Biology subjects

Wang, D.

Publications and source records attributed to Wang, D..

At least 379 records · Page 21Linked to original sources

bioRxiv2023

coRIC map: a framework for the exploration of multifaceted subcellular RNA-binding proteins

The ability of RNA-binding proteins (RBPs) to form complexes with other biomolecules underpins a broad range of functions and remarkable structural properties. Understanding the precise spatiotemporal dynamics of RBPs and their interacting partners in the steady state and upon perturbation is key to deciphering these aspects. Here, we present the coRIC (compartmentalized RNA Interactome Capture) map, an experimental resource and analytical pipeline to study the subcellular dynamics of RBPs through multimodal dataset integration and machine learning. Using this approach, we have generated an atlas comprising 1,768 RBPs distributed in a broad panel of subcellular compartments and delineated their intermolecular and intercompartmental relationships. We have also defined the hierarchy of RBP-containing complexes at multiple scales across the cell, uncovering previously unknown functions of multiple RBPs. Furthermore, we have investigated the changes in RBP complex composition and subcellular distribution in response to C9ORF72 amyotrophic lateral sclerosis/frontotemporal dementia dipeptide repeats and DNA damage stress. The coRIC map provides a valuable new approach for defining the roles of RBPs in homeostasis and disease.

cell biology↗

bioRxiv2023

Dual long-axis reorganization of hippocampus in youth

The reorganization of human hippocampus, especially its interaction with cortex, remains largely undefined in youth. The organization of a single hippocampal long-axis has been predominantly characterized as monotonic1-6, despite recent indications of nonmonotonic features in neuron density7 and geometric eigenmodes8. While the human cortical hierarchy has been well recognized for significant developmental and evolutionary advantages9-12, hippocampus has been typically considered an evolutionarily conserved brain structure1,13,14, and overlooked regarding its integrative role of cortical hierarchical processing during development. Here, we corroborated the presence and significance of a dual long-axis representation of the hippocampal connectome and geometry including both linear and quadratic gradients along its long-axis in youth. This finding was robust across two independent large-scale developmental cohorts. Charting development of the dual long-axis gradients underscored their specific contributions to the cortical hierarchy maturation from the frontoparietal and salience/ventral attention networks. The observed developmental variability in spontaneous brain activities in youth parallels the gradients of myelin content. During childhood through adolescence to early adulthood, the hippocampus reorganized the dual long-axis by gradually relaxing its geometric constraints on the intrinsic network organization of cortical spontaneous activity for refined executive functions. Molecular processes underlying such reorganization of the dual long-axis in hippocampus are linked to neural growth, stress hormone regulation, and neuroactive signaling. Our findings enrich the understanding of hippocampal-cortical reorganizational principles across structural, functional, and molecular dimensions as well as its maturation, and define the plasticity distribution within the human hippocampus at systems level, holding potentials to enhance and translate neurodevelopment and neuropsychiatric healthcare.

neuroscience↗

bioRxiv2023

Differences in transcription initiation directionality underlie distinctions between plants and animalsin chromatin modification patterns at genes and cis-regulatory elements

Transcriptional initiation is among the first regulated steps controlling eukaryotic gene expression. High-throughput profiling of fungal and animal genomes has revealed that RNA Polymerase II (Pol II) often initiates transcription in both directions at the promoter transcription start site (TSS), but generally only elongates productively into the gene body. Additionally, Pol II can initiate transcription in both directions at cis-regulatory elements (CREs) such as enhancers. These bidirectional Pol II initiation events can be observed directly with methods that capture nascent transcripts, and they are also revealed indirectly by the presence of transcription-associated histone modifications on both sides of the TSS or CRE. Previous studies have shown that nascent RNAs and transcription-associated histone modifications in the model plant Arabidopsis thaliana accumulate mainly in the gene body, suggesting that transcription does not initiate widely in the upstream direction from genes in this plant. We compared transcription-associated histone modifications and nascent transcripts at both TSSs and CREs in Arabidopsis thaliana, Drosophila melanogaster, and Homo sapiens. Our results provide evidence for mostly unidirectional Pol II initiation at both promoters and gene-proximal CREs of Arabidopsis thaliana, whereas bidirectional transcription initiation is observed widely at promoters in both Drosophila melanogaster and Homo sapiens, as well as CREs in Drosophila. Furthermore, the distribution of transcription-associated histone modifications around TSSs in the Oryza sativa (rice) and Glycine max (soybean) genomes suggests that unidirectional transcription initiation is the norm in these genomes as well. These results suggest that there are fundamental differences in transcriptional initiation directionality between flowering plant and metazoan genomes, which are manifested as distinct patterns of chromatin modifications around RNA polymerase initiation sites.

