Enhancement of dielectrophoresis-based particle collection from high conducting fluids due to partial electrode insulation.

Dielectrophoresis (DEP) is a successful method to recover nanoparticles from different types of fluid. The DEP force acting on these particles is created by an electrode microarray that produces a nonuniform electric field. To apply DEP to a highly conducting biological fluid, a protective hydrogel coating over the metal electrodes is required to create a barrier between the electrode and the fluid. This protects the electrodes, reduces the electrolysis of water, and allows the electric field to penetrate into the fluid sample. We observed that the protective hydrogel layer can separate from the electrode and form a closed domed structure and that collection of 100 nm polystyrene beads increased when this occurred. To better understand this collection increase, we used COMSOL Multiphysics software to model the electric field in the presence of the dome filled with different materials ranging from low-conducting gas to high conducting phosphate-buffered saline fluids. The results suggest that as the electrical conductivity of the material inside the dome is reduced, the whole dome acts as an insulator which increases electric field intensity at the electrode edge. This increased intensity widens the high-intensity electric field factor zone resulting in increased collection. This informs how dome formation results in increased particle collection and provides insight into how the electric field can be intensified to the increase collection of particles. These results have important applications for increasing the recovery of biologically-derived nanoparticles from undiluted physiological fluids that have high conductance, including the collection of cancer-derived extracellular vesicles from plasma for liquid biopsy applications.

SeekFusion - A Clinically Validated Fusion Transcript Detection Pipeline for PCR-Based Next-Generation Sequencing of RNA.

Detecting gene fusions involving driver oncogenes is pivotal in clinical diagnosis and treatment of cancer patients. Recent developments in next-generation sequencing (NGS) technologies have enabled improved assays for bioinformatics-based gene fusions detection. In clinical applications, where a small number of fusions are clinically actionable, targeted polymerase chain reaction (PCR)-based NGS chemistries, such as the QIAseq RNAscan assay, aim to improve accuracy compared to standard RNA sequencing. Existing informatics methods for gene fusion detection in NGS-based RNA sequencing assays traditionally use a transcriptome-based spliced alignment approach or a de-novo assembly approach. Transcriptome-based spliced alignment methods face challenges with short read mapping yielding low quality alignments. De-novo assembly-based methods yield longer contigs from short reads that can be more sensitive for genomic rearrangements, but face performance and scalability challenges. Consequently, there exists a need for a method to efficiently and accurately detect fusions in targeted PCR-based NGS chemistries. We describe SeekFusion, a highly accurate and computationally efficient pipeline enabling identification of gene fusions from PCR-based NGS chemistries. Utilizing biological samples processed with the QIAseq RNAscan assay and in-silico simulated data we demonstrate that SeekFusion gene fusion detection accuracy outperforms popular existing methods such as STAR-Fusion, TOPHAT-Fusion and JAFFA-hybrid. We also present results from 4,484 patient samples tested for neurological tumors and sarcoma, encompassing details on some novel fusions identified.

Design considerations for workflow management systems use in production genomics research and the clinic.

The changing landscape of genomics research and clinical practice has created a need for computational pipelines capable of efficiently orchestrating complex analysis stages while handling large volumes of data across heterogeneous computational environments. Workflow Management Systems (WfMSs) are the software components employed to fill this gap. This work provides an approach and systematic evaluation of key features of popular bioinformatics WfMSs in use today: Nextflow, CWL, and WDL and some of their executors, along with Swift/T, a workflow manager commonly used in high-scale physics applications. We employed two use cases: a variant-calling genomic pipeline and a scalability-testing framework, where both were run locally, on an HPC cluster, and in the cloud. This allowed for evaluation of those four WfMSs in terms of language expressiveness, modularity, scalability, robustness, reproducibility, interoperability, ease of development, along with adoption and usage in research labs and healthcare settings. This article is trying to answer, which WfMS should be chosen for a given bioinformatics application regardless of analysis type?. The choice of a given WfMS is a function of both its intrinsic language and engine features. Within bioinformatics, where analysts are a mix of dry and wet lab scientists, the choice is also governed by collaborations and adoption within large consortia and technical support provided by the WfMS team/community. As the community and its needs continue to evolve along with computational infrastructure, WfMSs will also evolve, especially those with permissive licenses that allow commercial use. In much the same way as the dataflow paradigm and containerization are now well understood to be very useful in bioinformatics applications, we will continue to see innovations of tools and utilities for other purposes, like big data technologies, interoperability, and provenance.

