Since the catabolism of amino acids in cheese results in the formation of most volatile flavor compounds, a proper intracellular pool of amino acids must be established in order to produce a desirable flavor production in cheese. Generation of this pool of amino acids requires complex interactions among casein and its derivatives, proteolytic enzymes, and transport systems in the associated bacteria, including lactococci. In this project, we hypothesized that casein hydrolysis by the extracellular proteinases of Brevibacterium linens BL2 modulates the expression profile of proteolytic related genes in Lactococcus lactis spp. lactis IL1403. In order to monitor the global gene regulation patterns in L. lactis ssp. lactis IL1403, a high-throughput gene expression tool was needed to study the gene expression profiles on a genomic scale. In this project, we developed a novel oligonucleotide-based filter DNA array protocol for this purpose. The success of this oligonucleotide-based DNA array was dependent on technical innovations including polyI tailing, indirect high density biotin labeling, careful probe design, and integrated computational data analysis. The utility and validity of this protocol were demonstrated by profiling the expression of 375 metabolically related genes in L. lactis ssp. lactis IL1403 during heat, acid, and osmotic stresses. Subsequently the DNA macroarray was used to profile the gene expression changes of L. lactis spp. lactis IL1403 growing in a peptide-limited medium, in a casitone-based peptide-rich medium, and in a casein hydrolyte by B. linens BL2 proteolytic enzymes. L. lactis ssp. lactis IL1403 experienced nitrogen starvation even with an abundance of peptide resources because of lack of expression of peptide transporter genes. Conversely, a peptide pool generated by B. linens BL2 proteolytic activities was sufficient to sustain the growth of L. lactis ssp. lactis IL1403. The repression of the peptide transporter and other peptidase genes of L. lactis ssp. lactis IL1403 was relieved in this medium. Interestingly, the Opt system, a di-tripeptide transporter, was used as a primary peptide transporter, instead of the Opp system whose genes were not actively transcripted in IL1403. We also conducted additional experiments to further describe the protease in B. linens BL2 responsible for the peptide pool generation. This enzyme was secreted as a non-active zymogen and matured into the active protease. Both proteolysis and maturation processes were regulated. Collectively, this work demonstrated that a unique protease of B. linens BL2 generated a pool of pep tides transportable by L. lactis IL1403 and induced changes in gene expression in L. lactis IL1403. Consequently, this body of work demonstrated the hypothesis to be true.

The goal of this dissertation was to evaluate genomic regulation during bovine mammary epithelial cell (BMEC) growth and differentiation. To accomplish this goal, a collagen gel cell culture system was developed that was capable of mimicking the prepartum stages of epithelial development and differentiation. In addition, a 4,600-cDNA bovine microarray was developed in order to profile gene expression. Analysis of BMEC in collagen cultures using various lactogenic conditions highlighted the critical importance of both hormonal and structural signals. The objective of the first study utilizing the microarray was to evaluate the contribution of the two prominent lactogenic factors in vitro, 1) prolactin and 2) gel release. Collectively, lactogenic stimulation appears to turn off genes associated with structural progression and morphogenesis, and turn on genes involved in alveolar MEC differentiation such as cell polarization, milk protein synthesis and ER/Golgi transport. The objective of the second study utilizing these resources was to evaluate the direct effects of thermal stress on BMEC growth and development. The structural response to thermal stress was characterized by morphogenic inhibition and dramatic regression of the ductal branches. Microarray analysis revealed an overall up-regulation of genes associated with stress response, DNA repair, protein degradation and cell death. In contrast, genes associated with cellular and MEC-specific biosynthesis, metabolism, and morphogenesis, were generally down-regulated. Subsequent to the analysis of BMEC differentiation was a targeted effort focusing on two small molecules hypothesized to be involved in regulating the BMEC secretory response: serotonin and prostaglandin E2. A pilot study suggested that serotonin is produced by bovine MEC and a model was proposed that describes serotonin's role as a feedback inhibitor during milk synthesis and secretion. A second pilot study demonstrated that PGE2 had a consistently positive influence on lumen diameter of alveolar structures in vitro. Overall, this dissertation provides new resources for studying bovine functional genomics, particularly within the mammary gland, and it provides a strong foundation for understanding genomic regulation of mammary epithelial structure and function. Furthermore, it establishes potential roles for local regulation of milk production by serotonin and PGE2.

