Rediscovering Bacteria through Single-Molecule Imaging in Living Cells

Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics

The classical three-stage model of stochastic gene expression predicts the statistics of single cell mRNA and protein number fluctuations as a function of the rates of promoter switching, transcription, translation, degradation and dilution. While this model is easily simulated, its analytical solution remains an unsolved problem. Here we modify this model to explicitly include cell-cycle dynamics and then derive an exact solution for the time-dependent joint distribution of mRNA and protein numbers. We show large differences between this model and the classical model which captures cell-cycle effects implicitly via effective first-order dilution reactions. In particular we find that the Fano factor of protein numbers calculated from a population snapshot measurement are underestimated by the classical model whereas the correlation between mRNA and protein can be either over- or underestimated, depending on the timescales of mRNA degradation and promoter switching relative to the mean cell-cycle duration time.

Bacterial Transcriptional Regulators: A Road Map for Functional, Structural, and Biophysical Characterization

The different niches through which bacteria move during their life cycle require a fast response to the many environmental queues they encounter. The sensing of these stimuli and their correct response is driven primarily by transcriptional regulators. This kind of protein is involved in sensing a wide array of chemical species, a process that ultimately leads to the regulation of gene transcription. The allosteric-coupling mechanism of sensing and regulation is a central aspect of biological systems and has become an important field of research during the last decades. In this review, we summarize the state-of-the-art techniques applied to unravel these complex mechanisms. We introduce a roadmap that may serve for experimental design, depending on the answers we seek and the initial information we have about the system of study. We also provide information on databases containing available structural information on each family of transcriptional regulators. Finally, we discuss the recent results of research about the allosteric mechanisms of sensing and regulation involving many transcriptional regulators of interest, highlighting multipronged strategies and novel experimental techniques. The aim of the experiments discussed here was to provide a better understanding at a molecular level of how bacteria adapt to the different environmental threats they face.

Parameter-free molecular super-structures quantification in single-molecule localization microscopy

Understanding biological function requires the identification and characterization of complex patterns of molecules. Single-molecule localization microscopy (SMLM) can quantitatively measure molecular components and interactions at resolutions far beyond the diffraction limit, but this information is only useful if these patterns can be quantified and interpreted. We provide a new approach for the analysis of SMLM data that develops the concept of structures and super-structures formed by interconnected elements, such as smaller protein clusters. Using a formal framework and a parameter-free algorithm, (super-)structures formed from smaller components are found to be abundant in classes of nuclear proteins, such as heterogeneous nuclear ribonucleoprotein particles (hnRNPs), but are absent from ceramides located in the plasma membrane. We suggest that mesoscopic structures formed by interconnected protein clusters are common within the nucleus and have an important role in the organization and function of the genome. Our algorithm, SuperStructure, can be used to analyze and explore complex SMLM data and extract functionally relevant information.

Evaluation of diffusion coefficient of P-glycoprotein molecules labeled with green fluorescent protein in living cell membrane

The movement of individual molecules inside living cells has recently been resolved by single particles tracking (SPT) method which is a powerful tool for probing the organization and dynamics of the plasma membrane constituents. Effective treatment of metastatic cancers requires the toxic chemotherapy, however this therapy leads to the multidrug resistance phenomenon of the cancer cells, in which the cancer cells resist simultaneously to different drugs with different targets and chemical structures. P-glycoprotein molecules which are responsible for multidrug resistance of many cancer cells have been studied by cancer biologists during past haft of century. Recently, advances in laser and detector technologies have enabled single fluorophores to be visualized in aqueous solution. The development of the total internal reflection fluorescent microscope (TIRFM) provided means to monitor dynamic molecular localization in living cells. In this paper, P-glycoproteins (PGP) were labeled with green fluorescent protein (GFP) in living cell membrane of Madin-Darby canine kidney (MDCK) and the TIRFM method was used to characterize the dynamics of individual protein molecules on the surface of living cells. An evanescent field was produced by a totally internally reflected and a laser beam was illuminated the glass-water interface. GFP-PGP proteins that entered the evanescent field appeared as individual spots of light which were slighter than background fluorescence. We obtained high-resolution images and diffusion maps of membrane proteins on cell surface and showed the local diffusion properties of specific proteins on single cells. We also determined the diffusion coefficient, the mean square displacement and the average velocity of the tracked particles, as well as the heterogeneity of the cell environment. This study enabled us to understand single-molecule features in living cell and measure the diffusion kinetics of membrane-bound molecules.