Characterization of a RAD51C-silenced high-grade serous ovarian cancer model during development of PARP inhibitor resistance.

Acquired PARP inhibitor (PARPi) resistance in BRCA1- or BRCA2-mutant ovarian cancer often results from secondary mutations that restore expression of functional protein. RAD51C is a less commonly studied ovarian cancer susceptibility gene whose promoter is sometimes methylated, leading to homologous recombination (HR) deficiency and PARPi sensitivity. For this study, the PARPi-sensitive patient-derived ovarian cancer xenograft PH039, which lacks HR gene mutations but harbors RAD51C promoter methylation, was selected for PARPi resistance by cyclical niraparib treatment in vivo. PH039 acquired PARPi resistance by the third treatment cycle and grew through subsequent treatment with either niraparib or rucaparib. Transcriptional profiling throughout the course of resistance development showed widespread pathway level changes along with a marked increase in RAD51C mRNA, which reflected loss of RAD51C promoter methylation. Analysis of ovarian cancer samples from the ARIEL2 Part 1 clinical trial of rucaparib monotherapy likewise indicated an association between loss of RAD51C methylation prior to on-study biopsy and limited response. Interestingly, the PARPi resistant PH039 model remained platinum sensitive. Collectively, these results not only indicate that PARPi treatment pressure can reverse RAD51C methylation and restore RAD51C expression, but also provide a model for studying the clinical observation that PARPi and platinum sensitivity are sometimes dissociated.

Sentieon DNASeq Variant Calling Workflow Demonstrates Strong Computational Performance and Accuracy.

As reliable, efficient genome sequencing becomes ubiquitous, the need for similarly reliable and efficient variant calling becomes increasingly important. The Genome Analysis Toolkit (GATK), maintained by the Broad Institute, is currently the widely accepted standard for variant calling software. However, alternative solutions may provide faster variant calling without sacrificing accuracy. One such alternative is Sentieon DNASeq, a toolkit analogous to GATK but built on a highly optimized backend. We conducted an independent evaluation of the DNASeq single-sample variant calling pipeline in comparison to that of GATK. Our results support the near-identical accuracy of the two software packages, showcase optimal scalability and great speed from Sentieon, and describe computational performance considerations for the deployment of DNASeq.

Author Correction: ZSCAN10 expression corrects the genomic instability of iPSCs from aged donors.

In the version of this Article originally published, Supplementary Fig. 6j showed incorrect values for the LS and AG4 glutathione samples, and Fig. 5c and Supplementary Fig. 6j did not include all n = 6 samples for the hESC, Y-hiPSC and AG4-ZSCAN10 groups as was stated in the legend. In addition, the bars for hESC, Y-hiPSC, AG4-ZCNAN10, AG4 and LS in Supplementary Fig. 6i and j have been reproduced from Fig. 5b and c, respectively. Fig. 6e was also reproduced in the lower panel of Supplementary Fig. 6h, to enable direct comparison of the data, however this was not explained in the original figure legends. The correct versions of these figures and their legends are shown below, and Supplementary Table 5 has been updated with the source data for all numerical data in the manuscript.

Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling.

Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate.

RNA Exosome Complex-Mediated Control of Redox Status in Pluripotent Stem Cells.

