Molecular electronics sensors on a scalable semiconductor chip: A platform for single-molecule measurement of binding kinetics and enzyme activity.

For nearly 50 years, the vision of using single molecules in circuits has been seen as providing the ultimate miniaturization of electronic chips. An advanced example of such a molecular electronics chip is presented here, with the important distinction that the molecular circuit elements play the role of general-purpose single-molecule sensors. The device consists of a semiconductor chip with a scalable array architecture. Each array element contains a synthetic molecular wire assembled to span nanoelectrodes in a current monitoring circuit. A central conjugation site is used to attach a single probe molecule that defines the target of the sensor. The chip digitizes the resulting picoamp-scale current-versus-time readout from each sensor element of the array at a rate of 1,000 frames per second. This provides detailed electrical signatures of the single-molecule interactions between the probe and targets present in a solution-phase test sample. This platform is used to measure the interaction kinetics of single molecules, without the use of labels, in a massively parallel fashion. To demonstrate broad applicability, examples are shown for probe molecule binding, including DNA oligos, aptamers, antibodies, and antigens, and the activity of enzymes relevant to diagnostics and sequencing, including a CRISPR/Cas enzyme binding a target DNA, and a DNA polymerase enzyme incorporating nucleotides as it copies a DNA template. All of these applications are accomplished with high sensitivity and resolution, on a manufacturable, scalable, all-electronic semiconductor chip device, thereby bringing the power of modern chips to these diverse areas of biosensing.

Multi-omic comparison of Alzheimer's variants in human ESC-derived microglia reveals convergence at APOE.

Variations in many genes linked to sporadic Alzheimer's disease (AD) show abundant expression in microglia, but relationships among these genes remain largely elusive. Here, we establish isogenic human ESC-derived microglia-like cell lines (hMGLs) harboring AD variants in CD33, INPP5D, SORL1, and TREM2 loci and curate a comprehensive atlas comprising ATAC-seq, ChIP-seq, RNA-seq, and proteomics datasets. AD-like expression signatures are observed in AD mutant SORL1 and TREM2 hMGLs, while integrative multi-omic analysis of combined epigenetic and expression datasets indicates up-regulation of APOE as a convergent pathogenic node. We also observe cross-regulatory relationships between SORL1 and TREM2, in which SORL1R744X hMGLs induce TREM2 expression to enhance APOE expression. AD-associated SORL1 and TREM2 mutations also impaired hMGL Aß uptake in an APOE-dependent manner in vitro and attenuated Aß uptake/clearance in mouse AD brain xenotransplants. Using this modeling and analysis platform for human microglia, we provide new insight into epistatic interactions in AD genes and demonstrate convergence of microglial AD genes at the APOE locus.

"Reprogram Enablement" as an Assay for Identifying Early Oncogenic Pathways by Their Ability to Allow Neoplastic Cells to Reacquire an Epiblast State.

One approach to understanding how tissue-specific cancers emerge is to determine the requirements for "reprograming" such neoplastic cells back to their developmentally normal primordial pre-malignant epiblast-like pluripotent state and then scrutinizing their spontaneous reconversion to a neoplasm, perhaps rendering salient the earliest pivotal oncogenic pathway(s) (before other aberrations accumulate in the adult tumor). For the prototypical malignancy anaplastic thyroid carcinoma (ATC), we found that tonic RAS reduction was obligatory for reprogramming cancer cells to a normal epiblast-emulating cells, confirmed by changes in their transcriptomic and epigenetic profiles, loss of neoplastic behavior, and ability to derive normal somatic cells from their "epiblast organoids." Without such suppression, ATCs re-emerged from the clones. Hence, for ATC, RAS inhibition was its "reprogram enablement" (RE) factor. Each cancer likely has its own RE factor; identifying it may illuminate pre-malignant risk markers, better classifications, therapeutic targets, and tissue-specification of a previously pluripotent, now neoplastic, cell.

Myc and Loss of p53 Cooperate to Drive Formation of Choroid Plexus Carcinoma.