This work investigates two distinct roles of lysine deacetylases (KDACs) in the budding yeast Saccharomyces cerevisiae. The first part focused on the classical, well characterized role of KDACs as transcriptional regulators and deciphering their role in G1 transcription. I show that two yeast KDACs, Rpd3 and Hos3 are recruited to G1 promoters through their interactions with the negative regulator Whi5 and that these KDACs are necessary for proper Whi5-mediated repression. The second part examines a newly discovered role for KDACs extending their role beyond the chromatin as modifiers of proteins other than the histones. I present here the first systematic approach that comprehensively examines these non-histone targets of KDACs in vivo. I identified 73 non-histone proteins acetylated in vivo involved in diverse cellular processes. Swi4, a component of the G1 transcription factor SBF, was identified in the Rpd3 screen and I show that the interaction between Swi4 and its heterodimeric partner Swi6 was regulated by acetylation. My findings significantly expand the scope of the yeast acetylome and demonstrate the utility of systematic functional genomic screens to explore enzymatic pathways.

This work investigates two distinct roles of lysine deacetylases (KDACs) in the budding yeast Saccharomyces cerevisiae. The first part focused on the classical, well characterized role of KDACs as transcriptional regulators and deciphering their role in G1 transcription. I show that two yeast KDACs, Rpd3 and Hos3 are recruited to G1 promoters through their interactions with the negative regulator Whi5 and that these KDACs are necessary for proper Whi5-mediated repression. The second part examines a newly discovered role for KDACs extending their role beyond the chromatin as modifiers of proteins other than the histones. I present here the first systematic approach that comprehensively examines these non-histone targets of KDACs in vivo. I identified 73 non-histone proteins acetylated in vivo involved in diverse cellular processes. Swi4, a component of the G1 transcription factor SBF, was identified in the Rpd3 screen and I show that the interaction between Swi4 and its heterodimeric partner Swi6 was regulated by acetylation. My findings significantly expand the scope of the yeast acetylome and demonstrate the utility of systematic functional genomic screens to explore enzymatic pathways.

One of the greatest challenges in modern biology is to understand quantitatively the mechanisms underlying messenger Ribonucleic acid (mRNA) transcription within the cell. To this end, integrated functional genomics attempts to use the vast wealth of data produced by modern large scale genomic projects to understand how the genome is deployed to create a diversity of tissues and species. The expression levels of tens or hundreds of thousands genes are profiled at multiple time points or different experimental conditions in the genomic projects. The profiling results are deposited in large scale quantitative data files that are not possible to analyse without systematic computational methods. In particular, it is much more difficult to experimentally measure the concentration level of transcription factor proteins and their affinity for the promoter region of genes, while it is relatively easy to measure the result of transcription using experimental techniques such as microarrays. In the absence of such biological experiments, it becomes necessary to use in silico techniques to determine the transcription factor regulatory activities given existing gene expression profile data. It therefore presents significant challenges and opportunities to the computer science community. This PhD Project made use of one such in silico technique to determine the differences (if any) in transcription factor regulatory activities of different experimental conditions and time points.The research aim of the Project was to understand the transcriptional regulatory mechanism that controls the sophisticated process of gene expression in cells. In particular, differences in the downstream signalling from which transcription factors can play a role in predisposition to diseases such as Parasitic disease, Cancer, and Neuroendocrine disease. To address this question I have had access to large integrated genomics datasets generated in studies on parasitic disease, lung cancer, and endocrine (hormone) disease. The current state-of-the-art takes existing knowledge and asks "How do these data relate to what we already know?" By applying machine learning approaches the project explored the role that such data can play in uncovering new biological knowledge.

