Quantum dots to monitor RNAi delivery and improve gene silencing

A critical issue in using RNA interference for identifying genotype/phenotype correlations is the uniformity of gene silencing within a cell population. Variations in transfection efficiency, delivery-induced cytotoxicity and ‘off target’ effects at high siRNA concentrations can confound the interpretation of functional studies. To address this problem, we have developed a novel method of monitoring siRNA delivery that combines unmodified siRNA with seminconductor quantum dots (QDs) as multi color biological probes. We co-transfected siRNA with QDs using standard transfection techniques, thereby leveraging the photostable fluorescent nanoparticles to track delivery of nucleic acid, sort cells by degree of transfection and purify homogenously-silenced subpopulations. Compared to alternative RNAi tracking methods (co-delivery of reporter plasmids and end-labeling the siRNA), QDs exhibit superior photostability and tunable optical properties for an extensive selection of non-overlapping colors. Thus this simple, modular system can be extended toward multiplexed gene knockdown studies, as demonstrated in a two color proof-of-principle study with two biological targets. When the method was applied to investigate the functional role of T-cadherin (T-cad) in cell–cell communication, a subpopulation of highly silenced cells obtained by QD labeling was required to observe significant downstream effects of gene knockdown

Label-free segmentation of co-cultured cells on a nanotopographical gradient

The function and fate of cells is influenced by many different factors, one of which is surface topography of the support culture substrate. Systematic studies of nanotopography and cell response have typically been limited to single cell types and a small set of topographical variations. Here, we show a radical expansion of experimental throughput using automated detection, measurement, and classification of co-cultured cells on a nanopillar array where feature height changes continuously from planar to 250 nm over 9 mm. Individual cells are identified and characterized by more than 200 descriptors, which are used to construct a set of rules for label-free segmentation into individual cell types. Using this approach we can achieve label-free segmentation with 84% confidence across large image data sets and suggest optimized surface parameters for nanostructuring of implant devices such as vascular stents

TBI lesion segmentation in head CT: impact of preprocessing and data augmentation

Automatic segmentation of lesions in head CT provides keyinformation for patient management, prognosis and disease monitoring.Despite its clinical importance, method development has mostly focusedon multi-parametric MRI. Analysis of the brain in CT is challengingdue to limited soft tissue contrast and its mono-modal nature. We studythe under-explored problem of fine-grained CT segmentation of multiplelesion types (core, blood, oedema) in traumatic brain injury (TBI). Weobserve that preprocessing and data augmentation choices greatly impactthe segmentation accuracy of a neural network, yet these factors arerarely thoroughly assessed in prior work. We design an empirical studythat extensively evaluates the impact of different data preprocessing andaugmentation methods. We show that these choices can have an impactof up to 18% DSC. We conclude that resampling to isotropic resolutionyields improved performance, skull-stripping can be replaced by using theright intensity window, and affine-to-atlas registration is not necessaryif we use sufficient spatial augmentation. Since both skull-stripping andaffine-to-atlas registration are susceptible to failure, we recommend theiralternatives to be used in practice. We believe this is the first work toreport results for fine-grained multi-class segmentation of TBI in CT. Ourfindings may inform further research in this under-explored yet clinicallyimportant task of automatic head CT lesion segmentation

A novel human skin chamber model to study wound infection ex vivo

Wound infections with multi-drug resistant bacteria increase morbidity and mortality and have considerable socioeconomic impact. They can lead to impaired wound healing, resulting in rising treatment costs. The aim of this study was to investigate an ex vivo human wound infection model. Human full-thickness skin from the operating room (OR) was placed into the Bo-Drum® and cultivated for 7 days in an air–liquid interphase. On day 8, the skin was inoculated with either (1) Pseudomonas aeruginosa, (2) Staphylococcus aureus (105 CFU, n = 3) or (3) carrier control. 1, 3 and 7 days after inoculation colony forming units in the tissue/media were determined and cytokine expression was quantified. A reliable and reproducible wound infection could be established for 7 days. At this timepoint, 1.8 × 108 CFU/g tissue of P. aeruginosa and 2 × 107 CFU/g tissue of S. aureus were detected. Immunohistochemical analysis demonstrated bacterial infection and epidermolysis in infected skin. RT-PCR analysis exhibited a significant induction of proinflammatory cytokines after infection. The BO-drum® is a robust, easy-to-use, sterilizable and reusable ex vivo full-skin culture system. For investigation of wound infection, treatment and healing, the BO-drum® presents a convenient model and may help to standardize wound research

Real-time imaging of hepatitis C virus infection using a fluorescent cell-based reporter system

Author Manuscript 2010 August 1Hepatitis C virus (HCV), which infects 2–3% of the world population, is a causative agent of chronic hepatitis and the leading indication for liver transplantation1. The ability to propagate HCV in cell culture (HCVcc) is a relatively recent breakthrough and a key tool in the quest for specific antiviral therapeutics. Monitoring HCV infection in culture generally involves bulk population assays, use of genetically modified viruses and/or terminal processing of potentially precious samples. Here we develop a cell-based fluorescent reporter system that allows sensitive distinction of individual HCV-infected cells in live or fixed samples. We demonstrate use of this technology for several previously intractable applications, including live-cell imaging of viral propagation and host response, as well as visualizing infection of primary hepatocyte cultures. Integration of this reporter with modern image-based analysis methods could open new doors for HCV research.New York (State). Dept. of Health (Empire State Stem Cell Fund Contract C023046)United States. Public Health Service (Grant R01 DK56966)National Institutes of Health (U.S.) (Roadmap for Medical Research Grant 1 R01 DK085713-01)Howard Hughes Medical Institute (Investigator

