Recommendations for Effective Integration of Ethics and Responsible Conduct of Research (E/RCR) Education into Course-Based Undergraduate Research Experiences: A Meeting Report.

Advancement of the scientific enterprise relies on individuals conducting research in an ethical and responsible manner. Educating emergent scholars in the principles of ethics/responsible conduct of research (E/RCR) is therefore critical to ensuring such advancement. The recent impetus to include authentic research opportunities as part of the undergraduate curriculum, via course-based undergraduate research experiences (CUREs), has been shown to increase cognitive and noncognitive student outcomes. Because of these important benefits, CUREs are becoming more common and often constitute the first research experience for many students. However, despite the importance of E/RCR in the research process, we know of few efforts to incorporate E/RCR education into CUREs. The Ethics Network for Course-based Opportunities in Undergraduate Research (ENCOUR) was created to address this concern and promote the integration of E/RCR within CUREs in the biological sciences and related disciplines. During the inaugural ENCOUR meeting, a four-pronged approach was used to develop guidelines for the effective integration of E/RCR in CUREs. This approach included: 1) defining appropriate student learning objectives; 2) identifying relevant curriculum; 3) identifying relevant assessments; and 4) defining key aspects of professional development for CURE facilitators. Meeting outcomes, including the aforementioned E/RCR guidelines, are described herein.

CUREs in biochemistry-where we are and where we should go.

Integration of research experience into classroom is an important and vital experience for all undergraduates. These course-based undergraduate research experiences (CUREs) have grown from independent instructor lead projects to large consortium driven experiences. The impact and importance of CUREs on students at all levels in biochemistry was the focus of a National Science Foundation funded think tank. The state of biochemistry CUREs and suggestions for moving biochemistry forward as well as a practical guide (supplementary material) are reported here. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):7-12, 2017.

A Myc-microRNA network promotes exit from quiescence by suppressing the interferon response and cell-cycle arrest genes.

The transition of mammalian cells from quiescence to proliferation is accompanied by the differential expression of several microRNAs (miRNAs) and transcription factors. However, the interplay between transcription factors and miRNAs in modulating gene regulatory networks involved in human cell proliferation is largely unknown. Here we show that the miRNA miR-22 promotes proliferation in primary human cells, and through a combination of Argonaute-2 immunoprecipitation and reporter assays, we identified multiple novel targets of miR-22, including several cell-cycle arrest genes that mediate the effects of the tumor-suppressor p53. In addition, we found that miR-22 suppresses interferon gene expression by directly targeting high mobility group box-1 and interferon regulatory factor (IRF)-5, preventing activation of IRF3 and NF-κB, which are activators of interferon genes. The expression of interferon genes is elevated in quiescent cells and their expression is inhibitory for cell proliferation. In addition, we find that miR-22 is activated by the transcription factor Myc when quiescent cells enter proliferation and that miR-22 inhibits the Myc transcriptional repressor MXD4, mediating a feed-forward loop to elevate Myc expression levels. Our results implicate miR-22 in downregulating the anti-proliferative p53 and interferon pathways and reveal a new transcription factor-miRNA network that regulates the transition of primary human cells from quiescence to proliferation.

ArrayPlex: distributed, interactive and programmatic access to genome sequence, annotation, ontology, and analytical toolsets.

ArrayPlex is a software package that centrally provides a large number of flexible toolsets useful for functional genomics, including microarray data storage, quality assessments, data visualization, gene annotation retrieval, statistical tests, genomic sequence retrieval and motif analysis. It uses a client-server architecture based on open source components, provides graphical, command-line, and programmatic access to all needed resources, and is extensible by virtue of a documented application programming interface. ArrayPlex is available at http://sourceforge.net/projects/arrayplex/.

Genetic reconstruction of a functional transcriptional regulatory network.

Although global analyses of transcription factor binding provide one view of potential transcriptional regulatory networks, regulation also occurs at levels distinct from transcription factor binding. Here, we use a genetic approach to identify targets of transcription factors in yeast and reconstruct a functional regulatory network. First, we profiled transcriptional responses in S. cerevisiae strains with individual deletions of 263 transcription factors. Then we used directed-weighted graph modeling and regulatory epistasis analysis to identify indirect regulatory relationships between these transcription factors, and from this we reconstructed a functional transcriptional regulatory network. The enrichment of promoter motifs and Gene Ontology annotations provide insight into the biological functions of the transcription factors.

Microarray data visualization and analysis with the Longhorn Array Database (LAD).

The wide availability and use of DNA microarrays has brought the power of whole-genome functional characterization to a large variety of research environments. Microarrays, however, also introduce significant infrastructural and analytical concerns with respect to the long-term warehousing, annotation, and visualization of immense data sets. The Longhorn Array Database (LAD) is a MIAME-compliant microarray database that operates on PostgreSQL and Linux. It is a free and completely open-source software solution, and provides a systematic and proven environment in which vast experiment sets can be safely archived, securely accessed, biologically annotated, quantitatively analyzed, and visually explored. This unit provides the complete set of information needed to successfully deploy, configure, and use LAD for the purposes of two-color DNA microarray analysis and visualization.

The Longhorn Array Database (LAD): an open-source, MIAME compliant implementation of the Stanford Microarray Database (SMD).

BACKGROUND: The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. DESCRIPTION: The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at http://www.longhornarraydatabase.org CONCLUSIONS: Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data.