c mice with or without Schistosoma japonicum infection: Clues to the abnormal growth and development of schistosome in SCID mice

Acta Tropica 200 (2019) 105186

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Comparative serum metabolomics between SCID mice and BALB/c mice with or without Schistosoma japonicum infection: Clues to the abnormal growth and development of schistosome in SCID mice Liu Rong, Ye Feng, Zhong Qin-Ping, Wang Shu-Hong, Chai Ting, Dong Hui-Fen, Ming Zhenping

T

⁎

School of Basic Medical Sciences, Wuhan University, Wuhan 430071, China

ARTICLE INFO

ABSTRACT

Keywords: BALB/c mice Growth and development retardation LC–MS/MS Serum metabolomics Schistosoma japonicum SCID mice

The small blood flukes of genus Schistosoma, which cause one of the most prevalent and serious parasitic zoonosis schistosomiasis, are dependent on immune-related factors of their mammalian host to facilitate their growth and development, and the formation of granulomatous pathology caused by eggs deposited in host's liver and intestinal wall. Schistosome development is hampered in the mice lacking just T cells, and is even more heavily retarded in the severe combined immunodeficient (SCID) mice lacking both T and B lymphocytes. Nevertheless, it's still not clear about the underlying regulatory molecular mechanisms of schistosome growth and development by host's immune system. This study, therefore, detected and compared the serum metabolic profiles between the immunodeficient mice and immunocompetent mice (SCID mice vs. BALB/c mice) before and after S. japonicum infection (on the thirty-fifth day post infection using liquid chromatography-mass spectrometry (LC–MS). Totally, 705 ion features in electrospray ionization in positive-ion mode (ESI+) and 242 ion features in ESI− mode were identified, respectively. First, distinct serum metabolic profiles were identified between SCID mice and BALB/c mice without S. japonicum worms infection. Second, uniquely perturbed serum metabolites and their enriched pathways were also obtained between SCID mice and BALB/c mice after S. japonicum infection, which included differential metabolites due to both species differences and differential responses to S. japonicum infection. The metabolic pathways analysis revealed that arachidonic acid metabolism, biosynthesis of unsaturated fatty acids, linoleic acid metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, alpha-linolenic acid metabolism, glycerophospholipid metabolism, sphingolipid metabolism and purine metabolism were enriched based on the differential serum metabolites between SCID mice and BALB/c mice after S. japonicum infection, which was addressed to be related to the retarded growth and development of S. japonicum in SCID mice. These findings provide new clues to the underlying molecular events of host's systemic metabolic changes on the growth and development of S. japonicum worms, and also provide quite promising candidates for exploitation of drugs or vaccines against schistosome and schistosomiasis.

1. Introduction Schistosomiasis, caused largely by infection with any of the small parasitic blood fluke S. mansoni, S. japonicum, S. haematobium, S. mekongi, S. guineensis and S. intercalatum, remains one of the most prevalent and serious parasitic diseases worldwide. An estimated 240 million people are suffering from the infection and 700 million people are at risk of being infected as living in the endemic areas in 76 countries and territories located mainly in tropical and subtropical regions (Adenowo et al., 2015; Gray et al., 2010; WHO, 2014), ranking it second only to malaria in the list of global neglected tropical diseases

(Utzinger et al., 2012). The schistosomes exhibit dioecy and have a complex life cycle, which comprises several distinct phenotypes in their definitive hosts mammals and intermediate hosts – snails (Ross et al., 2002). After burrowing out of their snail hosts, the free-swimming cercariae could penetrate the exposed skin of their mammalian hosts. After penetration, schistosomes migrate through the blood flow via the lung to the portal venous system, where they mate and mature. The adult pairs of worms then migrate to the superior mesenteric veins (in the case of S. mansoni), the inferior mesenteric and superior hemorrhoidal veins (in the case of S. japonicum), or the vesical plexus and veins draining the

⁎ Corresponding author at: Department of Medical Parasitology, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan 430071, Hubei, China. E-mail address: [email protected] (Z. Ming).

https://doi.org/10.1016/j.actatropica.2019.105186 Received 20 January 2019; Received in revised form 12 September 2019; Accepted 18 September 2019 Available online 19 September 2019 0001-706X/ © 2019 Elsevier B.V. All rights reserved.

Acta Tropica 200 (2019) 105186

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ureters (in the case of S. haematobium), where the females lay hundreds to thousands of eggs every day. Eggs deposited in the liver, intestinal wall and other tissues are the key pathogenic factor to severe schistosomiasis, which is manifested mainly as portal vein hypertension syndrome, i.e. enlargement of the liver, ascites and extensive liver fibrosis at the late stage (Ross et al., 2002). Eggs pass from the lumen of blood vessels into adjacent tissues, and many of them then pass through the intestinal or bladder mucosa and are shed finally in the feces (in the case of S. mansoni and S. japonicum) or urine (in the case of S. haematobium). Their life cycle is completed when the eggs hatch to release the free-swimming miracidia, which in turn infect specific freshwater snails (S. mansoni infects biomphalaria species, S. haematobium infects bulinus species, and S. japonicum infects oncomelania species), and further produce a huge quantity of cercariae. Numerous researches have reported that the schistosome worms require their mammal host-derived endocrine and immune factors as stimulators for their development, early fecundity and egg-laying (Amiri et al., 1992; Cheever et al., 1999; Davies et al., 2004; de Mendonca et al., 2000; Halton, 1997; Hernandez et al., 2004; Ozaki et al., 1997; Saule et al., 2002; You et al., 2015), although some discrepancies about some details of results were reported in some different researches (Amiri et al., 1992; Cheever et al., 1999). Interestingly and thought-provoking, it was a common finding that schistosome showed retarded growth, development and reproduction in the immunodeficient mammalian hosts, and exerted attenuated pathogenesis with decreased egg-laying and granulomas formation in the hosts (Blank et al., 2006; Cheng et al., 2008; Davies et al., 2001; Lamb et al., 2010; Tang et al., 2013). These researches, which focused mainly on the host factors, revealed that interleukin (IL)-2 and IL-7 indirectly modulated blood fluke development via affecting CD4+ T lymphocytes, which were also just limited to providing non-cognate help for mononuclear phagocyte function (Blank et al., 2006; Cheng et al., 2008; Davies et al., 2001; Lamb et al., 2010). Even though tumor necrosis factor (TNF) was identified to play a role in maintaining adult schistosome viability and egg-laying of female worms in the portal system with independence of the TNF receptors TNFR1 and TNFR2 (Amiri et al., 1992; Ozaki et al., 1997), these findings are limited and just a very small piece of the whole complex host's molecular networks, which should coordinately manage the growth and development of the parasitic worms (Halton, 1997; You et al., 2015). It is a promising approach to enhance our understanding about the effects of host factors on parasite's growth and development on a systemic level by exploring key molecules and signaling pathways competent for elucidating the distinct phenotypic variations (Fiehn, 2002), yet its potentiality for investigating molecular mechanism of parasite – host interactions has been underused. Metabolomics involves investigation of multivariate metabolic responses of host's inner environment to the complex multicellular parasite infection, which could reflect the modulation of parasites’ growth and development by their hosts, and the disease progress of host (Wang et al., 2006; Wu et al., 2010a,b; Zhou et al., 2017; Zhou et al., 2016). The high performance liquid chromatography and mass spectroscopy (HPLC-MS/MS), coupled with data-reduction techniques, is a powerful approach to generate and analyze high-dimensional information such as metabolic data on tissues. This high-throughput method is capable of simultaneously detecting a wide range of small molecule metabolites and providing a “metabolic fingerprint” of tissue. The multivariate analysis applied to complex spectral data can aid visualization and characterization of metabolites changes relating to biological perturbations. Metabolomics has been used as a well-established analytical tool with successful application in different fields, e.g., the evaluation of disease progress, detection of metabolites associated with inborn defects, differentiating phenotypes of experimental animal models (Adebayo et al., 2018; Ball et al., 1948; Balog et al., 2011; Cui et al., 2016; Park et al., 2015; Teng et al., 2009; Vincent and Barrett, 2015; von Brand, 1967; Zhou et al., 2017; Zhou et al., 2015; Zhou et al., 2016).

In this study, therefore, we investigated the serum metabonomic perturbations and variations of severe combined immunodeficient (SCID) mice when compared with those of BALB/c mice before and after S. japonicum infection for five weeks using HPLC-MS/MS and multivariate data analysis, with an aim to explore metabonomic clues of hosts for elucidating the effects of host's factors on abnormality in growth and development of S. japonicum worms in SCID mice. This will also offer a new insight from a systematic and metabolic aspect into the molecular regulation of schistosome growth and development by host's immune-related factors. 2. Materials and methods 2.1. Ethics statement All experiments using the S. japonicum parasite, Oncomelania hupensis (O. hupensis) snails, and mice were performed under protocols approved by Wuhan University Center for Animal Experiments (WUCAE) according to the Regulations for the Administration of Affairs Concerning Experimental Animals of China (Ethical approval number: 2016025). 2.2. Parasites and animals O. hupensis snails infected with S. japonicum were purchased from the Institute of Parasitic Disease Control and Prevention, Hunan Province, China. Cercariae were released by exposing the infected snails to artificial light in aged tap water for about 2 h at 25 °C. Twenty immunocompetent female BALB/c mice and twenty SCID female mice with BALB/c mice background, which were approximately 6–8 weeks old, were purchased from BEIJING HUAFUKANG BIOSCIENCE CO. INC via WUCAE. All mice were housed under specific pathogen-free conditions in an American Association for the Accreditation of Laboratory Animal Care internationally approved facility of WUCAE. All animals had free access to water and standard rodent diet. After twelve days of acclimatization, half of the SCID mice and BALB/c mice were infected percutaneously via the shaved abdominal skin with approximately 40 cercariae per mouse. The remaining mice were left uninfected as the controls. Thus, the mice were allocated into four groups, i.e. the uninfected BALB/c mice (Group OB), the infected BALB/c mice (Group IB), the uninfected SCID mice (Group OS) and the infected SCID mice (Group IS). On the thirty-fifth day post infection, when distinct phenotypic differences exhibited between schistosome worms from SCID mice and those from BALB/c mice (Ozaki et al., 1997; Tang et al., 2013), both the infected and control mice were sacrificed by blood-letting via removing one eyeball after anesthesia. The whole blood was collected and serum was isolated by centrifugation at 2 000 rpm for 10 min at 4 °C after clotting at 37 °C for 30 min and contracting at 4 °C for 30 min. Totally 40 mice serum samples with 100 µl serum in each sample of above four groups (labeled as OB1–OB10 for sera of control BALB/c mice, OS1–OS10 for sera of control SCID mice, IB1–IB10 for sera of infected BALB/c mice, and IS1-IS10 for sera of infected SCID mice), together with the QC sample made by mixing of isovolumetric serum from the above 40 samples, were finally allocated and preserved at −80 °C. Schistosome was recovered by hepatoportal perfusion of mice with phosphate buffered solution (PBS) containing heparin. The worms were washed with PBS twice and separated by sex manually under anatomical lens, and were finally allocated 20 worms for each aliquot and preserved at −80 °C for comparative metabolomics investigation of schistosome worms, the article about which had been published elsewhere (Liu et al., 2019). 2.3. Sample preparation Totally 40 frozen mice serum samples of the above four groups, 2

