Open-ST: High-resolution spatial transcriptomics in 3D.

Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.

Microscopic examination of spatial transcriptome using Seq-Scope.

Spatial barcoding technologies have the potential to reveal histological details of transcriptomic profiles; however, they are currently limited by their low resolution. Here, we report Seq-Scope, a spatial barcoding technology with a resolution comparable to an optical microscope. Seq-Scope is based on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides using an Illumina sequencing platform. The resulting clusters annotated with spatial coordinates are processed to expose RNA-capture moiety. These RNA-capturing barcoded clusters define the pixels of Seq-Scope that are ∼0.5-0.8 µm apart from each other. From tissue sections, Seq-Scope visualizes spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon) and inflammation-fibrosis (injured liver) axes, cellular components including single-cell types and subtypes, and subcellular architectures of nucleus and cytoplasm. Seq-Scope is quick, straightforward, precise, and easy-to-implement and makes spatial single-cell analysis accessible to a wide group of biomedical researchers.

Distinct Processing of lncRNAs Contributes to Non-conserved Functions in Stem Cells.

Long noncoding RNAs (lncRNAs) evolve more rapidly than mRNAs. Whether conserved lncRNAs undergo conserved processing, localization, and function remains unexplored. We report differing subcellular localization of lncRNAs in human and mouse embryonic stem cells (ESCs). A significantly higher fraction of lncRNAs is localized in the cytoplasm of hESCs than in mESCs. This turns out to be important for hESC pluripotency. FAST is a positionally conserved lncRNA but is not conserved in its processing and localization. In hESCs, cytoplasm-localized hFAST binds to the WD40 domain of the E3 ubiquitin ligase ß-TrCP and blocks its interaction with phosphorylated ß-catenin to prevent degradation, leading to activated WNT signaling, required for pluripotency. In contrast, mFast is nuclear retained in mESCs, and its processing is suppressed by the splicing factor PPIE, which is highly expressed in mESCs but not hESCs. These findings reveal that lncRNA processing and localization are previously under-appreciated contributors to the rapid evolution of function.

A Membraneless Organelle Associated with the Endoplasmic Reticulum Enables 3'UTR-Mediated Protein-Protein Interactions.

Approximately half of human genes generate mRNAs with alternative 3' untranslated regions (3'UTRs). Through 3'UTR-mediated protein-protein interactions, alternative 3'UTRs enable multi-functionality of proteins with identical amino acid sequence. While studying how information on protein features is transferred from 3'UTRs to proteins, we discovered that the broadly expressed RNA-binding protein TIS11B forms a membraneless organelle, called TIS granule, that enriches membrane protein-encoding mRNAs with multiple AU-rich elements. TIS granules form a reticular meshwork intertwined with the endoplasmic reticulum (ER). The association between TIS granules and the ER creates a subcellular compartment-the TIGER domain-with a biophysically and biochemically distinct environment from the cytoplasm. This compartment promotes 3'UTR-mediated interaction of SET with membrane proteins, thus allowing increased surface expression and functional diversity of proteins, including CD47 and PD-L1. The TIGER domain is a subcellular compartment that enables formation of specific and functionally relevant protein-protein interactions that cannot be established outside.

Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle.

Dissecting the regulatory mechanisms controlling mammalian transcripts from production to degradation requires quantitative measurements of mRNA flow across the cell. We developed subcellular TimeLapse-seq to measure the rates at which RNAs are released from chromatin, exported from the nucleus, loaded onto polysomes, and degraded within the nucleus and cytoplasm in human and mouse cells. These rates varied substantially, yet transcripts from genes with related functions or targeted by the same transcription factors and RNA-binding proteins flowed across subcellular compartments with similar kinetics. Verifying these associations uncovered a link between DDX3X and nuclear export. For hundreds of RNA metabolism genes, most transcripts with retained introns were degraded by the nuclear exosome, while the remaining molecules were exported with stable cytoplasmic lifespans. Transcripts residing on chromatin for longer had extended poly(A) tails, whereas the reverse was observed for cytoplasmic mRNAs. Finally, machine learning identified molecular features that predicted the diverse life cycles of mRNAs.

