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/lp/springer-journals/examination-of-the-xanthosine-response-on-gene-expression-of-mammary-OBsHnlX7il
- Publisher
- Springer Journals
- Copyright
- Copyright © 2018 by The Author(s).
- Subject
- Life Sciences; Animal Genetics and Genomics; Agriculture
- eISSN
- 2055-0391
- DOI
- 10.1186/s40781-018-0177-5
- Publisher site
- See Article on Publisher Site
Abstract
Background: Xanthosine treatment has been previously reported to increase mammary stem cell population and milk production in cattle and goats. However, the underlying molecular mechanisms associated with the increase in stem cell population and milk production remain unclear. Methods: Primiparous Beetal goats were assigned to the study. Five days post-partum, one mammary gland of each goat was infused with xanthosine (TRT) twice daily (2×) for 3 days consecutively, and the other gland served as a control (CON). Milk samples from the TRT and CON glands were collected on the 10th day after the last xanthosine infusion and the total RNA was isolated from milk fat globules (MEGs). Total RNA in MFGs was mainly derived from the milk epithelial cells (MECs) as evidenced by expression of milk synthesis genes. Significant differentially expressed genes (DEGs) were subjected to Gene Ontology (GO) terms using PANTHER and gene networks were generated using STRING db. Results: Preliminary analysis indicated that each individual goat responded to xanthosine treatment differently, with this trend being correlated with specific DEGs within the same animal’s mammary gland. Several pathways are impacted by these DEGs, including cell communication, cell proliferation and anti-microbials. Conclusions: This study provides valuable insights into transcriptomic changes in milk producing epithelial cells in response to xanthosine treatment. Further characterization of DEGs identified in this study is likely to delineate the molecular mechanisms of increased milk production and stem or progenitor cell population by the xanthosine treatment. Keywords: Goat, Milk fat globule, RNA sequencing, Xanthosine, RT-qPCR Background xanthosine (XS) into lactating cow, has been shown to Purine nucleoside xanthosine (XS) when added to asym- increase mammary stem cell population and has been metrically dividing stem cells, induceds a transition to hypothesized to increase milk production [2]. Contrar- symmetrical division, which ultimately leads proliferation ily, xanthosine treatment shown to have no effect on of stem cells. Suppression of asymmetrical division of cells mammary stem cell population [3]. Therefore, to make by XS is regulated through inosine monophosphate de- a distinct and clear effects of XS on mammary gland, hydrogenase (IMPDH) in p53 dependant fashion [1]. more research are warranted. XS is converted into xanthosine 5′-monophosphate Milk is secreted by the mammary epithelial cells (XMP) by the enzyme IMPDH. Thus, XS has the essential (MECs), which are gradually exfoliated during lactation. role in IMPDH regulation. The intramammary infusion of Because of the gradual exfoliation and constant replen- ishment of these MECs, it is likely that gene expression differences in these cells may be major contributors to * Correspondence: vetdrrkc@gmail.com the overall process of lactation. Several methodologies School of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab 101004, India have been developed to isolate and enrich MECs from Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 2 of 12 mammary glands for transcriptional profiling of MEC. additional injection of 1 mL XS was administered intra- One methodology involves the surgical biopsy of mam- parenchymally according to the methods used in a mary tissue followed by the preparation of singular cell similar study [2]. For each goat, one mammary gland suspension and in vitro propagation of MECs in culture was treated with XS while the other gland was used as [4]. Alternatively, immunomagnetic methods of MEC control (CON) and was not infused with XS. One week cell seperatation from milk somatic cells have also been after the last XS injection, milk was collected for RNA attempted by several studies [5, 6]. Recently, non-invasive isolation from both the TRT and CON glands of each approaches of extracting MECs from milk have been de- animal. veloped that involve the capture of milk fat globules (MFG) from the milk fat layer. These MFGs contain MEC Milk image analysis cytoplasmic remnants, called crescents, due to their moon Freshly collected milk were mixed with 0.1 0.1% acridine shaped appearance under the light microscopy [7]. The orange (AO) and incubated for 5 min at room percentage of MFG crescents in milk varied among the temperature to stain nucleic acids (DNA