Este estudo trata das proteínas relacionadas ao desenvolvimento e à formação da parede celular vegetal de cana-de-açúcar, com o objetivo de auxiliar no desenvolvimento de novas tecnologias para a produção de etanol celulósico a partir do bagaço de cana. Com isso, as proteínas de parede celular de entrenós e folhas de plantas com 4 meses de idade em dois estádios de desenvolvimento, juvenil e maduro, foram identificadas. Para extração foi utilizado o método não destrutivo por infiltração a vácuo utilizando dois sais, 0,2 M de CaCl2 e 2 M de LiCl seguido de centrifugação. As amostras complexas foram digeridas, fracionadas, sequenciadas por LC-MSE . Os peptídeos foram processados utilizando o ProteinLynx 2.5 e comparados com a base de dados de ESTs traduzidos de cana e sorgo. A anotação das proteínas foi realizada com base no programa PFAM e dividas em classes funcionais. Apenas as proteínas que apareceram em pelo menos duas das três repetições biológicas foram utilizadas na análise principal. Para prever a localização subcelular das proteínas selecionadas utilizaram-se os softwares: SignalP, TargetP, Predotar e TMHMM. Apenas aquelas proteínas que foram preditas para serem secretadas por dois ou mais programas foram consideradas como proteínas de parede celular (PPC). Ao todo, 543 proteínas foram consideradas como PPC: 205 em entrenós jovens, 143 em entrenós maduros, 124 em folhas jovens e 71 em folhas maduras. Dentre essas proteínas, 365 foram consideradas diferentes, e caracterizadas em dez classes funcionais. A análise estatística compreendeu a análise de PCA e PLS-DA, havendo diferença estatística entre os tratamentos analisados. Neste trabalho, foram encontradas 66 glicosil-hidrolases e 39 peroxidases, sendo 14 e 11 exclusivas de tecidos juvenis, respectivamente. Essas proteínas são conhecidas por terem funções relacionadas à quebra e ao remodelamento dos polissacarídeos da parede celular vegetal, e, portanto, foram indicadas neste estudo como alvo de pesquisas futuras que utilizem as próprias enzimas da planta para otimização da produção do etanol celulósico.Individualmente, este estudo foi o que mais identificou PPCs dentre a literatura existente, além de ter sido pioneiro na utilização da análise quantitativa para PPC. / This study provides information about the proteins of the cell wall of sugarcane at diferente stages of development and formation. The aim of this study is to assist in the development of new technologies for the production of cellulosic ethanol from sugarcane bagasse. Cell wall proteins from 4-month-old internodes and leaves of sugarcane in two developmental stages, juvenile and mature, have been identified. Protein extraction was performed with a non-destructive method by using vacuum infiltration with two salts, 0.2 M CaCl2 and 2 M LiCl, followed by centrifugation. Complex samples were digested, fractionated and sequenced by LC-MSE. Peptides were processed by ProteinLynx 2.5 and compared to the translated sugarcane and sorghum ESTs database. The annotation of the proteins was performed using PFAM and the functional classification was according the one used in other related studies. Only the proteins that appeared in at least two of the three biological replicates were used in the main analysis. In order to predict the subcellular localization of these proteins, SignalP, TargetP, TMHMM and Predotar softwares were used. Only those proteins that were predicted to be secreted by two or more programs were considered as cell wall proteins (PPS). Altogether, 543 proteins were classified as PPC: 205 inimmature internodes, 143 in mature internodes, 124 in young leaves and 71 in matured leaves. Among these proteins, 365 were considered different, and divided into ten functional classes. Statistical analysis was made with PCA and PLSDA, confirming that there were statistical differences among the treatments. In this work, 66 glycoside hydrolases and 39 peroxidases c identified, being 14 and 11 unique to young tissues, respectively. These proteins have their function related to plant cell wall polysaccharides breakdown and remodeling, and, therewith, the glycoside hydrolases and peroxidases found in this study were indicated to be the target of future research using the plant\'s own enzymes to optimize the cellulosic ethanol production. Individually, this study was the one that most identified PPC among the existing literature, and is a pioneer in the use of quantitative analysis for PPCs.

