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Amyloid aggregation is a hallmark of neurodegenerative diseases. Depending on the pathology, it involves different type of proteins, and interests different biological spaces. In the case of Alzheimer, the aggregation of Ab proteins occurs in the extracellular brain space. In this tortuous space, fluid flow may impact the localisation and aggregation process. However, it is really difficult to probe this effect in in vivo conditions. Idealised systems set up may be useful, at least from the computational point of view, to quantify when fluid flow becomes important for aggregation. Using multi-scale simulations we have quantify precisely when, for systems at nanoscale, the surrounding fluid flow impacts the aggregation kinetics decisively. At this length-scale, the transition from a diffusion dominated to an advection dominated dynamics of amyloid monomers and oligomers occurs at very high shear rate (10e6 s-1), causing a strong acceleration in aggregation kinetics. Moreover, the action of fluid on formed pre fibrils showed the possibility to form pathological annular-like structures as already detected in experiments, and that rely on a given elasticity of the aggregated states. This work provides a clear framework to study aggregation dynamics (not only pathological) under the action of flow and to mimic experimental microfluidic devises. Moreover, it can be extended to other relevant systems, for example a solution of antibodies when injected in the body. Enjoy the reading here. Thanks to Antonio Iorio for the huge work. 

Let’s talk again of life adaptation to extreme conditions. One of the most intriguing issues is how the molecular machinery of living organisms adapts to different thermal conditions. First, the machinery must stay stable where it works. Second, it should be flexible enough to function where it is needed, aka the thermal niche of the organism. Here, funny things happen. According to a historical view, and borrowing a concept from physics, it was proposed the so-called corresponding state principle for life adaptation. This principle mixes two ideas. First it assumes that the thermal stability of a protein relates to its structure rigidity. Second, that there is a threshold in the structure flexibility for an enzyme to function. If a protein is too rigid it lacks functionality. Ergo, very stable enzymes, can sustain high temperature before unfolding, and acquires functional flexibility only in hot environment. For cold adapted enzyme, the opposite is true, they should manifest functional flexibility even at low temperature. This picture, interesting enough, have some flows. For instance thermal stability can be achieved via entropic routes, and not only via an enthalpic rigidity. Second, it does not specify what kind of flexibility is required for functionality. Third, and here is the critical point I want to address, it just focuses on the protein internal structure and function, not in its environment. Well, it turns out that, if we are correct, what matters it is not the intrinsic thermal response of a protein, that in the cytoplasm scales with temperature very similarly for different organisms. What matters is the fluidity of the crowded environment where the protein moves and functions. In short, the average viscosity of the cytoplasm follows the thermal character of the organism. Less viscous for a cold-adapted bacteria, and more viscous for the hot-adapted bacteria. How this is possible? Here, the second interesting aspect, it seems that evolution has selected the charges of the proteins, proteins with more anionic character (enriched in negative charges, namely at the surface) are present in the proteome of cold-adapted organisms. This charge enrichment, in particular at the surface of the protein, because of relative repulsion between the macromolecules in the cytoplasm ensures enhanced fluidity at comparable temperature. Evolution has fine tuned proteome composition in such a way to control the cytoplasm fluidity. Enjoy it here. 

Coarse-graining the crowd. Considering bio-molecules in their in-vivo environment (eg the cell cytoplasm) is essential for any successful understanding of biological processes, and ultimately their manipulation. Because the characteristic size, the simulation of the intracellular space requires simplified molecular representations such as protein coarse-grained models. However, some care must be placed when using these simple models. For example when interested in transport properties (how a protein moves around, diffuses, encounters partners for functioning etc), some surprises may occur. In particular small unbalances in the force of the interactions may cause gelation: All the molecules stick together and do not move anymore. A painstaking work led us to optimise our model OPEP (Optimized Potential for Efficient Protein structure Prediction) for dealing with in-vivo like conditions and reproducing experimental data. The good part of the story is that the model now is public and available in two versions. Enjoy and use it (here). 

