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Results for “Bioinformatics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 901 records · Page 50Linked to original sources

bioRxiv2018

GoFish: A Streamlined Environmental DNA Presence/Absence Assay for Marine Vertebrates

Here we describe GoFish, a streamlined environmental DNA (eDNA) presence/absence assay. The assay amplifies a 12S segment with broad-range vertebrate primers, followed by nested PCR with M13-tailed, species-specific primers. Sanger sequencing confirms positives detected by gel electrophoresis. We first obtained 12S sequences from 77 fish specimens representing 36 northwestern Atlantic taxa not well documented in GenBank. Using the newly obtained and published 12S records, we designed GoFish assays for 11 bony fish species common in the lower Hudson River estuary and tested seasonal abundance and habitat preference at two sites. Additional assays detected nine cartilaginous fish species and a marine mammal, bottlenose dolphin, in southern New York Bight. GoFish sensitivity was equivalent to Illumina MiSeq metabarcoding. Unlike quantitative PCR (qPCR), GoFish does not require tissues of target and related species for assay development and a basic thermal cycler is sufficient. Unlike Illumina metabarcoding, indexing and batching samples are unnecessary and advanced bioinformatics expertise is not needed. The assay can be carried out from water collection to result in three days. The main limitations so far are species with shared target sequences and inconsistent amplification of rarer eDNAs. We think this approach will be a useful addition to current eDNA methods when analyzing presence/absence of known species, when turnaround time is important, and in educational settings.

ecology↗

bioRxiv2018

Identification and quantification of Lyme pathogen strains by deep sequencing of outer surface protein C (ospC) amplicons

Mixed infection of a single tick or host by Lyme disease spirochetes is common and a unique challenge for diagnosis, treatment, and surveillance of Lyme disease. Here we describe a novel protocol for differentiating Lyme strains based on deep sequencing of the hypervariable outer-surface protein C locus (ospC). Improving upon the traditional DNA-DNA hybridization method, the next-generation sequencing-based protocol is high-throughput, quantitative, and able to detect new pathogen strains. We applied the method to over one hundred infected Ixodes scapularis ticks collected from New York State, USA in 2015 and 2016. Analysis of strain distributions within individual ticks suggests an overabundance of multiple infections by five or more strains, inhibitory interactions among co-infecting strains, and presence of a new strain closely related to Borreliella bissettiae. A supporting bioinformatics pipeline has been developed. With the newly designed pair of universal ospC primers targeting intergenic sequences conserved among all known Lyme pathogens, the protocol could be used for culture-free identification and quantification of Lyme pathogens in wildlife and clinical specimens across the globe.

microbiology↗

bioRxiv2018

Applications for deep learning in ecology

A lot of hype has recently been generated around deep learning, a group of artificial intelligence approaches able to break accuracy records in pattern recognition. Over the course of just a few years, deep learning revolutionized several research fields such as bioinformatics or medicine. Yet such a surge of tools and knowledge is still in its infancy in ecology despite the ever-growing size and the complexity of ecological datasets. Here we performed a literature review of deep learning implementations in ecology to identify its benefits in most ecological disciplines, even in applied ecology, up to decision makers and conservationists alike. We also provide guidelines on useful resources and recommendations for ecologists to start adding deep learning to their toolkit. At a time when automatic monitoring of populations and ecosystems generates a vast amount of data that cannot be processed by humans anymore, deep learning could become a necessity in ecology.

ecology↗

bioRxiv2018

Removal of alleles by genome editing -- RAGE against the deleterious load

BackgroundIn this paper, we simulate deleterious load in an animal breeding program, and compare the efficiency of genome editing and selection for decreasing load. Deleterious variants can be identified by bioinformatics screening methods that use sequence conservation and biological prior information about protein function. Once deleterious variants have been identified, how can they be used in breeding?\n\nResultsWe simulated a closed animal breeding population subject to both natural selection against deleterious load and artificial selection for a quantitative trait representing the breeding goal. Deleterious load was polygenic and due to either codominant or recessive variants. We compared strategies for removal of deleterious alleles by genome editing (RAGE) to selection against carriers. Each strategy varied in how animals and variants were prioritized for editing or selection.\n\nConclusionsGenome editing of deleterious alleles reduces deleterious load, but requires simultaneous editing of multiple deleterious variants in the same sire to be effective when deleterious variants are recessive. In the short term, selection against carriers is a possible alternative to genome editing when variants are recessive. The dominance of deleterious variants affects both the efficiency of genome editing and selection against carriers, and which variant prioritization strategy is the most efficient. Our results suggest that in the future, there is the potential to use RAGE against deleterious load in animal breeding.

