Identification of CgeA as a glycoprotein that anchors polysaccharides to the spore surface in Bacillus subtilis.

The Bacillus subtilis spore is composed of a core, containing chromosomal DNA, surrounded by a cortex layer made of peptidoglycan, and a coat composed of concentric proteinaceous layers. A polysaccharide layer is added to the spore surface, and likely anchored to the crust, the coat outermost layer. However, the identity of the coat protein(s) to which the spore polysaccharides (SPS) are attached is uncertain. First, we showed that the crust proteins CotVWXYZ and CgeA were all contained in the peeled SPS layer obtained from a strain missing CotE, the outer coat morphogenetic protein, suggesting that the SPS is indeed bound to at least one of the spore surface proteins. Second, CgeA is known to be located at the most downstream position in the crust assembly pathway. An analysis of truncated variants of CgeA suggested that its N-terminal half is required for localization to the spore surface, while its C-terminal half is necessary for SPS addition. Third, an amino acid substitution strategy revealed that SPS was anchored at threonine 112 (T112), which constitutes a probable O-glycosylation site on CgeA. Our results indicated that CgeA is a glycoprotein required to initiate SPS assembly and serves as an anchor protein linking the crust and SPS layers.

Understanding vessel noise across a network of marine protected areas.

Protected areas are typically managed as a network of sites exposed to varying anthropogenic conditions. Managing these networks benefits from monitoring of conditions across sites to help prioritize coordinated efforts. Monitoring marine vessel activity and related underwater radiated noise impacts across a network of protected areas, like the U.S. National Marine Sanctuary system, helps managers ensure the quality of habitats used by a wide range of marine species. Here, we use underwater acoustic detections of vessels to quantify different characteristics of vessel noise at 25 locations within eight marine sanctuaries including the Hawaiian Archipelago and the U.S. east and west coasts. Vessel noise metrics, including temporal presence and sound levels, were paired with Automatic Identification System (AIS) vessel tracking data to derive a suite of robust vessel noise indicators for use across the network of marine protected areas. Network-wide comparisons revealed a spectrum of vessel noise conditions that closely matched AIS vessel traffic composition. Shifts in vessel noise were correlated with the decrease in vessel activity early in the COVID-19 pandemic, and vessel speed reduction management initiatives. Improving our understanding of vessel noise conditions in these protected areas can help direct opportunities for reducing vessel noise, such as establishing and maintaining noise-free periods, enhancing port efficiency, engaging with regional and international vessel quieting initiatives, and leveraging co-benefits of management actions for reducing ocean noise.

Targeting sphingolipid metabolism with the sphingosine kinase inhibitor SKI-II overcomes hypoxia-induced chemotherapy resistance in glioblastoma cells: effects on cell death, self-renewal, and invasion.

BACKGROUND: Glioblastoma patients commonly develop resistance to temozolomide chemotherapy. Hypoxia, which supports chemotherapy resistance, favors the expansion of glioblastoma stem cells (GSC), contributing to tumor relapse. Because of a deregulated sphingolipid metabolism, glioblastoma tissues contain high levels of the pro-survival sphingosine-1-phosphate and low levels of the pro-apoptotic ceramide. The latter can be metabolized to sphingosine-1-phosphate by sphingosine kinase (SK) 1 that is overexpressed in glioblastoma. The small molecule SKI-II inhibits SK and dihydroceramide desaturase 1, which converts dihydroceramide to ceramide. We previously reported that SKI-II combined with temozolomide induces caspase-dependent cell death, preceded by dihydrosphingolipids accumulation and autophagy in normoxia. In the present study, we investigated the effects of a low-dose combination of temozolomide and SKI-II under normoxia and hypoxia in glioblastoma cells and patient-derived GCSs. METHODS: Drug synergism was analyzed with the Chou-Talalay Combination Index method. Dose-effect curves of each drug were determined with the Sulforhodamine B colorimetric assay. Cell death mechanisms and autophagy were analyzed by immunofluorescence, flow cytometry and western blot; sphingolipid metabolism alterations by mass spectrometry and gene expression analysis. GSCs self-renewal capacity was determined using extreme limiting dilution assays and invasion of glioblastoma cells using a 3D spheroid model. RESULTS: Temozolomide resistance of glioblastoma cells was increased under hypoxia. However, combination of temozolomide (48 µM) with SKI-II (2.66 µM) synergistically inhibited glioblastoma cell growth and potentiated glioblastoma cell death relative to single treatments under hypoxia. This low-dose combination did not induce dihydrosphingolipids accumulation, but a decrease in ceramide and its metabolites. It induced oxidative and endoplasmic reticulum stress and triggered caspase-independent cell death. It impaired the self-renewal capacity of temozolomide-resistant GSCs, especially under hypoxia. Furthermore, it decreased invasion of glioblastoma cell spheroids. CONCLUSIONS: This in vitro study provides novel insights on the links between sphingolipid metabolism and invasion, a hallmark of cancer, and cancer stem cells, key drivers of cancer. It demonstrates the therapeutic potential of approaches that combine modulation of sphingolipid metabolism with first-line agent temozolomide in overcoming tumor growth and relapse by reducing hypoxia-induced resistance to chemotherapy and by targeting both differentiated and stem glioblastoma cells.