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R. Liu, et al.

together with the QC serum sample, were used for sample preparation and metabonomic detection and analysis using HPLC-MS/MS. The LC–MS grade methanol and acetonitrile was purchased from Merck & Co., Inc., and formic acid was purchased from Sigma-Aldrich Co. LLC. Other reagents were all analytically pure. The serum samples were thawed in dark at room temperature, 50 µl of each sample were mixed with 150 µl of methanol, in which 4 µg/ml of 2-Chloro-L-phenylalanine was added as the internal standard substance, and vortexed them for 5 min. The samples were then centrifuged at 13,000 rpm under 4 °C for 15 min, and 100 µl of the supernatant from each sample was carefully transferred to vials of autosampler for examination. All samples were kept at 4 °C and analyzed in a random manner.

(PCA), Partial Least Squares Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) using the embedded functional module ‘Statistical Analysis’ in the online application MetaboAnalyst (http://www.metaboanalyst.ca/) to discriminate comparison groups. Features were filtered out if their relative standard deviations (RSDs) were larger than 25% in the QC samples, and features with more than 50% missing values were also removed. The quality of the models was evaluated with the relevant parameters R2 and Q2 (Lee et al., 2003). Statistically significant differences between groups were determined using the Student's t-test, and the adjusted P-values (also represented as false discovery rates, FDR) were generated by Bonferroni correction to ensure that metabolite peaks were reproducibly detected. FDR value of <0.05 was set as the cutoff value for statistical significance. Relative fold change (FC) was used to show how the selected differential metabolites varied between compared groups, and metabolites with an FC ≥1.2 or ≤0.8 between the compared groups were considered as significantly different with potential biological effect (Feng et al., 2016). The online databases of HMDB and Kyoto Encyclopedia of Genes and Genomes (KEGG; http:// www.genome.jp/kegg) were used to check and confirm the putative identity of the differentially expressed metabolites by matching the exact molecular mass data (m/z) of samples with those from the database. The candidate metabolites were confirmed by MS/MS scans for the characteristic ions and fragmentation patterns of the compound. Metabolite classification was performed by searching metabolite classes against “The Human Metabolome Database” (HMDB, access via http:// www.hmdb.ca/) for metabolite terms enrichment analysis. Heatmaps, which were generated by using the Cluster 3.0 and TreeView softwares (http://bonsai.hgc.jp/∼mdehoon/software/ cluster/software.htm#ctv) based on the abundance of the differentially expressed metabolite data (log2-transformed), were used to depict the relatively disturbed metabolic signatures among the comparison groups (OS vs. OB, IB vs. OB, IS vs. OS, and IS vs. IB) (Halama et al., 2015). Metabolic Pathway Analysis (MetPA), that combines the results from powerful pathway enrichment analyses (by the algorithm Global Test) with those of pathway topology analyses (by the algorithm Relative-betweeness Centrality) in MetaboAnalyst using HMDB (The Human Metabolome Database) as the compound database sources (Wishart et al., 2009; Xia et al., 2015; Xia and Wishart, 2016), was applied to identify relevant pathways of the differential metabolites associated with the abnormal growth of schistosomes in mice. The identified pathways between the compared groups are presented according to -log (P) from the pathway enrichment analysis (y-axis) and pathway impact values from pathway topology analysis (x-axis), with the most impacted pathways colored in red. The P-value represents the enrichment of certain metabolites in a pathway (P ≤ 0.05 is indicative of significant enrichment).

2.4. Metabolomics analysis by HPLC-MS/MS Liquid chromatography was performed on a 1290 Infinity UHPLC system (Agilent Technologies, Santa Clara, CA, U.S.A.). The separation of all samples was performed on an ACQUITY UPLC @HSS T3 column (Waters, U.K.) (100 mm*2.1 mm, 2.5 µm). A gradient elution program was run for chromatographic separation with mobile phase A (0.1% formic acid in water) and mobile phase B (0.1% formic acid in acetonitrile) as follows: 0–2 min, 95%A–95%A; 2–13 min, 95%A–5%A; 13–15 min, 5%A–5%A. The sample injection volume was 3 µL and the flow rate was set as 0.4 mL/min. The column temperature was set at 25 °C, and the post time was set as 5 min. A 6538 UHD and AccurateMass Q-TOF (Agilent Technologies, Santa Clara, CA, USA) equipped with an electrospray ionization (ESI) source was used for mass spectrometric detection. The electrospray ionization mass spectra for sample analysis were acquired in both positive and negative ion modes (ESI+ and ESI−). The operating parameters were as follows: capillary, 4000 V (ESI+) or 3000 V (ESI−); sampling cone: 45 V; source temperature: 120 °C; desolvation gas temperature: 350 °C; desolvation gas flow, 11 L/min; source offset: 60 v; TOF acquisition mode: sensitivity (ESI+) or sensitivity (ESI−); acquisition method, continuum MSE; TOF mass range: 100–1000 Da; scan time: 0.2 s; collision energy function 2: trap CE ramp 20 to 40 eV. QC samples were used in order to assess the reproducibility and reliability of the LC–MS/MS system. QC samples prepared as mentioned above were used to provide a ‘mean’ profile representing all analytes encountered during the analysis. The pooled ‘QC’ samples were run before and after every four serum samples to ensure system equilibration. Two reference compounds purine (C5H4N4) (with m/z 121.0509 in ESI+ mode and m/z 119.0363 in ESI− mode) and hexakis (1H, 1H, 3H-tetrafluoro-pentoxy)-phosphazene (C18H18O6N3P3F24) (with m/z 922.0098 in ESI+ mode and m/z 966.0007 in ESI− mode) were continuously infused into the system to allow constant mass correction during the run. 2.5. Data processing and analysis

3. Results

Raw spectrometric data were analyzed with the MassHunter Qualitative Analysis B.04.00 software (Agilent Technologies, USA) for untargeted peak detection, peak alignment, peak grouping, normalization and integration on each full data set (study samples and QC samples). The molecular features, characterized by retention time, chromatographic peak intensity, and accurate mass, were obtained by using the Molecular Feature Extractor algorithm, which were then analyzed with the MassHunter Mass Profiler Professional software (Agilent Technologies, USA). Only features with an intensity of ≥20,000 counts (approximately three times the detection limit of the LC–MS/MS instrument used in this study) that were found in at least 80% of the samples at the same sampling time point were kept for further processing. Next, a tolerance window of 0.15 min and 2 mDa was used for alignment of retention time and m/z values, and the data were also normalized by the internal standard. The data matrix was then mean-centered and pareto-scaled prior to multivariate analysis (MVA) using Principal Component Analysis

3.1. Metabolic fingerprinting All total ion chromatograms of QC samples were analyzed and the result exhibited a stable retention time without obvious peaks’ drift in both ESI+ and ESI− modes (Fig. S1). Totally, 705 features in ESI+ mode and 242 features in ESI− modes in serum metabolome of SCID mice and BALB/c mice were obtained by electrospray ionization mass spectrometry. The stability and reproducibility of the HPLC-MS/MS method was evaluated by performing PCA on all the samples, including 11 QC samples. The QC samples are clustered in PCA score plots on both ESI+ and ESI− mode (Fig. 1A and B), which indicates good stability and reproducibility of the chromatographic separation during the whole sequence. The experimental samples IS7, IS9 and IS10 were removed from data analysis for obvious outliers among IS1–IS10 in the PCA score plots in order to avoid possible confusions caused by slight hemolysis at sample collection. Two dimensional PCA used to compare 3

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Fig. 1. Differential serum metabolic profiles of SCID mice and BALB/c mice with or without S. japonicum infection. Principal component analysis (PCA) score scatter plots of tested samples and QC samples obtained from LC-MS/MS fingerprints in ESI+ (A) and ESI- (B) modes. PCA score scatter plots of tested samples in ESI+ (C) and ESI− (D) modes. Partial least-squares discriminant analysis (PLS-DA) separating the four experimental groups of mice in ESI+ (E) and ESI− (F) modes. Uninfected BALB/c mice: OB, purple multiple signs. Infected BALB/c mice: IB, red triangles. Uninfected SCID mice: OS, blue diamond icons. Infected SCID mice: IS, green plus signs. Quality controls: QC, pink inverted triangles.

