Summary of Study ST001990

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001264. The data can be accessed directly via it's Project DOI: 10.21228/M8B39F This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST001990
Study TitleMetabolomics of the interaction between a consortium of entomopathogenic fungi and their target insect: mechanisms of attack and survival
Study TypeUntargeted Metabolomics
Study SummaryOne of the most concerning pests that attack strawberries in Brazil is Duponchelia fovealis, a non-native moth with no registered control methods to date. Our group recently observed that a fungal consortium formed by two strains of Beauveria bassiana increased the mortality of D. fovealis more than inoculation with each strain on its own. However, the molecular interaction between the fungal consortium and the caterpillars is unknown, raising several questions about the enhanced pest control observed. Furthermore, concerns over the emergency of resistance and the selection for resistance to chemical and biological products that are constantly applied in agriculture highlight the need for careful examination of novel pest control methods. Thus, in this work, we sought to pioneer the evaluation of the molecular interaction between a fungal consortium of B. bassiana and D. fovealis caterpillars. We aimed to understand the biocontrol process involved in this interaction and the defense system of the caterpillar. Therefore, seven days after D. fovealis caterpillars were inoculated with the B. bassiana consortium, the dead and surviving caterpillars were analyzed using GC-MS and LC-MS/MS.
Institute
Universidade Federal do Paraná
DepartmentPatologia Básica
LaboratoryLaboratório de Microbiologia e Biologia Molecular
Last NameKatiski da Costa Stuart
First NameAndressa
AddressAv. Cel. Francisco Heráclito dos Santos, 100, Curitiba, Paraná, 81530-000, Brazil
Emailandressa.katiski@gmail.com
Phone55 41 991922779
Submit Date2021-11-12
Num Groups7
Raw Data AvailableYes
Raw Data File Type(s)cdf, raw(Waters)
Analysis Type DetailAPI-MS
Release Date2023-05-12
Release Version1
Andressa Katiski da Costa Stuart Andressa Katiski da Costa Stuart
https://dx.doi.org/10.21228/M8B39F
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Project:

Project ID:PR001264
Project DOI:doi: 10.21228/M8B39F
Project Title:Metabolomics of the interaction between a consortium of entomopathogenic fungi and their target insect: mechanisms of attack and survival
Project Type:Untargeted Metabolomics
Project Summary:One of the most concerning pests that attack strawberries in Brazil is Duponchelia fovealis, a non-native moth with no registered control methods to date. Our group recently observed that a fungal consortium formed by two strains of Beauveria bassiana increased the mortality of D. fovealis more than inoculation with each strain on its own. However, the molecular interaction between the fungal consortium and the caterpillars is unknown, raising several questions about the enhanced pest control observed. Furthermore, concerns over the emergency of resistance and the selection for resistance to chemical and biological products that are constantly applied in agriculture highlight the need for careful examination of novel pest control methods. Thus, in this work, we sought to pioneer the evaluation of the molecular interaction between a fungal consortium of B. bassiana and D. fovealis caterpillars. We aimed to understand the biocontrol process involved in this interaction and the defense system of the caterpillar. Therefore, seven days after D. fovealis caterpillars were inoculated with the B. bassiana consortium, the dead and surviving caterpillars were analyzed using GC-MS and LC-MS/MS.
Institute:Universidade Federal do Paraná
Department:Patologia Básica
Laboratory:Laboratório de Microbiologia e Biologia Molecular
Last Name:Katiski da Costa Stuart
First Name:Andressa
Address:Av. Cel. Francisco Heráclito dos Santos, 100, Curitiba, Paraná, 81530-000, Brazil
Email:andressa.katiski@gmail.com
Phone:5541991922779
Project Comments:Previous studies by our research group showed the increased potential for biocontrol on the insect pest Duponchelia fovealis when two strains of Beauveria bassiana were used together as a fungal consortium. In this work we sought to identify the metabolites involved in the interaction between the consortium formed by different B. bassiana strains and its target insect, D. fovealis. We identify the metabolites using non-targeted metabolomics, applying gas and liquid chromatography coupled to mass spectrometers (GC-MS and LC-MS/MS). These analyses aimed to elucidate the molecular mechanisms involved in the biocontrol effect of the fungal consortium on D. fovealis and to examine possible explanations for the survival of some caterpillars due to a potential resistance mechanism. Dead and surviving caterpillars were analyzed separately.
Contributors:Jason Lee Furuie, Thais Regiani Cataldi, Rodrigo Makowiecky Stuart, Maria Aparecida Cassilha Zawadneak, Carlos Alberto Labate, Ida Chapaval Pimentel

