Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Occurrence, body mass and biomass of Syntermes spp. (Isoptera: Termitidae) in Reserva Ducke, Central Amazonia

The leaf-feeding species Syntermes molestus and S. spinosus are two dominant termite species in Reserva Ducke in Central Amazonia; two other species (S. aculeosus, S. longiceps) exist in the area. All species except S. aculeosus were also found in urban areas. The workers of S. molestus and S. spinosus have average body dry weights of 4.5±0.2 and 13.1±1.4 mg, and the weight of their soldiers is 8.2±0.2 and 51.0±1.7 mg, respectively. Therefore, S. spinosus is among the largest termites of the world. In both species, fresh weight is about 4.7 higher than dry weight (a wider relation than in other termite species). The biomass of the populations of both species amounted to about 1 g m-2 (dry weight; indirect estimate), which rises previous assessments of the total termite biomass by about 36-45%, to a value of 3.0-3.5 g m-2.

Forest biomass and wood consumption In the lower course of the Amazon: a case study of rhe Urubueua Island

Várzea and terra-firme forests in the lower course of the Amazon were compared in terms of forest structure, wood volume increments and forest biomass. The wood volume of várzea forests was smaller than that of terra-firme forests, particularly when severe human intervention such as the cultivation of açaí palm occurred. The difference was even greater in the forest weight comparison because of the lower wood density of várzea trees. These trees are not directly influenced by water stress during the dry season, while late wood with a high density is formed in the terra-firme trees. The annual forest disappearance area due to firewood for tile factories was estimated to be about 276 ha on the island investigated, which had an area of 36,200 ha. Assuming that the forests are rotatively cultivated every 25 to 30 years, the total deforestation area is 6,870-6,948 ha in 25 years and 8,244~8,337 ha in 30 years. This result means that the balance between forest biomass and utilization is not in crisis, however, this balance might be lost as long as substitutive energy such as electricity is not supplied.

Using stated preference methods to assess environmental impacts of forest biomass power plants in Portugal

As a renewable energy source, the use of forest biomass for electricity generation is advantageous in comparison with fossil fuels, however the activity of forest biomass power plants causes adverse impacts, affecting particularly neighbouring communities. The main objective of this study is to estimate the effects of the activity of forest biomass power plants on the welfare of two groups of stakeholders, namely local residents and the general population and we apply two stated preference methods: contingent valuation and discrete choice experiments, respectively. The former method was applied to estimate the minimum compensation residents of neighbouring communities of two forest biomass power plants in Portugal would be willing to accept. The latter method was applied among the general population to estimate their willingness to pay to avoid specific environmental impacts. The results show that the presence of the selected facilities affects individuals’ well-being. On the other hand, in the discrete choice experiments conducted among the general population all impacts considered were significant determinants of respondents’ welfare levels. The results of this study stress the importance of performing an equity analysis of the welfare effects on different groups of stakeholders from the installation of forest biomass power plants, as their effects on welfare are location and impact specific. Policy makers should take into account the views of all stakeholders either directly or indirectly involved when deciding crucial issues regarding the sitting of new forest biomass power plants, in order to achieve an efficient and equitable outcome.

Comparative environmental life-cycle analysis of concretes using biomass and coal fly ashes as partial cement replacement material

Nowadays, the concrete production sector is challenged by attempts to minimize the usage of raw materials and energy consumption, as well as by environmental concerns. Therefore, it is necessary to choose better options, e.g. new technologies or materials with improved life-cycle performance. One solution for using resources in an efficient manner is to close the materials' loop through the recycling of materials that result either from the end-of-life of products or from being the by-product of an industrial process. It is well known that the production of Portland cement, one of the materials most used in the construction sector, has a significant contribution to the environmental impacts, mainly related with carbon dioxide emission. Therefore, the study and utilization of by-products or wastes usable as cement replacement in concrete can supply more sustainable options, provided that these type of concrete produced has same durability and equivalent quality properties as standard concrete. This work studied the environmental benefits of incorporating different percentages of two types of fly ashes that can be used in concrete as cement replacement. These ashes are waste products of power and heat production sectors using coal or biomass as fuels. The results showed that both ashes provide a benefit for the concrete production both in terms of environmental impact minimization and a better environmental performance through an increase in cement replacement. It is possible to verify that the incorporation of fly ashes is a sustainable option for cement substitution and a possible path to improve the environmental performance of the concrete industry.

Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

Biomass accumulation, photochemical efficiency of photosystem II, nutrient contents and nitrate reductase activity in young rosewood plants (Aniba rosaeodora Ducke) submitted to different NO3-:NH4+ ratios

The rosewood (Aniba rosaeodora Ducke) is a native tree species of Amazon rainforest growing naturally in acidic forest soils with reduced redox potential. However, this species can also been found growing in forest gaps containing oxide soils. Variations in the forms of mineral nitrogen (NO3- or NH4+) may be predicted in these different edaphic conditions. Considering that possibility, an experiment was carried out to analyze the effects of different NO3-:NH4+ ratios on the growth performance, mineral composition, chloroplastid pigment contents, photochemical efficiency photosystem II (PSII), and nitrate redutase activity (RN, E.C.1.6.6.1) on A. rosaeodora seedlings. Nine-month-old seedlings were grown in pots with a washed sand capacity of 7.5 kg and submitted to different NO3-:NH4+ ratios (T1 = 0:100%, T2 = 25:75%, T3 = 50:50%, T4 = 75:25%, and T5 = 100:0%). The lowest relative growth rate was observed when the NO3-:NH4+ ratio was equal to 0:100%. In general, high concentrations of NO3- rather than NH4+ favored a greater nutrient accumulation in different parts of the plant. For the chloroplastid pigment, the highest Chl a, Chl b, Chl tot, Chl a/b and Chl tot/Cx+c contents were found in the treatment with 75:25% of NO3-:NH4+, and for Chl b and Cx+c it was observed no difference. In addition, there was a higher photochemical efficiency of PSII (Fv/Fm) when high NO3- concentrations were used. A linear and positive response for the nitrate reductase activity was recorded when the nitrate content increased on the culture substrate. Our results suggest that A. rosaeodora seedlings have a better growth performance when the NO3- concentrations in the culture substrate were higher than the NH4+ concentrations.

Biomass equations for forest regrowth in the eastern Amazon using randomized branch sampling

Forest regrowth occupies an extensive and increasing area in the Amazon basin, but accurate assessment of the impact of regrowth on carbon and nutrient cycles has been hampered by a paucity of available allometric equations. We develop pooled and species-specific equations for total aboveground biomass for a study site in the eastern Amazon that had been abandoned for 15 years. Field work was conducted using randomized branch sampling, a rapid technique that has seen little use in tropical forests. High consistency of sample paths in randomized branch sampling, as measured by the standard error of individual paths (14%), suggests the method may provide substantial efficiencies when compared to traditional procedures. The best fitting equations in this study used the traditional form Y=a×DBHb, where Y is biomass, DBH is diameter at breast height, and a and b are both species-specific parameters. Species-specific equations of the form Y=a(BA×H), where Y is biomass, BA is tree basal area, H is tree height, and a is a species-specific parameter, fit almost as well. Comparison with previously published equations indicated errors from -33% to +29% would have occurred using off-site relationships. We also present equations for stemwood, twigs, and foliage as biomass components.

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

An efficient Azorean thermophilic consortium for lignocellulosic biomass degradation

[Excerpt] Lignocellulosic plant biomass is being envisioned by biorefinery industry as an alternative to current petroleum platform because of the large scale availability, low cost and environmentally benign production. The industrial bioprocessing designed to transform lignocellulosic biomass into biofuels are harsh and the enzymatic reactions may be severely compromised reducing the production of fermentable sugars from lignocellulosic biomass. Thermophilic bacteria consortium are a potential source of cellulases and hemicellulases adapted to extreme environmental conditions, which can be exploited as a new source for the development of more robust enzymatic cocktails. (...)

Candida tropicalis biofilms: biomass, metabolic activity and secreted aspartyl proteinase production

According to epidemiological data, Candida tropicalis has been related to urinary tract infections and haematological malignancy. Several virulence factors seem to be responsible for C. tropicalis infections, for example: their ability to adhere and to form biofilms onto different indwelling medical devices; their capacity to adhere, invade and damage host human tissues due to enzymes production such as proteinases. The main aim of this work was to study the behaviour of C. tropicalis biofilms of different ages (24120 h) formed in artificial urine (AU) and their ability to express aspartyl proteinase (SAPT) genes. The reference strain C. tropicalis ATCC 750 and two C. tropicalis isolates from urine were used. Biofilms were evaluated in terms of culturable cells by colony-forming units enumeration; total biofilm biomass was evaluated using the crystal violet staining method; metabolic activity was evaluated by XTT assay; and SAPT gene expression was determined by real-time PCR. All strains of C. tropicalis were able to form biofilms in AU, although with differences between strains. Candida tropicalis biofilms showed a decrease in terms of the number of culturable cells from 48 to 72 h. Generally, SAPT3 was highly expressed. C. tropicalis strains assayed were able to form biofilms in the presence of AU although in a strain- and time-dependent way, and SAPT genes are expressed during C. tropicalis biofilm formation.

Portugal: Postdoc rights need not hurt productivity

[Excerpt] Portugal’s government is on the verge of a historic process, recognizing at last that postdoctoral researchers should have the same rights as the rest of the country’s workforce (see go.nature.com/famkkn; in Portuguese). In defiance of European Union practice, more than 90% of these early-career scientists are currrently classed as ‘advanced students’ and funded by student scholarships. (...)

Seleção de microalgas com potencial de produção de biocombustíveis

Dissertação de mestrado em Bioengenharia