Comparative Analysis of Neuronal Segmentation Methods for Single Cell Signal Extraction

In the Molecular Signaling Laboratory (MSLab), when working with neuronal cells that have been treated with a dye agent, a parameter extraction protocol is followed, mainly the intensity of the image, which requires advanced knowledge in programming languages and tools, as well as a prudent time to extract the information. The investigator, on most occasions, is limited by its researcher background. In this work, the master degree student has developed a tool that offers the extraction of the results, without necessitating the knowledge in image processing languages, and exposes them in plots that make it easier the interpretation for the investigator. This software also allows the export of the results in an Excel file. On this project, a method has been implemented that performs cellular segmentation and extracts the information in an image processing language, and desktop software that uses that method, transparently to the researcher, and exposes the results in graphs

Image Analysis Algorithms for Single-Cell Study in Systems Biology

With the contiguous shift of biology from a qualitative toward a quantitative field of research, digital microscopy and image-based measurements are drawing increased interest. Several methods have been developed for acquiring images of cells and intracellular organelles. Traditionally, acquired images are analyzed manually through visual inspection. The increasing volume of data is challenging the scope of manual analysis, and there is a need to develop methods for automated analysis. This thesis examines the development and application of computational methods for acquisition and analysis of images from single-cell assays. The thesis proceeds with three different aspects.First, a study evaluates several methods for focusing microscopes and proposes a novel strategy to perform focusing in time-lapse imaging. The method relies on the nature of the focus-drift and its predictability. The study shows that focus-drift is a dynamical system with a small randomness. Therefore, a prediction-based method is employed to track the focus-drift overtime. A prototype implementation of the proposed method is created by extending the Nikon EZ-C1 Version 3.30 (Tokyo, Japan) imaging platform for acquiring images with a Nikon Eclipse (TE2000-U, Nikon, Japan) microscope.Second, a novel method is formulated to segment individual cells from a dense cluster. The method incorporates multi-resolution analysis with maximum-likelihood estimation (MAMLE) for cell detection. The MAMLE performs cell segmentation in two phases. The initial phase relies on a cutting-edge filter, edge detection in multi-resolution with a morphological operator, and threshold decomposition for adaptive thresholding. It estimates morphological features from the initial results. In the next phase, the final segmentation is constructed by boosting the initial results with the estimated parameters. The MAMLE method is evaluated with de novo data sets as well as with benchmark data from public databases. An empirical evaluation of the MAMLE method confirms its accuracy.Third, a comparative study is carried out on performance evaluation of state-ofthe-art methods for the detection of subcellular organelles. This study includes eleven algorithms developed in different fields for segmentation. The evaluation procedure encompasses a broad set of samples, ranging from benchmark data to synthetic images. The result from this study suggests that there is no particular method which performs superior to others in the test samples. Next, the effect of tetracycline on transcription dynamics of tetA promoter in Escherichia coli (E. coli ) cells is studied. This study measures expressions of RNA by tagging the MS2d-GFP vector with a target gene. The RNAs are observed as intracellular spots in confocal images. The kernel density estimation (KDE) method for detecting the intracellular spots is employed to quantify the individual RNA molecules.The thesis summarizes the results from five publications. Most of the publications are associated with different methods for imaging and analysis of microscopy. Confocal images with E. coli cells are targeted as the primary area of application. However, potential applications beyond the primary target are also made evident. The findings of the research are confirmed empirically

Väärintaittuneiden proteiinien solun päihin eriytymisen robustisuus Escherichia coli bakteerissa

