Within-host phenotypic evolution and the population-level control of chronic viral infections by treatment and prophylaxis

Chronic viral infections can persist in an infected person for decades. From the perspective of the virus, a single infection can span thousands of generations, leading to a highly diverse population of viruses with its own complex evolutionary history. We propose a mathematical framework for understanding how the emergence of new viral strains and phenotype within infected persons affects the population-level control of those infections by both non-curative treatment and chemo-prophylactic measures. We consider the within-host emergence of new strains that lack phenotype novelty and also the evolution of variability in contagiousness, resistance to therapy, and efficacy of prophylaxis. Our framework balances the need for verisimilitude with our desire to retain a model that can be approached analytically. We show how to compute the population-level basic reproduction number accounting for the within-host evolutionary process where new phenotypes emerge and are lost in infected persons, which we also extend to include both treatment and prophylactic control efforts. This allows us to make clear statements about both the global and relative efficacy of different control efforts accounting for within-host phenotypic evolution. Finally, we give expressions for the endemic equilibrium of these models for certain constrained versions of the within-host evolutionary model providing a potential method for estimating within-host evolutionary parameters from population-level genetic sequence data

Processes and Rates of Bacterial Evolution

A long-standing question in evolutionary biology is whether adaptation will typically proceed through a few mutations with large selective effects or many mutations with small effects. Many studies have implicated few loci of major effect, but it has been predicted that small-effect mutations should exist and contribute to adaptation. However, such mutations have not been found in many studies, either because they do not exist or because the experimental design limited their detection. To determine the effects and types of mutations contributing to adaptation, I studied laboratory and wild populations of bacteria. I characterized the distribution of the effect sizes in laboratory populations of an aerobic bacterium, Methylobacterium extorquens, and studied the types of genetic changes associated with adaptation to a novel host in wild populations of Mycoplasma gallisepticum

Nestedness and Modularity in Bipartite Networks

Bipartite networks are a useful way of representing interactions between two sets of entities. Understanding the underlying structures of such networks may give insights into the functionality and behaviour of the systems they represent. Two important structural patterns identified in bipartite networks are nestedness and modularity. Nestedness describes a hierarchical ordering of nodes such that more specialised nodes have interactions with a subset of the partners with which the more generalised nodes interact. Modularity captures the community structure of a network as distinct clusters of interactions, such that there are more connections within communities than between communities. While these network architectures are easy to describe in writing, their quantitative measurement for a given network is a difficult task. Several different methods have been proposed in each case and it is currently unclear which of them should be used in practice. This thesis considers the use, measurement and interpretation of nestedness and modularity in bipartite networks. First, it is shown how bipartite networks can be an effective tool for linking data and theory in community ecology, though use of a coevolutionary model of virus-bacteria interactions. Next, a series of studies is presented that push towards clarification of the best procedures to measure nestedness and modularity in bipartite networks. Robustness of nestedness measures is tested on a synthetic ensemble of networks, showing that apparent nestedness depends strongly on the choice of measure, null model and effect size statistics. Recommendations for performing nestedness are made with relation to individual and cross-network comparisons. Additionally, a new algorithm for identifying weighted modularity is proposed that can be shown to outperform existing methods. Crucially, it is shown that quantitative modular structures differ from traditional binary modular structures with implications for how modularity is reported and used. Improving the way in which nestedness and modularity are measured is a necessary step for integrating data and theory in bipartite networks.University of Exete

Rich dynamics in multi-strain models:non-linear dynamics and deterministic chaos in dengue fever epidemiology

