bioRxiv Science⌕ Search

Biology subjects

Peng, C.

Publications and source records attributed to Peng, C..

At least 91 records · Page 5Linked to original sources

Pannexin-1 channels promote CD8+ T cell effector and memory responses through distinct intracellular pathways

Sensing of extracellular ATP (eATP) controls CD8+ T cell function. Their accumulation can occur through export by specialized molecules, such as the release channel Pannexin-1 (Panx1). Whether Panx1 controls CD8+ T cell immune responses in vivo, however, has not been previously addressed. Here, we report that T cell-specific Panx1 is needed for CD8+ T cell responses to viral infections and cancer. We found that CD8-specific Panx1 promotes both effector and memory CD8+ T cell responses. Panx1 favors initial effector CD8+ T cell activation through extracellular ATP (eATP) export and subsequent P2RX4 activation, which helps promote full effector differentiation through extracellular lactate accumulation and its subsequent recycling. In contrast, Panx1 promotes memory CD8+ T cell survival primarily through ATP export and subsequent P2RX7 engagement, leading to improved mitochondrial metabolism. In summary, Panx1-mediated eATP export regulates effector and memory CD8+ T cells through distinct purinergic receptors and different metabolic and signaling pathways.

immunology↗

AbFold -- an AlphaFold Based Transfer Learning Model for Accurate Antibody Structure Prediction

MotivationAntibodies are a group of proteins generated by B cells, which are crucial for the immune system. The importance of antibodies is ever-growing in pharmaceutics and biotherapeutics. Despite recent advancements pioneered by AlphaFold in general protein 3D structure prediction, accurate structure prediction of antibodies still lags behind, primarily due to the difficulty in modeling the Complementarity-determining regions (CDRs), especially the most variable CDR-H3 loop. ResultsThis paper presents AbFold, a transfer learning antibody structure prediction model with 3D point cloud refinement and unsupervised learning techniques. AbFold consistently produces state-of-the-art results on the prediction accuracy of the six CDR loops. The predictions of AbFold achieve an average RMSD of 1.51 [A] for both heavy and light chains and an average RMSD of 3.04 [A] for CDR-H3, bettering current models AlphaFold and IgFold. AbFold will contribute to antibody structure prediction and design processes.

bioinformatics↗

Protein multiple conformations prediction using multi-objective evolution algorithm

MotivationWith the breakthrough of AlphaFold2 and the publication of AlphaFold DB, the protein structure prediction has made remarkable progress, which may further promote many potential applications of proteomics in all areas of life. However, it should be noted that AlphaFold2 models tend to represent only a single static structure, and accurately predicting multiple conformations remains a challenge. Therefore, it is essential to develop methods for predicting multiple conformations, which enable us to gain knowledge of multiple conformational states and the broader conformational landscape to better understand the mechanism of action. ResultsIn this work, we proposed a multiple conformational states folding method using the distance-based multi-objective evolutionary algorithm framework, named MultiSFold. First, a multi-objective energy landscape with multiple competing constraints generated by deep learning is constructed. Then, an iterative modal exploration and exploitation strategy based on multi-objective optimization, geometric optimization and structural similarity clustering is designed to perform conformational sampling. Finally, the final population is generated using a loop-specific perturbation strategy to adjust the spatial orientations. MultiSFold was compared with state-of-the-art methods on a developed benchmark testset containing 81 proteins with two representative conformational states. Based on the proposed metric, the success ratio of MultiSFold predicting multiple conformations was 70.4% while that of AlphaFold2 was 9.88%, which may indicate that conformational sampling combined with knowledge gained through deep learning has the potential to produce conformations spanned the range between two experimental structures. In addition, MultiSFold was tested on 244 human proteins with low structural accuracy in AlphaFold DB to test whether it could further improve the accuracy of static structures. The experimental results demonstrate that the TM-score of MultiSFold is 2.97% and 7.72% higher than that of AlphaFold2 and RoseTTAFold, respectively, supporting our hypothesis that multiple competing optimization objectives can further assist conformational search to improve prediction accuracy.

