Journal of Bioinformatics, Proteomics and Imaging Analysis | Volume 1 | Issue 2 | 2015-11-10

Characterization and Larval Expression Analysis of Midgut Serine Proteases of Spodoptera Frugiperda (Lepidoptera: Noctuidae)

Vilmar Machado

Abstract

Spodoptera frugiperda (J. E. Smith) feeds on a variety of plants, causing economic losses in crops such as corn, rice and cotton in the Americas. Midgut serine proteases provide the ability to regulate host plant inhibitors. Despite the importance of these proteins in the adaptation to feeding on different plant species, few studies have dealt with their identification and description in S. frugiperda . This paper identifies, characterizes, obtains the sequence by 5 RACE-PCR and analyses the expression pattern of six serine protease genes from S. frugiperdain silico analyses detected a high level of expression of these two enzymes together with Sp_5_Sf in midgut cDNA libraries of larvae treated with xenobiotic substances. Understanding the functional significance of these proteins can contribute to the development of new strategies of pest control, such as inactivation of serine proteases.

Keywords: Expression Profiles, Midgut, qRT-PCR, Serine Proteases, Spodoptera frugiperda

Full text

Co-evolution processes, often described as an evolutionary arms race, shape many adaptive traits of plants and herbivorous insects. Among the various aspects of these processes, the co-evolution between insect digestive enzymes and the inhibitors of these proteins produced by the plant species is remarkable, resulting in a wide variety of substances in both groups [1,2] . Spodoptera frugiperda , is a polyphagous Lepidopteran pest that feeds on a variety of plant species throughout its distribution area. From an economic point of view, it causes significant losses in corn, rice and cotton crops. Some papers have demonstrated the presence of biotypes adapted to different host plants with different responses to chemical and biological control agents [3-8] . The digestive capacity of S. frugiperda , endowed mostly by serine proteases present in the midgut, provides the same high ability to adjust the presence of inhibitors of serine proteases in host plants [9-12] . The intestine is the main organ involved in digestion, food absorption and protection against invasion by insect pathogens, and, therefore, it has been a constant target for studies aimed at developing new strategies for chemical and biological control. Thus, the analysis of midgut gene expression patterns and the characteristics of these proteins is important in the investigation of new targets for these new control strategies. The objective of these strategies is to create ways to alter or disrupt the digestion process, reducing food absorption and therefore slowing growth and increasing susceptibility to other control agents [13-15] . Protease inhibitors are substances produced by plants capable of reducing or blocking the digestive activities of these proteins in phytophagous insects. Several studies have been conducted aimed at i) examining the power of these inhibitors to negatively affect larval development and adult emergence and ii) evaluating their potential as alternative strategies for pest control [16,17] . Some of these studies, which involve the evaluation of the potential of transgenic plants expressing protease inhibitors, have shown promising results [18,19] . Serine proteases, such as trypsin, chymotrypsin, cysteine proteases, aminopeptidases and carboxipeptidades, are major digestive enzymes from the larval midgut of Lepidoptera [20] and correspond to approximately 95% in some lepidopteran species [16,21] . Serine proteases are involved in the immune response [22] , digestion of proteins [23] and in the moulting of insects [24,25] . These enzymes are also associated with the activation and degradation processes of toxins produced by Bacillus thuringiensis [26] . Currently, the emergence of pest control techniques based on the application of interference RNA (RNAi) toblock the expression of genes crucial for development in insects has attracted renewed interest for the study of these and other digestive enzymes [27-31] . Analysis of expressed sequence tags (ESTs) libraries is an effective procedure for identifying and characterise genes expressed in tissues of interest, providing information on metabolic function. The availability of these libraries, especially for species of economic interest, has stimulated studies intended to identify genes that may serve as targets for new strategies for pest control. Currently, libraries are available for many species, which has enabled