Biology subjects

Wang, D.

Publications and source records attributed to Wang, D..

At least 703 records · Page 39Linked to original sources

bioRxiv2019

Volumetric Segmentation and Characterisation of the Paracingulate Sulcus on MRI Scans

Many architectures of deep neural networks have been designed to solve specific biomedical problems, among which segmentation is a critical step to detect and locate the boundaries of the target object from an image. In this paper, we develop a deep learning based framework to automatically segment the paracingulate sulcus (PCS) from the MRI scan and estimate lengths for its segments. The study is the first work on segmentation and characterisation of the PCS, and the model achieves a Dice score of over 0.77 on segmentation, which demonstrates its potential for clinical use to assist human annotation. Moreover, the proposed architecture as a solution can be generalised to other problems where the object has similar patterns.

bioinformatics↗

bioRxiv2019

Proximate causes of infertility and embryo mortality in captive zebra finches

AbstractSome species show high rates of reproductive failure, which is puzzling because natural selection works against such failure in every generation. Hatching failure is common in both captive and wild zebra finches (Taeniopygia guttata), yet little is known about its proximate causes. Here we analyze data on reproductive performance (fate of >23,000 eggs) based on up to 14 years of breeding of four captive zebra finch populations. We find that virtually all aspects of reproductive performance are negatively affected by inbreeding (mean r = -0.117), by an early-starting, age-related decline (mean r = -0.132), and by poor early-life nutrition (mean r = - 0.058). However, these effects together explain only about 3% of the variance in infertility, offspring mortality, fecundity and fitness. In contrast, individual repeatability of different fitness components varied between 15% and 50%. As expected, we found relatively low heritability in fitness components (median: 7% of phenotypic, and 29% of individually repeatable variation). Yet, some of the heritable variation in fitness appears to be maintained by antagonistic pleiotropy (negative genetic correlations) between male fitness traits and female and offspring fitness traits. The large amount of unexplained variation suggests a potentially important role of local dominance and epistasis, including the possibility of segregating genetic incompatibilities.

evolutionary biology↗

bioRxiv2019

RNA Sequencing by Direct Tagmentation of RNA/DNA Hybrids

Transcriptome profiling by RNA sequencing (RNA-seq) has been widely used to characterize cellular status but it relies on second strand cDNA synthesis to generate initial material for library preparation. Here we use bacterial transposase Tn5, which has been increasingly used in various high-throughput DNA analyses, to construct RNA-seq libraries without second strand synthesis. We show that Tn5 transposome can randomly bind RNA/DNA heteroduplexes and add sequencing adapters onto RNA directly after reverse transcription. This method, Sequencing HEteRo RNA-DNA-hYbrid (SHERRY), is versatile and scalable. SHERRY accepts a wide range of starting materials, from bulk RNA to single cells. SHERRY offers a greatly simplified protocol, and produces results with higher reproducibility and GC uniformity compared with prevailing RNA-seq methods. Significance StatementRNA sequencing is widely used to measure gene expression in biomedical research; therefore, improvements in the simplicity and accuracy of the technology are desirable. All existing RNA sequencing methods rely on the conversion of RNA into double-stranded DNA through reverse transcription followed by second strand synthesis. The latter step requires additional enzymes and purification, and introduces sequence-dependent bias. Here, we show that Tn5 transposase, which randomly binds and cuts double-stranded DNA, can directly fragment and prime the RNA/DNA heteroduplexes generated by reverse transcription. The primed fragments are then subject to PCR amplification. This provides a new approach for simple and accurate RNA characterization and quantification.

molecular biology↗

bioRxiv2019

Effect of the divalent cations zinc and calcium on the structure and mechanics of reconstituted vimentin intermediate filaments

