The Hedgehog (Hh) signaling pathway plays many important roles throughout embryonic development, including the regulation of tissue patterning, cell differentiation, proliferation, and apoptosis. The loss of SHH signaling in human development has been shown to cause holoprosencephaly. Conversely, inappropriately activated Shh signaling in adults has been implicated in many cancers. Furthermore, Shh has been found to be a key regulator of neural stem cells in the mammalian brain. To further study the roles of Hh, I have developed a transgenic zebrafish line as a tool to monitor tissues that respond to Hh signaling throughout the vertebrate life-cycle. A number of genes have been identified that are transcriptionally up-regulated by Hh signaling. Transcription of these genes is initiated through binding of activated Gli transcription factors to an identified Gli binding site (GBS) in the cis-regulatory region. This Gli binding site is largely conserved across vertebrate species. I have generated transgene constructs in which 12 GBSs have been placed upstream of a minimum promoter that drives GFP, RFP, or Kaede fluorescent proteins. These plasmid constructs are activated in embryonic regions known to be Hh responsive, such as the ventral CNS. Treatment with cyclopamine eliminates this expression, confirming that these transgenes accurately report an active Hh response. These transgenic lines will be extremely powerful tools for research into the mechanisms by which Hh signaling regulates adult cell types such as neural stem cells. These lines will also be important tools that will help understand how misregulation of Hh signaling can lead to cancer.

No / Red deer stags produce an androgen-dependent mane of long hairs only in the breeding season; in the non-breeding season, when circulating androgen levels are low, the neck hair resembles the rest of the coat. This study was designed to determine whether androgen receptors are present in deer follicles throughout the year or only in the mane (neck) follicles when circulating testosterone levels are high in the breeding season. Although androgens regulate much human hair growth the mechanisms are not well understood; they are believed to act on the hair follicle epithelium via the mesenchyme-derived dermal papilla. The location of androgen receptors in the follicle was investigated by immunohistochemistry and androgen binding was measured biochemically in cultured dermal papilla cells derived from mane and flank follicles during the breeding season and from neck follicles during the non-breeding season. Immunohistochemistry of frozen skin sections using a polyclonal antibody to the androgen receptor localised nuclear staining only in the dermal papilla cells of mane follicles. Saturation analysis assays of 14 primary dermal papilla cell lines using [(3)H]-mibolerone demonstrated high-affinity, low-capacity androgen receptors were present only in mane (breeding season neck) cells; competition studies with other steroids confirmed the specificity of the receptors. Androgen receptors were not detectable in cells from either the breeding season flank nor the non-breeding season neck follicles. The unusual biological model offered by red deer of androgen-dependent hair being produced on the neck in the breeding, but not the non-breeding season, has allowed confirmation that androgen receptors are required in follicle dermal papilla cells for an androgen response; this concurs with previous human studies. In addition, the absence of receptors in the non-breeding season follicles demonstrates that receptors are not expressed unless the follicle is responding to androgens. Androgen receptors may be induced in mane follicles by seasonal changes in circulating hormone(s).