Tese de doutoramento (co-tutela), Biology (Population Biology), Vrije Uiversity Amesterdam, Universidade de Lisboa, 2012Throughout human history, infectious diseases have caused debilitation and pre- mature death to large portions of the human population, leading to serious social- economic concerns. Many factors have contributed to the persistence and increa- se in the occurrence of infectious disease (such as demographic factors, political, social and economic changes, environmental change, public health care and infra- structure, microbial adaptation, etc.). According to the World Health Organiza- tion (WHO), are the second leading cause of death globally after cardiovascular diseases (WHO, 2010). In recent years, mathematical modeling became an im- portant tool for the understanding of infectious disease epidemiology and has led to great advances in conceiving disease control strategies, including vaccination programs. One of the most important infectious diseases is dengue, a major international public health concern with more than 55% of world population at risk of acquiring the infection. Dengue is a viral mosquito-borne infection, a leading cause of illness and death in the tropics and subtropics. Dengue fever is caused by four antigenically distinct viruses, designated dengue types 1, 2, 3 and 4. Infection by one serotype confers life-long immunity to only that serotype, and temporary cross-immunity to other related serotypes. The temporary cross-immunity period lasts from three to nine months and it is related to antibody levels created during the immune response to a previous dengue infection. It is stated that such high antibody levels would be enough to protect the individual against an immediately new dengue infection caused by a different but related serotype. Two variants of the disease exist: dengue fever (DF), a non-fatal form of illness, and dengue hemorrhagic fever (DHF), which may evolve toward a severe form known as dengue shock syndrome (DSS). Epidemiological studies support the association of DHF with secondary dengue infection. There is good evidence that sequential infection increases the risk of developing DHF due to a process described as antibody-dependent enhancement (ADE), where the pre-existing antibodies to previous dengue infection cannot neutralize but rather enhance the new infection. Treatment of uncomplicated dengue cases is only supportive, and severe den- gue cases requires careful attention to fluid management and proactive treatment of hemorrhagic symptoms. A vaccine against dengue is not yet available, since it would have to simulate a protective immune response to all four serotypes, although several candidates of tetravalent vaccines are at various stages of de- velopment. So far, prevention of exposure and vector control remain the only alternatives to prevent dengue transmission. In recent years, mathematical modeling became an interesting tool for the un- derstanding of infectious diseases epidemiology and dynamics. A series of deter- ministic compartment models such as Susceptible-Infected (SI) and Susceptible- Infected-Recovered (SIR) for example, have been proposed based on the flow patterns between compartments of hosts. The SIR epidemic model divides the population into three classes concerning the disease stages: susceptible (S), In- fected (I) and Recovered (R). This model framework can represent infectious diseases where waning immunity can happen. Assuming that the transmission of the disease is contagious from person to person, the susceptibles become infected and infectious, are cured and become recovered. After a waning immunity period, the recovered individual can become susceptible again to reinfection. Multi-strain dynamics, such as dengue epidemiology, are generally modeled with extended SIR-type models. Dengue fever dynamic is well known to be particularly complex with large fluctuations of disease incidences. To capture differences in primary and secondary dengue infections, a two-strain SIR-type model for the host population has to be considered. Dengue models including multi-strain interactions via ADE, but without temporary cross-immunity, have shown already deterministic chaos when strong infectivity on secondary infection was assumed. The addition of the temporary cross-immunity period in such models brings a new chaotic attractor in wider and unexpected parameter region. In this thesis we present different extensions of the classical single-strain SIR model motivated by modeling dengue fever epidemiology with its peculiar ADE phenomenology. We focus on a minimalistic model, where the notion of at least two different strains is needed to describe differences between primary and se- condary dengue infections. The models divide the host population into suscepti- ble, infected and recovered individuals with subscripts for the respective strains. The individuals can be (1) susceptibles without a previous dengue infection; (2) infected and recovered for the first time; (3) susceptible with an experienced pre- vious dengue infection and (4) infected for the second time with a different strain, more likely to be hospitalized due to the ADE effect leading to severe disease. Our analysis shows a rich dynamic structure, including deterministic chaos in wi- der and more biologically realistic parameter regions, just by adding temporary cross-immunity to previously existing dengue models. In Chapter 1 we present the properties of the basic SIR epidemic model applied to infectious diseases. A summary of the analysis of the dynamics identifying the thresholds and equilibrium points in order to introduce notation and terminology are presented. These results were then generalized to a more advanced models motivated by dengue fever epidemiology. In Chapter 2 the basic two-strain SIR- type model motivated by modeling dengue fever epidemiology is presented. In this chapter we focused on the multi-strain aspect and its effects on the host population. The effects of the vector dynamics or seasonality is taken in account only by the effective parameters of the SIR-type model, but these mechanisms are not modeled explicitly. In Chapter 3 a detailed bifurcation analysis for the basic multi-strain dengue model is presented where the ADE parameter A and the temporary cross-immunity parameter R are