Divalent cations in a concentration-dependent manner behave as effective crosslinkers of intermediate filaments (IFs) such as vimentin IF (VIF). These interactions have been mostly attributed to their multivalency. However, ion-protein interactions often depend on the ion species, and these effects have not been widely studied in IFs. Here we investigate the effects of two biologically important divalent cations, Zn2+ and Ca2+, on VIF network structure and mechanics in vitro. We find that the network structure is unperturbed at micromolar Zn2+ concentrations, but strong bundle formation is observed at a concentration of 100 M. Microrheological measurements show that network stiffness increases with cation concentration. However, bundling of filaments softens the network. This trend also holds for VIF networks formed in the presence of Ca2+, but remarkably, a concentration of Ca2+ that is two orders higher is needed to achieve the same effect as with Zn2+, which suggests the importance of salt-protein interactions as described by the Hofmeister effect. Furthermore, we find evidence of competitive binding between the two divalent ion species. Hence, specific interactions between VIFs and divalent cations are likely to be an important mechanism by which cells can control their cytoplasmic mechanics. SignificanceIntermediate filaments are key structural elements within cells; they are known to form networks that can be crosslinked by divalent cations, but the interactions between the ions and the filaments are not well understood. By measuring the effects that two divalent cations, zinc and calcium, have on the structure and mechanics of vimentin intermediate filaments (VIFs), we show that although both have concentration-dependent effects on VIFs, much more calcium is needed to achieve the same effect as a small amount of zinc. Furthermore, when mixtures of the ions are present, the results suggest that there is binding competition. Thus, cells may use the presence of different cation species to precisely control their internal mechanical properties.

biophysics↗

bioRxiv2019

Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder

Recent advances in consortium-scale genome-wide association studies (GWAS) have highlighted the involvement of common genetic variants in autism spectrum disorder (ASD), but our understanding of their etiologic roles, especially the interplay with rare variants, is incomplete. In this work, we introduce an analytical framework to quantify the transmission disequilibrium of genetically regulated gene expression from parents to offspring. We applied this framework to conduct a transcriptome-wide association study (TWAS) on 7,805 ASD proband-parent trios, and replicated our findings using 35,740 independent samples. We identified 31 associations at the transcriptome-wide significance level. In particular, we identified POU3F2 (p=2.1e-7), a transcription factor (TF) mainly expressed in developmental brain. TF targets regulated by POU3F2 showed a 2.1-fold enrichment for known ASD genes (p=4.6e-5) and a 2.7-fold enrichment for loss-of-function de novo mutations in ASD probands (p=7.1e-5). These results provide a clear example of the connection between ASD genes affected by very rare mutations and an unlinked key regulator affected by common genetic variations.

genetics↗

bioRxiv2019

DNB-Based On-Chip Motif Finding (DocMF): a High-Throughput Method to Profile Different Types of Protein-DNA Interactions

Here we report a highly sensitive DNB-based on-chip Motif Finding (DocMF) system that utilizes high throughput next-generation-sequencing (NGS) chips to profile protein binding or cleaving activity. Using DocMF, we successfully identified a variety of endonuclease recognition sites and the protospacer-adjacent-motif (PAM) sequences of different CRISPR systems. Our DocMF platform can simultaneously screen both 5 and 3 PAM regions with high coverage using the same NGS library/chip. For the well-studied SpCas9, our DocMF platform identified a small proportion of noncanonical 5-NAG-3 ([~]5%) and 5-NGA-3 ([~]1.6%), in addition to its common PAMs, 5-NGG-3 ([~]89.9%). We also used the DocMF to assay two uncharacterized Cas endonucleases, VeCas9 and BvCpf1. VeCas9 PAMs were not detected by the conventional PAM depletion method. However, DocMF discovered that both VeCas9 and BvCpf1 required broader and more complicated PAM sequences for target recognition. VeCas9 preferred the R-rich motifs, whereas BvCpf1 used the T-rich PAMs. Moreover, after slightly changing the experimental protocol, we observed that dCas9, a DNA-binding protein lacking endonuclease activity, preferably binded to the previously reported PAMs 5-NGG-3. In summary, our studies demonstrate that DocMF is the first tool with the capacity to exhaustively assay both the binding and the cutting properties of different DNA-binding proteins.

