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Evolution and Diversity of Sexually-Related Genes in the Arbuscular Mycorrhizal Fungus Rhizophagus irregularisCharron, Philippe January 2015 (has links)
Arbuscular mycorrhizal fungi (AMF) are ancient organisms that form symbioses with more than 80% of land plants. Fossil evidence of this partnership dates back 460Ma, when land was first colonized by plants. The mutualistic relationship between host roots and the fungus consists of an exchange of essential nutrients for the proliferation of both organisms, highlighting the importance of the mycorrhizal symbiosis. Despite their extreme longevity, a lack of evidence supporting sexual reproduction has labelled AMF as asexual organisms. However, recent evidence seems to point towards the potential of a cryptic sexuality. Specifically, AMF genomes encode for homologues of proteins that have a role in sexual processes in other fungi, including several typically involved in partner recognition, such as mating-type high mobility group (MATA-HMG) proteins found in mating-type loci. In my thesis, I expanded our analyses to five isolates of the AMF model organism Rhizophagus irregularis, through the acquisition of novel genome data. Some key findings consist of an expansion of MATA-HMG proteins, their unique organizations throughout the genome and the presence of a conserved fungal pheromone pathway. In retrospect, this research uncovers an unprecedented number of AMF genes that are homologues to sex-related genes of other fungi and reveals for the first time their atypical genomic architecture, providing valuable information towards the identification of a cryptic sexuality in these ecologically and economically important organisms.
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Parallel algorithms for real-time peptide-spectrum matchingZhang, Jian 16 December 2010
Tandem mass spectrometry is a powerful experimental tool used in molecular biology to determine the composition of protein mixtures. It has become a standard technique for protein identification. Due to the rapid development of mass spectrometry technology, the instrument can now produce a large number of mass spectra which are used for peptide identification. The increasing data size demands efficient software tools to perform peptide identification.<p>
In a tandem mass experiment, peptide ion selection algorithms generally select only the most abundant peptide ions for further fragmentation. Because of this, the low-abundance proteins in a sample rarely get identified. To address this problem, researchers develop the notion of a `dynamic exclusion list', which maintains a list of newly selected peptide ions, and it ensures these peptide ions do not get selected again for a certain time. In this way, other peptide ions will get more opportunity to be selected and identified, allowing for identification of peptides of lower abundance.
However, a better method is to also include the identification results into the `dynamic exclusion list' approach. In order to do this, a real-time peptide identification algorithm is required.<p>
In this thesis, we introduce methods to improve the speed of peptide identification so that the `dynamic exclusion list' approach can use the peptide identification results without affecting the throughput of the instrument. Our work is based on RT-PSM, a real-time program for peptide-spectrum matching with statistical significance. We profile the speed of RT-PSM and find out that the peptide-spectrum scoring module is the most time consuming portion.<p>
Given by the profiling results, we introduce methods to parallelize the peptide-spectrum scoring algorithm. In this thesis, we propose two parallel algorithms using different technologies. We introduce parallel peptide-spectrum matching using SIMD instructions. We implemented and tested the parallel algorithm on Intel SSE architecture. The test results show that a 18-fold speedup on the entire process is obtained. The second parallel algorithm is developed using NVIDIA CUDA technology. We describe two CUDA kernels based on different algorithms and compare the performance of the two kernels. The more efficient algorithm is integrated into RT-PSM. The time measurement results show that a 190-fold speedup on the scoring module is achieved and 26-fold speedup on the entire process is obtained. We perform profiling on the CUDA version again to show that the scoring module has been optimized sufficiently to the point where it is no longer the most time-consuming module in the CUDA version of RT-PSM.<p>
In addition, we evaluate the feasibility of creating a metric index to reduce the number of candidate peptides. We describe evaluation methods, and show that general indexing methods are not likely feasible for RT-PSM.
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Parallel algorithms for real-time peptide-spectrum matchingZhang, Jian 16 December 2010 (has links)
Tandem mass spectrometry is a powerful experimental tool used in molecular biology to determine the composition of protein mixtures. It has become a standard technique for protein identification. Due to the rapid development of mass spectrometry technology, the instrument can now produce a large number of mass spectra which are used for peptide identification. The increasing data size demands efficient software tools to perform peptide identification.<p>
In a tandem mass experiment, peptide ion selection algorithms generally select only the most abundant peptide ions for further fragmentation. Because of this, the low-abundance proteins in a sample rarely get identified. To address this problem, researchers develop the notion of a `dynamic exclusion list', which maintains a list of newly selected peptide ions, and it ensures these peptide ions do not get selected again for a certain time. In this way, other peptide ions will get more opportunity to be selected and identified, allowing for identification of peptides of lower abundance.
