Biology subjects

Tang, D.

Publications and source records attributed to Tang, D..

49 records · Page 3Linked to original sources

bioRxiv2022

Factorizing polygenic epistasis improves prediction and uncovers biological pathways in complex traits

Epistasis is central in many domains of biology, but it has not yet proven useful for complex traits. This is partly because complex trait epistasis involves polygenic interactions that are poorly captured in current models. To address this gap, we develop a new model called Epistasis Factor Analysis (EFA). EFA assumes that polygenic epistasis can be factorized into interactions between a few Epistasis Factors (EFs), which represent latent polygenic components of the observed complex trait. The statistical goals of EFA are to improve polygenic prediction and to increase power to detect epistasis, while the biological goal is to unravel genetic effects into more-homogeneous units. We mathematically characterize EFA and use simulations to show that EFA outperforms current epistasis models when its assumptions approximately hold. Applied to predicting yeast growth rates, EFA outperforms the additive model for several traits with large epistasis heritability and uniformly outperforms the standard epistasis model. We replicate these prediction improvements in a second dataset. We then apply EFA to four previously-characterized traits in the UK Biobank and find statistically significant epistasis in all four, including two that are robust to scale transformation. Moreover, we find that the inferred EFs partly recover pre-defined biological pathways for two of the traits. Our results demonstrate that more realistic models can identify biologically and statistically meaningful epistasis in complex traits, indicating that epistasis has potential for precision medicine and characterizing the biology underlying GWAS results.

genetics↗

bioRxiv2022

SARS-CoV-2 infected cells sprout actin-rich filopodia that facilitate viral invasion

Emerging COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a great threat to human health and economics. Although SARS-CoV-2 entry mechanism has been explored, little is known about how SARS-CoV-2 regulates the host cell remodeling to facilitate virus invasion process. Here we unveil that SARS-CoV-2 boosts and repurposes filopodia for entry to the target cells. Using SARS-CoV-2 virus-like particle (VLP), real-time live-cell imaging and simulation of active gel model, we reveal that VLP-induced Cdc42 activation leads to the formation of filopodia, which reinforce the viral entry to host cells. By single-particle tracking and sparse deconvolution algorithm, we uncover that VLP particles utilize filopodia to reach the entry site in two patterns, surfing and grabbing, which are more efficient and faster than entry via flat plasma membrane regions. Furthermore, the entry process via filopodia is dependent on the actin cytoskeleton and actin-associated proteins fascin, formin, and Arp2/3. Importantly, either inhibition the actin cross-linking protein fascin or the active level of Cdc42 could significantly hinders both the VLP and the authentic SARS-CoV-2 entry. Together, our results highlight that the spatial-temporal regulation of the actin cytoskeleton by SARS-CoV-2 infection makes filopodia as a highway for virus entry, which emerges as an antiviral target. Significance StatementRevealing the mechanism of SARS-CoV-2 invasion is of great significance to explain its high pathogenic and rapid transmission in the world. We discovered a previously unknown route of SARS-CoV-2 entry. SARS-CoV-2 virus-like particles boost cellular filopodia formation by activating Cdc42. Using state-of-art-technology, we spatial-temporally described how virus utilize filopodia to enter the target cell in two modes: surfing and grabbing. Filopodia can directly transport the virus to endocytic hot spots to avoid the virus from disorderly searching on the plasma membrane. Our study complements current knowledge of SARS-CoV-2 that filopodia and its components not only play an important role in virus release and cell-cell transmission, but also in the entry process, and provides several potential therapeutic targets for SARS-CoV-2. HighlightsO_LISARS-CoV-2 VLP infection promotes filopodia formation by activating Cdc42 C_LIO_LISARS-CoV-2 VLP utilizes filopodia to enter target cell via two modes, surfing and grabbing C_LIO_LIFilopodia disruption compromises the invasion of both VLP and authentic SARS-CoV-2 C_LI