and RNA). A mammalian species with a high percent volume (3–8%) 10 μL of AO-stained milk were placed onto positive in human milk to a low percent volume (< 1%) in cattle charged slides and covered with a coverslip which was [8, 9]. MFG crescents, being its cytoplasmic origin, are then sealed with nail polish to prevent milk evaporation. a source of MEC-specific RNA. In the analysis of the Slides were viewed immediately on an inverted fluorescent human MFG transcriptome using microarrays and microscope (Nikon Eclipse 90i, Tokyo, Japan). Two images RNA-sequencing, it has been confirmed that the MFG were captured for each slide, a red fluorescence channel transcriptome include genes uniquely expressed in the TRITC for AO-intercalated RNA, and a green fluores- MEC [7, 10, 11]. These studies have established MFGs cence channel FITC to view AO-intercalated DNA. as areliablesourcefor MEC-specific geneexpression AO-stained milk Images were analyzed using Fiji as analysis during lactation. described earlier [8]. The accuracy of this method was The main aim of the present study was to identify confirmed manually by comparing a subset of processed XS-induced, gene expression differences in MECs by deep and original images. Overlays of the AO- RNA channel sequencing of the total RNA associated with MFG during (Red) with the AO-DNA channel (green) images were early lactation in Beetal goats. Using RNA-sequencing, we analysed using Fiji [12](Fig. 1). sought to identify the differentially expressed genes (DEGs) between XS treated (TRT) and control glands RNA isolation from milk fat globules (CON). Additionally, using reverse transcriptase quantita- Total RNA was extracted using a combination of Trizol tive PCR (RT-qPCR), we sought to confirm observed (Invitrogen, Carlsbad, CA, USA) and GenElute Mam- differential gene expression and fully characterized the malian Total RNA isolation kit (Sigma, St. Louis, MO, transcript abundance of genes of interest. USA) as published earlier [13]. Briefly, for each 40 mL milk sample after centrifugation, 500–700 μgofmilk Methods fat was collected using a 1 mL sterile microtip, and put Animals and experimental design into a 5 mL nuclease free tube (Genaxy Scientific Pvt. Use of goats for this study was approved by the Ltd. New Delhi, India) containing 1.5 mL of Trizol™ “Committee for the Purpose of Control and Supervision reagent (ThermoFisher Scientific, Waltham, USA). The of Experiments on Animals” (CPCSEA; reference no. milk fat was homogenized in Trizol for 2–3minby 25/20/2016), Ministry of Environment, Forest and vortexing. The homogenized mixture was incubated at Climate Change (Animal Welfare Division), New Delhi. room temperature (RT) for 3 min and stored at − 80 °C Eight primiparous Beetal goats were used in this experi- for further use. The homogenates were thawed quickly ment. A 20 mL suspension of 10 mM XS was infused by rubbing with palm, vortexed briefly and centrifuged through the teat canal and 1 mL of intra-parenchymal at 12000 x g for 5 min at 4 °C to remove excess fat (on injection was given to one randomly chosen mammary top). Clean homogenate (mid layer) was transferred gland (half udder) for 3 consecutive days, twice daily into a new, 2 mL RNAase-free tube, containing 300 μL (once in the morning, and once in the evening immedi- of chloroform (HiMedia Laboratories Pvt. Ltd. Mumbai, ately after milking). Complete milk removal was per- India). After vigorous shaking for 30 s, the mixture was formed for each TRT glands, followed by the insertion incubated at RT for 10 min for complete solubilization of a sterile 20 gauge blunt needle into the teat canal to of fat. Tubes were centrifuged at 12000 x g for 15 min extract all of the remaining milk secretion. The XS at 4 °C. A 300 μL of the clear supernatant was used for powder was diluted in sterile saline and sterilized with total RNA extraction using the GenElute Mammalian a0.22 μm filter before infusions. To ensure the delivery Total RNA isolation kit, following the manufacturer’s of XS into the peripheral regions of the glands, an instructions. RNA quantity was measured using a Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 3 of 12 Fig. 1 Image analysis of goat milk with acridine orange (AO) to visualize milk fat globules (MFG) and crescents associated with MFG. Each image contained two channels one for DNA (green) and the other for RNA (red). DNA appered green under FITC channel (a) wherease, RNA appered red under the TRITC channel (b). Dark sphereical like structures of MFG are evident. Grey images are extracted from both the channels (c and c, respectively) and merged together (e) to show the presence of crescents over MFG. These crescents and membrance over MFG were source of mammary epithelial cell specific