the characterisation of proteins in different species, such as Manduca sexta; Helicoverpa armigera [16,26,32-35] and Spodoptera litura [36] . Moreover, some studies use available data to design primers, clone, characterise and analyse the pattern of expression of these proteins [37-41] . In this work, the EST library of S. frugiperda midgut is used to identify six serine proteases whose complete sequence is determined by the rapid amplification of cDNA ends and their expression pattern is evaluated by qRT-PCR in larvae of different stages. This work is part of a long-term study with the objectives of i) providing information that helps to understand theability of this species to exploit a diversity of host plants and ii) identifying enzymes that might well be used as targets for future control strategies. Material and Methods Sequences The identification of the serine protease genes was based on analysis of Sf_TR2012b assembly sequences downloaded from the LipidoDB database (http://www6.inra.fr/lepidodb/Private). In silico expression analysis was made by comparing the frequency of the tags (EST) between two midgut libraries of S. frugiperda larvae downloaded from the SPODOBASE database [non-treated (Sf1M) and treated (Sf2M) with xenobiotic substances (http://bioweb.ensam.inra.fr/spodobase/) . The libraries were assembled with SOAP2novo with the default settings available in the Japan Supercomputer [42] . The sequences were annotated using Blast2Go software [43] . Sequences annotatedas serine proteases or serine protease-like were selected for further analyses. The ORFs were identified using ORFinder [44] . Only complete ORF sequences and without significant blast similarity for proteases already described for S. frugiperda were selected for this work. Complementary DNA (cDNA) and amino acid sequences analyses: To identify and characterise Spodoptera frugiperda serine proteases, several bioinformatics tools were used. First, all sequences with complete open reading frame were blasted against the NCBI database (http://www.ncbi.nlm.nih.gov/) . The functional analysis was based on tools that provide information about family, domains and important proteins sites, such as InterProScan [45] , SignalP [46,47] and Disulphide Bonding Prediction [48] . To identify specific characteristics of the serine proteases (activation site, the location of the catalytic triad, substrate-binding site) the amino acid sequences were subjected to a BLAST against the MEROPS database [49] . RNA extraction and reverse transcription: Spodoptera frugiperda larvae were field collected from San Luis Potosi Mexico. Larvae were maintained in the laboratory with an artificial diet at 25 2 C. Previous to RNA extraction, larvae of different stages were individually fixed in RNA later. Total RNA from larvae was isolated using TRIzol Reagent (Life Technologies ) following the manufacturer s protocol. RNA extractions were treated with TURBO DNA-free (Ambion, Life Technologies) and reverse transcribed using QuantiTect Reverse Transcription kit (QUIAGEN). Rapid amplification of cDNA ends: The original ESTs were used as reference to construct gene-specific primers [50] (Table 1) for RACE PCR amplification. Total RNA from two S. frugiperda larvae was used to obtain the first strand of 3 and 5 RACE Ready CDNA. The 5 and 3 RACE libraries were produced using the Clontech SMARTer RACE cDNA amplification kit (Takara Bio.) following the manufacturer s instructions. The amplification products were sequenced directly by the dideoxy chain termination method using the Big Dye Terminator Cycle Sequencing Ready Reaction Kit with Ampli Taq DNA Polymerase, FS (Taq FS), in an ABI PRISM Tm 377 DNA Sequencer (Applied Biosystems, Foster City, CA) in the Molecular Biology Service of the University of Murcia. Sequences were assembled by Geneious v.5 [50] . All the analyses performed with the ORFs generated by the ESTs analysis were repeated with the race products to confirm the results. Table 1: Primer sets used to RACE PCR amplification of the serine proteases genes. Serine proteases Primers 5 - 3 SP_1_SF_F CAGGCGGGTCTCGTGATCCAAGTTT SP_1_SF_R CCATCACAGGGTTCGGTAGGTAAGA SP_2_SF_F CGGTCTCGGCTGCTAAGAACATC SP_2_SF_R GCAACCATCCCAGTGTCCGAAAGAG SP_3_SF_F GTTATTCAAGTCAATTCCGGTCCATTT SP_3_SF_R CCAGCGCCCGAAGATGACATGTC SP_4SF_F AGTGTCATCGTAAACTAAACTGTAA SP_4_SF_R GAGAATCTTCGATGTAAGCAATCTC SP_5_SF_F CCAACGTGCAGCCWTCCCGTCTGAT SP_5_SF_R CACCGCTGTCACCCTGGCAGGAAG SP_6_SF_F CCGTTGGAAGATGAAGGGTTTC SP_6_SF_R GGGCGAGTACTTGGTAGCACAATTA Quantitative real-time PCR (qRT-PCR): The expression of the serine protease genes was investigated by quantitative real- time