Identification of immune-related genes in thymus of breast cancer mouse model exposed to different calorie restriction
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Zehra Omeroglu Ulu
Abstract
Introduction
In the present study, RNA sequencing-mediated transcriptome analysis was performed in order to elucidate the molecular mechanisms of the immune response for different types of calorie restriction (CR) application using MMTV-TGF-α breast cancer mouse model.
Methods
Animals were applied to three different dietary regiments; ad libitum (AL), chronic calorie restriction (CCR) and intermittent calorie restriction (ICR). Using thymus tissues, 6091 differentially expressed genes (DEGs) were identified in three dietary groups. After clustering of total of 6091 DEGs using Gene Ontology (GO) categories, a total of 400 genes were identified to be involved in immune system process (GO:0002376) GO categories. KEGG pathway and gene co-expression network analysis of these immune-related DEGs were done using String database. The results were confirmed with measuring mRNA expression levels of four selected immune-related DEGs genes (Casp3, Thy1, IL-16 and CD4) using quantitative real-time PCR (qPCR).
Results
The expression levels of immune-related genes were different in three RNA-seq data.
Conclusion
The results provide useful information to investigate the immune-related transcriptional profiling in thymus tissue of breast cancer mouse model applied to two different types of CR and to identify the specific functional immune related genes in response to CR during cancer development.
Öz
Amaç
Bu çalışmada, MMTV-TGF-a meme kanseri fare modeli kullanılarak, farklı kalori kısıtlaması (KK) uygulamaları için immün yanıtın moleküler mekanizmalarını açıklamak amacıyla RNA sekanslama aracılıklı transkriptom analizi yapılmıştır.
Gereç ve Yöntem
Farelere üç farklı beslenme uygulanmıştır; ad libitum (AL), kronik kalorili kısıtlama (KKK) ve aralıklı kalori kısıtlaması (AKK). Timus dokuları alınarak üç beslenmedeki diferansiyel eksprese olan genlerin toplamda 6091 tane olduğu tanımlanmıştır. Bu genler genler Gen Ontolojisi (GO) kategorileri kullanılarak sınıflandırılmıştır. İmmün sistem proses (GO: 0002376) GO kategorisinde toplam 400 gen tespit edilmiştir. Bu genler için KEGG yolak ve ortak ifade ağ analizi, String veritabanı kullanılarak yapılmıştır. Daha sonra, kantitatif gerçek zamanlı PCR kullanılarak seçilmiş dört immün sistemde görevli geninin (Casp3, Thy1, IL-16 ve CD4) mRNA ekspresyon seviyeleri ölçülmüştür.
Sonuç
Üç RNA-seq datasında immün sistemle ilişkili genlerin ekspresyon seviyelerinin farklı olduğu gözlemlenmiştir.
Tartışma
Sonuçlar, iki farklı kalori kısıtlaması uygulanan meme kanseri fare modelinin timus dokusunda immün sistem ile ilgili transkripsiyonel profili araştırmak için ve kanser gelişimi sırasında kalori kısıtlamasına yanıt olarak spesifik fonksiyonel immün sistem ilişkili genleri tanımlamamıza yardımcı olacak bilgiler sağlamaktadır.
Introduction
Calorie restriction (CR) which involves a sustained, moderate reduction in calorie intake compared to ad libitum (AL) feeding is a dietary regimen [1]. CR has proven to be an effective method in multiple species to decrease the incidences of chronic disease [2], [3], hypertension, heart disease, kidney disease, and neurological dysfunction and increases sensitivity to insulin and the lifespan [4], [5], [6]. Two common CR types are chronic calorie restriction (CCR) and intermittent calorie restriction (ICR) which involves strong restriction on 1 or 2 days per week [7], [8].
MMTV-TGF-α transgenic mice have particular value in age-related mammary tumor (MT) development studies. These mice have been reported to develop MT in the second year of their life [9] due to over expression of TGF-α, epidermal growth factor, which also plays a critical role in development of human breast cancer [10]. In several animal studies, the protective effect of CR on MT development has been shown [11], [12], [13]. However, the results of different CR types with respect to cancer prevention is controversial. Some studies suggested CCR to be more preventive for MT development compared to ICR [14], [15], while other studies showed ICR is more effective than CCR [7], [16], [17].