4

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Fig. 2. Discrimination between SCID mice and BALB/c mice without and with S. japonicum infection based on ESI+ and ESI− mode-derived metabolic phenotypes of serum and heatmaps of the differential metabolites between the compared groups. A-B: Orthogonal partial leastsquares discriminant analysis (OPLS-DA) score plots in ESI+ mode (A) and ESI− mode (B) for comparison between SCID mice and BALB/c mice without S. japonicum infection (uninfected BALB/ c mice group is labeled OB and uninfected SCID mice group is labeled OS). C: Heatmap of the differential serum metabolites between SCID mice and BALB/c mice without S. japonicum infection. D: Enriched metabolite terms of the differentially expressed metabolites between uninfected SCID mice and BALB/c mice. The bars on x-axis represent the number of metabolites for the chemical classes mentioned on the y-axis. Green indicates down-changed expression, whereas red indicates up-changed expression of the differential metabolites between compared groups. E-F: OPLS-DA score plots in ESI+ mode (D) and ESI− mode (E) for comparison between BALB/c mice without and with S. japonicum infection (uninfected BALB/c mice group is labeled OB and infected BALB/c mice group is labeled IB). G: Heatmap of the differential serum metabolites between BALB/c mice without and with S. japonicum infection. H: Enriched metabolite terms of the differentially expressed metabolites of BALB/ c mice after infection. I-J: OPLS-DA score plots in ESI+ mode (G) and ESI− mode (H) for comparison between SCID mice without and with S. japonicum infection (uninfected SCID mice group is labeled OS and infected SCID mice group is labeled IS). K: Heatmap of the differential serum metabolites between SCID mice without and with S. japonicum infection. L: Enriched metabolite terms of the differentially expressed metabolites of SCID mice after infection. M-N: OPLS-DA score plots in ESI+ mode (J) and ESI− mode (K) for comparison between SCID mice and BALB/c mice with S. japonicum infection (infected BALB/c mice group is labeled IB and infected SCID mice group is labeled IS). O: Heatmap of the differential serum metabolites between SCID mice and BALB/ c mice with S. japonicum infection. P: Enriched metabolite terms of the differentially expressed metabolites between infected SCID mice and BALB/c mice. For the heat maps, normalized signal intensities (log2 transformed and row adjustment) are visualized as a color spectrum and the scale from least abundant to highest ranges is from −3.0 to 3.0 as shown in the colorbar. Green indicates decreased expression, whereas red indicates increased expression of the detected metabolites between compared groups.

the metabolic profiles across the different mice groups clearly differentiated BALB/c mice from SCID mice in both ESI+ and ESI− modes, and clearly differentiated uninfected BALB/c mice from infected BALB/ c mice in both ESI+ and ESI− modes, but did not clearly differentiate control SCID mice from infected SCID mice in both ESI+ or ESI− mode

(Fig. 1C and D). Furthermore, two-dimensional PLS-DA models yielded good separation between the uninfected and infected mice, and between infected BALB/c mice and SCID mice, but a part of intersection occurred between uninfected BALB/c mice and SCID mice (Fig. 1E and F). 5

m/z

194.0812

319.2268

317.2120

301.2162

301.2171

345.2430

329.2484 496.3408

343.2276

429.1767

590.3817

570.3555

586.3146

169.0358 828.5515

592.3612

327.2330

303.2321

546.3559

319.2278 182.0811

426.3579

400.3423

ESI Mode

+

+

-

+

-

-

+

-

-

+

6

+

-

+ +

-

-

+

+

+

+

+

11.17

11.41

11.77 1.18

10.83

11.69

13.54

11.52

1.02 14.53

9.92

10.72

11.61

7.68

11.66

13.86 10.7

11.92

13.14

11.07

11.16

11.9

5.22

RT(min)

0.000360

0.007787

0.010077 0.007667

0.000192

0.001183

0.000119

0.000222

0.003934 0.005661

0.004293

0.000520

2.64E−06

3.91E−05

0.000174

0.000128 0.000687

3.38E−07

9.25E−08

9.25E−08

1.59E−07

0.034932

2.42E−09

raw P (t-test)

0.000740

0.010477

0.013082 0.010477

0.000444

0.002245

0.000338

0.000483

0.006616 0.008913

0.007060

0.001040

1.63E-05

0.000181

0.000416

0.000352 0.001338

4.17E−06

2.28E-06

2.28E−06

2.95E-06

0.036928

1.79E−07

Adjusted Pvalue (FDR)

0.74

0.63

0.63 0.64

0.75

0.78

0.85

0.83

0.82 0.79

0.98

1.02

1.18

1.16

1.11

1.27 1.23

1.42

1.46

1.64

1.66

1.51

2.17

VIP

0.78

0.80

1.27 1.25

1.31

1.36

1.38

1.40

1.43 1.43

1.56

1.61

1.73

1.77

1.80

2.04 1.80

2.28

2.32

2.91

3.02

3.31

4.84

FC(OS vs OB)

b

Elaidic carnitineb/Vaccenyl carnitineb Palmitoylcarnitineb

9R-HETE /(+)-Beyerol L-threo-3-Phenylserinea

b

Uric acida PC(18:1/20:5)b/PC(16:1/22:5)b/ PC(18:3/20:3)b PC(O-18:2/2:0)b/PC(20:2/0:0)b/ LysoPC(20:2)b 8,11,14-Docosatriynoic acidb/ Neogrifolinb/7alpha-Methyl-4pregnene-3,20-dioneb 1,2,3,4,4a,9,10,10a-Octahydro-6hydroxy-7-isopropyl-1,4a-dimethyl1-phenanthrenemethanola LysoPC(20:3)a

PC(20:5/0:0)

HMDB0004610/ HMDB0006351 HMDB0000222

C23H45NO4

C25H47NO4

C20H32O3 C9H11NO3

C28H52NO7P

HMDB0010393 HMDB0004667 HMDB0002184

C20H30O2

C22H32O2

C28H55NO7P

C5H4N4O3 C46H80NO8P

C28H48NO7P

C30H52NO7P

C30H56NO8P

C20H30O10

C22H32O3

C22H34O2 C24H50NO7P

C21H32O

C20H30O2

C20H28O2

C20H30O3

C20H30O3

C10H11NO3

Formula

C15008

HMDB0000289 HMDB0008083/ HMDB0008022 HMDB0015387/ HMDB0010392 HMDB0062219/ HMDB0030053

NA

HMDB0010402

LysoPC(22:5)a a

NA

HMDB0000052/ HMDB0001939/ HMDB0014398 HMDB0032622

HMDB0015500/ HMDB0034944 HMDB0006528 HMDB0010382

C15070/ HMDB0001252

C15353/C15307

PC(11:1/11:1)b

Phenethyl rutinosideb

C22:5n-3,6,9,12,15a PC(0:0/16:0)b/PC(16:0/0:0)b/ LysoPC(16:0)b EpDPEb/Medroxyprogesteroneb/ Medrysoneb

17alpha-Methyl-17betahydroxyandrosta-4,6-dien-3-oneb/ 17beta-Hydroxy-7alphamethylandrost-1,4-diene-3-oneb 17beta-Hydroxy-1,17-dimethylestr5(10)-en-3-oneb/Palustric acidb/ Miboleroneb Allylestrenolb/Siderolb

HMDB0000752

C15434/ HMDB0001868/NA

HMDB0000821

Phenylacetylglycinea 11beta,17beta-Dihydroxy-12alphamethylandrost-4-en-3-oneb/ Galanolactone/Grandifloric acidb Eicosatetraenoic acida

HMDB ID/KEGG Entry

Metabolites

Table 1 List of differential serum metabolic profiles related to species differences between SCID mice and BALB/c mice without S. japonicum infection.

[M+H]+

[M+H]+

[M-H][M+H]+

[M+H]+

[M+H]+

[M-H]-

[M+FA-H]-

[M+H]+ [M+Na]+

[M+FA-H]-

[M+H]+

[M+H]+

[M+FA-H]-

[M−H]-

[M-H][M+H]+

[M+FA-H]-

[M−H]-

[M+H]+

[M−H]-

[M+H]+

[M+H]+

adduct

Fatty Acyls Carboxylic acids and derivatives Organonitrogen compounds Fatty Acyls

Glycerophospholipids

Prenol lipids

Fatty Acyls

Glycerophospholipids

Imidazopyrimidines Glycerophospholipids

Glycerophospholipids

Glycerophospholipids

Carbohydrates and carbohydrate conjugates Glycerophospholipids

Carboxylic acids and derivatives

Steroids and steroid derivatives Fatty Acyls Glycerophospholipids

Organonitrogen compounds

Steroids and steroid derivatives

Fatty Acyls

Carboxylic acids and derivatives Benzene and substituted derivatives

Class

(continued on next page)

Fatty acid degradation; Fatty acid metabolism

NA

Glycerophospholipid metabolism NA NA

NA

Glycerophospholipid metabolism Glycerophospholipid metabolism Glycerophospholipid metabolism Purine metabolism Glycerophospholipid metabolism Glycerophospholipid metabolism NA

NA

NA Glycerophospholipid metabolism NAn

NA

NA

Arachidonic acid metabolism; Linoleic acid metabolism; Biosynthesis of unsaturated fatty acids NA

NA

Phenylalanine metabolism

Related pathway

R. Liu, et al.

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OPLS-DA on serum samples of SCID mice and BALB/c mice without infection yielded good separation in groups (Fig. 2A and B). Thirtythree differential serum features/metabolites were identified between SCID mice and BALB/c mice without infection (OS vs. OB, Fig. 2C, Table 1), twenty-one metabolites of which had an FC ≥ 1.2, and twelve metabolites of which had an FC ≤ 0.8 (Table 1, Fig. S2). So, there were significant differences in the serum metabolic profiles between OS and OB. By searching against HMDB for metabolite classification, “glycerophospholipids”, “fatty acyls” and “carboxylic acids and derivatives” were found as the top three enriched terms (≥ 3 differential metabolites involved) of differential metabolites between uninfected SCID mice and BALB/c mice (Fig. 2D). Pathway analysis used to determine the underlying biochemical pathways associated with the species-oriented differential metabolites revealed the enriched pathways between OS and OB mainly included arachidonic acid metabolism, glycerophospholipid metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, arginine and proline metabolism, alanine/aspartate/glutamate metabolism (Table S1).