PCR (qRT-PCR) analysis. Experiments were carriedout on a StepOnePlus Real-Time PCR System using SYBR Green (Applied Biosystems ). Total RNA was extracted from three larvae of second, fourth and sixth stage. The RNA extraction and cDNA synthesis protocol were described above. The specific primers for qRT-PCR were designed based on gene sequences using Primer3 software [51] (Table 2). Primers from argenine kinase and ribosomal protein L10 were designed and used as endogenous controls, as they have previously proved useful in gene expression studies in Spodoptera species [37] . Gene efficiencies were first validated with the Quantification Standard Curve method using a serially diluted pool of cDNA. The gene expression experiment was carried out using the Comparative CT method [52] considering both endogenous genes as multiple controls and the second larval stage as reference sample. The experiment was carried out with three biological replicates under the following conditions: denaturation at 95 C for 2 min, followed by 40 cycles at 95 C for 15s and 60 C for 30s. All data were analysed with the program 7500 software v2.0.5 (Applied Biosystems ). Table 2: Primers used for expression analysis of the Spodoptera frugiperda serine proteases Argenine kinase_F TGGACTCTGGTGTCGGAATCT Argenine kinase_R CAGTTCTTGGCAGGGTGCTT Ribossomal protein L10_F AGGCTGCATCCATTCCATGT Ribossomal protein L10_R CACACGCGCTACGGTACCTT SP1_F TGGAGTCCACCCACAAGCACATCCA SP1_R ACGATACCGACTTGTGTGCGCTTGC SP2_F TGGAGTAGTGCTTGCGGTGGTTCCT SP2_R GAGGACCACCAGAGTCACCATGGCA SP3_F TCCTCATCACCTCCTCCAACGTGGC SP3_R AGCCCCAGGACACGATACCGAACTG SP4_F CGACTCGGAGACGTGGACAT SP4_R GGTCCAGCTTCAGAACTGCAA SP5_F CTCCTTCGTGGTTCGTTTCG SP5_R CCAGGTCGGCGGTTTG SP6_F TGTCCTCCACCCTGAGTACGA SP6_R CGCAGAAGGTTCCAGATTCG Differences in expression rate: The number of EST present in the midgut library were also used for analysing the differences in expression rate between the serine proteases, applying the statistical test suggested by [53] . In these approaches, the frequencies of those proteins in two midgut libraries (treated and non-treated) were compared. During these procedures, a preliminary test was conducted to define the BLAST condition to prevent the presence of ESTs paired with one or more S. frugiperda serine proteases. The BLAST was done with an e-value of 1e-30 and the results were carefully revised to eliminate sequences with two or more pairwise matches. The best score was selected to avoid assigning any given EST to more than one protein. Phylogenetic analysis: The sequences were aligned using the Clustal X software (version 1.81) [54] . Phylogenetic relationships were estimated by maximum likelihood analysis software PHYML [55] with LG substitution model with bootstrap 1000 replicates. In this analysis, 36 serine protease sequences of Lepidoptera were downloaded from GenBank. The species were Agrotis ipsilon (AF233728_1) , Diatraea saccharalis (AFW03964) , Heliothis virescens (AFM28253, AFM28256, AFM28249, ABR88234, ABR88235, ABR88236, ABR88239, AAF43709 and ABR88240 ), Helicoverpa punctigera ( AAV33657, CAA72951, AAV33653 and AAV33655 ), Helicoverpa armigera ( CAA72952, CAA72966, CAA72965, ABP96917 and ACB54938 ), Helicoverpa zea ( AF233732_1 ), Danaus plexippus ( EHJ71324 ), Spodoptera litura (ADK27715) , Bombyx mori ( NP_001037037 and AFD99127 ), Ostrinia nubilalis ( AFM77775, ACI45417 and ACI45415 ), and Mamestra configurata ( ACR15986, ACR15984, ACR15983, ACR15993, ACR15979, ADT80821, ADT80826 and ADT80829 ). Results The annotation process of the reference transcriptome assembly Sf_TR2012b of S. frugiperda , downloaded from the LepidoDB database, identified the presence of 21 sequences named serine proteases, of which only six showed complete open reading frames (ORFs). The size of the fragment amplified by RACE-PCR ranged from 705 to 972 bp. The molecular weight of these proteins ranged from approximately 24 to 30 kd and the isoelectric point between 4.39 and 8.79 pl. All sequences obtained were submitted to GeneBank with the following access numbers: KP690080 - KP690085 (Table 1). The BLAST analysis of these sequences showed high similarity to serine protease genes from Mamestra configurata [Sp1-Sf, Sp4-Sf, Sp6-Sf], Spodoptera litura [Sp2-Sf] and Heliothis virescens [Sp-Sf3, Sp-Sf5] (Table 3). The similarity with the homologous proteins ranged between 61% and 86%. The number of amino acid residues of the S. frugiperda proteins ranged between 234 and 308. All amino acid sequences presented significant e-value for the presence of Tryp_SP domain (Table 4). Table 3: Amino acid similarity and E value of putative serine proteases