The thymus is a primary lymphoid organ and a place of T-cell differentiation and maturation [18]. Importantly, the changes in the adaptive immune system increase with CR and aging [19], [20]. In rodents and in non-human primates, CR increases production of native T cells [21] and T cell proliferation [22], but these functions also decrease with aging. Studies have reported that although inflammatory cytokines such as IL-6, TNF-α and IFN-g were decreased by CR [22], [23], they were not changed with aging [24]. In addition, age-associated dysfunction of natural killer cells has been reported in mice [25] and human studies [26]. On the other hand, although there are many studies have been conducted to understand the roles of immune cells in cancer development and their responses to CR, the exact molecular mechanism of this process has not been clearly understood yet. Especially, the roles of specific gene(s) involved in immune system responses to CR needs be clarified. Therefore, the aim of the present study was by using RNA-seq transcriptome analysis method to identify the immune related genes in thymus of breast cancer mouse model in response to different types of CR application.
Materials and methods
Mouse model and tissue accession
In this study, MMTV-TGF-α (C57/BL6) female mice over-express human TGF-α, a part of epidermal growth factor receptor (EGFR)/ErbB cascade which is known to play a role in the development of human breast cancers, were used [10]. Mice colony were maintain using a breeding protocol and genotyping assay at Yeditepe University Animal Facility as previously described [12]. At 10 weeks of age female MMTV-TGF-α mice were assigned to one of three fed groups: AL, chronic caloric restricted (CCR) and intermittent caloric restricted (ICR). The CCR group received 85% of the daily food consumption of AL mice, in other words they were applied to 15% caloric restriction. The ICR group was fed AL for 3 weeks then following week 60% caloric restriction compared to AL were applied. Mice diets (Altromin TPF1414) were purchased from Kobay AS (Ankara, Turkey). All mice had free access to water. Food intakes were determined daily and body weights weekly. Animals were also checked by expert veterinarian on a regular basis at least once a week. Mice were euthanized after overnight fasting at the age of 17 or 18 weeks old. Mice in ICR group were euthanized after three weeks of AL feeding.
RNA isolation, library preparation and sequencing
Total RNA was isolated from the thymus tissue samples of three different individual mice in each different dietary groups. Preparation of cDNA library and RNA sequencing were performed by Beijing Institute of Genomics [27]. RNA-seq data has been deposited in NCBI Gene Expression Omnibus database under accession number GSE95371.
Statistical analysis and functional annotation of gene expression
The sequencing reads were aligned to GRCm38 mouse genome (Ensemble database) using the splice-aware TopHat aligner [28]. Filtered mapped reads were analyzed using the Cufflinks package with default parameters and the following additions. Differentially expressed genes (DEGs) were determined based on false discovery rate (FDR)-adjusted p-value <0.05 as calculated by Cuffdiff [29]. All of the data produced by a Cuffdiff analysis was visualized and integrated with R [30].
The DEGs have mapped to GO terms in the database (http://www.geneontology.org/, Panther GO-Slim), calculated gene numbers for immune system process (GO:0002376), using a hypergeometric distribution compared with the genome background. KEGG analysis and gene co-expression network was visualized by the String database (www.strindb.org) [31].
Validation of RNA-seq genes by qPCR
Four unigenes with significant expression difference (Casp3, Thy1, IL-16 and CD4) involved in immune system were chosen for validation by quantitative real-time PCR (qPCR). Using GM SYBR Green qPCR Kit qPCR was performed with the LightCycler Nano Real-Time System (Roche, Switzerland). The thermal cycling conditions were 95°C for 2 min, 45 cycles at 95°C for 20 s for denaturation, and 58°C and 72°C for 30 s and 45 s for annealing and extension. The 2−ΔCT method was used to calculate relative gene expression levels in each sample. Primer sequences were designed using IDT and Primerblast programs and Gapdh was used as an internal control (Table 1).