Choroid plexus carcinoma (CPC) is a rare brain tumor that occurs most commonly in very young children and has a dismal prognosis despite intensive therapy. Improved outcomes for patients with CPC depend on a deeper understanding of the mechanisms underlying the disease. Here we developed transgenic models of CPCs by activating the Myc oncogene and deleting the Trp53 tumor suppressor gene in murine neural stem cells or progenitors. Murine CPC resembled their human counterparts at a histologic level, and like the hypodiploid subset of human CPC, exhibited multiple whole-chromosome losses, particularly of chromosomes 8, 12, and 19. Analysis of murine and human CPC gene expression profiles and copy number changes revealed altered expression of genes involved in cell cycle, DNA damage response, and cilium function. High-throughput drug screening identified small molecule inhibitors that decreased the viability of CPC. These models will be valuable tools for understanding the biology of choroid plexus tumors and for testing novel approaches to therapy. SIGNIFICANCE: This study describes new mouse models of choroid plexus carcinoma and uses them to investigate the biology and therapeutic responsiveness of this highly malignant pediatric brain tumor.

Neutralizing antibody affords comparable protection against vaginal and rectal simian/human immunodeficiency virus challenge in macaques.

OBJECTIVE: Passive administration of broadly neutralizing antibodies has been shown to protect against both vaginal and rectal challenge in the simian/human immunodeficiency virus (SHIV)/macaque model of HIV transmission. However, the relative efficacy of antibody against the two modes of exposure is unknown and, given differences in the composition and immunology of the two tissue compartments, this is an important gap in knowledge. To investigate the significance of the challenge route for antibody-mediated protection, we performed a comparative protection study in macaques using the highly potent human monoclonal antibody, PGT126. DESIGN: Animals were administered PGT126 at three different doses before challenged either vaginally or rectally with a single dose of SHIVSF163P3. METHODS: Viral loads, PGT126 serum concentrations, and serum neutralizing titers were monitored. RESULTS: In vaginally challenged animals, sterilizing immunity was achieved in all animals administered 10 mg/kg, in two of five animals administered 2 mg/kg and in one of five animals administered 0.4 mg/kg PGT126. Comparable protection was observed for the corresponding groups challenged rectally as sterilizing immunity was achieved in three of four animals administered 10 mg/kg, in two of four animals administered 2 mg/kg and in none of four animals administered 0.4 mg/kg PGT126. Serological analysis showed similar serum concentrations of PGT126 and serum neutralization titers in animals administered the same antibody dose. CONCLUSION: Our data suggest that broadly neutralizing antibody-mediated protection is not strongly dependent on the mucosal route of challenge, which indicates that a vaccine aimed to induce a neutralizing antibody response would have broadly similar efficacy against both primary transmission routes for HIV.

Bayesian network analysis of multi-compartmentalized immune responses in a murine model of sepsis and direct lung injury.

BACKGROUND: Inflammatory disease processes involve complex and interrelated systems of mediators. Determining the causal relationships among these mediators becomes more complicated when two, concurrent inflammatory conditions occur. In those cases, the outcome may also be dependent upon the timing, severity and compartmentalization of the insults. Unfortunately, standard methods of experimentation and analysis of data sets may investigate a single scenario without uncovering many potential associations among mediators. However, Bayesian network analysis is able to model linear, nonlinear, combinatorial, and stochastic relationships among variables to explore complex inflammatory disease systems. In these studies, we modeled the development of acute lung injury from an indirect insult (sepsis induced by cecal ligation and puncture) complicated by a direct lung insult (aspiration). To replicate multiple clinical situations, the aspiration injury was delivered at different severities and at different time intervals relative to the septic insult. For each scenario, we measured numerous inflammatory cell types and cytokines in samples from the local compartments (peritoneal and bronchoalveolar lavage fluids) and the systemic compartment (plasma). We then analyzed these data by Bayesian networks and standard methods. RESULTS: Standard data analysis demonstrated that the lung injury was actually reduced when two insults were involved as compared to one lung injury alone. Bayesian network analysis determined that both the severity of lung insult and presence of sepsis influenced neutrophil recruitment and the amount of injury to the lung. However, the levels of chemoattractant cytokines responsible for neutrophil recruitment were more strongly linked to the timing and severity of the lung insult compared to the presence of sepsis. This suggests that something other than sepsis-driven exacerbation of chemokine levels was influencing the lung injury, contrary to previous theories. CONCLUSIONS: To our knowledge, these studies are the first to use Bayesian networks together with experimental studies to examine the pathogenesis of sepsis-associated lung injury. Compared to standard statistical analysis and inference, these analyses elucidated more intricate relationships among the mediators, immune cells and insult-related variables (timing, compartmentalization and severity) that cause lung injury. Bayesian networks are an effective tool for evaluating complex models of inflammation.

