Thesis (Ph. D.)--Northeastern University, 2009. / Title from title page (viewed June 4, 2009). Graduate School of Arts and Sciences, Dept. of Chemistry and Chemical Biology. Includes bibliographical references.

Liquid chromatography (LC) in tandem with mass spectrometry (MS) is a measurement tool for obtain information about the compounds in the investigated extracts. There were already developed methods for processing and analysis of measured data sets. However, only partial problems of processing/analysis task were handled independently. Therefore, the rst part describes existing methods and techniques commonly used in the LC-MS for the processing and analysis today. In this thesis an approach based on the theory of systems is used for description of abstract model above the measured data. This model encapsulated all processing/analysis steps into appropriate and consistent mathematical space. The creation of this model via description of the measurement device and data outputs is introduced. Abstract model of LC-MS data set is used to decompose the measurement into three partial contributions, the analyte signal, the random noise and the systemic noise. The separation process of the signal could be estimated using the probabilistic approach. That probabilistic approach to the LC-MS analysis was implemented in the developed software, which was published in the Bioinformatics Journal.

Tissues are heterogeneous ecosystems comprised of various cell types. For example, in tumor tissues, malignant cancer cells are surround by various non-malignant stromal cells. Proteins, especially N-linked glycoproteins, are key players in tumor microenvironment and respond to many extracellular stimuli for involving and regulating intercellular signaling. Understanding the human proteome and glycoproteome in heterogeneous tissues with spatial resolution are meaningful for exploring intercellular signaling networks and discovering protein biomarkers for various diseases, such as cancer. In this study, we aimed to develop new liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analytical methods for spatially-resolved proteome and glycoproteome profiling in tissue samples, and apply them for profiling potential biomarkers for pancreatic cancer. We first systematically and synchronously optimized the LC-MS parameters to increase peptide sequencing efficiency in data dependent proteomics. Taking advantage of its hybrid instrument design with various mass analyzer and fragmentation strageties, the Orbitrap Fusion mass spectrometer was used for systematically comparing the popular high-high approach by using orbitrap for both MS1 and MS2 scans and high-low approach by using orbitrap for MS1 scan and ion trap for MS2 scans. High-high approach outperformed high-low approach in terms of better saturation of the scan cycle and higher MS2 identification rate. We then systematically optimized various MS parameters for high-high approach. We investigated the influence of isolation window and injection time on scan speed and MS2 identification rate. We then explored how to properly set dynamic exclusion time according to the chromatography peak width. Furthermore, we found that the orbitrap analyzer, rather than the analytical column, was easily saturated with higher peptide loading amount, thus limited the dynamic range of MS1-based quantification. Finally, by using the optimized LC-MS parameters, more than 9000 proteins and 110,000 unique peptides were identified by using 10 hours of effective LC gradient time. The study therefore illustrated the importance of synchronizing LC-MS precursor targeting and high-resolution fragment detection for high-efficient data dependent proteomics. Understanding the tumor heterogeneity through spatially resolved proteome profiling is meaningful for biomedical research. Laser capture microdissection (LCM) is a powerful technology for exploring local cell populations without losing spatial information. Here, we designed an immunohistochemistry (IHC)-based workflow for cell type-resolved proteome analysis of tissue samples. Firstly, targeted cell type was stained by IHC using antibody targeting cell-type specific marker to improve accuracy and efficiency of LCM. Secondly, to increase protein recovery from chemically crosslinked IHC tissues, we optimized a decrosslinking procedure to seamlessly combine with the integrated spintip-based sample preparation technology SISPROT. This newly developed approach, termed IHC-SISPROT, has comparable performance with traditional H&E staining-based proteomic analysis. High sensitivity and reproducibility of IHC-SISPROT was achieved by combining with data independent proteomic analysis. This IHC-SISPROT workflow was successfully applied for identifying 6660 and 6052 protein groups from cancer cells and cancer- associated fibroblasts (CAFs) by using only 5 mm 2 and 12 μm thickness of hepatocellular carcinoma tissue section. Bioinformatic analysis revealed the enrichment of cell type-specific ligands and receptors and potentially new communications between cancer cells and CAFs by these signaling proteins. Therefore, IHC-SISPROT is sensitive and accurate