About the Authors:
Muhammad Raznisyafiq Razak
Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing
Affiliation: Faculty of Forestry and Environment, Department of Environment, Universiti Putra Malaysia, Selangor, Malaysia
ORCID logo https://orcid.org/0000-0001-7358-050X
Ahmad Zaharin Aris
Roles Conceptualization, Formal analysis, Funding acquisition, Supervision, Writing – review & editing
* E-mail: [email protected]
Affiliations Faculty of Forestry and Environment, Department of Environment, Universiti Putra Malaysia, Selangor, Malaysia, International Institute of Aquaculture and Aquatic Sciences, Universiti Putra Malaysia, Negeri Sembilan, Malaysia
ORCID logo https://orcid.org/0000-0002-4827-0750
Fatimah Md Yusoff
Roles Writing – review & editing
Affiliations International Institute of Aquaculture and Aquatic Sciences, Universiti Putra Malaysia, Negeri Sembilan, Malaysia, Faculty of Agriculture, Department of Aquaculture, Universiti Putra Malaysia, Selangor, Malaysia
Zetty Norhana Balia Yusof
Roles Methodology, Writing – review & editing
Affiliations Faculty of Biotechnology and Biomolecular Science, Department of Biochemistry, Universiti Putra Malaysia, Selangor, Malaysia, Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia
Sang Don Kim
Roles Writing – review & editing
Affiliation: School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Buk-gu, Gwangju, Republic of Korea
Kyoung Woong Kim
Roles Writing – review & editing
Affiliation: School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Buk-gu, Gwangju, Republic of Korea
Introduction
Comprehensive reports on the hazards, dose-response and exposure of chemicals are necessary to establish a precise assessment of chemicals’ effects on humans and the ecosystem [1]. Conventional ecotoxicological assessment is highly costly, time-consuming and dependent on testing animals as surrogates for exposure effects on humans [2]. Conventional assessments only emphasise traditional apical endpoints rather than evaluating the specific pathway of the chemicals. The pathway assessment is essential to assess the interactions of cells with tissues, tissues with organs and organs with the individual [3]. Restriction on the use of animals in ecotoxicological assessment is enforced by the European Union unless no other possible method is applicable [4,5]. The National Institutes of Health (NIH) in the United States suggested ecotoxicological testing using animal models should construct the assessment methodology using the Replacement, Reduction, and Refinement strategy [6]. Alternative computerised analysis programs to regulate emerging chemicals instead of animal models were established under the ‘Replacement’ strategy. The approach also encourages the usage of cells and tissues, including the substitution from higher taxonomic rank animals (mammals and primates) to lower taxonomic rank animals (invertebrates). Subsequently, the number of animals used per test would be reduced via the ‘Reduction’ strategy by preventing any irrelevant replication for each assessment process. Efficient and accurate experimental design through ‘Refinement’ would minimise test animals’ suffering.
Risk assessors have begun to utilise non-model organisms such as aquatic invertebrates as bioindicators in ecotoxicological studies [7–10]. As a result, the amount of molecular assessment of zooplankton in the ecotoxicity discipline has intensified in recent years [11–18]. Among the zooplankton species, cladocerans are the group most responsive to the miniscule concentration of toxicants, as compared with copepods and rotifers [16]. Cladocerans are located in the middle of the food chain and will act as a warning alarm towards any perturbations in the aquatic ecosystem [19]. For example, cladocerans generate a vital connection between primary production (diatom-rich phytoplankton) and higher trophic organisms (fish). Inexpensive cladocerans species have reduced the cost of toxicity testing; for example, laboratory sizes can be shrunk by 50% compared to those needed for fish/animal models [20]. However, most researchers used temperate cladocerans species such as Daphnia magna as a species model, whereas tropical zooplankton species have not been thoroughly studied [21,22].
Moina micrura is a native cladoceran that is highly abundant in tropical countries including Malaysia, Thailand, the Philippines, China, Sri Lanka, India, Mexico and Brazil [23–29]. Due to their high ecological relevance, native species should be utilised in ecotoxicological studies to show the actual potential risks posed to tropical freshwater life [30]. There are fewer logistical restraints due to the high availability of this species in the wild, thus prohibiting another foreign species from being introduced into the native ecosystems [31]. Numerous study utilised M. micrura as a bioindicator in ecotoxicological and risk assessment due to the sensitivity of the species. For example, M. micrura is the most sensitive species towards cyanobacteria compared to tropical cladocerans Daphnia laevis and temperate cladocerans Daphnia similis [32]. Furthermore, M. micrura was the most sensitive species towards chlorpyrifos with the LC50 value 0.08 μg/L compared with Ceriodaphnia dubia, D. magna and Daphnia duplex with the LC50 value of 0.117 μg/L, 0.30 μg/L and 1.0 μg/L respectively [33]. Similar with other cladocerans, M. micrura possess a rapid life cycle and significant offspring due to the parthenogenesis reproduction system [34]. These characteristics permit a large number of assessments, including multigenerational experiments, with shorter time frames and minimised costs [35]. The organism’s transparent carapace allows novel organ endpoints such as eggs in the brood chamber, gut and heart to indicate specific mechanistic responses [3]. Cladocerans’ unique characteristics allow the prospect of more comprehensive ecotoxicological studies at different organizational levels such as molecular, organ, individual, and population level.
Despite the advantages of cladocerans as a bioindicator in the ecotoxicity discipline, the absence of established protocols to extract nucleic acids from cladocerans have interrupted the assessment at molecular levels. Gene expression is an example of a molecular assessment used by molecular biologists and environmental toxicologists to link the expression of specific genes to a biological process [36]. This assessment can assist scientists in recognising biological pathways and identifying the genes that regulate cell behaviour, development and disease [37]. However, the consistent and comprehensive analysis of gene expression depends on the quantity, quality and integrity of extracted RNA of the sample [38]. Subsequently, RNA extraction methods can be divided into two primary categories: conventional phenol-chloroform methods and silica-based kits [39]. The methods have been modified with several reagents to enhance the quantity, quality and integrity of RNA. For example, glycogen was added during the RNA extraction process to increase the RNA quantity and quality in different types of samples such as human [40,41] and rat [42] and insects [43,44]. Glycogen contain a highly purified polysaccharide and commonly used as an inert carrier and acts as a free host to RNA [45]. Due to the insoluble characteristics of an ethanol solution, glycogen produces a precipitate that holds nucleic acids [46]. This precipitate will form a visible pallet, which will ease the handling of nucleic acids.
