Microscopy and mass spectrometry (MS) are complementary techniques: The former provides spatiotemporal information in living cells, but only for a handful of recombinant proteins at a time, whereas the latter can detect thousands of endogenous proteins simultaneously, but only in lysed samples. Here, we introduce technology that combines these strengths by offering spatially and temporally resolved proteomic maps of endogenous proteins within living cells. Our method relies on a genetically targetable peroxidase enzyme that biotinylates nearby proteins, which are subsequently purified and identified by MS. We used this approach to identify 495 proteins within the human mitochondrial matrix, including 31 not previously linked to mitochondria. The labeling was exceptionally specific and distinguished between inner membrane proteins facing the matrix versus the intermembrane space (IMS). Several proteins previously thought to reside in the IMS or outer membrane, including protoporphyrinogen oxidase, were reassigned to the matrix by our proteomic data and confirmed by electron microscopy. The specificity of peroxidase-mediated proteomic mapping in live cells, combined with its ease of use, offers biologists a powerful tool for understanding the molecular composition of living cells.

Proteomic Mapping of Mitochondria in Living Cells via Spatially Restricted Enzymatic Tagging

Many biological processes are executed and regulated through the molecular interactions of proteins and nucleic acids. Proximity labeling (PL) is a technology for tagging the endogenous interaction partners of specific protein ‘baits’, via genetic fusion to promiscuous enzymes that catalyze the generation of diffusible reactive species in living cells. Tagged molecules that interact with baits can then be enriched and identified by mass spectrometry or nucleic acid sequencing. Here we review the development of PL technologies and highlight studies that have applied PL to the discovery and analysis of molecular interactions. In particular, we focus on the use of PL for mapping protein–protein, protein–RNA and protein–DNA interactions in living cells and organisms. This Review describes proximity labeling methods that make use of peroxidases (APEX) or biotin ligases (TurboID, BioID), and their applications to studying protein–protein and protein–nucleic acid interactions in living systems.

Deciphering molecular interactions by proximity labeling.

RNA molecules start assembling into ribonucleoprotein (RNP) complexes during transcription. Dynamic RNP assembly, largely directed by cis-acting elements on the RNA, coordinates all processes in which the RNA is involved. To identify the sites bound by a specific RNA-binding protein on endogenous RNAs, cross-linking and immunoprecipitation (CLIP) and complementary, proximity-based methods have been developed. In this Primer, we discuss the main variants of these protein-centric methods and the strategies for their optimization and quality assessment, as well as RNA-centric methods that identify the protein partners of a specific RNA. We summarize the main challenges of computational CLIP data analysis, how to handle various sources of background and how to identify functionally relevant binding regions. We outline the various applications of CLIP and available databases for data sharing. We discuss the prospect of integrating data obtained by CLIP with complementary methods to gain a comprehensive view of RNP assembly and remodelling, unravel the spatial and temporal dynamics of RNPs in specific cell types and subcellular compartments and understand how defects in RNPs can lead to disease. Finally, we present open questions in the field and give directions for further development and applications. Ule and colleagues discuss cross-linking and immunoprecipitation (CLIP) methods for characterizing the RNA binding partners of RNA-binding proteins and explore the data analysis workflows, best practices and applications for these techniques. The Primer also considers methods for characterizing the protein binding partners of specific RNAs and discusses how data from these complementary methods can be integrated into CLIP workflows.

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CLIP and complementary methods

Recent transcriptome analyses have revealed that noncoding RNAs (ncRNAs) are broadly expressed in mammalian cells and abundant in the CNS, with tissue and cell type-specific expression patterns. Moreover, ncRNAs have been found to intricately and dynamically regulate various signaling pathways in neurodegeneration. As such, some antisense transcripts and microRNAs are known to directly affect neurodegeneration in disease contexts. The functions of ncRNAs in pathogenesis are unique for each disorder, as are the pertinent networks of ncRNA/miRNA/mRNA that mediate these functions. Thus, further understanding of ncRNA biogenesis and effects might aid the discovery of diagnostic biomarkers or development of effective therapeutics for neurodegenerative disorders. Here, we review the ncRNAs that have so far been identified in major neurodegenerative disease etiology and the mechanisms that link ncRNAs with disease-specific phenotypes, such as HTT aggregation in HD, α-synuclein in PD, and Aβ plaques and hyperphosphorylated Tau in AD. We also summarize the known lncRNA/miRNA/mRNA networks that participate in neurodegenerative diseases, and we discuss ncRNA-related treatments shown to delay disease onset and prolong lifespan in rodent models.

