Repositorio Nacional

"Potato microtuber (MT) development through in vitro techniques are ideal propagules for producing high quality potato plants. MT formation is influenced by several factors, i.e., photoperiod, sucrose, hormones, and osmotic stress. We have previously developed a protocol of MT induction in medium with sucrose (8% w/v), gelrite (6g/L), and 2iP as cytokinin under darkness. To understand the molecular mechanisms involved, we performed a transcriptome-wide analysis. Here we show that 1715 up- and 1624 down-regulated genes were involved in this biological process. Through the protein–protein interaction (PPI) network analyses performed in the STRING database (v11.5), we found 299 genes tightly associated in 14 clusters. Two major clusters of up-regulated proteins fundamental for life growth and development were found: 29 ribosomal proteins (RPs) interacting with 6 PEBP family members and 117 cell cycle (CC) proteins. The PPI network of up-regulated transcription factors (TFs) revealed that at least six TFs–MYB43, TSF, bZIP27, bZIP43, HAT4 and WOX9–may be involved during MTs development. The PPI network of down-regulated genes revealed a cluster of 83 proteins involved in light and photosynthesis, 110 in response to hormone, 74 in hormone mediate signaling pathway and 22 related to aging."

transcriptome-wide analysis, microtubers, potato, Solanum tuberosum, darkness, cell cycle, ribosomal proteins, PEBP family genes, cytokinin BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA GENÉTICA GENÉTICA MOLECULAR DE PLANTAS GENÉTICA MOLECULAR DE PLANTAS

The banana MaWRKY18, MaWRKY45, MaWRKY60 and MaWRKY70 genes encode functional transcription factors and display differential expression in response to defense phytohormones

SERGIO GARCIA LAYNES VIRGINIA AURORA HERRERA VALENCIA Lilia Guadalupe Tamayo Torres VERONICA LIMONES BRIONES FELIPE ALONSO BARREDO POOL FRAY MARTIN BAAS ESPINOLA Angel Alpuche-Solis CARLOS ALBERTO PUCH HAU SANTY PERAZA ECHEVERRIA (2022, [Artículo])

WRKY transcription factors (TFs) play key roles in plant defense responses through phytohormone signaling pathways. However, their functions in tropical fruit crops, especially in banana, remain largely unknown. Several WRKY genes from the model plants rice (OsWRKY45) and Arabidopsis (AtWRKY18, AtWRKY60, AtWRKY70) have shown to be attractive TFs for engineering disease resistance. In this study, we isolated four banana cDNAs (MaWRKY18, MaWRKY45, MaWRKY60, and MaWRKY70) with homology to these rice and Arabidopsis WRKY genes. The MaWRKY cDNAs were isolated from the wild banana Musa acuminata ssp. malaccensis, which is resistant to several diseases of this crop and is a progenitor of most banana cultivars. The deduced amino acid sequences of the four MaWRKY cDNAs revealed the presence of the conserved WRKY domain of ~60 amino acids and a zinc-finger motif at the N-terminus. Based on the number of WRKY repeats and the structure of the zinc-finger motif, MaWRKY18 and MaWRKY60 belong to group II of WRKY TFs, while MaWRKY45 and MaWRKY70 are members of group III. Their corresponding proteins were located in the nuclei of onion epidermal cells and were shown to be functional TFs in yeast cells. Moreover, expression analyses revealed that the majority of these MaWRKY genes were upregulated by salicylic acid (SA) or methyl jasmonate (MeJA) phytohormones, although the expression levels were relatively higher with MeJA treatment. The fact that most of these banana WRKY genes were upregulated by SA or MeJA, which are involved in systemic acquired resistance (SAR) or induced systemic resistance (ISR), respectively, make them interesting candidates for bioengineering broad-spectrum resistance in this crop. © 2022 by the authors.

