Keywords

13.1 Introduction

So far, most of the works on the elucidation of underlying molecular mechanisms for toxicity of environmental toxicants or stresses are relevant to those well-known signaling pathways. In nematode Caenorhabditis elegans, many environmental toxicants or stresses can potentially result in the toxicity at different aspects on animals [1,2,3,4,5,6,7,8]. Actually, during the toxicity induction of environmental toxicants or stresses, a complex network may exist and contain many relevant signaling pathways. Therefore, it is necessary to employ effective strategies to screen and to identify new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses.

In this chapter, we first introduced the importance of transcriptomic analysis and proteomic analysis for the screen and the identification of new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses. Moreover, we further introduced the importance of forward and reverse genetic screen techniques in screening and in identifying new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses. The related advantages and limitations for these strategies were further discussed.

13.2 Transcriptomic Screen and Identification of New Genetic Loci Involved in the Regulation of Toxicity of Environmental Toxicants or Stresses

In nematodes, the transcriptomic technique has been widely and frequently employed to screen and to identify the new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses [9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]. The nanotoxicological studies have demonstrated that some of the engineered nanomaterials (ENMs) can potentially induce the toxic effects on the functions of both primary and secondary targeted organs in organisms, including the nematodes [24,25,26,27,28,29,30]. We here selected the multiwalled carbon nanotubes (MWCNTs), a carbon-based ENM, as an example to discuss the use of transcriptomic technique in screening and in identifying new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses [31].

Using Illumina HiSeqTM 2000 sequencing technique, transcriptomes from both control and MWCNT exposure groups were sequenced to obtain clean read data after filtering raw sequence data containing adaptor fragments [31]. The analysis based on statistical significance and use of a 2.0-fold change cutoff was performed, and the acquired annotations of differentially expressed genes were compared with the databases of gene bank (Fig. 13.1) [31]. Among the detected 13,752 genes, totally, 1903 genes were differentially expressed in MWCNT-exposed nematodes compared with control (Fig. 13.1) [31]. Among these 1903 mRNAs, 924 mRNAs were upregulated, and 993 mRNAs were downregulated by MWCNT exposure [31]. Among these dysregulated genes, some genes were associated with the control of oxidative stress or intestinal development [31]. The dysregulated genes associated with the control of oxidative stress were sod-2, sod-3, mev-1, isp-1, gas-1, and clk-1, and the dysregulated genes associated with the control of intestinal development were pgp-3, gem-4, par-3, pkc-3, ajm-1, lin-7, inx-3, and abts-4 [31].

Fig. 13.1
figure 1

Dysregulated mRNAs induced by MWCNT exposure [31]. (a) Heat map showing the expression of mRNAs obtained from control and MWCNT-exposed nematodes. Relatively low Fig. 13.1 (continued) expression levels are represented as blue, and relatively high expression levels are represented in red. (b) Scatter diagram of relationship between mRNA coverage of the control group and the MWCNT exposure group. (c) qRT-PCR analysis of the expressions of some genes encoding insulin signaling pathway in nematodes exposed to MWCNTs. (d) MWCNT exposure influenced the nuclear translocation of DAF-16::GFP in nematodes. Scale bar, 150 μm. MWCNT (1 mg/L) exposure was performed from L1-larvae to young adult. Bars represent means ± SEM **P < 0.01 vs control

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To determine the biological processes mediated by the dysregulated genes in MWCNT-exposed nematodes, gene ontology analysis was performed. Based on the dysregulated mRNAs, the significantly influenced gene ontology terms could be mainly classified into several categories, which were at least associated with biological processes of development, reproduction, cell adhesion, apoptosis, enzyme activity, cellular component, cellular localization and transportation, response to stimulus, immune response, cell metabolism, macromolecular complex, transcription, and translation in organisms (Fig. 13.2) [31]. The KEGG pathway mapping, a bioinformatics resource used to map molecular data sets in genomics, was further analyzed. The signaling pathways for the MWCNT toxicity control at least contained signaling pathways related to development, cell cycle, cell death, oxidative stress response, cellular component, immune response, neuronal development and neurodegeneration, and cell metabolism (Fig. 13.2) [31]. These results provide important clues for further understanding or elucidating the potential functions of dysregulated genes in the MWCNT toxicity induction in nematodes.