Not long ago it was believed that symmetrically dividing bacteria didn't age, but fairly recently this belief has been challenged, as the development of microscopy techniques has allowed more detailed study of these organisms. The discovery of bacterial ageing has made it possible to study fundamental ageing related mechanisms in organisms where they can be observed on a molecular level with relative ease. As a result, the accumulation of misfolded proteins, corrupted end products of gene expression, has been identified to be the main ageing factor in Escherichia coli. This accumulation is also associated with many diseases in higher organisms, including humans. Studying the basic concepts related to ageing could thus potentially provide clues to develop methods of managing these diseases in the future, as well as improve our general understanding of ageing and it's evolutionary origin. The research this thesis is a part of takes a look at the effect of different types of stress on protein production and the mechanisms that cells use to cope with corrupted proteins. The main focus here is on the robustness of one of the mechanism the cells use to mitigate protein damage, which is the segregation, retention and eventual asymmetric inheritance of unwanted protein aggregates. The nucleoid, a denser region containing the genetic material of the cell, has been recently identified to have an instrumental role in this mechanism in Escherichia coli cells. Here we study the effects of stress, which alters the size of this region on the robustness of this mechanism. Some related results are also presented regarding the effects of stress on gene expression dynamics. The segregation and retention mechanisms are studied here using time lapse microscopy measurements to observe the relative movement of the nucleoids and unwanted protein aggregates within individual cells. In addition to presenting the results, this thesis focuses on the statistical and image analysis methods used during the project, as the majority of the work done for this thesis was done on this part. These methods are introduced in chapter 3 of the thesis. After that, we present the results which show that changes in the relative size of the nucleoid within the cell do cause significant changes in the spatial distribution and dynamics of the aggregates. Based on our observations, we conclude that even though the segregation and retention mechanisms are fairly robust to these changes, they are not completely immune. Additionally, we show that the functioning of these mechanisms seems to be optimized with moderate nucleoid sizes, whereas significant increases or decreases in nucleoid size lead to diminished functionality

Fluoresoivien partikkeleiden havaitseminen kolibakteereissa

Escherichia coli are one of the most commonly used bacteria to study important biolog-ical processes such as transcription and translation. This is due to its simple structure and gene expression system, as well as the easiness to maintain live cultures in a laboratory environment. Due to recent developments in fluorescence microscopy and fluorescence labeling, it is now possible to study such biological processes in live cells at single cell and single molecule level. When analyzing such biological processes, the detection of fluorescent objects and subcellular particles is usually one of the first tasks providing important information for subsequent data analysis. Although many algorithms have been proposed for the task, it still remains a challenge due to the limitations of image acquisition when imaging live cells. For example, the intensity of the illumination light and the exposure time is usually minimized to prevent damage to the cells, resulting in images with low signal-to-noise ratio. Due to this and the large amount of data typically used for these studies, automated, high quality parti-cle detection algorithms are needed. In this thesis, we present a novel method for detecting fluorescently labeled subcellular particles in Escherichia coli. The proposed method is tested in both synthetic and em-pirical images and is compared to previous, commonly used methods using standard performance evaluation metrics. The results indicate that the proposed algorithm has a good performance with all image types tested and that it outperforms the previous methods. It is also able to achieve good results with other types of cells than E. coli. Moreover, it allows a robust detection of particles from low signal-to-noise ratio images with good accuracy, thus providing accurate and unbiased results for subsequent analy-sis

Image Processing and Simulation Toolboxes of Microscopy Images of Bacterial Cells

Recent advances in microscopy imaging technology have allowed the characterization of the dynamics of cellular processes at the single-cell and single-molecule level. Particularly in bacterial cell studies, and using the E. coli as a case study, these techniques have been used to detect and track internal cell structures such as the Nucleoid and the Cell Wall and fluorescently tagged molecular aggregates such as FtsZ proteins, Min system proteins, inclusion bodies and all the different types of RNA molecules. These studies have been performed with using multi-modal, multi-process, time-lapse microscopy, producing both morphological and functional images. To facilitate the finding of relationships between cellular processes, from small-scale, such as gene expression, to large-scale, such as cell division, an image processing toolbox was implemented with several automatic and/or manual features such as, cell segmentation and tracking, intra-modal and intra-modal image registration, as well as the detection, counting and characterization of several cellular components. Two segmentation algorithms of cellular component were implemented, the first one based on the Gaussian Distribution and the second based on Thresholding and morphological structuring functions. These algorithms were used to perform the segmentation of Nucleoids and to identify the different stages of FtsZ Ring formation (allied with the use of machine learning algorithms), which allowed to understand how the temperature influences the physical properties of the Nucleoid and correlated those properties with the exclusion of protein aggregates from the center of the cell. Another study used the segmentation algorithms to study how the temperature affects the formation of the FtsZ Ring. The validation of the developed image processing methods and techniques has been based on benchmark databases manually produced and curated by experts. When dealing with thousands of cells and hundreds of images, these manually generated datasets can become the biggest cost in a research project. To expedite these studies in terms of time and lower the cost of the manual labour, an image simulation was implemented to generate realistic artificial images. The proposed image simulation toolbox can generate biologically inspired objects that mimic the spatial and temporal organization of bacterial cells and their processes, such as cell growth and division and cell motility, and cell morphology (shape, size and cluster organization). The image simulation toolbox was shown to be useful in the validation of three cell tracking algorithms: Simple Nearest-Neighbour, Nearest-Neighbour with Morphology and DBSCAN cluster identification algorithm. It was shown that the Simple Nearest-Neighbour still performed with great reliability when simulating objects with small velocities, while the other algorithms performed better for higher velocities and when there were larger clusters present