Prediction of kinase inhibitor response using activity profiling, in vitro screening, and elastic net regression.

BACKGROUND: Many kinase inhibitors have been approved as cancer therapies. Recently, libraries of kinase inhibitors have been extensively profiled, thus providing a map of the strength of action of each compound on a large number of its targets. These profiled libraries define drug-kinase networks that can predict the effectiveness of untested drugs and elucidate the roles of specific kinases in different cellular systems. Predictions of drug effectiveness based on a comprehensive network model of cellular signalling are difficult, due to our partial knowledge of the complex biological processes downstream of the targeted kinases. RESULTS: We have developed the Kinase Inhibitors Elastic Net (KIEN) method, which integrates information contained in drug-kinase networks with in vitro screening. The method uses the in vitro cell response of single drugs and drug pair combinations as a training set to build linear and nonlinear regression models. Besides predicting the effectiveness of untested drugs, the KIEN method identifies sets of kinases that are statistically associated to drug sensitivity in a given cell line. We compared different versions of the method, which is based on a regression technique known as elastic net. Data from two-drug combinations led to predictive models, and we found that predictivity can be improved by applying logarithmic transformation to the data. The method was applied to the A549 lung cancer cell line, and we identified specific kinases known to have an important role in this type of cancer (TGFBR2, EGFR, PHKG1 and CDK4). A pathway enrichment analysis of the set of kinases identified by the method showed that axon guidance, activation of Rac, and semaphorin interactions pathways are associated to a selective response to therapeutic intervention in this cell line. CONCLUSIONS: We have proposed an integrated experimental and computational methodology, called KIEN, that identifies the role of specific kinases in the drug response of a given cell line. The method will facilitate the design of new kinase inhibitors and the development of therapeutic interventions with combinations of many inhibitors.

Presence of putative repeat-in-toxin gene tosA in Escherichia coli predicts successful colonization of the urinary tract.

UNLABELLED: Uropathogenic Escherichia coli (UPEC) strains, which cause the majority of uncomplicated urinary tract infections (UTIs), carry a unique assortment of virulence or fitness genes. However, no single defining set of virulence or fitness genes has been found in all strains of UPEC, making the differentiation between UPEC and fecal commensal strains of E. coli difficult without the use of animal models of infection or phylogenetic grouping. In the present study, we consider three broad categories of virulence factors simultaneously to better define a combination of virulence factors that predicts success in the urinary tract. A total of 314 strains of E. coli, representing isolates from fecal samples, asymptomatic bacteriuria, complicated UTIs, and uncomplicated bladder and kidney infections, were assessed by multiplex PCR for the presence of 15 virulence or fitness genes encoding adhesins, toxins, and iron acquisition systems. The results confirm previous reports of gene prevalence among isolates from different clinical settings and identify several new patterns of gene associations. One gene, tosA, a putative repeat-in-toxin (RTX) homolog, is present in 11% of fecal strains but 25% of urinary isolates. Whereas tosA-positive strains carry an unusually high number (11.2) of the 15 virulence or fitness genes, tosA-negative strains have an average of only 5.4 virulence or fitness genes. The presence of tosA was predictive of successful colonization of a murine model of infection, even among fecal isolates, and can be used as a marker of pathogenic strains of UPEC within a distinct subset of the B2 lineage. IMPORTANCE: Escherichia coli is the primary cause of urinary tract infections, the most common bacterial infection of humans. Virulence of a uropathogenic strain is typically defined by the clinical source of the isolate, the ability to colonize the bladder and kidneys in a murine model, the phylogenetic group of the bacterium, and virulence gene content. Here we describe a novel single gene, the repeat-in-toxin gene tosA, the presence of which predicts virulence of E. coli isolates regardless of source. Rapid identification of uropathogenic strains of E. coli may aid in the development of therapeutic and preventive therapies.

