Comparative Effects of Silver Nanoparticles, Sucrose and Sodium Chloride as Osmotic Solutions for Tomato Slices: Antioxidant Activity, Microbial Quality and Modelling with Polynomial Regression Model

This study has reported comparative effects of silver nanoparticles  (AgNPs),  sucrose and sodium chloride as osmotic solutions on antioxidant activity and microbial quality of 10 mm tomato slices. 40 g of tomato slices were dehydrated osmotically (OD) at different temperatures (60, 70 and 80 °C) and time (30, 60, 90, 120 150 and 180 min).Water loss, solid  impregnation, water and solid diffusivities of tomato slices were found to increase with increase in solution temperatures and concentrations with AgNPs having the greatest influence. Antioxidant activities using 2,2-diphenyl-1-picrylhydrazyl increased with increase in solution concentrations but decreased with increase in temperature. Three-wayANOVA(R2=0.998) revealed additive statistically significant effects of osmotic agents,  concentrations and temperatures on antioxidant activity;   F(8,54)=67.854,P=0.00. Polynomial regression analysis with response surface methodology validated experiments such that for each unit increase in concentration and temperature, antioxidant activity increased with good coefficients of determination; sucrose (R2 = 0.87), NaCl, (R2 = 0.89) andAgNPs (R2 = 0.91). Potato dextrose and nutrient agars were used for isolating and identifying microorganisms in OD tomato slices. Tomato slices dehydrated with AgNPs had the highest microbial inhibition of fungi with growth occurring after 7 days, unlike in treatments with sucrose and NaCl where fungal growth appeared after 2 and 5 days, respectively. Aspergillus niger was the most prevalent fungus. It can be concluded that AgNPs may serve as a viable means to dehydrate and preserve tomatoes without loss of antioxidant activity.Keywords: Osmotic dehydration, polynomial regression, response surface, antioxidant activity, three-way ANOVA, silver nanoparticles

Optimization of Recombinant Protein Production by Streptomyces lividans Host

Interleukin-3 is a cytokine, which acts on many target cells within the haemopoietic system, often in synergy with the other cytokines. Streptomyces lividans NCIMB 11416/IL3 p002 secreting human interleukin-3 was used as the host organism in this study of improving target protein production. Streptomyces also produces several proteases including extracellular endoprotease that truncate the N-terminus of the recombinant protein. Federal guidelines and regulations banning animal-derived medium components necessitate the refinement or redevelopment of industrial medium formulations. The development of a defined medium without animal products is most desirable for the production of pure and safe biological products. The objective of the proposed research was the development and application of engineering methodology for the development of a defined medium and the analysis and optimization of a bacterial bioprocess for recombinant protein production. The underlying hypothesis is that a significant improvement of target protein productivity is achievable by using appropriate optimization techniques. During the first phase of this study the task was to develop a systematic procedure for the design and optimization of a chemically defined medium. The study aimed at replacing casein peptone in conventional medium for S. lividans with essential amino acids and determining the optimum proportion of the amino acids. To accomplish this, starvation trials with growth limiting amino acids were performed to establish the baseline for the nutritional requirement. The starvation trials revealed that essential amino acids for growth and product formation are amongst the following eight amino acids: Arg, Asn, Asp, Glu, Leu, Met, Phe, and Thr. Following these preliminary experiments, a statistically based experimental method called mixture experiments along with distance-based multivariate analysis revealed that Asp, Leu, Met, and Phe were the essential amino acids. Then, another mixture experiment design known as simplex lattice design was performed and artificial neural networks were employed to obtain the optimum proportions of the essential amino acids. The optimal medium was found to be composed of 56% Asp, 5% Met, and 39% Phe. It was found in previous studies that in complex media, several types of protease are produced during fermentation. Using the defined medium no proteolytic activity was detected in the fermentation broth. The second optimization method was based on metabolic flux analysis. A comprehensive metabolic network was developed for S. lividans. The metabolic network included carbohyderate and amino acid metabolism in both anabolic and catabolic reactions. According to the experimental results, the time course of the fermentation was divided into two phases, Phase E1 and Phase E2. In the first phase amino acids were used as a nitrogen source and in the second phase ammonia was the nitrogen source for growth and product formation. The metabolic network was used to form a set of linear algebraic equations based on the stoichiometry of the reactions by assuming pseudo-steady state for intracellular metabolites. The metabolic flux model consisted of 62 intracellular metabolites and 91 biochemical reactions. Two different objective functions were considered for optimization: maximizing the specific growth rate and minimizing the redox equivalent. A linear programming approach was used for optimizing the objective functions. The proposed model was able to predict the specific growth rate very accurately with a maximum error of 10%. The oxygen uptake rate and carbon dioxide evolution rate were evaluated with maximum error of 27% and 35%, respectively. Sensitivity analysis revealed that amino acid uptake was the growth limiting flux during the Phase E1 of the fermentation. During Phase E2 the uptake rate of ammonia had a significant effect on the specific growth rate. Sensitivity analysis of the specific growth rate and redox potential with respect to the biomass components showed that any additional supply of biomass building blocks (amino acids, nucleotides) would not significantly affect the specific growth rate and redox potential production as well as the calculated flux pattern