studied. In Chapter 4 the seasonally forced system with temporary cross-immunity and possible secondary infection is analyzed. This study was motivated by dengue hemorrhagic fever monitoring data. The role of seasonality and import of infected individuals are now considered as biologically relevant effects to determine the dynamical behavior of the system. A comparative study between three different scenarios (non-seasonal, low seasonal and high seasonal with a low import of infected individuals) is presented. The extended models show complex dynamics and qualitatively a good agreement between empirical DHF monitoring data and the obtained model simulation. At the moment only such minimalistic models have a chance to be qualitati- vely understood well and eventually tested against existing data. The simplicity of the model (low number of parameters and state variables) offer a promising perspective on parameter values inference from the DHF case notifications. Such a technical parameter estimation is notoriously difficult for chaotic time series due to the long term unpredictability versus short term predictability. Recent- ly, this short term predictability has been used for temporally local approaches in statistical inference on the cost of difficulty in obtaining a final definite best answer to the parameter estimation problem. Being able to predict future outbreaks of dengue in the absence of human interventions is a major goal if one wants to understand the effects of control measures. Even after a dengue virus vaccine has become accessible or available, this holds true for the implementation of a vaccination program. For example, to perform a vaccine trial in a year where the disease epidemic generate a low number of cases, would make the statistical tests of vaccine efficacy much more difficult compared with the information provided by a vaccine trial performed in a epidemic year with much higher numbers of cases. Thus predictability of the next season’s height of the dengue peak, on the basis of deterministic balance of infected and susceptible, would be of major practical use. Although the fact that disease propagation is an inherently stochastic phe- nomenon, dengue models are mainly expressed mathematically as a set of de- terministic differential equations, which are easier to analyze. The mean field approximation, an approximation of stochastic processes leading to deterministic dynamics, is a good approximation to be used in order to understand better the behavior of the stochastic systems in certain parameter regions, where the dyna- mics of the mean quantities are approximated by neglecting correlations. Howe- ver, it is only stochastic, as opposed to deterministic, models that can capture the fluctuations observed in some of the available time series data. In Chapter 5 the stochastic version of the minimalistic multi-strain model is presented. In this chapter we investigate the interplay between stochasticity, seasonality and impor- ted cases of the disease. The introduction of stochasticity reveal a scenario where noise and complex deterministic skeleton strongly interact. For large enough population size, the stochastic system could be well described by the determinis- tic skeleton, where the essential dynamics are captured, gaining insight into the relevant parameter values purely on topological information of the dynamics. The two-strain dengue model is a 9 dimensional system and therefore, future statistical inference can still attempt to estimate all initial conditions as well as the few model parameters. Concerning data availability, long term epidemiologi- cal data consist on monthly incidences of hospitalized DHF cases. For such a data scenario, models that are able to generate both primary and secondary infection cases (with a different strain, without the need of considering differences on the dynamics of different co-circulating dengue serotypes), have shown a good quali- tative agreement between empirical data and model output (see Chapter 4 and Chapter 5). These results were obtained just by combining the ADE effect, ge- nerating difference in transmissibility on primary and secondary infections, with the temporary cross-immunity aspect. Differently from the minimalistic dengue model, the four-strain model is mathematically represented by a system of 26 ODE’ s. It becomes a very high dimensional system and obviously very difficult to be used for parameter inference due to the high number of initial conditions. In Chapter 6 we present the multi-strain dengue model for the four existing se- rotypes. For four different strains, 1, 2, 3 and 4, we now label the SIR classes for the hosts that have seen each one of the possible strains. Again, without epidemi- ological asymmetry between strains, once the serotype data are recent and very short to give any realistic information concerning difference in biological parame- ters (such as infection and recovery rates) for a given strain. In this chapter we present the bifurcation diagram comparison for both two-strain and four-strain model. In the relevant parameter region of < 1, when dengue patients in a secondary infection evolving to severe disease due to the ADE phenomenon con- tribute less to the force of infection, the bifurcation points appear to happen at similar parameter regions, well below the region of interest 1. We conclude that the two-strain model in its simplicity is a good model to be analyzed giving the expected complex behavior to explain the fluctuations observed in empirical data. Statistical inference to estimate the basic parameters of