Due to the large extent to which important biological mechanisms are conserved evolutionarily, the study of a simple soil nematode, C. elegans, has provided the template for significant advances in biology. Use of this model organism has accelerated in recent years as developments of advanced reagents such as synapse localized fluorescent markers have provided powerful tools to study the complex process of synapse formation and remodeling. Even as much routine biology work, such as sequencing, has become faster and easier, imaging protocols have remained essentially unchanged over the past forty years of research. This, coupled with the ability to visualize small, complex features as a result of new fluorescent reagents, has resulted in genetic screens in C. elegans becoming increasingly labor intensive and slow because microscopy mainly relies on manual mounting of animals and phenotyping is usually visually done by experts. Genetic screens have become the rate limiting factor for much of modern C. elegans research. Furthermore, phenotyping of fluorescent expression has remained a primarily qualitative process which has prevented statistical analysis of subtle features. To address these issues, a comprehensive system to allow autonomous screening for novel mutants was created. This was done by developing novel microfluidic devices to enable high-throughput screening, systems-level components to allow automated operation, and a computer vision framework for identification and quantitative phenotyping of synaptic patterns. The microfluidic platform allows for imaging and sorting of thousands of animals at high-magnification within hours. The computer vision framework employs a two-stage feature extraction to incorporate local and regional features and allows for synapse identification in near real-time with an extremely low error rate. Using this system thousands of mutagenized animals were screened to indentify numerous novel mutants expressing altered synaptic placement and development. Fully automated screening and analysis of subtle fluorescent phenotypes will allow large scale RNAi and drug screens. Combining microfluidics and computer vision approaches will have a significant impact on the biological community by removing a significant bottleneck and allowing large-scale screens that would have previously been too labor intensive to attempt.

Abiotic and biotic variation has been shown to be important in regulating nutrient cycling and belowground communities in natural systems. However, genetic variation in dominant plants as a driver of rates of nutrient cycling is still poorly understood and few studies have looked at genotype interactions across multiple environments. Using Populus angustifolia and a common garden approach, we hypothesized that all three factors: tree genetic variation, environmental conditions and genetic by environment (G x E) interactions would affect soil carbon (C) storage and nitrogen (N) cycling. Replicated copies of five different reciprocally planted Populus genotypes were studied in three separate 18-21 year old common gardens at different elevations (1300m, 1384m and 1587m) in northern Utah, to measure the genotype and environmental effects on pools of soil C and N as well as rates of soil net N nitrification and net mineralization. Our results indicate that genotypes influence pools of soil C, total N and C:N, but genotype did not influence net rates of nitrogen mineralization. Environmental variation significantly influenced pools of soil C, total N, soil C:N and rates of net nitrification and net N mineralization. As predicted, G x E interactions significantly influenced both pools and processes of soil C and N cycling. Overall, we found that genetic variation in plant traits (tree diameter and leaf/root chemistry) as well as soil texture across gardens were significant predictors of soil C and N pools and fluxes across seasons. These data help us understand the relative role of genotypic variation on above- and belowground interactions in different environments and the consequences of these interactions on ecosystem processes. The results from this study show that across an environmental gradient Populus angustifolia genotypes can influence nitrogen mineralization through feedbacks between environmental variation, tree phenotype and soils.

Thesis (Ph. D.)--Ohio State University, 2009. / Title from first page of PDF file. Includes bibliographical references (p. 134-151).

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2009. / Härtill 4 uppsatser.

published_or_final_version / Pathology / Master / Master of Medical Sciences

published_or_final_version / abstract / toc / Medicine / Master / Doctor of Medicine

The main goal of this dissertation was to study the bifurcation structure underlying families of low dimensional dynamical systems that model cellular excitability. One of the main contributions of this work is a mathematical characterization of profiles of electrophysiological activity in excitable cells of the same identified type, and across cell types, as a function of the relative levels of expression of ion channels coded by specific genes. In doing so, a generic formulation for transmembrane transport was derived from first principles in two different ways, expanding previous work by other researchers. The relationship between the expression of specific membrane proteins mediating transmembrane transport and the electrophysiological profile of excitable cells is well reproduced by electrodiffusion models of membrane potential involving as few as 2 state variables and as little as 2 transmembrane currents. Different forms of the generic electrodiffusion model presented here can be used to study the geometry underlying different forms of excitability in cardiocytes, neurons, and other excitable cells, and to simulate different patterns of response to constant, time-dependent, and (stochastic) time- and voltage-dependent stimuli. In all cases, an initial analysis performed on a deterministic, autonoumous version of the system of interest is presented to develop basic intuition that can be used to guide analyses of non-autonomous or stochastic versions of the model. Modifications of the biophysical models presented here can be used to study complex physiological systems involving single cells with specific membrane proteins, possibly linking different levels of biological organization and spatio-temporal scales.

