A synthetic and systems biology approach for studying liposome extrusion

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Università degli studi di Pisa

Dipartimento di Biologia

Corso di Laurea Magistrale in Biotecnologie Molecolari e Industriali

A Synthetic and Systems Biology

Approach for studying Liposome

Extrusion

Anno Accademico 2013-2014 RELATORI:

PROF.ROBERTO MARANGONI

PROF PASQUALE STANO

CANDIDATO: FANTI ALESSIO

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Riassunto:

Le cellule minimali rappresentano il punto di incontro tra biologia sintetica e studi sull‟origine della vita. Basate su liposomi, sono strutture che mimano proprietà tipiche dei viventi (in quanto è possibile intrappolare nei liposomi componenti biochimici capaci di reazioni complesse). Risulta imperativo per lo sviluppo di tale concetto caratterizzare le interazioni tra membrana dei liposomi e soluti molecolari. In questo studio proponiamo un approccio innovativo all‟analisi delle interazioni liposoma-soluti: partendo da 4 popolazioni di GUVs (Giant Unilamellar Vesicles)contentente un soluto fluorescente diverso per peso molecolare e proprietà biochimiche.Abbiamo proceduto alla loro estrusione generando 4 popolazioni di VET (Vesicles by Extrusion Technique). Abbiamo caratterizzato la distribuzione delle dimensioni delle vescicole e le meccaniche di intrappolamento/redistribuzione dei soluti per ciascuna popolazione, sfruttando un modello in-silico dell‟intero processo per generare gli attesi a partire da diverse ipotesi sui meccanismi di generazione e di riempimento delle vescicole. le nostre conclusioni sono che l‟estrusione porta a una perdita netta di volume e di soluti rispetto alla GUV estrusa, e che il riempimento delle VET sembra essere guidato da un processo stocastico puro, che non fa emergere le anomalie di superconcentrazione descritte nelle vescicole ultra-piccole di formazione spontanea.

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Abstract:

Minimal cells represent a trait d’union between synthetic biology and origin-of-life studies. Based on liposomes, minimal cells are able to mime typical, and even complex, features of living organisms (as it is possible to equip liposomes with biomolecules capable of complex reactions). It is mandatory, to further develop the very concept of minimal cells, to better inquire interactions between liposomes and molecular solutes. In this study we propose a novel approach to solute entrapment analysis: we first generated 4 GUV (Giant Unilamellar Vesicles) populations, each containing a different fluorescent molecule, by varying their molecular mass and biochemical properties. By extruding GUV populations, we then produced 4 distinct VET populations: we characterized solutes entrapment distribution and size distributions for each population. In parallel with experimental procedures, we developed an in-silico model of the entire process: simulated data have been used in a reverse engineering approach to assess, among different hypotheses about solute partition during extrusion, which hypothesis turns out to be closest with experimental data. Our findings clearly show that during extrusion there is a large loss of volume and solutes. Moreover, the solutes entrapped in VET vesicles, differently from what reported in the literature for very small vesicles spontaneously formed, do not show any anomaly with respect to a pure random entrapment process.

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Introduction

Complexity represents one of the most striking characteristics of living organisms. The intricate network of metabolic pathways, elegantly linked one to another, and the structural architecture of cells shows a remarkable degree of complexity, which results even more astounding considering that each single element of living organisms is composed by simple chemicals. Such “elegant complexity” represents one of the most recurring topics in several cultural and scientific subjects, aiming to describe and characterize what we commonly define as “life”.

Figure 1: Properties of a Living Organism

The very definition of “life” changed along the time, evolving as our understanding of the world changed, following the increased possibility of observation and analysis brought by advances in technology. Modern definition of “life” is based upon biological systems: a living organism is defined by its properties of self-sustainment (represented by maintenance of homeostasis, presence of a metabolism and capability of growth) and reproduction (generation of other organisms that possess each property of the original organism); interaction with the environment (perception and response to stimuli) and adaptation to environment during generations (a process called evolution). Although definition of “life” is fairly immediate for complex, multicellular organisms, such definition blunders while considering biological entities such as viruses or bacteria, in a more fascinating way, while theorizing synthetic or computational models that could be considered as “living”.

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Page | 7 A different definition of “life” relies upon the concept of “autopoiesis” to express the notions of self-preservation, growth and metabolism previously used. The term autopoiesis was first introduced by Varela and Maturana (Maturana and Varela, 1980) and later extended by Pier Luigi Luisi (Luisi, 2003). Literally, autopoiesis stands for “self-making”, and expresses that an autopoietic system is composed by components organized in networks of production processes (such as demolition and transformation of resources), behaving like functional units in a defined space, and each component of said networks exert its function by continuously producing components deemed to network‟s maintenance and realization. Note that this concept is not limited to biologic life, but it can also be adapted to synthetic systems and even informatics networks. Autopoiesis encompasses the concepts of metabolism, growth and homeostasis, representing a “blueprint” of living organisms. Although representing a necessary property for living organisms, autopoiesis alone is not sufficient to define a living organism, as capability of reproduction and evolution are still needed to define a living being. Evolution is intended as a population property, which consists in continued adaptation of a population of organisms to the environment to which they are exposed. Finally, the concept of reproduction considers generation of other living organisms from a “parent” organism, whose characteristics are identical to the progeny. As stated before, “life” is a property of systems, and a system can be considered living (capable of “life”) if it shows three main properties: autopoiesis, reproduction and capability of evolution, complex properties that define life. Considering this elegant complexity it is possible to describe such properties, and it is logical to inquire how this complexity came to be, and at the same time characterization of properties typical of living organisms can lead to speculations about construction of systems that somehow mimic these properties. As studies about “origin of life” aim to inquire which conditions and components gave rise to living organisms, synthetic biology aims to produce artificial living organisms, complex systems that can be considered living.

Currently these two research topics rely on two main approaches: first, a reductionist approach, that starting from known living organisms aims to “reduce” their complexity until observing a system that is complex enough to be considered living, while at the same time maintaining a low degree of complexity, whose characteristics should be very similar to the very first living organism existed. The second approach consists in de-novo construction of systems using simple molecules, aiming to generate systems that somehow mimic living organisms, “synthetic organism” built in laboratory.

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Page | 8 These two approaches converge in the concept of “minimal cell”, a system that present the minimal characteristics necessary to be considered living. The notion of minimal cell represents the converge point of “origin of life” and synthetic biology studies, as realization of minimal cells represents the main goal of synthetic biology, and at the same time a minimal cell should show characteristics very similar to the first living organisms.

