Biology subjects

Yuan, Y.

Publications and source records attributed to Yuan, Y..

At least 253 records · Page 14Linked to original sources

bioRxiv2021

Development of a mini-replicon-based reverse-genetics system for rice stripe tenuivirus

Negative-stranded RNA (NSR) viruses include both animal- and plant-infecting viruses that often cause serious diseases in human and livestock, and in agronomic crops. Rice stripe tenuivirus (RSV), a plant NSR virus with four negative-stranded/ambisense RNA segments, is one of the most destructive rice pathogens in many Asian countries. Due to the lack of a reliable reverse-genetics technology, molecular studies of RSV gene functions and its interaction with host plants are severely hampered. To overcome this obstacle, we developed a mini-replicon-based reverse-genetics system for RSV gene functional analysis in Nicotiana benthamiana. We first developed a mini-replicon system expressing RSV genomic RNA3 eGFP reporter (MR3(-)eGFP), a nucleocapsid (NP), and a codon usage optimized RNA-dependent RNA polymerase (RdRpopt), respectively. Using this mini-replicon system we determined that RSV NP and RdRpopt are indispensable for the eGFP expression from MR3(-)eGFP. The expression of eGFP from MR3(-)eGFP can be significantly enhanced in the presence of NSs and P19-HcPro-{gamma}b. In addition, NSvc4, the movement protein of RSV, facilitated eGFP trafficking between cells. We also developed an antigenomic RNA3-based replicon in N. benthamiana. However, we found that the RSV NS3 coding sequence acts as a cis-element to regulate viral RNA expression. Finally, we made mini-replicons representing all four RSV genomic RNAs. This is the first mini-replicon-based reverse-genetics system for monocot-infecting tenuivirus. We believe that this mini-replicon system described here will allow the studies of RSV replication, transcription, cell-to-cell movement and host machinery underpinning RSV infection in plants. IMPORTANCEPlant-infecting segmented negative-stranded RNA (NSR) viruses are grouped into 3 genera: Orthotospovirus, Tenuivirus and Emaravirus. The reverse-genetics systems have been established for members in the genera Orthotospovirus and Emaravirus, respectively. However, there is still no reverse-genetics system available for Tenuivirus. Rice stripe virus (RSV) is a monocot-infecting tenuivirus with four negative-stranded/ambisense RNA segments. It is one of the most destructive rice pathogens and causes significant damages to rice industry in Asian countries. Due to the lack of a reliable reverse-genetics system, molecular characterizations of RSV gene functions and the host machinery underpinning RSV infection in plants are extremely difficult. To overcome this obstacle, we developed a mini-replicon-based reverse-genetics system for RSV in Nicotiana benthamiana. This is the first mini-replicon-based reverse-genetics system for tenuivirus. We consider that this system will provide researchers a new working platform to elucidate the molecular mechanisms dictating segmented tenuivirus infections in plant.

pathology↗

bioRxiv2021

Discovery of Dynamical Network Models for Genetic Circuits from Time-Series Data with Incomplete Measurements

Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector.

synthetic biology↗

bioRxiv2021

Cell Type Assignments for Spatial Transcriptomics Data

MotivationRecent advancements in fluorescence in situ hybridization (FISH) techniques enable them to concurrently obtain information on the location and gene expression of single cells. A key question in the initial analysis of such spatial transcriptomics data is the assignment of cell types. To date, most studies used methods that only rely on the expression levels of the genes in each cell for such assignments. To fully utilize the data and to improve the ability to identify novel sub-types we developed a new method, FICT, which combines both expression and neighborhood information when assigning cell types. ResultsFICT optimizes a probabilistic function that we formalize and for which we provide learning and inference algorithms. We used FICT to analyze both simulated and several real spatial transcriptomics data. As we show, FICT can accurately identify cell types and sub-types improving on expression only methods and other methods proposed for clustering spatial transcriptomics data. Some of the spatial sub-types identified by FICT provide novel hypotheses about the new functions for excitatory and inhibitory neurons. AvailabilityFICT is available at: https://github.com/haotianteng/FICT Contactzivbj@andrew.cmu.edu

bioinformatics↗

bioRxiv2021

CINS: Cell Interaction Network inference from Single cell expression data

Studies comparing single cell RNA-Seq (scRNA-Seq) data between conditions mainly focus on differences in the proportion of cell types or on differentially expressed genes. In many cases these differences are driven by changes in cell interactions which are challenging to infer without spatial information. To determine cell-cell interactions that differ between conditions we developed the Cell Interaction Network Inference (CINS) pipeline. CINS combines Bayesian network analysis with regression-based modeling to identify differential cell type interactions and the proteins that underlie them. We tested CINS on a disease case control and on an aging human dataset. In both cases CINS correctly identifies cell type interactions and the ligands involved in these interactions. We performed additional mouse aging scRNA-Seq experiments which further support the interactions identified by CINS.

