This is the first study to report a high-throughput approach integrating gene expression data from Spodoptera frugiperda guts and their associated metatranscriptomes. Our datasets provide information on the potential effects of environmental conditions on the expression profile of S. frugiperda larval guts, their associated metatranscriptome, and putative interactions between them.Fil: Mccarthy, Cristina Beryl. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cabrera, Natalia Alina. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; ArgentinaFil: Virla, Eduardo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucuman. Planta Piloto de Procesos Industriales Microbiologicos; Argentin

Cabrera, Natalia Alina

Mccarthy, Cristina Beryl

Virla, Eduardo Gabriel

Genome Announcements

English

PubMed

LAReferencia - Red Federada de Repositorios Institucionales de Publicaciones Científicas Latinoamericanas

Metatranscriptomic Analysis of Larval Guts from Field-Collected andLaboratory-Reared Spodoptera frugiperda from the South AmericanSubtropical RegionChristina B. McCarthy,a,b Natalia A. Cabrera,a,b Eduardo G. Virlac,dCentro Regional de Estudios Genómicos, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentinaa; Departamento de Informáticay Tecnología, Escuela de Ciencias Agrarias, Naturales y Ambientales, Universidad Nacional del Noroeste de la Provincia de Buenos Aires, Pergamino, Buenos Aires,Argentinab; PROIMI-Biotecnologia, División Control Biológico, San Miguel de Tucumán, Tucumán, Argentinac; Instituto de Entomología, Fundación Miguel Lillo, SanMiguel de Tucumán, Tucumán, ArgentinadThis is the first study to report a high-throughput approach integrating gene expression data from Spodoptera frugiperda gutsand their associated metatranscriptomes. Our datasets provide information on the potential effects of environmental conditionson the expression profile of S. frugiperda larval guts, their associated metatranscriptome, and putative interactions betweenthem.Received 7 June 2015 Accepted 12 June 2015 Published 16 July 2015Citation McCarthy CB, Cabrera NA, Virla EG. 2015. Metatranscriptomic analysis of larval guts from field-collected and laboratory-reared Spodoptera frugiperda from the SouthAmerican subtropical region. Genome Announc 3(4):e00777-15. doi:10.1128/genomeA.00777-15.Copyright © 2015 McCarthy et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license.Address correspondence to Christina B. McCarthy, mccarthychristina@gmail.com.Spodoptera frugiperda is a noctuid moth that devastates variouscrops including corn, rice, and cotton and is found in most ofthe American continent (1). Even though transgenic crops thatproduce insecticidal proteins from Bacillus thuringiensis are cur-rently the most successful biotechnological pest management ap-plication (2), S. frugiperda has developed field-evolved resistanceto Bt maize (3). In this sense, gut microbiota play important rolesin the growth and development of insects, and metatranscrip-tomic analyses of insect hosts represent an invaluable tool whichcould lead to new targets for pest control (4, 5). Nevertheless, theassessment of metabolically active components in the gut micro-biota (6) is surprisingly scarce. Furthermore, comprehensive anal-yses combining host gene expression data with information fromassociated microbiota (7), are even more rare. The purpose of thisstudy was to integrate gene expression data from S. frugiperda gutsand their associated metatranscriptomes, under natural and con-trolled conditions. For this, four S. frugiperda samples from theprovince of Tucumán (Argentina; subtropical region) were ana-lyzed. Specimens were obtained from different environments, al-titudes and food sources, namely, (1) a transgenic maize (Zeamays) field at 495 meters above sea level (MASL) where insecti-cides and fertilizers were applied (named Sf_MM; 26°49=50S,65°16=59.4W), (2) Sorghum halepense at 495 MASL (Sf_MS;26°49=50S, 65°16=59.4W), (3) a maize field at 2,283 MASL whereno insecticides or fertilizers were used (Sf_TV; 26°55=40.75S,65°45=19.90W), and (4) a colony established from larvae origi-nally collected from the same transgenic maize field as Sf_MM,reared for 9 generations under controlled conditions on an artifi-cial diet adapted from reference (8), without the addition of anti-biotics (Sf_LR). For all samples, total RNA extracted from fifthinstar larval guts (two digestive tracts per sample), was submittedto a one-step reverse transcription and PCR sequence-independent amplification procedure, modified from reference(9), as described previously (7, 10). High-throughput pyrose-quencing of the samples was performed using a Roche GS FLX(Macrogen, Inc., Republic of Korea), yielding ~1 Gb of metatran-scriptomic reads with lengths of 50 to 1,600 base nucleotides (nt)(652 nt average).Raw sequence reads were trimmed to remove nucleotides de-rived from the amplification primers using a custom application(7, 10). The nonredundant protein sequence NCBI database (DB:nr) was downloaded locally. Rapsearch2 (11) was used for theprotein homology search against DB:nr, using the trimmed singletreads, and the taxonomic and functional content of the datasetswas analyzed with MEGAN (12, 13). An average of ~97% of thetranscripts showed homology to eukaryota, as expected (less than1% corresponded to nonlepidopteran transcripts, includingfungi, kinetoplastida, and viridiplantae, among others), 0.28% to0.07% to bacteria, 0.003% to 0.001% to archaea, and 0.03% to 