bioinformatics↗

NULISA: a novel proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing

The blood proteome holds great promise for precision medicine but poses substantial challenges due to the low abundance of most plasma proteins and the vast dynamic range across the proteome. We report a novel proteomic technology - NUcleic acid Linked Immuno-Sandwich Assay (NULISA) - that incorporates a dual capture and release mechanism to suppress the assay background and improves the sensitivity of the proximity ligation assay by over 10,000-fold to the attomolar level. It utilizes pairs of antibodies conjugated to DNA oligonucleotides that enable immunocomplex purification and generate reporter DNA containing target- and sample-specific barcodes for a next-generation sequencing-based, highly multiplexed readout. A 200-plex NULISA targeting 124 cytokines and chemokines and 80 other immune response-related proteins demonstrated superior sensitivity for detecting low-abundance proteins and high concordance with other immunoassays. The ultrahigh sensitivity allowed the detection of previously difficult-to-detect, but biologically important, low-abundance biomarkers in patients with autoimmune diseases and COVID-19. Fully automated NULISA addresses longstanding challenges in proteomic analysis of liquid biopsies and makes broad and in-depth proteomic analysis accessible to the general research community and future diagnostic applications.

genomics↗

The BTB-ZF gene Bm-mamo regulate pigmentation in caterpillars

The color pattern of insects is one of the most diverse adaptive evolutionary phenotypes. However, the molecular regulation of this color pattern is not fully understood. In this study, we found that the transcription factor Bm-mamo is responsible for black dilute (bd) allele mutations in the silkworm. Bm-mamo belongs to the BTB zinc finger family and is orthologous to mamo in Drosophila melanogaster. This gene has a conserved function in gamete production in Drosophila and silkworms and has evolved a pleiotropic function in the regulation of color patterns in caterpillars. Using RNAi and clustered regularly interspaced short palindromic repeats (CRISPR) technology, we showed that Bm-mamo is a repressor or has dark melanin patterns in the larval epidermis. Using in vitro binding assays and gene expression profiling in wild-type and mutant larvae, we also showed that Bm-mamo likely regulates the expression of related pigment synthesis and cuticular protein genes in a coordinated manner to mediate its role in color pattern formation. This mechanism is consistent with the dual role of this transcription factor in regulating both the structure and shape of the cuticle and the pigments that are embedded within it. This study provides new insight into the regulation of color patterns as well as into the construction of more complex epidermis features in some insects.

genetics↗

Coupling of Slack and NaV1.6 sensitizes Slack to quinidine blockade and guides anti-seizure strategy development

Quinidine has been used as an anticonvulsant to treat patients with KCNT1-related epilepsy by targeting gain-of-function KCNT1 pathogenic mutant variants. However, the detailed mechanism underlying quinidines blockade against KCNT1 (Slack) remains elusive. Here, we report a functional and physical coupling of the voltage-gated sodium channel NaV1.6 and Slack. NaV1.6 binds to and highly sensitizes Slack to quinidine blockade. Homozygous knockout of NaV1.6 reduces the sensitivity of native sodium-activated potassium currents to quinidine blockade. NaV1.6-mediated sensitization requires the involvement of NaV1.6s N-and C-termini binding to Slacks C-terminus, and is enhanced by transient sodium influx through NaV1.6. Moreover, disrupting the Slack-NaV1.6 interaction by viral expression of Slacks C-terminus can protect against SlackG269S-induced seizures in mice. These insights about a Slack-NaV1.6 complex challenge the traditional view of "Slack as an isolated target" for anti-epileptic drug discovery efforts, and can guide the development of innovative therapeutic strategies for KCNT1-related epilepsy. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/532982v3_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1127858org.highwire.dtl.DTLVardef@19ad9f4org.highwire.dtl.DTLVardef@15b5542org.highwire.dtl.DTLVardef@13a86b4_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Human FAM111A inhibits vaccinia virus replication by degrading viral uncoating factor I3 and is antagonized by poxvirus host range factor SPI-1

Poxviruses are large double-stranded DNA viruses that infect a wide range of animals including humans. Since the eradication of smallpox, other members of the poxvirus family, such as monkeypox virus (MPXV) are still posing a great threat to public health. Vaccinia virus (VACV) is a prototypic poxvirus used as the vaccine strain for smallpox eradication. VACV encodes a serine protease inhibitor 1 (SPI-1) conserved in all orthopoxviruses, which has been recognized as a host range factor for modified vaccinia virus Ankara (MVA), an approved smallpox vaccine and a promising vaccine vector. FAM111A, a nuclear protein that regulates host DNA replication, was shown to restrict the replication of VACV-{Delta}SPI-1 in human cells. Nevertheless, the detailed antiviral mechanisms of FAM111A were unresolved. Here, we show that FAM111A is a potent restriction factor for VACV-{Delta}SPI-1 and MVA. Deletion of FAM111A rescued the replication of MVA and VACV-{Delta}SPI-1 and overexpression of FAM111A significantly reduced viral DNA replication and virus titers but did not affect viral early gene expression. The antiviral effect of FAM111A necessitated its trypsin-like protease domain and DNA binding domain but not the PCNA-interacting motif. We further discovered that FAM111A translocated into the cytoplasm upon VACV infection and this process was mediated by the cGAS-STING signaling pathway. Infection-triggered FAM111A degraded the nuclear pore complex via its protease activity, translocated to the cytoplasm, and interacted with and promoted the degradation of virus DNA binding protein I3 in a DNA-dependent manner. Interestingly, the protease activity of FAM111A was only needed for nuclear export but not I3 degradation as further analysis showed I3 was degraded through autophagy. Moreover, VACV SPI-1 was found primarily in the nucleus of infected cells and antagonized FAM111A by prohibiting its nuclear export. MPXV and lumpy skin disease virus SPI-1s also inhibited human FAM111A. Our findings reveal the detailed mechanism by which FAM111A functions to restrict a cytoplasmic DNA virus and provide explanations for the immune evasive function of VACV SPI-1.