genetics↗

bioRxiv2018

Identification of pathogens in culture-negative infective endocarditis with metagenomic analysis

Pathogens identification is critical for the proper diagnosis and precise treatment of infective endocarditis. Although blood and valve cultures are the gold standard for IE pathogens detection, many cases are culture-negative, especially in patients who had received long-term antibiotic treatment, and precise diagnosis has therefore become a major challenge in the clinic. Metagenomic sequencing can provide both information on the pathogenic strain and the antibiotic susceptibility profile of patient samples without culturing, offering a powerful method to deal with culture-negative cases. In this work, we assessed the feasibility of a metagenomic approach to detect the causative pathogens in resected valves from IE patients.\n\nUsing our in-house developed bioinformatics pipeline, we analyzed the sequencing results generated from both next-generation sequencing and Oxford Nanopore Technologies MinION nanopore sequencing for the direct identification of pathogens from the resected valves of seven clinically culture-negative IE patients according to the modified Duke criteria. Moreover, we were able to simultaneously characterize respective antimicrobial resistance features. This provides clinicians with valuable information to diagnose and treat IE patients after valve replacement surgery.

microbiology↗

bioRxiv2018

Ataxia Telangiectasia triggers deficits in Reelin pathway

Autosomal recessive Ataxia Telangiectasia (A-T) is characterized by radiosensitivity, immunodeficiency and cerebellar neurodegeneration. A-T is caused by inactivating mutations in the Ataxia-Telangiectasia-Mutated (ATM) gene, a serine-threonine protein kinase involved in DNA-damage response and excitatory neurotransmission. The selective vulnerability of cerebellar Purkinje neurons (PN) to A-T is not well understood.\n\nEmploying global proteomic profiling of cerebrospinal fluid from patients at ages around 15 years we detected reduced Calbindin, Reelin, Cerebellin-1, Cerebellin-3, Protocadherin Fat 2, Sempahorin 7A and increased Apolipoprotein -B, -H, -J peptides. Bioinformatic enrichment was observed for pathways of chemical response, locomotion, calcium binding and complement immunity. This seemed important, since secretion of Reelin from glutamatergic afferent axons is crucial for PN radial migration and spine homeostasis. Reelin expression is downregulated by irradiation and its deficiency is a known cause of ataxia. Validation efforts in 2-month-old Atm-/- mice before onset of motor deficits confirmed transcript reductions for Reelin receptors Apoer2/Vldlr with increases for their ligands Apoe/Apoh and cholesterol 24-hydroxylase Cyp46a1. Concomitant dysregulations were found for Vglut2/Sema7a as climbing fiber markers, glutamate receptors like Grin2b and calcium homeostasis factors (Atp2b2, Calb1, Itpr1), while factors involved in DNA damage, oxidative stress, neuroinflammation and cell adhesion were normal at this stage.\n\nThese findings show that deficient levels of Reelin signaling factors reflect the neurodegeneration in A-T in a sensitive and specific way. As an extracellular factor, Reelin may be accessible for neuroprotective interventions.

neuroscience↗

bioRxiv2018

Chromomycin A2 potently inhibits glucose-stimulated insulin secretion from pancreatic beta cells.

