Braveheart, a long noncoding RNA required for cardiovascular lineage commitment.

Long noncoding RNAs (lncRNAs) are often expressed in a development-specific manner, yet little is known about their roles in lineage commitment. Here, we identified Braveheart (Bvht), a heart-associated lncRNA in mouse. Using multiple embryonic stem cell (ESC) differentiation strategies, we show that Bvht is required for progression of nascent mesoderm toward a cardiac fate. We find that Bvht is necessary for activation of a core cardiovascular gene network and functions upstream of mesoderm posterior 1 (MesP1), a master regulator of a common multipotent cardiovascular progenitor. We also show that Bvht interacts with SUZ12, a component of polycomb-repressive complex 2 (PRC2), during cardiomyocyte differentiation, suggesting that Bvht mediates epigenetic regulation of cardiac commitment. Finally, we demonstrate a role for Bvht in maintaining cardiac fate in neonatal cardiomyocytes. Together, our work provides evidence for a long noncoding RNA with critical roles in the establishment of the cardiovascular lineage during mammalian development.

Dynamic and coordinated epigenetic regulation of developmental transitions in the cardiac lineage.

Heart development is exquisitely sensitive to the precise temporal regulation of thousands of genes that govern developmental decisions during differentiation. However, we currently lack a detailed understanding of how chromatin and gene expression patterns are coordinated during developmental transitions in the cardiac lineage. Here, we interrogated the transcriptome and several histone modifications across the genome during defined stages of cardiac differentiation. We find distinct chromatin patterns that are coordinated with stage-specific expression of functionally related genes, including many human disease-associated genes. Moreover, we discover a novel preactivation chromatin pattern at the promoters of genes associated with heart development and cardiac function. We further identify stage-specific distal enhancer elements and find enriched DNA binding motifs within these regions that predict sets of transcription factors that orchestrate cardiac differentiation. Together, these findings form a basis for understanding developmentally regulated chromatin transitions during lineage commitment and the molecular etiology of congenital heart disease.

GRWD1 Over-Expression Promotes Gastric Cancer Progression by Activating Notch Signaling Pathway via Up-Regulation of ADAM17.

BACKGROUND: Glutamate-rich WD repeat containing 1 (GRWD1) is over-expressed in a variety of malignant tumors and is considered to be a potential oncogene. However, its mechanism of action in gastric cancer (GC) is still unclear. METHODS: Data analysis, Immunohistochemistry, and Western Blot (WB) were performed to verify the expression of GRWD1 in GC and para-cancerous tissues. The association between GRWD1 expression and tumor size, tissue differentiation, lymph node metastasis, TNM stage, and prognosis was analyzed according to the high and low expression levels of GRWD1. The relationship between GRWD1 and Notch pathway was verified by data analysis and WB. The effects of GRWD1 on the proliferation, migration, and invasion of GC cells were verified by cell proliferation, migration, and invasion assays. We confirmed that the high expression of GRWD1 promoted the proliferation of GC cells in vivo through the tumor formation assay in nude mice. RESULTS: The expression of GRWD1 was higher in GC tissues than in para-cancerous tissues, and its expression was positively correlated with tumor size, lymph node metastasis, and TNM stage, but negatively correlated with differentiation grade and prognosis. GRWD1 over-expression increased ADAM metallopeptidase domain 17 (ADAM17) expression and promoted Notch1 intracellular domain (NICD) release to promote GC cell proliferation, migration, and invasion in vitro. Results from animal studies have shown that high GRWD1 expression could promote GC cell proliferation in vivo by activating the Notch signaling pathway. CONCLUSION: GRWD1 promotes GC progression through ADAM17-dependent Notch signaling, and GRWD1 may be a novel tumor marker and therapeutic target.

Tailoring support following summative assessments: a latent profile analysis of student outcomes across five medical specialities.