SoundScape learning: An automatic method for separating fish chorus in marine soundscapes.

Marine soundscapes provide the opportunity to non-invasively learn about, monitor, and conserve ecosystems. Some fishes produce sound in chorus, often in association with mating, and there is much to learn about fish choruses and the species producing them. Manually analyzing years of acoustic data is increasingly unfeasible, and is especially challenging with fish chorus, as multiple fish choruses can co-occur in time and frequency and can overlap with vessel noise and other transient sounds. This study proposes an unsupervised automated method, called SoundScape Learning (SSL), to separate fish chorus from soundscape using an integrated technique that makes use of randomized robust principal component analysis (RRPCA), unsupervised clustering, and a neural network. SSL was applied to 14 recording locations off southern and central California and was able to detect a single fish chorus of interest in 5.3 yrs of acoustically diverse soundscapes. Through application of SSL, the chorus of interest was found to be nocturnal, increased in intensity at sunset and sunrise, and was seasonally present from late Spring to late Fall. Further application of SSL will improve understanding of fish behavior, essential habitat, species distribution, and potential human and climate change impacts, and thus allow for protection of vulnerable fish species.

Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways.

In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas.

RNA sequencing for research and diagnostics in clinical oncology.

Molecular diagnostics is becoming one of the major drivers of personalized oncology. With hundreds of different approved anticancer drugs and regimens of their administration, selecting the proper treatment for a patient is at least nontrivial task. This is especially sound for the cases of recurrent and metastatic cancers where the standard lines of therapy failed. Recent trials demonstrated that mutation assays have a strong limitation in personalized selection of therapeutics, consequently, most of the drugs cannot be ranked and only a small percentage of patients can benefit from the screening. Other approaches are, therefore, needed to address a problem of finding proper targeted therapies. The analysis of RNA expression (transcriptomic) profiles presents a reasonable solution because transcriptomics stands a few steps closer to tumor phenotype than the genome analysis. Several recent studies pioneered using transcriptomics for practical oncology and showed truly encouraging clinical results. The possibility of directly measuring of expression levels of molecular drugs' targets and profiling activation of the relevant molecular pathways enables personalized prioritizing for all types of molecular-targeted therapies. RNA sequencing is the most robust tool for the high throughput quantitative transcriptomics. Its use, potentials, and limitations for the clinical oncology will be reviewed here along with the technical aspects such as optimal types of biosamples, RNA sequencing profile normalization, quality controls and several levels of data analysis.

Disparity between Inter-Patient Molecular Heterogeneity and Repertoires of Target Drugs Used for Different Types of Cancer in Clinical Oncology.

Inter-patient molecular heterogeneity is the major declared driver of an expanding variety of anticancer drugs and personalizing their prescriptions. Here, we compared interpatient molecular heterogeneities of tumors and repertoires of drugs or their molecular targets currently in use in clinical oncology. We estimated molecular heterogeneity using genomic (whole exome sequencing) and transcriptomic (RNA sequencing) data for 4890 tumors taken from The Cancer Genome Atlas database. For thirteen major cancer types, we compared heterogeneities at the levels of mutations and gene expression with the repertoires of targeted therapeutics and their molecular targets accepted by the current guidelines in oncology. Totally, 85 drugs were investigated, collectively covering 82 individual molecular targets. For the first time, we showed that the repertoires of molecular targets of accepted drugs did not correlate with molecular heterogeneities of different cancer types. On the other hand, we found that the clinical recommendations for the available cancer drugs were strongly congruent with the gene expression but not gene mutation patterns. We detected the best match among the drugs usage recommendations and molecular patterns for the kidney, stomach, bladder, ovarian and endometrial cancers. In contrast, brain tumors, prostate and colorectal cancers showed the lowest match. These findings provide a theoretical basis for reconsidering usage of targeted therapeutics and intensifying drug repurposing efforts.