transmission, infectivity, disease severity (ADE parameter) and temporary cross-immunity period using empirical data of incidence of severe disease is needed to identify eventual deviations from the simplest symmetric case investigated here. Further work on the parameter estimation using the minimalistic dengue model is in progress. The vector dynamics might also play a role in understanding the final picture when comparing the model output with the available empirical data. Following the investigations described in this thesis, a number of research directions could be addressed, involving the minimalistic dengue model. Future work would be to investigate extensions of the multi-strain model to address the following questi- ons and issues: (1) How much (more or less than first infection) does secondary infection contribute to the force of infection? (2) Does there exist a difference between the forces of infection for the different strains and to what extent can the bifurcation structure explain the viral diversity contribution? (3) Formulate hy- potheses using the mechanism of temporary cross-immunity suitable to recurrent infections protection. (4) Model the vaccine trials based on short term predic- tability of chaotic systems to be applied when tetravalent vaccines will become available. And (5) propose targets for intervention and control design according to the expected impact of the disease. My special interest would be to get the model fully parametrized on data referring to incidence of severe disease and pre- valence of infection. With such a model framework we would be able to give an insight into the predictability of upcoming dengue outbreaks. This epidemiolo- gical tool would help to understand the effects of control measures and therefore to guide the policies of prevention and control of the dengue virus transmissionAo longo da história, as doenças infecciosas veem causado o enfraquecimento e morte prematura de grandes parte da população humana, gerando sérias preocupações sociais e económicas. Muitos são os fatores quem têm contribuído para a persistência e o aumento na ocorrência de doenças infecciosas, tais como factores demográficos, mudanças políticas, sociais e económicas, mudanças ambientais, adaptação microbiana, etc. Segundo a Organizão Mundial de Saúde (OMS), as doenças infecciosas são a segunda principal causa de morte no mundo, depois das doenças cardiovasculares (WHO, 2010). Dentre as doenças transmissíveis mais preocupantes, o dengue ´e, de acordo com a OMS, um problema de saúde pública internacional, com mais de 55% da população mundial vivendo em áreas com risco de transmissão da infecção. O dengue, uma infecção ao viral transmitida por mosquitos, é uma das principais causas de doença e morte nos trópicos e subtrópicos. A infecção pelo vírus do dengue pode ser causada por qualquer uma das quatro cepas existentes, designadas por serotipos DEN − 1, DEN − 2, DEN − 3 e DEN − 4. Estes serotipos são distintos, porém, antigenicamente relacionados. A infecção gerada por um determinado serotipo confere imunidade total e permanente (ao longo da vida) para apenas aquele serotipo, e também imunidade cruzada temporária para os outros serotipos. A imunidade cruzada temporária tem uma duração estimada que varia de três a nove meses, e está relacionada com os n´níveis de anticorpos gerados durante a resposta imune a uma primeira infecção pelo vírus do dengue. Afirma-se que o alto nível destes anticorpos seria suficiente para a proteção contra outras infecções causadas por patogenos antigenicamente relacionados. O dengue pode se manifestar em duas formas clínicas: dengue clássico (DC), uma forma não-fatal da doença, e dengue hemorrágica (DH), que pode evoluir para uma forma muito grave conhecida como síndrome do choque do dengue (DSS). Estudos epidemiológicos associam os casos graves da doença (DH) com a segunda infecção do dengue. Existem boas evidências relacionando as infecções sequenciais pelos vírus do dengue e o aumento para os riscos do desenvolvimento do dengue hemorrágico. Esta associação se deve a um processo imunológico chamado de antibody-dependent enhancemet (ADE). O antibody-dependent enhan- cement ocorre quando os anticorpos pré-existentes, provenientes de uma primeira infecção do dengue, não neutralizam mas sim realçam a nova infecção pelo vírus do dengue. Não existe uma medicação específica para a infecção do dengue. O tratamento dos casos de dengue clássico é apenas de suporte e para os casos de dengue hemorrágico a hospitalização é frequentemente necessária para obtenção de um tratamento adequado. A vacina contra o dengue ainda não está disponível, uma vez que terá que simular proteccão para todos os quatro serotipos existentes. Atu- almente, algumas vacinas candidatas encontram-se em diversos estágios de desenvolvimento. Até o presente momento, a prevenção na exposição e o controle dos vetores são as únicas alternativas para a prevenção da transmissão do dengue. A modelação matemática tornou-se uma ferramenta importante para a compreensão da epidemiologia e da dinâmica das doenças infecciosas. Uma série de modelos deterministicos, tais como o modelo Susceptível-Infectado (SI) e o modelo Susceptível-Infectado-Recuperado (SIR), por exemplo, têm sido propostos com base nos padrões de fluxo para cada um dos compartimentos representando os estágios da doença. O modelo epidemiológico SIR divide a população de indivíduos em três classes: Susceptíveis (S), Infectados (I) e Recuperados (R). Este tipo de modelo pode ser utilizado para representar, por exemplo, as doenças infecciosas que não conferem imunidade