bioinformatics↗

bioRxiv2021

LncRNA SNHG1 suppresses LPS-induced acute lung injury by regulating miR-421/TIMP3 axis

Extensive evidence has revealed the crucial roles of long non-coding RNAs (lncRNAs) in acute lung injury (ALI). This study aimed to explore the mechanism of lncRNA SNHG1 in lipopolysaccharides (LPS)-induced ALI. RT-qPCR was employed to test the levels of SNHG1, miR-421 and TIMP3 in A549 cells. Cell viability and apoptosis were assessed by CCK-8 assay and flow cytometry. ELISA assay was adopted to examine the levels of inflammatory-related cytokines, including IL-1{beta}, IL-6 and TNF-. The binding sequences of miR-421 and SNHG1 or TIMP3 were predicted using starBase software. Then dual-luciferase reporter and RIP assays were adopted to verify the interaction between miR-421 and SNHG1 or TIMP3. The protein level of TIMP3 was measured by western blotting. It was found that LPS stimulation downregulated SNHG1 level and SNHG1 addition decreased viability, and induced apoptosis as well as promoted inflammatory responses in LPS-treated A549 cells. SNHG1 could sponge miR-421 and SNHG1 protected A549 cells from LPS-induced injury via inhibiting miR-421. Moreover, TIMP3 was a target of miR-421. MiR-421 silence protected A549 cells against the LPS-triggered inhibition in viability, and promotion in apoptosis and inflammatory responses. SNHG1 could upregulate TIMP3 through acting as a ceRNA of miR-421 in A549 cells. Altogether, the present study elaborated that SNHG1 inhibited LPS-stimulated ALI by modulating the miR-421/TIMP3 axis.

immunology↗

bioRxiv2021

SENP1 in the retrosplenial agranular cortex regulates core autistic-like symptoms in mice

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder, in which core symptoms are defects of social interaction and evidently repetitive behaviors. Although around 50-70 % of ASD patients have comorbidity of intellectual disabilities (ID) or developmental delay (DD), there are some ASD patients who exhibit only core symptoms but without ID/DD, raising the question whether there are genetic components and neural circuits specific for core symptoms of ASD. Here, by focusing on ASD patients who do not show compound ID or DD, we identified a de novo heterozygous gene-truncating mutation of the Sentrin-specific peptidase1 (SENP1) gene, coding the small ubiquitin-like modifiers (SUMO) deconjugating enzyme, as a potentially new candidate gene for ASD. We found that Senp1 haploinsufficient mice exhibited core symptoms of autism such as deficits in social interaction and repetitive behaviors, but normal learning and memory ability. Moreover, we found that the inhibitory and excitatory synaptic functions were severely affected in the retrosplenial agranular (RSA) cortex of Senp1 haploinsufficient mice. Lack of Senp1 led to over SUMOylation and degradation of fragile X mental retardation protein (FMRP) proteins, which is coded by the FMR1 gene, also implicated in syndromic ASD. Importantly, re-introducing SENP1 or FMRP specifically in RSA fully rescued the defects of synaptic functions and core autistic-like symptoms of Senp1 haploinsufficient mice. Together, these results demonstrated that disruption of the SENP1-FMRP regulatory axis in the RSA may cause core autistic symptoms, which provide a candidate brain region of ASD for potential therapeutic intervene by neural modulation approaches.

neuroscience↗

bioRxiv2021

Large field of view-spatially resolved transcriptomics at nanoscale resolution

Spatially resolved transcriptomic technologies are promising tools to study cell fate decisions in a physical microenvironment, which is fundamental for enhancing our knowledge of mammalian development. However, the imbalance between resolution, transcript capture and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation mammalian embryos. Here, we combined DNA nanoball (DNB) patterned arrays and tissue RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution and sensitivity. We have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in a time course of mouse organogenesis. We used this information to gain insight into the molecular basis of regional specification, neuronal migration and differentiation in the developing brain. Furthermore, we mapped the expression of a panel of developmental disease-related loci on our global transcriptomic maps to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal mammalian development.

cell biology↗

bioRxiv2021

Reconstructing tumor trajectories during therapy through integration of multiple measurement modalities.

