Integrated Transcriptomic and Proteomic Analyses Suggest the Participation of Endogenous Protease Inhibitors in the Regulation of Protease Gene Expression in Helicoverpa armigera
2018; Elsevier BV; Volume: 17; Issue: 7 Linguagem: Inglês
10.1074/mcp.ra117.000533
ISSN1535-9484
AutoresPurushottam R. Lomate, Veena Dewangan, Neha Mahajan, Yashwant Kumar, Abhijeet Kulkarni, Li Wang, Smita Saxena, Vidya S. Gupta, Ashok P. Giri,
Tópico(s)Aquaculture Nutrition and Growth
ResumoInsects adapt to plant protease inhibitors (PIs) present in their diet by differentially regulating multiple digestive proteases. However, mechanisms regulating protease gene expression in insects are largely enigmatic. Ingestion of multi-domain recombinant Capsicum annuum protease inhibitor-7 (CanPI-7) arrests growth and development of Helicoverpa armigera (Lepidoptera: Noctuidae). Using de novo RNA sequencing and proteomic analysis, we examined the response of H. armigera larvae fed on recombinant CanPI-7 at different time intervals. Here, we present evidence supporting a dynamic transition in H. armigera protease expression on CanPI-7 feeding with general down-regulation of protease genes at early time points (0.5 to 6 h) and significant up-regulation of specific trypsin, chymotrypsin and aminopeptidase genes at later time points (12 to 48 h). Further, coexpression of H. armigera endogenous PIs with several digestive protease genes were apparent. In addition to the differential expression of endogenous H. armigera PIs, we also observed a distinct novel isoform of endogenous PI in CanPI-7 fed H. armigera larvae. Based on present and earlier studies, we propose potential mechanism of protease regulation in H. armigera and subsequent adaptation strategy to cope with anti-nutritional components of plants. Insects adapt to plant protease inhibitors (PIs) present in their diet by differentially regulating multiple digestive proteases. However, mechanisms regulating protease gene expression in insects are largely enigmatic. Ingestion of multi-domain recombinant Capsicum annuum protease inhibitor-7 (CanPI-7) arrests growth and development of Helicoverpa armigera (Lepidoptera: Noctuidae). Using de novo RNA sequencing and proteomic analysis, we examined the response of H. armigera larvae fed on recombinant CanPI-7 at different time intervals. Here, we present evidence supporting a dynamic transition in H. armigera protease expression on CanPI-7 feeding with general down-regulation of protease genes at early time points (0.5 to 6 h) and significant up-regulation of specific trypsin, chymotrypsin and aminopeptidase genes at later time points (12 to 48 h). Further, coexpression of H. armigera endogenous PIs with several digestive protease genes were apparent. In addition to the differential expression of endogenous H. armigera PIs, we also observed a distinct novel isoform of endogenous PI in CanPI-7 fed H. armigera larvae. Based on present and earlier studies, we propose potential mechanism of protease regulation in H. armigera and subsequent adaptation strategy to cope with anti-nutritional components of plants. Adaptations of insects to a variety of plant compounds are partly attributed to their ability to breakdown or eliminate different phytotoxins (1.Dawkar V.V. Chikate Y.R. Lomate P.R. Dholakia B.B. Gupta V.S. Giri A.P. Molecular insights into resistance mechanisms of Lepidopteran insect pests against toxicants.J. Proteome Res. 2013; 12: 4727-4737Crossref PubMed Scopus (56) Google Scholar). Although plants produce various antifeedants and insecticidal molecules to deter insects from feeding on them, insects are known to overcome these using various specialized mechanisms (1.Dawkar V.V. Chikate Y.R. Lomate P.R. Dholakia B.B. Gupta V.S. Giri A.P. Molecular insights into resistance mechanisms of Lepidopteran insect pests against toxicants.J. Proteome Res. 2013; 12: 4727-4737Crossref PubMed Scopus (56) Google Scholar, 2.Mishra M. Lomate P.R. Joshi R.S. Punekar S.A. Gupta V.S. Giri A.P. Ecological turmoil in evolutionary dynamics of plant–insect interactions: defense to offence.Planta. 