0%to viruses. The highest number of bacterial transcripts wasfound in Sf_MS, whereas archaeal and viral transcripts weremore abundant in Sf_LR. Statistical analysis (Fisher’s exact test[14], P  0.05) mostly indicated significant differences be-tween samples.This is the first study to report S. frugiperda metatranscrip-tomic datasets, which provide information on the potential effectsof food source, insecticides, fertilizers, and environmental condi-tions on the expression profile of S. frugiperda larval guts, theirassociated metatranscriptome, and putative interactions betweenthem.Nucleotide sequence accession numbers. Nucleotide se-quences were submitted to the NCBI Sequence Read Archive(SRA) under accession numbers SRX1000994, SRX1000995, andSRX1000996 (field-collected S. frugiperda larval guts) andSRX684522 (laboratory-reared S. frugiperda larval guts).crossmarkGenome AnnouncementsJuly/August 2015 Volume 3 Issue 4 e00777-15 genomea.asm.org 1 on July 21, 2015 by guesthttp://genomea.asm.org/Downloaded from ACKNOWLEDGMENTSThis research was supported by Agencia Nacional de Promoción Cientí-fica y Tecnológica (PICT PRH 112), Consejo Nacional de InvestigacionesCientíficas y Técnicas (CONICET) (PIP 0294), and Universidad Nacionaldel Noroeste de la Provincia de Buenos Aires (UNNOBA) (Exp. 1388/2010 and Exp. 2581/2012) grants to C.B.M.We gratefully acknowledge the Faculty of Agronomy and Zootechnics(Tucumán National University, Finca El Manantial, Lules Department,Tucumán) and Ing. Zoot. Carlos Marino (Azucarera Justiniano Frías S.A.,Las Carreras, Valle de Tafí, Tucumán) for their support and for allowingus to collect S. frugiperda larvae from their fields.C.B.M. and E.G.V. are members of the CONICET research career.N.A.C. is the recipient of an UNNOBA fellowship.REFERENCES1. Pogue M. 2002. A world revision of the genus Spodoptera (Guenée)Lepidoptera: Noctuidae. American Entomological Society, Philadelphia, PA.2. Sanchis V. 2011. From microbial sprays to insect-resistant transgenicplants: history of the biospesticide Bacillus thuringiensis. A review. AgronSustain Dev 31:217–231. http://dx.doi.org/10.1051/agro/2010027.3. Storer NP, Babcock JM, Schlenz M, Meade T, Thompson GD, Bing JW,Huckaba RM. 2010. Discovery and characterization of field resistance toBt maize: Spodoptera frugiperda (Lepidoptera: Noctuidae) in Puerto Rico. JEcon Entomol 103:1031–1038.4. Morrison M, Pope PB, Denman SE, McSweeney CS. 2009. Plant biomassdegradation by gut microbiomes: more of the same or something new?Curr Opin Biotechnol 20:358 –363. http://dx.doi.org/10.1016/ j.cop-bio.2009.05.004.5. Dillon RJ, Dillon VM. 2004. The gut bacteria of insects: nonpathogenicinteractions. Annu Rev Entomol 49:71–92. http://dx.doi.org/10.1146/ an-nurev.ento.49.061802.123416.6. Shao Y, Arias-Cordero E, Guo H, Bartram S, Boland W. 2014. In vivopyro-SIP assessing active gut microbiota of the cotton leafworm,Spodoptera littoralis. PLoS One 9:e85948. http://dx.doi.org/10.1371/ jour-nal.pone.0085948.7. McCarthy CB, Santini MS, Pimenta PF, Diambra LA. 2013. First com-parative transcriptomic analysis of wild adult male and female Lutzomyialongipalpis, vector of visceral leishmaniasis. PLoS One 8:e58645. http://dx.doi.org/10.1371/journal.pone.0058645.8. Murúa G, Virla EG. 2003. Evaluación de cuatro dietas artificiales para lacria de Spodoptera frugiperda (Lep.: Noctuidae) destinada a mantener po-blaciones experimentales de himenópteros parasitoides. Bol San Veg Pla-gas 29:43–51.9. Sambade A, Martín S, Olmos A, García ML, Cambra M, Grau O, GuerriJ, Moreno P. 2000. A fast one-step reverse transcription and polymerasechain reaction (RT-PCR) amplification procedure providing highly spe-cific complementary DNA from plant virus RNA. J Virol Methods 87:25–28. http://dx.doi.org/10.1016/S0166-0934(00)00145-2.10. McCarthy CB, Diambra LA, Rivera Pomar RV. 2011. Metagenomicanalysis of taxa associated with Lutzomyia longipalpis, vector of visceralleishmaniasis, using an unbiased high-throughput approach. PLOS NeglTrop Dis 5:e1304. http://dx.doi.org/10.1371/journal.pntd.0001304.11. Zhao Y, Tang H, Ye Y. 2012. RAPSearch2: a fast and memory-efficientprotein similarity search tool for next-generation sequencing data. Bioin-formatics 28:125–126. http://dx.doi.org/10.1093/bioinformatics/btr595.12. Huson DH, Auch AF, Qi J, Schuster SC. 2007. MEGAN analysis ofmetagenomic data. Genome Res 17:377–386. http://dx.doi.org/10.1101/gr.5969107.13. Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC. 2011.Integrative analysis of environmental sequences using MEGAN4. GenomeRes 21:1552–1560. http://dx.doi.org/10.1101/gr.120618.111.14. Fisher R. 1970. Statistical methods for research workers. 14th ed. Hafner,New York, NY.McCarthy et al.Genome Announcements2 genomea.asm.org July/August 2015 Volume 3 Issue 4 e00777-15 on July 21, 2015 by guesthttp://genomea.asm.org/Downloaded from 

Metatranscriptomic analysis of larvae guts from field-collected and laboratory-reared Spodoptera frugiperda from the South American subtropical region

This is the first study to report a high-throughput approach integrating gene expression data from Spodoptera frugiperda guts and their associated metatranscriptomes. Our datasets provide information on the potential effects of environmental conditions on the expression profile of S. frugiperda larval guts, their associated metatranscriptome, and putative interactions between them.Centro Regional de Estudios Genómico

McCarthy, Christina Beryl

Cabrera, Natalia A.