genomics↗

bioRxiv2023

Deep Reinforcement Learning Enables Better Bias Control in Benchmark for Virtual Screening

Virtual screening (VS) has been incorporated into the paradigm of modern drug discovery. This field is now undergoing a new wave of revolution driven by artificial intelligence and more specifically, machine learning (ML). In terms of those out-of-the- box datasets for model training or benchmarking, their data volume and applicability domain are limited. They are suffering from the biases constantly reported in the ML application. To address these issues, we present a novel benchmark named MUBDsyn. The utilization of synthetic decoys (i.e., presumed inactives) is the main feature of MUBDsyn, where deep reinforcement learning was leveraged for bias control during decoy generation. Then, we carried out extensive validations on this new benchmark. First, we confirmed that MUBDsyn was superior to the classical benchmarks in control of domain bias, artificial enrichment bias and analogue bias. Moreover, we found that the assessment of ML models based on MUBDsyn was less biased as revealed by the analysis of asymmetric validation embedding bias. In addition, MUBDsyn showed better setting of benchmarking challenge for deep learning models compared with NRLiSt- BDB. Overall, we have proven that MUBDsyn is the close-to-ideal benchmark for VS. The computational tool is publicly available for the easy extension of MUBDsyn.

bioinformatics↗

bioRxiv2023

PEFT-SP: Parameter-Efficient Fine-Tuning on Large Protein Language Models Improves Signal Peptide Prediction

Signal peptides (SP) play a crucial role in protein translocation in cells. The development of large protein language models (PLMs) provides a new opportunity for SP prediction, especially for the categories with limited annotated data. We present a Parameter-Efficient Fine-Tuning (PEFT) framework for SP prediction, PEFT-SP, to effectively utilize pre-trained PLMs. We implanted low-rank adaptation (LoRA) into ESM-2 models to better leverage the protein sequence evolutionary knowledge of PLMs. Experiments show that PEFT-SP using LoRA enhances state-of-the-art results, leading to a maximum MCC2 gain of 0.372 for SPs with small training samples and an overall MCC2 gain of 0.048. Furthermore, we also employed two other PEFT methods, i.e., Prompt Tunning and Adapter Tuning, into ESM-2 for SP prediction. More elaborate experiments show that PEFT-SP using Adapter Tuning can also improve the state-of-the-art results with up to 0.202 MCC2 gain for SPs with small training samples and an overall MCC2 gain of 0.030. LoRA requires fewer computing resources and less memory compared to Adapter, making it possible to adapt larger and more powerful protein models for SP prediction.

bioinformatics↗

bioRxiv2023

Gamma sensory stimulation and effects on the brain

Findings by the Tsai lab and others 1-8 demonstrate that 40 Hz frequency sensory stimulation induces electrophysiological responses and attenuates pathology in mouse models of Alzheimers disease (AD). A recent study in Nature Neurosciene 9 concluded that the stimulation does not affect endogenous gamma oscillations or amyloid burden. We welcome research investigating 40 Hz sensory stimulation, and the article by Soula et al enhances our understanding of the brains electrophysiological response to 40Hz. However, we respectfully suggest that the data in Soula et al are consistent with a neuronal response to 40 Hz, which we further support with new data in humans. Moreover we contend the non-significant effects on amyloid are due to technical limitations of the study.

neuroscience↗

bioRxiv2023

NetREm: Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation

Transcription factor (TF) coordination plays a key role in target gene (TG) regulation via protein-protein interactions (PPIs) and DNA co-binding to regulatory elements. Single-cell technologies facilitate gene expression measurement for individual cells and cell-type identification, yet the connection between TF coordination and TG regulation of various cell types remains unclear. To address this, we have developed a novel computational approach, Network Regression Embeddings (NetREm), to reveal cell-type TF-TF coordination activities for TG regulation. NetREm leverages network-constrained regularization using prior knowledge of direct and/or indirect PPIs among TFs to analyze single-cell gene expression data. We test NetREm by simulation data and benchmark its performance in 4 real-world applications that have gold standard TF-TG networks available: mouse (mESCs) and simulated human (hESCs) embryonic stem (ESCs), human hematopoietic stem (HSCs), and mouse dendritic (mDCs) cells. Further, we showcase NetREms ability to prioritize valid novel TF-TF coordination links in human Peripheral Blood Mononuclear cell (PBMC) sub-types. We apply NetREm to analyze various cell types in both central (CNS) and peripheral (PNS) nerve system (NS) (e.g. neuronal, glial, Schwann cells (SCs)) as well as in Alzheimers disease (AD). Our findings uncover cell-type coordinating TFs and identify new TF-TG candidate links. We validate our top predictions using Cut&Run and knockout loss-of-function expression data in rat/mouse models and compare results with additional functional genomic data, including expression quantitative trait loci (eQTL) and Genome-Wide Association Studies (GWAS) to link genetic variants (single nucleotide polymorphisms (SNPs)) to TF coordination. NetREm is open-source available on GitHub as a software package.