Résumé : Malgré l’apport de nouvelles armes thérapeutiques, le cancer du sein reste la première cause de décès par cancer chez la femme de moins de 65 ans. Le cancer du sein dit «triple-négatif», un sous-type représentant environ 10 % des cancers du sein, est caractérisé par l’absence de récepteurs hormonaux aux oestrogènes et à la progestérone et aussi par l’absence d’expression du récepteur de croissance HER-2. Ce type de cancer considéré comme étant le plus agressif des cancers du sein, possède un profil clinique défavorable avec un haut risque de rechute métastatique. Les seuls outils thérapeutiques disponibles actuellement contre ce type de cancer sont la chimiothérapie et la radiothérapie, qui s’avèrent être très toxiques pour le patient et ne ciblent pas de manière spécifique la tumeur. Il a été ainsi démontré qu’il existe au sein du kinome (i.e. l’ensemble des protéines kinases du génome humain), 26 protéines kinases surexprimées dans le cancer du sein dit «triple-négatif» et dont le rôle s’avère être critique dans la croissance de ces cellules cancéreuses. Nous avons utilisé différentes méthodes computationnelles développées au sein de notre laboratoire afin de caractériser le site de liaison de l’ensemble de ces 26 protéines kinases. Plus précisément, nous avons calculé les similitudes entre les protéines kinases à plusieurs niveaux: 1. séquence globale, 2. séquence des sites de liaison, 3. structure des sites de liaison et 4. profils de liaison. Nous avons utilisé des outils de visualisation de données afin de mettre en évidence ces similarités. Le profil de liaison de 38 molécules inhibitrices a été déterminé pour un ensemble de 290 protéines kinases humaines, incluant 15 des protéines kinases appartenant à notre sous-ensemble de protéines d'intérêt. Ces profils de liaison sont utilisés pour définir les similarités fonctionnelles entre les protéines kinases d'intérêt, en utilisant le coefficient tau de corrélation des rangs de Kendall ([tau]). Nous avons effectué des simulations d’arrimage à l’aide du logiciel FlexAID, pour chacune des protéines et l’ensemble des 38 molécules inhibitrices afin d’élargir l’analyse précédente aux autres protéines qui n’ont pas été testé par Karaman et al. Grâce aux différentes études structurales et computationnelles effectuées ci-dessus, nous avons été à même de hiérarchiser les protéines kinases en fonction des similarités moléculaires vis-à-vis de leurs profils de liaison, en vue du développement futur d’outils thérapeutiques poly-pharmacologiques. // Abstract : Despite the development of novel therapeutic agents, breast cancer represents a major cause of death among women. Among breast cancer patients, triple negative (TN) breast cancer (TNBC) represents approximately 15% of cases. TNBC is characterized by the absence of the estrogen receptor, the progesterone receptor as well as the HER2 protein kinase. Recently, it has been shown that a subset of 26 protein kinases (TNVT set) is overexpressed in TNBC. Their inhibition in siRNA knockdown experiments leads to varying levels of growth inhibition in TN and sometimes non-TN cancer cell lines. These studies validate TNVT set kinases as potential therapeutic targets. The aim of this project is to characterize the binding site of TNVT set kinases using different computational methods developed in our research group and to determine which protein kinases of this subset could be more likely to bind similar ligands as part of a poly-pharmacological approach. We calculated global sequence similarities, binding-site sequence similarities and 3D atomic binding-site similarities for the TNVT set of kinases. This analysis shows that binding-site sequence similarities somehow reflect global sequence similarities. Binding-site 3D atomic similarities reflect binding-site sequence similarities but are more widespread. This may have potential functional consequences in terms of small-molecule molecular recognition. Such similarities can potentially lead to cross-reactivity effects but they can also be exploited in the development of multi-functional poly-pharmacological drugs. Recently, the dissociation constants (K[indice inférieur d]) of 38 small-molecule inhibitors for 290 protein kinases (including 17 kinases in the TNVT set) were calculated. These experimental bindingprofiles were used to define a measure of functional profile similarity using Kendall rank correlations ([tau]). We will present results using our docking program FlexAID for the 38 small-molecules tested by Karaman et al. against the 26 kinases in the TNVT set. Similar to experimental binding-profiles, the docking scores can be used to define docking bindingprofiles similarities using [tau] rank correlations. Docking binding-profile similarities are then used to cluster the 26 kinases in the TNVT set. Clusters represent subsets of kinases within the TNVT set with functionally similar binding-sites. Finally, we compare functional docking profile similarities to the sequence and 3D atomic similarities discussed above. This analysis will allow us to detect subsets of kinases in the TNVT set for which it may be possible to develop multi-functional inhibitors.

