Transcriptome sequencing and characterization of ungerminated and germinated spores of Nosema bombycis

Abstract

Nosema bombycis is an obligate intracellular parasitic fungus that utilizes a distinctive mechanism to infect Bombyx mori. Germination, an indispensible process through which microsporidia infect the host cells, is regarded as a key developmental turning point for microsporidia from dormant state to reproduction state. Thus, elucidating the transcriptome changes before and after germination is crucial for parasite control. However, the molecular basis of germination of microsporidia remains unknown. To investigate this germination process, the transcriptome of N. bombycis ungerminated spores and germinated spores were sequenced and analyzed. More than 60 million high-quality transcript reads were generated from these two groups using RNA-Seq technology. After assembly, 2756 and 2690 unigenes were identified, respectively, and subsequently annotated based on known proteins. After analysis of differentially expressed genes, 66 genes were identified to be differentially expressed (P ≤ 0.05) between these two groups. A protein phosphatase-associated gene was first identified to be significantly up-regulated as determined by RNA-Seq and immunoblot analysis, indicating that dephosphorylation might potentially contribute to microsporidia germination. The DEGs that encode proteins involved in glycometabolism, spore wall proteins and ricin B lectin of N. bombycis were also analyzed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed genes responsible for some specific biological functions and processes. The datasets generated in this study provide a basic characterization of the transcriptome changes in N. bombycis during germination. The analysis of transcriptome data and identification of certain functional genes which are robust candidate genes related to germination will help to provide a deep understanding of spore germination and invasion.

Keywords: Nosema bombycis; dephosphorylation; germination; microsporidia; transcriptome.

Figure 1.

Morphological analysis of N. bombycis using a phase-contrast microscope (A) UGS (arrow). (B) GS (arrow). Scale bar = 14 μm.

Figure 2.

Size distribution of unigenes

Figure 3.

The relative expression levels of 15 randomly selected genes in two groups (UGS and GS) measured by qRT-PCR and RNA-seq The results of all the selected genes are similar to those measured by RNA-seq. The internal control gene is β-tubulin. For qRT-PCR, the fold change of each gene was calculated by the 2^−ΔΔCT method. For RNA-seq, the fold change of each gene was calculated by the FPKM. The fold change for each gene was determined by three independent quantitative PCR amplifications of RNA extracted independently and three independent RNA-seqs. Data were presented as mean ± SD from three independent biological replications. PTP2, polar tube protein 2; PTP3, polar tube protein 3; MAP1, microtubule-associated protein 1A; TKL1, Transketolase 1; NUP170, Nucleoporin NUP170; GNRP, glutamate NMDA receptor-associated protein 1; SWP5, spore wall protein 5; G6PI, glucose-6-phosphate isomerase; PP2A, protein phosphatase PP2-A regulatory subunit A; M1PG, mannose-1-phosphate guanyltransferase 2; NTFY, nuclear transcription factor Y subunit B-2; ATRS: alanyl-tRNA synthetase; PP, protein peanut; 60RP, 60S ribosomal protein L6; MADS, MADS domain containing protein.

Figure 4.

Hierarchical clustering of DEGs Heatmap of DEGs The four main clusters are shown, the expression values for the UGS and GS sets are presented, and the DEGs with decreased (green) and increased (red) expression in the different groups are shown. Expression patterns of genes in the four main clusters, namely C1–C4, corresponding to the hierarchical heatmap are shown on the right.

Figure 5.

Gene ontology classification of UGS and GS transcriptome

Figure 6.

Detection of phosphorylated protein levels in the UGS and GS samples of N. bombycis The level of dephosphorylation was increased significantly after germination (*P< 0.05). The β-actin protein and target protein were quantified using Quantify One software. Data were presented as the mean ± SD from three independent biological replications. Statistical analyses were performed using the Statistical Package for the Social Sciences, version 13.0. Results were analyzed using one-way ANOVA followed by Student's t-test. A P-value <0.05 was considered statistically significant.