The problem in this investigation is to determine the effects of various concentrations of sodium chloride upon the growth of three species of bacteria. An effort has been made to solve this problem, not only by a study of the relevant literature, but also by laboratory research consisting of cultivation and observation of the three organisms which were arbitrarily chosen for this study.

A mechanistic model was developed, which described the growth of a bacterial colony on an agar medium. Diffusion of substrate (nutrients/oxygen) through the colony are considered. Rate of substrate use by the organisms is assumed to follow Michaelis-Menton kinetics for substrate concentrations between prescribed limits. Above and below the prescribed concentration limits, the substrate use rate is assumed constant and zero, respectively. Supply of substrate to the colony was assumed to be non-limiting. Under these conditions, the model predicted that diffusion of substrate through the colony will eventually control colony growth. It also described a slower eponential growth rate of the colony when the organisms utilized an alternate substrate for one that became deficient throughout a portion of the colony, and a constant linear growth rate when an alternate substrate was not utilized. Consistent with published literature, a mathematical description of substrate supply through the agar indicated that, under normal conditions, glucose supply through the agar to the colony would not be expected to limit colony growth before oxygen diffusion through the colony limited growth.

The bacterial flora of groundwater obtained from wells and distribution sites was investigated from both an ecological and a public health perspective. A majority of the isolates were oxidase positive, non-fermentative, gramnegative bacilli. Extensive heterogeneity of groundwater microflora, as determined by biochemical characterization and antibiograms, was observed both within and among welldistribution (N-D) systems. Of the unique isolates (sorts) found in the W-D systems, 75% were resistant to 2 or more antibiotics at clinically significant concentrations. Community diversity within W-D systems was evaluated by rarefaction which failed to reveal a general trend. Standard plate counts in 2 of 3 wells were significantly higher on Standard Methods Agar diluted ten-fold than on the same medium at the standard concentration. Pseudomonas aeruginosa, Flavobacterium sp., Aeromonas hydrophila and Yersinia enterocolitica were detected in 21, 18, 7 and 3% respectively of water samples analyzed over a 12 month period. A selective medium was developed for the isolation of Flavobacterium sp. and was effective in suppressing 98% of the background flora when used in a membrane filtration (MF) procedure. Yersinia Selective Agar was employed in an MF procedure for the isolation of Y. enterocolitica. The use of anaerobic incubation in this procedure effectively suppressed background growth both in the presence and absence of an antimicrobic supplement. Anaerobic incubation of m-endo LES Agar (AN-MF) was effective in suppressing non-coliform growth in the total coliform MF test and markedly reduced the frequency of overgrown plates. The AN-MF appeared to obviate the need for selective chemical agents and thus has potential value in the isolation of stressed coliforms.

Cyanide is a well known toxicant that arises in the environment from both biological and industrial sources. Bacteria have evolved novel coping mechanisms for cyanide and function as principal agents in the biosphere for cyanide recycling. Some bacteria exhibit the unusual ability of growing on cyanide as the sole nitrogen source. One such organism is Pseudomonas fluorescens NCIMB 11764 (Pf11764) which employs a novel oxidative mechanism for detoxifying and assimilating cyanide. A unique complex of enzymes referred to as cyanide oxygenase (CNO) is responsible for this ability converting cyanide to ammonia which is then assimilated. Because one component of the four member CNO complex was previously shown to act on cyanide independent of the other members, its characterization was sought as a means of gaining a better understanding of the overall catalytic mechanism of the complex. Preliminary studies suggested that the enzyme belonged to a subset of nitrilase enzymes known as cyanide dihydratases (CynD), however, a cynD-like gene in Pf11764 could not be detected by PCR. Instead, a separate nitrilase (Nit) linked to cyanide metabolism was detected. The corresponding nit gene was shown to be one of a conserved set of nit genes traced to a unique cluster in bacteria known as Nit1C. To determine whether the previously described CynD enzyme was instead Nit, efforts were undertaken to isolate the enzyme. This was pursued by cloning and expressing the recombinant enzyme and by attempting to isolate the native enzyme. This thesis is concerned with the latter activity and describes the purification of a Nit-like cyanide-degrading nitrilase (NitCC) from Pf11764 to ~95% homogeneity. Purification was greatly facilitated by the discovery that fumaronitrile, as opposed to cyanide, was the preferred substrate for the enzyme (20 versus 1 U/mg protein, respectively). While cyanide was less effective as a substrate, the specificity for cyanide far outweighed that (10,000 fold) of the recombinant enzyme (NitPG) implying that the native NitCC protein purified in this work is different from that of the cloned recombinant. Further evidence of this was provided by molecular studies indicating that the two proteins differ in mass (34.5 and 38 kDa, respectively) and amino acid sequence. In summary, two different Nit enzymes are encoded by Pf11764. While the two share greater than 50% amino acid sequence identity, the results suggest that the native NitCC enzyme purified in this work functions better as a cyanide-degrading nitrilase and is one of four enzyme components comprising CNO required for Pf11764 cyanide assimilation.