Single-molecule localisation microscopy: accounting for chance co-localisation between foci in bacterial cells

Using single-molecule fluorescence microscopes, individual biomolecules can be observed within live bacterial cells. Using differently coloured probes, physical associations between two different molecular species can be assessed through co-localisation measurements. However, bacterial cells are finite and small (~ 1 μm) relative to the resolution limit of optical microscopes (~ 0.25 μm). Furthermore, the images produced by optical microscopes are typically two-dimensional projections of three-dimensional objects. These limitations mean that a certain proportion of object pairs (molecules) will inevitably be assigned as being co-localised, even when they are distant at molecular distance scales (nm). What is this proportion? Here, we attack this problem, theoretically and computationally, by creating a model of the co-localisation expected purely due to chance. We thus consider a bacterial cell wherein objects are distributed at random and evaluate the co-localisation in a fashion that emulates an experimental analysis. We consider simplified geometries where we can most transparently investigate the effect of a finite size of the cell and the effect of probing a three-dimensional cell in only two dimensions. Coupling theory to simulations, we also study the co-localisation expected due to chance using parameters relevant to bacterial cells. Overall, we show that the co-localisation expected purely due to chance can be quite substantial and describe the parameters that it depends upon.

Parameter-free molecular super-structures quantification in single-molecule localization microscopy

Understanding biological function requires the identification and characterization of complex patterns of molecules. Single-molecule localization microscopy (SMLM) can quantitatively measure molecular components and interactions at resolutions far beyond the diffraction limit, but this information is only useful if these patterns can be quantified and interpreted. We provide a new approach for the analysis of SMLM data that develops the concept of structures and super-structures formed by interconnected elements, such as smaller protein clusters. Using a formal framework and a parameter-free algorithm, (super-)structures formed from smaller components are found to be abundant in classes of nuclear proteins, such as heterogeneous nuclear ribonucleoprotein particles (hnRNPs), but are absent from ceramides located in the plasma membrane. We suggest that mesoscopic structures formed by interconnected protein clusters are common within the nucleus and have an important role in the organization and function of the genome. Our algorithm, SuperStructure, can be used to analyze and explore complex SMLM data and extract functionally relevant information.

Biochemistry: one molecule at a time

Biological processes are orchestrated by complex networks of molecules. Conventional approaches for studying the action of biomolecules operate on a population level, averaging out any inhomogeneities within the ensemble. Investigating one biological macromolecule at a time allows researchers to directly probe individual behaviours, and thus characterise the intrinsic molecular heterogeneity of the system. Single-molecule methods have unravelled unexpected modes of action for many seemingly well-characterised biomolecules and often proved instrumental in understanding the intricate mechanistic basis of biological processes. This collection of reviews aims to showcase how single-molecule techniques can be used to address important biological questions and to inspire biochemists to ‘zoom in’ to the population and probe individual molecular behaviours, beyond the ensemble average. Furthermore, this issue of Essays in Biochemistry is the very first written and edited entirely by early career researchers, and so it also highlights the strength, diversity and excellence of the younger generation single-molecule scientists who drive this exciting field of research forward.