Next-generation sequencing has generated enormous amount of DNA and RNA sequences that potentially carry volumes of genetic information, e.g. protein-coding genes. The thesis is divided into three main parts describing i) GeneMarkS-2, ii) GeneMarkS-T, and iii) MetaGeneTack. In prokaryotic genomes, ab initio gene finders can predict genes with high accuracy. However, the error rate is not negligible and largely species-specific. Most errors in gene prediction are made in genes located in genomic regions with atypical GC composition, e.g. genes in pathogenicity islands. We describe a new algorithm GeneMarkS-2 that uses local GC-specific heuristic models for scoring individual ORFs in the first step of analysis. Predicted atypical genes are retained and serve as ‘external’ evidence in subsequent runs of self-training. GeneMarkS-2 also controls the quality of training process by effectively selecting optimal orders of the Markov chain models as well as duration parameters in the hidden semi-Markov model. GeneMarkS-2 has shown significantly improved accuracy compared with other state-of-the-art gene prediction tools. Massive parallel sequencing of RNA transcripts by the next generation technology (RNA-Seq) provides large amount of RNA reads that can be assembled to full transcriptome. We have developed a new tool, GeneMarkS-T, for ab initio identification of protein-coding regions in RNA transcripts. Unsupervised estimation of parameters of the algorithm makes unnecessary several steps in the conventional gene prediction protocols, most importantly the manually curated preparation of training sets. We have demonstrated that the GeneMarkS-T self-training is robust with respect to the presence of errors in assembled transcripts and the accuracy of GeneMarkS-T in identifying protein-coding regions and, particularly, in predicting gene starts compares favorably to other existing methods. Frameshift prediction (FS) is important for analysis and biological interpretation of metagenomic sequences. Reads in metagenomic samples are prone to sequencing errors. Insertion and deletion errors that change the coding frame impair the accurate identification of protein coding genes. Accurate frameshift prediction requires sufficient amount of data to estimate parameters of species-specific statistical models of protein-coding and non-coding regions. However, this data is not available; all we have is metagenomic sequences of unknown origin. The challenge of ab initio FS detection is, therefore, twofold: (i) to find a way to infer necessary model parameters and (ii) to identify positions of frameshifts (if any). We describe a new tool, MetaGeneTack, which uses a heuristic method to estimate parameters of sequence models used in the FS detection algorithm. It was shown on several test sets that the performance of MetaGeneTack FS detection is comparable or better than the one of earlier developed program FragGeneScan.

Herewithin, two transcription factor (TF) regulatory complexes were investigated. A bHLH–MYB–WDR (BMW) DNA-binding complex from maize was the first complex to be studied. R, a maize bHLH involved in the activation of genes in the anthocyanin pathway, had been characterized to indirectly bind DNA despite the presence of a functional DNA-binding domain. Findings presented here reveal that this is only partially correct. Direct DNA-binding by R was found to be dependent upon two distinct dimerization domains that function as a switch. This switch-like mechanism allows R to be repurposed for the activation of promoters of differing cis-element structure. The second regulatory complex studied was of the Arabidopsis thaliana MIKC-MADS TF family. For many TFs, DNA-binding site recognition is relatively straightforward and very sequence specific, while others exhibit relaxed sequence specificity. MADS-domain TFs are one family of TFs with a wider range of cis-element sequences. Though consensus cis-element sequences have been determined for various MADS-domains, correctly predicting and identifying biologically functional cis-elements has been a challenge. In order to study the influence of nucleobase associations within the cis-element, a DNA-Protein Interaction (DPI)-ELISA method was modified and optimized to screen a panel of specific probes. Screening of the SEP3 homodimer against a panel of sequential, palindromic probes revealed that nucleobases in position -1:+1 of the CArG-box influence binding strength between the MADS-domain and DNA. Additionally, the specificity of AGL15 towards CT-W6-AG forms was discovered to be determined by the functional groups present in the minor groove at position -4:+4 using inosine:cytosine (I:C) base pairs. Finally, the FLC–SVP MADS-domain heterodimer, bound to a native cis-element, was modeled and binding simulated using molecular dynamics. In conjunction with simulations of AGL15 and SEP3 homodimers, a potential binding mechanism was identified for this unique heterodimer. DNA sequence recognition by the MADS-domain was found to occur asymmetrically. In the case of the FLC–SVP heterodimer, the direction of asymmetrical DNA-binding in heterodimers was found to be fixed. Furthermore, the molecular dynamics simulations provided insight towards understanding the results generated from previous DPI-ELISA experiments, which should provide an improved means for predicting biologically significant CArG-boxes around genes.