proteomic approach for spatial profiling of cell type-specific proteome from tissues. N-linked glycoproteins are promising candidates for diagnostic and prognostic biomarkers and therapeutic targets. They often locate at plasma membrane and extracellular space with distinct cell type distribution in tissue microenvironment. Due to access to only low microgram of proteins and low abundance of glycoproteins in tissue sections harvested by LCM, region- and cell type-resolved glycoproteome analysis of tissue sections remains challenging. Here we designed a fully integrated spintip-based glycoproteomic approach (FISGlyco) which achieved all the steps for glycoprotein enrichment, digestion, deglycosylation and desalting in a single spintip device. Sample loss is significantly reduced and the total processing time is reduced to 4 hours, while detection sensitivity and label-free quantification precision is greatly improved. 607 N-glycosylation sites were successfully identified and quantified from only 5 μg of mouse brain proteins. By seamlessly combining with LCM, the first region-resolved N-glycoproteome profiling of four mouse brain regions, including isocortex, hippocampus, thalamus, and hypothalamus, was achieved, with 1,875, 1,794, 1,801, and 1,417 N-glycosites identified, respectively. Our approach could be a generic approach for region and even cell type specific glycoproteome analysis of tissue sections. Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with five year survival rate of around 8%. No effective biomarkers and targeted therapy are one of the major reasons for this urgent clinical situation. To explore potential protein biomarkers and drug targets located at intercellular space of pancreatic tumor microenvironment, we established chemical proteomic approach for deep glycoproteome profiling of PDAC clinical tissue samples based on the above- mentioned new proteomic methods. Taking advantage of a long chain biotin- hydrazide probe with less space hindrance, the new method outperformed traditional hydrazide chemistry method in terms of sensitivity, time efficiency and glycoproteome coverage. The method was successfully applied to enrich and validate LIF and its receptors as potential biomarkers for PDAC. In addition, to explore the full map of pancreatic tumor microenvironment glycoproteome with diagnostic and therapeutic values, we collected 114 pancreatic tissues, including 30 PDAC tumor tissues, 30 adjacent non-tumor (NT) tissues, 32 chronic pancreatitis tissues and 22 normal pancreatic tissues, and systematically profiled their glycoprotein expression pattern by using the developed glycoproteomic strategy. The deepest glycoproteome of PDAC was achieved, which covered the majority of previously reported glycoprotein biomarkers and drug targets for PDAC. Importantly, we discovered many new glycoproteins with differential expression in PDAC and normal tissue types. Moreover, LCM-based cell-type proteome profiling was achieved for 13 PDAC tissue samples, which covered more than 8000 proteins for both pancreatic stromal cells and pancreatic cancer cells in each sample. We therefore provided a valuable resource for screening novel and cancer specific glycoprotein biomarkers for pancreatic cancer with spatial resolution

Tissues are heterogeneous ecosystems comprised of various cell types. For example, in tumor tissues, malignant cancer cells are surround by various non-malignant stromal cells. Proteins, especially N-linked glycoproteins, are key players in tumor microenvironment and respond to many extracellular stimuli for involving and regulating intercellular signaling. Understanding the human proteome and glycoproteome in heterogeneous tissues with spatial resolution are meaningful for exploring intercellular signaling networks and discovering protein biomarkers for various diseases, such as cancer. In this study, we aimed to develop new liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analytical methods for spatially-resolved proteome and glycoproteome profiling in tissue samples, and apply them for profiling potential biomarkers for pancreatic cancer. We first systematically and synchronously optimized the LC-MS parameters to increase peptide sequencing efficiency in data dependent proteomics. Taking advantage of its hybrid instrument design with various mass analyzer and fragmentation strageties, the Orbitrap Fusion mass spectrometer was used for systematically comparing the popular high-high approach by using orbitrap for both MS1 and MS2 scans and high-low approach by using orbitrap for MS1 scan and ion trap for MS2 scans. High-high approach outperformed high-low approach in terms of better saturation of the scan cycle and higher MS2 identification rate. We then systematically optimized various MS parameters for high-high approach. We investigated the influence of isolation window and injection time on scan speed and MS2 identification rate. We then explored how to properly set dynamic exclusion time according to the chromatography peak width. Furthermore, we found that the orbitrap analyzer, rather than the analytical column, was easily saturated with higher peptide loading