microbiology↗

When do longer reads matter? A benchmark of long read de novo assembly tools for eukaryotic genomes

BackgroundAssembly algorithm choice should be a deliberate, well-justified decision when researchers create genome assemblies for eukaryotic organisms from third-generation sequencing technologies. While third-generation sequencing by Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) have overcome the disadvantages of short read lengths specific to next-generation sequencing (NGS), third-generation sequencers are known to produce more error-prone reads, thereby generating a new set of challenges for assembly algorithms and pipelines. Since the introduction of third-generation sequencing technologies, many tools have been developed that aim to take advantage of the longer reads, and researchers need to choose the correct assembler for their projects. ResultsWe benchmarked state-of-the-art long-read de novo assemblers, to help readers make a balanced choice for the assembly of eukaryotes. To this end, we used 13 real and 72 simulated datasets from different eukaryotic genomes, with different read length distributions, imitating PacBio CLR, PacBio HiFi, and ONT sequencing to evaluate the assemblers. We include five commonly used long read assemblers in our benchmark: Canu, Flye, Miniasm, Raven and Redbean. Evaluation categories address the following metrics: reference-based metrics, assembly statistics, misassembly count, BUSCO completeness, runtime, and RAM usage. Additionally, we investigated the effect of increased read length on the quality of the assemblies, and report that read length can, but does not always, positively impact assembly quality. ConclusionsOur benchmark concludes that there is no assembler that performs the best in all the evaluation categories. However, our results shows that overall Flye is the best-performing assembler, both on real and simulated data. Next, the benchmarking using longer reads shows that the increased read length improves assembly quality, but the extent to which that can be achieved depends on the size and complexity of the reference genome.

bioinformatics↗

Structure of human NaV1.6 channel reveals Na+ selectivity and pore blockade by 4,9-anhydro-tetrodotoxin

The sodium channel NaV1.6 is widely expressed in neurons of the central and peripheral nervous systems, which plays a critical role in regulating neuronal excitability. Dysfunction of NaV1.6 has been linked to epileptic encephalopathy, intellectual disability and movement disorders. Here we present cryo-EM structures of human NaV1.6/{beta}1/{beta}2 alone and complexed with a guanidinium neurotoxin 4,9-anhydro-tetrodotoxin (4,9-ah-TTX), revealing molecular mechanism of NaV1.6 inhibition by the blocker. In the apo-form structure, two potential Na+ binding sites were revealed in the selectivity filter, suggesting a possible mechanism for Na+ selectivity and conductance. In the 4,9-ah-TTX-bound structure, 4,9-ah-TTX binds to a pocket similar to the tetrodotoxin (TTX) binding site, which occupies the Na+ binding sites and completely blocks the channel. Molecular dynamics simulation results show that subtle conformational differences in the selectivity filter affect the affinity of TTX analogues. Taken together, our results provide important insights into NaV1.6 structure, ion conductance, and inhibition.

biophysics↗

Multiple conformational states assembly of multidomain proteins using evolutionary algorithm based on structural analogues and sequential homologues

With the breakthrough of AlphaFold2, nearly all single-domain protein structures can be built at experimental resolution. However, accurate modelling of full-chain structures of multidomain proteins, particularly all relevant conformations for those with multiple states remain challenging. In this study, we develop a multidomain protein assembly method, M-SADA, for assembling multiple conformational states. In M-SADA, a multiple population-based evolutionary algorithm is proposed to sample multiple conformational states under the guidance of multiple energy functions constructed by combining homologous and analogous templates with inter-domain distances predicted by deep learning. On a developed benchmark dataset containing 72 multidomain proteins with multiple conformational states, the performance of M-SADA is significantly better than that of AlphaFold2 on multiple conformational states modelling, where 29/72 (40.3%) of proteins can be assembled with a TM-score >0.90 for highly distinct conformational states with M-SADA while AlphaFold2 does so in only 2/72 (2.8%) of proteins. Furthermore, M-SADA is tested on a developed benchmark dataset containing 296 multidomain proteins with single conformational state, and results show that the average TM-score of M-SADA on the best models is 0.913, which is 5.2% higher than that of AlphaFold2 models (0.868).

