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Transcriptomic analysis of male and female Schistosoma mekongi adult worms

  • 1,
  • 2,
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  • 4,
  • 1,
  • 5,
  • 1,
  • 1,
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  • 1Email author
Parasites & Vectors201811:504

https://doi.org/10.1186/s13071-018-3086-z

  • Received: 14 May 2018
  • Accepted: 29 August 2018
  • Published:

Abstract

Background

Schistosoma mekongi is one of five major causative agents of human schistosomiasis and is endemic to communities along the Mekong River in southern Lao People’s Democratic Republic (Laos) and northern Cambodia. Sporadic cases of schistosomiasis have been reported in travelers and immigrants who have visited endemic areas. Schistosoma mekongi biology and molecular biology is poorly understood, and few S. mekongi gene and transcript sequences are available in public databases.

Results

Transcriptome sequencing (RNA-Seq) of male and female S. mekongi adult worms (a total of three biological replicates for each sex) were analyzed and the results demonstrated that approximately 304.9 and 363.3 million high-quality clean reads with quality Q30 (> 90%) were obtained from male and female adult worms, respectively. A total of 119,604 contigs were assembled with an average length of 1273 nt and an N50 of 2017 nt. From the contigs, 20,798 annotated protein sequences and 48,256 annotated transcript sequences were obtained using BLASTP and BLASTX searches against the UniProt Trematoda database. A total of 4658 and 3509 transcripts were predominantly expressed in male and female worms, respectively. Male-biased transcripts were mostly involved in structural organization while female-biased transcripts were typically involved in cell differentiation and egg production. Interestingly, pathway enrichment analysis suggested that genes involved in the phosphatidylinositol signaling pathway may play important roles in the cellular processes and reproductive systems of S. mekongi worms.

Conclusions

We present comparative transcriptomic analyses of male and female S. mekongi adult worms, which provide a global view of the S. mekongi transcriptome as well as insights into differentially-expressed genes associated with each sex. This work provides valuable information and sequence resources for future studies of gene function and for ongoing whole genome sequencing efforts in S. mekongi.

Keywords

  • Schistosoma mekongi
  • Transcriptome
  • Differentially-expressed genes
  • Gene expression
  • RNA-Seq

Background

Mekong schistosomiasis is an important human parasitic disease and is caused by infection with Schistosoma mekongi. The parasite is highly prevalent along the Mekong River in southern Lao People’s Democratic Republic (Laos) and northern Cambodia [13]. Individuals infected by S. mekongi are mostly villagers living in endemic areas, but cases also occur in immigrants who resettle in other countries. Moreover, S. mekongi has been identified in international travelers who visited endemic areas, making this infection an important travel medicine issue in Southeast Asia [46].

As with other schistosome infections, disease develops after free-swimming S. mekongi larvae (cercariae) are released from a snail intermediate host, Neotricula aperta, and penetrate the human skin during swimming, bathing, farming and fishing [7]. Infection with S. mekongi is associated with a chronic local inflammatory response when eggs become entrapped in host tissues, resulting in intestinal disease, hepatosplenic inflammation and liver fibrosis [8]. No effective vaccine against S. mekongi is available, and anthelmintic treatment relies upon a single drug, praziquantel, against which resistance is becoming occurrence in some areas [913]. Thus, identification of novel targets for drug and vaccine development is urgently needed [14].

In previous studies, transcriptomic analyses of schistosomes have been conducted using expressed sequence tags (ESTs) [1519], microarray hybridization [2024] and serial analysis of gene expression [2527]. However, data obtained using these technologies have limitations, including low throughput, short sequence length and resulting in challenges in assembly and the ability to analyze only known sequences. Recently, next-generation sequencing (NGS) technologies have significantly accelerated research in genomics, transcriptomics, epigenomics and metagenomics [28], which has dramatically improved the efficiency of gene discovery and gene expression analysis (RNA-Seq) in diverse species of plants and animals [2933]. Transcriptomic analyses of human and animal schistosomes including S. mansoni, S. japonicum, S. haematobium and S. turkestanicum have been performed using RNA-Seq technology [3443] and have contributed significantly to systematic efforts to identify gene targets. Despite recent advances in sequencing technology and bioinformatic methods, there is little information on the complete transcriptome of S. mekongi. Here, RNA-Seq technology and de novo assembly were used to provide a global view of the transcriptomes of male and female S. mekongi adult worms. The aim of our study was to produce transcriptomic data that would enhance our understanding of the biology of S. mekongi and facilitate the identification of candidate drug and vaccine targets.

Results

RNA-Seq and de novo transcriptome assembly

RNA-Seq analysis of S. mekongi adult worms using Illumina PE sequencing technology yielded a total of 346,331,720 and 411,906,616 raw reads from male and female worms, respectively. After quality assessment and trimming, 304,934,770 and 363,296,510 clean reads were obtained from male and female worms, respectively. Per-base quality distributions for each biological replicate are shown in Additional file 1: Figure S1.

Clean reads longer than 200 nt were used for de novo assembly. A total of 190,741 and 190,922 contigs with N50 values of 1844 and 1965 nt were generated from assemblies with k-mer sizes 25 and 31, respectively. The assembly with k-mer size 31 was subsequently selected, due to its high realignment rate and higher N50 value, to filter redundant sequences. Summaries of both transcriptome assemblies’ quality and realignment rate are shown in Additional file 2: Table S1. A total of 119,604 contigs were obtained in the final assembly with an average contig length of 1273 nt. The shortest contig was 201 nt long, while the longest contig was 30,465 nt long. The N50 length of the final assembly was 2107 nt. A total of 42,600 contigs were longer than 1 kb and 625 contigs were longer than 10 kb. The overall GC content was 34.1% (Table 1).
Table 1

Statistical summary of de novo assembled transcriptome sequences from male and female S. mekongi adult worms

Parameter

Male worms

Female worms

Summary of raw sequencing reads

 Total raw readsa

346,331,720

411,906,616

 Total raw read nucleotides above Q30 (%)

48,771,315,768 (93.9%)

57,423,179,186 (92.9%)

Summary of trimmed sequencing reads

 Total clean readsa

304,934,770

363,296,510

 Total clean read nucleotides above Q30 (%)

43,463,738,987 (97.4%)

51,257,988,579 (96.9%)

Summary of final transcriptome assembly contigs

 Number of contigs

119,604

 

 Smallest contig length (nt)

201

 

 Largest contig length (nt)

30,465

 

 Number of contigs with length < 200 nt

0

 

 Number of contigs with length > 1k nt

42,600

 

 Number of contigs with length > 10k nt

625

 

 N50 (nt)

2107

 

 GC content (%)

34.1

 

aReads of three replicates

Functional annotation and GO classification

To annotate protein function, all 119,604 assembled contigs were subjected to prediction of protein CDS regions (Table 2). A total of 20,798 putative proteins were identified of which 19,744 could be annotated after BLASTP searching against the UniProt Trematoda database with an E-value cut-off < 10-5. Transcripts for which CDS regions could not be predicted were alternatively annotated using a BLASTX sequence similarity search against the UniProt Trematoda database with an E-value cut-off < 10-5. Following this analysis, 48,256 additional contigs could be assigned to functional proteins. All annotated transcripts produced from both analyses were further annotated using the GO databases of BLAST and Pfam. A total of 21,833 and 8462 assembled contigs were assigned to at least one of three GO terms of the BLAST and Pfam databases, respectively. GO assignments were grouped into three different categories: biological processes, molecular functions and cellular components, containing 8694, 16,366 and 11,055 transcripts, respectively.
Table 2

Summary of assembled transcript annotation

Transcript annotation

No. of transcripts

Total transcripts

119,604

Total protein sequences

20,798

Number of protein sequences with BLASTP hits

19,744

Number of transcript sequences with BLASTX hits

48,256

Number of transcript sequences with GO terms (BLAST)

21,833

Number of transcript sequences with GO terms (Pfam)

8462

Analysis of differential expression

Of 119,604 total transcripts, 18,643 were DE in male and female adult worms with cpm > 1 (Fig. 1). In total, 8169 transcripts were significantly DE between male and female worms (FDR value < 0.05 and fold change > 2.0), spanning a log2 fold change range of -18.5 to 16.2. The red spots shown in Fig. 1 represent DE transcripts. Among all significantly DE transcripts, 4659 and 3510 transcripts were upregulated in male and female worms, respectively. The functional annotations of DE transcripts demonstrated that 2391 transcripts upregulated in male worms could be annotated but 2268 transcripts had unknown functions, while 1308 transcripts upregulated in female worms could be annotated but 2202 transcripts had unknown functions.
Fig. 1
Fig. 1

Smear plot of all DE transcripts with cpm > 1.0 from S. mekongi male and female worms. The graph shows average log2(cpm) on the x-axis vs log2(fold change in gene expression) between male and female worms on the y-axis. DE transcripts are shown in red and non-DE transcripts are shown in black

