Quantification of lymphocyte

dynamics by in vivo labelling

Dr. José Borghans and Dr. Kiki Tesselaar

Marie Curie ITN: QuanTI

Mid-term review meeting – DKFZ, Heidelberg

Mariona Baliu Piqué

About me

University of Barcelona:

BSc. Molecular

Biotechnology

MSc. Translational

Medicine

About me

UMC Utrecht:

Nov. 2014

PhD Marie Curie ITN

Quantify dynamics of different lymphocyte subsets

mice men

Healthy aging Immune

reconstitution

1. Explain differences in the labels used to quantify lymphocyte dynamics

2.

Objectives

• Build in the DNA of cells

• Non-radioactive, non-toxic: Suitable for human (clinical) investigation

• Mathematical model needed

P P

N

Hydrogen Deuterium

Methods

Stable isotope labeling: Deuterium

Lymphocyte maintenance during healthy aging requires no substantial alterations in cellular turnover

Liset Westera, Vera van Hoeven, Julia Drylewicz, Gerrit Spierenburg, Jeroen F van Velzen, Rob J de Boer, Kiki Tesselaar, José AM Borghans

Healthy aging Different labels Immune reconstitution

Results

Young individuals

Elderly individuals

No substantial alterations in lymphocyte turnover

during healthy aging

Healthy aging Different labels Immune reconstitution

Estimated turnover rate

Results

Signs of homeostatic compensation in lymphopenic

situations in humans

0.00

0.05

0.10

0.15

0.20 d2-glu normalized 0.65 x plasma AUC

D2O

d2-glu normalized to thymocytes

PBMC Splenocytes

pro

life

rati

on

rate

p (

day

-1)

0.00

0.05

0.10

0.15

0.20 d2-glu normalized 0.65 x plasma AUC

D2O

d2-glu normalized to thymocytes

PBMC Splenocytes

pro

life

rati

on

rate

p (

day

-1)

0.00

0.05

0.10

0.15

0.20 d2-glu normalized 0.65 x plasma AUC

D2O

d2-glu normalized to thymocytes

PBMC Splenocytes

pro

life

rati

on

rate

p (

day

-1)

Healthy aging Different labels Immune reconstitution

Results

Reconciling estimates of cell proliferation from stable isotope labeling experiments Raya Ahmed1*, Liset Westera2*, Julia Drylewicz2,3, Marjet Elemans4, Yan Zhang1, Elizabeth Kelly1, Kiki Tesselaar2, Rob J de Boer3, Derek C

Macallan1‡, José AM Borghans2‡ and Becca Asquith4‡

Normalization of the D-glucose to fast cells (thymocytes)

0.00

0.05

0.10

0.15

0.20 d2-glu normalized 0.65 x plasma AUC

D2O

d2-glu normalized to thymocytes

PBMC Splenocytes

pro

life

rati

on

rate

p (

day

-1)

Training events

• Attendance to the "5th International Workshop on CMV

and Immunosenescence“, Amsterdam, The Netherlands,

Nov 2014.

• Attendance to the Annual Meeting of the Dutch Society for

Immunology (NVVI), Amsterdam, The Netherlands, Dec

2014.

• Course on Advanced Immunology at the University Medical

Centre of Utrecht (UMCU), Jan 2015.

Healthy aging Different labels Immune reconstitution

• Dynamics of different cell

populations

• Dynamics of different cell populations

• Increase number of patients

• Studies in mice

Future

• Compare estimates

based on different labels

and see if they provide

additional information?

• Course on Laboratory Animal Science at the Utrecht University,

Feb 2015.

• QUANTI WP1 partners meetings.

• Secondments:

• Experimental: Paris (QuanTI).

• Mathematical modelling: London (WP1).

• Outreach activities and dissemination of my research.