METABOLIC MODELING AND OMICS-INTEGRATIVE ANALYSIS OF SINGLE AND MULTI-ORGANISM SYSTEMS: DISCOVERY AND REDESIGN

Computations and modeling have emerged as indispensable tools that drive the process of understanding, discovery, and redesign of biological systems. With the accelerating pace of genome sequencing and annotation information generation, the development of computational pipelines for the rapid reconstruction of high-quality genome-scale metabolic networks has received significant attention. These models provide a rich tapestry for computational tools to quantitatively assess the metabolic phenotypes for various systems-level studies and to develop engineering interventions at the DNA, RNA, or enzymatic level by careful tuning in the biophysical modeling frameworks. in silico genome-scale metabolic modeling algorithms based on the concept of optimization, along with the incorporation of multi-level omics information, provides a diverse array of toolboxes for new discovery in the metabolism of living organisms (which includes single-cell microbes, plants, animals, and microbial ecosystems) and allows for the reprogramming of metabolism for desired output(s). Throughout my doctoral research, I used genome-scale metabolic models and omics-integrative analysis tools to study how microbes, plants, animal, and microbial ecosystems respond or adapt to diverse environmental cues, and how to leverage the knowledge gleaned from that to answer important biological questions. Each chapter in this dissertation will provide a detailed description of the methodology, results, and conclusions from one specific research project. The research works presented in this dissertation represent important foundational advance in Systems Biology and are crucial for sustainable development in food, pharmaceuticals and bioproduction of the future. Advisor: Rajib Sah