[EN] Our understanding of the biological mechanisms for most common human diseases is far from complete. Even with well established genetic landscapes, our capacity to make accurate phenotypical predictions or determine personalised disease risk using genetics alone is not possible for most diseases due to our lack of understanding of the mechanisms by which genetic alterations cause disease. Several suggestions have been proposed to explain this manifested lack of direct relation between genotype and phenotype, including interactions with other molecules, pleiotropy and environmental perturbations. Due to their essential role in carrying cellular functions, proteins and its interactions seem crucial to translate genomic data to phenotypic states. In this thesis I present three different and independent approaches to integrate human genomic data with prior knowledge in terms of protein-protein interactions (PPIs). The overall objective is, by making use of the interactome structure, to propose functional hypotheses that help to interpret the genetic variability observed in different human phenotypes. First I developed a methodology to extract the network component associated to any gene list ranked by any experimental parameter, as the one coming from case-control genome-wide associations studies. Second I performed a systematic analysis of human variants in the context of the protein interactome. There I study how the interactome structure can help us to explain the amount of apparently deleterious variation observed in actual populations and, therefore, give insight in its role in shaping the patterns of variability. Results are compared against somatic mutation found in Leukemia patients. Finally, I structurally resolved the protein interactome and used it to study how somatic mutations found in primary tumours distribute across the interacting interfaces and identify those with a potential role in driving oncogenesis. Although each chapter covers a different question, all of them demonstrate the potential of the interactome in helping to interpret genomic variation observed under diverse research scenarios. / [ES] Nuestro conocimiento acerca de los mecanismos biológicos causantes de la mayoría de enfermedades humanas comunes es aun pobre. Incluso con mapas genéticos de alta resolución, nuestra capacidad para hacer predicciones fenotípicas certeras o determinar el riesgo de una persona a padecer una enfermedad utilizando solamente marcadores genéticos es muy baja. Entre las principales causas de esta aparente falta de relación directa entre genotipo y fenotipo están las interacciones moleculares, los fenómenos de pleiotropía y la influencia de los factores externos. Debido al papel esencial que ejercen en llevar a cabo las funciones celulares, las proteínas y sus interacciones han adquirido una atención especial en la traducción de los datos genotípicos a estados fenotípicos. En esta tesis se presentan tres estrategias diferentes para la integración de datos genómicos humanos con la red de interacciones proteicas (interactoma). El objetivo común de todas ellas es, haciendo uso de la estructura del interactoma, proponer hipótesis funcionales que ayuden a interpretar los patrones de variabilidad observados en diferentes estados fenotípicos humanos. Primero, se propone una metodología para extraer el componente del interactoma asociado a los genes relevantes en una lista ranqueada por cualquier parámetro experimental, como el estadístico derivado de los estudios de asociación genómicos. Es segundo lugar se describe un análisis sistemático de las variantes genéticas observadas en humanos sanos en el contexto del interactoma. En él se estudia cómo la estructura del interactoma puede ayudar en explicar la aparentemente elevada cantidad de variantes deletéreas observadas en los últimos estudios poblacionales de secuenciación de genomas. Los resultados son comparados con las mutaciones somáticas observadas en pacientes de Leucemia. Finalmente, se presenta un estudio de las mutaciones somáticas observadas en tumores primarios utilizando una versión del interactoma que incluye la estructura tridimensional de las proteínas. Aunque cada estudio presentado en la tesis pretende resolver preguntas diferentes, todos ellos demuestran el potencial del interactoma de proteínas en ayudar a interpretar la variación genómica humana observada en un contexto tanto evolutivo como de enfermedad. / [CAT] El nostre coneixement sobre els mecanismes biològics causants de la majoria de malalties humanes comuns es encara pobre. Tot i que en l'actualitat tenim mapes genètics d'alta resolució, la nostra capacitat per a fer prediccions fenotípiques certeres utilitzant únicament marcadors genètics es encara molt baixa degut a que no entenem les bases moleculars a traves de les quals les alteracions genètiques condicionen un fenotip de malaltia. Entre les principals causes d'aquesta aparent falta de relació directa entre genotip i fenotip estan la complexitat introduïda per les interacciones moleculars, els fenòmens de peleiotropia i la influencia dels