BackgroundAccurately determining changes in tumor size during therapy is essential to evaluating response or progression. However, individual imaging methodologies often poorly reflect pathologic response and long-term treatment efficacy in patients with estrogen receptor positive (ER+) early-stage breast cancer. Mathematical models that measure tumor progression over time by integrating diverse imaging and tumor measurement modalities are not currently used but could increase accuracy in measuring response and provide biological insights into cancer evolution. MethodsFor ER+ breast cancer patients enrolled on a neoadjuvant clinical trial, we reconstructed their tumor size trajectories during therapy by combining all available information on tumor size, including different imaging modalities, physical examinations and pathological assessment data. Tumor trajectories during six months of treatment were generated, using a Gaussian process and the most probable trajectories were evaluated, based on clinical data, using measurement models that account for biases and differences in precision between tumor measurement methods, such as MRI, ultrasound and mammograms. ResultsReconstruction of tumor trajectories during treatment identified five distinct patterns of tumor size changes, including rebound growth not evident from any single modality. These results increase specificity to distinguish innate or acquired resistance compared to using any single measurement alone. The speed of therapeutic response and extent of subsequent rebound tumor growth quantify sensitivity or resistance in this patient population. ConclusionsTumor trajectory reconstruction integrating multiple modalities of tumor measurement accurately describes tumor progression on therapy and reveals various patterns of patient responses. Mathematical models can integrate diverse response assessments and account for biases in tumor measurement, thereby providing insights into the timing and rate at which resistance emerges.

systems biology↗

bioRxiv2021

Identification of Nocardia species using Autof MS 1000 and Bruker MALDI-TOF MS systems: A comparison

Nocardia is an important cause of clinically invasive disease, but for most clinical laboratories, identification of these isolates to the species level is challenging. Recently, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been widely used for identification of most bacterial and fungal isolates. In this multicenter study, we evaluated the identification of Nocardia isolates using Autof MS1000 and Bruker Biotyper. A total of 86 non-duplicate Nocardia isolates from 7 hospital laboratories were evaluated. Further, we carried out sequence analysis of 16S rRNA, gyrB, secA1, hsp65, and rpoB genes as a reference method for Nocardia species identification. The 86 isolates were directly spotted on the target plate and plate protein extraction was performed. Data were analyzed by SPSS 19.0. In total, 72 (83.7%) strains (score [≥] 9.0) and 70 (81.4%) strains (score [≥] 2.0) were correctly identified by the Autof MS1000 and Bruker Biotyper systems, respectively, at the species level. There was no significant difference (P > 0.05) between the two systems using the same protein extraction method. In conclusion, the Autof MS 1000 and Bruker MALDI-TOF systems showed no difference in identification of Nocardia spp. to the species level and could meet the most important clinical requirement for species identification.

microbiology↗

bioRxiv2021

Single-molecule super-resolution imaging of T-cell plasma membrane CD4 redistribution upon HIV-1 binding

The first step of cellular entry for the human immunodeficiency virus type-1 (HIV-1) occurs through the binding of its envelope protein (Env) with the plasma membrane receptor CD4 and co-receptor CCR5 or CXCR4 on susceptible cells, primarily CD4+ T cells and macrophages. Although there is considerable knowledge of the molecular interactions between Env and host cell receptors that lead to successful fusion, the precise way in which HIV-1 receptors redistribute to sites of virus binding at the nanoscale remains unknown. Here, we quantitatively examine changes in the nanoscale organisation of CD4 on the surface of CD4+ T cells following HIV-1 binding. Using single-molecule super-resolution imaging, we show that CD4 molecules are distributed mostly as either individual molecules or small clusters of up to 4 molecules. Following virus binding, we observe a local 3-to-10-fold increase in cluster diameter and molecule number for virus-associated CD4 clusters. Moreover, a similar but smaller magnitude reorganisation of CD4 was also observed with recombinant gp120. For the first time, our results quantify the nanoscale CD4 reorganisation triggered by HIV-1 on host cells. Our quantitative approach provides a robust methodology for characterising the nanoscale organisation of plasma membrane receptors in general with the potential to link spatial organisation to function.