genes of spodoptera frugiperda and best match in NCBI (Blastx) Gene name (Sf) GenBank accession numbers cDNA (pb) Organism Protein name Similarity E value GenGank accession number of homologous Sp_1_Sf KP690080 876 Mamestra configurata Serine protease 11 78% 6e-163 ACR15986.2 Sp_2_Sf KP690081 885 Spodoptera litura Chymotrypsin-like protein 2 75% 3e-129 ADK27715.1 Sp_3_Sf KP690082 840 Heliothis virescens Chymotrypsin-like protease C1 85% 8e-175 ABR88231.1 Sp_4_Sf KP690083 927 Mamestra configurata Serine protease 40 65% 5e-119 ACR15979.2 Sp_5_Sf KP690084 972 Heliothis virescens Chymotrypsin 86% 5e-174 AFM28256.1 Sp_6_Sf KP690085 705 Mamestra configurata Serine protease 38 61% 8e-86 ACR15993.2 Table 4: Characteristic of six serine proteases of Spodoptera frugiperda deduced from cDNA from larval midgut Gene name Number of amino acid residues Peptide signal prepetide Predicted molecular mass (D) Predicted isoletric point (pl) Tryp_SPc domain E-value Sp_1_Sf 291 1-18 17-56 30215.17 7.61 5.49e-40 Sp_2_Sf 294 1-16 17-59 30911.93 6.04 3.25e-74 Sp_3_Sf 279 1-18 19-38 29510.65 8.79 7.39e-55 Sp_4_Sf 308 1-18 19-35 34560.63 4.61 1.3e-41 Sp_5_Sf 323 1-18 19-40 34847.60 4.49 7.74e-49 Sp_6_Sf 234 1-16 17-36 24413.37 4.39 2e-77 Alignments performed with the MEROPS database indicated that five of the six mature proteins (Sp_1_Sf, Sp_2_Sf, Sp_3_Sf, Sp_4_Sf and Sp_5_S) have typical serine protease characteristics, such as i) the presence of the signal peptide necessary for secretion (Table 4, Table 5 and Figure 1) at the N-terminal activation site, where the pre-peptide is removed from the mature protein (IVGG), ii) an arginine residue in the previous position and iii) six cysteine residues to form disulphide bridges. The five proteins have residues corresponding to the catalytic triad (His, Asp, Ser) at the expected positions, as indicated by the alignment. In the first position of the S1 pocket, we found glycine (Sp_1_Sf, Sp_3_Sf), asparagine (Sp_4_Sf), serine (Sp_2_Sf) and alanine (Sp_5_Sf), Sp_6_Sf protein has a substitution at the active site, similar to those found in Mamestra configurata [56,57] and in this case the amino acid serine replaces histidine at position 68 and asparagine replaces aspartic acid at position 111 (Figure 2). That protein shows only four cysteine residues for disulphide bridges. The MEROPS database classified the Sp_6_Sf as a non-peptidase homologue protein, due to the replacement found in the traditional catalytic residues. Table 5: Designations and key amino acid residues of serine proteases deduced from cDNA of larval midgut of Spodoptera frugiperda Protease name Family/Subfamilia Merops N-terminal activation residue Catalytic triad residues (His/Asp/Ser) MEROPS Number of Cys for disulfide bonds S1 pocket Sp_1_Sf S1.A Arg His/Asp/Ser 6 Gly/Ser/Gly Sp_2_Sf S1.A Arg His/Asp/Ser 6 Ser/Ser/Gly Sp_3_Sf S1.A Arg His/Asp/Ser 6 Gly/Ser/Gly Sp_4_Sf S1.A Arg His/Asp/Ser 6 Ans/Ser/Gly Sp_5_Sf S1.A Arg His/Asp/Ser 6 Ala/Ser/Gly Sp_6_Sf S1.A non-peptidase homologues Ser/asn/ 4 Figure 1: Alignment of five serine proteases homologous from Spodoptera frugiperda larvae. The cleavage site (underline), catalytic triads (arrow) and S1 pocket (star) Figure 2: Figure 1. Alignment of SP_5_SF with similar protein from Helicoverpa armigera (ABP96917) and Mamestra configurata (ACR15993). The amino acid replacements at position 68 (serine) and position 111 (asparagine) are boxed. Expression levels of the six serine protease genes described were analysed by qRT-PCR in second, fourth and sixth stages larvae (Figure 3). Five of the genes (Sp_1_Sf, Sp_2_Sf, Sp_3_Sf,Sp_4_Sf and Sp_6_Sf) displayed significant changes in gene expression in the sixth larval stage, with Sp_1_Sf, Sp_2_Sf and Sp_6_Sf (P < 0.01) being those that showed the most remarkable expressionincrease. Only gene Sp_5_Sf shows a small, although statistically significant, reduction in the sixth stage. Likewise, Sp_3_Sf and Sp_4_Sf showed small, although statistically significant, expression increases. Additionally, the expression analysis based on EST frequencies showed significant differences between midgut cDNA libraries obtained from larvae non-treated and treated with xenobiotic substances. Genes Sp_2_Sf, Sp_5_Sf and Sp_6_Sf showed a high expression rate in larvae exposed to xenobiotic substances (P< 0.001). Figure 3: Relative quantification of serine proteases genes for second, fourth and sixth larval stage of the Spodoptera frugirperda . Statistical significance is indicated by * (P < 0.05). Phylogenetic analysis (maximum likelihood) indicated that the proteins analysed belong to different groups, with greater similarity