The 50 most significantly DE transcripts of both male and female worms were shown in a heatmap (Fig. 2), with11 and 39 of these transcripts being significantly upregulated in male and female worms, respectively. However, 22 of these transcripts had unknown functions (4 and 18 transcripts in male and female worms, respectively). Transcript identification and protein descriptions are listed in Additional file 3: Table S2.
Fig. 2
Fig. 2

Heatmap of 50 most significantly DE transcripts from S. mekongi male vs female worms with three biological replicates. DE transcripts with higher expression levels are shown in red. DE transcripts with lower expression levels are shown in blue

Among the significantly upregulated transcripts for each sex, the 50 transcripts with the highest upregulation are listed in Tables 3 and 4. In male worms, these were transcripts related to cytoskeleton-, motor-, and neuronal-associated proteins (dynein, tropomyosin 2, myosin light chain kinase and plexin A1) and to cell adhesion (integrin, CD97 antigen and serine-rich adhesin for platelets). Several transcripts associated with signaling pathways were also upregulated in male worms including serine/threonine kinase, receptor protein-tyrosine kinase, putative multiple ankyrin repeats single KH domain protein, serine/threonine-protein kinase PAK 3, rapamycin-insensitive companion of mTOR and regulator of G-protein signaling 3 (Table 3).
Table 3

Top 50 most significantly upregulated transcripts in S. mekongi male worms

Transcript ID

Protein description

Log2(FC)

P-value

FDR

Pfam annotation

comp65_seq18

Reverse transcriptase

16.2

2.66E-92

1.24E-88

comp2831_seq1

Uncharacterized protein

15.2

1.47E-70

2.29E-67

comp1481_seq2

Clone ZZD1216 mRNA sequence

14.8

1.19E-70

2.01E-67

comp926_seq0

Uncharacterized protein

14.2

3.84E-56

3.01E-53

comp2062_seq0

Uncharacterized protein

13.8

1.53E-45

6.63E-43

comp4508_seq0

Integrin

13.7

2.79E-47

1.30E-44

comp4099_seq6

Uncharacterized protein

13.6

3.96E-41

1.34E-38

G-patch domain, FtsJ-like methyltransferase

comp556_seq2

Hypothetical protein

13.6

3.35E-32

4.84E-30

comp4395_seq2

Putative poly(Rc) binding protein

13.6

1.45E-43

5.73E-41

KH domain

comp298_seq2

Uncharacterized protein

13.5

2.02E-41

7.11E-39

Ankyrin repeats

comp5387_seq1

Serine/threonine kinase

13.2

1.95E-36

4.39E-34

Protein kinase domain, protein tyrosine kinase

comp3544_seq2

Dynein-associated protein

13.2

1.51E-34

2.79E-32

comp510_seq4

Tropomyosin-2

13.0

1.04E-22

6.12E-21

Aida N-terminus,

tropomyosin

comp1917_seq1

Lysine-tRNA ligase

12.8

2.43E-26

2.02E-24

tRNA anti-codon, OB-fold nucleic acid binding domain

comp7221_seq1

Uncharacterized protein

12.6

3.04E-27

2.75E-25

comp8398_seq0

Putative homeobox protein

12.6

6.23E-25

4.54E-23

N-terminal of Homeobox Meis and PKNOX1

comp3445_seq0

Receptor protein-tyrosine kinase

12.6

1.84E-26

1.55E-24

Receptor L domain, furin-like cysteine rich region

comp3797_seq0

Uncharacterized protein

12.5

2.10E-26

1.75E-24

BTG family

comp3182_seq1

Putative multiple ankyrin repeats single KH domain protein

12.4

2.95E-17

9.84E-16

Ankyrin repeats

comp115_seq0

Uncharacterized protein

12.4

1.44E-22

8.37E-21

Arrestin (or S-antigen), N-terminal domain

comp7837_seq2

Uncharacterized protein

12.2

8.70E-24

5.69E-22

Cadherin domain

comp5447_seq1

Myosin light chain kinase, smooth muscle

12.2

1.17E-15

3.10E-14

Immunoglobulin I-set domain

comp3754_seq1

Metastasis suppressor protein 1

12.1

3.29E-19

1.38E-17

IRSp53/MIM homology domain

comp8738_seq10

Uncharacterized protein

12.1

2.30E-21

1.20E-19

comp4029_seq0

Plexin-A1

12.1

4.14E-20

1.88E-18

Plexin repeat, IPT/TIG domain

comp138_seq8

SJCHGC08958 protein

12.0

1.54E-13

3.00E-12

Trematode eggshell synthesis protein

comp5826_seq0

Uncharacterized protein

12.0

2.10E-22

1.19E-20

Leucine rich repeat

comp3044_seq3

Uncharacterized protein

12.0

1.01E-20

4.89E-19

NIF3 (NGG1p interacting factor 3)

comp8147_seq2

Uncharacterized protein

11.9

4.28E-20

1.94E-18

Laminin G domain

comp595_seq0

Choline dehydrogenase, mitochondrial

11.9

7.87E-15

1.85E-13

GMC oxidoreductase

comp1402_seq1

Uncharacterized protein

11.9

1.25E-16

3.78E-15

comp490_seq3

Serine/threonine-protein kinase PAK 3

11.9

5.01E-19

2.07E-17

P21-Rho-binding domain

comp8255_seq1

Uncharacterized protein

11.8

3.00E-20

1.38E-18

comp4371_seq0

Putative ABC transporter

11.8

1.63E-19

7.01E-18

ABC transporter

comp5811_seq8

Rapamycin-insensitive companion of mTOR

11.8

2.32E-17

7.85E-16

Rapamycin-insensitive companion of mTOR, domain 5

comp9143_seq1

Regulator of G-protein signaling 3

11.8

5.29E-21

2.64E-19

C2 domain, PDZ domain (DHR or GLGF)

comp9843_seq1

Uncharacterized protein

11.8

6.13E-20

2.71E-18

Rhodopsin family

comp8166_seq1

Uncharacterized protein

11.8

4.38E-21

2.20E-19

comp1561_seq0

Uncharacterized protein

11.6

2.16E-12

3.55E-11

comp6197_seq1

Uncharacterized protein

11.6

3.52E-17

1.17E-15

comp9531_seq0

Putative ankyrin 2,3/unc44

11.6

2.07E-16

6.05E-15

Ankyrin repeats

comp9039_seq1

Centrosomal protein of 120 kDa

11.6

2.64E-19

1.11E-17

C2 domain, Cep120 protein

comp2906_seq3

CD97 antigen

11.6

3.96E-18

1.47E-16

Secretin family

comp3517_seq2

Rho guanine nucleotide exchange factor 12

11.6

1.38E-19

6.00E-18

Regulator of G protein signalling-like domain

comp2195_seq3

Uncharacterized protein

11.6

1.91E-15

4.93E-14

Galactoside-binding lectin

comp5487_seq0

Uncharacterized protein C7orf63-like protein

11.6

8.05E-20

3.52E-18

comp4205_seq4

Serine-rich adhesin for platelets

11.5

2.14E-14

4.76E-13

comp3759_seq1

Putative Alstrom syndrome protein

11.5

1.86E-16

5.50E-15

comp9022_seq1

Uncharacterized protein

11.5

1.97E-18

7.61E-17

MORN repeat

comp10754_seq0

Uncharacterized protein

11.4

8.21E-19

3.31E-17

Cadherin-like

Table 4

Top 50 most significantly upregulated transcripts in S. mekongi female worms

Transcript ID

Protein description

Log2(FC)