2015; 242: 761-771Crossref PubMed Scopus (19) Google Scholar). For instance, plant defensive protease inhibitors (PIs) 1The abbreviations used are: PI, protease inhibitor; AD, artificial diet; BApNA, benzoyl-L-arginyl p-nitroanilide; CanPI, Capsicum annuum protease inhibitor; CCK, cholecystokinin; CCK-RF, cholecystokinin-releasing factor; CmCatB, Callosobruchus maculatus cathepsin B; DDA, data dependent acquisition; FDR, false discovery rate; HGP, Helicoverpa armigera gut proteases; TMOF, trypsin-modulation oostatic factor; TOM, topological overlap matrix; WGCNA, Weighted correlation network analysis. 1The abbreviations used are: PI, protease inhibitor; AD, artificial diet; BApNA, benzoyl-L-arginyl p-nitroanilide; CanPI, Capsicum annuum protease inhibitor; CCK, cholecystokinin; CCK-RF, cholecystokinin-releasing factor; CmCatB, Callosobruchus maculatus cathepsin B; DDA, data dependent acquisition; FDR, false discovery rate; HGP, Helicoverpa armigera gut proteases; TMOF, trypsin-modulation oostatic factor; TOM, topological overlap matrix; WGCNA, Weighted correlation network analysis. interfere with the insect protein digestion whereas insects counteract by producing battery of digestive proteases with wide specificity. Gut proteolytic activity, especially in the lepidopteran insects is comprised of a variety of proteases with broad activity and diverse specificity. Insect proteases are responsive to the type and content of the diet with respect to their expression and activities. Resistance to plant PIs has been noted in several insects feeding on a variety of inhibitors (3.Giri A.P. Harsulkar A.M. Deshpande V.V. Sainani M.N. Gupta V.S. Ranjekar P.K. Chickpea defensive proteinase inhibitors can be inactivated by podborer gut proteinases.Plant Physiol. 1998; 116: 393-401Crossref Scopus (158) Google Scholar, 4.Jongsma M.A. Bakker P.L. Peters J. Bosch D. Stiekema W.J. Adaptation of Spodoptera exigua larvae to plant proteinase inhibitors by induction of gut proteinase activity insensitive to inhibition.Proc. Natl. Acad. Sci. U.S.A. 1995; 92: 8041-8045Crossref PubMed Scopus (384) Google Scholar, 5.Bown D.P. Wilkinson H.S. Gatehouse J.A. Differentially regulated inhibitor-sensitive and insensitive protease genes from the phytophagous insect pest, Helicoverpa armigera, are members of complex multigene families.Insect Biochem. Mol. Biol. 1997; 27: 625-638Crossref PubMed Scopus (298) Google Scholar, 6.Broadway R.M. Dietary regulation of serine proteinases that are resistant to serine proteinase inhibitors.J. Insect Physiol. 1997; 43: 855-874Crossref PubMed Scopus (133) Google Scholar, 7.Zhu-Salzman K. Zeng R.S. Insect response to plant defensive protease inhibitors.Annu. Rev. Entomol. 2015; 60: 233-252Crossref PubMed Scopus (175) Google Scholar). These studies provide clues to presume remarkable diversity and plasticity in the insect digestive processes as counter-defense mechanisms in insects. In general, three adaptive mechanisms, to counter ingestion of plant PIs have been prominently observed in insects. These include, (1) overproduction of proteases so that the concentration of PIs would be insufficient to inhibit proteolytic activity (5.Bown D.P. Wilkinson H.S. Gatehouse J.A. Differentially regulated inhibitor-sensitive and insensitive protease genes from the phytophagous insect pest, Helicoverpa armigera, are members of complex multigene families.Insect Biochem. Mol. Biol. 1997; 27: 625-638Crossref PubMed Scopus (298) Google Scholar, 6.Broadway R.M. Dietary regulation of serine proteinases that are resistant to serine proteinase inhibitors.J. Insect Physiol. 1997; 43: 855-874Crossref PubMed Scopus (133) Google Scholar), (2) incorporation of change in the PI binding site of the protease to make it PI insensitive (4.Jongsma M.A. Bakker P.L. Peters J. Bosch D. Stiekema W.J. Adaptation of Spodoptera exigua larvae to plant proteinase inhibitors by induction of gut proteinase activity insensitive to inhibition.Proc. Natl. Acad. Sci. U.S.A. 1995; 92: 8041-8045Crossref PubMed Scopus (384) Google Scholar, 6.Broadway R.M. Dietary regulation of serine proteinases that are resistant to serine proteinase inhibitors.J. Insect Physiol. 1997; 43: 855-874Crossref PubMed Scopus (133) Google Scholar), and (3) expression of proteases that can recognize the cleavage site in the PIs and degrade them (3.Giri A.P. Harsulkar A.M. Deshpande V.V. Sainani M.N. Gupta V.S. Ranjekar P.K. Chickpea defensive proteinase inhibitors can be inactivated by podborer gut proteinases.Plant Physiol. 