0.59 0.58 0.52 1.18 0.98 1.28 2.41E-05 0.030415 0.002648 4.24E−06 0.026305 0.001503 0.79 9.09 9.19 254.9815 404.2063 431.1710 + -

ESI mode: +, positive ion mode; −, negative ion mode. VIP: variable importance in the projection. m/z: mass-to-charge ratio. RT: retention time. FC: fold change. NA: not available. a identified by both precise molecular weight and MS/MS spectral alignment. b identified by precise molecular weight alignment.

NA NA NA [M−H][M+Na]+ [M−H]C6H8O9S C20H31NO6 C23H28O8

Dihydrofurans NA Prenol lipids

NA [M+Na]+

HMDB0009465/ HMDB0009463 C02812 C10409/C10408 HMDB0035865/ C20196/NA Dimethyl hexaneb/4-Methylheptaneb/2,5-Dimethyl-heptaneb Ascorbate 2-sulfateb Symphytineb/Symlandineb Melledonal Ab/Salvinorin Ab/ Pseudolaric Acid Bb 0.66 0.87 0.009159 0.006188 151.1440 +

0.71

L-Glutamic acid n-butyl ester 2-Aminooctanoic acida 0.68 0.67 1.02 0.88 5.96E-06 0.003488 5.64E−07 0.002027 204.1232 160.1332 + +

0.95 0.86

C9H20

NA Carboxylic acids and derivatives Glycerophospholipids [M+H]+ [M+H]+ NA HMDB0000991

C9H17NO4 C8H17NO2

Glycerophospholipids [M+H]+ C27H56NO7P 538.3869 +

12.8

1.79E−05

9.46E-05

0.89

0.72

PC(19:0/0:0)

a

588.3307 -

10.48

6.08E−05

0.000204

0.84

0.75

a

HMDB0015385

[M+FA-H]C28H50NO7P HMDB0010395 LysoPC(20:4)a/PC(20:4/0:0)a

[M+H]+ 502.2932 +

10.41

2.06E−05

0.000102

0.83

0.76

HMDB0011517

C25H44NO7P

Glycerophospholipids

Glycerophospholipid metabolism Glycerophospholipid metabolism Glycerophospholipid metabolism NA NA

NA

Benzene and substituted derivatives Glycerophospholipids [M+H]+ C16H22O4 HMDB0013248 279.1594 +

12.09

1.55E−06

1.04E-05

0.82

0.76

Phthalic acid Mono-2-ethylhexyl Estera LysoPE(20:4/0:0)a

adduct m/z ESI Mode

Table 1 (continued)

RT(min)

raw P (t-test)

Adjusted Pvalue (FDR)

VIP

FC(OS vs OB)

Metabolites

HMDB ID/KEGG Entry

Formula

Class

Related pathway

3.2. Differential serum metabolic profiles related to species differences between SCID mice and BALB/c mice

3.3. Differential serum metabolic responses to S. japonicum infection between SCID mice and BALB/c mice OPLS-DA on serum samples of BALB/c mice five weeks post infection also yielded good separation in groups when compared with the uninfected controls (Fig. 2E and F). Specifically, thirty-three differential serum metabolites of BALB/c mice showed an increased or decreased change trend after S. japonicum infection (IB vs. OB, Fig. 2G, Table S2). Only dihydrocordoin/myricanone/2,3-dehydrosalvipisone had an FC > 1.2, and the rest of them had an FC ≤ 0.8, five of them had an FC < 0.5 (Fig. S3, Table S2). Metabolite classification analysis found that the “glycerophospholipids” was the top enriched metabolite terms of differential metabolites BALB/c mice after infection (Fig. 2H). In addition, OPLS-DA on serum samples of SCID mice at five weeks post infection also yielded good separation when compared with the uninfected controls (Fig. 2I and J). Nineteen differential serum metabolites of SCID mice showed an increased or decreased change trend after S. japonicum infection (IS vs. OS, Fig. 2K, Table S3), five of which had an FC ≥ 1.2 (Fig. S4). Fourteen of these metabolites showed a decreased trend in SCID mice after infection, but none of them had an FC < 0.5. Metabolite classification found “glycerophospholipids” and “fatty acyls” were the top two enriched terms of differential metabolites of SCID mice after infection (Fig. 2L). Furthermore, four metabolites/features were found commonly present in both the list of differential metabolites of SCID mice after S. japonicum infection (IS vs. OS) and that of BALB/c mice after infection (IB vs. OB) (Fig. 3A and B, Table S4). Two of them had the same change direction both groups of mice after infection, while the other two, LysoPE(18:2/0:0)/LysoPE(0:0/18:2)/PE(18:2/0:0) and PC(18:1/20:5)/ PC(16:1/22:5)/PC(18:3/20:3) decreased in BALB/c mice but increased in SCID mice after S. japonicum infection (Table S4). After the common differential metabolites being removed, the remaining species-specific differential metabolites due to S. japonicum infection were separated and listed in Table 2 and Fig. 3C for BALB/c mice-specific metabolites, which were all decreased after infection. The species-specific differential metabolites of SCID mice after S. japonicum infection were separated and listed in Table 3 and Fig. 3E, three metabolites of which, phytosphingosine, PE(22:6/0:0) and LysoPE(0:0/16:0)/PC(13:0/0:0), increased after infection, while the other twelve decreased after infection. Metabolite classification found that “glycerophospholipids” was the top one enriched term for BALB/c mice-specific differential metabolites after infection (Fig. 3D), and “fatty acyls” and “glycerophospholipids” were the top two enriched terms for SCID mice-specific 7

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Fig. 3. Comparison of the serum metabolic response to S. japonicum infection between BALB/c mice and SCID mice. A: Venn diagram shows significantly different metabolic responses to S. japonicum infection between BALB/c mice and SCID mice. B: Heat map of shared differential serum metabolites between SCID mice and BALB/c mice after S. japonicum infection. C: Heat map of BALB/c mice-specific differential serum metabolites between SCID mice and BALB/c mice after S. japonicum infection. D: Enriched metabolite terms of BALB/c mice-specific differential serum metabolites between SCID mice and BALB/c mice after S. japonicum infection. The bars on x-axis represent the number of metabolites for the chemical classes mentioned on the y-axis. Green indicates down- changed expression, whereas red indicates up- changed expression of the differential metabolites between compared groups. E: Heat map of SCID mice-specific differential serum metabolites between SCID mice and BALB/c mice after S. japonicum infection. F: Enriched metabolite terms of SCID mice-specific differential serum metabolites between SCID mice and BALB/c mice after S. japonicum infection. For the heatmaps, each row shows the relative fold of ion intensity for a specific metabolite to the specific means. Each column shows the serum metabolic profiles of BALB/c mice or SCID mice with infection compared with those of uninfected controls, respectively. Normalized signal intensities (log2 transformed and row adjustment) are visualized as a color spectrum and the scale from least abundant to highest ranges is from −3.0 to 3.0 in the colorbar. Green indicates low expression, whereas red indicates high expression of the detected metabolites.

differential metabolites after infection (Fig. 3F). Metabolic pathways analysis found that phenylalanine metabolism, glycerophospholipid metabolism, glycosylphosphatidylinositol (GPI)anchor biosynthesis, arachidonic acid metabolism, linoleic acid metabolism, alpha-linolenic acid metabolism, phenylalanine/tyrosine/tryptophan biosynthesis, and aminoacyl-tRNA biosynthesis were mainly enriched based on the specific differential metabolites in BALB/c mice after infection (Table S5). And arachidonic acid metabolism, glycerophospholipid metabolism, sphingolipid metabolism, linoleic acid metabolism, alpha-linolenic acid metabolism, and biosynthesis of unsaturated fatty acids were perturbed and enriched based on the specific differential metabolites in SCID mice after infection (Table S6).

enriched terms of differential metabolites between infected SCID mice and BALB/c mice (Fig. 2P). So, there were significant differences in serum metabolic response to S. japonicum infection between SCID mice and BALB/c mice. Moreover, seventeen of the differential metabolites between IS vs. IB were also present in the list of differential metabolites between uninfected SCID mice and BALB/c mice (Table 5, Fig. 4A and B). Most of them had the same change directions, except that dimethylhexane/ methyloctane/methylheptane had a lower level in SCID mice than in BALB/c mice without infection, but had a higher level in infected SCID mice; 9R-HETE/(+)-beyerol had a higher level in SCID mice than in BALB/c mice without infection, but had a lower level in infected SCID mice. After the above common differential metabolites related to species differences being removed, the remained differential metabolites between SCID mice and BALB/c mice with infection were specifically induced by schistosome infection between SCID mice and BALB/c mice (Table 6 and Fig. 4D). These differential metabolites related to species differences and induced specifically by schistosome infection between SCID mice and BALB/c mice might be associated with the morphological dysplasia of S. japonicum worms in SCID mice. Metabolite classification found “glycerophospholipids” and “fatty acyls” were the top two enriched terms for the common differential serum metabolites between comparisons of OS vs. OB and IS vs. IB (Fig. 4C), and “glycerophospholipids” were found as the top one enriched term for the