amount, thus limited the dynamic range of MS1-based quantification. Finally, by using the optimized LC-MS parameters, more than 9000 proteins and 110,000 unique peptides were identified by using 10 hours of effective LC gradient time. The study therefore illustrated the importance of synchronizing LC-MS precursor targeting and high-resolution fragment detection for high-efficient data dependent proteomics. Understanding the tumor heterogeneity through spatially resolved proteome profiling is meaningful for biomedical research. Laser capture microdissection (LCM) is a powerful technology for exploring local cell populations without losing spatial information. Here, we designed an immunohistochemistry (IHC)-based workflow for cell type-resolved proteome analysis of tissue samples. Firstly, targeted cell type was stained by IHC using antibody targeting cell-type specific marker to improve accuracy and efficiency of LCM. Secondly, to increase protein recovery from chemically crosslinked IHC tissues, we optimized a decrosslinking procedure to seamlessly combine with the integrated spintip-based sample preparation technology SISPROT. This newly developed approach, termed IHC-SISPROT, has comparable performance with traditional H&E staining-based proteomic analysis. High sensitivity and reproducibility of IHC-SISPROT was achieved by combining with data independent proteomic analysis. This IHC-SISPROT workflow was successfully applied for identifying 6660 and 6052 protein groups from cancer cells and cancer- associated fibroblasts (CAFs) by using only 5 mm 2 and 12 μm thickness of hepatocellular carcinoma tissue section. Bioinformatic analysis revealed the enrichment of cell type-specific ligands and receptors and potentially new communications between cancer cells and CAFs by these signaling proteins. Therefore, IHC-SISPROT is sensitive and accurate proteomic approach for spatial profiling of cell type-specific proteome from tissues. N-linked glycoproteins are promising candidates for diagnostic and prognostic biomarkers and therapeutic targets. They often locate at plasma membrane and extracellular space with distinct cell type distribution in tissue microenvironment. Due to access to only low microgram of proteins and low abundance of glycoproteins in tissue sections harvested by LCM, region- and cell type-resolved glycoproteome analysis of tissue sections remains challenging. Here we designed a fully integrated spintip-based glycoproteomic approach (FISGlyco) which achieved all the steps for glycoprotein enrichment, digestion, deglycosylation and desalting in a single spintip device. Sample loss is significantly reduced and the total processing time is reduced to 4 hours, while detection sensitivity and label-free quantification precision is greatly improved. 607 N-glycosylation sites were successfully identified and quantified from only 5 μg of mouse brain proteins. By seamlessly combining with LCM, the first region-resolved N-glycoproteome profiling of four mouse brain regions, including isocortex, hippocampus, thalamus, and hypothalamus, was achieved, with 1,875, 1,794, 1,801, and 1,417 N-glycosites identified, respectively. Our approach could be a generic approach for region and even cell type specific glycoproteome analysis of tissue sections. Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with five year survival rate of around 8%. No effective biomarkers and targeted therapy are one of the major reasons for this urgent clinical situation. To explore potential protein biomarkers and drug targets located at intercellular space of pancreatic tumor microenvironment, we established chemical proteomic approach for deep glycoproteome profiling of PDAC clinical tissue samples based on the above- mentioned new proteomic methods. Taking advantage of a long chain biotin- hydrazide probe with less space hindrance, the new method outperformed traditional hydrazide chemistry method in terms of sensitivity, time efficiency and glycoproteome coverage. The method was successfully applied to enrich and validate LIF and its receptors as potential biomarkers for PDAC. In addition, to explore the full map of pancreatic tumor microenvironment glycoproteome with diagnostic and therapeutic values, we collected 114 pancreatic tissues, including 30 PDAC tumor tissues, 30 adjacent non-tumor (NT) tissues, 32 chronic pancreatitis tissues and 22 normal pancreatic tissues, and systematically profiled their glycoprotein expression pattern by using the developed glycoproteomic strategy. The deepest glycoproteome of PDAC was achieved, which covered the majority of previously reported glycoprotein biomarkers and drug targets for PDAC. Importantly, we discovered many new glycoproteins with differential expression in PDAC and normal tissue types. Moreover, LCM-based cell-type proteome profiling was achieved for 13 PDAC tissue samples, which covered more than 8000 proteins for both pancreatic stromal cells and pancreatic cancer cells in each sample. We therefore provided a valuable resource for screening novel and cancer specific glycoprotein biomarkers for pancreatic cancer with spatial resolution

No description available.

