i

Decoding the Cell Receptor Signaling Pathway via Phosphoproteomics Approaches:

Preparation for the Investigation of the Crosstalk Between Positive Regulator and

Negative Regulator

By

Mengzhou Hu

B.S., University of Wisconsin Madison, 2018

Thesis

Submitted in partial fulfillment of the requirements for the Degree of Master of Science

in the Graduate Program of Biotechnology at Brown University

PROVIDENCE, RHODE ISLAND

May 2021

ii

AUTHORIZATION TO LEND AND REPRODUCE THE THESIS

As the sole author of this thesis, I authorize Brown University to lend it to other

institutions for the purpose of scholarly research.

Date

Mengzhou Hu, Author

I further authorize Brown University to reproduce this thesis by photocopying or

other means, in total or in part, at the request of other institutions or individuals for

the purpose of scholarly research.

Date

Mengzhou Hu, Author

iii

This thesis by Mengzhou Hu is accepted in its present form by the Graduate Program in

Biotechnology as satisfying the thesis requirements for the degree of Master of Science

Date Signature:

Dr. Arthur Salomon, Advisor

Date Signature:

Dr. Wayne Bowen, Reader

Date Signature:

Dr. Nicolas Fawzi, Reader

Approved by the Graduate Council

Date Signature:

Dr. Andrew G. Campbell, Dean of the Graduate School

iv

Acknowledgements

I am grateful to have the opportunity to work in Dr. Arthur Salomon’s laboratory as a

Master’s student. I would like to express my appreciation to Dr. Salomon for being my thesis

advisor and a wonderful mentor. I would like to thank his support and insightful thoughts on my

Master’s research at Brown University. Additionaly, I sincerely thank my family for supporting

me for the study at Brown University and the research I have been done for the past years.

I wish to express my appreciation to all lab members and alumni from the Salomon’s lab

who made this thesis possible. I thank Xien Yu Chua, the PhD student in the Salomon lab, for his

guidance on my project and the collaborations on parts of the experiments for my thesis project.

Also, I would like to thank him for training me the lab techniques. I appreciate the support from

Alijah Griffith for my research and her collaborations on the experiments. Also, I would like to

thank her for proofreading my writings. I thank Theresa Mensah, a former lab technician, for

training me when I first join the group. I would also like to thank Nick Mroz, a former

undergraduate student in the Salomon lab, for preparing the CRISPR knocked out cell lines that

are used for this thesis project. I appreciate all the support for my research from the Salomon’s

lab.

I would like to thank Dr. Samuel G.Mackintosh, Dr. Ricky Edmondson, and Dr. Aaron

Storey from University of Arkansas for Medical Sciences (UAMS) for providing the MS

instrument and running the proteomics samples, as well as attempting to apply new data analysis

method on our samples.

I wish to thank Dr. Wayne Bowen and Dr. Nicolas Fawzi for serving as members on my

committee and providing support and advice on my research.

v

Table of Contents ACKNOWLEDGEMENTS ................................................................................................................... IV LIST OF ABBREVIATIONS .............................................................................................................. VIII

ABSTRACT ........................................................................................................................................ 9

CHAPTER 1: INTRODUCTION ........................................................................................................... 11

OVERVIEW OF THE IMMUNE SYSTEM .............................................................................. 11

T CELL RECEPTOR ACTIVATION AND SIGNALING PATHWAY……………………………………...11

NEGATIVE AND POSITIVE FEEDBACK PATHWAYS……………………………………………………….13

MASS SPECTROMETRY-BASED PHOSPHOPROTEOMICS………………………………………………..14

APPROACHES IN THE PROJECT…………………………………………………………………………………….16

CHAPTER 2: METHODS ................................................................................................................... 18

CELL CULTURE……………………………………………..……………………………………………………………..18

IMMUNOFLUORESCENCE STAINING AND CELL SORTING…………………………………………….18

ERK INHIBITOR TREATMENT……………………………………………………………………………………….19

T CELL STIMULATION AND CELL LYSIS………………………………………………………………………19

PROTEIN REDUCTION, ALKYLATION, AND DIGESTION………………………………………………19

PEPTIDE IMMUNOPRECIPITATION……………………………………………………………………………….20

AUTOMATED LIQUID CHROMATOGRAPHY-MASS SPECTROMETRY……………………….…..21

DATABASE SEARCH AND QUANTITATIVE ANALYSIS OF PHOSPHOPEPTIDE

ABUNDANCE ……………………………………………………………………………...……………………………….21

WESTERN BLOTTING……………………………………………………………...………..…………………………22

CHAPTER 3: RESULTS ..................................................................................................................... 24

PRELIMINARY CELL SELECTION AND STIMULATION VALIDATION……………………..………24

ERK INHIBITOR TREATMENT DEVELOPMENT AND INHIBITION VALIDATION……..………27

LABEL FREE PROTEOMICS QUALITY CONTROL……………………..……………………………..….…32

CHAPTER 4: DISCUSSION AND CONCLUSIONS ................................................................................ 37

REFERENCES ................................................................................................................................... 42

APPENDIX A ................................................................................................................................... 44

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Table of Figures

Figure 1.1 Overview of T cell receptor activation and Erk feedback pathway…………………………..13

Figure 1.2 General workflow of MS based proteomics…………………………………………………………....16

Figure 3.1 Western blot of the preliminary time-course stimulation…………………………..…………....25

Figure 3.2 Histograms of CD3 and CD4 expression in all cell lines………………………………………….27

Figure 3.3 Western blot of Erk inhibition titration test……………………………………………………………..28

Figure 3.4 Western blot of small scale versus large scale TCR expression after 2.5hr

incubation………………………………………………………………………………………………………………………………..29

Figure 3.5 Western blot of the inhibitor incubation method development experiment……………...31

Figure 3.6 Western blot of stimulation and Erk inhibition validation………………………………………..32

Figure 3.7 Volcano plot of the distribution of q values against log fold change and density plot of

the distribution of the ratio between stimulated and unstimulated samples……………………………….33

Figure 3.8 Density plots of the distribution of ratios between superbinder and antibody

enrichment condition……………………………………………………………………………………………………………….34

vii

Table of Tables

Table 3.1 Proteomics data of the pTyr enrichment method development………………………..………..36

viii

List of Abbreviations

APC: antigen presenting cell

CST: Cell Signaling Technology (Danvers, MA)

DMSO: Dimethyl Sulfoxide

DPBS: Dulbecco’s Phosphate Buffered Saline

Erk: extracellular signal-regulated kinase

FDR: false discovery rate

Fyn: proto-oncogene tyrosine-protein kinase Fyn

ITAM: immunoreceptor tyrosine-based activation motif

Itk: IL2-inducible T-cell kinase

LAT: linker for activation of T cells

Lck: lymphocyte-specific protein tyrosine kinase

LC-MS/MS: liquid chromatography coupled to tandem mass spectrometry

MHC: major histocompatibility complex

MS: mass spectrometry

SHP-1: SH2 domain-containing protein tyrosine phosphoatase 1

SLP-76: SH2 domain containing leukocyte protein of 76 kDa

TCR: T cell receptor

ZAP-70: zeta-associated protein kinase 70kDa

9

Abstract of Decoding the Cell Receptor Signaling Pathway via Phosphoproteomics Approaches:

Preparation for the Investigation of the Crosstalk Between Positive Regulator and Negative

Regulator, by Mengzhou Hu ScM, Brown University, MAY, 2021.

