Heksaari- ja heksuronihapporeittien karakterisointi ja muokkaus mikrosienissä

Citrus juice production and sugar beet processing produce pectin-rich residues which are mainly used as animal feed. Food industry also uses pectin produced from citrus peel as gelling agent. The main constituent of pectin is D-galacturonic acid. The filamentous fungus Aspergillus niger is naturally capable of hydrolyzing pectin and it can catabolize galacturonic acid through pyruvate and glycerol. Hence, pectin-rich residues could provide a cost effective alternative for producing value-added products, for example, galactaric acid which has many potential applications in polymer synthesis and as a platform chemical. Galactaric acid could be produced by engineered A. niger. However, the acid is catabolized by the mould resulting in the lowered yield. This catabolic pathway of galactaric acid is still not known. The objectives of the Master’s thesis were to unravel the pathway for galactaric acid catabolism, characterize the proteins and construct a galactaric acid producing A. niger strain. In this study, eight potential genes involved in the catabolic pathways were investigated. The genes were deleted from the wild-type strain ATCC 1015 utilizing CRISPR/Cas9 technology, and galactaric acid utilization of the resulting mutant strains was investigated. To the best of my knowledge, this is the first report of using in vitro gRNA successfully in A. niger for targeted gene deletion by the CRISPR/Cas9 genome editing tool. Three of the investigated genes, 39114, 1090836 and 1121140, were concluded to be involved in the pathway. Blocking galacturonic and galactaric acid pathways by deleting genes gaaA and 39114, respectively, and expressing a heterologous gene udh, A. niger ΔgaaA udh Δ39114 was able to produce 4.3 ± 0.2 g/l galactaric acid from galacturonic acid in submerged fermentation. In solid-state and submerged fermentation, the strain produced 15.4 ± 0.6 and 82.3 ± 3.9 mg galactaric acid/g citrus processing waste on dry mass basis, respectively.Sitrusmehun tuotannossa ja sokerijuurikkaan käsittelyssä muodostuu runsaasti pektiiniä sisältävää jätettä, jota pääsääntöisesti käytetään rehuna. Elintarviketeollisuus käyttää myös sitrushedelmien kuorista valmistettua pektiiniä hyytelöimisaineena. Pektiinin pääkomponentti on D-galakturonihappo. Filamenttihome Aspergillus niger kykenee luonnostaan hydrolysoimaan pekniitiä ja katabolisoimaan galakturonihapon pyruvaatiksi ja glyseroliksi. Näin ollen runsaasti pektiiniä sisältävät jätteet voisivat tarjota taloudellisesti kannattavan vaihtoehdon arvokkaiden tuotteiden, esimerkiksi galaktaarihapon, valmistukselle. Galaktaarihapolla on monia potentiaalisia sovelluksia polymeerisynteesissä. Geenimuokatulla A. niger –homeella voidaan tuottaa galaktaarihappoa, mutta home myös kykenee katabolisoimaan galaktaarihappoa, mikä alentaa saantoa. Galaktaarihapon kataboliareitti A. niger –homeessa ei kuitenkaan ole tunnettu. Tämän diplomityön tarkoituksena oli selvittää galaktaarihapon kataboliareitti, karakterisoida reittiin kuuluvat entsyymit ja konstruoida galaktaarihappoa tuottava A. niger –kanta. Tässä työssä tutkittiin kahdeksan geeniä, jotka ovat mahdollisesti osana galaktaarihapon kataboliareittiä. Nämä geenit deletoitiin villityyppikannasta ATCC 1015 käyttämällä CRISPR/Cas9-teknologiaa. Parhaimman tiedon mukaan tämä on ensimmäinen raportti, jossa on käytetty in vitro gRNA:ta onnistuneesti geenien deletoimiseen CRISPR/Cas9 genomin muokkaustekniikalla. Kolme tutkituista geeneistä, 39114, 1090836 ja 1121140, todettiin olevan osana kataboliareittiä. Deletoimalla geenit gaaA ja 39114, jotka ovat galakturoni- ja galaktaarihapon kataboliareiteissä, ja ekpressoimalla heterologinen uhd geeni A. niger –homeessa, saatiin ΔgaaA udh Δ39114-kanta, joka tuotti nestekasvatuksessa 4.3 ± 0.2 g/l galaktaarihappoa galakturonihaposta. Kiintoaine- ja nestekasvatuksessa käytettäessä sitrushedelmien kuorijätettä substraattina kanta tuotti 15.4 ± 0.6 ja 82.3 ± 3.9 mg galaktaarihappoa/g sitrushedelmien kuorijäte kuivapainona

Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics.

