18
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Transcriptomic response of Anopheles gambiae sensu stricto mosquito larvae to Curry tree ( Murraya koenigii) phytochemicals

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Insect growth regulators (IGRs) can control insect vector populations by disrupting growth and development in juvenile stages of the vectors. We previously identified and described the curry tree ( Murraya koenigii (L.) Spreng) phytochemical leaf extract composition (neplanocin A, 3-(1-naphthyl)- l-alanine, lumiflavine, terezine C, agelaspongin and murrayazolinol), which disrupted growth and development in Anopheles gambiae sensu stricto mosquito larvae by inducing morphogenetic abnormalities, reducing locomotion and delaying pupation in the mosquito. Here, we attempted to establish the transcriptional process in the larvae that underpins these phenotypes in the mosquito.

          Methods

          We first exposed third-fourth instar larvae of the mosquito to the leaf extract and consequently the inherent phytochemicals (and corresponding non-exposed controls) in two independent biological replicates. We collected the larvae for our experiments sampled 24 h before peak pupation, which was 7 and 18 days post-exposure for controls and exposed larvae, respectively. The differences in duration to peak pupation were due to extract-induced growth delay in the larvae. The two study groups (exposed vs control) were consequently not age-matched. We then sequentially (i) isolated RNA (whole larvae) from each replicate treatment, (ii) sequenced the RNA on Illumina HiSeq platform, (iii) performed differential bioinformatics analyses between libraries (exposed vs control) and (iv) independently validated the transcriptome expression profiles through RT-qPCR.

          Results

          Our analyses revealed significant induction of transcripts predominantly associated with hard cuticular proteins, juvenile hormone esterases, immunity and detoxification in the larvae samples exposed to the extract relative to the non-exposed control samples. Our analysis also revealed alteration of pathways functionally associated with putrescine metabolism and structural constituents of the cuticle in the extract-exposed larvae relative to the non-exposed control, putatively linked to the exoskeleton and immune response in the larvae. The extract-exposed larvae also appeared to have suppressed pathways functionally associated with molting, cell division and growth in the larvae. However, given the age mismatch between the extract-exposed and non-exposed larvae, we can attribute the modulation of innate immune, detoxification, cuticular and associated transcripts and pathways we observed to effects of age differences among the larvae samples (exposed vs control) and to exposures of the larvae to the extract.

          Conclusions

          The exposure treatment appears to disrupt cuticular development, immune response and oxidative stress pathways in Anopheles gambiae s.s larvae. These pathways can potentially be targeted in development of more efficacious curry tree phytochemical-based IGRs against An. gambiae s.s mosquito larvae.

          Related collections

          Most cited references74

          • Record: found
          • Abstract: found
          • Article: not found

          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A new mathematical model for relative quantification in real-time RT-PCR.

            M. Pfaffl (2001)
            Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Mapping and quantifying mammalian transcriptomes by RNA-Seq.

              We have mapped and quantified mouse transcriptomes by deeply sequencing them and recording how frequently each gene is represented in the sequence sample (RNA-Seq). This provides a digital measure of the presence and prevalence of transcripts from known and previously unknown genes. We report reference measurements composed of 41-52 million mapped 25-base-pair reads for poly(A)-selected RNA from adult mouse brain, liver and skeletal muscle tissues. We used RNA standards to quantify transcript prevalence and to test the linear range of transcript detection, which spanned five orders of magnitude. Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3' untranscribed regions, as well as new candidate microRNA precursors. RNA splice events, which are not readily measured by standard gene expression microarray or serial analysis of gene expression methods, were detected directly by mapping splice-crossing sequence reads. We observed 1.45 x 10(5) distinct splices, and alternative splices were prominent, with 3,500 different genes expressing one or more alternate internal splices.
                Bookmark

                Author and article information

                Contributors
                cmmangera@gmail.com
                fkhamis@icipe.org
                otieno43@gmail.com
                ahmedhassanali786@gmail.com
                lombura@icipe.org
                mireji.paul@gmail.com
                Journal
                Parasit Vectors
                Parasit Vectors
                Parasites & Vectors
                BioMed Central (London )
                1756-3305
                2 January 2021
                2 January 2021
                2021
                : 14
                : 1
                Affiliations
                [1 ]GRID grid.8301.a, ISNI 0000 0001 0431 4443, Department of Biochemistry and Molecular Biology, , Egerton University, ; Njoro Campus, PO Box 536-20115, Egerton, Kenya
                [2 ]GRID grid.9762.a, ISNI 0000 0000 8732 4964, Department of Biochemistry, Microbiology and Biotechnology, School of Pure and Applied Sciences, , Kenyatta University, ; Ruiru Campus, PO Box 43844-00100, Nairobi, Kenya
                [3 ]GRID grid.419326.b, ISNI 0000 0004 1794 5158, International Centre of Insect Physiology and Ecology (ICIPE), ; Duduville Campus, Kasarani, PO Box 30772-00100, Nairobi, Kenya
                [4 ]GRID grid.449038.2, Department of Biological Sciences, , Meru University of Science and Technology, ; PO Box 972-60200, Meru, Kenya
                [5 ]GRID grid.9762.a, ISNI 0000 0000 8732 4964, Department of Chemistry, School of Pure and Applied Sciences, , Kenyatta University, ; Ruiru Campus, PO Box 43844-00100, Nairobi, Kenya
                [6 ]GRID grid.473294.f, Biotechnology Research Institute-Kenya Agricultural and Livestock Research Organization, ; PO Box 362-00902, Kikuyu, Kenya
                Author information
                http://orcid.org/0000-0002-3972-2284
                https://orcid.org/0000-0002-7965-2428
                Article
                4505
                10.1186/s13071-020-04505-4
                7777392
                33388087
                8fc281d4-4032-4d5d-8318-82ccf24b2b1e
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 4 June 2020
                : 30 November 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004828, Grand Challenges Canada;
                Award ID: 02691
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Parasitology
                anopheles gambiae s.s,growth disruption,mosquito larvae,differential gene expression,murraya koenigii

                Comments

                Comment on this article