Timothy An, Jessica Lisle, Adrianna Pleigo Zamora, Chris ... · real-time PCR. The PCR media...

Macquarie Matrix: Special edition, ACUR 2017

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Abnormal genetic changes in hematopoietic stem cells of pre-leukemic mice

Timothy An, Jessica Lisle, Adrianna Pleigo Zamora, Chris Slape

The University of Queensland

Abstract

Blood malignancies, such as leukaemia, are often a result of accumulated mutations to the

hematopoietic stem cells in the bone marrow. Inappropriate bone marrow niche, driven by all cell

types in the bone marrow, can cause the selective advantage for the disease driven stem cells than

healthy stem cells. Therefore, it is important to identify the genes and proteins in the pre-leukemic

stem cells that maintains and worsens this leukemic state before the condition exacerbates. mRNA

expression of selected genes was analysed by real-time PCR in different populations of

hematopoietic stem cells in both pre-leukemic and wild-type mice. Clec4e, TJP3 and Pcdh7 genes

had notable increased expression in the pre-leukemic stem cells and Pcdh17 gene appeared to be

abundantly expressed in the diseased state and not expressed at all in the healthy state. In addition,

Ryk gene had a decreased expression in the diseased state, which indicates its potential role in

regulating healthy bone marrow niche. These examined changes are mostly consistent with the

array data and warrants further testings, including pharmacological interventions and knockout

studies.

Keywords: myelodysplastic syndrome, leukemic stem cells, bone marrow niche

Abnormal genetic changes in hematopoietic stem cells of pre-leukemic mice T An et al.

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1. Introduction

Hematopoietic stem cells (HSC) are a rare, heterogeneous population of cells in the bone

marrow that are capable of lifelong haematopoiesis. The proliferative and differentiation

properties of HSCs are closely regulated by the bone marrow niche. The niche is a complex

ecological system with specialised cells that regulate HSC activities by intercellular cytokines

(Schepers, Cambell & Passegue, 2015). HSC support cells, such as osteoblasts and

mesenchymal stromal cells, often has functional overlap in HSC maintenance, resulting in

the resilience of HSC niche in the bone marrow (Pandolfi, Barreyro & Steidl, 2013). HSCs,

due to its proliferative nature, are under constant stress of intrinsic mutations and extrinsic

bone marrow niche remodelling. This leads to their transformation into disease-initiating

leukemic stem cells (LSC). LSCs often retains the self-renewal capabilities and can give rise to

various blood cell lineages, but in a dysregulated manner and translates into blood cell

malignancies in vivo (Balderman et al., 2016).

Accumulation of HSC mutations can induce physiological changes. Myelodysplastic

syndrome (MDS) is a pre-leukaemia condition, characterised by ineffective haematopoiesis,

prominent cytopenia and variable propensity in transforming towards severe leukemic

conditions (Guirguis et al., 2016). Previous literature had identified possibility of MDS-

related intracellular interactions that modified the bone marrow niche and had induced

endothelial, osteoblastic and mesenchymal cell dysfunction (Ferrer et al, 2013). Although

recent studies have identified two novel intercellular proteins Epha3 and integrin beta-3

(Miller et al., 2013) for their potential role in HSC and leukaemia progression, much of the

niche-HSC interactions remain unknown (Charmsaz & Boyd, 2013).

In this study, NHD13 mice, which has direct expression of NUP98-HOXD13 fusion

gene on the hematopoietic tissues, is used to recapitulate MDS condition in murine model


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(Slape et al., 2008). DNA microarray assay had been previously done on their LK cell

populations, which is a heterogeneous HSC population marked by negative lineage and

positive c-Kit markers (Copley, Beer & Eaves, 2012). This assay had analysed the gene

expression differences between NHD13 transgenic and wild-type mice. The data will be

examined in identifying potential abnormally expressed genes. Furthermore, identified

genes and its mRNA expression will also be examined in the LSK cell population, a long-term

HSC (LT-HSC) subset of LK cells (Mullally et al., 2012). The initial gene selections will be

based on the relative expression levels and the predicted intercellular functions in

regulating cell-cell interaction between HSC and bone marrow. It is hypothesised that there

are proteins that mediate cell-cell interactions between HSCs and bone marrow stroma that

contribute to pre-leukaemia condition.