Molecular pathway activation - New type of biomarkers for tumor morphology and personalized selection of target drugs.

Anticancer target drugs (ATDs) specifically bind and inhibit molecular targets that play important roles in cancer development and progression, being deeply implicated in intracellular signaling pathways. To date, hundreds of different ATDs were approved for clinical use in the different countries. Compared to previous chemotherapy treatments, ATDs often demonstrate reduced side effects and increased efficiency, but also have higher costs. However, the efficiency of ATDs for the advanced stage tumors is still insufficient. Different ATDs have different mechanisms of action and are effective in different cohorts of patients. Personalized approaches are therefore needed to select the best ATD candidates for the individual patients. In this review, we focus on a new generation of biomarkers - molecular pathway activation - and on their applications for predicting individual tumor response to ATDs. The success in high throughput gene expression profiling and emergence of novel bioinformatic tools reinforced quick development of pathway related field of molecular biomedicine. The ability to quantitatively measure degree of a pathway activation using gene expression data has revolutionized this field and made the corresponding analysis quick, robust and inexpensive. This success was further enhanced by using machine learning algorithms for selection of the best biomarkers. We review here the current progress in translating these studies to clinical oncology and patient-oriented adjustment of cancer therapy.

GARP as an Immune Regulatory Molecule in the Tumor Microenvironment of Glioblastoma Multiforme.

Glycoprotein A repetition predominant (GARP), a specific surface molecule of activated regulatory T cells, has been demonstrated to significantly contribute to tolerance in humans by induction of peripheral Treg and regulatory M2-macrophages and by inhibition of (tumorantigen-specific) T effector cells. Previous work identified GARP on Treg, and also GARP on the surface of several malignant tumors, as well as in a soluble form being shedded from their surface, contributing to tumor immune escape. Preliminary results also showed GARP expression on brain metastases of malignant melanoma. On the basis of these findings, we investigated whether GARP is also expressed on primary brain tumors. We showed GARP expression on glioblastoma (GB) cell lines and primary GB tissue, as well as on low-grade glioma, suggesting an important influence on the tumor micromilieu and the regulation of immune responses also in primary cerebral tumors. This was supported by the finding that GB cells led to a reduced, in part GARP-dependent effector T cell function (reduced proliferation and reduced cytokine secretion) in coculture experiments. Interestingly, GARP was localized not only on the cell surface but also in the cytoplasmatic, as well as nuclear compartments in tumor cells. Our findings reveal that GARP, as an immunoregulatory molecule, is located on, as well as in, tumor cells of GB and low-grade glioma, inhibiting effector T cell function, and thus contributing to the immunosuppressive tumor microenvironment of primary brain tumors. As GARP is expressed on activated Treg, as well as on brain tumors, it may be an interesting target for new immunotherapeutic approaches using antibody-based strategies as this indication.

In vivo multiphoton tomography and fluorescence lifetime imaging of human brain tumor tissue.

High resolution multiphoton tomography and fluorescence lifetime imaging differentiates glioma from adjacent brain in native tissue samples ex vivo. Presently, multiphoton tomography is applied in clinical dermatology and experimentally. We here present the first application of multiphoton and fluorescence lifetime imaging for in vivo imaging on humans during a neurosurgical procedure. We used a MPTflex™ Multiphoton Laser Tomograph (JenLab, Germany). We examined cultured glioma cells in an orthotopic mouse tumor model and native human tissue samples. Finally the multiphoton tomograph was applied to provide optical biopsies during resection of a clinical case of glioblastoma. All tissues imaged by multiphoton tomography were sampled and processed for conventional histopathology. The multiphoton tomograph allowed fluorescence intensity- and fluorescence lifetime imaging with submicron spatial resolution and 200 picosecond temporal resolution. Morphological fluorescence intensity imaging and fluorescence lifetime imaging of tumor-bearing mouse brains and native human tissue samples clearly differentiated tumor and adjacent brain tissue. Intraoperative imaging was found to be technically feasible. Intraoperative image quality was comparable to ex vivo examinations. To our knowledge we here present the first intraoperative application of high resolution multiphoton tomography and fluorescence lifetime imaging of human brain tumors in situ. It allowed in vivo identification and determination of cell density of tumor tissue on a cellular and subcellular level within seconds. The technology shows the potential of rapid intraoperative identification of native glioma tissue without need for tissue processing or staining.