Dispersal influences the genetic and social composition of populations, yet it has been difficult to understand the mechanisms underlying dispersal and this limits our ability to understand how dispersal may be influencing population dynamics. Behavioral traits, such as aggression, have been implicated as drivers of both dispersal and population dynamics. However, the influence on both has never been addressed in a single system. Western bluebirds (Sialia mexicana) provide an excellent opportunity to address this question, as their dispersal propensity is dependent upon aggressive phenotype and we have detailed observations over a period of more than a decade. I show that natal dispersal is influenced by an interaction between father and son aggressive phenotypes, in addition to available resources on the natal territory. Furthermore, population density is influenced by resource availability and an interaction between population aggression and recruitment of offspring as breeders. Males that breed for multiple seasons once the population has reached saturation recruit a higher proportion of offspring into the population, as do males that are nonaggressive. Males that are nonaggressive are more likely to breed for multiple seasons, which suggests an added cost to aggressive behavior in this species. Both aggressive behavior and the availability of resources are mechanisms influencing dispersal of individuals that manifest at the population scale.

During normal development, face processing involves a gradual shift from a featurally oriented style to a mature configural style by adolescence. This shift may coincide with increased right hemispheric dominance for faces supporting configural processing. Previous studies suggest that individuals diagnosed with ASD continue to process faces using individual parts and features into adulthood. This continued bias may be due to deficits in configural processing abilities. The current study investigated measures of functional connectivity during featural and configural processing of faces in broad autism phenotype sibling (ASD-sibs) children compared to age, sex, and handedness matched normal developing (ND) controls and in children diagnosed with an Autism Spectrum Disorder compared to ASD-matched ND controls. Results indicate that children with ASD and ASD-sibs were capable of performing configural processing tasks at similar performance levels to those of ND children. Additionally, patterns of functional network connectivity for configural processing in ASD-sibs were similar to those observed in ND controls. Few network-wide hemispheric differences emerged between groups. While behavioral performance and overall network-wide patterns of connectivity suggest a face processing network that is capable of supporting configural processing in ASD and ASD-sibs, abnormalities were observed in specific regions. The amygdala and fusiform face area showed fewer interactions with the rest of the face processing network in ASD children compared to ND during configural, but not featural processing. Additionally, hemispheric comparisons show greater differences between ASD and ND controls in the right fusiform face area. The ability of these regions to communicate with other regions in the face network could be important for social motivation and attention during configural processing. Interestingly, network connectivity in ASD children during passive viewing of faces, objects, and textures without featural or configural manipulations showed a more functionally integrated, and less segregated network with a lower “wiring cost” during non-face conditions compared to ND children. ASD-sibs may demonstrate a similar milder pattern.

Azithromycin improves clinical outcomes in patients with cystic fibrosis (CF), specifically in patients infected with Pseudomonas aeruginosa. Azithromycin shifts macrophage programming away from a pro-inflammatory classical (M1) phenotype, and towards an anti-inflammatory alternative (M2) phenotype; however, little is known about this mechanism, nor of its impact upon immune response to pulmonary infection. We set out to determine the mechanism by which azithromycin is able to alter macrophage phenotype, and assess the effect of azithromycin induced macrophage polarization on inflammation during pulmonary infections. Utilizing macrophage cell culture, we found that azithromycin increased IKKβ, a signaling molecule in the NFκB pathway, which likely is altering macrophage programming. Using a Pseudomonas infection model in mice that lack physiologic alternative macrophage activation, we showed that azithromycin’s ability to alter macrophage function and decrease lung damage was independent of interleukin control of macrophage programming. Azithromycin increased fibrotic protein production both in vivo and in vitro, but blunted immune-driven fibrotic damage. We extended our study to patients with CF, describing gene expression in macrophages isolated from sputum samples. We found markers consistent with a shift toward M2 polarization in these patients. These data suggest potential mechanisms by which azithromycin benefits patients with CF.