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Page | 9 Minimal Cells: A Challenge

Figure 3: Notion of minimal cell (redrawn from Luisi et al., 2006)

As stated before, minimal cells represent the convergence between synthetic biology and studies about origin of life. The very notion of minimal cell represents the fusion between several disciplines, melded together to achieve insights upon the very processes that define life. In particular, the choice of liposomes as “physical boundaries” for solute entrapment and metabolic reactions represents a promising field of work. As several liposome preparation methods exist, and entrapment of solutes inside liposomes is a widely diffused practice, it has been possible to use liposome as “proto-cell” models, achieving insights on compartmentalized reactions and solute entrapment behavior (Stano et al., 2011).

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Figure 4:Semi-synthetic minimal cell (redrawn from Stano et al., 2011)

Our research line focuses on realizing in-silico and experimental models of compartmentalized structures with the ultimate goal to discover which conditions and components gave rise to organization of membranes and compartmentalization. Concerning our group, we developed a model for complex biochemical reactions by encapsulating cell-free translation apparatus (commercially available), , inside vesicles of various size (Stano et al.,2011) .In-silico models have been developed utilizing software especially designed for stochastic description of biochemical reactions, QDC software (based on Gillespie‟s algorithm), describing translation kinetics for every component of cell free translation system, defining which components and molecules act as “limiting components” in reaction course (Lazzerini-Ospri et al., 2012). Experimental data obtained via fluorescence measurements of protein translation (using EGFP production as a reporter of effective and functional protein production) has been supported by development of simplified stochastic models for protein translation in liposomes, considering only the main steps of the complex reaction to develop models focused on describing combination of macromolecular components indispensable for functional protein translation. Although simplified and based upon several assumptions, these models proved as a very reliable tool in predicting system‟s behavior under several conditions. From this simplified model it has been possible to focus on a more accurate kinetic description (Calviello et al., 2013) accounting for energy balance and limit steps for every reaction, thus achieving a detailed stochastic simulation of protein translation inside vesicles, capable of simulating different reactions under several experimental conditions. Using this model as a basis for expected data a confrontation between expected data and experimental measurements obtained by directly measuring protein production in various populations of vesicles has been developed.

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Page | 11 Analysis has been conducted utilizing liposomes of different size, to ascertain the minimal vesicle volume that permitted efficient protein synthesis, thus defining an inferior limit for possible synthetic pseudo-cells. At the same time reaction efficiency and entrapment mechanics have been analyzed using population of vesicles of various size .While data obtained from vesicles with relatively high radius (range between 1µm and 150 nm) perfectly fit data expected from stochastic model, anomalous data regarding entrapment events in vesicle populations whose radius is comprised between 50 and 150 nm has been observed. Such vesicles, deemed “SUV” (small unilamellar vesicles) should show a significantly low probability of efficient protein production according to theoretical model (which is based on the assumption that entrapment of single molecules inside vesicles occur as independent events), while their entrapment mechanics should yield a distribution of vesicles filled with a low number of molecules. Instead, experimental data showed large numbers of empty vesicles, while at the same we obtained a small number of vesicles that not only showed an unusual crowding of molecules inside them, but also showed a totally unexpected protein production. This anomalous entrapment event has been observed in several works (Pereira de Souza et al, 2009; Luisi et al., 2010), however literature lacks a detailed description of such phenomenon. Another important aspect that draws attention is solute and boundary (membrane) behavior during reproduction. As stated before, reproduction represents one of the defining properties of life, and it represents a challenging aspect of living organisms, especially when considering the high regulated and precise division and reorganization that lead to cell reproduction. For single cells (and consequently for minimal cells) reproduction can be considered as cell division. A successful cell division not only produces two elements starting from a “mother” element, but produces two elements that comprise each and every component constituting the “mother” element. In living cells division represents a highly regulated and concerted procedure, as numerous molecular components exert redistribution of cell components and membrane division during a relatively short amount of time, leading to a perfect redistribution of components between the two “daughter” cells. Starting from these observations it is possible to theorize successful “reproduction” for minimal cells, although minimal cell reproduction still represents a fairly difficult property to achieve for liposome based proto-cells. Simple vesicles and micelles (in particular oleate micelles) show coupled phenomena of growth and division following incorporation of free fatty acid in vesicle membrane, dividing when reaching a critical size (Rasi et al., 2003; Zhu et al., 2009).

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Page | 12 Vesicle division can also be achieved by induced methods, such as agitation or extrusion. These simple division methods lead to loss of solutes following division, in a process poetically defined “death by dilution” which describes the progressive loss of internal solutes. It is necessary to achieve a division procedure that ensures a sufficient number of components for each daughter cell, and this procedure must repeat successfully at each division.

As a matter of fact, although it is possible to conduct several complex biochemical reactions inside vesicles, and even “build” complex structures capable of processes that mimic properties typical of living organisms, the production of a genuine “minimal cell” still represents a far goal. To further advance such concept it is mandatory to achieve better understanding of phenomena like solute entrapment behavior inside vesicles and interactions between solutes and lipid bilayer, as they represent key aspects of minimal cell theory. A valid support for minimal cell theory is given from in-silico simulation of structures and biochemical processes, as they lead to new insights regarding complex network‟s behavior and permit to better design the desired metabolic pathway or elements that compose the desired structure. As simulation and experimental data are generated and combined in a conjoined effort, it is possible to better characterize phenomena and thus design experiments in a more focused way, for example by discovering which elements represents the limiting steps in a enzymatic reaction, and thus improving the experimental design considering such insights, or by characterizing enzyme activity by stochastic simulation and determining which conditions are best suited to obtain best results in terms of product production or reaction rate, or even exclude experimental condition that represents unfavorable conditions.-Simulated data is also often used to validate hypotheses, by conducting simulations under certain hypotheses and confronting in-silico results with experimentally obtained data, thus verifying if the studied phenomena follows expected behavior or if deviation from such behavior are observed.

Combination between experimental work and simulated data leads to new insights, which allow for better experimental designs and permit progress towards a specific goal: production of minimal cells.

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Page | 13 Liposomes

Liposomes (Lasic, 1995) are peculiar structures, composed of lipid double layers organized as vesicles. Such structures are composed of amphiphilic molecules known as phospholipids, common components of cell membranes. Phospholipids present a hydrophilic group, named “head group” (usually containing phosphate) and a lipophilic “tail” composed of long chain fatty acids; presence of polar and non-polar portions confers amphiphilic properties to phospholipid molecules, which show a peculiar behavior when exposed to polar solvents: phospholipids tend to rearrange themselves by forming aggregates, whose structure presents head groups oriented towards the solvent while tail groups are excluded from solvent phase.