Most zooplankton, including cladoceran species, consists of 18S and 28S rRNA. High- integrity RNA will show distinguished 18S and 28S rRNA peaks, with no smearing towards a smaller nucleotide (nt) [43]. Agarose gels are the conventional method to assess 18S and 28S rRNA bands. However, this method has several drawbacks; for example, the rRNA bands can be influenced by the electrophoresis conditions, the volume of loaded RNA and the saturation of ethidium bromide fluorescence [47]. Table 1 shows the summary of the study’s analysis to characterise the RNA quantity, quality and integrity. As the table indicates, this study conducted the analysis using the bioanalyzer instrument, which combines fluorescence, microfluidics and capillary electrophoresis to minimise errors during the evaluation of RNA integrity. The bioanalyzer utilised automatic microfluidics-based electrophoretic techniques that determine the RNA quality value based on the analysis of digitalised electropherograms by proprietary algorithms [48]. Additionally, the minimal input as low as 50 pg/μl of RNA sample permitted the characterisation of RNA integrity [49]. This feature is critical for determining RNA integrity in small samples like cladocerans because the quantity of extracted RNA is not high.
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Table 1. Summary of analysis to characterise RNA quantity, quality and integrity.
https://doi.org/10.1371/journal.pone.0264989.t001
In this study, a comprehensive assessment of RNA extracted from Cladocerans M. micrura with the addition of glycogen was reported for both the phenol-chloroform extraction method and the column-based kit method. This study provides a reliable and simple method for the molecular assessment of M. micrura for downstream applications such as reverse transcription polymerase chain reaction (RT-PCR) and next-generation sequencing (NGS) for potential application in functional genomic research such as gene expression profiling.
Material and methods
Chemicals and reagents
The chemicals, reagents, micropipette tips and micropestles used were molecular grade and certified Rnase-free. Chloroform, isopropanol, ethanol, β mercaptoethanol were purchased from Merck (Steinheim, Germany). RNase- QIAzol reagents, free water and Qiagen Micro kits were acquired from Qiagen (Hilden, Germany). RNA-grade glycogen was obtained from Thermo Fisher Scientific (MA, United States). To ensure a high quality of RNA extraction, workspaces such as lab benches and laminar flows were cleaned using 100% ethanol each time to ensure their cleanliness and to remove all contaminants. During handling of the reagent and RNA samples, gloves are utilised at all times and changed regularly as the protocol progresses from crude extract to more purified material.
M. micrura culture specifications
Live samples of Cladocerans M. micrura were obtained from the culture in the Aquatic Animal Health and Therapeutics Laboratory (AquaHealth), Institute of Bioscience, Universiti Putra Malaysia. The culture was cultivated based on the International Organization for Standardization (ISO) method (ISO 6341:2012). The culture specifications were regulated to the light/dark cycle of 12: 12 h and 27 ± 1°C. The media was changed every two days with the daily supplementation of a green microalga species, Chlorella vulgaris (1.0 × 106~8 cells/ ml, 1 ml/day), as the food supply.
M. micrura controlled samples collection
The standardization of sample collection to ensure the M. micrura in controlled condition throughout the RNA extraction process. Live M. micrura females were sorted from the culture sample under a Zeiss Axioskop 2 microscope (Zeiss, Germany). Females of M. micrura were collected similarly from the controlled culture prior to the RNA extraction. All experiments were performed in accordance with UK legislation under the Animals (Scientific Procedures) Act 1986 Amendment Regulations (SI 2012/3039).
RNA extraction
QIAzol (Method A).
1. Ten (10) and thirty (30) individuals of female M. micrura were transferred into a microcentrifuge tube.
2. Deionised water (1 ml) was added and the samples were gently rinsed using a micropipette to wash away any impurities attached to them. The samples were transferred into a new microcentrifuge tube.
3. QIAzol (100 μl) was added into the microcentrifuge tubes.
4. The samples were homogenised using a cordless microtube homogeniser (Bel-Art, NJ, USA) attached to the disposable plastic micropestle (Bel-Art, NJ, USA). The homogeniser was rotated 30 to 50 times under pressure until no large particles were visible under direct light.
5. The micropestle was rinsed with fresh QIAzol (900 μl) of reagent added into the microcentrifuge. The samples were vortexed briefly and incubated for 5 minutes at room temperature.
6. Chloroform (200 μl) was added to the samples, vortexed briefly and incubated at room temperature for 3 minutes.
7. The samples were centrifuged at >12,000 rpm, 4°C for 15 min. The supernatant (upper layer) was transferred to a clean microcentrifuge tube.
8. Isopropanol (500 μl) was added, and then the samples were vortexed briefly and incubated for 10 minutes at room temperature.
9. The samples were centrifuged at >12,000 rpm in 4°C for 20 minutes and the supernatant was removed.
10. The pellet was washed with 1000 μl of 75% ethanol (diluted with RNase-free water). Then, the samples were centrifuged at 7500 rpm at 4°C for 2 min.
11. The supernatant was carefully removed and the washing process was repeated once more (step 10). The supernatant was completely removed and air-dried for 10 min
12. The pallet was dissolved with 20 μl of RNase-free water. The samples were placed in the water bath at 45°C for 5 minutes and immediately held in ice for 2 minutes.
13. The extracted RNA was stored at -80°C prior to characterisation analysis. Fig 1 illustrates the QIAzol (Method A) method and the QIAzol + glycogen (Method B) method.
[Figure omitted. See PDF.]
Fig 1. Method of extraction by using QIAzol (Method A) and QIAzol + glycogen (Method B).
https://doi.org/10.1371/journal.pone.0264989.g001
QIAzol + glycogen (Method B).
1. Use a similar method with Method A but with the addition of 2 μl of RNA-grade glycogen during the RNA precipitation process.
Qiagen Micro Kit (Method C).
1. Ten (10) and thirty (30) individuals of female M. micrura were transferred into a microcentrifuge tube.
2. The samples were homogenised in of RLT buffer (350 μl) and β mercaptoethanol (4 μl) by using a similar procedure to that of the previous method.
3. The Qiagen Micro Kit was used according to the manufacturer’s protocol.
4. To avoid RNA degradation, all centrifugations were carried out at 4°C and samples were kept on ice during the entire procedure
5. The RNA was eluted in RNase-free water (20 μl).
6. The extracted RNA was stored at -80°C prior to characterisation analysis. Fig 2 illustrates the Qiagen Micro Kit (method C) method and the Qiagen Micro Kit + glycogen (Method D) method.
[Figure omitted. See PDF.]
Fig 2. Method of extraction by using Qiagen Micro Kit (method C) and Qiagen Micro Kit + glycogen (Method D).
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Qiagen Micro Kit + glycogen (Method D).
1. Use a similar method with Method C but with the addition of 2 μl of RNA-grade glycogen (Thermo Fisher Scientific, MA, United States) during the RNA precipitation process.