RNA NanoDrop 1000 (ThermoFiesher Scientific, Waltham, 5–10 μg of total RNA was isolated and prepared using a USA). RNA integrity was determined using a Tapesta- TruSeq RNA sample preparation kit V2 (Cat:RS-122-2001, tion (Agilent Technologies, Santa Clara, USA) before Illumina, San Diego, CA, USA). Size distribution of the the samples were processed for RNA sequencing. sequencing library was determined by gel electrophoresis. Library quantification was done using Qubit 3.0 fluoromet- Library preparation and RNA sequencing ric quantitation system (ThermoFisher Scientific, Waltham, Library preparation, quality control, sequencing and data USA). Paired-end sequencing was performed on Illumi- analysis were performed at a commercial sequencing na’s HiSeq 2500 platform. Approximately 40 million facilty (SciGenome, Kochi, India). Due to budget con- paired-end, 2 × 100 bp reads were generated for each straints and feasibility of RNA sequencing of milk fat sample. Raw fastq files have been submitted to NCBI derived RNA, only four libraries (two XS treated- 741 L Sequence Read Archive (SRA) database with the study and 647 L and two control- 741R and 647R) were consid- accession PRJNA389156 (https://www.ncbi.nlm.nih.gov/ ered from two individual goats. To generate each library, bioproject/PRJNA389156/). Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 4 of 12 RNA-sequencing quality control, read mapping and data performed with the following cycling conditions: 95 °Cfor analysis 3 min; 340 repeating cycles of 95 °C for 10 s (denaturation) Initial checking of raw sequences for the quality has at respective annealing temperature (Additional file 1: been performed by the sequencing vendor. Briefly, Table S1) for a set of primers for 30 s (annealing); reads containing adaptors were filtered from the data- 95.0 °C for 3 min, 65.0 °Cfor 30s, andthena set. To avoid base composition bias, 12 bases were temperature increase at 0.5 °C increment to 95.0 °C trimmed at the 5′ end of both read pairs. RNA sequen- (melting curve). Each assay included a no-template cing read quality checks included base quality score control and a no reverse-transcriptase control. For no distribution, sequence quality score distribution, aver- template control, 1 μLofRNase/DNase free waterwas age base content per read, GC distribution in the read used as template. For the no reverse-transcriptase con- and occurrence of over-represented sequences. Raw trol, reverse-transcriptase enzyme was excluded during reads were filtered when the average of their base qual- cDNA synthesis and resultant cDNA used as template. ity scores was less than 20. Processed reads were A total set of 22 genes were selected for RT-qPCR aligned to the goat reference genome downloaded from analysis. Genes that are expressed in MEC during lacta- NCBI (GCA_001704415.1_ARS1) [14]. Sequencing tion and affected by the XS treatment, were selected as reads from non-coding RNAs were excluded from the candidate genes for RT-qPCR analysis. A subset of DEGs analysis. Sequence alignment was performed using the obtained from RNA-seq data were also selected to STAR program (ver.2.5.2b). Two methods were used validate the sequencing data. The RPL4 and RPS23 were for differential gene expression analysis. First, the quan- selected as reference genes as reported in earlier study tification of the raw expression of genes and transcripts [18]. Threshold (Ct) values of target genes were nor- was performed using the cufflinks program (ver. 2.2.1). malized to the geometric mean of two reference genes The expression values were normalized to a FPKM to obtain ΔCt values (target gene Ct – reference gene (fragment per kilo per million) value for each of the mean Ct = ΔCt) [19]. All reactions were conducted in genes and transcripts. Differential expression analysis duplicate and Ct values were averaged for each tested was performed using cuffdiff program within the cuf- gene-condition-sample combination. flinks package. Second, Deseq2 [15] was also used to identify significant differentially expressed genes. In this Statistical analysis analysis, RUVseq [16] was used to remove any potential For the functional annotation and pathway analyses of unwanted variation in gene quantification using several RNA-seq data, pathways were tested for statistical signifi- housekeeping genes. We compared the mRNA profile cance using a false positive threshold of 0.05 after Bonfer- of TRT samples to that of the CON samples. A total of roni’s correction. For the RT-qPCR data analysis, the raw four mRNA sequence datasets (741 L, 741R, 647 L and ΔCt values of genes were log transformed after discover- 647R, as described in previous section) were used. ing that their values were not normally distributed (esti- mated by