When particles, dust or pathogens like bacteria and viruses, get inhaled and travel in the respiratory tract, they are trapped in a special fluid, the mucus, that covers the epithelial cells. Mucus is a highly viscous environment, whose viscosity can be several orders of magnitude larger than that of water. It is like to have a layer of honey protecting us. Inside the mucus, because of its inherent chemical composition, invading particles get trapped and neutralized. The mucus is also a battleground for antibodies that can recognize, bind and stop pathogens at the front-line. 

The accumulation of pathogens in the mucus is then cleared out by the rhythmic beating motion of the underlying cilia carpet. Cilia look like hair filaments and move thanks to their internal molecular motors. The sort of breakdance of each individual cilium becomes synchronised and collectively organised like a choreography because of the hydrodynamic interactions mediated by the surrounding fluid. In fact, the fluid wave created by the motion of one cilium propagates to other moving ones and help them synchronize. The net result is a collective motion named metachronal wave.

It turns out that the distribution of carpets of cilia is not necessarily very ordered in living organisms where ciliated and non-ciliated cells alternate, and the direction of individual cilium motion may vary between regions as well. This is a hot point: how does this disorder affect the clearing efficiency? Is the ordered picture of aligned cilia the best scenario for pushing mucus away? Or has nature found in the disorder a variable that can be tuned for clearance optimisation? 

Let’s keep in mind, also, that disorder can originate from pathological conditions. In some diseases cilia die and leave empty spaces, in other ones, some cilia are immotile and do not contribute to the clearance process. Just to recall the recent pandemics, it was demonstrated that covid-19 can induce death of ciliated cells. 

While visualising and studying all these aspects experimentally can be tricky, computer simulations might be of great help. In this spirit we designed an operative framework to study the mucus clearance in a realistic 3D mesoscale model. The work is here, 

https://lnkd.in/ef72ervC

and featured with a beautiful cover in JCP, and in SciLight.

Critics, suggestions, comments… feel free to call. 

The CNRS news is here, and the ILL news here.

Organisms have adapted to thrive in a well defined and narrow range of temperatures. Humans are confortable around ambient conditions, but other organisms can sustain much higher temperatures, even beyond the water boiling temperature. How temperature kills a cell is not completely understood but is crucial in many aspects. For example for understanding how life evolved in the planet, and how it can expand elsewhere. Also, we must account how even small temperature changes in the environment due to climat issues may unbalance the present distribution of living organisms. Finally, how therapeutical approaches can be optimised to kill cancerous cells via raising locally the cell temperature. 

The main reason why a cell dies upon thermal increase is because proteins, the most abundant macromolecules in the cells, stop functioning as effect of their structural unfolding. But the tricky part is that we do not know if all proteins stop working (see this beautiful work by K. Dill group) or just a few of them, playing a critical role, are affected by the thermal stress, an amazing contribution by P. Piccotti group here.  

To expand and simplify the story let’s use a metaphor. A cell looks like a factory where the proteins represent it is laborious and wonderful working-class. They transform energy and compounds, they provide mechanical force for motility, and stability; they decode the genetic informations. Quite amazing. When we increase slightly the temperature the efficiency of their activity increases. It is like a boost of energy. They have more “strength” and “energy” to accomplish the task. From the physical point of view, this is explained by what is known as Boltzmann factor. Temperature also influences another and subtle aspect, it increases the transport of matters inside the cell. Again using our metaphor, it is like we accelerate the assembly line, do you remember 'Modern times' by C. Chaplin? However, when a critical temperature is reached proteins get destabilised. They get weak and unable to work because of high fever. The efficiency of the work is compromised. Back to the original question: at the critical temperature (known as cell death temperature) all the working class stops producing or just a bunch of workers, that control key positions in the productive chain, stop their activity? 