T cell receptor (TCR) activation, driven by the phosphorylation of tyrosine kinases, is

crucial in mounting proper adaptive immune responses. Although major kinases and phosphatases

that participate in the signaling transduction within TCR were identified and well-studied, their

underlying mechanisms remain mysterious. The delicate balance between the positive and

negative regulatory pathways is essential to fine-tuning TCR activation. TCPTP and PTPN22 are

two phosphatases known to attenuate the activation of the upstream kinase (Lck) activation on its

Y394 site, while a downstream kinase, Erk, upregulates the phosphorylation of Lck activation site,

and both mechanisms remain obscure. Therefore, this project aimed to study whether Erk

overcomes the inhibitory signal, aggregated by one of the phosphatases on Lck Y394, to positively

regulate the upstream TCR signaling via quantitative phosphoproteomics. In order to test this

hypothesis, TCR-stimulated TCPTP and PTPN22-deficient Jurkat T cells was compared to wild

type Jurkat T cells in the presence or absence of Erk inhibitor. This project mainly focused on

refining sample preparation for the major quantitative proteomics experiment. The preliminary

study selected the cell line clones that have similar TCR expression as the wild type and developed

optimal conditions for Erk inhibitor treatment. The Erk inhibition and TCR stimulation were

validated and determined to be reproducible by immunoblot analysis. The wide-range label free

quantitative proteomic analysis preparation was well-developed in this study and samples were

well-prepared for data analysis. The goal of the future proteomics analysis is to identify the

phosphatase that coordinates with Erk in providing balanced TCR activation signals. The

identification of the phosphatase that associates with Erk positive feedback loop may provide clues

10

to the mechanism of Erk feedback pathway and bring new insight to the balance between activation

and inhibitory networks within TCR signaling pathways.

11

Chapter 1: Introduction

Overview of the immune system

The human immune system plays a key role in protecting humans from foreign

substances that may be harmful to their health. The immune system consists of two critical

mechanisms of immunity, innate and adaptive. In response to pathogens, the innate immune

system passively induces nonspecific acute responses, while the adaptive immune system

distinguishes specific foreign antigens and mounts the response to destroy them. When the

immune system fails to differentiate foreign and self-substances and attacks its own molecules, it

leads to autoimmune disease such as Type 1 Diabetes, Rheumatoid Arthritis and

hypothyroidism[1]. There are two major effector cell types of the adaptive immunity which are T

lymphocytes (T cells) and B lymphocytes (B cells). B cells recognize antigens of the infectious

substances and generate antibodies to the pathogens as markers for destruction. T cells contribute

to the cell-mediated responses that kill infected cells and stop the pathogens when they detect the

foreign antigens. Due to the importance of eliminating pathogens, the proper function of T cells

is essential to maintaining the homeostasis of human immunity. As a result, our research aims to

specifically elucidate the intracellular structure of the T cell signaling networks, which will be

explained in later sections.

T cell receptor activation and signaling pathway

Antigen presenting cells (APC), such as B cells, present either exogenous or endogenous

peptides on the major histocompatibility complex (MHC), which are bound by T cell receptor

(TCR), leading to proper immune responses[2]. The interaction between TCR and antigenic

ligands triggers the TCR activation, resulting in T cell differentiation, proliferation and the

destruction of pathogens. The signal transduction in T cells is a highly dynamic and complex

interconnected network that has not been fully comprehended[3]. Overall, it is crucial to unravel

12

the TCR signaling network in order to bring new insight to the pathogenesis of human immune

disease and to improve various therapeutic strategies.

Phosphorylation is one of the important post translational modifications (PTMs) on

proteins that plays an essential role in modulating signal transduction, protein-protein interaction,

and various enzymatic activities [4]. The addition of a phosphate group to the polar residues of

the amino acid, such as tyrosine, threonine and serine, is catalyzed by protein kinases, while the

reverse reaction of dephosphorylation is performed by phosphatases. It is well known that TCR

activation is driven by a series of reversible tyrosine phosphorylation events which fine tune the

regulation of T-cell signaling (Figure 1.1). Consequently, most TCR signal transduction studies

focus on tyrosine phosphorylation (pTyr or pY), as tyrosines are known to be part of the

immunoreceptor tyrosine-based activation motif (ITAMs)[2-4].

While TCR signaling is complex and not fully understood, major components within the

TCR signaling network are known. The TCR associated cytoplasmic domains, CD3 and ζ chains,

first initiates the signal propagation. Following the initial stage of the signal transduction, the

tyrosine kinase, Lck, is activated. Phosphorylation of Lck activation sites then stimulates ZAP-

70, the zeta-chain associated protein of 70 kDa[5]. Subsequently, the scaffolding protein, LAT

(linker of activated T cells), and SLP-76 (SH2 domain containing leukocyte phosphoprotein of

76kDa) are phosphorylated and assembled into a complex inducing the downstream signaling

pathway, Ras-Raf-MEK-ERK[5-9].

13

Figure 1.1 Overview of T cell receptor activation and Erk feedback pathway (Helou et.al.,2013)

Negative and positive feedback pathways

The balance between the activating and inhibitory pathways is crucial in understanding

and regulating the TCR mechanism. Phosphatases that act on Lck Tyr394 site, one of the

activation sites, have been identified, TCPTP[10], SHP1[11], JKAP[12] and PTPN22[13], but

the mechanisms of their regulations on the Lck activation site remains unknown (Figure 1.1).

Previous research reported that a downstream kinase in the TCR signaling network, Erk,

promotes the T cell activation by positively regulating Lck Ser59 and blocking interaction

between phosphatases and Lck [14-17](Figure 1.1). Helou et al. performed a wide scale

quantitative analysis on TCR associated phosphorylation sites in wild type Jurkat T cells under

the Erk inhibition condition and confirmed that major phosphorylation of kinases upstream from

Erk (CD3 δ, ε, γ and ζ chain, Lck and ZAP-70) are downregulated significantly by the inhibition

of Erk activation [18]. Such findings suggest that Erk may be critical in the regulation of TCR

activation but the mechanism of Erk positive feedback loop on Lck remains obscure.

T cell receptor complexSLP76 complex

orTCPTPorPTPN22

?

?

14

The competition between activation and inhibitory pathways are crucial in fine-tuning the

sensitivity of the TCR in response to antigens[14, 15]. A common kinase complex, SLP-76,

regulates both negative and positive feedback pathways in response to TCR activation [19, 20].

