Data-driven adaptive model-based predictive control with application in wastewater systems

This study is concerned with the development of a new data-driven adaptive model-based predictive controller (MBPC) with input constraints. The proposed methods employ subspace identification technique and a singular value decomposition (SVD)-based optimisation strategy to formulate the control algorithm and incorporate the input constraints. Both direct adaptive model-based predictive controller (DAMBPC) and indirect adaptive model-based predictive controller (IAMBPC) are considered. In DAMBPC, the direct identification of controller parameters is desired to reduce the design effort and computational load while the IAMBPC involves a two-stage process of model identification and controller design. The former method only requires a single QR decomposition for obtaining the controller parameters and uses a receding horizon approach to process input/output data for the identification. A suboptimal SVD-based optimisation technique is proposed to incorporate the input constraints. The proposed techniques are implemented and tested on a fourth order non-linear model of a wastewater system. Simulation results are presented to compare the direct and indirect adaptive methods and to demonstrate the performance of the proposed algorithms

Microbial carbon use efficiency: accounting for population, community, and ecosystem-scale controls over the fate of metabolized organic matter

Microbial carbon use efficiency (CUE) is a critical regulator of soil organic matter dynamics and terrestrial carbon fluxes, with strong implications for soil biogeochemistry models. While ecologists increasingly appreciate the importance of CUE, its core concepts remain ambiguous: terminology is inconsistent and confusing, methods capture variable temporal and spatial scales, and the significance of many fundamental drivers remains inconclusive. Here we outline the processes underlying microbial efficiency and propose a conceptual framework that structures the definition of CUE according to increasingly broad temporal and spatial drivers where (1) CUEP reflects population-scale carbon use efficiency of microbes governed by species-specific metabolic and thermodynamic constraints, (2) CUEC defines community-scale microbial efficiency as gross biomass production per unit substrate taken up over short time scales, largely excluding recycling of microbial necromass and exudates, and (3) CUEE reflects the ecosystem-scale efficiency of net microbial biomass production (growth) per unit substrate taken up as iterative breakdown and recycling of microbial products occurs. CUEE integrates all internal and extracellular constraints on CUE and hence embodies an ecosystem perspective that fully captures all drivers of microbial biomass synthesis and decay. These three definitions are distinct yet complementary, capturing the capacity for carbon storage in microbial biomass across different ecological scales. By unifying the existing concepts and terminology underlying microbial efficiency, our framework enhances data interpretation and theoretical advances

Analysis of the central carbon metabolism of the unicellular cyanobacterium Synechocystis sp. PCC 6803 in photomixotrophic and heterotrophic growth mode using 13C metabolic flux analysis

Cyanobacteria are a promising host for sustainable production of a wide variety of biotechnological products. One of these specimens is the unicellular cyanobacterium Synechocystis sp. PCC 6803 that has been extensively studied and became a model organism for photosynthesis. Recently two novel pathways have been identified: Gens for two phosphoketolases and the Entner-Doudoroff pathway (ED). Resolution of the core metabolism of Synechocystis sp. PCC 6803 was encumbered by model topology and the unique demands for cultivation techniques. Identification of optimum tracer and analysis setups for generation of a data basis with sufficient resolution power was achieved by in silico experiments and aided by detailed analysis of cultivation methods. All optimization efforts were finalised in complete and precise resolution of the core metabolism of Synechocystis sp. PCC 6803 under photomixotrophic and heterotrophic growth regime. Photomixotrophic growth is dominated by high Calvin-Benson-Basham cycle activity that is boosted with glucose from medium, whereas heterotrophic metabolism is dominated by the oxidative branch of the pentose phosphate pathway. Tricarboxylic acid cycle was providing biomass building blocks in both growth modes. Novel pathways were found inactive during both tested conditions. This work demonstrated the impact of cultivation parameters and experimental setup on physiology.Cyanobakterien sind eine vielversprechende Gruppe von Organismen, die für eine diverse Palette biotechnologischer Produkte genutzt werden könnten. Kürzlich wurden zwei neue Stoffwechselwege identifiziert: Zwei Phosphoketolasen und der Entner-Doudoroff-Weg. Die Auflösung des Zentralstoffwechsels wurde maßgebliche durch die einzigartigen Anforderungen an Kultivierungsmethoden und Modellierung erschwert. Detaillierte Analyse der Kultivierungssystemen und in silico basiertes experimentelles Design hat schlussendlich ermöglicht qualitativ hochwertige Markierungsdaten für metabolischen Steady-State zu generieren. Alle Optimierungs-Anstrengungen erlaubten die detaillierte Auflösung des Zentralstoffwechsel von Synechocystis sp. PCC 6803 unter photomixotrophen und heterotrophen Wachstumsbedingungen. Dabei war photomixotrophischer Metabolismus vom Calvin-Benson- Basham-Zyklus dominiert, in den Glucose aus dem Medium als zusätzliches Substrat eingeflossen ist. Unter heterotrophen Bedingungen war vor allem der oxidative Teil des Pentosephosphatweg aktiv. Unter beiden Bedingungen stellte der Tricarbonsäurezyklus Biomasse-Bausteine bereit. Neue Stoffwechselwege waren inaktiv, unabhängig vom Wachstumsregime. Diese Arbeit demonstriert den Einfluss von Kultivierungsparametern auf die Physiologie von Mikroorganismen.Deutsche Forschungsgemeinschaft: INST 256/418-1, WI 1796/3-1, GU 1522/2-1; Horizon 2020 Research Infrastructure: 730976 (HIGHFLUX); Agence Nationale de la Recherche: MetaboHUB-ANR-11-INBS-001

