Biology subjects

Franca, L.

Publications and source records attributed to Franca, L..

4 recordsLinked to original sources

bioRxiv2024

Cycling reduces the entropy of neuronal activity in the human adult cortex

Electroencephalogram (EEG) data is often analyzed from a Brain Complexity (BC) perspective, having successfully been applied to study the brain in both health and disease. In this study, we employed recurrence entropy to quantify BC associated with the neurophysiology of movement by comparing BC in both resting state and cycling movement. We measured EEG in 24 healthy adults, and placed the electrodes on occipital, parietal, temporal and frontal sites, on both the right and left sides. EEG measurements were performed for cycling and resting states and for eyes closed and open. We then computed recurrence entropy for the acquired EEG series. Our results show that open eyes show larger entropy compared to closed eyes; the entropy is also larger for resting state, compared to cycling state for all analyzed brain regions. The decrease in neuronal complexity measured by the recurrence entropy could explain the neural mechanisms involved in how the cycling movements suppress the freezing of gate in patients with Parkinsons disease due to the constant sensory feedback caused by cycling that is associated with entropy reduction.

neuroscience↗

bioRxiv2021

Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies

Multiple studies have demonstrated less favourable childhood outcomes in infants born in early term (37-38 weeks gestation) compared to those born at full term (40-41 weeks gestation). While this could be due to higher perinatal morbidity, gestational age at birth may also have a direct effect on the brain and subsequent neurodevelopment in term-born babies. Here we characterise structural brain correlates of gestational age at birth in healthy term-born neonates and their relationship to later neurodevelopmental outcome. We used T2 and diffusion weighted Magnetic Resonance Images acquired in the neonatal period from a cohort (n=454) of healthy babies born at term age (>37 weeks gestation) and scanned between 1 and 41 days after birth. Images were analysed using tensor based morphometry (TBM) and tract based spatial statistics (TBSS). Neurodevelopment was subsequently assessed at age 18 months using the Bayley-III Scales of Infant and Toddler Development, and the effects of gestational age at birth and related neuroimaging findings on outcome were analysed with linear regression. Infants born earlier had areas of higher relative ventricular volume, and lower relative brain volume in the basal ganglia, cerebellum and brainstem. Earlier birth was also associated with lower fractional anisotropy, higher mean, axial and radial diffusivity in major white matter tracts. Gestational age at birth was positively associated with all Bayley-III subscales at age 18 months. Linear regression models predicting outcome from gestational age at birth were significantly improved by adding neuroimaging features associated with gestational age at birth. This work adds to the growing body of evidence of the impact of early term birth and highlights the importance of considering the effect of gestational age at birth in future neuroimaging studies including term-born babies.

neuroscience↗

bioRxiv2020

Production of moth sex pheromones for pest control by yeast fermentation

The use of insect sex pheromones is an alternative technology for pest control in agriculture and forestry, which, in contrast to insecticides, does not have adverse effects on human health or environment and is efficient also against insecticide-resistant insect populations.1,2 Due to the high cost of chemically synthesized pheromones, mating disruption applications are currently primarily targeting higher value crops, such as fruits.3 Here we demonstrate a biotechnological method for the production of pheromones of economically important moth pests using engineered yeast cell factories. Biosynthetic pathways towards several pheromones or their precursors were reconstructed in the oleaginous yeast Yarrowia lipolytica, which was further metabolically engineered for improved pheromone biosynthesis by decreasing fatty alcohol degradation and downregulating storage lipid accumulation. The sex pheromone of the cotton bollworm Helicoverpa armigera was produced by oxidation of fermented fatty alcohols into corresponding aldehydes. The resulting pheromone was just as efficient and specific for trapping of H. armigera male moths in cotton fields in Greece as a synthetic pheromone mixture. We further demonstrated the production of the main pheromone component of the fall armyworm Spodoptera frugiperda. Our work describes a biotech platform for the production of commercially relevant titres of moth pheromones for pest control by yeast fermentation. Significance statementAgriculture largely relies on insecticides and genetically modified crops for pest control, however alternative solutions are required due to emerging resistance, toxicity and regulatory issues, and consumer preferences. Mating disruption with sex pheromones that act by preventing insect reproduction is considered the most promising and scalable alternative to insecticides. This method is highly efficient and safe for human health and environment. The likelihood of insect resistance development is very low and can be handled by adjusting the pheromone composition. The high cost of chemically synthesized pheromones is the major barrier for the wider adoption of pheromones. A novel method based on yeast fermentation enables the production of insect sex pheromones as a lower cost from renewable feedstocks.

bioengineering↗

bioRxiv2019

A metabolic reconstruction of Lactobacillus reuteri JCM 1112 and analysis of its potential as a cell factory

BackgroundLactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data.\n\nResultsA genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden-Meyerhof-Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden-Meyerhof-Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies.\n\nConclusionWe have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.

systems biology↗