Shapiro Wilk’s Test; data not shown). Paired cDNA synthesis and RT-qPCR t-tests were employed to test significant differences among First-strand cDNA was synthesized from 1000 ng of gene-condition comparisons. Data were analysed using total RNA using iScript Reverse Transcription Super- the SPSS ver. 22 (IBM SPSS Statistics for Windows mix (BioRad Laboratories, CA, USA) according to the Armonk, NY). A p-value < 0.05 were considered statisti- manufacturer’s instructions. Resultant cDNA was stored cally significant value. at − 20 °C. The RNA isolated from MFG was used to quantify changes in gene expression by real time thermo- cycler (CFX96 Touch™ Real-Time PCR) using iTaq™ Uni- Results versal SYBR Green Supermix (BioRad Lab. California, Total RNA extraction from milk fat USA). Gene specific primers were designed on the basis of We obtained a high quality of total RNAs from goat milk goat reference mRNA sequence obtained from NCBI fat. The total RNA concentration averaged 770.12 ± using NCBI Primer-BLAST following guidelines described 754.7 ng/μl (mean ± SD). RNA extraction protocol pro- previously [17]. Desalted oligos (25 mM) were pur- vided high purity for extracted RNA having optical density chased from Integrated DNA Technologies (IDT Inc., (OD) ratios of 260/280 and 260/230 to 2.04 ± 0.04 and Iowa, USA). 1.84 ± 0.38 (mean ± SD), respectively. All the RNA sam- Each 10 μL of PCR reaction contained each 0.25 μLof ples of goat milk fat were suitable for RT-qPCR analysis. forward and reverse primers (2.5 pmol), 5 μL of Brilliant Samples having RNA integrity numbers (RIN) greater III Ultra-Fast SYBR® QPCR (Agilent Technologies, Santa than 7 were sent for RNA sequencing. RIN of other RNA Clara, USA), 3 μL of cDNA (1:10 dilution) and 1.5 μLof samples were between 6 and 7 and were suitable for nuclease free water. Two-step RT-qPCR assays were RT-qPCR analysis. Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 5 of 12 RNA-seq and mammary transcriptome involved in cellular process (GO:0009987), metabolic Four RNA samples (RIN > 7.0) were selected for RNA process (GO:0008152) and cellular component organization sequencing from an initial group of 16 samples. The (GO:0071840) (Fig. 2b). Additionally, milk protein genes percentage of mapped reads to the ARS1 goat reference (LALBA, CSN2, CSN3, PAEP, CSN1S1)werehighly assembly [14] averaged 93.4 + 2.1 (Mean ± SD) for each expressed in both the TRT and CON groups. sequenced sample. There were 10,267 to 11,470 genes per sample with an FPKM value ≥ 0.2, indicating some Functional annotation of differentially expressed genes level of detectable transcription (Table 1). Functional (DEGs) annotation of these transcripts were enriched for cellular A total of 58 genes were differentially expressed MEC and metabolic pathways that were involved with catalytic after XS treatment of mammary glands. A majority of and binding activities (Additional file 1: Table S2). In each DEGs (46) were found to be down-regulated after XS of the four RNA sequencing samples, majority of the tran- treatment whereas 12 genes were up-regulated (Table 2). scripts were lowly expressed (FPKM < 15; 84.3%). One Pathway analysis of DEG showed enrichment of genes for animal (741) had fewer number of DEG than the other the following biological processes: defense response to tested sample (647). This discrepancy could have been other organsm, cytokine regulated signalling pathway, influenced by the difference in animal genetics, or due to regulation of the response to other stimuli, regulation of the differences in mammary gland permeability that cytokine production, and response to endogenous stimu- allowed xanthosine to diffuse into the CON gland. For lus. The most prevalent GO-CC (cellular component) abundantly expressed genes (FPKM ≥ 500), we observed terms were associated with the cell surface (10 genes) and an enrichment of cellular and metabolic processes (on the the plasma membrane (15 genes). Among the 10 basis of PANTHER classification system). Transcripts cor- up-regulated genes, both B2M and LTF are of particular responding to milk protein genes (CSN3, LALBA, PAEP, interest. Our data did not show the up-regulation of heat GLYCAM1, TPT1, PLIN2 and FABP3) were the most shock protein genes in the TRT glands, suggesting that XS abundantly expressed genes. Our study showed high ex- infusion did not cause mammary tissue damage. pression of perilipin 2 (PLIN2- a protein involved in milk PANTHER pathway enrichment analyses showed fat globule formation), fatty acid binding protein (FABP3), down-regulation of inflammation signaling pathway medi- and many ribosomal proteins during early lactation in ated by chemokine and cytokine (CXCR1, CXCR2, PTAFR, goats. The PLIN2 gene abundantly expressed in macaque