RNA characterisation
The quantity (RNA yield) and quality (A260/230 and A260/280 ratios) of total RNA were measured by the Genova Nano spectrophotometer Jenway (OSA, UK). The integrity of RNA (RIN value) was measured by Agilent 2100 Bioanalyzer Agilent Technologies (Waldbronn, Germany). The bioanalyzer instrument used the Agilent RNA 6000 Pico Kit and was supplied by Agilent Technologies (Waldbronn, Germany).
First-strand complementary DNA (cDNA) Synthesis and Reverse-Transcription Polymerase Chain Reaction (RT-PCR)
Two (2) replicate of RNA extraction samples from the best extraction method were used for cDNA synthesis and subsequent RT-PCR using primers based on previous literature [50]. Tetro cDNA Synthesis Kit (Bioline, USA) was utilised to synthesis complementary DNA (cDNA) by mixing 2 μg/μl of total RNA, 8 μl of Reverse Transcriptase Buffer, 2 μl of 10 mM dNTP mix, 2 μl of Oligo (dT)18 Primer, 2 μl of Ribosafe RNase Inhibitor, 2 μl of Tetro Reverse Transcriptase and RNase free Water to make up to 40 μl. The reaction mixture was homogenised by pipetting gently and incubated inside T100™ thermal cycler (Bio-Rad, USA) at 45°C for 30 minutes. This was followed by an incubation at 85°C for 5 minutes to stop the reverse transcriptase reaction and the holding temperature was finally held at 4°C. The cDNA was kept at -20°C before RT-PCR analysis.
Two (2) genes (Table 2) will be validated using SensiFAST™ SYBR No-ROX Kit (Bioline, USA). 0.3 μg of cDNA template will be mixed with 0.4 μl of 10 μM forward qPCR primer, 0.4 μl of 10 μM reverse qPCRprimer, 10 μl of 2 x SensiFast SYBR No-ROX Mix (containing 10 μM of dNTP mixture, 3 mM of MgCl2, SYBR® Green I dye, Taq Polymerase buffer, Taq DNA Polymerase, stabilisers and enhancers) and 8.2 μl of PCR grade distilled water. Each mixture will be pipetted into a 0.2 ml PCR tube, vortexed and centrifuged for a short spin prior to placing it into the Rotor-Gene Q thermocycler (QIAGEN, Germany). Two step RT-PCR will be performed with the cycling conditions consisting of an initial denaturation step at 95°C for 2 minutes, 40 cycles of denaturation (95°C for 5 seconds) and 65°C of annealing reaction.
[Figure omitted. See PDF.]
Table 2. Genes and primers used in the present study for Moina micrura [50].
https://doi.org/10.1371/journal.pone.0264989.t002
Statistical analysis
Data analysis was performed using statistical software IBM SPSS (Version 25). One-way analysis of variance (ANOVA) and Tukey’s post hoc pair-wise comparison test were employed to assess the effect of different RNA extraction methods on RNA quantity, quality (A260/280 and A260/230 ratios) and integrity (RIN values).
Results and discussion
RNA quantity
The efficacy of total RNA extraction methods should be validated by examining the quantity, quality and integrity of RNA to avoid repeated experiments, utilisation of toxic reagents, labour costs and instrumentation [51]. The comparison of the quantity (ng/individual), purity (A260/230 and A260/280 ratios) and integrity (RIN values) of the total RNA extracted from zooplankton using different extraction and preservation methods (Table 3 and S1 File). The current study utilised different sample pools of 10 individuals and 30 individuals for both extraction methods. For both extraction methods, RNA concentration was higher in sample pools of 30 individuals than in sample pools of 10 individuals. A similar result was observed by Roy et. al. (2020), suggesting that when the initial sample size or mass is increased, the RNA concentration will also increase. Moreover, the Individual contents of RNA in Artemia salina were increased exponentially with the life stages and number of incubation days as observed by Kobari et. al. (2017). The study also suggested that samples of early life stages of zooplankton do not contain RNA in amounts that are sufficient for any molecular study. Thus, extra individuals in the sample pools are needed during RNA extraction from zooplankton samples in the early life stages [52]. For this reason, phenol-chloroform method extraction is the best method of RNA extraction during the early life stages due to the fact that it can yield 2.4 to 93 times more RNA than the column-based kit method [39]. Furthermore, RNA concentration plateaus in the middle to late life stages (22–27 days of incubation). Thus, to ensure a sufficient concentration of RNA, the appropriate life stage for zooplankton to be taken as a sample is from 9 days onwards [52].
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Table 3. The comparison of quantity (ng/individual), purity (A260/230 and A260/280 ratios) and integrity (RIN values), of total RNA extracted from zooplankton using different extraction and preservation methods.
https://doi.org/10.1371/journal.pone.0264989.t003
Overall, the phenol-chloroform method showed a higher quantity of RNA compared to the column-based kit method. Spectrophotometric analysis indicates that the use of glycogen increased the RNA yield in the phenol-chloroform method. In the sample pools consisting of 10 individuals, the addition of glycogen successfully increased the RNA yield by three (3)fold from 35.61 ± 20.91 ng/μl to 113.71 ± 27.10 ng/μl. However, numerous precautions must be taken during extraction when using this method because several contaminants such as phenol, chloroform, salt and guanidine may persist in samples. In this study, a micro kit is used as the representative of a column-based kit instead of a mini kit because it is suitable for purification of total RNA using samples as small as 5 mg for animal tissues or 5x105 cells for animal cells [53]. Study by Asai et. al. (2015) shows the RNA extracted from zooplankton by using the micro kit yielded more RNA compared to a mini kit, with RNA concentrations of 57.69 ± 12.0 and 8.57 ± 2.0, respectively. Additionally, the column-based micro kit method saves time, can be conducted rapidly and possesses easier protocol compared to the phenol-chloroform extraction method [39]. However, the addition of glycogen in the column-based kit caused a significant decrease in RNA yield from 26.90 ± 6.89 ng/μl to 17.52 ± 5.84 ng/μl. It is suggested that the mix between glycogen and lysate in the spin columns will interfere with the dynamics of column extraction. Subsequently, whenever the number of samples is high or samples are taken during the middle and late life stages, the column-based kit is the best extraction method, as it successfully eliminates residual contaminants, thus increasing the RNA quality and integrity.
RNA quality and integrity
The total RNA extracted with the phenol-chloroform from the sample taken in the pools consisting of 10 individuals method had higher purity (A260/230 and A260/280 ratios) with the addition of glycogen during the extraction process. However, the column-based kit showed a decrease in A260/230 and A260/280 values when glycogen was added during the extraction process. In this study, the Qiagen micro kit without the addition of glycogen resulted in the best A260/230 and A260/280 ratio values, or 1.95 ± 0.15 and 1.85 ± 0.09, respectively. Nevertheless, in the sample pools consisting of 30 individuals, the addition of individuals into the pools decreased the A260/230 and A260/280 values for both extraction methods. This is because well-known contaminants such as ribonucleases (RNases) converge more strongly in the larger pooled samples, thus extensively digesting the RNA in the sample [54]. To prevent this phenomenon from occurring, multiple washing steps are required in extraction methods to eliminate the contaminants in the samples. Subsequently, rapid extraction methods and avoidance of environmental heat are also essential to ensure high-quality RNA in the samples [55]. The quality of the RNA extracted, with a reading of A260/230 and an A260/280 ratio between 1.8–2.0, indicated that the extracted RNA was free from contaminants and suitable for downstream applications [54].