Subject:

Subject ID:SU002071
Subject Type:Insect
Subject Species:Duponchelia fovealis

Factors:

Subject type: Insect; Subject species: Duponchelia fovealis (Factor headings shown in green)

mb_sample_id local_sample_id Factor
SA185990CatS_2Control
SA185991CatS_4Control
SA185992CatS_5Control
SA185993CatS_1Control
SA185994CatS_3Control
SA185995CatM_Bov2_1Duponchelia fovealis killed by the Bov2 strain of Beauveria bassiana
SA185996CatM_Bov2_2Duponchelia fovealis killed by the Bov2 strain of Beauveria bassiana
SA185997CatM_Bov2_5Duponchelia fovealis killed by the Bov2 strain of Beauveria bassiana
SA185998CatM_Bov2_3Duponchelia fovealis killed by the Bov2 strain of Beauveria bassiana
SA185999CatM_Bov2_4Duponchelia fovealis killed by the Bov2 strain of Beauveria bassiana
SA186000CatM_Bov3_5Duponchelia fovealis killed by the Bov3 strain of Beauveria bassiana
SA186001CatM_Bov3_4Duponchelia fovealis killed by the Bov3 strain of Beauveria bassiana
SA186002CatM_Bov3_2Duponchelia fovealis killed by the Bov3 strain of Beauveria bassiana
SA186003CatM_Bov3_3Duponchelia fovealis killed by the Bov3 strain of Beauveria bassiana
SA186004CatM_Bov3_1Duponchelia fovealis killed by the Bov3 strain of Beauveria bassiana
SA186005CatM_Cons_3Duponchelia fovealis killed by the consortium
SA186006CatM_Cons_2Duponchelia fovealis killed by the consortium
SA186007CatM_Cons_4Duponchelia fovealis killed by the consortium
SA186008CatM_Cons_5Duponchelia fovealis killed by the consortium
SA186009CatM_Cons_1Duponchelia fovealis killed by the consortium
SA186010CatS_Bov2_1Duponchelia fovealis that survived the application of the Bov 2 strain of Beauveria bassiana
SA186011CatS_Bov2_4Duponchelia fovealis that survived the application of the Bov 2 strain of Beauveria bassiana
SA186012CatS_Bov2_3Duponchelia fovealis that survived the application of the Bov 2 strain of Beauveria bassiana
SA186013CatS_Bov2_2Duponchelia fovealis that survived the application of the Bov 2 strain of Beauveria bassiana
SA186014CatS_Bov2_5Duponchelia fovealis that survived the application of the Bov 2 strain of Beauveria bassiana
SA186015CatS_Bov3_1Duponchelia fovealis that survived the application of the Bov 3 strain of Beauveria bassiana
SA186016CatS_Bov3_3Duponchelia fovealis that survived the application of the Bov 3 strain of Beauveria bassiana
SA186017CatS_Bov3_5Duponchelia fovealis that survived the application of the Bov 3 strain of Beauveria bassiana
SA186018CatS_Bov3_4Duponchelia fovealis that survived the application of the Bov 3 strain of Beauveria bassiana
SA186019CatS_Bov3_2Duponchelia fovealis that survived the application of the Bov 3 strain of Beauveria bassiana
SA186020CatS_Cons_1Duponchelia fovealis that survived the application of the consortium
SA186021CatS_Cons_2Duponchelia fovealis that survived the application of the consortium
SA186022CatS_Cons_3Duponchelia fovealis that survived the application of the consortium
SA186023CatS_Cons_4Duponchelia fovealis that survived the application of the consortium
SA186024CatS_Cons_5Duponchelia fovealis that survived the application of the consortium
Showing results 1 to 35 of 35