In the early stage of the TCR stimulation, SLP-76 is thought to recruit a phosphatase to bind to

Lck for inactivation before Erk activation and participation in the positive feedback loop. The

specific phosphatase that participates at this stage remains unidentified[21]. However, it is also

known that at later timepoints during TCR stimulation that the downstream kinase, Erk, is

phosphorylated and able to compete with the inhibitory phosphatase, effectively acting as a

positive regulator in the TCR signaling pathway. Therefore, it is crucial to identify the

phosphatase that coordinates with Erk in balancing the TCR activation signals and determine the

rolw SLP-76 play in regulating both positive and negative feedback pathways.

Therefore, the major goal of this study is to determine which one of the phosphatases is

participating in the inhibitory function triggered by SLP76 and whether the Erk positive

feedback loop works in dissociation of that phosphatase. The immunoblot analysis followed by a

wide-scale quantitative proteomic analysis of specific T cells was used to achieve this goal.

Mass spectrometry-based phosphoproteomics

Proteomics is the study of large-scale identification and quantification of proteomes. As

mentioned previously, the regulation of TCR activation is dependent on the phosphorylation of

tyrosine kinases. Phosphorylation is the one of the natural biological processes associated with

proteins and the study of the phosphorylation sites on amino acids is designated to

phosphoproteomics. Since the activities of phosphorylation sites are fundamental units within the

large and intricate network of TCR signal transduction, the identification and quantification of

these sites will bring clues to the understanding of TCR signaling pathways.

15

Western blots are commonly used for quantitative analysis of a specific protein or the

phosphorylation site. However, the study of phosphorylation sites by immunoblots is limited by

antibody selection and the limited quantitative capacity of the technique. To compensate the

limitation of immunoblot analysis, mass spectrometry (MS) is used for a sensitive and broad-

scale proteomics research, which is beneficial for cell signaling analysis[22]. The TCR signaling

network is not a straightforward line but consists of multiple complex branches, and MS analysis

allows a high-resolution wide-range screening of phosphopeptides that helps to depict the large

picture of the phosphorylation activities within the TCR signaling pathways. The basic workflow

of MS proteomics studies is shown in Figure 1.2. Protein samples are extracted from cells and

then digested to break into peptides. After separation with li quid chromatography (LC), peptides

are converted into ions in gas phase with tandem mass spectrometry (MS) for the generation of

mass spectra, which are plots of ion signals based their mass to charge ratio (m/z). The data were

analyzed based on the spectra collected. The spectra will be assigned to corresponding peptide

sequences, including PTMs, for the identification of wide range proteins via database matching.

Furthermore, the relative quantitation of the protein abundance can be obtained based on the area

under the curve of each peak corresponding to a peptide and the relative abundance of peptides is

normalized by the peak area of synthesized standards that were spiked into each sample. The

label-free quantification approach was applied for this study that allows multiple cellular states

to be processed in separate MS runs and compared by their relative abundance of peptides.

Although the label-free strategy less accurate than other quantitative methods, it is cost-effective

and allows for comparison of a large number of cellular states[23, 24].

16

Figure 1.2 General workflow of MS based proteomics (Steen and Mann, 2004)

Approaches in the project

The aim of this project was to elucidate the connection between the positive regulator Erk

and the negative regulator phosphatases. We hypothesized that SLP-76 recruits one of the

phosphatases to negatively regulate Lck activation at early timepoints and, at a later stage, Erk

phosphorylation overcomes the inhibitory pathway and dissociates that phosphatase from Lck.

To accomplish this goal, we aimed to conduct a wide-scale proteomics analysis on phosphatase

knockout cell lines to determine how each phosphatase regulates Lck Tyr394 and under the

condition wherein Erk activation is inhibited, which may unravel the pathway that connects the

inhibitory and activation mechanisms.

Previous work in our laboratory applied the CRISPR/Cas9 to knockout SHP1, PTPN22,

and TCPTP genes from the wild type Jurkat T cells respectively. The preliminary experiment for

this project selected the cell lines for future exploration of the signaling pathway using

immunofluorescence staining, followed by the western blot analysis to validate the TCR

activation. The clones that are used for this proteomics study were selected based on their TCR

expression and their stimulation signals on the immunoblots. The efficacy of Erk inhibitor was

validated by a titration test on wild type control cell lines. A time-course experiment was

conducted to optimize the condition for Erk inhibitor treatment. Moreover, due to the low

accuracy nature of the label-free quantification, the method was optimized for a higher yield of

unique peptide identification on the MS. Phosphopeptides account an extremely small portion in

the total proteome, with phosphorylation of tyrosine accounting for a mere fraction of said

17

phosphopeptides (0.05% of total phosphorylation)[25]. Therefore, enrichment of pTyr is

necessary for the detection by mass spectrometry. Multiple conditions for the phosphorylated

tyrosine enrichment were tested using label free quantitation to determine the method that

provides highest identifications of peptides and phosphotyrosine sites, as well as the most sites

that are statistically significant in the abundance. The optimal method was implemented for the

large-scale proteomics analysis with wild type cell line (JE6), PTPN22 knockout cell line and

TCPTP knockout cell line under treatment of Erk inhibition and TCR stimulation. Here, we

present all the preliminary data and method development achieved which was utilized to launch

an ongoing wide-scale quantitative proteomics study focused on the investigation of the crosstalk

between phosphatases and Erk.

18

Chapter 2: Methods

Cell culture

The wild type Jurkat T cells (Clone E6-1) were obtained from American Tissue Culture

Collection (ATCC, Manassas, VA). SHP1 knockout cell lines, PTPN22 knockout cell lines and

TCPTP knockout cell lines were generated by CRISPR/Cas 9 targeted gene knockout

engineering[26] performed by a former lab member, Nick Mroz. The vector control line,

JE6.px458 cell lines were engineered by CRISPR/Cas 9 without gene knocked out. All the cell

lines were cultured in RPMI 1640 media with 2mM L-glutamine, 100 U/mL penicillin G and 100

ug/ml streptomycin (HyClone, Logan, UT), and 10% heat-inactivated fetal bovine serum (FBS)

(Sigma-Aldrich, st. Louis, MO) in a humidified incubator with 5% CO2 at 37 °C. Cells used in

this work were tested by the PCR mycoplasma Detection Kit from Applied Biological Materials

(ABMgood, Vancouver, Canada) according to the manufacture’s supporting protocol and

confirmed as mycoplasma-free.

Immunofluorescence staining and cell sorting

2×106 cells were collected for unstained control and stained samples that were incubated

with both mouse anti human CD3ε (clone: UCHT1) (BD, Franklin Lakes, NJ) coupled with PE

and mouse anti-human CD4 (clone: RPA-T4) conjugated with APC in dark for 30 minutes. Cells

were then washed and reconstituted in FACS buffer (DPBS with 2% heat inactivated FBS, 2mM

EDTA, pH 7.2) prior to the flow cytometry analysis. The flow cytometry analysis and cell

sorting were performed at the flow cytometry facility at Brown University with FACSArialIIu

(BD). FACS data are visualized with FlowJo V10.6.1 (BD). Cells were sorted based on the top

20% CD4 APC expression.