However, a better method is to also include the identification results into the `dynamic exclusion list' approach. In order to do this, a real-time peptide identification algorithm is required.<p>
In this thesis, we introduce methods to improve the speed of peptide identification so that the `dynamic exclusion list' approach can use the peptide identification results without affecting the throughput of the instrument. Our work is based on RT-PSM, a real-time program for peptide-spectrum matching with statistical significance. We profile the speed of RT-PSM and find out that the peptide-spectrum scoring module is the most time consuming portion.<p>
Given by the profiling results, we introduce methods to parallelize the peptide-spectrum scoring algorithm. In this thesis, we propose two parallel algorithms using different technologies. We introduce parallel peptide-spectrum matching using SIMD instructions. We implemented and tested the parallel algorithm on Intel SSE architecture. The test results show that a 18-fold speedup on the entire process is obtained. The second parallel algorithm is developed using NVIDIA CUDA technology. We describe two CUDA kernels based on different algorithms and compare the performance of the two kernels. The more efficient algorithm is integrated into RT-PSM. The time measurement results show that a 190-fold speedup on the scoring module is achieved and 26-fold speedup on the entire process is obtained. We perform profiling on the CUDA version again to show that the scoring module has been optimized sufficiently to the point where it is no longer the most time-consuming module in the CUDA version of RT-PSM.<p>
In addition, we evaluate the feasibility of creating a metric index to reduce the number of candidate peptides. We describe evaluation methods, and show that general indexing methods are not likely feasible for RT-PSM.
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Caracterização estrutural da interação de serino proteinases de Spodoptera frugiperda (Lepidoptera: Noctuidae) e inibidores de proteinases de plantas / Structural characterisation of Spodoptera frugiperda (Lepidoptera: Noctuidae) serine proteinase interactions with plant proteinase inhibitors.Ligia Hansen Arruda 18 May 2011 (has links)
As plantas desenvolveram diferentes mecanismos para reduzir o ataque de insetos, incluindo compostos protéicos de defesa, como os inibidores de proteinases (IPs). Os insetos, ao longo da evolução, desenvolveram estratégias para superar as barreiras defensivas das plantas, permitindo a sua alimentação e desenvolvimento, como a super expressão de genes de enzimas digestivas sensíveis e insensíveis aos IPs de plantas. Uma das abordagens desse trabalho foi identificar novas serinoproteinases no intestino de lagartas de Spodoptera frugiperda. Duas novas quimotripsinas e trê novas tripsinas foram identificadas e juntamente com mais 10 genes já conhecidos que codificam estas enzimas foram submetidos à análise de expressão gênica por PCR em tempo real. Entre essas duas famílias de serinoproteinases (SPs) os genes que codificam as quimotripsinas apresentam uma regulação positiva mais ampla do que aqueles que codificam as tripsinas. Estudos de modelagem molecular das quimotripsinas também foram realizados. Foram construídos modelos tridimensionais à partir de modelagem por homologia além de análises de dinâmica molecular e docagem com oito diferentes IPs do tipo Bowman- Birk. Os resultados mostram quais quimotripsinas apresentam as maiores afinidades aos inibidores testados de maneira geral e individual, inferidos à partir da estimativa de energia livre do sistema. Também foi encontrada uma serina extra próxima ao sítio catalítico de três quimotrispsinas modeladas que pode interferir na afinidade dessas enzimas já que este aminoácido apresenta perda de área acessível ao solvente quando complexada ao IP de soja testado. Os resultados de expressão gênica e grau de sensibilidade foram comparados e não se observou qualquer relação entre esses parâmentros. Isso sugere que as lagartas da espécie S. frugiperda combinam diferentes estratégias adaptativas como o aumento de expressão de todas as suas quimotripsinas independentemente do grau de sensibilidade das enzimas. / Plants have developed different mechanisms to reduce insect attack, including defence proteins such as proteinase inhibitors (PIs). In turn, insects have evolved strategies to overcome these plant defence mechanisms, such as the hyperexpression of PI-sensitive and insensitive digestive enzymes, allowing the insect to thrive. One of the aims of this work was to identify new serine proteinases (SPs) in the gut of the fall armyworm larvae, Spodoptera frugiperda. Two new chymotrypsins and three new trypsins were identified, and together with 10 previously identified genes, the genes that encode these enzymes were subjected to real-time PCR and gene expression analysis. Between these two families of serine-proteinases the genes that encode chymotrypsins show a greater positive regulation then those encoding the trypsins. Molecular modelling studies of the chymotrypsins were carried out, and 3D models were generated using homology modelling, which were then further refined by dynamic molecular and docking analyses with 8 different Bowman-Birk type PIs. The results demonstrate which chymotrypsins possess the highest affinities to the tested inhibitors in a general and individual manner, inferred from the estimated free energies. A serine residue in very close proximity to the catalytic site was present in three of chymotrypsins investigated, which may be affecting the enzymes affinity since the residue has a reduced accessible area to the solvent when complexed to the soya PI tested. The genetic expression patterns and the degree of PI-sensitivity were also compared and no relation between the parameters was found. This suggests that the larvae of the species S. frugiperda combine different adaptive strategies like the increase in expression of its entire chymotrypsin arsenal regardless of the degree of PI-sensitivity of the enzymes.
