Nils Kurzawa

In situ sequencing (ISS) offers a powerful approach for spatially resolved gene expression profiling within tissue samples, but the complexity of analyzing the resulting data has limited its broader use. Here, we present iss-nf, a Nextflow-based, end-to-end workflow designed to streamline the decoding of large ISS datasets. The workflow automates critical steps, including image registration, fluorescent spot detection, transcript decoding, and quality control (QC), offering a scalable, reproducible, and user-friendly solution for ISS data analysis. We successfully applied iss-nf on multiple large datasets, including publicly available mouse brain and breast cancer tissue datasets, as well as an in-house non-small cell lung cancer (NSCLC) ISS dataset. The workflow is designed to be accessible for both experienced researchers, as well as newcomers to spatial transcriptomics, providing a robust tool for analyzing large-scale ISS data. Our results suggest that iss-nf is a valuable contribution to the growing field of spatial transcriptomics, enabling precise, modular, reproducible, and, by means of automated tiling and parallelization, scalable analysis of tissue-specific gene expression.

Mitochondria are membrane-bound organelle hubs of cellular metabolism and signaling. The dysregulation of mitochondria is related to the genesis of several highly prevalent diseases, including cancer and cardiovascular disorders, urging the development of novel technologies to systematically study this organelle and its dynamics. Thermal proteome profiling (TPP) allows the unbiased study of the interactions of proteins with drugs, metabolites, and other proteins, providing a unique understanding of the state of the proteome. Here, we develop and introduce an optimized TPP workflow, mito-TPP, for the direct and extensive study of this organelle. We demonstrate that our approach detects both direct mitochondrial small molecule-protein and metabolite-protein interactions, as well as indirect downstream effects. We also show that mito-TPP preserves features from whole-cell systems, such as the coaggregation of interacting proteins. Finally, we explore the mitochondrial proteoform map, detecting more than 180 proteins with multiple proteoform groups. Overall, we demonstrate that mito-TPP is a powerful new tool for the functional study of the mitochondrial proteome.

The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.

Reversible protein phosphorylation is an important mechanism for regulating (dis)assembly of biomolecular condensates. However, condensate-specific phosphosites remain largely unknown, thereby limiting our understanding of the underlying mechanisms. Here, we combine solubility proteome profiling with phosphoproteomics to quantitatively map several hundred phosphosites enriched in either soluble or condensate-bound protein subpopulations, including a subset of phosphosites modulating protein–RNA interactions. We show that multi-phosphorylation of the C-terminal disordered segment of heteronuclear ribonucleoprotein A1 (HNRNPA1), a key RNA-splicing factor, reduces its ability to locate to nuclear clusters. For nucleophosmin 1 (NPM1), an essential nucleolar protein, we show that phosphorylation of S254 and S260 is crucial for lowering its partitioning to the nucleolus and additional phosphorylation of distal sites enhances its retention in the nucleoplasm. These phosphorylation events decrease RNA and protein interactions of NPM1 to regulate its condensation. Our dataset is a rich resource for systematically uncovering the phosphoregulation of biomolecular condensates.

The complexity of the functional proteome extends significantly beyond the protein coding genome resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases, but challenging to perform systematically. Here, we apply thermal proteome profiling with deep peptide coverage to detect functional proteoforms in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detect 15,846 proteoforms, capturing differently spliced, post-translationally modified, and cleaved proteins expressed from 9,290 genes. We identify differential coaggregation of proteoform pairs and establish links to disease biology. Moreover, we systematically make use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach thus provides a powerful and unique tool for systematic detection and functional annotation of proteoforms.

The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a global threat to human health and has compromised economic stability. In addition to the development of an effective vaccine, it is imperative to understand how SARS‐CoV‐2 hijacks host cellular machineries on a system‐wide scale so that potential host‐directed therapies can be developed. In situ proteome‐wide abundance and thermal stability measurements using thermal proteome profiling (TPP) can inform on global changes in protein activity. Here we adapted TPP to high biosafety conditions amenable to SARS‐CoV‐2 handling. We discovered pronounced temporal alterations in host protein thermostability during infection, which converged on cellular processes including cell cycle, microtubule and RNA splicing regulation. Pharmacological inhibition of host proteins displaying altered thermal stability or abundance during infection suppressed SARS‐CoV‐2 replication. Overall, this work serves as a framework for expanding TPP workflows to globally important human pathogens that require high biosafety containment and provides deeper resolution into the molecular changes induced by SARS‐CoV‐2 infection.

Numerous drugs and endogenous ligands bind to cell surface receptors leading to modulation of downstream signaling cascades and frequently to adaptation of the plasma membrane proteome. In-depth analysis of dynamic processes at the cell surface is challenging due to biochemical properties and low abundances of plasma membrane proteins. Here we introduce cell surface thermal proteome profiling for the comprehensive characterization of ligand-induced changes in protein abundances and thermal stabilities at the plasma membrane. We demonstrate drug binding to extracellular receptors and transporters, discover stimulation-dependent remodeling of T cell receptor complexes and describe a competition-based approach to measure target engagement of G-protein-coupled receptor antagonists. Remodeling of the plasma membrane proteome in response to treatment with the TGFB receptor inhibitor SB431542 leads to partial internalization of the monocarboxylate transporters MCT1/3 explaining the antimetastatic effects of the drug.

Recent developments in high-throughput reverse genetics^1,2 have revolutionized our ability to map gene function and interactions^3,4,5,6. The power of these approaches depends on their ability to identify functionally associated genes, which elicit similar phenotypic changes across several perturbations (chemical, environmental or genetic) when knocked out^7,8,9. However, owing to the large number of perturbations, these approaches have been limited to growth or morphological readouts¹⁰. Here we use a high-content biochemical readout, thermal proteome profiling¹¹, to measure the proteome-wide protein abundance and thermal stability in response to 121 genetic perturbations in Escherichia coli. We show that thermal stability, and therefore the state and interactions of essential proteins, is commonly modulated, raising the possibility of studying a protein group that is particularly inaccessible to genetics. We find that functionally associated proteins have coordinated changes in abundance and thermal stability across perturbations, owing to their co-regulation and physical interactions (with proteins, metabolites or cofactors). Finally, we provide mechanistic insights into previously determined growth phenotypes¹² that go beyond the deleted gene. These data represent a rich resource for inferring protein functions and interactions.