This experiment aims to identify abnormal gene expressions in pre-leukemic NHD13

mice, through an initial validation of previous LK cells data and a novel mRNA expression

analysis in the LSK cells subset. As earlier study induced bone marrow niche changes that

improved hematopoietic recovery and inhibited malignancy progression, further

identifications of targetable niche components in MDS may provide beneficial therapies

(Balderman et al., 2016).

2. Materials & methods

2.1 Data mining

The gene microarray data of 3 NHD13 transgenic mice and 3 WT mice were obtained from

the Slape group. Genes of interest were shortlisted on the basis of having more than 2x or

less than 0.5x ratio in the gene fold expression and an average p-value less than 0.05 in both


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groups. These shortlisted genes were further cross-referenced with past literature for

potential cell-cell functions.

2.2 Primer design

DNA primers were designed for the selected genes based on a stringent set of criteria: 40-

60% GC content; GC clamp on both forward and reverse primers; expected TM between

60oC–63oC; 18–22 base pair primer size; low self-complementarity and hetero-

complementarity (<4 consecutive base pairs); 200 – 250 base pair for total amplicon length;

the amplicon crosses more than one mRNA exon; using BLAST to ensure the capturing of all

gene variants.

2.3 Cell Sorting

Bone marrow of 6 mice (3 transgenic, 3 WT) were collected and cells were processed in the

TRI flow cytometry facility. LK and LSK cell populations were sorted by FACS for each mice

and stored in the freezer for future use. Partial gating strategies are displayed in the results

section.

2.4 mRNA extraction and quantification

Total RNA were extracted from the sorted LK and LSK cells using the GenEluteTM mRNA

Miniprep Kit according to the manufacturer’s protocol*. mRNA content was analysed and

recorded with NanodropTM. The content was then stored in the freezer.

*During the extraction, one of the filtration column broke and resulted in the leakage of one

LK cell line. That particular cell line was excluded from further analysis.


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2.5 cDNA synthesis

8µL of extracted mRNA of each cell line was added with 1µL of hex primer, 1µL of dNTP and

heated at 65oC in thermal cycler for 5 minutes. Following this, 10µL of the cDNA synthesis

mix (2µL 10x reverse transcriptase buffer, 4µL 25mM MgCl2, 2µL 0.1M Dithiothreitol, 1µL

Superscript II reverse transcriptase) was added to the mRNA solution. This solution was ran

through the thermal cycler at 25oC for 10 minutes, 50oC for 50 minutes and a terminal

reaction at 85oC for 5 minutes in obtaining cDNA. The cDNA was treated with 1µL of RNase

H, incubated at 37oC for 20 minutes and stored in freezer. A RT- control sample was made

for each cell line, by replacing the reverse transcriptase with DNAse-free water. A single

RNA- control sample was made by replacing the 8µL of mRNA with DNAse-free water.

2.6 PCR validation with gel electrophoresis

Every set of designed primers was amplified with a randomly selected cDNA sample through

real-time PCR. The PCR media contained 1µL forward, 1µL reverse primer, 10µL SYBR Green

agent, 6µL DNAse-free water and 2µL cDNA sample. A randomly selected RT- control sample

was also amplified with each set of primers. The sample was then ran through the ViiA real-

time PCR system (Thermo Fisher). Each of the amplified cDNA sampled is further added with

4µL of DNA gel loading dye (Thermo Fisher) and loaded onto a 1.5% agarose gel, with a 4µL

reference sample a 50bp DNA ladder. The gel was run at 100V for 50 minutes.

2.7 Real-time PCR

cDNA templates were used for RT-PCR on a ViiA 7 real-time PCR system (Thermo Fisher) to

assay gene expressions. Triplicate samples was ran for each gene of interest from each of

the cell lines. All aforementioned controls were also ran through the PCR. Each well’s PCR


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media contained 1µL forward, 1µL reverse designed primers, 10µL SYBR Green agent, 6µL

DNAse-free water and 2µL cDNA sample. Mouse HPRT was selected and used as

housekeeping gene for the RT-PCR. RT-PCR analyses were ran with the following settings:

initial 95oC heat activation for 2 minutes, followed by 40 cycles of denaturation for 5

seconds at 95oC and annealing/extension at 55oC for 30 seconds.

