Borrelia burgdorferi is an elongated and helically shaped bacterium that is the causal agent of the tick-borne illness Lyme disease. The disease manifests with initial flu-like symptoms and, in many cases, the appearance of a skin rash called erythema migrans at the site of the tick bite. If left untreated the disease might cause impairment of various organs such as the skin, heart, joints and the nervous system. The bacteria have a parasitic lifestyle and are always present within a host. Hosts are usually ticks or different animals and birds that serve as reservoirs for infection. B. burgdorferi are unable to synthesize building blocks for many vital cellular processes and are therefore highly dependent on their surroundings to obtain nutrients. Because of this, porins situated in the outer membrane, involved in nutrient uptake, are believed to be very important for B. burgdorferi. Except for a role in nutrient acquisition, porins can also have a function in binding extracellular matrix proteins, such as integrins, and have also been implicated in bacterial adaptation to new environments with variations in osmotic pressure. P13 and P66 are two integral outer membrane proteins in B. burgdorferi previously shown to have porin activities. In addition to its porin function, P66 also has integrin binding activity. In this thesis, oligomeric structures formed by the P13 and P66 protein complexes were studied using the Black lipid bilayer technique in combination with nonelectrolytes. Initial attempts were also made to study the structure of P13 in Nanodiscs, whereby membrane proteins can insert into artificial lipid bilayers in their native state and the structure can be analyzed by electron microscopy. In addition, the role of P13 and P66 in B. burgdorferi osmotic stress adaptation was examined and also the importance and role of the integrin-binding activity of P66 in B. burgdorferi infections in mice. Using Black lipid bilayer studies, the pore forming activity of P13 was shown to be much smaller than previously thought, exhibiting activity at 0.6 nS. The complex formed by P13 was approximately 300 kDa and solely composed of P13 monomers. The channel size was calculated to be roughly 1.4 nm. Initial Nanodisc experiments showed a pore size of 1.3 nm, confirming the pore size determined by Black lipid bilayer experiments. P66 form pores with a single channel conductance of 11 nS and a channel size of 1.9 nm. The porin assembles in the outer membrane into a large protein complex of 420 kDa, containing exclusively P66 monomers. The integrin-binding function of P66 was found to be important for efficient bacterial dissemination in the murine host but was not essential for B. burgdorferi infectivity. Neither P13 nor P66 had an active role in osmotic stress adaptation. Instead, two p13 paralogs were up-regulated at the transcript level in B. burgdorferi cultured under glycerol-induced osmotic stress. / Borrelia burgdorferi är en bakterie med många unika egenskaper som orsakar sjukdomen Lyme borrelios. Borrelia kan idag lätt behandlas med antibiotika om sjukdomen upptäcks i ett tidigt stadium. Det är först om sjukdomen tillåts fortgå som symptom som nervsmärta och ansiktsförlamning kan uppstå och dessutom vara svåra att koppla till en Borrelia-infektion. Multiresistenta bakterier har blivit en stor del av vår vardag och även om Borrelia-bakterierna idag inte är resistenta mot flertalet antibiotika är det kanske speciellt viktigt, innan det är för sent, med forskning som kan leda till upptäckter av unika angreppsställen för nya läkemedel. Målet med denna avhandling var att studera hur två Borrelia proteiner, P13 och P66, ser ut, är uppbyggda och även vilken funktion de har. Dessa proteiner är tänkbara vaccinkandidater eftersom de sitter i yttre membranet hos bakterierna och sticker ut på ytan mot våra värdceller, vilket gör att vi reagerar mot dem vid en infektion. P13 och P66 är också viktiga kanaler för bakterierna vid upptag av näringsämnen och byggstenar från omgivningen. Ämnen som bakterierna inte kan producera själva. Pga. denna funktion är P13 och P66 tänkbara proteiner för blockering med ett läkemedel som skulle förhindra bakterien från att föröka sig i och med att de förlorar möjligheten att tillgodogöra sig näring. Detta i sin tur skulle leda till att vårt eget immunförsvar hinner rensa undan bakterierna innan infektionen blivit för stor och vi blivit sjuka. P66 har förutom porin funktionen även en adhesions funktion när proteinet kan binda integriner som sitter på olika typer av celler i vår kropp, bl. a. immunceller och epitelceller i våra blodkärl och vävnader. Den integrin bindande funktionen är viktig för bakterierna vid en infektion eftersom det gör det möjligt för bakterierna att binda till våra celler. Ett steg som är viktigt för att de senare ska kunna ta sig ut från blodkärlen till våra vävnader. P13 och P66 visade sig kunna bilda stora proteinkomplex i ytter membranet hos bakterierna med en storlek på 300 kDa respektive 420 kDa. De är inga specifika poriner som bara kan transportera en viss typ av molekyl med t.ex. en viss laddning, utan kan ombesörja upptaget av många olika typer av ämnen. Eliminering av p66 orsakade att ett annat adhesionsprotein, uppreglerades. En omplacering av ett normalt cytoplasmatiskt lokaliserat chaperon-protein till ytter-membranet hos bakterierna kunde också ses i frånvaro av P66. Chaperonet GroEL har i andra bakterier, bl. a. Helicobacter pylori, bakterien som orsakar magsår, beskrivits som ett protein som kan förflytta sig till ytan av bakterierna och där ha en liknande funktion som P66, dvs. att binda extracellulära matrisprotein. Förändringen i uttryck av adhesionsproteinet och förflyttningen av chaperonet till membranet var en följd av p66-eliminering och mest troligt ett sätt för bakterierna att komplettera den förlorade integrinbindande funktionen av P66. Det har tidigare visats att poriner är involverade i skyddet mot osmotisk stress i andra bakterier. Denna funktion hos P13 och P66 i Borrelia kunde inte ses när bakterier utsattes för osmotisk stress med glycerol, som orsakar en form av membranstress. Däremot kunde vi med hjälp av transkriptomanalys se att Borrelia-bakterier uppreglerade transkriptionen av två paraloger till P13 vid hyper-osmotisk stress. Borrelia bakteriens användning av dessa paraloga proteiner har tidigare trotts ske enbart i frånvaro av ett funktionellt P13 protein. Nu visade det sig att P13-paraloger har en egen funktion även i närvaro av P13, nämligen att vara involverade i regleringen av hyperosmotisk stress och därmed skydda bakterierna i denna stressituation. Andra gener som påverkades av osmotisk stress med glycerol var gener för stressfaktorer och pumpar i inre membranet hos bakterien.