between pairs Sp_1_Sf: Sp_2_Sf (50%) and Sp_4_Sf: Sp_5_Sf (45.8%); the other similarity values ranged between 16.6% and 29.47% (Table 6, Figure 4). Figure 4: Phylogenetic analysis of serine protease from Spodoptera frugiperda with 37 other serine proteases from ten Lepidoptera species. The genebank access numbers are indicated in the tree. Table 6: Similarity matrix between serine proteases deduced from cDNA of midgut larva of Spodoptera frugiperda Proteins Sp_6_Sf Sp_3_Sf Sp_1_Sf Sp_2_Sf Sp_4_Sf Sp_5_Sf Sp_6_Sf 16.8% 16.6% 17.4% 20.5% 22.7% Sp_3_Sf 23.9% 26.0% 21.7% 23.5% Sp_1_Sf 50.0% 23.1% 23.8% Sp_2_Sf 24.2% 29.4% Sp_4_Sf 45.8% Sp_5_Sf Discussion In this study, six cDNA sequences involved in serine protease synthesis were characterised. Coding amino acid sequences of five of those genes exhibited the structural features expected for serine proteases, like catalytic triad (His/Asp/Ser), six cysteine residues, a signal peptide containing between 16 and 23 amino acids and activation site in the N-terminal region IVGG [21,38,58,59] . All these proteins belong to the S1A sub-family, known to be involved in several important physiological processes [60,61] . They also present amino acids that are characteristic of trypsin (amino acids with negative charge) and chymotrypsin serine proteases (hydrophobic) at the first position of the specificity site (S1 pocket). However, only Sp_1_Sf and Sp_3_Sf have the amino acid typical of trypsin in the first position of the S1 pocket (Gly) and Sp_2_Sf has that typical of chymotrypsin (Ser). Substitutions in the specificity site, as documented in this study, were recorded for several species of insects [21,39,41] , i.e. asparagine (Sp_4_Sf) and alanine (Sp_5_Sf) residues. The replacement of amino acids in the S1 pocket region, where the enzyme recognizes and cleaves the substrate, was observed in other species and has been subject of debates, given that this region is essential for enzyme specificity. These changes, especially in site specificity, may be associated with adaptations to different hosts and may have occurred in response to modifications in protease inhibitors produced by plants [26,36,39,41] . According to [60] , variations in that position produceadjustments in the dynamic properties of serine proteases, and, therefore, lead to alterations in substrate specificity. This diversity may be due to the co-evolution process (arms race) between herbivorous insects and plants [1,2,61] . In Lepidoptera these modifications can be understood as adaptations to minimize the impact of protease inhibitors [26] and this may well be the case of the serine protease genes characterized in this paper for S. frugiperda . One relevant aspect of this study is the identification of the serine protease Sp_6_Sf, similar to that found in H. armigera (ABP96917), which is associated to resistance to the Cr1AC toxin from Bacilus thuringiensis , producing poor or inadequate processing of the protoxin [57] and as a consequence, blocking the conversion to in active toxin. However, the physiological importance of this protein still needs to be clarified in S. frugiperda . The description of these proteins is the first step of the process to be able to understand their specific importance in larval metabolism and their contribution to larval survival and adaptation. The observed change in gene expression pattern indicates that the Sp_1_Sf, Sp_2_Sf and Sp_6_Sf enzymes might have an important role in digestion in S. frugiperda larvae. On the other hand, the high frequency of these enzymes in EST libraries from larvae treated with xenobiotic products may also indicate their involvement in eliminating and neutralizing toxins. Thus, in silico analysis showed high frequency of the EST of enzyme Sp_5_Sf in the library from intestine of the treated larvae. Alterations in the expression patterns of serine proteases have been described for various species of insects, and they are associated with increases in food consumption rate and detoxification processes [61-63] . Serine proteases can perform basic functions during the development of an insect [30] which may explain the observed differences in their expression in S. frugiperda . The outcome of the expression analysis shows that at least three of the serine proteases described here (Sp_2_Sf, Sp_6_Sf and Sp_5_Sf) deserves further study to elucidate their actual involvement in the S. frugiperda intestine metabolic processes. This attention is justified by its experimentally verified high expression level, particularly in the sixth stage of larval development, and the in silico -detected high EST frequency of these enzymes