Bacterial Vivisection: How Fluorescence-Based Imaging Techniques Shed a Light on the Inner Workings of Bacteria

The rise in fluorescence-based imaging techniques over the past 3 decades has improved the ability of researchers to scrutinize live cell biology at increased spatial and temporal resolution. In microbiology, these real-time vivisections structurally changed the view on the bacterial cell away from the "watery bag of enzymes" paradigm toward the perspective that these organisms are as complex as their eukaryotic counterparts. Capitalizing on the enormous potential of (time-lapse) fluorescence microscopy and the ever-extending pallet of corresponding probes, initial breakthroughs were made in unraveling the localization of proteins and monitoring real-time gene expression. However, later it became clear that the potential of this technique extends much further, paving the way for a focus-shift from observing single events within bacterial cells or populations to obtaining a more global picture at the intra- and intercellular level. In this review, we outline the current state of the art in fluorescence-based vivisection of bacteria and provide an overview of important case studies to exemplify how to use or combine different strategies to gain detailed information on the cell's physiology. The manuscript therefore consists of two separate (but interconnected) parts that can be read and consulted individually. The first part focuses on the fluorescent probe pallet and provides a perspective on modern methodologies for microscopy using these tools. The second section of the review takes the reader on a tour through the bacterial cell from cytoplasm to outer shell, describing strategies and methods to highlight architectural features and overall dynamics within cells.

Extracting Transition Rates in Particle Tracking Using Analytical Diffusion Distribution Analysis

Single-particle tracking is an important technique in the life sciences to understand the kinetics of biomolecules. The analysis of apparent diffusion coefficients in vivo, for example, enables researchers to determine whether biomolecules are moving alone, as part of a larger complex, or are bound to large cellular components such as the membrane or chromosomal DNA. A remaining challenge has been to retrieve quantitative kinetic models, especially for molecules that rapidly switch between different diffusional states. Here, we present analytical diffusion distribution analysis (anaDDA), a framework that allows for extracting transition rates from distributions of apparent diffusion coefficients calculated from short trajectories that feature less than 10 localizations per track. Under the assumption that the system is Markovian and diffusion is purely Brownian, we show that theoretically predicted distributions accurately match simulated distributions and that anaDDA outperforms existing methods to retrieve kinetics, especially in the fast regime of 0.1-10 transitions per imaging frame. AnaDDA does account for the effects of confinement and tracking window boundaries. Furthermore, we added the option to perform global fitting of data acquired at different frame times to allow complex models with multiple states to be fitted confidently. Previously, we have started to develop anaDDA to investigate the target search of CRISPR-Cas complexes. In this work, we have optimized the algorithms and reanalyzed experimental data of DNA polymerase I diffusing in live Escherichia coli. We found that long-lived DNA interaction by DNA polymerase are more abundant upon DNA damage, suggesting roles in DNA repair. We further revealed and quantified fast DNA probing interactions that last shorter than 10 ms. AnaDDA pushes the boundaries of the timescale of interactions that can be probed with single-particle tracking and is a mathematically rigorous framework that can be further expanded to extract detailed information about the behavior of biomolecules in living cells.

Imaging live bacteria at the nanoscale: comparison of immobilisation strategies

Atomic force microscopy (AFM) provides an effective, label-free technique enabling the imaging of live bacteria under physiological conditions with nanometre precision. However, AFM is a surface scanning technique, and the accuracy of its performance requires the effective and reliable immobilisation of bacterial cells onto substrates. Here, we compare the effectiveness of various chemical approaches to facilitate the immobilisation of Escherichia coli onto glass cover slips in terms of bacterial adsorption, viability and compatibility with correlative imaging by fluorescence microscopy. We assess surface functionalisation using gelatin, poly-l-lysine, Cell-Tak™, and Vectabond®. We describe how bacterial immobilisation, viability and suitability for AFM experiments depend on bacterial strain, buffer conditions and surface functionalisation. We demonstrate the use of such immobilisation by AFM images that resolve the porin lattice on the bacterial surface; local degradation of the bacterial cell envelope by an antimicrobial peptide (Cecropin B); and the formation of membrane attack complexes on the bacterial membrane.

