Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota
The shrimp has become the most valuable traded marine product in the world, and its microbiota plays an essential role in its development and overall health status. Massive high-throughput sequencing techniques using several hypervariable regions of the 16S rRNA gene are broadly applied in shrimp mi...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-01-01
|
| Series: | Microorganisms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-2607/8/1/134 |
| _version_ | 1811199235997040640 |
|---|---|
| author | Rodrigo García-López Fernanda Cornejo-Granados Alonso A. Lopez-Zavala Filiberto Sánchez-López Andrés Cota-Huízar Rogerio R. Sotelo-Mundo Abraham Guerrero Alfredo Mendoza-Vargas Bruno Gómez-Gil Adrian Ochoa-Leyva |
| author_facet | Rodrigo García-López Fernanda Cornejo-Granados Alonso A. Lopez-Zavala Filiberto Sánchez-López Andrés Cota-Huízar Rogerio R. Sotelo-Mundo Abraham Guerrero Alfredo Mendoza-Vargas Bruno Gómez-Gil Adrian Ochoa-Leyva |
| author_sort | Rodrigo García-López |
| collection | DOAJ |
| description | The shrimp has become the most valuable traded marine product in the world, and its microbiota plays an essential role in its development and overall health status. Massive high-throughput sequencing techniques using several hypervariable regions of the 16S rRNA gene are broadly applied in shrimp microbiota studies. However, it is essential to consider that the use of different hypervariable regions can influence the obtained data and the interpretation of the results. The present study compares the shrimp microbiota structure and composition obtained by three types of amplicons: one spanning both the V3 and V4 hypervariable regions (V3V4), one for the V3 region only (V3), and one for the V4 region only (V4) using the same experimental and bioinformatics protocols. Twenty-four samples from hepatopancreas and intestine were sequenced and evaluated using the GreenGenes and silva reference databases for clustering and taxonomic classification. In general, the V3V4 regions resulted in higher richness and diversity, followed by V3 and V4. All three regions establish an apparent clustering effect that discriminates between the two analyzed organs and describe a higher richness for the intestine and a higher diversity for the hepatopancreas samples. Proteobacteria was the most abundant phyla overall, and Cyanobacteria was more common in the intestine, whereas Firmicutes and Actinobacteria were more prevalent in hepatopancreas samples. Also, the genus <i>Vibrio</i> was significantly abundant in the intestine, as well as <i>Acinetobacter</i> and <i>Pseudomonas</i> in the hepatopancreas suggesting these taxa as markers for their respective organs independently of the sequenced region. The use of a single hypervariable region such as V3 may be a low-cost alternative that enables an adequate description of the shrimp microbiota, allowing for the development of strategies to continually monitor the microbial communities and detect changes that could indicate susceptibility to pathogens under real aquaculture conditions while the use of the full V3V4 regions can contribute to a more in-depth characterization of the microbial composition. |
| first_indexed | 2024-04-12T01:44:36Z |
| format | Article |
| id | doaj.art-0d432fb8c2c04e9bad3d16594c93e2e4 |
| institution | Directory Open Access Journal |
| issn | 2076-2607 |
| language | English |
| last_indexed | 2024-04-12T01:44:36Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Microorganisms |
| spelling | doaj.art-0d432fb8c2c04e9bad3d16594c93e2e42022-12-22T03:53:06ZengMDPI AGMicroorganisms2076-26072020-01-018113410.3390/microorganisms8010134microorganisms8010134Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp MicrobiotaRodrigo García-López0Fernanda Cornejo-Granados1Alonso A. Lopez-Zavala2Filiberto Sánchez-López3Andrés Cota-Huízar4Rogerio R. Sotelo-Mundo5Abraham Guerrero6Alfredo Mendoza-Vargas7Bruno Gómez-Gil8Adrian Ochoa-Leyva9Departamento de Microbiología Molecular, Instituto de Biotecnología (IBT), Universidad Nacional Autónoma de México (UNAM) Av. Universidad #2001, Col. Chamilpa, Cuernavaca, Morelos 62210, MexicoDepartamento de Microbiología Molecular, Instituto de Biotecnología (IBT), Universidad Nacional Autónoma de México (UNAM) Av. Universidad #2001, Col. Chamilpa, Cuernavaca, Morelos 62210, MexicoDepartamento de Ciencias Químico Biológicas, Universidad de Sonora (UNISON). Blvd., Rosales y Luis Encinas, Hermosillo, Sonora 83000, MexicoDepartamento de Microbiología Molecular, Instituto de Biotecnología (IBT), Universidad Nacional Autónoma de México (UNAM) Av. Universidad #2001, Col. Chamilpa, Cuernavaca, Morelos 62210, MexicoCamarones el Renacimiento S.P.R. de R.I. Justino Rubio No. 26, Col. Ejidal, Higuera de Zaragoza, Sinaloa 81330, MexicoLaboratorio de Estructura Biomolecular, Centro de Investigación en Alimentación