permanente, possibilitando a reinfecçã. Assumindo que a transmissão da doença se faz de pessoa para pessoa, os indivíduos susceptíveis tornam-se infectados e infecciosos (capazes de transmitir a doença), se curam e se tornam recuperados (com imunidade temporária ao patógeno causador da doença). Depois de um determinado período tempo, acontece a perda desta imunidade e o indivíduo tornar-se novamente susceptível, podendo se reinfectar. A dinâmica multi-estirpe é geralmente modelada utilizando extensões dos modelos do tipo SIR. Para capturar as diferenças entre a primeira e a segunda infecção é preciso considerar pelo menos dois serotipos diferentes na composição do modelo do tipo SIR. A dinâmica da epidemiologia do dengue é particularmente complexa, com grandes flutuações (variações em quantidade ao longo do tempo) na incidência da doença. Modelos matemáticos recentes para a transmissão do vírus do den- gue se concentram no efeito ADE e na imunidade cruzada temporária. Estes modelos apresentam resultados de flutuações críticas com distribuição em lei de potência para os casos da doença, caos determinístico e dessincronização caótica, devido a sua estrutura multi-estirpe. O comportamento caótico é obtido quando assumindo infectividade muito alta para a segunda infecção do dengue, isto é, assumindo que os indivíduos na segunda infecção pelo vírus do dengue transmitem a doença com uma taxa muita mais elevada do que os indivíduos na primeira infecção. Considerações da imunidade cruzada temporária associada ao efeito ADE gera uma nova janela caótica inesperada e biologicamente mais realistas, onde a infectividade dos indivíduos na segunda infecção do dengue é reduzida devido a severidade da doença e a provável hospitalização causada pelo processo imunológico do ADE. Nesta tese apresentamos a análise e os resultados obtidos em diferentes extensões do modelo clássico SIR. Estes modelos foram motivado pela epidemiologia do dengue e a sua peculiar característica imunológica causada pelo antibody- dependent enhancement. O nosso estudo se concentra em um modelo minimalístico, em que pelo menos dois serotipos diferentes são necessários para descrever as diferenças entre as infecções primária e secundária causadas pelas diferentes cepas do vírus do dengue. Os modelos dividem a população humana em susceptíveis, infectados e recuperados, e utiliza índices para diferenciar cada um dos serotipos. Os indivíduos podem ser: (1) susceptíveis sem nenhuma infecção prévia pelo vírus do dengue, (2) infectados e recuperados pela primeira vez, (3) susceptíveis com um histórico de infecção prévia e (4) infectados pela segunda vez (por uma cepa diferente da primeira infecção) e, provavelmente hospitalizados devido ao processo de ADE. O modelo minimalístico apresenta uma dinâmica estrutural rica ao incorporar aos modelos já existentes para a transmissão do dengue, o período de imunidade cruzada temporária associada ao processo de antibody-dependent enhancement capaz de gerar diferenças nas taxas de transmissão para as infecçoes primárias e secundárias da doença. No Capítulo 1 apresentamos as propriedades do modelo básico SIR aplicado ao estudo das doenças transmissíveis. A análise da dinâmica apresentada, identificando os limites e os pontos de equilíbrio, com o objectivo de introduzir a notação e a terminologia utilizada. Estes resultados são posteriormente generalizados para os modelos motivados pela epidemiologia do dengue. No Capítulo 2, o modelo básico do tipo SIR para dois serotipos diferentes é apresentado e analisado. Este capítulo enfatiza o aspecto multi-estirpe e seus efeitos sobre a população humana. Os efeitos da dinâmica dos vetores e ou da sazonalidade não são modelados explicitamente, sendo levados em conta apenas pelos parâmetros efetivos do modelo. No Capítulo 3 apresentamos uma análise detalhada dos pontos de bifurcações encontrados para os parâmetros de ADE () e de imunidade cruzada temporária (). No Capítulo 4, o modelo sazonal do dengue é apresentado. Com base nos dados disponíveis de monitoramento do dengue, o papel da força sazonal e os casos importados da doença foram considerados como efeitos biologicamente relevantes para a de

The role of visual adaptation in cichlid fish speciation

D. Shane Wright (1) , Ole Seehausen (2), Ton G.G. Groothuis (1), Martine E. Maan (1) (1) University of Groningen; GELIFES; EGDB(2) Department of Fish Ecology &amp; Evolution, EAWAG Centre for Ecology, Evolution and Biogeochemistry, Kastanienbaum AND Institute of Ecology and Evolution, Aquatic Ecology, University of Bern.In less than 15,000 years, Lake Victoria cichlid fishes have radiated into as many as 500 different species. Ecological and sexual sel ection are thought to contribute to this ongoing speciation process, but genetic differentiation remains low. However, recent work in visual pigment genes, opsins, has shown more diversity. Unlike neighboring Lakes Malawi and Tanganyika, Lake Victoria is highly turbid, resulting in a long wavelength shift in the light spectrum with increasing depth, providing an environmental gradient for exploring divergent coevolution in sensory systems and colour signals via sensory drive. Pundamilia pundamila and Pundamilia nyererei are two sympatric species found at rocky islands across southern portions of Lake Victoria, differing in male colouration and the depth they reside. Previous work has shown species differentiation in colour discrimination, corresponding to divergent female preferences for conspecific male colouration. A mechanistic link between colour vision and preference would provide a rapid route to reproductive isolation between divergently adapting populations. This link is tested by experimental manip ulation of colour vision - raising both species and their hybrids under light conditions mimicking shallow and deep habitats. We quantify the expression of retinal opsins and test behaviours important for speciation: mate choice, habitat preference, and fo raging performance

