Suborganellar Localization of Mitochondrial Proteins and Transcripts in Human Cells

Approaches and challenges in identifying, quantifying, and manipulating dynamic mitochondrial genome variations

Mitochondria, the cellular powerhouses, possess their own unique genetic system, including replication, transcription, and translation. Studying these processes is crucial for comprehending mitochondrial disorders, energy production, and their related diseases. Over the past decades, various approaches have been applied in detecting and quantifying mitochondrial genome variations with also the purpose of manipulation of mitochondria or mitochondrial genome for therapeutics. Understanding the scope and limitations of above strategies is not only fundamental to the understanding of basic biology but also critical for exploring disease-related novel target(s), as well to develop innovative therapies. Here, this review provides an overview of different tools and techniques for accurate mitochondrial genome variations identification, quantification, and discuss novel strategies for the manipulation of mitochondria to develop innovative therapeutic interventions, through combining the insights gained from the study of mitochondrial genetics with ongoing single cell omics combined with advanced single molecular tools.

Higher-Order Structural Organization of the Mitochondrial Proteome Charted by In Situ Cross-Linking Mass Spectrometry

Mitochondria are densely packed with proteins, of which most are involved physically or more transiently in protein-protein interactions (PPIs). Mitochondria host among others all enzymes of the Krebs cycle and the oxidative phosphorylation pathway and are foremost associated with cellular bioenergetics. However, mitochondria are also important contributors to apoptotic cell death and contain their own genome indicating that they play additionally an eminent role in processes beyond bioenergetics. Despite intense efforts in identifying and characterizing mitochondrial protein complexes by structural biology and proteomics techniques, many PPIs have remained elusive. Several of these (membrane embedded) PPIs are less stable in vitro hampering their characterization by most contemporary methods in structural biology. Particularly in these cases, cross-linking mass spectrometry (XL-MS) has proven valuable for the in-depth characterization of mitochondrial protein complexes in situ. Here, we highlight experimental strategies for the analysis of proteome-wide PPIs in mitochondria using XL-MS. We showcase the ability of in situ XL-MS as a tool to map suborganelle interactions and topologies and aid in refining structural models of protein complexes. We describe some of the most recent technological advances in XL-MS that may benefit the in situ characterization of PPIs even further, especially when combined with electron microscopy and structural modeling.

CoLoC-seq probes the global topology of organelle transcriptomes

Proper RNA localisation is essential for physiological gene expression. Various kinds of genome-wide approaches permit to comprehensively profile subcellular transcriptomes. Among them, cell fractionation methods, that couple RNase treatment of isolated organelles to the sequencing of protected transcripts, remain most widely used, mainly because they do not require genetic modification of the studied system and can be easily implemented in any cells or tissues, including in non-model species. However, they suffer from numerous false-positives since incompletely digested contaminant RNAs can still be captured and erroneously identified as resident transcripts. Here we introduce Controlled Level of Contamination coupled to deep sequencing (CoLoC-seq) as a new subcellular transcriptomics approach that efficiently bypasses this caveat. CoLoC-seq leverages classical enzymatic kinetics and tracks the depletion dynamics of transcripts in a gradient of an exogenously added RNase, with or without organellar membranes. By means of straightforward mathematical modelling, CoLoC-seq infers the localisation topology of RNAs and robustly distinguishes between genuinely resident, luminal transcripts and merely abundant surface-attached contaminants. Our generic approach performed well on human mitochondria and is in principle applicable to other membrane-bounded organelles, including plastids, compartments of the vacuolar system, extracellular vesicles, and viral particles.