Title:	Exploration of dark microbial proteomes
DNr:	Berzelius-2025-37
Project Type:	LiU Berzelius
Principal Investigator:	Courtney Stairs <courtney.stairs@biol.lu.se>
Affiliation:	Lunds universitet
Duration:	2025-02-18 – 2025-09-01
Classification:	10615
Homepage:	https://thelabupstairs.online/
Keywords:

Abstract

Anaerobic protists represent a fascinating yet underexplored group of eukaryotes, thriving in oxygen-deprived habitats and employing metabolic strategies that remain largely enigmatic. Their proteomes are often dominated by “dark” or uncharacterized proteins, which provide an invaluable window into ancient biological processes and the evolutionary underpinnings of early-branching eukaryotes. Central to this project is the characterization of some these proteins, with particular emphasis on [FeFe]-hydrogenases, Quinone proteins, and large electron transport chain (ETC) complexes which are difficult to experimentally study. Understanding these components will not only illuminate how anaerobes function under oxygen-limited conditions but also deepen our overall insight into eukaryotic evolution and potential biotechnological applications. To achieve these goals, we would use protein structure prediction primarily using AlphaFold 3. Online implementations such as the AlphaFold 3 do not accommodate custom ligands or mega-complexes—critical features for fully modeling many of these proteins. Consequently, local installations of AlphaFold must be employed to flexibly handle these specialized tasks. This computationally intensive approach requires robust GPU resources. We will apply Foldseek to detect distant structural similarities that are often missed by sequence-based analyses. This will enable us to identify putative functions and evolutionary relationships for uncharacterized proteins. We will then carry out ligand docking studies on these models to pinpoint binding sites, catalytic residues, and potential interactions with unknown substrates—particularly important for investigating novel enzymes. These docking simulations are likewise computationally demanding, further underscoring the need for parallelized GPU processing to efficiently handle the large volumes of data. Finally, to place these structural and functional findings within a broader evolutionary framework, we will employ FoldTree for structure-based phylogenetic analyses. This holistic approach will allow us to map how these anaerobic pathways arose and diversified, shedding new light on the evolutionary trajectories of early eukaryotic life. By integrating cutting-edge computational tools with emerging experimental data, we aim to elucidate the adaptations that enable anaerobic protists to thrive in low-oxygen environments. In summary, this project seeks to exploit high-performance GPU resources to explore the dark proteomes of anaerobic protists, with a particular focus on FeFe hydrogenases, RQUA, and ETC mega-complexes. The inability of the AlphaFold 3 server to handle custom ligands or massive protein complexes necessitates local, large-scale computations on dedicated HPC nodes. We anticipate that the insights gained will significantly advance our understanding of eukaryotic evolution, illuminate poorly understood metabolic processes, and potentially inspire new proteins to study.