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Biology subjects

Milano, F.

Publications and source records attributed to Milano, F..

3 recordsLinked to original sources

VASP phase separation with priming proteins of fast endophilin mediated endocytosis modulates actin polymerization

Actin polymerization is essential in several clathrin-independent endocytic pathways including fast endophilin mediated endocytosis (FEME), however the actin machinery involved in FEME has been elusive. Here, we show that the actin polymerase VASP colocalizes and interacts directly with the FEME priming complex. We identify Endophilin as a VASP binding partner and establish novel non-canonical interactions between Endophilin and VASP. The major FEME regulators Endophilin and Lamellipodin interact multivalently with VASP to form liquid-like condensates both in solution and on lipid membranes that localize actin polymerization with the extent of actin polymerized regulated by multivalent Endophilin-Lamellipodin interactions. We identify a novel function for Endophilin condensates in bundling actin filaments and show that Endophilin directly binds filamentous actin. Our findings support a model that explains the connection between local actin polymerization and dynamic formation and dissolution of endocytic priming patches in FEME.

biochemistry↗

SiCoDEA: a simple, fast and complete app for analyzing the effect of individual drugs and their combinations

The administration of combinations of drugs is a method widely used in the treatment of different pathologies as it can lead to an increase in the therapeutic effect and a reduction in the dose compared to the administration of the single drugs. For these reasons, it is of interest to study combinations of drugs and in particular to determine whether a specific combination has a synergistic, antagonistic or additive effect, i.e greater, less than or equal to the effect expected by the sum of the individual drugs. For this purpose, various mathematical models have been developed, which use different methods to evaluate the synergy of a combination of drugs. Most of these methods are based on the Loewe Additivity Principle (Loewe et al., 1953), which has its key step in choosing the model used for predicting the effect of individual drugs. Creating a model for this purpose and calculating its parameters, however, requires a certain level of mathematical and programming knowledge or the use of commercial software. For this purpose, therefore, we have developed an open access and easy to use app that allows to explore different models and to choose the most fitting for the specific experimental data: SiCoDEA (Single and Combined Drug Effect Analysis, https://sicodea.shinyapps.io/shiny/). The data used to test SiCoDEA comes from cell line samples treated with different drug combinations and analyzed through metabolic or viability assays. SiCoDEA is developed through a Shiny interactive and easy-to-use interface (R based). There are five models taken into consideration for the analysis of single drugs and the calculation of combination index. The first is one of the most used, that of the median-effect; while the others are different forms of the log-logistic equation, with two, three and four parameters. The purpose of SiCoDEA is, on the one hand, to provide an easy-to-use tool for analyzing drug combination data and, on the other hand, also to have a view of the various steps and to offer different results based on the model chosen. An important prerequisite in analyzing drug combinations is in fact the dose-response curve calculated for individual drugs. For this purpose, SiCoDEA allows you to view the plots of the individual drugs both to evaluate the distribution of the calculated points and therefore identify any outliers, and to view the curve of the different models taken into consideration and evaluate which one best fits the data. A table showing all the R2 values for the five different models is created with the curve plot. In addition to the type of model, it is also possible to choose between two different normalization methods, one based on the maximum or minimum value and the other on the value calculated at drug concentrations equal to zero. For the chosen options, a plot is then created that shows the trend of the combination index for the different drug combinations and consequently whether it is synergy, antagonism or additivity. Finally, it is possible to export the results in single png files or in a summary report in pdf. SiCoDEA is an open-source app among the most complete and offers more functions even than the famous CompuSyn (Chou et al., 2010), as it allows you to analyze drug curves with different models, rather than just one, and it also allows the analysis of single drug curves.

bioinformatics↗

Light-driven ATP production promotes mRNA biosynthesis inside hybrid multi-compartment artificial protocells

The construction of energetically autonomous artificial protocells is one of the most urgent and challenging requirements in bottom-up synthetic biology. Here we show a hybrid multi-compartment approach to build Artificial Simplified-Autotroph Protocells (ASAPs) in an effective manner. Chromatophores obtained from Rhodobacter sphaeroides accomplish the photophosphorylation of ADP to ATP functioning as nanosized photosynthetic organellae when encapsulated inside artificial giant phospholipid vesicles. Under continuous illumination chromatophores produce ATP that in turn sustains the transcription of a DNA gene by T7 RNA polymerase inside ASAPs. Cryo-EM and time-resolved spectroscopy were used for characterizing the chromatophore morphology and the orientation of the photophosphorylation proteins, which allow high ATP production rates (up to ~100 ATP/s per ATP synthase). mRNA biosynthesis inside individual vesicles has been determined by confocal microscopy. The hybrid multi-compartment approach here proposed appears at the same time convenient and effective, and thus very promising for the construction of full-fledged artificial protocells.

synthetic biology↗