Thesis (Ph. D.)--Cornell University, May, 2007. / Vita. Includes bibliographical references (leaves 79-89).

No description available.

No description available.

Much research has been directed toward understanding the roles of essential components in the cell, such as proteins, microRNAs, and genes. This dissertation focuses on two interesting problems in bioinformatics research: microRNA-target prediction and the identification of conserved protein complexes across species. We define the two problems and develop novel approaches for solving them. MicroRNAs are short non-coding RNAs that mediate gene expression. The goal is to predict microRNA targets. Existing methods rely on sequence features to predict targets. These features are neither sufficient nor necessary to identify functional target sites and ignore the cellular conditions in which microRNA and mRNA interact. We developed MicroTarget to predict microRNA-mRNA interactions using heterogeneous data sources. MicroTarget uses expression data to learn candidate target set for each microRNA. Then, sequence data is used to provide evidence of direct interactions and ranking the predicted targets. The predicted targets overlap with many of the experimentally validated ones. The results indicate that using expression data helps in predicting microRNA targets accurately. Protein complexes conserved across species specify processes that are core to cell machinery. Methods that have been devised to identify conserved complexes are severely limited by noise in PPI data. Behind PPIs, there are domains interacting physically to perform the necessary functions. Therefore, employing domains and domain interactions gives a better view of the protein interactions and functions. We developed novel strategy for local network alignment, DONA. DONA maps proteins into their domains and uses DDIs to improve the network alignment. We developed novel strategy for constructing an alignment graph and then uses this graph to discover the conserved sub-networks. DONA shows better performance in terms of the overlap with known protein complexes with higher precision and recall rates than existing methods. The result shows better semantic similarity computed with respect to both the biological process and the molecular function of the aligned sub-networks. / Ph. D. / Much research has been directed toward understanding the roles of essential components in the cell, such as proteins, microRNAs, and genes. The processes within the cell include a mixture of small molecules. It is of great interest to utilize different information sources to discover the interactions among these molecules. This dissertation focuses on two interesting problems: microRNA-target prediction and the identification of conserved protein complexes across species. We define the two problems and develop novel approaches for solving them. MicroRNAs are a recently discovered class of non-coding RNAs. They play key roles in the regulation of gene expression of as much as 30% of all mammalian protein encoding genes. MicroRNAs regulation activity has been implicated in a number of diseases including cancer, heart disease and neurological diseases. We developed MicroTarget to predict microRNAgene interactions using heterogeneous data sources. The predicted target genes overlap with many of the experimentally validated ones. Proteins carry out their tasks in the cell by interacting with each other. Protein complexes conserved among species specify the cell core processes. We identify conserved complexes by constructing an alignment graph leveraging on the conservation of PPIs between species through domain conservation and domain-domain interactions (DDI) in addition to PPI networks. Better integration of domain conservation and interactions in our developed conserved protein complexes identification system helps biologists benefit from verified data to predict more reliable similarity relationships among species. All the test data sets and source code for this dissertation are available at: https://bioinformatics.cs.vt.edu/∼htorkey/Software.

