (nm)

CharacteristicSpectra

High spectral resolution increases utility of spectrally responsive indicator dyesSlide from Dr. Richard Levenson, CRi, Inc.,35B Cabot Rd.,Woburn, MA 01801, www.cri-inc.com

Count

log green log red

dead

live

reduce temperatureless than 15°C

liquid

solid hydrogel

Flow Cytometry

Confocal Microscopy

Analysis of complex Microbial Systems

Count

log green log red

dead

live

Phenotypically different but mixed populations

Extracellular Matrix (ECM)

Tissue Engineering ApplicationsScaffold to support tissue growth Structure and function are closely relatedNeed in vitro models to study such as

MatrigelVitrogen

Small Intestinal Submucosa (SIS)Basal Lamina of the Avian OvarianFollicle

Visualization of morphology of cells embedded within a collagen matrix

Visualization of cell morphology within native ECM

Study 1: Cell growth in 3D matrix

With Professor Sophie LelièvreProfessor of Veterinary Medicine

Purdue University

Three-dimensional models of breast epithelial cell culturesrecapitulate tissue differentiation and tumor formation

1 10

normal

tumor

days

acini

Invasive tumornodule

In the presence of extracellular matrix enriched in laminin, non-neoplastic breast epithelial cells (HMT-3522 S1) form phenotypically normal tissue-like glandular structures (acini) while malignant breast epithelial cells (HMT-3522 T4-2) develop into tumor-like nodules. Cells are plated as single cells at day 1 and full differentiation and formation of large tumors is seen at day 10 of culture. A) In 3D culture, S1 cells arrest growth and differentiate after a few days of proliferation. B) In 3D culture, S1-derived T4 –2 cells continue to proliferate to form tumor-like nodules.

A

B

Cross-section indicatesthe presence of a central lumen

S1 phenotype

T4-2 phenotype

days6 8 10

30 microns

As tumors develop they enter in contact with cells from nonmalignant tissue

Contact co-culture: T4-2 cells grow toward S1 glandular structures and surround these structures. T4-2 cells were added to pre-formed S1 acini and cultured for 10 days. T4-2 cells were stained with DiI(red) prior to being plated, and S1 cells are stably transfected with green fluorescent protein(GFP). Images show co-cultures of S1 and T4-2 cells at days 6, 8, and 10. At day 6:Tumor cells (red) proliferate when in contact with S1 structures (green, arrow). Day 8:T4-2 cells expand over several S1 structures (5 glandular structures can be seen in green). Day 10: A single tumor (red) is in development; at least four S1 glandular structures (green) have been engulfed.

S1 phenotype(normal)

T4-2 phenotype(tumor)

Study

Flow Sorting followed by protein profiling

• Sort dsRed stained tumor cells (T4-2_ from GFP-non-malignant cells (S1) population after 3 weeks of co-culture

• Analyze the changes in protein expression profile compared to the control (separately cultured) T4-2 and S1 cell populations

Phenotypically S1 Normal Malignant T4-2 PhenotypeDifferences

HMT-3522 epithelial cells

Study 2Professor Eli Asem

School of Veterinary Medicine, Purdue University

Isolation and Characterization of Extracellular matrix

Basement Membrane• The maintenance of normal function of vertebrate cells

depends on the integrity of the extracellularmicroenvironment of the tissue/organ.

• Basement membranes (basal laminae) are specialized ECM sheets that participate in numerous physiological processes and play key roles in regulating proliferation and differentiation of cells.

• Only some of the proteins of basement membranes have been identified due to the complex protein composition and the unavailability of pure preparations.

• Recently a pure preparation was identified and shown to be biologically active

Background

Study 3

• A “standardized” cell culture environment

• Establishing a “normal” profile for HepG2 cell line

• Interest from pharmaceutical companies for some relatively fast classification systems

A Study of HepG2 cells

• HepG2 - cell line that is a human, primary liver cancer • Human hepatocellular liver carcinoma cell line, Epithelial

cells.• An established human hepatocarcinoma cell line with

epithelial morphology. HepG2 cells are used routinely for a variety of biochemical and cell biological studies. HepG2 is the most commonly used cell line for examining the regulation of hepatic protein synthesis by cytokines .

HepG2Cell Cycle analysis

Flow cytometry analysis of cell cycle using propidium iodide (PI) staining

# cells sorted3 x 106

# cells sorted1 x 106

Cells were sorted on a Beckman-Coulter Altra cell sorter prior to PF2D

Cell/system complexity can be reduced using tools such as flow cytometry

Figures from Roederer, et al

Concluding Thoughts

Beckman-Coulter automated PF2D protein separation system

Cell Sorter

• Developing an understanding of complex biological systems should be approached by first considering the heterogeneity of the system• Using a cytomics approach reduces the complexity at an earlier stage• Tools such as the PF2D offer a significant opportunity for cell biologists to approach proteomic solutions

Acknowledgements• Contributors – Collaborators

Dan Hirleman (ME)Yinlong Sun (CS)Kinam Park (IP)

• PostdocsGerald J. Gregori (Microbiology)Valery Patsekin (Photonics)Tytus Bernas (Proteomics)Sang Youp Lee (Fluidics)Bartek Rajwa (Biophysics)

• Graduate StudentsWamiq Ahmed (Computational)Murugesan Venkatapathi (M.Eng)Bulent Bayraktar (Computational)Silas Leavesley (BioEng)Jia Liu (Cell Biology)Connie Paul (Pharmaceutical)

• StaffJennie SturgisKathy RaghebCheryl HoldmanGretchen LawlerSteve Kelley

Departments & CentersPurdue University Cytometry LabsBasic Medical ScienceBiomedical Engineering Electrical & Computing EngineeringMechanical EngineeringBindley Bioscience CenterDiscovery ParkPurdue Cancer Center

Funding:NIH, NSF, USDA, Purdue UniversityCorporate: Beckman-Coulter, Point-Source,Parker-Hannifin, Bio-Rad, Polysciences

Purdue University Cytometry Laboratorieshttp://www.cyto.purdue.edu

Human Cytome Project:http://www.cytomic.info

Free copy from www.bangslabs.com