Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Imaging and 3D reconstruction of membrane protein complexes by cryo-electron microscopy and single particle analysis

Cryo-electron microscopy (cryo-EM) in combination with single particle image processing and volume reconstruction is a powerful technology to obtain medium-resolution structures of large protein complexes, which are extremely difficult to crystallize and not amenable to NMR studies due to size limitation. Depending on the stability and stiffness as well as on the symmetry of the complex, three-dimensional reconstructions at a resolution of 10-30 ˚ can be achieved. In this range of resolution, we may not be able to answer A chemical questions at the level of atomic interactions, but we can gain detailed insight into the macromolecular architecture of large multi-subunit complexes and their mechanisms of action. In this thesis, several prevalently large membrane protein complexes of great physiological importance were examined by various electron microscopy techniques and single particle image analysis. The core part of my work consists in the imaging of a mammalian V-ATPase, frozen-hydrated in amorphous ice and of the completion of the first volume reconstruction of this type of enzyme, derived from cryo-EM images. This ubiquitous rotary motor is essential in every eukaryotic cell and is of high medical importance due to its implication in various diseases such as osteoporosis, skeletal cancer and kidney disorders. My contribution to the second and third paper concerns the volume reconstruction of two bacterial outer membrane pore complexes from cryo-EM images recorded by my colleague Mohamed Chami. PulD from Klebsiella oxytoca constitutes a massive translocating pore capable of transporting a fully folded cell surface protein PulA through the membrane. It is part of the Type II secretion system, which is common for Gram-negative bacteria. The second volume regards ClyA, a pore-forming heamolytic toxin of virulent Escherichia coli and Salmonella enterica strains that kill target cells by inserting pores into their membranes. To the last two papers, I contributed with cryo-negative stain imaging of the cell division protein DivIVA from Bacillus subtilis and with image processing of the micrographs displaying the siderophore receptor FrpB from Neisseria meningitidis

Heat Transfer at the Interface of Graphene Nanoribbons with Different Relative Orientations and Gaps

Because of their high thermal conductivity, graphene nanoribbons (GNRs) can be employed as fillers to enhance the thermal transfer properties of composite materials, such as polymer-based ones. However, when the filler loading is higher than the geometric percolation threshold, the interfacial thermal resistance between adjacent GNRs may significantly limit the overall thermal transfer through a network of fillers. In this article, reverse non-equilibrium molecular dynamics is used to investigate the impact of the relative orientation (i.e., horizontal and vertical overlap, interplanar spacing and angular displacement) of couples of GNRs on their interfacial thermal resistance. Based on the simulation results, we propose an empirical correlation between the thermal resistance at the interface of adjacent GNRs and their main geometrical parameters, namely the normalized projected overlap and average interplanar spacing. The reported correlation can be beneficial for speeding up bottom-up approaches to the multiscale analysis of the thermal properties of composite materials, particularly when thermally conductive fillers create percolating pathways