cell biology↗

bioRxiv2022

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass spectrometry (MS). Despite improved instrumentation and software, de novo MS data analysis remains challenging. In recent years, deep learning models have represented a performance breakthrough. Incorporating that technology into de novo protein sequencing workflows require machine-learning models capable of handling highly diverse MS data. In this study, we analyzed the requirements for assembling such generalizable deep learning models by systematically varying the composition and size of the training set. We assessed the generated models performances using two test sets composed of peptides originating from the multienzyme digestion of samples from various species. The peptide recall values on the test sets showed that the deep learning models generated from a collection of highly N- and C-termini diverse peptides generalized 76% more over the termini-restricted ones. Moreover, expanding the training sets size by adding peptides from the multienzymatic digestion with five proteases of several species samples led to a 2-3 fold generalizability gain. Furthermore, we tested the applicability of these multienzyme deep learning (MEM) models by fully de novo sequencing the heavy and light monomeric chains of five commercial antibodies (mAbs). MEM models extracted over 10000 matching and overlapped peptides across six different proteases mAb samples, achieving a 100% sequence coverage for 8 of the ten polypeptide chains. We foretell that the MEM models proven improvements to de novo analysis will positively impact several applications, such as analyzing samples of high complexity, unknown nature, or the peptidomics field.

bioinformatics↗

bioRxiv2022

An environmentally-responsive transcriptional state modulates cell identities during root development

Roots are fundamental organs for plant development and response to their environment: they anchor the plant to its growth substrate, uptake nutrients and water vital to plant growth, and can sense and respond to a variety of biotic and abiotic stresses. The architecture of root systems and their growth are known to be strongly affected by the environmental conditions found in the soil. However, the acquisition of cell identities at the root meristem is still mainly viewed as ontogenetically driven, where a small number of stem cells generate all the cell types through stereotyped divisions followed by differentiation, along a simple developmental trajectory. The extent to which environmental cues precisely shape and affect these developmental trajectories remains an open question. We used single-cell RNA-seq, combined with spatial mapping, to deeply explore the trajectories of cell states at the tip of Arabidopsis roots, known to contain multiple developing lineages. Surprisingly, we found that most lineage trajectories exhibit a stereotyped bifid topology with two developmental trajectories rather than one. The formation of one of the trajectories is driven by a strong and specific activation of genes involved in the responses to various environmental stimuli, that affects only of a subset of the cells in multiple cell types simultaneously, revealing another layer of patterning of cell identities in the root that is independent of cell ontogeny. We demonstrate the robustness of this environmentally responsive transcriptional state by showing that it is present in a mutant where cell type identities are greatly perturbed, as well as in different Arabidopsis ecotypes. We also show that the root can adapt the proportion of cells that acquire this particular state in response to environmental signals such as nutrient availability. The discovery of this cell state reveals new layers of cell identity that may underpin the adaptive potential of plant development.

plant biology↗

bioRxiv2021

scBERT: a Large-scale Pretrained Deep Langurage Model for Cell Type Annotation of Single-cell RNA-seq Data

Annotating cell types based on the single-cell RNA-seq data is a prerequisite for researches on disease progress and tumor microenvironment. Here we show existing annotation methods typically suffer from lack of curated marker gene lists, improper handling of batch effect, and difficulty in leveraging the latent gene-gene interaction information, impairing their generalization and robustness. We developed a pre-trained deep neural network-based model scBERT (single-cell Bidirectional Encoder Representations from Transformers) to overcome the challenges. Following BERTs approach of pre-train and fine-tune, scBERT obtains a general understanding of gene-gene interaction by being pre-trained on huge amounts of unlabeled scRNA-seq data and is transferred to the cell type annotation task of unseen and user-specific scRNA-seq data for supervised fine-tuning. Extensive and rigorous benchmark studies validated the superior performance of scBERT on cell type annotation, novel cell type discovery, robustness to batch effect, and model interpretability.

bioinformatics↗

bioRxiv2021

Bacterial clearance caused by a single anti-M protein antibody simultaneously binding two separate epitopes

Group A streptococci have evolved multiple strategies to evade human antibodies, making it challenging to create effective vaccines or antibody treatments. Here, we have generated antibodies derived from the memory B cells of an individual who had successfully cleared a group A streptococcal infection. The antibodies bind with high affinity in the central region of the surface-bound M protein. Such antibodies are typically non-opsonic. However, one antibody could effectively promote vital immune functions, including phagocytosis and in vivo protection. Remarkably, this antibody primarily interacts through a bivalent dual-Fab cis mode, where the Fabs bind to two distinct epitopes in the M protein. The dual-Fab cis binding phenomenon is conserved across different groups of M types. In contrast, other antibodies binding with normal single-Fab mode to the same region can not bypass the M proteins virulent effects. A broadly binding, protective monoclonal antibody could be a candidate for anti-streptococcal therapy. Our findings highlight the concept of dual-Fab cis binding as a means to access conserved, and normally non-opsonic regions, for protective antibody targeting.