The current study indicates that the addition of individuals in the sample pools reduces RNA integrity for both extraction methods. This result is due to numerous contaminants such as RNases becoming more concentrated in the pooled samples [54]. Thus, the current study established 10 individuals per sample pool as the optimised sample size for both extraction methods. Fig 3 shows the bioanalyzer assessment of the RNA extracted from 10 individuals of female M. micrura. Fig 3B shows glycogen did not cause 18S rRNA and 28S rRNA to peak, indicating that glycogen did not interfere with any of the proposed methods. The heat denaturing step, which stored RNA at 70°C for 2 min before loading it onto the chip, was excluded in this method. The denaturing step is recommended in the Agilent 2100 Bioanalyzer manufacturer’s instructions. However, this step causes the 28S rRNA peak to disappear from the electropherograms. During the heat denaturation step, the two fragments of 28S rRNA separate and migrate with the 18S rRNA. This phenomenon was associated with the ’hidden break’ present in protostome 28S rRNA [56]. A similar suggestion was made by Asai et al. (2015) to skip the heat denaturation step when assessing RNA integrity with zooplankton species. Additionally, RNA integrity is one of the most vital factors in the effectiveness of RNA extraction, since a low integrity value could intensely influence downstream analysis [57,58].
[Figure omitted. See PDF.]
Fig 3. The bioanalyzer assessment of total RNA from ten (10) female M. micrura extracted using different RNA extraction methods with the agilent RNA 6000 pico kit on the agilent 2100 bioanalyzer.
X-axis units in nt (Nucleotides); Y-axis units in FU (Fluorescence Units); N/A (Not Applicable) a) RNA ladder, b) glycogen, c) QIAzol method, d) QIAzol + glycogen method, e) Qiagen Micro Kit method, f) Qiagen Micro Kit + glycogen method, and g) Electrophoretic gel for each sample.
https://doi.org/10.1371/journal.pone.0264989.g003
Glycogen effectively increased the RNA integrity of the phenol-chloroform method from 5.87 ± 0.18 to 6.25 ± 0.10, However, glycogen has undesirable effects on the column-based kit as it was shown to decrease RNA integrity from 7.20 ± 0.16 to 6.73 ± 0.27. Total RNA from M. micrura extracted with the phenol-chloroform method showed a single peak corresponding to the 18S rRNA subunit, an absence of a 28S rRNA peak and a small amount of small RNA occurring between 25 nt and 200 nt. Subsequently, the column-based kit showed a clear 28S rRNA peak and a tiny amount of small RNA appearing between 25 nt and 200 nt. Additionally, the RIN values obtained by using column-based kit methods were significantly higher than those achieved with the phenol-chloroform method. The low RIN values, particularly in the phenol-chloroform method, were associated with the absence of 28S rRNA. The dissociation of the 28S rRNA was caused by the denaturation process of hydrogen bond breaking during the RNA extraction [51]. A similar discovery related to the denaturing effect of the lysis reagent on the 28S rRNA was reported in molluscs, insects and other zooplankton species [44]. A previous extraction study shows that the dissociation of 28S RNA caused by using the phenol-chloroform extraction method causes the RIN value to drop to 3.90 ± 1.13 [51]. As a result, the phenol-chloroform method is suggested to be unsuitable for extracting RNA from these organisms. Several studies showed that the extracted RNA in a RIN value of 6–10, indicating RNA from human and animal tissues that is high quality and non-degraded, and thus suitable for downstream applications [59,60]. This study showed that the column-based kit extraction is the most reliable method to extract RNA from freshwater Cladocerans species, specifically M. micrura. The effects of glycogen on RNA quantity, quality (A260/230 and A260/280 ratios) and integrity (RIN values) in both phenol-chloroform and column-based kit methods (Fig 4).
[Figure omitted. See PDF.]
Fig 4. The effect of glycogen on RNA quantity, quality (A260/230 and A260/280 ratios) and integrity (RIN values).
Box plots illustrate a) total yield of RNA extracted, b) A230/260 ratios of RNA extracted, c) A230/280 ratios of RNA extracted and d) RIN values of RNA extracted. Significant differences were analysed by ANOVA (Tukey’s post hoc test; ρ < 0.05) and are expressed as different letters. The results are based on the RNA extraction from the sample pools of ten (10) female M. micrura.
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The Qiagen Micro Kit (Method C) was the most optimised method and surpassed the minimum requirement of RNA quality control. Thus, the RNA extracted from this method was used for cDNA synthesis and subsequent RT-PCR analysis. Alpha tubulin and actin genes were employed as housekeeping genes in this study. Both genes have been identified as cladocerans’ cellular maintenance genes that regulate basic and ubiquitous cellular functions [50]. Thus, the genes were ideal candidates for serving as internal controls for gene expression analysis towards cladocerans. Moreover, the consistent expression of a housekeeping gene is required in any RT-PCR analysis since it is crucial for in the interpretation of the final result [61]. In all samples, the RT-PCR amplification cycle graphs showed that both alpha tubulin and actin genes exponential increase started at 33–35 cycles and the cycle threshold (Ct) values were between 32.64–33.48, respectively (S2 File). The stable reference genes identified in this study indicates current extraction method produces useful genetic material for testing the hypotheses involving genetic expression assays.