Este estudo trata das proteínas relacionadas ao desenvolvimento e à formação da parede celular vegetal de cana-de-açúcar, com o objetivo de auxiliar no desenvolvimento de novas tecnologias para a produção de etanol celulósico a partir do bagaço de cana. Com isso, as proteínas de parede celular de entrenós e folhas de plantas com 4 meses de idade em dois estádios de desenvolvimento, juvenil e maduro, foram identificadas. Para extração foi utilizado o método não destrutivo por infiltração a vácuo utilizando dois sais, 0,2 M de CaCl2 e 2 M de LiCl seguido de centrifugação. As amostras complexas foram digeridas, fracionadas, sequenciadas por LC-MSE . Os peptídeos foram processados utilizando o ProteinLynx 2.5 e comparados com a base de dados de ESTs traduzidos de cana e sorgo. A anotação das proteínas foi realizada com base no programa PFAM e dividas em classes funcionais. Apenas as proteínas que apareceram em pelo menos duas das três repetições biológicas foram utilizadas na análise principal. Para prever a localização subcelular das proteínas selecionadas utilizaram-se os softwares: SignalP, TargetP, Predotar e TMHMM. Apenas aquelas proteínas que foram preditas para serem secretadas por dois ou mais programas foram consideradas como proteínas de parede celular (PPC). Ao todo, 543 proteínas foram consideradas como PPC: 205 em entrenós jovens, 143 em entrenós maduros, 124 em folhas jovens e 71 em folhas maduras. Dentre essas proteínas, 365 foram consideradas diferentes, e caracterizadas em dez classes funcionais. A análise estatística compreendeu a análise de PCA e PLS-DA, havendo diferença estatística entre os tratamentos analisados. Neste trabalho, foram encontradas 66 glicosil-hidrolases e 39 peroxidases, sendo 14 e 11 exclusivas de tecidos juvenis, respectivamente. Essas proteínas são conhecidas por terem funções relacionadas à quebra e ao remodelamento dos polissacarídeos da parede celular vegetal, e, portanto, foram indicadas neste estudo como alvo de pesquisas futuras que utilizem as próprias enzimas da planta para otimização da produção do etanol celulósico.Individualmente, este estudo foi o que mais identificou PPCs dentre a literatura existente, além de ter sido pioneiro na utilização da análise quantitativa para PPC. / This study provides information about the proteins of the cell wall of sugarcane at diferente stages of development and formation. The aim of this study is to assist in the development of new technologies for the production of cellulosic ethanol from sugarcane bagasse. Cell wall proteins from 4-month-old internodes and leaves of sugarcane in two developmental stages, juvenile and mature, have been identified. Protein extraction was performed with a non-destructive method by using vacuum infiltration with two salts, 0.2 M CaCl2 and 2 M LiCl, followed by centrifugation. Complex samples were digested, fractionated and sequenced by LC-MSE. Peptides were processed by ProteinLynx 2.5 and compared to the translated sugarcane and sorghum ESTs database. The annotation of the proteins was performed using PFAM and the functional classification was according the one used in other related studies. Only the proteins that appeared in at least two of the three biological replicates were used in the main analysis. In order to predict the subcellular localization of these proteins, SignalP, TargetP, TMHMM and Predotar softwares were used. Only those proteins that were predicted to be secreted by two or more programs were considered as cell wall proteins (PPS). Altogether, 543 proteins were classified as PPC: 205 inimmature internodes, 143 in mature internodes, 124 in young leaves and 71 in matured leaves. Among these proteins, 365 were considered different, and divided into ten functional classes. Statistical analysis was made with PCA and PLSDA, confirming that there were statistical differences among the treatments. In this work, 66 glycoside hydrolases and 39 peroxidases c identified, being 14 and 11 unique to young tissues, respectively. These proteins have their function related to plant cell wall polysaccharides breakdown and remodeling, and, therewith, the glycoside hydrolases and peroxidases found in this study were indicated to be the target of future research using the plant\'s own enzymes to optimize the cellulosic ethanol production. Individually, this study was the one that most identified PPC among the existing literature, and is a pioneer in the use of quantitative analysis for PPCs.