The information of the primer pairs used to analyze gene expression levels by qPCR.
| Gene names | Primer sequences |
|---|---|
| Thy-1 | 5′TCTCAGGCACCCTTGGGATA 3′ 5′GTAGTCGCCCTCATCCTTGG 3′ |
| IL-16 | 5′ATGGTGCTCCCAGAGTTTAC 3′ 5′CTGAATGGCTGAGGCTACTT 3′ |
| CD4 | 5′TGGATCAAAGGGCAGTGTATAG 3′ 5′GCAGCCTCTCAGTCTTCA TT 3′ |
| Casp3 | 5′AGCTTGGAACGGTACGCT 3′ 5′AGA TCCCAGAGTCCACTGAC 3′ |
| Gapdh | 5′ACT CCA CTC ACG GCA AAT TC3′ 5′CAGTAGACTCCACGACATACT C3′ |
GAPDH was used as an internal control.
Results
Summary of RNA-seq analysis
In our previous project, three sequencing libraries were constructed from thymus tissues of MMTV-TGF-α mice in AL, CCR and ICR diet groups for RNA-seq. Approximately 127 million clean reads were mapped to GRCm38 mouse assembly in the Ensemble database with TopHat. Ratio of mapped reads approximately 92.5%. Corrected FPKM values were subjected to analysis of DEGs, a total of 6091 significantly DEGs were identified in three different diet groups, by using corrected p-value <0.05 as the filter [27]. The 2821, 2825 and 445 significantly DEGs were detected between diet groups AL-CCR, CCR-ICR, AL-ICR, respectively (p<0.05). According to these results; 916, 1877 and 200 genes were up-regulated and 1905, 948 and 245 genes down-regulated in DEGs between the diet groups AL and CCR, CCR and ICR, AL and ICR, respectively [27].
Identification of immune-related genes
DEGs obtained from these libraries, between AL and CCR, AL and ICR, CCR and ICR diet groups (p<0.05), were classified according to cellular components, biological processes and molecular functions GO main categories. The biological process category includes “immune system process (GO:0002376)” GO category. The DEGs obtained from these libraries were further subjected to GO functional enrichment analysis, which provided to describe immune-related genes in “immune system process (GO:0002376)” term. In GO:0002376 term, 188 of 2821, 36 of 445, 176 of 2825 genes differential expressed between AL-CCR, AL-ICR, CCR-ICR diet groups, respectively.
Besides, 67, 92 and 17 of immune-related genes were up-regulated and 121, 19 and 84 genes down-regulated between AL and CCR, CCR and ICR, AL and ICR fed groups, respectively. These immune-related genes were shown according to the log2Fold change <−2 and log2Fold change >2 value (Tables 2–4).
Immune-related genes between AL and ICR filtered log2Fold change <−2 and log2Fold change >2 value.
| Gene names | Sample_1 | Sample_2 | log2(Fold_change) | p-Value |
|---|---|---|---|---|
| Pcolce | AL | ICR | 3.19965 | 5E-05 |
| Spint1 | AL | ICR | −2.13611 | 0.0123 |
| Col15a1 | AL | ICR | −2.54181 | 0.00275 |
Immune-related genes between AL and CCR filtered log2Fold change <−2 and log2Fold change >2 value.
| Gene names | Sample_1 | Sample_2 | log2(Fold_change) | p-Value |
|---|---|---|---|---|
| Tns1 | AL | CCR | 2.81267 | 5.00000E−05 |
| Cfh | AL | CCR | 3.86202 | 5.00000E−05 |
| Csrp2 | AL | CCR | 2.43296 | 0.0015 |