molecular biology↗

bioRxiv2019

ECMarker: Interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

Gene expression and regulation, a key molecular mechanism driving human disease development, remains elusive, especially at early stages. Integrating the increasing amount of population-level genomic data and understanding gene regulatory mechanisms in disease development are still challenging. Machine learning has emerged to solve this, but many machine learning methods were typically limited to building an accurate prediction model as a "black box", barely providing biological and clinical interpretability from the box. To address these challenges, we developed an interpretable and scalable machine learning model, ECMarker, to predict gene expression biomarkers for disease phenotypes and simultaneously reveal underlying regulatory mechanisms. Particularly, ECMarker is built on the integration of semi- and discriminative- restricted Boltzmann machines, a neural network model for classification allowing lateral connections at the input gene layer. This interpretable model is scalable without needing any prior feature selection and enables directly modeling and prioritizing genes and revealing potential gene networks (from lateral connections) for the phenotypes. With application to the gene expression data of non-small cell lung cancer (NSCLC) patients, we found that ECMarker not only achieved a relatively high accuracy for predicting cancer stages but also identified the biomarker genes and gene networks implying the regulatory mechanisms in the lung cancer development. Additionally, ECMarker demonstrates clinical interpretability as its prioritized biomarker genes can predict survival rates of early lung cancer patients (p-value < 0.005). Finally, we identified a number of drugs currently in clinical use for late stages or other cancers with effects on these early lung cancer biomarkers, suggesting potential novel candidates on early cancer medicine. ECMarker is open source as a general-purpose tool at https://github.com/daifengwanglab/ECMarker.

bioinformatics↗

bioRxiv2019

Minutes-timescale 3D isotropic imaging of entire organs at subcellular resolution by content-aware compressed-sensing light-sheet microscopy

Instant 3D imaging of entire organs and organisms at cellular resolution is a recurring challenge in life science. Here we report on a computational light-sheet microscopy able to achieve minute-timescale mapping of entire macro-scale organs at high spatial resolution, thereby overcoming the throughput limit of current 3D microscopy implementations. Through combining a dual-side confocally-scanned Bessel light-sheet illumination which provides thinner-and-wider optical sectioning of deep tissues, with a content-aware compressed sensing (CACS) computation pipeline which further improves the contrast and resolution based on a single acquisition, our method yields 3D images with high, isotropic spatial resolution and rapid acquisition improved by two-orders of magnitude. We demonstrate the imaging of whole brain ([~]400 mm3), entire gastrocnemius and tibialis muscles ([~]200 mm3) of mouse at subcellular resolution (0.5-m isovoxel) and ultra-high throughput of 5[~]10 minutes per sample. Various system-level cellular analyses, such as mapping cell populations at different brain sub-regions, tracing long-distance projection neurons over the entire brain, and calculating neuromuscular junction occupancy across whole muscle, were also readily enabled by our method.

bioengineering↗

bioRxiv2019

Reconstructing lost BOLD signal in individual participants using deep machine learning

The blood oxygen level-dependent (BOLD) signal in functional neuroimaging suffers from magnetic susceptibility artifacts and interference from metal implants. The resulting signal loss hampers functional neuroimaging studies and can lead to misinterpretation of findings. Here, we reconstructed compromised BOLD signal using deep machine learning. We trained a deep learning model to learn principles governing BOLD activity in one dataset and reconstructed artificially-compromised regions in another dataset, frame by frame. Strikingly, BOLD time series extracted from reconstructed frames were correlated with the original time series, even though the frames did not independently carry information about BOLD fluctuations through time. Moreover, reconstructed functional connectivity (FC) maps exhibited good correspondence with the original FC maps, indicating that the deep learning model recovered functional relationships among brain regions. We replicated this result in patients whose scans suffered signal loss due to intracortical electrodes. Critically, the reconstructions captured individual-specific information rather than group information learned during training. Deep machine learning thus presents a unique opportunity to reconstruct compromised BOLD signal while capturing features of an individuals own functional brain organization.

neuroscience↗

bioRxiv2019

Selective targeting of an oncogenic KRAS mutant allele by CRISPR/Cas9 induces efficient tumor regression