The Role of Nucleoid Exclusion in the Intracellular Spatial Organization of Escherichia coli

Not long ago, bacterial cells were regarded as organisms with hardly any internal organization, due to lack of visible physical compartments and, thus, proteins were believed to be distributed randomly. Since then, advances in microscopy, in in vivo protein labeling with fluorescent tags, and in image analysis techniques have enabled us to probe biological events at a single-cell, singletime moment, and single-molecule level. The results from these observations have led to a radical change in this view and, thus, revolutionized the field of bacterial cell biology. Namely, this novel source of information has made evident that proper bacterial functioning is not possible without a highly spatially organized, dynamic internal composition that depends on the deployment of functional proteins and other cellular components in specific locations, at specific moments.The spatiotemporal organization of the functional proteins and other cellular components play a fundamental role in several key regulatory processes, such as transcription, translation and cell division. One class of proteins, termed as ‘DNA-binding proteins’, are associated with DNA replication and segregation. Not surprisingly, they preferentially locate at midcell, where the chromosomal DNA is condensed into a dynamic structure called ‘nucleoid’. Another class of proteins, termed as ‘polar proteins’, are majorly involved in physiological behaviors such as chemotaxis, sugar uptake, motility and adhesion. In agreement, they are preferentially localized at the cell poles in the case of rod-shaped bacteria such as E. coli. Finally, there is a third class of proteins, called as ‘cytoskeletal proteins’, whose location differ widely during cell growth. For example, the Min system, a major cell division regulatory system, consisting of MinCDE proteins have a remarkable dynamic pattern inside the cell. These proteins localize for about half a minute in one cell half and then switch rapidly to the opposite half. This back and forth motion continues until the polymerization of the division protein FtsZ results in a ring-like structure at the cell center prior to cell division.Cellular components, other than functional proteins, also exhibit a highly-organized spatial distribution. These components include plasmids, enzyme megacomplexes and unwanted protein aggregates. For example, protein aggregates, formed as a result of environment stress or errors in protein homeostasis, are generally sequestered into inclusion bodies (IBs) that localize at the cell poles. This process of polar localization is symmetric. However, following several cell division events, results in progeny cells containing the old pole having more aggregates than the new pole possessing progeny cells. Subsequent divisions lead to cell generations where some cells inherit more aggregates than others. Importantly, this was found to be positively correlated with increased division times, i.e., cellular aging. It is believed that such asymmetric partitioning of unwanted aggregates may be critical for the rejuvenation of bacterial populations. It is thus of major importance to understand the underlying mechanisms that are responsible for the above-described events.In this thesis, using Escherichia coli as our model organism, we started by investigating and validating the hypothesis that the presence of the nucleoid at the midcell is responsible for the ability of this organism to segregate unwanted protein aggregates to the cell poles. We next investigated and characterized the robustness of these mechanisms to external perturbations and stressful environmental conditions. Afterwards, we hypothesized that the phenomenon of nucleoid exclusion should not be limited to protein aggregates alone but, instead, for physical reasons, it should influence any large macromolecule that is not affected by a transport or self-propelling mechanism (which is the case of all proteins in E. coli). Consequently, we hypothesized and subsequently proved that it should influence self-assembling proteins, such as the transmembrane Tsr chemoreceptors, which have a major role in bacterial chemotaxis. In addition, we also investigated to what extent cell-to-cell diversity in nucleoid sizes contributes to the cell-to-cell diversity in the spatial distribution of polar-localized proteins. For these studies, we made use of efficient fluorescent tags, in vivo single-cell, single-molecule time-lapse microscopy, tailored image and signal processing techniques and stochastic biophysical models.Our results provide new perspectives regarding the role of the nucleoid in the spatial organization of protein aggregates as well as chemoreceptor clusters in E. coli. Interestingly, regarding the latter, nucleoid exclusion from midcell was shown not to be the sole phenomenon for the proper localization of Tsr protein clusters. However, it is expected to be the most robust, namely, in stressful environments or when the cell is subject to external perturbations, than the diffusion-andcapture mechanism mediated by the Tol-Pal complexes, as it does not require production of proteins or is under stringent control. Further, unlike the other mechanism, it is energy-free.Given the rapid developments in single-cell biology techniques, particularly the emergence of super-resolution microscopy techniques, improved fluorescent probes, high-throughput and largescale biochemical methods and theoretical tools, we expect several developments in the near future that will allow assessing further the role of the nucleoid as a ‘spatial organizer’ of the cellular architecture of E. coli