1998; 116: 393-401Crossref Scopus (158) Google Scholar). Insects also overexpress protease from one class to compensate with the inhibition of another class (8.Lomate P.R. Hivrale V.K. Differential responses of midgut soluble aminopeptidases of Helicoverpa armigera to feeding on various host and non-host plant diets.Arthropod-Plant Interact. 2011; 5: 359-368Crossref Scopus (21) Google Scholar). Many insects use combination of multiple strategies to avoid the antinutritional effects of plant PIs. However, the mechanism or factors by which the insects recognize the presence of PI and adjust their gene expression accordingly, remain largely unknown in phytophagous insects. Hyperproduction of proteases to compensate the inhibition of activity was attributed to feedback mechanisms in response to dietary PIs. Blood feeding insects including mosquito and blackfly showed induction of trypsin-encoding genes after a blood meal (9.Lehane M.J. Muller H.M. Crisanti A. Mechanisms controlling the synthesis and secretion of digestive enzymes in insects.in: Lehane M.J. Billingsley P.F. Biology of the Insect Midgut. Chapman & Hall, London1996: 195-205Crossref Google Scholar, 10.Barillas-Mury C.V. Noriega F.G. Wells M.A. Early trypsin activity is part of the signal transduction system that activates transcription of the late trypsin gene in the midgut of the mosquito Aedes aegypti.Insect Biochem. Mol. Biol. 1995; 25: 241-246Crossref PubMed Scopus (89) Google Scholar). Promoters of inhibitor-induced trypsin and chymotrypsin genes from larval midguts of Helicoverpa zea and Agrotis ipsilon showed presence of different regulatory motifs suggesting diverse regulatory mechanism of protease expression (11.Mazumdar-Leighton S. Broadway R.M. Transcriptional induction of diverse midgut trypsins in larval Agrotis ipsilon Helicoverpa zea feeding on the soybean trypsin inhibitor.Insect Biochem. Mol. Biol. 2001; 31: 645-657Crossref PubMed Scopus (103) Google Scholar). Analysis of CmCatB, a cathepsin B gene from the cowpea bruchid (Callosobruchus maculatus) larval midgut, revealed intricate transcriptional regulation underlying the adaptive measures (12.Moon J. Salzman R.A. Ahn J.E. Koiwa H. Zhu-Salzman K. Transcriptional regulation in cowpea bruchid guts during adaptation to a plant defence protease inhibitor.Insect Mol. Biol. 2004; 13: 283-291Crossref PubMed Scopus (52) Google Scholar). Later CmCatB was found to play a role in cowpea bruchid adaptation by rendering it less susceptible to soybean cysteine PI inhibition (12.Moon J. Salzman R.A. Ahn J.E. Koiwa H. Zhu-Salzman K. Transcriptional regulation in cowpea bruchid guts during adaptation to a plant defence protease inhibitor.Insect Mol. Biol. 2004; 13: 283-291Crossref PubMed Scopus (52) Google Scholar, 13.Koo Y.D. Ahn J.E. Salzman R.A. Moon J. Chi Y.H. Yun D.J. Lee S.Y. Koiwa H. Zhu-Salzman K. Functional expression of an insect cathepsin B-like counter-defence protein.Insect Mol. Biol. 2008; 17: 235-245Crossref PubMed Scopus (48) Google Scholar). It is yet to be determined how insects sense the presence of dietary PIs and how the signal of amino acid deficiency is transmitted, leading to subsequent activation of counter defense-related genes. Investigations in mammals indicate that cholecystokinin (CCK) is the most significant regulator of the physiological pathways related to the secretion of intestinal digestive enzymes (14.Liddle R.A. Regulation of cholecystokinin secretion by intraluminal releasing factors.Am. J. Physiol. 1995; 269: G319-G327PubMed Google Scholar). Two other peptides, a monitor peptide and the CCK-releasing factor (CCK-RF) stimulate the release of CCK by interacting with cell surface receptors in the intestine, which later triggers the secretion of digestive enzymes into the intestine. CCK-RF-like or monitor-peptide-like factors have not yet been identified in phytophagous insects, but similar mechanisms may be responsible for regulation of digestive enzymes in the midgut (6.Broadway R.M. Dietary regulation of serine proteinases that are resistant to serine proteinase inhibitors.J. Insect Physiol. 1997; 43: 855-874Crossref PubMed Scopus (133) Google Scholar). For instance, a hemolymph circulating decapeptide trypsin-modulating oostatic factor (TMOF) has been found to downregulate the synthesis of trypsin in the larval gut of Helicoverpa virescens (15.Nauen R. Sorge D. Sterner A. Borovsky D. TMOF-like factor controls the biosynthesis of serine proteases in the larval gut of Heliothis virescens.Arch. Insect Biochem. Physiol. 