Figure 5: Phospholipid Structure (available for public domain at http://www.freethought-forum.com/forum/showthread.php?t=24978&garpg=6#content_start)

Such behavior can be explained by considering the solvent-lipid system‟s total entropy variation: free phospholipids are surrounded by solvent molecules which form a solvation shell around phospholipids; as phospholipids form aggregates they exclude a considerably large portion of the molecule from solvent, reducing the number of solvent molecules. Such solvent molecules, free from interactions with phospholipids are thus free to move in the solvent, leading to an increase in system‟s total entropy.

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Figure 6: Phospholipid Bilayer Structure (available for public domain at www.freethought-forum.com/forum/showthread.php?t=24978&garpg=6#content_start).

Figure 7: Schematics of Liposome Structure.

Different kind of lipids form different aggregates, most recurrent structures are micelles, single layers and double layers. The main property that drives aggregate formation is the shape of molecule, expressed by ratio between area occupied by head group and area occupied by tail groups (Tu, 2006):

If Ra>1 phospholipids tend to form micelle aggregates (micelles are vesicular structures composed of layer of polar heads oriented towards solvent, while tails are committed in the hydrophobic core of micelle). If Ra=1 phospholipid molecule can be considered of cylindrical shape; such molecules organize themselves by forming layers of lipids parallel one to another

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Page | 15 and oriented in the same way (heads facing solvent). Monolayers arise when lipids aggregate adhere to recipient‟s walls, thus forming lipid film along recipient‟s surface; double layers are originated when external two inversely oriented layers unite themselves forming a hydrophobic phase composed by the tails of the two layers, comprised between two layers of hydrophilic heads. Such aggregates vary from a unique double layer to several layers stacked one upon another, each separated by a thin volume of solvent. By supplying mechanical energy to a liposome solution lipid aggregates tend to break, releasing planar bilayer sheets that present free edges. Such edges expose a significant amount of hydrophobic molecules, so they tend to rearrange to minimize interaction between solvent and lipophilic layers, reorganizing themselves in shapes that minimize superficial tension (spherical or quasi spherical shapes are the most common, although there are reports of toroid liposomes or even biconcave discs).

Assuming that spherical vesicles are the most recurring structures, we can classify liposomes using two main parameters: vesicle size (using radius as a classification parameter) and lamellar organization. Regarding lamellar organization liposomes are classified as:

 Unilamellar vesicles (unique bilayer ,enclosing a specific amount of solution)

 Oligolamellar (2 to 10 concentric bilayers, separate one from another by a thin layer of solvent)

 Multilamellar (n>10 concentric layers, each separated from the other by a thin film of solvent)

 Multivesicular ( basically giant vesicles encapsulating other smaller vesicles)

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Figure 9: Liposome Classification based on Vesicle Size (radius)

Classification based upon vesicle size marks different kind of vesicles:  Small vesicles (radius between 40 and 100 nm)

 Large vesicles (radius between 100 nm and 500 nm)  Giant vesicles (radius > 500 nm)

Small unilamellar vesicles are deemed SUV and are one of the most common types of vesicles; unilamellar vesicle of large and even giant diameter are possible although they are considerably less stable than small vesicles (Large unilamellar vesicles are deemed LUV, while GUV are giant unilamellar); multilamellar vesicles are only of large and giant size (deemed LMV and GMV) while multivesicular vesicles are only giant vesicles.

In our work we will focus our attention upon two main vesicle types: Giant Unilamellar Vesicles (GUVs) and Large Unilamellar Vesicles (LUVs); although we will refer several times to SUV (Small Unilamellar Vesicles) in relation to previous studies conducted by our research group.

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Page | 17 Liposome preparation methods

There are several methods to produce liposomes, and such methods can be categorized under three main groups (Walde et al., 2010)

 Mechanical dispersion Methods  Solvent dispersion methods  Solvent removal methods

Mechanical dispersion methods are usually based in the production of lamellar structures from a concentrated lipid solution, usually utilizing dried or lyophilized lipid mixtures rehydrated using a hydrophilic solvent (hydration medium is usually decided in regards to the application of liposome vesicles; in our works we use water as hydration medium). First it is necessary to prepare a lipid suspension in organic solvent (chloroform or ether) which is subsequently dried (solvent evaporation is achieved by applying a nitrogen stream to the recipient containing the solution, or by exposing the mixture to vacuum) to obtain a thin lipid film, often referred as “lipid cake”. This thin film is then dried and frozen for future use. Liposome preparation requires rehydration of lipid cake, achieved by adding polar solvent to the lipid film and gently stirring. In these conditions phospholipids form large lamellar aggregates attached to the recipient‟s walls, composed of several bilayers separated by small amounts of solvent between each other. Liposome preparation is achieved by giving energy to the solution, usually by vigorous stirring or sonication. During this process the lamellar formations are shredded into small lamellae that detach and float in the solution as floccular sheets, exposing a hydrophobic layer side towards the solvent, so to minimize solvent-lipid interaction the sheets rearrange themselves to exclude edges from solvent forming spherical vesicles of various diameter; mechanical dispersion methods comprehend lipid film hydration and freeze-thawing preparation. Lipid film hydration is achieved by slowly hydrating a dehydrated mixture of phospholipids (usually commercial preparations are utilized, but it is possible to prepare in laboratory such mixture), while freeze-thawing methods consists in rapid freezing of pre-existing liposomes followed by thawing when the preparation is needed. Mechanical energy can be transferred to the mixture manually via gentle or vigorous stirring of the mixture, but usually sonication yields the best results. Sonication is achieved via probe sonicators or bath sonicators, the latter is more suited for pharmaceutical preparation of liposomes (because such treatment does little to none damage to vesicles or solute molecules entrapped inside them), whereas probe sonicators are more rapid but present a major risk of

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Page | 18 contamination by heavy metals (probe tips are usually composed of titanium) and potential damage of vesicles and solutes. These methods of preparation usually yield large multilamellar vesicles (diameter comprised between 100 nm and 1 µm; this population can be downsized via sonication, obtaining a population of small unilamellar vesicles whose diameter ranges between 20 and 100 nm. Solvent dispersion methods consist of injection of lipid mixtures inside a polar solvent, usually ethanol or ether. These methods consist in an initial dispersion of phospholipids inside a solution of organic solvent (ether or ethanol) followed by injection of this mixture inside water at high temperature (50-60° C), followed by removal of the organic solvent via vacuum or exposing the mixture to a stream of dry nitrogen. The main drawbacks of these methods are the impossibility to completely remove organic solvent, and the production of non-homogeneous liposome populations; however solvent injection methods permit to control the production of liposomes by varying the lipid concentration in the mixture (low concentration yields to formation of SUV populations, while high lipid concentrations lead to formation of a mixed population, mainly composed of LMV but containing also LUV and SUV).Another solvent injection method is the so-called “reverse phase evaporation method”. It consists in the preparation of a two-phase solution composed of lipids dissolved in organic solvent and then injected in water buffer, which is then sonicated briefly and agitated under reduced pressure. In this way the organic solvent is gradually removed, and the solution slowly forms a viscous gel. Liposomes form with the gradual evaporation of organic solvent, and this method permits to obtain high encapsulation efficiency. Detergent removal methods are based on a different strategy: lipids are mixed with a solution containing a detergent in his critical micelle concentration. In these conditions detergent molecules form micelles, structures similar to reverse vesicles.

