Proteomic profiling of quality protein Maize kernels using mass spectrometry

Authors

  • Benito Minjarez Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias, 2100 Camino Ramón Padilla Sánchez, Nextipac, Zapopan, Jalisco, México, 45200.
  • Yury Rodríguez Yañez Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias, 2100 Camino Ramón Padilla Sánchez, Nextipac, Zapopan, Jalisco, México, 45200.
  • Eiko Osawa Martínez Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias, 2100 Camino Ramón Padilla Sánchez, Nextipac, Zapopan, Jalisco, México, 45200.
  • Oscar García Leal Centro de Estudios e Investigaciones en Comportamiento (Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias), Universidad de Guadalajara, 180 Francisco de Quevedo Street, Col. Arcos Vallarta, Guadalajara, Jalisco, México, 44130.
  • Jonathan Buriticá Centro de Estudios e Investigaciones en Comportamiento (Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias), Universidad de Guadalajara, 180 Francisco de Quevedo Street, Col. Arcos Vallarta, Guadalajara, Jalisco, México, 44130.
  • Juan Pedro Luna Arias Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Departamento de Biología Celular, 2508 Instituto Politécnico Nacional Avenue, Gustavo A. Madero, San Pedro Zacatenco, México city, México, 07360.
  • Aida Longán Zarzoso Centro de Estudios e Investigaciones en Comportamiento (Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias), Universidad de Guadalajara, 180 Francisco de Quevedo Street, Col. Arcos Vallarta, Guadalajara, Jalisco, México, 44130.
  • Raúl Páez Quiñones Centro de Estudios e Investigaciones en Comportamiento (Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias), Universidad de Guadalajara, 180 Francisco de Quevedo Street, Col. Arcos Vallarta, Guadalajara, Jalisco, México, 44130.
  • Laurent Ávila Chauvet Centro de Estudios e Investigaciones en Comportamiento (Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias), Universidad de Guadalajara, 180 Francisco de Quevedo Street, Col. Arcos Vallarta, Guadalajara, Jalisco, México, 44130.
  • Milagros Ascencio Guirado Centro de Estudios e Investigaciones en Comportamiento (Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias), Universidad de Guadalajara, 180 Francisco de Quevedo Street, Col. Arcos Vallarta, Guadalajara, Jalisco, México, 44130.
  • Moisés Martín Morales-Rivera Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias, 2100 Camino Ramón Padilla Sánchez, Nextipac, Zapopan, Jalisco, México, 45200.
  • Salvador Mena Munguía Universidad de Guadalajara, Centro Universitario de Ciencias Biológicas y Agropecuarias, 2100 Camino Ramón Padilla Sánchez, Nextipac, Zapopan, Jalisco, México, 45200.

Keywords:

Amino acids, bioinformatics, kernels, mass spectrometry, proteomics, quality protein maize

Abstract

Maize (Zea mays L.) is the third most crucial crop worldwide and is of paramount importance in both humans
and livestock diets. Conventional maize varieties have less than half of the amino acids recommended for human
nutrition, and this deficiency results in an imbalance of amino acids and low protein content, which has been associated
with several pathologies, including malnutrition. Thus, different countries have focused on research on
fortified foods, such as quality protein maize (QPM) noting that these improved varieties may contain up to 100%
more essential amino acids residues than conventional maize. Hence, this study aimed to characterize through
tandem mass spectrometry and bioinformatics analysis, relative expression of polypeptides contained in a hybrid
variety of QPM, which allow to identify potential markers with implications in the management and improvement
of this crops maintaining their intrinsic characteristics. We identify 262 polypeptides, highlighting those related to
molecular function (catalytic activity, structural molecule activity, and binding) and biological process (cellular and
metabolic process). These results provide the necessary information, not only for the characterization of the QPM
proteome through novel tools such as proteomics, but also to describe mechanisms related to different biological
processes such as the embryogenesis, development and growth of grains and eventually plants. Potentially
It promotes the discovery of molecular markers (biomarkers) that would allow the improvement of agronomical
processes.

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Published

2020-08-13

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Articles