Molecular profiling of human blastocysts reveals primitive endoderm defects among embryos of decreased implantation potential.

Human embryo implantation is remarkably inefficient, and implantation failure remains among the greatest obstacles in treating infertility. Gene expression data from human embryos have accumulated rapidly in recent years; however, identification of the subset of genes that determine successful implantation remains a challenge. We leverage clinical morphologic grading-known for decades to correlate with implantation potential-and transcriptome analyses of matched embryonic and abembryonic samples to identify factors and pathways enriched and depleted in human blastocysts of good and poor morphology. Unexpectedly, we discovered that the greatest difference was in the state of extraembryonic primitive endoderm (PrE) development, with relative deficiencies in poor morphology blastocysts. Our results suggest that implantation success is most strongly influenced by the embryonic compartment and that deficient PrE development is common among embryos with decreased implantation potential. Our study provides a valuable resource for those investigating the markers and mechanisms of human embryo implantation.

Discovery and verification of extracellular microRNA biomarkers for diagnostic and prognostic assessment of preeclampsia at triage.

We report on the identification of extracellular miRNA (ex-miRNA) biomarkers for early diagnosis and prognosis of preeclampsia (PE). Small RNA sequencing of maternal serum prospectively collected from participants undergoing evaluation for suspected PE revealed distinct patterns of ex-miRNA expression among different categories of hypertensive disorders in pregnancy. Applying an iterative machine learning method identified three bivariate miRNA biomarkers (miR-522-3p/miR-4732-5p, miR-516a-5p/miR-144-3p, and miR-27b-3p/let-7b-5p) that, when applied serially, distinguished between PE cases of different severity and differentiated cases from controls with a sensitivity of 93%, specificity of 79%, positive predictive value (PPV) of 55%, and negative predictive value (NPV) of 89%. In a small independent validation cohort, these ex-miRNA biomarkers had a sensitivity of 91% and specificity of 57%. Combining these ex-miRNA biomarkers with the established sFlt1:PlGF protein biomarker ratio performed better than either set of biomarkers alone (sensitivity of 89.4%, specificity of 91.3%, PPV of 95.5%, and NPV of 80.8%).

SnRNA sequencing defines signaling by RBC-derived extracellular vesicles in the murine heart.

Extracellular vesicles (EVs) mediate intercellular signaling by transferring their cargo to recipient cells, but the functional consequences of signaling are not fully appreciated. RBC-derived EVs are abundant in circulation and have been implicated in regulating immune responses. Here, we use a transgenic mouse model for fluorescence-based mapping of RBC-EV recipient cells to assess the role of this intercellular signaling mechanism in heart disease. Using fluorescent-based mapping, we detected an increase in RBC-EV-targeted cardiomyocytes in a murine model of ischemic heart failure. Single cell nuclear RNA sequencing of the heart revealed a complex landscape of cardiac cells targeted by RBC-EVs, with enrichment of genes implicated in cell proliferation and stress signaling pathways compared with non-targeted cells. Correspondingly, cardiomyocytes targeted by RBC-EVs more frequently express cellular markers of DNA synthesis, suggesting the functional significance of EV-mediated signaling. In conclusion, our mouse model for mapping of EV-recipient cells reveals a complex cellular network of RBC-EV-mediated intercellular communication in ischemic heart failure and suggests a functional role for this mode of intercellular signaling.

Discovery and Verification of Extracellular miRNA Biomarkers for Non-invasive Prediction of Pre-eclampsia in Asymptomatic Women.

Development of effective prevention and treatment strategies for pre-eclampsia is limited by the lack of accurate methods for identification of at-risk pregnancies. We performed small RNA sequencing (RNA-seq) of maternal serum extracellular RNAs (exRNAs) to discover and verify microRNAs (miRNAs) differentially expressed in patients who later developed pre-eclampsia. Sera collected from 73 pre-eclampsia cases and 139 controls between 17 and 28 weeks gestational age (GA), divided into separate discovery and verification cohorts, are analyzed by small RNA-seq. Discovery and verification of univariate and bivariate miRNA biomarkers reveal that bivariate biomarkers verify at a markedly higher rate than univariate biomarkers. The majority of verified biomarkers contain miR-155-5p, which has been reported to mediate the pre-eclampsia-associated repression of endothelial nitric oxide synthase (eNOS) by tumor necrosis factor alpha (TNF-α). Deconvolution analysis reveals that several verified miRNA biomarkers come from the placenta and are likely carried by placenta-specific extracellular vesicles.

Profiling Extracellular Long RNA Transcriptome in Human Plasma and Extracellular Vesicles for Biomarker Discovery.

