Fine-tuning tomato agronomic properties by computational genome redesign

Analysis of the Implementation of the Single Minute Exchange of Die Methodology in an Agroindustry through Action Research

This work aims to implement and analyze the effect of the Single Minute Exchange of Die (SMED) implementation in the bean packaging operation in a company in east Minas Gerais, Brazil. Design/Methodology/Approach: The research methodology used was action research. Two cycles of action research were conducted; the first to carry out phase one of SMED, and the second to execute phases two and three. Originality/Research gap: There are few studies on the application of Lean Manufacturing tools in agroindustry. Some works present case studies, mainly in the food supply chain aiming to fill this gap. Regarding SMED applied in agribusiness, no work was found. Key statistical results: The implementation of this methodology allowed the reduction of setup time by around 58%, the distance travelled by operators in the process by approximately 50%, in addition to gains in a production capacity of 14%. Practical Implications: It is concluded that the application of the methodology caused an increase in the company’s productivity, as it was possible to obtain gains in productive capacity without changing the amount of hours worked or the number of employees involved in the production process. Limitations of the investigation: This methodology was applied only once and the challenges encountered were not documented.

Use of Natural Diversity and Biotechnology to Increase the Quality and Nutritional Content of Tomato and Grape

Improving fruit quality has become a major goal in plant breeding. Direct approaches to tackling fruit quality traits specifically linked to consumer preferences and environmental friendliness, such as improved flavor, nutraceutical compounds, and sustainability, have slowly been added to a breeder priority list that already includes traits like productivity, efficiency, and, especially, pest and disease control. Breeders already use molecular genetic tools to improve fruit quality although most advances have been made in producer and industrial quality standards. Furthermore, progress has largely been limited to simple agronomic traits easy-to-observe, whereas the vast majority of quality attributes, specifically those relating to flavor and nutrition, are complex and have mostly been neglected. Fortunately, wild germplasm, which is used for resistance against/tolerance of environmental stresses (including pathogens), is still available and harbors significant genetic variation for taste and health-promoting traits. Similarly, heirloom/traditional varieties could be used to identify which genes contribute to flavor and health quality and, at the same time, serve as a good source of the best alleles for organoleptic quality improvement. Grape (Vitis vinifera L.) and tomato (Solanum lycopersicum L.) produce fleshy, berry-type fruits, among the most consumed in the world. Both have undergone important domestication and selection processes, that have dramatically reduced their genetic variability, and strongly standardized fruit traits. Moreover, more and more consumers are asking for sustainable production, incompatible with the wide range of chemical inputs. In the present paper, we review the genetic resources available to tomato/grape breeders, and the recent technological progresses that facilitate the identification of genes/alleles of interest within the natural or generated variability gene pool. These technologies include omics, high-throughput phenotyping/phenomics, and biotech approaches. Our review also covers a range of technologies used to transfer to tomato and grape those alleles considered of interest for fruit quality. These include traditional breeding, TILLING (Targeting Induced Local Lesions in Genomes), genetic engineering, or NPBT (New Plant Breeding Technologies). Altogether, the combined exploitation of genetic variability and innovative biotechnological tools may facilitate breeders to improve fruit quality tacking more into account the consumer standards and the needs to move forward into more sustainable farming practices.

An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli

Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. Here, we present an integrative modeling methodology that unifies under a common framework the various biological processes and their interactions across multiple layers. We trained this methodology on an extensive normalized compendium for the gram-negative bacterium Escherichia coli, which incorporates gene expression data for genetic and environmental perturbations, transcriptional regulation, signal transduction, and metabolic pathways, as well as growth measurements. Comparison with measured growth and high-throughput data demonstrates the enhanced ability of the integrative model to predict phenotypic outcomes in various environmental and genetic conditions, even in cases where their underlying functions are under-represented in the training set. This work paves the way toward integrative techniques that extract knowledge from a variety of biological data to achieve more than the sum of their parts in the context of prediction, analysis, and redesign of biological systems.

Plant science and agricultural productivity: why are we hitting the yield ceiling?