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Caracterização estrutural da interação de serino proteinases de Spodoptera frugiperda (Lepidoptera: Noctuidae) e inibidores de proteinases de plantas / Structural characterisation of Spodoptera frugiperda (Lepidoptera: Noctuidae) serine proteinase interactions with plant proteinase inhibitors.Arruda, Ligia Hansen 18 May 2011 (has links)
As plantas desenvolveram diferentes mecanismos para reduzir o ataque de insetos, incluindo compostos protéicos de defesa, como os inibidores de proteinases (IPs). Os insetos, ao longo da evolução, desenvolveram estratégias para superar as barreiras defensivas das plantas, permitindo a sua alimentação e desenvolvimento, como a super expressão de genes de enzimas digestivas sensíveis e insensíveis aos IPs de plantas. Uma das abordagens desse trabalho foi identificar novas serinoproteinases no intestino de lagartas de Spodoptera frugiperda. Duas novas quimotripsinas e trê novas tripsinas foram identificadas e juntamente com mais 10 genes já conhecidos que codificam estas enzimas foram submetidos à análise de expressão gênica por PCR em tempo real. Entre essas duas famílias de serinoproteinases (SPs) os genes que codificam as quimotripsinas apresentam uma regulação positiva mais ampla do que aqueles que codificam as tripsinas. Estudos de modelagem molecular das quimotripsinas também foram realizados. Foram construídos modelos tridimensionais à partir de modelagem por homologia além de análises de dinâmica molecular e docagem com oito diferentes IPs do tipo Bowman- Birk. Os resultados mostram quais quimotripsinas apresentam as maiores afinidades aos inibidores testados de maneira geral e individual, inferidos à partir da estimativa de energia livre do sistema. Também foi encontrada uma serina extra próxima ao sítio catalítico de três quimotrispsinas modeladas que pode interferir na afinidade dessas enzimas já que este aminoácido apresenta perda de área acessível ao solvente quando complexada ao IP de soja testado. Os resultados de expressão gênica e grau de sensibilidade foram comparados e não se observou qualquer relação entre esses parâmentros. Isso sugere que as lagartas da espécie S. frugiperda combinam diferentes estratégias adaptativas como o aumento de expressão de todas as suas quimotripsinas independentemente do grau de sensibilidade das enzimas. / Plants have developed different mechanisms to reduce insect attack, including defence proteins such as proteinase inhibitors (PIs). In turn, insects have evolved strategies to overcome these plant defence mechanisms, such as the hyperexpression of PI-sensitive and insensitive digestive enzymes, allowing the insect to thrive. One of the aims of this work was to identify new serine proteinases (SPs) in the gut of the fall armyworm larvae, Spodoptera frugiperda. Two new chymotrypsins and three new trypsins were identified, and together with 10 previously identified genes, the genes that encode these enzymes were subjected to real-time PCR and gene expression analysis. Between these two families of serine-proteinases the genes that encode chymotrypsins show a greater positive regulation then those encoding the trypsins. Molecular modelling studies of the chymotrypsins were carried out, and 3D models were generated using homology modelling, which were then further refined by dynamic molecular and docking analyses with 8 different Bowman-Birk type PIs. The results demonstrate which chymotrypsins possess the highest affinities to the tested inhibitors in a general and individual manner, inferred from the estimated free energies. A serine residue in very close proximity to the catalytic site was present in three of chymotrypsins investigated, which may be affecting the enzymes affinity since the residue has a reduced accessible area to the solvent when complexed to the soya PI tested. The genetic expression patterns and the degree of PI-sensitivity were also compared and no relation between the parameters was found. This suggests that the larvae of the species S. frugiperda combine different adaptive strategies like the increase in expression of its entire chymotrypsin arsenal regardless of the degree of PI-sensitivity of the enzymes.
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