| Msrb3 | AL | CCR | 3.25099 | 0.0004 |
| Gpx3 | AL | CCR | 3.71675 | 5.00000E−05 |
| Cd79b | AL | CCR | 2.05737 | 0.00135 |
| Ighv3-6 | AL | CCR | 3.75866 | 0.00065 |
| Ighv1-19 | AL | CCR | 2.52651 | 0.0126 |
| Tns2 | AL | CCR | 3.02069 | 5.00000E−05 |
| Adipoq | AL | CCR | 3.42312 | 5.00000E−05 |
| Adgrf5 | AL | CCR | 3.63443 | 5.00000E−05 |
| C4b | AL | CCR | 3.22915 | 5.00000E−05 |
| Slc27a2 | AL | CCR | 4.29046 | 0.00045 |
| Acss2 | AL | CCR | 2.54708 | 5.00000E−05 |
| Cd302 | AL | CCR | 2.63002 | 0.0167 |
| S100a6 | AL | CCR | 2.57191 | 5.00000E−05 |
| Adgrl4 | AL | CCR | 2.50311 | 0.0095 |
| S100a1 | AL | CCR | 3.33725 | 5.00000E−05 |
| Hspb1 | AL | CCR | 3.02974 | 0.00195 |
| Cd36 | AL | CCR | 4.31277 | 5.00000E−05 |
| Sh2b2 | AL | CCR | 3.59971 | 0.00095 |
| March8 | AL | CCR | 2.13474 | 0.00235 |
| Igkv4-72 | AL | CCR | 2.41746 | 0.00505 |
| Cebpa | AL | CCR | 2.84059 | 5.00000E−05 |
| Acsm3 | AL | CCR | 5.10879 | 5.00000E−05 |
| Fcgrt | AL | CCR | 2.35414 | 5.00000E−05 |
| Slc27a1 | AL | CCR | 3.44268 | 5.00000E−05 |
| Fhl1 | AL | CCR | 4.49713 | 5.00000E−05 |
| Cybb | AL | CCR | 2.19663 | 0.00135 |
| Iglc1 | AL | CCR | 2.85077 | 5E-05 |
| Pcolce | AL | CCR | 3.47498 | 5E-05 |
| Zap70 | AL | CCR | −3.11197 | 5.00000E−05 |
| Slamf6 | AL | CCR | −2.81828 | 0.00025 |
| Mr1 | AL | CCR | −2.07319 | 5.00000E−05 |
| Lcp2 | AL | CCR | −2.24039 | 0.0001 |
| Grap | AL | CCR | −2.14867 | 4 |
| Skap1 | AL | CCR | −3.86327 | 5.00000E−05 |
| Itk | AL | CCR | −3.41276 | 5.00000E−05 |
| Nlk | AL | CCR | −2.05006 | 0.00035 |
| Stat5b | AL | CCR | −2.19968 | 5.00000E−05 |
| Spata13 | AL | CCR | −2.13382 | 0.00025 |
| Elf1 | AL | CCR | −2.07977 | 5.00000E−05 |
| Grap2 | AL | CCR | −2.91878 | 5.00000E−05 |
| Sla | AL | CCR | −3.65399 | 5.00000E−05 |
| Def6 | AL | CCR | −3.12154 | 5.00000E−05 |
| Crip3 | AL | CCR | −2.53914 | 0.0001 |
| Vav1 | AL | CCR | −2.84485 | 5.00000E−05 |
| Tagap1 | AL | CCR | −2.19823 | 0.00025 |
| Ppp1r14b | AL | CCR | −2.14199 | 5.00000E−05 |
| Dntt | AL | CCR | −5.67572 | 5.00000E−05 |
| Cd5 | AL | CCR | −3.64272 | 5.00000E−05 |
| Lef1 | AL | CCR | −3.91587 | 5.00000E−05 |
| Sit1 | AL | CCR | −4.22883 | 0.00145 |
| Lck | AL | CCR | −3.86171 | 5.00000E−05 |
| Txk | AL | CCR | −2.65584 | 5.00000E−05 |
| Gimap9 | AL | CCR | −2.36907 | 5.00000E−05 |
| Cd8a | AL | CCR | −4.8846 | 5.00000E−05 |
| Cd4 | AL | CCR | −3.77405 | 5.00000E−05 |
| Il21r | AL | CCR | −2.81807 | 5.00000E−05 |
| Spint2 | AL | CCR | −2.05501 | 5.00000E−05 |
| Ccl25 | AL | CCR | −3.01229 | 5.00000E−05 |
| Casp3 | AL | CCR | −3.05056 | 5.00000E−05 |
| Rltpr | AL | CCR | −4.35955 | 5.00000E−05 |
| Thy1 | AL | CCR | −4.29803 | 5.00000E−05 |
| Trbc1 | AL | CCR | −4.64904 | 5E−05 |
| Trac | AL | CCR | −2.47246 | 5E−05 |
| Trbc2 | AL | CCR | −4.63055 | 5E−05 |
| Colq | AL | CCR | −2.3138 | 5E−05 |
Immune-related genes between CCR and ICR filtered log2Fold change <−2 and log2Fold change >2 value.
