Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Proteome Regulation during Olea europaea Fruit Development

Widespread in the Mediterranean basin, Olea europaea trees are gaining worldwide popularity for the nutritional and cancer-protective properties of the oil, mechanically extracted from ripe fruits. Fruit development is a physiological process with remarkable impact on the modulation of the biosynthesis of compounds affecting the quality of the drupes as well as the final composition of the olive oil. Proteomics offers the possibility to dig deeper into the major changes during fruit development, including the important phase of ripening, and to classify temporal patterns of protein accumulation occurring during these complex physiological processes.In this work, we started monitoring the proteome variations associated with olive fruit development by using comparative proteomics coupled to mass spectrometry. Proteins extracted from drupes at three different developmental stages were separated on 2-DE and subjected to image analysis. 247 protein spots were revealed as differentially accumulated. Proteins were identified from a total of 121 spots and discussed in relation to olive drupe metabolic changes occurring during fruit development. In order to evaluate if changes observed at the protein level were consistent with changes of mRNAs, proteomic data produced in the present work were compared with transcriptomic data elaborated during previous studies.This study identifies a number of proteins responsible for quality traits of cv. Coratina, with particular regard to proteins associated to the metabolism of fatty acids, phenolic and aroma compounds. Proteins involved in fruit photosynthesis have been also identified and their pivotal contribution in oleogenesis has been discussed. To date, this study represents the first characterization of the olive fruit proteome during development, providing new insights into fruit metabolism and oil accumulation process

SAM levels, gene expression of SAM synthetase, methionine synthase and ACC oxidase, and ethylene emission from N. suaveolens flowers

S′adenosyl-l-methionine (SAM) is a ubiquitous methyl donor and a precursor in the biosynthesis of ethylene, polyamines, biotin, and nicotianamine in plants. Only limited information is available regarding its synthesis (SAM cycle) and its concentrations in plant tissues. The SAM concentrations in flowers of Nicotiana suaveolens were determined during day/night cycles and found to fluctuate rhythmically between 10 and 50 nmol g−1 fresh weight. Troughs of SAM levels were measured in the evening and night, which corresponds to the time when the major floral scent compound, methyl benzoate, is synthesized by a SAM dependent methyltransferase (NsBSMT) and when this enzyme possesses its highest activity. The SAM synthetase (NsSAMS1) and methionine synthase (NsMS1) are enzymes, among others, which are involved in the synthesis and regeneration of SAM. Respective genes were isolated from a N. suaveolens petal cDNA library. Transcript accumulation patterns of both SAM regenerating enzymes matched perfectly those of the bifunctional NsBSMT; maximum mRNA accumulations of NsMS1 and NsSAMS1 were attained in the evening. Ethylene, which is synthesized from SAM, reached only low levels of 1–2 ppbv in N. suaveolens flowers. It is emitted in a burst at the end of the life span of the flowers, which correlates with the increased expression of the 1-aminocyclopropane-1-carboxylate oxidase (NsACO)

Noise regulation by quorum sensing in low mRNA copy number systems

<p>Abstract</p> <p>Background</p> <p>Cells must face the ubiquitous presence of noise at the level of signaling molecules. The latter constitutes a major challenge for the regulation of cellular functions including communication processes. In the context of prokaryotic communication, the so-called quorum sensing (QS) mechanism relies on small diffusive molecules that are produced and detected by cells. This poses the intriguing question of how bacteria cope with the fluctuations for setting up a reliable information exchange.</p> <p>Results</p> <p>We present a stochastic model of gene expression that accounts for the main biochemical processes that describe the QS mechanism close to its activation threshold. Within that framework we study, both numerically and analytically, the role that diffusion plays in the regulation of the dynamics and the fluctuations of signaling molecules. In addition, we unveil the contribution of different sources of noise, intrinsic and transcriptional, in the QS mechanism.</p> <p>Conclusions</p> <p>The interplay between noisy sources and the communication process produces a repertoire of dynamics that depends on the diffusion rate. Importantly, the total noise shows a non-monotonic behavior as a function of the diffusion rate. QS systems seems to avoid values of the diffusion that maximize the total noise. These results point towards the direction that bacteria have adapted their communication mechanisms in order to improve the signal-to-noise ratio.</p