<p>Recent technological advances enable us to examine bacterial population dynamics with high temporal resolution with capacity for collecting high throughput data. Precise quantification of bacterial population dynamics can help us to further extend our understanding of how bacteria respond to environmental conditions. Such analysis provides critical information for improving antibiotic treatment protocols and for predictable engineering cellular behavior with synthetic gene circuits. </p><p>A fundamental question in bacterial population dynamics is how fast bacteria are killed in response to antibiotics. Due to their mode of action, β-lactams are more effective against fast-growing bacteria than against slow-growing bacteria. Indeed, it has been recognized that the rate of lysis by β-lactam antibiotics depends on the growth rate of the bacteria, based on previous works. However, past studies examined the growth rate modulation of lysis only during balanced growth and for very limited combinations of bacteria and drugs. Although there is evidence that growth plays key role in determining bacterial response to antibiotics, more comprehensive understanding on how wide range of growth rates affect antibiotic dose response had been overlooked. Instead, bacterial growth has been largely described to be in either growing or non-growing states. </p><p>To examine the general applicability of this growth rate dependence of antibiotic response, I examined how growth rate influences the lysis rate induced by beta-lactams. I found that there is a robust correlation between growth and lysis rates beyond what had been demonstrated in the previous work. Even during unbalanced growth, and regardless of how growth rate was modulated, the robust correlation between growth and lysis rates in bacterial populations were observed. Also, my data suggested a striking versatility of this correlation in different bacterial specie-drug pairs. Thus, my quantification greatly expands previous work by further examining the dependence of lysis rate on growth rate, and extends our understanding of the phenomenon associated with β-lactam antibiotic treatment, and of possible consequences arising from variable lysis rate. My strategy on modulating growth rates and measuring corresponding lysis rates demonstrates a simple and robust method for examining this phenomenon. These results have direct implications in two aspects.</p><p> First, my quantification method allows greater degree of freedom in modulating growth states of bacteria. Indeed, I was able to examine a wide range of growth rates in bacteria that allowed analyses of robust correlation in growth and lysis rates. The simple correlation reported from my work suggests the underlying reasoning for slow or fast lysis of bacterial population that can lead to designing optimal protocols depending on the growth rates of bacterial population. Due to frequent observation of slow-growing cells under conditions such as biofilm of pathogenic bacteria that complicates clinical symptoms and treatments in patients, they have been an important aspect of study for antibiotic tolerance. A quantitative understanding of the robust correlation between growth and lysis rates is critical for designing effective treatment protocols using β-lactams. </p><p> Second, the robust correlation serves as a foundation for predicting dynamics of synthetic gene circuits engineered for practical applications. In my work, I developed a prototype microbial swarmbot, which employs spatial arrangement to control growth dynamics of engineered bacteria. I demonstrated an engineered safeguard strategy to prevent unintended bacterial proliferation with this platform technology. In this work, I adopted several synthetic gene circuits to program collective survival in Escherichia coli: the engineered bacteria could only survive when present at sufficiently high population densities. When encapsulated by permeable membranes, these bacteria can sense the local environment and respond accordingly. The cells inside microbial swarmbots will survive due to their high densities. Those escaping from a capsule, however, will be killed due to a decrease in their densities. In this work, using antibiotics to control growth dynamics of the engineered populations was critical, and optimization of the growth dynamics depended on their environmental conditions that modulated their growth rates.</p><p>Together, my investigation on quantifying and analyzing bacterial growth dynamics demonstrated that understanding of bacterial population dynamics is crucial in addressing antibiotic tolerance in bacteria as well as in using them for engineered functions. By further examining the dependence of lysis rate on growth rate, we extended our understanding of the phenomenon associated with β-lactam antibiotic treatment, and of possible consequences arising from variable lysis rate. This information is important in designing a modular and readily generalizable platform technology as well. Therefore, my work demonstrates quantitative approach towards understanding of bacterial populations, and lays the foundation for engineering integrated and programmable control of hybrid biological-material systems for diverse applications.</p> / Dissertation