3.4. Differential serum metabolic profiles between SCID mice and BALB/c mice with S. japonicum infection OPLS-DA on serum samples between SCID mice and BALB/c mice at five weeks post infection yielded good separation in groups (Fig. 2M and N). Twenty-nine differential serum metabolites were identified between infected SCID mice and BALB/c mice (IS vs. IB, Fig. 2O, Table 4). Twenty-four of the differential metabolites had higher levels in the infected SCID mice, and the other five metabolites showed lower levels in the infected SCID mice (Fig. S5). Metabolite classification found “glycerophospholipids” and “fatty acyls” were the top two 8

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Table 2 List of BALB/c mice-specific differential serum metabolites after S. japonicum infection. m/z 151.1440 570.3555 204.1232 182.0811 568.3402 542.3222 538.3869 546.3559 546.3537 476.2779 586.3146 166.0862 281.2486 610.3606 538.3147 279.1594 482.3242 482.3611 111.0092 568.3619 540.3307 548.3714 191.0201 522.3561 564.3307 255.2329 588.3307 510.3560 802.5595

RT (min) 0.71 10.72 0.95 1.18 10.4 10.18 12.8 10.83 12.13 10.39 9.92 2.23 14.71 11.19 10.04 12.09 10.21 11.09 1.09 12.18 10.85 11.48 0.97 11.15 10.43 14.54 10.48 11.37 14.95

Metabolites b

b

b

Dimethylhexane /Methyloctane /Ethylheptane LysoPC(22:5)a L-Glutamic acid n-butyl estera L-threo-3-Phenylserinea PC(22:6/0:0)b/LysoPC(22:6)b/ PC(18:2/0:0)b/LysoPC(18:2)b PC(19:0/0:0)a LysoPC(20:3)a PC(18:0/0:0)a LysoPE(18:2/0:0)b/LysoPE(0:0/18:2)b/PE(18:2/0:0)b PC(20:5/0:0)a L-Phenylalaninea Hexadecenyl acetatea Zizyphine Aa PC(16:1/0:0)a Phthalic acid Mono-2-ethylhexyl Estera PC(14:0/O-1:0)a PC(O-16:0/0:0)a 3-Hydroxy-2H-pyran-2-onea PC(O-16:0/2:0)b/PC(0:0/18:0)b/LysoPC(18:0)b PC(0:0/16:0)b/PC(16:0/0:0)b/LysoPC(16:0)b PC(20:2/0:0)b 5-Hydroxy-2,4-dioxopentanoatea PC(0:0/18:1)a LysoPC(18:2)b/PC(18:2/0:0)b Dodecyl 2-methylpropanoatea LysoPC(20:4)a/PC(20:4/0:0)a LysoPC(17:0)b PE(18:1/19:1)b/PC(14:0/20:2)b/PE-NMe(18:1/18:1)b

Class

raw P (t-test)

Adjusted P-value (FDR)

FC (IB vs OB)

Glycerophospholipids Glycerophospholipids NA Carboxylic acids and derivatives Glycerophospholipids Glycerophospholipids Glycerophospholipids Glycerophospholipids Glycerophospholipids Glycerophospholipids Glycerophospholipids Carboxylic acids and derivatives Glycerophospholipids NA Glycerophospholipids Benzene and substituted derivatives Glycerophospholipids Glycerophospholipids Pyrans Glycerophospholipids Glycerophospholipids Glycerophospholipids Keto acids and derivatives Glycerophospholipids Glycerophospholipids Fatty Acyls Glycerophospholipids Glycerophospholipids Glycerophospholipids

3.39E−08 0.000114 0.011781 0.021518 0.045147 7.21E−05 2.80E−06 1.17E−06 0.001043 0.000199 7.56E−07 0.007387 0.001536 2.45E−07 0.006313 7.09E−06 0.002660 0.017901 1.63E−07 3.37E−06 1.61E−09 0.003689 0.037671 1.77E−05 1.63E−08 3.90E−05 0.000518 6.99E−06 0.001520

2.80E−07 0.000198 0.012746 0.022543 0.045841 0.000132 9.43E−06 4.55E−06 0.001405 0.000321 3.12E−06 0.008126 0.001914 1.51E−06 0.007062 1.80E−05 0.003079 0.019056 1.20E−06 9.43E−06 1.06E−07 0.004198 0.038849 4.32E−05 2.80E−07 8.96E−05 0.000777 1.80E−05 0.001913

0.80 0.79 0.78 0.76 0.73 0.72 0.70 0.70 0.69 0.69 0.68 0.67 0.66 0.66 0.66 0.66 0.65 0.65 0.62 0.61 0.60 0.59 0.59 0.56 0.53 0.52 0.47 0.34 0.25

m/z: mass-to-charge ratio. RT: retention time. FC: fold change. a identified by both precise molecular weight and MS/MS spectral alignment. b identified by precise molecular weight alignment.

differential metabolites related to different responses to S. japonicum infection between SCID mice and BALB/c mice (Fig. 4E). The enriched serum metabolic pathways based on the differential metabolites between SCID mice and BALB/c mice with S. japonicum infection found arachidonic acid metabolism, glycerophospholipid metabolism and glycosylphosphatidylinositol (GPI)-anchor biosynthesis were the top three enriched metabolic pathways (Table S7). The enriched serum metabolic pathways based on the common differential

metabolites between SCID mice and BALB/c mice with or without infection found arachidonic acid metabolism, glycerophospholipid metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, purine metabolism, linoleic acid metabolism, alpha-linolenic acid metabolism, and biosynthesis of unsaturated fatty acids (Table S8). And the enriched serum metabolic pathways based on the differential metabolites specifically induced by S. japonicum infection between SCID mice and BALB/c mice included glycerophospholipid metabolism,

Table 3 List of SCID mice-specific differential serum metabolites after S. japonicum infection. m/z

RT (min)

Metabolites

Class

raw P (t-test)

Adjusted P-value (FDR)

FC (IS vs OS)

318.3002 526.2937 452.2780 393.2862

8.58 10.4 10.81 9.68

Organonitrogen compounds Glycerophospholipids Glycerophospholipids Fatty Acyls

1.79E−09 0.014399 0.004264 0.000516

7.90E−08 0.024368 0.012862 0.004543

6.509 1.219 1.217 0.796

160.1332 280.0924 327.2330

0.86 0.66 13.54

Carboxylic acids and derivatives Glycerophospholipids Fatty Acyls

0.012726 0.001286 0.020930

0.023332 0.006287 0.024890

0.779 0.773 0.762

303.2321

11.69

Prenol lipids

0.001623

0.006655

0.742

303.2330 301.2162

13.72 11.07

Prenol lipids Steroids and steroid derivatives

0.011280 0.020612

0.022004 0.024890

0.693 0.676

256.2636 824.2519 319.2278 317.2120 284.2949

13.53 5.57 11.77 11.16 14.86

Phytosphingosineb PE(22:6/0:0)a LysoPE(0:0/16:0)b/PC(13:0/0:0)b 3-Hydroxy-10′-apo-b,y-carotenalb/Docosanedioic acid/Octyl hexanedioate 2-Aminooctanoic acida Glycerophosphocholineb/sn-glycero-3-Phosphocholineb 8,11,14-Docosatriynoic acidb/Neogrifolinb/Neogrifolinb/7alphaMethyl-4-pregnene-3,20-dioneb 1,2,3,4,4a,9,10,10a-Octahydro-6-hydroxy-7-isopropyl-1,4adimethyl-1-phenanthrenemethanola 7,13-Eicosadiynoic acida 17alpha-Methyl-17beta-hydroxyandrosta-4,6-dien-3-oneb/4Oxoretinolb/8,11,14,18-Eicosatetraynoic acidb Palmitic amidea 3′-Sialyl-3-fucosyllactoseb 9R-HETEb/(+)-Beyerolb Eicosatetraenoic acida Stearamidea

Fatty Acyls Glycerophospholipids Fatty Acyls Fatty Acyls Fatty Acyls

0.001664 0.016086 0.004677 0.015850 0.001099

0.006655 0.024500 0.012862 0.024500 0.006287

0.635 0.626 0.601 0.578 0.555

m/z: mass-to-charge ratio. RT: retention time. FC: fold change. a identified by both precise molecular weight and MS/MS spectral alignment. b identified by precise molecular weight alignment. 9

m/z

586.3146

151.144

301.2171

524.3718

828.5514

329.2484 496.3408

570.3555

546.3559

169.0358 318.3002

542.3222

317.212

550.387

802.5595

548.3714

610.3606

182.0811

281.2486 327.233

476.2779

ESI Mode

-

+

-

+

+

+

+

+

+ +

+

10

-

+

-

+

-

+

-

-

10.39

14.71 13.54

1.18

11.19

11.48

14.95

12.44

11.16

10.18

1.02 8.58

10.83

10.72

13.86 10.7

13.83

12.05

13.14

0.71

9.92

RT (min)

9.60E−05

0.014266 0.006875

0.001255

5.52E−05

0.000383

0.001462

1.53E−05

0.003148

4.75E−06

0.000713 2.15E−06

8.75E−06

1.04E−06

3.25E−05 1.86E−17

3.20E−05

7.31E−15

5.76E−06

3.14E−05

2.57E−08

raw P (t−test)

0.000156

0.015784 0.008125

0.001864

9.91E−05

0.000604

0.002

4.68E−05

0.004163

2.14E−05

0.001765 1.24E−05

2.84E−05

6.75E−06

6.76E−05 9.69E−16

6.76E−05

1.90E−13

2.14E−05

6.76E−05

2.68E−07

Adjusted Pvalue (FDR)

0.72

0.63 0.68

0.79

0.80

0.81

0.84

0.92

0.94

1.10

1.15 1.16

1.22

1.27

1.27 0.71

1.38

1.50

1.34

1.49

1.68

VIP

1.456

1.491 1.490

1.590

1.620

1.697

1.736

1.794

2.298

2.317

2.591 2.382

2.777

2.872

3.306 3.217

3.457

3.881

3.690

4.952

6.178

FC (IS vs IB)