We have recently looked at the issue (read the manuscript open access here), and found support to the idea that just a few amount of proteins actually unfold and stop to be operative at the cell death temperature. We discovered something else too. In fact when the few proteins unfold, they actually not only stop to function; but by melting they alter the dynamical properties of the sourrounding environment. The local viscosity dramatically increases. In some sense, according to our initial metaphor, it is like that by unfolding they slow down all the assembly-lines inside the factory. The molecular reason of this effect is not surprising at all. When a protein unfolds it becomes a floppy and long spaghetti that tends to glue the surrounding macromolecules and the environment starts looking like a gel. In short, not necessarily the few proteins that unfold must act as pivotal enzymes in critical metabolic patterns. Their unfolding might be enough for suppressing some metabolic reactions that are controlled by the local diffusivity, this because by unfolding the proteins induce a local very high viscosity. The question is open…..

Thanks to LEXMA Technology for LBMD simulations

Two post doc positions available soon in my group. The first project concerns the application of multi-scale simulations to the study of membranelles molecular condensates in the cytoplasm. We are especially interested in the investigation of fluid flow perturbation on the molecular structure of the condensates. The work will be done in collaboration with the groups of M. Feing and L. Lapidus at the Michigan State University (US). The second project concerns the emergence of allostery as regulatory mechanism in enzymes. We will apply molecular dynamics and modelling to support the interpretation of experiments from . P Shanda (ISTA, Vienna) and D. Manerd (IBS, Grenoble)(NMR and biochemical easy).

To apply follow the links:

Position 1: here.

Position 2: here.

At the edge of allostery. Allostery is a wonderful mechanism used by proteins for functional regulation. Let’s be simple, some proteins “have” a switch, like an engine, that makes them function or not. Why? Well, we do not need an engine to provide power all time, right? Similarly, for metabolic reason, proteins are not needed to work full time. The switch can be activated by the presence of other molecules that bind to the proteins. Once bonded to these activators, the allosteric protein, generally, changes the conformation to achieve a highly functional state. Allostery, is a molecular “skill” that emerged as the results of evolution. What happened at the edge of this transition is a hot topic in molecular biology. In order to understand it, we can use molecular resurrection, design and produce proteins that do not exist anymore but are considered ancestors of the evolved and survived ones. This is a time travel, back in time to discover the non-allosteric ancestors. Alternatively, we can explore the variety of organisms still alive today, and try to guess the “speciation” of allostery. This is exactly what we did, and it is a species journey. We travelled across a protein family, and focused -in the protein sequence sense- at the edge of the transition among non-allosteric and allosteric members. Then we played a bit, and transformed one non-allosteric member into an allosteric one by single point mutations. Finally, we did a third journey. Now, we travelled in the space of conformations that are explored by proteins. We demonstrated that by introducing a few key changes we could make allostery to emerge from an original non-allosteric enzyme, and we clarified the conformations pertinent to the “switch” activation. 

 It is a mechanism happening in the cell when temperature suddenly raises causing some proteins to unfold or misfold. When a protein mis-behaves it can alter the overall cell functioning. In order to avoid the propagation in space of this broken state, inside the cell a set of molecules gather together and isolate the damaged proteins. They create a sort of quarantine team and avoid propagation of the damage. We studied how these membraneless organelles sequestrate a target protein involved in ALS, and how things differ between in vitro and in vivo. Great experimental work by Simon Ebbinghaus group, and a little simulative contribution from our team. Paper open acces.. Enjoy it here.

We have devised multi-scale simulations of its three-domains fragment A1A2A3. These three domains are essential for the functional regulation of vWf. Namely the A2 domain hosts the site where the protease ADAMTS13 cleavages the multimeric vWf allowing for its length control that prevents thrombotic conditions. The exposure of the cleavage site follows the elongation/unfolding of the domain that is caused by an increased shear stress in blood. By deploying Lattice Boltzmann molecular dynamics simulations based on the OPEP coarse-grained model for proteins, we investigated at molecular level the unfolding of the A2 domain under the action of a perturbing shear flow. The manuscript is open access. Enjoy it here.