Molecular markers to study competition and diversity of Rhizobium

The research described in this thesis was directed to the development of molecular identification and detection techniques for studying the ecology of Rhizobium, a nitrogen- fixing bacterium of agricultural importance. Competition of inoculant strains with indigenous microbes is a serious problem in agricultural practice and was therefore addressed in this work using the developed tools. Furthermore, various molecular techniques have been applied to analyse rhizobial populations nodulating common bean and a new species was characterized.In this chapter the results obtained are summarized and potential future applications are discussed.Development of gusA - and celB -minitransposons and their use in rhizobial competition studiesThe use of marker genes in rhizobial competition studies is reviewed in Chapter 1. Specific attention is given to the gusA gene, encoding β-glucuronidase (GUS). This gene is a highly suitable marker for studying plant-microbe interactions due to the absence of GUS activity in plants and in most bacteria that are of relevance in agriculture. In Chapter 2 the construction of several GUS transposons containing the marker gene in combination with different regulation systems to be used for ecological and genetic studies is described. The minitransposon mTn5SS gusA 20 contains the aph promoter which was demonstrated to be expressed in a wide variety of Gram-negative bacteria (de Bruijn and Lupski, 1984) and its use in Rhizobium resulted in high-level constitutive expression. Transposon mTn5SS gusA 21 is similar to mTn5SS gusA 20, except that it contains a unique site for Spe I, a rare-cutting enzyme in bacteria with high G+C contents such as rhizobia (Sobral et al., 1991). The use of mTn5SS gusA 2I therefore may be instrumental for the genetic mapping of insertions. The tac promoter was used to drive the expression of the gusA gene in the transposon mTn5SS gusA 11 resulting in high GUS activity in the free-living state. The transposons with constitutive gusA expression are optimal for studying rhizosphere colonization and for studying nodule occupancy in young plants. In order to reduce any metabolic load due to GUS production, the mTn5SS gusA 10 transposon with regulated gusA expression was constructed. It contains the tac promoter in combination with the lacl q repressor gene and gusA gene expression is repressed until an inducer, such as IPTG, is added. This regulation should avoid possible effects on the ecological fitness, Two transposons carrying symbiotically activated gusA genes, mTn5SS gusA 30 and mTn5SS gusA 31, were made by using the nifH promoter of a Rhizobium and a Bradyrhizobium strain, respectively. The nifH gene encodes the Fecomponent of nitrogenase and is only expressed in symbiotic or microaerobic conditions (Fischer, 1994). These constructs are recommended for longer-term nodule occupancy experiments. Furthermore, a promoter-less GUS transposon,mTn5SS gusA 40, is described that should be of use for molecular genetic studies as well as for screening bacteria for their response to specific environmental conditions or signals. The developed transposons carry a gene conferring resistance tospectinomycin and streptomycin that proved to be an appropriate marker for many strains. Nevertheless, few strains with an endogenous resistance exist. Therefore, the development of additional transposons conferring an alternative resistance would be advantageous. This may be realized by inserting the developed GUS expression cassettes into minitransposons: containing other antibiotic (de Lorenzo et al., 1990) or natural resistance markers (Herrero et al., 1990). Chapter 2 also addresses also theapplication of the different transposons in studies on root colonization and nodule occupancy, while various GUS assays are described in detail.Potential effects on the fitness of a strain due to insertion of a GUS transposon were evaluated in Chapter 3. Only few data exist on the impact of foreign genes on the fitness of an organism (Doyle et al., 1995) and before using any marker system for ecological studies its ecological effects have to be studied rigorously. In the case of Rhizobium, it is essential that the nodulation behaviour and competitive ability are maintained. The competitive abilities, nodulation characteristics, and growth rates of five independent derivatives of R. tropici strain CIAT899 marked with the gusA gene on minitransposon mTn5SS gusA 10 were determined relative to the parent strain. Insertion of mTn5SS gusA 10 did not affect the nodulation or nitrogen fixation efficiency of the wild-type strain. Nevertheless, the competitiveness index of the different gusA derivatives relative to the parental strain CIAT899 varied between isolates. One isolate was less competitive than the wild-type strain in three independent experiments, while the other isolates proved to be either equally competitive or more competitive. The utilization of this methodology to assess competitivity resulted in highly significant calculations as all the nodules on each plant were analysed for nodule occupancy. The results showed that the insertion of mTn5SS gusA 10 may have an impact on the ecological