bioinformatics↗

bioRxiv2023

Real-Time Computation of Brain E-Field for Enhanced Transcranial Magnetic Stimulation Neuronavigation and Optimization

Transcranial Magnetic Stimulation (TMS) coil placement and pulse wave-form current are often chosen to achieve a specified E-field dose on targeted brain regions. TMS neuronavigation could be improved by including real-time accurate distributions of the E-field dose on the cortex. We introduce a method and develop software for computing brain E-field distributions in real-time enabling easy integration into neuronavigation and with the same accuracy as 1st-order finite element method (FEM) solvers. Initially, a spanning basis set (< 400) of E-fields generated by white noise magnetic currents on a surface separating the head and permissible coil placements are orthogonalized to generate the modes. Subsequently, Reciprocity and Huygens principles are utilized to compute fields induced by the modes on a surface separating the head and coil by FEM, which are used in conjunction with online (real-time) computed primary fields on the separating surface to evaluate the mode expansion. We conducted a comparative analysis of E-fields computed by FEM and in real-time for eight subjects, utilizing two head model types (SimNIBSs headreco and mri2mesh pipeline), three coil types (circular, double-cone, and Figure-8), and 1000 coil placements (48,000 simulations). The real-time computation for any coil placement is within 4 milliseconds (ms), for 400 modes, and requires less than 4 GB of memory on a GPU. Our solver is capable of computing E-fields within 4 ms, making it a practical approach for integrating E-field information into the neuronavigation systems without imposing a significant overhead on frame generation (20 and 50 frames per second within 50 and 20 ms, respectively). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/564044v1_fig8.gif" ALT="Figure 8"> View larger version (27K): org.highwire.dtl.DTLVardef@1520141org.highwire.dtl.DTLVardef@d05835org.highwire.dtl.DTLVardef@4f1aa9org.highwire.dtl.DTLVardef@15f7b90_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 8:C_FLOATNO Mean computational time for pre-processing stage (mode and field generation stage) for mri2mesh models (A) and headreco models (B). At any rank (mode), the time is calculated across 8 head models from 8 subjects.) C_FIG

bioengineering↗

bioRxiv2023

Biosensor capability of the endometrium is mediated in part, by altered miRNA cargo from conceptus-derived extracellular vesicles.

We tested the hypothesis that the biosensor capability of the endometrium is mediated in part, by the effect of different cargo contained in the extracellular vesicles secreted by the conceptus during the peri-implantation period of pregnancy. We transferred Bos taurus taurus embryos of different origin: In vivo (high developmental potential (IV)), in vitro (intermediate developmental potential (IVF)), or cloned (low developmental potential (NT)), into Bos taurus indicus recipients. Extracellular vesicles (EVs) recovered from Day 16 conceptus conditioned medium were characterized and their microRNA (miRNA) cargo sequenced alongside RNA sequencing of their respective endometria. There were substantial differences in the endometrial response to in vivo Vs in vitro and in vivo Vs cloned conceptuses (1153 and 334DEGs respectively) with limited differences between in vitro Vs cloned conceptuses (36 DEGs). miRNA cargo was similar between all three groups (426 common cargo) differences between in vivo and cloned (8 miRNAs), and in vivo and in vitro (6 miRNAs) observed. Treatment of endometrial epithelial cells with mimic or inhibitors for miR-128 and miR-1298 changes to the proteomic content of target cells (96, and 85 respectively) of which mRNAs are altered in the endometrium in vivo (PLXDC2, COPG1, HSPA12A, MCM5, TBL1XR1, and TTF). In conclusion, we have determined that the biosensor capability of the endometrium is mediated in part, by its response to different EVs miRNA cargo produced by the conceptus during the peri-implantation period of pregnancy. SIGNIFICANCE STATEMENTDuring the peri-implantation period of pregnancy in mammals, the endometrium acts as a biosensor for the developmental competency of the embryo. However, the mechanism by which biosensor capability of the endometrium is established, remains elusive. In this study, we show that embryos of different developmental competencies have distinct microRNA cargo contained in their extracellular vesicles (EVs). Exposure of the endometrium to these conceptuses alters the transcriptional response of the endometrium during the process of pregnancy recognition. This differential response is mediated in part, by the delivery and action of the these differentially abundant microRNAs into EVs. Here we propose differences in EV-mediated miRNA cargo are responsible in part for this biosensor capability of the endometrium.