factors externs. Degut al paper clau en dur a terme la majoria de funcions cel·lulars, les proteïnes i les seues interaccions han adquirit una especial atenció en la traducció de les dades genotípiques en estats fenotípics. Aquesta tesi presenta tres estartègies diferents per a la integració de dades genòmiques humanes amb la xarxa d'interaccions proteiques (interactoma). L'objectiu comú es, fent ús de l'estructura del interactoma, proposar hipòtesis funcionals que ajuden a interpretar els patrons de variabilitat genètica observats en diferents estats fenotípics. En primer lloc, es proposa una metodologia per a extraure el component de l'interactoma associat als gens rellevants en una llista ranquejada per qualsevol paràmetre experimental, com l'estadístic derivat d'estudis d'assocaició de genoma. En segon lloc, es descriu un anàlisi sistemàtic de les variants genètiques observades en humans sans en el context del interactoma. Ací s'analitza com l'estructura del interactoma pot ajudar a explicar l'aparent elevada quantitat de variants deletèries observades en els últims estudis poblacionals de sequenciació de genomes. Els resultats son comparats amb les mutacions somàtiques observades en pacients de Leucèmia. Finalment, es presenta un estudi de les mutacions somàtiques observades en tumors primaris de més de 20 tipus utilitzant una versió del interactoma més resolutiva, que inclou l'estructura tridimensional de les proteïnes. Encara que cada estudi presentat en la tesi planteja resoldre qüestions diferents, tots ells demostren el potencial del interactoma de proteïnes en ajudar a interpretar la variació genòmica humana observada en un context tant poblacional com de malaltia. / García Alonso, LM. (2015). Functional profiling of human genomic data using the protein interactome [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/55848 / TESIS

Tomato (Solanum lycopersicum) is a member of the Solanaceae family. In this research project tomato, more specifically the M82 cultivar was chosen as a model plant for Agrobacterium-mediated gene transfer by cotyledon inoculation. Our objective was to transform tomato with a T-DNA construct bearing a transposon from maize that can be used for mutagenesis when it transposes or moves around the genome of the tomato. The vector used is a two-component in-cis Ac-Ds system which needs a single transformation event. It was proved that it worked in Arabidopsis and rice according to Trijatmiko (2005). The construct consists of the BAR gene conferring resistance to herbicide Basta, hygromycin (HYG) gene conferring resistance to the antibiotic hygromycin and the green fluorescent protein (GFP) gene, which are driven by specific plant promoters. The selectable marker genes such as HYG and BAR were used to select the rare transformation events by making the transformed tomato tissue resistant to the toxic chemicals (antibiotic and herbicide) compared to the untransformed tissue in which growth was inhibited. The results described consist of developing a transformation protocol which enabled the production of transgenic tomato lines by the help of the antibiotic augmetin (amoxicillin/clavulanic acid). The transgenic lines were tested through polymerase chain reaction (PCR) and herbicide bioassays. / Master of Science

Zymoseptoria tritici is an ascomycete fungus that causes Septoria tritici leaf blotch disease, which is one of the most devastating diseases of wheat. The lack of molecular tools has withheld functional genomics and consequently has left extensive gaps in the knowledge of the biology of infection by Z. tritici. The current research was conducted to develop molecular tools in order to facilitate forward and reserves genetic screens in Z. tritici. These tools include an optimised genetic manipulation protocol, the Z. tritici strains that provide high frequency targeted genome manipulations, a strategy for gene overexpression and protein tagging, and regulatable promoters for controlled gene expression in Z. tritici. The regulatable promoters served to reveal that the Z. tritici β-(1,3)- glucan synthase (BGS1) gene encoded an essential protein, which regulated cell wall stress tolerance and was therefore, a potential drug target. In addition, these molecular tools revealed a virulence-associated role of the glyoxylate cycle in Z. tritici as inactivation of this pathway impeded pre-penetration morphogenesis, which was restored by exogenous glucose application. This result implied that Z. tritici engaged the glyoxylate cycle to produce energy though gluconeogenesis by channelling the by-products of lipolysis. This significance of the glyoxylate cycle during initiation of the bi-phasic infection cycle suggests that Z. tritici is not a hemibiotroph, but a necrotrophic pathogen with an extended asymptomatic phase of infection. Overall, the molecular tools developed in this study will facilitate large-scale functional genomic analyses to interrogate the biology of infection by Z. tritici. The resulting data will inform the development of durable control strategies to combat Z. tritici outbreaks.

