Biology is full of complexities, and the more we learn, the more we realize how much remains unknown. A major debate in microbiology is whether DNA alone dictates an organism’s function or if metabolism and energy flows play an equally fundamental role. This question is particularly relevant for microbes in dynamic environments, where survival depends on metabolic adaptability.

This thesis focuses on “Candidatus Accumulibacter”, a key microorganism in wastewater treatment that removes excess phosphorus from water. These bacteria endure feast-famine cycles by storing and utilizing energy reserves as conditions change. While extensively studied, much remains unknown about their metabolic strategies and how environmental factors shape their function. This research combines computational models, laboratory cultivation, and multi-omics analysis to explore how “Ca. Accumulibacter” optimizes its metabolism.

Chapter 1 introduces the central debate: Is DNA the sole blueprint for microbial function, or do metabolism and energy constraints shape microbial behavior? It traces the shift from biochemical models to genome-centric approaches and highlights the potential of a metabolism-first perspective. It also contextualizes “Ca. Accumulibacter” within existing research, outlining its role in biological phosphorus removal and summarizing past findings.

Chapter 2 investigates extracellular polymeric substances (EPS) produced by “Ca. Accumulibacter”, revealing novel glycans and glycoproteins that challenge genome-based predictions. These biomolecules are crucial for biofilm formation and microbial interactions, emphasizing the need for direct biochemical analysis alongside genetic data.

Chapter 3 uses elementary flux mode analysis (EFMA) to map the metabolic potential of “Ca. Accumulibacter”. While genome annotations suggest flexibility, thermodynamic constraints limit feasible metabolic strategies, highlighting the role of energy availability in shaping microbial function.

Chapter 4 introduces the development of the Conditional Flux Balance Analysis (cFBA) Toolbox, an open-source Python framework for modeling metabolism in fluctuating environments. Unlike conventional models that assume steady-state conditions, cFBA enables dynamic predictions of resource allocation over time.

Chapter 5 explores the impact of temperature on “Ca. Accumulibacter” metabolism using cFBA. The findings confirm that biomass synthesis is mainly aerobic but also uncover metabolic shifts at lower temperatures that influence phosphorus removal efficiency and microbial competition.

Chapter 6 examines how “Ca. Accumulibacter” metabolizes multiple substrates simultaneously, revealing unexpected synergies that enhance survival in microbial communities. Combining experimental enrichment cultures with cFBA, this study identifies key metabolic trade-offs and resource optimization strategies.

Finally, Chapter 7 synthesizes the thesis findings, advocating for a shift beyond genome-based interpretations toward a metabolism-centric understanding of microbial function. It discusses broader implications for microbial ecology, wastewater engineering, and metabolic modeling, emphasizing the need for multi-omics approaches and potential applications in synthetic biology.
By integrating experimental and computational approaches, this research deepens our understanding of how “Ca. Accumulibacter” thrives in fluctuating environments. More broadly, it highlights the importance of metabolism and energy flows in shaping microbial function, offering insights that extend beyond wastewater treatment to microbial ecology and engineered bioprocesses.@en

Biological wastewater treatment relies on microorganisms that grow as flocs, biofilms, or granules for efficient separation of biomass from cleaned water. This biofilm structure emerges from the interactions between microbes that produce, and are embedded in, extracellular polymeric substances (EPS). The true composition and structure of the EPS responsible for dense biofilm formation are still obscure. We conducted a bottom-up approach utilizing advanced glycomic techniques to explore the glycan diversity in the EPS from a highly enriched “Candidatus Accumulibacter” granular sludge. Rare novel sugar monomers such as N-Acetylquinovosamine (QuiNAc) and 2-O-Methylrhamnose (2-OMe-Rha) were identified to be present in the EPS of both enrichments. Further, a high diversity in the glycoprotein structures of said EPS was identified by means of lectin based microarrays. We explored the genetic potential of “Ca. Accumulibacter” high quality metagenome assembled genomes (MAGs) to showcase the shortcoming of top-down bioinformatics based approaches at predicting EPS composition and structure, especially when dealing with glycans and glycoconjugates. This work suggests that more bottom-up research is necessary to understand the composition and complex structure of EPS in biofilms since genome based inference cannot directly predict glycan structures and glycoconjugate diversity.