Enhancers or inhibitors of insulin secretion could become therapeutics as well as lead to the identification of requisite {beta}-cell regulatory pathways and increase our understanding of pancreatic islet function. Toward this goal, we previously used an insulin-linked luciferase that is co-secreted with insulin in MIN6 {beta}-cells to perform a high-throughput natural product screen for chronic effects on glucose-stimulated insulin secretion. Using multiple phenotypic analyses, we identified that one of the top natural product hits, chromomycin A2 (CMA2), potently inhibited insulin secretion through at least three mechanisms: disruption of Wnt signaling, interfering with {beta}-cell gene expression, and suppression of triggering calcium (Ca2+) influx. Chronic treatment with CMA2 largely ablated glucose-stimulated insulin secretion even post-washout, but did not inhibit glucose-stimulated generation of ATP or Ca2+ influx. However, by using the KATP channel-opener diazoxide, we uncovered defects in depolarization-induced Ca2+ influx which may contribute to the suppressed secretory response. Glucose-responsive ERK1/2 and S6 phosphorylation were also disrupted by chronic CMA2 treatment. The FUSION bioinformatic database indicated that the phenotypic effects of CMA2 clustered with a number of Wnt/GSK3 pathway-related genes. Consistently, CMA2 decreased GSK3 phosphorylation and suppressed activation of a {beta}-catenin activity reporter. CMA2 and a related compound mithramycin are described to have DNA-interaction properties, possibly abrogating transcription factor binding to critical {beta}-cell gene promoters. We observed that CMA2, but not mithramycin, suppressed expression of PDX1 and UCN3. However, neither expression of INSI/II nor insulin content was affected by chronic CMA2. The mechanisms of CMA2-induced insulin secretion defects may involve components both proximal and distal to Ca2+ influx. Therefore, CMA2 is an example of a chemical that can simultaneously disrupt {beta}-cell function through both non-cytotoxic and cytotoxic mechanisms. Future applications of CMA2 and similar aureolic acid analogs for disease therapies should consider the potential impacts on pancreatic islet function.

cell biology↗

bioRxiv2018

TuxNet: A simple interface to process RNA sequencing data and infer gene regulatory networks

Predicting gene regulatory networks (GRNs) from gene expression profiles has become a common approach for identifying important biological regulators. Despite the increase in the use of inference methods, existing computational approaches do not integrate RNA-sequencing data analysis, are often not automated, and are restricted to users with bioinformatics and programming backgrounds. To address these limitations, we have developed TuxNet, an integrated user-friendly platform, which, with just a few selections, allows to process raw RNA-sequencing data (using the Tuxedo pipeline) and infer GRNs from these processed data. TuxNet is implemented as a graphical user interface and, using expression data from any organism with an existing reference genome, can mine the regulations among genes either by applying a dynamic Bayesian network inference algorithm, GENIST, or a regression tree-based pipeline that uses spatiotemporal data, RTP-STAR. To illustrate the use of TuxNet while getting insight into the regulatory cascade downstream of the Arabidopsis root stem cell regulator PERIANTHIA (PAN), we obtained time course gene expression data of a PAN inducible line and inferred a GRN using GENIST. Using RTP-STAR, we then inferred the network of a PAN secondary downstream gene, ATHB13, for which we obtained wildtype and mutant expression profiles. Our case studies feature the versatility of TuxNet to infer networks using different types of gene expression data (i.e time course and steady-state data) as well as how inference networks are used to identify important regulators.\n\nSUMMARYTuxNet offers a simple interface for non-computational biologists to infer GRNs from raw RNA-seq data.

plant biology↗

bioRxiv2018

Developing A Programmable, Self-Assembling Squash Leaf Curl China Virus (SLCCNV) Capsid Proteins Into \"Nano-Cargo\"-Like Architecture: A Next-Generation \"Nanotool\" For Biomedical Applications

A new era has begun in which pathogens have become useful scaffolds for nanotechnology applications. In this research/study, an attempt has been made to generate an empty cargo-like architecture from a high-profile plant pathogen of Squash leaf curl China virus (SLCCNV). In this approach, SLCCNV coat protein monomers are obtained efficiently by using a yeast Pichia pastoris expression system. Further, dialysis of purified SLCCNV-CP monomers against various pH strengthenened (5-10) disassembly and assembly buffers produced a self-assembled \"Nanocargo\"-like architecture, which also exhibited an ability to encapsulate the magnetic nanoparticles at in vitro. Bioinformatics tools were also utilized to predict the possible self-assembly kinetics and bioconjugation sites as well. The biocompatibility of \"SLCNNV-CP-Nanocargo\" particles was also evaluated by in vitro cancer cells, which eventually proved the particles to be versatile material for the next generation \"nanotool\" capable of housing various therapeutic or imaging agents.