| Gene names | Sample_1 | Sample_2 | log2(Fold_change) | p-Value |
|---|---|---|---|---|
| Cd2 | CCR | ICR | 2.01665 | 5.00000E−05 |
| Plekhg2 | CCR | ICR | 2.02515 | 5.00000E−05 |
| Elf1 | CCR | ICR | 2.04993 | 5.00000E−05 |
| Casp8 | CCR | ICR | 2.05028 | 5.00000E−05 |
| Tagap1 | CCR | ICR | 2.20259 | 0.0001 |
| Stat5b | CCR | ICR | 2.22228 | 5.00000E−05 |
| Spata13 | CCR | ICR | 2.24812 | 0.00015 |
| Slfn2 | CCR | ICR | 2.32184 | 5.00000E−05 |
| Slamf6 | CCR | ICR | 2.33621 | 3 |
| Cd84 | CCR | ICR | 2.3897 | 5.00000E−05 |
| Colq | CCR | ICR | 2.40085 | 0.0001 |
| Mr1 | CCR | ICR | 2.41042 | 5.00000E−05 |
| Lcp2 | CCR | ICR | 2.44881 | 5.00000E−05 |
| Clec2i | CCR | ICR | 2.4591 | 5.00000E−05 |
| Casp3 | CCR | ICR | 2.51841 | 5.00000E−05 |
| Grap | CCR | ICR | 2.52795 | 0.00055 |
| Gimap9 | CCR | ICR | 2.57845 | 5.00000E−05 |
| Crip3 | CCR | ICR | 2.82336 | 5.00000E−05 |
| Cd69 | CCR | ICR | 2.85433 | 0.0003 |
| Trac | CCR | ICR | 2.93217 | 5E−05 |
| Grap2 | CCR | ICR | 2.95583 | 5.00000E−05 |
| Zap70 | CCR | ICR | 2.99931 | 5.00000E−05 |
| Ccl25 | CCR | ICR | 3.04315 | 5.00000E−05 |
| Txk | CCR | ICR | 3.05417 | 5.00000E−05 |
| Il21r | CCR | ICR | 3.14165 | 5.00000E−05 |
| Vav1 | CCR | ICR | 3.16942 | 5.00000E−05 |
| Cd5 | CCR | ICR | 3.22315 | 5.00000E−05 |
| Itk | CCR | ICR | 3.43302 | 5.00000E−05 |
| Skap1 | CCR | ICR | 3.52315 | 5.00000E−05 |
| Lef1 | CCR | ICR | 3.56139 | 5.00000E−05 |
| Def6 | CCR | ICR | 3.7327 | 5.00000E−05 |
| Lck | CCR | ICR | 3.82005 | 5.00000E−05 |
| Sla | CCR | ICR | 3.95902 | 5.00000E−05 |
| Cd4 | CCR | ICR | 4.03836 | 5.00000E−05 |
| Sit1 | CCR | ICR | 4.06077 | 0.0013 |
| Rltpr | CCR | ICR | 4.09504 | 5.00000E−05 |
| Thy1 | CCR | ICR | 4.18136 | 5.00000E−05 |
| Trbc1 | CCR | ICR | 4.83734 | 5E−05 |
| Trbc2 | CCR | ICR | 4.84636 | 5E−05 |
| Cd8a | CCR | ICR | 5.06282 | 5.00000E−05 |
| Slamf1 | CCR | ICR | 5.21796 | 0.0147 |
| Dntt | CCR | ICR | 5.82443 | 5.00000E−05 |
| Ighv3-6 | CCR | ICR | −4.416 | 0.00345 |
| Pla2g7 | CCR | ICR | −2.06739 | 0.0029 |
| Abhd4 | CCR | ICR | −2.07835 | 0.0002 |
| Ighv1-82 | CCR | ICR | −2.1234 | 0.0163 |
| Fcgrt | CCR | ICR | −2.12974 | 5.00000E−05 |
| C2 | CCR | ICR | −2.1523 | 5E−05 |
| Col4a1 | CCR | ICR | −2.1836 | 5.00000E−05 |
| Msrb3 | CCR | ICR | −2.31109 | 0.0009 |
| S100a6 | CCR | ICR | −2.3115 | 0.0002 |
| S100a1 | CCR | ICR | −2.31869 | 5.00000E−05 |
| Ighv1-26 | CCR | ICR | −2.31928 | 0.0054 |
| Slc27a2 | CCR | ICR | −2.41265 | 0.00045 |
| Igkv1-110 | CCR | ICR | −2.52224 | 0.00035 |
| Cd302 | CCR | ICR | −2.54036 | 0.0151 |
| Adgrf5 | CCR | ICR | −2.55154 | 5.00000E−05 |
| Slc27a1 | CCR | ICR | −2.56109 | 5.00000E−05 |
| Fbln1 | CCR | ICR | −2.57612 | 0.0033 |