Visualizing the inner life of microbes: practices of multi-color single-molecule localization microscopy in microbiology

In this review, we discuss multi-color single-molecule imaging and tracking strategies for studying microbial cell biology. We first summarize and compare the methods in a detailed literature review of published studies conducted in bacteria and fungi. We then introduce a guideline on which factors and parameters should be evaluated when designing a new experiment, from fluorophore and labeling choices to imaging routines and data analysis. Finally, we give some insight into some of the recent and promising applications and developments of these techniques and discuss the outlook for this field.

From single bacterial cell imaging towards in vivo single-molecule biochemistry studies

Bacteria as single-cell organisms are important model systems to study cellular mechanisms and functions. In recent years and with the help of advanced fluorescence microscopy techniques, immense progress has been made in characterizing and quantifying the behavior of single bacterial cells on the basis of molecular interactions and assemblies in the complex environment of live cultures. Importantly, single-molecule imaging enables the in vivo determination of the stoichiometry and molecular architecture of subcellular structures, yielding detailed, quantitative, spatiotemporally resolved molecular maps and unraveling dynamic heterogeneities and subpopulations on the subcellular level. Nevertheless, open challenges remain. Here, we review the past and current status of the field, discuss example applications and give insights into future trends.

Combining Modules for Versatile and Optimal Labeling of Lactic Acid Bacteria: Two pMV158-Family Promiscuous Replicons, a Pneumococcal System for Constitutive or Inducible Gene Expression, and Two Fluorescent Proteins

Labeling of bacterial cells with fluorescent proteins allows tracking the bacteria in competition and interactomic in vivo and in vitro studies. During the last years, a few plasmid vectors have been developed aimed at the fluorescent labeling of specific members of the lactic acid bacteria (LAB), a heterogeneous group that includes microorganisms used in the food industry, as probiotics, or as live vectors for mucosal vaccines. Successful and versatile labeling of a broad range of LAB not only requires a vector containing a promiscuous replicon and a widely recognized expression system for the constitutive or regulated expression of the fluorescence determinant, but also the knowledge of the main features of the entire plasmid/host/fluorescent protein ensemble. By using the LAB model species Lactococcus lactis, we have compared the utility properties of a set of labeling vectors constructed by combining a promiscuous replicon (pMV158 or pSH71) of the pMV158 plasmid family with the gene encoding either the EGFP or the mCherry fluorescent protein placed under control of promoter P_X or P_M from the pneumococcal mal gene cluster for maltosaccharide uptake and utilization, respectively. Some vectors carrying P_M also harbor the malR gene, whose product represses transcription from this promoter, thus enabling maltose-inducible synthesis of the fluorescent proteins. We have determined the plasmid copy number (PCN) and segregational stability of the different constructs, as well as the effect of these features on the fitness and fluorescence intensity of the lactococcal host. Constructs based on the pSH71 replicon had a high copy number (∼115) and were segregationally stable. The copy number of vectors based on the pMV158 replicon was lower (∼8–45) and varied substantially depending on the genetic context of the plasmid and on the bacterial growth conditions; as a consequence, inheritance of these vectors was less stable. Synthesis of the fluorescent proteins encoded by these plasmids did not significantly decrease the host fitness. By employing inducible expression vectors, the fluorescent proteins were shown to be very stable in this bacterium. Importantly, conditions for accurate quantification of the emitted fluorescence were established based on the maturation times of the fluorescent proteins.