P-value

FDR

Pfam annotation

comp837_seq1

SJCHGC05677 protein

18.5

1.51E-88

4.69E-85

comp546_seq10

O-glycosyltransferase

16.5

6.50E-54

4.04E-51

Tetratricopeptide repeat

comp1_seq2

Uncharacterized protein

16.2

2.08E-09

2.06E-08

comp1141_seq3

Putative scythe/bat3 DNA repair

15.9

7.99E-51

4.51E-48

Ubiquitin family

comp401_seq5

SJCHGC09037 protein

15.8

7.56E-34

1.29E-31

Protein similar to CwfJC-terminus 1

comp7058_seq0

Uncharacterized protein

15.7

6.12E-20

2.71E-18

comp524_seq5

Uncharacterized protein

14.8

8.48E-19

3.41E-17

comp5822_seq2

DNA excision repair protein ERCC-6 DNA repair

14.2

7.21E-29

7.68E-27

Type III restriction enzyme, res subunit

comp5430_seq10

Inositol 1,4,5-trisphosphate receptor

14.0

5.20E-88

1.39E-84

Inositol 1,4,5-trisphosphate/ryanodine receptor

comp3416_seq1

Thioredoxin domain-containingprotein 4

13.9

1.32E-48

7.02E-46

Thioredoxin-like domain

comp3035_seq0

Uncharacterized protein

13.7

7.86E-27

6.85E-25

DnaJ domain

comp6618_seq1

Uncharacterized protein

13.6

3.75E-67

4.99E-64

comp247_seq3

SJCHGC09430 protein

13.5

2.43E-64

2.66E-61

comp3544_seq3

Mannosyltransferase

13.5

4.23E-24

2.84E-22

Alg9-like mannosyltransferase family

comp7684_seq1

Uncharacterized protein

13.0

2.85E-26

2.34E-24

comp1544_seq2

EH domain-bindingprotein 1

12.9

5.14E-22

2.83E-20

CAMSAP CH domain

comp4065_seq0

Uncharacterized protein

12.9

7.78E-31

1.00E-28

comp3239_seq2

Uncharacterized protein

12.8

1.94E-19

8.30E-18

Phosphatidylethanolamine-binding protein

comp167028_seq0

Uncharacterized protein

12.7

2.33E-64

2.66E-61

comp7307_seq0

Uncharacterized protein

12.7

1.97E-31

2.68E-29

comp6088_seq2

Uncharacterized protein

12.6

7.12E-39

1.92E-36

comp4607_seq0

Uncharacterized protein

12.5

7.98E-33

1.23E-30

comp8587_seq1

Pol polyprotein

12.4

2.50E-40

7.78E-38

comp5229_seq0

Uncharacterized protein

12.3

4.78E-15

1.16E-13

comp8246_seq0

Uncharacterized protein

12.3

4.60E-25

3.41E-23

comp2149_seq0

Uncharacterized protein

12.2

4.45E-97

2.77E-93

comp5198_seq1

Uncharacterized protein

12.2

1.16E-28

1.20E-26

comp475_seq2

Ccr4-not transcription complex gene regulation

12.2

1.52E-37

3.94E-35

comp8567_seq0

Uncharacterized protein

12.0

1.58E-31

2.17E-29

comp7704_seq0

Uncharacterized protein

12.0

7.90E-28

7.63E-26

comp1502_seq0

Uncharacterized protein

12.0

3.49E-20

1.59E-18

comp9595_seq0

Uncharacterized protein

11.9

4.66E-30

5.57E-28

comp29_seq2

SJCHGC05410 protein

11.9

1.22E-17

4.25E-16

comp5733_seq0

Elastase 2b

11.9

5.02E-60

4.92E-57

Trypsin-like peptidase domain

comp785_seq0

Uncharacterized protein

11.9

1.50E-22

8.68E-21

comp11219_seq0

Uncharacterized protein

11.9

3.03E-36

6.57E-34

comp9353_seq1

Uncharacterized protein

11.8

2.73E-21

1.40E-19

comp969_seq7

Uncharacterized protein

11.8

6.68E-27

5.93E-25

comp5698_seq0

Uncharacterized protein

11.8

1.13E-35

2.34E-33

comp10698_seq1

Uncharacterized protein

11.7

6.86E-34

1.18E-31

comp7614_seq1

Uncharacterized protein

11.7

2.55E-21

1.32E-19

comp4729_seq2

Uncharacterized protein

11.6

1.17E-30

1.45E-28

Alpha amylase, catalytic domain

comp10183_seq1

Uncharacterized protein

11.5

1.90E-21

1.01E-19

comp5834_seq0

SJCHGC06880 protein

11.5

2.91E-33

4.68E-31

RING-variant domain

comp268_seq0

Putative 26S proteasome non-ATPase regulatory subunit 11 protein misfolding repair

11.5

8.14E-05

3.44E-4

PCI domain

comp9969_seq1

Uncharacterized protein

11.4

2.39E-33

3.87E-31

comp1262_seq5

Uncharacterized protein

11.2

3.05E-22

1.70E-20

Dynein heavy chain

comp1218_seq2

Connector enhancer of kinase suppressor of Ras2

11.2

5.59E-30

6.52E-28

PDZ domain (DHR or GLGF)

comp5896_seq0

Uncharacterized protein

11.2

5.53E-90

2.06E-86

comp5214_seq0

Uncharacterized protein

11.1

2.20E-29

2.42E-27

Among the 50 most upregulated transcripts in female worms, transcripts with known function primarily related to glycosylation activity (O-glycosyltransferase, mannosyltransferase), peptidase activity (elastase 2b) and antioxidant enzyme activity (thioredoxin domain-containing protein 4). Moreover, several genes related to DNA- and protein-misfolding repair activity (scythe/bat3, DNA excision repair protein ERCC-6, 26S proteasome non-ATPase regulatory subunit 11), gene regulation activity (Ccr4-not transcription complex) and cellular and physiological control activity (inositol 1,4,5-trisphosphate receptor) were upregulated (Table 4).

GO and KEGG pathway analyses of DE transcripts

According to the GO classification of DE transcripts, there were 2916, 14,141 and 6693 transcripts assigned to biological process, cellular component and molecular function categories, respectively, of which 1627, 7461 and 3963 transcripts were significantly DE (FDR value < 0.05) (Additional file 4: Table S3). The top three predominant terms for ‘biological process’ were cell communication, signaling, and single organism signaling; for ‘cellular component’ they were membrane, membrane part, and intrinsic component of membrane; and for ‘molecular function’ they were transporter activity, transmembrane transporter activity and substrate-specific transporter activity (Fig. 3a-c).
Fig. 3
Fig. 3

GO analysis of DE transcripts in S. mekongi male and female worms. GO categories are organized according to three main ontologies: biological process (a), cellular component (b) and molecular function (c). The x-axis shows the numbers of transcripts. The y-axis shows the GO term. GO terms with higher FDR values are shown in light blue, whereas GO terms with lower FDR values are shown in dark blue

Furthermore, significant GO terms in each sex was analyzed and demonstrated that the male upregulated transcripts composed of cell communication, single organism signaling and signaling were the top three significant GO terms for ‘biological process’, intrinsic component of membrane, integral component of membrane and plasma membrane were significant GO terms for ‘cellular component’, signal transducer activity, receptor activity and molecular transducer activity were significant GO terms for ‘molecular function’ (Additional file 5: Table S4 and Additional file 6: Figure S2). While, significant GO terms in female upregulated transcripts revealed that cellular amide metabolic process, peptide metabolic process, and amide biosynthetic process were significant GO terms for ‘biological process’, intracellular ribonucleoprotein complex, ribonucleoprotein complex and ribosome were significant GO terms for ‘cellular component’, structural constituent of ribosome, structural molecule activity, and RNA binding were significant GO terms for ‘molecular function’ (Additional file 7: Table S5, Additional file 8: Figure S3).

KEGG pathway enrichment analysis revealed that a total of 122 pathways were significantly enriched comparing male vs female worms (FDR value < 0.05) (Additional file 9: Table S6). These pathways were composed of 397 DE transcripts distributed among the following classes: organismal systems (29.5%), human disease (22.7%), environmental Information processing (17.3%), cellular processes (17.3%), genetic information processing (7.4%) and metabolism (5.7%). The enrichment pathway analysis suggested that the top three sub-classes were composed of transcripts relating to signal transduction (17.3%), endocrine system (9.8%) and cell growth and death (7.8%) (Fig. 4). Analysis of the top 30 most significantly enriched pathways showed that the phosphatidylinositol signaling system was the most significantly enriched pathway (P = 4.28E10-09), followed by cell cycle - yeast (P = 3.52E-09), meiosis - yeast (P = 3.93E-09), cell cycle (P = 1.92E-08) and focal adhesion pathways (P = 1.02E-07) (Fig. 5). Upregulated transcripts involved in the phosphatidylinositol signaling system are shown in Fig. 6 and Additional file 10: Table S7.
Fig. 4
Fig. 4

Enrichment pathway analysis of DE transcripts in S. mekongi male vs female worms (Q-value ≤ 0.05). The bar graph shows the number of annotated DE transcripts (y-axis) associated with each sub-class of an enriched pathway (x-axis)

Fig. 5
Fig. 5

Top 30 most significantly enriched pathways in S. mekongi male and female worms. The bar graph shows the number of annotated DE transcripts (x-axis) with each significantly enriched pathway (y-axis). Blue and red colors are the numbers of upregulated transcripts in male and female worms, respectively

Fig. 6
Fig. 6

Phosphatidylinositol signaling pathway. Red background indicates upregulated genes in male worms and green background indicates upregulated genes in female worms

The significant KEGG pathway in each sex demonstrated that the top three significant KEGG pathways in the male worm comprised of focal adhesion, axon guidance and phosphatidylinositol signaling system, respectively. While, cell cycle - yeast, meiosis - yeast and cell cycle were top three significant KEGG pathways in female worms (Additional file 11: Table S8).