in the midgut cDNA library of larvae treated with xenobiotic substances. The phylogenetic analysis of serine proteases provides a graphic illustration of their clustering but this does not represent a precise construction of the volutionary history. The tree represents the distance between the proteins described and its proximity to serine protease from other lepidopteran species. Conclusion This study identifies and describes three serine proteases that deserve special attention when we consider the variations observed in their expression patterns. Thus, proteins SP_2_SF and SP_6_SF show high expression change between the second and sixth larval stage. Protein SP_5_SF showed a high frequency in cDNA libraries of larvae treated with xenobiotic substances, despite the minimal changes in the expression rate between the different larval stages. The study of these proteins i) contributes to the understanding of the mechanisms that enable Spodoptera frugiperda to explore several host plants found in its distribution area, and ii) helps to clarify the differences in the response to control agents observed in some populations. In addition, understanding the functional significance of these proteins may be important for the development of tools that target inactivation of serine proteases as an improvement for pest control strategies. Acknowledgment The authors thank the CNPq for their support in granting a postdoctoral scholarship (PDE) to V.M. We acknowledge MPA. Carlos Edwing Escalante Nolasea and MPA. Jorge Luis Borja Gonz lez (Facultad de Agronom a y Veterinaria de la Universidad Aut noma de San Luis Potosi, Mexico) for collecting the larvae of Spodoptera frugiperda . References 1. Bronstein, J.L. Proteases hold the key to an exclusive mutualism. (2013) Mol Ecol 22(15): 3882 3884. 2. Joshi, R.S., Mishra, M., Suresh, C.G., et al. Complementation of intramolecular interactions for structural functional stability of plant serine proteinase inhibitors. (2013) Biochim Biophys Acta 1830(11): 5087 5094. 3. Nagoshi, R.N., Silvie, P., Meagher, R.L., et al. Identification and Comparison of Fall Armyworm (Lepidoptera: Noctuidae) Host Strains in Brazil, Texas, and Florida. (2007) Ann Entomol Soc Am 100(3): 394 402 4. Machado, V., Wunder, M., Baldissera, V.D., et al. Molecular Characterization of Host Strains of Spodoptera frugiperda (Lepidoptera: Noctuidae) in Southern Brazil. (2008) Ann Entomol Soc Am 101(3): 619 626. 5. Groot, A.T., Marr, M., Sch fl, G., et al. Host strain specific sex pheromone variation in Spodoptera frugiperda. (2008) Front Zool 5: 20. 6. Barros, E.M., Torres, J.B., Ruberson, J.R., et al. Development of Spodoptera frugiperda on different hosts and damage to reproductive structures in cotton. (2010) Entomol Exp Appl 137(3): 237 245. 7. R os-D ez, J.D., Siegfried, B., Saldamando-Benjumea, C.I. Susceptibility of Spodoptera frugiperda (Lepidoptera: Noctuidae) Strains from Central Colombia to Cry1Ab and Cry1Ac Entotoxins of Bacillus thuringiensis . (2012) Southwest Entomol 37(3): 281 293. 8. Devappa, R.K., Angulo-Escalante, M.A., Makkar, H.P.S., et al. Potential of using phorbol esters as an insecticide against Spodoptera frugiperda . (2012) Ind Crops Prod 38: 50 53. 9. Brioschi, D., Nadalini, L.D., Bengtson, M.H., et al. General up regulation of Spodoptera frugiperda trypsins and chymotrypsins allows its adaptation to soybean proteinase inhibitor. (2007) Insect Biochem Mol Biol 37(12): 1283 1290. 10. De Oliveira, C.F.R., De Paula Souza, T., Parra, J.R., et al. Insensitive trypsins are differentially transcribed during Spodoptera frugiperda adaptation against plant protease inhibitors. (2013) Comp Biochem Physiol B Biochem Mol Biol 165: 19 25. 11. Jakka, S.R., Knight, V.R., Jurat-Fuentes, J.L. Spodoptera frugiperda (JE Smith) with field-evolved resistance to Bt maize are susceptible to Bt pesticides. (2014) J Invertebr Pathol 122: 52-54. 12. Saldamando-Benjumea, C.I., Estrada-Piedrah ta, K., Vel squez-V lez, M.I., et al. Assortative Mating and Lack of Temporality Between Corn and Rice Strains of Spodoptera frugiperda (Lepidoptera, Noctuidae) from Central Colombia. (2014) J Insect Behav 27(5): 555 566. 13. Guo, S., Ye, S., Liu, Y., et al. Crystal structure of Bacillus thuringiensis Cry8Ea1: An insecticidal toxin toxic to underground pests, the larvae of Holotrichia parallela. (2009) J Struct Biol 168(2): 259 266. 14. Bravo, A., Likitvivatanavong, S., Gill, S.S., et al. Bacillus thuringiensis: A story of a successful bioinsecticide. (2011) Insect Biochem Mol Biol 41(7): 423 431. 15. Macedo, M.R., Freire, M. das G.M. Insect digestive enzymes as a target for pest control. (2011) I S J 8: 190 198. 