The recent discovery of extracellular RNAs in blood, including RNAs in extracellular vesicles (EVs), combined with low-input RNA-sequencing advances have enabled scientists to investigate their role in human disease. To date, most studies have been focusing on small RNAs, and methodologies to optimize long RNAs measurement are lacking. We used plasma RNA to assess the performance of six long RNA sequencing methods, at two different sites, and we report their differences in reads (%) mapped to the genome/transcriptome, number of genes detected, long RNA transcript diversity, and reproducibility. Using the best performing method, we further compare the profile of long RNAs in the EV- and no-EV-enriched RNA plasma compartments. These results provide insights on the performance and reproducibility of commercially available kits in assessing the landscape of long RNAs in human plasma and different extracellular RNA carriers that may be exploited for biomarker discovery.

Design and in vitro characterization of multistage silicon-PLGA budesonide particles for inflammatory bowel disease.

Inflammatory bowel disease (IBD) affects a confined area of the intestine and, therefore, administration of drugs via oral route is preferable. However, obstacles such as changes in the pH along gastrointestinal tract (GIT), enzymatic activity, and intraluminal pressure may cause low drug availability in the target tissue when delivered orally. Previous studies have pointed out the benefits of using micron-sized particles for targeting inflamed intestinal mucosa and nanoparticles for delivery of anti-inflammatory agents to the affected epithelial cells. We hypothesized that by combining the benefits of micro- and nano- particles, we could create a more efficient delivery system for budesonide, a glucocorticosteroid commonly used for anti-inflammatory IBD therapy. The aim of this study was to develop a novel multistage system for oral delivery designed to increase concentrations budesonidein the inflamed intestinal tissue. The multistage system consists of Stage 1 mesoporous silicon microparticles (S1MP) loaded with stage 2 poly-lactic-glycolic acid (PLGA) budesonide-encapsulating nanoparticles (BNP). BNP were efficiently loaded into S1MP (loading efficiency of 45.9 ± 14.8%) due to the large pore volume and high surface area of S1MP and exhibited controlled release profiles with enhanced drug dissolution rate in biologically relevant pHs. Due to the robustness in acidic pH and their geometry, S1MP protected the loaded budesonide in the acidic (gastric) pH with only 20% release. This allowed for the prolonged release of the BNP in the higher pH conditions (intestinal pH). The sustained release of BNP could facilitate accumulation in the inflamed tissue, enabling BNP to penetrate inflamed mucosa and release active budesonide to the target site. The multistage systems of S1MP and BNP were further evaluated in three-dimensional (3D) in vitro model of IBD and were found to (1) increase accumulation of BNP in the inflamed areas, (2) restore the barrier function of Caco-2 inflamed monolayer, and (3) significantly reduce pro-inflammatory cytokine release almost to the level of the healthy control.

Glioma-Derived miRNA-Containing Extracellular Vesicles Induce Angiogenesis by Reprogramming Brain Endothelial Cells.

Glioblastoma (GBM) is characterized by aberrant vascularization and a complex tumor microenvironment. The failure of anti-angiogenic therapies suggests pathways of GBM neovascularization, possibly attributable to glioblastoma stem cells (GSCs) and their interplay with the tumor microenvironment. It has been established that GSC-derived extracellular vesicles (GSC-EVs) and their cargoes are proangiogenic in vitro. To further elucidate EV-mediated mechanisms of neovascularization in vitro, we perform RNA-seq and DNA methylation profiling of human brain endothelial cells exposed to GSC-EVs. To correlate these results to tumors in vivo, we perform histoepigenetic analysis of GBM molecular profiles in the TCGA collection. Remarkably, GSC-EVs and normal vascular growth factors stimulate highly distinct gene regulatory responses that converge on angiogenesis. The response to GSC-EVs shows a footprint of post-transcriptional gene silencing by EV-derived miRNAs. Our results provide insights into targetable angiogenesis pathways in GBM and miRNA candidates for liquid biopsy biomarkers.

Comparison of Reproducibility, Accuracy, Sensitivity, and Specificity of miRNA Quantification Platforms.

Given the increasing interest in their use as disease biomarkers, the establishment of reproducible, accurate, sensitive, and specific platforms for microRNA (miRNA) quantification in biofluids is of high priority. We compare four platforms for these characteristics: small RNA sequencing (RNA-seq), FirePlex, EdgeSeq, and nCounter. For a pool of synthetic miRNAs, coefficients of variation for technical replicates are lower for EdgeSeq (6.9%) and RNA-seq (8.2%) than for FirePlex (22.4%); nCounter replicates are not performed. Receiver operating characteristic analysis for distinguishing present versus absent miRNAs shows small RNA-seq (area under curve 0.99) is superior to EdgeSeq (0.97), nCounter (0.94), and FirePlex (0.81). Expected differences in expression of placenta-associated miRNAs in plasma from pregnant and non-pregnant women are observed with RNA-seq and EdgeSeq, but not FirePlex or nCounter. These results indicate that differences in performance among miRNA profiling platforms impact ability to detect biological differences among samples and thus their relative utility for research and clinical use.