systems biology↗

bioRxiv2018

Connectivity analyses of bioenergetic changes in schizophrenia: Identification of novel treatments

We utilized a cell-level approach to examine glycolytic pathways in the DLPFC of subjects with schizophrenia (n=16) and control (n=16) subjects and found decreased mRNA expression of glycolytic enzymes in pyramidal neurons, but not astrocytes. To replicate these novel bioenergetic findings, we probed independent datasets for bioenergetic targets and found similar abnormalities. Next, we used a novel strategy to build a schizophrenia bioenergetic profile by a tailored application of the Library of Integrated Network-Based Cellular Signatures data portal (iLINCS) and investigated connected cellular pathways, kinases, and transcription factors using Enrichr. Finally, with the goal of identifying drugs capable of \"reversing\" the bioenergetic schizophrenia signature, we performed a connectivity analysis with iLINCS and identified peroxisome proliferator-activated receptor (PPAR) agonists as promising therapeutic targets. We administered a PPAR agonist to the GluN1 knockdown model of schizophrenia and found it improved long-term memory. Taken together, our findings suggest that tailored bioinformatics approaches, coupled with the LINCS library of transcriptional signatures of chemical and genetic perturbagens may be employed to identify novel treatment strategies for schizophrenia and related diseases.

neuroscience↗

bioRxiv2018

Adomaviruses: an emerging virus family provides insights into DNA virus evolution

Adenoviruses, papillomaviruses, and polyomaviruses are collectively known as small DNA tumor viruses. Although it has long been recognized that small DNA tumor virus oncoproteins and capsid proteins show a variety of structural and functional similarities, it is unclear whether these similarities reflect descent from a common ancestor, convergent evolution, horizontal gene transfer among virus lineages, or acquisition of genes from host cells. Here, we report the discovery of a dozen new members of an emerging virus family, the Adomaviridae, that unite a papillomavirus/polyomavirus-like replicase gene with an adenovirus-like virion maturational protease. Adomaviruses were initially discovered in a lethal disease outbreak among endangered Japanese eels. New adomavirus genomes were found in additional commercially important fish species, such as tilapia, as well as in reptiles. The search for adomavirus sequences also revealed an additional candidate virus family, which we refer to as xenomaviruses, in mollusk datasets. Analysis of native adomavirus virions and expression of recombinant proteins showed that the virion structural proteins of adomaviruses are homologous to those of both adenoviruses and another emerging animal virus family called adintoviruses. The results pave the way toward development of vaccines against adomaviruses and suggest a framework that ties small DNA tumor viruses into a shared evolutionary history. Author SummaryIn contrast to cellular organisms, viruses do not encode any universally conserved genes. Even within a given family of viruses, the amino acid sequences encoded by homologous genes can diverge to the point of unrecognizability. Although members of an emerging virus family, the Adomaviridae, encode replicative DNA helicase proteins that are recognizably similar to those of polyomaviruses and papillomaviruses, the functions of other adomavirus genes have been difficult to identify. Using a combination of laboratory and bioinformatic approaches, we identify the adomavirus virion structural proteins. The results link adomavirus virion protein operons to those of other midsize non-enveloped DNA viruses, including adenoviruses and adintoviruses.