biophysics↗

bioRxiv2020

YAP1-TAZ/TEAD transcriptional networks restrain differentiation downstream of oncogenic Hedgehog-SMO activity

Disruption of the transcriptional activity of the Hippo pathway members YAP1 and TAZ has become a major target for cancer treatment. However, detailed analysis of the effectivity and networks affected by YAP1/TAZ transcriptional targeting are limited. Here, by comparing the effects of YAP1/TAZ knockdown with those resulting from TEAD blockage, we unveil the consequences of YAP1/TAZ transcriptional inhibition in cancer cells. We utilize TEADi, an inhibitor of the binding of YAP1 and TAZ with their main transcriptional target TEAD. In a mouse model of basal cell carcinoma (BCC) driven by the smoothened oncogene (SmoM2), TEADi and YAP1/TAZ knockdown lead to reduced proliferation and increased differentiation of tumor cells both in vitro and in vivo. We find that TEAD transcriptional networks inactivate differentiation in BCC by regulating KLF4. Furthermore, we determine YAP1/TAZ TEAD-independent effects in cancer cells that impact Stat3 and NF-{kappa}B gene networks. Our results reveal the TEAD dependent and independent roles of YAP1/TAZ in cancer and expose potential pitfalls for targeting TEAD transcription in tumors.

cancer biology↗

bioRxiv2020

Super-robust data storage in DNA by de Bruijn graph-based decoding

DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as the strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. Through a de novo assembly strategy, we developed an algorithm based on the de Bruijn graph and greedy path search (DBGPS) to address these issues. DBGPS shows distinct advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large data scale simulations. Remarkably, 6.8 MB of data can be retrieved accurately from a seriously corrupted sample that has been treated at 70 {degrees}C for 70 days. With DBGPS, we were able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g. One-Sentence SummaryA de Bruijn graph-based de novo assembly algorithm for DNA data storage enables fast and robust data readouts even with DNA samples that have been severely corrupted.

bioinformatics↗

bioRxiv2020

Kaposi's Sarcoma Herpesvirus Is Associated with Osteosarcoma in Xinjiang Uyghur Population

Osteosarcoma is the most common malignant tumor of bone predominately affecting adolescents and young adults. Viral etiology of osteosarcoma has been proposed more than a half-century ago but never been proven by identifying any virus authentically associated with human osteosarcoma. The Uyghur ethnic population in Xinjiang China has an unusually high prevalence of Kaposis sarcoma-associated herpesvirus (KSHV) infection and elevated incidence of osteosarcoma. In the current study, we explored the possible association of KSHV infection and osteosarcoma occurrence. Our seroepidemiological study revealed that KSHV prevalence was significantly elevated in osteosarcoma patients versus the general population in the Xinjiang Uyghur population (OR, 10.23; 95%CI, 4.25, 18.89). The KSHV DNA genome and viral latent nuclear antigen LANA were detected in most osteosarcoma tumor cells. Gene expression profiling analysis showed that KSHV positive osteosarcoma represents a distinct subtype of osteosarcomas with viral gene-driven signaling pathways that are important for osteosarcoma development. We conclude that KSHV infection is a risk factor for osteosarcoma and KSHV is associated with some osteosarcomas, representing a newly identified viral-associated endemic cancer. SignificanceViral etiology of osteosarcoma was proposed previously but has never been proven by identifying any virus that is authentically associated with human osteosarcoma. The current study revealed an association of human osteosarcoma with KSHV infection in Uyghur osteosarcoma patients. First, this study provides the first evidence that supports the possible viral etiology of human osteosarcoma. The gene expression profiling study showed that KSHV-positive osteosarcoma represents a distinct subtype of osteosarcomas, which is of diagnostic, prognostic and therapeutic significance. Second, KSHV-associated osteosarcomas preferentially occur in children and young adults, predicting that KSHV-positive children in KSHV endemic region may be at great risk for osteosarcoma. Third, the finding extended the range of human cancers associated with viruses.

microbiology↗

bioRxiv2020

Single-cell Multi-omics reveal heterogeneity and metastasis potential in different liver cancer cell lines