Bayesian network expansion identifies new ROS and biofilm regulators.

Signaling and regulatory pathways that guide gene expression have only been partially defined for most organisms. However, given the increasing number of microarray measurements, it may be possible to reconstruct such pathways and uncover missing connections directly from experimental data. Using a compendium of microarray gene expression data obtained from Escherichia coli, we constructed a series of Bayesian network models for the reactive oxygen species (ROS) pathway as defined by EcoCyc. A consensus Bayesian network model was generated using those networks sharing the top recovered score. This microarray-based network only partially agreed with the known ROS pathway curated from the literature and databases. A top network was then expanded to predict genes that could enhance the Bayesian network model using an algorithm we termed 'BN+1'. This expansion procedure predicted many stress-related genes (e.g., dusB and uspE), and their possible interactions with other ROS pathway genes. A term enrichment method discovered that biofilm-associated microarray data usually contained high expression levels of both uspE and gadX. The predicted involvement of gene uspE in the ROS pathway and interactions between uspE and gadX were confirmed experimentally using E. coli reporter strains. Genes gadX and uspE showed a feedback relationship in regulating each other's expression. Both genes were verified to regulate biofilm formation through gene knockout experiments. These data suggest that the BN+1 expansion method can faithfully uncover hidden or unknown genes for a selected pathway with significant biological roles. The presently reported BN+1 expansion method is a generalized approach applicable to the characterization and expansion of other biological pathways and living systems.

BN+1 Bayesian network expansion for identifying molecular pathway elements.

A Bayesian network expansion algorithm called BN+1 was developed to identify undocumented gene interactions in a known pathway using microarray gene expression data. In our recent paper, the BN+1 algorithm has been successfully used to identify key regulators including uspE in the E. coli ROS pathway and biofilm formation.18 In this report, a synthetic network was designed to further evaluate this algorithm. The BN+1 method was found to identify both linear and nonlinear relationships and correctly identify variables near the starting network. Using experimentally derived data, the BN+1 method identifies the gene fdhE as a potentially new ROS regulator. Finally, a range of possible score cutoff methods are explored to identify a set of criteria for selecting BN+1 calls.

VIOLIN: vaccine investigation and online information network.

Vaccines are among the most efficacious and cost-effective tools for reducing morbidity and mortality caused by infectious diseases. The vaccine investigation and online information network (VIOLIN) is a web-based central resource, allowing easy curation, comparison and analysis of vaccine-related research data across various human pathogens (e.g. Haemophilus influenzae, human immunodeficiency virus (HIV) and Plasmodium falciparum) of medical importance and across humans, other natural hosts and laboratory animals. Vaccine-related peer-reviewed literature data have been downloaded into the database from PubMed and are searchable through various literature search programs. Vaccine data are also annotated, edited and submitted to the database through a web-based interactive system that integrates efficient computational literature mining and accurate manual curation. Curated information includes general microbial pathogenesis and host protective immunity, vaccine preparation and characteristics, stimulated host responses after vaccination and protection efficacy after challenge. Vaccine-related pathogen and host genes are also annotated and available for searching through customized BLAST programs. All VIOLIN data are available for download in an eXtensible Markup Language (XML)-based data exchange format. VIOLIN is expected to become a centralized source of vaccine information and to provide investigators in basic and clinical sciences with curated data and bioinformatics tools for vaccine research and development. VIOLIN is publicly available at http://www.violinet.org.