Improving quantitative prediction of protein subcellular locations in fluorescence images through deep generative models.

Machine learning has been employed in recognizing protein localization at the subcellular level, which highly facilitates the protein function studies, especially for those multi-label proteins that localize in more than one organelle. However, existing works mostly study the qualitative classification of protein subcellular locations, ignoring fraction of one multi-label protein in different locations. Actually, about 50 % proteins are multi-label proteins, and the ignorance of quantitative information highly restricts the understanding of their spatial distribution and functional mechanism. One reason of the lack of quantitative study is the insufficiency of quantitative annotations. To address the data shortage problem, here we proposed a generative model, PLocGAN, which could generate cell images with conditional quantitative annotation of the fluorescence distribution. The model was a conditional generative adversarial network, in which the condition learning utilized partial label learning to overcome the lack of training labels and allowed training with only qualitative labels. Meanwhile, it used contrastive learning to enhance diversity of the generated images. We assessed the PLocGAN on four pixel-fused synthetic datasets and one real dataset, and demonstrated that the model could generate images with good fidelity and diversity, outperforming existing state-of-the-art generative methods. To verify the utility of PLocGAN in the quantitative prediction of protein subcellular locations, we replaced the training images with generated quantitative images and built prediction models, and found that they had a boosting effect on the quantitative estimation. This work demonstrates the effectiveness of deep generative models in bioimage analysis, and provides a new solution for quantitative subcellular proteomics.

Subcellular localization of viral proteins after porcine epidemic diarrhea virus infection and their roles in the viral life cycle.

Porcine epidemic diarrhea virus (PEDV) is one of the most devastating diseases affecting the pig industry globally. Due to the emergence of novel strains, no effective vaccines are available for prevention and control. Investigating the pathogenic mechanisms of PEDV may provide insights for creating clinical interventions. This study constructed and expressed eukaryotic expression vectors containing PEDV proteins (except NSP11) with a 3' HA tag in Vero cells. The subcellular localization of PEDV proteins was examined using endogenous protein antibodies to investigate their involvement in the viral life cycle, including endocytosis, intracellular trafficking, genome replication, energy metabolism, budding, and release. We systematically analyzed the potential roles of all PEDV viral proteins in the virus life cycle. We found that the endosome sorting complex required for transport (ESCRT) machinery may be involved in the replication and budding processes of PEDV. Our study provides insight into the molecular mechanisms underlying PEDV infection. IMPORTANCE: The global swine industry has suffered immense losses due to the spread of PEDV. Currently, there are no effective vaccines available for clinical protection. Exploring the pathogenic mechanisms of PEDV may provide valuable insights for clinical interventions. This study investigated the involvement of viral proteins in various stages of the PEDV lifecycle in the state of viral infection and identified several previously unreported interactions between viral and host proteins. These findings contribute to a better understanding of the pathogenic mechanisms underlying PEDV infection and may serve as a basis for further research and development of therapeutic strategies.

The functions of triple gene block proteins and coat protein of apple stem pitting virus in viral cell-to-cell movement.

Apple stem pitting virus is a species in the genus Foveavirus in the family Betaflexiviridae. Apple stem pitting virus (ASPV) commonly infects apple and pear plants grown worldwide. In this study, by integrating bimolecular fluorescence complementation, split-ubiquitin-based membrane yeast two-hybrid, and Agrobacterium-mediated expression assays, the interaction relationships and the subcellular locations of ASPV proteins TGBp1-3 and CP in Nicotiana benthamiana leaf cells were determined. Proteins CP, TGBp1, TGBp2, and TGBp3 were self-interactable, and TGBp2 played a role in the formation of perinuclear viroplasm and enhanced the colocalization of TGBp3 with CP and TGBp1. We found that the plant microfilament and endoplasmic reticulum structures were involved in the production of TGBp3 and TGBp2 vesicles, and their disruption decreased the virus accumulation level in the systemic leaves. The TGBp3 motile vesicles functioned in delivering the viral ribonucleoprotein complexes to the plasma membrane. Two cysteine residues at sites 35 and 49 of the TGBp3 sorting signal were necessary for the diffusion of TGBp3-marked vesicles. Furthermore, our results revealed that TGBp1, TGBp2, and CP could increase plasmodesmal permeability and move to the adjacent cells. This study demonstrates an interaction network and a subcellular location map of four ASPV proteins and for the first time provides insight into the functions of these proteins in the movement of a foveavirus.