Thesis (Ph.D.)--University of Florida, 2004. / Typescript. Title from title page of source document. Document formatted into pages; contains 100 pages. Includes Vita. Includes bibliographical references.

Vesicle trafficking provides the solution to the 'sorting problem' - how the eukaryotic cell maintains the distinct identities, and thus functional properties, of its membrane-bound organelles. During vesicle trafficking, proteins are selectively sorted into membrane bound transport intermediates by vesicle adaptors, which include those of the highly conserved adaptor protein (AP) complex family. Each AP complex has a distinct subcellular localisation and functions in the sorting of a specific subset of transmembrane cargo proteins. Adaptor protein complex 4 (AP-4) is one of the more recently identified AP complexes, whose function has largely remained elusive. In humans, AP-4 deficiency causes a severe neurological disorder, suggesting an important role in neuronal development and homeostasis. However, the pathomechanisms that underly the neuronal pathology in AP-4 deficiency are currently unknown. AP-4 is proposed to function in protein sorting at the trans-Golgi network (TGN), so AP-4 deficiency can be thought of as a disease of missorting. The aim of this study was to apply unbiased global proteomic approaches to define the composition of AP-4 vesicles and to identify physiological cargo proteins of the AP-4 pathway. Using 'Dynamic Organellar Maps' and comparative analysis of vesicle-enriched fractions from wild-type and AP-4-depleted cells, three ubiquitously expressed transmembrane cargo proteins, ATG9A, SERINC1 and SERINC3, were found to be mislocalised in AP-4-deficient cells. Two novel cytosolic AP-4 accessory proteins, RUSC1 and RUSC2, were also identified. Further proteomic analyses confirmed the interactions between these proteins. AP-4 deficiency was found to cause missorting of ATG9A in diverse cell types, including patient derived cells, as well as dysregulation of autophagy. RUSC2 facilitates the transport of AP-4-derived, ATG9A and SERINC-positive vesicles from the TGN to the cell periphery. These vesicles cluster in close association with autophagosomes, suggesting they are the 'ATG9 reservoir' required for autophagosome biogenesis. This study uncovers ATG9A trafficking as a ubiquitous function of the AP-4 pathway. Furthermore, it provides a potential molecular pathomechanism of AP-4 deficiency, through dysregulated spatial control of autophagy.

High expression of B-Myb (encoded by MYBL2), an oncogenic transcription factor, is associated with cell cycle deregulation and poor prognosis in several cancers, including ovarian cancer. However, the mechanism by which B-Myb alters the cell cycle is not fully understood. In proliferating cells, B-Myb interacts with the MuvB core complex including LIN9, LIN37, LIN52, RBBP4, and LIN54, forming the MMB (Myb-MuvB) complex, and promotes transcription of genes required for mitosis. Alternatively, the MuvB core interacts with Rb-like protein p130 and E2F4-DP1 to form the DREAM complex that mediates global repression of cell cycle genes in G0/G1, including a subset of MMB target genes. Here, we show that overexpression of B-Myb disrupts the DREAM complex in human cells, and this activity depends on the intact MuvB-binding domain in B-Myb. Furthermore, we found that B-Myb regulates the protein expression levels of the MuvB core subunit LIN52, a key adaptor for assembly of both the DREAM and MMB complexes, by a mechanism that requires the S28 phosphorylation site in LIN52. To validate our cellular findings, we determined the effect of B-Myb levels on DREAM target gene expression in HGSOC tissue samples and corresponding patient outcomes. Given that high expression of B-Myb correlates with global loss of repression of DREAM target genes in breast and ovarian cancer, our findings offer mechanistic insights for aggressiveness of cancers with MYBL2 amplification and establish the rationale for targeting B-Myb to restore cell cycle control.