Fig. 13.2
figure 2

Analysis of gene ontology terms and signaling pathways [31]. (a) Gene ontology terms with gene counts based on both down- and upregulated mRNAs in MWCNT-exposed nematodes. (b) Predicted KEGG signal pathways based on both down- and upregulated mRNAs in MWCNT-exposed nematodes

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In nematodes, MWCNT exposure could induce the dysregulation of a series of miRNAs [32]. Among the dysregulated miRNAs, the bioinformatics analysis further demonstrated that lin-4, mir-228, mir-249, mir-47, mir-355, mir-45, mir-2210, mir-57, mir-1018, mir-360, mir-64, mir-2209, mit-793, mir-1830, mir-2210, mir-83, mir-789, and mir-806 might be involved in the regulation of MWCNT toxicity through affecting the functions of identified dysregulated genes in exposed nematodes [31]. For example, isp-1 gene might serve as a molecular target for mir-249 to regulate the induction of oxidative stress in MWCNT-exposed nematodes [31]. Mutation of mir-249 enhanced the induction of ROS production in MWCNT-exposed nematodes [31]. Mutation of isp-1 inhibited the induction of ROS production in MWCNT-exposed nematodes, and mutation of isp-1 gene suppressed the enhanced induction of ROS production observed in MWCNT-exposed mir-249(n4983) mutant nematodes [31]. The raised miRNA–mRNA network provides another important clue for the further elucidation of underlying molecular mechanisms of MWCNT toxicity induction in nematodes.

In nematodes, the insulin signaling pathway plays a crucial role in the regulation of toxicity of environmental toxicants or stresses [1, 33,34,35]. Among the genes encoding the insulin signaling pathway, the transcriptional expressions of daf-16 and daf-18 were decreased, and the transcriptional expressions of age-1, daf-2, pdk-1, and akt-1 were increased in MWCNT (1 mg/L)-exposed nematodes compared with control (Fig. 13.1) [31]. The qRT-PCR assay confirmed these changes (Fig. 13.1) [31]. daf-2 encodes a protein that is homologous to human insulin receptor InR, age-1 encodes a protein that is homologous to human phosphoinositide 3-kinase PI3K, daf-18 encodes a protein that is homologous to human lipid phosphatase PTEN, akt-1 encodes a protein that is homologous to human serine/threonine kinase Akt/PKB, and daf-16 encodes a protein that is homologous to human transcription factor FOXO. Meanwhile, it was observed that the percentage of nematodes with DAF-16::GFP in nucleus was significantly increased compared with control after the exposure to MWCNTs (Fig. 13.1) [31].

Moreover, it was found that mutation of daf-2, age-1, or akt-1 led to the obvious inhibition in induction of ROS production in the intestine and the significant increase in brood size or locomotion behavior in MWCNT (1 mg/L)-exposed nematodes; however, mutation of daf-16 or daf-18 resulted in the enhanced induction of ROS production in the intestine and the more severe decrease in brood size or locomotion behavior in MWCNT (1 mg/L)-exposed nematodes (Fig. 13.3) [31]. Therefore, the functional analysis demonstrated the crucial role of the insulin signaling pathway in regulating the MWCNT toxicity in nematodes.

Fig. 13.3
figure 3

Genes encoding insulin signaling pathway were involved in the control of MWCNT toxicity in nematodes [31]. (a) Intestinal ROS production assay in mutants for genes encoding insulin signaling pathway. Scale bar, 150 μm. (b) Brood size assay in mutants for genes encoding insulin signaling pathway. (c) Locomotion behavior assay in mutants for genes encoding insulin signaling pathway. Locomotion behavior was assessed by the endpoints of head thrash and body bend. The used nematode strains were wild-type N2, daf-16(mu86), daf-2(e1370), age-1(hx546), daf-18(e1375), and akt-1(ok525). MWCNT (1 mg/L) exposure was performed from L1-larvae to young adult. Bars represent means ± SEM **P < 0.01 vs N2