BANANA TRANSCRIPTION FACTOR WRKY DEFENSE PHYTOHORMONES SALICYLIC ACID METHYL JASMONATE SAR ISR BROAD-SPECTRUM RESISTANCE BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA GENÉTICA GENÉTICA MOLECULAR DE PLANTAS GENÉTICA MOLECULAR DE PLANTAS

Transcriptome mining provides insights into cell wall metabolism and fiber lignification in Agave tequilana Weber

Luis Fernando Maceda Lopez ELSA BEATRIZ GONGORA CASTILLO Enrique Ibarra-Laclette DALIA C. MORAN VELAZQUEZ AMARANTA GIRON RAMIREZ Matthieu Bourdon José Luis Villalpando Aguilar Gabriela Chavez-Calvillo Toomer John Tang Parastoo Azadi Jorge Manuel Santamaría Fernández Itzel López-Rosas Mercedes G Lopez June Simpson FULGENCIO ALATORRE COBOS (2022, [Artículo])

Resilience of growing in arid and semiarid regions and a high capacity of accumulating sugar-rich biomass with low lignin percentages have placed Agave species as an emerging bioen-ergy crop. Although transcriptome sequencing of fiber-producing agave species has been explored, molecular bases that control wall cell biogenesis and metabolism in agave species are still poorly understood. Here, through RNAseq data mining, we reconstructed the cellulose biosynthesis pathway and the phenylpropanoid route producing lignin monomers in A. tequilana, and evaluated their expression patterns in silico and experimentally. Most of the orthologs retrieved showed differential expression levels when they were analyzed in different tissues with contrasting cellulose and lignin accumulation. Phylogenetic and structural motif analyses of putative CESA and CAD proteins allowed to identify those potentially involved with secondary cell wall formation. RT-qPCR assays revealed enhanced expression levels of AtqCAD5 and AtqCESA7 in parenchyma cells associated with extraxylary fibers, suggesting a mechanism of formation of sclerenchyma fibers in Agave similar to that reported for xylem cells in model eudicots. Overall, our results provide a framework for un-derstanding molecular bases underlying cell wall biogenesis in Agave species studying mechanisms involving in leaf fiber development in monocots. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

AGAVE CELL WALLS LIGNOCELLULOSE CAD PROTEIN CESA PROTEIN SCLERENCHYMA BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA GENÉTICA GENÉTICA MOLECULAR DE PLANTAS GENÉTICA MOLECULAR DE PLANTAS

Búsqueda de un conjunto óptimo de descriptores moleculares para la modelación QSAR

Search for an optimal subset of molecular descriptors for QSAR modeling

Luis Antonio García González (2023, [Tesis de doctorado])

En la actualidad, se estima que más de 10 millones de vertebrados son utilizados cada año en estudios toxicológicos. Dadas estas circunstancias, varias agencias regulatorias están impulsando activamente a la comunidad científica para el desarrollo de una alternativa a la experimentación con animales. Entre las alternativas existentes se pueden encontrar los estudios in-silico, especialmente los métodos de Relación Cuantitativa Estructura-Actividad (QSAR por sus siglas en inglés), los cuales se destacan como uno de los más utilizados. Los estudios QSAR se basan en la hipótesis de que compuestos estructuralmente similares presentan una actividad similar, lo que permite predecir la actividad de nuevos compuestos en función de compuestos estructuralmente similares, para los cuales se definió su actividad de forma experimental. Estudios han demostrado que la selección del subconjunto “óptimo” de las variables (descriptores moleculares) que caracterizan estructuralmente los compuestos tiene mayor importancia para la construcción de un modelo QSAR robusto que la estrategia de modelación utilizada. Actualmente, los descriptores moleculares (DMs) utilizados para la modelación QSAR son calculados con herramientas computacionales que no tienen en cuenta si estos caracterizan bien la actividad que se quiere modelar y los compuestos que se están analizando. En este trabajo se describen las limitaciones del enfoque actual, teniendo en cuenta que, si se sigue este enfoque, se puede pasar por alto información relevante al suponer que el conjunto de DMs calculado caracteriza bien las estructuras químicas que se están analizando, cuando en realidad puede que esto no suceda. Estas limitaciones se deben principalmente a que dichas herramientas limitan el número de DMs que calculan, restringiendo el dominio de los parámetros en los que se definen los algoritmos que calculan los DMs, parámetros que definen el Espacio de Configuración de Descriptores (DCS por sus siglas en inglés). En este trabajo se propone relajar estas restricciones en un enfoque DCS abierto, de manera que se pueda considerar inicialmente un universo más amplio de DMs y que estos caractericen de manera adecuada las estructuras a modelar. La generación de DMs se aborda entonces como un problema de optimización multicriterio, y para darle solución, dos algoritmos evolutivos son propuestos. Estos algoritmos incluyen conceptos de coevolución cooperativa para medir la sinergia entre descriptores moleculares ...

