Biology subjects

Jiang, Y.

Publications and source records attributed to Jiang, Y..

At least 379 records · Page 21Linked to original sources

bioRxiv2022

Structural Genomics of the Human Dopamine Receptor System

The dopamine system, including five dopamine receptors (D1R to D5R), plays essential roles in the central nervous system (CNS) and ligands that activate dopamine receptors have been used to treat many neuropsychiatric disorders, including Parkinsons Disease (PD) and schizophrenia. Here, we report five cryo-EM structures of all subtypes of human dopamine receptors in complex with G-protein and bound to the pan agonist, Rotigotine, which is used to treat PD and restless legs syndrome. The structures reveal the basis of Rotigotine binding modes to different dopamine receptors. Structural analysis together with functional assays illuminate determinants of ligand polypharmacology and selectivity. The structures also uncover the mechanisms of the dopamine receptor activation, unique structural features among the five receptor subtypes, and the basis of G-protein coupling specificity. Our works provide a comprehensive set of structural templates for the rational design of specific ligands to treat CNS diseases targeting the dopaminergic system.

biochemistry↗

bioRxiv2022

CryoFIB milling large tissue samples for cryo-electron tomography

Cryo-electron tomography (cryoET), a powerful tool for exploring the molecular structure of large organisms. However, technical challenges still limit cryoET applications on large samples. In particular, locating and cutting out objects of interest from a large tissue sample is an important but difficult step. In this study, we report a sample thinning strategy and workflow for tissue samples based on cryo-focused ion beam (cryoFIB) milling. This workflow provides a full solution for isolating objects of interest by starting from a millimeter-sized tissue sample and ending with hundred-nanometer thin lamellae. The workflow involves sample fixation, pre-sectioning, a two-step milling strategy, and locating the object of interest using cellular secondary electron imaging (CSEI). The two-step milling strategy introduces a coarse milling method to solve the milling efficiency problem for samples as thick as tens of microns, followed by a fine milling method to create a furrow-ridge structure. The furrow-ridge structure guarantees the generation of large, thin lamellae with enhanced mechanical stability and charge-reducing design. CSEI is highlighted in the workflow, which provides conventional, on-the-fly locating during cryoFIB milling. Tests of the complete workflow were conducted to demonstrate the high efficiency and high feasibility of the proposed method.

biophysics↗

bioRxiv2022

Effects of protoscoleces excretory-secretory products of Echinococcus granulosus on hepatocyte growth, function, and glucose metabolism

Cystic echinococcosis (CE) is one of the most widespread and harmful zoonotic parasitic diseases and it most commonly affects the liver. In this study, we characterized multiple changes in mouse hepatocytes following treatment with excretory-secretory (ES) products of Echinococcus granulosus protoscoleces by a factorial experiment. The cell counting kit-8 assay (CCK-8), the 5-ethynyl-2-deoxyuridine (EdU) assay, and flow cytometry were used to detect the growth of hepatocytes. Inverted microscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) were used to observe the morphology and ultrastructure of hepatocytes. An automatic biochemical analyzer and an ELISA detection kit were used to determine six conventional hepatocyte enzymatic indices, the levels of five hepatocyte-synthesized substances, and the contents of glucose and lactate. Western blot analysis was conducted to analyze the protein expression of six rate-limiting enzymes in the glucose metabolism pathway in hepatocytes: glutamic-pyruvic transaminase (ALT), glutamic-oxalacetic transaminase (AST), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), gamma-glutamyl transpeptidase (GGT), and leucine arylamidase (LAP). The results of the CCK-8 and EdU assays both showed that ES could inhibit the proliferation of hepatocytes, and flow cytometry indicated that ES could promote apoptosis of hepatocytes. After ES treatment, the ultrastructure of hepatocytes was disrupted to a certain extent. The changes in the cell membrane and microvilli were observed through SEM, and the changes in the nucleus, mitochondria, and rough endoplasmic reticulum were observed through TEM. After ES treatment, the enzymatic activities of the six hepatocyte enzymes were increased in addition to the Fe metabolism and the synthesis of albumin (ALB), uric acid (UA), and urea, whereas the synthesis of transferrin (TRF) was decreased. The expression levels of all six key enzymes in the glucose metabolism pathway in hepatocytes were decreased, and the biological effects were significantly inhibited. We analyzed the causes and possible complications caused by various changes and advocate corresponding measures. We also propose possible mechanisms by which protoscoleces cause hepatocyte necrosis, but the specific mechanism requires further study. Author SummaryEchinococcus granulosus, the most widely distributed and most infected tapeworm, has caused serious economic and social burdens to pastoral areas in China. The metacestodes of Echinococcus granulosus mainly infect the liver of intermediate hosts (humans, cattle, sheep, etc.). Currently, the effects of Echinococcus granulosus on hepatocytes ultrastructure, enzymology, function, and glucose metabolism have not been characterized, and accurate characterization is crucial in the study of related pathogenesis and preventive therapy. Here, we characterize multiple changes in hepatocytes using excretory-secretory (ES) products of Echinococcus granulosus protoscoleces and mouse hepatocyte action by a factorial experiment. We found that ES inhibited hepatocyte proliferation and promoted hepatocyte apoptosis. ES can cause a certain degree of damage to the cell membrane, nucleus, mitochondria, and endoplasmic reticulum of hepatocytes. After ES treatment, six enzymatic indexes of hepatocytes were elevated, they were ALT, AST, LDH, ALP, GGT, and LAP, and Fe, ALB, UA, and urea levels synthesized by hepatocytes were significantly higher and TRF levels were significantly lower. Reduced expression of rate-limiting enzymes in six pathways of glucose metabolism in hepatocytes, including PFK-1, IDH, G-6-PD, GS, GP, and GLUT-2, indicating that ES inhibits glucose metabolism in hepatocytes. Our study not only characterized the effects of ES on hepatocytes in detail but also proposed the possible mechanisms causing these effects, which provided a basis for subsequent studies on related pathogenesis and prevention, and treatment.