19

Erk inhibitor treatment

Cells were incubated in 20 µM U0126 (Cell Signaling Technology, Danvers, MA) for

2.5, 4, and 6 hours in a 37 °C water bath or in a 5% CO2, 37 °C humidified incubator for the

incubation condition development. Erk inhibition was confirmed by Western blots. In the large-

scale proteomics experiment, cells were treated in 20 µM U0126 for 2.5 hours[18] in the

humidified incubator with 5% CO2 at 37 °C before TCR stimulation. Control cells without Erk

inhibition treatment were incubated in 0.04% Dimethyl sulfoxide (DMSO) (Avantor, Radnor,

PA) for 2.5 hrs at 37 °C.

T cell stimulation and cell lysis

Prior to TCR stimulation, cells were washed with Dulbecco’s phosphate-buffered saline

(DPBS) and rested in 1×108 cells/ml in DPBS for 20 minutes at 37°C. Cells were stimulated for

5 minuetes using the anti-TCR antibody (C305), provided by the Weiss lab, which was added to

6 replicates at a final concentration of 1 µg/mL C305 to 1×108 cells/mL at 37°C. The stimulation

was halted by addition of lysis buffer (8M urea, 20 mM HEPES, 1mM sodium orthovanadate,

2.5mM Na pyrophosphate, 1mM ß-glycerophosphate, pH 8.0) at 4°C for 20 minutes. The lysis

buffer was also added to control samples without the addition of C305. All lysates were

sonicated at 30W output for 2 rounds of 30 seconds and centrifuged at 20,000×g for 5 minutes at

20°C

Protein Reduction, Alkylation, and Digestion

Protein concentration of the cell lysates was measured by Pierce BCA Protein Assay

(Thermo Fisher Scientific, Waltham, MA). After the protein concentration was determined, the

portion of lysates containing 5mg proteins was collected from each replicate respectively.

Lysates were then diluted 4-fold with 20mM HEPES buffer (pH 8.0), reduced with 10mM DTT

20

for 30 minutes at 37°C , and alkylated by 100mM iodoacetamide for 30 minutes in the dark at

room temperature. Trypsin (Promega, Madison, WI) was added to lysate (20µg:1mg

Trypsin:Protein ratio) for an overnight digestion at 37°C. Digested peptides were then acidified

to 0.1% trifluoroacetic acid (TFA) and desalted using Sep-Pak C18 Plus Cartridge (Waters,

Milford, MA) as previously described[21]. 10 pmol of a quantitation standard, synthetic

phosphopeptide LIEDAEpYTAK, was then spiked into each sample eluents and lyophilized for

48 hours.

Peptide Immunoprecipitation

The peptide immunoprecipitation was performed using the SH2 superbinder beads (made

following a previously described protocol[27]) and p-Tyr-1000 phosphotyrosine antibody beads

(Cell Signalling Technology, Danvers, MA). Dry samples were reconstituted in IAP buffer (10

mM sodium phosphate, 50mM sodium chloride, 50mM MOPS, pH7.2) and p-Tyr-1000

immunopreciptation process was performed as described previously[28]. The SH2 superbinder

beads were washed with IAP buffer 3 times at 4°C before introducing the peptide samples. Then

the bead-peptide slurries were incubated on a 4-rpm rotator for 2 hours at 4°C. Beads were then

washed either: 3 times with IAP buffer and one time with Milli-Q water; washed 4 times with

IAP buffer followed by one MQ water wash; or 2 IAP buffer washes with 3 HPLC water washes.

All the water and buffers mentioned in the washes are pre-chilled at 4˚C. Between each wash

samples were either inverted 5 times, mixed with a pipette, or vortexed. Peptides were then

eluted by the addition of 0.15% TFA on a 1150 rpm mixer at room temperature for 10 minutes or

gently tapping the tube for 10 minutes. Eluates were then desalted using 100 µl C18 Zip Tip

(Thermo Scientific Pierce, Waltham, MA) according to manufacturer’s instructions. 100 fmol of

21

human phospho-angiotensin II peptides are added to each eluate as the second internal standard

prior to the LC-MS/MS analysis.

Automated Liquid Chromatography-Mass Spectrometry

A fully automated phospho-proteomic technology platform was used to perform mass

spectrometry analysis as described[29-31]. Tryptic peptides were separated on a 25cm reversed

phase analytical column (75µm inner diameter) packed with CSH C18 2.5µm resin (Waters)

using an Agilent 1200 Series Quaternary HPLC system (Agilent Technologies, Santa Clara, CA)

and were analyzed by a Q Exactive mass spectrometer (Thermo Fisher Scientific). Peptides were

eluted with a total of 120 minutes gradient consisting of a 95 minutes gradient from 5 to 30%

0.1M acetic acid in acetonitrile and a 5 minutes gradient from 30 to 95% % 0.1M acetic acid in

acetonitrile. The mass spectrometer acquired a full MS scan range from 400 to 1800 m/z for

precursor ions with change state from 2-5 with a resolution of 70,000, a maximum injection

time(IT) of 200 ms, and an automatic gain control(AGC) value of 300,000 ions. Top 9 precursor

ions were then fragmented in the data dependent mode via high-energy collision dissociation (28

NCE) within a 2.5 m/z mass isolation window, with a 30s dynamic exclusion time and an

intensity threshold of 1,000. The MS/MS scan were then collected with a range of 200-2000 m/z,

at a resolution of 17,500, AGC of 20,000, and maximum IT of 200 ms.

Database Search and quantitative analysis of phosphopeptide abundance

The MS/MS spectra were searched by Mascot (Matrix Science, London, UK) and

matched against a human-specific UNIPROT non-redundant “complete proteome set” protein

dataset(homo sapiens)[32], which contains 75,777 protein sequences. The search parameters

were as follows: tyrosine enzyme specificity, 7 ppm mass tolerance for precursor ions, 20 mmu

mass tolerance for fragment ions, a maximum of 2 possible missed cleavages, and modifications

22

of oxidation on methionine and phosphorylation of serine, threonine and tyrosine as well as fixed

modifications of carbamidomethyl on cysteine. False discovery rate (FDR) was estimated using

the reversed decoy sequences from the database and was set to 1% for the search. An Ascore

algorithm[33] was applied to all data to validate the position of phosphorylation sites.

Label-free quantitative analysis of relative phosphopeptide abundance was calculated by

the selected ion chromatogram(SIC) peak areas with our in-house software [29, 30] and the

parameters are described previously[28]. SIC peak areas for phosphopeptides that were acquired

from the MS/MS were normalized to the peak area of standard peptide LIEDApYTAK. p values

were calculated for at least 3 replicates if applicable. The q-value was determinated from the in-

house software as described previously[28]. The comparison of phosphopeptide in different

conditions were measured and the natural log of the ratio of the fold change were generated in

the software as well. Other data analysis and graphic visualization were performed in R.

