Biology subjects

Ma, J.

Publications and source records attributed to Ma, J..

At least 271 records · Page 15Linked to original sources

bioRxiv2022

OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow

For refining and designing protein structures, it is essential to have an efficient protein folding and docking framework that generates a protein 3D structure based on given constraints. In this study, we introduce OPUS-Fold3 as a gradient-based, all-atom protein folding and docking framework, which accurately generates 3D protein structures in compliance with specified constraints, such as a potential function as long as it can be expressed as a function of positions of heavy atoms. Our tests show that, for example, OPUS-Fold3 achieves performance comparable to pyRosetta in backbone folding, and significantly better in side-chain modeling. Developed using Python and TensorFlow 2.4, OPUS-Fold3 is user-friendly for any source-code level modifications and can be seamlessly combined with other deep learning models, thus facilitating collaboration between the biology and AI communities. The source code of OPUS-Fold3 can be downloaded from http://github.com/OPUS-MaLab/opus_fold3. It is freely available for academic usage.

bioinformatics↗

bioRxiv2022

A Small Subset of Cytosolic dsRNAs Must Be Edited by ADAR1 to Evade MDA5-Mediated Autoimmunity

The innate immune system detects viral infection via pattern recognition receptors and induces defense reactions such as production of type I interferon1. One such receptor, MDA5, is activated upon the recognition of double-stranded RNAs (dsRNAs) that are often produced during viral replication2. Endogenous dsRNAs evade MDA5 activation through RNA editing by ADAR1, thus preventing autoimmunity3-5. Among the large number of endogenous dsRNAs, the key substrates whose editing is critical to evade MDA5 activation (termed as immunogenic dsRNAs) remain elusive. Here we reveal the identity of human immunogenic dsRNAs, a surprisingly small fraction of all cellular dsRNAs, to fill the gap in the ADAR1-dsRNA-MDA5 axis. We found that, in contrast to previous findings6,7, the immunogenic dsRNAs were highly enriched in mRNAs and depleted of introns, an expected indication of bona fide substrates of cytosolic MDA5. The immunogenic dsRNAs, in contrast to non-immunogenic dsRNAs, tended to have shorter loop between the stems, which may facilitate dsRNA formation. They also tended to be enriched at the GWAS signals of common inflammatory diseases, implying that they are truly immunogenic. We validated the MDA5-dependent immunogenicity of the dsRNAs, which was dampened following ADAR1-mediated RNA editing. We anticipate that a focused analysis of immunogenic dsRNAs will greatly facilitate the understanding and treatment of cancer and inflammatory diseases in which the important roles of dsRNA editing and sensing continue to be revealed8-13.

genetics↗

bioRxiv2022

Single-cell Atlas of Human Fetal Cerebellum Decoding Medulloblastoma Origin and Oncogenesis

Medulloblastoma (MB) is the most common malignant childhood brain tumor1,2, yet the origin of the most aggressive subgroup-3 form remains elusive, impeding development of effective targeted treatments. Previous analyses of mouse cerebella3,4 or human counterparts from frozen tissue nuclei5 have not fully defined the compositional heterogeneity of MBs. Here, we undertook an unprecedented single-cell profiling of freshly-isolated human fetal cerebella to establish a reference map delineating hierarchical cellular states in MBs. We identified a unique transitional cerebellar progenitor connecting neural stem cells to neuronal lineages in developing fetal cerebella. Intersectional analysis revealed that the transitional progenitors were enriched in aggressive MB subgroups, including group-3 and metastatic tumors. Single-cell multi-omics revealed underlying regulatory networks in the transitional progenitor populations, including transcriptional determinants HNRNPH1 and SOX11, which are correlated with clinical prognosis in group-3 MBs. Genomic and Hi-C profiling identified de novo long-range chromatin-loops juxtaposing HNRNPH1/SOX11-targeted super-enhancers to cis-regulatory elements of MYC, an oncogenic driver for group-3 MBs. Targeting the transitional progenitor regulators inhibited MYC expression and MYC-driven group-3 MB growth. Our integrated single-cell atlases of human fetal cerebella and MBs reveal potential cell populations predisposed to transformation and regulatory circuitries underlying tumor cell states and oncogenesis, highlighting hitherto unrecognized transitional progenitor intermediates predictive of disease prognosis and potential therapeutic vulnerabilities.