Regulation of Single-Cell Bacterial Gene Expression at the Stage of Transcription Initiation

One of the qualities that allow bacterial cells to survive in diverse, fluctuating environments is phenotypic plasticity, which is the ability to exhibit different phenotypes depending on the environmental conditions. Phenotypic plasticity arises via coordinated work of small genetic circuits that provide the cell with the means for decision-making. The behavior of these circuits depends, among other factors, on the ability of protein numbers to cross certain thresholds for a sufficient amount of time. In bacteria, RNA numbers largely define protein numbers and thus can be used to study the decision-making processes. Previous research outlined the effects of mean and variance in RNA or protein numbers on the behavior of small genetic circuits. However, noise in gene expression is often highly asymmetric. This could impact the threshold-crossing abilities of molecular numbers in a way that is not detectable by considering only their mean and variance. The focus of this thesis is to study the regulation of multi-step kinetics of bacterial gene expression in live bacteria and its effects on the shape of the distribution of RNA or protein levels. In particular, the thesis investigates how the rate-limiting steps in bacterial transcription, such as closed and open complex formation, intermittent inactive states, and promoter escape contribute to the dynamics of RNA numbers, and how this dynamics propagates to the distribution of protein levels in a cell population. This study made use of already existing techniques such as measurements at the single-RNA level and dynamically accurate stochastic modeling, complemented by the novel methodology developed in this work. First, the thesis introduced a new method for estimating the numbers of fluorescently tagged molecules present in a cell from time series data obtained by microscopy. This method allows improving the accuracy of the estimation when fluorescently tagged molecules are absent from the cell image for time intervals comparable with cell lifetime. Second, the new methodology for dissecting in vivo kinetics of rate-limiting steps in transcription initiation was proposed. Applying this methodology to study initiation kinetics at lac/ara-1 promoter provided insights on the amount, duration, and reversibility of the rate-limiting steps in this process. Further, the thesis investigated the kinetics of transcription activation of lac/ara-1 promoter at various temperatures. The results indicate that additional rate-limiting steps emerge in inducer intake kinetics as temperature decreases from optimal (37 °C). Finally, the focus was shifted specifically to quantifying the asymmetry and tailedness in RNA and protein level distributions, since these features are relevant for determining threshold crossing propensities. Here, these features were found to depend both on promoter sequence and on regulatory molecules, thus being evolvable and adaptable. Overall, the work conducted in this thesis suggests that asymmetries in RNA and protein numbers may be crucial for decision-making in bacteria, since they can be regulated by promoter sequence, regulatory molecules levels, and temperature shifts. The thesis also contributes to the pool of existing methodology for studying in vivo bacterial gene expression using single-cell biology approach. These findings should be of use both for better understanding of natural systems and for fine-tuning behavior of synthetic gene circuits