developmental biology↗

bioRxiv2023

Adipokinetic hormone signaling mediates the fecundity of Diaphorina citri infected by Candidatus Liberibacter asiaticus

Diaphorina citri serves as the primary vector for Candidatus Liberibacter asiaticus (CLas), the bacterium associated with the severe Asian form of huanglongbing. CLas-positive D. citri are more fecund than their CLas-negative counterparts and require extra energy expenditure. Therefore, understanding the molecular mechanisms linking metabolism and reproduction is of particular importance. In this study, we found adipokinetic hormone (DcAKH) and its receptor (DcAKHR) were essential for increasing lipid metabolism and fecundity in response to CLas infection in D. citri. Knockdown of DcAKH and DcAKHR not only resulted in the accumulation of triacylglycerol and a decline of glycogen, but also significantly decreased fecundity and CLas titer in ovaries. Combined in vivo and in vitro experiments showed that miR-34 suppresses DcAKHR expression by binding to its 3 untranslated region, whilst overexpression of miR-34 resulted in a decline of DcAKHR expression and CLas titer in ovaries and caused defects that mimicked DcAKHR knockdown phenotypes. Additionally, knockdown of DcAKH and DcAKHR significantly reduced juvenile hormone (JH) titer and JH signaling pathway genes in fat bodies and ovaries, including the JH receptor, methoprene-tolerant (DcMet), and the transcription factor, Kruppel homolog 1 (DcKr-h1), that acts downstream of it, as well as the egg development related genes vitellogenin 1-like (DcVg-1-like), vitellogenin A1-like (DcVg-A1-like) and the vitellogenin receptor (DcVgR). As a result, CLas hijacks AKH/AKHR-miR-34-JH signaling to improve D. citri lipid metabolism and fecundity, while simultaneously increasing the replication of CLas, suggesting a mutualistic interaction between CLas and D. citri ovaries.

ecology↗

bioRxiv2023

Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with [≥]2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

genomics↗

bioRxiv2023

Pharmacologically inducing regenerative cardiac cells by small molecule drugs

Adult mammals, unlike some lower organisms, lack the ability to regenerate damaged hearts through cardiomyocytes (CMs) dedifferentiation into cells with regenerative capacity. Developing conditions to induce such naturally unavailable cells with potential to proliferate and differentiate into CMs, i.e., regenerative cardiac cells (RCCs), in mammals will provide new insights and tools for heart regeneration research. In this study, we demonstrate that a two-compound combination, CHIR99021 and A-485 (2C), effectively induces RCCs from human embryonic stem cell (hESC)-derived TNNT2+ CMs in vitro, as evidenced by lineage tracing experiments. Functional analysis shows that these RCCs express a broad spectrum of cardiogenesis genes and have the potential to differentiate into functional CMs, endothelial cells (ECs), and smooth muscle cells (SMCs). Importantly, similar results were observed in neonatal rat CMs both in vitro and in vivo. Remarkably, administering 2C in adult mouse hearts significantly enhances survival and improves heart function post-myocardial infarction. Mechanistically, CHIR99021 is crucial for the transcriptional and epigenetic activation of genes essential for RCC development, while A-485 primarily suppresses H3K27Ac and particularly H3K9Ac in CMs. Their synergistic effect enhances these modifications on RCC genes, facilitating the transition from CMs to RCCs. Therefore, our findings demonstrate the feasibility and reveal the mechanisms of pharmacological induction of RCCs from endogenous CMs, which could offer a promising regenerative strategy to repair injured hearts.

cell biology↗

bioRxiv2023

Alasemenia, the earliest ovule with three wings and without cupule

The ovules or seeds (fertilized ovules) with wings are widespread and especially important for wind dispersal. However, the earliest ovules in the Famennian of the Late Devonian are rarely known about the dispersal syndrome and usually surrounded by a cupule. From Xinhang, Anhui, China, we report a new taxon of Famennian ovules, Alasemenia tria gen. et sp. nov. Each ovule possesses three integumentary wings evidently extending outwards, folding inwards along abaxial side and enclosing most part of nucellus. The ovule is borne terminally on smooth dichotomous branches and lacks a cupule. Alasemenia suggests that the integuments of the earliest ovules without a cupule evolved functions in wind dispersal and probable photosynthetic nutrition. It indicates that the seed wing originated earlier than other wind dispersal mechanisms such as seed plume and pappus, and that three- or four-winged seeds were followed by seeds with less wings. Mathematical analysis shows that three-winged seeds are more adapted to wind dispersal than seeds with one, two or four wings under the same condition.

paleontology↗

bioRxiv2023

The Bias of Using Cross-Validation in Genomic Predictions and Its Correction

Cross-validation (CV) is a widely used technique in statistical learning for model evaluation and selection. Meanwhile, various of statistical learning methods, such as Generalized Least Square (GLS), Linear Mixed-Effects Models (LMM), and regularization methods are commonly used in genomic predictions, a field that utilizes DNA polymorphisms to predict phenotypic traits. However, due to high dimensionality, relatively small sample sizes, and data sparsity in genomic data, CV in these scenarios may lead to an underestimation of the generalization error. In this work, we analyzed the bias of CV in eight methods: Ordinary Least Square (OLS), GLS, LMM, Lasso, Ridge, elastic-net (ENET), and two hybrid methods: one combining GLS with Ridge regularization (GLS+Ridge), and the other combining LMM with Ridge regularization (LMM+Ridge). Leveraging genomics data from the 1,000 Genomes Project and simulated phenotypes, our investigation revealed the presence of bias in all these methods. To address this bias, we adapted a variance-structure method known as Cross-Validation Correction (CVc). This approach aims to rectify the cross-validation error by providing a more accurate estimate of the generalization error. To quantify the performance of our adapted CVc towards all these methods, we applied the trained model to an independently generated dataset, which served as a gold standard for validating the models and calculating the generalization error. The outcomes show that, by leveraging CVc, we corrected the CV bias for most of the methods mentioned above, with two exceptions that are unrectifiable methods: ENET and Lasso. Our work revealed the substantial bias in the use of CV in genomics, a phenomenon under-appreciated by the field of statistical genomics and medicine. Additionally, we demonstrated that bias-corrected models may be formed by adapting CVc, although more work is needed to cover the full spectrum.

bioinformatics↗

bioRxiv2023

Neuroprotective Mechanism of Ribisin A on H 2 O 2 -induced PC12 cell injury model

Ribisin A has been shown to have neurotrophic activity. The aim of this study was to evaluate the neuroprotective effect of Ribisin A on injured PC12 cells and elucidate its mechanism. In this project, PC12 cells were induced by H2O2 to establish an injury model. After treatment with Ribisin A, the neuroprotective mechanism of Ribisin A was investigated by methyl tetrazolium (MTT) assay, Enzyme-linked immunosorbent assay (ELISA), flow cytometric analysis, fluorescent probe analysis, and western blot. We found that Ribisin A decreased the rate of lactate dehydrogenase (LDH) release, increased cellular superoxide dismutase (SOD) activity, decreased the levels of tumor necrosis factor- (TNF-), interleukin-6 (IL-6), Ca2+ expression and reactive oxygen species (ROS). Moreover, Ribisin A significantly increased mitochondrial membrane potential (MMP) and inhibited apoptosis of PC12 cells. Meanwhile, Ribisin A activated the phosphorylation of ERK1/2 and its downstream molecule CREB by upregulating the expression of Trk A and Trk B, the upstream molecules of the ERK signaling pathway. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/559840v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@ff9604org.highwire.dtl.DTLVardef@1d1ee75org.highwire.dtl.DTLVardef@17e4441org.highwire.dtl.DTLVardef@b347c4_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2023

AutoMolDesigner for Antibiotic Discovery: An AI-based Open-source Software for Automated Design of Small-molecule Antibiotics