Traditional proteomics studies can measure many protein biomarkers simultaneously from a single patient-derived sample, promising the possibility of syndromic diagnoses of multiple diseases sharing common symptoms. However, precious cellular-level information is lost in conventional bulk-scale studies that measure tissues comprising many types of cells. As single cells are the building blocks of organisms and are easier to biopsy than traditional bulk samples, performing proteomics on a single-cell level would benefit clinicians and patients. Single-cell proteomics, combined with mass spectrometry imaging, can be used to analyze cells in their microenvironment, preserving spatial information. We have previously used laser-capture microdissection to isolate single motor neurons from tissue and analyze them in our single-cell proteomics platform. However, our sampled population of cells was necessarily limited by the low throughput of the measurement platform, and by the sensitivity of our liquid chromatography-mass spectrometry system to debris introduced in the laser-capture microdissection isolation workflow. In the work described in this dissertation, we dramatically improved the throughput of single-cell proteomics, created a method for removing insoluble debris that clogged our liquid chromatography-mass spectrometry system, and developed a high-performance, low-cost method for nanoflow gradient formation. Together, these methodologies will increase the depth of information and the number of biological replicates that can measured in single-cell proteomics. We hope that these technologies will be applied to future liquid chromatography systems to enable large scale single-cell proteomics studies of tissues. This will reveal the cellular origins of disease on a multimolecular level, while keeping important spatial information. Thus, we expect the technologies and ideas developed here to play a key role in understanding the cellular proteomics in biomedical and clinical settings.

Vascular risk factors inducing a state of chronic cerebral hypoperfusion and metabolic stress are thought to influence the onset and progression of Alzheimer’s disease (AD). To investigate the complex molecular changes underpinning cellular adaptation to metabolic stress, the first aim of this thesis was to define the proteomic response of the SH-SY5Y human neuroblastoma cell line after exposure to the metabolic challenge of oxygen glucose deprivation (OGD). 958 proteins across multiple subcellular compartments were detected and quantified by label-free liquid chromatography mass spectrometry (LC-MS). The levels of 130 proteins were significantly increased (P<0.01) after OGD and the levels of 63 proteins were significantly decreased (P<0.01) while expression of the majority of proteins (765) was not altered. Ingenuity Pathway Analysis identified novel protein-protein interactomes involved with mitochondrial energy production, protein folding, and protein degradation, indicative of coherent and integrated proteomic responses to the metabolic challenge. Approximately one third (61) of the differentially expressed proteins were associated with the endoplasmic reticulum and mitochondria. Electron microscopic analysis of these subcellular structures showed morphologic changes consistent with the identified proteomic alterations. Pertinent to AD research, amyloid binding alcohol dehydrogenase (ABAD) was found to be significantly increased in response to OGD. ABAD is emerging as a key player in mitochondrial dysfunction in AD, yet full understanding of the biochemical pathways in which this protein is involved remain elusive. Using immunoprecipitation coupled to LC-MS (IP-MS), the second aim of the thesis was to characterise the ABAD protein interactome in SH-SY5Y cells and its response to metabolic stress. 67 proteins were identified as potential ABAD interactors under control conditions, and 69 proteins were identified as potential ABAD interactors under OGD conditions. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to determine the subcellular locations and biological functions of the ABAD interacting proteins in control and OGD conditions. DAVID identified the nuclei and mitochondria to contain the greatest number of changes in ABAD interacting proteins following OGD. “Glucose Metabolic Process” (GO:0006006) was the top functional cluster for ABAD interacting proteins in both control and OGD conditions. Independent immunoprecipitations, western blotting, immunohistochemistry and electron microscopy were used to validate specific protein interactions. OGD was found to initiate a novel interaction between ABAD and glucose-regulated protein 75 (GRP75), a finding confirmed in human AD tissue. GRP75 is a mitochondrial protein and marker of the mitochondrial associated membrane (MAM), a specialised region between the mitochondria and the ER. The MAM is known to be enriched with presenilin proteins, involved in the proteolytic cleavage of amyloid precursor protein (APP). These data were used to generate an “ABAD-GRP75-MAM hypothesis of mitochondrial dysfunction in AD”, which might provide a novel link between chronic metabolic stress, ABAD, mitochondrial dysfunction and the onset / progression of AD. The third aim of the thesis was to test this novel hypothesis. Western blotting revealed APP to be significantly decreased following OGD, concurrent with an increase in ABAD protein levels. Over-expression of ABAD protein in SH-SY5Y cells was used to test whether the increased levels of ABAD following OGD were the driving force behind APP down-regulation. ABAD over-expression in SH-SY5Y cells was found to have no detectable effect on APP. Conversely, electron microscopy revealed a dynamic response of the MAM to metabolic stress. This result, along with the interaction of ABAD with GRP75, and the enrichment of presenilins at the MAM, suggests that this specialised membrane region may have an important role to play in AD.