cell biology↗

bioRxiv2022

Intranasal delivery of NS1-deleted influenza virus vectored COVID-19 vaccine restrains the SARS-CoV-2 inflammatory response

The emergence of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) variants and "anatomical escape" characteristics threaten the effectiveness of current coronavirus disease (COVID-19) vaccines. There is an urgent need to understand the immunological mechanism of broad-spectrum respiratory tract protection to guide broader vaccines development. In this study, we investigated immune responses induced by an NS1-deleted influenza virus vectored intranasal COVID-19 vaccine (dNS1-RBD) which provides broad-spectrum protection against SARS-CoV-2 variants. Intranasal delivery of dNS1-RBD induced innate immunity, trained immunity and tissue-resident memory T cells covering the upper and lower respiratory tract. It restrained the inflammatory response by suppressing early phase viral load post SARS-CoV-2 challenge and attenuating pro-inflammatory cytokine (IL-6, IL-1B, and IFN-{gamma}) levels, thereby reducing excess immune-induced tissue injury compared with the control group. By inducing local cellular immunity and trained immunity, intranasal delivery of NS1-deleted influenza virus vectored vaccine represents a broad-spectrum COVID-19 vaccine strategy to reduce disease burden.

immunology↗

bioRxiv2022

DeepBIO is an automated and interpretable deep-learning platform for biological sequence prediction, functional annotation, and visualization analysis

Here, we present DeepBIO, the first-of-its-kind automated and interpretable deep-learning platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop-shop web service that enables researchers to develop new deep-learning architectures to answer any biological question. Specifically, given any biological sequence data, DeepBIO supports a total of 42 state-of-the-art deep-learning algorithms for model training, comparison, optimization, and evaluation in a fully automated pipeline. DeepBIO provides a comprehensive result visualization analysis for predictive models covering several aspects, such as model interpretability, feature analysis, functional sequential region discovery, etc. Additionally, DeepBIO supports 9 base-level functional annotation tasks using deep-learning architectures, with comprehensive interpretations and graphical visualizations to validate the reliability of annotated sites. Empowered by high-performance computers, DeepBIO allows ultra-fast prediction with up to million-scale sequence data in a few hours, demonstrating its usability in real application scenarios. Case study results show that DeepBIO provides an accurate, robust, and interpretable prediction, demonstrating the power of deep learning in biological sequence functional analysis. Overall, we expect DeepBIO to ensure the reproducibility of deep-learning biological sequence analysis, lessen the programming and hardware burden for biologists, and provide meaningful functional insights at both sequence-level and base-level from biological sequences alone. DeepBIO is publicly available at http://inner.wei-group.net/DeepBIO.