2001; 47: 169-180Crossref PubMed Scopus (40) Google Scholar). Altogether, various studies suggest presence of several mechanisms for regulation of proteases both at transcriptional and post-translational level. However, understanding the post-translational regulation of protease activity by endogenous PIs has received less attention in insects and remains a major challenge despite biochemical and comparative genomic data on insect endogenous PIs. Usually, the insect endogenous PIs with varied proteinase inhibitory activities seem to regulate a range of physiological responses like their mammalian counterparts. In addition to inhibitors of digestive enzymes and pathogen-encoded virulence factors, endogenous protease inhibitors in Drosophila melanogaster are shown to be involved in many aspects of the innate immune response (16.Gubb D. Sanz-Parra A. Barcena L. Troxler L. Fullaondo A. Protease inhibitors and proteolytic signaling cascades in insects.Biochimie. 2010; 92: 1749-1759Crossref PubMed Scopus (48) Google Scholar). Therefore, in the present study we sought to determine the potential role of endogenous PIs in the regulation of protease gene expression against plant PIs in H. armigera. First, we comprehensively examined transcriptional and proteomic responses of H. armigera to ingested multi-domain recombinant Capsicum annuum protease inhibitor (CanPI-7). High throughput transcriptomic and proteomic analysis suggested that CanPI-7 ingestion influences general metabolism of the insect as well as proteolytic enzymes and endogenous protease inhibitors. Further, functional assays have been performed to evaluate qualitative and quantitative changes in proteases and PI activities in the larval digestive track and hemolymph of H. armigera feeding on CanPI-7. Finally, the probable role of insect endogenous protease inhibitors in regulation of gut proteases after ingestion of plant protease inhibitor has been discussed. H. armigera larvae were procured from Division of Insect Ecology, Indian Council of Agriculture Research-National Bureau of Agricultural Insect Resources, Bangalore, Karnataka, India. Feeding experiments were carried out with neonates of H. armigera maintained in the laboratory at optimum growth conditions (27 ± 2 °C, 60 ± 5% relative humidity and a photoperiod of 14 h light and 10 h dark). Artificial diet (AD) was prepared based on our earlier report (17.Mahajan N.S. Mishra M. Tamhane V.A. Gupta V.S. Giri A.P. Plasticity of protease gene expression in Helicoverpa armigera upon exposure to multidomain Capsicum annuum protease inhibitor.Biochim. Biophys. Acta. 2013; 1830: 3414-3420Crossref PubMed Scopus (20) Google Scholar). The major ingredients of the diets were chickpea flour, sorbic acid, ascorbic acid, methyl P-hydroxy benzoate, and vitamin and mineral mix. 150 μg of recombinant Capsicum annum protease inhibitor (CanPI-7) was incorporated per gram of AD for the feeding bioassays. In present study, first instar larvae were fed on AD or CanPI-7 incorporated AD for 48 h. Each larva was maintained in an individual vial. A set of 200 larvae (100 larvae each on AD and PI incorporated AD diet) was maintained in the laboratory at optimum growth conditions (27 ± 2 °C, 60 ± 5% relative humidity and a photoperiod of 14 h light and 10 h dark) and whole larvae were harvested at various time intervals (0.5, 2, 6, 12, 24, and 48 h). At each stage of bioassay, the harvested insect tissues were snap frozen in liquid nitrogen and stored at −80 °C until further use. These tissues were used for transcriptome sequencing. For proteomics, samples obtained from different time points on CanPI-7 exposure were pooled into three stages i.e. early (0.5, 2, and 6 h), mid (12 and 24 h) and late (48 h) stages. Each sample was acquired in AB-Sciex 5600 Triple TOF mass-spectrometer using two biological replicates and two technical replicates in DDA mode for spectral library preparation. SWATH-MS was carried out using three replicates to minimize retention time variation and for better statistical multivariate data analysis. H. armigera larval samples (in triplicate) from each time point of feeding