Improved methods for single-particle cryogenic electron microscopy

Biological macromolecules such as enzymes are nanoscale machines. This is true in a concrete sense: if the atomic structure of a biological macromolecule can be obtained, the theories of mechanics and intermolecular forces can be applied to explain how the machine works in terms that engineers would understand, including motors, ratchets, gates and transducers. Nevertheless, biological macromolecules are complex, fragile and extremely small, so obtaining their structures is a challenging experimental endeavor. Single-particle cryogenic electron microscopy (cryo-EM) is a technique for determining the 3D structure of a biological macromolecule from a large set of 2D electron micrographs of individual structurally-identical particles. To obtain such images, a solution of the macromolecules must be prepared in the frozen-hydrated state, embedded in a thin electron-transparent glassy film of water. This specimen must then be imaged with a very short exposure to avoid radiation damage. A powerful computer must then be used to sort, align, and average the 2D particle images to back-calculate the 3D structure. At its best, cryo-EM can determine the structures of biological macromolecules to atomic resolution. In practice, this goal is usually not achieved. Cryo-EM has gotten significantly more powerful in the past few years due to improvements in equipment and methodology. Several of the most significant advances originated in the labs of David Agard and Yifan Cheng at UCSF. When I began my PhD with Yifan, the spirit in the lab was that cryo-EM could keep getting better and better: with enough engineering, determining the 3D structure of an arbitrary biological macromolecule would be as routine an experiment as gel electrophoresis or DNA sequencing. Inspired, I took on projects in the lab that I thought would move the field closer to that goal. In the first chapter of this thesis, I describe work I did supporting a project initiated by David Agard and his long-time scientific programmer Shawn Zheng. They developed and implemented an algorithm, MotionCor2, for correcting the complex, anisotropic movements that occur when a frozen-hydrated specimen interacts with the high-energy electron beam. My role was to benchmark MotionCor2 on a panel of real-world 3D reconstruction tasks. I was able to show that MotionCor2 restored the highest resolution details in the images, ultimately yielding significantly better structures than simpler algorithms. For me, this projected highlighted the importance of benchmarking an algorithm for use in routine real-world conditions with the right metrics. In chapter 1, I include the manuscript for the MotionCor2 study, formatted to highlight my contributions that were moved to the supplement in the original publication by Nature Methods. One of the major remaining issues with cryo-EM is sample preparation: preparing the thin freestanding films of frozen-hydrated particles necessarily exposes those particles to air-water interfaces. Many fragile macromolecular complexes denature when exposed to such interfaces, preventing structure determination with cryo-EM. In chapters 2 and 3, I describe my efforts to develop a simple, robust approach to stabilizing fragile macromolecular complexes during the vitrification process. In chapter 2, I develop a method for coating EM grids with an electron-transparent and functionalizable graphene-oxide support film. I demonstrate that such GO grids are compatible with high-resolution structure determination. This work was published in the Journal of Structural Biology in 2018. In chapter 3, I extend this work by functionalizing GO grids with nucleic acids, enabling routine structure determination of uncrosslinked chromatin specimens. In on-going work, I used nucleic acid grids to solve high-resolution structures of a highly fragile specimen, the snf2h-nucleosome complex, and analyzed the conformational heterogeneity of the nucleosome substrate. These results were made possible by the nucleic acid grid, as the other major approach for stabilizing chromatin specimens, chemical crosslinking, not work for this specimen.Perhaps the most fundamental problem with single-particle cryo-EM is the radiation sensitivity of frozen-hydrated macromolecules. To image biological matter with electrons is to destroy it, so obtaining images of undamaged specimens requires very short, highly under sampled exposures. The resultant images are extremely noisy and low contrast, with most particles barely visible from the background. In chapter 4, I describe a novel computational approach to generating contrast in cryo-EM. Using a recently described machine learning strategy for training a parameterized denoising algorithm, I developed a computer program, restore, that denoises cryo-EM images, greatly enhancing their contrast and interpretability. This program leverages recent advances in computer vision and deep learning which have not yet been widely used in cryo-EM image processing algorithms. To characterize the performance of the algorithm on real-world data, I extended conventional metrics for image resolution to measure how an arbitrary transformation affects images at different spatial frequencies. These novel metrics are general and may be useful for characterizing other nonlinear reconstruction algorithms in cryo-EM and medical imaging. Finally, I showed that denoised cryo-EM images maintain the high-resolution information required for accurate 3D reconstruction. Denoising can be applied to conventional cryo-EM images and can be reversed whenever necessary. I have made the software for restore program publicly available and have submitted a manuscript for peer-reviewed publication

In situ high-resolution structure of the baseplate antenna complex in <i>Chlorobaculum tepidum</i>