Currently, it is estimated that more than 10 million vertebrates are used per year for toxicological studies. Numerous regulatory agencies are actively advocating for the development of alternative methods to avoid unnecessary experimentation on animals. Among the existing alternatives in silico studies, especially Quantitative Structure Activity Relationships (QSAR) methods, stands out as one ofthe most widely used approaches. QSAR Methods are based on the premise that molecules with similar structures presents similar activities, which makes it possible to predict the activity of new compounds based on structurally similar compounds, for which their activity has been defined experimentally. Studies have demonstrated that the selection of the “optimal” set of molecular descriptors (MDs) is more important to build a robust QSAR models than the choice of the learning algorithm. Nowadays, the molecular descriptors (MD) used for QSAR modeling are calculated using computational tools that do not consider whether they accurately characterize the activity to be modeled and the compounds being analyzed. We demonstrate here that this approach may miss relevant information by assuming that the initial universe of MDs codifies, when it does not, all relevant aspects for the respective learning task. We argue that the limitation is mainly because of the constrained intervals of the parameters used in the algorithms that compute the MDs, parameters that define the Descriptor Configuration Space (DCS). We propose to relax these constraints in an open CDS approach, so that a larger universe of MDs can initially be considered, and these descriptors can adequately characterize the structures to be modeled. We model the MD generation as a multicriteria optimization problem, and two genetic algorithms-based approaches are proposed to solve it. These algorithms include cooperative-coevolutionary concepts to consider the synergism between theoretically different MDs during the evolutionary process. As a novel component, the individual fitness function is computed by aggregating four criteria via the Choquet Integral using a fuzzy non-additive measure. Experimental outcomes on benchmarking chemical datasets show that models created from an “optimized” sets of MDs present greater probability to achieve better performances than models created from sets of MDs obtained without optimizing their DCSs. Therefore, it can be concluded that the proposed algorithms are more suitable ..

algoritmos genéticos, descriptores moleculares QuBiLS-MAS, QSAR, DILI, cooperación coevolutiva genetics algorithms, QuBiLS-MAS molecular descriptors, QSAR, DILI, cooperativecoevolutionary algorithms INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES DISEÑO CON AYUDA DE ORDENADOR DISEÑO CON AYUDA DE ORDENADOR

Morphological Alterations in Human Skeletal Muscle Cells Exposed to di-(2-Ethylhexyl) Phthalate (dehp) in Primary Cell Culture Conditions

Alteraciones Morfológicas en Células Musculares Esqueléticas Humanas Expuestas a Ftalato de di-(2-etilhexilo) (dehp) en Condiciones de Cultivo Celular Primario

Pablo Hernández Almaraz ORLANDO LUGO LUGO Ramón Gaxiola Robles OSCAR KURT BITZER QUINTERO Luis Javier Ramírez Jirano Elizabeth Brassea Pérez TANIA ZENTENO SAVIN (2022, [Artículo])

"Di-(2-ethylhexyl) phthalate (DEHP) is among the most common plasticizer additives that humans are in contact with daily. DEHP can be released from plastic and enter the human body, whereby it is metabolized and transformed into oxidative hydrophilic molecules. Clinical follow-ups in patients exposed to this phthalate and investigations in cultures of several cell types have provided information on its effects. For example, it is associated with inhibition of diploid human cell development and morphological changes in cultured germ cells. Although skeletal muscle represents around 50 % of the human body mass, knowledge about the effects of DEHP on this tissue is poor. Cultured skeletal muscle cells were exposed to DEHP (1 mM) for 13 days with the aim of exploring and evaluating some of the potential morphological effects. Three culture development parameters and nine cell characteristics were monitored during the bioassay. At 13 days, growth area, cell viability, and concentration of total proteins were lower in DEHP exposed than in control cells. Cell width and area, as well as the diameter of the nucleus and nucleolus, were greater in exposed cells than in control cells. These are interpreted as signs of cytotoxicity and suggest potential adverse effects on the development of skeletal muscle cells from DEHP exposure, as reported for other cell types."

Emerging pollutants, Morphometry, Phthalates, Plasticizers, Toxicity MEDICINA Y CIENCIAS DE LA SALUD CIENCIAS MÉDICAS BIOLOGÍA HUMANA FISIOLOGÍA DEL MÚSCULO FISIOLOGÍA DEL MÚSCULO