bioinformatics↗

Inter-domain distance prediction based on deep learning for domain assembly

AlphaFold2 achieved a breakthrough in protein structure prediction through the end-to-end deep learning method, which can predict nearly all single-domain proteins at experimental resolution. However, the prediction accuracy of full-chain proteins is generally lower than that of single-domain proteins because of the incorrect interactions between domains. In this work, we develop an inter-domain distance prediction method, named DeepIDDP. In DeepIDDP, we design a neural network with attention mechanisms, where two new inter-domain features are used to enhance the ability to capture the interactions between domains. Furthermore, we propose a data enhancement strategy termed DPMSA, which is employed to deal with the absence of co-evolutionary information on targets. We integrate DeepIDDP into our previously developed domain assembly method SADA, termed SADA-DeepIDDP. Tested on a given multi-domain benchmark dataset, the accuracy of SADA-DeepIDDP inter-domain distance prediction is 11.3% and 21.6% higher than trRosettaX and trRosetta, respectively. The accuracy of the domain assembly model is 2.5% higher than that of SADA. Meanwhile, we reassemble 68 human multi-domain protein models with TM-score [≤]0.80 from the AlphaFold protein structure database, where the average TM-score is improved by 11.8% after the reassembly by our method. The online server is at http://zhanglab-bioinf.com/DeepIDDP/.

bioinformatics↗

Molecular insights into the gating mechanisms of voltage-gated calcium channel CaV2.3

High-voltage-activated R-type CaV2.3 channel plays pivotal roles in many physiological activities and is implicated in epilepsy, convulsions, and other neurodevelopmental impairments. Here, we determine the high-resolution cryo-electron microscopy (cryo-EM) structure of human CaV2.3 in complex with the 2{delta}1 and {beta}1 subunits. The VSDII is stabilized in the resting state. Electrophysiological experiments elucidate that the conformational change of VSDII in response to variation in membrane potential is not required for channel activation, whereas the other VSDs are essential for channel opening. The intracellular gate is blocked by the W-helix. A pre-W-helix adjacent to the W-helix can significantly regulate closed-state inactivation (CSI) by modulating the association and dissociation of the W-helix with the gate. Electrostatic interactions formed between the negatively charged domain on S6II, which is exclusively conserved in the CaV2 family, and nearby regions at the alpha-interacting domain (AID) and S4-S5II helix are identified. Further functional analyses indicate that these interactions are critical for the open-state inactivation (OSI) of CaV2 channels.

biophysics↗

Dysregulation of mTOR Signaling Mediates Common Neurite and Migration Defects in Both Idiopathic and 16p11.2 Deletion Autism Neural Precursor Cells

Autism spectrum disorder (ASD) is defined by common behavioral characteristics, raising the possibility of shared pathogenic mechanisms. Yet, vast clinical and etiological heterogeneity suggests personalized phenotypes. Surprisingly, our iPSC studies find that six individuals from two distinct ASD-subtypes, idiopathic and 16p11.2 deletion, have common reductions in neural precursor cell (NPC) neurite outgrowth and migration even though whole genome sequencing demonstrates no genetic overlap between the datasets. To identify signaling differences that may contribute to these developmental defects, an unbiased phospho-(p)-proteome screen was performed. Surprisingly despite the genetic heterogeneity, hundreds of shared p-peptides were identified between autism subtypes including the mTOR pathway. mTOR signaling alterations were confirmed in all NPCs across both ASD-subtypes, and mTOR modulation rescued ASD phenotypes and reproduced autism defects in controls. Thus, our studies demonstrate that genetically distinct ASD subtypes have common defects in neurite outgrowth and migration which are driven by the shared pathogenic mechanism of mTOR signaling dysregulation.

neuroscience↗

SCING: Single Cell INtegrative Gene regulatory network inference elucidates robust, interpretable gene regulatory networks