Another factor that can influence the quality and integrity of RNA used for downstream analysis besides the extraction method is the preservation of RNA samples. Previous studies have utilised several preservation methods, including preservation in RNAlater and storage at -80°C [44,51,54,62–67], preservation in lysis reagent and storage at -80°C [51,54,62,64], preservation in ethanol and storage at -80°C [38,68] and immersion in liquid nitrogen and storage at -80°C [62,63,65]. Preservation in formalin or 95–100% ethanol and flash freezing by using liquid nitrogen is a conventional method and most regularly used for bulk fixation of zooplankton samples [69,70]. However, this method does not preserve the integrity of proteins and degrades the genomic RNA. Moderate nucleic acid degradation in ethanol-preserved samples of Parvocalanus crassirostris after a month of preservation was observed by Goetze and Jungbluth (2013). The conventional method requires toxic chemicals and relies on liquid nitrogen, which is expensive. TRIzol as a preservation reagent for zooplankton, as no significant RNA degradation (p > 0.05) was detected in Acartia hudsonica preserved in TRIzol at 4°C for up to two weeks, or −80°C for two years as suggested by Zhang et. al. (2013). A similar study indicated RNAlater was not a suitable preservation reagent for Acartia hudsonica because no RNA was detectable in 6 out of 24 samples during the extraction process after preservation in RNAlater. The study indicated RNAlater fixation is not suitable for the preservation of individual small-sized zooplankton. Thus, the number of zooplankton samples preserved in RNAlater should be increased to reduce RNA loss during the preservation process [54]. Different observations were obtained by Gorokhova (2005), who revealed that RNAlater was capable of preserving RNA from an Artemia spp. sample for about 1 month at room temperature and 4 months at 5°C. Subsequently, the study indicates that -80°C is the best temperature for sample storage because no significant RNA degradation was observed until after 8 months. Accordingly, if the sample requires longer storage time, the temperature during storage must be kept as low as possible to ensure the RNA in the sample remains intact and is not degraded. Previous study by Asai et. al. (2015) also proposed RNAlater as a preservation reagent if liquid nitrogen is not available for flash freezing of zooplankton samples. A similar study indicated the integrity of Calanus helgolandicus was increased by 2.5-fold when it was preserved with RNAlater, from 3.90 ± 1.13 to 9.9 ± 0.14. Additionally, the effects of RNAlater on zooplankton depend on the exoskeleton structure of zooplankton species. A thin and noncalcified cuticle exoskeleton will increase the effectiveness of RNA preservation, as the RNAlater can easily penetrate the tissue, particularly before the samples are refrigerated. Preservation methods are essential to maintain the integrity of RNA from samples, thus determining the success of downstream analysis. Therefore, further studies by using several preservation methods before the RNA extraction are recommended to increase the integrity of RNA from several zooplankton samples.
Furthermore, the occurrence of RNases in both the sample and the environment causes the breakdown of RNA into smaller components [56]. The hydroxyl (-OH) group and diatomic carbon (C2) group in RNA chemical structure play a crucial role in the nonenzymatic degradation process [71]. Degraded RNA will not become amplified at the same level as cDNA derived from intact RNA during gene expression analysis. As RNA becomes degraded, quantitative expression levels determined by RT-PCR decrease and may cause inaccurate and unreliable gene expression assessment in the samples. RNA sequencing (RNA-seq) is an established high-throughput sequencing assay that applies next-generation sequencing (NGS) to determine any changes in the cellular transcriptome [72,73]. The transcript level of various genes changes with even slight differences in RNA integrity as observed by Reiman et. al. (2017). The highly degraded RNA did not yield enough sequencing library data; thus, the diversity and the coverage of transcript level values were significantly understated [65]. Samples with RIN values below 2.2 showed significant differences in gene expression profiles, producing only 30 million sequenced reads compared to 50 million sequenced reads of high-quality RNA [65]. However, data normalisation techniques can be implemented to increase the accuracy of gene expression assessments in RNA-seq analysis for degraded samples [74]. Data normalisation during RNA-seq analysis could determine several expressed genes, even when RNA samples with RIN values as low as 4 were included as examined by Romero et. al. (2014).
Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis
Worldwide communities must integrate all available ecotoxicological data, especially at molecular levels, by providing more detailed mechanistic information. The Organisation for Economic Co-operation and Development (OECD) established the adverse outcome pathway (AOP) framework to compile, incorporate and integrate ecotoxicological data through pathway assessment to clarify adverse outcomes. The framework examines the effects of chemicals through several levels of biological organisation (e.g., neuronal, cells, tissue, organ and individual) leading to adverse outcomes that are important to chemical and risk assessment [75]. Fig 5 shows a) key apical endpoints in several organisation levels and b) workflow at the molecular level for risk and pathway assessment. The figure shows the critical molecular assessment as a core interaction that causes adverse outcomes to the organisms. As more ecotoxicological data at the molecular level is recorded, it is possible to predict and evaluate potential adverse outcomes based on toxicity mechanistic understanding [76]. OECD established AOP Knowledge Base (AOP-KB) as the central repository for accelerating AOP applications (https:/aopkb.oecd.org/). AOP-KB consists of AOP-Wiki, Effectopedia, and AOP Xplorer for gathering mechanistic information and evaluating existing AOPs. The framework provides a means of collecting, organising and integrating data from numerous sources to allow accurate evaluations for chemical risk assessment, hazard projection and regulatory decision making [77]. Comparison assessment between vertebrate and invertebrate species is essential to determine the relationships in both species. The latest study shows several similar reactions across both species at the molecular levels of biological organisation, indicating potentially numerous overlapping responses to specific stressors. Unfortunately, only a fraction of molecular assessment data is reported on invertebrate species, especially zooplankton. Subsequently, the comparative analysis of two commonly used RNA extraction approaches in this study will support studies on cladocerans as non-model organisms for molecular assessment. A Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis of the phenol-chloroform extraction method and the column-based kit for the RNA extraction of zooplankton samples (Fig 6). Although the column-based kit is more expensive than the phenol-chloroform extraction method, the column-based kit offers high-quality extracted RNA and a rapid method that is more suitable for downstream application with zooplankton samples.
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Fig 5.
a) Key apical endpoints in various levels of organisation and b) workflow of Cladocerans bioindicator in risk and pathway assessment.
https://doi.org/10.1371/journal.pone.0264989.g005
[Figure omitted. See PDF.]
Fig 6. SWOT analysis of the phenol-chloroform extraction method and the column-based kit for the RNA extraction of zooplankton samples.
https://doi.org/10.1371/journal.pone.0264989.g006
Conclusions
RNA quality control is an essential step when evaluating gene expression profiles for downstream applications. In this study, a comprehensive assessment of RNA extracted from M. micrura was conducted using phenol-chloroform and column-based extraction methods. This study also showed the usefulness of a well known inert carrier, glycogen, in enhancing the quantity, quality and integrity of RNA, albeit only for a specific extraction method, namely the phenol-chloroform method. However, the phenol-chloroform method is not compatible with M. micrura or other zooplankton, insects and molluscs species because the lysis reagent used in this method will eventually denature 28S rRNA. On the other hand, the incorporation of glycogen is not compatible with the column-based kit method due to its interference with the dynamics of column extraction. However, the column-based kit method surpassed the minimum requirement of RNA quality control for downstream applications such as reverse transcription polymerase chain reaction (RT-PCR) and next-generation sequencing (NGS).
Supporting information
S1 File. Quantity, purity and integrity of the total RNA.
https://doi.org/10.1371/journal.pone.0264989.s001
(XLSX)
S2 File. RT-PCR cycle graphs and bioanalyzer raw data.
https://doi.org/10.1371/journal.pone.0264989.s002
(DOCX)
Acknowledgments
The Authors would like to acknowledge Aquatic Animal Health and Therapeutics Laboratory (AquaHealth), Universiti Putra Malaysia for laboratory equipments. First author also would like to thank Aisamuddin Ardi bin Zainal Abidin for his kind assistances during the course of this project.