Cis-regulatory elements are the short regions of DNA to which specific regulatory proteins bind and these interactions subsequently influence the level of transcription for associated genes, by inhibiting or enhancing the transcription process. It is known that much of the genetic change underlying morphological evolution takes place in these regions, rather than in the coding regions of genes. Identifying these sites in a genome is a non-trivial problem. Experimental (wet-lab) methods for finding binding sites exist, but all have some limitations regarding their applicability, accuracy, availability or cost. On the other hand computational methods for predicting the position of binding sites are less expensive and faster. Unfortunately, however, these algorithms perform rather poorly, some missing most binding sites and others over-predicting their presence. The aim of this thesis is to develop and improve computational approaches for the prediction of transcription factor binding sites (TFBSs) by integrating the results of computational algorithms and other sources of complementary biological evidence. Previous related work involved the use of machine learning algorithms for integrating predictions of TFBSs, with particular emphasis on the use of the Support Vector Machine (SVM). This thesis has built upon, extended and considerably improved this earlier work. Data from two organisms was used here. Firstly the relatively simple genome of yeast was used. In yeast, the binding sites are fairly well characterised and they are normally located near the genes that they regulate. The techniques used on the yeast genome were also tested on the more complex genome of the mouse. It is known that the regulatory mechanisms of the eukaryotic species, mouse, is considerably more complex and it was therefore interesting to investigate the techniques described here on such an organism. The initial results were however not particularly encouraging: although a small improvement on the base algorithms could be obtained, the predictions were still of low quality. This was the case for both the yeast and mouse genomes. However, when the negatively labeled vectors in the training set were changed, a substantial improvement in performance was observed. The first change was to choose regions in the mouse genome a long way (distal) from a gene over 4000 base pairs away - as regions not containing binding sites. This produced a major improvement in performance. The second change was simply to use randomised training vectors, which contained no meaningful biological information, as the negative class. This gave some improvement over the yeast genome, but had a very substantial benefit for the mouse data, considerably improving on the aforementioned distal negative training data. In fact the resulting classifier was finding over 80% of the binding sites in the test set and moreover 80% of the predictions were correct. The final experiment used an updated version of the yeast dataset, using more state of the art algorithms and more recent TFBSs annotation data. Here it was found that using randomised or distal negative examples once again gave very good results, comparable to the results obtained on the mouse genome. Another source of negative data was tried for this yeast data, namely using vectors taken from intronic regions. Interestingly this gave the best results.

Abstract : Activation of the antigen presentation mechanisms by cancer cells is one of the main pathways used by the immune system for tumor detection and suppression. Induction of the expression of molecules of the Major Histocompatibility complex class II (MHC-II) by the interferon- (IFN) is important for the efficient presentation of tumor antigens. Nevertheless, it has been observed that expression of these molecules is supressed in tissular contexts where the concentration of estradiol (E2) is high. In this work we attempted to explain if the down-regulation exerted by estradiol on the expression of the MHC-II molecules in breast cancer cells was mediated by a silencing effect of the estrogen receptor- (ER) through a possible estrogen receptor binding site (ERBS) in the locus of promoter IV (pIV) of the master regulator of MHC-II expression, the class II transactivator (CIITA). The breast cancer cell line MDA-MB-231 (ER-/ERβ-) and its stable transfectants MC2 (ER+) and VC5 (empty vector) were used as model cell lines. Expression of the MCH-II molecules is controlled by CIITA, and stimulation with IFN activates the transcription of the pIV of