HMDB0010393

LysoPC(20:3)a

HMDB0013426 HMDB0009025/ HMDB0009026/ HMDB0009059/ HMDB0009058/ HMDB0007880/ HMDB0112971 HMDB0015387 C10015

PC(O-18:1/2:0)a PE(18:1/19:1)b/PC(14:0/20:2)b/PENMe(18:1/18:1)b

Zizyphine Aa

LysoPE(18:2/0:0)b/LysoPE(0:0/ 18:2)b/PE(18:2/0:0)b

Hexadecenyl acetate 8,11,14-Docosatriynoic acidb/ Docosatriynoic acidb/Neogrifolinb

a

L-threo-3-Phenylserine

a

PC(20:2/0:0)b/PC(O-18:2/2:0)b

HMDB0010076 HMDB0062219/ HMDB0011356/ HMDB0030053 HMDB0011507/ HMDB0011477/ HMDB0015387

HMDB0002184

HMDB0015387/ HMDB0010386 HMDB0000752

PC(18:2/0:0)b/LysoPC(18:2)b Eicosatetraenoic acida

HMDB0000289 HMDB0004610

Uric acid Phytosphingosineb

a

HMDB0010402

HMDB0008083/ HMDB0008022/ HMDB0008178 NA HMDB0010382

HMDB0011128

HMDB0009465/ HMDB0009595/ HMDB0009575 C15070/C15184/C15036

C22:5n-3,6,9,12,15a PC(0:0/16:0)b/PC(16:0/0:0)b/ LysoPC(16:0)b LysoPC(22:5)a

PC(18:1/20:5)b/PC(16:1/22:5)b/ PC(18:3/20:3)b

17beta-Hydroxy-1,17-dimethylestr5(10)-en-3-oneb/17beta-Hydroxy6alpha-methylandrost-4-en-3-oneb/ 2alpha-Methyl-5alpha-androstane3,17-dioneb PC(0:0/18:0)a

Dimethylhexane /Methyloctane / Methylheptaneb

b

NA

PC(20:5/0:0)a b

HMDB ID/KEGG Entry

Metabolites

Table 4 List of the differential serum metabolites between SCID mice and BALB/c mice with S. japonicum infection.

C23H44NO7P

C18H34O2 C22H32O2

C9H11NO3

C33H49N5O6

C28H54NO7P

C42H80NO8P

C28H56NO7P

C20H30O3

C26H50NO7P

C5H4N4O3 C18H39NO3

C28H52NO7P

C30H52NO7P

C22H34O2 C24H50NO7P

C46H80NO8P

C26H54NO7P

C20H30O2

C9H20

C28H48NO7P

Formula

[M-H]−

−

[M−H] [M−H]−

[M+H]

+

[M−H]−

[M+H]+

[M+FA-H]−

[M+H]+

[M−H]−

[M+Na]+

[M+H] [M+H]+

+

Glycerophospholipids

Carboxylic acids and derivatives Glycerophospholipids Fatty Acyls

Glycerophospholipids

Glycerophospholipids

Glycerophospholipids

Glycerophospholipids

Fatty Acyls

Imidazopyrimidines Organonitrogen compounds Glycerophospholipids

Glycerophospholipids

Glycerophospholipids

[M+H]+ [M+H]+

Fatty Acyls Glycerophospholipids

[M-H]− [M+H]+

Glycerophospholipids

Glycerophospholipids

[M+H]+ [M+Na]+

Steroids and steroid derivatives

Glycerophospholipids

Glycerophospholipids

Class

[M-H]−

[M+Na]

+

[M+FA-H]−

adduct

(continued on next page)

Glycerophospholipid metabolism

NA NA

Glycerophospholipid metabolism Glycerophospholipid metabolism NA

Glycerophospholipid metabolism Arachidonic acid metabolism; Linoleic acid metabolism; Biosynthesis of unsaturated fatty acids Glycerophospholipid metabolism Glycerophospholipid metabolism

NA Glycerophospholipid metabolism Glycerophospholipid metabolism Glycerophospholipid metabolism Purine metabolism Sphingolipid metabolism

Glycerophospholipid metabolism Glycerophospholipid metabolism

NA

Glycerophospholipid metabolism NA

Related pathway

R. Liu, et al.

Acta Tropica 200 (2019) 105186

Acta Tropica 200 (2019) 105186

The schistosomes evolved in a long time to adapt to the hostile living environment in their definitive hosts, they finally acquired the ability to evade the host's immune attack and to exploit host's endocrine and immune factors for their normal growth and reproduction (Halton, 1997). Morphological abnormalities like retarded growth, decreased oviposition of S. japonicum worms and attenuated granulomas formation in the host's liver were observed in the SCID mice and nude mice during the experiments in our previous study, and it was more severe for the worms in the SCID mice (Tang et al., 2013). However, very limited knowledge about the pathophysiology of host's factors on the parasites’ growth and production is available. Therefore, here in this study, we collected the sera of SCID mice and BALB/c mice and compared their metabolomics profiles before and after five weeks post infection with S. japonicum worms by a non-targeted LC–MS/MSbased method, when distinct morphological differences in the worms collected from SCID mice could be observed when compared with those from BALB/c mice (Tang et al., 2013). In the results, plots from the multivariate analyses PCA and OPLSDA of serum metabolic profiles clearly showed different strain biosignatures of SCID mice when compared with BALB/c mice. The significantly differential serum metabolites between SCID mice and BALB/ c mice without schistosome infection were predominantly enriched in the metabolic pathways arachidonic acid metabolism, glycerophospholipid metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, phenylalanine metabolism, and so on, which indicated distinct systemic serum lipids and phospholipids metabolism between SCID mice and BALB/c mice. For example, the phenylacetylglycine, which is a product of phenylalanine metabolism catalysed by glycine Nphenylacetyltransferase, is a biomarker for abnormal phospholipid accumulation and disorders associated with mitochondrial fatty acid betaoxidation (Delaney et al., 2004). The abundance of phenylacetylglycine in SCID mice was more than four folds of that in BALB/c mice (FCOS/ OB = 4.84), which probably indicated abnormal phospholipid accumulation or disorders in SCID mice. In addition, the galanolactone, which has the same molecular weight as 11beta,17beta-dihydroxy12alpha-methylandrost-4-en-3-one and grandifloric acid, is known to be an antagonist of 5-HT3 (serotonin) receptors (Huang et al., 1991). Several studies has reported that serotonin is an important regulator in numerous aspects of flatworm biology, ranging from neuromuscular function to sexual maturation and egg laying (Boyle et al., 2000; Chan et al., 2017; Estey and Mansour, 1987; Mansour, 1984; Marchant et al., 2018; Patocka et al., 2014; Pax et al., 1984; Ribeiro et al., 2012). The higher abundance of galanolactone in SCID mice than in BALB/c mice (FCOS/OB = 3.31) could produce antagonistic effect on serotonin receptors of worms, resulting in adverse influences in motility, sexual maturation and egg laying. Moreover, eicosatetraenoic acid with two isomers (8Z,11Z,14Z,17Z)-icosa-8,11,14,17tetraenoic acid and (5Z,8Z,11Z,14Z)-icosa-5,8,11,14-tetraenoic acid appears to act as a dual inhibitor of arachidonic acid oxygenation through both the cyclooxygenase (COX) and lipoxygenase pathway. Arachidonic acid can be metabolized to both proinflammatory and antiinflammatory eicosanoids during and after the inflammatory response, respectively. Higher abundance of eicosatetraenoic acid in SCID mice than in BALB/c mice (FCOS/OB = 3.02) suggests disorganized inflammatory response towards schistosome infection. Salvinorin A or the similar feature melledonal A, which is a non-nitrogenous κ-opioid selective agonist activating G protein-coupled receptors (Chavkin et al., 2004; Roth et al., 2002), has antiinflammatory and antinociceptive effects by inhibiting leukotriene synthesis (Fichna et al., 2012; Rossi et al., 2016). Lower abundance of salvinorin A in SCID mice

[M+H] C8H17NO2 HMDB0000991 0.482 1.04 2.23E−05 6.43E−06 160.1332 +

0.86

279.1594 +

ESI mode: +, positive ion mode; -, negative ion mode. VIP: variable importance in the projection. m/z: mass-to-charge ratio. RT: retention time. FC: fold change. NA: not available. a identified by both precise molecular weight and MS/MS spectral alignment. b identified by precise molecular weight alignment.

NA

Benzene and substituted derivatives Carboxylic acids and derivatives C16H22O4 HMDB0013248

Phthalic acid Mono-2-ethylhexyl Estera 2-Aminooctanoic acida 0.515 1.05 4.64E−09 3.57E−10

824.2519 -

12.09

3′-Sialyl-3-fucosyllactosea 0.551 0.84 0.008125 0.006435

204.1232 319.2278 + -

5.57

L-Glutamic acid n-butyl ester 9R-HETEb/(+)-Beyerolb 0.684 0.670 0.69 0.83 0.001146 0.015784 0.000749 0.014216

+

[M+H]+

Glycerophospholipid metabolism NA Glycerophospholipids [M+FA-H]− C29H49NO23

NA Fatty Acyls [M+H] [M−H]−

NA HMDB0004667/ HMDB0008181 HMDB0006606

C9H17NO4 C20H32O3

+

522.3561 +

0.95 11.77

1.311 0.54 0.004163 0.003202

546.3537 +

11.15

1.416 0.71 1.53E−05 2.94E−06

215.0332 -

12.13

1.427 0.69 7.93E−05 4.27E−05

4. Discussions

m/z

0.72

glycosylphosphatidylinositol (GPI)-anchor biosynthesis, sphingolipid metabolism, arachidonic acid metabolism, linoleic acid metabolism, and alpha-linolenic acid metabolism (Table S9).