Citation: Razak MR, Aris AZ, Md Yusoff F, Yusof ZNB, Kim SD, Kim KW (2022) Assessment of RNA extraction protocols from cladocerans. PLoS ONE 17(4): e0264989. https://doi.org/10.1371/journal.pone.0264989
1. Hamm J, Sullivan K, Clippinger AJ, Strickland J, Bell S, Bhhatarai B, et al. Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing. Toxicol Vitr. 2017;41: 245–259. pmid:28069485
2. Bopp SK, Kienzler A, Richarz AN, van der Linden SC, Paini A, Parissis N, et al. Regulatory assessment and risk management of chemical mixtures: challenges and ways forward. Crit Rev Toxicol. 2019;49: 174–189. pmid:30931677
3. Archer E, Petrie B, Kasprzyk-Hordern B, Wolfaardt GM. The fate of pharmaceuticals and personal care products (PPCPs), endocrine disrupting contaminants (EDCs), metabolites and illicit drugs in a WWTW and environmental waters. Chemosphere. 2017;174: 437–446. pmid:28187390
4. Doke SK, Dhawale SC. Alternatives to animal testing: A review. Saudi Pharm J. 2015;23: 223–229. pmid:26106269
5. Cozigou G, Crozier J, Hendriksen C, Manou I, Ramirez-Hernandez T, Weissenhorn R. The European Partnership for Alternative Approaches to Animal Testing (EPAA): Promoting alternative methods in europe and beyond. J Am Assoc Lab Anim Sci. 2015;54: 209–213. pmid:25836968
6. Russell WMS, Burch RL. The Principles of Humane Experimental Technique. London: Methuen; 1959.
7. Ebele AJ, Abou-Elwafa Abdallah M, Harrad S. Pharmaceuticals and personal care products (PPCPs) in the freshwater aquatic environment. Emerging Contaminants. 2017. pmid:28989983
8. Jeong T, Asselman J, De Schamphelaere KAC, Van Nieuwerburgh F, Deforce D, Kim SD. Effect of β-adrenergic receptor agents on cardiac structure and function and whole-body gene expression in Daphnia magna. Environ Pollut. 2018;241: 869–878. pmid:29913414
9. Lee JW, Won EJ, Raisuddin S, Lee JS. Significance of adverse outcome pathways in biomarker-based environmental risk assessment in aquatic organisms. J Environ Sci (China). 2015;35: 115–127. pmid:26354700
10. Razak MR, Aris AZ, Zakaria NAC, Wee SY, Ismail NAH. Accumulation and risk assessment of heavy metals employing species sensitivity distributions in Linggi River, Negeri Sembilan, Malaysia. Ecotoxicol Environ Saf. 2021;211: 111905. pmid:33453636
11. Giraudo M, Dubé M, Lépine M, Gagnon P, Douville M, Houde M. Multigenerational effects evaluation of the flame retardant tris(2-butoxyethyl) phosphate (TBOEP) using Daphnia magna. Aquat Toxicol. 2017;190: 142–149. pmid:28711770
12. Kim RO, Kim H, Lee YM. Evaluation of 4-nonylphenol and bisphenol A toxicity using multiple molecular biomarkers in the water flea Daphnia magna. Ecotoxicology. 2019;28: 167–174. pmid:30612256
13. Asselman J, Semmouri I, Jackson CE, Keith N, Van Nieuwerburgh F, Deforce D, et al. Genome-Wide Stress Responses to Copper and Arsenic in a Field Population of Daphnia. Environ Sci Technol. 2019;53: 3850–3859. pmid:30817885
14. Kim HY, Asselman J, Jeong T-Y, Yu S, De Schamphelaere KAC, Kim SD. Multigenerational Effects of the Antibiotic Tetracycline on Transcriptional Responses of Daphnia magna and Its Relationship to Higher Levels of Biological Organizations. Environ Sci Technol. 2017;51: 12898–12907. pmid:29023098
15. Ravindran SP, Lüneburg J, Gottschlich L, Tams V, Cordellier M. Daphnia stressor database: Taking advantage of a decade of Daphnia ‘-omics’ data for gene annotation. Sci Rep. 2019;9: 1–9. pmid:30626917
16. Pan Y, Yan SW, Li RZ, Hu YW, Chang XX. Lethal/sublethal responses of Daphnia magna to acute norfloxacin contamination and changes in phytoplankton-zooplankton interactions induced by this antibiotic. Sci Rep. 2017;7: 1–10. pmid:28127051
17. Liu Y, Wang L, Pan B, Wang C, Bao S, Nie X. Toxic effects of diclofenac on life history parameters and the expression of detoxification-related genes in Daphnia Magna. Aquat Toxicol. 2017;183: 104–113. pmid:28043021
18. İçoğlu Aksakal F. Acute and chronic effects of thifluzamide on daphnia magna. Turkish J Zool. 2019;43: 554–559.
19. Xiong W, Huang X, Chen Y, Fu R, Du X, Chen X, et al. Zooplankton biodiversity monitoring in polluted freshwater ecosystems: A technical review. Environ Sci Ecotechnology. 2020;1: 100008.
20. Dahms H, Won E, Kim H, Han J, Gi H, Souissi S, et al. Potential of the small cyclopoid copepod Paracyclopina nana as an invertebrate model for ecotoxicity testing. Aquat Toxicol. 2016;180: 282–294. pmid:27770640
21. Ghose SL, Donnelly MA, Kerby J, Whitfield SM. Acute toxicity tests and meta-analysis identify gaps in tropical ecotoxicology for amphibians. Environ Toxicol Chem. 2014;33: 2114–2119. pmid:24934557
22. Pham TL, Bui HM. Comparison of Diazinon Toxicity to Temperate and Tropical Freshwater Daphnia Species. J Chem. 2018;2018.
23. Sinev AY, Gu Y, Han BP. Cladocera of Hainan Island, China. Zootaxa. 2015;4006: 569–585. pmid:26623784
24. Vijverberg J. Zooplankton, zooplanktivorous fish and their interactions in Southeast Asian waterbodies with special reference to Sri Lanka: a review. Sri Lanka J Aquat Sci. 2018;23: 3.
25. Kar S, Das P, Das U, Bimola M, Kar D, Aditya G. Culture of the zooplankton as fish food: Observations on three freshwater species from Assam, India. AACL Bioflux. 2017;10: 1210–1220.
26. Boonthai C, Somparn A, Noller B. Using Zooplankton, Moina Micrura Kurz to Evaluate the Ecotoxicology of Pesticides Used in Paddy Fields of Thailand. Pestic Mod World—Risks Benefits. 2011.