High performance liquid chromatography was used to measure ribonucleoside triphosphates in microbial samples. Anion exchange columns in a radial compression module were used to separate and quantify purine and pyrimidine ribonucleotides. Endogenous ribonucleoside triphosphates were extracted from Escherichia coli and pseudomonas aeruginosa using three different solvents, namely trifluorocetic acid (TFA; 0.5M), trichloroacetic acid (TCA; 6 per cent w/v) and formic acid (1.0M) Extracts were assayed for uridine 5'-triphosphate (ATP), and guanosine 5'-triphosphate (GTP) by using anion exchange radial compression high performance (pressure) liquid chromatography. The three extraction produres were compared for yield of triphosphates. E. coli, the TFA extraction procedure was more sensitive and reliable than TCA and formic acid extraction procedures, but , in P. aeruginosa, the best yields of ATP and GTP were obrained following extraction with TFA. Yields of UTP and CTP increased when extraction was performed in TCA. These data illustrate that different extraction produres produce different measures for different triphosphates, a point often overlooked.

Cette thèse porte sur la modélisation, l'analyse et le contrôle de réseaux de régulation génétique dans la bactérie E. Coli, avec les outils de la Théorie du Contrôle. On utilise plusieurs formalismes (qualitatif/quantitatif, déterministe/stochastique) pour décrire les différents systèmes. Dans la première partie de la thèse, on considère le problème du contrôle du taux de croissance pour les bactéries. Le taux de croissance est une caractéristique essentielle pour l'industrie des biotechnologies, et cette recherche peut ouvrir la voie à de nouvelles stratégies antimicrobiennes. Nous avons développé de nouveaux formalismes qualitatifs, basé sur les systèmes affines par morceaux différentiels, qui couplent l'expression des gènes et la croissance. Nous appliquons ces formalismes à de petits modèles de circuits génétiques synthétiques (conçus avec nos collaborateurs de Ibis, Inria Grenoble), et étudions des boucles de contrôle ouvertes ou fermées. Par une étude du portrait de phase et des bifurcations, nous montrons que la stratégie qualitative de contrôle proposée, qui agit sur la machinerie cellulaire globale, permet de contrôler le taux de croissance. Pour trouver les composants les plus représentatifs de cette machinerie cellulaire, nous testons plusieurs modèles de taux de croissance, avec des outils de calcul booléens. Dans la seconde partie de la thèse, nous développons un modèle simplifié de la machinerie cellulaire globale chez E. Coli, basé sur des équations différentielles, et dont les paramètres sont identifiés à partir de données de la littérature pour plusieurs taux de croissance. / This thesis deals with modelling, analysis and control of gene regulatory networks in the bacterium E. coli, with tools of Control Theory. Different mathematical methodologies (qualitative/quantitative, deterministic/stochastic) have been used to best describe the different biological systems under investigation. Notably, in the first part of the thesis we mainly addressed the problem of controlling the growth rate of bacterial cells. Growth control is essential in industrial biotechnology and fundamental research of this kind could pave the way to novel types of antimicrobial strategies. To this aim we developed new qualitative mathematical formalisms, derived from piecewise linear systems, to couple gene expression with growth rate. We applied these formalisms to small E. coli synthetic gene circuit models (conceived with our collaborators from Ibis, Inria Grenoble) implementing both open and closed loop configurations. By means of phase plane analysis and bifurcation diagrams we showed that the proposed qualitative control strategies, which act on the gene expression machinery (GEM), can mathematically control the cell growth rate. Moreover, in order to identify the key components of GEM that mostly determine the bacterial growth rate, we also tested several growth rate models using Boolean computational tools. In the second part of the thesis, we developed a coarse-grained, but quantitative, ODE model of E. coli GEM whose parameter values have been identified from published experimental data at different steady state growth rate values.

