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Transcriptomic analysis of porcine PBMCs in response to Actinobacillus pleuropneumoniae reveals the dynamic changes of differentially expressed genes related to immuno-inflammatory responses

  • Hexiang Jiang
  • Rining Zhu
  • Hongtao Liu
  • Chuntong Bao
  • Jianfang Liu
  • Abdalla Eltahir
  • Paul R. Langford
  • Diangang Sun
  • Zhonghua Liu
  • Changjiang Sun
  • Jingmin Gu
  • Wenyu Han
  • Xin Feng
  • Liancheng Lei
ORIGINAL PAPER
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Abstract

Actinobacillus pleuropneumoniae is the cause of porcine pleuropneumonia, for which the mortality rate is high. Host peripheral blood is a body site for the immune clearance of pathogens mediated by release of inflammatory factors. However, “out of control” inflammatory factor release can contribute to host death. To further understand the changes in the transcription level of immune-related effectors, samples of peripheral blood mononuclear cells (PBMCs) collected from piglets at different stages of infection (0, 24 and 120 h) were sequenced on an Illumina HiSeq™ 4000 platform. We found 3818 differentially expressed genes (DEGs) in the 24 h-infection group compared to the 0 h-infection group (Pb24-Vs-Pb0). DEGs mainly involved in the Gene ontology and KEGG pathways that included nucleic acid metabolism regulation, cell growth, cell differentiation, and organ morphological maintenance were not significantly enriched (P > 0.05). However, DEGs associated with protein kinase activity, receptor activation, metabolism, local adhesion and immune inflammatory responses were significantly enriched in Pb120-Vs-Pb24 (P < 0.05), as were those related to the T cell receptor signalling pathway, with most being down-regulated compared to the preceding stage (Pb24-Vs-Pb0). In PBMCs there were some changes in glucose metabolism, local adhesion and the immune inflammatory response (Pb120-Vs-Pb0). In addition, up-regulated DEGs, such as IL8, IL1β, and CCL2, and were significantly enriched in immune-inflammatory related pathways compared to the uninfected stage, although they began to decline after 24 h.

Keywords

A. pleuropneumoniae Porcine pleuropneumonia Transcriptomic PBMC 

Abbreviations

APP

Actinobacillus pleuropneumoniae

PBMCs

Peripheral blood mononuclear cells

BALF

Bronchoalveolar lavage fluid

ELISA

Enzyme linked immunosorbent assay

DEGs

Differentially expressed genes

QC

Quality control

RPKM

Reads per kb per million reads

FDR

Pre-set false discovery rate

GO

Gene Ontology

KEGG

Kyoto Encyclopedia of Genes and Genomes

DAVID

Database of Annotation, Visualization, and Integrated Discovery

PAMs

Porcine alveolar macrophages

qRT-PCR

Quantitative real time-PCR

Notes

Funding

This research was supported by a Grant from the National Natural Science Foundation of China (No. 31520103917).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

All authors approved the final version of the manuscript.

Supplementary material

10482_2018_1126_MOESM1_ESM.doc (30 kb)
Supplementary material 1 (DOC 30 kb)
10482_2018_1126_MOESM2_ESM.doc (30 kb)
Supplementary material 2 (DOC 29 kb)
10482_2018_1126_MOESM3_ESM.doc (31 kb)
Supplementary material 3 (DOC 31 kb)
10482_2018_1126_MOESM4_ESM.doc (44 kb)
Supplementary material 4 (DOC 43 kb)
10482_2018_1126_MOESM5_ESM.tif (135 kb)
Fig. S1. Summary of the sequence assembly. After filtering, the percentage of clean data in all samples is more than 80%, indicating that this sequencing machine is stable and has no other operation errors (TIFF 134 kb)
10482_2018_1126_MOESM6_ESM.tif (126 kb)
Fig. S2. The Reads random distribution. On the X-axis, 0–1 represents the relative position of the gene normalized in the 5′ – > 3′ direction, the y-axis represents the number of Reads in the mapping. In the case of no random bias in sequencing, the entire curve should be stable, indicating that reads are evenly distributed in all parts of the gene, and the randomization of this sequencing is qualified (TIFF 126 kb)
10482_2018_1126_MOESM7_ESM.tif (177 kb)
Fig. S3. The summary of all DEGs involved in the immune response and inflammatory response, respectively (TIFF 176 kb)
10482_2018_1126_MOESM8_ESM.tif (130 kb)
Fig. S4. qRT-PCR validation of ten selected genes that were differentially expressed in the transcriptomic data. Data are representative of three independent experiments and error bars areplotted as mean ± SEM. The height of each bar chart represents the mean average of sample-specifi 2 −ΔΔCt values (*P < 0.05, **P < 0.01) (TIFF 130 kb)

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Hexiang Jiang
    • 1
  • Rining Zhu
    • 1
  • Hongtao Liu
    • 1
  • Chuntong Bao
    • 1
  • Jianfang Liu
    • 1
  • Abdalla Eltahir
    • 1
  • Paul R. Langford
    • 2
  • Diangang Sun
    • 1
  • Zhonghua Liu
    • 1
  • Changjiang Sun
    • 1
  • Jingmin Gu
    • 1
  • Wenyu Han
    • 1
  • Xin Feng
    • 1
  • Liancheng Lei
    • 1
  1. 1.College of Veterinary MedicineJilin UniversityChangchunChina
  2. 2.Section of PaediatricsImperial College LondonLondonUK

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