Brevetoxins are natural neurotoxins that are produced by “red tide” algae. In this study, brevetoxin-1 and brevetoxin-2 were incubated with rat liver hepatocytes and rat liver microsomes, respectively. After clean-up steps, samples were analyzed by liquid chromatography-electrospray mass spectrometry (LC-ES-MS). Two metabolites were found for brevetoxin-1: brevetoxin-1-M1 (MW 900 Da), formed by converting one double bond in the E or F ring into a diol; and brevetoxin-1-M2 (MW 884 Da), a hydrolysis product of brevetoxin-1 involving opening of the lactone ring. The incubation study of brevetoxin-2 found two metabolites. Brevetoxin-2-M1 (MW 912 Da) was elucidated by negative mode LC-MS/MS to be the hydrolysis product of brevetoxin-2. The second metabolite (brevetoxin-2-M2, MW 896 Da) was deduced to be brevetoxin-3. All brevetoxins have high affinities for sodium ions. Attempts to obtain informative product ions from the collision induced decomposition (CID) of [M + Na]+ brevetoxin precursor ions only resulted in uninformative sodium ion signals. In our nano-electrospray experiments, the addition of ammonium fluoride resulted in the formation of the ammonium adduct or protonated brevetoxin with a concomitant decrease of the sodium adduct peak. Product ion spectra of [M + NH4]+ and [M + H]+ were similar and provided useful structural information. The optimal values for ammonium fluoride concentration and the cone voltage were experimentally determined. In negative mode electrospray, without additives, deprotonated molecules of brevetoxins do not appear in high abundances, and thus are not well-suited for CID experiments. Several anions were tested for their abilities to form brevetoxin-anion adducts by mixing ammonium salts of these anions with brevetoxin-2 and brevetoxin-3. Under CID, [M + Cl]-, [M + Br]-, [M + OAc]-, [M + HCOO]-, [M + NO3]- adducts all produced only the respective anions in CID experiments, and thus, gave no structural information. In contrast, upon CID, both [M + F]- and [M + HCO3]- precursor adducts gave structurally-informative fragment peaks that exhibited similarities to those of [M - H]- ions; the detailed fragmentation mechanisms are discussed. In comparison, fluoride is a better choice to study brevetoxins in negative ES-MS by the anionic adduct approach.

Lisdexanfetamina (LDX) é um pró-fármaco estimulante de longa duração indicado para o tratamento dos sintomas do transtorno do déficit de atenção e hiperatividade e do transtorno da compulsão alimentar periódica. A hidrólise da ligação amida da LDX ocorre in vivo liberando a molécula terapeuticamente ativa d-anfetamina (d-ANF) e o aminoácido l-lisina. Visto que a LDX se biotransforma à d-ANF – um potente estimulante do sistema nervoso central com destaque tanto na clínica quanto na toxicologia – existe potencial para uso inadequado, abuso e desvio para fins não terapêuticos. Nos laboratórios de toxicologia, amostras biológicas com resultados positivos para anfetamina (ANF) são um desafio, uma vez que alguns testes toxicológicos podem detectar ANF devido à utilização de alguns medicamentos, dificultando a sua interpretação. Assim, são necessários métodos bioanalíticos eficientes aliados ao conhecimento farmacocinético, que permite a verificação da possibilidade de detecção, a estimativa da janela de detecção e as concentrações que podem ser alcançadas em diferentes matrizes biológicas. Dessa forma, neste trabalho, foram desenvolvidos métodos bioanalíticos para quantificação simultânea da LDX e de seu produto de biotransformação, a ANF, nas matrizes biológicas fluido oral, plasma e urina utilizando a cromatografia líquida acoplada a detector de massas sequencial (CL-EM/EM). A preparação de amostra é simples, utilizando a precipitação de proteínas para o plasma, com pouca quantidade de solvente orgânico, a diluição para o fluido oral e a filtração para urina, ambas com nenhuma quantidade de solvente orgânico. As curvas de calibração utilizando o padrão interno ANF deuterada apresentaram linearidade entre 1 e 128 ng/mL para o fluido oral e o plasma e entre 4 e 256 ng/mL para a urina. A menor concentração das curvas de calibração é igual ao limite inferior de quantificação. Precisão e exatidão intra e interdia ficaram dentro dos limites de ± 15% para os controles e ± 20% para o limite de quantificação. Os métodos foram seletivos e sem efeito residual, porém apresentaram um leve efeito matriz, frequentemente encontrado em métodos de CL-EM/EM. O método foi aplicado para análise das amostras do