Western Blotting

Cell lysates were diluted in the sample loading buffer (2% w/v SDS, 62.5 mM TRIS-HCl,

10% v/v glycerol, 2.5% v/v 2-mercaptoethanol and 0.0005% w/v bromophenol blue) with equal

volume. Equal amounts of protein were loaded on 4-20% ClearPAGE SDS-PAGE gel

(Expedeon) and separated by the gel electrophoresis. Proteins were then transferred to

Immobilon-FL polyvinylidene fluoride membranes (EMD Millipore, Billerica, MA). Membranes

were then be blocked with Odyssey Blocking Buffer (Li-Cor, Lincoln, NE) for an hour at room

temperature followed by the addition of primary antibody and incubated for an hour at room

temperature or overnight at 4°C. The primary antibodies was then washed for 4 times by PBS

with 0.1% Tween-20 for 5 minutes each wash. Membranes were then incubated with IRDyes-

conjugated anti-mouse IgG, and anti-rabbit IgG antibodies (Li-Cor) for an hour followed by 4

23

washes with 0.1% Tween-20 in PBS and 2 washes with PBS. Blots were then visualized and

analyzed by the Odyssey CLx Imaging System and ImageStudio (Li-Cor). Primary antibodies,

mouse anti-p44/42 MAPK (Erk 1/2, 3A7), and rabbit anti-phospho-p44/42 MAPK (Erk1/2,

Thr202/Tyr204) obtained from Cell Signaling Technology. Total Protein Stain Kits were used

for scanning the total proteins in samples following the manufacturer’s protocol.

24

Chapter 3: Results

Preliminary cell selection and stimulation validation

Three of the four phosphatases that target Lck Tyr394 site were knocked out in the Jurkat

T cells by previous work in the lab, generating three respective cell lines (J.PTPN22-, J.SHP1-,

J.TCPTP-), Jurkat T cell E6 clone (JE6) was used for the wild type control in our lab. A vector

control cell line, JE6.px458, was also generated by CRISPR knock out process but retained the

physiology of the wild type. Although the cell lines were knocked out previously, the evaluations

on these cell lines have not been done before. The knockout efficiency and the conservation of

stimulation signals was validated by Western blot in this study (Figure 3.1). The initial time

course TCR stimulation was performed on each of the cell lines for 0, 1, 5, 10 minutes anti-TCR

(C305) stimulation. Blots in Figure 3.1C confirmed that the corresponding phosphatase was

knocked out in each cell line, and no phosphatases are knocked out in the vector control;

However, a weak signal of SHP1 was still presented in SHP1 KO cell line which may be a

concern in the later study of the signaling pathway, as the SHP1 residual may still participate in

the inhibitory pathway. Phosphorylated Erk (pErk) is commonly used in the validation of TCR

stimulation. From both the total phosphorylated tyrosine blot and the pErk blot (Figure 3.1 A, B),

TCR in all cell lines were able to activate, and 5-min C305 stimulation promotes the strongest

stimulation signals across all of the presented cell line. As a result, the optimal stimulation time

point was confirmed to be 5 minutes.

Lck is a member in the Src family and the pSrc blot shows all the phosphorylation within

the Src family. The Lck/pSrc blots (Figure 3.1 B) was shown to confirm that the Lck and Src

family are well conserved in the engineered cell lines exhibit proper function. The signals for

pSrc were not elevated as strong as pErk in response to TCR stimulation because there are some

inhibitory sites presented in the Src family that may not be phosphorylated and compensate the

25

phosphorylation of active sites. Our hypothesis for the TCR stimulation in phosphatase deficient

cells is that the stimulation should be enhanced as the phosphatases were removed and the

inhibitory pathway was blocked. However, in blots showed on Figure 3.1B, the phosphatase KO

cell lines gives weaker pErk signals than the vector control, implying that the removal of

phosphatase may not necessarily intensify the TCR stimulation. As the western blot does not

provide a broad screen of all the phosphorylation sites corresponding to TCR signaling

transduction, it may not suggest the participation of other pathways that compensate for the loss

of phosphatases. Moreover, differences in the number of TCR expressions may presumably lead

to different extent of stimulation. Since all these cell lines presented have been gene edited, we

hypothesize that some cell lines may lose TCR in the engineering process that may weaken the

stimulation.

Figure 3.1 Western blot of the preliminary time-course stimulation

TCR expressions of all clones were then screened using immunofluorescence stains

against CD3 ε, one of the components on TCR complex, and CD4, part of TCR co-receptor. The

staggered histograms in Figure 3.2 illustrate the distribution of CD3 ε and CD4 respectively. Cell

JE6.px458 J.PTPN22- J.SHP1- J. TCPTP-0 5 101 0 5 101 0 5 101 0 5 101 min(s) C305 stimulation0 5 101 0 5 101 0 5 101 0 5 101 min(s) C305 stimulation0 5 101 0 5 101 0 5 101 0 5 101 min(s) C305 stimulation0 5 101 0 5 101 0 5 101 0 5 101 min(s) C305 stimulation

Total pTyr

Total Protein

JE6.px458 J.PTPN22- J.SHP1- J. TCPTP-0 5 101 0 5 101 0 5 101 0 5 101 min(s) C305 stimulation

Erk

pErk

3850

70

50

90

Lck

pSrc Family

GAPDH

AB

JE6.px458 J.PTPN22- J.SHP1-0 5 101 0 5 101 0 5 101 0 5 101 min(s) C305 stimulation

GAPDH

PTPN22

SHP1

TCPTP

GAPDH

125

70

50

J. TCPTP-C

26

lines used for the western blot in Figure 3.1 were JE6.px458 #2 clone, J.TCPTP- #1 clone,

J.SHP1 #2 clone, and J.PTPN22- #2 clone. The JE6.px458 #2 has higher CD3 ε expression than

other cell lines and the JE6 wild type control, and has relatively higher CD4. Therefore, this cell

line will have stronger signals after stimulation as expected. Other cell lines, such as J.SHP1 #1

and #2, have both low CD3 and CD4 expression suggesting that they may have fewer TCR and

the comparison between these cells with other cell lines may not be fair. As a result, cell lines

that are suitable for the proteomics study were selected based on the TCR expression pattern. In

order to reduce the biological variability, the cell selection was based on the similarity of TCR

expression, CD3 and CD4 distributions, between cell lines and the reference control, JE6.

Finally, the JE6.px458 #1, J.TCPTP- #1, J.PTPN22- #1 along with JE6 wild type control were

selected for the future proteomic study. The SHP1 knock outs were excluded as their TCR

expressions are weak which may introduce noises in the future proteomics analysis, and the

residual SHP1 signals shown in the western blot may be distracting as well. However, the

exclusion does not mean that this phosphatase is worthless in understanding the connection

between positive and negative pathways, but better and robust clones of such phosphatase

knockout cell line are required for the future exploration. The stimulation of the selected cell

lines was validated in Figure 3.6 and was explained in detail later in this chapter.