3. Results

3.1 FACS plots of LK and LSK cells

The LK and LSK cell populations were obtained from transgenic NHD13 and wild-type mice

bone marrow through FACS. Figures 1 and 2 show the partial gating strategies for transgenic

and wild-type mice, respectively. It was observed that both LK and LSK cells constituted a

larger percentage of overall cells in the wild-type mice compared to the transgenic.


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3.2 Primer validation via gel

The PCR procedure and primer sets was validated with a trial PCR run with the LK cell

population, where the synthesized cDNA were examined through gel electrophoresis

against a DNA ladder. Negative controls (RT-, RNA- and template-) were also validated.

Figure 3a-c demonstrated the gel products for the tested primers. All of the amplified LK

samples had the brightest band between 200-250 base pairs, with the exception of Robo4

LK sample. The bands in the negative controls are noticeably smaller in most the tested

primers, with the exception of GJB2 RT-.


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3.3 mRNA expression analysis

Real-time PCR was completed on all cell lines’ transcribed cDNA with all sets of primers.

Table 1 shows the relative gene expression of the 14 examined genes in the LK cells, the

expression being compared against mouse housekeeping HPRT gene. Notably, there was a

substantial increased expression of Clec4e, NTN4, Pcdh17, Slamf1, GJB2, Pcdh7, Rik and

TMEM56, and a decreased expression of Ryk in the LK cells of transgenic NHD13 mice. All Ct

values above 37 were excluded from the analysis.

Table 1. Gene expressions of LK cells from NHD13 transgenic mice (n=2) and WT mice (n=3). Gene relative expression was the average expression of the cell line PCR triplicates of corresponding experimental condition

(transgenic or WT). The expression is calculated by the CT method followed by the 2-ΔΔCT equation.

Gene

NHD13 relative

expression (±SEM)

WT relative expression

(±SEM)

Expression fold change

Clec4e 0.17 (±0.013) 0.029(±0.0061) 5.697316

Agrin 0.0086(±0.0019) 0.0096(±0.0017) 0.903391

NTN4 0.13(±0.031) 0.062(±0.015) 2.097171

TJP3 0.032(±0.0029) 0.026(±0.0043) 1.24729

SLC39A8 0.0030(±0.00017) 0.0020(±0.00051) 1.482726

Pcdh17 1.15(±0.50) 0.00060(±0.00059) 1916.481

Slamf1 0.063(±0.0075) 0.017(±0.0031) 3.664089

Robo4 0.0068(±0.00012) 0.0070(±0.0016) 0.967095

RYK 0.0071(±0.0015) 0.022(±0.0068) 0.32564

GJB2 0.096(±0.034) 0.0042(±0.0019) 22.80027

Ociad1 2.62(±0.28) 1.74(±0.32) 1.507106

Pcdh7 0.15(±0.024) 0.015(±0.003485) 9.80113

Rik 0.12(±0.034) 0.055(±0.0093) 2.080072

TMEM56 0.13(±0.033) 0.015(±0.0037) 8.682309


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10 genes were further examined in the LSK cell populations, with Ociad1, Rik, Agrin and

Robo4 excluded, due to their lackluster gene expression fold change in LK population.

Relative expressions were analysed against mouse housekeeping HPRT gene. All Ct values

above 37 were excluded from the analyses. In the LSK cells, many triplicates did not produce

results or quantifiable Ct value, resulting in blanks in the expression analysis. Notably,

Clec4e, TJP3 and Pcdh7 expressions were substantially increased in transgenic mice and Ryk

expression was decreased.

Table 2. Gene expression averages of LSK cells from NHD13 transgenic mice and WT mice triplicates. The

expression is calculated by the CT method followed by the 2-ΔΔCT equation. Empty columns represent primer-sequenced cDNA that failed to amplify to the target threshold after 40 cycles.