Identifying and Overcoming the Factors Limiting Growth and Substrate Utilization in \u3ci\u3eCaldicellulosiruptor bescii\u3c/i\u3e

Caldicellulosiruptor bescii is an anaerobic extreme thermophile being studied for production of lignocellulosic biofuels due to its potential for plant biomass deconstruction. It can grow on a wide range of substrates and co-metabolize C5 and C6 sugars. However, incomplete biomass utilization and low cell growth, among other bottlenecks, majorly limit its bioconversion potential. The work in this dissertation aimed at identifying and overcoming the factors that hinder growth and substrate utilization in C. bescii and focused on low pH and high osmolarity as the investigated conditions that may serve as inhibitors. An RNA-seq data analysis pipeline was developed using a Bacillus thuringiensis data-set that determined essential parameters such as required number of reads and replicates for achieving results with high statistical confidence. This was further used for examining the physiological and systems level responses of C. bescii to acidic pH using integrated omics. In this study, lowering pH from 7.2 to 6.0 in mid-log and post stationary growth phases demonstrated lowered membrane potential/proton motive force (PMF) as a cause of these limitations. Dramatic increase in growth, improved substrate utilization and higher product generation was observed upon alleviating the PMF limitations post-acid addition. Patterns of elevated membrane potential and higher ATP pools further supported the hypothesis. In a follow-up study using liquid and crystalline cellulose it was demonstrated that C. bescii also benefits from the lowered pH on solid substrates indicating PMF limitation exists irrespective of the substrate and alleviation of the limitation under lower pH improves growth. Moreover, this study revealed osmolarity as the next immediate factor limiting the bioconversion potential of C. bescii once PMF limitation is alleviated. The ability of C. bescii to maintain growth at pH 5.5 (0.1 hr-1 dilution rate) in chemostat on Avicel was also displayed here which has not been previously reported, extending its growth pH range (5.5-7.3). Finally, an attempt to expand the genetic tools available for C. bescii was made, exploring RNA interference (RNAi) technology as a basis for developing a genome-wide screening tool in the future, which would aid to identify genetic elements that could confer robustness under various stress conditions

Nonlinear Sliding Mode Observer Applied to Microalgae Growth

Modeling biological processes, such as algae growth, is an area of ongoing research. The ability to understand the multitude of parameters that influence this system provides a platform for better understanding the dynamics of microalgae growth. Empirical modeling efforts look to understand sources of driving nutrients that influence harmful algal blooms (HABs). These harmful algal blooms are dense aggregates that have an increasingly negative impact on local economics, marine and freshwater systems, and public health. They result from a high influx of nitrogen and nutrients that drive the algae biomass to exponentially grow. This growth blocks out the sun, potentially releases dangerous toxins, and suffocates marine life, damaging ecosystems, especially in Florida. Modeling microalgae behavior and growth is complex due to its nonlinear behavior and coupled variables. Recently, cultivating oleaginous microalgae for biofuel production has been another region of ongoing research, especially application of observer theory to estimate internal parameters that are not easily measured in algal systems. Linear observer theory has generally been applied to algae growth systems to estimate internal parameters that are beyond hardware sensor capabilities, but they are still severely limited. Nonlinear observer theory application to biological systems is still relatively new. This thesis explores the application of a nonlinear observer based off sliding mode to an algae system. Sliding mode is derived from modern control theory and is based off variable structure control. An algae system is modeled using the widely accepted Droop model for algae growth and a linear and nonlinear sliding mode observer is developed for the system to estimate internal nitrogen within the algae biomass

Functional and mathematical analysis of the glyoxylate shunt in Streptomyces coelicolor