27

Figure 3.2 Histograms of CD3 and CD4 expression in all cell lines

Erk inhibitor treatment development and inhibition validation

Erk inhibition experiments on the western blot provide an overview of how phosphatase

KO cells respond to Erk inhibition. According to Helou’s article[18], they had already performed

a titration test for the ERK inhibitor (U0126) incubation with 10µM, and 20 µM U0126 and a

time-course incubation with 2 and 2.5hrs at 37˚C. The condition of 20 µM U0126 for 2.5hrs at

37˚C deactivated Erk phosphorylation the most efficiently when the TCR was stimulated by the

OKT3 and OKT4 antibodies. In this study, Erk inhibition was tested on a small scale of JE6 cells

(5×106 per replicate) for reproducibility. The titration test of 0, 20, 35, and 50 µM U0126 was

applied for the inhibition validation on the vector control (Je6.px458, 5×106 per replicate). Both

cell lines were treated with U0126 for 2.5 hours at 37˚C before the TCR stimulation with either

OKT3/4 or C305 antibodies. The Western blot (Figure 3.3) confirms that 20 µM inhibitor was

sufficient to deactivate Erk phosphorylation. Although higher concentration of inhibitor may lead

to a greater suppression of pErk expressio, the potential off-label target may also exist with

higher concentration and may lead to noise in the future large-scale experiment. Moreover, the

U0126 was constituted in DMSO which have been shown to be harmful for live cells with at a

JE6 control *

Negative control

J.TCPTP- #2

J.PTPN22- #2

JE6.px458 #1JE6.px458 #2JE6.px458 #3JE6.px458 #4JE6.px458 #5

J.TCPTP- #1

J.SHIP1- #2J.SHP1- #1

J.PTPN22- #1J.SHP1- #3

J.LCK- #2J.LCK- #1

CD3ε expression CD4 expression

28

higher concentration[34]. As a result, the optimal concentration of U0126 should be high enough

to inhibit Erk activation but low enough to maintain cell’s viability.

Figure 3.3 Western blot of Erk inhibition titration test

The 20 µM U0126 with 2.5hrs incubation were then applied to a larger scaled cell

stimulation (1×108 per replicate) for further Erk inhibition validation. The first iteration of Erk

inhibition in large scale samples leads to null signals in pErk blot under the condition in absence

of U0126 and presence of low concentration of DMSO (Supplement Figure 1), suggesting the

2.5 hours incubation may not be the optimal condition for normal cell physiology. The

differences between the small-scale and large-scale are not only the number of cells but also the

type of lysis buffer. In order to confirm that the failure of TCR stimulation is not cause by the

lysis buffer and to determine the cause of cell inactivity, the follow-up experiment compiled the

small-scale and large-scale samples with equal concentration of DMSO for a 2.5-hr, 37˚C

incubation and lysed with two types of lysis buffer. The WB lysis buffer (also called sample

loading buffer), consisting SDS, is commonly used for small scale western blot cell lysis and the

urea lysis buffer was made from 8M urea that lyse cells for the preparation of large-scale

proteomics studies. In contrast with the result in Figure 3.3, the new small-scale experiment

leads to no or weak pErk signal (Figure 3.4), which implies that the incubation condition may not

be reproducible. Pervanadate is a nonspecific phosphatase inhibitor and was used for positive

controls for TCR stimulation in the experiment. The stimulation signal under PV treatment

29

suggests that the weak signal is not due to the western blot process. As the western blot in Figure

3.4 suggests, the 2.5-hr incubation may lead to unexpected cell death or inactivity that impairs

the TCR stimulation, and the condition for the incubation needs to be optimized. Nevertheless, at

the large-scale stimulation under the same condition, JE6 may be more tolerant to the incubation

condition than JE6.px458. Additionally, JE6.px458 shows reduction in TCR expression (87.4%

versus 96.5% in JE6) (Supplement Figure 2) at later passages. As a result, JE6 were selected for

future proteomics study as a control.

Figure 3.4 Western blot of small scale versus large scale TCR expression after 2.5hr incubation

The experiment shown in Figure 3.4 incubated cells in 1×108/ml (1e8/mL) density in

37˚C water bath in sealed tubes. The assumption is that cells may be stressed in a high-density

condition without air exchanges for a long time which may cause cell death and inactivity even

without the Erk inhibition. Moreover, the previous experiment incubated cells in DPBS instead

of in non-serum medium for 2.5-hr suggesting that cells may die due to malnutrition. In order to

optimize the incubation condition for large-scale samples, a time-course experiment was done to

evaluate the conditions that may lead to the failure in the previous experiment. The time points

for incubation were 20 mins, which is the standard cell resting time, 2.5-hr, which is the standard

Erk inhibition time, 4-hr and 6-hr in order to examine whether cells can tolerate the extreme

30

conditions for a long time. The old condition was tested which is incubating at 37˚C in DPBS

(with the same amount of DMSO as in 20µM U0126) where cells are in sealed tubes with

1e8/mL. The second condition cell incubation under 1e6/mL in the humidified, 37˚C, 5% CO2

incubator in non-serum RPMI (with DMSO), as well as the same condition but cell concentrated

to 1e8/mL. Cells in DPBS are then stimulated with C305 anti-TCR antibody for 5 mins. Cells in

RPMI were centrifuged and reconstituted in DPBS at 1e6/mL after the preincubation. Prior to the

5-minute C305 stimulation, these cells were rested for 20 minutes at 37˚C. According to Figure

3.5, preincubating cells at 37˚C in DPBS and water bath reduces the TCR stimulation signals

(both pTyr and pErk blot) at 2.5-hr. Cells are too dense and in absence of gas exchanges in a

sealed tube. Therefore, the cell condition may vary between experiments which leads to different

results from different experiment days. There is no stimulation at any incubation timepoint

beyond 2.5-hr under that condition, since cells may not survive at such a stressful condition for

too long. At the high concentration, even the cells are in the 37˚C, 5% CO2 incubator with

nutrients from the media, the stimulation is weak as well. However, the 1e6/mL condition

satisfied cells and allows strong TCR stimulation regardless of the incubation time. Base on the

result from this time course experiment, gas exchange and cell culture media improve the TCR’s

response to stimulation at 2.5-hr incubation. Additionally, the lower density provides cells a

more comfortable environment to be able to respond to the stimulation and stay alive. Therefore,

the 2.5-hr incubation for the proteomics study will be done in non-serum RPMI in absence of

U0126 but with same concentration of DMSO, and in the incubator at 1e6/mL cell density.

31

Figure 3.5 Western blot of the inhibitor incubation method development experiment

Cells for the proteomics study were treated in 20µM U0126 or 0.04% DMSO in non-

serum RPMI, at 1×106 /mL, inside of a 37˚C, 5% CO2 incubator. After the 2.5-hr incubation, the

1×108 cells were transferred to DPBS with either 20µM U0126 or 0.04% DMSO for the 20 min

resting at 37˚C and followed by a 5 minutes C305 stimulation or directly lysed by the urea lysis

buffer. Control cells are able to tolerant the optimized preincubation condition and the TCR

stimulation was validated (Figure 3.6, DMSO control). Under the treatment of U0126, sufficient

Erk inhibition was confirmed under stimulation condition. With three replicates showing in

Figure 3.6, the result is reliable and reproducible. As a result, cells that prepared for the future

proteomics study are well stimulated under control and the phosphorylation of Erk is muted in

the presence of Erk inhibitor.