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13.3 Proteomic Screen and Identification of New Genetic Loci Involved in the Regulation of Toxicity of Environmental Toxicants or Stresses

With the acrylamide as an example, the second-dimension SDS-PAGE was performed to analyze the differences in protein expressions in acrylamide-exposed nematodes. Totally 274 ± 31 spots from the control extracts and 334 ± 29 spots from acrylamide (500 mg/l)-treated extracts were detected (Fig. 13.4) [36]. Among these spots, 14 spots were identified as dysregulated spots by MALDI-TOF mass spectrometer (Fig. 13.4) [36]. Moreover, four proteins were clearly upregulated by 500 mg/l of acrylamide, and these were all GSTs [36].

Fig. 13.4
figure 4

2-DE gel images of Caenorhabditis elegans total protein [36]. Five hundred microgram of protein was separated in the first dimension by pH gradient (pH 4–7, 18 cm) and in the second dimension by molecular weight. (a) Proteins from animals grown on control plates without acrylamide; 277 ± 31 (mean ± SD) protein spots were detected from four independent experiments. (b) Proteins from animals grown on 500 mg/l acrylamide; 334 ± 29 (mean ± SD) protein spots were detected from four independent experiments. (c) Eighteen identified spots are indicated on a 2-DE gel image

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It was further observed that the GST expressions were induced by acrylamide (500 mg/l) exposure for 12, 24, and 48 h (Fig. 13.5) [36]. Especially, the obvious alteration in expressions of GST-4, GST-7, GST-38, and GST-30 could be induced by acrylamide (500 mg/l) [36]. After acrylamide (500 mg) exposure for 48 h, the GST-4 expression was strongest, and RNAi knockdown of skn-1 suppressed this expression induction in the pharynx and in the body wall muscle [36].

Fig. 13.5
figure 5

Changes in the GST expression of the eight transgenic animals exposed from the L1 stage to 500 mg/l of acrylamide for 12, 24, and 48 h [36]. Animals were alive after all measurements. Data points indicate mean values ± SEM of three independent experiments. Statistical significance was shown by the GFP signals from 12 h for GST-4, GST-7, and GST-30 and from 24 h for GST-38 (p < 0.05)

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13.4 Forward Genetic Screen and Identification of New Genetic Loci Involved in the Regulation of Toxicity of Environmental Toxicants or Stresses

The forward genetic screen is a powerful genetic tool to identify new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses in nematodes [37, 38]. In nematodes, the excess iodide caused pleiotropic defects on animals [39]. We here selected the iodide toxicity as an example to introduce the use of forward genetics for the screen and the identification of new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses.

The P0 nematodes were mutagenized with ethyl methanesulfonate, and the phenotypes were screened in 5000 F1 animals [39]. The mutants that could survive in 5 mM NaI were saved, and 12 independent isolates were obtained [39]. After mapping using SNPs and genetic complementation tests of all 12 mutations, these mutations might affect at least 4 genes [39].

Using nuclear-binding fluorescence dye Hoechst 33258, five isolates (mac33, mac38, mac40, mac42, and mac43) exhibited a defective cuticle integrity (Fig. 13.6) [39], suggesting the genetic lesions affecting cuticle formation. In nematodes, mutations affecting cuticles usually cause blisters on cuticle (Bli), dumpy (Dpy), long (Lon), roller (Rol), and/or squat (Sqt). Because only an obviously Bli phenotype was detected in mac isolates, it was postulated that the Bli mutants might potentially survive in excess iodide [39]. Nevertheless, the further test on a series of Bli mutants (bli-1(e769), bli-2(e768), bli-3(e767), bli-4(e937), bli-5(e518), bli-6(n776, sc16), and tsp-15(sv15)) indicated that only bli-3(e767) and tsp-15(sv15) mutant nematodes could survive in the excess iodide [39].