Improving Signal and Transit Peptide Predictions Using AlphaFold2-predicted Protein Structures.

Many proteins contain cleavable signal or transit peptides that direct them to their final subcellular locations. Such peptides are usually predicted from sequence alone using methods such as TargetP 2.0 and SignalP 6.0. While these methods are usually very accurate, we show here that an analysis of a protein's AlphaFold2-predicted structure can often be used to identify false positive predictions. We start by showing that when given a protein's full-length sequence, AlphaFold2 builds experimentally annotated signal and transit peptides in orientations that point away from the main body of the protein. This indicates that AlphaFold2 correctly identifies that a signal is not destined to be part of the mature protein's structure and suggests, as a corollary, that predicted signals that AlphaFold2 folds with high confidence into the main body of the protein are likely to be false positives. To explore this idea, we analyzed predicted signal peptides in 48 proteomes made available in DeepMind's AlphaFold2 database (https://alphafold.ebi.ac.uk). Applying TargetP 2.0 and SignalP 6.0 to the 561,562 proteins in the database results in 95,236 being predicted to contain a cleavable signal or transit peptide. In 95.1% of these cases, the AlphaFold2 structure of the full-length protein is fully consistent with the prediction of TargetP 2.0 or SignalP 6.0. In the remaining 4.9% of cases where the AlphaFold2 structure does not appear consistent with the prediction, the signal is often only predicted with low confidence. The potential false positives identified here may be useful for training even more accurate signal prediction methods.

Integrated analysis of HSP20 genes in the developing flesh of peach: identification, expression profiling, and subcellular localization.

BACKGROUND: Plant HSP20s are not only synthesized in response to heat stress but are also involved in plant biotic and abiotic stress resistance, normal metabolism, development, differentiation, survival, ripening, and death. Thus, HSP20 family genes play very important and diverse roles in plants. To our knowledge, HSP20 family genes in peach have not yet been characterized in detail, and little is known about their possible function in the development of red flesh in peach. RESULTS: In total, 44 PpHSP20 members were identified in the peach genome in this study. Forty-four PpHSP20s were classified into 10 subfamilies, CI, CII, CIII, CV, CVI, CVII, MII, CP, ER, and Po, containing 18, 2, 2, 10, 5, 1, 1, 2, 1, and 2 proteins, respectively. Among the 44 PpHSP20 genes, 6, 4, 4, 3, 7, 11, 5, and 4 PpHSP20 genes were located on chromosomes 1 to 8, respectively. In particular, approximately 15 PpHSP20 genes were located at both termini or one terminus of each chromosome. A total of 15 tandem PpHSP20 genes were found in the peach genome, which belonged to five tandemly duplicated groups. Overall, among the three cultivars, the number of PpHSP20 genes with higher expression levels in red flesh was greater than that in yellow or white flesh. The expression profiling for most of the PpHSP20 genes in the red-fleshed 'BJ' was higher overall at the S3 stage than at the S2, S4-1, and S4-2 stages, with the S3 stage being a very important period of transformation from a white color to the gradual anthocyanin accumulation in the flesh of this cultivar. The subcellular localizations of 16 out of 19 selected PpHSP20 proteins were in accordance with the corresponding subfamily classification and naming. Additionally, to our knowledge, Prupe.3G034800.1 is the first HSP20 found in plants that has the dual targets of both the endoplasmic reticulum and nucleus. CONCLUSIONS: This study provides a comprehensive understanding of PpHSP20s, lays a foundation for future analyses of the unknown function of PpHSP20 family genes in red-fleshed peach fruit and advances our understanding of plant HSP20 genes.

Dual-Signal Feature Spaces Map Protein Subcellular Locations Based on Immunohistochemistry Image and Protein Sequence.