Gene

NHD13 relative

expression (±SEM)

WT relative

expression (±SEM)

Expression fold

change

Clec4e 0.26(±0.076) 0.078(±0.0083) 3.28

NTN4 0.040(±0.041) 0.037(±0.010) 1.09

TJP3 0.056(±0.010) 0.026(±0.0053) 2.21

SLC39A8 - - -

Pcdh17 0.26(±1.42) - -

Slamf1 0.26(±0.13) 0.30(±0.21) 0.86

RYK 0.072(±0.018) 0.12(±0.033) 0.60

GJB2 - - -

Pcdh7 0.33(±0.084) 0.11(0.097) 3.09

TMEM56 - - -


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3.4 Graphs of relative mRNA expression of selected genes

Selected genes were graphed in figure 4a-d based on their expressions in Table 1 and Table

2. Each panel shows the side-by-side comparison of relative gene expressions between

transgenic NHD13 and wild-type, in both LK and LSK conditions.

Figure 4. RT-PCR of selected gene expressions in LK and LSK cell populations of wild-type (grey bars) and

transgenic NHD13 mice (black bars). Genes were selectively displayed on the basis of expression fold change in

mice types. Data is represented as relative expression ± SEM, n = 2-3 per group. *P < 0.05; **P <0.01.

4. Discussion

The RT-PCR procedure and primers were first validated with gel electrophoresis prior to the

gene analysis experiment in figure 3. The results showed a clear amplification of cDNA of

200 to 250 base pair length and consistent with the designed primer length. However,

Robo4 and Rik cDNA did not amplify as expected. The Robo4 band was highly scattered,

suggesting potential genomic DNA contamination during amplification. In contrast, the Rik

cDNA was smaller than 100 base pairs, which suggest the possibility of the formation of

primer dimer. Most of the negative controls did not form a distinct band, with the exception


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of GJB2 RT-, which suggests contamination in the sample. In addition, mouse HPRT

housekeeping gene amplified as expected in both LK and LSK cDNA, which highlights its

usability in the analysis.

cDNA expression was analysed on the LK cell population as the validation tool for the

original microarray data. The expression was normalised to the HPRT housekeeping gene.

Results suggests the potentially increased expressions of Clec4e, NTN4, TJP3, SLC39A8,

Pcdh17, Slamf1, GJB2, Ociad1, Pcdh7, Rik and TMEM56 in the NHD13 mice, as well as the

decreased expression of Ryk. Thus, 12 out of the 14 genes were validated in the LK cells with

respect to prior data.

A selection of ten genes were further analysed in the LSK cells cDNA. Amplified gene

cDNA expression was normalised to the HPRT housekeeping gene. It was observed that

many of the genes did not produce significant amplifications, that is, expression was not

detectable after 35 cycles. Compared to the LK subset, LSK cells are a distinctly different HSC

population and as such, it may provide different hematopoietic function and different gene

expressions (Du et al., 2012). This could potentially explain the lack of primer-specific cDNA

amplification in many sets of LSK cells. Nevertheless, 3 genes were consistently over

expressed in pre-leukemic LK and LSK cells, namely Clec4e, TJP3 and Pcdh7. In addition, Ryk

gene was consistently under expressed in pre-leukemic LK and LSK cells.

As per figure 4, Clec4e relative expression was significantly increased in both LK and

LSK NHD13 mice, corresponding to the microarray data. Prior studies had suggested Clec4e

expression within human and mouse atherosclerotic lesions and its role in the signalling

pathways of macrophages and proinflammatory mediators. In the context of bone marrow,

Clec4e knockout model had shown reduced inflammation and proliferation (Clement et al.,


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2016). This highlights the potential cell-cell signalling properties of clec4e on HSCs in pre-

leukemic mouse. Further studies should be taken to examine clec4e activity in context of

early bone marrow haematopoiesis.

Gene expression analysis also revealed significant overexpression of TJP3, tight

junction protein 3, in LSK cells of NHD13 mice. It is noted that TJP3 expression was increased

by a miniscule extent in the LK cells. However, its strong predicted intercellular function

warrants its further investigation in LSK cells over other genes such as Rik and Ociad1, which

had scarce literature reports and little potential link to the bone stroma. Previous

experiment had demonstrated effects of immature leukemic blast cells in disrupting the

regulatory tight junction protein interactions in endothelial cells in the blood brain barrier

(Feng et al., 2011). This could potentially explain the TJP3 overexpression in LSK cells, where

increased TJP3 expression aided the production of regulatory tight junction proteins that

compensates its accelerated degradation from the accumulating leukemic blast cells. If this

was true, it would further suggest a relevant interaction between HSC’s tight junction

protein and stromal niche. This working theory must be further examined in a bone marrow

context. An alternative explanation for this significant expression level was that it occurred

due to chance, which was substantiated by the large error bars and the low sample size in

the experiment. Due to the contradictory TJP3 results and its potential lukemogenesis role,

it warrants further investigation with a larger sample size.