RT-qPCR validation

Thirty representative transcripts (10 upregulated in male worms, 10 upregulated in female worm and 10 non-DE transcripts) were randomly selected for validation of the RNA-Seq analysis using RT-qPCR. The expression of these genes in male and female worms was validated by RT-qPCR, which was highly correlated with the results obtained by RNA-Seq (10 upregulated transcripts in male worms, r = 0.793, P= 0.006; 10 upregulated transcripts in female worms, r = 0.98, P < 0.000001; non-DE transcripts, r = 0.98, P < 0.000001 (Additional file 12: Figure S4).

Discussion

Mekong schistosomiasis caused by S. mekongi remains a health problem in both humans and animals resident in endemic areas [4446]. Moreover, Mekong schistosomiasis has sporadically emerged throughout the world due to immigration, travel and animal trading [47]. To prevent and control this infection, several strategies have been implemented including mass administration of praziquantel in human and reservoir animals, rapid diagnosis to identify asymptomatic cases, snail control and health education. These interventions showed variable results (both successful and unsuccessful) in each area [47]. Thus, novel prevention and control strategies need to be developed based on basic and applied S. mekongi biology, especially genomic, transcriptomic and proteomic analyses. However, public databases contain few S. mekongi sequences. Herein, we provide the first transcriptomic database of S. mekongi adult worms, and compared gene expression between male and female adult parasites.

In this study, RNA-Seq of S. mekongi was performed using the Illumina PE sequencing platform with a read length of 150 bases. De novo assembly was carried out prior to annotation and downstream analysis. As there was no available reference genome, de novo assembly was required to generate contigs. In this regard, the de novo transcriptome assembler Bridger was selected as it provides the highest accuracy for paired end reads and the most complete reconstruction of transcripts compared to other assemblers [48].

After annotation, we demonstrated that 4659 and 3510 DE transcripts were significantly upregulated in adult male and female worms, respectively. Genes encoding cytoskeleton-, motor- and neuronal-associated proteins (dynein, tropomyosin 2, myosin light chain kinase and plexin A1) were predominantly upregulated in male worms. Our findings are consistent with previous studies of S. mansoni and S. japonicum [20, 21, 23, 4951]. Upregulation of cytoskeleton and motor proteins in male worms may imply their role in the physical support of female worms to facilitate their migration against blood flow from hepatic portal sites to the smaller mesenteric circulation where they lay their eggs [24].

In addition, high expression of adhesion molecule, integrin, was observed in S. mekongi male worms. In S. mansoni, integrins were predominantly transcribed in reproductive tissue including testes, ovary, vitellarium and ootype. Downexpression of integrins using RNAi affected shape abnormality of oocyte. These indicate an indispensable role of integrin in reproductive processes of S. mansoni that may implied to other Schistosoma spp. and other Platyhelminthes [52, 53]. CD97 homolog is another adhesion molecule highly upregulated in S. mekongi male worms. CD97 is a member of adhesion G protein-coupled receptor expressed on the surface of hematopoietic stem cells, immune cells, smooth muscle, etc. The three known ligands interacting with CD97 have been identified and characterized including complement decay-accelerating factor (CD55), chondroitin sulfate and integrin α5β1 that they are the key molecules playing important roles in several biological and physiological processes in the cells [54]. However, basic function, property and tissue localization of CD97 in parasitic helminths and other pathogens are still unknown and need to be investigated in the future.

In addition to genes associated with cytoskeleton, motor and adhesion, several proteins involved in signaling pathways, including G protein-coupled receptors, tyrosine kinases and serine/threonine kinase pathways were upregulated in male worms. Previously, several studies demonstrated that these signaling pathways were involved in the schistosome life-cycle to control growth, development, sexual differentiation, maturity and even host-parasite interactions. Thus, members of these pathways should be proposed as promising new therapeutic targets against schistosomiasis [5558].

In the female worm, the antioxidant protein, thioredoxin domain-containing protein 4, was upregulated, which is consistent with the other studies of S. mansoni and S. japonicum [5964]. Due to blood degradation in female worms, oxidative stress is generated as a by-product. Thus, higher expression of antioxidant enzymes in female worms has been proposed as a mechanism to protect against damage from oxidative stress. In S. mansoni, thioredoxin was not only highly upregulated in female worms but also in eggs. Thus, it has also been proposed that antioxidant mechanisms protect the embryo from oxidative damage resulting from host immunity [59, 61]. The elastase 2b was upregulated and was found among the top 50 most significantly DE transcripts in female worms. RT-qPCR of elastase 2b comparing among male worms, female worms and eggs was performed and the result demonstrated that the gene was expressed the highest in female worms followed by eggs and male worms (Additional file 13: Figure S5). High expression of elastase 2b in mature eggs may facilitate miracedia invade snail intermediate host as same as being required by cercariae to penetrate definitive host skin [65]. However, the real function of elastase 2b in miracedia of schistosomes has not been mentioned elsewhere and need to be investigated in the future. Genes involved in glycosylation, DNA- and protein-misfolding repair and gene regulation were highly enriched in female worms. These may be related to the active cell cycle, proliferation and differentiation during egg production [51].

Among the most significant GO terms in male and female upregulated transcripts, different patterns of gene expression in biological processes were revealed between male and female worms. The result showed that the majority of upregulated genes in male worms were intimately involved in the cell communication, cell signaling and cell adhesion such as delta-like protein, calcium ion binding, putative sodium/calcium exchanger, Rho GTPase-activating protein, G protein-coupled receptor kinase, serine/threonine-protein phosphatase, guanine nucleotide binding protein (G protein), GTP-binding protein, indicating more active host-parasite communication and interaction in male worms. In comparison, these contrasts with the upregulated genes in female worms that played roles in metabolic and biosynthetic processes especially to amide and peptide, indicating that the nutritional acquisition is more crucial for female worms. This is probably reflective of its status of oviposition, which requires abundant nutrition for egg production [51].

The most significant KEGG pathway in male and female upregulated transcripts revealed that structural elements expressed differentially in the male worm included components involved in focal adhesion, regulation of the actin cytoskeleton and tight junctions. In contrast, female worms mostly upregulated genes involved in the cell cycle and meiosis specifically relating to cell division and cell differentiation, such as nipped-B protein, putative cell division cycle 20 (Cdc20) (Fizzy), cell division control protein 45-like protein, cell division cycle 7-related protein kinase, structural maintenance of chromosomes protein, family C50 non-peptidase homologue (C50 family) and the tyrosine-protein kinase Abl. In addition, a set of genes involved in DNA replication processes, DNA polymerase, DNA helicase, putative chromosome transmission fidelity factor and putative DNA primase large subunit are preferentially expressed in the female worm. These results are presumably due to oogenesis and vitellogenesis in female worms [51, 6668]. Moreover, we found several genes involved in the response to DNA damage or spindle abnormalities assigned to the cell cycle pathway. These included putative rad1 DNA damage checkpoint protein, putative meiotic checkpoint regulator cut4 and putative phosphatidylinositol 3-and 4-kinase, as well as putative DNA polymerase delta small subunit and DNA polymerase III gamma-tau subunit assigned to the genetic information processing pathway (all upregulated in female worms). These observations potentially reflect cell division processes and the need to repair DNA damage caused by oxygen radicals released during the process of hemoglobin digestion, as mentioned in the previous section.

The KEGG pathway analysis revealed pathways associated with sexual differentiation and development, as well as the sex maintenance pathway for female and male worms of S. mekongi. These included the GnRH signaling pathway, the insulin signaling pathway and the progesterone-mediated oocyte maturation pathway; these were also identified in previous studies [40, 69, 70]. Our finding that the phosphatidylinositol signaling pathway was most highly enriched was interesting. Inositol hexakisphosphate, calcium-dependent protein kinase C, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha PI3K, diacylglycerol kinase (DAG kinase), phosphatidylinositol 4-phosphate 3-kinase C2 domain-containing subunit alpha and myotubularin-related protein were upregulated in male worms and inositol 1,4,5-trisphosphate receptor was specifically upregulated in female worms.

Phosphatidylinositol is a phospholipid, which is a crucial component of cellular membranes, and plays important roles in various cellular processes including growth, differentiation and vesicular secretion. The phosphatidylinositol pathway consists of a series of conversions of phosphatidylinositol into singly, doubly and triply phosphorylated forms, and has been implicated in the regulation of numerous cellular functions and responses to extracellular signals [71]. The phosphatidylinositol signaling pathway have been reported to play important roles in a multitude of cellular processes such as membrane trafficking, cell motility, cytoskeletal reorganization, DNA synthesis, the cell cycle, adhesion, signal transduction and reproductive systems [72, 73]. Studies of the role of the phosphatidylinositol pathway in C. elegans found that its phosphorylated forms have multiple functions; for example, phosphatidylinositol-3-OH kinase, diacylglycerol kinase, phosphatidylinositol 4-phosphate 5-kinase and phosphatidylinositol 3-kinase, play important roles in longevity and diapause [74], thermotactic behavior [75], ovulation and fertilization [76] and the behavioral learning response [77], respectively.