microbiology↗

bioRxiv2018

Predicting clone genotypes from tumor bulk sequencing of multiple samples

MotivationAnalyses of data generated from bulk sequencing of tumors have revealed extensive genomic heterogeneity within patients. Many computational methods have been developed to enable the inference of genotypes of tumor cell populations (clones) from bulk sequencing data. However, the relative and absolute accuracy of available computational methods in estimating clone counts and clone genotypes is not yet known.\n\nResultsWe have assessed the performance of nine methods, including eight previously-published and one new method (CloneFinder), by analyzing computer simulated datasets. CloneFinder, LICHeE, CITUP, and cloneHD inferred clone genotypes with low error (<5% per clone) for a majority of datasets in which the tumor samples contained evolutionarily-related clones. Computational methods did not perform well for datasets in which tumor samples contained mixtures of clones from different clonal lineages. Generally, the number of clones was underestimated by cloneHD and overestimated by Phy-loWGS, and BayClone2, Canopy, and Clomial required prior information regarding the number of clones. AncesTree and Canopy did not produce results for a large number of datasets.\n\nConclusionsDeconvolution of clone genotypes from single nucleotide variant (SNV) frequency differences among tumor samples remains challenging, so there is a need to develop more accurate computational methods and robust software for clone genotype inference.\n\nAvailability and ImplementationCloneFinder is implemented in Python and is available from https://github.com/gstecher/CloneFinderAPI.\n\nContacts.kumar@temple.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online

cancer biology↗

bioRxiv2018

A novel amidase signature family amidase from the marine actinomycete Salinispora arenicola CNS-205

We cloned a new gene from the amidase signature (AS) family, designated am, from the marine actinomycete Salinispora arenicola CNS-205. As indicated by bioinformatics analysis and site-directed mutagenesis, the AM protein belonged to the AS family. AM was expressed, purified, and characterised in Escherichia coli BL21 (DE3), and the AM molecular mass was determined to be 51 kDa. The optimal temperature and pH were 40 {degrees}C and pH 8.0, respectively. AM exhibited a wide substrate spectrum and showed amidase, aryl acylamidase, and acyl transferase activities. AM had high activity towards aromatic and aliphatic amides. The AM substrate specificity for anilides was very narrow; only propanil could be used as an effective substrate. The extensive substrate range of AM indicates it may have broad potential applications in biosynthetic processes and biodegradation.

molecular biology↗

bioRxiv2018

Identification and characterization of conserved and divergent genes encoding the nuclear envelope LINC complex in maize (Zea mays L.).

The LINC (Linker of Nucleoskeleton to Cytoskeleton) complex is an essential multi-protein structure spanning the nuclear envelope. It connects the cytoplasm to the nucleoplasm, functions to maintain nuclear shape and architecture, and regulates chromosome dynamics during cell division. Knowledge of LINC complex composition and function in the plant kingdom is primarily limited to Arabidopsis, but critically missing from the evolutionarily distant monocots which include grasses, the most important agronomic crops worldwide. To fill this knowledge gap, we identified and characterized 22 maize genes, including a new grass-specific KASH gene family. Using bioinformatic, biochemical, and cell biological approaches, we provide evidence that representative KASH candidates localize to the nuclear periphery and interact with ZmSUN2 in vivo. FRAP experiments using domain-deletion constructs verified that this SUN-KASH interaction was dependent on the SUN but not the coiled-coil domain of ZmSUN2. A summary working model is proposed for the entire maize LINC complex encoded by conserved and divergent gene families. These findings expand our knowledge of the plant nuclear envelope in a model grass species, with implications for both basic and applied cellular research.\n\nSUMMARY STATEMENTGenes encoding maize candidates for the core LINC and associated complex proteins have been comprehensively identified with functional validation by one or more assays for several of the KASH genes.