BackgroundKRAS is one of the most frequently mutated oncogenes in human cancers, but its activating mutations have remained undruggable due to its picomolar affinity for GTP/GDP and its smooth protein structure resulting in the absence of known allosteric regulatory sites. ResultsWith the goal of treating mutated KRAS-driven cancers, two CRISPR systems, CRISPR-SpCas9 genome-editing system and transcription-regulating system dCas9-KRAB, were developed to directly deplete KRAS mutant allele or to repress its transcription in cancer cells, respectively, through guide RNA specifically targeting the mutant but not wild-type allele. The effect of in vitro proliferation and cell cycle on cancer cells as well as in vivo tumor growth was examined after delivery of Cas9 system. SpCas9 and dCas9-KRAB systems with sgRNA targeting the mutant allele both blocked the expression of mutant KRAS gene, leading to an inhibition of cancer cell proliferation. Local adenoviral injections using SpCas9 and dCas9-KRAB systems both suppressed tumor growth in vivo. The gene-depletion system (SpCas9) performed more effectively than the transcription-suppressing system (dCas9-KRAB) on tumor inhibition. Application of both Cas9 systems to wild-type KRAS tumor cells did not affect cell proliferation in vitro and in vivo. Furthermore, through bioinformatic analysis of 31555 SNP mutations of the top 20 cancer driver genes, we showed that our mutant-specific editing strategy could be extended to a list of oncogenic mutations with high editing potentials, and this pipeline can be applied to analyze the distribution of PAM sequence in the genome to survey the best targets for other editing purpose. ConclusionsWe successfully developed both gene-depletion and transcription-suppressing systems to specifically target an oncogenic mutant allele of KRAS which led to significant tumor regression. It provides a promising strategy for the treatment of tumors with driver gene mutations.

genetics↗

bioRxiv2019

scCancer: a package for automated processing of single cell RNA-seq data in cancer

SummaryMolecular heterogeneities bring great challenges for cancer diagnosis and treatment. Recent advance in single cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer transcriptomic heterogeneities at single cell level. Here, we develop an R package named scCancer which focuses on processing and analyzing scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features. Firstly, the package introduced comprehensive quality control metrics. Secondly, it used a data-driven machine learning algorithm to accurately identify major cancer microenvironment cell populations. Thirdly, it estimated a malignancy score to classify malignant (cancerous) and non-malignant cells. Then, it analyzed intra-tumor heterogeneities by key cellular phenotypes (such as cell cycle and stemness) and gene signatures. Finally, a user-friendly graphic report was generated for all the analyses.\n\nAvailabilityhttp://lifeome.net/software/sccancer/.\n\nContactjgu@tsinghua.edu.cn

bioinformatics↗

bioRxiv2019

Multistep metabolic engineering of Bacillus licheniformis to improve pulcherriminic acid production

Pulcherriminic acid, a cyclodipeptide, possesses the excellent antibacterial activities by chelating iron ions from environment, however, the low yield has hindered its application. In this study, high-level production of pulcherriminic acid was achieved by the multistep metabolic engineering of Bacillus licheniformis DWc9n*. Firstly, leucine (Leu) supply was increased by overexpressing the genes ilvBHC-leuABCD and ilvD involved in the Leu synthetic pathway and deleting the gene bkdAB encoding a branched-chain -keto acid dehydrogenase. The intracellular Leu content and pulcherriminic acid yield of strain W2 reached 147.4 mg/g DCW and 189.9 mg/L respectively, which corresponded to a 226.7% and 49.1% higher than those of DWc9n*. Secondly, the strain W3 was obtained by overexpressing leucyl-tRNA synthase LeuS in W2, which lead to a 190% improvement compared to DWc9n*, pulcherriminic acid yield increase to 367.7 mg/L. Thirdly, overexpression of the cytochrome synthase gene cluster yvmC-cypX further increased the yield of pulcherriminic acid to 507.4 mg/L. Finally, the secretion capability was improved by overexpressing the pulcherriminic acid transporter gene yvmA. This resulted in the 556.1 mg/L pulcherriminic acid was produced in W4/pHY-yvmA, increased by 340% as compared with DWc9n*, and it is the highest pulcherriminic acid production currently reported. Taken together, this study provided an efficient strategy for enhancing pulcherriminic acid production and might also be applied for high-level production of other cyclodipeptides.\n\nImportancePulcherriminic acid is a cyclodipeptide that derived from cyclo(L-Leu-L-Leu), which has the same iron chelation group with hydroxamate siderophores. Pulcherriminic acid producing strains can inhibit the growths of various bacteria and plant pathogenic fungi. However, the expected pulcherriminic acid yield was not achieved. This study reports efficient microbial production of pulcherriminic acid in Bacillus licheniformis DWc9n* via multistep metabolic engineering strategies. The combination of these interventions resulted in the establishment of a pulcherriminic acid overproducing strain. In combination with bioprocess engineering efforts, pulcherriminic acid was produced at a final yield of 556 mg/L in a shake flask. This is the highest pulcherriminic acid yield ever reported so far using rationally engineered microbial cell factories.