In mammals, the phosphatidylinositol 3-kinase (PI3K) signal transduction pathway is necessary for seminiferous cord formation, testis and vascular development during testis morphogenesis. Inhibition of PI3K using the specific inhibitor, LY294002, blocked cord formation and impacted the number of cords and their vascular density [78, 79]. The phosphatidylinositol signaling pathway may be indispensable for S. mekongi survival, especially development of the male reproductive system. In the future, the functions and properties of the phosphatidylinositol signaling pathway in sex development of schistosomes need to be elucidated prior to consideration of pathway members as novel therapeutic targets against schistosomiasis.

Conclusions

In this study, we presented a transcriptomic analysis of male and female S. mekongi adult worms using RNA-Seq data. The study revealed the key biological and physiological features of male and female S. mekongi worms. These data will serve as a sequence resource for future studies of gene functions and will aid the ongoing whole genome sequencing efforts for S. mekongi, which may further facilitate the discovery of novel interventions against this persistent parasite.

Methods

Parasite materials

Adult S. mekongi worms used in this study were maintained by alternating infection of the intermediate snail host, N. aperta, and mice (Mus musculus) according to a standard protocol [80]. The N. aperta snails were collected from the Mekong River, Ubon Ratchathani Province, Thailand. Eight-week-old female ICR mice were purchased from the National Laboratory Animal Center, Mahidol University. Mice were infected with 25–30 cercariae by percutaneous exposure at the abdomen and then housed in the Animal Care Unit, Faculty of Tropical Medicine, Mahidol University. Eight weeks post-infection, mature adult worms were recovered from the infected mice by hepatic perfusion with 0.85% normal saline solution. Adult males and females were separated manually under a dissecting microscope. The worms were carefully washed in normal saline solution and immediately frozen at -80 °C until the time of RNA extraction.

RNA extraction, cDNA library construction, RNA sequencing and quality control

Total RNA was extracted from pooled adult male (n = 20) and female (n = 40) worms. Extractions for each sex were performed with three biological replicates using TRIZOLTM reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. RNA quantity and quality were assessed using a NanoDrop® ND-1000 spectrophotometer (Thermo Fisher Scientific Inc., Wilington, DE, USA) and a 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA).

For each replicate, cDNA libraries were constructed from 1 μg of total RNA (Additional file 14: Figure S6) using the NEBNext® UltraTM RNA Library Prep Kit for Illumina® according to the manufacturer’s protocol (New England Biolabs (NEB), Ipswich, MA, USA). Briefly, mRNA isolation was performed using oligo(dT) magnetic beads contained in the NEBNext® Poly(A) mRNA Magnetic Isolation Module (NEB). The mRNAs were fragmented and reverse transcribed using NEBNext® First Strand Synthesis Reaction Buffer and NEBNext® Random Primers. First-strand cDNA was synthesized using ProtoScript II Reverse Transcriptase and second-strand cDNA was synthesized using Second Strand Synthesis Enzyme Mix. Double-stranded cDNA was purified using the AxyPrep™ Mag PCR Clean-up kit (Axygen Biosciences, Union City, CA, USA) and treated with End Prep Enzyme Mix to repair both ends, add a dA-tail, and add adaptors to both ends via TA ligation. Size selection of adaptor-ligated DNA was performed using the AxyPrep™ Mag PCR Clean-up kit, and fragments of ~360 bp were recovered. Each sample was then amplified by PCR for 11 cycles using P5 and P7 primers; both of these primers carried sequences that can anneal to the Illumina flow cell and perform bridge PCR, and the P7 primer carried a six-base index sequence allowing for multiplexing. The PCR products were purified using the AxyPrep™ Mag PCR Clean-up kit, analyzed using an Agilent 2100 Bioanalyzer and quantified using a Qubit 2.0 Fluorometer (Invitrogen). Barcoded libraries with different index sequences were multiplexed and loaded on an Illumina HiSeq X instrument according to the manufacturer’s instructions (Illumina, San Diego, CA, USA). Sequencing was carried out using a 2 × 150 bp paired-end (PE) configuration; image analysis and base calling were conducted using the HiSeq Control Software (HCS) + RTA 2.7 (Illumina) on the HiSeq X instrument.

In order to assess sequencing quality, the raw sequencing reads were processed using the following steps. First, raw sequencing reads was assessed with FastQC software (v0.11.2) (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to estimate read quality using PHRED quality scores. Secondly, adaptor sequences and low-quality bases (below Q30) were trimmed from the raw reads with Trimmomatic software (v.0.32) [81]. Finally, any resulting reads that were at least 50 bases long were selected for further analysis.

Assembly of transcripts

De novo assembly of clean reads was performed using the Bridger assembler [82] with either 25 or 31 k-mer sizes. The quality of each assembly was assessed using Transrate (v.1.0.3) [83] and the sequence read realignment rates for each assembly’s contigs were computed with HISAT2 (v.2.0.5) [84]. In this study, the contig sequences from the assembly with k-mer size 31 were selected for analysis due to this assembly’s high realignment rate and higher N50 value. Contig sequences with coverage > 10 reads were extracted and clustered with the CD-HIT-EST algorithm [85] to filter redundant sequences. The longest sequences from each cluster were selected as the final assembly.

Annotation of transcripts

Protein-coding sequence (CDS) regions and open reading frames (ORFs) were predicted for each assembled transcript using the TransDecoder v.5.0.1 algorithm (http://transdecoder.github.io). The function of the predicted protein sequences was annotated using BLAST v.2.2.31 (BLASTP algorithm) [86], with searches against the UniProt Trematoda database (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2238893/) [87]. Transcripts for which no CDS regions were predicted were subsequently analyzed with BLAST v.2.2.31 (BLASTX algorithm) [86] for alternative functional assignment. The protein family of annotated proteins was analyzed through a protein profile database (Pfam) search using HMMER3 software [88]. A threshold of E-value < 10-5 was applied in all the functional prediction analyses.

Analysis of differentially expressed (DE) transcripts

Trimmed sequence reads were aligned back to the assembled transcriptome using Bowtie2 (v.2.2.9) [89]. Discordant alignments were excluded. TPM (transcripts per million), FPKM (Fragments Per Kilobase Of Exon Per Million Fragments Mapped), credibility intervals and expected counts were computed using RSEM (v.1.3.0) [90]. Transcripts with expression values of more than 1 count per-million (cpm) were extracted for differential expression analysis. Analysis of DE transcripts comparing male vs female worms was conducted using edgeR v.3.20.7 [91]. The expression fold change between sexes were calculated and log-transformed. Significantly DE transcripts between sexes were extracted according to the following criteria: false discovery rate (FDR) < 0.05 and fold change > 2.0.

Gene ontology (GO) and KEGG pathway analyses

Significantly DE transcripts were annotated with GO terms for assignment to three major GO categories: cellular components, biological processes and molecular functions. The GO annotation was performed with the R package topGO (v.2.28.0) (https://bioconductor.org/packages/release/bioc/html/topGO.html). Enrichment was assessed with classic Fisher’s exact tests in topGO and multiple testing was done with FDR. Significant GO terms with FDR values < 0.05 were extracted. Significantly DE transcripts were annotated with pathway information from the KEGG pathway database using the R package clusterProfiler [92]. Pathway over-representation was assessed with a significance cut-off of 0.05.

Quantitative real-time polymerase chain reaction (RT-qPCR)

A total of 10 male-associated and 10 female-associated DE transcripts, as well as 10 non-DE transcripts, were randomly selected for validation using RT-qPCR. First-strand cDNA synthesis and qPCR validation experiments were performed with three different biological replicates from the same samples used in RNA-Seq experiments. Total RNA (1 μg) from each biological replicate was treated with 1 U of DNase I (Thermo Fisher Scientific, Waltham, MA, USA) and used to synthesize first-strand cDNA using a RevertAid First Strand cDNA Synthesis kit (Thermo Fisher Scientific) according to the manufacturer’s instructions. The expression level of each gene was determined by SYBR Green RT-qPCR. Each 20 μl reaction mixture contained 2 μl of first-strand cDNA, 1× iTaq Universal SYBR Green Supermix (Bio-Rad Laboratories, Philadelphia, PA, USA), and 300 nM each of forward and reverse primers. To normalize gene expression levels, 18S ribosomal RNA (rRNA) was used as an internal control [93, 94]. Amplification was performed on a CFX96 Real-Time PCR System (Bio-Rad Laboratories, Hercules, CA, USA), according to the following protocol: pre-incubation at 95 °C for 5 min, followed by 40 cycles of 95 °C for 20 s and 60 °C for 1 min. A melting curve analysis was performed from 65–95 °C. Gene expression levels were calculated using the 2-∆∆Ct method [95]. RT-qPCR experiments were performed with three replicates. Primer sequences for each target gene were designed using Primer3Plus (http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi) with default parameters and are listed in Additional file 15: Table S9. Correlation between RNA-Seq and qPCR results for 30 representative transcripts was analyzed using the Spearman’s rank test.