CIITA. Stimulation of these cell lines with IFN induced expression of the MCH-II molecules and addition of E2 repressed such expression only in the MC2 cell line, as observed by flow cytometry analysis. Six other breast cancer cell lines were tested, with only the MCF7 cell line showing a significant inhibition. Then we analyzed if the inhibition of the MHC-II expression was due to a down-regulation of CIITA. Protein analysis performed by western blot and mRNA quantification by RT-qPCR both revealed down-regulation of CIITA in the cells exposed to IFN+E2 compared to those treated only with IFN. However, reporter gene analysis did not demonstrate any influence of our candidate ERBS in the inhibition of the activation of CIITA-pIV. ChIP-seq analysis of the VC5 and MC2 cell lines for ER also failed to demonstrate any binding of the receptor anywhere in the vicinity of the CIITA locus. However gene ontology and disease ontology analysis of the sequencing data showed a higher activation of tumorigenic cellular pathways in the cells treated with IFN + E2 than in the cells treated only with E2. These results suggest that activation of the inflammatory pathways by IFN could exert a detrimental effect on the cancer development. / Résumé : L’activation des mécanismes de présentation antigénique par les cellules cancéreuses est l’une des voies principales employées par le système immunitaire pour la détection et la suppression des tumeurs. L’induction de l’expression de molécules du complexe majeur d’histocompatibilité de classe II (CMH-II) par l’interféron- (IFN) est importante pour la présentation efficace des antigènes tumoraux. Cependant, il a été observé que l’expression de ces molécules est supprimée dans certains tissus dans lesquels la concentration d’estradiol (E2) est élevée. Dans ce travail, nous avons tenté de déterminer si l’inhibition exercée par l’estrogène (E2) sur l'expression des molécules du CMH-II dans des cellules de cancer du sein est médiée par un effet de silençage du récepteur de l’estrogène- (ER) à travers d’un possible site de liaison de récepteur d'estrogène (ERBS) dans le locus du promoteur IV du régulateur clé de l’expression du CMH-II, CIITA. La lignée cancéreuse mammaire cellulaire de cancer de sein MDA-MB-231 (ER-/ERβ-) et ses transfectants stables MC2 (ER+) et VC5 (vecteur vide) ont été utilisés comme des lignées cellulaires modèles. L'expression des molécules du CMH-II est contrôlée par CIITA, et la stimulation avec l’IFN active la transcription du pIV de CIITA. La stimulation de ces lignées cellulaires avec l’IFN induit l'expression des molécules du CMH-II et l'addition d’E2 réprime de cette expression seulement dans la lignée cellulaire MC2, telle qu'elle est observée par analyse de cytométrie de flux. Six autres lignées de cancer de sein ont été testées et seulement la lignée cellulaire MCF7 montrait une inhibition significative. Ensuite, nous avons analysé si l'inhibition de l'expression du CMH-II était due à une régulation de CIITA. L'analyse des protéines effectuée par Western blot et la quantification de l'ARNm par RT-qPCR quantitative ont révélé une inhibition de CIITA dans les cellules exposées à l’IFN + E2 par rapport à celles traitées seulement avec l’IFN. Cependant, des analyses avec un gène rapporteur n'ont pas démontré une influence quelconque de notre site de liaison de récepteur d'estrogène candidat dans l'inhibition de l'activation de CIITA-pIV. Des analyses de ChIP-seq dans les lignées cellulaires MC2 et VC5 pour l’ER n’ont également pas démontré la présence d’une liaison du récepteur dans le voisinage du locus de CIITA. Cependant, des analyses sur l'ontologie des gènes et des maladies sur les données de séquençage ont montré une activation accrue des voies cellulaires cancéreuses dans les cellules traitées avec IFN + E2 comparé avec les cellules traitées uniquement avec E2. Ces résultats suggèrent que l'activation des voies inflammatoires par l’IFN pourrait exercer un effet plus négatif qu’anticipé sur le développement du cancer. [Symboles non conformes]