Summative assessments are often underused for feedback, despite them being rich with data of students' applied knowledge and clinical and professional skills. To better inform teaching and student support, this study aims to gain insights from summative assessments through profiling students' performance patterns and identify those students missing the basic knowledge and skills in medical specialities essential for their future career. We use Latent Profile Analysis to classify a senior undergraduate year group (n = 295) based on their performance in applied knowledge test (AKT) and OSCE, in which items and stations are pre-classified across five specialities (e.g. Acute and Critical Care, Paediatrics,…). Four distinct groups of students with increasing average performance levels in the AKT, and three such groups in the OSCE are identified. Overall, these two classifications are positively correlated. However, some students do well in one assessment format but not in the other. Importantly, in both the AKT and the OSCE there is a mixed group containing students who have met the required standard to pass, and those who have not. This suggests that a conception of a borderline group at the exam-level can be overly simplistic. There is little literature relating AKT and OSCE performance in this way, and the paper discusses how our analysis gives placement tutors key insights into providing tailored support for distinct student groups needing remediation. It also gives additional information to assessment writers about the performance and difficulty of their assessment items/stations, and to wider faculty about student overall performance and across specialities.

Spatial transcriptomics atlas reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment components in colorectal cancer.

BACKGROUND: The tumor-promoting role of tumor microenvironment (TME) in colorectal cancer has been widely investigated in cancer biology. Cancer-associated fibroblasts (CAFs), as the main stromal component in TME, play an important role in promoting tumor progression and metastasis. Hence, we explored the crosstalk between CAFs and microenvironment in the pathogenesis of colorectal cancer in order to provide basis for precision therapy. METHODS: We integrated spatial transcriptomics (ST) and bulk-RNA sequencing datasets to explore the functions of CAFs in the microenvironment of CRC. In detail, single sample gene set enrichment analysis (ssGSEA), gene set variation analysis (GSVA), pseudotime analysis and cell proportion analysis were utilized to identify the cell types and functions of each cell cluster. Immunofluorescence and immunohistochemistry were applied to confirm the results based on bioinformatics analysis. RESULTS: We profiled the tumor heterogeneity landscape and identified two distinct types of CAFs, which myo-cancer-associated fibroblasts (mCAFs) is associated with myofibroblast-like cells and inflammatory-cancer-associated fibroblasts (iCAFs) is related to immune inflammation. When we carried out functional analysis of two types of CAFs, we uncovered an extensive crosstalk between iCAFs and stromal components in TME to promote tumor progression and metastasis. Noticeable, some anti-tumor immune cells such as NK cells, monocytes were significantly reduced in iCAFs-enriched cluster. Then, ssGSEA analysis results showed that iCAFs were related to EMT, lipid metabolism and bile acid metabolism etc. Besides, when we explored the relationship of chemotherapy and microenvironment, we detected that iCAFs influenced immunosuppressive cells and lipid metabolism reprogramming in patient who underwent chemotherapy. Additionally, we identified the clinical role of iCAFs through a public database and confirmed it were related to poor prognosis. CONCLUSIONS: In summary, we identified two types of CAFs using integrated data and explored their functional significance in TME. This in-depth understanding of CAFs in microenvironment may help us to elucidate its cancer-promoting functions and offer hints for therapeutic studies.

Characterization of the Extracellular Matrix of Normal and Diseased Tissues Using Proteomics.

The extracellular matrix (ECM) is a complex meshwork of insoluble fibrillar proteins and signaling factors interacting together to provide architectural and instructional cues to the surrounding cells. Alterations in ECM organization or composition and excessive ECM deposition have been observed in diseases such as fibrosis, cardiovascular diseases, and cancer. We provide here optimized protocols to solubilize ECM proteins from normal or tumor tissues, digest the proteins into peptides, analyze ECM peptides by mass spectrometry, and interpret the mass spectrometric data. In addition, we present here two novel R-script-based web tools allowing rapid annotation and relative quantification of ECM proteins, peptides, and intensity/abundance in mass spectrometric data output files. We illustrate this protocol with ECMs obtained from two pairs of tissues, which differ in ECM content and cellularity: triple-negative breast cancer and adjacent mammary tissue, and omental metastasis from high-grade serous ovarian cancer and normal omentum. The complete proteomics data set generated in this study has been deposited to the public repository ProteomeXchange with the data set identifier: PXD005554.

