Biology subjects

Nguyen, N.

Publications and source records attributed to Nguyen, N..

6 recordsLinked to original sources

bioRxiv2018

EGFR confers exquisite specificity of Wnt9a-Fzd9b signaling in hematopoietic stem cell development

The mechanisms of Wnt-Frizzled (Fzd) signaling selectivity and their biological implications remain unclear. We demonstrate for the first time that the epidermal growth factor receptor (EGFR) is required as a co-factor for Wnt signaling. Using genetic studies in zebrafish, paired with in vitro cell biology and biochemistry, we have determined that Fzd9b signals specifically with Wnt9a in vivo and in vitro to elicit {beta}-catenin dependent Wnt signals that regulate hematopoietic stem and progenitor cell (HSPC) development in the dorsal aorta. This requirement is conserved in the derivation of HSPCs from human embryonic stem cells. Wnt9a-Fzd9b specificity requires two intracellular domains in Fzd9b, which interact with EGFR as a required co-factor to promote signal transduction. EGFR phosphorylates one tyrosine residue on Fzd9b, a requirement for the Wnt signal. These findings indicate that Wnt signaling interactions can be exquisitely specific and inform protocols for derivation of HSPCs in vitro.\n\nHighlightsO_LIAn in vitro signaling screen identifies Fzd9b as a Wnt9a-specific receptor.\nC_LIO_LIFzd9b and Wnt9a regulate hematopoietic stem cell development as a cognate pair.\nC_LIO_LIWNT9A and FZD9 are required for HSPC derivation from human pluripotent cells in vitro.\nC_LIO_LIEGFR confers specificity to Wnt9a-Fzd9b signaling in zebrafish and human cells.\nC_LI

developmental biology↗

bioRxiv2018

A novel virulence phenotype rapidly assesses Candida fungal pathogenesis in healthy and immunocompromised Caenorhabditis elegans hosts

The yeast Candida albicans is an opportunistic pathogen of humans, meaning that despite commensal interactions with its host, it can transition to a harmful pathogen. While C. albicans is the predominant species isolated in the human mycobiome and implicated in fungal infection, infections due to non-albicans Candida species are rapidly rising. Studying the factors that contribute to virulence is often challenging and frequently depends on many contexts including host immune status and pathogen genetic background. Here, we utilize the nematode Caenorhabditis elegans as a perspicuous and efficient model host system to study fungal infections of Candida pathogens. We find that in addition to reducing lifetime host survival, exposure to C. albicans results in delayed reproduction, which significantly reduced lineage growth over multiple generations. Furthermore, we assessed fungal pathogen virulence in C. elegans hosts compromised for innate immune function and detected increased early mortality, reduced brood sizes and delayed reproduction relative to infected healthy hosts. Importantly, by assessing virulence in both healthy and immunocompromised host backgrounds we reveal the pathogen potential in non-albicans Candida species. Taken together, we present a novel lineage growth assay to measure reduction in host fitness associated with fungal infection and demonstrate significant interactions between pathogen and host immune function that contribute to virulence.

microbiology↗

bioRxiv2018

GABARAP Like-1 enrichment on membranes: Direct observation of trans-homo-oligomerization between membranes and curvature-dependent partitioning into membrane tubules.

The Atg8/LC3/GABARAP protein family has been implicated in membrane remodeling events on the growing autophagosome. In particular, each of these proteins can form a protein-lipid conjugate that has been shown in vitro to drive liposome aggregation and in some cases membrane fusion. Furthermore, yeast Atg8 has been described as a curvature sensing protein, through its natural capacity to concentrate on highly curved membranes. A key advance with yeast Atg8, was the introduction of Giant Unilamellar Vesicles (GUVs) as an in vitro support that could allow membrane deformation and tethering to be observed by simple microscopy. Further, micromanipulation of an individual GUV could be used to create local areas of curvature to follow Atg8 partitioning. Here, we use a recently developed method to decorate GUVs with the mammalian Atg8 protein GABARAPL1 and establish the generality of the observations made on yeast Atg8. Then we apply double micromanipulation, the capture and positioning of two independently prepared GUVs, to test elements of the mechanism, speed and reversibility of mammalian Atg8 protein-mediated tethering. We find that the membranes adhere through GABARAPL1/GABARAPL1 homotypic trans-interactions. On a single membrane with two regions with significantly different curvatures we observed that the regions of higher curvature can be enriched up to 10 times in GABARAPL1 compared to the planar regions. This approach has the potential to allow the formation and study of specific topographically-controlled interfaces involving Atg8-proteins and their targets on apposing membranes.

biophysics↗

bioRxiv2017

Minor spliceosome inactivation in the developing mouse cortex causes self-amplifying radial glial cell death and microcephaly.

Inactivation of the minor spliceosome has been linked to microcephalic osteodysplastic primordial dwarfism type 1 (MOPD1). To interrogate how minor intron splicing regulates cortical development, we employed Emx1-Cre to ablate Rnu11, which encodes the minor spliceosome-specific U11 small nuclear RNA (snRNA), in the developing cortex (pallium). Rnu11 cKO mice were born with microcephaly, caused by death of self-amplifying radial glial cells (RGCs). However, both intermediate progenitor cells (IPCs) and neurons were produced in the U11-null pallium. RNAseq of the pallium revealed elevated minor intron retention in the mutant, particularly in genes regulating cell cycle. Moreover, the only downregulated minor intron-containing gene (MIG) was Spc24, which regulates kinetochore assembly. These findings were consistent with the observation of fewer RGCs entering cytokinesis prior to RGC loss, underscoring the requirement of minor splicing for cell cycle progression in RGCs. Overall, we provide a potential explanation of how disruption of minor splicing might cause microcephaly in MOPD1.\n\nSummary StatementHere we report the first mammalian model to investigate the role of the minor spliceosome in cortical development and microcephaly.\n\nList of abbreviations usedMOPD1=microcephalic osteodysplastic primordial dwarfism type 1; snRNA=small nuclear RNA; cKO=conditional knockout; NPC=neural progenitor cell; RGC=radial glial cell; IPC=intermediate progenitor cell; MIG=minor intron-containing gene

developmental biology↗

bioRxiv2017

Inhibition of DNA2 nuclease as a therapeutic strategy targeting replication stress in cancer cells.

Replication stress is a characteristic feature of cancer cells, which is resulted from sustained proliferative signaling induced by activation of oncogenes or loss of tumor suppressors. In cancer cells, oncogene-induced replication stress manifests as replication-associated lesions, predominantly double-strand DNA breaks (DSBs). An essential mechanism utilized by cells to repair replication-associated DSBs is homologous recombination (HR). In order to overcome replication stress and survive, cancer cells often require enhanced HR repair capacity. Therefore, the key link between HR repair and cellular tolerance to replication-associated DSBs provides us with a mechanistic rationale for exploiting synthetic lethality between HR repair inhibition and replication stress. Our studies showed that DNA2 nuclease is an evolutionarily conserved essential component of HR repair machinery. Here we demonstrate that DNA2 is indeed overexpressed in pancreatic cancers, one of the deadliest and more aggressive forms of human cancers, where mutations in the KRAS are present in 90%-95% of cases. In addition, depletion of DNA2 significantly reduces pancreatic cancer cell survival and xenograft tumor growth, suggesting the therapeutic potential of DNA2 inhibition. Finally, we develop a robust high-throughput biochemistry assay to screen for inhibitors of the DNA2 nuclease activity. The top inhibitors were shown to be efficacious against both yeast Dna2 and human DNA2. Treatment of cancer cells with DNA2 inhibitors recapitulates phenotypes observed upon DNA2 depletion, including decreased DNA end resection and attenuation of HR repair. Similar to genetic ablation of DNA2, chemical inhibition of DNA2 selectively attenuates the growth of various cancer cells with oncogene-induced replication stress. Taken together, our findings open a new avenue to develop a new class of anti-cancer drugs by targeting druggable nuclease DNA2. We 4, 16. In propose DNA2 inhibition as new strategy in cancer therapy by targeting replication stress, a molecular property of cancer cells that is acquired as a result of oncogene activation instead of targeting undruggable oncoprotein itself such as KRAS.

molecular biology↗

bioRxiv2016

Creating a universal SNP and small indel variant caller with deep neural networks

Next-generation sequencing (NGS) is a rapidly evolving set of technologies that can be used to determine the sequence of an individuals genome1 by calling genetic variants present in an individual using billions of short, errorful sequence reads2. Despite more than a decade of effort and thousands of dedicated researchers, the hand-crafted and parameterized statistical models used for variant calling still produce thousands of errors and missed variants in each genome3,4. Here we show that a deep convolutional neural network5 can call genetic variation in aligned next-generation sequencing read data by learning statistical relationships (likelihoods) between images of read pileups around putative variant sites and ground-truth genotype calls. This approach, called DeepVariant, outperforms existing tools, even winning the \"highest performance\" award for SNPs in a FDA-administered variant calling challenge. The learned model generalizes across genome builds and even to other mammalian species, allowing non-human sequencing projects to benefit from the wealth of human ground truth data. We further show that, unlike existing tools which perform well on only a specific technology, DeepVariant can learn to call variants in a variety of sequencing technologies and experimental designs, from deep whole genomes from 10X Genomics to Ion Ampliseq exomes. DeepVariant represents a significant step from expert-driven statistical modeling towards more automatic deep learning approaches for developing software to interpret biological instrumentation data.

genomics↗