RGS14, C5AR and JUNB) in TRT group. Notably, adhesion milk (Lemay et al., 2013) and FABP3 gene in cattle [20]. molecules (PECAM1, SSH2, SYNE1, CYTIP, SELL)were down-regulated upon XS treatment. Next, we investigated Functional annotation analysis of abundantly expressed protein-protein interactions of DEGs using the STRING genes database. Out of 58 DEGs, STRING identified only 47 hu- To characterize functions of most abundantly expressed man homologs for calculating protein-protein interaction genes (FPKM ≥500), list of genes were subjected to gene with a predicted confidence score of > 0.4. The interaction ontology (GO) classification and functional analysis enrichment analysis result showed that the network has using PANTHER [21]. In the TRT group, three key significantly more interactions (PPI enrichment p-value genes, GNB2L1, EEF1B2 and TPT1, encode key 2.3e-09) than the expected and the entire network con- ribosome-associated proteins (Fig. 2a). Consistently, tained three sub-divisions (Fig. 3) indicative of three distinct KEGG pathway analysis showed significant enrichment biological processes. of ribosome-associated gene families, including the structural constituents of ribosomal genes (RPL4, RT-qPCR confirmation of genes of interest RPS9, RPS10 and other ribosomal genes). Our data in- An elaborate RT-qPCR analyses of many target genes dicated that the highly expressed genes are mainly were done for three explicit purposes: 1) to validate Table 1 Whole transcriptomic signature (FPKM ≥ 0.2) of milk fat globules RNA expressed in xanthosine treated (TRT) and control glands (CON) during early lactation of Beetal goats # of genes 647 L (TRT) 647R (CON) 741 L (TRT) 741R (CON) Mean of all four samples Abundantly expressed 112 110 115 111 112 (1%) Moderately expressed 171 203 186 178 184.5 (1.7%) Rarely expressed 1253 1564 1402 1402 1405 (12.9%) Very rarely expressed 8731 9593 9171 9162 9164 (84.3%) Total number of genes 10,267 11,470 10,874 10,853 10,866 Difference in # of genes between TRT and CON glands 1203 21 Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 6 of 12 Fig. 2 Categorization of abundantly expressed genes based on GO:Biological Process. Abundantly expressed genes of TRT group showing strong hub of ribosomal pathway (a) and their Molecular Function (b). Likewise, in CON group ribosomal pathway (c) and majority of these genes were involved with cellular and metabolic process (d) similar to TRT group RNAseq data; 2) to assess whether MFG RNA are quantita- Our RT-qPCR experiments validated many of our tively representative of the transcriptional information con- findings. We confirmed an absence of expression of tained in MEC; and 3) to assess the potential effect of XS stem cell markers (HNF4A NR5A2, MSI1, FNDC3B) that on milk production. Major milk protein genes (LALBA and were not present in RNA-seq data. Among the list of CSN2), steroid receptors (ESR1 and PRB), proliferation DEGs, lactotransferrin (LTF) was up-regulated whereas, (PCNA) and apoptosis marker (TP53) and cell differenti- Fos proto-oncogenes (FOS) was down-regulated in TRT. ation marker (MUC1) were analysed in addition to DEGs. RT-qPCR analyses showed similar pattern of expression Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 7 of 12 Table 2 List of differentially expressed genes (DEGs) of goat mammary epithelial cells after xanthosine infusion into the gland Genes log2 Fold Change p-value Name of protein 1. CXCR2 −1.017323 3.11E-05 C-X-C Motif Chemokine Receptor 2 2. SAMD9 −0.8044989 0.00048 Sterile alpha motif domain-containing protein 9 3. LOC102168687 −0.798857 0.00067757 interferon-induced protein with tetratricopeptide repeats 1 4. FOS −0.7106714 0.00150655 Proto-oncogene c-Fos 5. LOC106502722 −0.706349 0.00609026 elongation factor 1-alpha 1 pseudogene 6. CXCR1 −0.7019749 0.00156437 C-X-C Motif Chemokine Receptor 1 7. MXD1 −0.6870472 0.00377718 Max dimerization protein 1 8. TNFRSF1B −0.6679126 0.00536264 Tumor necrosis factor receptor superfamily member 1B precursor 9. CLEC5A −0.6519524 0.00334639 C-type lectin domain family 5 member A 10. ANTXR2 −0.6468424 0.00671523 Anthrax toxin receptor 2 precursor 11. EMB −0.6415234 0.00454368 Embigin 12. LOC102180659 −0.6380424 0.01443435 elongation factor 1-alpha 1 pseudogene 13. PLEK −0.6376403 0.00658301 Pleckstrin 14. DUSP1 −0.6345636 0.00825818 Dual specificity protein phosphatase 1 15. IFIT1 −0.6331932 0.00311884 subfamily A member 5 16. PECAM1 −0.6115827 0.00567366 Platelet endothelial cell adhesion molecule 17. FAM65B −0.6020531 0.01551968 Protein FAM65B 18. ISG15 −0.591961 0.00810711 Ubiquitin-like protein ISG15 19. NCF2 −0.5901478 0.00763365 Neutrophil cytosol factor 2 20. C5AR2 −0.5877041 0.00674769 Complement Component 5a Receptor 2 21. SAMSN1 −0.5803822 