Metatranscriptomic Analysis of Larval Guts from Field-Collected andLaboratory-Reared Spodoptera frugiperda from the South AmericanSubtropical RegionChristina B. McCarthy,a,b Natalia A. Cabrera,a,b Eduardo G. Virlac,dCentro Regional de Estudios Genómicos, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentinaa; Departamento de Informáticay Tecnología, Escuela de Ciencias Agrarias, Naturales y Ambientales, Universidad Nacional del Noroeste de la Provincia de Buenos Aires, Pergamino, Buenos Aires,Argentinab; PROIMI-Biotecnologia, División Control Biológico, San Miguel de Tucumán, Tucumán, Argentinac; Instituto de Entomología, Fundación Miguel Lillo, SanMiguel de Tucumán, Tucumán, ArgentinadThis is the first study to report a high-throughput approach integrating gene expression data from Spodoptera frugiperda gutsand their associated metatranscriptomes. Our datasets provide information on the potential effects of environmental conditionson the expression profile of S. frugiperda larval guts, their associated metatranscriptome, and putative interactions betweenthem.Received 7 June 2015 Accepted 12 June 2015 Published 16 July 2015Citation McCarthy CB, Cabrera NA, Virla EG. 2015. Metatranscriptomic analysis of larval guts from field-collected and laboratory-reared Spodoptera frugiperda from the SouthAmerican subtropical region. Genome Announc 3(4):e00777-15. doi:10.1128/genomeA.00777-15.Copyright © 2015 McCarthy et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license.Address correspondence to Christina B. McCarthy, mccarthychristina@gmail.com.Spodoptera frugiperda is a noctuid moth that devastates variouscrops including corn, rice, and cotton and is found in most ofthe American continent (1). Even though transgenic crops thatproduce insecticidal proteins from Bacillus thuringiensis are cur-rently the most successful biotechnological pest management ap-plication (2), S. frugiperda has developed field-evolved resistanceto Bt maize (3). In this sense, gut microbiota play important rolesin the growth and development of insects, and metatranscrip-tomic analyses of insect hosts represent an invaluable tool whichcould lead to new targets for pest control (4, 5). Nevertheless, theassessment of metabolically active components in the gut micro-biota (6) is surprisingly scarce. Furthermore, comprehensive anal-yses combining host gene expression data with information fromassociated microbiota (7), are even more rare. The purpose of thisstudy was to integrate gene expression data from S. frugiperda gutsand their associated metatranscriptomes, under natural and con-trolled conditions. For this, four S. frugiperda samples from theprovince of Tucumán (Argentina; subtropical region) were ana-lyzed. Specimens were obtained from different environments, al-titudes and food sources, namely, (1) a transgenic maize (Zeamays) field at 495 meters above sea level (MASL) where insecti-cides and fertilizers were applied (named Sf_MM; 26°49=500S,65°16=59.40W), (2) Sorghum halepense at 495 MASL (Sf_MS;26°49=500S, 65°16=59.40W), (3) a maize field at 2,283 MASL whereno insecticides or fertilizers were used (Sf_TV; 26°55=40.750S,65°45=19.900W), and (4) a colony established from larvae origi-nally collected from the same transgenic maize field as Sf_MM,reared for 9 generations under controlled conditions on an artifi-cial diet adapted from reference (8), without the addition of anti-biotics (Sf_LR). For all samples, total RNA extracted from fifthinstar larval guts (two digestive tracts per sample), was submittedto a one-step reverse transcription and PCR sequence-independent amplification procedure, modified from reference(9), as described previously (7, 10). High-throughput pyrose-quencing of the samples was performed using a Roche GS FLX(Macrogen, Inc., Republic of Korea), yielding ~1 Gb of metatran-scriptomic reads with lengths of 50 to 1,600 base nucleotides (nt)(652 nt average).Raw sequence reads were trimmed to remove nucleotides de-rived from the amplification primers using a custom application(7, 10). The nonredundant protein sequence NCBI database (DB:nr) was downloaded locally. Rapsearch2 (11) was used for theprotein homology search against DB:nr, using the trimmed singletreads, and the taxonomic and functional content of the datasetswas analyzed with MEGAN (12, 13). An average of ~97% of thetranscripts showed homology to eukaryota, as expected (less than1% corresponded to nonlepidopteran transcripts, includingfungi, kinetoplastida, and viridiplantae, among others), 0.28% to0.07% to bacteria, 0.003% to 0.001% to archaea, and 0.03% to 0%to viruses. The highest number of bacterial transcripts wasfound in Sf_MS, whereas archaeal and viral transcripts weremore abundant in