Photosynthetic antenna systems enable organisms harvesting light and transfer the energy to the photosynthetic reaction centre, where the conversion to chemical energy takes place. One of the most complex antenna systems, the chlorosome, found in the photosynthetic green sulfur bacterium Chlorobaculum (Cba.) tepidum contains a baseplate, which is a scaffolding super-structure, formed by the protein CsmA and bacteriochlorophyll a. Here we present the first high-resolution structure of the CsmA baseplate using intact fully functional, light-harvesting organelles from Cba. tepidum, following a hybrid approach combining five complementary methods: solid-state NMR spectroscopy, cryo-electron microscopy, isotropic and anisotropic circular dichroism and linear dichroism. The structure calculation was facilitated through development of new software, GASyCS for efficient geometry optimization of highly symmetric oligomeric structures. We show that the baseplate is composed of rods of repeated dimers of the strongly amphipathic CsmA with pigments sandwiched within the dimer at the hydrophobic side of the helix

Spatio-temporal analysis of architecture and growth in bacterial colonies

Most microorganisms prefer to live in surface associated communities called biofilms, where their lifestyle differs considerably compared to their planktonic counterpart. The cell shape, as well as physical interactions determine the structure of bacterial biofilms. Due to cell growth, the size of the biofilm increases with time and the structure changes during biofilm maturation. This work aims at characterizing the structure and growth dynamics of dense colonies formed by gonococci. The first part of this thesis focuses on the characterization of the spatial structure of gonococcal colonies. Image analysis tools were developed that allowed determin- ing the positions of single cells within the spherical colonies. Using the position data, the radial distribution function (RDF) was calculated. The RDF showed short-ranged order but not long range order, reminiscent of liquids. Neisseria gonorrhoeae interact via their type 4 pilus (T4P) with surfaces and cells. T4P- T4P binding between adjacent cells generates attractive force that controls colony formation. We investigated the effect of T4P retraction of the local and meso- scopic structure of gonococcal colonies using strains with varying T4P retraction phenotypes. Reducing speed and frequency of T4P retraction reduced cell density and increased order in 6 h old colonies. Deleting T4P retraction results in loss of local order. After 24 h, density and local order increase for all strains, and larger holes inside the structures of gonococcal colonies emerged, which were independent of T4P motor activity. In conclusion, we show that gonococcal T4P active force generation is not necessary for development of local order, but it accelerates the process of achieving higher densities and local ordering inside spherical colonies. 1 1 Abstract In the second part of this thesis, we developed methods for measuring growth rates of colony-bound bacteria with spatial and temporal resolution. Growing gonococci generated a radial velocity field inside colonies that pointed from the centre of mass (COM) of colonies to its periphery. Close to the colony centres, velocities were minimal and increased towards the periphery of colonies. We showed that by characterizing the velocity field within the colony, the local growth rates can be measured. Independently, growth rates were determined by counting the offspring of single fluorescent cells that were distributed homogeneously inside the colonies. Both methods complement each other, because they have different advantages and disadvantages. Unexpectedly, heterogeneous growth profiles inside small gonococcal colonies emerged after 2 h of growth. To assess the hypothesis that nutrient limitation causes growth heterogeneity, we optimized the nutrient supply with a higher flow rate. Even though gonococcal growth improved slightly, growth profiles were still heterogeneous, indicating different limitations like mechanical constraints. Surprisingly, colonies that could not activate the stringent response developed heterogeneity in spatial and temporal growth even earlier. We suggest that stringent response is important for gonococcal biofilm maturation. Finally, the effect of azithromycin treatment on colony growth dynamics was investigated. We observed that after two generations times, growth rates dropped to low values throughout the colony indicating that azithromycin diffuses quickly through the whole colony and effects the majority of cells. In summary, we established tools for characterizing growth and death within dense spherical colonies at spatial and temporal resolution. This method will be useful to study the mechanisms of development of heterogeneity inside gonococcal colonies and their response to environmental changes like antimicrobial treatment

Emergent properties of microbial activity in heterogeneous soil microenvironments:Different research approaches are slowly converging, yet major challenges remain