bioinformatics↗

bioRxiv2022

GutMeta: online microbiome analysis and interactive visualization with build-in curated human gut microbiome database

BackgroundThe human gut microbiome is associated with numerous human diseases. The whole-genome shotgun metagenomics sequencing helps accumulate a massive amount of gut microbiome data. However, few curated integrated platforms are available to explore the vast dataset. Advances in data generation pose new challenges to researchers attempting to analyze, visualize, and reuse published data. ResultGutMeta (human GUT whole-genome shotgun METAgenomics data analysis platform) is a one-stop online human gut metagenomic research platform that integrates a curated database, analyses, and visualizations. First, we built the Human Gut Metagenomics Database (HGMD), which contained taxonomy profiling and metadata of the metagenomics. HGMD collected the published human gut microbiome samples with whole metagenome shotgun (WMGS) sequencing data and consistently performed taxonomy classification using MetaPhlan3 for each sample. The various related metadata information was curated, and phenotypes were according to the MeSH ID. At this moment, HGMD contains 20,898 samples from 91 projects related to 65 diseases. Embedded tools could help users to explore the samples by keywords. Second, GutMeta provides researchers with user-friendly metagenomics analysis modules, including community diversity calculation, differential testing, dimension reduction, disease classifier construction, etc. Then, GutMeta provides corresponding interactive visualizations which can download as Scalable Vector Graphics (SVG), providing high-quality images. Further, GutMeta supplies two additional visualizations for the multi-level taxonomy overview for advanced investigations. GutMeta also supports online editing, including attribute adjustment, recoloring, reordering, and drag-and-drop. Third, GutMeta supports users in building their metagenomics analysis workspaces, including standard profiles uploading and built-in HGMD data import for online customized analyses and visualization. ConclusionGutMeta offers a solution to improve reproducibility in metagenomic research, with the standardized procedure from input data to downstream analysis and visualization. GutMeta is a free access analysis platform that integrates human gut WMGS sequencing data, nine online bioinformatics analysis and data visualization modules/pipelines, and a customized workspace. GutMeta is avaiable at https://GutMeta.deepomics.org.

bioinformatics↗

bioRxiv2022

Systemic and intrinsic functions of ATRX in glial cell fate and CNS myelination

Neurodevelopmental disorders are often characterized by abnormal production of myelin, an extension of the oligodendrocyte plasma membrane wrapped around axons to facilitate nerve conduction. However, the molecular mechanisms that control myelination during brain development are incompletely resolved. Here, we provide evidence that loss of ATRX, encoded by the gene mutated in the ATR-X intellectual disability syndrome, leads to myelin deficits in the mouse CNS. While postnatal systemic thyroxine administration can improve myelination, the rescue is incomplete, pointing to additional roles of ATRX in this process. We show that targeted inactivation of ATRX in postnatal oligodendrocyte progenitor cells (OPCs), but not in neurons, also leads to myelination deficits, demonstrating cell-intrinsic effects of ATRX deficiency. A subset of ATRX-null OPCs express lower levels of oligodendrocyte specification and differentiation markers, including the basic helix-loop-helix Olig2 transcription factor. Mechanistically, we provide evidence that ATRX occupies genomic sites in OPCs marked by H3K27Ac, CHD7 and CHD8 and demonstrate that reduced Olig2 expression is associated with decreased H3K27Ac. Finally, our data suggest that ATRX-null OPCs acquire a more plastic state and can exhibit astrocyte-like features in vitro and in vivo, supporting a model in which ATRX regulates the onset of myelination by promoting OPC identity and suppressing astrogliogenesis. These previously unrecognized functions of ATRX might explain white matter pathogenesis in ATR-X syndrome patients.

neuroscience↗

bioRxiv2022

Novel Small Molecular Compound AE-848 Showed Potent Inhibitory Activity Against Human Hepatoblastoma Cells