Enhanced killing of antibiotic-resistant bacteria enabled by massively parallel combinatorial genetics.

New therapeutic strategies are needed to treat infections caused by drug-resistant bacteria, which constitute a major growing threat to human health. Here, we use a high-throughput technology to identify combinatorial genetic perturbations that can enhance the killing of drug-resistant bacteria with antibiotic treatment. This strategy, Combinatorial Genetics En Masse (CombiGEM), enables the rapid generation of high-order barcoded combinations of genetic elements for high-throughput multiplexed characterization based on next-generation sequencing. We created ∼ 34,000 pairwise combinations of Escherichia coli transcription factor (TF) overexpression constructs. Using Illumina sequencing, we identified diverse perturbations in antibiotic-resistance phenotypes against carbapenem-resistant Enterobacteriaceae. Specifically, we found multiple TF combinations that potentiated antibiotic killing by up to 10(6)-fold and delivered these combinations via phagemids to increase the killing of highly drug-resistant E. coli harboring New Delhi metallo-beta-lactamase-1. Moreover, we constructed libraries of three-wise combinations of transcription factors with >4 million unique members and demonstrated that these could be tracked via next-generation sequencing. We envision that CombiGEM could be extended to other model organisms, disease models, and phenotypes, where it could accelerate massively parallel combinatorial genetics studies for a broad range of biomedical and biotechnology applications, including the treatment of antibiotic-resistant infections.

Transcriptomic response during phage infection of a marine cyanobacterium under phosphorus-limited conditions.

The transcriptomic responses of bacteria to environmental stresses have been studied extensively, yet we know little about how the stressed cells respond to bacteriophage infection. Here, we conducted the first whole transcriptome sequencing (RNA-seq) study of stressed bacteria to phage infection by infecting the marine picocyanobacterium Prochlorococcus NATL2A with cyanomyovirus P-SSM2 under P limitation, a strong selective force in the oceans. Transcripts of the P-acquisition genes in the uninfected cells were enriched after P limitation, including the high-affinity phosphate-binding protein gene pstS. They were still enriched in the infected cells under P-limited conditions. In contrast, transcripts of adenosine triphosphate (ATP) synthase and ribosomal protein genes were depleted in the uninfected cells after P limitation but were enriched during phage infection of P-starved cells. Cyanophage P-SSM2 contains pstS, and pstS and its adjacent gene g247 of unknown function were the only phage genes that were enriched under P-limited conditions. We further found that the host pstS transcript number per cell decreased after infection, however, it was still much higher in the P-limited infected cells than that in the nutrient-replete cells. Moreover, phage pstS transcript number per cell was ∼ 20 times higher than the host copy, which may help maintain the host phosphate uptake rate during infection.

ProPortal: a resource for integrated systems biology of Prochlorococcus and its phage.

ProPortal (http://proportal.mit.edu/) is a database containing genomic, metagenomic, transcriptomic and field data for the marine cyanobacterium Prochlorococcus. Our goal is to provide a source of cross-referenced data across multiple scales of biological organization--from the genome to the ecosystem--embracing the full diversity of ecotypic variation within this microbial taxon, its sister group, Synechococcus and phage that infect them. The site currently contains the genomes of 13 Prochlorococcus strains, 11 Synechococcus strains and 28 cyanophage strains that infect one or both groups. Cyanobacterial and cyanophage genes are clustered into orthologous groups that can be accessed by keyword search or through a genome browser. Users can also identify orthologous gene clusters shared by cyanobacterial and cyanophage genomes. Gene expression data for Prochlorococcus ecotypes MED4 and MIT9313 allow users to identify genes that are up or downregulated in response to environmental stressors. In addition, the transcriptome in synchronized cells grown on a 24-h light-dark cycle reveals the choreography of gene expression in cells in a 'natural' state. Metagenomic sequences from the Global Ocean Survey from Prochlorococcus, Synechococcus and phage genomes are archived so users can examine the differences between populations from diverse habitats. Finally, an example of cyanobacterial population data from the field is included.