Controlled withdrawal of detergent causes phospholipids to progressively substitute detergent molecules in micelle structure, finally obtaining phospholipid micelle, subsequently dispersed in hydrophilic buffer, thus forming vesicles (vesicles obtained with this preparation method are large unilamellar vesicles).Obviously, preparation methods are chosen keeping in mind the final utilization of liposomes. Each method differs from other in mean of obtained size distribution, encapsulation efficiency and relative yield of the reaction. Many preparation protocols usually produce large or multilamellar vesicles, and for some experimental purposes it is necessary to downsize these vesicles to obtain a population of small, unilamellar vesicles. There are various methods of vesicle downsizing, however most used methods are based on sonication and extrusion via French press. We already presented treatment with sonication;

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Page | 19 extrusion via French press utilizes a controlled pressure to force liposomes throughout a small pore or a porous membrane. With this method large multilamellar vesicles are downsized obtaining a population of SUV whose diameter ranges between 80 and 100 nm. Preparation method and any eventual downsizing procedure are to be chosen regarding the final purpose of produced liposomes. Each preparation method does not yield a single type of vesicle (characterized by the same size and organization) but rather a population of vesicles with the same lamellar organization but whose radius ranges between two limit values. This process is due to random events during vesicle formation depending upon selected method of production and lipid composition (although a certain degree of variation is always present, such as vesicle population prepared with the same composition). For our experimental purposes we produced liposome populations by two methods. Giant Unilamellar Vesicles (GUV) has been prepared via “natural swelling method”. Such preparation method consists in dehydrating a lipid solution (consisting in phospholipid dissolved in organic solvent) first under controlled evaporation, subsequently by solvent removal by pneumatic void until achieving formation of lipid film. Such lipid film is then hydrated with a “hydration buffer” containing molecular solutes, which acts as a polar phase causing swelling of lipid film and subsequently spontaneous formation of liposomes. Such method yields a population of Giant Unilamellar Vesicles very heterogeneous for vesicle radius (ranging from 1 µm to 30 µm) and solute content. After generating GUV populations we utilize them to produce sub-populations of small unilamellar vesicles by extrusion technique. Downsizing via extrusion technique is a very common method, used for liposome manipulation in various fields of application. Such preparation method consists in forcing liposome through a polycarbonate membrane filter, thus producing several small unilamellar vesicles whose radius is (in theory) the same as membrane pores „radius. Small Unilamellar Vesicles prepared by extrusion technique are deemed as “VET” (Vesicles by Extrusion Technique).

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Page | 20 Liposome size distribution

Formation of lipid aggregates can be considered as equilibrium between the phospholipids dispersed in solution and the ones committed in aggregates; it depends from chemical potential of free lipids and chemical potential of lipid aggregates (Helfrick 1986); the probability of finding a lipid aggregate composed of N molecules in a lipid solution is:

_{(Eq: 1)}

Which is a simple exponential distribution; the term stands for mean number of molecules

committed in aggregate, while =chemical potential of free lipids and =chemical potential of lipid aggregates. If the quantity ( ) <0, formation of aggregates is energetically favored. Formation of aggregates depends upon such aggregate‟s shape. For our purposes we are interested in formation of spherical vesicles, which are composed by one or more lipid double layers, which enclose a defined amount of solvent. For our purposes, vesicles can be considered as spherical, so we can adapt equation 2 considering that the number of molecules committed in spherical aggregates is

N=2 (eq: 2)

Where is the total area occupied by lipids. By substituting eq: 1 in eq: 2 we obtain:

(

) _{(Eq: 3)}

Where R term stands for vesicle radius, and stand for maximum value in radius probability distribution. Such probability distribution can be approximated by a Gaussian curve for high values of R. Following this probability distribution we are able to ascertain that formation and stability of vesicles is highly dependent upon size, and vesicle stability is very low for vesicles with small (R<30 nm) and big (R>1 µm) radius, while vesicle whose radius is comprised between 70 nm and 1 µm tend to be more stable (this area correspond to area under the bell-shaped curve). This probability distribution well explains spherical shape of vesicle, but fails to explain the high heterogeneity observed in vesicle size (following this probability distribution we expect a narrow radius range, while experimental measurements show very different results).

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Figure 10: Helfrick distribution (redrawn from Helfrick, 1986).

Curvature model does not account for thermal fluctuations at the interface; accounting for them decreases the total elastic energy of the membrane, which depends upon the specific macroscopic size of the vesicle : large vesicles appear to be more “flexible”, than smaller ones, and this flexibility increases with radius until reaching a limit value. Vesicles whose radius exceeds the maximum value tend to divide themselves in smaller vesicles (usually by buddying of new, smaller vesicles).

To include thermal fluctuation in eq 3 the parameter is replaced by an effective parameter,

, that substituted in eq 3 leads to :

_(Eq:4)

This distribution, described by Helfrick and thus deemed “Helfrick distribution” fits very well for large vesicles, however empirical size distribution obtained from measurement of small vesicles present several deviations from this distribution.

Schulz distribution (Kucerka et al., 2008) results more suited for describing size dispersion of liposome population, because we can consider such population like a polydispersed particle population. (Schulz distribution is specifically used to describe particle size in polydispersed solutions) .This probability distribution depends upon two parameters: z and r. The “r” parameter is vesicle radius, while “z” is a dispersion index (a parameter that accounts for

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Page | 22 distribution‟s width).The population of vesicles that, given a fixed value for “r” present radius equal to “r” are:

[ ] (

)

(Eq: 6)

Where r is vesicle radius, R is mean vesicle radius and z is a dispersion index. For large values of z the Schulz distribution can be approximated by a Gaussian curve.

Figure 11: Schulz Distribution.

Bearing this description in mind we can analyze liposome properties in relation to vesicle radius. Our main aim is to ascertain whether liposome size bears some influence on complex reactions inside liposomes, and to uncover which is the minimal size that permits efficient biochemical reactions inside such compartments.

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Page | 23 Solute Entrapment Mechanics

So our attention focuses on two main populations of liposomes: first population is composed of giant unilamellar vesicles, while the second population is composed by large unilamellar vesicles. Previous works from our research group already explored such situations, achieving an accurate description and establishing in silico models for encapsulation mechanics and protein production. Briefly, the encapsulation and size dependency problem has been treated considering the event of encapsulation of a single component like a rare event, thus describing sub-sequential encapsulation events using a Poisson distribution ( Luisi et al., 2010). We chose a Poisson distribution as an approximation of a binomial distribution, considering several conditions: we can consider negligible the volume occupied by each macromolecular component; encapsulation events are considered independent event (encapsulation of a molecule does not influence the event of encapsulation of a second molecule).Poisson distribution is a discrete probability distribution, which expresses the probability of a specific number of events to happen in a specific interval of time (or space), knowing that events are independent one from another and that a mean number ʎ of events happen during a certain amount of time; it is used to describe systems in which the state at time t depends solely on the state of the system at time (t-1); such systems are defined memory-less systems.

Poisson distributions depend on two parameters, ʎ and k, and the probability of observing k events knowing that the medium number of events is ʎ is :

(Eq:6)

Poisson distribution well describes encapsulation events regarding vesicles of great radius; however experimental data collected on population of SUV shows discrepancies between theoric expectations and data readings.

Considering the total bulk volume, Vt, in which we have a known concentration of molecular solute, named “A” for our purposes, we have that the probability that a single molecule of our molecular solute is enclosed inside our liposome is:

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Page | 24 Considering this value the “a priori” probability to observe the entrapment of a component inside such vesicle, it is possible to calculate the mean number of entrapped molecules of solute A (indicated with a):

a=P Nt (eq:8)

Where Nt represents total number of “A” molecules in Vt. Considering the event “entrapment of molecule A inside vesicle” as a rare event, we can use Poisson distribution to calculate the probability of entrapping n molecules of “a” inside the same vesicle:

(Eq:9)

Just considering this equation, and assuming “A” as the unique molecular species considered and fixing vesicle volume to fit SUV volume we obtain, with such considerations, a very low probability value. Following this consideration it is unlikely to observe Small Unilamellar Vesicles that retain high concentration of “A”, while the expected observation consists in several “empty” vesicles with few “A” molecules inside each vesicle. Several studies however proved that entrapment of solutes inside Small Unilamellar Vesicles does not exactly follow a Poisson probability, as vesicles containing unexpectedly high concentration of solutes have been observed in several experiments. Data obtained by nuclear microscopy have shown that SUV preparations containing ferritin as molecular solute show unexpected entrapment mechanics (Luisi et al., 2010). In this study several SUVs with radius < 100 show an unusually high ferritin concentration.

This unexpected entrapment behavior represents a significant deviation from expected Poisson entrapment mechanics, showing that entrapment mechanics in nano scale liposomes follow a distribution that presents several similarities with a power-law distribution.

Successive works further inquired this subject, reporting "anomalous entrapment” evidence in SUV populations (Pereira de Souza et al., 2011). Populations of small unilamellar vesicles equipped with “PUREsystem®” (a cell-free protein translation system) and a plasmid coding for GFP protein.

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Figure 12: Confrontation between expected ferritin concentration and experimental concentration (redrawn from Luisi et al., 2010).

PUREsystem is composed by several macromolecular components (83 species in total) plus co-factors necessary for protein production (it is the minimum protein translation apparatus). Following previous considerations it is expected that the probability of co-entrapping N molecules of a single molecular compound inside a single liposome is

(Eq:10)

Experimental data showed a very different situation, however. With these predictions it is expected to find a series of vesicles encapsulating few components, while none of the vesicle should have more than 2-5 type of molecules entrapped inside. Instead, experimental data showed the presence of a great number of empty vesicles, while a small number of vesicles show an unusually high concentration of components.

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Page | 26 For small unilamellar vesicle population a peculiar phenomenon has been observed: a low number of vesicles not only show an unusually high number of encapsulated components but express functional protein translation. Such event, observed via fluorescent microscopy (using expression of EGFP ad a reporter for achieved protein translation) and cryo-TEM analysis has been observed in population of small unilamellar vesicles containing either a single molecular solute (ferritin) or several molecular species (PUREsystem). This unexpected behavior could either be an artifact of some sort, or it could be the evidence of a new and undescribed phenomenon. One of the first questions that could arise while considering this unexpected solute entrapment behavior consists in the exclusivity of this phenomenon, which has been described only for small unilamellar vesicles. Solute entrapment inside liposomes has been well characterized for giant vesicles and for small vesicles, but literature still lacks a description of entrapment mechanics in vesicles of intermediate size. It is possible that vesicles larger than SUV show deviations from expected entrapment mechanics, thus revealing unexpected interactions between solutes and membranes that could explain anomalous entrapment events.

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Aim of the thesis

Our experimental work attempts to further shed light upon interaction between liposome membrane and molecular solutes entrapped inside liposomes, aiming at inquiring whether anomalous entrapment phenomena emerge only in populations of newly-produced small unilamellar vesicles, or if it is a more common property, arising even from simple solute redistribution events. As a matter of facts, solute entrapment distribution has been characterized only for giant vesicles, and literature still lacks insights about solute entrapment in small liposomes. In our work we focused our attention on entrapment distribution inside Giant Unilamellar Liposomes, describing entrapment events as events regulated by a Poisson distribution. Starting from populations of giant vesicles we then reduced their size via manual extrusion, achieving production of large unilamellar vesicles in which entrapment mechanics are not well characterized, aiming to shed some light upon entrapment process inside vesicles whose size is intermediate between giant vesicles and small unilamellar vesicles, in which anomalous entrapment event have been reported (see the previous section). To address these problems we adopted a semi-synthetic experimental approach, by combining in-silico generated data (describing vesicle formation and solute entrapment mechanics) with experimental data. We generated several populations of liposomes via “natural swelling method”, producing 4 populations of giant unilamellar vesicles (GUV, radius ranging from 1.5 to 20 µm) each containing a different solute (Calcein, pyranine, FITC-Dextrane, BSA-FITC). From each GUV population we generated a sub-population of vesicles by manual extrusion method (VET, vesicles by extrusion technique, whose radius ranges between 0.4 and 1 µm). Extrusion is a simple, effective and widely used size reduction method, which yields liposome populations characterized by narrow size distributions. In our work extrusion is used as a mean to achieve vesicle division, aiming to introduce a random solute redistribution between daughters VETs generated from GUVs, and subsequently characterizing VET populations produced by extrusion by means of solute and size analysis. We used several molecules with different molecular mass to inquire any relation between entrapment mechanics and solute size. These solutes are fluorescent (calcein and pyranine), or conjugated with fluorescent probes: BSA and Dextrane are conjugated with FITC (fluorescein isothiocyanate) .Therefore, in all the cases solute concentration inside vesicles can be inferred by measuring fluorescence intensity.

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Page | 28 GUVs and VETs have been analyzed by confocal microscopy to determine vesicle size and solute concentration inside each vesicle, thus determining vesicle size distribution and the distribution of solute concentrations inside vesicles. Generation of vesicle sub-populations by extrusion method permits to investigate if supercrowding events are due to simple solute redistribution during vesicle formation or if anomalous entrapment mechanics emerge as consequences of unknown solute/membrane interactions. Using several molecular solutes to generate our vesicle populations we analyze relation between solute molecular mass and entrapment mechanics.

Although anomalous entrapment phenomena have been observed in small vesicles (radius <200 nm) we used larger vesicles (VET radius ranging from 0.2 to 1 µm; GUV r >1 µm) aiming to inquire possible relations between vesicle size and entrapment mechanics. In parallel to experimental work we developed an in-silico model describing entrapment mechanics and vesicle size distribution for both GUV and VET populations. This theoretical model permits to generate size/solute distributions according to both current literature and our proposed hypotheses, allowing us to forecast solute/size distributions and to discern whether in-silico experimental data follows expected distributions or if significant deviations from expected values emerge. By confronting predicted values with experimental data we aim to further improve our model, thus achieving an accurate description of size and solute distributions for both GUV and VET populations. With this experimental setup we aim to inquire which events regulate solute entrapment during vesicle formation, providing a robust in-silico model for entrapment mechanics inside giant vesicles, and to analyze solute redistribution during forceful division events (consisting in manual extrusion of giant vesicle populations) while at the same providing an in-silico model that describes stochastic redistribution of solutes during extrusion. By confronting simulated data and experimental data we aim to inquire if induced vesicle division leads to a stochastic, random solute redistribution between “daughter” liposomes or if solute redistribution between extruded vesicles shows unexpected behavior.

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Page | 29

Materials and Methods:

Materials: 8-Hydroxypyrene-1,3,6-trisulfonic acid trisodium salt (pyranine, #H1529, MW

524.39 Da), calcein (#C0875, 666 Da), bovine serum albumin-fluorescein isothiocyanate conjugate (BSA-FITC, #A9771, 66 kDa), dextran-fluorescein isothiocyanate conjugate (dextran-FITC, MW 140 kDa),

GUV preparation:

Liposomes have been generated by “natural swelling method” (also known as gentle hydration method). Such method ensures a high-yield (Dominak and Keating, 2007) and is among the simplest and quickest liposome production methods, although it produces highly heterogeneous liposome populations with respect to both size and inner solute concentration. Natural swelling method is based on lipid film formation by controlled solvent evaporation (usually under pneumatic vacuum or rotational evaporation) starting from lipid solution in organic solvent. POPC films were prepared in round-bottom cylindrical glass vials (diameter ca. 2 cm) by introducing POPC (2.5 mol, from a stock chloroform solution) and removing the solvent at 36 °C (for about 20 minutes) under reduced pressure (15 mbar) by a Rotavapor (Büchi). The last solvent traces were removed with a membrane pump (1 mbar, 25 °C, 30 minutes). The lipid film was gently hydrated, without stirring, vortexing or pipetting the mixture, with 1.0 mL of “hydration buffer” (200 mM sucrose, 5 mM Na-bicine pH 8.5 (bicine, sodium salt), including a known amount of the solute that need to be encapsulated inside GVs), and left undisturbed for at least 12 hours (overnight incubation). The resulting GVs sample ([POPC] = 2.5 mM) was then treated as described below. Four different GVs samples were obtained by using five different hydrating buffers, each containing, respectively, (a) 10 M calcein: ,(b) 10 M pyranine; (c) 10 M BSA-FITC; (d) 1.75 M for dextran-FITC;

Removal of non-entrapped solutes and isolation of small size GVs:

To separate GVs from non-entrapped solutes, 3 volumes of GVs were diluted with 1 volume of 200 mM glucose, 5 mM Na-bicine pH 8.5, in order to create a density gradient that allows GVs centrifugation (inside: 200 mM sucrose; outside: 150 mM sucrose, 50 mM glucose). Next, the samples were centrifuged according to an optimized centrifugation protocol consisting in three sequential centrifugation and washing steps (700; 1,000; 5,000 rpm), and the final GVs pellet was suspended in 150 mM sucrose, 50 mM glucose, 5 mM Na-bicine pH 8.5. Due to material loss during this procedure, it was convenient to prepare large sample

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Page | 30 volumes (2-4 mL) by pooling together 2-4 GVs samples (1 mL each). This procedure allows (1) the removal of non-trapped solutes as well as small vesicles (found in the supernatant during each centrifugation step), and (2) the fractionation of GVs in three sub-populations. In this work only GVs with the smaller diameter are used (diameters from 1.5 to 6 m), which are collected after the 5,000 rpm centrifugation step.

Figure 13: Schematic of Centrifugation Procedure Used.

This novel vesicle separation method has been developed considering the relation between particle density and sedimentation speed during centrifugation. Starting from a simple centrifugation step, consisting in a rapid centrifugation at 10000 rpm we further enhanced the separation procedure, achieving effective separation of vesicles by size with 3 centrifugation steps.

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Page | 31 Molecular Solutes

To inquire solute entrapment mechanics in liposomes we filled our liposomes with solutions containing specific molecular solutes, using one solute for each liposome population. As our analysis is conducted by measuring solute concentration inside liposomes, we used either fluorescent molecules (as Calcein and Pyranine) or molecules conjugated with fluorescent probes (BSA and Dextrane conjugated to FITC). Solutes are trapped inside liposomes as a result of chosen liposome preparation method. We produced 4 Giant Unilamellar Vesicles populations, each containing a single molecular solute in vesicle‟s inner volume. From these 4 GUV populations we produced derived vesicle populations by extrusion technique, analyzing solute concentration inside vesicles (both GUV and VET) by confocal microscopy to infer solute concentration from fluorescence measurement. Each molecular solute used differs from the other, concerning molecular weight and chemical properties:

 Pyranine (trisodium 8-hydroxypyrene-1,3,6-trisulfonate; MW 524.37 Da) is a small hydrophilic molecule. It shows a pH-dependent fluorescence (λex 460 nm; λem 510 nm in 0.1 M Tris pH 8.0).

Figure 14: Pyranine Molecular Structure (available for public domain at www.wikipedia.org)

 Calcein (fluorexon) is a small fluorescent dye (excitation 495-emission 515; MW 622.55 Da).

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Page | 32  FITC (Fluorescein 5-IsoThioCyanate) is a functionalized fluorescein molecule, in which

an isothiocyanate replaces a hydrogen atom from the bottom ring of fluorescein. FITC molecules have a 389.382 molecular mass and pH-dependent fluorescence (excitation 490 emission 520 at pH 8). We used FITC molecules conjugated with BSA or dextran, with several fluorophores attached to a single BSA or dextran molecule.

Figure 16:FITC Molecular Structure (available for public domain at www.wikipedia.org)

 FITC-DEX: Dextran molecules conjugated with FITC molecules. Dextran is a polysaccharide composed of glucose molecules (such polysaccharides are named glucans) and characterized by complex and branched organization. Its structure consists in a strait chain (alfa-1,6 glycosidic) of glucose molecules while branches begin from alfa-1,3 linkages. Dextran molecular mass varies, there are various commercial dextran populations with different molecular mass. In our work we used 140 kDa Dextran labeled with FITC (FITC molecules are randomly conjugated to dextran at a frequency of 0.003 to 0.020 moles of FITC per glucose mole).



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Page | 33  BSA-FITC: Bovine Serum Albumin (BSA) conjugated with FITC molecules. BSA is a

serum albumin protein derived from cows (583 aa; molecular weight 69 kDa ), often used as molecular weight standard. BSA-FITC consists in BSA conjugated with FITC molecules ( >7 FITC moles per BSA mole).

Figure 18: Model of BSA molecular structure (available for public domain at www.wikipedia.org).

Solute concentrations have been chosen to avoid artifacts during image analysis (as elevated solute concentration could lead to out-of-scale fluorescence measurement, thus complicating solute concentration estimation during image analysis step). Buffer solutions have been chosen according to the optimal pH for fluorescence emission for molecular solute, leading to choice of Sodium-Bicine buffer at pH 8.5. To reduce variation between GUV populations we adopted the same buffer composition for each GUV population, thus reducing any possible variation due to buffer effect on both vesicle production and solute fluorescence emission.

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Page | 34 VET preparation:

Solute-containing GVs were extruded in order to prepare sub-micrometric extruded vesicles (Vesicles by the Extrusion Technique, VETs), by means of a hand-extruder (Liposofast, Avestin, Canada). GVs samples (0.5-1 mL) were passed back and forth (7×) through two 0.8 m-pores polycarbonate membranes (Corning Nuclepore Track-Etch Membranes) sandwiched between three support drain discs, in order to obtain VET800.VET (Vesicles by Extrusion Technique) have been obtained by manually extruding previously generated GUV populations.

Manual Extrusion Technique consists in applying controlled pressure (usually with a syringe) to solution containing liposomes, forcing them to pass inside small pores in a porous membrane, thus downsizing Giant Vesicles to Small Unilamellar Vesicles with diameter roughly equal to membrane pore‟s diameter. Extrusion apparatus consists in two syringes used to load the sample and to exert pressure, the two syringes are connected to a small metallic cylinder containing extrusion membrane surrounded by two “drain disks” and kept in place between two plastic cylinders positioned one on top of the another. Each plastic cylinder contains a small capillary inside which the sample is injected and forced towards extrusion membrane, which is juxtaposed to the second cylinder‟s capillary, directly leading inside the second syringe.

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Page | 35 After the sample is forced from the loading syringe to cross membrane and fill the second syringe, pressure is re-applied to the sample to force it crossing back the membrane and fill the loading syringe thus completing a single extrusion step. To our experimental purposes we used a manual extrusion apparatus (Lipofast extruder) with polycarbonate pores of 800, 1000 nm diameter. 1 ml samples for each GUV population have been loaded inside the extrusion syringe and treated with manual extrusion procedure, consisting into 6 complete passages between the two syringes; during extrusion process a lot of sample is lost, yielding 200-300 µL samples from 1ml of original sample.

The main drawbacks of extrusion process consist in sample loss during extrusion step, due to manual extruder‟s conformation and to extrusion‟s principle. It is also expected that membrane reorganization during extrusion causes liberation of molecular solute inside the sample, thus leading to a high background noise during image analysis step. This free molecular solute could not be removed by centrifugation (as for GUVs), because to precipitate extruded vesicles (whose radius is supposed 400 nm) are necessary very high centrifugal fields (200000 rpm), and vesicle membranes rupture at these speeds.

Extrusion has been extensively used as a mean to produce liposome populations with a narrow size distribution, although literature still lacks a detailed biophysical description of membrane and solute reorganization during extrusion process. For our purposes extrusion represents a rapid method to achieve vesicle division and solute redistribution, leading to production of derived vesicle populations. In our work we aim to characterize solute redistribution after extrusion, to better characterize this process and determine whether solute redistribution can be considered as a random redistribution event, or if evidence of anomalous solute redistribution emerges from our observations. Vesicle populations produced by extrusion technique show narrow size distributions, whose mean value is equal to extrusion membrane pore‟s radius.

Although vesicle downsizing via extrusion is widely used, literature still lacks a detailed biophysical description of extrusion procedure. Supposedly, giant vesicles are pressed against extrusion membrane‟s pores, where pressure gradient across the membrane causes formation of smaller vesicles. It is still unknown if vesicles rupture upon contact with membranes, and small vesicles are re-formed at the interface between membrane and external solution (rupture of vesicles should explain solute loss observed during extrusion procedure), or if vesicles are simply “squeezed” across membranes, leading to formation of smaller vesicles.

