The role of splicing factors and small nuclear RNAs in spliceosomal formation

Protein coding genes are comprised of protein-coding exons and non-protein-coding introns. The process of splicing involves removal of the introns and joining of the exons to form a mature messenger RNA, which subsequently undergoes translation into polypeptide. The spliceosome is a large, RNA/protein assembly of five small nuclear RNAs as well as over 300 proteins, which catalyzes intron removal and exon ligation. The selection of specific exons for inclusion in the mature messenger RNA is spatiotemporally regulated and results in production of an enormous diversity of polypeptides from a single gene locus. This phenomenon, known as alternative splicing, is regulated, in part, by protein splicing factors, which target the spliceosome to exon/intron boundaries. The first part of my dissertation (Chapters II and III) focuses on the discovery and characterization of the 45 kilodalton FK506 binding protein (FKBP45), which I discovered in the silk moth, Bombyx mori, as a U1 small nuclear RNA binding protein. This protein family binds the immunosuppressants FK506 and rapamycin and contains peptidyl-prolyl cis-trans isomerase activity, which converts polypeptides from cis to trans about a proline residue. This is the first time that an FKBP has been identified in the spliceosome. The second section of my dissertation (Chapters IV, V, VI and VII) is an investigation of the potential role of small nuclear RNA sequence variants in the control of splicing. I identified 46 copies of small nuclear RNAs in the 6X whole genome shotgun of the Bombyx mori p50T strain. These variants may play a role in differential binding of specific proteins that mediate alternative splicing. Along these lines, further investigation of U2 snRNA sequence variants in Bombyx mori demonstrated that some U2 snRNAs preferentially assemble into high molecular weight spliceosomal complexes over others. Expression of snRNA variants may represent another mechanism by which the cell is able to fine tune the splicing process.

Fire and grazing in a mesic tallgrass prairie: impacts on plant species and functional traits

Fire is a globally distributed disturbance that impacts terrestrial ecosystems and has been proposed to be a global “herbivore.” Fire, like herbivory, is a top-down driver that converts organic materials into inorganic products, alters community structure, and acts as an evolutionary agent. Though grazing and fire may have some comparable effects in grasslands, they do not have similar impacts on species composition and community structure. However, the concept of fire as a global herbivore implies that fire and herbivory may have similar effects on plant functional traits. Using 22 years of data from a mesic, native tallgrass prairie with a long evolutionary history of fire and grazing, we tested if trait composition between grazed and burned grassland communities would converge, and if the degree of convergence depended on fire frequency. Additionally, we tested if eliminating fire from frequently burned grasslands would result in a state similar to unburned grasslands, and if adding fire into a previously unburned grassland would cause composition to become more similar to that of frequently burned grasslands. We found that grazing and burning once every four years showed the most convergence in traits, suggesting that these communities operate under similar deterministic assembly rules and that fire and herbivory are similar disturbances to grasslands at the trait-group level of organization. Three years after reversal of the fire treatment we found that fire reversal had different effects depending on treatment. The formerly unburned community that was then burned annually became more similar to the annually burned community in trait composition suggesting that function may be rapidly restored if fire is reintroduced. Conversely, after fire was removed from the annually burned community trait composition developed along a unique trajectory indicating hysteresis, or a time lag for structure and function to return following a change in this disturbance regime. We conclude that functional traits and species-based metrics should be considered when determining and evaluating goals for fire management in mesic grassland ecosystems.

Host and network optimizations for performance enhancement and energy efficiency in data center networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

A software tool that generates symbolic model verifier (SMV) input language from a predicate transition net

The purpose of this research was to apply model checking by using a symbolic model checker on Predicate Transition Nets (PrT Nets). A PrT Net is a formal model of information flow which allows system properties to be modeled and analyzed. The aim of this thesis was to use the modeling and analysis power of PrT nets to provide a mechanism for the system model to be verified. Symbolic Model Verifier (SMV) was the model checker chosen in this thesis, and in order to verify the PrT net model of a system, it was translated to SMV input language. A software tool was implemented which translates the PrT Net into SMV language, hence enabling the process of model checking. The system includes two parts: the PrT net editor where the representation of a system can be edited, and the translator which converts the PrT net into an SMV program.