Over the last 60 years, soil microbiologists have accumulated a wealth of experimental data showing that the usual bulk, macroscopic parameters used to characterize soils (e.g., granulometry, pH, soil organic matter and biomass contents) provide insufficient information to describe quantitatively the activity of soil microorganisms and some of its outcomes, like the emission of greenhouse gases. Clearly, new, more appropriate macroscopic parameters are needed, which reflect better the spatial heterogeneity of soils at the microscale (i.e., the pore scale). For a long time, spectroscopic and microscopic tools were lacking to quantify processes at that scale, but major technological advances over the last 15 years have made suitable equipment available to researchers. In this context, the objective of the present article is to review progress achieved to date in the significant research program that has ensued. This program can be rationalized as a sequence of steps, namely the quantification and modeling of the physical-, (bio)chemical-, and microbiological properties of soils, the integration of these different perspectives into a unified theory, its upscaling to the macroscopic scale, and, eventually, the development of new approaches to measure macroscopic soil characteristics. At this stage, significant progress has been achieved on the physical front, and to a lesser extent on the (bio)chemical one as well, both in terms of experiments and modeling. In terms of microbial aspects, whereas a lot of work has been devoted to the modeling of bacterial and fungal activity in soils at the pore scale, the appropriateness of model assumptions cannot be readily assessed because relevant experimental data are extremely scarce. For the overall research to move forward, it will be crucial to make sure that research on the microbial components of soil systems does not keep lagging behind the work on the physical and (bio)chemical characteristics. Concerning the subsequent steps in the program, very little integration of the various disciplinary perspectives has occurred so far, and, as a result, researchers have not yet been able to tackle the scaling up to the macroscopic level. Many challenges, some of them daunting, remain on the path ahead

Raman spectral imaging in tissue engineering & regenerative medicine applications

The label-free nature of Raman spectroscopy makes it a valuable tool for cellular and tissue characterisation. Its ability to probe molecular vibrations within biological structures without affecting their biochemistry offers an advantage over conventional histological and biochemical assays. Providing a pure investigation of unperturbed biological processes, without the need for introduction of exogenous molecules for labelling, makes the information Raman spectroscopy offers very valuable in deciphering complex biological functions and mechanisms. Raman spectral signatures are unique "fingerprints" of each biomolecule probed and can be used for cellular phenotype characterisation, tissue composition, disease development in a cellular or tissue level and much more. This thesis focuses on the use of Raman spectral imaging in novel biological applications displaying its flexibility across the fields of tissue engineering and regenerative medicine. Bone regeneration was the first biological process investigated, where Raman spectral imaging was used to characterise bioactive glass-assisted bone repair using standard and novel glass compositions. Newly-formed bone quality was assessed using multivariate analysis, showing similar quality between glass compositions and existing bone. Morphological analysis after in vivo implantation of bioactive glass particles showed distinct spectral zones confirming results from existing in vitro models. The second application, focused on the development of a novel Raman-based gene delivery tracking methodology. Viral particles, containing modified viral-nucleotides with alkyne bonds were produced were successfully detected using Raman spectral imaging in cells after infection. The implications of this technology offer a new cell screening methodology for gene therapy. Finally, the potential of Raman spectral imaging as a complementary technique for 3D cell culture systems was explored. A computational framework was developed which allows for the visualisation and quantification of subcellular structures. The accurate 3D reconstruction of whole cells of known architecture from a volumetric hyperspectral Raman dataset was reported here for the first time. Moreover, using spectral unmixing algorithms to quantify subcellular components, revealed an unprecedented molecular specificity. This allowed imaging of cells within hydrogel-based 3D cell culture systems. The synergy of Raman spectral imaging, multivariate and image analysis to answer complex biological questions offers objective biomolecular characterisation, quantification and visualisation of molecular architecture. This work demonstrates the potential of Raman spectroscopy as a valuable complementary tool in tissue engineering and regenerative medicine applications.Open Acces