Genetic interaction maps in Escherichia coli reveal functional crosstalk among cell envelope biogenesis pathways.

As the interface between a microbe and its environment, the bacterial cell envelope has broad biological and clinical significance. While numerous biosynthesis genes and pathways have been identified and studied in isolation, how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear. To this end, we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic (rich medium) and prototrophic (minimal medium) culture conditions. The differential patterns of genetic interactions detected among > 235,000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance. These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria (including pathogens) and an important target.

The synthetic genetic interaction spectrum of essential genes.

The nature of synthetic genetic interactions involving essential genes (those required for viability) has not been previously examined in a broad and unbiased manner. We crossed yeast strains carrying promoter-replacement alleles for more than half of all essential yeast genes to a panel of 30 different mutants with defects in diverse cellular processes. The resulting genetic network is biased toward interactions between functionally related genes, enabling identification of a previously uncharacterized essential gene (PGA1) required for specific functions of the endoplasmic reticulum. But there are also many interactions between genes with dissimilar functions, suggesting that individual essential genes are required for buffering many cellular processes. The most notable feature of the essential synthetic genetic network is that it has an interaction density five times that of nonessential synthetic genetic networks, indicating that most yeast genetic interactions involve at least one essential gene.

Copper in Cancer: from transition metal to potential target.

In recent years, with the continuous in-depth exploration of the molecular mechanisms of tumorigenesis, numerous potential new targets for cancer treatment have been identified, some of which have been further developed in clinical practice and have produced positive outcomes. Notably, researchers' initial motivation for studying copper metabolism in cancer stems from the fact that copper is a necessary trace element for organisms and is closely connected to body growth and metabolism. Moreover, over the past few decades, considerable progress has been made in understanding the molecular processes and correlations between copper and cancer. Certain achievements have been made in the development and use of relevant clinical medications. The concept of "cuproptosis," a novel concept that differs from previous forms of cell death, was first proposed by a group of scientists last year, offering fresh perspectives on the targeting capabilities of copper in the treatment of cancer. In this review, we introduced the fundamental physiological functions of copper, the key components of copper metabolism, and a summary of the current research contributions on the connection between copper and cancer. In addition, the development of new copper-based nanomaterials and their associated mechanisms of action are discussed. Finally, we described how the susceptibility of cancer cells to this metallic nutrition could be leveraged to further improve the existing cancer treatment paradigm in the new setting.

Correction: Long non-coding RNA LINC02163 accelerates malignant tumor behaviors in breast cancer by regulating the microRNA-511-3p/HMGA2 axis as a competing endogenous RNA.

[This corrects the article DOI: 10.3727/096504020X15928179818438.].

Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.

Global quantitative analysis of genetic interactions is a powerful approach for deciphering the roles of genes and mapping functional relationships among pathways. Using colony size as a proxy for fitness, we developed a method for measuring fitness-based genetic interactions from high-density arrays of yeast double mutants generated by synthetic genetic array (SGA) analysis. We identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate single- and double-mutant fitness measurements, which rival the accuracy of other high-resolution studies. We applied the SGA score to examine the relationship between physical and genetic interaction networks, and we found that positive genetic interactions connect across functionally distinct protein complexes revealing a network of genetic suppression among loss-of-function alleles.

Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map.