ESI Mode

Table 4 (continued)

RT (min)

raw P (t−test)

Adjusted Pvalue (FDR)

VIP

FC (IS vs IB)

Metabolites

a

HMDB0015388 PC(0:0/18:1)a

C26H52NO7P

[M+H]+

Glycerophospholipids

Glycerophospholipid metabolism Glycerophospholipid metabolism NA NA Glycerophospholipids HMDB0010384

C26H54NO7P

[M+Na]+

Biosynthesis of terpenoids and steroids Coumarins and derivatives [M−H]−

2-C-Methyl-D-erythritol 4phosphateb/Norvisnaginb/ Methoxsalenb PC(18:0/0:0)a

C11434/HMDB0014693

C5H13O7P

Class HMDB ID/KEGG Entry

Formula

adduct

Related pathway

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11

12

9.92 0.71 13.14

13.83 13.86 10.70 10.72 11.16 10.83 1.02 11.48 1.18 13.54 11.77 0.95 12.09

0.86

586.3146 151.1440 301.2171

828.5514 329.2484 496.3408 570.3555 317.2120 546.3559 169.0358 548.3714 182.0811 327.2330 319.2278 204.1232 279.1594

160.1332

2-Aminooctanoic acida

Glycerophospholipids Glycerophospholipids Organonitrogen compounds

PC(20:5/0:0)a Dimethylhexaneb/Methyloctaneb/Methylheptaneb 17beta-Hydroxy-1,17-dimethylestr-5(10)-en-3-oneb/17beta-Hydroxy-6alphamethylandrost-4-en-3-oneb/2alpha-Methyl-5alpha-androstane-3,17-dioneb PC(18:1/20:5)b/PC(16:1/22:5)b/PC(18:3/20:3)b C22:5n-3,6,9,12,15a PC(0:0/16:0)b/PC(16:0/0:0)b/LysoPC(16:0)b LysoPC(22:5)a Eicosatetraenoic acida LysoPC(20:3)a Uric acida PC(20:2/0:0)b/PC(O-18:2/2:0)b L-threo-3-Phenylserinea 8,11,14-Docosatriynoic acidb/Docosatriynoic acidb/ Neogrifolinb 9R-HETEb/(+)-Beyerolb L-Glutamic acid n-butyl estera Phthalic acid Mono-2-ethylhexyl Estera Glycerophospholipids Fatty Acyls Glycerophospholipids Glycerophospholipids Fatty Acyls Glycerophospholipids Imidazopyrimidines Glycerophospholipids Carboxylic acids and derivatives Fatty Acyls Fatty Acyls NA Benzene and substituted derivatives Carboxylic acids and derivatives

Class

Metabolites

m/z: mass-to-charge ratio. RT: retention time. FC: fold change. a identified by both precise molecular weight and MS/MS spectral alignment. b identified by precise molecular weight alignment.

RT (min)

m/z

Table 5 List of the common differential serum metabolites between comparisons of OS vs. OB and IS vs. IB.

0.002027

0.005661 0.000129 0.000687 0.000520 1.59E−07 0.000192 0.003934 0.000222 0.007667 0.000119 0.010077 5.64E−07 1.55E−06

0.004293 0.006189 9.25E−08

0.003489

0.008913 0.000352 0.001338 0.001041 2.95E−06 0.000444 0.006616 0.000483 0.010477 0.000338 0.013082 5.96E−06 1.04E−05

0.007060 0.009159 2.28E−06

0.67

1.43 2.04 1.8 1.61 3.02 1.31 1.43 1.4 1.25 1.38 1.27 0.68 0.76

1.56 0.66 2.32

6.43E−06

3.20E−05 3.25E−05 1.86E−17 1.04E−06 0.003148 8.75E−06 0.000713 0.000383 0.001255 0.006875 0.014216 0.000749 3.57E−10

2.57E−08 3.14E−05 5.76E−06

raw P (t-test)

FC

raw P (t-test)

Adjusted P-value (FDR)

IS vs IB

OS vs OB

2.23E−05

6.76E−05 6.76E−05 9.69E−16 6.75E−06 0.004163 2.84E−05 0.001765 0.000604 0.001864 0.008125 0.015784 0.001146 4.64E−09

2.68E−07 6.76E−05 2.14E−05

Adjusted P-value (FDR)

0.48

3.46 3.31 3.22 2.87 2.30 2.78 2.59 1.70 1.59 1.49 0.67 0.68 0.52

6.18 4.95 3.69

FC

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Acta Tropica 200 (2019) 105186

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Fig. 4. Comparison of the serum metabolic profiles between BALB/c mice and SCID mice without and with S. japonicum infection. A: Venn diagram shows significantly different metabolic profiles between BALB/c mice and SCID mice without and with S. japonicum infection. B: Heatmap of the common differential serum metabolites between SCID mice and BALB/c mice without and with S. japonicum infection, i.e. the differential serum metabolites shared between comparisons of OS vs. OB and IS vs. IB samples. C: Enriched metabolite terms of the common differential serum metabolites between SCID mice and BALB/c mice without and with S. japonicum infection. The bars on x-axis represent the number of metabolites for the chemical classes mentioned on the y-axis. Green indicates down- changed expression, red indicates up- changed expression of the differential metabolites, and whereas yellow indicates the differential metabolites have opposite expression changes between compared groups. D: Heatmap of differential serum metabolites between SCID mice and BALB/c mice associated specifically with S. japonicum infection. E: Enriched metabolite terms of the differential serum metabolites between SCID mice and BALB/c mice associated specifically with S. japonicum infection. For the heatmaps, each row shows the relative fold of ion intensity for a specific metabolite to the specific means. Each column shows the serum metabolic profiles of BALB/c mice or SCID mice without or with S. japonicum infection, or their ratio. Normalized signal intensities (log2 transformed and row adjustment) are visualized as a color spectrum and the scale from least abundant to highest ranges is from −3.0 to 3.0 in the colorbar. Green indicates low expression, whereas red indicates high expression of the detected metabolites.

(FCOS/OB = 0.52) indicated stronger proinflammatory effect in SCID mice than in BALB/c mice. These findings indicate disordered immune response and regulation towards schistosome infection in SCID mice, which is consistent with the detected lower level of immunosuppressor IL-10 in serum of SCID mice in our previous study (Tang et al., 2013), and it thus probably contributes partially to the abnormal growth and development of schistosome worms in SCID mice. Lipids have various

biological functions and are fundamental components of biological membranes and organelles. Significant changes in abundance of fatty acyls and glycerophospholipids with lysoPCs and PCs as the top two classes of varied metabolites in serum of SCID mice indicate their inherent disordered glycerophospholipid and fatty acid metabolism when compared with the BALB/c mice, making the SCID mice less susceptible to schistosome infection and the disease it causes.

Table 6 List of differential serum metabolites related to different response to S. japonicum infection between SCID mice and BALB/c mice. m/z 524.3718 318.3002 542.3222 802.5595 550.3870 610.3606 476.2779 215.0332 520.3405 281.2486 522.3561 824.2519

RT (min) 12.05 8.58 10.18 14.95 12.44 11.19 10.39 0.72 10.36 14.71 11.15 5.57

Metabolites a

PC(0:0/18:0) Phytosphingosineb PC(18:2/0:0)b/LysoPC(18:2)b PE(18:1/19:1)b/PC(14:0/20:2)b/PE-NMe(18:1/18:1)b PC(O-18:1/2:0)a Zizyphine Aa LysoPE(18:2/0:0)b/LysoPE(0:0/18:2)b/PE(18:2/0:0)b 2-C-Methyl-D-erythritol 4-phosphateb/Norvisnaginb/Methoxsalenb PC(18:2/0:0)b/LysoPC(18:2)b Hexadecenyl acetatea PC(0:0/18:1)a 3′-Sialyl-3-fucosyllactosea

m/z: mass-to-charge ratio. RT: retention time. FC: fold change. a identified by both precise molecular weight and MS/MS spectral alignment. b identified by precise molecular weight alignment. 13

Class

raw P (t-test)

Adjusted P-value (FDR)

FC (IS vs IB)

Glycerophospholipids Organonitrogen compounds Glycerophospholipids Glycerophospholipids Glycerophospholipids Glycerophospholipids Glycerophospholipids Coumarins and derivatives Glycerophospholipids Glycerophospholipids Glycerophospholipids Glycerophospholipids

7.31E−15 2.15E−06 4.75E−06 0.001462 1.53E−05 5.52E−05 9.60E−05 4.27E−05 1.64E−05 0.014266 0.003202 0.006435

1.90E−13 1.24E−05 2.14E−05 0.002000 4.68E−05 9.91E−05 0.000156 7.93E−05 4.74E−05 0.015784 0.004163 0.008125

3.881 2.382 2.317 1.736 1.794 1.620 1.456 1.427 1.463 1.491 1.311 0.551

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Fig. 5. Summary of the aberrant metabolic pathways based on the significantly altered serum metabolites of four comparison groups of mice as analyzed by MetaboAnalyst. Plots show the matched pathways depicted according to P-value from pathway enrichment analysis and pathway impact score from pathway topology analysis. A: the enriched metabolic pathways based on differential serum metabolites between OS vs. OB. B: the enriched metabolic pathways based on differential serum metabolites between IB vs. OB. C: the enriched metabolic pathways based on differential serum metabolites between IS vs. OS. D: the enriched metabolic pathways based on differential serum metabolites between IS vs IB. Color gradient and circle size indicate the significance of the pathway ranked by P-value (yellow: higher P-values and red: lower P-values) and pathway impact score (the larger the circle the higher the impact score), respectively. Significantly affected pathways with low P-value and high pathway impact score are identified by name.