assay were processed for RNA library preparation. Total RNA was isolated from the whole-body homogenates of insect tissues using Trizol reagent (Invitrogen, Carlsbad, CA) based on the manufacturer's protocol. RNA was quantified and checked for purity and integrity using agarose gel electrophoresis, Nanodrop (Thermo Scientific, Waltham, MA) and the Agilent 2100 Bioanalyzer. Total RNA (1 μg) passing all the quality check was used to isolate poly(A)-Tailed mRNA using poly T oligo beads. The purified mRNA was fragmented in the range of 100 to 140 bases (the optimum at around 120 bases) and cDNA was synthesized using TruSeq RNA sample preparation kit v2 (Illumina, San Diego, CA) according to manufacturer's protocol. The end repair, A-tailing and adapter ligation was performed as per the manufacturer's instructions. The libraries were then subjected to PCR enrichment (15 cycles) and again validated using Bioanalyzer. Libraries were then sequenced (in triplicate) in a paired-end 100 base run using TruSeq PE Cluster Kit v3-cBot-HS (Illumina) for cluster generation on C-Bot and TruSeq SBS Kit v3-HS for sequencing on the Illumina HiSeq1000 platform according to manufacturer recommended protocols. RNA sequencing was performed using the HiSeq1000 sequencing system from Illumina at Centre for Cellular and Molecular Platforms (C-CAMP), Bengaluru, Karnataka, India. Raw sequencing data were processed using CASAVA software from Illumina to generate files in FASTQ format along with a QC report. The obtained sequence tags from the Illumina sequencing were subjected to primary analysis in which low-quality tags and adaptor contaminants were discarded. Adapters were trimmed using Cut adapt v1.2.1 and the read quality was assessed using FastQC v0.10.1 program (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The low-quality reads were removed and reads with Phred Score ≥30 were processed for further analysis. The two FASTQ files (R1 and R2) generated for each sequenced sample were merged and subjected to assembly using Trinity software (http://trinityrnaseq.sourceforge.net/) with default k-mer size of 25 bp (18.Grabherr M.G. Haas B.J. Yassour M. Levin J.Z. Thompson D.A. Amit I. Adiconis X. Fan L. Raychowdhury R. Zeng Q. Chen Z. Mauceli E. Hacohen N. Gnirke A. Rhind N. Palma D. Birren B.W. Nusbaum C. Lindblad-Toh C. Friedman N. Regev A. Full-length transcriptome assembly from RNA-Seq data without a reference genome.Nat. Biotechnol. 2011; 29: 644-652Crossref PubMed Scopus (12706) Google Scholar). The non-redundant full-length transcriptome was then generated by clustering the assembled transcripts with sequence length longer than 200 bp at >90% identity using uclustv1.2.22q clustering tool (19.Edgar R.C. Search and clustering orders of magnitude faster than BLAST.Bioinformatics. 2010; 26: 2460-2461Crossref PubMed Scopus (14043) Google Scholar) and by extracting the centroid sequence of each cluster. The non-redundant transcriptome was validated by mapping back the good quality reads from all the 12 libraries separately using Bowtie2 v2.2.1 program (20.Langmead B. Salzberg S. Fast gapped-read alignment with Bowtie 2.Nat. Methods. 2012; 9: 357-359Crossref PubMed Scopus (26447) Google Scholar) with default parameters (http://bowtie-bio.sourceforge.net/index.shtml). Transcripts with 70% or more mapping coverage and minimum alignment of 5 reads from either of the libraries (control and treated libraries of a particular time point) were termed as true transcripts. A set of non-redundant transcripts (unigenes) from all the libraries was assembled in final assembly. The assembly was then annotated by homology search against National Center for Biotechnology Information Non-Redundant (NCBI-NR) protein database (ftp://ftp.ncbi.nlm.nih.gov/blast/db/) using standalone blast package v2.2.29+−1.x86_64.rpm (ftp://ftp.ncbi.nih.gov/blast/executables/LATEST/). BLAST hits with e-value ≤ 0.001 and query coverage above 50% were considered as best hits. Protein identifiers were then mapped to these hits using Uniprot id mapping tool (http://www.uniprot.org/mapping/). Similarly information such as Entrez gene identifiers, species information, gene ontology (GO) and pathway annotation for these hits were extracted using either Uniprot KB (http://www.uniprot.org/), DAVID Bioinformatics (http://david.abcc.ncifcrf.gov/) or Flink at NCBI (http://www.ncbi.nlm.nih.gov/Structure/flink/flink.cgi). We also used an online annotation server, Fast Annotator (http://fastannotator.cgu.edu.tw), to annotate these transcripts particularly with enzyme EC numbers and Pfam domain information. Expression levels of true transcripts in the individual libraries (all the controls and treated samples at different time points) were assessed by mapping good quality reads using BOWTIE2 (20.Langmead B. Salzberg S. Fast gapped-read alignment with Bowtie 2.Nat. Methods. 