Protein is one of the primary biochemical macromolecular regulators in the compartmental cellular structure, and the subcellular locations of proteins can therefore provide information on the function of subcellular structures and physiological environments. Recently, data-driven systems have been developed to predict the subcellular location of proteins based on protein sequence, immunohistochemistry (IHC) images, or immunofluorescence (IF) images. However, the research on the fusion of multiple protein signals has received little attention. In this study, we developed a dual-signal computational protocol by incorporating IHC images into protein sequences to learn protein subcellular localization. Three major steps can be summarized as follows in this protocol: first, a benchmark database that includes 281 proteins sorted out from 4722 proteins of the Human Protein Atlas (HPA) and Swiss-Prot database, which is involved in the endoplasmic reticulum (ER), Golgi apparatus, cytosol, and nucleoplasm; second, discriminative feature operators were first employed to quantitate protein image-sequence samples that include IHC images and protein sequence; finally, the feature subspace of different protein signals is absorbed to construct multiple sub-classifiers via dimensionality reduction and binary relevance (BR), and multiple confidence derived from multiple sub-classifiers is adopted to decide subcellular location by the centralized voting mechanism at the decision layer. The experimental results indicated that the dual-signal model embedded IHC images and protein sequences outperformed the single-signal models with accuracy, precision, and recall of 75.41%, 80.38%, and 74.38%, respectively. It is enlightening for further research on protein subcellular location prediction under multi-signal fusion of protein.

HAR_Locator: a novel protein subcellular location prediction model of immunohistochemistry images based on hybrid attention modules and residual units.

Introduction: Proteins located in subcellular compartments have played an indispensable role in the physiological function of eukaryotic organisms. The pattern of protein subcellular localization is conducive to understanding the mechanism and function of proteins, contributing to investigating pathological changes of cells, and providing technical support for targeted drug research on human diseases. Automated systems based on featurization or representation learning and classifier design have attracted interest in predicting the subcellular location of proteins due to a considerable rise in proteins. However, large-scale, fine-grained protein microscopic images are prone to trapping and losing feature information in the general deep learning models, and the shallow features derived from statistical methods have weak supervision abilities. Methods: In this work, a novel model called HAR_Locator was developed to predict the subcellular location of proteins by concatenating multi-view abstract features and shallow features, whose advanced advantages are summarized in the following three protocols. Firstly, to get discriminative abstract feature information on protein subcellular location, an abstract feature extractor called HARnet based on Hybrid Attention modules and Residual units was proposed to relieve gradient dispersion and focus on protein-target regions. Secondly, it not only improves the supervision ability of image information but also enhances the generalization ability of the HAR_Locator through concatenating abstract features and shallow features. Finally, a multi-category multi-classifier decision system based on an Artificial Neural Network (ANN) was introduced to obtain the final output results of samples by fitting the most representative result from five subset predictors. Results: To evaluate the model, a collection of 6,778 immunohistochemistry (IHC) images from the Human Protein Atlas (HPA) database was used to present experimental results, and the accuracy, precision, and recall evaluation indicators were significantly increased to 84.73%, 84.77%, and 84.70%, respectively, compared with baseline predictors.

PFKP: More than phosphofructokinase.

Phosphofructokinase (PFK) is one of the key enzymes that functions in glycolysis. Studies show that PFKP regulates cell proliferation, apoptosis, autophagy, cell migration/metastasis, and stemness through glycolysis and glycolysis-independent functions. PFKP performs its function not only in the cytoplasm, but also at the cell membrane, on the mitochondria, at the lysosomal membrane, and in the nucleus. The functions of PFKP are extensively studied in cancer cells. PFKP is also highly expressed in certain immune cells; nevertheless, the study of the PFKP's role in immune cells is limited. In this review, we summarize how the expression and activity of PFKP are regulated in cancer cells. PFKP may be applied as a prognostic marker due to its overexpression and significant functions in cancer cells. As such, specifically targeting/inhibiting PFKP may be a critical and promising strategy for cancer therapy.

A Lean Reverse Vaccinology Pipeline with Publicly Available Bioinformatic Tools.

