Alternative methods, including green synthetic approaches for the preparation of various types of nanoparticles are important to maintain sustainable development. Extracellular or intracellular extracts of fungi are perfect candidates for the synthesis of metal nanoparticles due to the scalability and cost efficiency of fungal growth even on industrial scale. There are several methods and techniques that use fungi-originated fractions for synthesis of gold nanoparticles. However, there is less knowledge about the drawbacks and limitations of these techniques. Additionally, identification of components that play key roles in the synthesis is challenging. Here we show and compare the results of three different approaches for the synthesis of gold nanoparticles using either the extracellular fraction, the autolysate of the fungi or the intracellular fraction of 29 thermophilic fungi. We observed the formation of nanoparticles with different sizes (ranging between 6 nm and 40 nm) and size distributions (with standard deviations ranging between 30% and 70%) depending on the fungi strain and experimental conditions. We found by using ultracentrifugal filtration technique that the size of reducing agents is less than 3 kDa and the size of molecules that can efficiently stabilize nanoparticles is greater than 3 kDa.

Pattern formation is a frequent phenomenon in physics, chemistry, biology and material science. Bottom-up pattern formation occurs usually in the interaction of the transport phenomena of chemical species with their chemical reaction. The oldest pattern formation is the Liesegang phenomenon (or periodic precipitation), which was discovered and described by Raphael Edward Liesegang in 1896, who was a German chemist and photographer, and he was born 150 years ago. The purpose of this review is to provide a comprehensive overview of this type of pattern formation. Liesegang banding occurs due to the coupling of the diffusion process of the reagents to their chemical reactions in solid hydrogels. We will discuss several phenomena observed and discovered in the past century including reverse patterns, precipitation patterns with dissolution (due to complex formation), helicoidal patterns, and precipitation waves. Additionally, we will review all existing models of the Liesegang phenomenon including pre- and post-nucleation scenarios. Finally, we will highlight several applications of periodic precipitation.

Self-division is one of the most common phenomena in living systems and one of the most important properties of life driven by internal mechanisms of cells. Design and engineering of synthetic cells from abiotic components can recreate a life-like function thus contributing to the understanding of the origin of life. Existing methods to induce the self-division of vesicles require external and non-autonomous triggers (temperature change and the addition of membrane precursors). Here we show that pH-responsive giant unilamellar vesicles on the micrometer scale can undergo self-division triggered by an internal autonomous chemical stimulus driven by an enzymatic (urea–urease) reaction coupled to a cross-membrane transport of the substrate, urea. The bilayer of the artificial cells is composed of a mixture of phospholipids (POPC, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine) and oleic acid molecules. The enzymatic reaction increases the pH in the lumen of the vesicles, which concomitantly changes the protonation state of the oleic acid in the inner leaflet of the bilayer causing the removal of the membrane building blocks into the lumen of the vesicles thus decreasing the inner membrane area with respect to the outer one. This process coupled to the osmotic stress (responsible for the volume loss of the vesicles) leads to the division of a mother vesicle into two smaller daughter vesicles. These two processes must act in synergy; none of them alone can induce the division. Overall, our self-dividing system represents a step forward in the design and engineering of a complex autonomous model of synthetic cells.

Helical and helicoidal precipitation patterns emerging in the wake of reaction-diffusion fronts are studied. In our experiments, these chiral structures arise with well-defined probabilities ${P}_{\mathrm{H}}$ controlled by conditions such as, e.g., the initial concentration of the reagents. We develop a model which describes the observed experimental trends. The results suggest that ${P}_{\mathrm{H}}$ is determined by a delicate interplay among the time and length scales related to the front and to the unstable precipitation modes and, furthermore, that the noise amplitude also plays a quantifiable role.