Collection:

Collection ID:CO002064
Collection Summary:Groups of 10 third instar caterpillars were placed on strawberry leaves and sprayed with 1 mL of B. bassiana conidia-suspension: 2 x 107 conidia/mL in 0.85% saline solution with Tween 80® adhesive spreader added. Therefore, the treatments applied were: control caterpillars (consisting only of 0.85% saline solution and Tween 80®), caterpillars inoculated with Bov 3 strain of B. bassiana, caterpillars inoculated with Bov 2 strain of B. bassiana and caterpillars inoculated with the Bov3-Bov 2 consortium. On the seventh day, caterpillars that did not respond to the stimulus provided by the touch of a brush were considered dead. All caterpillars were identified as living or dead at the end of the seven days and were subsequently stored in a freezer at -80ºC.
Collection Protocol Filename:Metabolite_Extraction
Sample Type:Insect tissue
Storage Conditions:-80℃

Treatment:

Treatment ID:TR002083
Treatment Summary:The treatments applied were: control caterpillars (consisting only of 0.85% saline solution and Tween 80®), caterpillars inoculated with Bov 3 strain of B. bassiana, caterpillars inoculated with Bov 2 strain of B. bassiana and caterpillars inoculated with the Bov3-Bov2 consortium.
Treatment Protocol Filename:Metabolite_Extraction
Treatment Dosevolume:2 x 10^7 conidia/mL

Sample Preparation:

Sampleprep ID:SP002077
Sampleprep Summary:After the direct contact bioassay, the caterpillars were arranged by treatment, then macerated in liquid nitrogen (N2). Extraction was performed with 200 mg of the macerate added to a 1 mL microtube (Eppendorf, Germany) previously treated with methanol. Following this, 125 μL of chloroform (CHCl3), 50 μL ultra-pure water (H2O), and 250 μL cold methanol (CH3OH) were added to the macerate. The microtubes were vigorously vortexed and placed in an ultrasonic bath (Odontobrás, Ribeirão-SP) at 20 Hz and approximately 4ºC for 10 minutes. Then, 50 μL of CHCl3 and 50 μL of H2O were added, and the tubes were vortexed again. The samples were centrifuged (Eppendorf, Germany) for 5 minutes at 14000 rpm and 4°C, and the supernatant was filtered on a Whatman® 0.22 µm filter (Merck, Germany) and transferred to a glass vial. The vial was taken to a lyophilizer (Thermo Fischer Scientific, MA) until the samples had completely dried. Finally, the lyophilized samples were resuspended in 200 µL of extraction solution and aliquoted for use in the GC-MS and LC-MS/MS.
Sampleprep Protocol Filename:Metabolite_Extraction
Extract Storage:-80℃

Combined analysis:

Analysis ID AN003242 AN003243 AN003244 AN003245 AN003246 AN003247
Analysis type MS MS MS MS MS MS
Chromatography type GC GC Reversed phase Reversed phase Reversed phase Reversed phase
Chromatography system Agilent 7890A Agilent 7890A Waters Acquity UPLC Waters Acquity UPLC Waters Acquity UPLC Waters Acquity UPLC
Column Agilent DB-5 (20m x 0.18mm, 0.18um); Restek RX-T 17 (0.9m x 0.10mm, 0.10um) Agilent DB-5 (20m x 0.18mm, 0.18um); Restek RX-T 17 (0.9m x 0.10mm, 0.10um) Waters Acquity UPLC HSS (100 x 2.1mm, 1.7um) Waters Acquity UPLC HSS (100 x 2.1mm, 1.7um) Waters Acquity UPLC HSS (100 x 2.1mm, 1.7um) Waters Acquity UPLC HSS (100 x 2.1mm, 1.7um)
MS Type EI API ESI ESI ESI ESI
MS instrument type GC x GC-TOF GC x GC-TOF QTOF QTOF QTOF QTOF
MS instrument name Leco Pegasus 4D GCxGC TOF Leco Pegasus 4D GCxGC TOF Waters Acquity UPLC Waters Acquity UPLC Waters Acquity UPLC Waters Acquity UPLC
Ion Mode UNSPECIFIED UNSPECIFIED NEGATIVE POSITIVE NEGATIVE POSITIVE
Units peak area Relative intensity Relative intensity Relative intensity Relative intensity