Fig. 13.6
figure 6

Mutants that survive in 5 mM NaI have defective cuticle integrity [39]. (a) Cuticle blisters (arrows) of bli mutants, tsp-15(sv15) mutants, and two mac mutants (left and middle panels). Hoechst 33258 labels numerous nuclei in mac33 and mac40 mutants (right panels). Scale bars, 20 mm. (b) Ratios of Hoechst 33258-positive animals. Statistics, different from wild type. Bars, SEs of four biological replicates (n = 50 for each replicate). * P < 0.01 (Bonferroni test with one-way ANOVA)

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It was found that three of four complementation groups were mapped to chromosome I, on which both bli-3 and tsp-15 locate [39]. Moreover, mac40 is an allele of bli-3, mac33 is an allele of tsp-15, and mac32 represents an unknown gene (Fig. 13.7) [39]. Meanwhile, the blisters of mac33 and mac40 mutant nematodes resemble those of tsp-15(sv15) and bli-3(e767) mutant nematodes but are still different from the clear blisters of bli-1(e769) mutants (Fig. 13.7) [39]. Additionally, nematodes with RNAi knockdown of bli-3 or tsp-15 could survive in 5 mM NaI [39].

Fig. 13.7
figure 7

Some mac mutations affect bli-3 and tsp-15 [39]. (a) The mac mutations in bli-3 affect conserved (mac41, G44S; mac38, S694F) or nonconserved (mac40, A1263T; mac37, A1330V) amino acids in different domains of BLI-3. Nucleotide changes, amino acid changes, and BLI-3 DUOX1 partial sequence alignments of different species were presented. TM, transmembrane domain. (b) mac33 affects a nonconserved amino acid residue in the fourth transmembrane domain of TSP-15. Nucleotide change, amino acid change, and TSP-15 partial sequence alignment were presented

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In nematodes, the DOXA-1, an ortholog of mammalian dual oxidase maturation factor, forms a complex with BLI-3 and TSP-15, and each component of BLI-3/TSP-15/DOXA-1 dual oxidase complex was found to be required for the development-arresting effect of excess iodide [39]. The nematodes with RNAi knockdown of mtl-7 encoding a ShkT (Shk toxin)-domain-containing heme peroxidase were Bli but failed to survive in 5 mM NaI [39]. Meanwhile, RNAi knockdown of mlt-7 and each skpo gene (skpo-1, skpo-2, or skpo-3) encoding other ShkT-domain-containing peroxidases individually or in combination did not result in the survival phenotype in excess iodide [39], suggesting that MLT-7 and each of the SKPO proteins might not be redundantly required for development-arresting effect in response to the excess iodide.

13.5 Reverse Genetic Screen and Identification of New Genetic Loci Involved in the Regulation of Toxicity of Environmental Toxicants or Stresses

13.5.1 Using a Certain Number of Mutants to Screen and to Identify Genetic Loci Involved in the Regulation of Toxicity of Environmental Toxicants or Stresses

The mutant resources for nematodes are very rich, and thus, using a certain number of mutants is frequently employed to screen and to identify genetic loci involved in the regulation of toxicity of environmental toxicants or stresses [40,41,42]. Environmental pathogens can potentially cause the toxicity or even kill the host organisms, including the nematodes [43,44,45,46,47,48,49,50]. We here further select the pathogen infection as an example to introduce the use of mutants to screen and to identify microRNAs (miRNAs) involved in the regulation of toxicity of environmental toxicants or stresses in nematodes [51].

Using deletion mutants, a large-scale screen was performed to identify the miRNAs involved in the control of P. aeruginosa PA14 infection and the corresponding innate immune response [51]. Based on the phenotypic analysis of survival in miRNA mutants infected with P. aeruginosa PA14, totally 11 out of the examined 82 miRNA mutants with the abnormal survival phenotype were identified (Fig. 13.8) [51]. These miRNA mutants were let-7(mg279), mir-45(n4280), mir-63(n4568), mir-75(n4472), mir-84(n4307), mir-233(n4761), mir-241(n4316), mir-246(n4636), mir-256(n4471), mir-355(n4618), and mir-360(n4635) (Fig. 13.8) [51]. Loss-of-function mutation of let-7, mir-45, mir-75, mir-84, mir-241, mir-246, or mir-256 caused a resistance to P. aeruginosa PA14 infection in reducing survival (Fig. 13.8) [51]. In contrast, loss-of-function mutation of mir-63, mir-233, mir-360, or mir-355 resulted in a susceptibility to P. aeruginosa PA14 infection in reducing survival (Fig. 13.8) [51].