PurposeAE-848/33345007, is a novel small molecular compound that was independently synthesized by our laboratory. The aim of the current study was to investigate potential therapeutic effects of the small molecule compound AE-848 on human hepatoblastoma cells. MethodsHuman hepatoblastoma cell line HepG2 was cultured under different concentrations of AE-848. MTT assay was used to detect the inhibitory ability of AE-848 on the activity of this cell line, while flow cytometry was applied to quantify apoptosis. Western-blot technique was used to determine expression levels of signaling pathway-associated molecules. The antitumor in vivo activity of AE-848 against hepatoblastoma was evaluated using hepatoblastoma-bearing nude mice randomly divided into AE-848 (experimental) and saline (control) groups respectively. Changes in survival and tumor sizes were compared between these two groups. ResultsAE-848 significantly inhibited proliferation and induced apoptosis of HepG2 cells, and induced activation of PI3K/Akt/mTOR signaling pathways. More importantly, AE-848 administration significantly inhibited tumor growth and prolonged survival of hepatoblastoma-bearing mice. ConclusionAE-848 had a strong anti-hepatoblastoma activity both in vitro and in vivo, indicating the importance of developing AE-848 as a potential drug for hepatoblastoma treatment.

cancer biology↗

bioRxiv2022

Structural insights into the elevator-type transport mechanism of a bacterial ZIP metal transporter

The Zrt-/Irt-like protein (ZIP) family consists of ubiquitously expressed divalent metal transporters critically involved in maintaining systemic and cellular homeostasis of zinc, iron, and manganese. Here, we present a study on a prokaryotic ZIP from Bordetella bronchiseptica (BbZIP) by combining structural biology, evolutionary covariance, computational modeling, and a variety of biochemical assays to tackle the issue of the transport mechanism which has not been established for the ZIP family. The apo state structure in an inward-facing conformation revealed a disassembled transport site, altered inter-helical interactions, and importantly, a rigid body movement of a 4-transmembrane helix (TM) bundle relative to the other TMs. The computationally generated and biochemically validated outward-facing conformation model revealed a slide of the 4-TM bundle, which carries the transport site(s), by approximately 8 [A] toward the extracellular side against the static TMs which mediate dimerization. These findings allowed us to conclude that BbZIP is an elevator-type transporter.

biochemistry↗

bioRxiv2022

Investigating microglia-neuron crosstalk by characterizing microglial contamination in human and mouse Patch-seq datasets

Microglia are dynamic immune cells with diverse functional roles, including the regulation of neuronal excitability. Here, we leveraged an inconvenient truth of neuronal Patch-seq datasets -- that they routinely display evidence of contamination by surrounding microglia -- to better understand aspects of microglia-neuronal crosstalk. We first quantified the presence of microglial transcripts in three Patch-seq datasets of human and mouse neocortical neurons and observed extensive off-target contamination by microglia in each. Variation in microglial contamination was explained foremost by donor identity, especially in human samples, and neuronal cell type identity. Differential expression testing and enrichment analyses suggest that microglial contamination in Patch-seq is reflective of activated microglia and that these transcriptional signatures are distinct from those captured via single-nucleus RNAseq. Finally, neurons with greater microglial contamination differed markedly in their electrophysiological characteristics, including lowered input resistances and more depolarized action potential thresholds. Our results suggest microglial contamination contributes to cell- and donor-related electrophysiological variability and sheds light on how microglia might impact neurons in vivo.

neuroscience↗

bioRxiv2022

ApoE4 causes severe COVID-19 outcomes via downregulation of ACE2

The coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); host cell entry by this virus relies on the interaction between the receptor-binding domain (RBD) of its spike glycoprotein and the angiotensin-converting enzyme 2 (ACE2) receptor on cell membranes. In addition to serving as a receptor for SARS-CoV-2, ACE2 was originally discovered as a protective factor in the renin-angiotensin system (RAS) that catalyses the degradation of angiotensin II (Ang II) to Ang 1-7, which is involved in multiple organ pathology. Recent genetic and clinical studies reported that ApoE4 expression is associated with increased susceptibility to SARS-CoV-2 infection and the development of severe COVID-19, but the underlying mechanism is currently unclear. In the present study, by using immunofluorescence staining, molecular dynamics simulations, proximity ligation assay (PLA) and coimmunoprecipitation (Co-IP) combined with a biolayer interferometry (BLI) assay, we found that ApoE interacts with both the spike protein and ACE2 but does not show obvious isoform-dependent binding effects. These data suggest that ApoE4 increases SARS-CoV-2 infectivity in a manner that may not depend on differential interactions with the spike protein or ACE2. Importantly, further immunoblotting and immunofluorescence staining results showed that ApoE4 significantly downregulates ACE2 protein expression in vitro and in vivo and subsequently decreases the conversion of Ang II to Ang 1-7, which could worsen tissue lesions; these findings provide a possible explain by which ApoE4 exacerbates COVID-19 disease.