behaviour of a strain, but derivatives indistinguishable from the parent strain can be obtained. A primary selection of marked strains is recommended, which may be achieved by coinoculating the parent and the marked derivative in a one to one ratio and ensuring that the proportion of blue nodules does not differ significantly from the expected 50%.Furthermore, in Chapter 3, the detection of dual nodule occupancy is discussed. The appearance of partially stained nodules in mixed inoculum treatments but not in single strain treatments led to the conclusion that these were due to mixed infections. This was confirmed by nodule isolation and plating experiments. Partially stained nodules were also observed by Krishnan and Pueppke (1992) who reported that nodules were occupied by either a lacZ- marked or a non-marked R. fredii strain and X-gal was used for detection. However, the lacZ marker system has several disadvantages due to high background activity in plant and rhizobia whereas the gusA marker gene can be used to readily detect dual nodule occupancy on plant.A new marker gene system based on the celB gene is presented in Chapter 4. The celB gene has been isolated from the hyperthermophilic archaeon Pyrococcus juriosus and it encodes a thermostable and thermoactive β-glucosidase with a high β-galactosidase activity (Voorhorst et al., 1995). The latter enzyme activity can be used for the detection of rhizobia as endogenous background activity in plants as well as in bacteria can be easily eliminated by a heat treatment. Moreover, cheap histochemical substrates are available to determine β-galactosidase activity. The E. coli β-galactosidase gene, lacZ , has been used to monitor engineered soil bacteria (Drahos et al., 1986; Hartel et al., 1994) but was only found to be appropiate when used with Lac- bacteria. Transposons containing the ce1B gene were constructed in E. coli , based on the existing gusA transposons. The first transposon, mTn5SS celB 10 , contains the tac promoter which is regulated by the lacI q gene product and should reduce any metabolic stress to the marked strain due to marker gene activity. Transposon mTn5SS celB 31 carries celB expressed from a Bradyrhizobium nifH promoter and is active in nitrogen-fixing legume nodules. A third celB minitransposon, which contains the marker gene constitutively expressed is described elsewhere (Sessitsch et al., submitted). The celB marker gene system has several advantages in rhizobial competition studies over conventional techniques as the assay is simple to perform and the histochemical substrates are cheap. However, the greatest advantage is that gusA and celB marked strains can be localized simultaneously on a plant and a combined gusA/celB assay will enable studies of multi-strain rhizobial inocula competing with indigenous rhizobial populations. Although simultaneous detection of differently marked strains has been reported (Thompson et al., 1995; Bauchrowitz et al., 1996), the celB gene encoding the thermostable marker is better suited for double staining. In addition, a procedure has been described allowing detection of gusA and celB marked strains on plates (Sessitsch et al., submitted). In Chapter 4 the application of the celB marker gene is demonstrated for Rhizobium. However, because of the wide host range of the Tn5 based transposons and the portable expression signals this marking system is suitable for use in a variety of Gram-negative bacteria.The advantages of the different gusA and celB marker gene cassettes are discussed in Chapter 1, but also other reporter genes and their applications in studies on microbial ecology are presented. Moreover, the development of a GUS Gene Marking Kit is reported. This kit was made particularly for agronomists and microbiologists in developing countries who are not familiar with molecular techniques and who do not have the resources to establish this methodology in their laboratories. Meanwhile, a CelB Gene Marking Kit is also available that can be used either in combination with or instead of the GUS Gene Marking Kit (FAO/IAEA, 1992-1997).Ecology of rhizobia nodulating common beanIn the fields around the Seibersdorf laboratory common bean has not been cultivated during the last decades but is well nodulated. In earlier studies, common bean rhizobia populations in this soil have been found to be very competitive in nodulation (see Chapter 1). They were shown to outcompete R. tropici strain CIAT899 when inoculating Phaseolus vulgaris at an inoculation level of 10 5cells per seed. When increasing inoculation to 10 8cells per seed, 65% of the nodules were still occupied by the native strains. In Chapter 5, rhizobial populations isolated from common bean nodules grown in the Seibersdorf soil were characterized. Molecular methods targeting the whole genome such as PCR with repetitive primers were used, and specific chromosomal loci such as the 16S rRNA gene or the 16S- 23S rDNA intergenic spacer were analyzed. Plasmid profiles and Southern hybridization with a nifH probe gave information on symbiotic regions. In addition, the nodulation host range was determined. Two distinct groups were found, one of them was classified as R. etli according to the RFLP analysis of the 16S rRNA gene and because of the presence of three copies of the nifH gene. The members of the second group could not be assigned to any recognized common bean nodulating Rhizobium species, i.e. R. leguminosarum bv. phaseoli, R. etli and R. tropici, but showed high similarity to Rhizobium sp. (Phaseolus) strain R602sp isolated in France (Laguerre et al., 1993). Isolates