immunology↗

bioRxiv2020

Deep mining of early antibody response in COVID-19 patients yields potent neutralisers and reveals high level of convergence

Passive immunisation using monoclonal antibodies will play a vital role in the fight against COVID-19. Until now, the majority of anti-SARS-CoV-2 antibody discovery efforts have relied on screening B cells of patients in the convalescent phase. Here, we describe deep-mining of the antibody repertoires of hospitalised COVID-19 patients using a combination of phage display technology and B cell receptor (BCR) repertoire sequencing to isolate neutralising antibodies and gain insights into the early antibody response. This comprehensive discovery approach has yielded potent neutralising antibodies with distinct mechanisms of action, including the identification of a novel non-ACE2 receptor blocking antibody that is not expected to be affected by any of the major viral variants reported. The study highlighted the presence of potent neutralising antibodies with near germline sequences within both the IgG and IgM pools at early stages of infection. Furthermore, we highlight a highly convergent antibody response with the same sequences occurring both within this study group and also within the responses described in previously published anti-SARS-CoV-2 studies.

immunology↗

bioRxiv2020

A Prediction Tool for Plaque Progression Based on Patient-specific Multi-Physical Modeling

Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. Based on the follow-up coronary intravascular ultrasound imaging data, we performed patient-specific multi-physical modeling study on four patients to obtain the evolutional processes of the microenvironment during plaque progression. Four main pathophysiological processes, i.e., lipid deposition, inflammatory response, migration and proliferation of smooth muscle cells (SMCs), and neovascularization were coupled based on the interactions demonstrated by experimental and clinical observations. A scoring table integrating the dynamic microenvironmental indicators with the classical risk index was proposed to differentiate their progression to stable and unstable plaques. The heterogeneity of plaque microenvironment for each patient was demonstrated by the growth curves of the main microenvironmental factors. The possible plaque developments were predicted by incorporating the systematic index with microenvironmental indicators. Five microenvironmental factors (LDL, ox-LDL, MCP-1, SMC, and foam cell) showed significant differences between stable and unstable group (p < 0.01). The inflammatory microenvironments (monocyte and macrophage) had negative correlations with the necrotic core (NC) expansion in the stable group, while very strong positive correlations in unstable group. The inflammatory microenvironment is strongly correlated to the NC expansion in unstable plaques, suggesting that the inflammatory factors may play an important role in the formation of a vulnerable plaque. This prediction tool will improve our understanding of the mechanism of plaque progression and provide a new strategy for early detection and prediction of high-risk plaques. Author summaryBesides the traditional systematic factors, the influences of the local microenvironmental factors on atherosclerotic plaque progression have been demonstrated. Mathematical and computational modeling is an important tool to investigate the complex interplay between plaque progression and the microenvironment, and provides a potential way toward the prediction of plaque vulnerability according to the comprehensive evaluation of both morphological and/or biochemical factors in tissue level with microenvironmental factors in cellular level. We performed patient-specific multi-physical modeling study on four patients to obtain the evolutional processes of the microenvironment during plaque progression and predicted the possible plaque developments. A scoring table integrating the dynamic microenvironmental indicators with the classical risk index was proposed to differentiate their progression to stable and unstable plaques. Based on patient-specific imaging data, the mathematical model will provide a novel method to predict the changes of plaque microenvironment and improve ability to access the personal therapeutic strategy for atherosclerotic plaque.

bioengineering↗

bioRxiv2020

Cryo-EM structure of C9ORF72-SMCR8-WDR41 reveals the role as a GAP for Rab8a and Rab11a