https://link.springer.com/content/pdf/10.1186/s12929-020-00636-z.pdf

Functional roles and networks of non-coding RNAs in the pathogenesis of neurodegenerative diseases

Chemically modified biomacromolecules-i.e., proteins, nucleic acids, glycans, and lipids-have become crucial tools in chemical biology. They are extensively used not only to elucidate cellular processes but also in industrial applications, particularly in the context of biopharmaceuticals. In order to enable maximum scope for optimization, it is pivotal to have a diverse array of biomacromolecule modification methods at one's disposal. Chemistry has driven many significant advances in this area, and especially recently, numerous novel visible-light-induced photochemical approaches have emerged. In these reactions, light serves as an external source of energy, enabling access to highly reactive intermediates under exceedingly mild conditions and with exquisite spatiotemporal control. While UV-induced transformations on biomacromolecules date back decades, visible light has the unmistakable advantage of being considerably more biocompatible, and a spectrum of visible-light-driven methods is now available, chiefly for proteins and nucleic acids. This review will discuss modifications of native functional groups (FGs), including functionalization, labeling, and cross-linking techniques as well as the utility of oxidative degradation mediated by photochemically generated reactive oxygen species. Furthermore, transformations at non-native, bioorthogonal FGs on biomacromolecules will be addressed, including photoclick chemistry and DNA-encoded library synthesis as well as methods that allow manipulation of the activity of a biomacromolecule.

Visible-Light-Mediated Modification and Manipulation of Biomacromolecules.

RNA molecules are highly compartmentalized in eukaryotic cells, with their localizations intimately linked to their functions. Despite the importance of RNA targeting, our current knowledge of the spatial organization of the transcriptome has been limited by a lack of analytical tools. In this study, we develop a chemical biology approach to label RNAs in live cells with high spatial specificity. Our method, called CAP-seq, capitalizes on light-activated, proximity-dependent photo-oxidation of RNA nucleobases, which could be subsequently enriched via affinity purification and identified by high-throughput sequencing. Using this technique, we investigate the local transcriptomes that are proximal to various subcellular compartments, including the endoplasmic reticulum and mitochondria. We discover that messenger RNAs encoding for ribosomal proteins and oxidative phosphorylation pathway proteins are highly enriched at the outer mitochondrial membrane. Due to its specificity and ease of use, CAP-seq is a generally applicable technique to investigate the spatial transcriptome in many biological systems.

Mapping spatial transcriptome with light-activated proximity-dependent RNA labeling.

Purpose Modern Linacs are equipped with multiple photon energies for radiation therapy, and proper energy is chosen for each case based on tumor characteristics and patient anatomy. The aim of this study is to investigate whether it is necessary to have more than two photons energies. Methods The principle of photon energy synthesis is presented. It is shown that a photon beam of any intermediate energy (Esyn) can be synthesized from a linear combination of a low energy (Elow) and a high energy (Ehigh). The principle is validated on a wide range of scenarios: different intermediate photon energies on the same Linac; between Linacs from the same manufacturer or different manufacturers; open and wedge beams; and extensive photon energies available from published reference data. In addition, 3D dose distributions in water phantom are compared using Gamma analysis. The method is further demonstrated in clinical cases of various tumor sites and multiple treatment modalities. Experimental measurements are performed for IMRT plans and they are analyzed using the standard clinical protocol. Results The synthesis coefficients vary with energy and field size. The root mean square error (RMSE) is within 1.1% for open and wedge fields. Excellent agreement was observed for British Journal of Radiology (BJR) data with an average RMSE of 0.11%. The 3D Gamma analysis shows a good match for all field sizes in the water phantom and all treatment modalities for the five clinical cases. The minimum gamma passing rate of 95.7% was achieved at 1%/1mm criteria for two measured dose distributions of IMRT plans. Conclusion A Linac with two photon energies is capable of producing dosimetrically equivalent plans of any energy in-between through the photon energy synthesis, supporting the notion that there is no need to equip more than two photon energies on each Linac. This can significantly reduce the cost of equipment for radiation therapy.

/pdf/does-radiation-therapy-need-more-than-two-photon-energies-17vnxggg.pdf

Tianyu Xiong

Papers

Mapping spatial transcriptome with light-activated proximity-dependent RNA labeling.

Does radiation therapy need more than two photon energies from Linac?