Hepatocellular carcinoma (HCC) is a malignant neo-plasm with a high recurrence and metastatic rate, accounted for poor prognosis. Commonly existed heterogeneity is concerned with neoplasia, cancer progression, therapeutic resistance and metastasis is the principal cause of cancer lethality. As development of multi-omics methods in single-cell technology provides multi-faceted insight into disease processes in the era of precision medicine. Here, we interrogated single-cell transcriptomes, proteomes and epigenetic information, revealing metastasis potential heterogeneity in 5 HCC cell lines across different metastasis capacity. We confirmed that higher mesenchymal (M) status but not proliferation rate was associated with stronger metastasis ability of cell lines. Besides, we identified a subgroup being common in several cell lines, showing a higher hypoxic signature. A gene set involving 14 genes were chosen to represent the hypoxia state, much consistent than previous reported gene set, and showed worse prognosis association in TCGA data. This hypoxic subgroup prefers glycolysis metabolism than OXPO, and showed non-cycling, quiescent state which could be resistant to many proliferation-targeting drugs. Our results provide a comprehensive understanding of characteristic associated with metastasis capacity of HCC cell line, which will guide the metastasis mechanism study of HCC.

cancer biology↗

bioRxiv2020

Activated Expression of Master Regulator MYB31 and of Capsaicinoid Biosynthesis Genes Results in Capsaicinoid Biosynthesis and Accumulation in the Pericarp of the Extremely Pungent Capsicum chinense

Capsaicinoids confer pungency in Capsicum fruits, and the capsaicinoid content varies greatly among the five domesticated Capsicum species. Although it is generally recognized that capsaicinoid biosynthesis occurs exclusively in the placenta, few studies have focused on capsaicinoid biosynthesis gene (CBG) expression in the pericarp. Therefore, the transcriptional regulation mechanisms of capsaicinoid biosynthesis in the pericarp remain elusive. Here, the capsaicinoid contents of 32 accessions from five domesticated Capsicum species were analyzed. The results showed that the capsaicinoid contents of C. chinense accessions are significantly higher than those of the other four Capsicum species due to the increased accumulation of capsaicinoids, especially in the pericarp. Compared to that in accessions with low pericarp capsaicinoid content, the expression of the master regulator MYB31 is significantly upregulated in the pericarp in C. chinense accessions, which leads to high levels of CBG expression. Moreover, in fruits of the extremely pungent Trinidad Moruga Scorpion (C. chinense) and low-pungency 59 inbred line (C. annuum) at different developmental stages, the capsaicinoid accumulation patterns were consistent with the MYB31 and CBG expression levels in the pericarp. Taken together, our results provide novel insights into the molecular mechanism arising from the expression of a master regulator in the pericarp that results in exceedingly hot peppers. The genetic resources identified in this study could be used as genetic resources for the genetic improvement of pepper pungency.

plant biology↗

bioRxiv2020

Integrated Single Cell Atlas of Endothelial Cells of the Human Lung

BackgroundDespite its importance in health and disease, the cellular diversity of the lung endothelium has not been systematically characterized in humans. Here we provide a reference atlas of human lung endothelial cells (ECs), to facilitate a better understanding of the phenotypic diversity and composition of cells comprising the lung endothelium, both in health and disease. MethodsWe reprocessed control single cell RNA sequencing (scRNAseq) data from five datasets of whole lungs that were used for the analysis of pan-endothelial markers, we later included a sixth dataset of sorted control EC for the vascular subpopulation analysis. EC populations were characterized through iterative clustering with subsequent differential expression analysis. Marker genes were validated by immunohistochemistry and in situ hybridization. Signaling network between different lung cell types was studied using connectomic analysis. For cross species analysis we applied the same methods to scRNAseq data obtained from mouse lungs. ResultsThe six lung scRNAseq datasets were reanalyzed and annotated to identify over 15,000 vascular EC cells from 73 individuals. Differential expression analysis of EC revealed signatures corresponding to endothelial lineage, including pan-endothelial, pan-vascular and subpopulation-specific marker gene sets. Beyond the broad cellular categories of lymphatic, capillary, arterial and venous ECs we found previously indistinguishable subpopulations; among venous EC we identified two previously indistinguishable populations, pulmonary-venous ECs (COL15A1neg) localized to the lung parenchyma and systemic-venous ECs (COL15A1pos) localized to the airways and the visceral pleura; among capillary EC we confirmed their subclassification into recently discovered aerocytes characterized by EDNRB, SOSTDC1 and TBX2 and general capillary EC. We confirmed that all six endothelial cell types, including the systemic-venous EC and aerocytes are present in mice and identified endothelial marker genes conserved in humans and mice. Ligand-Receptor connectome analysis revealed important homeostatic crosstalk of EC with other lung resident cell types. Our manuscript is accompanied by an online data mining tool (www.LungEndothelialCellAtlas.com). ConclusionOur integrated analysis provides the comprehensive and well-crafted reference atlas of lung endothelial cells in the normal lung and confirms and describes in detail previously unrecognized endothelial populations across a large number of humans and mice.