Fig. 13.8
figure 8

Survival in miRNA mutants infected with P. aeruginosa PA14 [51]. Bars represent mean ± SD

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Colony-forming unit (CFU) was employed to determine the PA14 colony formation in the body of miRNA mutant after P. aeruginosa infection. After P. aeruginosa PA14 infection, loss-of-function mutation of mir-63, mir-360, or mir-355 enhanced the PA14 colony formation in the body of nematodes; however, loss-of-function mutation of mir-45, mir-75, mir-246, or mir-256 suppressed the PA14 colony formation in the body of nematodes (Fig. 13.9) [51].

Fig. 13.9
figure 9

P. aeruginosa PA14 CFU in the body of miRNA mutants infected with P. aeruginosa PA14 [51]. Bars represent mean ± SD. **P < 0.01 vs wild type

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P. aeruginosa PA14 infection can increase the transcriptional expression of antimicrobial genes. Some putative antimicrobial genes (lys-1, lys-8, clec-85, dod-22, K08D8.5, F55G11.7, and F55G11.4) were selected to determine the innate immune response in P. aeruginosa PA14 infected miRNA mutants. lys-1 and lys-8 encode lysozymes, clec-85 encodes a C-type lectin protein, dod-22 and F55G11.7 encode orthologs of human epoxide hydrolase 1, and K08D8.5 and F55G11.4 encode CUB-like domain-containing proteins. After P. aeruginosa PA14 infection, mutation of mir-45 increased the expressions of lys-8, clec-85, dod-22, F55G11.7, and F55G11.4; mutation of mir-75 increased the expressions of lys-1, lys-8, dod-22, F55G11.7, and F55G11.4; mutation of mir-246 increased the expressions of lys-8, clec-85, dod-22, K08D8.5, and F55G11.7; and mutation of mir-256 increased the expressions of lys-1, lys-8, clec-85, dod-22, and K08D8.5 (Fig. 13.10) [51]. Different from these, mutation of mir-63 decreased the expressions of lys-1, dod-22, F55G11.7, and F55G11.4; mutation of mir-355 decreased the expressions of lys-1, lys-8, K08D8.5, F55G11.7, and F55G11.4; and mutation of mir-360 decreased the expressions of lys-8, dod-22, K08D8.5, and F55G11.7 (Fig. 13.10) [51]. These results suggest that loss-of-function mutation of these seven miRNAs alters the innate immune response of nematodes to P. aeruginosa PA14 infection in nematodes.

Fig. 13.10
figure 10

Expression patterns of putative antimicrobial genes in P. aeruginosa PA14 infected miRNA mutant nematodes [51]. Normalized expression is presented relative to wild-type expression. Bars represent mean ± SD

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13.5.2 Using RNAi Knockdown Technique to Screen and to Identify Genetic Loci Involved in the Regulation of Toxicity of Environmental Toxicants or Stresses

Myotonic dystrophy disorders can be induced by expanded CUG repeats in noncoding regions. The reporter constructs without any CUG repeats in the 384-nt 3′ UTR from let-858 (0CUG) showed a strong GFP fluorescence, whereas the presence of 123 CUG repeats in the 3′ UTR (123CUG) resulted in a sharp decline in GFP fluorescence [52]. Using the decline in adult-stage GFP fluorescence in 123CUG transgenic nematodes, RNAi screen was performed to identify the gene inactivations that can modify toxicity of expanded-CUG-repeat RNA [52]. After an initial fluorescence-based RNAi screen, a secondary motility-based screen of hits from the primary screen was further performed [52]. An RNAi library of 403 clones targeting genes that encode RNA-binding proteins and factors implicated in small-RNA pathways was screened. After the rescreening in triplicate, 84 gene inactivations were observed to induce an increase in late-developmental-stage GFP fluorescence in the 123CUG strain without affecting the control 0CUG strain (Fig. 13.11) [52]. Among these genes, 14 gene inactivations could further significantly increase or decrease the velocity of 123CUG animals without affecting the control (0CUG) animals (Fig. 13.11) [52].