Gene regulatory network (GRN) inference is an integral part of understanding physiology and disease. Single cell/nuclei RNAseq (scRNAseq/snRNAseq) data has been used to elucidate cell-type GRNs; however, the accuracy and speed of current scRNAseq-based GRN approaches are suboptimal. Here, we present Single Cell INtegrative Gene regulatory network inference (SCING), a gradient boosting and mutual information based approach for identifying robust GRNs from scRNAseq, snRNAseq, and spatial transcriptomics data. Performance evaluation using held-out data, Perturb-seq datasets, and the mouse cell atlas combined with the DisGeNET database demonstrates the improved accuracy and biological interpretability of SCING compared to existing methods. We applied SCING to the entire mouse single cell atlas, human Alzheimers disease (AD), and mouse AD spatial transcriptomics. SCING GRNs reveal unique disease subnetwork modeling capabilities, have intrinsic capacity to correct for batch effects, retrieve disease relevant genes and pathways, and are informative on spatial specificity of disease pathogenesis.

bioinformatics↗

Development of highly potent non-covalent inhibitors of SARS-CoV-2 3CLpro

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses, and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, non-covalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. One-Sentence SummaryA oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.

microbiology↗

Pathway and mechanism of tubulin folding mediated by TRiC/CCT conjugated with its ATPase cycle revealed by cryo-EM

The eukaryotic chaperonin TRiC/CCT assists the folding of about 10% of cytosolic proteins through an ATP-driven conformational cycle, and the essential cytoskeleton protein tubulin is the obligate substrate of TRiC. Here, we present an ensemble of cryo-EM structures of human TRiC throughout its ATPase cycle, with three of them revealing endogenously engaged tubulin in different folding stages. Our structural and XL-MS analyses suggested a gradual upward translocation and stabilization of tubulin within the TRiC chamber accompanying TRiC ring closure. Remarkably, in the closed TRiC-tubulin-S3 map resolved to 3.1-[A]-resolution, we captured a near-natively folded tubulin. We found the near-natively folded tubulin engaging through its N and C domains mainly with the A and I domains of the CCT3/6/8 subunits through electrostatic and hydrophilic interactions, while the tubulin I domain was found to remain dynamic. Moreover, we also showed the potential role of TRiC C-terminal tails in substrate stabilization and folding. Our study delineates the pathway and molecular mechanism of TRiC-mediated tubulin folding conjugated with TRiC ATPase cycle, and may also inform the design of therapeutic agents targeting TRiC-tubulin interactions.

biochemistry↗

Structural basis of plp2-mediated cytoskeletal protein folding by TRiC/CCT

The eukaryotic chaperonin TRiC/CCT assists the folding of ~10% cytosolic proteins. The essential cytoskeletal proteins tubulin and actin are the obligate substrates of TRiC and their folding involves cochaperone and co-factors. Here, through cryo-EM analysis, we present a more complete picture of yeast TRiC-assisted tubulin and actin folding in the ATPase-cycle, under the coordination of cochaperone plp2. Our structures revealed that in the open C1 and C2 states, plp2 and substrates tubulin/actin engage with TRiC inside its chamber, one per ring. Noteworthy, we captured a ternary TRiC-plp2-tubulin complex in the closed C3 state, engaged with a full-length {beta}-tubulin in the native folded state even loaded with a GTP, and with a plp2 occupying the opposite ring, not reported before. Another closed C4 state revealed an actin in the intermediate state of folding and a plp2 occupying the other ring. Intriguingly, along with TRiC ring closure, we captured a large translocation of plp2 within TRiC chamber coordinating substrate translocation on the CCT6 hemisphere, potentially facilitating substrate stabilization and folding. Our findings provide structural insights into the folding mechanism of the major cytoskeletal proteins tubulin/actin under the coordination of the complex biogenesis machinery TRiC and plp2, and could extend our understanding on the links between cytoskeletal proteostasis and related human diseases.

biophysics↗

In situ architecture and membrane fusion of SARS-CoV-2 Delta variant

Among the current five Variants of Concern, infections caused by the SARS-CoV-2 B.1.617.2 (Delta) variant are often associated with the greatest severity. Despite recent advances on the molecular basis of elevated pathogenicity using recombinant proteins, architecture of intact Delta virions remains veiled. Moreover, molecular evidences for the detailed mechanism of S-mediated membrane fusion are missing. Here we reported the in situ structure and distribution of S on the authentic Delta variant, and discovered invagination in the distinctive Delta architecture. We also captured fusion snapshots from the virus-virus fusion events, provided structural evidences for Deltas attenuated dependency on cellular factors for fusion activation, and proposed a model of S-mediated membrane fusion. Site-specific glycan analysis revealed increased oligomannose-type glycosylation of native Delta S over that of the Wuhan-Hu-1 S. Together, these results disclose distinctive factors of Delta being the most virulent SARS-CoV-2 variant. In BriefCryo-ET of intact SARS-CoV-2 Delta variant revealed its distinctive architecture and captured snapshots of its membrane fusion in action.

biophysics↗