cancer biology↗

bioRxiv2022

High-resolution de novo structure prediction from primary sequence

Recent breakthroughs have used deep learning to exploit evolutionary information in multiple sequence alignments (MSAs) to accurately predict protein structures. However, MSAs of homologous proteins are not always available, such as with orphan proteins or fast-evolving proteins like antibodies, and a protein typically folds in a natural setting from its primary amino acid sequence into its three-dimensional structure, suggesting that evolutionary information and MSAs should not be necessary to predict a proteins folded form. Here, we introduce OmegaFold, the first computational method to successfully predict high-resolution protein structure from a single primary sequence alone. Using a new combination of a protein language model that allows us to make predictions from single sequences and a geometry-inspired transformer model trained on protein structures, OmegaFold outperforms RoseTTAFold and achieves similar prediction accuracy to AlphaFold2 on recently released structures. OmegaFold enables accurate predictions on orphan proteins that do not belong to any functionally characterized protein family and antibodies that tend to have noisy MSAs due to fast evolution. Our study fills a much-encountered gap in structure prediction and brings us a step closer to understanding protein folding in nature.

bioinformatics↗

bioRxiv2022

Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models

Antibodies are immune system proteins that protect the host by binding to specific antigens such as viruses and bacteria. The binding between antibodies and antigens is mainly determined by the complementarity-determining regions (CDR) of the antibodies. In this work, we develop a deep generative model that jointly models sequences and structures of CDRs based on diffusion probabilistic models and equivariant neural networks. Our method is the first deep learning-based method that generates antibodies explicitly targeting specific antigen structures and is one of the earliest diffusion probabilistic models for protein structures. The model is a "Swiss Army Knife" capable of sequence-structure co-design, sequence design for given backbone structures, and antibody optimization. We conduct extensive experiments to evaluate the quality of both sequences and structures of designed antibodies. We find that our model could yield competitive results in binding affinity measured by biophysical energy functions and other protein design metrics.

bioinformatics↗

bioRxiv2022

Candesartan treatment preserves learning and working memory in female TgF344-AD rats

BackgroundTargeting the renin angiotensin system, especially with angiotensin receptor II blockers (ARB), and related vascular dysfunction is a promising therapeutic intervention for cognitive impairment including Alzheimers Disease (AD). The underlying mechanisms of the effects of ARB is unclear. This study sought to examine if treatment with candesartan, an ARB, affects neurobehavioral manifestation and the underlying neuro- and vascular mechanisms in male and female TgF344-AD rats. MethodsCandesartan or vehicle was administered to TgF344-AD rats (n=127) daily from 12-months to 18-months of age. Behavioral assays (spontaneous alternation test, novel object recognition, water radial arm maze) and neuropathologic assessment were completed along with brain proteome and measures of contractility in 12- and 18-month rat brains. ResultsUntreated 18-month TgF344-AD showed impairments in learning and increased perseverative working memory errors on the water radial arm maze (WRAM). These behavioral changes were corrected with candesartan treatment in female rats only. Treatment with candesartan was also associated with improved vascular reactivity and reduced blood pressure in both wild type and TgF344-AD male and female rats. Although there was no effect on amyloid-{beta}, treatment with candesartan reduced whole brain clusterin, an AD-risk associated protein, and GFAP in female TgF344-AD. ConclusionsOur results demonstrate that candesartan administered in the early stages of AD has a sexual dimorphic response in Tgf344-AD rat, where it reduced cognitive disturbances only in female TgF344-AD rat. These effects appear to be independent of changes in blood pressure and amyloid-{beta} reduction and are likely mediated through mechanisms related to clusterin and GFAP pathways.