The Role of Splicing Factors and Small Nuclear RNAS in Spliceosomal Formation

Protein coding genes are comprised of protein-coding exons and non-protein-coding introns. The process of splicing involves removal of the introns and joining of the exons to form a mature messenger RNA, which subsequently undergoes translation into polypeptide. The spliceosome is a large, RNA/protein assembly of five small nuclear RNAs as well as over 300 proteins, which catalyzes intron removal and exon ligation. The selection of specific exons for inclusion in the mature messenger RNA is spatio-temporally regulated and results in production of an enormous diversity of polypeptides from a single gene locus. This phenomenon, known as alternative splicing, is regulated, in part, by protein splicing factors, which target the spliceosome to exon/intron boundaries. The first part of my dissertation (Chapters II and III) focuses on the discovery and characterization of the 45 kilodalton FK506 binding protein (FKBP45), which I discovered in the silk moth, Bombyx mori, as a U1 small nuclear RNA binding protein. This protein family binds the immunosuppressants FK506 and rapamycin and contains peptidyl-prolyl cis-trans isomerase activity, which converts polypeptides from cis to trans about a proline residue. This is the first time that an FKBP has been identified in the spliceosome. The second section of my dissertation (Chapters IV, V, VI and VII) is an investigation of the potential role of small nuclear RNA sequence variants in the control of splicing. I identified 46 copies of small nuclear RNAs in the 6X whole genome shotgun of the Bombyx mori p50T strain. These variants may play a role in differential binding of specific proteins that mediate alternative splicing. Along these lines, further investigation of U2 snRNA sequence variants in Bombyx mori demonstrated that some U2 snRNAs preferentially assemble into high molecular weight spliceosomal complexes over others. Expression of snRNA variants may represent another mechanism by which the cell is able to fine tune the splicing process.

Mechanisms of Arsenic Detoxification and Resistance

Arsenic is a ubiquitous environmental toxic substance. As a consequence of continual exposure to arsenic, nearly every organism, from Escherichia coli to humans have evolved arsenic detoxification pathways. One of the pathways is extrusion of arsenic from inside the cells, thereby conferring resistance. The R773 arsRDABC operon in E. coli encodes an ArsAB efflux pump that confers resistance to arsenite. ArsA is the catalytic subunit of the pump, while ArsB forms the oxyanion conducting pathway. ArsD is an arsenite metallochaperone that binds arsenite and transfers it to ArsA. The interaction of ArsA and ArsD allows for resistance to As(III) at environmental concentrations. The interaction between ArsA ATPase and ArsD metallochaperone was examined. A quadruple mutant in the arsD gene encoding a K2A/K37A/K62A/K104A ArsD is unable to interact with ArsA. An error-prone mutagenesis approach was used to generate random mutations in the arsA gene that restored interaction with the quadruple arsD mutant in yeast two-hybrid assays. Three such mutants encoding Q56R, F120I and D137V ArsA were able to restore interaction with the quadruple ArsD mutant. Structural models generated by in silico docking suggest that an electrostatic interface favors reversible interaction between ArsA and ArsD. Mutations in ArsA that propagate changes in hydrogen bonding and salt bridges to the ArsA-ArsD interface also affect their interactions. The second objective was to examine the mechanism of arsenite resistance through methylation and subsequent volatilization. Microbial ArsM (As(III) S-adenosylmethyltransferase) catalyzes the formation of trimethylarsine as the volatile end product. The net result is loss of arsenic from cells. The gene for CrArsM from the eukaryotic green alga Chlamydomonas reinhardtii was chemically synthesized and expressed in E. coli. The purified protein catalyzed the methylation of arsenite into methyl-, dimethyl- and trimethyl products. Synthetic purified CrArsM was crystallized in an unliganded form. Biochemical and biophysical studies conducted on CrArsM sheds new light on the pathways of biomethylation. While in microbes ArsM detoxifies arsenic, the human homolog, hAS3MT, converts inorganic arsenic into more toxic and carcinogenic forms. An understanding of the enzymatic mechanism of ArsM will be critical in deciphering its parallel roles in arsenic detoxification and carcinogenesis.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.