Rate-limiting Steps in Transcription Initiation are Key Regulatory Mechanisms of Escherichia coli Gene Expression Dynamics

In all living organisms, the “blueprints of life” are documented in the genetic material. This material is composed of genes, which are regions of DNA coding for proteins. To produce proteins, cells read the information on the DNA with the help of molecular machines, such as RNAp holoenzymes and a factors. Proteins carry out the cellular functions required for survival and, as such, cells deal with challenging environments by adjusting their gene expression pattern. For this, cells constantly perform decision- making processes of whether or not to actively express a protein, based on intracellular and environmental cues. In Escherichia coli, gene expression is mostly regulated at the stage of transcription initiation. Although most of its regulatory molecules have been identified, the dynamics and regulation of this step remain elusive. Due to a limited number of specific regulatory molecules in the cells, the stochastic fluctuations of these molecular numbers can result in a sizeable temporal change in the numbers of transcription outputs (RNA and proteins) and have consequences on the phenotype of the cells. To understand the dynamics of this process, one should study the activity of the gene by tracking mRNA and protein production events at a detailed level. Recent advancements in single-molecule detection techniques have been used to image and track individually labeled fluorescent macromolecules of living cells. This allows investigating the intermolecular dynamics under any given condition. In this thesis, by using in vivo, single-RNA time-lapse microscopy techniques along with stochastic modelling techniques, we studied the kinetics of multi-rate limiting steps in the transcription process of multiple promoters, in various conditions. Specifically, first, we established a novel method of dissecting transcription in Escherichia coli that combines state-of-the-art microscopy measurements and model fitting techniques to construct detailed models of the rate-limiting steps governing the in vivo transcription initiation of a synthetic Lac-ara-1 promoter. After that, we estimated the duration of the closed and open complex formation, accounting for the rate of reversibility of the first step. From this, we also estimated the duration of periods of promoter inactivity, from which we were able to determine the contribution from each step to the distribution of intervals between consecutive RNA productions in individual cells. Second, using the above method, we studied the a factor selective mechanisms for indirect regulation of promoters whose transcription is primarily initiated by RNAp holoenzymes carrying a70. From the analysis, we concluded that, in E. coli, a promoter’s responsiveness to indirect regulation by a factor competition is determined by its sequence-dependent, dynamically regulated multi-step initiation kinetics. Third, we investigated the effects of extrinsic noise, arising from cell-to-cell variability in cellular components, on the single-cell distribution of RNA numbers, in the context of cell lineages. For this, first, we used stochastic models to predict the variability in the numbers of molecules involved in upstream processes. The models account for the intake of inducers from the environment, which acts as a transient source of variability in RNA production numbers, as well as for the variability in the numbers of molecular species controlling transcription of an active promoter, which acts as a constant source of variability in RNA numbers. From measurement analysis, we demonstrated the existence of lineage-to-lineage variability in gene activation times and mean transcription rates. Finally, we provided evidence that this can be explained by differences in the kinetics of the rate-limiting steps in transcription and of the induction scheme, from which it is possible to conclude that these variabilities differ between promoters and inducers used. Finally, we studied how the multi-rate limiting steps in the transcription initiation are capable of tuning the asymmetry and tailedness of the distribution of time intervals between consecutive RNA production events in individual cells. For this, first, we considered a stochastic model of transcription initiation and predicted that the asymmetry and tailedness in the distribution of intervals between consecutive RNA production events can differ by tuning the rate-limiting steps in transcription. Second, we validated the model with measurements from single-molecule RNA microscopy of transcription kinetics of multiple promoters in multiple conditions. Finally, from our results, we concluded that the skewness and kurtosis in RNA and protein production kinetics are subject to regulation by the kinetics of the steps in transcription initiation and affect the single-cell distributions of RNAs and, thus, proteins. We further showed that this regulation can significantly affect the probability of RNA and protein numbers to cross specific thresholds. Overall, the studies conducted in this thesis are expected to contribute to a better understanding of the dynamic process of bacterial gene expression. The advanced data and image analysis techniques and novel stochastic modeling approaches that we developed during the course of these studies, will allow studying in detail the in vivo regulation of multi-rate limiting steps of transcription initiation of any given promoter. In addition, by tuning the kinetics of the rate-limiting steps in the transcription initiation as executed here should allow engineering new promoters, with predefined RNA and, thus, protein production dynamics in Escherichia coli