Mass spectrometry is the primary technology of proteomics. For the analysis of complex proteomes, protein identities and quantities are inferred from their peptides that are generated by cleaving all proteins with the endopeptidase trypsin. But there is one major disadvantage that is due to biophysical differences, different peptides cause different intensities. Miscellaneous approaches have been developed to circumvent this problem based on the chemical or metabolic introduction of heavy stable isotopes. This enables to monitor protein abundance differences of two or more samples on the same tryptic peptides that differ in mass only. Absolute quantification can be achieved similar by spiking-in synthetic isotopical labeled counterparts of a sample’s tryptic peptides. However, labeling technics suffer from high prices, introduced biases, need for extensive manual control, laborious implementation and implementation restrictions. Therefore, a multiplicity of label-free approaches have been developed that profit from instrumental improvements targeting reliability of identifications and reproducibility of quantitative values. No extensive systematic comparison of label-free quantitative parameters has been published so far presumably because of the laborious implementation. An analysis of primary label-free parameters and associated normalization methods is presented here that compares dynamic and linear ranges and accuracies in the estimation of protein amounts. This facilitated the establishment of label-free procedures addressing three fundamental questions in proteomics: what is a sample’s composition, are proteins that share a specific property enriched and what are the differences between two (or more) samples. A new mathematic model is presented that defines and elucidates enrichment. The procedures were applied first to analyze and compare stem cell plasma membrane proteomes. This is an ambitious model for proteomics because of only small amounts of arduous to analyze, partial hydrophobic proteins in a complex proteomic and chemical background. It is of scientific relevance, as membrane proteins are the cell’s communication interface that enable cell type specific processes and hence can be used to define, isolate and quantify those. The success of cell surface proteome enrichment, the quantitative composition of the proteome and the proteomic difference between stem cells isolated from the dental pulp and cultivated in different media is shown. Secondly, the procedures were applied to the analysis of transient protein networks that assemble onto proteo-liposomes in a newly designed recruitment assay that fully recapitulates membrane sorting as seen in vivo. All transmembrane proteins need to be trafficked to other organelles’ membranes by vesicular trafficking. Sorting signals within the cytosolic regions of the protein cargos trigger the formation of trafficking complexes around those. The transient membrane complexes additionally recognize organelle or organelle-domain specific membrane lipids, such as phosphatidylinositol phosphates. Different trafficking ways are characterized by different trafficking complexes. The elucidation of trafficking complexes that form around a transmembrane protein of interest discloses its trafficking routes and involved signaling processes. The synthetic proteo-liposomes were prepared from chemically defined lipids and heterologous expressed cytosolic domains of type I or type II membrane receptors. The proteomic analyses of such samples are challenging because of huge proteomic backgrounds of proteins binding to the liposomes irrespective of the receptor and relatively small amounts and numbers of receptor-specific binders. Though the basic idea is to elucidate sorting machineries and study membrane trafficking processes, such experiments are untargeted and miscellaneous discoveries were achieved. We elucidated that the apical determinant crumbs 2 is a cargo of the retromer complex. This revealed a fameless level of control for the establishment of cell polarity. We found retromer along with the adapter complexes AP 4 and AP 5 trafficking the beta amyloid precursor protein APP. This confirmed recent publications and yielded new insights. Moreover, many more proteins and complexes appeared to associate with the cytosolic part of APP (AICD) in a membrane context-dependent or -independent manner. Among those, some were so far unknown to interact with AICD, like mTORC1 and the PIKFyve complex.