neuroscience↗

bioRxiv2022

Constitutive Inhibition of Transient Receptor Potential CanonicalType 6 (TRPC6) by O-GlcNAcylation at Threonine-221

Transient receptor potential canonical type 6 (TRPC6) is a non-voltage gated cation channel that principally conducts calcium to regulate signaling in cardiac, vascular, neuronal and other cells. Abnormally increased TRPC6 expression/conductance and genetic gain of function mutations contribute to fibrosis, hypertrophy, proteinuria, and edema, notably linked to its stimulation of nuclear factor of activated T-cells (NFAT) signaling. Hyperglycemia (HG) also activates TRPC6/NFAT as a cause of diabetic renal disease. While prior work linked HG-TRPC6 activation to oxidant stress, the role of another major HG modification - O-GlcNAcylation, is unknown. Here we show TRPC6 is constitutively O-GlcNAcylated, TRPC6 and O-GlcNAc transferase proteins interact, this modification potently suppresses basal channel conductance and NFAT activity, and it is unaltered by HG. Proteomics identifies O-GlcNAcylation at Ser14, Thr70, and Thr221 in the N-terminus ankyrin-4 (AR4) and neighboring linker (LH1) domains of TRPC6. Of these, T221 is most impactful as a T221A mutation increases basal NFAT activity 11-fold, TRPC6 conductance 75-80% vs wild-type, and when expressed in cardiomyocytes amplifies NFAT-pro-hypertrophic gene expression. T221 is highly conserved and mutating homologs in TRPC3 and TRPC7 also markedly elevates basal NFAT activity. Molecular models predict electrostatic interactions between T221 O-GlcNAc and Ser199, Glu200, and Glu246, and we find similarly elevated NFAT activity from alanine substitutions at these coordinating sites as well. Thus, O-GlcNAcylation at T221 and its interaction with coordinating residues in AR4-LH1 is required for basal TRPC6 channel conductance and regulation of NFAT.

biochemistry↗

bioRxiv2022

A remodeled RNA polymerase II complex catalyzing viroid RNA-templated transcription

Viroids, a group of plant pathogens, are mysterious subviral agents composed of single-stranded circular noncoding RNAs. Nuclear-replicating viroids exploit host RNA polymerase II (Pol II) activity for transcription from circular RNA genome to minus-strand intermediates, a classic example illustrating the intrinsic RNA-dependent RNA polymerase activity of Pol II. The mechanism for Pol II to accept single-stranded RNAs as templates for transcription remains poorly understood. Here, we reconstituted a robust in vitro transcription system and demonstrated that Pol II also accepts the minus-strand viroid RNA template to generate plus-strand RNAs. Based on this reconstituted system, we purified the Pol II complex on RNA templates for nano-liquid chromatography-tandem mass spectrometry analysis. We identified a remodeled Pol II missing Rpb4, Rpb5, Rpb6, Rpb7, and Rpb9, which contrasts to the canonical 12-subunit Pol II or the 10-subunit Pol II core on DNA templates. This remodeled Pol II is active in transcription with the aid of TFIIIA-7ZF. Interestingly, this remodeled Pol II appears not to require other canonical general transcription factors (such as TFIIA, TFIIB, TFIID, TFIIE, TFIIF, TFIIH, and TFIIS), indicating a different mechanism/machinery regulating RNA-templated transcription. Transcription elongation factors, such as FACT complex, PAF1 complex, and SPT6, were also absent in the transcription complex on RNA templates. We further analyzed the critical zinc finger domains in TFIIIA-7ZF for aiding Pol II activity on RNA template and revealed the first three zinc finger domains pivotal for template binding. Collectively, our data illustrated a distinct organization of Pol II complex on viroid RNA templates, providing new insights into the evolution of transcription machinery, the mechanism of RNA-templated transcription, as well as viroid replication.

plant biology↗

bioRxiv2022

PPARγ/ETV2 Axis Regulates Endothelial-to-Mesenchymal Transition in Pulmonary Hypertension