This thesis aimed to investigate the role of alveolar epithelial cells (AEC) on immune responses against mycobacterial infections, specifically, the role of AEC in modulating macrophage functions through the secretion of broad variety of factors. In paper I, we compared murine AEC with interstitial macrophages (PuM) in their ability to take up and control mycobacterial growth and their capacity as antigen-presenting cells. We found that AEC were able to internalize and control bacterial growth and present antigens to T cells from immunized mice. In addition, both AEC and PuM exhibited distinct patterns of secreted factors, and a more comprehensive profile of AEC responses revealed that AEC were able to secrete different factors important to generate various effects in other cells. Paper II: Since AEC secrete a broad variety of factors, we hypothesized that being in the interface; AEC may play an important role in transmitting signals from the external to the internal compartment and in modulating the activity of PuM. Thus, we prepared AEC-derived media and tested their effect on bacteria and a number of macrophage functions a) migration, b) phagocytosis and control of intracellular bacterial growth, and c) alteration in cell morphology and expression of surface markers. We found that AEC-secreted factors had a dual effect, in one hand controlling bacterial growth and on the other hand increasing macrophage activity. In paper III, we first investigated the responsible mechanisms of intracellular bacterial growth control mediated by AEC-derived media. We found that infected macrophages upon AEC-secreted factors increased the control of intracellular bacterial growth by iNOS-independent pathways. Compared with other macrophage types, PuM, did not control the intracellular bacterial growth upon the well-known potent macrophage activator, IFN-γ. We found that SOCS1 was involved in the un-responsiveness to IFN-γ by PuM to control the intracellular bacterial growth. We suggested that PuM are restricted in their inflammatory responses perhaps for avoiding tissue damage. Overall, the current findings highlight the importance of AEC in the defense against bacterial infection in the lungs by secreting factors involved in activation and differentiation of immune cells such as macrophages. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p>