| Crip2 | CCR | ICR | −2.59587 | 5.00000E−05 |
| Cebpa | CCR | ICR | −2.61195 | 5.00000E−05 |
| C4b | CCR | ICR | −2.74532 | 0.00055 |
| Acsm3 | CCR | ICR | −2.74966 | 0.00245 |
| Cd55 | CCR | ICR | −2.76376 | 0.00015 |
| Sh2b2 | CCR | ICR | −2.90785 | 0.0018 |
| Tns1 | CCR | ICR | −3.05026 | 5.00000E−05 |
| Fhl1 | CCR | ICR | −3.12463 | 5.00000E−05 |
| Adipoq | CCR | ICR | −3.1317 | 5.00000E−05 |
| Cd36 | CCR | ICR | −3.14103 | 5.00000E−05 |
| Gpx3 | CCR | ICR | −3.31306 | 5.00000E−05 |
| Cfh | CCR | ICR | −3.4394 | 5.00000E−05 |
| Csrp3 | CCR | ICR | −3.63321 | 0.00545 |
| Cxcl13 | CCR | ICR | −3.66985 | 0.00405 |
| Adgrl4 | CCR | ICR | −3.68165 | 0.0018 |
| Tns2 | CCR | ICR | −3.77329 | 0.0001 |
| Iglv1 | CCR | ICR | −3.8441 | 0.0001 |
| Cryab | CCR | ICR | −3.97295 | 0.0014 |
| Hspb7 | CCR | ICR | −4.50642 | 0.00925 |
Pathway and gene network analysis
A KEGG pathway analysis was performed in identified immune-related DEGs pertaining to the AL-CCR, AL-ICR, CCR-ICR diet groups. When filtered by FDR, the most significant two KEGG terms were antigen processing and presentation (pathway ID: 04612), T cell receptor signaling pathway (pathway ID: 04660) for between AL-CCR DEGs; T cell receptor signaling pathway (pathway ID: 04660) and TNF signaling pathway (pathway ID: 04668) for between CCR-ICR DEGs; tuberculosis (pathway ID: 05152) and toxoplazmosis (pathway ID: 05145) for between AL-ICR DEGs. Some immune-related KEGG pathways and the DEGs count were shown in Table 5.
The results of KEGG pathway analysis of AL-CCR, CCR-ICR and AL-ICR DEGs.
| KEGG pathways | AL-CCR | CCR-ICR | AL-ICR | |||
|---|---|---|---|---|---|---|
| Gene count | FDR | Gene count | FDR | Gene count | FDR | |
| T cell receptor signaling pathway | 12 | 1.73E-09 | 11 | 3.17E-08 | – | – |
| TNF signaling pathway | 9 | 1.53E-06 | 10 | 1.71E-07 | – | – |
| Natural killer cell mediated cytotoxicity | 10 | 2.54E-07 | 9 | 2.25E-06 | – | – |
| Antigen processing and presentation | 12 | 5.1E-11 | 5 | 0.00106 | 3 | 0.00442 |
| B cell receptor signaling pathway | 8 | 9.82E-07 | 6 | 0.000115 | – | – |
To identify co-expression profiles of AL-CCR, AL-ICR, CCR-ICR immune-related DEGs, a gene co-expression network was generated using gene expression data from DEGs identified in this study (Figure 1A–C).
A gene co-expression network of immune related DEGs.
(A) A gene co-expression network between AL-CCR immune-related DEGs. (B) A gene co-expression network between CCR-ICR immune-related DEGs. (C) A gene co-expression network between AL-ICR immune-related DEGs.
Nodes indicated the immune-related DEGs and edges presented the interaction between immune-related DEGs (Table 6).