A massive intronic hexanucleotide repeat (GGGGCC) expansion in C9ORF72 is a genetic origin of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Recently, C9ORF72, together with SMCR8 and WDR41, has been shown to regulate autophagy and function as Rab GEF. However, the precise function of C9ORF72 remains unclear. Here, we report the cryo-EM structure of the human C9ORF72-SMCR8-WDR41 complex at a resolution of 3.2 [A]. The structure reveals the dimeric assembly of a heterotrimer of C9ORF72-SMCR8-WDR41. Notably, the C-terminal tail of C9ORF72 and the DENN domain of SMCR8 play critical roles in the dimerization of the two protomers of the C9ORF72-SMCR8-WDR41 complex. In the protomer, C9ORF72 and WDR41 are joined by SMCR8 without direct interaction. WDR41 binds to the DENN domain of SMCR8 by the C-terminal helix. Interestingly, the prominent structural feature of C9ORF72-SMCR8 resembles that of the FLNC-FNIP2 complex, the GTPase activating protein (GAP) of RagC/D. Structural comparison and sequence alignment revealed that Arg147 of SMCR8 is conserved and corresponds to the arginine finger of FLCN, and biochemical analysis indicated that the Arg147 of SMCR8 is critical to the stimulatory effect of the C9ORF72-SMCR8 complex on Rab8a and Rab11a. Our study not only illustrates the basis of C9ORF72-SMCR8-WDR41 complex assembly but also reveals the GAP activity of the C9ORF72-SMCR8 complex. Significance StatementC9ORF72, together with SMCR8 and WDR41, has been shown to form a stable complex that participates in the regulation of membrane trafficking. We report the cryo-EM structure of the C9ORF72-SMCR8-WDR41 complex at atomic resolution. Notably, the stoichiometry of the three subunits in the C9ORF72-SMCR8-WDR41 complex is 2:2:2. Interestingly, the C-termini of C9ORF72 and the DENN domain of SMCR8 mediate the dimerization of the two C9ORF72-SMCR8-WDR41 protomers in the complex. Moreover, WDR41 binds to the DENN domain of SMCR8 by the C-terminal helix without direct contact with C9ORF72. Most importantly, the C9ORF72-SMCR8 complex works as a GAP for Rab8a and Rab11a in vitro, and the Arg147 of SMCR8 is the arginine finger.

biochemistry↗

bioRxiv2020

Colorectal cancer marker identification using the aging immune system-related blood cell DNA methylome

ObjectiveThere is a body of evidence that the aging immune system is linked to cancer. Here, we hypothesized that ubiquitination might play a key gatekeeper role in immune system aging and tumorigenesis in CRC. Therefore, we will systematically study the DNA methylation of ubiquitination genes and screen candidate CRC marker that are correlated with both aging and immune cell compositions. DesignThrough aging- and immune-related DNA methylation data, we investigated the DNA methylation regulation changes in promoters with other regions of genes during aging and their association with the immune cell proportion in the circulating whole blood of healthy individuals. Then, by collecting a cohort of 100 colon cancer patients and 50 healthy individuals, we used nucleic acid mass spectrometry to test whether ubiquitination genes can be used as candidate markers for the early screening of CRC. ResultsThe biological analyses for aging- and CD4 T cell proportion-derived differential genes showed that they are associated with ubiquitination. Among them, DZIP3 was significantly associated with both aging (P-value = 3.86E-06) and CD4 T cell proportion (P-value = 1.97E-05) in circulating blood. Then, we validated that the 1st exon DNA methylation of DZIP3 could predict the onset of early stage CRC (AUC = 0.833, OR = 8.82) and all pTNM stages of CRC (AUC = 0.782, OR = 5.70). ConclusionsThe epigenetically regulated ubiquitination plays an important role in immune aging and tumorigenesis. DNA methylation characteristic of DZIP3 can be used as a promising marker of CRC early screening. Summary boxO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIThe aging immune system is associated with cancer. C_LIO_LIUbiquitination plays potent roles in regulating a variety of signals in both innate and adaptive immune cells. C_LIO_LIThe abnormalities of ubiquitination are closely related to the occurrence of various tumors. C_LIO_LIBlood cell DNA methylome analysis provides a promising tool to probe the key components of immune cell dysregulation in aging and tumorigenesis. C_LI What are the new findings?O_LIThe aging- and immune cell proportion-derived differential genes are associated with ubiquitination. C_LIO_LIThe epigenetically regulated ubiquitination plays an important role in immune aging and tumorigenesis. C_LIO_LIDNA methylation characteristic of DZIP3, an E3 ubiquitin ligase with no reports on its function in immune cells and tumorigenesis, can be used as a promising markers of CRC early screening. C_LI How might it impact on clinical practice in the foreseeable future?O_LIThe in-depth study for DNA methylome of ubiquitination will open up a new path for the study of CRC pathogenesis, diagnosis and treatment. C_LIO_LIIn addition, DZIP3-focused screening technique only needs to extract the whole blood of individuals for MassARRAY analysis; the samples are easy to obtain, and the results are objective. Therefore, this method may have important applications in clinical CRC screening. C_LI

cancer biology↗

bioRxiv2019

Pharmacokinetics Modeling and Simulation of Voriconazole Dosing and Safety in Patients with Liver Cirrhosis