Reverse vaccinology (RV) marked an outstanding improvement in vaccinology employing bioinformatics tools to extract effective features from protein sequences to drive the selection of potential vaccine candidates (Rappuoli, Curr Opin Microbiol 3(5):445-450, 2000). Pioneered by Rino Rappuoli and first used against serogroup B meningococcus, since then, it has been used on several other bacterial vaccines, varying during time the adopted bioinformatics tools. Based on our experience in the field of RV and following an extensive literature review, we consolidate a lean RV pipeline of publicly available bioinformatic tools whose usage is described in this contribution. The protein features, whose extraction is reported in this contribution, can be also the input in a matrix format for machine learning-based approaches.

LcWRKY17, a WRKY Transcription Factor from Litsea cubeba, Effectively Promotes Monoterpene Synthesis.

The WRKY gene family is one of the most significant transcription factor (TF) families in higher plants and participates in many secondary metabolic processes in plants. Litsea cubeba (Lour.) Person is an important woody oil plant that is high in terpenoids. However, no studies have been conducted to investigate the WRKY TFs that regulate the synthesis of terpene in L. cubeba. This paper provides a comprehensive genomic analysis of the LcWRKYs. In the L. cubeba genome, 64 LcWRKY genes were discovered. According to a comparative phylogenetic study with Arabidopsis thaliana, these L. cubeba WRKYs were divided into three groups. Some LcWRKY genes may have arisen from gene duplication, but the majority of LcWRKY evolution has been driven by segmental duplication events. Based on transcriptome data, a consistent expression pattern of LcWRKY17 and terpene synthase LcTPS42 was found at different stages of L. cubeba fruit development. Furthermore, the function of LcWRKY17 was verified by subcellular localization and transient overexpression, and overexpression of LcWRKY17 promotes monoterpene synthesis. Meanwhile, dual-Luciferase and yeast one-hybrid (Y1H) experiments showed that the LcWRKY17 transcription factor binds to W-box motifs of LcTPS42 and enhances its transcription. In conclusion, this research provided a fundamental framework for future functional analysis of the WRKY gene families, as well as breeding improvement and the regulation of secondary metabolism in L. cubeba.

Unravel the regulatory mechanism of Yrr1p phosphorylation in response to vanillin stress in Saccharomyces cerevisiae.

Improving the resistance of Saccharomyces cerevisiae to vanillin, derived from lignin, will benefit the design of robust cell factories for lignocellulosic biorefining. The transcription factor Yrr1p mediates S. cerevisiae resistance to various compounds. In this study, eleven predicted phosphorylation sites were mutated, among which 4 mutants of Yrr1p, Y134A/E and T185A/E could improve vanillin resistance. Both dephosphorylated and phosphorylated mutations at Yrr1p 134 and 185 gathered in the nucleus regardless of the presence or absence of vanillin. However, the phosphorylated mutant Yrr1p inhibited target gene expression, while dephosphorylated mutants promoted expression. Transcriptomic analysis showed that the dephosphorylated Yrr1p T185 mutant, under vanillin stress, upregulated ribosome biogenesis and rRNA processing. These results demonstrate the mechanism by which Yrr1p phosphorylation regulates the expression of target genes. The identification of key phosphorylation sites in Yrr1p offers novel targets for the rational construction of Yrr1p mutants to improve resistance to other compounds.

Prediction of apoptosis protein subcellular location based on amphiphilic pseudo amino acid composition.

Introduction: Apoptosis proteins play an important role in the process of cell apoptosis, which makes the rate of cell proliferation and death reach a relative balance. The function of apoptosis protein is closely related to its subcellular location, it is of great significance to study the subcellular locations of apoptosis proteins. Many efforts in bioinformatics research have been aimed at predicting their subcellular location. However, the subcellular localization of apoptotic proteins needs to be carefully studied. Methods: In this paper, based on amphiphilic pseudo amino acid composition and support vector machine algorithm, a new method was proposed for the prediction of apoptosis proteins\x{2019} subcellular location. Results and Discussion: The method achieved good performance on three data sets. The Jackknife test accuracy of the three data sets reached 90.5%, 93.9% and 84.0%, respectively. Compared with previous methods, the prediction accuracies of APACC_SVM were improved.

Novel Epitopes Mapping of African Swine Fever Virus CP312R Protein Using Monoclonal Antibodies.