27. Rietzler AC, Maia-Barbosa PM, Ribeiro MM, Menendez RM. On the first record of the exotic Moina macrocopa (Straus, 1820) in Minas Gerais State, Brazil. Brazilian J Biol. 2014;74: 518–520. pmid:25166341
28. Semenova AS, Tchougounov VK. The Distribution of Moina micrura Kurz, 1875 (Crustacea: Moinidae) in the Russian Part of the Vistula Lagoon (Baltic Sea). Russ J Biol Invasions. 2018;9: 175–183.
29. Elías-Gutiérrez M, Juračka PJ, Montoliu-Elena L, Miracle MR, Petrusek A, Kořínek V. Who is Moina micrura? Redescription of one of the most confusing cladocerans from terra typica, based on integrative taxonomy. Limnetica. 2019;38: 227–252.
30. Damasceno de Oliveira LL, Nunes B, Antunes SC, Campitelli-Ramos R, Rocha O. Acute and Chronic Effects of Three Pharmaceutical Drugs on the Tropical Freshwater Cladoceran Ceriodaphnia silvestrii. Water Air Soil Pollut. 2018;229.
31. Parmar TK, Rawtani D, Agrawal YK. Bioindicators: the natural indicator of environmental pollution. Front Life Sci. 2016;9: 110–118.
32. Ferrão-Filho A da S, Silva D de AS, Oliveira TA de, Magalhães VF de, Pflugmacher S, Silva EM da. Single and combined effects of microcystin- and saxitoxin-producing cyanobacteria on the fitness and antioxidant defenses of cladocerans. Environ Toxicol Chem. 2017;36: 2689–2697. pmid:28409869
33. Boonthai C, Somparn A, Noller B. Using Zooplankton, Moina Micrura Kurz to Evaluate the Ecotoxicology of Pesticides Used in Paddy Fields of Thailand. Pesticides in the Modern World—Risks and Benefits. 2011.
34. Azuraidi OM, Yusoff FM, Shamsudin MN, Raha RA, Alekseev VR, Matias-Peralta HM. Effect of food density on male appearance and ephippia production in a tropical cladoceran, Moina micrura Kurz, 1874. Aquaculture. 2013;412–413: 131–135.
35. Flores GJL, Salas HME, Sarma SSS, Nandini S. Four Transgenerational Demographic Performance of Moina macrocopa Exposed to Chronic Levels of Cadmium. Dose-Response. 2017;15: 1–8. pmid:28835748
36. Heckmann LH, Bouetard A, Hill CJ, Sibly RM, Callaghan A. A simple and rapid method for preserving RNA of aquatic invertebrates for ecotoxicogenomics. Ecotoxicology. 2007;16: 445–447. pmid:17530397
37. Wuerz M, Whyard S, Loadman NL, Wiegand MD, Huebner JD. Sex determination and gene expression in Daphnia magna exposed to juvenile hormone. J Plankton Res. 2019;41: 393–406.
38. Astrid T, Margit E, Leopold F. Ethanol: A simple and effective RNA-preservation for freshwater insects living in remote habitats. Limnol Oceanogr Methods. 2016;14: 186–195.
39. Toni LS, Garcia AM, Jeffrey DA, Jiang X, Stauffer BL, Miyamoto SD, et al. Optimization of phenol-chloroform RNA extraction. MethodsX. 2018;5: 599–608. pmid:29984193
40. Ford KL, Anwar M, Heys R, Ahmed EM, Caputo M, Game L, et al. Optimisation of laboratory methods for whole transcriptomic RNA analyses in human left ventricular biopsies and blood samples of clinical relevance. PLoS One. 2019;14: 1–18. pmid:30870483
41. Ban E, Chae DK, Yoo YS, Song EJ. An improvement of miRNA extraction efficiency in human plasma. Anal Bioanal Chem. 2017;409: 6397–6404. pmid:28842743
42. Brown RAM, Epis MR, Horsham JL, Kabir TD, Richardson KL, Leedman PJ. Total RNA extraction from tissues for microRNA and target gene expression analysis: Not all kits are created equal. BMC Biotechnol. 2018;18: 1–11. pmid:29316906
43. Deleo DM, Pérez-Moreno JL, Vázquez-Miranda H, Bracken-Grissom HD. RNA profile diversity across arthropoda: Guidelines, methodological artifacts, and expected outcomes. Biol Methods Protoc. 2018;3: 1–10. pmid:32161805
44. Gayral P, Weinert L, Chiari Y, Tsagkogeorga G, Ballenghien M, Galtier N. Next-generation sequencing of transcriptomes: A guide to RNA isolation in nonmodel animals. Mol Ecol Resour. 2011;11: 650–661. pmid:21481219
45. Monteiro MB, Santos-Bezerra DP, Thieme K, Passarelli M, Machado UF, Lin CJ, et al. Optimization of total RNA isolation from human urinary sediment. Clin Chim Acta. 2016;462: 158–161. pmid:27666760
46. Sharma R, Meister P. Generation of Inexpensive, Highly Labeled Probes for Fluorescence In Situ Hybridization (FISH). STAR Protoc. 2020;1: 100006. pmid:33111068
47. Stanta G. Guidelines for Molecular Analysis in Archive Tissues. Stanta G, editor. London, New York: Springer; 2011.
48. Padhi BK, Singh M, Rosales M, Pelletier G, Cakmak S. A PCR-based quantitative assay for the evaluation of mRNA integrity in rat samples. Biomol Detect Quantif. 2018;15: 18–23. pmid:29922590
49. Krupp G. Stringent RNA quality control using the Agilent 2100 bioanalyzer. 2005. Available: http://www.chem.agilent.com/Library/applications/5989-1086EN.pdf.
50. Imhof HK, Rusek J, Thiel M, Wolinska J, Laforsch C. Do microplastic particles affect Daphnia magna at the morphological, life history and molecular level? PLoS One. 2017;12: 1–20. pmid:29145427
51. Asai S, Ianora A, Lauritano C, Lindeque PK, Carotenuto Y. Marine Genomics High-quality RNA extraction from copepods for Next Generation Sequencing: A comparative study. Mar Genomics. 2015;24: 115–118. pmid:25546577
52. Kobari T, Kori S, Mori H. Ontogenetic variations in dry mass and nucleic acid contents of Artemia salina. Plankt Benthos Res. 2016;11: 1–8.
53. Kim Tiam S, Laderriere V, Gillis CA, Fortin C, Lavoie I. qPCR detection versus microscopy observations for assessing presence–absence of Didymosphenia geminata in Quebec rivers (Canada). Water Qual Res J Canada. 2017;52: 119–120.