Sf_LR. Statistical analysis (Fisher’s exact test[14], P , 0.05) mostly indicated significant differences be-tween samples.This is the first study to report S. frugiperda metatranscrip-tomic datasets, which provide information on the potential effectsof food source, insecticides, fertilizers, and environmental condi-tions on the expression profile of S. frugiperda larval guts, theirassociated metatranscriptome, and putative interactions betweenthem.Nucleotide sequence accession numbers. Nucleotide se-quences were submitted to the NCBI Sequence Read Archive(SRA) under accession numbers SRX1000994, SRX1000995, andSRX1000996 (field-collected S. frugiperda larval guts) andSRX684522 (laboratory-reared S. frugiperda larval guts).crossmarkGenome AnnouncementsJuly/August 2015 Volume 3 Issue 4 e00777-15 genomea.asm.org 1 on September 4, 2019 by guesthttp://mra.asm.org/Downloaded from ACKNOWLEDGMENTSThis research was supported by Agencia Nacional de Promoción Cientí-fica y Tecnológica (PICT PRH 112), Consejo Nacional de InvestigacionesCientíficas y Técnicas (CONICET) (PIP 0294), and Universidad Nacionaldel Noroeste de la Provincia de Buenos Aires (UNNOBA) (Exp. 1388/2010 and Exp. 2581/2012) grants to C.B.M.We gratefully acknowledge the Faculty of Agronomy and Zootechnics(Tucumán National University, Finca El Manantial, Lules Department,Tucumán) and Ing. Zoot. Carlos Marino (Azucarera Justiniano Frías S.A.,Las Carreras, Valle de Tafí, Tucumán) for their support and for allowingus to collect S. frugiperda larvae from their fields.C.B.M. and E.G.V. are members of the CONICET research career.N.A.C. is the recipient of an UNNOBA fellowship.REFERENCES1. Pogue M. 2002. A world revision of the genus Spodoptera (Guenée)Lepidoptera: Noctuidae. American Entomological Society, Philadelphia, PA.2. Sanchis V. 2011. From microbial sprays to insect-resistant transgenicplants: history of the biospesticide Bacillus thuringiensis. A review. AgronSustain Dev 31:217–231. http://dx.doi.org/10.1051/agro/2010027.3. Storer NP, Babcock JM, Schlenz M, Meade T, Thompson GD, Bing JW,Huckaba RM. 2010. Discovery and characterization of field resistance toBt maize: Spodoptera frugiperda (Lepidoptera: Noctuidae) in Puerto Rico. JEcon Entomol 103:1031–1038.4. Morrison M, Pope PB, Denman SE, McSweeney CS. 2009. Plant biomassdegradation by gut microbiomes: more of the same or something new?Curr Opin Biotechnol 20:358 –363. http://dx.doi.org/10.1016/ j.cop-bio.2009.05.004.5. Dillon RJ, Dillon VM. 2004. The gut bacteria of insects: nonpathogenicinteractions. Annu Rev Entomol 49:71–92. http://dx.doi.org/10.1146/ an-nurev.ento.49.061802.123416.6. Shao Y, Arias-Cordero E, Guo H, Bartram S, Boland W. 2014. In vivopyro-SIP assessing active gut microbiota of the cotton leafworm,Spodoptera littoralis. PLoS One 9:e85948. http://dx.doi.org/10.1371/ jour-nal.pone.0085948.7. McCarthy CB, Santini MS, Pimenta PF, Diambra LA. 2013. First com-parative transcriptomic analysis of wild adult male and female Lutzomyialongipalpis, vector of visceral leishmaniasis. PLoS One 8:e58645. http://dx.doi.org/10.1371/journal.pone.0058645.8. Murúa G, Virla EG. 2003. Evaluación de cuatro dietas artificiales para lacria de Spodoptera frugiperda (Lep.: Noctuidae) destinada a mantener po-blaciones experimentales de himenópteros parasitoides. Bol San Veg Pla-gas 29:43–51.9. Sambade A, Martín S, Olmos A, García ML, Cambra M, Grau O, GuerriJ, Moreno P. 2000. A fast one-step reverse transcription and polymerasechain reaction (RT-PCR) amplification procedure providing highly spe-cific complementary DNA from plant virus RNA. J Virol Methods 87:25–28. http://dx.doi.org/10.1016/S0166-0934(00)00145-2.10. McCarthy CB, Diambra LA, Rivera Pomar RV. 2011. Metagenomicanalysis of taxa associated with Lutzomyia longipalpis, vector of visceralleishmaniasis, using an unbiased high-throughput approach. PLOS NeglTrop Dis 5:e1304. http://dx.doi.org/10.1371/journal.pntd.0001304.11. Zhao Y, Tang H, Ye Y. 2012. RAPSearch2: a fast and memory-efficientprotein similarity search tool for next-generation sequencing data. Bioin-formatics 28:125–126. http://dx.doi.org/10.1093/bioinformatics/btr595.12. Huson DH, Auch AF, Qi J, Schuster SC. 2007. MEGAN analysis ofmetagenomic data. Genome Res 17:377–386. http://dx.doi.org/10.1101/gr.5969107.13. Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC. 2011.Integrative analysis of environmental sequences using MEGAN4. GenomeRes 21:1552–1560. http://dx.doi.org/10.1101/gr.120618.111.14. Fisher R. 1970. Statistical methods for research workers. 14th ed. Hafner,New York, NY.McCarthy et al.Genome Announcements2 genomea.asm.org July/August 2015 Volume 3 Issue 4 e00777-15 on September 4, 2019 by guesthttp://mra.asm.org/Downloaded from 

