Shuttling of intermediary metabolites such as lactate and pyruvate contribute to the dynamic energy needs of tissues. Tracer kinetic studies offer a powerful method to measure the metabolism of substrates like lactate and pyruvate that are simultaneously taken up from and released into the circulation by organs. We examined the transpulmonary lactate and pyruvate kinetics in an anesthetized rat model during an unstimulated (Con), lactate clamp (LC) and epinephrine infusion (Epi) using a primed-continuous infusion of [U-13C]lactate and pyruvate. Compared to Con and Epi stimulation, LC significantly increased mixed central venous ([v]) and arterial ([a]) pyruvate and lactate concentrations (P < 0.05). Transpulmonary net lactate and pyruvate balances were positive during all three conditions indicating net metabolite uptake. Net balance was significantly greater during epinephrine stimulation compared to the unstimulated control for both lactate and pyruvate (P < 0.05). Tracer measured lactate fractional extractions were similar for unstimulated and lactate clamp conditions, but negative during Epi stimulation when a transpulmonary production of lactate from venous pyruvate occurred. Tracer measured pyruvate fractional extraction averaged 42.8 ± 5.8% for all three conditions, and was significantly higher during epinephrine stimulation (P < 0.05) than during either Con or LC conditions, which did not significantly differ from each other. Lactate total release (= tracer measured uptake - net release) increased due to a lactate load (i.e., LC) and decreased (i.e., negative) from epinephrine stimulation because of the transpulmonary pyruvate to lactate conversion. Pyruvate total release was significantly higher during epinephrine stimulation (400 ± 100 µg/min) vs. Con (30 ± 20 µg/min) (P < 0.05). For lactate, we conclude that transpulmonary concentration difference measurements across the lungs provide an incomplete - and perhaps misleading - picture of parenchymal lactate metabolism, especially during epinephrine stimulation. Regarding pyruvate, significant extraction occurs during circulatory transport across the lungs. The extent of pulmonary parenchymal pyruvate extraction predicts high expression of monocarboxylate (lactate/pyruvate) transporters (MCTs) in the tissue and western blot analysis of whole lung homogenates detected three isoforms: MCT1, MCT2, and MCT4. We conclude that a critical site of circulating pyruvate extraction resides in the lungs. Furthermore, during times of elevated circulating pyruvate or epinephrine stimulation, pyruvate extraction increases.

There are approximately 5 x 1030 bacteria on Earth [1]. These microorganisms are found in every type of environment, soil, aquatic, air, on every surface in our world. In fact, there is roughly 1 million times more bacteria on earth than stars in the observable universe [2]. These microbes represent a universe on a microscopic scale. Life as a bacterium is challenging and dangerous. Small viruses capable of infecting these bacteria (called bacteriophages or phages), can turn a happy and healthy bacterium to a sick and dying one in less than 30 minutes. Before long, the virus has multiplied in number and an outbreak poses a great risk to the bacterial population. However, some bacteria are immune or protected from certain phages because they encode anti-phage genes or defense genes. This phage-bacteria warfare has been undergoing for millions of years at a scale larger than the observable universe. This has led the evolution of various defense systems and mechanisms that protect bacteria from phages, and conversely the evolution of diverse anti-defense genes that phages use to counteract the defenses. This arms race can be traced by analyzing the genomes of bacteria and phages. In 2011, it was observed that these defense systems are encoded near each other [3]. This is a remarkable observation given the null hypothesis, which is the placement of genes along the genome is random. This led to the term “defense islands” which are genomic regions that encode genes related to anti-phage immunity. One of the most common systems found in these defense islands are restriction modification (RM) systems which generally consists of two components, a restriction enzyme and a modification enzyme (methyltransferase). The RM system recognizes small patterns of DNA and modifies it. This allows the bacteria to mark its own DNA and degrade any DNA without the modification. This allows for protection against foreign DNA injected during a phage infection [4]. This system is by far the most common system seen amongst bacteria. Another remarkable example of an immune system is the CRISPR system which represents an adaptative immune system. CRISPR uses RNA molecules and Cas proteins to recognize specific patterns of DNA from the invading phage. Fragments from the invading phage can be integrated into the bacterium’s genome in the CRISPR array [5]. These two systems alone have been the focus of research for years and has led to the development of several biomedical tools. Discovering more of these systems can help us understand the phage-bacteria arms race and has potential to uncover new biology and development of new technologies.Defense Islands are a focus for discovering new immune systems. Instead of testing the several thousand genes of a bacteria for anti-phage function, defense islands can narrow the search space to the several genes within the island. This has led to the discovery of several immune since 2018 [6]. Defense Islands have been considered potentially mobile elements that are horizontally transferred between bacteria, something that has been known to exist for antibiotic resistance genes. Additionally, defense islands have been considered to be randomly placed in a genome. However, closely related bacterial isolates are known to carry completely different immune systems despite most their genome being identical. These defense islands may utilize the same genomic site for closely related isolates. Indeed, this was observed in the work outlined in the first chapter of this dissertation. This allows for better predications of immune systems because instead of predicting the system itself, it predicts the genomic locus that is likely to encode an immune system, agnostic to previously known systems, which other methods rely on. In Pseudomonas aeruginosa, there are two predominate defense hotspots, (core defense hotspot 1 and 2, cDHS1/2) which is a core and conserved region found in every P. aeruginosa isolate that is hotspot for several defense islands. These hotpots are likely built by the accumulation of several mobile defense islands or systems in this region. Phages also have the ability to evolve proteins that are antagonistic to bacteria. Anti-defense genes like AcrIF11, an anti-CRISPR that prevents phages from being targeted from the CRISPR Cas Type I-F system. ArdA, an anti-RM protein that inhibits RM systems and allows phages to infect bacteria despite having an RM system. A recent study reported seven novel anti-CRISPR protiens that protect phage from the type IV-A system, But, when we looked at the study, we found several issues. We tested the Acr sequences in E. coli and mammalian cells but did not find any anti-Cas13a activity. This makes us question the original study’s claim. The details on findings is the topic of chapter 2 of this dissertation.