of this group also formed nodules on cowpea, Leucaena and Gliricidia. For a long time, R. leguminosarum bv. phaseoli was believed to be the only microsymbiont in Europe, but recently R. tropici and two new species have been found in French soils (Laguerre et al., 1993; Amarger, 1994). These studies and the results obtained in Chapter 5 indicate that strains originating in Mesoamerica could establish well in European soils. However, diversity was not high among the Austrian isolates due to the long absence of the host plant in this soil.The focus of Chapter 6 is on the taxonomy and phylogeny of the Austrian isolates showing high similarity to Rhizobium sp. R602sp. A Mexican common bean isolate, FL27, was included in this study since Laguerre et al. (1993) found the partial 16S rRNA gene sequence of R602sp to be identical to FL27. Sequence analysis of the 16S rRNA gene, determination of the copy number and heterogeneity of ribosomal genes, plasmid profiles and DNA-DNA hybridization resulted in valuable taxonomic information on these strains. Based on these results it was proposed that these strains belong to a new species that was named R. pueblae sp. nov., referring to the state Puebla, Mexico, where FL27 was isolated. The Mexican, French and Austrian isolates showed very similar 16S rDNA sequences with a maximum of two nucleotide substitutions. Comparison of the 16S rDNA sequences with those of other bacteria revealed highest similarity to R. leguminosarum strain IAM 12609, R. sp. OK50 and to R. etli. Although phylogenetic dendrograms always positioned R. pueblae sp. nov. strains in the vicinity of the above-mentioned species, the new species was found to belong to a lineage different from those of described Rhizobium species. The whole DNA relatedness among the European isolates was very high but showed lower levels with FL27, probably due to the presence of different plasmids. The DNA homology to other bean-nodulating species was very low. R. pueblae sp. nov. strains possess at least three copies of the 16S rRNA gene and the ribosomal gene organization is different to other species. Despite the high competitive ability of some strains in the Seibersdorf soil, little is known on the agronomic value of this species.Concluding remarksTo improve biological nitrogen fixation, adapted efficient nitrogen-fixing plant genotypes, effective rhizobial inoculants and appropiate agricultural management practices are needed. Consequently, plant breeders, microbiologists, soil scientists, agronomists as well as farmers have to cooperate in order to achieve this goal.The selection of superior sources of natural plant genetic variability and plant breeding in the presence of rhizobia instead of applying nitrogen fertilizers may lead to the identification of high-fixing lines. Other desirable traits such as disease resistance or stress tolerance could be transferred by appropiate breeding methods or by genetic engineering. Soils, in which legumes are cultivated, vary greatly and can be opposed to various environmental stresses such as low pH or high temperature. Efforts have been undertaken to develop appropiate plant genotypes whereas for a long time the stress tolerance of inoculant strains has not been considered. Inoculant strains have been recommended based on good symbiotic performance in a particular environmentbeen recommended based on good symbiotic performance in a particular environment while the soil status or the agroecological zone of the final application has not been taken into account. The vast genetic pool of natural soils containing not yet identified strains and species can provide a variety of inoculant strains that may show better performance in the field. A strong correlation between the indigenous population size and the nodule occupancy of the inoculant strain has been established (Thies et al., 1991). However, the effect of the diversity of indigenous rhizobia on competition has not been determined. Probably, different strategies are needed in order to outcompete highly dominant field isolates or to achieve successful competition of an inoculant strain with a variety of different indigenous strains that are present in low numbers. In addition, inoculation practices have to be developed that are convenient for the farmer and that allow distribution of the introduced strain into the entire rooting zone.It seems that the various aspects important for efficient nodulation and nitrogen fixation are presently not linked sufficiently. A more rational selection of efficient and competitive strains could be realized when a database existed containing data on soil properties, environmental conditions, rhizobial diversity and population size, as well as on the competitive ability and effectiveness of rhizobial strains in combination with particular plant genotypes. Furthermore, these data could be of use for the development of new strains or plants by genetic engineering.In this thesis, the development of new methods to assess rhizobial competition is presented. These marker gene-based techniques are appropiate for the large-scale screening of inoculant strains but can be also used for genetic analysis of a variety of Gram-negative bacteria. Molecular methods have facilitated the analysis of strains nodulating common bean and resulted in the description of a new Rhizobium species that includes strains with possible beneficial properties

Functional organization of cutaneous reflex pathways during locomotion and reorganization following peripheral nerve and/or spinal cord lesions

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