Effects of Intracellular and Partitioning Asymmetries in Escherichia coli

Cell divisions in Escherichia coli are, in general, morphologically symmetric. However, in a few cases, significant asymmetries between sister cells exist. These asymmetries between sister cells result in functional differences between them. For example, cells inheriting the older pole, over generations, accumulate more unwanted protein aggregates than their sister and, consequently, have a reduced growth rate. The reduced ability of these cells to reproduce shows that even these unicellular organisms are susceptible to the effects of aging. To understand senescence in these organisms, it is critical to investigate the sources as well as the functional consequences of asymmetries in division.In this thesis, we characterize mechanisms responsible for functional and morphological asymmetries in division in E. coli cells, using live, single-cell, single-molecule imaging techniques and detailed stochastic models. First, to understand the functional asymmetries due to the heterogeneous spatial distribution of large, inert protein complexes, we study the kinetics of segregation and retention of such complexes by observing these events, one event at a time. For that, we track individual MS2-GFP tagged RNA complexes, as they move in the cell cytoplasm, and characterize the mechanisms responsible for their long-term spatial distribution and resulting partitioning. Next, to understand the morphological asymmetries, we study the difference in cell sizes between sister cells at division under different environmental conditions. Finally, we present the models and simulators developed to characterize and mimic these processes, as well as to explore their functional consequences.Our results suggest that functional and morphological asymmetries in division, in the growth conditions studied, appear to be mostly driven by the nucleoid. In particular, we find that the fluorescent complexes are retained at the poles due to nucleoid occlusion. Further, the positioning of the point of division is also regulated by the degree of proximity between the two replicated nucleoids in the cell at the moment preceding division. Finally, based on simulation results of the models in extreme conditions, we suggest that asymmetries in these processes in division can enhance the mean vitality of E. coli cell populations. Overall, the results suggest that nucleoid occlusion contributes, in different ways, to heterogeneities in E. coli cells that ultimately generate phenotypic differences between sister cells

Studies of the plasticity of transcription in Escherichia coli using single-molecule, in vivo detection techniques

The phenotypic characteristics of living organisms are shaped by the interactions of the genotype with the environment. In their lifetime, organisms are subject to various environmental changes, some of which are stressful. They cope up with these by means of phenotypic plasticity. In prokaryotes, this plasticity is achieved mostly by rapid adaptations of the gene expression profile. To better understand this, it is critical to study the mechanisms by which these adaptations are implemented. In Escherichia coli, transcription initiation is the first and most regulated step in gene expression. In vitro studies suggest that this is a complex, sequential process. Its rate-limiting steps regulate both the rate and the fluctuations of RNA production. These then determine the protein numbers and, thus, the cellular phenotype. In this work, we make use of state-of-the-art techniques in microscopy imaging, image processing and molecular probing to perform a quantitative analysis of the in vivo dynamics of transcription initiation in different environments in the prokaryotic model organism, E. coli. From the measurements, we characterize the plasticity of this process. For this, we used MS2-GFP fluorescent tagging of mRNA that allows detection of single mRNA molecules with confocal microscopy, shortly after their production. We also developed a tool to automatically track cell lineages in a time-lapse movie, and extract the spatiotemporal distribution of fluorescently tagged molecules in individual cells. From the analysis of the results, we show that, in vivo, the process of transcription initiation in E. coli is multi-stepped, as in vitro measurements had previously suggested. Also, the kinetics of each step can be independently controlled by different regulatory molecules. Further, the number and timing of the rate-limiting steps are affected by physiological changes that occur in cells when subject to changing environmental conditions. We conclude that the phenotypic plasticity of E. coli arises, partially, from the plasticity of the kinetics of the rate-limiting steps in transcription initiation