0.0086767 SAM domain-containing protein SAMSN-1 22. MX1 −0.5801172 0.01102704 Interferon-induced GTP-binding protein Mx1 23. PTAFR −0.5571907 0.00830068 Platelet-activating factor 24. VSIR −0.546773 0.02426786 V-Set Immunoregulatory Receptor 25. JUNB −0.5417107 0.0151331 Transcription factor jun-B 26. PLAU −0.5322312 0.00924439 Urokinase-type plasminogen activator 27. RSAD2 −0.5225815 0.01513903 Radical S-adenosyl methionine domain-containing protein 2 28. DUSP2 −0.5221989 0.01338515 Dual specificity protein phosphatase 2 29. HCLS1 −0.5198929 0.00978145 Hematopoietic lineage cell-specific protein 30. SSH2 −0.519027 0.01453977 Slingshot Protein Phosphatase 2 31. SYNE1 −0.5130198 0.04286633 Spectrin Repeat Containing Nuclear Envelope Protein 1 32. NOTCH1 −0.5090343 0.01658702 Notch 1 protein receptor 33. CYTIP −0.5084053 0.01266586 Cytohesin-interacting protein 34. SELL −0.4994215 0.01581525 L-selectin precursor 35. THBS1 −0.4897332 0.02190149 Thrombospondin-1 precursor 36. LDH-A −0.4831976 0.06139028 Lactate Dehydrogenase A 37. PSTPIP2 −0.4826517 0.02163436 Proline-serine-threonine phosphatase-interacting protein 2 38. ARHGAP45 −0.4824378 0.02094921 Rho GTPase Activating Protein 45 39. HCAR2 −0.4787442 0.03908657 Hydroxycarboxylic Acid Receptor 2 40. HCK −0.4786929 0.0215455 Tyrosine-protein kinase HCK isoform 2 41. ADGRE1 −0.4760767 0.01657563 Adhesion G Protein-Coupled Receptor E1 42. HK3 −0.4725703 0.0154585 Hexokinase-3 43. RGS2 −0.4722578 0.05622303 Regulator of G-protein signaling 2 44. RGS14 −0.4673717 0.02127159 Regulator of G-protein signaling 14 Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 8 of 12 Table 2 List of differentially expressed genes (DEGs) of goat mammary epithelial cells after xanthosine infusion into the gland (Continued) Genes log2 Fold Change p-value Name of protein 45. TMEM154 −0.4579886 0.07281125 Transmembrane Protein 154 46. C5AR1 −0.4556632 0.02037596 Complement C5a Receptor 1 47. MBLAC2 0.40364221 0.12046919 Metallo-beta-lactamase domain-containing protein 2 48. B2M 0.4105621 0.09027626 beta-2-microglobulin 49. LOC108635405 0.4289959 0.08146865 collagen alpha-1(II) chain-like 50. TAF15 0.43142113 0.0956541 TATA-Box Binding Protein Associated Factor 15 51. COX7A2 0.46584597 0.07022808 cytochrome c oxidase subunit 7A2 52. LOC108635296 0.50689456 0.03272288 collagen alpha-1(I) chain-like 53. LTF 0.54549056 0.03459662 Lactotransferrin Lactoferricin-B 54. LOC108635078 0.55728309 0.0257517 basic proline-rich protein-like 55. RPL37A 0.60565486 0.01970951 putative 60S ribosomal protein L37a 56. LOC108634776 0.6232389 0.00864377 zinc finger protein 532-like 57. LOC108634774 0.70202338 0.00454456 collagen alpha-1(I) chain-like 58. LOC108635079 0.71456286 0.00591021 basic salivary proline-rich protein 1-like Fig. 3 Visualization of protein interaction neworks of diffentially expressed genes between the TRT and CON group. Network showing 3 k-means clustering indicated by three different colors and their interactions Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 9 of 12 as observed in DEG of RNA-seq data. However, our An advantage of our study is that XS treated (TRT) and qPCR result was not consistent with the RNA-seq ex- control (CON) glands were present with the same goat. pression results of JUNB and PECAM1 genes. This dif- This should reduce any biological bias resulting from the ference may be attributed because of low abundance of sampling of different individual goats due to different transcripts that limits the detection by qPCR. We also genetic profiles. Thus, our experimental method captured failed to amplify two genes, SELL and THBS1, using true variation in milk producing cells affected by XS RT-qPCR (Fig. 4). Later, we confirmed the extremely low treatment, with less noise due to a different genetic abundance of SELL and THBS1 gene transcripts in milk background of sampled individuals. However, we cannot fat RNA using droplet digital PCR (data not shown). entirely rule out genetics as a major determinant of XS treatment response as our data also indicated that there is Discussion an individual-specific responses. This finding should be The effects of XS treatment in the culture of bovine mam- considered and evaluated for the future application of XS mary epithelial cells have been shown, in vitro, to increase treatment in goats and other dairy animals for milk cell population and enhance symmetric cell division [22]. production. A non-invasive, in vivo method is desirable for under- Several genes, LALBA (α-lactalbumin), CSN2 (β-casein), standing the role of XS treatment in promoting mammary CSN1S1 (α-S1-casein), CSN3 (κ-casein), GLYCAM1 epithelial cell proliferation, as an increase in the popula- (glycosylation dependent cell adhesion molecule-1) and tion