The COVID-19 pandemic stressed the need for accelerating the development of novel vaccines. Over the past decades, the bottleneck in the biopharmaceutical process development shifted from optimizing fermentation processes to developing suitable purification strategies. Thereby, improving process understanding can significantly accelerate the development of purification processes. Unlike other biopharmaceutical products, vaccines are often more complex products containing molecules from different origins. The manufacturing process is therefore also more demanding. Consequently, no platform process is available for protein subunit vaccine purification. In the case of expressing a novel antigen in a host cell system, knowledge of the possible impurities – in this case host cell proteins (HCPs) – allows for rational and systematic process development. Therefore, this thesis focuses on developing characterization strategies of recurrent HCP impurities (from E. coli host cells) and on the integration of this information into modeling tools that advance removal strategies of these proteins, with a focus on protein-based antigen vaccines.

Firstly, the complete host cell proteome from antigen expressing E. coli host cells (BLR(DE3) and HMS174(DE3)) were characterized in chapter 2. Around 2000 HCPs were identified from the E. coli harvest sample using mass spectrometry based proteomics. Furthermore, an extensive HCP database including their expression levels, and physicochemical properties was constructed. Additionally, the profiles of an antigen expressing and null plasmid strain were compared. From a downstream processing perspective, the differences may be minor and the findings from the BLR(DE3) null strain can be applied to determine a purification strategy for the BLR(DE3) antigen-producing strain and HMS174(DE3) strain. The dataset of identified proteins was connected to databases describing the physicochemical properties of HCPs. Finally, protein property maps that help to identify a suitable downstream processing (DSP) strategy in comparison with the physicochemical properties of the target antigen, were generated.

Preparative chromatography based on differences in physicochemical properties is one of the main techniques for purification of vaccines. As follow-up to chapter 2, an experimental retention map of the host cell proteome during a salt gradient on hydrophobic interaction chromatography (HIC) and ion exchange chromatography (IEX) was constructed and reported and described in chapter 3. Furthermore, this study identified patterns in the retention behavior of HCPs based on their protein-protein interactions, molecular function, and cell location. To be able to predict the retention behavior of yet uncharacterized proteins, a quantitative structure-property relationship (QSPR) model was constructed using IEX retention data. Subsets of proteins, identified according to retention patterns, were used to build additional QSPR models, with monomer subsets yielding the most accurate predictions.

To achieve a higher level of process understanding, mechanistic models (MM) of chromatography columns are used in process development. These models primarily describe behavior of the target protein and selected process- or product-related impurities. However, it is beneficial to also include recurring HCP impurities in MMs. Hereby, critical HCPs causing issues when remaining in the product, are not necessarily abundant in the cell lysate and are often not individually described. A method for determining binding parameters of the entire host cell proteome including low abundant proteins to selected chromatography resins is still lacking.

Chapter 4 introduces a method to determine the above mentioned isotherm parameters of individual HCPs in a comprehensive manner. Fractions obtained from linear gradient elution experiments with different gradient lengths are analyzed by shotgun proteomics in order to extract the retention times of the individual HCPs. From the extracted retention volumes per gradient, isotherm parameters for all individual HCPs detected in the harvest were regressed. This method was exemplified using the BLR E. coli harvest, validated, and subsequently employed to optimize a capture step in silico.

Finally, chapter 5 gives an overview of the additionally investigated high-throughput sample preparation and analysis methods. This involved packing filter plates with resin for batch adsorption, which was explored to determine isotherm parameters instead of low gradient elution (LGE) experiments. Additionally, ion exchange high-performance liquid chromatography (IEX-HPLC) was investigated as an analytical technique instead of mass spectrometry (MS).

In summary, this thesis presents a comprehensive, large-scale characterization of HCPs from widely employed E. coli host cell strains for the production of protein vaccines. Moreover, a validated approach to determine isotherm parameters of all detectable HCPs in the harvest sample is presented.

Microbes have evolved to thrive in diverse and extreme environments. Understanding these microbes in engineered ecosystems, such as those used for wastewater treatment and drinking water production, is crucial for elucidating their roles in sanitation, nutrient cycling, and overall system stability. Traditional methods, such as microscopy and in situ staining, provide limited insight into microbial diversity and function, particularly for low-abundance species. The rise of culture-independent techniques like 16S rRNA and whole metagenome sequencing has revolutionized microbial ecology, enabling deeper analysis of taxonomic profiles, but does not answer questions beyond the metabolic potential.
Mass spectrometry is a powerful technology which enables the identification and characterization of proteins at a large scale from small amounts of cell material, referred to as proteomics. This has gained wide interest in the scientific community and industries, as proteins mediate fundamental processes in cells, such as enzymatic catalysis, molecular transport, signaling, cell division, and defense mechanisms.
Most recent advances in mass spectrometry allowed to transition the field of proteomics to investigate microbes, and complete microbial communities. Advantageously, microbial proteomics provides insights into the active metabolic pathways in microbes and microbial communities, thereby complementing the information obtained from DNA-based approaches.
While microbial proteomics has already been widely employed in various fields of research, including medical applications and biotechnology e.g. for understanding cell factories, much less has been done on environmental microbes, including those found in engineered ecosystems like wastewater and drinking water production systems.
This thesis aims to advance the application of microbial proteomics for studying microbial communities in engineered ecosystems, specifically within wastewater and drinking water environments. By analyzing the proteins present in these environments, this approach provides critical insights into the expressed metabolic functions of individual microbes and the protein biomass composition of microbial ecosystems. Additionally, investigating the microbial secretome provides new insights into metabolic versatility of microorganisms in nutrient-poor environments...

Vaccination is a strong and effective way to prevent spreading of infectious diseases and promotes global health. In the future, the importance of vaccines is expected only to increase, driven by factors such as increased international traveling, higher healthcare expenditures, and a growing population. To meet the growing demands, it is necessary to shorten process development timelines for the production of new vaccines without compromising on safety, efficacy, consistency, and stability of the product. Therefore, it is necessary to advance process development approaches of vaccines to respond quickly and in event of an emerging infectious disease. The work in this thesis employed mathematical modeling and simulation techniques to accelerate this process development. The developed methods are particularly valuable for early phase process development, aiming to enhance process knowledge and minimize the consumption of valuable resources and material. While the project has a focus on vaccine production processes, the modeling tools and methods developed are also applicable to other (bio)pharmaceutical processes. In Chapter 2, we discussed the present and future process development approaches in (bio)pharmaceutical purification with an emphasis on vaccines. The primary needs are to establish standardized processes and to improve understanding of both production processes and host cell impurities. Modeling, when combined with high throughput experimentation, can play a crucial role in achieving these goals...