Hexokinase 1 cellular localization regulates the metabolic fate of glucose.

The product of hexokinase (HK) enzymes, glucose-6-phosphate, can be metabolized through glycolysis or directed to alternative metabolic routes, such as the pentose phosphate pathway (PPP) to generate anabolic intermediates. HK1 contains an N-terminal mitochondrial binding domain (MBD), but its physiologic significance remains unclear. To elucidate the effect of HK1 mitochondrial dissociation on cellular metabolism, we generated mice lacking the HK1 MBD (ΔE1HK1). These mice produced a hyper-inflammatory response when challenged with lipopolysaccharide. Additionally, there was decreased glucose flux below the level of GAPDH and increased upstream flux through the PPP. The glycolytic block below GAPDH is mediated by the binding of cytosolic HK1 with S100A8/A9, resulting in GAPDH nitrosylation through iNOS. Additionally, human and mouse macrophages from conditions of low-grade inflammation, such as aging and diabetes, displayed increased cytosolic HK1 and reduced GAPDH activity. Our data indicate that HK1 mitochondrial binding alters glucose metabolism through regulation of GAPDH.

Quantitative subcellular acyl-CoA analysis reveals distinct nuclear metabolism and isoleucine-dependent histone propionylation.

Quantitative subcellular metabolomic measurements can explain the roles of metabolites in cellular processes but are subject to multiple confounding factors. We developed stable isotope labeling of essential nutrients in cell culture-subcellular fractionation (SILEC-SF), which uses isotope-labeled internal standard controls that are present throughout fractionation and processing to quantify acyl-coenzyme A (acyl-CoA) thioesters in subcellular compartments by liquid chromatography-mass spectrometry. We tested SILEC-SF in a range of sample types and examined the compartmentalized responses to oxygen tension, cellular differentiation, and nutrient availability. Application of SILEC-SF to the challenging analysis of the nuclear compartment revealed a nuclear acyl-CoA profile distinct from that of the cytosol, with notable nuclear enrichment of propionyl-CoA. Using isotope tracing, we identified the branched chain amino acid isoleucine as a major metabolic source of nuclear propionyl-CoA and histone propionylation, thus revealing a new mechanism of crosstalk between metabolism and the epigenome.

Taking Me away: the function of phosphorylation on histone lysine demethylases.

Histone lysine demethylases (KDMs) regulate eukaryotic gene transcription by catalysing the removal of methyl groups from histone proteins. These enzymes are intricately regulated by the kinase signalling system in response to internal and external stimuli. Here, we review the mechanisms by which kinase-mediated phosphorylation influence human histone KDM function. These include the changing of histone KDM subcellular localisation or chromatin binding, the altering of protein half-life, changes to histone KDM complex formation that result in histone demethylation, non-histone demethylation or demethylase-independent effects, and effects on histone KDM complex dissociation. We also explore the structural context of phospho-sites on histone KDMs and evaluate how this relates to function.

Proximity RNA Labeling by APEX-Seq Reveals the Organization of Translation Initiation Complexes and Repressive RNA Granules.

Diverse ribonucleoprotein complexes control mRNA processing, translation, and decay. Transcripts in these complexes localize to specific regions of the cell and can condense into non-membrane-bound structures such as stress granules. It has proven challenging to map the RNA composition of these large and dynamic structures, however. We therefore developed an RNA proximity labeling technique, APEX-seq, which uses the ascorbate peroxidase APEX2 to probe the spatial organization of the transcriptome. We show that APEX-seq can resolve the localization of RNAs within the cell and determine their enrichment or depletion near key RNA-binding proteins. Matching the spatial transcriptome, as revealed by APEX-seq, with the spatial proteome determined by APEX-mass spectrometry (APEX-MS), obtained precisely in parallel, provides new insights into the organization of translation initiation complexes on active mRNAs and unanticipated complexity in stress granule composition. Our novel technique allows a powerful and general approach to explore the spatial environment of macromolecules.