Metatranscriptomic analysis of larval guts from field-collected and laboratory-reared Spodoptera frugiperda from the South American subtropical region

El Servicio de Difusión de la Creación Intelectual

Metatranscriptomic Analysis of Larval Guts from Field-Collected and
Laboratory-Reared Spodoptera frugiperda from the South American
Subtropical Region
Christina B. McCarthy,a,b Natalia A. Cabrera,a,b Eduardo G. Virlac,d
Centro Regional de Estudios Genómicos, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentinaa; Departamento de Informática
y Tecnología, Escuela de Ciencias Agrarias, Naturales y Ambientales, Universidad Nacional del Noroeste de la Provincia de Buenos Aires, Pergamino, Buenos Aires,
Argentinab; PROIMI-Biotecnologia, División Control Biológico, San Miguel de Tucumán, Tucumán, Argentinac; Instituto de Entomología, Fundación Miguel Lillo, San
Miguel de Tucumán, Tucumán, Argentinad
This is the first study to report a high-throughput approach integrating gene expression data from Spodoptera frugiperda guts
and their associated metatranscriptomes. Our datasets provide information on the potential effects of environmental conditions
on the expression profile of S. frugiperda larval guts, their associated metatranscriptome, and putative interactions between
them.
Received 7 June 2015 Accepted 12 June 2015 Published 16 July 2015
CitationMcCarthy CB, Cabrera NA, Virla EG. 2015. Metatranscriptomic analysis of larval guts from field-collected and laboratory-reared Spodoptera frugiperda from the South
American subtropical region. Genome Announc 3(4):e00777-15. doi:10.1128/genomeA.00777-15.
Copyright © 2015 McCarthy et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license.
Address correspondence to Christina B. McCarthy, mccarthychristina@gmail.com.
Spodoptera frugiperda is a noctuid moth that devastates variouscrops including corn, rice, and cotton and is found in most of
the American continent (1). Even though transgenic crops that
produce insecticidal proteins from Bacillus thuringiensis are cur-
rently the most successful biotechnological pest management ap-
plication (2), S. frugiperda has developed field-evolved resistance
to Bt maize (3). In this sense, gut microbiota play important roles
in the growth and development of insects, and metatranscrip-
tomic analyses of insect hosts represent an invaluable tool which
could lead to new targets for pest control (4, 5). Nevertheless, the
assessment of metabolically active components in the gut micro-
biota (6) is surprisingly scarce. Furthermore, comprehensive anal-
yses combining host gene expression data with information from
associatedmicrobiota (7), are evenmore rare. The purpose of this
studywas to integrate gene expression data from S. frugiperda guts
and their associated metatranscriptomes, under natural and con-
trolled conditions. For this, four S. frugiperda samples from the
province of Tucumán (Argentina; subtropical region) were ana-
lyzed. Specimens were obtained from different environments, al-
titudes and food sources, namely, (1) a transgenic maize (Zea
mays) field at 495 meters above sea level (MASL) where insecti-
cides and fertilizers were applied (named Sf_MM; 26°49=500S,
65°16=59.40W), (2) Sorghum halepense at 495 MASL (Sf_MS;
26°49=500S, 65°16=59.40W), (3) amaize field at 2,283MASLwhere
no insecticides or fertilizers were used (Sf_TV; 26°55=40.750S,
65°45=19.900W), and (4) a colony established from larvae origi-
nally collected from the same transgenic maize field as Sf_MM,
reared for 9 generations under controlled conditions on an artifi-
cial diet adapted from reference (8), without the addition of anti-
biotics (Sf_LR). For all samples, total RNA extracted from fifth
instar larval guts (two digestive tracts per sample), was submitted
to a one-step reverse transcription and PCR sequence-
independent amplification procedure, modified from reference
(9), as described previously (7, 10). High-throughput pyrose-
quencing of the samples was performed using a Roche GS FLX
(Macrogen, Inc., Republic of Korea), yielding ~1 Gb of metatran-
scriptomic reads with lengths of 50 to 1,600 base nucleotides (nt)
(652 nt average).
Raw sequence reads were trimmed to remove nucleotides de-
rived from the amplification primers using a custom application
(7, 10). The nonredundant protein sequence NCBI database (DB:
nr) was downloaded locally. Rapsearch2 (11) was used for the
protein homology search againstDB:nr, using the trimmed singlet
reads, and the taxonomic and functional content of the datasets
was analyzed with MEGAN (12, 13). An average of ~97% of the
transcripts showed homology to eukaryota, as expected (less than
1% corresponded to nonlepidopteran transcripts, including
fungi, kinetoplastida, and viridiplantae, among others), 0.28% to
0.07% to bacteria, 0.003% to 0.001% to archaea, and 0.03% to 0%
to viruses. The highest number of bacterial transcripts was
found in Sf_MS, whereas archaeal and viral transcripts were
more abundant in Sf_LR. Statistical analysis (Fisher’s exact test
[14], P , 0.05) mostly indicated significant differences be-
tween samples.
This is the first study to report S. frugiperda metatranscrip-
tomic datasets, which provide information on the potential effects
of food source, insecticides, fertilizers, and environmental condi-
tions on the expression profile of S. frugiperda larval guts, their
associated metatranscriptome, and putative interactions between
them.
Nucleotide sequence accession numbers. Nucleotide se-
quences were submitted to the NCBI Sequence Read Archive
(SRA) under accession numbers SRX1000994, SRX1000995, and
SRX1000996 (field-collected S. frugiperda larval guts) and
SRX684522 (laboratory-reared S. frugiperda larval guts).
crossmark
Genome AnnouncementsJuly/August 2015 Volume 3 Issue 4 e00777-15 genomea.asm.org 1
 on Septem
ber 4, 2019 by guest
http://m
ra.asm
.org/
D
ow
nloaded from
 
