Genome introgressions drive evolution across the animal1 , plant 2 and fungal 3 kingdoms. Introgressions initiate from archaic admixtures followed by repeated backcrossing to one parental species. However, how introgressions arise in reproductively isolated species, such as yeasts 4 , has remained unclear. Here, we discovered a clonal descendant of the ancestral yeast hybrid that founded the extant S. cerevisiae Alpechin lineage 5 , which carries abundant S. paradoxus introgressions. We show that this clonal descendant, hereafter defined as "living ancestor", retained the ancestral genome structure of the first-generation hybrid with contiguous S. cerevisiae and S. paradoxus subgenomes. The ancestral first-generation hybrid underwent catastrophic genomic instability through more than a hundred mitotic recombination events, mainly manifesting as homozygous genome blocks generated by loss-of-heterozygosity. These homozygous sequence blocks rescue hybrid fertility by restoring meiotic recombination and are the direct origins of the introgressions present in the Alpechin lineage. We suggest a plausible route for introgression evolution through reconstruction of extinct stages and propose genome instability to allow hybrids to overcome reproductive isolation and enable introgressions to emerge.

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Wearable sensors are nowadays largely employed to assess physiological signals derived from the human body without representing a burden in terms of obtrusiveness. One of the most intriguing fields of application for such systems include the assessment of physiological responses to sensory stimuli. In this specific regard, it is not yet known which are the main psychophysiological drivers of olfactory-related pleasantness, as the current literature has demonstrated the relationship between odor familiarity and odor valence, but has not clarified the consequentiality between the two domains. Here, we enrolled a group of university students to whom olfactory training lasting 3 months was administered. Thanks to the analysis of electrocardiogram (ECG) and galvanic skin response (GSR) signals at the beginning and at the end of the training period, we observed different autonomic responses, with higher parasympathetically-mediated response at the end of the period with respect to the first evaluation. This possibly suggests that an increased familiarity to the proposed stimuli would lead to a higher tendency towards relaxation. Such results could suggest potential applications to other domains, including personalized treatments based on odors and foods in neuropsychiatric and eating disorders.

The encapsulation of transcription-translation (TX-TL) cell-free machinery inside lipid vesicles (liposomes) is a key element in synthetic cell technology. The PURE system is a TX-TL kit composed of well-characterized parts, whose concentrations are fine tunable, which works according to a modular architecture. For these reasons, the PURE system perfectly fulfils the requirements of synthetic biology and is widely used for constructing synthetic cells. In this work, we present a simplified mathematical model to simulate the PURE system operations. Based on Michaelis-Menten kinetics and differential equations, the model describes protein synthesis dynamics by using 9 chemical species, 6 reactions and 16 kinetic parameters. The model correctly predicts the time course for messenger RNA and protein production and allows quantitative predictions. By means of this model, it is possible to foresee how the PURE system species affect the mechanism of proteins synthesis and therefore help in understanding scenarios where the concentration of the PURE system components has been modified purposely or as a result of stochastic fluctuations (for example after random encapsulation inside vesicles). The model also makes the determination of response coefficients for all species involved in the TX-TL mechanism possible and allows for scrutiny on how chemical energy is consumed by the three PURE system modules (transcription, translation and aminoacylation).

BackgroundThe process of solutes entrapment during liposomes formation is interesting for the investigation of the relationship between the formation of compartments and the distribution of molecules inside them; a relevant issue in the studies of the origin of life. Theoretically, when no interactions are supposed among the chemical species to be entrapped, the entrapment is described by a standard Poisson process. But very recent experimental findings show that, for small liposomes (100 nm diameter), the distribution of entrapped molecules is best described by a power-law function. This is of a great importance, as the two random processes give rise to two completely different scenarios. Here we present an in silico stochastic simulation of the encapsulation of a cell-free molecular translation system (the PURE system), obtained following two different entrapment models: a pure Poisson process, and a power-law. The protein synthesis inside the liposomes has been studied in both cases, with the aim to highlight experimental observables that could be measured to assess which model gives a better representation of the real process.ResultsFirstly, a minimal model for in vitro protein synthesis, based on the PURE system molecular composition, has been formalized. Then, we have designed a reliable experimental simulation where stochastic factors affect the reaction course inside the compartment. To this end, 24 solutes, which represent the PURE system components, have been stochastically distributed among vesicles by following either a Poisson or a power-law distribution. The course of the protein synthesis within each vesicle has been consequently calculated, as a function of vesicle size. Our study can predict translation yield in a population of small liposomes down to the attoliter (10-18 L) range. Our results show that the efficiency of protein synthesis peaks at approximately 3·10-16 L (840 nm diam.) with a Poisson distribution of solutes, while a relative optimum is found at around 10-17 L (275 nm diam.) for the power-law statistics.ConclusionsOur simulation clearly shows that the wet-lab measurement of an effective protein synthesis at smaller volumes than 10-17 L would rule out, according to our models, a Poisson distribution of solutes.