Voriconazole is used to treat invasive fungal disease and the optimal dose regimens are still unknown in cirrhotic Patients. The aim of this study was to determine the safety, to describe pharmacokinetics characteristics, and to optimize dosage regimens of voriconazole in cirrhotic patients. Data pertaining to voriconazole were collected retrospectively and analyzed using a population pharmacokinetics model. A total of 219 trough concentrations (Cmin) from 120 patients were analyzed. Voriconazole-related adverse events developed in 29 patients, with 69.0% of AEs developing within the first week after voriconazole treatment. The threshold Cmin for AEs was 5.12 mg/L. A one-compartment model with first-order absorption and elimination adequately described the data. The Child-Pugh class was the only covariate in final model. Voriconazole clearance in patients with Child-pugh A and B cirrhosis (CP-A/CP-B) and Child-pugh C cirrhosis (CP-C) were 1.79 L/h and 0.99 L/h, respectively, the volume of distribution was 159.6 L, and the oral bioavailability was 91.8%. The elimination half-life was significantly extended for up to 61.8 - 111.7 h in cirrhotic patients. Model-based simulations showed that the appropriate maintenance doses are 75 mg/12 h and 150 mg/24 h intravenously or orally for CP-A/CP-B patients, and 50 mg/12 h and 100 mg/24 h intravenously or orally for CP-C patients. The results support voriconazole maintenance doses in LC patients should be reduced to one-fourth for CP-C patients and to one-third for CP-A/CP-B patients compared to that for patients with normal liver function. Monitoring Cmin early could be a useful strategy to ensure the safety.

pharmacology and toxicology↗

bioRxiv2019

Bacterial Glycogen as a Durable Energy Reserve Contributing to Persistence: An Updated Bibliography and Mathematical Model

Glycogen is conventionally viewed as a transient energy reserve that can be rapidly synthesized for glucose accumulation or mobilized for ATP production and blood glucose homeostasis in higher organisms. However, this understanding is not completely applicable to prokaryotes due to glycogen structural heterogeneity. A number of studies have noted that glycogen with short average chain length gc in bacteria has the potential to degrade slowly, which might prolong bacterial survival in the environment and thus enhance potential for transmission to new hosts. This phenomenon has been examined over the past few years and called the durable energy storage mechanism hypothesis (DESM). In this updated bibliography, we summarize recent progress and provide a mathematical model of glycogen as a durable energy reserve.

microbiology↗

bioRxiv2018

QTL mapping of leaf angle on eight nodes in maize enable the optimize canopy by differential operating of leaf angle at different levels of plant

Leaf angle (LA) is one of the most important canopy architecture related traits of maize (Zea mays L.). Currently, there is an urgent need to elucidate the genetic mechanism of LA at canopy-wide levels for optimizing dense-planting canopy architecture. In present study, one RIL population derived from two parent lines which show distinct plant architecture was used to perform QTL mapping for LA at eight leaves below the tassel under three environments. Dozens of QTL for LA at eight leaves were identified, which were mapped on all maize chromosomes except for the tenth chromosome. Among them, there were nine common QTL as they were identified for LA more than 1 leaves or in two or three environments. And individual QTL could explain 1.29% - 20.14% of the phenotypic variation and affect LA of 1-8 leaves, including qLA5.1 affected LA of all eight leaves, qLA3.1 affected LA of the upper leaves (1stLA to 4thLA), and qLA9.1 could affect LA of the lower leaves (5thLA to 8thLA). Furthermore, the results indicated that the genetic architecture of LA at eight leaves was different. Specifically, 8thLA was mainly affected by major and minor QTL; 1stLA, 4thLA and 5thLA were affected by epistatic interactions beside major and minor QTL; while the other four LAs were simultaneously affected by major QTL, minor QTL, epistatic interactions and environments. These results provide a comprehensive understanding of genetic basis of LA at canopy-wide levels, which will be beneficial to design ideal plant architecture under dense planting in maize. Author contribution statementJ. L. and D. T. designed and supervised the study, D. T., Z.C., J.N., Q.J., P.L., L.W., J.Z., C.L. performed the phenotypic data collection. D. T. analyzed the data and drafted the manuscript, D. T. and Z.C. revised and finalized the manuscript. All the authors read and approved the manuscript. Key messageDozens of QTL for leaf angle of eight consecutive leaves were identified in the RIL population across three environments, providing the information that optimization of canopy architecture at various canopy levels.

plant biology↗