y Desarrollo, A.C. Hermosillo, Sonora 83304, MexicoCentro de Investigación en Alimentación y Desarrollo, A.C. Mazatlán, Sinaloa 82100, MexicoInstituto Nacional de Medicina Genómica, Secretaría de Salud (INMEGEN), Periférico Sur No. 4809, Mexico 14610, MexicoCentro de Investigación en Alimentación y Desarrollo, A.C. Mazatlán, Sinaloa 82100, MexicoDepartamento de Microbiología Molecular, Instituto de Biotecnología (IBT), Universidad Nacional Autónoma de México (UNAM) Av. Universidad #2001, Col. Chamilpa, Cuernavaca, Morelos 62210, MexicoThe shrimp has become the most valuable traded marine product in the world, and its microbiota plays an essential role in its development and overall health status. Massive high-throughput sequencing techniques using several hypervariable regions of the 16S rRNA gene are broadly applied in shrimp microbiota studies. However, it is essential to consider that the use of different hypervariable regions can influence the obtained data and the interpretation of the results. The present study compares the shrimp microbiota structure and composition obtained by three types of amplicons: one spanning both the V3 and V4 hypervariable regions (V3V4), one for the V3 region only (V3), and one for the V4 region only (V4) using the same experimental and bioinformatics protocols. Twenty-four samples from hepatopancreas and intestine were sequenced and evaluated using the GreenGenes and silva reference databases for clustering and taxonomic classification. In general, the V3V4 regions resulted in higher richness and diversity, followed by V3 and V4. All three regions establish an apparent clustering effect that discriminates between the two analyzed organs and describe a higher richness for the intestine and a higher diversity for the hepatopancreas samples. Proteobacteria was the most abundant phyla overall, and Cyanobacteria was more common in the intestine, whereas Firmicutes and Actinobacteria were more prevalent in hepatopancreas samples. Also, the genus <i>Vibrio</i> was significantly abundant in the intestine, as well as <i>Acinetobacter</i> and <i>Pseudomonas</i> in the hepatopancreas suggesting these taxa as markers for their respective organs independently of the sequenced region. The use of a single hypervariable region such as V3 may be a low-cost alternative that enables an adequate description of the shrimp microbiota, allowing for the development of strategies to continually monitor the microbial communities and detect changes that could indicate susceptibility to pathogens under real aquaculture conditions while the use of the full V3V4 regions can contribute to a more in-depth characterization of the microbial composition.https://www.mdpi.com/2076-2607/8/1/134<i>litopenaeus vannamei</i> (<i>l. vannamei</i>)microbiotabioinformatics16s rrnahigh-throughput sequencingshrimp intestineshrimp hepatopancreasshrimp metagenomics |
| spellingShingle | Rodrigo García-López Fernanda Cornejo-Granados Alonso A. Lopez-Zavala Filiberto Sánchez-López Andrés Cota-Huízar Rogerio R. Sotelo-Mundo Abraham Guerrero Alfredo Mendoza-Vargas Bruno Gómez-Gil Adrian Ochoa-Leyva Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota Microorganisms <i>litopenaeus vannamei</i> (<i>l. vannamei</i>) microbiota bioinformatics 16s rrna high-throughput sequencing shrimp intestine shrimp hepatopancreas shrimp metagenomics |
| title | Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota |
| title_full | Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota |
| title_fullStr | Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota |
| title_full_unstemmed | Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota |
| title_short | Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota |
| title_sort | doing more with less a comparison of 16s hypervariable regions in search of defining the shrimp microbiota |
| topic | <i>litopenaeus vannamei</i> (<i>l. vannamei</i>) microbiota bioinformatics 16s rrna high-throughput sequencing shrimp intestine shrimp hepatopancreas shrimp metagenomics |
| url | https://www.mdpi.com/2076-2607/8/1/134 |
| work_keys_str_mv | AT rodrigogarcialopez doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT fernandacornejogranados doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT alonsoalopezzavala doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT filibertosanchezlopez doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT andrescotahuizar doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT rogeriorsotelomundo doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT abrahamguerrero doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT alfredomendozavargas doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT brunogomezgil doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota AT adrianochoaleyva doingmorewithlessacomparisonof16shypervariableregionsinsearchofdefiningtheshrimpmicrobiota |