ColiCoords: A Python package for the analysis of bacterial fluorescence microscopy data

Single-molecule fluorescence microscopy studies of bacteria provide unique insights into the mechanisms of cellular processes and protein machineries in ways that are unrivalled by any other technique. With the cost of microscopes dropping and the availability of fully automated microscopes, the volume of microscopy data produced has increased tremendously. These developments have moved the bottleneck of throughput from image acquisition and sample preparation to data analysis. Furthermore, requirements for analysis procedures have become more stringent given the demand of various journals to make data and analysis procedures available. To address these issues we have developed a new data analysis package for analysis of fluorescence microscopy data from rod-like cells. Our software ColiCoords structures microscopy data at the single-cell level and implements a coordinate system describing each cell. This allows for the transformation of Cartesian coordinates from transmission light and fluorescence images and single-molecule localization microscopy (SMLM) data to cellular coordinates. Using this transformation, many cells can be combined to increase the statistical power of fluorescence microscopy datasets of any kind. ColiCoords is open source, implemented in the programming language Python, and is extensively documented. This allows for modifications for specific needs or to inspect and publish data analysis procedures. By providing a format that allows for easy sharing of code and associated data, we intend to promote open and reproducible research. The source code and documentation can be found via the project's GitHub page.

A Single-Molecule View of Archaeal Transcription

The discovery of the archaeal domain of life is tightly connected to an in-depth analysis of the prokaryotic RNA world. In addition to Carl Woese's approach to use the sequence of the 16S rRNA gene as phylogenetic marker, the finding of Karl Stetter and Wolfram Zillig that archaeal RNA polymerases (RNAPs) were nothing like the bacterial RNAP but are more complex enzymes that resemble the eukaryotic RNAPII was one of the key findings supporting the idea that archaea constitute the third major branch on the tree of life. This breakthrough in transcriptional research 40years ago paved the way for in-depth studies of the transcription machinery in archaea. However, although the archaeal RNAP and the basal transcription factors that fine-tune the activity of the RNAP during the transcription cycle are long known, we still lack information concerning the architecture and dynamics of archaeal transcription complexes. In this context, single-molecule measurements were instrumental as they provided crucial insights into the process of transcription initiation, the architecture of the initiation complex and the dynamics of mobile elements of the RNAP. In this review, we discuss single-molecule approaches suitable to examine molecular mechanisms of transcription and highlight findings that shaped our understanding of the archaeal transcription apparatus. We furthermore explore the possibilities and challenges of next-generation single-molecule techniques, for example, super-resolution microscopy and single-molecule tracking, and ask whether these approaches will ultimately allow us to investigate archaeal transcription in vivo.

Single-Molecule Tracking Approaches to Protein Synthesis Kinetics in Living Cells

Decades of traditional biochemistry, structural approaches, and, more recently, single-molecule-based in vitro techniques have provided us with an astonishingly detailed understanding of the molecular mechanism of ribosome-catalyzed protein synthesis. However, in order to understand these details in the context of cell physiology and population biology, new techniques to probe the dynamics of molecular processes inside the cell are needed. Recent years' development in super-resolved fluorescence microscopy has revolutionized imaging of intracellular processes, and we now have the possibility to directly peek into the microcosm of biomolecules in their native environment. In this Perspective, we discuss how these methods are currently being applied and further developed to study the kinetics of protein synthesis directly inside living cells.

Understanding Protein Mobility in Bacteria by Tracking Single Molecules

Protein diffusion is crucial for understanding the formation of protein complexes in vivo and has been the subject of many fluorescence microscopy studies in cells; however, such microscopy efforts are often limited by low sensitivity and resolution. During the past decade, these limitations have been addressed by new super-resolution imaging methods, most of which rely on single-particle tracking and single-molecule detection; these methods are revolutionizing our understanding of molecular diffusion inside bacterial cells by directly visualizing the motion of proteins and the effects of the local and global environment on diffusion. Here we review key methods that made such experiments possible, with particular emphasis on versions of single-molecule tracking based on photo-activated fluorescent proteins. We also discuss studies that provide estimates of the time a diffusing protein takes to locate a target site, as well as studies that examined the stoichiometries of diffusing species, the effect of stable and weak interactions on diffusion, and the constraints of large macromolecular structures on the ability of proteins and their complexes to access the entire cytoplasm.