Personal Vehicles Evaluated against Climate Change Mitigation Targets.

Meeting global climate change mitigation goals will likely require that transportation-related greenhouse gas emissions begin to decline within the next two decades and then continue to fall. A variety of vehicle technologies and fuels are commercially available to consumers today that can reduce the emissions of the transportation sector. Yet what are the best options, and do any suffice to meet climate policy targets? Here, we examine the costs and carbon intensities of 125 light-duty vehicle models on the U.S. market today and evaluate these models against U.S. emission-reduction targets for 2030, 2040, and 2050 that are compatible with the goal of limiting mean global temperature rise to 2 °C above preindustrial levels. Our results show that consumers are not required to pay more for a low-carbon-emitting vehicle. Across the diverse set of vehicle models and powertrain technologies examined, a clean vehicle is usually a low-cost vehicle. Although the average carbon intensity of vehicles sold in 2014 exceeds the climate target for 2030 by more than 50%, we find that most hybrid and battery electric vehicles available today meet this target. By 2050, only electric vehicles supplied with almost completely carbon-free electric power are expected to meet climate-policy targets.

Simplified homology-assisted CRISPR for gene editing in Drosophila.

In vivo genome editing with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 generates powerful tools to study gene regulation and function. We revised the homology-assisted CRISPR knock-in method to convert Drosophila GAL4 lines to LexA lines using a new universal knock-in donor strain. A balancer chromosome-linked donor strain with both body color (yellow) and eye red fluorescent protein (RFP) expression markers simplified the identification of LexA knock-in using light or fluorescence microscopy. A second balancer chromosome-linked donor strain readily converted the second chromosome-linked GAL4 lines regardless of target location in the cis-chromosome but showed limited success for the third chromosome-linked GAL4 lines. We observed a consistent and robust expression of the yellow transgene in progeny harboring a LexA knock-in at diverse genomic locations. Unexpectedly, the expression of the 3xP3-RFP transgene in the "dual transgene" cassette was significantly increased compared with that of the original single 3xP3-RFP transgene cassette in all tested genomic locations. Using this improved screening approach, we generated 16 novel LexA lines; tissue expression by the derived LexA and originating GAL4 lines was similar or indistinguishable. In collaboration with 2 secondary school classes, we also established a systematic workflow to generate a collection of LexA lines from frequently used GAL4 lines.

Sequence-specific and DNA structure-dependent interactions of Escherichia coli MutS and human p53 with DNA.

Many proteins involved in DNA repair systems interact with DNA that has structure altered from the typical B-form helix. Using magnetic beads to immobilize DNAs containing various types of structures, we evaluated the in vitro binding activities of two well-characterized DNA repair proteins, Escherichia coli MutS and human p53. E. coli MutS bound to double-stranded DNAs, with higher affinity for a G/T mismatch compared to a G/A mismatch and highest affinity for larger non-B-DNA structures. E. coli MutS bound best to DNA between pH 6 and 9. Experiments discriminated between modes of p53-DNA binding, and increasing ionic strength reduced p53 binding to nonspecific double-stranded DNA, but had minor effects on binding to consensus response sequences or single-stranded DNA. Compared to nonspecific DNA sequences, p53 bound with a higher affinity to mismatches and base insertions, while binding to various hairpin structures was similar to that observed to its consensus DNA sequence. For hairpins containing CTG repeats, the extent of p53 binding was proportional to the size of the repeat. In summary, using the flexibility of the magnetic bead separation assay we demonstrate that pH and ionic strength influence the binding of two DNA repair proteins to a variety of DNA structures.