Total pTyr

32

Figure 3.6 Western blot of stimulation and Erk inhibition validation

Label free proteomics quality control

As the stimulation was validated by the immunoblot analysis, three replicates of each

unstimulated JE6 and stimulated JE6 without inhibitor treatment were prepared for the label free

proteomics study for the quantification of stimulation. As shown in the density plot on the right-

hand side of Figure 3.7, most of the phosphorylation site under KEGG TCR signaling pathways

are upregulated in the stimulation conditions, which validates the stimulation process during

sample preparation. The red dashed vertical line represents 0 on a log2 scale meaning that the

raw ratio is 1, and the peak in the right side of the red line indicates the ratio of stim/unstim is

greater than 1. Moreover, over 57% of the sites (red dots on the left plot in Figure 3.7) are

significantly upregulated by the stimulation suggesting that the TCR activation successfully

phosphorylate the signaling pathways.

50

Erk

pErk

38

R1 R2 R3

Unstim

R1 R2 R3 R1 R2 R3 R1 R2 R3

UnstimC305 C305

DMSO control U0126

Erk38

R1 R2 R3

Unstim

R1 R2 R3 R1 R2 R3 R1 R2 R3

UnstimC305 C305

Uns

tim JE

6 co

ntro

l

JE6

C305

con

trol

DMSO control U0126

Cell line: J.TCPTP-

50 pErk

Uns

tim JE

6 co

ntro

l

JE6

C305

con

trol

Cell line: J.PTPN22-

50Erk

pErk38

R1 R2 R3

Unstim

R1 R2 R3 R1 R2 R3 R1 R2 R3

UnstimC305 C305

DMSO control U0126

Uns

tim JE

6 co

ntro

l

JE6

C305

con

trol

Cell line: JE6

33

Figure 3.7 Volcano plot of the distribution of q values against log fold change and density plot of the distribution of the ratio

between stimulated and unstimulated samples

However, in the stimulation validation experiment, there are 295 total unique

phosphotyrosine sites identified in all samples and 53 of them are under the KEGG T cell

signalling pathways. Our previous proteomics studies were able to identify at least double the

sites[28, 35]. Therefore, the yield of pTyr sites may be problematic for continuing the

quantitative analysis.

The modification of the pTyr enrichment process in the label free proteomics workflow

can potentially be the breakthrough for addressing the yield issue. The standard protocol for the

enrichment is using SH2 superbinder (sSH2) for the immunoprecipitation, while pTyr-1000 (ab)

is an antibody that is also commonly used in the immunoprecipitation process to enrich pTyr

yield. As a result, the method of using sSH2 following standard lab protocol and using pTyr-

1000 following the CST manual were compared. The density plots in Figure 3.8 illustrate the

distributions the ratio of 3 replicates of superbinder enrichment condition against 3 replicates of

antibody enrichment condition (SH2/ab) as well as the ratio of stimulated versus unstimulated

samples. There are a RPMI condition since the optimized cell preparation requires an incubation

in RPMI, and there may be some RPMI residue in samples. Therefore, the RPMI condition was

included in the method development to ensure that it would not interfere with the TCR

34

stimulation and would not damage the MS instrument. The red dashed line indicates 0 on a log

scale as well as 1 in the raw ratio. The peaks are all on the right side of the red line implying that

superbinder may perform better in quantifying KEGG TCR sites than the pTyr-1000 antibody

enrichment (Figure 3.8). As a result, superbinder beads were kept for further method

development of the enrichment step.

Figure 3.8 Density plots of the distribution of ratios between superbinder and antibody enrichment condition

The superbinder based pTyr enrichment method development was then performed to

evaluate the optimal condition for higher pY yield. For the immunoprecipitation process, 8

conditions were tested. The control samples used the original process that Salomon lab used[36],

which included IAP buffer washes of the beads, sample and beads incubation, IAP buffer wash

of the sample-beads slurry followed by one water wash, and then elution of the beads for eluates.

One hypothesis is that increasing the contact between buffer and beads may assist the wash of

unwanted peptides. Using pipette tip to pipette up and down (Pipette up/down) and vortex tubes

between washes are the two approaches to improve the washing process by increasing contact

frequencies. However, the potential drawback for the two methods is that vigorous interference

of beads may weaken the chemical properties. The assumption pays strong attention on the

washing step and refereeing the pTyr-1000 manufacturer’s protocol, it is recommended to use 2

35

times of IAP buffer wash followed by three water washes (2IAP+3water). Therefore, it was one

of the approaches that was tested in this experiment. In addition, as the 2IAP +3 water condition

requires 5 washes, a new test condition of four IAP wash with one water wash (4IAP + 1water)

was added to the examination to match the number of washes. Later in the process, after the

elution, samples were mixed at a relatively high speed in the original protocol. The vigorous

mixing was replaced by gentle tap with palms for the same amount of time in the 7th condition.

Moreover, the superbinder enrichment should be performed at 4˚C, but a new condition of

performing at room temperature was examined as well. As Table 3.1 showed, there is no

dramatic increase of total phosphotyrosine site from the control to modified conditions. The top

2 highest pY yield were the 4IAP+1water and 2IAP+3water conditions, and they had low total

unique peptide identification suggesting that the enrichment conditions were more specific in

selecting phosphotyrosines and able to exclude other peptides. Although 4 IAP washing is

leading in the 8 conditions, the experiment did not have replicates to validate the reproducibility.

On the other hand, 3 water wash was proven in the antibody immunoprecipitation protocol.

Therefore, the 2IAP+3water wash was selected as the optimized enrichment process. Even

though the 3 water wash was the optimized protocol, the pY yield was not expected to have a

spike from the previous control condition as the improvement was small in this developed

method (Table 3.1). As for now, samples are prepared with the optimized methods explained

above for the label-free quantitative analysis. The final proteomics data are not available at the

time this thesis is written. Therefore, the results of the quantitative analysis for the TCR

signaling pathway between positive and negative regulator will not be discussed in this thesis

report.

36

Sample

FDR 1% unique

peptide number Total pY

RoomTemp 5003 86 Gentle tap 3008 169

4IAP + 1water wash 2581 237 2IAP + 3water wash 2693 218

Vortex 3033 209 Pipette up/down 2552 199

Control 4211 173 Table 3.1 Proteomics data of the pTyr enrichment method development

37

Chapter 4: Discussion and Conclusions

T cells play critical roles in human adaptive immune system mounting immune responses

for the recognition of foreign and self-ligands. The T cell receptor activation, in response to the

binding of antigens, was driven by series of tyrosine kinase phosphorylation. Understanding and

regulating the kinases and phosphatases activities are crucial to maintain the normal physiology

of the adaptive immune system. Although major kinases with in the TCR signaling network were

profiled, there are some underlying mechanisms within the pathway that remains unexplored.