Chromatography:

Chromatography ID:CH002391
Methods Filename:Metabolomics_Methods
Instrument Name:Agilent 7890A
Column Name:Agilent DB-5 (20m x 0.18mm, 0.18um); Restek RX-T 17 (0.9m x 0.10mm, 0.10um)
Column Temperature:70 - 320 ºC
Flow Rate:1 mL.min-1
Injection Temperature:280 ºC
Sample Injection:1 uL
Oven Temperature:70°C for 2 min, increasing by 15°C·min-1 until it reached 320°C and then held at this temperature for 4 min.
Chromatography Type:GC
  
Chromatography ID:CH002392
Methods Filename:Metabolomics_Methods
Instrument Name:Waters Acquity UPLC
Column Name:Waters Acquity UPLC HSS (100 x 2.1mm, 1.7um)
Column Temperature:35 ºC
Flow Gradient:95% solvent A and 5% B. The gradient increased linearly to 75% A and 25% B over the next 6 min. The polarity was reversed to 25% A and 75% B for 6 min, and finally 5% A and 95% B for 1 min
Flow Rate:0.5 mL·min-1
Solvent A:Water; formic acid
Solvent B:100% acetonitrile; formic acid.
Capillary Voltage:3 kV
Chromatography Type:Reversed phase

MS:

MS ID:MS003015
Analysis ID:AN003242
Instrument Name:Leco Pegasus 4D GCxGC TOF
Instrument Type:GC x GC-TOF
MS Type:EI
MS Comments:Data from GC-MS was processed using ChromaTOF 4.32 software to conduct baseline correction, deconvolution, retention index (RI), retention time correction (RT), identification, and alignment of peaks. NIST library version 11 was used for the identification of metabolites. Only metabolites with a score of 700 or above were considered. The intensity of each metabolite was normalized by the total ion count (TIC) of each sample. Statistical analyses were performed using the MetaboAnalyst 4.0 online software (available at http://www.metaboanalyst.ca/MetaboAnalyst/)
Ion Mode:UNSPECIFIED
Fragmentation Method:EI
Ion Source Temperature:250 ºC
Ionization Energy:70 eV
Analysis Protocol File:metabolomics_methods.pdf
  
MS ID:MS003016
Analysis ID:AN003243
Instrument Name:Leco Pegasus 4D GCxGC TOF
Instrument Type:GC x GC-TOF
MS Type:API
MS Comments:Data from GC-MS was processed using ChromaTOF 4.32 software to conduct baseline correction, deconvolution, retention index (RI), retention time correction (RT), identification, and alignment of peaks. NIST library version 11 was used for the identification of metabolites. Only metabolites with a score of 700 or above were considered. The intensity of each metabolite was normalized by the total ion count (TIC) of each sample. Statistical analyses were performed using the MetaboAnalyst 4.0 online software (available at http://www.metaboanalyst.ca/MetaboAnalyst/)
Ion Mode:UNSPECIFIED
Fragmentation Method:EI
Ion Source Temperature:250 ºC
Ionization Energy:70 eV
Analysis Protocol File:metabolomics_methods.pdf
  
