terclim by ICS banner
IVES 9 IVES Conference Series 9 Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Abstract

Genetic variants known to produce single residue missense mutations have been associated with phenotypic traits of commercial interest in grapevine. This is the case of the K284N substitution in VviDXS1 associated with muscat aroma, or the R197L in VviAGL11 causing stenospermocarpic seedless grapes. The impact of such mutations on protein structure, stability, dynamics, interactions, or functional mechanism can be studied by computational methods, including our pyDock scoring, previously developed. For this, knowledge on the 3D structure of the protein and its complexes with other proteins and biomolecules is required, but such knowledge is not available for virtually none of the proteins and complexes in grapevine. Fortunately, the possibility of modeling proteins and complex structures with Artificial Intelligence (AI)-based methods like AlphaFold2 and AlphaFold2-Multimer will facilitate the application of this approach to proteins and complexes without available structure. Moreover, we are developing new methods based on AI to combine AlphaFold models, molecular dynamics (MD), pyDock energy scoring, and CCharPPI descriptors to predict the impact of protein mutations at the molecular level. As a case study, we have modelled the impact of the R197L seedlessness-associated substitution in VviAGL11. This protein is a homo-dimeric transcription factor that interacts with VviMADS4 dimeric protein to form a functional hetero-tetramer. Structural modeling of this complex provides insights into the functional mechanism of this protein and the role of the mentioned mutation. This protein modeling approach could be extended for grapevine mutation analysis at the genomic level.

DOI:

Publication date: June 14, 2024

Issue: Open GPB 2024

Type: Poster

Authors

Luis Ángel Rodríguez-Lumbreras1, Víctor Monteagudo1, Pablo Carbonell-Bejerano1, Fabian Glaser2, Juan Fernández-Recio1*

1 Instituto de Ciencias de la Vid y del Vino (ICVV), CSIC-UR-Gobierno de La Rioja, Spain
2 Technion Institute of Technology, Israel

Contact the author*

Keywords

AI-based modeling, Seedless grapes, Protein-protein interactions, Mutation impact analysis, Protein structure

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

Grapevine xylem embolism resistance spectrum reveals which varieties have a lower mortality risk in a future dry climate

Wine growing regions have recently faced intense and frequent droughts that have led to substantial economical losses, and the maintenance of grapevine productivity under warmer and drier climate will rely notably on planting drought-resistant cultivars. Given that plant growth and yield depend on water transport efficiency and maintenance of photosynthesis, thus on the preservation of the vascular system integrity during drought, a better understanding of drought-related hydraulic traits that have a significant impact on physiological processes is urgently needed. We have worked towards this end by assessing vulnerability to xylem embolism in 30 grapevine commercial varieties encompassing red and white Vitis vinifera varieties, hybrid varieties characterized by a polygenic resistance for powdery and downy mildew, and commonly used rootstocks. These analyses further allowed a global assessment of wine regions with respect to their varietal diversity and resulting vulnerability to stem embolism. Hybrid cultivars displayed the highest vulnerability to embolism, while rootstocks showed the greatest resistance. Significant variability also arose among Vitis vinifera varieties, with Ψ12 and Ψ50 values ranging from -0.4 to -2.7 MPa and from -1.8 to -3.4 MPa, respectively. Cabernet franc, Chardonnay and Ugni blanc featured among the most vulnerable varieties while Pinot noir, Merlot and Cabernet Sauvignon ranked among the most resistant. In consequence, wine regions bearing a significant proportion of vulnerable varieties, such as Poitou-Charentes, France and Marlborough, New Zealand, turned out to be at greater risk under drought. These results highlight that grapevine varieties may not respond equally to warmer and drier conditions, outlining the importance to consider hydraulic traits associated with plant drought tolerance into breeding programmes and modeling simulations of grapevine yield maintenance under severe drought. They finally represent a step forward to advise the wine industry about which varieties and regions would have the lowest risk of drought-induced mortality under climate change.

Impact of changing climatic factors on physiological and vegetative growth

Scientific information on grapevine response to predicted levels of climate parameters is scarce and not sufficient to properly position the Wine Industry for the future. It is critical that the combined effects of increased temperature and CO2 on grapevines should be examined, without omitting the important link to soil water conditions. The purpose of this study is to quantify the effects of envisioned changes in climatic parameters on the functioning and growth of young grafted grapevines under controlled conditions, simulating expected future climate changes. Scientific knowledge of precisely how the newly-planted grapevine will react morphologically, anatomically and physiologically (at leaf, root and whole plant level) to the expected changes in important climatic parameters will enable producers to make better-informed decisions regarding terroir, cultivar and rootstock choices as well as the adaptation of current cultivation practices.

Acceptability of canned wines: effect of the level of involvement of consumers and type of wine

In recent years there has been a growing demand for alternative packaging designs in the food industry focused on diminishing the carbon footprint. Despite the environmental advantages of cans versus bottles, the traditional environment of wine has hindered the establishment of less contaminant containers. In this context, the objective of this study was to understand and generate knowledge about consumers´ perception of canned wines in comparison to bottled wines.

Investigating the Ancient Egyptian wines: The wine jars database

In Ancient Egypt, wine was a luxury product consumed mainly by the upper classes and the royal family and offered to gods in daily religious rituals in the temples.
Since the Predynastic (4000-3100 BC) period, wine jars were placed in tombs as funerary offerings. From the Old Kingdom (2680-2160 BC) to the Greco-Roman (332 BC-395 AD) period, viticulture and winemaking scenes were depicted on the private tombs’ walls. During the New Kingdom (1539-1075 BC), wine jars were inscribed to indicate: vintage year, product, quality, provenance, property and winemaker’s name and title.

Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile 

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.