Finding the missing honey bee genes: lessons learned from a genome upgrade

BACKGROUND: The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. RESULTS: Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. CONCLUSIONS: Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination.Funding for the project was provided by a grant to RG from the National Human Genome Research Institute, National Institutes of Health (NHGRI, NIH) U54 HG003273. Contributions from members of the CGE lab were supported by Agriculture and Food Research Initiative Competitive grant no. 2010- 65205-20407 from the USDA National Institute of Food Agriculture. AKB was supported by a Clare Luce Booth Fellowship at Georgetown University

Aging Predisposes Oocytes to Meiotic Nondisjunction When the Cohesin Subunit SMC1 Is Reduced

In humans, meiotic chromosome segregation errors increase dramatically as women age, but the molecular defects responsible are largely unknown. Cohesion along the arms of meiotic sister chromatids provides an evolutionarily conserved mechanism to keep recombinant chromosomes associated until anaphase I. One attractive hypothesis to explain age-dependent nondisjunction (NDJ) is that loss of cohesion over time causes recombinant homologues to dissociate prematurely and segregate randomly during the first meiotic division. Using Drosophila as a model system, we have tested this hypothesis and observe a significant increase in meiosis I NDJ in experimentally aged Drosophila oocytes when the cohesin protein SMC1 is reduced. Our finding that missegregation of recombinant homologues increases with age supports the model that chiasmata are destabilized by gradual loss of cohesion over time. Moreover, the stage at which Drosophila oocytes are most vulnerable to age-related defects is analogous to that at which human oocytes remain arrested for decades. Our data provide the first demonstration in any organism that, when meiotic cohesion begins intact, the aging process can weaken it sufficiently and cause missegregation of recombinant chromosomes. One major advantage of these studies is that we have reduced but not eliminated the SMC1 subunit. Therefore, we have been able to investigate how aging affects normal meiotic cohesion. Our findings that recombinant chromosomes are at highest risk for loss of chiasmata during diplotene argue that human oocytes are most vulnerable to age-induced loss of meiotic cohesion at the stage at which they remain arrested for several years

A systematic review evaluating the psychometric properties of measures of social inclusion

Introduction: Improving social inclusion opportunities for population health has been identified as a priority area for international policy. There is a need to comprehensively examine and evaluate the quality of psychometric properties of measures of social inclusion that are used to guide social policy and outcomes. Objective: To conduct a systematic review of the literature on all current measures of social inclusion for any population group, to evaluate the quality of the psychometric properties of identified measures, and to evaluate if they capture the construct of social inclusion. Methods: A systematic search was performed using five electronic databases: CINAHL, PsycINFO, Embase, ERIC and Pubmed and grey literature were sourced to identify measures of social inclusion. The psychometric properties of the social inclusion measures were evaluated against the COSMIN taxonomy of measurement properties using pre-set psychometric criteria. Results: Of the 109 measures identified, twenty-five measures, involving twenty-five studies and one manual met the inclusion criteria. The overall quality of the reviewed measures was variable, with the Social and Community Opportunities Profile-Short, Social Connectedness Scale and the Social Inclusion Scale demonstrating the strongest evidence for sound psychometric quality. The most common domain included in the measures was connectedness (21), followed by participation (19); the domain of citizenship was covered by the least number of measures (10). No single instrument measured all aspects within the three domains of social inclusion. Of the measures with sound psychometric evidence, the Social and Community Opportunities Profile-Short captured the construct of social inclusion best. Conclusions: The overall quality of the psychometric properties demonstrate that the current suite of available instruments for the measurement of social inclusion are promising but need further refinement. There is a need for a universal working definition of social inclusion as an overarching construct for ongoing research in the area of the psychometric properties of social inclusion instruments

Discovering Networks of Perturbed Biological Processes in Hepatocyte Cultures

The liver plays a vital role in glucose homeostasis, the synthesis of bile acids and the detoxification of foreign substances. Liver culture systems are widely used to test adverse effects of drugs and environmental toxicants. The two most prevalent liver culture systems are hepatocyte monolayers (HMs) and collagen sandwiches (CS). Despite their wide use, comprehensive transcriptional programs and interaction networks in these culture systems have not been systematically investigated. We integrated an existing temporal transcriptional dataset for HM and CS cultures of rat hepatocytes with a functional interaction network of rat genes. We aimed to exploit the functional interactions to identify statistically significant linkages between perturbed biological processes. To this end, we developed a novel approach to compute Contextual Biological Process Linkage Networks (CBPLNs). CBPLNs revealed numerous meaningful connections between different biological processes and gene sets, which we were successful in interpreting within the context of liver metabolism. Multiple phenomena captured by CBPLNs at the process level such as regulation, downstream effects, and feedback loops have well described counterparts at the gene and protein level. CBPLNs reveal high-level linkages between pathways and processes, making the identification of important biological trends more tractable than through interactions between individual genes and molecules alone. Our approach may provide a new route to explore, analyze, and understand cellular responses to internal and external cues within the context of the intricate networks of molecular interactions that control cellular behavior