of such cell is directly associated with milk producing CSN1S2 (casein-α-S2), were abundantly expressed in ability of the glands [23]. A milk-based assay could be sheep mammary gland during lactation [29]. In our study, used to track gene expression of milk producing mam- these genes are among the highest expressed genes found mary epithelial cells [11]. It has been well documented by in our milk fat samples during early lactation. Addition- many researchers that the milk fat fraction is rich in RNA ally, we observed abundant expression of tumor protein transcripts specific to mammary epithelial cells, as these translationally-controlled 1 (TPT1), fatty acid binding are devoid of stromal cells, nerve cells, endotheial cells, fat protein 3 (FABP3), perilipin 2 (PLIN2) and ribosomal cells and inflammatory cells [24]. Though the number of proteins, which were among the top 20 abundantly cytoplasmic crescents in ruminant milk is fewer in count expressed genes of goat mammary gland (Additional file than it is in human and macaque milk, the sensitivity of 1: Table S3). FABP3 protein is a candidate for tumor sup- our RNA-seq analysis of milk fat isolates meant that our pressor of human breast cancer with a suggested role in study was not limited by the lower proportion of cyto- arresting growth of mammary epithelial cells. TPT1 has plasmic crescents in goat milk [25]. We demonstrate been shown to reduce oxidative stress, minimize apotosis that this method provides abundant quantity and good and promote cell survival in a p53-dependant manner quality of RNA suitable for RNA sequencing. This [29]. PLIN2 is associated with MFG membrane and found shows consistency with the findings of other studies, in in a wide variety of cells, including lactating mammary which milk fat has been used to assess the transcrip- epithelial cells. Additionally, PLIN2 regulates lipid and tome profile of milk production related genes in human protein metabolism in lactating dairy goats [30]. It is sug- [7], buffalo [26], bovine [27]and goat [28]. gested that elevated expression of TPT1, PLIN2 and Fig. 4 Validation of genes of interest by RT-qPCR. Genes which were abundantly expressed and did not expressed in RNAseq data were validated. Furthermore, differentially expressed genes of RNA-seq date were analyzed to validate RNA-seq data Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 10 of 12 FABP3 might play a role in suppressing goat mammary which is mediated by chemokine and cytokine detection tumor formation. Precisely, the role of FABP3 has been by the cells. When activated, this pathway could pro- associated to import/export of fatty acids in the cell and mote chemokine-induced adhesion and migration of highly upregulated during bovine lactation [31]. Although, leukocytes in the local tissue. We hypothesize that the reports on the incidence of mammary tumors in rumi- down regulation of inflammatory signaling pathways in- nants are rare [32], our group has encountered duced by XS, could prevent the excessive recruitment epithelial-mesenchymal transition, mammary epithelial of leukocytes to inflammatory sites. XS up-regulated cell hyperplasia and mammary pre-cancer in both goats expression of anti-bacterial genes (LTF and B2M), and water buffalo [33, 34] with no sign of mammary tissue which may be beneficial to the host by preventing the damage. incidence of mastitis. The Beta-2-microglobulin (B2M) We found that XS administration twice a day for 3 days gene codes for a protein that is associated with the consecutively, altered the gene expression in TRT glands major histocompatibility complex class 1 (MHC I) and in goats compared to an non-inoculated CON gland on is a precursor of an anti-bacterial chemokine [37]. Lacto- the same animal. Differential response of XS treatment transferrin (LTF) is a gene that encodes a major iron bind- was evidenced by varied number of DEGs between TRT ing milk protein. LTF has a wide spectrum of properties and CON glands. The duration of XS administration that include anti-bacterial, anti-viral, and anti-cancer ac- (3 days) was based on an inosine study conducted in tivities and is involved in the regulation of cellular growth transgenic goat [35]. XS did prouduce deleterioius [38]. Future experiments are warranted to further investi- effects to the gland neigther causes any inflammatory gate whether XS inoculation may increase general mam- reactions. We observed absence of mesenchymal cell mary gland health in ruminants. marker (VIM), and inflammatory markers (TLR4, In our candidate gene expression analysis using CXCL14 and CXCR1) amplification in the RNA har- RT-qPCR, we found increased expression of ALDH1A1, a vested from mlk fat layer, indicating XS did not cause mammary stem marker [39], in the