ACKNOWLEDGMENTS
This research was supported by Agencia Nacional de Promoción Cientí-
fica y Tecnológica (PICT PRH 112), Consejo Nacional de Investigaciones
Científicas y Técnicas (CONICET) (PIP 0294), andUniversidadNacional
del Noroeste de la Provincia de Buenos Aires (UNNOBA) (Exp. 1388/
2010 and Exp. 2581/2012) grants to C.B.M.
We gratefully acknowledge the Faculty of Agronomy and Zootechnics
(Tucumán National University, Finca El Manantial, Lules Department,
Tucumán) and Ing. Zoot. CarlosMarino (Azucarera Justiniano Frías S.A.,
Las Carreras, Valle de Tafí, Tucumán) for their support and for allowing
us to collect S. frugiperda larvae from their fields.
C.B.M. and E.G.V. are members of the CONICET research career.
N.A.C. is the recipient of an UNNOBA fellowship.
REFERENCES
1. Pogue M. 2002. A world revision of the genus Spodoptera (Guenée)
Lepidoptera: Noctuidae. American Entomological Society, Philadelphia, PA.
2. Sanchis V. 2011. From microbial sprays to insect-resistant transgenic
plants: history of the biospesticide Bacillus thuringiensis. A review. Agron
Sustain Dev 31:217–231. http://dx.doi.org/10.1051/agro/2010027.
3. Storer NP, Babcock JM, Schlenz M, Meade T, Thompson GD, Bing JW,
Huckaba RM. 2010. Discovery and characterization of field resistance to
Bt maize: Spodoptera frugiperda (Lepidoptera: Noctuidae) in Puerto Rico. J
Econ Entomol 103:1031–1038.
4. MorrisonM, Pope PB, Denman SE, McSweeney CS. 2009. Plant biomass
degradation by gut microbiomes: more of the same or something new?
Curr Opin Biotechnol 20:358–363. http://dx.doi.org/10.1016/ j.cop-
bio.2009.05.004.
5. Dillon RJ, Dillon VM. 2004. The gut bacteria of insects: nonpathogenic
interactions. Annu Rev Entomol 49:71–92. http://dx.doi.org/10.1146/ an-
nurev.ento.49.061802.123416.
6. Shao Y, Arias-Cordero E, Guo H, Bartram S, Boland W. 2014. In vivo
pyro-SIP assessing active gut microbiota of the cotton leafworm,
Spodoptera littoralis. PLoS One 9:e85948. http://dx.doi.org/10.1371/ jour-
nal.pone.0085948.
7. McCarthy CB, Santini MS, Pimenta PF, Diambra LA. 2013. First com-
parative transcriptomic analysis of wild adult male and female Lutzomyia
longipalpis, vector of visceral leishmaniasis. PLoS One 8:e58645. http://
dx.doi.org/10.1371/journal.pone.0058645.
8. Murúa G, Virla EG. 2003. Evaluación de cuatro dietas artificiales para la
cria de Spodoptera frugiperda (Lep.: Noctuidae) destinada a mantener po-
blaciones experimentales de himenópteros parasitoides. Bol San Veg Pla-
gas 29:43–51.
9. Sambade A, Martín S, Olmos A, García ML, Cambra M, Grau O, Guerri
J, Moreno P. 2000. A fast one-step reverse transcription and polymerase
chain reaction (RT-PCR) amplification procedure providing highly spe-
cific complementary DNA from plant virus RNA. J Virol Methods 87:
25–28. http://dx.doi.org/10.1016/S0166-0934(00)00145-2.
10. McCarthy CB, Diambra LA, Rivera Pomar RV. 2011. Metagenomic
analysis of taxa associated with Lutzomyia longipalpis, vector of visceral
leishmaniasis, using an unbiased high-throughput approach. PLOS Negl
Trop Dis 5:e1304. http://dx.doi.org/10.1371/journal.pntd.0001304.
11. Zhao Y, Tang H, Ye Y. 2012. RAPSearch2: a fast and memory-efficient
protein similarity search tool for next-generation sequencing data. Bioin-
formatics 28:125–126. http://dx.doi.org/10.1093/bioinformatics/btr595.
12. Huson DH, Auch AF, Qi J, Schuster SC. 2007. MEGAN analysis of
metagenomic data. Genome Res 17:377–386. http://dx.doi.org/10.1101/
gr.5969107.
13. Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC. 2011.
Integrative analysis of environmental sequences usingMEGAN4.Genome
Res 21:1552–1560. http://dx.doi.org/10.1101/gr.120618.111.
14. Fisher R. 1970. Statistical methods for research workers. 14th ed. Hafner,
New York, NY.
McCarthy et al.
Genome Announcements2 genomea.asm.org July/August 2015 Volume 3 Issue 4 e00777-15
 on Septem
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ABSTRACT
          