Defining the functional relationships between proteins is critical for understanding virtually all aspects of cell biology. Large-scale identification of protein complexes has provided one important step towards this goal; however, even knowledge of the stoichiometry, affinity and lifetime of every protein-protein interaction would not reveal the functional relationships between and within such complexes. Genetic interactions can provide functional information that is largely invisible to protein-protein interaction data sets. Here we present an epistatic miniarray profile (E-MAP) consisting of quantitative pairwise measurements of the genetic interactions between 743 Saccharomyces cerevisiae genes involved in various aspects of chromosome biology (including DNA replication/repair, chromatid segregation and transcriptional regulation). This E-MAP reveals that physical interactions fall into two well-represented classes distinguished by whether or not the individual proteins act coherently to carry out a common function. Thus, genetic interaction data make it possible to dissect functionally multi-protein complexes, including Mediator, and to organize distinct protein complexes into pathways. In one pathway defined here, we show that Rtt109 is the founding member of a novel class of histone acetyltransferases responsible for Asf1-dependent acetylation of histone H3 on lysine 56. This modification, in turn, enables a ubiquitin ligase complex containing the cullin Rtt101 to ensure genomic integrity during DNA replication.

Downregulated KDM6A mediates gastric carcinogenesis via Wnt/ß-catenin signaling pathway mediated epithelial-to-mesenchymal transition.

This study explored the connection between KDM6A expression and patient prognosis and the mechanism of KDM6A's role in developing GC (GC). From the immunohistochemical Analysis of 107 GC patients' tumors, we discovered that patients with reduced KDM6A expression had a shorter survival time. There was a correlation between KDM6A expression and the degree of differentiation of tumor tissue, T stage, N stage, and TNM stage. KDM6A gene expression was positively connected with the expression level of E-cadherin and negatively connected with the expression level of N-cadherin and vimentin in vitro tests. KDM6A gene suppression prevented GC cell proliferation, migration, and invasion, whereas high KDM6A gene expression promoted these processes. Second, low expression of KDM6A down-regulates GSK3ß, p-GSK3ß, up-regulates C-Myc, CyclinD1, and promotes ß-catenin protein expression in the nucleus, while the high expression does the opposite. Then, we used ICG001 to block the Wnt/ß-catenin signal transduction pathway, and the results revealed that ICG001 could reduce the promoting effect of low KDM6A expression on aggressiveness and EMT in GC cells. KDM6A down-regulation stimulates the proliferation of GC cells, while ICG001 reverses this action in vivo tests. Patients whose KDM6A expression was found to be low had a poor prognosis, as this study found. The EMT is inhibited by regulating theWnt/ß-catenin signaling by KDM6A, which reduces GC cell proliferation, migration, and invasion. KDM6A may be a viable target for GC in clinical therapy.

DRYGIN: a database of quantitative genetic interaction networks in yeast.

Genetic interactions are highly informative for deciphering the underlying functional principles that govern how genes control cell processes. Recent developments in Synthetic Genetic Array (SGA) analysis enable the mapping of quantitative genetic interactions on a genome-wide scale. To facilitate access to this resource, which will ultimately represent a complete genetic interaction network for a eukaryotic cell, we developed DRYGIN (Data Repository of Yeast Genetic Interactions)-a web database system that aims at providing a central platform for yeast genetic network analysis and visualization. In addition to providing an interface for searching the SGA genetic interactions, DRYGIN also integrates other data sources, in order to associate the genetic interactions with pathway information, protein complexes, other binary genetic and physical interactions, and Gene Ontology functional annotation. DRYGIN version 1.0 currently holds more than 5.4 million measurements of genetic interacting pairs involving approximately 4500 genes, and is available at http://drygin.ccbr.utoronto.ca.

NExtSEEK: Extending SEEK for Active Management of Interoperable Metadata.