MS ID:MS003017
Analysis ID:AN003244
Instrument Name:Waters Acquity UPLC
Instrument Type:QTOF
MS Type:ESI
MS Comments:Generated data were pre-processed using MassLynx 4.1 software (Waters Corporation, MA, USA) and then analyzed using MetaboAnalyst 4.0 online software. Fragmentation was performed under the same conditions as the ionization source, using collision energies between 15 and 50 eV. The search for metabolites was performed in the Human Metabolome Database (HMDB) using a mass tolerance of up to 0.1 Da and considering the adduct of [M-H]-. The structures of the molecules were imported and underwent in silico fragmentation using ACD/MS Structure ID software suite (ACD/labs, Toronto, Canada). The fragmentation profile of each molecule proposed by the program was then compared to the fragments generated by MS/MS to accept or reject the identification of metabolites according to similarity.
Ion Mode:NEGATIVE
Capillary Voltage:3 kV
Dry Gas Flow:50 L/hr
Source Temperature:150 ºC
Desolvation Gas Flow:550 L/hr.
Analysis Protocol File:metabolomics_methods.pdf
  
MS ID:MS003018
Analysis ID:AN003245
Instrument Name:Waters Acquity UPLC
Instrument Type:QTOF
MS Type:ESI
MS Comments:Generated data were pre-processed using MassLynx 4.1 software (Waters Corporation, MA, USA) and then analyzed using MetaboAnalyst 4.0 online software. Fragmentation was performed under the same conditions as the ionization source, using collision energies between 15 and 50 eV. The search for metabolites was performed in the Human Metabolome Database (HMDB) using a mass tolerance of up to 0.1 Da and considering the adduct of [M-H]-. The structures of the molecules were imported and underwent in silico fragmentation using ACD/MS Structure ID software suite (ACD/labs, Toronto, Canada). The fragmentation profile of each molecule proposed by the program was then compared to the fragments generated by MS/MS to accept or reject the identification of metabolites according to similarity.
Ion Mode:POSITIVE
Capillary Voltage:3 kV
Dry Gas Flow:50 L/hr
Source Temperature:150 ºC
Desolvation Gas Flow:550 L/hr
Analysis Protocol File:metabolomics_methods.pdf
  
MS ID:MS003019
Analysis ID:AN003246
Instrument Name:Waters Acquity UPLC
Instrument Type:QTOF
MS Type:ESI
MS Comments:Generated data were pre-processed using MassLynx 4.1 software (Waters Corporation, MA, USA) and then analyzed using MetaboAnalyst 4.0 online software. Fragmentation was performed under the same conditions as the ionization source, using collision energies between 15 and 50 eV. The search for metabolites was performed in the Human Metabolome Database (HMDB) using a mass tolerance of up to 0.1 Da and considering the adduct of [M-H]-. The structures of the molecules were imported and underwent in silico fragmentation using ACD/MS Structure ID software suite (ACD/labs, Toronto, Canada). The fragmentation profile of each molecule proposed by the program was then compared to the fragments generated by MS/MS to accept or reject the identification of metabolites according to similarity.
Ion Mode:NEGATIVE
Capillary Voltage:3 kV
Dry Gas Flow:50 L/hr
Source Temperature:150 ºC
Desolvation Gas Flow:550 L/hr
Analysis Protocol File:metabolomics_methods.pdf
  
MS ID:MS003020
Analysis ID:AN003247
Instrument Name:Waters Acquity UPLC
Instrument Type:QTOF
MS Type:ESI
MS Comments:Generated data were pre-processed using MassLynx 4.1 software (Waters Corporation, MA, USA) and then analyzed using MetaboAnalyst 4.0 online software. Fragmentation was performed under the same conditions as the ionization source, using collision energies between 15 and 50 eV. The search for metabolites was performed in the Human Metabolome Database (HMDB) using a mass tolerance of up to 0.1 Da and considering the adduct of [M-H]-. The structures of the molecules were imported and underwent in silico fragmentation using ACD/MS Structure ID software suite (ACD/labs, Toronto, Canada). The fragmentation profile of each molecule proposed by the program was then compared to the fragments generated by MS/MS to accept or reject the identification of metabolites according to similarity.
Ion Mode:POSITIVE
Capillary Voltage:3 kV
Dry Gas Flow:50 L/hr
Source Temperature:150 ºC
Desolvation Gas Flow:550 L/hr
Analysis Protocol File:metabolomics_methods.pdf
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