            This is the first study to report a high-throughput approach integrating gene expression data from
            Spodoptera frugiperda
            guts and their associated metatranscriptomes. Our datasets provide information on the potential effects of environmental conditions on the expression profile of
            S. frugiperda
            larval guts, their associated metatranscriptome, and putative interactions between them.
          </jats:p

Christina B. McCarthy

Natalia A. Cabrera

Eduardo G. Virla

Crossref

Metatranscriptomic Analysis of Larval Guts from Field-Collected and Laboratory-Reared Spodoptera frugiperda from the South American Subtropical Region

CONICET Digital

Metatranscriptomic Analysis of Larval Guts from Field-Collected andLaboratory-Reared Spodoptera frugiperda from the South AmericanSubtropical RegionChristina B. McCarthy,a,b Natalia A. Cabrera,a,b Eduardo G. Virlac,dCentro Regional de Estudios Genómicos, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentinaa; Departamento de Informáticay Tecnología, Escuela de Ciencias Agrarias, Naturales y Ambientales, Universidad Nacional del Noroeste de la Provincia de Buenos Aires, Pergamino, Buenos Aires,Argentinab; PROIMI-Biotecnologia, División Control Biológico, San Miguel de Tucumán, Tucumán, Argentinac; Instituto de Entomología, Fundación Miguel Lillo, SanMiguel de Tucumán, Tucumán, ArgentinadThis is the first study to report a high-throughput approach integrating gene expression data from Spodoptera frugiperda gutsand their associated metatranscriptomes. Our datasets provide information on the potential effects of environmental conditionson the expression profile of S. frugiperda larval guts, their associated metatranscriptome, and putative interactions betweenthem.Received 7 June 2015 Accepted 12 June 2015 Published 16 July 2015CitationMcCarthy CB, Cabrera NA, Virla EG. 2015. Metatranscriptomic analysis of larval guts from field-collected and laboratory-reared Spodoptera frugiperda from the SouthAmerican subtropical region. Genome Announc 3(4):e00777-15. doi:10.1128/genomeA.00777-15.Copyright © 2015 McCarthy et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license.Address correspondence to Christina B. McCarthy, mccarthychristina@gmail.com.Spodoptera frugiperda is a noctuid moth that devastates variouscrops including corn, rice, and cotton and is found in most ofthe American continent (1). Even though transgenic crops thatproduce insecticidal proteins from Bacillus thuringiensis are cur-rently the most successful biotechnological pest management ap-plication (2), S. frugiperda has developed field-evolved resistanceto Bt maize (3). In this sense, gut microbiota play important rolesin the growth and development of insects, and metatranscrip-tomic analyses of insect hosts represent an invaluable tool whichcould lead to new targets for pest control (4, 5). Nevertheless, theassessment of metabolically active components in the gut micro-biota (6) is surprisingly scarce. Furthermore, comprehensive anal-yses combining host gene expression data with information fromassociatedmicrobiota (7), are evenmore rare. The purpose of thisstudywas to integrate gene expression data from S. frugiperda gutsand their associated metatranscriptomes, under natural and con-trolled conditions. For this, four S. frugiperda samples from theprovince of Tucumán (Argentina; subtropical region) were ana-lyzed. Specimens were obtained from different environments, al-titudes and food sources, namely, (1) a transgenic maize (Zeamays) field at 495 meters above sea level (MASL) where insecti-cides and fertilizers were applied (named Sf_MM; 26°49=50S,65°16=59.4W), (2) Sorghum halepense at 495 MASL (Sf_MS;26°49=50S, 65°16=59.4W), (3) amaize field at 2,283MASLwhereno insecticides or fertilizers were used (Sf_TV; 26°55=40.75S,65°45=19.90W), and (4) a colony established from larvae origi-nally collected from the same transgenic maize field as Sf_MM,reared for 9 generations under controlled conditions on an artifi-cial diet adapted from reference (8), without the addition of anti-biotics (Sf_LR). For all samples, total RNA extracted from fifthinstar larval guts (two digestive tracts per sample), was submittedto a one-step reverse transcription and PCR sequence-independent amplification procedure, modified from reference(9), as described previously (7, 10). High-throughput pyrose-quencing of the samples was performed using a Roche GS FLX(Macrogen, Inc., Republic of Korea), yielding ~1 Gb of metatran-scriptomic reads with lengths of 50 to 1,600 base nucleotides (nt)(652 nt average).Raw sequence reads were trimmed to remove nucleotides de-rived from the amplification primers using a custom application(7, 10). The nonredundant protein sequence NCBI database (DB:nr) was downloaded locally. Rapsearch2 (11) was used for theprotein homology search againstDB:nr, using the trimmed singletreads, and the taxonomic and functional content of the datasetswas analyzed with MEGAN (12, 13). An average of ~97% of thetranscripts showed homology to eukaryota, as expected (less than1% corresponded to nonlepidopteran transcripts, includingfungi, kinetoplastida, and viridiplantae, among