estudo farmacocinético da LDX e ANF nas matrizes biológicas fluido oral, plasma e urina após administração oral de LDX. Seis voluntários do sexo masculino coletaram amostras de fluido oral e plasma em tempos pré-determinados durante 72 horas e amostras de urina em intervalos pré-determinados durante 120 horas. Os dados foram avaliados de maneira não-compartimental e compartimental. Considerando a análise não-compartimental, a concentração máxima média da d-ANF foi quase seis vezes inferior no plasma em relação ao fluido oral e ocorreu em 3,8 e 4 horas, respectivamente, após a administração oral. A LDX atingiu a concentração máxima no plasma e no fluido oral em 1,2 e 1,8 horas após a administração oral, respectivamente, com um valor médio de pico de concentração quase duas vezes mais elevado no plasma em comparação com o fluido oral. A eliminação da d-ANF a partir do plasma e a partir do fluido oral foi semelhante, porém para LDX a eliminação a partir do fluido oral foi mais lenta, mesmo com concentrações mais baixas do que no plasma. A detecção da d-ANF ocorreu até 48-72 horas no plasma e fluido oral e até 120 horas em urina. Já para a LDX, a detecção ocorreu até 3, 5 e 12 horas no plasma, fluido oral e urina, respectivamente. LDX intacta e d-ANF foram detectadas nas três matrizes avaliadas. Na análise compartimental, o melhor ajuste de modelo foi observado para 1 compartimento para ambos os analitos tanto no plasma quanto no fluido oral. Houve uma correlação entre as concentrações do fluido oral e do plasma para d-ANF e entre as proporções de LDX intacta/d-ANF pelo tempo no plasma e no fluido oral. O método analítico desenvolvido pode ser aplicado em diferentes áreas do conhecimento a fim de certificar os resultados de uma análise de triagem positiva para ANF. Porém, para interpretação das situações tanto de triagem quanto de confirmação é necessário aliar o conhecimento farmacocinético gerado no trabalho, que demonstra se há a possibilidade de detecção na matriz analisada e por quanto tempo após a administração da LDX. Isto auxilia na diferenciação do uso de outros medicamentos derivados da ANF e do uso ilegal, para que as devidas providências legais e de manejos clínicos de tratamento e controle de dependência sejam tomadas quando necessário. / Lisdexamfetamine (LDX) is a long-acting prodrug stimulant indicated for the treatment of attention-deficit/hyperactivity disorder and binge-eating disorder symptoms. In vivo hydrolysis of lisdexamfetamine amide bond releases the therapeutically active d-amphetamine (d-AMPH) and the amino acid l-lysine. Since LDX biotransformation gives rise to d-AMPH - a potent stimulant of the central nervous system that stands out in clinical and toxicology - there is potential for misuse, abuse and diversion for non-therapeutic purposes. In laboratories of toxicology, biological samples with positive results for amphetamine (AMPH) are a challenge, since some toxicological tests can detect AMPH due to the use of some medications hindering the interpretation. Therefore, we need efficient bioanalytical methods combined with the pharmacokinetic knowledge, which allows to verify the possibility of detection, to assess the detection window and the concentrations that can be reached in different biological matrices. Hence, bioanalytical methods were developed for simultaneous quantification of LDX and its main biotransformation product AMPH in the biological matrices oral fluid, plasma and urine by liquid chromatography-mass spectrometry (LC-MS/MS). The sample preparation is simple, using protein precipitation for plasma, with a small amount of organic solvent, dilution for oral fluid and filtration to urine, both with no amount of organic solvent. Calibration curves using deuterated AMPH internal standard showed linearity between 1 and 128 ng/mL for oral fluid and plasma, and between 4 and 256 ng/mL for urine. The lowest concentration of the calibration curve is the lower limit of quantification. Intra and interday precision and accuracy were within the limits of ± 15% for controls and ± 20% for the limit of quantification. The methods were selective and no carry-over was observed, however with some matrix effect, often found in LC-MS/MS methods. The method was applied to analyze samples from LDX and AMPH pharmacokinetics study in the biological matrices oral fluid, plasma and urine following oral administration of LDX. Six male volunteers collected oral fluid and plasma samples at predetermined times during 72 hours and urine samples at