Iron-sulfur (Fe-S) clusters are critical protein cofactors found in all life forms. In eukaryotes, a well-conserved biosynthetic pathway located in the mitochondria is used to assemble Fe-S clusters. Although proteins required for Fe-S cluster biosynthesis have been identified, their precise function and mechanism remain elusive. In this study, biochemical and biophysical methods are applied to understand molecular details for the core components of the human Fe-S cluster biosynthesis: Nfs1, Isd11, Isu2, and frataxin (Fxn). Nfs1 is a cysteine desulfurase that converts cysteine into alanine and transfers the sulfur to a scaffold protein Isu2 for Fe-S clusters. Fxn depletion is associated with the neurodegenerative disease Friedreich’s ataxia (FRDA), and results in a complicated phenotype that includes loss of Fe-S clusters. The results presented here provide the first in vitro evidence for a stable protein complex that exists in at least two forms: an inactive complex with Nfs1, Isd11, and Isu2 (SDU) components and an active form that also includes Fxn (SDUF). Fxn binding dramatically changes the catalytic efficiency (kcat/KM) of Nfs1 from 25 to 10,100 M-1s-1 and enhances the rate of Fe-S cluster biosynthesis 25 fold. Oxidizing conditions diminish the levels of both complex formation and Fxn-based activation, whereas Fe2 further stimulates Nfs1 activity. Mutagenesis coupled to enzyme kinetics indicate that one of the three conserved cysteines (C104) on Isu2 accepts the sulfane sulfur from Nfs1 and that this transfer event likely requires prior binding of Fxn. In vitro interrogation of FRDA I154F and W155R and related Fxn variants revealed the binding affinity to SDU followed the trend Fxn ~ I154F > W155F > W155A ~ W155R. The Fxn variants also have diminished ability to facilitate both sulfur transfer and Fe-S cluster assembly. Fxn crystallographic structures reveal specific rearrangements associated with the loss of function. Importantly, the weaker binding and lower activity of the W155R variant compared to I154F explains the earlier onset and more severe disease progression. Finally, these experimental results coupled with computational docking studies suggest a model for how human Fxn functions as an allosteric activator and triggers sulfur transfer and Fe-S cluster assembly.

Both the maximum agreement forest problem and the multicut on trees problem are NP-hard, thus cannot be solved efficiently if P /=NP. The maximum agreement forest problem was motivated in the study of evolution trees in bioinformatics, in which we are given two leaf-labeled trees and are asked to find a maximum forest that is a subgraph of both trees. The multicuton trees problem has applications in networks, in which we are given a forest and a set of pairs of termianls and are asked to find a cut that separates all pairs of terminals. We develop combinatorial and algorithmic techniques that lead to improved parameterized algorithms, approximation algorithms, and kernelization algorithms for these problems. For the maximum agreement forest problem, we proceed from the bottommost level of trees and extend solutions to whole trees. With this technique, we show that the maxi- mum agreement forest problem is fixed-parameterized tractable in general trees, resolving an open problem in this area. We also provide the first constant ratio approximation algorithm for the problem in general trees. For the multicut on trees problem, we take a new look at the problem through the eyes of vertex cover problem. This connection allows us to develop an kernelization algorithm for the problem, which gives an upper bound of O(k3) on the kernel size, significantly improving the previous best upper bound O(k6). We further exploit this connection to give a parameterized algorithm for the problem that runs in time O∗ (1.62k), thus improving the previous best algorithm of running time O∗ (2k). In the protein complex prediction problem, which comes directly from the study of bioinformatics, we are given a protein-protein interaction network, and are asked to find dense regions in this graph. We formulate this problem as a graph clustering problem and develop an algorithm to refine the results for identifying protein complexes. We test our algorithm on yeast protein- protein interaction networks, and we show that our algorithm is able to identify complexes more accurately than other existing algorithms.