Perturbations in serum metabolome of BALB/c mice due to S. japonicum infection for five weeks showed a global decrease in most of serum metabolites except for only a slight increase in dihydrocordoin/ myricanone/2,3-dehydrosalvipisone. The global decrease in serum metabolites of BALB/c mice were mainly enriched in glycerophospholipid metabolism, tryptophan metabolism and glycosylphosphatidylinositol (GPI) - anchor biosynthesis, etc, which is in accord with the results of other infection diseases observed in most studies (Garcia-Perez et al., 2008; Li et al., 2009; Saz, 1981; Sengupta et al., 2013; Suzuki et al., 1980; Wang et al., 2004; Wang et al., 2008; Wu et al., 1992; Zhou et al., 2015; Zhou et al., 2016). It is, however, obviously different for the perturbations in serum metabolome of SCID mice after S. japonicum infection that there were fewer differential

metabolites with more of which increased after infection in SCID mice when compared with those of BALB/c mice. This suggests less influence caused by schistosome infection in SCID mice than in BALB/c mice. Four of the differential metabolites were commonly present in both of BALB/c mice and SCID mice after infection, but LysoPE(18:2/0:0)/LysoPE(0:0/18:2)/PE(18:2/0:0) and PC(18:1/20:5)/PC(16:1/22:5)/ PC(18:3/20:3) showed opposite change directions after infection between BALB/c and SCID mice, and the other metabolites were speciesspecific response to the parasites infection. These differential metabolites with opposite change directions in the common differential metabolites after infection and those of species-specificity between BALB/c and SCID mice after S. japonicum infection could be addressed to be related with the abnormal growth and development of schistosome in 14

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SCID mice. For example, the specifically increased phytosphingosine, PE(22:6/0:0) and LysoPE(0:0/16:0)/PC(13:0/0:0) in SCID mice after infection may exert negative effect on the growth and development of schistosome in SCID mice. Moreover, there are also a series of differential metabolites between the infected BALB/c mice and SCID mice. Some of the differential metabolites were also present in the list of differential metabolites between uninfected BALB/c mice and SCID mice, and were selected as species-attributable differential metabolites. A list of differential metabolites specifically induced by S. japonicum infection was also obtained. Of these metabolites, for example, the involved sphingolipid metabolism of the increased phytosphingosine in SCID mice induced by S. japonicum infection could control the properties of cell membranes, the rate of cell growth–proliferation–destruction, apoptotic processes, the phosphorylation and dephosphorylation of proteins, the formation of reactive oxygen species (ROS), the hydrolysis of some proteins, the acetylation of nuclear histones, etc (Merrill AH Jr, 2000). And the involved alpha-linolenic acid metabolism of increased products of ALA metabolism was also detected in SCID mice due to S. japonicum infection, which may indicate less taking up fatty acids from the plasma by worms in SCID mice. And it was also the first reported in plasma of patient with Plasmodium falciparum infection, which was ever known to exist in plants (Lakshmanan et al., 2012). Summary of the aberrant metabolic pathways based on the differential serum metabolites of the above four comparison sets of mice found, for example, that the glycerophospholipid metabolism was commonly involved in species differences and S. japonicum infection between BALB/c mice and SCID mice (Fig. 5). It's well-known that one of the main functions of glycerophospholipid is to serve as a structural component of biological membranes. Glycerophospholipids are generally metabolized in several steps with different intermediates, including lysophosphatidic acid (LPA), phosphatidic acid (PA), phosphatidylchline (PC), phosphatidylserine (PS), phosphatidylethanolamine (PE), etc. Glycerophospholipids consumption by the pathogenic agents like virus and parasites from the host could be usually observed after infection (Castorena et al., 2010; Chen et al., 2017; Dechamps et al., 2010; Suzuki et al., 1980; Uppal et al., 2017; Wu et al., 1992). Of these, most PC and PE had higher levels in SCID mice compared with those in BALB/c mice after S. japonicum infection, which may lead to the defective growth and development of S. japonicum in SCID mice because of possible insufficient or inhibited utilization of these lipids for the formation of lipid bilayer structure of membranes by abnormal worms in SCID mice (Hu et al., 2017). In addition, the pathway biosynthesis of unsaturated fatty acids was specifically enriched in OS vs. OB, IS vs. OS, and IS vs. IB, which indicated the difference in biosynthesis of unsaturated fatty acids between SCID mice and BALB/c mice was due to species and infection. The pathway sphingolipid metabolism was specifically enriched in IS vs. OS and IS vs. IB, which suggested sphingolipid metabolism would reflect differential response to S. japonicum infection between SCID mice and BALB/c mice. And the pathway purine metabolism was specifically enriched in OS vs. OB and IS vs. IB, indicating the difference in purine metabolism between SCID mice and BALB/c mice was species-attributable. In summary, this study has demonstrated the ability of LC–MS/MSbased metabolomics to detect a broad range of differential metabolites in mice serum and to detect serum metabolic signatures that strongly distinguished BALB/c mice from SCID mice, and their differential metabolic response to S. japonicum infection. Our approach has enabled us to unravel a hitherto undiscovered aspect of the differences of serum metabolites and metabolic pathways between SCID mice and BALB/c mice after infection, which could in a great extent account for the abnormality in growth and development of S. japonicum worms in them. The identified differential metabolites may likely participate in affecting the growth and development of schistosome in SCID mice though the underlying molecular mechanisms remain unclear, which still needs further investigations to reveal them. Some of these

metabolites would be the great target candidates for exploitation of drugs or vaccines against schistosome and schistosomiasis. Funding Dr. Liu R. was supported by ‘the Fundamental Research Funds for the Central Universities’ of China (Grant no. 2042017kf0033), the Special Projects for Schistosomiasis from Health and Planning Commission of Hubei Province (currently named as Health Commission of Hubei Province) (Grant no. WJ2017X002), and the Natural Science Foundation of Hubei Province (Grant no. 2017CFB239). Dr. Ming Z.P. was supported by the National Natural Science Foundation of China (Grant NSFC no. 31372194). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CRediT authorship contribution statement Liu Rong: Conceptualization, Writing - original draft, Writing review & editing, Validation, Visualization, Project administration. Ye Feng: Validation, Visualization, Writing - review & editing. Zhong QinPing: Validation, Visualization, Writing - review & editing. Wang ShuHong: Validation, Visualization, Writing - review & editing. Chai Ting: Validation, Visualization, Writing - review & editing. Dong Hui-Fen: Project administration, Writing - review & editing. Ming Zhenping: Project administration, Writing - review & editing. Declaration of Competing Interest The authors disclose no conflict of interest. Supplementary material Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.actatropica.2019.105186. References Adebayo, A.S., Mundhe, S.D., Awobode, H.O., Onile, O.S., Agunloye, A.M., Isokpehi, R.D., Shouche, Y.S., Santhakumari, B., Anumudu, C.I., 2018. Metabolite profiling for biomarkers in Schistosoma haematobium infection and associated bladder pathologies. PLoS Negl.Trop. Dis. 12, e0006452. Adenowo, A.F., Oyinloye, B.E., Ogunyinka, B.I., Kappo, A.P., 2015. Impact of human schistosomiasis in sub-Saharan Africa. Brazil. J. Infect. Dis 19, 196–205. Amiri, P., Locksley, R.M., Parslow, T.G., Sadick, M., Rector, E., Ritter, D., McKerrow, J.H., 1992. Tumour necrosis factor alpha restores granulomas and induces parasite egglaying in schistosome-infected SCID mice. Nature 356, 604–607. Ball, E.G., Mc, K.R., et al., 1948. Studies on malarial parasites; chemical and metabolic changes during growth and multiplication in vivo and in vitro. J. Biol. Chem. 175, 547–571. Balog, C.I., Meissner, A., Goraler, S., Bladergroen, M.R., Vennervald, B.J., Mayboroda, O.A., Deelder, A.M., 2011. Metabonomic investigation of human Schistosoma mansoni infection. Mol. Biosyst. 7, 1473–1480. Blank, R.B., Lamb, E.W., Tocheva, A.S., Crow, E.T., Lim, K.C., McKerrow, J.H., Davies, S.J., 2006. The common gamma chain cytokines interleukin (IL)-2 and IL-7 indirectly modulate blood fluke development via effects on CD4+ T cells. J. Infect. Dis. 194, 1609–1616. Boyle, J.P., Zaide, J.V., Yoshino, T.P., 2000. Schistosoma mansoni: effects of serotonin and serotonin receptor antagonists on motility and length of primary sporocysts in vitro. Exp. Parasitol. 94, 217–226. von Brand, T., 1967. The metabolism of parasites. Its relations to the pathogenesis and chemotherapy of parasitic infections. Die Naturwissenschaften 54, 580–585. Castorena, K.M., Stapleford, K.A., Miller, D.J., 2010. Complementary transcriptomic, lipidomic, and targeted functional genetic analyses in cultured Drosophila cells highlight the role of glycerophospholipid metabolism in Flock House virus RNA replication. BMC Genom. 11, 183. Chan, J.D., Cupit, P.M., Gunaratne, G.S., McCorvy, J.D., Yang, Y., Stoltz, K., Webb, T.R., Dosa, P.I., Roth, B.L., Abagyan, R., Cunningham, C., Marchant, J.S., 2017. The anthelmintic praziquantel is a human serotoninergic G-protein-coupled receptor ligand. Nat. Commun. 8, 1910. Chavkin, C., Sud, S., Jin, W., Stewart, J., Zjawiony, J.K., Siebert, D.J., Toth, B.A., Hufeisen, S.J., Roth, B.L., 2004. Salvinorin A, an active component of the hallucinogenic sage salvia divinorum is a highly efficacious kappa-opioid receptor agonist: structural and functional considerations. J. Pharmacol. Exp. Ther. 308, 1197–1203. Cheever, A.W., Poindexter, R.W., Wynn, T.A., 1999. Egg laying is delayed but worm fecundity is normal in SCID mice infected with Schistosoma japonicum and S. mansoni

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