La microbiologia predictiva és una de les parts més importants de la microbiologia dels aliments. En el creixement d'un cultiu bacterià es poden observar quatre fases: latència, exponencial, estacionària i mort. La fase de latència té un interès específic en microbiologia predictiva; al llarg de dècades ha estat abordada des de dues perspectives diferents: a nivell cel·lular i intracel·lular (escala microscòpica), i a nivell de població (escala macroscòpica). La primera estudia els processos que tenen lloc a l'interior dels bacteris durant la seva adaptació a les noves condicions del medi, com els canvis en l'expressió gènica i en el metabolisme. La segona descriu l'evolució de la població bacteriana per mitjà de models matemàtics continus i d'experiments que avaluen variables relacionades amb la densitat cel·lular. L'objectiu d'aquest treball és millorar la comprensió de la fase de latència dels cultius bacterians i dels fenòmens intrínsecs a la mateixa. Aquest objectiu s'ha abordat amb la metodologia Individual-based Modelling (IbM) amb el simulador INDISIM (INDividual DIScrete SIMulation), que ha calgut optimitzar. La IbM introdueix una perspectiva mecanicista a través de la modelització de les cèl·lules com a unitats bàsiques. Les simulacions IbM permeten estudiar el creixement d'entre 1 i 106 bacteris, així com els fenòmens que emergeixen de la interacció entre ells. Aquests fenòmens pertanyen al que anomenem escala mesoscòpica. Aquesta perspectiva és imprescindible per entendre l'efecte en la població dels processos d'adaptació individuals. Per tant, la metodologia IbM és un pont entre els individus i la població o, el que és el mateix, entre els models a escala microscòpica i a escala macroscòpica.En primer lloc hem estudiat dos dels diversos mecanismes que poden causar la fase de latència: inòculs amb massa mitjana petita, i canvis de medi.S'ha verificat també la relació de la durada de la latència amb variables com la temperatura o la grandària de l'inòcul. En aquest treball s'ha identificat la distribució de biomassa del cultiu com una variable cabdal per analitzar l'evolució del cultiu durant el cicle de creixement. S'han definit les funcions matemàtiques que anomenem distàncies per avaluar quantitativament l'evolució d'aquesta distribució.Hem abordat, també, la fase de latència des d'un punt de vista teòric. L'evolució de la velocitat de creixement al llarg del cicle ha permès distingir dues etapes en la fase de latència que anomenem inicial i de transició. L'etapa de transició s'ha descrit per mitjà d'un model matemàtic continu validat amb simulacions INDISIM. S'ha constatat que la fase de latència ha de ser vista com un procés dinàmic, i no com un simple període de temps descrit per un paràmetre. Les funcions distància també s'han utilitzat per avaluar les propietats del creixement balancejat.Alguns dels resultats de les simulacions amb INDISIM s'han corroborat experimentalment per mitjà de citometria de flux. S'ha comprovat, al llarg de les diverses fases del creixement, el comportament de la distribució de biomassa previst per simulació, així com l'evolució de les funcions distància. La coincidència entre els resultats experimentals i els de simulació no és trivial, ja que el sistema estudiat és molt complex. Per tant, aquests resultats permeten comprovar la bondat de la metodologia INDISIM.Finalment, hem avançat en l'optimització d'eines per parametritzar IbMs, un pas essencial per poder utilitzar les simulacions INDISIM de manera quantitativa. S'han adaptat i assajat els mètodes grid search, NMTA i NEWUOA. Aquest darrer mètode ha donat els millors resultats en termes de temps, mantenint una bona precisió en els valors òptims dels paràmetres. Per concloure, podem afirmar que INDISIM ha estat validat com una bona eina per abordar l'estudi dels estats transitoris com la fase de latència. / Predictive food microbiology has become an important specific field in microbiology. Bacterial growth of a batch culture may show up to four phases: lag, exponential, stationary and death. The bacterial lag phase, which is of specific interest in the framework of predictive food microbiology, has generally been tackled with two generic approaches: at a cellular and intracellular level, which we call the microscopic scale, and at a population level, which we call the macroscopic scale. Studies at the microscopic level tackle the processes that take place inside the bacterium during its adaptation to the new conditions such as the changes in genetic expression and in metabolism. Studies at the macroscopic scale deal with the description of a population growth cycle by means of mathematical continuous modelling and experimental measurements of the variables related to cell density evolution.In this work we aimed to improve the understanding of the lag phase in bacterial cultures and the intrinsic phenomena behind it. This has been carried out from the perspective of Individual-based Modelling (IbM) with the simulator INDISIM (INDividual DIScrete SIMulation), which has been specifically improved for this purpose. IbM introduces a mechanistic approach by modelling the cell as an individual unit. IbM simulations deal with 1 to 106 cells, and allow specific study of the phenomena that emerge from the interaction among cells. These phenomena belong to the mesoscopic level.Mesoscopic approaches are essential if we are to understand the effects of cellular adaptations at an individual level in the evolution of a population.Thus, they are a bridge between individuals and population, or, to put it another way, between models at a microscopic scale and models at a macroscopic scale.First, we studied separately two of the several mechanisms that may cause a lag phase: the lag caused by the initial low mean mass of the inoculum, and the lag caused by a change in the nutrient source. The relationship among lag duration and several variables such as temperature and inoculum size were also checked. This analysis allowed identification of the biomass distribution as a very important variable to follow the evolution of the culture during the growth cycle. A mathematical tool was defined in order to assess its evolution during the different phases of growth: the distance functions.A theoretical approach to the culture lag phase through the dynamics of the growth rate allowed us to split this phase into two stages: initial and transition. A continuous mathematical model was built in order to shape the transition stage, and it was checked with INDISIM simulations. It was seen that the lag phase must be defined as a dynamic process rather than as a simple period of time. The distance functions were also used to discuss the balanced growth conditions.Some of the reported INDISIM simulation results were subjected to experimental corroboration by means of flow cytometry, which allow the assessment of size distributions of a culture through time. The dynamics of biomass distribution given by INDISIM simulations were checked, as well as the distance function evolution during the different phases of growth. The coincidence between simulations and experiments is not trivial: the system under study is complex; therefore, the coincidence in the dynamics of the different modelled parameters is a validation of both the model and the simulation methodology.Finally, we have made progress in IbM parameter estimation methods, which is essential to improve quantitative processing of INDISIM simulations.Classic grid search, NMTA and NEWUOA methods were adapted and tested, the latter providing better results with regard to time spent, which maintains satisfactory precision in the parameter estimation results.Above all, the validity of INDISIM as a useful tool to tackle transient processes such as the bacterial lag phase has been amply demonstrated.

Thesis (M.S.)--University of Michigan, 1970.