IN SILICO MODELING AND “-OMICS” DATA ANALYSIS FOR RICE SYSTEMS AGROBIOTECHOLOGY

Ph.DDOCTOR OF PHILOSOPH

EXTENDED METHODOLOGY FOR WATER RESOURCES AND WATER-RELATED ENERGY ASSESSMENT ADDRESSING WATER QUALITY

Problémy s vodou, zejména její nedostatek a znečištění, ovlivňují každodenní lidský život a hospodářský vývoj. Globální změny klimatu zvyšují pravděpodobnost a četnost extrémních událostí jako jsou sucho a záplavy. Rostoucí problémy s nepravidelnou dostupností a znečištěním vody vyžadují pokročilejší metodiky hodnocení vodních zdrojů, které povedou k efektivnímu využití a hospodaření s vodou. Tato práce se zabývá rozšířenými metodikami pro hodnocení vody z pohledu její kvality a kvantity a pro hodnocení spotřeby energie a produkce emisí souvisejících s vodou. Tři hlavní metodiky jsou navrženy na základě konceptu vodní stopy (Water Footprint) a pinch analýzy vody (Water Pinch Analysis) pro posouzení kvantitativních a kvalitativních hledisek využití a spotřeby vody. Použití těchto metod je rovněž demonstrováno pomocí numerických a empirických případových studií zaměřených na hodnocení a optimalizaci využití regionálních a průmyslových vodních zdrojůDále jsou diskutovány souvislosti mezi vodou a energií (Water-Energy Nexus) za účelem analýzy problémů týkající se vody z širší perspektivy. Z pohledu vody a vodních zdrojů je provedeno počáteční zhodnocení energetické náročnosti a produkce emisí skleníkových plynů v problematice odsolování mořské vody. Výsledky prezentované v této práci navazují na současné metodiky hodnocení vodních zdrojů. Stopa dostupnosti vody (Water Availability Footprint) byla navržena pro zohlednění dopadu degradace kvality vody ve stávajících postupech pro posuzování nedostatku vody, ve kterých nebyla dříve řešena. Druhým přínosem této práce je návrh konceptu kvantitativní-kvalitativní vodní stopy (Quantitative-Qualitative Water Footprint - QQWFP), ve kterém je definována vodní stopa z pohledu nákladů a následně je stanovena v souvislosti s celkovými náklady na spotřebu vody a odstraňování kontaminantů, které se do vody dostávají v průběhu jejího využití. Vodní stopa založená na nákladech poskytuje výsledky, které jsou intuitivnější jak pro management vodních zdrojů tak i pro veřejnost. Tento přístup umožňuje lépe kontrolovat a řídit průmyslové a regionální využívání a správu vody. Třetím přínosem této práce je rozšíření pinch analýzy nedostatku vody (Water Scarcity Pinch Analysis - WSPA), ve které je aplikována pinch analýzy vody na makroúrovni se zaměřením na regionální hodnocení a optimalizaci zdrojů a využívání vody. Všechny tři navržené metody jsou zaměřeny na stanovení dopadů využití vody z hlediska jejího množství a kvality, analýzy QQWFP a WSPA také pokrývají dopady vícečetných kontaminantů. Kromě hledání řešení se tato práce také pokouší naznačit potenciální směry pro budoucí výzkum v dané oblasti. Mezi významná potenciální témata k diskuzi patří 1) pokročilejší metoda kvantifikace vlivu více kontaminantů a 2) implementace a analýza ekonomické proveditelnosti přístupů WSPA a QQWFP s lokalizovanými daty s cílem nalézt přizpůsobené řešení pro optimální využití regionální a průmyslové vody.Water issues, especially water scarcity and water pollution, have been affecting human lives and economic developments for a long time. Global climate changes exacerbate the probability and frequency of extreme events such as water scarcity and severe floods. The increasing irregular water supply and water pollution issues require more advanced water resources assessment methodologies to guide practical water use and management. This thesis presents the extended methods for water quantity-quality assessment and water-related energy consumption and emissions. Three major methodologies are proposed based on the Water Footprint concept and Water Pinch Analysis frameworks to assess the quantity and quality impact of water use. These methods are also demonstrated with numerical and empirical case studies targeting regional and industrial water resource assessment and optimisation. In addition, the Water-Energy Nexus is discussed to investigate the water issues from a broader perspective. An initial assessment of the water-related energy and GHG emissions of the seawater desalination industries is carried out. The studies in this thesis convey several contributions to the current water resource assessment methodologies. The proposed Water Availability Footprint made an initial effort to cover the water quality degradation impact into the existing water scarcity assessment frameworks, which was not addressed previously. The second contribution of this work is the proposal of the Quantitative-Qualitative Water Footprint (QQWFP), where a cost-based water footprint is defined and determined with the total cost of water consumption and removing contaminants generated during the water use process. The cost-based water footprint provides results which are more intuitive for water managers and the public and can better guide industrial and regional water use and management. The third contribution is the development of the Water Scarcity Pinch Analysis (WSPA), which applied the Water Pinch Analysis at a macro level for regional water use assessment and optimisation. All three proposed methods determine the water use impact in terms of water quantity and quality, and the QQWFP and WSPA also cover the impact of multiple contaminants. In addition to seeking solutions, this thesis also proposes potential directions for future investigations. Significant potential aspects to be further discussed include 1) a more advanced quantification method of the impact of multiple contaminants, and 2) an implementation and economic feasibility analysis of the WSPA and QQWFP with localised data, which seek a customised solution to regional and industrial water use optimisation.