Information of co-expression network analysis.
| Results of network analysis | AL-CCR | CCR-ICR | AL-ICR |
|---|---|---|---|
| Number of nodes | 167 | 152 | 30 |
| Number of edges | 602 | 447 | 19 |
| Average node degree | 7.21 | 5.88 | 1.27 |
| PPI enrichment p-value | 1.0E-16 | 1.0E-16 | 2.32E-07 |
Validation with qPCR
To validate the reliability of the expression of immune-related DEGs obtained from RNA-seq analysis, qPCR was used to dissect dynamic change in gene expression level in four genes; Casp3, Thy1, IL-16 and CD4. The results of RNA-seq and qPCR for four DEGs were shown in Figures 2 and 3, respectively. According to the results of RNA-seq and qPCR; Casp3, Thy1, IL-16 and CD4 were up-regulated in AL fed group compared with ICR and CCR diet groups (Figures 2 and 3).
qPCR validation of showing the expression levels of Casp3, Thy1, IL-16 and CD4 genes in CCR, ICR and AL fed groups.
Heat map showing the expression profiles of Casp3, Thy1, IL-16 and CD4 genes in the CCR, AL, and ICR groups revealed by RNA-seq.
Discussion
Thymus is a primary lymphoid organ in the immune system that is largely replaced with fat at an early age independent of adiposity or disease. Given that the function of thymus is to establish and maintain T cell arm of immunity and not to regulate energy homeostasis, the adipocytes develop within the thymic [5], [18]. Thymus and other lymphoid organs react to nutrition deficiency more rapidly than most of the other organs [32], [33]. Several studies from animal models show that CR has a significant impact on the immune system. Most of the studies suggest that CR improves many parameters of immune responses [20], [34], [11].
In this study, RNA were isolated from thymus tissue of AL, chronically calorie restriction (CCR) and ICR fed MMTV-TGF-α mice from 10 weeks of age to 17 weeks of age or 18 weeks of age. RNA-seq resulted in 6091 significantly DEGs were obtained between three fed groups; 2821, 2825, 445 significantly DEGs between the fed groups AL-CCR, CCR-ICR, AL-ICR, respectively. These DEGs were annotated into molecular function, cellular component and biological process GO terms. DEGs in “immune system process (GO:0002376)” GO term were obtained for fed groups. According to these results, 188, 36, 176 differential immune-related genes were determined between AL-CCR, AL-ICR, CCR-ICR fed groups, respectively. These results show that CR and/or the types of calorie consumption have a great effect on immune system. Compared to AL group, although only 15% of CR was applied to CCR fed group, 188 significantly immune-related DEGs were shown between AL and CCR fed groups. Besides, 36 significantly immune-related DEGs were obtained between AL and ICR groups. When the feeding cycle considered, ICR group had 2 weeks of CR (60%) in total of two complete feeding cycles compared to AL. This might suggest that most of the genes were not instantly affected from restriction or they were recovered immediately due to AL feeding part of the cycle. The number of immune-related DEGs were higher in between AL-CCR and CCR-ICR fed groups, than between AL-ICR fed groups. This shows that the expression of immune system genes were regulated up or down by feeding. Moreover the number of up or down regulated genes was more due to chronic but mild feeding restriction compared to severe and acute application.
In this study, Thy1, IL-16, CD4 and Casp3 which play important roles in immune response have been reported as determining expression level in RNA-seq data and qPCR. Expression levels of these genes reduce in CCR fed. Also, many studies have reported decreased level of Thy1, IL-16, CD4 and Casp3 with CR [35], [36], [37]. Because, CR is an intervention that dramatically decreases fat mass, helps prevents age-associated diseases, and prolongs lifespan [38]. So, CR decreases disease-associated increases immune genes mRNA levels [39]. Our results showed that the expression level of Thy1, IL-16, CD4 and Casp3 genes in the thymus tissue reduced with CR. These results indicate that application of short-term CR during early age may affect development of immune function positively and Casp3, Thy1, IL-16 and CD4 gens may play important roles in this process.