Uniformly shaped harmonization combines human transcriptomic data from different platforms while retaining their biological properties and differential gene expression patterns.

Introduction: Co-normalization of RNA profiles obtained using different experimental platforms and protocols opens avenue for comprehensive comparison of relevant features like differentially expressed genes associated with disease. Currently, most of bioinformatic tools enable normalization in a flexible format that depends on the individual datasets under analysis. Thus, the output data of such normalizations will be poorly compatible with each other. Recently we proposed a new approach to gene expression data normalization termed Shambhala which returns harmonized data in a uniform shape, where every expression profile is transformed into a pre-defined universal format. We previously showed that following shambhalization of human RNA profiles, overall tissue-specific clustering features are strongly retained while platform-specific clustering is dramatically reduced. Methods: Here, we tested Shambhala performance in retention of fold-change gene expression features and other functional characteristics of gene clusters such as pathway activation levels and predicted cancer drug activity scores. Results: Using 6,793 cancer and 11,135 normal tissue gene expression profiles from the literature and experimental datasets, we applied twelve performance criteria for different versions of Shambhala and other methods of transcriptomic harmonization with flexible output data format. Such criteria dealt with the biological type classifiers, hierarchical clustering, correlation/regression properties, stability of drug efficiency scores, and data quality for using machine learning classifiers. Discussion: Shambhala-2 harmonizer demonstrated the best results with the close to 1 correlation and linear regression coefficients for the comparison of training vs validation datasets and more than two times lesser instability for calculation of drug efficiency scores compared to other methods.

Association of Adverse Childhood Experiences and Resilience With Obesity, High Blood Pressure, and Parental Report of Behavioral Health Symptoms in Children: A Cross Sectional Study.

The interplay between Adverse Childhood Experiences (ACEs) and resilience on health in children is not well understood. Parents completed 3 questionnaires: ACEs, Child and Youth Resilience Measure (CYRM), and the Pediatric Symptom Checklist-17(PSC-17). BMI and blood pressure were measured. 19.8% of children had 4 or more ACEs, resilience ranged from 25 to 51, 14.3% had a positive PSC-17 score, 25.6% were obese, 3.1% had systolic hypertension, and 1.2% had diastolic hypertension. Higher ACEs (ACE OR: 1.398, 95% CI = 1.044-1.893, P = .026) and lower resilience (Resilience OR: 0.740, 95% CI 0.668-0.812; P = 1.13 × 10-9) were predictive of increased reports of behavioral health symptoms, but not obesity or hypertension. The personal resilience subscale was a predictor of positive PSC-17 score (OR 0.646, 95% CI = 0.546-0.749, P = 3.18 × 10-8); relationship subscale was not. Cultivating resilience, especially personal aspects, may provide an effective intervention for behavioral health symptoms in children.

Concurrent Activation of Both Survival-Promoting and Death-Inducing Signaling by Chloroquine in Glioblastoma Stem Cells: Implications for Potential Risks and Benefits of Using Chloroquine as Radiosensitizer.

Lysosomotropic agent chloroquine was shown to sensitize non-stem glioblastoma cells to radiation in vitro with p53-dependent apoptosis implicated as one of the underlying mechanisms. The in vivo outcomes of chloroquine or its effects on glioblastoma stem cells have not been previously addressed. This study undertakes a combinatorial approach encompassing in vitro, in vivo and in silico investigations to address the relationship between chloroquine-mediated radiosensitization and p53 status in glioblastoma stem cells. Our findings reveal that chloroquine elicits antagonistic impacts on signaling pathways involved in the regulation of cell fate via both transcription-dependent and transcription-independent mechanisms. Evidence is provided that transcriptional impacts of chloroquine are primarily determined by p53 with chloroquine-mediated activation of pro-survival mevalonate and p21-DREAM pathways being the dominant response in the background of wild type p53. Non-transcriptional effects of chloroquine are conserved and converge on key cell fate regulators ATM, HIPK2 and AKT in glioblastoma stem cells irrespective of their p53 status. Our findings indicate that pro-survival responses elicited by chloroquine predominate in the context of wild type p53 and are diminished in cells with transcriptionally impaired p53. We conclude that p53 is an important determinant of the balance between pro-survival and pro-death impacts of chloroquine and propose that p53 functional status should be taken into consideration when evaluating the efficacy of glioblastoma radiosensitization by chloroquine.