cell biology↗

bioRxiv2018

Long-read metagenomics reveals cryptic and abundant marine viruses

Marine viruses impact global biogeochemical cycles via their influence on host community structure and function, yet our understanding of viral ecology is constrained by limitations in culturing of important hosts and the lack of a universal gene to facilitate community surveys. Short-read viral metagenomic studies have provided clues to viral function and first estimates of global viral gene abundance and distribution. However, short-read assemblies are confounded by populations with high levels of strain evenness and nucleotide diversity (microdiversity), limiting assembly of some of the most abundant viruses on Earth. Assembly across genomic islands which likely contain niche-defining genes that drive ecological speciation is also challenging. While such populations and features are successfully captured by single-virus genomics and fosmid-based approaches, both techniques require considerable cost and technical expertise. Here we established a low-cost, low-input, high throughput alternative method for improving assembly of viral metagenomics using long read technology. Named VirION (Viral, long-read metagenomics via MinION sequencing), our sequencing approach and complementary bioinformatics pipeline (i) increased number and completeness of assembled viral genomes compared to short-read sequencing methods; (ii) captured populations of abundant viruses with high microdiversity missed by short-read methods and (iii) captured more and longer genomic islands than short-read methods. Thus, VirION provides a high throughput and cost-effective alternative to fosmid and single-virus genomic approaches to more comprehensively explore viral communities in nature.

genomics↗

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

Signal sequences in the genome of Mononegavirales regulate the generation of copy-back defective viral genomes

Defective viral genomes of the copy-back type (cbDVGs) are the primary initiators of the antiviral immune response during infection with respiratory syncytial virus (RSV) both in vitro and in vivo. However, the mechanism governing cbDVG generation remains unknown, thereby limiting our ability to manipulate cbDVG content in order to modulate the host response to infection. Here we report a specific genomic signal that mediates the generation of RSV cbDVGs. Using a customized bioinformatics tool, we identified regions in the RSV genome frequently used to generate cbDVGs during infection. We then created a minigenome system to validate the function of one of these sequences and to determine if specific nucleotides were essential for cbDVG generation at that position. Further, we created a recombinant virus that selectively produced a specific cbDVG based on variations introduced in this sequence. The identified sequence was also found as a common site for cbDVG generation during natural RSV infections, and common cbDVGs generated at this sequence were found among samples from various infected patients. These data demonstrate that sequences encoded in the viral genome are critical determinants of the location of cbDVG generation and, therefore, this is not a stochastic process. Most importantly, these findings open the possibility of genetically manipulating cbDVG formation to modulate infection outcome. Author summaryCopy-back defective viral genomes (cbDVGs) regulate infection and pathogenesis of Mononegavirales. cbDVG are believed to arise from random errors that occur during virus replication and the predominant hypothesis is that the viral polymerase is the main driver of cbDVG generation. Here we describe a specific genomic sequence in the RSV genome that is necessary for the generation of a large proportion of the cbDVG population present during infection. We identified specific nucleotides that when modified altered cbDVG generation at this position, and we created a recombinant virus that selectively produced cbDVGs based on mutations in this sequence. These data demonstrate that the generation of RSV cbDVGs is regulated by specific viral sequences and that these sequences can be manipulated to alter the content and quality of cbDVG generated during infection.

microbiology↗

bioRxiv2018

14-3-3 recruits keratin intermediate filaments to mechanically sensitive cell-cell contacts

AbstractIntermediate filament cytoskeletal networks simultaneously support mechanical integrity and influence signal transduction pathways. Marked remodeling of the keratin intermediate filament network accompanies collective cellular morphogenetic movements that occur during early embryonic development in the frog Xenopus laevis. While this reorganization of keratin is initiated by force transduction on cell-cell contacts mediated by C-cadherin, the mechanism by which keratin filament reorganization occurs remains poorly understood. In this work we demonstrate that 14-3-3 proteins regulate keratin reorganization dynamics in embryonic mesendoderm cells from Xenopus gastrula. 14-3-3 co-localizes with keratin filaments near cell-cell junctions in migrating mesendoderm. Co-immunoprecipitation, mass spectrometry and bioinformatic analyses indicate Keratin 19 is a target of 14-3-3 in the whole embryo and, more specifically, mesendoderm tissue. Inhibition of 14-3-3 results in both the decreased exchange of keratin subunits into filaments and blocks keratin filament recruitment toward cell-cell contacts. Synthetically coupling 14-3-3 to Keratin 19 through a unique fusion construct conversely induces the localization of this keratin population to the region of cell-cell contacts. Taken together, these findings indicate that 14-3-3 acts on keratin intermediate filaments and is involved in their reorganization to sites of cell adhesion.

cell biology↗