Marina worked in my group as young PhD student, and helped me in shaping, advancing a challenging ERC project on extremophilic proteins. She later on challenged herself in several post-doctoral positions, and awarded the prestigious Marie Sk􏰀lodowska-Curie fellowship to start working on her own projects. I am very happy, and proud! Read more here.

Proteins in the purinosome.

The goal of the project is to investigate by multi-scale computer simulations the structure, dynamics and ultimately function of a metabolon: the purinosome. The project will be carried out under the supervision of Fabio Sterpone at the LBT/IBPC in collaboration with S. Melchionna (Lexma-Technology, Rome, Italy), and it will benefit from the tight collaboration with the experimental group of S. Ebbinghaus (TU Braunschweig, Germany).  

Metabolic enzymes form regulatory clusters in cells, the metabolons, where enzymes are spatially and temporally organized into multienzyme complexes. One example is the purinosome that controls the metabolic pathway for de novo purine synthesis in eukaryotes involving ten chemical steps catalyzed by six enzymes [1]. We apply a unique combination of multi-scale simulations to investigate the complex and its individual enzymes on a molecular level. We will identify protein-protein interactions between the enzymes that lead to the assembly/disassembly of the complex under different cellular conditions. We will analyze structural changes, conformational dynamics of the individual enzymes in the complex compared to their counterparts in the cytoplasm. By characterizing the structure of the purinosome we will gain molecular insights into the control of a metabolic flux and its regulation, and possibly unravel novel therapeutic strategies.

The computational investigation will be based on the innovative technique developed in the host laboratory, the lattice Boltzmann Molecular Dynamics based on coarse-grained models for proteins [2,3], combined to atomistic simulations. The group of F. Sterpone has already applied the approach to study protein stability and dynamics in crowded solutions and cellular environments, see figure 1 and Ref. [4,5]. The multi-scale strategy will allow to explore the time-dependent aggregation of the core of the purinosome and its packing organization, tracing the assembling pattern, the preferential interactions among the constituents, the local clustering under different cellular crowding conditions. The investigation will be partnered by the experimental investigation carried out on the same system in the laboratory of S. Ebbinghaus (TU Braunschweig, Germany) and based on single molecule spectroscopy [6]. The candidate will also contribute, in collaboration with S. Melchionna (Lexma-Technology) to the software development in order to improve performance and scalability so to handle in the future very large biomolecular systems/complexes in the cellular environment. The natural secondment for this project is the start-up Lexma-Technology

References

[1] An, S., Kumar, R., Sheets, E.D., Benkovic, S.J., 2008. Reversible Compartmentalization of de novo Purine Biosynthetic Complexes in Living Cells. Science 320, 103–106

[2] Sterpone, F., Derreumaux, P., Melchionna, S., 2015. Protein simulations in fluids: coupling the OPEP coarse-grained force field with hydrodynamics. J. Chem. Theory Comput. 11, 1843-1853.

[3] Sterpone F., et al. 2014. The OPEP coarse-grained protein model: from single molecules, amyloid formation, role of macromolecular crowding and hydrodynamics to RNA/DNA complexes. Chem. Soc. Rev. 43, 4871-4893.

[4] Timr, S., Gnutt, D., Ebbinghaus, S., Sterpone, F., 2020. The Unfolding Journey of Superoxide Dismutase 1 Barrels under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions with Crowders, J. Phys. Chem. Lett. 11, 4206-421. 

[5]Timr, S., Sterpone, F., 2021. Stabilizing or Destabilizing: Simulations of Chymotrypsin Inhibitor 2 under Crowding Reveal Existence of a Crossover Temperature, J. Phys. Chem. Lett. 12, 1741-1746.