cell biology↗

bioRxiv2020

Light transport modeling in highly complex tissues using implicit mesh-based Monte Carlo algorithm

The mesh-based Monte Carlo (MMC) technique has grown tremendously since its initial publication nearly a decade ago. It is now recognized as one of the most accurate Monte Carlo (MC) methods, providing accurate reference solutions for the development of novel biophotonics techniques. In this work, we aim to further advance MMC to address a major challenge in biophotonics modeling, i.e. light transport within highly complex tissues, such as dense microvascular networks, porous media and multi-scale tissue structures. Although the current MMC framework is capable of simulating light propagation in such media given its generality, the run-time and memory usage grow rapidly with increasing media complexity and size. This greatly limits our capability to explore complex and multi-scale tissue structures. Here, we propose a highly efficient implicit mesh-based Monte Carlo (iMMC) method that incorporates both mesh- and shape-based tissue representations to create highly complex yet memory efficient light transport simulations. We demonstrate that iMMC is capable of providing accurate solutions for dense vessel networks and porous tissues while reducing memory usage by greater than a hundred- or even thousand-fold. In a sample network of microvasculature, the reduced shape complexity results in nearly 3x speed acceleration. The proposed algorithm is now available in our open-source MMC software at http://mcx.space/#mmc.

biophysics↗

bioRxiv2020

Clock proteins regulate spatiotemporal organization of clock genes to control circadian rhythms

Circadian clocks regulate [~]24 hour oscillations in gene expression, behavior, and physiology. While the molecular and neural mechanisms of circadian rhythms are well characterized, how cellular organization of clock components controls circadian clock regulation remains poorly understood. Here, we elucidate how clock proteins regulate circadian rhythms by controlling the spatiotemporal organization of clock genes. Using high-resolution live imaging techniques we demonstrate that Drosophila clock proteins are concentrated in a few discrete foci and are organized at the nuclear envelope; these results are in contrast to longstanding expectations that clock proteins are diffusely distributed in the nucleus. We also show that clock protein foci are highly dynamic and change in number, size, and localization over the circadian cycle. Further, we demonstrate that clock genes are positioned at the nuclear periphery by the clock proteins precisely during the circadian repression phase, suggesting that subnuclear localization of clock genes plays an important role in the control of rhythmic gene expression. Finally, we show that Lamin B receptor, a nuclear envelope protein, is required for peripheral localization of clock protein foci and clock genes and for normal circadian rhythms. These results reveal that clock proteins form dynamic nuclear foci and play a hitherto unexpected role in the subnuclear reorganization of clock genes to control circadian rhythms, identifying a novel mechanism of circadian regulation. Our results further suggest a new role for clock protein foci in the clustering of clock-regulated genes during the repression phase to control gene co-regulation and circadian rhythms. SIGNIFICANCEAlmost all living organisms have evolved circadian clocks to tell time. Circadian clocks regulate [~]24-hour oscillations in gene expression, behavior and physiology. Here, we reveal the surprisingly sophisticated spatiotemporal organization of clock proteins and clock genes and its critical role in circadian clock function. We show, in contrast to current expectations, that clock proteins are concentrated in a few discrete, dynamic nuclear foci at the nuclear envelope during the repression phase. Further, we uncovered several unexpected features of clock protein foci, including their role in positioning the clock genes at the nuclear envelope precisely during the repression phase to enable circadian rhythms. These studies provide fundamental new insights into the cellular mechanisms of circadian rhythms and establish direct links between nuclear organization and circadian clocks.

neuroscience↗