Increased Soluble CrkL in Serum of Breast Cancer Patients Is Associated with Advanced Disease.

Over-expression of Crk-like protein (CrkL), an intracellular adaptor protein, in breast cancer biopsies has been linked to poor prognosis. CrkL can be secreted from cancer cells binding to ß1 integrin on the cell membrane. In this study, we evaluated, for the first time, the levels of soluble CrkL in serum of breast cancer patients. Expression of CrkL and secreted fractions from human breast cancer cell lines and clinical patient samples were assessed by immunohistochemistry and Enzyme Linked Immuno-Sorbent Assay (ELISA). CrkL levels in tissues and sera of patients with different disease stages were compared and statistically analyzed by Chi-square test and Student's t-test. Culture media from human breast cancer cell lines SUM159, MDA-MB231, and MCF7 showed over a 21-, 15-, and 11-fold higher concentration of soluble CrkL as compared to normal breast epithelium cell line MCF10A. Expression of CrkL was elevated in 85% of breast tumor tissue sections. Serum levels of CrkL were significantly higher in breast cancer patients than in healthy donors. All patients with metastatic disease had significantly elevated concentration of soluble CrkL in the serum with on average three-fold increase from the baseline. The data suggest that soluble fraction of CrkL can be further evaluated as a serum biomarker for advanced disease in breast cancer patients.

Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation.

Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and high-density lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids.

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling.

RNA-seq is increasingly used for quantitative profiling of small RNAs (for example, microRNAs, piRNAs and snoRNAs) in diverse sample types, including isolated cells, tissues and cell-free biofluids. The accuracy and reproducibility of the currently used small RNA-seq library preparation methods have not been systematically tested. Here we report results obtained by a consortium of nine labs that independently sequenced reference, 'ground truth' samples of synthetic small RNAs and human plasma-derived RNA. We assessed three commercially available library preparation methods that use adapters of defined sequence and six methods using adapters with degenerate bases. Both protocol- and sequence-specific biases were identified, including biases that reduced the ability of small RNA-seq to accurately measure adenosine-to-inosine editing in microRNAs. We found that these biases were mitigated by library preparation methods that incorporate adapters with degenerate bases. MicroRNA relative quantification between samples using small RNA-seq was accurate and reproducible across laboratories and methods.

Isolation of Extracellular RNA from Serum/Plasma.

Extracellular RNAs are initiating increased interest due to their potentials in serving as novel biomarkers, mediators of intercellular communication, and therapeutic applications. As a newly emerging field, one of the main obstacles is the lack of standardized protocols for RNA isolations. Here we describe protocols for commercially available kits that have been modified to yield consistent results for isolation of extracellular RNA from both whole serum/plasma and extracellular vesicle-enriched serum/plasma samples.

Miniaturization Technologies for Efficient Single-Cell Library Preparation for Next-Generation Sequencing.

As the cost of next-generation sequencing has decreased, library preparation costs have become a more significant proportion of the total cost, especially for high-throughput applications such as single-cell RNA profiling. Here, we have applied novel technologies to scale down reaction volumes for library preparation. Our system consisted of in vitro differentiated human embryonic stem cells representing two stages of pancreatic differentiation, for which we prepared multiple biological and technical replicates. We used the Fluidigm (San Francisco, CA) C1 single-cell Autoprep System for single-cell complementary DNA (cDNA) generation and an enzyme-based tagmentation system (Nextera XT; Illumina, San Diego, CA) with a nanoliter liquid handler (mosquito HTS; TTP Labtech, Royston, UK) for library preparation, reducing the reaction volume down to 2 µL and using as little as 20 pg of input cDNA. The resulting sequencing data were bioinformatically analyzed and correlated among the different library reaction volumes. Our results showed that decreasing the reaction volume did not interfere with the quality or the reproducibility of the sequencing data, and the transcriptional data from the scaled-down libraries allowed us to distinguish between single cells. Thus, we have developed a process to enable efficient and cost-effective high-throughput single-cell transcriptome sequencing.

Low pressure mediated enhancement of nanoparticle and macromolecule loading into porous silicon structures.

Ensuring drug loading efficiency and consistency is one of the most critical stages in engineering drug delivery vectors based on porous materials. Here we propose a technique to significantly enhance the efficiency of loading by employing simple and widely available methods: applying low pressure with and without centrifugation. Our results point toward the advantages the proposed method over the passive loading, especially where the size difference of loaded materials and the pore size of the porous silicon particles is smaller, an increase up to 20-fold can be observed. The technique described in the study can be used for efficient and reproducible loading of porous materials with therapeutic molecules, nanoparticles and contrast imaging agents for biomedical application.