Furthermore, Pcdh7, or protocadherin-7, was another gene that was over expressed

in both LK and LSK subsets of the pre-leukemic mice, corresponding to the microarray data.

The protocadherin protein family are cell-adhesion proteins present in the bone marrow (Li

et al., 2012). However, the roles of many specific protocadherins, including Pcdh7 remain

unclear. Given its status of being significantly increased in LK transgenic samples and a


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borderline significant increase (p= 0.0676) in the LSK cell population, it certainly warrants

further investigation. Interestingly, another Protocadherin gene, namely Pcdh17, was also

investigated and though its expression was not graphed, it may be the most significant gene

of this study. The Pcdh17 fold increase was at an astronomical level in the LK cells and it was

not quantifiable in the LSK cells, due to all of the WT LSK samples failing to reach the

threshold. However, in comparison, samples from the transgenic strains’ LSK cells had low

and consistent Ct values. These two results suggested that the Pcdh17 gene was potentially

only expressed in the diseased pre-leukemic state and not in the healthy HSCs.

In contrast, Ryk gene has been observed to a reduced expression in LK and LSK cells,

similar to its expression in the microarray data. This result suggested that Ryk was

potentially related in the maintenance and regulation of the healthy stem cell state (Hollis

et al., 2016). Past literature had identified Ryk to be involved in axon regulation in

embryonic develop. There is currently no information relating Ryk to the bone marrow, or

leukemic conditions.

Caveats of this experiment also require consideration. An important limitation was

the samples’ differences between the prior microarray data and this study. The original

microarray analysis did not discriminate the LSK subset and as such, its LK cell population

that was used for the array would encompass the LSK subset. However, this current

experiment had excluded the LSK cells from the rest of LK cells in the cell sorting. Thus, the

current experiment’s LK gene expression may be misrepresented with respect to the original

microarray, due to the difference in gating strategy. Lastly, small sample size has been a

particular issue with this experiment. Since there were only 6 mice used in total, this does


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not constitute enough statistical power to draw conclusion in many cases in the results. A

larger sample would produce more robust and confident results.

This experiment was aimed to investigate potential intercellular proteins that

mediate cell-cell interaction in pre-leukemic mice with the NHD13 model. This was

completed by gene validation on the LK cell population against a previous microarray data

set. A further expression analysis was completed on the LSK cells, a long term HSC

subpopulation. It was found that Clec4e, TJP3, Pcdh7 genes had been quantifiably

overexpressed in the pre-leukemic HSCs, compared to the wild type control. Pcdh17 was

another gene likely to be expressed in pre-leukemic HSCs, however, its expression appeared

to following an “on-off” pattern, such that it was not expressed in healthy HSCs. In contrast,

Ryk gene expression was found to be consistently decreased in the pre-leukemic HSCs.

Following the results of this study, it would beneficial to examine the functional

consequences of the ablation or reduction of these genes. A knockdown study can be

potential conducted, where shRNA is used in silencing the target gene expressions in

examining the subsequent phenotype. Pharmacological intervention is another avenue that

is worth exploring, such that specific inhibitors for the Clec4e, TJP3, Pcdh7 and Pcdh17

proteins can be administered in vivo, functional consequences can then be observed. Ryk,

due to its reduced expression in diseased state, has limited relevant therapeutic interest.

Lastly, human trials, involving healthy and pre-leukemic bone marrow, must also be

investigated as murine models can never fully recapitulate complex human physiology.

Overall, this experiment had successfully identified several gene targets that have been

abnormally expressed in pre-leukemic, disease-initiating HSCs, which can serve as the

genetic basis for future functionally-related experiments.


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