Endothelial-to-mesenchymal transition (EndoMT) plays an important role in pulmonary hypertension (PH). Also, the molecular mechanisms regulating EndoMT in PH remain to be defined. In this study, we first showed that reduced expression of the transcription factors ETV2 (ETS variant 2) and PPAR{gamma} (Peroxisome Proliferator-Activated Receptor gamma) along with reduced endothelial markers and increased EndoMT markers were consistently observed in lungs and pulmonary artery endothelial cells (PAECs) of idiopathic pulmonary arterial hypertension (IPAH) patients, in hypoxia-exposed mouse lungs, human PAECs, and in induced EndoMT cells. Base on this observation, we aimed to investigate the function of ETV2 and PPAR{gamma} in EndoMT. We have explored the function of ETV2 and PPAR{gamma} and its mechanism in PH using in Etv2+/- mice or PPAR{gamma} KO mice. Etv2+/- mice spontaneously developed PH and right ventricular hypertrophy, associated with increased EndoMT markers and decreased EC markers. PPAR{gamma} transcriptionally activated the ETV2 promoter. Endothelial PPAR{gamma} expression in mice is positively correlated with ETV2 expression, but inversely with EndoMT markers. Overexpression of ETV2 in hypoxia-exposed rat pulmonary artery led to vascular relaxation. We conclude that PPAR{gamma}-ETV2 signaling can function as a novel pathway in PH pathogenesis by attenuating EndoMT.

physiology↗

bioRxiv2022

Studying protein-protein interaction through side-chain modeling method OPUS-Mut

Protein side chains are vitally important to many biological processes such as protein-protein interaction. In this study, we evaluate the performance of our previous released side-chain modeling method OPUS-Mut, together with some other methods, on three oligomer datasets, CASP14 (11), CAMEO-Homo (65), and CAMEO-Hetero (21). The results show that OPUS-Mut outperforms other methods measured by all residues or by the interfacial residues. We also demonstrate our method on evaluating protein-protein docking pose on a dataset Oligomer-Dock (75) created using the top 10 predictions from ZDOCK 3.0.2. Our scoring function correctly identifies the native pose as the top-1 in 45 out of 75 targets. Different from traditional scoring functions, our method is based on the overall side-chain packing favorableness in accordance with the local packing environment. It emphasizes the significance of side chains and provides a new and effective scoring term for studying protein-protein interaction.

bioinformatics↗

bioRxiv2022

OPUS-Mut: studying the effect of protein mutation through side-chain modeling

Predicting the effect of protein mutation is crucial in many applications such as protein design, protein evolution, and genetic disease analysis. Structurally, the mutation is basically the replacement of the side chain of a particular residue. Therefore, accurate side-chain modeling is useful in studying the effect of mutation. Here, we propose a computational method, namely OPUS-Mut, which significantly outperforms other backbone-dependent side-chain modeling methods including our previous method OPUS-Rota4. We evaluate OPUS-Mut by four case studies on Myoglobin, p53, HIV-1 protease, and T4 lysozyme. The results show that the predicted structures of side chains of different mutants are consistent well with their experimentally determined results. In addition, when the residues with significant structural shifts upon the mutation are considered, it is found that the extent of the predicted structural shift of these affected residues can be correlated reasonably well with the functional changes of the mutant measured by experiments. OPUS-Mut can also help one to identify the harmful and benign mutations, and thus may guide the construction of a protein with relatively low sequence homology but with similar structure.

bioinformatics↗

bioRxiv2022

CONCERT: Genome-wide prediction of sequence elements that modulate DNA replication timing