In Silico Modeling and Analysis for Improving Desulfurizing Bacterial Strains

Ph.DDOCTOR OF PHILOSOPH

Towards COP27: The Water-Food-Energy Nexus in a Changing Climate in the Middle East and North Africa

Due to its low adaptability to climate change, the MENA region has become a "hot spot". Water scarcity, extreme heat, drought, and crop failure will worsen as the region becomes more urbanized and industrialized. Both water and food scarcity are made worse by civil wars, terrorism, and political and social unrest. It is unclear how climate change will affect the MENA water–food–energy nexus. All of these concerns need to be empirically evaluated and quantified for a full climate change assessment in the region. Policymakers in the MENA region need to be aware of this interconnection between population growth, rapid urbanization, food safety, climate change, and the global goal of lowering greenhouse gas emissions (as planned in COP27). Researchers from a wide range of disciplines have come together in this SI to investigate the connections between water, food, energy, and climate in the region. By assessing the impacts of climate change on hydrological processes, natural disasters, water supply, energy production and demand, and environmental impacts in the region, this SI will aid in implementation of sustainable solutions to these challenges across multiple spatial scales

Genome-scale metabolic modeling of cyanbacteria: network structure, interactions, reconstruction and dynamics

2016 Fall.Includes bibliographical references.Metabolic network modeling, a field of systems biology and bioengineering, enhances the quantitative predictive understanding of cellular metabolism and thereby assists in the development of model-guided metabolic engineering strategies. Metabolic models use genome-scale network reconstructions, and combine it with mathematical methods for quantitative prediction. Metabolic system reconstructions, contain information on genes, enzymes, reactions, and metabolites, and are converted into two types of networks: (i) gene-enzyme-reaction, and (ii) reaction-metabolite. The former details the links between the genes that are known to code for metabolic enzymes, and the reaction pathways that the enzymes participate in. The latter details the chemical transformation of metabolites, step by step, into biomass and energy. The latter network is transformed into a system of equations and simulated using different methods. Prominent among these are constraint-based methods, especially Flux Balance Analysis, which utilizes linear programming tools to predict intracellular fluxes of single cells. Over the past 25 years, metabolic network modeling has had a range of applications in the fields of model-driven discovery, prediction of cellular phenotypes, analysis of biological network properties, multi-species interactions, engineering of microbes for product synthesis, and studying evolutionary processes. This thesis is concerned with the development and application of metabolic network modeling to cyanobacteria as well as E. coli. Chapter 1 is a brief survey of the past, present, and future of constraint-based modeling using flux balance analysis in systems biology. It includes discussion of (i) formulation, (ii) assumption, (iii) variety, (iv) availability, and (v) future directions in the field of constraint based modeling. Chapter 2, explores the enzyme-reaction networks of metabolic reconstructions belonging to various organisms; and finds that the distribution of the number of reactions an enzyme participates in, i.e. the enzyme-reaction distribution, is surprisingly similar. The role of this distribution in the robustness of the organism is also explored. Chapter 3, applies flux balance analysis on models of E. coli, Synechocystis sp. PCC6803, and C. reinhardtii to understand epistatic interactions between metabolic genes and pathways. We show that epistatic interactions are dependent on the environmental conditions, i.e. carbon source, carbon/oxygen ratio in E. coli, and light intensity in Synechocystis sp. PCC6803 and C. reinhardtii. Cyanobacteria are photosynthetic organisms and have great potential for metabolic engineering to produce commercially important chemicals such as biofuels, pharmaceuticals, and nutraceuticals. Chapter 4 presents our new genome scale reconstruction of the model cyanobacterium, Synechocystis sp. PCC6803, called iCJ816. This reconstruction was analyzed and compared to experimental studies, and used for predicting the capacity of the organism for (i) carbon dioxide remediation, and (ii) production of intracellular chemical species. Chapter 5 uses our new model iCJ816 for dynamic analysis under diurnal growth simulations. We discuss predictions of different optimization schemes, and present a scheme that qualitatively matches observations