2012; 9: 357-359Crossref PubMed Scopus (26447) Google Scholar). Mapped reads were further normalized using DESeq method (21.Anders S. Huber W. Differential expression analysis for sequence count data.Genome Biol. 2010; 11: R106Crossref PubMed Scopus (10367) Google Scholar). Transcripts with fold change ≥1.5 over control and p value ≤0.05 were considered as differentially expressed. The Padj value provided by DESeq was used to determine the False Discovery Rate (FDR) for statistical analysis of significant mRNA changes. A high throughput label free quantitative proteomic analysis was conducted to understand digestive physiology of H. armigera larvae when fed on CanPI-7 diet. For proteomic analysis, samples obtained from different time points on CanPI-7 exposure (each set containing 100 insects) were pooled into three stages i.e. early (0.5, 2, and 6 h), mid (12 and 24 h) and late (48 h) stages. Proteins from whole insects were extracted according to the method of Schuster and Davies, (22.Schuster A.M. Davies E. Ribonucleic acid and protein metabolism in pea epicotyls I. The aging process.Plant Physiol. 1983; 73: 809-816Crossref PubMed Google Scholar) with few modifications. Whole insect tissues were finely ground using mortar and pestle in liquid nitrogen. Tissue (100 mg) was homogenized in 1 ml of extraction buffer (0.7 m sucrose, 0.5 m Tris-HCl, 50 mm EDTA, 0.1 m KCl, 2% [v/v] beta mercaptoethanol and 5% insoluble polyvinylpolypyrrolidone), vortexed thoroughly and centrifuged at 13,000 × g for 20 min at 4 °C. The supernatant was transferred to a fresh tube and equal volume of water-saturated phenol was added. The mixture was vortexed thoroughly and centrifuged at 13,000 × g for 30 min at 4 °C. The phenol phase was precipitated overnight with 5 volumes of 0.1 m ammonium acetate in methanol at 20 °C. The pellet was washed twice with 0.1 m ammonium acetate in methanol and once with 100% acetone, air dried and resuspended in lysis buffer (8 m urea, 2 m thio urea and 50 mm DTT). The suspension was centrifuged and clear solution containing total proteins was used for tryptic digestion. Protein concentration was determined by Bradford's method (23.Bradford M.M. Rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding.Anal. Biochem. 1976; 72: 248-254Crossref PubMed Scopus (216178) Google Scholar). Total 100 μg of proteins were reduced by 100 mm DTT for 15 min at 60 °C, alkylated with 200 mm iodoacetamide for 30 min in dark and kept overnight at 37 °C for tryptic digestion using Promega sequencing grade trypsin (Promega, Madison, WI). The digestion reaction was stopped after 16 h by adding concentrated formic acid and further incubating for 10 min at 37 °C before brief vortex and centrifuge. The peptides were desalted by using Zip-tip C18 ((Millipore, Billerica, MA)), concentrated by vacuum centrifuge and stored at −80 °C until further use. Samples were acquired in TripleTOF 5600 (AB Sciex) using instrumental methods, Parameters, acquisition methods, peptide spectral library, SWATH MS and Data processing described by Korwar et al. (24.Korwar A.M. Vannuruswamy G. Jagadeeshaprasad M.G. Jayaramaiah R.H. Bhat S. Regin B.S. Ramaswamy S. Giri A.P. Mohan V. Balasubramanyam M. Kulkarni M.J. Development of diagnostic fragment ion library for glycated peptides of human serum albumin: targeted quantification in prediabetic, diabetic and microalbuminuria plasma by PRM, SWATH and MSE.Mol. Cell. Proteomics. 