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We present py_cFBA, a Python-based toolbox for conditional flux balance analysis (cFBA). Our toolbox allows for an easy implementation of cFBA models using a well-documented and modular approach and supports the generation of Systems Biology Markup Language models. The toolbox is designed to be user-friendly, versatile, and freely available to non-commercial users, serving as a valuable resource for researchers predicting metabolic behaviour with resource allocation in dynamic-cyclic environments.

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With the rapid growing availability of metagenome assembled genomes (MAGs) and associated metabolic models, the identification of metabolic potential in individual community members has become possible. However, the field still lacks an unbiassed systematic evaluation of the generated metagenomic information to uncover not only metabolic potential, but also feasibilities of these models under specific environmental conditions. In this study, we present a systematic analysis of the metabolic potential in species of "Candidatus Accumulibacter", a group of polyphosphate-accumulating organisms (PAOs). We constructed a metabolic model of the central carbon metabolism and compared the metabolic potential among available MAGs for “Ca. Accumulibacter” species. By combining Elementary Flux Modes Analysis (EFMA) with max-min driving force (MDF) optimization, we obtained all possible flux distributions of the metabolic network and calculated their individual thermodynamic feasibility. Our findings reveal significant variations in the metabolic potential among “Ca. Accumulibacter” MAGs, particularly in the presence of anaplerotic reactions. EFMA revealed 700 unique flux distributions in the complete metabolic model that enable the anaerobic uptake of acetate and its conversion into polyhydroxyalkanoates (PHAs), a well-known phenotype of “Ca. Accumulibacter”. However, thermodynamic constraints narrowed down this solution space to 146 models that were stoichiometrically and thermodynamically feasible (MDF > 0 kJ/mol), of which only 8 were strongly feasible (MDF > 7 kJ/mol). Notably, several novel flux distributions for the metabolic model were identified, suggesting putative, yet unreported, functions within the PAO communities. Overall, this work provides valuable insights into the metabolic variability among "Ca. Accumulibacter" species and redefines the anaerobic metabolic potential in the context of phosphate removal. More generally, the integrated workflow presented in this paper can be applied to any metabolic model obtained from a MAG generated from microbial communities to objectively narrow the expected phenotypes from community members.

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The understanding of microbial communities and the biological regulation of its members is crucial for implementation of novel technologies using microbial ecology. One poorly understood metabolic principle of microbial communities is resource allocation and biosynthesis. Resource allocation theory in polyphosphate accumulating organisms (PAOs) is limited as a result of their slow imposed growth rate (typical sludge retention times of at least 4 days) and limitations to quantify changes in biomass components over a 6 hours cycle (less than 10% of their growth). As a result, there is no direct evidence supporting that biosynthesis is an exclusive aerobic process in PAOs that alternate continuously between anaerobic and aerobic phases. Here, we apply resource allocation metabolic flux analysis to study the optimal phenotype of PAOs over a temperature range of 4 °C to 20 °C. The model applied in this research allowed to identify optimal metabolic strategies in a core metabolic model with limited constraints based on biological principles. The addition of a constraint limiting biomass synthesis to be an exclusive aerobic process changed the metabolic behaviour and improved the predictability of the model over the studied temperature range by closing the gap between prediction and experimental findings. The results validate the assumption of limited anaerobic biosynthesis in PAOs, specifically “Candidatus Accumulibacter” related species. Interestingly, the predicted growth yield was lower, suggesting that there are mechanistic barriers for anaerobic growth not yet understood nor reflected in the current models of PAOs. Moreover, we identified strategies of resource allocation applied by PAOs at different temperatures as a result of the decreased catalytic efficiencies of their biochemical reactions. Understanding resource allocation is paramount in the study of PAOs and their currently unknown complex metabolic regulation, and metabolic modelling based on biological first principles provides a useful tool to develop a mechanistic understanding.

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Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.@en