Streptomyces coelicolor is the model organism for the genus Streptomyces, which produces many bioactive secondary metabolites with clinical applications. Based on work done in Escherichia coli, the glyoxylate shunt was thought to be the main anapleurotic pathway in S. coelicolor during growth on fatty acids and therefore an important pathway in providing precursors for secondary metabolism. The S. coelicolor genome contains genes for a second anapleurotic pathway, the ethylmalonyl-CoA pathway. The relative importance of both to anapleurosis in streptomycete metabolism was unclear. The function of the glyoxylate shunt was investigated in this thesis using sequence analysis, genetic manipulation, transcriptomics and mathematical modelling. Analysis of orthologues of aceA, ccr and genes encoding tricarboxylic acid (TCA) cycle genes revealed that all are subject to a similar level of purifying selection pressure. The operons of the glyoxylate shunt and the ethylmalonyl-CoA pathway share a 15 bp palindromic motif in their upstream sequences, which was also found upstream of other genes. This suggests an overlap in regulation and thus an overlap in function. The sequence analysis is contradicted by results of experiments with an aceA⁻ aceB1⁻ mutant, which did not display a phenotype during growth on Tween 40, a model carbon source for fatty acids. Results obtained by total RNA sequencing indicate that the ethylmalonyl-CoA pathway is the main anapleurotic pathway during growth of S. coelicolor on fatty acids whereas expression of the glyoxylate shunt is minimal. This apparent contradiction is resolved by hypothesising that the ethylmalonyl-CoA pathway is the main anapleurotic pathway, but that the glyoxylate shunt provides a backup when acyl-CoA thioesters are withdrawn from the ethylmalonyl-CoA pathway for secondary metabolite biosynthesis. Enzymes of the isocitrate branchpoint were isolated following heterologous expression and analysed. The resulting kinetic parameters, as well as their specific activities measured during growth on Tween 40 and additional data from literature, were used to set up a mathematical model of the TCA cycle and the glyoxylate shunt. Simulations of this model predicted that, as growth proceeds from early to mid and late exponential phase, the relative concentrations of TCA cycle intermediates changed from promoting gluconeogenesis to accomodating secondary metabolism. Further model refinement is needed using data on the flux through the ethylmalonyl- CoA pathway as these were unavailable at the time of writing.Streptomyces coelicolor is the model organism for the genus Streptomyces, which produces many bioactive secondary metabolites with clinical applications. Based on work done in Escherichia coli, the glyoxylate shunt was thought to be the main anapleurotic pathway in S. coelicolor during growth on fatty acids and therefore an important pathway in providing precursors for secondary metabolism. The S. coelicolor genome contains genes for a second anapleurotic pathway, the ethylmalonyl-CoA pathway. The relative importance of both to anapleurosis in streptomycete metabolism was unclear. The function of the glyoxylate shunt was investigated in this thesis using sequence analysis, genetic manipulation, transcriptomics and mathematical modelling. Analysis of orthologues of aceA, ccr and genes encoding tricarboxylic acid (TCA) cycle genes revealed that all are subject to a similar level of purifying selection pressure. The operons of the glyoxylate shunt and the ethylmalonyl-CoA pathway share a 15 bp palindromic motif in their upstream sequences, which was also found upstream of other genes. This suggests an overlap in regulation and thus an overlap in function. The sequence analysis is contradicted by results of experiments with an aceA⁻ aceB1⁻ mutant, which did not display a phenotype during growth on Tween 40, a model carbon source for fatty acids. Results obtained by total RNA sequencing indicate that the ethylmalonyl-CoA pathway is the main anapleurotic pathway during growth of S. coelicolor on fatty acids whereas expression of the glyoxylate shunt is minimal. This apparent contradiction is resolved by hypothesising that the ethylmalonyl-CoA pathway is the main anapleurotic pathway, but that the glyoxylate shunt provides a backup when acyl-CoA thioesters are withdrawn from the ethylmalonyl-CoA pathway for secondary metabolite biosynthesis. Enzymes of the isocitrate branchpoint were isolated following heterologous expression and analysed. The resulting kinetic parameters, as well as their specific activities measured during growth on Tween 40 and additional data from literature, were used to set up a mathematical model of the TCA cycle and the glyoxylate shunt. Simulations of this model predicted that, as growth proceeds from early to mid and late exponential phase, the relative concentrations of TCA cycle intermediates changed from promoting gluconeogenesis to accomodating secondary metabolism. Further model refinement is needed using data on the flux through the ethylmalonyl- CoA pathway as these were unavailable at the time of writing

Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies

On 31 March 1983, the University of Delaware's Center for Remote Sensing initiated a study to evaluate the spatial, radiometric and spectral performance of the LANDSAT Thematic Mapper for coastal and estuarine studies. The investigation was supported by Contract NAS5-27580 from the NASA Goddard Space Flight Center. The research was divided into three major subprojects: (1) a comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in Chesapeake Bay; (2) remote sensing of submerged aquatic vegetation - a radiative transfer approach; and (3) remote sensing of coastal wetland biomass using Thematic Mapper wavebands

Estimation of neutral lipid and carbohydrate quotas in microalgae using adaptive interval observers

International audienceUnder stress conditions, microalgae are known to accumulate large amounts of neutral lipids and carbohydrates, which can be used for biofuel production. However, on-line measurement of microalgal biochemical composition is a difficult task which makes the microalgal process rather difficult to manage. In this paper, we propose a so called adaptive interval observer for the on-line estimation of neutral lipid and carbohydrate quotas in microalgae. The observer is based on a change of coordinates that involves a time-varying gain. We introduce dynamics for the gain, whose trajectory converges toward a predefined optimal value (which maximizes the convergence rate of the observer). The observer performance is illustrated with experimental data of Isochrysis sp. cultures under nitrogen limitations and day-night cycle. The proposed observer design appears to be a suitable robust estimation technique