The RNA exosome complex targets AU-rich element (ARE)-containing mRNAs in eukaryotic cells. We identified a transcription factor, ZSCAN10, which binds to the promoters of multiple RNA exosome complex subunits in pluripotent stem cells to maintain subunit gene expression. We discovered that induced pluripotent stem cell clones generated from aged tissue donors (A-iPSC) show poor expression of ZSCAN10, leading to poor RNA exosome complex expression, and a subsequent elevation in ARE-containing RNAs, including glutathione peroxidase 2 (Gpx2). Excess GPX2 leads to excess glutathione-mediated reactive oxygen species scavenging activity that blunts the DNA damage response and apoptosis. Expression of ZSCAN10 in A-iPSC recovers RNA exosome gene expression, the DNA damage response, and apoptosis. These findings reveal the central role of ZSCAN10 and the RNA exosome complex in maintaining pluripotent stem cell redox status to support a normal DNA damage response.

ZSCAN10 expression corrects the genomic instability of iPSCs from aged donors.

Induced pluripotent stem cells (iPSCs), which are used to produce transplantable tissues, may particularly benefit older patients, who are more likely to suffer from degenerative diseases. However, iPSCs generated from aged donors (A-iPSCs) exhibit higher genomic instability, defects in apoptosis and a blunted DNA damage response compared with iPSCs generated from younger donors. We demonstrated that A-iPSCs exhibit excessive glutathione-mediated reactive oxygen species (ROS) scavenging activity, which blocks the DNA damage response and apoptosis and permits survival of cells with genomic instability. We found that the pluripotency factor ZSCAN10 is poorly expressed in A-iPSCs and addition of ZSCAN10 to the four Yamanaka factors (OCT4, SOX2, KLF4 and c-MYC) during A-iPSC reprogramming normalizes ROS-glutathione homeostasis and the DNA damage response, and recovers genomic stability. Correcting the genomic instability of A-iPSCs will ultimately enhance our ability to produce histocompatible functional tissues from older patients' own cells that are safe for transplantation.

Conserved DNA methylation combined with differential frontal cortex and cerebellar expression distinguishes C9orf72-associated and sporadic ALS, and implicates SERPINA1 in disease.

We previously found C9orf72-associated (c9ALS) and sporadic amyotrophic lateral sclerosis (sALS) brain transcriptomes comprise thousands of defects, among which, some are likely key contributors to ALS pathogenesis. We have now generated complementary methylome data and combine these two data sets to perform a comprehensive "multi-omic" analysis to clarify the molecular mechanisms initiating RNA misregulation in ALS. We found that c9ALS and sALS patients have generally distinct but overlapping methylome profiles, and that the c9ALS- and sALS-affected genes and pathways have similar biological functions, indicating conserved pathobiology in disease. Our results strongly implicate SERPINA1 in both C9orf72 repeat expansion carriers and non-carriers, where expression levels are greatly increased in both patient groups across the frontal cortex and cerebellum. SERPINA1 expression is particularly pronounced in C9orf72 repeat expansion carriers for both brain regions, where SERPINA1 levels are strictly down regulated across most human tissues, including the brain, except liver and blood, and are not measurable in E18 mouse brain. The altered biological networks we identified contain critical molecular players known to contribute to ALS pathology, which also interact with SERPINA1. Our comprehensive combined methylation and transcription study identifies new genes and highlights that direct genetic and epigenetic changes contribute to c9ALS and sALS pathogenesis.

LIN28 Regulates Stem Cell Metabolism and Conversion to Primed Pluripotency.

The RNA-binding proteins LIN28A and LIN28B play critical roles in embryonic development, tumorigenesis, and pluripotency, but their exact functions are poorly understood. Here, we show that, like LIN28A, LIN28B can function effectively with NANOG, OCT4, and SOX2 in reprogramming to pluripotency and that reactivation of both endogenous LIN28A and LIN28B loci are required for maximal reprogramming efficiency. In human fibroblasts, LIN28B is activated early during reprogramming, while LIN28A is activated later during the transition to bona fide induced pluripotent stem cells (iPSCs). In murine cells, LIN28A and LIN28B facilitate conversion from naive to primed pluripotency. Proteomic and metabolomic analysis highlighted roles for LIN28 in maintaining the low mitochondrial function associated with primed pluripotency and in regulating one-carbon metabolism, nucleotide metabolism, and histone methylation. LIN28 binds to mRNAs of proteins important for oxidative phosphorylation and modulates protein abundance. Thus, LIN28A and LIN28B play cooperative roles in regulating reprogramming, naive/primed pluripotency, and stem cell metabolism.