TRT. We were unable MEC inflammation. A pronounced effects of XS treat- to amplify two DEGs namely, SELL and THBS1 in ment on goat milk production may require further RT-qPCR. One possibility for the inconsistency could be optimization of XS dose and duration, and may need to the low amount of transcripts in our cDNA, evidenced by account for animal genetic variation. It is also imperative Ct value of these target genes > 35 cycles. In comparison to note that a comparison of effects of inosine and to RNA-seq, RT-qPCR has less sensitivity in accurately de- xanthosine should be tested individually to evaluate if in- tecting low abundance transcripts. Droplet digital PCR osine administration is more suitable for enhancing milk (ddPCR) is useful for low abundance targets and is better production. In using Beetal goats as a test subject, the than the qPCR [40]. This observation supports the facts disparity of left and right mammary half gland should be that mammary stem cells and progenitor cells may be considered for evaluation of true milk production poten- present in the milk [41, 42]. However, we failed to quantify tials. The down-regulation of a dominant portion (48 out the transcripts of other putative mammary stem cell 58) of the identified DEGs, like FOS, PECAM1, JUNB, markers. Absence of basal or mesenchymal cell marker SELL, THBS1, indicated XS primarily down-regulates the gene (vimentin or VIM) expression in our study indicated expresson of genes. Platelet and endothelial cell adhesion that RNA extracted from milk fat is specific to luminal molecule (PECAM1), selectin L (SELL) and Thrombos- mammary epithelial cells but not the basal or myopethelial pondin 1 (THBS1) are the cell surface adhesion molecules cells. VIM is a basal or myoepithelal cell marker. Absence that mediates cell-to-cell and cell-to-matrix intereactions. of expression of inflammatory markers (TLR4, CXCR1, Down-regulation of cell adhesion molecules is typically as- CXCL14) provided the evidence that RNA harvested from sociated with an inhibition of cell growth [36]. Due to the milk fat is mainly derived from epithelial cells but not limited number of goats used in this study, the number of from the polymorphonuclear cells which was consistent DEG was limited. We did not find significant enrichment with previous findings [27]. of KEGG pathways from the list of DEG; however, we did find several Gene Ontology (GO) terms for biological Conclusions process were enriched for immune responses and cellular This study characterized the global gene expression pro- response to organic substance. file of goat mammary epithelial cells obtained form milk Previous studies have showed a pronounced effect of fat layer and characterized XS inoculation-associated dif- inosine on milk production in transgenic goats [35]sug- ferential gene expression in mammary epithelial cells of gesting that exogenous nucleosides may stimulate milk early lactating Beetal goat. Our study showed individual production in ruminant species. PANTHER pathway ana- goats responded to XS treatment differently, suggesting lysis revealed that several XS-induced down-regulated a genetic predisposition to the treatment persists. Our genes were involved in inflammation signalling pathway, findings further indicated that the administration of XS Choudhary et al. Journal of Animal Science and Technology (2018) 60:18 Page 11 of 12 into the mammary gland has roles in down-regulation of Author details School of Animal Biotechnology, Guru Angad Dev Veterinary and Animal inflammation signalling pathway, cell adhesion molecules Sciences University, Ludhiana, Punjab 101004, India. Cell Wall Biology and and up-regulation of anti-bacterial genes. Down-regulation Utilization Research, USDA-ARS, Madison, WI 53706, USA. of inflammation signal and up-regulation of anti-bacterial Received: 1 February 2018 Accepted: 9 July 2018 genes may provide beneficial effects to mammary gland health.Our findingsarepromising.However,theywere limited by a small number of goats (n =2) included in this References study, indicating that future studies with more number of 1. Rambhatla L, Ram-Mohan S, Cheng JJ, Sherley JL. Immortal DNA strand animals are warranteed. cosegregation requires p53/IMPDH-dependent asymmetric self-renewal associated with adult stem cells. Cancer Res. 2005;65:3155–61. 2. Capuco AV, Evock-Clover CM, Minuti A, Wood DL. In vivo expansion of the Additional file mammary stem/ progenitor cell population by xanthosine infusion. Exp Biol Med (Maywood). 2009;234:475–82. 3. Rauner G, Barash I. Xanthosine administration does not affect the Additional file 1: Table S1. 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Journal of Animal Science and Technology – Springer Journals
Published: Jul 13, 2018