16. Chougule, N.P., Doyle, E., Fitches, E., et al. Biochemical characterization of midgut digestive proteases from Mamestra brassicae (cabbage moth; Lepidoptera: Noctuidae) and effect of soybean Kunitz inhibitor (SKTI) in feeding assays. (2008) J Insect Physiol 54(3): 563 572. 17. George, D., Ferry, N., Back, E.J., et al. Characterisation of midgut digestive proteases from the maize stem borer Busseola fusca. (2008) Pest Manag Sci 64(11): 1151 1158. 18. Senthilkumar, R., Cheng, C.P., Yeh, K.W. Genetically pyramiding protease-inhibitor genes for dual broad-spectrum resistance against insect and phytopathogens in transgenic tobacco. (2010) Plant Biotechnol J 8: 65 75. 19. Gatehouse, J.A. Prospects for using proteinase inhibitors to protect transgenic plants against attack by herbivorous insects. (2011) Curr Protein Pept Sci 12(5): 409 416. 20. Broehan, G., Kemper, M., Driemeier, D., et al. Cloning and expression analysis of midgut chymotrypsin-like proteinases in the tobacco hornworm. (2008) J Insect Physiol 54(8): 1243 1252. 21. Srinivasan, A., Giri, A.P., Gupta, V.S. Structural and functional diversities in lepidopteran serine proteases. (2006) Cell Mol Biol Lett 11: 132 154. 22. Kanost, M.R., Jiang, H., Yu, X.Q. Innate immune responses of a lepidopteran insect, Manduca sexta. (2004) Immunol Rev 198: 97 105. 23. Herrero, S., Combes, E., Van Oers, M.M., et al. Identification and recombinant expression of a novel chymotrypsin from Spodoptera exigua. (2005) Insect Biochem Mol Biol 35(10): 1073 1082. 24. Wei, Z., Yin, Y., Zhang, B., et al. Cloning of a novel protease required for the molting of Locusta migratoria manilensis. (2007) Dev Growth Differ 49(7): 611 621. 25. He, W.Y., Zheng, Y.P., Tang, L., et al. Cloning, expression and localization of a trypsin-like serine protease in the spruce budworm, Choristoneura fumiferana . (2009) Insect Sci 16(6): 455 464. 26. Yao, J., Buschman, L.L., Oppert, B., et al. Characterization of cDNAs encoding serine proteases and their transcriptional responses to Cry1Ab protoxin in the gut of Ostrinia nubilalis larvae. (2012) PloS One 7(8): e44090. 27. Broehan, G., Arakane, Y., Beeman, R.W., et al. Chymotrypsin-like peptidases from Tribolium castaneum: A role in molting revealed by RNA interference. (2010) Insect Biochem Mol Biol 40(3): 274 283. 28. Jayachandran, B., Hussain, M., Asgari, S. An insect trypsin-like serine protease as a target of microRNA: utilization of microRNA mimics and inhibitors by oral feeding. (2013) Insect Biochem Mol Biol 43(4): 398 406. 29. Asokan, R., Chandra, G.S., Manamohan, M., et al. Response of various target genes to diet-delivered dsRNA mediated RNA interference in the cotton bollworm, Helicoverpa armigera . (2014) J Pest Sci 87: 163 172. 30. Bao, Y.Y., Qin, X., Yu, B., et al. Genomic insights into the serine protease gene family and expression profile analysis in the planthopper, Nilaparvata lugens (2014) BMC Genomics 15: 507. 31. Sapountzis, P., Duport, G., Balmand, S., et al. New insight into the RNA interference response against cathepsin-L gene in the pea aphid, Acyrthosiphon pisum: Molting or gut phenotypes specifically induced by injection or feeding treatments. (2014) Insect Biochem Mol Biol 51: 20 32. 32. Peterson, A.M., Fernando, G.J., Wells, M.A. Purification, characterization and cDNA sequence of an alkaline chymotrypsin from the midgut of Manduca sexta. (1995) Insect Biochem Mol Biol 25(7): 765 774. 33. Chevignon, G., Cambier, S., Da Silva, C., et al. Transcriptomic response of Manduca sexta immune tissues to parasitization by the bracovirus associated wasp Cotesia congregata. (2015) Insect Biochem Mol Biol 62: 86-99. 34. Bian, G., Raikhel, A.S., Zhu, J. Characterization of a juvenile hormone-regulated chymotrypsin-like serine protease gene in Aedes aegypti mosquito. (2008) Insect Biochem Mol Biol 38(2): 190 200. 35. Coates, B.S., Sumerford, D.V., Hellmich, R.L., et al. Mining an Ostrinia nubilalis midgut expressed sequence tag (EST) library for candidate genes and single nucleotide polymorphisms (SNPs). (2008) Insect Mol Biol 17(6): 607 620. 36. Zhang, C., Zhou, D., Zheng, S., et al. A chymotrypsin- like serine protease cDNA involved in food protein digestion in the common cutworm, Spodoptera litura: Cloning, characterization, developmental and induced expression patterns, and localization. (2010) J Insect Physiol 56(7): 788 799. 37. Shi, M., Zhu, N., Yi, Y., et al. Four serine protease cDNAs from the midgut of Plutella xylostella and their proteinase activity are influenced by the endoparasitoid, cotesia vestalis. (2013) Arch Insect Biochem Physiol 83(2): 101 114. 