The James Webb Space Telescope (JWST) is expected to revolutionize the current understanding of Jovian worlds over the coming decade. However, as the field pushes towards characterizing cooler, smaller, “terrestrial-like” planets, dedicated next-generation facilities will be required to tease out the small spectral signatures indicative of biological activity. Here, the feasibility of determining atmospheric properties, from near to mid-infrared transmission spectra, of transiting temperate terrestrial M-dwarf companions, has been evaluated. Specifically, atmospheric retrievals were utilized to explore the trade space between spectral resolution, wavelength coverage, and signal-to-noise on the ability to both detect molecular species and constrain their abundances. Increasing spectral resolution beyond R=100 for near-infrared wavelengths, shorter than 5um, proves to reduce the degeneracy between spectral features of different molecules and thus greatly benefits the abundance constraints. However, this benefit is greatly diminished beyond 5um as any overlap between broad features in the mid-infrared does not deconvolve with higher resolutions. Additionally, the inclusion of features beyond 11um did not meaningfully improve the detection significance nor abundance constraints results. The findings of this study indicate that an instrument with continuous wavelength coverage from approximately 2-11um and with a resolution of R~50-300, would be capable of detecting H2O, CO2, CH4, O3, and N2O in the atmosphere of an Earth-analog transiting an M-dwarf (magK=8.0) within 50 transits, and obtain better than an order-of-magnitude constraint on each of their abundances.

The Origins Space Telescope (Origins) is one of four flagship mission concepts, under review by the 2020 Decadal Survey, that may take the mantle of the next-generation space-based observatory. In conjunction with this research, a secondary trade space study was performed on behalf of the Origins Exoplanets Working Group. The primary purpose of this collaboration was to provide a scientific basis to the technical specifications for the mid-infrared detectors onboard the Mid-Infrared Spectrometer Camera Transit Spectrometer (MISC-T) instrument. The results of this work directly contributed to the alteration of the official technical specifications of the instrument design concept.

The greatest barrier to understanding how life interacts with its environment is the complexity in which biology operates. In this work, I present experimental designs, analysis methods, and visualization techniques to overcome the challenges of deciphering complex biological datasets. First, I examine an iron limitation transcriptome of Synechocystis sp. PCC 6803 using a new methodology. Until now, iron limitation in experiments of Synechocystis sp. PCC 6803 gene expression has been achieved through media chelation. Notably, chelation also reduces the bioavailability of other metals, whereas naturally occurring low iron settings likely result from a lack of iron influx and not as a result of chelation. The overall metabolic trends of previous studies are well-characterized but within those trends is significant variability in single gene expression responses. I compare previous transcriptomics analyses with our protocol that limits the addition of bioavailable iron to growth media to identify consistent gene expression signals resulting from iron limitation. Second, I describe a novel method of improving the reliability of centroid-linkage clustering results. The size and complexity of modern sequencing datasets often prohibit constructing distance matrices, which prevents the use of many common clustering algorithms. Centroid-linkage circumvents the need for a distance matrix, but has the adverse effect of producing input-order dependent results. In this chapter, I describe a method of cluster edge counting across iterated centroid-linkage results and reconstructing aggregate clusters from a ranked edge list without a distance matrix and input-order dependence. Finally, I introduce dendritic heat maps, a new figure type that visualizes heat map responses through expanding and contracting sequence clustering specificities. Heat maps are useful for comparing data across a range of possible states. However, data binning is sensitive to clustering cutoffs which are often arbitrarily introduced by researchers and can substantially change the heat map response of any single data point. With an understanding of how the architectural elements of dendrograms and heat maps affect data visualization, I have integrated their salient features to create a figure type aimed at viewing multiple levels of clustering cutoffs, allowing researchers to better understand the effects of environment on metabolism or phylogenetic lineages.

The taxonomic and metabolic profile of the microbial community inhabiting a natural system is largely determined by the physical and geochemical properties of the system. However, the influences of parameters beyond temperature, pH and salinity have been poorly analyzed with few studies incorporating the comprehensive suite of physical and geochemical measurements required to fully investigate the complex interactions known to exist between biology and the environment. Further, the techniques used to classify the taxonomic and functional composition of a microbial community are fragmented and unwieldy, resulting in unnecessarily complex and often non-consilient results.

This dissertation integrates environmental metagenomes with extensive geochemical metadata for the development and application of multidimensional biogeochemical metrics. Analysis techniques including a Markov cluster-based evolutionary distance between whole communities, oligonucleotide signature-based taxonomic binning and principal component analysis of geochemical parameters allow for the determination of correlations between microbial community dynamics and environmental parameters. Together, these techniques allow for the taxonomic classification and functional analysis of the evolution of hot spring communities. Further, these techniques provide insight into specific geochemistry-biology interactions which enable targeted analyses of community taxonomic and functional diversity. Finally, analysis of synonymous substitution rates among physically separated microbial communities provides insights into microbial dispersion patterns and the roles of environmental geochemistry and community metabolism on DNA transfer among hot spring communities.

The data presented here confirms temperature and pH as the primary factors shaping the evolutionary trajectories of microbial communities. However, the integration of extensive geochemical metadata reveals new links between geochemical parameters and the distribution and functional diversification of communities. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial community functional composition and inter-community DNA transfer rates. Finally, the taxonomic classification and clustering techniques developed within this dissertation will facilitate future genomic and metagenomic studies through enhanced community profiling obtainable via Markov clustering, longer oligonucleotide signatures and insight into PCR primer biases.