From "wet biology" to statistical analysis of structural features with bioinformatics tools

Many new Escherichia coli outer membrane proteins have recently been identified by proteomics techniques. However, poorly expressed proteins and proteins expressed only under certain conditions may escape detection when wild-type cells are grown under standard conditions. Here, we have taken a complementary approach where candidate outer membrane proteins have been identified by bioinformatics prediction, cloned and overexpressed, and finally localized by cell fractionation experiments. Out of eight predicted outer membrane proteins, we have confirmed the outer membrane localization for five—YftM, YaiO, YfaZ, CsgF, and YliI—and also provide preliminary data indicating that a sixth—YfaL—may be an outer membrane autotransporter.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.

Catalytic processes for the transformation of ethanol into acetonitrile

This thesis deals with the transformation of ethanol into acetonitrile. Two approaches are investigated: (a) the ammoxidation of ethanol to acetonitrile and (b) the amination of ethanol to acetonitrile. The reaction of ethanol ammoxidation to acetonitrile has been studied using several catalytic systems, such as vanadyl pyrophosphate, supported vanadium oxide, multimetal molibdates and antimonates. The main conclusions are: (I) The surface acidity must be very low, because acidity catalyzes several undesired reactions, such as the formation of ethylene, and of heavy compounds as well. (II) Supported vanadium oxide is the catalyst showing the best catalytic behaviour, but the role of the support is of crucial importance. (III) Both metal molybdates and antimonates show interesting catalytic behaviour, but are poorly active, and probably require harder conditions than those used with the V oxide-based catalysts. (IV) One key point in the reaction network is the rate of reaction between acetaldehyde (the first intermediate) and ammonia, compared to the parallel rates of acetaldehyde transformation into by-products (CO, CO2, HCN, heavy compounds). Concerning the non-oxidative process, two possible strategies are investigated: (a) the ethanol ammonolysis to ethylamine coupled with ethylamine dehydrogenation, and (b) the direct non-reductive amination of ethanol to acetonitrile. Despite the good results obtained in each single step, the former reaction does not lead to good results in terms of yield to acetonitrile. The direct amination can be catalyzed with good acetonitrile yield over catalyst based on supported metal oxides. Strategies aimed at limiting catalyst deactivation have also been investigated.

A chemical-loop approach for the generation of hydrogen by means of ethanol reforming

The work investigates the feasibility of a new process aimed at the production of hydrogen with inherent separation of carbon oxides. The process consists in a cycle in which, in the first step, a mixed metal oxide is reduced by ethanol (obtained from biomasses). The reduced metal is then contacted with steam in order to split the water and sequestrating the oxygen into the looping material’s structure. The oxides used to run this thermochemical cycle, also called “steam-iron process” are mixed ferrites in the spinel structure MeFe2O4 (Me = Fe, Co, Ni or Cu). To understand the reactions involved in the anaerobic reforming of ethanol, diffuse reflectance spectroscopy (DRIFTS) was used, coupled with the mass analysis of the effluent, to study the surface composition of the ferrites during the adsorption of ethanol and its transformations during the temperature program. This study was paired with the tests on a laboratory scale plant and the characterization through various techniques such as XRD, Mössbauer spectroscopy, elemental analysis... on the materials as synthesized and at different reduction degrees In the first step it was found that besides the generation of the expected CO, CO2 and H2O, the products of ethanol anaerobic oxidation, also a large amount of H2 and coke were produced. The latter is highly undesired, since it affects the second step, during which water is fed over the pre-reduced spinel at high temperature. The behavior of the different spinels was affected by the nature of the divalent metal cation; magnetite was the oxide showing the slower rate of reduction by ethanol, but on the other hand it was that one which could perform the entire cycle of the process more efficiently. Still the problem of coke formation remains the greater challenge to solve.

1st and 2nd Generation Ethanol from Biomass Crops

In chapter 1 and 2 calcium hydroxide as impregnation agent before steam explosion of sugarcane bagasse and switchgrass, respectively, was compared with auto-hydrolysis, assessing the effects on enzymatic hydrolysis and simultaneous saccharification and fermentation (SSF) at high solid concentration of pretreated solid fraction. In addition, anaerobic digestion of pretreated liquid fraction was carried out, in order to appraise the effectiveness of calcium hydroxide before steam explosion in a more comprehensive way. In As water is an expensive input in both cultivation of biomass crops and subsequent pretreatment, Chapter 3 addressed the effects of variable soil moisture on biomass growth and composition of biomass sorghum. Moreover, the effect of water stress was related to the characteristics of stem juice for 1st generation ethanol and structural carbohydrates for 2nd generation ethanol. In the frame of chapter 1, calcium hydroxide was proven to be a suitable catalyst for sugarcane bagasse before steam explosion, in order to enhance fibre deconstruction. In chapter 2, effect of calcium hydroxide on switchgrass showed a great potential when ethanol was focused, whereas acid addition produced higher methane yield. Regarding chapter 3, during crop cycle the amount of cellulose, hemicellulose and AIL changed causing a decrease of 2G ethanol amount. Biomass physical and chemical properties involved a lower glucose yield and concentration at the end of enzymatic hydrolysis and, consequently, a lower 2G ethanol concentration at the end of simultaneous saccharification and fermentation, proving that there is strong relationship between structure, chemical composition, and fermentable sugar yield. The significantly higher concentration of ethanol at the early crop stage could be an important incentive to consider biomass sorghum as second crop in the season, to be introduced into some agricultural systems, potentially benefiting farmers and, above all, avoiding the exacerbation of the debate about fuel vs food crops.