Afin de caractériser les voies de signalisation du système immunitaire inné, nous étudions l'interaction entre le ver C. elegans et le champignon Drechmeria coniospora. Une des réponses du ver à l'infection consiste en une augmentation de la production de peptides antimicrobiens (PAM) dans l'épiderme. Des vers transgéniques exprimant le gène rapporteur de la GFP sous le contrôle du promoteur d'un PAM, fluorescent vert après infection. Si un gène nécessaire à l'expression des PAM est inactivé, alors les vers transgéniques ne fluorescent plus après infection. Nous avons effectué un crible pour identifier les molécules de signalisation nécessaires à l'expression des PAM en utilisant une approche quantitative et semi-automatique par ARN interference (ARNi). Deux banques d'ARNi couvrant 95% du génome, soit 20 000 gènes, ont été criblées et 360 candidats bloquant l'induction de la GFP après infection ont été obtenus, correspondant à 343 gènes. Une caractérisation phénotypique a permis de placer les candidats dans différentes catégories fonctionnelles et permis d'identifier d'une part un récepteur agissant en amont de la voie de signalisation p38 nécessaire à l'activation des gènes PAM, d'autre part une implication des granules de stress lors de l'infection. Ces analyses sont le fondement pour l'établissement d'une description compréhensive du réseau génétique régulant le système immunitaire inné du ver et permettront de révéler les interactions complexes entre l'immunité et les processus physiologiques au niveau moléculaire, cellulaire et au niveau de l'organisme. / To investigate innate immune signaling, we study the interaction of C. elegans with the fungus Drechmeria coniospora. One of the responses of the worm to this infection is the up-regulation of a variety of antimicrobial peptide (AMP) genes in the epidermis. Transgenic worms carrying a GFP reporter gene under the control of an AMP promoter fluoresce green after infection by D. coniospora. If a gene required for AMP gene expression is inactivated, the reporter strain will not turn green upon infection. Using this fluorescent read-out, we have been able to screen for signaling molecules required for AMP gene expression using a quantitative semi-automated RNAi approach. We have screened two RNAi libraries that together cover 95% of the ca. 20,000 genes in the C. elegans genome and we obtained 360 high-confidence candidates that reduced the level of induction of green fluorescence after infection, and correspond to 343 genes. A further phenotypic characterization allowed the candidates to be grouped into distinct functional categories and allowed the identification of both a receptor acting upstream the p38 MAPK pathway necessary for the activation of the AMPs, and the implication of stress granules during infection. Altogether, the screen data and its analysis represent the foundation for the establishment of a comprehensive description of the signaling network regulating the innate immune system of the worm and will shed light on the complex interactions between immunity and other physiological processes at the molecular, cellular and organismal level.

Le paludisme est responsable de la mort de près d'un million de personnes chaque année. Cette maladie est causée par le Plasmodium, parasite protozoaire appartenant à la famille des Apicomplexes. Dans cette thèse, nous avons développé des approches de biologie de systèmes pour l'étude du métabolisme des phospholipides (PL) métabolisme et de sa régulation chez Plasmodium. Ces voies métaboliques sont d'une importance primordiale pour la survie du parasite. À l'étape intra-érythrocytaire du développement, les espèces de Plasmodium exploitent un nombre important de voies de synthèse phospholipidique, qui sont rarement trouvées ensemble dans un seul organisme : (i) la voie dépendante ancestrale CDP-diacylglycerol des procaryotes ( ii) les voies eucaryotes de novo CDP- choline et CDP-éthanolamine (Kennedy) ( iii ) de plus P.falciparum et P. knowlesi emploient des réactions supplémentaires qui relient une à l'autre certaines de ces routes. Une voie de synthèse caractéristique aux plantes, qui utilise la sérine en tant que source supplémentaire de phosphatidyl-choline (PC) et de phosphatidyl-éthanolamine (PE), est nommée la voie méthyltransférase décarboxylase - phosphoéthanolamine sérine (SDPM). Pour comprendre la dynamique d'acquisition et le métabolisme des phospholipides chez Plasmodium, nous avons construit un modèle cinétique quantitatif basé sur des données fluxomiques. La dynamique in vitro d'incorporation de phospholipides révèle plusieurs voies de synthèse. Nous avons construit un réseau métabolique détaillé et nous avons identifié les valeurs de ses paramètres cinétiques (taux maximaux et constantes Michaelis). Afin d'obtenir une recherche globale dans l'espace de paramètres, nous avons conçu une méthode d'optimisation hybride, discrète et continue. Des paramètres discrets ont été utilisés pour échantillonner le cône des flux admissibles, alors que les constantes