Proper control of replication timing (RT) is of vital importance to maintain genome and epigenome integrity. However, the genome-wide sequence determinants regulating RT remain unclear. Here, we develop a new machine learning method, named CO_SCPLOWONCERTC_SCPLOW, to simultaneously predict RT from sequence features and identify RT-modulating sequence elements in a genome-wide manner. CO_SCPLOWONCERTC_SCPLOW integrates two functionally cooperative modules, a selector, which performs importance estimationbased sampling to detect predictive sequence elements, and a predictor, which incorporates bidirectional recurrent neural networks and self-attention mechanism to achieve selective learning of longrange spatial dependencies across genomic loci. We apply CO_SCPLOWONCERTC_SCPLOW to predict RT in mouse embryonic stem cells and multiple human cell types with high accuracy. The identified RT-modulating sequence elements show novel connections with genomic and epigenomic features such as 3D chromatin interactions. In particular, CO_SCPLOWONCERTC_SCPLOW reveals a class of RT-modulating elements that are not transcriptional regulatory elements but are enriched with specific repetitive sequences. As a generic interpretable machine learning framework for predicting large-scale functional genomic profiles based on sequence features, CO_SCPLOWONCERTC_SCPLOW provides new insights into the potential sequence determinants of RT.

bioinformatics↗

bioRxiv2022

Ultrafast and interpretable single-cell 3D genome analysis with Fast-Higashi

Single-cell Hi-C (scHi-C) technologies can probe three-dimensional (3D) genome structures in single cells and their cell-to-cell variability. However, existing scHi-C analysis methods are hindered by the data quality and the complex 3D genome patterns. The lack of computational scalability and interpretability poses further challenges for large-scale scHi-C analysis. Here, we introduce Fast-Higashi, an ultrafast and interpretable method based on tensor decomposition that can jointly identify cell identities and chromatin meta-interactions. Fast-Higashi is able to simultaneously model multiple tensors with unmatched features of different sizes. A new partial random walk with restart (Partial RWR) algorithm in Fast-Higashi efficiently mitigates data sparseness. Extensive evaluations on real scHi-C datasets demonstrate the advantage of Fast-Higashi over existing methods for embedding, leading to improved delineation of rare cell types and better reconstruction of developmental trajectories. Fast-Higashi can directly infer chromatin meta-interactions, identify 3D genome features that define distinct cell types, and help elucidate cell type-specific connections between genome structure and function. Moreover, Fast-Higashi can be generalized to incorporate other single-cell omics data. Fast-Higashi provides a highly efficient and interpretable scHi-C analysis solution that is applicable to a broad range of biological contexts.

bioinformatics↗

bioRxiv2022

Proximal Exploration for Model-guided Protein Sequence Design

Designing protein sequences with a particular biological function is a long-lasting challenge for protein engineering. Recent advances in machine-learning-guided approaches focus on building a surrogate sequence-function model to reduce the burden of expensive in-lab experiments. In this paper, we study the exploration mechanism of model-guided sequence design. We leverage a natural property of protein fitness landscape that a concise set of mutations upon the wild-type sequence are usually sufficient to enhance the desired function. By utilizing this property, we propose Proximal Exploration (PEX) algorithm that prioritizes the evolutionary search for high-fitness mutants with low mutation counts. In addition, we develop a specialized model architecture, called Mutation Factorization Network (MuFacNet), to predict low-order mutational effects, which further improves the sample efficiency of model-guided evolution. In experiments, we extensively evaluate our method on a suite of in-silico protein sequence design tasks and demonstrate substantial improvement over baseline algorithms.

bioinformatics↗

bioRxiv2022

Electron tomography analysis of the prolamellar body and its transformation into grana thylakoids in the cryofixed Arabidopsis cotyledon

The para-crystalline structure of prolamellar bodies (PLBs) and light-induced etioplasts-to-chloroplasts transformation have been investigated with electron microscopy methods. However, these studies suffer from chemical fixation artifacts and limited volumes of three-dimensional reconstruction. We have examined Arabidopsis thaliana cotyledon cells with electron tomography (ET) to visualize etioplasts and their conversion into chloroplasts. We employed the scanning mode of ET for imaging large volumes and high-pressure freezing to improve sample preservation. PLB tubules were arranged in a zinc blende-type lattice like carbon atoms in diamonds. Within 2 hours after illumination, the lattice collapsed from the PLB exterior and the disorganized tubules merged to form thylakoid sheets, a.k.a. pre-granal thylakoids. These pre-granal thylakoids in PLBs vicinity folded and overlapped with each other to create grana stacks. Since the nascent pre-granal thylakoids had curved membranes in their tips, we examined the expression and localization of CURT1 proteins. CURT1A transcript was most abundant in de-etiolating cotyledon samples, and CURT1A concentrated to the PLB periphery. In curt1a etioplasts, PLB-associated thylakoids were swollen and failed to form grana stacks. By contrast, PLBs had cracks in their lattices in curt1c etioplasts. Our data provide evidence that CURT1A is required for pre-granal thylakoid assembly from PLB tubules during de-etiolation, while CURT1C contributes to the cubic crystal growth under darkness.