Die vorliegende Arbeit untersucht mit bioinformatischen Methoden die biologische Bedeutung von Ähnlichkeiten in Kleinstrukturen und peptidischen Sequenzmotiven sowie lokaler und globaler Sequenzähnlichkeit. Der erste Teil der Arbeit behandelt chemische Ähnlichkeiten. Ausgehend von bekannten Inhibitoren der Fehlfaltung des Prionproteins wurde eine Datenbank pharmakologischer Wirkstoffe nach chemisch und strukturell ähnlichen Substanzen durchsucht und 16 Substanzen als neue potentielle Inhibitoren der Fehlfaltung vorgeschlagen. Der nächste Teil untersucht Ähnlichkeiten in Sequenzmotiven, die eine Interaktion mit Pex19, dem Importrezeptor für peroxisomale Membranproteine, vermitteln. In Zusammenarbeit mit einer experimentellen Arbeitsgruppe konnte die Bindestelle charakterisiert und Präferenzen für bestimmte Aminosäuren herausgearbeitet werden. Das Bindemotiv ist eine vermutlich helikale Region mit verzweigtkettigen aliphatischen und basischen Aminosäuren. Aus experimentellen Daten konnte eine positionsabhängige Vorhersagematrix erstellt und validiert werden. Die Beziehung zwischen lokalen Sequenzähnlichkeiten und der Konformation von Prolylbindungen in Proteinen ist Thema des dritten Teils. Die Aminosäurepräferenzen in der Nachbarschaft von cis- und trans-Prolylresten unterscheiden sich, und beide zeigen unterschiedliche Austauschpräferenzen bei Mutationen. Im Gegensatz zu lokaler Sequenzähnlichkeit ist eine globale Sequenzähnlichkeit von nur 20% ein wesentlich besserer Indikator für das Auftreten von cis-Prolylbindungen. Der letzte Teil befaßt sich mit inverser Sequenzähnlichkeit zwischen Proteinen, die wesentlich öfter auftritt als erwartet. Proteine aus einem nichtredundanten Datensatz wurden gleich- und gegenläufig aligniert und strukturelle Ähnlichkeiten zwischen den aufgefundenen Proteinpaaren untersucht. Es konnte gezeigt werden, daß bis auf kurze Sekundärstruktur-Einheiten eine inverse Sequenzähnlichkeit zwischen Proteinen keine strukturelle Ähnlichkeit impliziert. / This work is dealing with the biological impact of similarities between chemical structures, protein sequence motifs and local sequence surrounding as well as global sequence similarity. All four aspects are analyzed by computational methods. The first part is dealing with chemical similarities. Based on a recently published set of prion protein misfolding inhibitors, a data base of approved drugs has been screened for compounds with chemical and structural similarities to these substances. 16 drugs are proposed as new potential inhibitors of prion protein aggregation. The next part addresses similarities of sequence motifs which mediate the interaction with the peroxisomal membrane protein import receptor Pex19. In cooperation with an experimental group, the binding site could be characterized, and amino acid preferences of the different positions of the motif have been determined. The binding motif is a probably helical region of target proteins bearing branched aliphatic and basic residues. A position specific scoring matrix for the prediction of Pex19 binding sites could be generated and validated. The relation between local sequence similarity and prolyl bond conformation is examined in the third part. Amino acid preferences of neighboring residues differ between cis and trans prolyl residues, and both species show different amino acid exchange patterns upon mutation. In contrast to local sequence similarity, overall sequence similarity between proteins as low as 20% is a much better indicator for the occurrence of cis prolyl bonds. The last part focuses on inverse sequence similarity between proteins which occurs far more often than expected by chance. Proteins from a nonredundant data set have been aligned in parallel and antiparallel, and structural similarities between the detected protein pairs have been examined. It could be shown that, with the exception of short secondary structural elements, inverse sequence similarity does not imply structural similarity.

Die Tailspike Proteine (TSP) der Bakteriophagen P22, Sf6 und HK620 dienen der Erkennung von Kohlenhydratstrukturen auf ihren gram-negativen Wirtsbakterien und zeigen, von den ersten 110 Aminosäuren des N-Terminus abgesehen, keine Sequenzübereinstimmung. Mit Röntgenkristallstrukturanalyse konnte gezeigt werden, dass HK620TSP und Sf6TSP ebenfalls zu einer parallelen, rechtsgängigen beta-Helix falten, wie dies schon für P22TSP bekannt war. Die Kohlenhydratbindestelle ist bei Sf6TSP im Vergleich zu P22TSP zwischen die Untereinheiten verschoben. / The bacteriophages P22, Sf6 and HK620 need their tailspike proteins (TSP) for recognition of surface carbohydrates on their gram-negative host bacteria. Sequence identity is completely lacking in their C-terminal 500 to 600 amino acids. The three TSP have the same fold, an oligomeric parallel beta-helix, as shown by crystal structure analyses of HK620TSP and Sf6TSP. Compared with P22TSP, the carbohydrate binding site of Sf6TSP is located at the interface between two monomers and not on a single monomer.