pre-determined intervals during 120 hours. Data were evaluated through non-compartmental and compartmental analysis. Considering the noncompartmental analysis, the mean maximum concentration of d-AMPH was almost 6-fold lower in plasma than in oral fluid and occurred at 3.8 and 4 hours, respectively, after LDX administration. LDX maximum concentration was reached at 1.2 and 1.8 hours after LDX oral administration for oral fluid and plasma, respectively, with a mean peak concentration almost 2-fold higher in plasma when compared with oral fluid. Elimination of d-AMPH from oral fluid and from plasma were similar, albeit for LDX elimination from oral fluid was slower even with lower concentrations than plasma. Detection occurred until 48 to 72 hours in plasma and oral fluid and until 120 hours in urine for d-AMPH. Whereas for LDX, detection could be done for up to 3, 5 and 12 hours in plasma, oral fluid and urine, respectively. Intact LDX and d-AMPH were detected in the three evaluated matrices. In compartmental analysis, the best model fit was observed for 1-compartment model for both analytes in plasma and in oral fluid. There was a correlation between oral fluid and plasma d-AMPH concentrations and between intact LDX/d-AMPH ratios along time in plasma as well as in oral fluid. The bioanalytical methods developed can be applied in different fields of knowledge in order to ensure the results of a positive screening analysis for AMPH. Nevertheless, for interpretation of situations in both screening and confirmation tests is necessary to combine the pharmacokinetic knowledge produced in this study, which shows if there is the possibility of detection in the analyzed matrix and for how long after the administration of LDX. This results aid in the differentiation from other AMPH derived drugs use and from illegal use, so that appropriate legal action and clinical management strategies for treatments and control of dependence be taken when necessary.

The initial research of this thesis involves the evaluation of different strategies for developing diverse chemistries of highly stable coatings for the automated 96-blade (thin-film) solid phase microextraction (SPME) system. Thin-film geometry increases the volume of extractive phase, and consequently improves the sensitivity of the analysis. Sol-gel technology was used for the preparation of octadecyl (C18)-silica gel thin-film coating. The evaluation of the C18-silica gel SPME extractive phase resulted in stable physical and chemical characteristics and long-term reusability with a high degree of reproducibility. Biocompatible polyacrylonitrile (PAN) polymer was used for the preparation of particle-based extractive phases in order to improve the biocompatible characteristics of SPME coatings for the extraction from biological samples. Three different immobilization strategies were evaluated for developing highly stable coatings for the automated 96-blade SPME system. The spraying was found to be the optimal method in terms of stability and reusability for long-term use. The optimized C18-PAN coating demonstrated improved biocompatibility, stability, and reusability for the extraction of benzodiazepines from human plasma in comparison with those of C18-silica gel coating. To improve the biocompatible properties of the C18-PAN SPME coating for long-term direct analysis from whole blood, different modification strategies were studied and evaluated. The modification of the coating with an extra layer of biocompatible polyacrylonitrile resulted in significant improvement in the blood compatibility in long-term use. ‘Extracted blood spot’ (EBS) sampling was introduced as a novel approach to overcome the limitations of dried blood spot sampling. EBS includes the application of a biocompatible SPME coating for spot sampling of blood or other biofluids. The compatibility of EBS sampling with different analytical methods was demonstrated. The utilization of EBS as a fast sampling and sample preparation method resulted in a significant reduction of matrix effects through efficient sample clean-up. Modified polystyrene-divinylbenzene (PS-DVB)-PAN and phenylboronic acid (PBA)-PAN 96-blade SPME coatings were developed and evaluated for the extraction of analytes in a wide range of polarity. These coatings demonstrated efficient extraction recovery for both polar and non-polar groups of compounds, and presented chemical and mechanical stabilities and reproducible extraction efficiencies for more than 100 usages in biological sample.