Fig. 13.11
figure 11

Identification of gene inactivations that modulate expanded-CUG-repeat toxicity [52]. (a) Gene inactivations that disrupt the late-stage downregulation of GFP fluorescence mediated by 123CUG in the 3′ UTR. Fluorescence microscopy images of the strains 123CUG and the control 0CUG, on different RNAi gene inactivations: empty vector control (ctrl), npp-4, hda-1, C06A1.6, and smg-2. Images were taken at the 3-day-old adult stage. Bar, 200 μm. (b) Genetic suppressors and enhancers of expanded-CUG-repeat toxicity. Graph of velocity measurements of 0CUG (gray) and 123CUG (white) animals fed on different gene inactivations. The plotted velocities (x-axis, in μm/s) correspond to the median values of three independent experiments for aly-3, asd-1, C52B9.8, C06A1.6, cfim-2, dpy-2, F26B1.2, F48E8.6, grld-1, hda-1, hda-2, mrt-2, msh-6, nhr-2, nol-9, nth-1, pst-2, puf-6, puf-9, R05D10.1, R06C1.4, rnp-3, sago-1, sec-24.2, sfa-1, sir-2.2, smg-2, str-67, ung-1, and Y65B4A1 of 2 experiments for all other tested genes and of 22 experiments for control L4440. Red bars, strains fed on control vector; red line, median velocity; white shading, 25th and 75th percentiles, as indicated, for the 123CUG animals fed on control vector; dotted orange lines, maximum (upper) and minimum (lower) of the median velocity for 123CUG animals fed on control vector; and red asterisks, significant gene inactivations, as determined by Kolmogorov–Smirnov P value. The number of animals analyzed varied from 50 to 250 animals depending on the RNAi clone (further described in Online Methods), with a total of 1384 animals analyzed for the L4440 control. The black asterisk indicates the gene smg-2

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13.6 Perspectives

No doubt, all the four introduced strategies in this chapter are powerful and effective for the screen and the identification of new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses. Nevertheless, meanwhile, these strategies have certain limitations.

With the concern on the transcriptomic analysis, it has at least two aspects of limitations. Firstly, this strategy cannot reflect the alterations at the translational level. Secondly, this strategy itself cannot tell us the biological or toxicological function of candidate genes. Nevertheless, this strategy can provide us a large number of candidate genes for further consideration.

With the concern on the proteomic analysis, it has also at least two aspects of limitations. Firstly, largely due to the 2-D SDS-PAGE technical limitation, usually only very limited dysregulated proteins can be identified. Secondly, data from this strategy still need the further functional analysis and confirmation.

With the concern on the forward genetics, these two aspects should be paid attention to. On the one hand, the number of obtained candidate mutants is usually largely affected by the examined phenotype or endpoint. The subtle phenotype or sensitive endpoint may be helpful for us to obtain more candidate mutants. On the other hand, this strategy still needs the further examination on the expression of candidate genes corresponding to the obtained mutants in nematodes exposed to environmental toxicants or stresses. The important advantage for this strategy is to be able to obtain the mutants with the anticipated phenotypes.

With the concern on the reverse genetics, it has at least two aspects of limitations. Firstly, this strategy also needs the further examination on the expression of candidate genes corresponding to the obtained mutants in nematodes exposed to environmental toxicants or stresses. Secondly, the powerfulness of this strategy to identify new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses is somewhat limited. Usually, for the screened mutants, the functions of corresponding genes are already known. That is, for this strategy, a large-scale screen is suggested.

Taken together, to screen and to identify new genetic loci involved in the regulation of toxicity of environmental toxicants or stresses, we should consider both of these two aspects simultaneously. On the one hand, we hope to be able to identify candidate genetic loci with the functions in regulating the toxicity of environmental toxicants or stresses. On the other hand, we need to carefully examine the alterations in expression of these candidate genetic loci in nematodes exposed to environmental toxicants or stresses. Lacking any one aspect is not reasonable for the elucidation of underlying molecular mechanisms for the observed toxicity induced by certain environmental toxicants or stresses in nematodes.