Obtain a broader view about immunology and get training

on mathematical modelling

Acknowledgements

This research was funded by the European Union

WP1:

Busch et al., Nature Protocols 2007

Deuterium (2H) labeling

Label uptake

Label loss

Cell death

Cell

differentiation or

migration

X

% la

bele

d

time

p/d*

d*

% la

bele

d

time

p/d*

d*

P P

N

Hydrogen Deuterium

In vivo deuterium labeling in humans

Blood/urine withdrawals

during and after label

administration

GC-MS

Mathematical modeling

2. Sampling

1. Labeling

3. Analysis

4. Interpretation

M0

M1

2H2O D2-glucose

Stem Cell Transplantation

Heavy water labeling

~1 year

after STC

Adapted from Westera et al. Methods Mol Biol 2013

Healthy aging

QuanTI in Healthy aging and autologus SCT

Study protocol

Up-labeling phase

Post-labeling phase

Healthy aging

Patient Age Age group Cell subsets Gender

A 24 Young (Vrisekoop et al., 2008) T cells M

B 22 Young (Vrisekoop et al., 2008) T cells M

C 25 Young (Vrisekoop et al., 2008) T cells M

D 20 Young (Vrisekoop et al., 2008) T cells M

E 22 Young (Vrisekoop et al., 2008) T cells M

Y01 24 Young B cells, γδ T cells F

Y02 23 Young B cells, γδ T cells F

Y03 21 Young B cells, γδ T cells M

Y04 20 Young B cells, γδ T cells M

Y05 21 Young B cells, γδ T cells M

A01 66 Aged T cells M

A02 72 Aged T cells M

A04 68 Aged T cells M

A07 68 Aged T cells M

A09 69 Aged T cells M

A03 67 Aged B cells, γδ T cells F

A05 66 Aged B cells, γδ T cells M

A06 75 Aged B cells, γδ T cells F

A10 69 Aged B cells, γδ T cells F

A11 67 Aged B cells, γδ T cells F

Patient Age Malignancy Reconstitution period at

time of enrollment (days) Induction therapy

Conditioning

Regimen

L01 61 NHL 287 R-CHOP, Ara-C BEAM

L02 54 MM 420

Thalidomide,

Dexamethasone,

Carfilzomib

Melphalan

L03 57 MM 358

Thalidomide,

Dexamethasone,

Adriamycin

Melphalan

NHL: Mantle Cell Lymphoma

MM: Multiple Myeloma

R-CHOP = Rituximab, Cyclophosphamide, Adriamycin, Vincristin, Prednisone

BEAM = Carmustine, Etoposide, Ara-C (cytarabin), Melphalan

Autologus Stem Cell Transplantation

Immune reconstitution after HSCT

Naive and memory CD4+ T cells recovery typically takes at least 2-3 years

Molldrem; Nat Med. 2005 Nov;11(11):1162-3

Reconciling estimates of cell proliferation from stable isotope labeling experiments

Raya Ahmed1*, Liset Westera2*, Julia Drylewicz2,3, Marjet Elemans4, Yan Zhang1, Elizabeth Kelly1, Kiki Tesselaar2, Rob J de Boer3, Derek C

Macallan1‡, José AM Borghans2‡ and Becca Asquith4‡

Problem

• D-glucose and D2O labeling

experiments performed in different

laboratories give different results

Why?

• Biochemical differences?

• Protocol differences?

• ….

In vivo and in vitro, no

fundamental differences

between D-glucose and D2O

labeling

D-glucose and D2O direct comparison in mice

Differences between D2O and D-glucose

Reconciling estimates of cell proliferation from stable isotope labeling experiments

Raya Ahmed1*, Liset Westera2*, Julia Drylewicz2,3, Marjet Elemans4, Yan Zhang1, Elizabeth Kelly1, Kiki Tesselaar2, Rob J de Boer3, Derek C

Macallan1‡, José AM Borghans2‡ and Becca Asquith4‡

0.00

0.05

0.10

0.15

0.20 d2-glu normalized 0.65 x plasma AUC

D2O

d2-glu normalized to thymocytes

PBMC Splenocytes

pro

life

rati

on

rate

p (

day

-1)

0.00

0.05

0.10

0.15

0.20 d2-glu normalized 0.65 x plasma AUC

D2O

d2-glu normalized to thymocytes

PBMC Splenocytes

pro

life

rati

on

rate

p (

day

-1)

D-glucose Plasma glucose x 0.65

Normalization Result

D2O Plasma D2O Fast cells

Mathematical modeling

Normalization of the D-glucose to fast cells (thymocytes)

Differences between D2O and D-glucose

Healthy aging and STC

2. TCM

2. TTM

2. TEM

2. TTD

1. Antigen specific

memory T cells

3. T regs

CD4+ memory

CD8+ memory

CD

4

CD

45R

O

CD

45R

O

SSC

A

CD8 CD3

CD27

CD27

Dynamics of different cell populations