A role for the bacterial GATC methylome in antibiotic stress survival.

Antibiotic resistance is an increasingly serious public health threat. Understanding pathways allowing bacteria to survive antibiotic stress may unveil new therapeutic targets. We explore the role of the bacterial epigenome in antibiotic stress survival using classical genetic tools and single-molecule real-time sequencing to characterize genomic methylation kinetics. We find that Escherichia coli survival under antibiotic pressure is severely compromised without adenine methylation at GATC sites. Although the adenine methylome remains stable during drug stress, without GATC methylation, methyl-dependent mismatch repair (MMR) is deleterious and, fueled by the drug-induced error-prone polymerase Pol IV, overwhelms cells with toxic DNA breaks. In multiple E. coli strains, including pathogenic and drug-resistant clinical isolates, DNA adenine methyltransferase deficiency potentiates antibiotics from the ß-lactam and quinolone classes. This work indicates that the GATC methylome provides structural support for bacterial survival during antibiotic stress and suggests targeting bacterial DNA methylation as a viable approach to enhancing antibiotic activity.

Distinct brain transcriptome profiles in C9orf72-associated and sporadic ALS.

Increasing evidence suggests that defective RNA processing contributes to the development of amyotrophic lateral sclerosis (ALS). This may be especially true for ALS caused by a repeat expansion in C9orf72 (c9ALS), in which the accumulation of RNA foci and dipeptide-repeat proteins are expected to modify RNA metabolism. We report extensive alternative splicing (AS) and alternative polyadenylation (APA) defects in the cerebellum of c9ALS subjects (8,224 AS and 1,437 APA), including changes in ALS-associated genes (for example, ATXN2 and FUS), and in subjects with sporadic ALS (sALS; 2,229 AS and 716 APA). Furthermore, heterogeneous nuclear ribonucleoprotein H (hnRNPH) and other RNA-binding proteins are predicted to be potential regulators of cassette exon AS events in both c9ALS and sALS. Co-expression and gene-association network analyses of gene expression and AS data revealed divergent pathways associated with c9ALS and sALS.

Cardiac transcriptome and dilated cardiomyopathy genes in zebrafish.

BACKGROUND: Genetic studies of cardiomyopathy and heart failure have limited throughput in mammalian models. Adult zebrafish have been recently pursued as a vertebrate model with higher throughput, but genetic conservation must be tested. METHODS AND RESULTS: We conducted transcriptome analysis of zebrafish heart and searched for fish homologues of 51 known human dilated cardiomyopathy-associated genes. We also identified genes with high cardiac expression and genes with differential expression between embryonic and adult stages. Among tested genes, 30 had a single zebrafish orthologue, 14 had 2 homologues, and 5 had ≥3 homologues. By analyzing the expression data on the basis of cardiac abundance and enrichment hypotheses, we identified a single zebrafish gene for 14 of 19 multiple-homologue genes and 2 zebrafish homologues of high priority for ACTC1. Of note, our data suggested vmhc and vmhcl as functional zebrafish orthologues for human genes MYH6 and MYH7, respectively, which are established molecular markers for cardiac remodeling. CONCLUSIONS: Most known genes for human dilated cardiomyopathy have a corresponding zebrafish orthologue, which supports the use of zebrafish as a conserved vertebrate model. Definition of the cardiac transcriptome and fetal gene program will facilitate systems biology studies of dilated cardiomyopathy in zebrafish.

The Geogenomic Mutational Atlas of Pathogens (GoMAP) web system.

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼ 502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/

Outbreak of pneumocystis pneumonia in renal and liver transplant patients caused by genotypically distinct strains of Pneumocystis jirovecii.