Euglena gracilis is a species of unicellular photosynthetic flagellate that inhibits aquatic ecosystems. E. gracilis belongs to the supergroup Excavata, and are an important component of the global biosphere, have biotechnological potential and is useful biological model due to their evolutionary history and complex biology. Whilst the evolutionary position of E. gracilis is now clear, their relationship with other protists such as Naegleria, Giardia, and Kinetoplastids, remains to be investigated in detail. Investigating and understanding the biology of this complex organism is a promising way to approach many evolutionary puzzles, including secondary endosymbiotic events and the evolution of parasitism, due to their relationship with Kinetoplastids. Here, I report a draft genome for E. gracilis, together with a high quality transcriptome and proteomic analysis. The estimated genome size is ~ 2 Gbp, with a GC content of ~ 50 % and a protein coding potential predicted at 36,526 Open Reading Frames (ORFs). Less than 25% of the genome is single copy sequence, indicating extensive repeat structure. There are evidences for large number of paralogs amongst specific gene families, indicating expansions and possible polyploidy as well as extensive sharing of genes with other non photosynthetic and photosynthetic eukaryotes: red and green algael genes, together with trypanosomes and other members of the excavates. Functional resolution into several of the biological systems indicates multiple similarities with the trypanosomatids in terms of orthology, paralogy, relatedness and complexity. Several biological systems such as nuclear architecture (e.g. chromosome segregation, nuclear pore complex, nuclear lamins), protein trafficking, translation, surface, consist of conserved and divergent components. For instance, several gene families likely associated with the cell surface and signal transduction possess very large numbers of lineage-specific paralogs, suggesting great flexibility in environmental monitoring and, together with divergent mechanisms for metabolic control, novel solutions to adaptation to extreme environments. I also demonstrate that the majority of control of protein expression levels is post-transcriptional and absence of transcriptional regulation, despite the presence of conventional introns. These data are a major advance in the understanding of the nuclear genome of Euglenids and provide a platform for investigation of the contributions of E. gracilis and relatives to the biosphere.

The feasibility of FTIR-based spectroscopy as a tool to measure cellular response to therapeutics was investigated. Fourier transform mid-infrared spectroscopy has been used in conjunction with multivariate analysis (MVA) to assess the chemistry of many clinically relevant biological materials; however, the technique has not yet found its place in a clinical setting. One issue that has held the technique back is due to the spectral distortions caused by resonant Mie scattering (RMieS), which affects the ability to confidently assign molecular assignments to the spectral signals from biomaterials. In the light of recently improved understanding of RMieS, resulting in a novel correction algorithm, the analytical robustness of corrected FTIR spectra was validated against multi-discipline methods to characterise a set of renal cell lines which were selected for their difference in morphology.After validation of the FTIR methodology by discriminating different cell lines, the second stage of analyses tested the sensitivity of FTIR technique by determining if discrete chemical differences could be highlighted within a cell population of the same origin. The renal carcinoma cell line 2245R contains a sub-population to contain a sub-population of cells displaying 'stem-cell like' properties. These stem-like cells, however, are difficult to isolate and characterise by conventional '-omic' means. Finally, cellular response to chemotherapeutics was investigated using the established renal cell lines CAKI-2 and A-498. For the model, 5-fluorouracil (5FU), an established chemotherapeutic agent with known mechanisms of action was used. Novel gold-based therapeutic compounds were also assessed in parallel to determine their efficacy against renal cell carcinoma. The novel compounds displayed initial activity, as the FTIR evidence suggested compounds were able to enter the cells in the first instance, evoking a cellular response. The long-term performance, tracked with standard proliferation assays and FTIR spectroscopy in the renal cancer cell model, however, was poor. Rather than dismissing the compounds as in-active, the compounds may simply be more effective in cancer cell types of a different nature. The FTIR-based evidence provided the means to suggest such a conclusion. Overall, the initial results suggest that the combination of FTIR and MVA, in the presence of the novel RMieS-EMSC algorithm can detect differences in cellular response to chemotherapeutics. The results were also in-line with complimentary biological-based techniques, demonstrating the powerful potential of the technique as a promising drug screening tool.