Acknowledgments
This work was supported by Yildiz Technical University Scientific Research Projects Coordinator (Grant 2016-01-07-DOP01). The animal experiments were supported by The Scientific and Technological Research Council of Turkey (TUBITAK 114S429). The authors thank Dr. Margot P. Cleary for generously donating the breeding colony of the MMTV-TGF-α transgenic mice. The authors thank Munevver Burcu Cicekdal, Ilker Coban, Busra Kazan, and Mustafa Erhan Ozer for overseeing the breeding and genotyping protocols to obtain the experimental animals. The authors also thank the veterinarian and animal technicians who handle the animals at Yeditepe University Animal Facility (YUDETAM).
Conflicts of interest statement: The authors declare that they have no conflicts of interest.
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©2019 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Review Article
- Does vitamin D prevent radiotherapy-induced toxicity?
- Research Articles
- Compliance of medical biochemistry education in medical schools with national core education program 2014
- The importance of parathormone in determining the deficiency of vitamin D
- Association between serum vitamin D level and liver MRI T2 star in patients with β-thalassemia major
- Role of O-GlcNAcylation and endoplasmic reticulum stress on obesity and insulin resistance
- Effects of cellular energy homeostasis modulation through AMPK on regulation of protein translation and response to hypoxia
- Perceived barriers to diabetes management at home: a qualitative study
- The effect of automated hemolysis index measurement on sample and test rejection rates
- Identification of immune-related genes in thymus of breast cancer mouse model exposed to different calorie restriction
- Effect of xylitol on gut microbiota in an in vitro colonic simulation
- Fibrinopeptide-A and fibrinopeptide-B may help to D-dimer as early diagnosis markers for acute mesenteric ischemia
- Plasma homocysteine and aminothiol levels in idiopathic epilepsy patients receiving antiepileptic drugs
- Apelin-13 serum levels in type 2 diabetic obese women: possible relations with microRNAs-107 and 375
- An evaluation of biomarkers indicating endothelial cell damage, inflammation and coagulation in children with Henoch-Schönlein purpura
- Enteroprotective effect of Tsukamurella inchonensis on streptozotocin induced type 1 diabetic rats
- The in vitro cytotoxicity, genotoxicity and oxidative damage potential of dapagliflozin, on cultured human blood cells
- Investigation and isolation of peptide based antiglycating agents from various sources
- Effect of skin-to-skin contact on the placental separation time, mother’s oxytocin and pain levels: randomized controlled trial
- The protective role of oleuropein against diethylnitrosamine and phenobarbital induced damage in rats
- Letter to the Editor
- ICD code specific reference ranges
Articles in the same Issue
- Frontmatter
- Review Article
- Does vitamin D prevent radiotherapy-induced toxicity?
- Research Articles
- Compliance of medical biochemistry education in medical schools with national core education program 2014
- The importance of parathormone in determining the deficiency of vitamin D
- Association between serum vitamin D level and liver MRI T2 star in patients with β-thalassemia major
- Role of O-GlcNAcylation and endoplasmic reticulum stress on obesity and insulin resistance
- Effects of cellular energy homeostasis modulation through AMPK on regulation of protein translation and response to hypoxia
- Perceived barriers to diabetes management at home: a qualitative study
- The effect of automated hemolysis index measurement on sample and test rejection rates
- Identification of immune-related genes in thymus of breast cancer mouse model exposed to different calorie restriction
- Effect of xylitol on gut microbiota in an in vitro colonic simulation
- Fibrinopeptide-A and fibrinopeptide-B may help to D-dimer as early diagnosis markers for acute mesenteric ischemia
- Plasma homocysteine and aminothiol levels in idiopathic epilepsy patients receiving antiepileptic drugs
- Apelin-13 serum levels in type 2 diabetic obese women: possible relations with microRNAs-107 and 375
- An evaluation of biomarkers indicating endothelial cell damage, inflammation and coagulation in children with Henoch-Schönlein purpura
- Enteroprotective effect of Tsukamurella inchonensis on streptozotocin induced type 1 diabetic rats
- The in vitro cytotoxicity, genotoxicity and oxidative damage potential of dapagliflozin, on cultured human blood cells
- Investigation and isolation of peptide based antiglycating agents from various sources
- Effect of skin-to-skin contact on the placental separation time, mother’s oxytocin and pain levels: randomized controlled trial
- The protective role of oleuropein against diethylnitrosamine and phenobarbital induced damage in rats
- Letter to the Editor
- ICD code specific reference ranges