The endoplasmic reticulum as an active liquid network.

The peripheral endoplasmic reticulum (ER) forms a dense, interconnected, and constantly evolving network of membrane-bound tubules in eukaryotic cells. While individual structural elements and the morphogens that stabilize them have been described, a quantitative understanding of the dynamic large-scale network topology remains elusive. We develop a physical model of the ER as an active liquid network, governed by a balance of tension-driven shrinking and new tubule growth. This minimalist model gives rise to steady-state network structures with density and rearrangement timescales predicted from the junction mobility and tubule spawning rate. Several parameter-independent geometric features of the liquid network model are shown to be representative of ER architecture in live mammalian cells. The liquid network model connects the timescales of distinct dynamic features such as ring closure and new tubule growth in the ER. Furthermore, it demonstrates how the steady-state network morphology on a cellular scale arises from the balance of microscopic dynamic rearrangements.

Subcellular location of source proteins improves prediction of neoantigens for immunotherapy.

Antigen presentation via the major histocompatibility complex (MHC) is essential for anti-tumor immunity. However, the rules that determine which tumor-derived peptides will be immunogenic are still incompletely understood. Here, we investigated whether constraints on peptide accessibility to the MHC due to protein subcellular location are associated with peptide immunogenicity potential. Analyzing over 380,000 peptides from studies of MHC presentation and peptide immunogenicity, we find clear spatial biases in both eluted and immunogenic peptides. We find that including parent protein location improves the prediction of peptide immunogenicity in multiple datasets. In human immunotherapy cohorts, the location was associated with a neoantigen vaccination response, and immune checkpoint blockade responders generally had a higher burden of neopeptides from accessible locations. We conclude that protein subcellular location adds important information for optimizing cancer immunotherapies.

Localization of RNAs to the mitochondria-mechanisms and functions.

The mammalian mitochondrial proteome comprises over 1000 proteins, with the majority translated from nuclear-encoded messenger RNAs (mRNAs). Mounting evidence suggests many of these mRNAs are localized to the outer mitochondrial membrane (OMM) in a pre- or cotranslational state. Upon reaching the mitochondrial surface, these mRNAs are locally translated to produce proteins that are cotranslationally imported into mitochondria. Here, we summarize various mechanisms cells use to localize RNAs, including transfer RNAs (tRNAs), to the OMM and recent technological advancements in the field to study these processes. While most early studies in the field were carried out in yeast, recent studies reveal RNA localization to the OMM and their regulation in higher organisms. Various factors regulate this localization process, including RNA sequence elements, RNA-binding proteins (RBPs), cytoskeletal motors, and translation machinery. In this review, we also highlight the role of RNA structures and modifications in mitochondrial RNA localization and discuss how these features can alter the binding properties of RNAs. Finally, in addition to RNAs related to mitochondrial function, RNAs involved in other cellular processes can also localize to the OMM, including those implicated in the innate immune response and piRNA biogenesis. As impairment of messenger RNA (mRNA) localization and regulation compromise mitochondrial function, future studies will undoubtedly expand our understanding of how RNAs localize to the OMM and investigate the consequences of their mislocalization in disorders, particularly neurodegenerative diseases, muscular dystrophies, and cancers.

Interpretable feature extraction and dimensionality reduction in ESM2 for protein localization prediction.

As the application of large language models (LLMs) has broadened into the realm of biological predictions, leveraging their capacity for self-supervised learning to create feature representations of amino acid sequences, these models have set a new benchmark in tackling downstream challenges, such as subcellular localization. However, previous studies have primarily focused on either the structural design of models or differing strategies for fine-tuning, largely overlooking investigations into the nature of the features derived from LLMs. In this research, we propose different ESM2 representation extraction strategies, considering both the character type and position within the ESM2 input sequence. Using model dimensionality reduction, predictive analysis and interpretability techniques, we have illuminated potential associations between diverse feature types and specific subcellular localizations. Particularly, the prediction of Mitochondrion and Golgi apparatus prefer segments feature closer to the N-terminal, and phosphorylation site-based features could mirror phosphorylation properties. We also evaluate the prediction performance and interpretability robustness of Random Forest and Deep Neural Networks with varied feature inputs. This work offers novel insights into maximizing LLMs' utility, understanding their mechanisms, and extracting biological domain knowledge. Furthermore, we have made the code, feature extraction API, and all relevant materials available at https://github.com/yujuan-zhang/feature-representation-for-LLMs.

PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs.

The microRNAs (miRNAs) play crucial roles in several biological processes. It is essential for a deeper insight into their functions and mechanisms by detecting their subcellular localizations. The traditional methods for determining miRNAs subcellular localizations are expensive. The computational methods are alternative ways to quickly predict miRNAs subcellular localizations. Although several computational methods have been proposed in this regard, the incomplete representations of miRNAs in these methods left the room for improvement. In this study, a novel computational method for predicting miRNA subcellular localizations, named PMiSLocMF, was developed. As lots of miRNAs have multiple subcellular localizations, this method was a multi-label classifier. Several properties of miRNA, such as miRNA sequences, miRNA functional similarity, miRNA-disease, miRNA-drug, and miRNA-mRNA associations were adopted for generating informative miRNA features. To this end, powerful algorithms [node2vec and graph attention auto-encoder (GATE)] and one newly designed scheme were adopted to process above properties, producing five feature types. All features were poured into self-attention and fully connected layers to make predictions. The cross-validation results indicated the high performance of PMiSLocMF with accuracy higher than 0.83, average area under the receiver operating characteristic curve (AUC) and area under the precision-recall curve (AUPR) exceeding 0.90 and 0.77, respectively. Such performance was better than all previous methods based on the same dataset. Further tests proved that using all feature types can improve the performance of PMiSLocMF, and GATE and self-attention layer can help enhance the performance. Finally, we deeply analyzed the influence of miRNA associations with diseases, drugs, and mRNAs on PMiSLocMF. The dataset and codes are available at https://github.com/Gu20201017/PMiSLocMF.

TransGCN: a semi-supervised graph convolution network-based framework to infer protein translocations in spatio-temporal proteomics.

Protein subcellular localization (PSL) is very important in order to understand its functions, and its movement between subcellular niches within cells plays fundamental roles in biological process regulation. Mass spectrometry-based spatio-temporal proteomics technologies can help provide new insights of protein translocation, but bring the challenge in identifying reliable protein translocation events due to the noise interference and insufficient data mining. We propose a semi-supervised graph convolution network (GCN)-based framework termed TransGCN that infers protein translocation events from spatio-temporal proteomics. Based on expanded multiple distance features and joint graph representations of proteins, TransGCN utilizes the semi-supervised GCN to enable effective knowledge transfer from proteins with known PSLs for predicting protein localization and translocation. Our results demonstrate that TransGCN outperforms current state-of-the-art methods in identifying protein translocations, especially in coping with batch effects. It also exhibited excellent predictive accuracy in PSL prediction. TransGCN is freely available on GitHub at https://github.com/XuejiangGuo/TransGCN.

NF-κB dynamics in the language of immune cells.

Biological discovery has been driven by advances in throughput and resolution of analysis technologies. They have also created an indelible bias for snapshot-based knowledge. Even though recent methods such as multi-omics single-cell assays have empowered immunological investigations, they still provide snapshots of cellular behaviors and thus, have inherent limitations in reconstructing unsynchronized dynamic events across individual cells. Here, we present a rationale for how NF-κB may convey specificity of contextual information through subtle quantitative features of its signaling dynamics. The next frontier of predictive understanding should involve functional characterization of NF-κB signaling dynamics and their immunological implications. This may help solve the apparent paradox that a ubiquitously activated transcription factor can shape accurate responses to different immune challenges.

BioID organelle mapping: you are the company you keep.