African Swine Fever (ASF) is a highly contagious and lethal pig disease and poses a huge threat to the pig industry worldwide. ASF virus (ASFV) encodes more than 150 different proteins, but the biological properties of most viral proteins are still unknown. ASFV CP312R protein has been proven to be one of the most immunogenic proteins during ASFV infection in pigs; however, its specific epitopes have yet to be identified. In this study, we verified the immunogenicity of CP312R protein in the sera from attenuated ASFV-inoculated pigs. We generated seven anti-ASFV CP312R mouse monoclonal antibodies (mAbs) from mice immunized with recombinant CP312R protein (rCP312R). All seven mAbs are the IgG2b-Kappa isotype and specifically interacted with the CP312R protein expressed in various cells that were infected by ASFVs or transfected with plasmid CP312R. The epitope mapping was performed by using these characterized mAbs and the peptide scanning (Pepscan) method followed by Western blot. As a result, two antigenic determinant regions were identified: two of the seven mAbs recognized the 122KNEQGEEIYP131 amino acids, and the remaining five mAbs recognized the 78DEEVIRMNAE87 amino acids of the CP312R protein. These antigenic determinants of CP312R are conserved in different ASFV strains of seven genotypes. By using the characterized mAb, confocal microscopy observation revealed that the CP312R was mainly localized in the cytoplasm and, to some extent, in nuclei and on the nuclear membrane of infected host cells. In summary, our results benefit our understanding on the antigenic regions of ASFV CP312R and help to develop better serological diagnosis of ASF and vaccine research.

Construction of eukaryotic expression plasmid of human promyelocytic leukemia gene of six transcripts and subcellular location analysis of its recombinant proteins / 中国生物制品学杂志

@#Objective To construct eukaryotic expression plasmids of human promyelocytic leukaemia(hPML) gene of six transcripts and analyze the subcellular location of the recombinant proteins.Methods Primers were designed according to the hPML gene sequences registered in GenBank databases.Six transcripts of hPML gene fragments(hPML Ⅰ,Ⅱ,Ⅳ,Ⅴ,Ⅵ and Ⅶ) were amplified by RT-PCR,which were linked to the eukaryotic expression vector pCAGGS respectively.The obtained eukaryotic expression plasmids of six transcripts of hPML gene were transfected into 293T cells respectively and detected for their protein expression by Western blot,while transfected into Vero cells and detected for their subcellular location by indirect immunofluorescence assay(IFA).Results The target gene fragments of the six eukaryotic expression plasmids were consistent with the hPML gene sequences registered in GenBank.All the six recombinant proteins showed specific binding with Myc antibody,among which the recombinant protein hPML Ⅰ,Ⅱ,Ⅳ,Ⅴ and Ⅵ were located in the nucleus and cytoplasm,while the recombinant protein hPML Ⅶ was mainly located in the cytoplasm,rarely in the nucleus.Conclusion The eukaryotic expression plasmids of six transcripts of hPML gene all can be expressed correctly in mammalian cells,and the expressed recombinant proteins were located in nucleus and cytoplasm simultaneously or mainly in cytoplasm.This study provides an experimental basis for subsequent study on the antiviral and other biological functions of recombinant protein hPML.

G3BP2: Structure and function.

Ras-GAP SH3 domain binding proteins (G3BPs) are a family of RNA-binding proteins that include G3BP1 and G3BP2 in mammals. The protein structure of G3BP2 allows it to bind with RNA or protein and regulate the nucleoplasmic shuttle, therefore participating in a variety of biological functions such as cell growth, differentiation and migration, and RNA and protein metabolism. G3BP2 is abnormally expressed in many tumors and diseases, such as breast cancer, lung cancer, prostate cancer, cardiac hypertrophy, and atherosclerosis. Many researchers have found that G3BP2 may be a potential therapeutic target. In this review, we examine the structure and expression regulation of G3BP2, and further summarize the function of G3BP2 from three aspects: RNA stabilization, protein subcellular localization, and stress granules assembling to provide a broader understanding of the role of G3BP2.

Dual-Functionalized Nanoliposomes Achieve a Synergistic Chemo-Phototherapeutic Effect.