BACKGROUND: An outbreak of 29 cases of Pneumocystis jirovecii pneumonia (PCP) occurred among renal and liver transplant recipients (RTR and LTR) in the largest Danish transplantation centre between 2007 and 2010, when routine PCP prophylaxis was not used. METHODS: P. jirovecii isolates from 22 transplant cases, 2 colonized RTRs, and 19 Pneumocystis control samples were genotyped by restriction fragment length polymorphism and multilocus sequence typing analysis. Contact tracing was used to investigate transmission. Potential risk factors were compared between PCP cases and matched non-PCP transplant patients. RESULTS: Three unique Pneumocystis genotypes were shared among 19 of the RTRs, LTRs, and a colonized RTR in three distinct clusters, two of which overlapped temporally. In contrast, Pneumocystis control samples harbored a wide range of genotypes. Evidence of possible nosocomial transmission was observed. Among several potential risk factors, only cytomegalovirus viremia was consistently associated with PCP (P=0.03; P=0.009). Mycophenolate mofetil was associated with PCP risk only in the RTR population (P=0.04). CONCLUSION: We identified three large groups infected with unique strains of Pneumocystis and provide evidence of an outbreak profile and nosocomial transmission. LTRs may be infected in PCP outbreaks simultaneously with RTRs and by the same strains, most likely by interhuman transmission. Patients are at risk several years after transplantation, but the risk is highest during the first 6 months after transplantation. Because patients at risk cannot be identified clinically and outbreaks cannot be predicted, 6 months of PCP chemoprophylaxis should be considered for all RTRs and LTRs.

Independent of 5-HT1A receptors, neurons in the paraventricular hypothalamus mediate ACTH responses from MDMA.

Acute and chronic complications from the substituted amphetamine 3,4-methylenedioxymethamphetamine (MDMA) are linked to activation of the hypothalamic-pituitary-adrenal (HPA) axis. How MDMA activates the HPA axis is not known. HPA responses to stress are known to be mediated through the paraventricular (PVH) hypothalamus and to involve serotonin-1a (5-HT1A) receptors. We sought to determine if the PVH and 5-HT1A receptors were also involved in mediating HPA responses to MDMA. Rats were pretreated with either saline or a 5-HT1A antagonist, WAY-100635 (WAY), followed by a systemic dose of MDMA (7.5mg/kg i.v.). Animals pretreated with WAY had significantly lower plasma ACTH concentrations after MDMA. To determine if neurons in the PVH were involved, and if their involvement was mediated by 5-HT1A receptors, rats implanted with guide cannulas targeting the PVH were microinjected with the GABAA receptor agonist muscimol, aCSF, or WAY followed by MDMA. Compared to aCSF, microinjections of muscimol significantly attenuated the MDMA-induced rise in plasma ACTH (126 vs. 588pg/ml, P=<0.01). WAY had no effect. Our data demonstrates that neurons in the PVH, independent of 5-HT1A receptors, mediate ACTH responses to MDMA.

Single-cell and metagenomic analyses indicate a fermentative and saccharolytic lifestyle for members of the OP9 lineage.

OP9 is a yet-uncultivated bacterial lineage found in geothermal systems, petroleum reservoirs, anaerobic digesters and wastewater treatment facilities. Here we use single-cell and metagenome sequencing to obtain two distinct, nearly complete OP9 genomes, one constructed from single cells sorted from hot spring sediments and the other derived from binned metagenomic contigs from an in situ-enriched cellulolytic, thermophilic community. Phylogenomic analyses support the designation of OP9 as a candidate phylum for which we propose the name 'Atribacteria'. Although a plurality of predicted proteins is most similar to those from Firmicutes, the presence of key genes suggests a diderm cell envelope. Metabolic reconstruction from the core genome suggests an anaerobic lifestyle based on sugar fermentation by Embden-Meyerhof glycolysis with production of hydrogen, acetate and ethanol. Putative glycohydrolases and an endoglucanase may enable catabolism of (hemi)cellulose in thermal environments. This study lays a foundation for understanding the physiology and ecological role of the 'Atribacteria'.

Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning.

Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7-8.5 at concentrations up to 6.6×10(6) 16S rRNA gene copies g(-1) wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology.