Biology subjects

Park, S.

Publications and source records attributed to Park, S..

17 recordsLinked to original sources

bioRxiv2026

OsPATROL1 overexpression accelerates stomatal opening to enhance photosynthetic induction and growth under fluctuating light in rice

Slow stomatal opening after increases in irradiance constrains carbon gain under fluctuating light, yet stomatal kinetics remain an underexplored target for crop improvement. Here, we investigated Oryza sativa PROTON ATPASE TRANSLOCATION CONTROL 1 (OsPATROL1), which encodes a Munc13-like protein implicated in stomatal regulation in Arabidopsis thaliana. OsPATROL1 overexpression had modest, condition-dependent effects on steady-state gas exchange and did not alter stomatal morphology or biochemical traits. In contrast, it consistently accelerated stomatal opening and photosynthetic induction, reducing the stomatal conductance time constant during induction by 41-43%. During 12 h of simulated natural fluctuating light, OsPATROL1-overexpressing plants maintained higher stomatal conductance and net CO2 assimilation rate, increasing cumulative assimilation by 8-12% while maintaining their intrinsic water-use efficiency (iWUE). Under artificial fluctuating light, overexpression alleviated growth reductions relative to steady light. Under glasshouse conditions, total biomass increased by 34-44%, accompanied by greater tiller number, root biomass, bleeding sap rate, and leaf nitrogen content. Taken together, these results indicate that OsPATROL1 overexpression accelerates stomatal opening, enhances photosynthetic induction and daytime carbon gain without compromising iWUE, and is associated with greater growth.

plant biology↗

bioRxiv2018

Cullin3-RING ubiquitin ligases are intimately linked to the unfolded protein response of the endoplasmic reticulum

CUL3-RING ubiquitin ligases (CRL3s) are involved in various cellular processes through different Bric a brac, Tramtrack and Broad-Complex (BTB)-domain proteins. KLHL12, a BTB-domain protein, appears to play an essential role in export of large cargo molecules like procollagen from the endoplasmic reticulum (ER). It has been suggested that CRL3KLHL12 mono-ubiquitinates SEC31 and mono-ubiquitinated SEC31 increases the dimension of a COPII coat to accommodate the large cargo molecules. As we examined this model, we found that functional CRL3KLHL12 was indeed critical for the assembly of large COPII structures. Interestingly, we noticed that CRL3KLHL12 influences collagen synthesis in human skin fibroblasts (HSFs). Our results also suggest that there is a CRL3KLHL12-independent collagen secretion route in HSFs. In addition, we found that CRL3KLHL12 strongly influences levels of sensors of the unfolded protein response (UPR). Different cell lines reacted differently to CUL3 depletion with respect to UPR regulation. This cell line-dependency appears to rely on a cell line-specific BTB-domain protein(s). Consistent with this idea, depletion of a muscle-specific BTB-domain protein KLHL41 recapitulated the effects of CUL3 depletion in C2C12 myotubes in UPR regulation. Based on these results we propose that CRL3KLHL12 and CRL3KLHL41 are regulators of the UPR.

cell biology↗

bioRxiv2018

Deep structural brain lesions associated with consciousness impairment early after haemorrhagic stroke

BackgroundThe significance of deep structural lesions on level of consciousness early after intracerebral haemorrhage (ICH) is largely unknown.\n\nMethodsWe studied a consecutive series of patients with spontaneous ICH that underwent MRI within 7 days of the bleed. We assessed consciousness by testing for command following from time of MRI to hospital discharge, and determined 3-months functional outcomes using the Glasgow Outcome Scale-Extended (GOS-E). ICH and oedema volumes, intraventricular haemorrhage (IVH), and midline shift (MLS) were quantified. Presence of blood and oedema in deep brain regions previously implicated in consciousness were assessed. A machine learning approach using logistic regression with elastic net regularization was applied to identify parameters that best predicted consciousness at discharge controlling for confounders.\n\nResultsFrom 158 ICH patients that underwent MRI, 66% (N=105) were conscious and 34% (N=53) unconscious at the time of MRI. Almost half of unconscious patients (49%, N= 26) recovered consciousness by ICU discharge. Focal lesions within subcortical structures predicted persistent impairment of consciousness at discharge together with MLS, IVH, and ICH and oedema volumes (AUC 0.74; 95%-CI 0.73-0.75). Caudate nucleus, midbrain peduncle, and pontine tegmentum were implicated as critical structures. Unconscious patients predicted to recover consciousness had better 3-month functional outcomes than those predicted to remain unconscious (35% vs 0% GOS-E [≥]4; p-value=0.02).\n\nConclusionMRI lesions within key subcortical structures together with measures reflecting the mass effect of the haemorrhage (lesion volumes, IVH, MLS) obtained within one week of ICH can help predict early recovery of consciousness and 3-month functional outcome.

neuroscience↗

bioRxiv2018

TDP-43 is more toxic in respiring than in non-respiring cells, but respiration is not absolutely required for TDP-43 toxicity.

The trans-activating response DNA-binding protein 43 (TDP-43) is a transcriptional repressor and splicing factor. TDP-43 is normally mostly in the nucleus, although it shuttles to the cytoplasm. Mutations in TDP-43 are one cause of familial amyotrophic lateral sclerosis (ALS). In neurons of these patients, TDP-43 forms cytoplasmic aggregates. In addition, wild-type TDP-43 is also frequently found in neuronal cytoplasmic aggregates in patients with neurodegenerative diseases not caused by TDP-43 mutations. TDP-43 expressed in yeast causes toxicity and forms cytoplasmic aggregates. This disease model has been validated because genetic modifiers of TDP-43 toxicity in yeast have led to the discovery that conserved genes in humans are ALS genetic risk factors. While it is still unknown how TDP-43 is associated with toxicity, several studies find that TDP-43 alters mitochondrial function. We now report that TDP-43 is much more toxic when yeast is grown in non-fermentable media requiring respiration than when grown on fermentable carbon sources. However, we also establish that TDP-43 remains toxic in the absence of respiration. Thus, there is a TDP-43 toxicity target in yeast distinct from respiration and respiration is not required for this toxicity. Since we find that H2O2 increases the toxicity of TDP-43, the free oxygen radicals associated with respiration could likewise enhance the toxicity of TDP-43. In this case, the TDP-43 toxicity targets in the presence or absence of respiration could be identical, with the free radical oxygen species produced by respiration activating TDP-43 to become more toxic or making TDP-43 targets more vulnerable.\n\nHighlightsO_LITDP-43 toxicity and aggregation is enhanced when yeast are grown in media that requires respiration.\nC_LIO_LIRespiration is not the sole target of TDP-43 toxicity because TDP-43 still aggregates and is toxic in cells that are not respiring.\nC_LIO_LIHydrogen peroxide enhances TDP-43 toxicity in the absence of respiration suggesting that reactive oxygen species (ROS) produced by respiration may likewise enhance TDP-43 toxicity.\nC_LIO_LIROS could activate TDP-43 to become more toxic or make TDP-43 targets more vulnerable.\nC_LI\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/415893_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@85d24aorg.highwire.dtl.DTLVardef@1b103d3org.highwire.dtl.DTLVardef@72280dorg.highwire.dtl.DTLVardef@a3a82e_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2018

A yeast model of calcium-responsive transactivator protein (CREST) proteinopathy shows that PBP1/ATXN2 modifies CREST aggregation and toxicity.

Proteins associated with familial neurodegenerative disease often aggregate in patients neurons. Several such proteins, e.g. TDP-43, aggregate and are toxic when expressed in yeast. Deletion of the ATXN2 ortholog, PBP1, reduces yeast TDP-43 toxicity, which led to identification of ATXN2 as an amyotrophic lateral sclerosis (ALS) risk factor and therapeutic target. Likewise, new yeast neurodegenerative disease models could facilitate identification of other risk factors and targets. Mutations in SS18L1, encoding the calcium-responsive transactivator (CREST) chromatin-remodeling protein, are associated with ALS. We show that CREST is toxic in yeast and forms nuclear and occasionally cytoplasmic foci that stain with Thioflavin-T, a dye indicative of amyloid-like protein. Like the yeast chromatin-remodeling factor SWI1, CREST inhibits silencing of FLO genes. Toxicity of CREST is enhanced by the [PIN+] prion and reduced by deletion of the HSP104 chaperone required for the propagation of many yeast prions. Likewise, deletion of PBP1 reduced CREST toxicity and aggregation. In accord with the yeast data, we show that the Drosophila ortholog of human ATXN2, dAtx2, is a potent enhancer of CREST toxicity. Downregulation of dAtx2 in flies overexpressing CREST in retinal ganglion cells was sufficient to largely rescue the severe degenerative phenotype induced by human CREST. Overexpression caused considerable co-localization of CREST and PBP1/ATXN2 in cytoplasmic foci in both yeast and mammalian cells. Thus, co-aggregation of CREST and PBP1/ATXN2 may serve as one of the mechanisms of PBP1/ATXN2-mediated toxicity. These results extend the spectrum of ALS associated proteins whose toxicity is regulated by PBP1/ATXN2, suggesting that therapies targeting ATXN2 may be effective for a wide range of neurodegenerative diseases.\n\nAuthor summaryMutations in the calcium-responsive transactivator (CREST) protein have been shown to cause amyotrophic lateral sclerosis (ALS). Here we show that the human CREST protein expressed in yeast forms largely nuclear aggregates and is toxic. We also show that the HSP104 chaperone required for propagation of yeast prions is likewise required for CREST toxicity. Furthermore deletion of HSP104 affects CREST aggregation. ATXN2, previously shown to modify ALS toxicity caused by mutations in the TDP-43 encoding gene, also modifies toxicity of CREST expressed in either yeast or flies. In addition, deletion of the yeast ATXN2 ortholog reduces CREST aggregation. These results extend the spectrum of ALS associated proteins whose toxicity is regulated by ATXN2, suggesting that therapies targeting ATXN2 may be effective for a wide range of neurodegenerative diseases.

molecular biology↗

bioRxiv2018

Accelerated FRET-PAINT Microscopy

Recent development of FRET-PAINT microscopy significantly improved the imaging speed of DNA-PAINT, the previously reported super-resolution fluorescence microscopy with no photobleaching problem. Here we try to achieve the ultimate speed limit of FRET-PAINT by optimizing the camera speed, dissociation rate of DNA probes, and bleed-through of the donor signal to the acceptor channel, and further increase the imaging speed of FRET-PAINT by 8-fold. Super-resolution imaging of COS-7 microtubules shows that high-quality 40-nm resolution images can be obtained in just tens of seconds.

biophysics↗

bioRxiv2018

Low-dose cadmium potentiates lung inflammatory response to 2009 pandemic H1N1 influenza virus in mice

BACKGROUNDCadmium (Cd) is a toxic, pro-inflammatory metal ubiquitous in the diet that accumulates in body organs due to inefficient elimination. Many individuals exposed to dietary Cd are also infected by seasonal influenza virus. The H1N1 strain causes mild to severe pneumonia which can be fatal.\n\nOBJECTIVESTo determine the influence of low-dose Cd exposure on inflammatory responses to H1N1 influenza A virus.\n\nMETHODSWe exposed mice to low-dose (1 mg CdCl2/l) Cd or vehicle (water) for 16 weeks prior to infection with a sub-lethal dose of H1N1. Lung inflammation was assessed by histopathology and flow cytometry. We used a combination of transcriptomics, metabolomics and bioinformatics to determine the molecular associations of inflammatory cells important in Cd-exacerbated responses.\n\nRESULTSCd-treated mice had increased lung tissue inflammatory cells, including neutrophils, monocytes, T lymphocytes and dendritic cells, following H1N1 infection. Lung genetic responses to infection (increasing TNF-a, interferon and complement, and decreasing myogenesis) were also exacerbated. Global correlations with immune cell counts, leading edge gene transcripts and metabolites revealed that Cd increased correlation of myeloid immune cells with pro-inflammatory genes, particularly interferon-{gamma}, and metabolites in amino acid, nucleobase, glycerophospholipid and vitamin B3 pathways.\n\nDISCUSSIONCd burden in mice increased inflammation in response to sub-lethal H1N1 challenge, which was coordinated by genetic and metabolic responses, and could provide new targets for intervention against lethal inflammatory pathology of clinical H1N1 infection.

pharmacology and toxicology↗

bioRxiv2018

MMOD-induced structural changes of hydroxylase in soluble methane monooxygenase

Soluble methane monooxygenase in methanotrophs converts methane to methanol under ambient conditions1-3. The maximum catalytic activity of hydroxylase (MMOH) is achieved via interplay of its regulatory protein (MMOB) and reductase4-6. An additional auxiliary protein, MMOD, is believed to function as an inhibitor of the catalytic activity of MMOH; however, the mechanism of its action remains unknown7,8. Herein, we report the crystal structure of MMOH-MMOD complex from Methylosinus sporium strain 5 (2.6 [A]), which illustrates that two molecules of MMOD associate symmetrically with the canyon region of MMOH in a manner similar to MMOB, indicating that MMOD competes with MMOB for MMOH recognition. Further, MMOD binding disrupts the geometry of the di-iron centre and opens the substrate access channel. Notably, the electron density of 1,6-hexanediol at the substrate access channel mimics products of sMMO in hydrocarbon oxidation. The crystal structure of MMOH-MMOD unravels the inhibitory mechanism by which MMOD suppresses the MMOH catalytic activity, and reveals how hydrocarbon substrates/products access to the di-iron centre.

biochemistry↗

bioRxiv2018

Impact of Chronic Total Occlusion Lesion Length onSix-month Angiographic and 2-year Clinical Outcomes

BackgroundSuccessful chronic total occlusion (CTO) percutaneous coronary intervention (PCI) is known to be associated with improved clinical outcomes compared with failed CTO PCI. However, it is not clear whether the angiographic and clinical outcomes of long CTO lesionis different with those of short CTO lesion in the drug eluting stent (DES) era.\n\nMethod sand ResultsA total of 235 consecutive patients underwent successful CTO intervention were divided into two groups according the CTO lesion length. Six-month angiographic and two-year clinical outcomes were compared between the two groups. The baseline clinical characteristics were similar between the two groups except prior PCI was more frequent in long CTO group whereas bifurcation lesion was more frequent in the short CTO group. In-hospital complications were similar between the two groups except intimal dissection was more frequent in long CTO group. Both groups had similar angiographic outcomes at 6 months and clinical outcomes up to 2 years except the incidence of repeat PCI, predominantly target vessel revascularization (TVR) was higher in long CTO group. In multivariate analysis, long CTO was an important predictor for repeat PCI (OR;4.26, CI 1.53-11.9, p=0.006).\n\nConclusionThe safety profile, angiographic and 2-year clinical outcomes were similar between the two groups except higher incidence of repeat PCI in long CTO group despite of successful PCI with DESs.

physiology↗

bioRxiv2018

Automatic Classification of Prostate Cancer Gleason Scores from Digitized Whole Slide Tissue Biopsies

Histological Gleason grading of tumor patterns is one of the most powerful prognostic predictors in prostate cancer. However, manual analysis and grading performed by pathologists are typically subjective and time-consuming. In this paper, we propose an automatic technique for Gleason grading of prostate cancer from H&E stained whole slide biopsy images using a set of novel completed and statistical local bi-nary pattern (CSLBP) descriptors. First the technique divides the whole slide image into a set of small image tiles, where salient tumor tiles with high nuclei densities are selected for analysis. The CSLBP texture features that encode pixel intensity variations from circularly surrounding neighborhoods are then extracted from salient image tiles to characterize different Gleason patterns. Finally, CSLBP texture features computed from all tiles are integrated and utilized by the multi-class support vector machine (SVM) that assigns patient biopsy with different Gleason score of 6, 7 or [≥]8. Experiments have been performed on 312 different patient cases selected from the cancer genome atlas (TCGA) and have achieved more than 79% classification accuracies, which is superior to state-of-the-art textural descriptors for prostate cancer Gleason grading.

bioinformatics↗

bioRxiv2018

Molecular Subtypes of Anaplastic Gliomas Identified with Somatic-Mutation and Pathway Based Gene Signature

PurposeAnaplastic gliomas constitute heterogeneous population with variable outcomes and no consensus on therapeutic approach. Molecular profiling may provide prognostication beyond clinical and pathologic factors and help guide treatment decisions.\n\nExperimental DesignThe Cancer Genome Atlas (TCGA) was utilized to derive a 39-gene low grade glioma-specific gene signature. Consensus clustering based on expression of the signature identified subgroups for 176 patients with anaplastic glioma from TCGA. Overall survival (OS) was analyzed for each subgroup. A total of 68 patients from Repository for Molecular Brain Neoplasia Data (REMBRANDT) were used as an independent validation dataset.\n\nResultsConsensus clustering separated the TCGA group into two distinct cohorts. The OS was significantly different between two subgroups, 20 vs. 67 months (p<0.001). On univariate analysis, the molecular subgroup, age, KPS, IDH1/2 mutation, 1p19q-co-deletion, chemotherapy, and use of both chemotherapy and radiation-therapy were significantly associated with OS. On multivariable analysis, the molecular subgroup remained significant with HR of 2.6 (p=.047, 95%CI [1.01-6.68]). In an independent validation with REMBRANDT, consensus clustering based on the signature successfully identified similarly poor prognostic subgroup with median survival of 14 months and concordance of expression patterns in 21 of the genes.\n\nConclusionExpression patterns of the 39 gene stratified anaplastic gliomas into two distinct subgroups with substantially different OS. This molecular prognostication was validated in an external dataset. Utilization of molecular subgroup, in addition to known prognostic factors may help define those requiring aggressive therapeutic intervention. Characteristic genes within the poor prognostic group may represent potential targets for therapeutic intensification.\n\nSource code and dataset used in this work is available for reviewers at: https://www.taehyunlab.org/ntripath\n\nImportance of the studyDespite the revolution of tailored therapy, anaplastic gliomas represent a category of tumors without clear treatment recommendations. While current prognostic factors help guide therapy recommendations, further refinement with the addition of molecular markers can help physicians with treatment recommendations. In this study, we developed a 39 gene prognostic gene signature by utilizing Pan-Cancer TCGA mutation profiles of over 5,000 patients across 19 different TCGA cancer types to stratify patients with anaplastic gliomas. We performed consensus clustering based on gene expression profiles of our 39-gene signature without any consideration of clinical factors or outcomes to TCGA anaplastic gliomas patients as well as an independent dataset and successfully identified two molecular subgroups with distinct clinical outcome. We found that subgroups have remarkably different survivals with a clear poor prognostic group. Furthermore, the poor prognostic group showed significant benefits for aggressive multimodality therapy, justifying the use of intensive therapy based on molecular stratification.

genomics↗

bioRxiv2018

B7-H1(PD-L1) confers chemoresistance through ERK and p38 MAPK pathway in tumor cells

Development of resistance to chemotherapy and immunotherapy is a major obstacle in extending the survival of patients with cancer. Although several molecular mechanisms have been identified that can contribute to chemoresistance, the role of immune checkpoint molecules in tumor chemoresistance remains underestimated. It has been recently observed that overexpression of B7-H1(PD-L1) confers chemoresistance in human cancers, however the underlying mechanisms are unclear. Here we show that the development of chemoresistance depends on the increased activation of ERK pathway in tumor cells overexpressing B7-H1. Conversely, B7-H1 deficiency renders tumor cells susceptible to chemotherapy in a cell-context dependent manner through activation of the p38 MAPK pathway. B7-H1 in tumor cells associates with the catalytic subunit of a DNA-dependent serine / threonine protein kinase (DNA-PKcs). DNA-PKcs is required for the activation of ERK or p38 MAPK in tumors expressing B7-H1, but not in B7-H1 negative or B7-H1 deficient tumors. Ligation of B7-H1 by anti-B7-H1 monoclonal antibody (H1A) increased the sensitivity of human triple negative breast tumor cells to cisplatin therapy in vivo. Our results suggest that B7-H1(PD-L1) expression in cancer cells modifies their chemosensitivity towards certain drugs and targeting B7-H1 intracellular signaling pathway is a new way to overcome cancer chemoresistance.

cancer biology↗

bioRxiv2018

Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy

Identifying functional enhancers elements in metazoan systems is a major challenge. For example, large-scale validation of enhancers predicted by ENCODE reveal false positive rates of at least 70%. Here we use the pregrastrula patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held out data results from heterogeneity of functional signatures in enhancer elements. We show that two classes of enhancer are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, over 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well predicted elements is composed predominantly of enhancers driving multi-stage, segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naive Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome, 916 of which are novel. An analysis of 32 novel SDEs using wholemount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.\n\nSignificance StatementWe demonstrate a high accuracy method for predicting enhancers genome wide with > 85% precision as validated by transgenic reporter assays in Drosophila embryos. This is the first time such accuracy has been achieved in a metazoan system, allowing us to predict with high-confidence 1640 enhancers, 916 of which are novel. The predicted enhancers are demarcated by heterogeneous collections of epigenetic marks; many strong enhancers are free from classical indicators of activity, including H3K27ac, but are bound by key transcription factors. H3K27ac, often used as a one-dimensional predictor of enhancer activity, is an uninformative parameter in our data.

genomics↗

bioRxiv2017

Wx: a neural network-based feature selection algorithm for next-generation sequencing data

MotivationNext-generation sequencing (NGS), which allows the simultaneous sequencing of billions of DNA fragments simultaneously, has revolutionized how we study genomics and molecular biology by generating genome-wide molecular maps of molecules of interest. For example, an NGS-based transcriptomic assay called RNA-seq can be used to estimate the abundance of approximately 190,000 transcripts together. As the cost of next-generation sequencing sharply declines, researchers in many fields have been conducting research using NGS. The amount of information produced by NGS has made it difficult for researchers to choose the optimal set of target genes (or genomic loci).\n\nResultsWe have sought to resolve this issue by developing a neural network-based feature (gene) selection algorithm called Wx. The Wx algorithm ranks genes based on the discriminative index (DI) score that represents the classification power for distinguishing given groups. With a gene list ranked by DI score, researchers can institutively select the optimal set of genes from the highest-ranking ones. We applied the Wx algorithm to a TCGA pan-cancer gene-expression cohort to identify an optimal set of gene-expression biomarker (universal gene-expression biomarkers) candidates that can distinguish cancer samples from normal samples for 12 different types of cancer. The 14 gene-expression biomarker candidates identified by Wx were comparable to or outperformed previously reported universal gene expression biomarkers, highlighting the usefulness of the Wx algorithm for next-generation sequencing data. Thus, we anticipate that the Wx algorithm can complement current state-of-the-art analytical applications for the identification of biomarker candidates as an alternative method.\n\nAvailabilityhttps://github.com/deargen/DearWX\n\nContactkangk1204@dankook.ac.kr\n\nSupplementary informationSupplementary data are available at online.

bioinformatics↗

bioRxiv2017

p53 suppresses mutagenic RAD52 and POLθ pathways by orchestrating DNA replication restart homeostasis

Classically, p53 tumor-suppressor acts in transcription, apoptosis, and cell-cycle arrest. Yet, replication-mediated genomic instability is integral to oncogenesis, and p53 mutations promote tumor progression and drug-resistance. By delineating human and murine separation-of-function p53 alleles, we find that p53 null and gain-of-function (GOF) mutations exhibit defects in restart of stalled or damaged DNA replication forks driving genomic instability independent of transcription activation. By assaying protein-DNA fork interactions in single cells, we unveil a p53-MLL3-enabled recruitment of MRE11 DNA replication restart nuclease. Importantly, p53 defects or depletion unexpectedly allow mutagenic RAD52 and POL{theta} pathways to hijack stalled forks, which we find reflected in p53 defective breast-cancer patient COSMIC mutational signatures. These data uncover p53 as a keystone regulator of replication homeostasis within a DNA restart network. Mechanistically, this has important implications for development of resistance in cancer therapy. Combined, these results define an unexpected role for p53 suppression of replication genome instability.

genetics↗

bioRxiv2017

Holographic deep learning for rapid optical screening of anthrax spores

Establishing early warning systems for anthrax attacks is crucial in biodefense. Here we present an optical method for rapid screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells. After training, the network outperforms previous techniques in all accuracy measures, achieving single-spore sensitivity and sub-genus specificity. The unique representation learning capability of deep learning enables direct training from raw images instead of manually extracted features. The method automatically recognizes key biological traits encoded in the images and exploits them as fingerprints. This remarkable learning ability makes the proposed method readily applicable to classifying various single cells in addition to B. anthracis, as demonstrated for the diagnosis of Listeria monocytogenes, without any modification. We believe that our strategy will make holographic microscopy more accessible to medical doctors and biomedical scientists for easy, rapid, and accurate diagnosis of pathogens, and facilitate exciting new applications.

microbiology↗

bioRxiv2016

Super-resolution Imaging of Synaptic and Extra-synaptic Pools of AMPA Receptors with Different-sized Fluorescent Probes

Whether AMPA receptors (AMPARs) enter into neuronal synapses, by exocytosis from an internal pool, or by diffusion from an external membrane-bound pool, is hotly contested. 3D super-resolution fluorescent nanoscopy to measure the dynamics and placement of AMPAR is a powerful method for addressing this issue. However, probe size and accessibility to tightly packed spaces can be limiting. We have therefore labeled AMPARs with differently sized fluorophores: small organic fluorescent dyes (~ 4 nm), small quantum dots (sQD, ~10 nm in diameter), or big (commercial) quantum dots (bQD, ~ 20 nm in diameter). We then compared their diffusion rate, trajectories, and placement with respect to a postsynaptic density (PSD) protein, Homer 1c. Labeled with the small probes of sQDs or organic fluorophores, we find that AMPARs are located largely within PSDs (~73-93%), and generally reside in \"nanodomains\" with constrained diffusion. In contrast, when labeled with bQDs, only 5-10% of AMPARs are within PSDs. The results can be explained by relatively free access, or lack thereof, to synaptic clefts of the AMPARs when labeled with small or big probes, respectively. This implies that AMPARs primarily enter PSDs soon after their exocytosis and not from a large diffusive pool of extrasynaptic AMPARs.

neuroscience↗