others), 0.28% to0.07% to bacteria, 0.003% to 0.001% to archaea, and 0.03% to 0%to viruses. The highest number of bacterial transcripts wasfound in Sf_MS, whereas archaeal and viral transcripts weremore abundant in Sf_LR. Statistical analysis (Fisher’s exact test[14], P  0.05) mostly indicated significant differences be-tween samples.This is the first study to report S. frugiperda metatranscrip-tomic datasets, which provide information on the potential effectsof food source, insecticides, fertilizers, and environmental condi-tions on the expression profile of S. frugiperda larval guts, theirassociated metatranscriptome, and putative interactions betweenthem.Nucleotide sequence accession numbers. Nucleotide se-quences were submitted to the NCBI Sequence Read Archive(SRA) under accession numbers SRX1000994, SRX1000995, andSRX1000996 (field-collected S. frugiperda larval guts) andSRX684522 (laboratory-reared S. frugiperda larval guts).crossmarkGenome AnnouncementsJuly/August 2015 Volume 3 Issue 4 e00777-15 genomea.asm.org 1 on July 21, 2015 by guesthttp://genomea.asm.org/Downloaded from ACKNOWLEDGMENTSThis research was supported by Agencia Nacional de Promoción Cientí-fica y Tecnológica (PICT PRH 112), Consejo Nacional de InvestigacionesCientíficas y Técnicas (CONICET) (PIP 0294), andUniversidadNacionaldel Noroeste de la Provincia de Buenos Aires (UNNOBA) (Exp. 1388/2010 and Exp. 2581/2012) grants to C.B.M.We gratefully acknowledge the Faculty of Agronomy and Zootechnics(Tucumán National University, Finca El Manantial, Lules Department,Tucumán) and Ing. Zoot. CarlosMarino (Azucarera Justiniano Frías S.A.,Las Carreras, Valle de Tafí, Tucumán) for their support and for allowingus to collect S. frugiperda larvae from their fields.C.B.M. and E.G.V. are members of the CONICET research career.N.A.C. is the recipient of an UNNOBA fellowship.REFERENCES1. Pogue M. 2002. A world revision of the genus Spodoptera (Guenée)Lepidoptera: Noctuidae. American Entomological Society, Philadelphia, PA.2. Sanchis V. 2011. From microbial sprays to insect-resistant transgenicplants: history of the biospesticide Bacillus thuringiensis. A review. AgronSustain Dev 31:217–231. http://dx.doi.org/10.1051/agro/2010027.3. Storer NP, Babcock JM, Schlenz M, Meade T, Thompson GD, Bing JW,Huckaba RM. 2010. Discovery and characterization of field resistance toBt maize: Spodoptera frugiperda (Lepidoptera: Noctuidae) in Puerto Rico. JEcon Entomol 103:1031–1038.4. MorrisonM, Pope PB, Denman SE, McSweeney CS. 2009. Plant biomassdegradation by gut microbiomes: more of the same or something new?Curr Opin Biotechnol 20:358–363. http://dx.doi.org/10.1016/ j.cop-bio.2009.05.004.5. Dillon RJ, Dillon VM. 2004. The gut bacteria of insects: nonpathogenicinteractions. Annu Rev Entomol 49:71–92. http://dx.doi.org/10.1146/ an-nurev.ento.49.061802.123416.6. Shao Y, Arias-Cordero E, Guo H, Bartram S, Boland W. 2014. In vivopyro-SIP assessing active gut microbiota of the cotton leafworm,Spodoptera littoralis. PLoS One 9:e85948. http://dx.doi.org/10.1371/ jour-nal.pone.0085948.7. McCarthy CB, Santini MS, Pimenta PF, Diambra LA. 2013. First com-parative transcriptomic analysis of wild adult male and female Lutzomyialongipalpis, vector of visceral leishmaniasis. PLoS One 8:e58645. http://dx.doi.org/10.1371/journal.pone.0058645.8. Murúa G, Virla EG. 2003. Evaluación de cuatro dietas artificiales para lacria de Spodoptera frugiperda (Lep.: Noctuidae) destinada a mantener po-blaciones experimentales de himenópteros parasitoides. Bol San Veg Pla-gas 29:43–51.9. Sambade A, Martín S, Olmos A, García ML, Cambra M, Grau O, GuerriJ, Moreno P. 2000. A fast one-step reverse transcription and polymerasechain reaction (RT-PCR) amplification procedure providing highly spe-cific complementary DNA from plant virus RNA. J Virol Methods 87:25–28. http://dx.doi.org/10.1016/S0166-0934(00)00145-2.10. McCarthy CB, Diambra LA, Rivera Pomar RV. 2011. Metagenomicanalysis of taxa associated with Lutzomyia longipalpis, vector of visceralleishmaniasis, using an unbiased high-throughput approach. PLOS NeglTrop Dis 5:e1304. http://dx.doi.org/10.1371/journal.pntd.0001304.11. Zhao Y, Tang H, Ye Y. 2012. RAPSearch2: a fast and memory-efficientprotein similarity search tool for next-generation sequencing data. Bioin-formatics 28:125–126. http://dx.doi.org/10.1093/bioinformatics/btr595.12. Huson DH, Auch AF, Qi J, Schuster SC. 2007. MEGAN analysis ofmetagenomic data. Genome Res 17:377–386. http://dx.doi.org/10.1101/gr.5969107.13. Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC. 2011.Integrative analysis of environmental sequences usingMEGAN4.GenomeRes 21:1552–1560. http://dx.doi.org/10.1101/gr.120618.111.14. Fisher R. 1970. Statistical methods for research workers. 14th ed. Hafner,New York, NY.McCarthy et al.Genome Announcements2 genomea.asm.org July/August 2015 Volume 3 Issue 4 e00777-15 on July 21, 2015 by guesthttp://genomea.asm.org/Downloaded from 

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Metatranscriptomic analysis of larvae guts from field-collected and laboratory-reared Spodoptera frugiperda from the South American subtropical region

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