Abbreviations

CDS: 

Coding DNA sequence

CPM: 

Counts per million

DE: 

Differentially expressed

ESTs: 

Expressed sequence tags

FC: 

Fold change

FDR: 

False discovery rate

FPKM: 

Fragments per kilobase of exon per million fragments mapped

GO: 

Gene ontology

KEGG: 

Kyoto Encyclopedia of Genes and Genomes

NGS: 

Next-generation sequencing

ORFs: 

Open reading frames

PF: 

Paired-end

Pfam: 

Protein profile database

SRA: 

Sequence read archive

TPM: 

Transcripts per million

UniProt: 

The Universal Protein Knowledgebase

Declarations

Acknowledgements

We thank the Department of Helminthology and the Applied Malacology Laboratory, Department of Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University for supporting all facilities and providing S. mekongi in this study, respectively. Our gratitude also goes to the Central Equipment Unit, Faculty of Tropical Medicine, Mahidol University for facilitating us all necessary instruments. We thank Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.

Funding

This study was supported by FTM grant (Fiscal Year 2013) through Dr. Poom Adisakwattana, and ICTM Grants from the Faculty of Tropical Medicine, Mahidol University.

Availability of data and materials

RNA-Seq reads have been deposited in the NCBI-Sequence Read Archive (SRA) database under accession numbers SRP136896 and PRJNA445936.

Authors’ contributions

OP, PAJ and PAD conceived and designed the study. OP SN and SC performed the experiments. OP, PAJ and PAD analyzed the data. OP, BES and PAD drafted the manuscript. YL, OR, SA, PD and DW helped in study design, study implementation and manuscript revision. All authors read and approved the final manuscript.

Ethics approval

All procedures performed on animals in this study were conducted following the ethical principles and guidelines for the use of animals at the National Research Council of Thailand (NRCT) and with permission from the Faculty of Tropical Medicine Animal Care and Use Committee (FTM-ACUC), Mahidol University, with approval number FTM-ACUC 014/2016.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis 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.

Authors’ Affiliations

(1)
Department of Helminthology, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
(2)
Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, Thailand
(3)
Department of Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
(4)
Department of Molecular Tropical Medicine and Genetics, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
(5)
Department of Tropical Pathology, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
(6)
Department of Enteric Diseases, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand

References

  1. Attwood SW. Schistosomiasis in the Mekong region: epidemiology and phylogeography. Adv Parasitol. 2001;50:87–152.View ArticlePubMedGoogle Scholar
  2. Ross AG, Sleigh AC, Li Y, Davis GM, Williams GM, Jiang Z, et al. Schistosomiasis in the People’s Republic of China: prospects and challenges for the 21st century. Clin Microbiol Rev. 2001;14:270–95.Google Scholar
  3. Muth S, Sayasone S, Odermatt-Biays S, Phompida S, Duong S, Odermatt P. Schistosoma mekongi in Cambodia and Lao People’s Democratic Republic. Adv Parasitol. 2010;72:179–203.View ArticlePubMedGoogle Scholar
  4. Clerinx J, Van Gompel A. Schistosomiasis in travellers and migrants. Travel Med Infect Dis. 2011;9:6–24.View ArticlePubMedGoogle Scholar
  5. Campa P, Develoux M, Belkadi G, Magne D, Lame C, Carayon MJ, et al. Chronic Schistosoma mekongi in a traveler-a case report and review of the literature. J Travel Med. 2014;21:361–3.View ArticlePubMedGoogle Scholar
  6. Leshem E, Meltzer E, Marva E, Schwartz E. Travel-related schistosomiasis acquired in Laos. Emerg Infect Dis. 2009;15:1823–6.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Attwood SW. Chapter 11. Mekong schistosomiasis: where did it come from and where is it going? In: Campbell IC, editor. Aquatic Ecology, The Mekong. New York: Academic Press, Elsevier; 2009. p. 273–95.Google Scholar
  8. Gray DJ, Ross AG, Li YS, McManus DP. Diagnosis and management of schistosomiasis. BMJ. 2011;342:d2651.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Wang W, Wang L, Liang Y-S. Susceptibility or resistance of praziquantel in human schistosomiasis: a review. Parasitol Res. 2012;111:1871–7.View ArticlePubMedGoogle Scholar
  10. Fallon PG, Doenhoff MJ. Drug-resistant schistosomiasis: resistance to praziquantel and oxamniquine induced in Schistosoma mansoni in mice is drug specific. Am J Trop Med Hyg. 1994;51:83–8.View ArticlePubMedGoogle Scholar
  11. King CH, Muchiri EM, Ouma JH. Evidence against rapid emergence of praziquantel resistance in Schistosoma haematobium, Kenya. Emerg Infect Dis. 2000;6:585–94.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Seto EYW, Wong BK, Lu D, Zhong B. Human schistosomiasis resistance to praziquantel in China: should we be worried? Am J Trop Med Hyg. 2011;85:74–82.View ArticlePubMedPubMed CentralGoogle Scholar
  13. French MD, Churcher TS, Gambhir M, Fenwick A, Webster JP, Kabatereine NB, et al. Observed reductions in Schistosoma mansoni transmission from large-scale administration of praziquantel in Uganda: a mathematical modelling study. PLoS Negl Trop Dis. 2010;4:e897.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Tebeje BM, Harvie M, You H, Loukas A, McManus DP. Schistosomiasis vaccines: where do we stand? Parasit Vectors. 2016;9:528.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Franco GR, Adams MD, Soares MB, Simpson AJG, Venter JC, Pena SDJ. Identification of new S chistosoma mansoni genes by the EST strategy using a directional cDNA library. Gene. 1995;152:141–7.Google Scholar
  16. Franco GR, Rabelo EM, Azevedo V, Pena HB, Ortega JM, Santos TM, et al. Evaluation of cDNA libraries from different developmental stages of Schistosoma mansoni for production of expressed sequence tags (ESTs). DNA Res. 1997;4:231–40.View ArticlePubMedGoogle Scholar
  17. Merrick JM, Osman A, Tsai J, Quackenbush J, LoVerde PT, Lee NH. The Schistosoma mansoni gene index: gene discovery and biology by reconstruction and analysis of expressed gene sequences. J Parasitol. 2003;89:261–9.View ArticlePubMedGoogle Scholar
  18. Peng HJ, Chen XG, Wang XZ, Lun ZR. Analysis of the gene expression profile of Schistosoma japonicum cercariae by a strategy based on expressed sequence tags. Parasitol Res. 2003;90:287–93.View ArticlePubMedGoogle Scholar
  19. Fung MC, Lau MT, Chen XG. Expressed sequence tag (EST) analysis of a Schistosoma japonicum cercariae cDNA library. Acta Trop. 2002;82:215–24.View ArticlePubMedGoogle Scholar
  20. Fitzpatrick JM, Johansen MV, Johnston DA, Dunne DW, Hoffmann KF. Gender-associated gene expression in two related strains of Schistosoma japonicum. Mol Biochem Parasitol. 2004;136:191–209.View ArticlePubMedGoogle Scholar
  21. Fitzpatrick JM, Johnston DA, Williams GW, Williams DJ, Freeman TC, Dunne DW, et al. An oligonucleotide microarray for transcriptome analysis of Schistosoma mansoni and its application/use to investigate gender-associated gene expression. Mol Biochem Parasitol. 2005;141:1–13.View ArticlePubMedGoogle Scholar
  22. Fitzpatrick JM, Hoffmann KF. Dioecious Schistosoma mansoni express divergent gene repertoires regulated by pairing. Int J Parasitol. 2006;36:1081–9.View ArticlePubMedGoogle Scholar
  23. Moertel L, McManus DP, Piva TJ, Young L, McInnes RL, Gobert GN. Oligonucleotide microarray analysis of strain- and gender-associated gene expression in the human blood fluke, Schistosoma japonicum. Mol Cell Probes. 2006;20:280–9.View ArticlePubMedGoogle Scholar
  24. Waisberg M, Lobo FP, Cerqueira GC, Passos LK, Carvalho OS, Franco GR, et al. Microarray analysis of gene expression induced by sexual contact in Schistosoma mansoni. BMC Genomics. 2007;8:181.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Ojopi EP, Oliveira PS, Nunes DN, Paquola A, DeMarco R, Gregorio SP, et al. A quantitative view of the transcriptome of Schistosoma mansoni adult-worms using SAGE. BMC Genomics. 2007;8:186.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Williams DL, Sayed AA, Bernier J, Birkeland SR, Cipriano MJ, Papa AR, et al. Profiling Schistosoma mansoni development using serial analysis of gene expression (SAGE). Exp Parasitol. 2007;117:246–58.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Cogswell AA, Kommer VP, Williams DL. Transcriptional analysis of a unique set of genes involved in Schistosoma mansoni female reproductive biology. PLoS Negl Trop Dis. 2012;6:e1970.View ArticleGoogle Scholar
  28. Rho M. New bioinformatics algorithms applied to deep sequencing projects. In: Bagnoli F, Rappuoli R, editors. Advanced Vaccine Research Methods for the Decade of Vaccines. Norfolk: Caister Academic Press. 2015. p. 33–64.Google Scholar
  29. Chauhan P, Hansson B, Kraaijeveld K, de Knijff P, Svensson EI, Wellenreuther M. De novo transcriptome of Ischnura elegans provides insights into sensory biology, colour and vision genes. BMC Genomics. 2014;15:808.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Liu J, Wang S, Qin T, Li N, Niu Y, Li D, et al. Whole transcriptome analysis of Penicillium digitatum strains treatmented with prochloraz reveals their drug-resistant mechanisms. BMC Genomics. 2015;16:855.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Petrella V, Aceto S, Musacchia F, Colonna V, Robinson M, Benes V, et al. De novo assembly and sex-specific transcriptome profiling in the sand fly Phlebotomus perniciosus (Diptera, Phlebotominae), a major Old World vector of Leishmania infantum. BMC Genomics. 2015;16:847.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Hagel JM, Morris JS, Lee EJ, Desgagne-Penix I, Bross CD, Chang L, et al. Transcriptome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants. BMC Plant Biol. 2015;15:227.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Gu XC, Zhang YN, Kang K, Dong SL, Zhang LW. Antennal transcriptome analysis of odorant reception genes in the Red Turpentine Beetle (RTB), Dendroctonus valens. PLoS One. 2015;10:e0125159.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Sun J, Wang SW, Li C, Hu W, Ren YJ, Wang JQ. Transcriptome profilings of female Schistosoma japonicum reveal significant differential expression of genes after pairing. Parasitol Res. 2014;113:881–92.View ArticlePubMedGoogle Scholar
  35. Protasio AV, Tsai IJ, Babbage A, Nichol S, Hunt M, Aslett MA, et al. A systematically improved high quality genome and transcriptome of the human blood fluke Schistosoma mansoni. PLoS Negl Trop Dis. 2012;6:e1455.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Anderson L, Amaral MS, Beckedorff F, Silva LF, Dazzani B, Oliveira KC, et al. Schistosoma mansoni egg, adult male and female comparative gene expression analysis and identification of novel genes by RNA-Seq. PLoS Negl Trop Dis. 2015;9:e0004334.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Picard MA, Boissier J, Roquis D, Grunau C, Allienne JF, Duval D, et al. Sex-biased transcriptome of Schistosoma mansoni: host-parasite interaction, genetic determinants and epigenetic regulators are associated with sexual differentiation. PLoS Negl Trop Dis. 2016;10:e0004930.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Wang J, Yu Y, Shen H, Qing T, Zheng Y, Li Q, et al. Dynamic transcriptomes identify biogenic amines and insect-like hormonal regulation for mediating reproduction in Schistosoma japonicum. Nat Commun. 2017;8:14693.View ArticlePubMedPubMed CentralGoogle Scholar
  39. Wang X, Xu X, Lu X, Zhang Y, Pan W. Transcriptome bioinformatical analysis of vertebrate stages of Schistosoma japonicum reveals alternative splicing events. PLoS One. 2015;10:e0138470.View ArticlePubMedPubMed CentralGoogle Scholar
  40. Liu GH, Xu MJ, Chang QC, Gao JF, Wang CR, Zhu XQ. De novo transcriptomic analysis of the female and male adults of the blood fluke Schistosoma turkestanicum. Parasit Vectors. 2016;9:143.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Almeida GT, Amaral MS, Beckedorff FC, Kitajima JP, DeMarco R, Verjovski-Almeida S. Exploring the Schistosoma mansoni adult male transcriptome using RNA-seq. Exp Parasitol. 2012;132:22–31.View ArticlePubMedGoogle Scholar
  42. Lu Z, Sessler F, Holroyd N, Hahnel S, Quack T, Berriman M, et al. A gene expression atlas of adult Schistosoma mansoni and their gonads. Sci Data. 2017;4:170118.View ArticlePubMedPubMed CentralGoogle Scholar
  43. Young ND, Jex AR, Li B, Liu S, Yang L, Xiong Z, et al. Whole-genome sequence of Schistosoma haematobium. Nat Genet. 2012;44:221–5.View ArticlePubMedGoogle Scholar
  44. Sinuon M, Tsuyuoka R, Socheat D, Odermatt P, Ohmae H, Matsuda H, et al. Control of Schistosoma mekongi in Cambodia: results of eight years of control activities in the two endemic provinces. Trans R Soc Trop Med Hyg. 2007;101:34–9.View ArticlePubMedGoogle Scholar
  45. Sayasone S, Utzinger J, Akkhavong K, Odermatt P. Multiparasitism and intensity of helminth infections in relation to symptoms and nutritional status among children: a cross-sectional study in southern Lao People’s Democratic Republic. Acta Trop. 2015;141:322–31.View ArticlePubMedGoogle Scholar