bioengineering↗

bioRxiv2019

A mathematical modeling approach to explore kinetics of Chimeric Antigen Receptor (CAR) T-cell Response in glioma: the CARRGO model

Chimeric antigen receptor (CAR) T-cell therapy has shown promise in the treatment of hematological cancers and is currently being investigated for solid tumors including high-grade glioma brain tumors. There is a desperate need to quantitatively study the factors that contribute to the efficacy of CAR T-cell therapy in solid tumors. In this work we use a mathematical model of predator-prey dynamics to explore the kinetics of CAR T-cell killing in glioma: the Chimeric Antigen Receptor t-cell treatment Response in GliOma (CARRGO) model. The model includes rates of cancer cell proliferation, CAR T-cell killing, CAR T-cell proliferation and exhaustion, and CAR T-cell persistence. We use patient-derived and engineered cancer cell lines with an in vitro real-time cell analyzer to parameterize the CARRGO model. We observe that CAR T-cell dose correlates inversely with the killing rate and correlates directly with the net rate of proliferation and exhaustion. This suggests that at a lower dose of CAR T-cells, individual T-cells kill more cancer cells but become more exhausted as compared to higher doses. Furthermore, the exhaustion rate was observed to increase significantly with tumor growth rate and was dependent on level of antigen expression. The CARRGO model highlights nonlinear dynamics involved in CAR T-cell therapy and provides novel insights into the kinetics of CAR T-cell killing. The model suggests that CAR T-cell treatment may be tailored to individual tumor characteristics including tumor growth rate and antigen level to maximize therapeutic benefit. Statement of SignificanceWe utilize a mathematical model to deconvolute the nonlinear contributions of CAR T-cell proliferation and exhaustion to predict therapeutic efficacy and dependence on CAR T-cell dose and target antigen levels.

immunology↗

bioRxiv2019

Satellite Imaging of Global Urbanicity relate to Adolescent Brain Development and Behavior

Urbanicity, the impact of living in urban areas, is among the greatest environmental challenges for mental health. While urbanicity might be distinct in different sociocultural conditions and geographic locations, there are likely to exist common features shared in different areas of the globe. Understanding these common and specific relations of urbanicity with human brain and behavior will enable to assess the impact of urbanicity on mental disorders, especially in childhood and adolescence, where prevention and early interventions are likely to be most effective.\n\nWe constructed from satellite-based remote sensing data a factor for urbanicity that was highly correlated with population density ground data. This factor, UrbanSat was utilized in the Chinese CHIMGEN sample (N=831) and the longitudinal European IMAGEN cohort (N=810) to investigate if exposure to urbanicity during childhood and adolescence is associated with differences in brain structure and function in young adults, and if these changes are linked to behavior.\n\nUrbanicity was found negatively correlated with medial prefrontal cortex volume and positively correlated with cerebellar vermis volume in young adults from both China and Europe. We found an increased correlation of urbanicity with functional network connectivity within- and between- brain networks in Chinese compared to European participants. Urbanicity was highly correlated with a measure of perceiving a situation from the perspective of others, as well as symptoms of depression in both datasets. These correlations were mediated by the structural and functional brain changes observed. Susceptibility to urbanicity was greatest in two developmental windows during mid-childhood and adolescence.\n\nUsing innovative technology, we were able to probe the relationship between urban upbringing with brain change and behavior in different sociocultural conditions and geographic locations. Our findings help to identify shared and distinct determinants of adolescent brain development and mental health in different regions of the world, thus contributing to targeted prevention and early-intervention programs for young people in their unique environment. Our approach may be relevant for public health, policy and urban planning globally.

neuroscience↗

bioRxiv2019

Exploiting a Mechanical Perturbation of Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways

Molecular mechanics force fields have been shown to differ in their predictions of processes such as protein folding. To test how force field differences affect predicted protein behavior, we created a mechanically perturbed model of the beta-stranded I91 titin domain based on atomic force spectroscopy data and examined its refolding behavior using six different force fields. To examine the transferability of the force field discrepancies identified by this model, we compared the results to equilibrium simulations of the weakly helical peptide Ac-(AAQAA)3-NH2. The total simulation time was 80 {micro}s. From these simulations we found significant differences in I91 perturbation refolding ability between force fields. Concurrently, Ac-(AAQAA)3-NH2 equilibration experiments indicated that although force fields have similar overall helical frequencies, they can differ in helical lifetimes. The combination of these results suggests that differences in force field parameterization may allow a more direct transition between the beta and alpha regions of the Ramachandran plot thereby affecting both beta-strand refolding ability and helical lifetimes. Furthermore, the combination of results suggests that using mechanically perturbed models can provide a controlled method to gain more insight into how force fields affect protein behavior.

biophysics↗

bioRxiv2019

The inverse relationship between fibronectin and neuroligins in the embryonic rat colon

Our previous study identified that the abnormal expression of fibronectin (FN), neuroligin-1 (NL1) and neuroligin-2 (NL2) in the colons of children with Hirschsprung disease (HSCR), but the correlated relationship between the three in the development of the enteric nervous system (ENS) remains unclear. Colons of Wistar rats and PC12 neurons were used to investigate the relationship between FN and the neuroligins (NLs). Colon tissues from thirty healthy embryonic rats, including fifteen at embryonic day 16 (E16), eight at E18, seven at E20, and fifteen newborn rats within 24 hours (Ep0) were analyzed to determine the correlated expression of FN and NLs using Western blot (WB) analysis and real-time fluorescence quantitative PCR (qRT-PCR) methods. Small interfering ribonucleic acid (siRNA) targeting and gene plasmids were used to explore the functional interaction between FN and NLs by using PC12 neuron cells. Furthermore, we used recombinant FN and NL proteins to confirm their interactions. Our studies showed that there were downregulatory effects between FN and the NLs in the embryonic rat colon and different cell lines, indicating that FN and NLs could directly regulate each other, and there is a negative linear correlation between them. The imbalanced interaction between extracellular matrix and synapse-related genes may provide a new perspective for the pathogenesis and treatment of HSCR and neuronal intestinal malformations (NIMs).

cell biology↗

bioRxiv2019

Trading Genome Vulnerability for Stable Genetic Inheritance: Active Retrotransposons Help Maintain Pericentromeric Heterochromatin Required for Faithful Cell Division

Retrotransposons are extensively populated in vertebrate genomes, which, when active, are thought to cause genome instability with potential benefit to genome evolution. Retrotransposon-derived RNAs are also known to give rise to small endo-siRNAs to help maintain heterochromatin at their sites of transcription; however, as not all heterochromatic regions are equally active in transcription, it remains unclear how heterochromatin is maintained across the genome. Here, we attack these problems by defining the origins of repeat-derived RNAs and their specific chromatin registers in Drosophila S2 cells. We demonstrate that repeat RNAs are predominantly derived from active Gypsy elements, and upon their processing by Dicer-2, these endo-siRNAs act in cis and trans to help maintain pericentromeric heterochromatin. Remarkably, we show that synthetic repeat-derived siRNAs are sufficient to rescue Dicer-2 deficiency-induced defects in heterochromatin formation in interphase and chromosome segregation during mitosis, thus demonstrating that active retrotransposons are actually required for stable genetic inheritance.

genomics↗

bioRxiv2019

Entry by multiple picornaviruses is dependent on a pathway that includes TNK2, WASL and NCK1

Comprehensive knowledge of the host factors required for picornavirus infection would facilitate antiviral development. Here we demonstrate roles for three human genes, TNK2, WASL, and NCK1, in infection by multiple picornaviruses. CRISPR deletion of TNK2, WASL or NCK1 reduced encephalomyocarditis virus (EMCV), coxsackievirus B3 (CVB3), poliovirus and enterovirus D68 infection, and chemical inhibitors of TNK2 and WASL decreased EMCV infection. Reduced EMCV lethality was observed in mice lacking TNK2. TNK2, WASL and NCK1 were important in early stages of the viral lifecycle, and genetic epistasis analysis demonstrated that the three genes function in a common pathway. Mechanistically, reduced internalization of EMCV was observed in TNK2 deficient cells demonstrating that TNK2 functions in EMCV entry. Domain analysis of WASL demonstrated that its actin nucleation activity was necessary to facilitate viral infection. Together, these data support a model wherein TNK2, WASL, and NCK1 comprise a pathway critical for multiple picornaviruses.

microbiology↗