Data management is a critical challenge required to improve the rigor and reproducibility of large projects. Adhering to Findable, Accessible, Interoperable, and Reusable (FAIR) standards provides a baseline for meeting these requirements. Although many existing repositories handle data in a FAIR-compliant manner, there are limited tools in the public domain to handle the metadata burden required to connect data from multi-omic projects that span multiple institutions and are deposited in diverse repositories. One promising approach is the SEEK platform, which allows for diverse metadata and provides an established repository. SEEK is challenged by the assumption of single deposition events where a sample is immutable once entered in the database. This is structured for published data but presents a limitation for ongoing studies where multiple sequential events may occur in a single sample at different sites. To address this issue, we have created a modified wrapper around the SEEK platform that allows for active data management by establishing more discrete sample types that are mutable to permit the expansion of the types of metadata, allowing researchers to track additional information. The use of discrete nodes also converts assays from nodes to edges, creating a network model of the study and more accurately representing the experimental process. With these changes to SEEK, users are able to collect and organize the information that researchers need to improve reusability and reproducibility as well as make data and metadata available to the scientific community through public repositories.

Machine-learning aided in situ drug sensitivity screening predicts treatment outcomes in ovarian PDX tumors.

Long-term treatment outcomes for patients with high grade ovarian cancers have not changed despite innovations in therapies. There is no recommended assay for predicting patient response to second-line therapy, thus clinicians must make treatment decisions based on each individual patient. Patient-derived xenograft (PDX) tumors have been shown to predict drug sensitivity in ovarian cancer patients, but the time frame for intraperitoneal (IP) tumor generation, expansion, and drug screening is beyond that for tumor recurrence and platinum resistance to occur, thus results do not have clinical utility. We describe a drug sensitivity screening assay using a drug delivery microdevice implanted for 24 h in subcutaneous (SQ) ovarian PDX tumors to predict treatment outcomes in matched IP PDX tumors in a clinically relevant time frame. The SQ tumor response to local microdose drug exposure was found to be predictive of the growth of matched IP tumors after multi-week systemic therapy using significantly fewer animals (10 SQ vs 206 IP). Multiplexed immunofluorescence image analysis of phenotypic tumor response combined with a machine learning classifier could predict IP treatment outcomes against three second-line cytotoxic therapies with an average AUC of 0.91.

Long Noncoding RNA LINC02163 Accelerates Malignant Tumor Behaviors in Breast Cancer by Regulating the MicroRNA-511-3p/HMGA2 Axis.

Long intergenic nonprotein-coding RNA 02163 (LINC02163) has been reported to be upregulated and work as an oncogene in gastric cancer. The aims of the present study were to determine the expression profile and clinical value of LINC02163 in breast cancer. Additionally, the detailed functions of LINC02163 in breast cancer were explored, and relevant molecular events were elucidated. In this study, LINC02163 was upregulated in breast cancer, and its expression level was closely associated with tumor size, lymph node metastasis, and TNM stage. Patients with breast cancer presenting high LINC02163 expression exhibited shorter overall survival than those presenting low LINC02163 expression. Knockdown of LINC02163 resulted in a decrease in breast cancer cell proliferation, migration, and invasion and an increase in cell apoptosis in vitro. In addition, silencing of LINC02163 impeded breast cancer tumor growth in vivo. Mechanistic investigation revealed that LINC02163 served as a competing endogenous RNA for microRNA-511-3p (miR-511-3p) and consequently upregulated the expression of the high-mobility group A2 (HMGA2), a downstream target of miR-511-3p. Intriguingly, miR-511-3p inhibition and HMGA2 restoration counteracted the effects of LINC02163 deficiency on the malignant properties of breast cancer cells. LINC02163 exerts cancer-promoting effects during the initiation and progression of breast cancer via regulation of the miR-511-3p/HMGA2 axis. Our findings add to our understanding of the roles of the LINC02163/miR-511-3p/HMGA2 pathway as a regulator of breast cancer pathogenesis and may be useful in the development of lncRNA-directed cancer diagnosis, prognosis, and therapy.