  46. Vonghachack Y, Sayasone S, Khieu V, Bergquist R, van Dam GJ, Hoekstra PT, et al. Comparison of novel and standard diagnostic tools for the detection of Schistosoma mekongi infection in Lao People’s Democratic Republic and Cambodia. Infect Dis Poverty. 2017;6:127.View ArticlePubMedPubMed CentralGoogle Scholar
  47. Ohmae H, Sinuon M, Kirinoki M, Matsumoto J, Chigusa Y, Socheat D, et al. Schistosomiasis mekongi: from discovery to control. Parasitol Int. 2004;53:135–42.View ArticlePubMedGoogle Scholar
  48. Rana SB, Zadlock FJ, Zhang Z, Murphy WR, Bentivegna CS. Comparison of de novo transcriptome assemblers and k-mer strategies using the killifish, Fundulus heteroclitus. PLoS One. 2016;11:e0153104.View ArticlePubMedPubMed CentralGoogle Scholar
  49. Hoffmann KF, Johnston DA, Dunne DW. Identification of Schistosoma mansoni gender-associated gene transcripts by cDNA microarray profiling. Genome Biol. 2002;3:41.Google Scholar
  50. Piao X, Cai P, Liu S, Hou N, Hao L, Yang F, et al. Global expression analysis revealed novel gender-specific gene expression features in the blood fluke parasite Schistosoma japonicum. PLoS One. 2011;6:e18267.View ArticlePubMedPubMed CentralGoogle Scholar
  51. Cai P, Liu S, Piao X, Hou N, Gobert GN, McManus DP, et al. Comprehensive transcriptome analysis of sex-biased expressed genes reveals discrete biological and physiological features of male and female Schistosoma japonicum. PLoS Negl Trop Dis. 2016;10:e0004684.View ArticlePubMedPubMed CentralGoogle Scholar
  52. Beckmann S, Quack T, Dissous C, Cailliau K, Lang G, Grevelding CG. Discovery of platyhelminth-specific alpha/beta-integrin families and evidence for their role in reproduction in Schistosoma mansoni. PLoS One. 2012;7:e52519.View ArticlePubMedPubMed CentralGoogle Scholar
  53. Gelmedin V, Morel M, Hahnel S, Cailliau K, Dissous C, Grevelding CG. Evidence for integrin-venus kinase receptor 1 alliance in the ovary of Schistosoma mansoni females controlling cell survival. PLoS Pathog. 2017;13:e1006147.View ArticlePubMedPubMed CentralGoogle Scholar
  54. Safaee M, Clark AJ, Ivan ME, Oh MC, Bloch O, Sun MZ, et al. CD97 is a multifunctional leukocyte receptor with distinct roles in human cancers (Review). Int J Oncol. 2013;43:1343–50.View ArticlePubMedGoogle Scholar
  55. Morel M, Vanderstraete M, Hahnel S, Grevelding CG, Dissous C. Receptor tyrosine kinases and schistosome reproduction: new targets for chemotherapy. Front Genet. 2014;5:238.View ArticlePubMedPubMed CentralGoogle Scholar
  56. Campos TD, Young ND, Korhonen PK, Hall RS, Mangiola S, Lonie A, et al. Identification of G protein-coupled receptors in Schistosoma haematobium and S. mansoni by comparative genomics. Parasit Vectors. 2014;7:242.View ArticlePubMedPubMed CentralGoogle Scholar
  57. Hahnel S, Wheeler N, Lu Z, Wangwiwatsin A, McVeigh P, Maule A, et al. Tissue-specific transcriptome analyses provide new insights into GPCR signalling in adult Schistosoma mansoni. PLoS Pathog. 2018;14:e1006781.View ArticleGoogle Scholar
  58. Walker AJ, Ressurreicao M, Rothermel R. Exploring the function of protein kinases in schistosomes: perspectives from the laboratory and from comparative genomics. Front Genet. 2014;5:229.View ArticlePubMedPubMed CentralGoogle Scholar
  59. Alger HM, Sayed AA, Stadecker MJ, Williams DL. Molecular and enzymatic characterisation of Schistosoma mansoni thioredoxin. Int J Parasitol. 2002;32:1285–92.View ArticlePubMedGoogle Scholar
  60. Angelucci F, Sayed AA, Williams DL, Boumis G, Brunori M, Dimastrogiovanni D, et al. Inhibition of Schistosoma mansoni thioredoxin-glutathione reductase by auranofin: structural and kinetic aspects. J Biol Chem. 2009;284:28977–85.View ArticlePubMedPubMed CentralGoogle Scholar
  61. Boumis G, Angelucci F, Bellelli A, Brunori M, Dimastrogiovanni D, Miele AE. Structural and functional characterization of Schistosoma mansoni thioredoxin. Protein Sci. 2011;20:1069–76.View ArticlePubMedPubMed CentralGoogle Scholar
  62. Huang HH, Day L, Cass CL, Ballou DP, Williams CH Jr, Williams DL. Investigations of the catalytic mechanism of thioredoxin glutathione reductase from Schistosoma mansoni. Biochemistry. 2011;50:5870–82.View ArticlePubMedPubMed CentralGoogle Scholar
  63. Song L, Li J, Xie S, Qian C, Wang J, Zhang W, et al. Thioredoxin glutathione reductase as a novel drug target: evidence from Schistosoma japonicum. PLoS One. 2012;7:e31456.View ArticlePubMedPubMed CentralGoogle Scholar
  64. Li Y, Li P, Peng Y, Wu Q, Huang F, Liu X, et al. Expression, characterization and crystal structure of thioredoxin from Schistosoma japonicum. Parasitology. 2015;142:1044–52.View ArticlePubMedGoogle Scholar
  65. Salter JP, Lim KC, Hansell E, Hsieh I, McKerrow JH. Schistosome invasion of human skin and degradation of dermal elastin are mediated by a single serine protease. J Biol Chem. 2000;275:38667–73.View ArticlePubMedGoogle Scholar
  66. Gobert GN, McManus DP, Nawaratna S, Moertel L, Mulvenna J, Jones MK. Tissue specific profiling of females of Schistosoma japonicum by integrated laser microdissection microscopy and microarray analysis. PLoS Negl Trop Dis. 2009;3:e469.View ArticlePubMedPubMed CentralGoogle Scholar
  67. Lu Z, Sessler F, Holroyd N, Hahnel S, Quack T, Berriman M, et al. Schistosome sex matters: a deep view into gonad-specific and pairing-dependent transcriptomes reveals a complex gender interplay. Sci Rep. 2016;6:31150.View ArticlePubMedPubMed CentralGoogle Scholar
  68. Kunz W. Schistosome male-female interaction: induction of germ-cell differentiation. Trends Parasitol. 2001;17:227–31.View ArticlePubMedGoogle Scholar
  69. You H, Zhang W, Moertel L, McManus DP, Gobert GN. Transcriptional profiles of adult male and female Schistosoma japonicum in response to insulin reveal increased expression of genes involved in growth and development. Int J Parasitol. 2009;39:1551–9.View ArticlePubMedGoogle Scholar
  70. You H, Gobert GN, Cai P, Mou R, Nawaratna S, Fang G, et al. Suppression of the insulin receptors in adult Schistosoma japonicum impacts on parasite growth and development: further evidence of vaccine potential. PLoS Negl Trop Dis. 2015;9:e0003730.View ArticlePubMedPubMed CentralGoogle Scholar
  71. Hassan BA, Prokopenko SN, Breuer S, Zhang B, Paululat A, Bellen HJ. skittles, a Drosophila phosphatidylinositol 4-phosphate 5-kinase, is required for cell viability, germline development and bristle morphology, but not for neurotransmitter release. Genetics. 1998;150:1527–37.PubMedPubMed CentralGoogle Scholar
  72. Corvera S, D’Arrigo A, Stenmark H. Phosphoinositides in membrane traffic. Curr Opin Cell Biol. 1999;11:460–5.Google Scholar
  73. Tawk L, Chicanne G, Dubremetz JF, Richard V, Payrastre B, Vial HJ, et al. Phosphatidylinositol 3-phosphate, an essential lipid in Plasmodium, localizes to the food vacuole membrane and the apicoplast. Eukaryot Cell. 2010;9:1519–30.View ArticlePubMedPubMed CentralGoogle Scholar
  74. Morris JZ, Tissenbaum HA, Ruvkun G. A phosphatidylinositol-3-OH kinase family member regulating longevity and diapause in Caenorhabditis elegans. Nature. 1996;382:536–9.View ArticlePubMedGoogle Scholar
  75. Biron D, Shibuya M, Gabel C, Wasserman SM, Clark DA, Brown A, et al. A diacylglycerol kinase modulates long-term thermotactic behavioral plasticity in C. elegans. Nat Neurosci. 2006;9:1499–505.View ArticlePubMedGoogle Scholar
  76. Xu X, Guo H, Wycuff DL, Lee M. Role of phosphatidylinositol-4-phosphate 5′ kinase (ppk-1) in ovulation of Caenorhabditis elegans. Exp Cell Res. 2007;313:2465–75.View ArticlePubMedPubMed CentralGoogle Scholar
  77. Ohno H, Kato S, Naito Y, Kunitomo H, Tomioka M, Iino Y. Role of synaptic phosphatidylinositol 3-kinase in a behavioral learning response in C. elegans. Science. 2014;345:313–7.View ArticlePubMedGoogle Scholar
  78. Uzumcu M, Westfall SD, Dirks KA, Skinner MK. Embryonic testis cord formation and mesonephric cell migration requires the phosphotidylinositol 3-kinase signaling pathway. Biol Reprod. 2002;67:1927–35.View ArticlePubMedGoogle Scholar
  79. Bott RC, McFee RM, Clopton DT, Toombs C, Cupp AS. Vascular endothelial growth factor and kinase domain region receptor are involved in both seminiferous cord formation and vascular development during testis morphogenesis in the rat. Biol Reprod. 2006;75:56–67.View ArticlePubMedPubMed CentralGoogle Scholar
  80. Duvall RH, DeWitt WB. An improved perfusion technique for recovering adult schistosomes from laboratory animals. Am J Trop Med Hyg. 1967;16:483–6.View ArticlePubMedGoogle Scholar
  81. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.View ArticlePubMedPubMed CentralGoogle Scholar
  82. Chang Z, Li G, Liu J, Zhang Y, Ashby C, Liu D, et al. Bridger: a new framework for de novo transcriptome assembly using RNA-seq data. Genome Biol. 2015;16:30.View ArticlePubMedPubMed CentralGoogle Scholar
  83. Smith-Unna R, Boursnell C, Patro R, Hibberd JM, Kelly S. TransRate: reference-free quality assessment of de novo transcriptome assemblies. Genome Res. 2016;26:1134–44.View ArticlePubMedPubMed CentralGoogle Scholar
  84. Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357–60.View ArticlePubMedPubMed CentralGoogle Scholar
  85. Li W, Godzik A. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22:1658–9.View ArticlePubMedGoogle Scholar
  86. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: Architecture and applications. BMC Bioinformatics. 2009;10:421.View ArticlePubMedPubMed CentralGoogle Scholar
  87. The UniProt Consortium. The Universal Protein Resource (UniProt). Nucleic Acids Res. 2007;35(Database issue):d193–7.View ArticleGoogle Scholar
  88. Eddy SR. Profile hidden Markov models. Bioinformatics. 1998;14:755–63.View ArticlePubMedGoogle Scholar
  89. Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10:R25.View ArticlePubMedPubMed CentralGoogle Scholar
  90. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323.View ArticlePubMedPubMed CentralGoogle Scholar
  91. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.Google Scholar
  92. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–7.Google Scholar
  93. Dillon GP, Feltwell T, Skelton J, Coulson PS, Wilson RA, Ivens AC. Altered patterns of gene expression underlying the enhanced immunogenicity of radiation-attenuated schistosomes. PLoS Negl Trop Dis. 2008;2:e240.View ArticlePubMedPubMed CentralGoogle Scholar
  94. Parker-Manuel SJ, Ivens AC, Dillon GP, Wilson RA. Gene expression patterns in larval Schistosoma mansoni associated with infection of the mammalian host. PLoS Negl Trop Dis. 2011;5:e1274.View ArticlePubMedPubMed CentralGoogle Scholar
  95. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 2001;25:402–8.View ArticlePubMedGoogle Scholar

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