38. Chen, H., Zhu, Y.C., Whitworth, R.J., et al. Serine and cysteine protease-like genes in the genome of a gall midge and their interactions with host plant genotypes. (2013) Insect Biochem Mol Biol 43(8): 701 711. 39. Chikate, Y.R., Tamhane, V.A., Joshi, R.S., et al. Differential protease activity augments polyphagy in Helicoverpa armigera. (2013) Insect Mol Biol 22(3): 258-272. 40. Ge, Z.Y., Wan, P.J., Li, G.Q., et al. Characterization of cysteine protease-like genes in the striped rice stem borer, Chilo suppressalis. (2014) Genome 57(2): 79 88. 41. Hou, M.Z., Shen, G.M., Wei, D., et al. Characterization of Bactrocera dorsalis serine proteases and evidence for their indirect role in insecticide tolerance. (2014) Int J Mol Sci 15(2): 3272 3286. 42. Nagasaki, H., Mochizuki, T., Kodama, Y., et al. DDBJ read annotation pipeline: A cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data. (2013) DNA Res 20(4): 383 390. 43. Conesa, A., G tz, S., Garc a-G mez, J.M., et al. Blast2GO: A universal tool for annotation, visualization and analysis in functional genomics research. (2005) Bioinformatics 21(18): 3674 3676. 44. Wheeler, D.L., Church, D.M., Federhen, S., et al. Database resources of the National Center for Biotechnology. (2003) Nucleic Acids Res 31(1): 28 33. 45. Jones, P., Binns, D., Chang, H.Y., et al. InterProScan 5: genome-scale protein function classification. (2014) Bioinformatics 30(9): 1236 1240. 46. Bendtsen, J.D., Nielsen, H., Heijne, G.V., et al. Improved prediction of signal peptides: SignalP 3.0. (2004) J Mol Biol 340(4): 783 795. 47. Artimo, P., Jonnalagedda, M., Arnold, K., et al. ExPASy: SIB bioinformatics resource portal. (2012) Nucleic Acids Res 40: W597 603. 48. Yaseen, A., Li, Y. Dinosolve: A protein disulfide bonding prediction server using context-based features to enhance prediction accuracy. (2013) BMC Bioinformatics 14: S9. 49. Rawlings, N.D., Waller, M., Barrett, A.J., et al. MEROPS: The database of proteolytic enzymes, their substrates and inhibitors. (2014) Nucleic Acids Res 42: D503-509. 50. Kearse, M., Moir, R., Wilson, A., et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. (2012) Bioinformatics 28(12): 1647 1649. 51. Untergasser, A., Cutcutache, I., Koressaar, T., et al. Primer3 new capabilities and interfaces. (2012) Nucleic Acids Res. 40(15): e115. 52. Livak, K.J., Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(Delta Delta C(T)) Method. (2001) Methods 25(4): 402 408. 53. Romualdi, C., Bortoluzzi, S., Danieli, G.A. Detecting differentially expressed genes in multiple tag sampling experiments: Comparative evaluation of statistical tests. (2001) Hum Mol Genet 10(19): 2133 2141. 54. Thompson, J.D., Gibson, T., Higgins, D.G. Multiple sequence alignment using ClustalW and ClustalX. (2002) Curr Protoc Bioinforma 2 3. 55. Guindon, S., Lethiec, F., Duroux, P., et al. PHYML Online A web server for fast maximum likelihood-based phylogenetic inference. (2005) Nucleic Acids Res 33: W557 559. 56. Erlandson, M.A., Hegedus, D.D., Baldwin, D., et al. Characterization of the Mamestra configurata (Lepidoptera: Noctuidae) larval midgut protease complement and adaptation to feeding on artificial diet, Brassica species, and protease inhibitor. (2010) Arch Insect Biochem Physiol 75(2): 70 91. 57. Rajagopal, R., Arora, N., Sivakumar, S., et al. Resistance of Helicoverpa armigera to Cry1Ac toxin from Bacillus thuringiensis is due to improper processing of the protoxin. (2009) Biochem J 419(2): 309 316. 58. Hegedus, D., Baldwin, D., O Grady, M., et al. Midgut proteases from Mamestra configurata (Lepidoptera: Noctuidae) larvae: characterization, cDNA cloning, and expressed sequence tag analysis. (2003) Arch Insect Biochem Physiol 53: 30 47. 59. Page, M.J., Di Cera, E. Serine peptidases: classification, structure and function. (2008) Cell Mol Life Sci 65(7-8): 1220 1236. 60. Ma, W., Tang, C., Lai, L. Specificity of trypsin and chymotrypsin: loop-motion- controlled dynamic correlation as a determinant. (2005) Biophys J 89(2): 1183 1193. 61. Lin, S.J., Dong, K.C., Eigenbrot, C., et al. Structures of Neutrophil Serine Protease 4 Reveal an Unusual Mechanism of Substrate Recognition by a Trypsin-Fold Protease. (2014) Structure 22(9): 1333 1340. 62. Liu, Y., Sui, Y.P., Wang J.X., et al. Characterization of the trypsin-like protease (Ha-TLP2) constitutively expressed in the integument of the cotton bollworm, Helicoverpa armigera. (2009)Arch Insect Biochem Physiol 72(2): 74 87. 63. Oppert, B., Dowd, S.E., Bouffard, P., et al. Transcriptome profiling of the intoxication response of Tenebrio molitor larvae to Bacillus thuringiensis Cry3Aa protoxin. (2012) PloS One 7(4): e34624.