| Integral membrane proteins play a fundamental role in sensing and interacting with the environment, maintaining homeostasis, and allowing the influx and efflux of ions and molecules into the cell. The major work of this thesis investigates membrane protein variation in metagenomic samples from ocean habitats and relates this variation to features of the environment. Using 29 samples, we annotated ∼900 membrane proteins from 7.7 million shotgun sequencing reads and integrated environmental and anthropogenic features from various databases. This allowed us to study membrane protein variation in terms of natural features, such as phosphate and nitrate concentrations, and also in terms of human impacts, such as pollution and climate change. Further, using these data, we developed a method, Protein Families and Environment Features Network (PEN), to quantify and visualize the results of the correlations we found. Using this approach, we find that the affinity of phosphate transporters is related to the concentration of phosphate and that the occurrence of iron transporters is connected to the amount of shipping, pollution, and iron-containing dust.;The second section of the thesis focuses on the analysis of coevolution and coevolution scoring functions in a dataset of 14 membrane protein families. It has long been appreciated that studying the sequence information in a protein family, such as conservation and mutation, can shed light on functional and structural constraints. We analyzed 101 variations of three distinct types of coevolution functions on their accuracy in predicting structural contacts in these membrane protein families. The results show that the various normalizations and sequence weightings we have implemented improve the accuracy over current published results; however, we find that the accuracies achieved are too small for practical use in structure prediction. |