The enhancement of photodynamic therapy (PDT) effectiveness by combining it with other treatment modalities and improved drug delivery has become an interesting field in cancer research. We have prepared and characterized nanoliposomes containing the chemotherapeutic drug irinotecan (CPT11lip), the photodynamic agent protoporphyrin IX (PpIXlip), or their combination (CPT11-PpIXlip). The effects of individual and bimodal (chemo-phototherapeutic) treatments on HeLa cells have been studied by a combination of biological and photophysical studies. Bimodal treatments show synergistic cytotoxic effects on HeLa cells at relatively low doses of PpIX/PDT and CPT11. Mechanistic cell inactivation studies revealed mitotic catastrophe, apoptosis, and senescence contributions. The enhanced anticancer activity is due to a sustained generation of reactive oxygen species, which increases the number of double-strand DNA breaks. Bimodal chemo-phototherapeutic liposomes may have a very promising future in oncological therapy, potentially allowing a reduction in the CPT11 concentration required to achieve a therapeutic effect and overcoming resistance to individual cancer treatments.

Identification and functional characterization of complement regulatory protein CD59 in golden pompano (Trachinotus ovatus).

CD59, one of the essential inhibitors of the complement membrane attack complex (MAC), plays a crucial role in regulation of complement activation. In this study, we cloned and identified the CD59 gene (named ToCD59) of golden pompano (Trachinotus ovatus). The ORF sequence of ToCD59 is 357 bp long encoding 118 amino acids with a molecular weight of 13.09 kDa. Prediction of protein domains showed that ToCD59 contained an Lu domain and a C-terminal glycosylphosphatidylinositol (GPI) partial anchor. Homology comparisons indicated that ToCD59 shared the high sequence similarity with other fish CD59. RT-qPCR analysis showed that ToCD59 was expressed in all tested healthy tissues of golden pompano, with the highest level of expression in the brain. After stimulation with bacteria, ToCD59 expression levels were significantly up-regulated in head kidney, liver, gill and brain, but down-regulated in spleen. Subcellular localization results showed that ToCD59 localized to the cytoplasm of A549 cells. The hemolytic activity analysis showed that rToCD59 might have complement inhibitory activity through the alternative complement pathway. In addition, antibacterial test showed that rToCD59 had antibacterial ability against S. agalactiae and V. alginolyticus in vitro. These results suggest that ToCD59 might play an important role in the immune response against pathogens, which would provide basic information for elucidating the functional evolutionary history of complement system in teleost.

Leader gene identification for digestive system cancers based on human subcellular location and cancer-related characteristics in protein-protein interaction networks.

Stomach, liver, and colon cancers are the most common digestive system cancers leading to mortality. Cancer leader genes were identified in the current study as the genes that contribute to tumor initiation and could shed light on the molecular mechanisms in tumorigenesis. An integrated procedure was proposed to identify cancer leader genes based on subcellular location information and cancer-related characteristics considering the effects of nodes on their neighbors in human protein-protein interaction networks. A total of 69, 43, and 64 leader genes were identified for stomach, liver, and colon cancers, respectively. Furthermore, literature reviews and experimental data including protein expression levels and independent datasets from other databases all verified their association with corresponding cancer types. These final leader genes were expected to be used as diagnostic biomarkers and targets for new treatment strategies. The procedure for identifying cancer leader genes could be expanded to open up a window into the mechanisms, early diagnosis, and treatment of other cancer types.

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.

The role of spatiotemporal organization and dynamics of clock complexes in circadian regulation.

Circadian clocks are cell autonomous timekeepers that regulate ∼24-h oscillations in the expression of many genes and control rhythms in nearly all our behavior and physiology. Almost every cell in the human body has a molecular clock and networks of cells containing clock proteins orchestrate daily rhythms in many physiological processes, from sleep-wake cycles to metabolism to immunity. All eukaryotic circadian clocks are based on transcription-translation delayed negative feedback loops in which activation of core clock genes is negatively regulated by their cognate protein products. Our current understanding of circadian clocks has been accumulated from decades of genetic and biochemical experiments, however, what remains poorly understood is how clock proteins, genes, and mRNAs are spatiotemporally organized within live clock cells and how such subcellular organization affects circadian rhythms at the single cell level. Here, we review recent progress in understanding how clock proteins and genes are spatially organized within clock cells over the circadian cycle and the role of such organization in generating circadian rhythms and highlight open questions for future studies.