plant biology↗

bioRxiv2022

Development of a ferritin-based nanoparticle vaccine against the SARS-CoV-2 Omicron variant

A new SARS-CoV-2 variant named Omicron (B.1.1.529) discovered initially in South Africa has recently been proposed as a variant of concern (VOC) by the World Health Organization, because of its high transmissibility and resistance to current vaccines and therapeutic antibodies. Therefore, rapid development of vaccines against prevalent variants including Omicron is urgently needed for COVID-19 prevention. Here, we designed a self-assembling ferritin-based nanoparticle (FNP) vaccine against the SARS-CoV-2 Omicron variant. The purified Fc-RBDOmicron automatically formed a dimer depending on the nature of the Fc tag, thus assembling onto the nanoparticles by the Fc-protein A tag interaction (FNP-Fc-RBDOmicron). The results of hACE2-transgenic mice immunization showed that SARS-CoV-2 Omicron RBD-specific IgG titer induced by FNP-Fc-RBDOmicron was much higher than that by Fc-RBDOmicron. Consistently, the sera showed a higher neutralizing activity against SARS-CoV-2 Omicron BA.1 and BA.2 in the FNP-Fc-RBDOmicron immunized mice, indicating that immunization of a self-assembling ferritin-based nanoparticle vaccine offers a robust humoral immune response against Omicron variants. This study offers a great potential for the quick response of the emerging SARS-CoV-2 variants and affords versatility to develop universal vaccines against other emerging and reemerging coronaviruses in the future.

microbiology↗

bioRxiv2022

Plant autophagosomes mature into amphisomes prior to their delivery to the central vacuole

Autophagosomes are double-membraned vesicles that traffic harmful or unwanted cellular macromolecules to the vacuole for recycling. Although autophagosome biogenesis has been extensively studied, mechanisms of autophagosome maturation, i.e., delivery and fusion with the vacuole, remain largely unknown in plants. Here, we have identified an autophagy adaptor, CFS1, that directly interacts with the autophagosome marker ATG8 and localizes on both membranes of the autophagosome. Autophagosomes form normally in Arabidopsis thaliana cfs1 mutants, but their delivery to the vacuole is disrupted. CFS1s function is evolutionarily conserved in plants as it also localizes to the autophagosomes and plays a role in autophagic flux in the liverwort Marchantia polymorpha. CFS1 regulates autophagic flux by connecting autophagosomes with the ESCRT-I component VPS23, leading to the formation of amphisomes. Disrupting the VPS23-CFS1 interaction affects autophagic flux and renders plants sensitive to starvation stress. Altogether, our results reveal a deeply conserved mechanism of vacuolar delivery in plants that is mediated by amphisomes.

plant biology↗

bioRxiv2022

Nucleome Browser: An integrative and multimodal data navigation platform for 4D Nucleome

We introduce Nucleome Browser (http://www.nucleome.org), an interactive, multimodal data visualization and exploration platform for 4D Nucleome research. Our tool effectively integrates heterogeneous datasets (e.g., genomics, imaging, 3D genome structure models, and single-cell data) and external data portals by a new adaptive communication mechanism. Nucleome Browser provides a scalable solution for integrating massive amounts of 4D Nucleome data to navigate multiscale nuclear structure and function in a wide range of biological contexts, enabling hypothesis generation and data sharing with the broad community.

bioinformatics↗