2015; 14: 2150-2159Abstract Full Text Full Text PDF PubMed Scopus (40) Google Scholar) with few modifications. In brief, Peptide digest (3 μg) were separated by Eksigent C18-reverse phase column (100*0.3 mm, 3 μm, 120Å) using Eksigent MicroLC 200 system (Eksigent, Dublin, CA). The sample was loaded onto the column with 97% of mobile phase A (100% water, 0.1% FA) and 3% of mobile phase B (100% ACN, 0.1% FA) at 8 μl/min flow rate. Peptides were eluted with a 120 min linear gradient of 3 to 50% mobile phase B with the flow rate of 8 μl/min. The column temperature was set to 40 °C and auto sampler at 4 °C. The same chromatographic conditions were used for both DDA and SWATH acquisition. All samples were analyzed on AB-Sciex 5600 Triple TOF mass-spectrometer in positive and high-sensitivity mode. The dual source parameters were optimized for better results: ion source gases GS1, GS2, curtain gas at 25 psi. Temperature 200 °C and ion spray voltage floating (ISVF) at 5500 V. The DDA acquisition consist of full scan (MS) and information dependent MS/MS. The accumulation time in full scan was 250 ms for a mass range of 350–1800 m/z. The parent ions are selected based on the following criteria: ions in the MS scan with intensities more than 120 counts per second (CPS), charge stage between +2 to +5, mass tolerance 50 mDa and once a precursor ion was fragmented by MS/MS its mass and the mass of its isotopes were excluded for a period of 15 s. Ions were fragmented in the collision cell using rolling collision energy with an additional CE spread of ± 15 eV. In SWATH-MS mode, the instrument was specifically tuned to optimize the quadrupole settings for the selection of precursor ion selection windows 25 m/z wide. Using an isolation width of 26 m/z (containing 1 m/z for the window overlap), a set of 34 overlapping windows was constructed covering the precursor mass range of 400–1250 m/z. SWATH MS/MS spectra were collected from 100 to 2000 m/z. Ions were fragmented in the collision cell using rolling collision energy with an additional CE spread of ± 15 eV. An accumulation time (dwell time) of 96 ms was used for all fragment-ion scans in high-sensitivity mode, and for each SWATH-MS cycle a survey scan in high-resolution mode was acquired for 100 ms resulting in a duty cycle of 3.33 s. The source parameters are like that of DDA acquisition. Samples from early stage, mid stage and late stage were acquired in 2 biological replicates and 2 technical replicates in DDA method and 3 technical replicate in SWATH MS. All DDA mass spectrometric files were searched using ProteinPilot software (version 5.0.1, AB Sciex) with the Paragon algorithm against the H. armigera six frame translated transcriptome (number of entries in database = 213314). The search parameters were as follows: sample type: identification; cys alkylation: iodoacetamide; digestion: Trypsin (specificity - C terminus of Lys and Arg); instrument: Triple TOF 5600; special factors: None; and False Discovery Rate (FDR): 5%. FDR was calculated using ProteomicS Performance Evaluation Pipeline Software (PSPES) installed within ProteinPilot software. The Protein Pilot output file was used as a standard spectral library. For each stage, a combined spectral library was prepared containing biological and technical replicates of both control and CanPI-7 fed samples. All samples were acquired in 3 technical triplicates using the SWATH-MS, data independent acquisition method. The standard spectral library was loaded into the Peak view software (version 1.2.03, AB Sciex). The spectral alignment and targeted data extraction of SWATH-MS data was performed using Peak view software with the following parameters: Number of peptides per protein 6, number of transitions per peptide 10, Peptide confidence 95%, FDR threshold 1%, XIC extraction window 3 min, XIC width 30 ppm and shared peptides were excluded. All the data independent acquisition files were loaded and exported in to MarkerView software (version 1.2.1.1 AB Sciex), where they were used for the further quantitative and statistical analyzed. Normalization was performed using total area sum. The statistics were performed using t test and the significant p value was considered 30% were used for further study. Multivariate data analysis was done using SIMCA-P software (version 13.0, Umetrics). Principle Component Analysis (PCA) was employed on the whole data set to check overall trend in data and to establish CanPI-7 induced proteomics change using Pareto scaling. In order to investigate whether protease genes and endogenous PI genes were coexpressed, we constructed t
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