Trends in conventional plant breeding and in biotechnology research are analyzed with a focus on production and productivity of individual organisms. Our growing understanding of the productive/adaptive potential of (crop) plants is a prerequisite to increasing this potential and also its expression under environmental constraints. This review concentrates on growth rate, ribosome activity, and photosynthetic rate to link these key cellular processes to plant productivity. Examples of how they may be integrated in heterosis, organ growth control, and responses to abiotic stresses are presented. The yield components in rice are presented as a model. The ultimate goal of research programs, that concentrate on yield and productivity and integrating the panoply of systems biology tools, is to achieve "low input, high output" agriculture, i.e. shifting from a conventional "productivist" agriculture to an efficient sustainable agriculture. This is of critical, strategic importance, because the extent to which we, both locally and globally, secure and manage the long-term productive potential of plant resources will determine the future of humanity.

An integrative "omics" approach identifies new candidate genes to impact aroma volatiles in peach fruit

BACKGROUND

Ever since the recent completion of the peach genome, the focus of genetic research in this area has turned to the identification of genes related to important traits, such as fruit aroma volatiles. Of the over 100 volatile compounds described in peach, lactones most likely have the strongest effect on fruit aroma, while esters, terpenoids, and aldehydes have minor, yet significant effects. The identification of key genes underlying the production of aroma compounds is of interest for any fruit-quality improvement strategy.

RESULTS

Volatile (52 compounds) and gene expression (4348 genes) levels were profiled in peach fruit from a maturity time-course series belonging to two peach genotypes that showed considerable differences in maturation characteristics and postharvest ripening. This data set was analyzed by complementary correlation-based approaches to discover the genes related to the main aroma-contributing compounds: lactones, esters, and phenolic volatiles, among others. As a case study, one of the candidate genes was cloned and expressed in yeast to show specificity as an ω-6 Oleate desaturase, which may be involved in the production of a precursor of lactones/esters.

CONCLUSIONS

Our approach revealed a set of genes (an alcohol acyl transferase, fatty acid desaturases, transcription factors, protein kinases, cytochromes, etc.) that are highly associated with peach fruit volatiles, and which could prove useful in breeding or for biotechnological purposes.

Systems biology and "omics" tools: a cooperation for next-generation mycorrhizal studies

Omics tools constitute a powerful means of describing the complexity of plants and soil-borne microorganisms. Next generation sequencing technologies, coupled with emerging systems biology approaches, seem promising to represent a new strategy in the study of plant-microbe interactions. Arbuscular mycorrhizal fungi (AMF) are ubiquitous symbionts of plant roots, that provide their host with many benefits. However, as obligate biotrophs, AMF show a genetic, cellular and physiological complexity that makes the study of their biology as well as their effective agronomical exploitation rather difficult. Here, we speculate that the increasing availability of omics data on mycorrhiza and of computational tools that allow systems biology approaches represents a step forward in the understanding of arbuscular mycorrhizal symbiosis. Furthermore, the application of this study-perspective to agriculturally relevant model plants, such as tomato and rice, will lead to a better in-field exploitation of this beneficial symbiosis in the frame of low-input agriculture.

Computational design of host transcription-factors sets whose misregulation mimics the transcriptomic effect of viral infections

The molecular mechanisms underlying viral pathogenesis are yet poorly understood owed to the large number of factors involved and the complexity of their interactions. Could we identify a minimal set of host transcription factors (TF) whose misregulation would result in the transcriptional profile characteristic of infected cells in absence of the virus? How many of such sets exist? Are all orthogonal or share critical TFs involved in specific biological functions? We have developed a computational methodology that uses a quantitative model of the transcriptional regulatory network (TRN) of Arabidopsis thaliana to explore the landscape of all possible re-engineered TRNs whose transcriptomic profiles mimic those observed in infected plants. We found core sets containing between six and 34 TFs, depending on the virus, whose in silico knockout or overexpression in the TRN resulted in transcriptional profiles that minimally deviate from those observed in infected plants.