54. Zhang H, Finiguerra M, Dam HG, Huang Y, Xu D, Liu G, et al. An improved method for achieving high-quality RNA for copepod transcriptomic studies. J Exp Mar Bio Ecol. 2013;446: 57–66.
55. Macedo NJ, Ferreira TL. Maximizing Total RNA Yield from TRIzol® Reagent Protocol: A Feasibility Study. ASEE 2014 Zone I Conference. 2014.
56. Winnebeck EC, Millar CD, Warman GR. Why does insect RNA look degraded? J Insect Sci. 2010;10: 1–7. pmid:20569122
57. Wever DJ, Tulkens D, Verwaeren J, Everaert H, Rottiers H, Dewettinck K, et al. A combined rna preservation and extraction protocol for gene expression studies in cacao beans. Front Plant Sci. 2020;11. pmid:32117362
58. Ching T, Huang S, Garmire LX. Power analysis and sample size estimation for RNA-Seq differential expression. Rna. 2014;20: 1684–1696. pmid:25246651
59. Fleige S, Pfaffl MW. RNA integrity and the effect on the real-time qRT-PCR performance. Mol Aspects Med. 2006;27: 126–139. pmid:16469371
60. White K, Yang P, Li L, Farshori A, Medina AE, Zielke HR. Effect of Postmortem Interval and Years in Storage on RNA Quality of Tissue at a Repository of the NIH NeuroBioBank. Biopreserv Biobank. 2018;16: 148–157. pmid:29498539
61. Kim H, Yim B, Bae C, Lee YM. Acute toxicity and antioxidant responses in the water flea Daphnia magna to xenobiotics (cadmium, lead, mercury, bisphenol A, and 4-nonylphenol). Toxicol Environ Health Sci. 2017;9: 41–49.
62. Portela P-R, Riesgo A. Optimizing preservation protocols to extract high-quality RNA from different tissues of echinoderms for next-generation sequencing. Mol Ecol Resour. 2013;13: 884–889. pmid:23683108
63. Mathay C, Yan W, Chuaqui R, Skubitz APN, Jeon JP, Fall N, et al. Short-term stability study of RNA at room temperature. Biopreserv Biobank. 2012;10: 532–542. pmid:24845140
64. McCarthy A, Chiang E, Schmidt ML, Denef VJ. RNA preservation agents and nucleic acid extraction method bias perceived bacterial community composition. PLoS One. 2015;10: 1–14. pmid:25798612
65. Kono N, Nakamura H, Ito Y, Tomita M, Arakawa K. Evaluation of the impact of RNA preservation methods of spiders for de novo transcriptome assembly. Mol Ecol Resour. 2016;16: 662–672. pmid:26561354
66. Ruocco N, Costantini S, Zupo V, Romano G, Ianora A, Fontana A, et al. High-quality RNA extraction from the sea urchin Paracentrotus lividus embryos. PLoS One. 2017;12: 1–11. pmid:28199408
67. Gorokhova E. Effects of preservation and storage of microcrustaceans in RNAlater on RNA and DNA degradation. Limnol Oceanogr Methods. 2005;3: 143–148.
68. Goetze E, Jungbluth MJ. Acetone preservation for zooplankton molecular studies. J Plankton Res. 2013;35: 972–981.
69. Shankar S, Roy S, Geary-Teeter A, Martin GM, Ladd PD. A low-cost and easy-to-use cell preservation reagent for 4°C or room temperature sample storage. bioRxiv. 2019.
70. Black AR, Dodson SI. Ethanol: a better preservation technique for Daphnia. Limnol Oceanogr Methods. 2011;1: 45–50.
71. Fattorini P, Bonin S, Marrubini G, Bertoglio B, Grignani P, Recchia E, et al. Highly degraded RNA can still provide molecular information: An in vitro approach. Electrophoresis. 2020;41: 386–393. pmid:31967656
72. Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A, et al. A survey of best practices for RNA-seq data analysis. Genome Biol. 2016;17: 1–19. pmid:26753840
73. Reiman M, Laan M, Rull K, Sõber S. Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples. FASEB J. 2017;31: 3298–3308. pmid:28446590
74. Xiong B, Yang Y, Fineis FR, Wang JP. DegNorm: Normalization of generalized transcript degradation improves accuracy in RNA-seq analysis. Genome Biol. 2019;20: 1–18. pmid:30606230
75. Ankley GT, Bennett RS, Erickson RJ, Hoff DJ, Hornung MW, Johnson RD, et al. Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environ Toxicol Chem. 2010;29: 730–741. pmid:20821501
76. Burden N, Sewell F, Andersen ME, Boobis A, Chipman JK, Cronin MTD, et al. Adverse outcome pathways can drive non-animal approaches for safety assessment. J Appl Toxicol. 2015;35: 971–975. pmid:25943792
77. Perkins EJ, Antczak P, Burgoon L, Falciani F, Garcia-Reyero N, Gutsell S, et al. Adverse outcome pathways for regulatory applications: Examination of four case studies with different degrees of completeness and scientific confidence. Toxicol Sci. 2015;148: 14–25. pmid:26500288
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Abstract
The usage of cladocerans as non-model organisms in ecotoxicological and risk assessment studies has intensified in recent years due to their ecological importance in aquatic ecosystems. The molecular assessment such as gene expression analysis has been introduced in ecotoxicological and risk assessment to link the expression of specific genes to a biological process in the cladocerans. The validity and accuracy of gene expression analysis depends on the quantity, quality and integrity of extracted ribonucleic acid (RNA) of the sample. However, the standard methods of RNA extraction from the cladocerans are still lacking. This study evaluates the extraction of RNA from tropical freshwater cladocerans Moina micrura using two methods: the phenol-chloroform extraction method (QIAzol) and a column-based kit (Qiagen Micro Kit). Glycogen was introduced in both approaches to enhance the recovery of extracted RNA and the extracted RNA was characterised using spectrophotometric analysis (NanoDrop), capillary electrophoresis (Bioanalyzer). Then, the extracted RNA was analysed with reverse transcription polymerase chain reaction (RT-PCR) to validate the RNA extraction method towards downstream gene expression analysis. The results indicate that the column-based kit is most suitable for the extraction of RNA from M. micrura, with the quantity (RNA concentration = 26.90 ± 6.89 ng/μl), quality (A260:230 = 1.95 ± 0.15, A280:230 = 1.85 ± 0.09) and integrity (RNA integrity number, RIN = 7.20 ± 0.16). The RT-PCR analysis shows that the method successfully amplified both alpha tubulin and actin gene at 33–35 cycles (i.e. Ct = 32.64 to 33.48). The results demonstrate that the addition of glycogen is only suitable for the phenol-chloroform extraction method. RNA extraction with high and comprehensive quality control assessment will increase the accuracy and reliability of downstream gene expression, thus providing more ecotoxicological data at the molecular biological level on other freshwater zooplankton species.
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