In a recent study, Go, Knight et al. combined a panel of protein markers with BioID proximity-dependent labeling to profile the composition of 20 distinct subcellular compartments. Comparison with similar global datasets acquired using imaging or fractionation-based approaches confirmed the consistency of the results while highlighting unique advantages.

Shaping subcellular tubes through vesicle trafficking: Common and distinct pathways.

Cells with subcellular lumens form some of the most miniature tubes in the tubular organs of animals. These are often crucial components of the system, executing functions at remote body locations. Unlike tubes formed by intercellular or autocellular junctions, the cells with junctionless subcellular lumens face unique challenges in modifying the cell shape and plasma membrane organization to incorporate a membrane-bound tube within, often associated with dramatic cellular growth and extensions. Results in the recent years have shown that membrane dynamics, including both the primary delivery and recycling, is crucial in providing the cell with the flexibility to face these challenges. A significant portion of this information has come from two in vivo invertebrate models; the Drosophila tracheal terminal cells and the C. elegans excretory cell. This review focuses on the data obtained from these systems in the recent past about how trafficking pathways influence subcellular tube and branching morphogenesis. Given that such tubes occur in vertebrate vasculature, these insights are relevant to human health, and we contrast our conclusions with the less understood subcellular tubes of angiogenesis.

Spatial organization of bacterial sphingolipid synthesis enzymes.

Sphingolipids are produced by nearly all eukaryotes where they play significant roles in cellular processes such as cell growth, division, programmed cell death, angiogenesis, and inflammation. While it was previously believed that sphingolipids were quite rare among bacteria, bioinformatic analysis of the recently identified bacterial sphingolipid synthesis genes suggests that these lipids are likely to be produced by a wide range of microbial species. The sphingolipid synthesis pathway consists of three critical enzymes. Serine palmitoyltransferase catalyzes the condensation of serine with palmitoyl-CoA (or palmitoyl-acyl carrier protein), ceramide synthase adds the second acyl chain, and a reductase reduces the ketone present on the long-chain base. While there is general agreement regarding the identity of these bacterial enzymes, the precise mechanism and order of chemical reactions for microbial sphingolipid synthesis is more ambiguous. Two mechanisms have been proposed. First, the synthesis pathway may follow the well characterized eukaryotic pathway in which the long-chain base is reduced prior to the addition of the second acyl chain. Alternatively, our previous work suggests that addition of the second acyl chain precedes the reduction of the long-chain base. To distinguish between these two models, we investigated the subcellular localization of these three key enzymes. We found that serine palmitoyltransferase and ceramide synthase are localized to the cytoplasm, whereas the ceramide reductase is in the periplasmic space. This is consistent with our previously proposed model wherein the second acyl chain is added in the cytoplasm prior to export to the periplasm where the lipid molecule is reduced.

The N-terminal signature motif on the transporter MCT1 is critical for CD147-mediated trafficking.

The human Solute Carrier (SLC) family member, monocarboxylate transporter 1 (MCT1), transports lactic and pyruvic acid across biological membranes to regulate cellular pH and metabolism. Proper trafficking of MCT1 from the endoplasmic reticulum to the plasma membrane hinges on its interactions with the membrane-bound chaperone protein, CD147. Here, using AlphaFold2 modeling and copurification, we show how a conserved signature motif located in the flexible N-terminus of MCT1 is a crucial region of interaction between MCT1 and the C-terminus of CD147. Mutations to this motif-namely, the thymic cancer linked G19C and the highly conserved W20A-destabilize the MCT1-CD147 complex and lead to a loss of proper membrane localization and cellular substrate flux. Notably, the monomeric stability of MCT1 remains unaffected in mutants, thus supporting the role of CD147 in mediating the trafficking of the heterocomplex. Using the auxiliary chaperone, GP70, we demonstrated that W20A-MCT1 can be trafficked to the plasma membrane, while G19C-MCT1 remains internalized. Overall, our findings underscore the critical role of the MCT1 transmembrane one signature motif for engaging CD147 and identify altered chaperone binding mechanisms between the CD147 and GP70 glycoprotein chaperones.