Three-dimensional in vitro co-culture model of breast tumor using magnetic levitation.

In this study, we investigate a novel in vitro model to mimic heterogeneous breast tumors without the use of a scaffold while allowing for cell-cell and tumor-fibroblast interactions. Previous studies have shown that magnetic levitation system under conventional culturing conditions results in the formation of three-dimensional (3D) structures, closely resembling in vivo tissues (fat tissue, vasculature, etc.). Three-dimensional heterogeneous tumor models for breast cancer were designed to effectively model the influences of the tumor microenvironment on drug efficiency. Various breast cancer cells were co-cultured with fibroblasts and then magnetically levitated. Size and cell density of the resulting tumors were measured. The model was phenotypically compared to in vivo tumors and examined for the presence of ECM proteins. Lastly, the effects of tumor stroma in the 3D in vitro model on drug transport and efficiency were assessed. Our data suggest that the proposed 3D in vitro breast tumor is advantageous due to the ability to: (1) form large-sized (millimeter in diameter) breast tumor models within 24 h; (2) control tumor cell composition and density; (3) accurately mimic the in vivo tumor microenvironment; and (4) test drug efficiency in an in vitro model that is comparable to in vivo tumors.

Design and in vitro evaluation of layer by layer siRNA nanovectors targeting breast tumor initiating cells.

Efficient therapeutics and early detection has helped to increase breast cancer survival rates over the years. However, the recurrence of breast cancer remains to be a problem and this may be due to the presence of a small population of cells, called tumor initiating cells (TICs). Breast TICs are resistant to drugs, difficult to detect, and exhibit high self-renewal capabilities. In this study, layer by layer (LBL) small interfering RNA (siRNA) nanovectors (SNVs) were designed to target breast TICs. SNVs were fabricated using alternating layers of poly-L-lysine and siRNA molecules on gold (Au) nanoparticle (NP) surfaces. The stability, cell uptake, and release profile for SNVs were examined. In addition, SNVs reduced TIC-related STAT3 expression levels, CD44+/CD24-/EpCAM+ surface marker levels and the number of mammospheres formed compared to the standard transfection agent. The data from this study show, for the first time, that SNVs in LBL assembly effectively delivers STAT3 siRNA and inhibit the growth of breast TICs in vitro.

Tumor targeting profiling of hyaluronan-coated lipid based-nanoparticles.

Hyaluronan (HA), a naturally occurring high Mw (HMw) glycosaminoglycan, has been shown to play crucial roles in cell growth, embryonic development, healing processes, inflammation, and tumor development and progression. Low Mw (LMw, <10 kDa) HA has been reported to provoke inflammatory responses, such as induction of cytokines, chemokines, reactive nitrogen species and growth factors. Herein, we prepared and characterized two types of HA coated (LMw and HMw) lipid-based targeted and stabilized nanoparticles (tsNPs) and tested their binding to tumor cells expressing the HA receptor (CD44), systemic immunotoxicity, and biodistribution in tumor bearing mice. In vitro, the Mw of the surface anchored HA had a significant influence on the affinity towards CD44 on B16F10 murine melanoma cells. LMw HA-tsNPs exhibited weak binding, while binding of tsNPs coated with HMw HA was characterized by high binding. Both types of tsNPs had no measured effect on cytokine induction in vivo following intravenous administration to healthy C57BL/6 mice suggesting no immune activation. HMw HA-tsNPs showed enhanced circulation time and tumor targeting specificity, mainly by accumulating in the tumor and its vicinity compared with LMw HA-tsNPs. Finally, we show that methotrexate (MTX), a drug commonly used in cancer chemotherapy, entrapped in HMw HA-tsNPs slowly diffused from the particles with a half-life of 13.75 days, and improved the therapeutic outcome in a murine B16F10 melanoma model compared with NPs suggesting an active cellular targeting beyond the Enhanced Permeability and Retention (EPR) effect. Taken together, these findings have major implications for the use of high molecular weight HA in nanomedicine as a selective and safe active cellular targeting moiety.

Protein adsorption enhanced radio-frequency heating of silica nanoparticles.

Measurements of specific-absorption-rate (SAR) of silica 30, 50, and 100 nm nanoparticles (NP) suspended in water were carried out at 30 MHz in 7 kV/m radio-frequency (rf) electric field. Size dependent, NP-suspension interface related heating of silica NP was observed. To investigate a possible mechanism of heating, bovine serum albumin was adsorbed on the surface of silica NPs in suspension. It resulted in significant enhancement of SAR when compared to bare silica NPs. A calorimetric and rf loss model was used to calculate effective conductivity of silica NP with/without adsorbed albumin as a function of silica size and albumin concentration.