[6] Gnutt, D., Timr, S., Ahlers, J., König, B., Manderfeld, E., Heyden, M., Sterpone, F., Ebbinghaus, S., 2019b. Stability Effect of Quinary Interactions Reversed by Single Point Mutations. J. Am. Chem. Soc.

Biophysical basis of cell death

Life on Earth exhibits an amazing adaptive capacity. One of the most striking evidence of adaptation to extremely adverse environments is the presence of microbial life in a vast temperature range from below 0 °C in glacial waters to above 100 °C in deep ocean hot springs. The mechanisms that preserve bacteria from decline under these extreme conditions are still elusive. A deep knowledge of such mechanisms is key to understand the origin of life on Earth and for astrobiology, other than for possible applicative reasons.

Proteins are both the least stable and most common biomolecule, then the thermal stability of proteome must be tightly linked to that of cells. In fact, in the last years we successfully revealed the dynamical features occurring in correspondence of the cell’s death takes and showed that there is a strong connection with a denaturation catastrophe of its proteome.

Here we propose a PhD thesis where state-of-the-art neutron scattering and molecular dynamics simulations will be used to investigate the structural basis of the cell’s death and the relationship with the denaturation catastrophe in a variety of organisms. The work will be based at the University of Perugia (Perugia, Italy) and IBPC-CNRS (Paris, France), the candidate will be supervised by Prof. A. Paciaroni and Dr. F. Sterpone. The work will be done in collaboration with J. Peter (Univ. Grenoble and ILL, France)

The candidate must obtain the Master Degree in Physics or equivalent disciplines before September 30th 2021 in a country different than Italy. 

The interested candidate must contact Alessandro Paciaroni and Fabio Sterpone to prepare the candidature for the selection from the University of Perugia.

Alessandro Paciaroni,  Dept. Physics, Univ. Perugia, Italy. alessandro.paciaroni@unipg.it

Fabio Sterpone, CNRS, Paris, France, fabio.sterpone@ibpc.fr

Judith Peter, Univ. Grenoble, France, jpeters@ill.fr

The Hamlet curse of a protein: to be or not stabilized by the crowd. Question is: if excluded volume stabilizes the native state in the interior of a cell this means entropy rules. But, if not, this means the enthalpy contribution from local protein-protein interactions engage. Unfortunately, to make the story just a bit more complicate, temperature may alter the balance of the force. In short, do we need a thermodynamic version of Shakespeare? Or maybe just detect the crossover! A nice press-release from INC, is here.

Organisms can thrive in extremes conditions, from glacial water (0°C) to hot springs (100°C). An amazing view of this adaptation is given by the color gradient in Yellowstone’s hot springs. A puzzling question is how organisms can fight the degrading action of temperature, and more, how they optimize the chemical processes of their metabolism as function of the living temperature. To answer this, we need to go down to proteins, soft-matter entities, that make life in action. Some interesting aspects are discussed in two twin-papers just out. Enjoy them! https://lnkd.in/d7EMs4r and https://lnkd.in/dEnhVjZ.  

To feel the concept, try to stretch and move in a crowded space, like in an underground train at rush hours. I can suggest RER B in Paris or Line A at Furio Camillo in Rome at 18h. Difficult, right? Well this is what happens in vivo inside cells where proteins experience a permanent fluctuating crowded environment made up by proteins, RNAs, DNAs, lipids, osmolytes, ions. The effect can be formalized in physical concepts. Moving under crowding means for instance that the diffusion occurs in a space of reduced dimensionality. Stretching becomes difficult because the space available for the associated movement is reduced, we lose entropy! Again, a little game helps: try to extend a pearl-necklace in a small jewel box, if the box is too small no way to succeed. To help visualizing the reality for proteins get a look at the video. We overlapped the unfolding states of SOD1 to the sampled trajectory of SOD1 in a cell-like crowded solution. To enjoy the real science, get a look at the paper here (https://lnkd.in/dgbshgY).