neuroscience↗

bioRxiv2022

Molecular insights into peptide agonist engagement with the PTH1 receptor

The parathyroid hormone (PTH) 1 receptor (PTH1R) is a class B1 G protein-coupled receptor (GPCR) that critically regulates skeletal development and calcium homeostasis. Despite extensive study, the molecular underpinnings of PTH1R stimulation by its cognate hormones, as well as by therapeutic agents, remain unclear. Here, we describe cryo-EM structures of the PTH1R in complex with active fragments of the two hormones, PTH and parathyroid hormone related protein (PTHrP), the peptidic drug abaloparatide, as well as the engineered tool compounds, long-acting PTH (LA-PTH) and the truncated peptide, M-PTH(1-14). We found that the N-terminus of each agonist that is critical for activity, engages the transmembrane bundle in a topologically similar fashion, which reflects similarities in measures of Gs activation. The full-length peptides bind the extracellular domain (ECD) using a shared interface but induce subtly different ECD orientations relative to the transmembrane domain (TMD). In the structure bound to M-PTH, an agonist which only binds the TMD, the ECD is completely unresolved, demonstrating that the ECD is highly dynamic when unconstrained by a peptide. High resolutions enabled identification of water molecules near the peptide and G protein binding sites, some of which are structurally conserved with other class B1 GPCRs. Our results shed light on the action of orthosteric agonists of the PTH1R and provide a foundation for structure based-drug design.

biochemistry↗

bioRxiv2022

Deep autoregressive generative models capture the intrinsics embedded in T-cell receptor repertoires

T-cell receptors (TCRs) play an essential role in the adaptive immune system. Probabilistic models for TCR repertoires can help decipher the underlying complex sequence patterns and provide novel insights into understanding the adaptive immune system. In this work, we develop TCRpeg, a deep autoregressive generative model to unravel the sequence patterns of TCR repertoires. TCRpeg outperforms state-of-the-art methods in estimating the probability distribution of a TCR repertoire, boosting the accuracy from 0.672 to 0.906 measured by the Pearson correlation coefficient. Furthermore, with promising performance in probability inference, TCRpeg improves on a range of TCR-related tasks: revealing TCR repertoire-level discrepancies, classifying antigen-specific TCRs, validating previously discovered TCR motifs, generating novel TCRs, and augmenting TCR data. Our results and analysis highlight the flexibility and capacity of TCRpeg to extract TCR sequence information, providing a novel approach to decipher complex immunogenomic repertoires.

bioinformatics↗

bioRxiv2022

Inter-group Heterogeneity of Regional Homogeneity (REHO)

Regional Homogeneity (REHO) measures the similarity between the time series of a given voxel and those of its neighbors. First discovered in a task-activation paradigm, REHO was considered as a complementary method to model-driven analysis of fMRI time series. With the increased popularity of resting-state paradigms, REHO has become a widely used method for inferring neural activity in the resting state. However, the neural/physiological processes that give rise to REHO are poorly understood. Differences in REHO across groups may not be indicative of differences in neuronal activity. Here, we investigate physiological contributions to REHO across 412 subjects in 9 separate datasets downloaded from OpenNeuro where both physiological signals (respiratory rate, heart rate, and motion) and resting state data are available. Overall, we find an inverse correlation between heart rate and REHO across subjects, an inverse correlation between respiratory rate and REHO across time, and differences in REHO across groups is driven primarily by FWHM of data and motion. We conclude that, due to REHOs highly significant correlation with motion, heart rate, and respiratory rate, REHO should be used with caution to infer differences in neuronal activity across groups.

bioinformatics↗

bioRxiv2022

Locating cellular contents during cryoFIB milling by cellular secondary-electron imaging

Cryo-electron tomography (cryoET) is a powerful technique that enables the direct study of the molecular structure of tissues and cells. Cryo-focused ion beam (cryoFIB) milling plays an important role in preparation of high-quality thin lamellar samples for cryoET studies, promoting the rapid development of cryoET in recent years. However, locating the regions of interest in a large cell or tissue during cryoFIB milling remains a major challenge limiting cryoET applications on arbitrary biological samples. Here, we report an on-the-fly location method based on cellular secondary electron imaging (CSEI). CSEI is derived from a basic imaging function of the cryoFIB instruments and enables high-contrast imaging of the cellular contents of frozen hydrated biological samples, highlighted by that both fluorescent labels and additional devices are not required. The present work discusses the imaging principles and settings for optimizing CSEI. Tests on several commercially available cryoFIB instruments demonstrated that CSEI was feasible on mainstream instruments to observe all types of cellular contents and was reliable under different milling conditions. Assisted by CSEI, we established a simple milling-location workflow and tested it using the basal body of Chlamydomonas reinhardtii.