Lck as one of the kinases that triggers the initiation of singling propagation requires refined

regulation in order to fine-tune the immune responses from TCRs. Previous research unraveled

that there are four phosphatases, SHIP1[11], PTPN22[13], JKAP[12], and TCPTP[10], that

negatively regulate Lck on the Tyr394 site. The downstream kinase, Erk, was previously found to

participate in the positive feedback to Lck [14-18], suggesting that the activation of Erk elevates

the upstream kinases, but the mechanism remains obscure. The balance between the positive

regulator and the negative regulator is crucial in tuning the TCR activation, while the underlying

network between Erk and Lck related phosphatases has not yet been studied. Moreover, there are

data suggesting that the kinase complex, SLP-76, was able to recruit the phosphatase to attenuate

Lck activation at early timepoints when Erk has not been phosphorylated yet [21]. However, as

the TCR activation progresses, Erk will then be phosphorylated at later timepoints suggesting a

potential competition between Erk and the phosphatase that deactivate Lck Tyr394. Therefore, the

goal of this study was to understand the coordination between the negative feedback network and

the positive feedback loop. We hypothesized that, at later time points, Erk was able to overcome

the phosphatase that was recruited by SLP-76 and promote the positive activation on Lck. In

order to test the hypothesis, the phosphatase deficient Jurkat cells will be compared with TCR

38

stimulated wild type JE6 (by C305 antibody) respectively in the presence or absence of Erk

inhibition condition.

In order to proceed the comparison, the knockout cell lines were selected based on their

TCR stimulation responses and TCR expression distribution. Appreciating the work from former

lab members, there are three types of phosphatase deficient cell lines (TCPTP-, PTPN22- and

SHP1-). The anti-TCR stimulation by C305 was performed on each of the cell lines, and weak

stimulation signals were shown compared to the control cell lines. The immunofluorescent

staining was used to visualize the TCR expression, mainly the expression of CD3 and CD4.

Based on the distribution pattern, four cell lines, JE6, JE6.px458, J.PTPN22-, J.TCPTP-, were

selected for further proteomics study, while JE6.px458 failed to maintain the TCR expression at

later passages and was abandoned from the study. SHP1 knock out cell lines were not selected as

they have relatively lower TCR expression and there are weak signals indicating SHP1 residuals

in the clone. The residuals are concerning since they may still be able to participate in the

inhibitory pathway and be misleading in the future result. This phosphatase is still interesting for

further research if a better clone is generated in the future, but for quality control, SHP1 deficient

cell lines are excluded from this study.

The Erk inhibition condition was reproduced according to Helou’s study[18]. However,

the incubation condition was not explicitly explained in that paper and leads to the failure in the

stimulation of TCR without Erk inhibitor in large-scale cell samples. The time-course plus

condition modification experiment was conducted to pinpoint the issue leading to cell inactive or

death. The source of the unexpected cell death was identified to be lack of gas exchange and lack

of nutrients during the 2.5-hour incubation. In addition, cells were too dense to survive or to stay

satisfied during the incubation. As a result, the incubation condition was optimized to be in non-

39

serum medium, in the 37˚C, 5%CO2 incubator at 1×106 cells/mL. With the optimized incubation

condition, the stimulation signal in absence of Erk inhibitor is strong and reproducible and the

stimulation was reproducibly and well restrained under the Erk inhibition condition in all cell

lines picked for the proteomics study.

The immunoblot analysis allows the detection of single, site-specific phosphorylation,

which is strongly dependent on the specific antibodies that are available. However, the TCR

signaling pathways contain complex phosphorylation networks and using the site-specific

western blots may limited the understanding of the boarder picture. As a result, our lab applies

mass spectrometry-based proteomics for a wide screening of peptides and for accurate

quantifications. The quantification of TCR stimulation under the optimized incubation condition

was then validated. However, the unique phosphotyrosine sites that are identified are far below

the number identified with previous methods. The pTyr immunoprecipitation method was then

developed by using an alternative antibody, pTyr-1000, was compared with the SH2 superbinder

beads. However, the pTyr-1000 did not significantly increase the phosphotyrosine yield. Later,

multiple modifications of the method for SH2 superbinder immunoprecipitation were compared

with the original protocol. The addition of one wash of the beads-sample slurry generates the

highest pTyr yield among all conditions, but the improvement is not predominant. The 2 IAP

buffer wash followed by 3 water wash was eventually chosen for the proteomics study to

potentially improve the specificity of binding to pTyr. The cause of the low pTyr yield may be

due to the sensitivity of the MS instrument in our lab and may be due to the nature of the cell

property that may be difficult to control of. As a result, the proteomics samples with 6 replicates

under each condition were prepared according to the optimized incubation method and the

immunoprecipitation method as mentioned above. These sample were processed in the high-

40

resolution mass spectrometer at University of Arkansas for Medical Sciences for wide range

peptide screening and quantitative analysis. A new data acquisition, data independent acquisition

(DIA), will potentially be applied to these samples for the comparison with data dependent

acquisition (DDA) for a higher pTyr yield. Currently, more control samples have been prepared

for creating the DIA library of Jurkat T cells.

The expectation of this set of proteomics research is the identification of regulatory

phosphorylation sites that is able to explain the connection between a positive regulatory

pathway and negative regulatory pathway. In the phosphatase knockout sample in absence of Erk

inhibitor, we expect the elevation of Lck Y394 phosphorylation from the quantitative proteomics.

The reduction of the phosphorylation of CD3 chains Lck Y394, Zap70, Itk, and PLC γ1 should be

validated in the Erk inhibitor treated JE6 wild type samples as well. If Erk positively regulate

Lck via the specific phosphatase, that phosphatase knock out cell line in combination of Erk

inhibition will leads to no significant changes comparing with wild type cell lines that was

treated with Erk inhibitor alone. Otherwise, if the TCR signaling was downregulated further than

Erk inhibitor alone, the data may suggest that Erk may be working on other negative regulators

than the phosphatases that this study selected. In such case, further study of the competition

between negative regulators and Erk will be conducted. Additionally, as we assume that SLP-76

may play a crucial role in balancing the two opposite functioning pathways, the next step would

be studying the Erk inhibition response in SLP-76 mutant cells. Once the phosphatase that is

predominantly involved in the regulation of Erk positive feedback, the SLP-76 mutant cells with

such phosphatase knocked out will be made for the study of SLP-76’s role in tuning the balance

between positive and negative feedback loops. Moreover, if the coordination between the

positive and negative regulators is explained, the same wide-scale proteomic study will be

41

applied on primary T cells from mouse as a better biological model to reflect physiology similar

to that of humans.

42

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Appendix A

Supplement Figure 1 Western blot of the TCR stimulation failure in JE6.px458

Supplement Figure 2 Distribution of CD3 expression in JE6 and JE6.px458 later passages

Perc. of expressionJE6.px458_CD3JE6_CD3JE6.px458 negativeJE6 negative