des Michaelis et les taux maximaux ont été obtenus par la minimisation locale d'une fonction objective. Cette méthode nous a également permis de prédire la répartition des flux au sein du réseau pour différents précurseurs métaboliques. Cette analyse quantitative a également été utilisée pour comprendre les liens éventuels entre les différentes voies. La principale source de PC est la voie Kennedy CDP-choline. Des expériences de knock-out in silico ont montré l'importance comparable des voies phosphoéthanolamine-N-méthyltransférase (PMT) et de la phosphatidyléthanolamine-N-méthyltransférase (PEMT) pour la synthèse de PC. Les valeurs des flux indiquent que plus grande partie de la PE dérivée de la sérine est formée par décarboxylation, alors que la synthèse de PS est majoritairement effectuée par des réactions d'échange de base. L'analyse de sensitivité de la voie CDP- choline montre que l'entrée de choline dans le parasite et la réaction cytidylyltransferase de la phosphocholine ont les plus grands co-efficients de contrôle sur cette voie, mais ne permet pas de distinguer une réaction comme l'unique étape limitante. Ayant comme objectif la compréhension de la régulation de l'expression génique chez Plasmodium falciparum et son influence sur le fonctionnement métabolique, nous avons effectué une étude bioinformatique intégrative des données du transcriptome et du métabolome pour les principales enzymes impliquées dans le métabolisme PL. L'étude de la dépendance temporelle des variables métaboliques et transcriptomiques au cours du cycle intra-érythrocytaire, a mis en évidence deux modes d'activation des voies PL. Les voies Kennedy sont activées pendant la phase schizogonique et au début de la phase anneau, alors que les voies SDPM et d'échange de bases sont activées lors de la fin de la phase anneau cycle et lors de la phase tropozoïte. / Malaria is responsible of the death of up to one million people each year. This disease is caused by Plasmodium, a protozoan parasite. In this thesis we have developed systems biology approaches to the study of phospholipid (PL) metabolism and its regulation in Plasmodium. These pathways are of primary importance for the survival of the parasite. At the blood stage, Plasmodium species display a bewildering number of PL synthetic pathways that are rarely found together in a single organism (i) the ancestral prokaryotic CDPdiacylglycerol dependent pathway (ii) the eukaryotic type de novo CDP-choline and CDPethanolamine (Kennedy) pathways (iii) P. falciparum and P. knowlesi exhibits additional reactions that bridge some of these routes. A plant-like pathway that relies on serine to provide additional PC and PE, is named the serine decarboxylase-phosphoethanolamine methyltransferase (SDPM) pathway. To understand the dynamics of PL acquisition and metabolism in Plasmodium we have used fluxomic data to build a quantitative kinetic model. In vitro incorporation dynamics of phospholipids unravels multiple synthetic pathways. A detailed metabolic network with values of the kinetic parameters (maximum rates and Michaelis constants) has been built. In order to obtain a global search in the parameter space, we have designed a hybrid, discrete and continuous, optimisation method. Discrete parameters were used to sample the cone of admissible fluxes, whereas the continuous Michaelis and maximum rates constants were obtained by local minimization of an objective function.The model was used to predict the distribution of fluxes within the network of various metabolic precursors. The quantitative analysis was used to understand eventual links between different pathways. The major source of phosphatidylcholine (PC) is the CDP-choline Kennedy pathway. In silico knock-out experiments showed comparable importance of phosphoethanolamine-N-methyltransferase (PMT) and phosphatidylethanolamine-N-methyltransferase (PEMT) for PC synthesis. The flux values indicate that, major part of serine derived phosphatidylethanolamine (PE) is formed via serine decarboxylation, whereas the phosphatidylserine (PS) is mainly predominated by base-exchange reactions. Metabolic control analysis of CDP-choline pathway shows that the carrier-mediated choline entry into the parasite and the phosphocholine cytidylyltransferase reaction have the largest control coefficients in this pathway, but does not distinguish a reaction as an unique rate-limiting step.With a vision to understand regulation of gene expression in Plasmodium falciparum and its influence on the metabolite expression, we have performed an integrative bioinformatic studies. The study integrates transcriptome and metabolome data for the main enzymes involved in PL metabolism. The study of the correlated time dependence of metabolic and transcriptomic variables during the intraerythrocytic cycle showed that there are two modes of activation of PL pathways. Kennedy pathways are activated during schizogony and early ring stages, whereas SDPM and base exchange pathways are activated during late ring and tropozoite stages.