G. Tugui
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Wastewater metaproteomics
Tracking microbial and human protein biomarkers
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...
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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...
Anaerobic carboxydotrophy is a widespread catabolic trait in bacteria, with two dominant pathways: hydrogenogenic and acetogenic. The marginal mode by direct oxidation to CO2 using an external e-acceptor has only a few examples. Use of sulfidic sediments from two types of hypersaline lakes in anaerobic enrichments with CO as an e-donor and elemental sulfur as an e-acceptor led to isolation of two pure cultures of anaerobic carboxydotrophs belonging to two genera of sulfur-reducing haloarchaea: Halanaeroarchaeum sp. HSR-CO from salt lakes and Halalkaliarchaeum sp. AArc-CO from soda lakes. Anaerobic growth of extremely halophilic archaea with CO was obligatory depended on the presence of elemental sulfur as the electron acceptor and yeast extract as the carbon source. CO served as a direct electron donor and H2 was not generated from CO when cells were incubated with or without sulfur. The genomes of the isolates encode a catalytic Ni,Fe-CODH subunit CooS (distantly related to bacterial homologs) and its Ni-incorporating chaperone CooC (related to methanogenic homologs) within a single genomic locus. Similar loci were also present in a genome of the type species of Halalkaliarchaeum closely related to AArc-CO, and the ability for anaerobic sulfur-dependent carboxydotrophy was confirmed for three different strains of this genus. Moreover, similar proteins are encoded in three of the four genomes of recently described carbohydrate-utilizing sulfur-reducing haloarchaea belonging to the genus Halapricum and in two yet undescribed haloarchaeal species. Overall, this work demonstrated for the first time the potential for anaerobic sulfur-dependent carboxydotrophy in extremely halophilic archaea.
Metaproteomics has emerged as one of the most promising approaches for determining the composition and metabolic functions of complete microbial communities. Conventional metaproteomics approaches rely on the construction of protein sequence databases and efficient peptide-spectrum-matching algorithms, an approach that is intrinsically biased towards the content of the constructed sequence database. Here, we introduce a highly efficient, database-independent de novo metaproteomics approach and systematically evaluate its quantitative performance using synthetic and natural microbial communities comprising dozens of taxonomic families. Our work demonstrates that the de novo sequencing approach can vastly expand many metaproteomics applications by enabling rapid quantitative profiling and by capturing unsequenced community members that otherwise remain inaccessible for further interpretation. Kleikamp et al., describe a novel de novo metaproteomics pipeline (NovoBridge) that enables rapid community profiling without the need for constructing protein sequence databases.