biophysics↗

bioRxiv2022

Universal mechanism of hormone and allosteric agonist mediated activation of glycoprotein hormone receptors as revealed by structures of follicle stimulating hormone receptor

Follicle stimulating hormone (FSH) is an essential glycoprotein hormone for human reproduction, which functions are mediated by a G protein-coupled receptor, FSHR. Aberrant FSH-FSHR signaling causes infertility and ovarian hyperstimulation syndrome. Here we report cryo-EM structures of FSHR in both inactive and active states, with the active structure bound to FSH and an allosteric agonist compound 21f. The structures of FSHR are similar to other glycoprotein hormone receptors, highlighting a conserved activation mechanism of hormone-induced receptor activation. Compound 21f formed extensive interactions with the TMD to directly activate FSHR. Importantly, the unique residue H6157.42 in FSHR plays an essential role in determining FSHR selectivity for various allosteric agonists. Together, our structures provide a molecular basis of FSH and small allosteric agonist-mediated FSHR activation, which could inspire the design of FSHR-targeted drugs for the treatment of infertility and controlled ovarian stimulation for in vitro fertilization.

cell biology↗

bioRxiv2022

Integrated single-cell multiomic analysis of HIV latency reversal reveals novel regulators of viral reactivation.

Despite the success of antiretroviral therapy, HIV cannot be cured because of a reservoir of latently infected cells that evades therapy. To understand the mechanisms of HIV latency, we employed an integrated single-cell RNA-seq/ATAC-seq approach to simultaneously profile the transcriptomic and epigenomic characteristics of ~4000 latently infected cells after reactivation using three different latency-reversing agents (LRAs). Differentially expressed genes and differentially accessible motifs were used to examine transcriptional pathways and transcription factor (TF) activities across the cell population. We identify cellular transcripts and TFs whose expression/activity was correlated with viral reactivation and demonstrate that a machine learning model trained on these data was 68% accurate at predicting viral reactivation. Finally, we validate the role of a new candidate HIV-regulating factor, GATA3, in the viral response to prostratin stimulation. These data demonstrate the power of integrated multimodal single-cell analysis to uncover novel relationships between host cell factors and HIV latency.

microbiology↗

bioRxiv2022

Digitally Predicting Protein Localization and Manipulating Protein Activity in Fluorescence Images Using Four-dimensional Reslicing GAN

MotivationWhile multi-channel fluorescence microscopy is a vital imaging method in biological studies, the number of channels that can be imaged simultaneously is limited by technical and hardware limitations such as emission spectra cross-talk. One feasible solution is using deep neural networks to model the localization relationship between two proteins so that the localization of a protein can be digitally predicted. Furthermore, the input and predicted localization implicitly reflects the modeled relationship. Accordingly, observing the predictions via repeatedly manipulating input localizations is an explainable and feasible way to analyze the modeled relationships between the input and the predicted proteins. ResultsWe propose a Protein Localization Prediction (PLP) method using a cGAN named Four-dimensional Reslicing Generative Adversarial Network (4DR-GAN) to digitally generate additional channels. 4DR-GAN models the joint probability distribution of imaged and target proteins by simultaneously incorporating the protein localization signals in four dimensions including space and time. Because protein localization often correlates with protein activation state, with accurate PLP, we further propose two novel tools: digital activation (DA) and digital inactivation (DI) to digitally activate and inactivate a protein and observe the response of the predicted protein localization. Compared with genetic approaches, these tools allow precise spatial and temporal control. A comprehensive experiment on four groups of proteins shows that 4DR-GAN achieves higher-quality PLP than Pix2Pix and the DA and DI responses are consistent with the known protein functions. The proposed PLP method helps simultaneously visualize additional proteins and DA and DI provide guidance to study localization-based protein functions. Availability and ImplementationThe open-source code is at https://github.com/YangJiaoUSA/4DR-GAN.

bioinformatics↗