BACKGROUND: The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executable model of the EGFR pathway using the stochastic pi-calculus as a modeling language. RESULTS: Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness. Downstream parts, like the parts controlling Ras and ERK, have fewer redundancies, and more than 50% inhibition of specific reactions in those parts greatly attenuates signal response. In addition, we suggest an abstract model that captures the main control mechanisms in the pathway. Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated. In terms of specific control mechanisms, we have identified positive feedback loops whose role is to prolong the active state of key components (e.g., MEK-PP, Ras-GTP), and negative feedback loops that help promote signal adaptation and stabilization. CONCLUSIONS: The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

BTR: training asynchronous Boolean models using single-cell expression data

Abstract Background Rapid technological innovation for the generation of single-cell genomics data presents new challenges and opportunities for bioinformatics analysis. One such area lies in the development of new ways to train gene regulatory networks. The use of single-cell expression profiling technique allows the profiling of the expression states of hundreds of cells, but these expression states are typically noisier due to the presence of technical artefacts such as drop-outs. While many algorithms exist to infer a gene regulatory network, very few of them are able to harness the extra expression states present in single-cell expression data without getting adversely affected by the substantial technical noise present. Results Here we introduce BTR, an algorithm for training asynchronous Boolean models with single-cell expression data using a novel Boolean state space scoring function. BTR is capable of refining existing Boolean models and reconstructing new Boolean models by improving the match between model prediction and expression data. We demonstrate that the Boolean scoring function performed favourably against the BIC scoring function for Bayesian networks. In addition, we show that BTR outperforms many other network inference algorithms in both bulk and single-cell synthetic expression data. Lastly, we introduce two case studies, in which we use BTR to improve published Boolean models in order to generate potentially new biological insights. Conclusions BTR provides a novel way to refine or reconstruct Boolean models using single-cell expression data. Boolean model is particularly useful for network reconstruction using single-cell data because it is more robust to the effect of drop-outs. In addition, BTR does not assume any relationship in the expression states among cells, it is useful for reconstructing a gene regulatory network with as few assumptions as possible. Given the simplicity of Boolean models and the rapid adoption of single-cell genomics by biologists, BTR has the potential to make an impact across many fields of biomedical research

Wetting Behavior of Inkjet-Printed Electronic Inks on Patterned Substrates

In inkjet printing technology, one important factor influencing the printing quality and reliability of printed films is the interaction of the jetted ink with the substrate surface. This short-range interaction determines the wettability and the adhesion of the ink to the solid surface and is hence responsible for the final shape of the deposited ink. Here, we investigate wetting morphologies of inkjet-printed inks on patterned substrates by carefully designed experimental test structures and simulations. The contact angles, the surface properties, and drop shapes, as well as their influence on the device variability, are experimentally and theoretically analyzed. For the simulations, we employ the phase-field method, which is based on the free energy minimization of the two-phase system with the given wetting boundary conditions. Through a systematic investigation of printed drops on patterned substrates consisting of hydrophilic and hydrophobic areas, we report that the printed morphology is related not only to the designed layout and the drop volume but also to the printing strategy and the wettability. Furthermore, we show how one can modify the intrinsic wettability of the patterned substrates to enhance the printing quality and reliability. Based on the present findings, we cast light on the improvement of the fabrication quality of thin film transistors

SelVReflect: A Guided VR Experience Fostering Reflection on Personal Challenges

Reflecting on personal challenges can be difficult. Without encouragement, the reflection process often remains superficial, thus inhibiting deeper understanding and learning from past experiences. To allow people to immerse themselves in and deeply reflect on past challenges, we developed SelVReflect, a VR experience which offers active voice-based guidance and a space to freely express oneself. SelVReflect was developed in an iterative design process (N=5) and evaluated in a user study with N=20 participants. We found that SelVReflect enabled participants to approach their challenge and its (emotional) components from different perspectives and to discover new relationships between these components. By making use of the spatial possibilities in VR, participants developed a better understanding of the situation and of themselves. We contribute empirical evidence of how a guided VR experience can support reflection. We discuss opportunities and design requirements for guided VR experiences that aim to foster deeper reflection

The Phenotypic Effects of Royal Jelly on Wild-Type \u3cem\u3eD. melanogaster\u3c/em\u3e Are Strain-Specific

The role for royal jelly (RJ) in promoting caste differentiation of honeybee larvae into queens rather than workers is well characterized. A recent study demonstrated that this poorly understood complex nutrition drives strikingly similar phenotypic effects in Drosophila melanogaster, such as increased body size and reduced developmental time, making possible the use of D. melanogaster as a model system for the genetic analysis of the cellular mechanisms underlying RJ and caste differentiation. We demonstrate here that RJ increases the body size of some wild-type strains of D. melanogaster but not others, and report significant delays in developmental time in all flies reared on RJ. These findings suggest that cryptic genetic variation may be a factor in the D. melanogaster response to RJ, and should be considered when attempting to elucidate response mechanisms to environmental changes in non-honeybee species