Discovery of small-molecule antibiotics with novel chemotypes serves as one of the essential strategies to address antibiotic resistance. Although a considerable number of computational tools committed to molecular design have been reported, there is a deficit in the holistic and efficient tool specifically developed for small-molecule antibiotic discovery. To address this issue, we report AutoMolDesigner, a computational modeling software dedicated to small-molecule antibiotic design. It is a generalized framework comprising two functional modules, i.e., generative deep learning-enabled molecular generation and automated machine learning based-antibacterial activity/property prediction, wherein individually trained models and curated datasets are out-of-the-box for whole cell-based antibiotic screening and design. It is open-source thus allows for the incorporation of new features for flexible use. Unlike most software programs based on Linux and command lines, this application equipped with Qt-based graphical user interface can be run on personal computers with multiple operating systems, making it much easier to use for experimental scientists. The software and related materials are freely available at GitHub (https://github.com/taoshen99/AutoMolDesigner) and Zenodo (https://zenodo.org/record/8366085).

bioinformatics↗

bioRxiv2023

Transcriptome-wide RNA structure probing with temporal resolution

Reactive small-molecule probes are widely used for RNA structure probing, however current approaches largely measure average RNA transcript dynamics and do not resolve structural differences that occur during folding or transcript maturation. Here, we present SNIPER-seq, an RNA structure probing method relying upon metabolic labeling with 2-aminodeoxycytidine, structure-dependent 2-amino reaction with an aromatic isothiocyanate, and high-throughput RNA sequencing. Our method maps cellular RNA structure transcriptome-wide with temporal resolution enabling determination of transcript age-dependent RNA structural dynamics. We benchmark our approach against known RNA structures and investigate the dynamics of human 5S rRNA during ribosome biogenesis, revealing specific structural changes in 5S rRNA loops that occur over the course of several hours. Taken together, our work sheds light on the maturation and coordinated conformational changes that take place during ribosome biogenesis and provides a general strategy for surveying evolving RNA structural dynamics across the transcriptome.

biochemistry↗

bioRxiv2023

Requirement of microtubules for secretion of a micronemal protein CpTSP4 in the invasive stage of the apicomplexan Cryptosporidium parvum

The zoonotic Cryptosporidium parvum is a global contributor to infantile diarrheal diseases and opportunistic infections in immunocompromised/weakened individuals. Like other apicomplexans, it possesses several specialized secretory organelles, including micronemes, rhoptry and dense granules. However, the understanding of cryptosporidial micronemal composition and secretory pathway remains limited. Here we report a new micronemal protein in C. parvum, namely thrombospondin repeat domain-containing protein-4 (CpTSP4), providing insights into these ambiguities. Immunostaining and enzyme-linked assays show that CpTSP4 is prestored in the micronemes of unexcysted sporozoites but secreted during sporozoite excystation, gliding and invasion. In excysted sporozoites, CpTSP4 is also distributed on the two central microtubules unique to Cryptosporidium. The secretion and microtubular distribution could be completely blocked by selective kinesin-5 inhibitors, SB-743921 and SB-715992, resulting in the accumulation of CpTSP4 in micronemes. These support the kinesin-dependent microtubular trafficking of CpTSP4 for secretion. We also localize {gamma}-tubulin, consistent with kinesin-dependent anterograde trafficking. Additionally, recombinant CpTSP4 displays nanomolar binding affinity to host cell surface, for which heparin acts as one of the host ligands. A novel heparin-binding motif is identified and biochemically validated for its contribution to the adhesive property of CpTSP4 by peptide competition assays and site-directed mutagenesis. These findings shed light on the mechanisms of intracellular trafficking and secretion of a cryptosporidial micronemal protein and the interaction of a TSP-family protein with host cells. Importance Cryptosporidium parvum is a globally distributed apicomplexan parasite infecting humans and/or animals. Like other apicomplexans, it possesses specialized secretory organelles in the zoites, in which micronemes discharge molecules to facilitate the movement and invasion of zoites. Although past and recent studies have identified several proteins in cryptosporidial micronemes, our understanding on the composition, secretory pathways and domain-ligand interactions of micronemal proteins remains limited. This study identifies a new micronemal protein, namely CpTSP4, that is discharged during excystation, gliding and invasion of C. parvum sporozoites. The CpTSP4 secretion depends on the intracellular trafficking on the two Cryptosporidium-unique microtubes that could be blocked by kinesin-5/Eg5 inhibitors. Additionally, a novel heparin-binding motif is identified and biochemically validated, which contributes to the nanomolar binding affinity of CpTSP4 to host cells. These findings indicate that kinesin-dependent microtubular trafficking is critical to CpTSP4 secretion and heparin/heparan sulfate is one of the ligands for this micronemal protein.

microbiology↗