The bacterium Escherichia coli (E. coli) is in many situations an ideal host for production of recombinant proteins, since it generally provides a rapid and economical means to achieve sufficiently high product quantities. However, there are several factors that may limit this host’s ability to produce large amounts of heterologous proteins in a soluble and native form. For many applications a high purity of the recombinant protein is demanded, which implies a purification strategy where the product efficiently can be isolated from the complex milieu of host cell contaminants. In this thesis, different strategies based on both rational and combinatorial genetic engineering principles have been investigated, aiming at improving and facilitating recombinant E. coli protein production and purification. One objective was to improve the PEG/salt aqueous two-phase system (ATPS) purification process of the lipase cutinase, by increasing the selectivity of the protein for the system top-phase. Peptide tags, with varying properties, were designed and genetically fused to the C-terminal end of ZZ-cutinase. Greatly increased partitioning values were observed for purified protein variants fused to tryptophan containing peptide tags, particularly a (WP)4 peptide. The partitioning properties of the ZZ-cutinase-(WP)4 protein were also retained when added to the ATPS directly from an E. coli total cell disintegrate, emphasizing the applicability of this genetic engineering strategy for primary protein purification in ATPSs. Further on, a combinatorial library approach using phage display technology was investigated as a tool for identification of peptide tags capable of improving partitioning properties of ZZ-cutinase in an ATPS. Repeated ATPS-based partitioning-selection cycles of a large phagemid (pVIII) peptide library, resulted in isolation of phage particles preferentially decorated with peptides rich in tyrosine and proline residues. Both a peptide corresponding to a phage library derived peptide sequence as well as peptides designed based on information of amino acid appearance frequencies in later selection rounds, were shown to improve partitioning several-fold when genetically fused to the C-terminal end of ZZ-cutinase. From the two- to four–fold increased production yields observed for these fusion proteins compared to ZZ-cutinase-(WP)4, it was concluded that the selection system used allowed for selection of desired peptide properties related to both partitioning and E. coli protein production parameters. Bacterial protein production is affected by several different mRNA and protein sequence-related features. Attempts to address single parameters in this respect are difficult due to the inter-dependence of many features, for example between codon optimization and mRNA secondary structure effects. Two combinatorial expression vector libraries (ExLib1 and ExLib2) were constructed using a randomization strategy that potentially could lead to variations in many of these sequence-related features and which would allow a pragmatic search of vector variants showing positive net effects on the level of soluble protein production. ExLib1 was constructed to encode all possible synonymous codons of an eight amino acid N-terminal extension of protein Z, fused to the N-terminal of an enhanced green fluorescent reporter protein (EGFP). In ExLib2, the same eight positions were randomized using an (NNG/T) degeneracy code, which could lead to various effects on both the nucleotide and protein level, through the introduction of nucleotide sequences functional as e.g. alternative ribosome binding or translation initiation sites or as translated codons for an Nterminal extension of the target protein by a peptide sequence. Flow cytometric analyses and sorting of library cell cultures resulted in isolation of clones displaying several-fold increases in whole cell fluorescence compared to a reference clone. SDS-PAGE and western blot analyses verified that this was a result of increases (up to 24-fold) in soluble intracellular ZEGFP product protein content. Both position specific codon bias effects and the appearance of new ribosomal binding sites in the library sequences were concluded to have influenced the protein production. To explore the possibility of applying the same combinatorial library strategy for improving soluble intracellular production of heterologous proteins proven difficult to express in E. coli, three proteins with either bacterial (a transcriptional regulator (DntR)) or human (progesterone receptor ligand binding domain (PRLBD) and 11-β Hydroxysteroid dehydrogenase type I (11-β)) origin, were cloned into the ExLib2 library. Flow cytometric sorting of libraries resulted in isolation of DntR library clones showing increased soluble protein production levels and PR-LBD library clones with up to ten-fold increases in whole cell fluorescence, although the product under these conditions co-separated with the insoluble cell material. / QC 20100623