An Induced Mutation in Tomato eIF4E Leads to Immunity to Two Potyviruses

BACKGROUND: The characterization of natural recessive resistance genes and Arabidopsis virus-resistant mutants have implicated translation initiation factors of the eIF4E and eIF4G families as susceptibility factors required for virus infection and resistance function. METHODOLOGY/PRINCIPAL FINDINGS: To investigate further the role of translation initiation factors in virus resistance we set up a TILLING platform in tomato, cloned genes encoding for translation initiation factors eIF4E and eIF4G and screened for induced mutations that lead to virus resistance. A splicing mutant of the eukaryotic translation initiation factor, S.l_eIF4E1 G1485A, was identified and characterized with respect to cap binding activity and resistance spectrum. Molecular analysis of the transcript of the mutant form showed that both the second and the third exons were miss-spliced, leading to a truncated mRNA. The resulting truncated eIF4E1 protein is also impaired in cap-binding activity. The mutant line had no growth defect, likely because of functional redundancy with others eIF4E isoforms. When infected with different potyviruses, the mutant line was immune to two strains of Potato virus Y and Pepper mottle virus and susceptible to Tobacco each virus. CONCLUSIONS/SIGNIFICANCE: Mutation analysis of translation initiation factors shows that translation initiation factors of the eIF4E family are determinants of plant susceptibility to RNA viruses and viruses have adopted strategies to use different isoforms. This work also demonstrates the effectiveness of TILLING as a reverse genetics tool to improve crop species. We have also developed a complete tool that can be used for both forward and reverse genetics in tomato, for both basic science and crop improvement. By opening it to the community, we hope to fulfill the expectations of both crop breeders and scientists who are using tomato as their model of study

Engineering Melon Plants with Improved Fruit Shelf Life Using the TILLING Approach

Background: Fruit ripening and softening are key traits that have an effect on food supply, fruit nutritional value and consequently, human health. Since ethylene induces ripening of climacteric fruit, it is one of the main targets to control fruit over ripening that leads to fruit softening and deterioration. The characterization of the ethylene pathway in Arabidopsis and tomato identified key genes that control fruit ripening. [br/] Methodology/Principal Findings: To engineer melon fruit with improved shelf-life, we conducted a translational research experiment. We set up a TILLING platform in a monoecious and climacteric melon line, cloned genes that control ethylene production and screened for induced mutations that lead to fruits with enhanced shelf life. Two missense mutations, L124F and G194D, of the ethylene biosynthetic enzyme, ACC oxidase 1, were identified and the mutant plants were characterized with respect to fruit maturation. The L124F mutation is a conservative mutation occurring away from the enzyme active site and thus was predicted to not affect ethylene production and thus fruit ripening. In contrast, G194D modification occurs in a highly conserved amino acid position predicted, by crystallographic analysis, to affect the enzymatic activity. Phenotypic analysis of the G194D mutant fruit showed complete delayed ripening and yellowing with improved shelf life and, as predicted, the L124F mutation did not have an effect. [br/] Conclusions/Significance: We constructed a mutant collection of 4023 melon M2 families. Based on the TILLING of 11 genes, we calculated the overall mutation rate of one mutation every 573 kb and identified 8 alleles per tilled kilobase. We also identified a TILLING mutant with enhanced fruit shelf life. This work demonstrates the effectiveness of TILLING as a reverse genetics tool to improve crop species. As cucurbits are model species in different areas of plant biology, we anticipate that the developed tool will be widely exploited by the scientific community

Q&A: How do plants respond to ethylene and what is its importance?

Ethylene gas is a major plant hormone that influences diverse processes in plant growth, development and stress responses throughout the plant life cycle. Responses to ethylene, such as fruit ripening, are significant to agriculture. The core molecular elements of the ethylene-signaling pathway have been uncovered, revealing a unique pathway that is negatively regulated. Practical applications of this knowledge can lead to substantial improvements in agriculture.https://doi.org/10.1186/s12915-016-0230-