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Page | 36 Confocal Microscopy and Image Analysis:

Sample analysis has been conducted by confocal laser scanning microscopy. A confocal microscope allows to obtain high resolution optical images by optical sectioning (acquisition of images from selected depths) achieved by controlled and highly limited focus depth. Light originating from a laser is focused into a small focal volume in the sample, while the instrument collects fluorescence light (from the sample), scattered and reflected light. A filter selectively blocks original excitation wavelength; after passing a pinhole, light intensity reaches a detector (photomultiplier tube). Only light originated from focal point, as out of focus light is blocked by the pinhole. Selection and image acquisition at different focal points permits “sample scanning”, an imaging technique peculiar to confocal microscopes: by moving the laser light source it is possible to detect light originating in a single sample point. Complete image is reconstructed by software assemblage of each single point record. Horizontal scanning speed can be directly controlled (it influences signal to noise ratio, so slower scans present better resolution but are more time consumptive) while selection of different focal planes can be achieved by raising or lowering microscope stage or objective lens. One of the main drawbacks of confocal microscopy results in its high signal-to-noise-ratio dependence, caused by the small photon number available: the vast majority of photons emitted from the sample are blocked by pinhole and detector aperture, thus augmenting resolution at the cost of sample brightness. Confocal microscopy also permits fluorescence intensity measurement, which we used for solute quantification. GVs and VET800 have been observed by means of a Leica TCS SP5 confocal microscope. Images (8 bits) were acquired at 1024 x 1024 resolution and 63x magnification. All fluorophores used in this study can be excited by the 488 nm Argon laser line and emitted in the green region (500-550 nm) of the spectrum. Vesicles (30 µL) have been diluted with 70 µL of isotonic isopycnic buffer (150 mM sucrose, 50 mM glucose, 5 mM Na-bicine pH 8.5) and directly visualized without any pre-treatment. Visualization chambers have been created by overlapping a microscope glass slide and a 0.17 mm coverslip above each other, using as a spacer two properly shaped molten Parafilm® layers (holding together the glass slide and the coverslip). Due to the complete removal of non-trapped solutes, GVs background was not fluorescent, whereas VETs background was partially fluorescent, as expected, because of solute loss during GVs extrusion. Fluorescence of non-encapsulated molecular solutes has been measured using the same settings as vesicle analysis, to construct calibration curves later used to infer solute concentration inside liposomes.

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Figure 20: a) GUV sample; b)VET sample (images taken at 63 x magnification, resolution 1024x1024, scale bar 100 micrometers)

Care was taken to imaged vesicles and free solutes at approximately the same depth (along the sample z-direction). In all cases, stock solutions of fluorophores in the hydration buffer were prepared and measured in the same day of GVs preparation. Image analysis was carried out by using the public domain Java image processing program ImageJ (version 1.46 R) (Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, http://imagej.nih.gov/ij/, 1997-2014), according to the following protocol.

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Page | 38 Images generated from Leica Application Suite Advanced Fluorescence (LAS AF) were first exported as RGB 8-bit TIFF images.

Figure 21: a) Sample image (3 color channels); b) Sample Image (1 color channel).

Next operations were done on the green channel only. The average value m and the standard deviation (sd) of the background fluorescence (pixel luminosity) were measured and the value m + 3sd were used to threshold the image. Vesicles were identified by the “analyze particles” Image J algorithm and recorded as regions of interest (ROIs), which were then applied to the original image (green channel) in order to obtain (1) the ROI size (corresponding to the 2D projection of vesicles) and (2) the average intra-vesicle luminosity. These values were converted to (1) vesicle size (under the hypothesis that their 2D projection correspond in most cases to the vesicle equatorial section) and (2) intra-vesicle solute content by means of a calibration curve. Each analysis produced an output composed by lists of ROIs recognized inside each image and listed by number, followed by data such as total area of each ROI (measured in pixel 2), mean and modal fluorescence values (measured inside each ROI in grey-scale values), fluorescence standard deviation. Several shape parameters are listed for each ROI, such as circularity, roundness, solidity and aspect ratio. Circularity is calculated for each ROI as :

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Page | 39 Circularity ranges between 0 and 1, being1 a perfect circle and 0 an infinitely elongated polygon. Solidity represents a measure of ROI “filling”, as its value represents the ratio of ROI‟s area against the convex area measured for selected ROI:

Aspect Ratio represents how much the selected ROI resembles an elliptical shape. It is calculated as:

Aspect Ratio is equal to 1 for circular shapes. Round parameter expresses the roundness of measured ROIs; it is measured as the inverse of Aspect Ratio, or by the formula:

For each image analyzed we obtained a dataset comprising each parameter above mentioned. Each ROI measured by the program has been selected by analysis of shape parameters: ROIs with Circularity >0.8, Aspect Ratio> 0.8, Round> 0.5 and Solidity>0.8 (these values have been obtained by measuring a circular shape) have been considered as valid vesicles and thus used for size and solute concentration analysis, whereas vesicles whose shape parameters where lower than selected values have been discarded. These parameters have been used for both GUV and VET analysis.

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Page | 40 To eliminate false positives ,which in our case correspond to elements recognized as ROI by ImageJ program ,but whose nature corresponds to out-of-focus vesicles (for whom fluorescence measurements present a bias) or lipid aggregates which retain fluorescence but do not represent vesicles; a direct evaluation of each vesicle by confronting non-tresholded images with ROIs recognized by the program permits a quick detection and subsequent elimination of those false-positives, producing a corrected data set upon which we conduced our analysis. For VET images selection of vesicles has been made by considering shape descriptors to determine whether each recognized ROI represented a vesicle or a false positive. We considered a bona fide vesicle any element recognized by the program which possessed these qualities: area>2 pixel (which correspond to particles of 0.29 um radius), circularity >0.7 (circularity varies between 0 and 1, 1 being a perfect circular area); Aspect Ratio >0.5; solidity> 0.8,; round >0.5. By following this selection we reduced our data set, but application of this selection procedure permits elimination of false positives, whose unchecked presence would lead to severe bias during data interpretation. Our final dataset, comprising area, mean and modal fluorescence values, fluorescence standard deviation and shape descriptors have been used to calculate vesicle radius (considering each ROI as the equatorial section of a vesicle and calculating vesicle radius from ROI area) and solute concentration inside each vesicle (by using mean fluorescence value inside each ROI). Radius and solute concentration have been used to construct experimental size distributions and solute distributions for all samples analyzed.

Data obtained from image analysis has been used to construct size distribution and solute concentration distribution for all experimental vesicle populations (both GUVs and VETs). At

a

)

b

)

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Page | 41 the same time simulated vesicle populations (both GUVs and VETs) have been constructed and characterized, obtaining size distributions and solute concentration distributions for silico vesicle populations, aiming to confront each experimental vesicle population with in-silico generated vesicles. Simulated vesicle populations have been constructed according to theoretical size distributions and solute entrapment mechanics, thus permitting to confront our experimental data with data corresponding to theoretically expected size distributions and solute entrapment mechanics.

This confrontation can show if experimentally generated vesicle populations behave according to our theoric predictions, or if we observe deviations from our expected results, thus permitting to inquire several key aspects of solute entrapment mechanics and size distribution of vesicle populations.

In both simulated and experimental vesicle populations we considered two key parameters to construct size and solute distributions: vesicle radius and internal solute concentration for each vesicle.