Nuclear Glycoprotein A Repetitions Predominant (GARP) Is a Common Trait of Glioblastoma Stem-like Cells and Correlates with Poor Survival in Glioblastoma Patients.

Glioblastoma (GB) is notoriously resistant to therapy. GB genesis and progression are driven by glioblastoma stem-like cells (GSCs). One goal for improving treatment efficacy and patient outcomes is targeting GSCs. Currently, there are no universal markers for GSCs. Glycoprotein A repetitions predominant (GARP), an anti-inflammatory protein expressed by activated regulatory T cells, was identified as a possible marker for GSCs. This study evaluated GARP for the detection of human GSCs utilizing a multidimensional experimental design that replicated several features of GB: (1) intratumoral heterogeneity, (2) cellular hierarchy (GSCs with varied degrees of self-renewal and differentiation), and (3) longitudinal GSC evolution during GB recurrence (GSCs from patient-matched newly diagnosed and recurrent GB). Our results indicate that GARP is expressed by GSCs across various cellular states and disease stages. GSCs with an increased GARP expression had reduced self-renewal but no alterations in proliferative capacity or differentiation commitment. Rather, GARP correlated inversely with the expression of GFAP and PDGFR-α, markers of astrocyte or oligodendrocyte differentiation. GARP had an abnormal nuclear localization (GARPNU+) in GSCs and was negatively associated with patient survival. The uniformity of GARP/GARPNU+ expression across different types of GSCs suggests a potential use of GARP as a marker to identify GSCs.

Pan-cancer antagonistic inhibition pattern of ATM-driven G2/M checkpoint pathway vs other DNA repair pathways.

DNA repair mechanisms keep genome integrity and limit tumor-associated alterations and heterogeneity, but on the other hand they promote tumor survival after radiation and genotoxic chemotherapies. We screened pathway activation levels of 38 DNA repair pathways in nine human cancer types (gliomas, breast, colorectal, lung, thyroid, cervical, kidney, gastric, and pancreatic cancers). We took RNAseq profiles of the experimental 51 normal and 408 tumor samples, and from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium databases - of 500/407 normal and 5752/646 tumor samples, and also 573 normal and 984 tumor proteomic profiles from Proteomic Data Commons portal. For all the samplings we observed a congruent trend that all cancer types showed inhibition of G2/M arrest checkpoint pathway compared to the normal samples, and relatively low activities of p53-mediated pathways. In contrast, other DNA repair pathways were upregulated in most of the cancer types. The G2/M checkpoint pathway was statistically significantly downregulated compared to the other DNA repair pathways, and this inhibition was strongly impacted by antagonistic regulation of (i) promitotic genes CCNB and CDK1, and (ii) GADD45 genes promoting G2/M arrest. At the DNA level, we found that ATM, TP53, and CDKN1A genes accumulated loss of function mutations, and cyclin B complex genes - transforming mutations. These findings suggest importance of activation for most of DNA repair pathways in cancer progression, with remarkable exceptions of G2/M checkpoint and p53-related pathways which are downregulated and neutrally activated, respectively.

Generation of LexA enhancer-trap lines in Drosophila by an international scholastic network.

Conditional gene regulation in Drosophila through binary expression systems like the LexA-LexAop system provides a superb tool for investigating gene and tissue function. To increase the availability of defined LexA enhancer trap insertions, we present molecular, genetic, and tissue expression studies of 301 novel Stan-X LexA enhancer traps derived from mobilization of the index SX4 line. This includes insertions into distinct loci on the X, II, and III chromosomes that were not previously associated with enhancer traps or targeted LexA constructs, an insertion into ptc, and seventeen insertions into natural transposons. A subset of enhancer traps was expressed in CNS neurons known to produce and secrete insulin, an essential regulator of growth, development, and metabolism. Fly lines described here were generated and characterized through studies by students and teachers in an international network of genetics classes at public, independent high schools, and universities serving a diversity of students, including those underrepresented in science. Thus, a unique partnership between secondary schools and university-based programs has produced and characterized novel resources in Drosophila, establishing instructional paradigms devoted to unscripted experimental science.