An Innovative Approach to Impacting Student Academic Achievement and Attitudes: Pilot Study of the HEADS UP Virtual Molecular Biology Lab

Introduction: The Virtual Molecular Biology Lab is an innovative, computer-based educational program designed to teach advanced high school biology students how to create a transgenic mouse model in a simulated laboratory setting. It was created in an effort to combat the current decrease in adolescent enthusiasm for and academic achievement in science and science careers, especially in Hispanic students. Because studies have found that hands-on learning, particularly computer-based instruction, is effective in enhancing science achievement, the Virtual Lab is a potential tool for increasing the number of Hispanic students that choose to enter science fields. [See PDF for complete abstract]

An integrated molecular biology and computational approach to CYP1A1 expression in human brain

The cytochromes P450 comprise a superfamily of heme-containing mono-oxygenases. These enzymes metabolize numerous xenobiotics, but also play a role in metabolism of endogenous compounds. The P450 1A1 enzyme generally metabolizes polycyclic aromatic hydrocarbons, and its expression can be induced by aryl hydrocarbon receptor (AhR) activation. CYP1A1 is an exception to the generality that the majority of CYPs demonstrate highest expression in liver; CYP1Al is present in numerous extrahepatic tissues, including brain. This P450 has been observed in two forms, wildtype (WT) and brain variant (BV), arising from alternatively spliced mRNA transcripts. The CYP1A1 BV mRNA presented an exon deletion and was detected in human brain but not liver tissue of the same individuals. ^ Quantitative PCR analyses were performed to determine CYP1A1 WT and BV transcript expression levels in normal, bipolar disorder or schizophrenic groups. In our samples, we show that CYP1A1 BV mRNA, when present, is found alongside the full-length form. Furthermore, we demonstrate a significant decrease in expression of CYP1A1 in patients with bipolar disorder or schizophrenia. The expression level was not influenced by post-mortem interval, tissue pH, age, tobacco use, or lifetime antipsychotic medication load. ^ There is no indication of increased brain CYP1A1 expression in normal smokers versus non-smokers in these samples. We observed slightly increased CYP1A1 expression only in bipolar and schizophrenic smokers versus non-smokers. This may be indicative of complex interactions between neuronal chemical environments and AhR-mediated CYP1A1 induction in brain. ^ Structural homology modeling demonstrated that P450 1A1 BV has several alterations to positions/orientations of substrate recognition site residues compared to the WT isoform. Automated substrate docking was employed to investigate the potential binding of neurological signaling molecules and neurotropic drugs, as well as to differentiate specificities of the two P450 1A1 isoforms. We consistently observed that the BV isoform produced energetically favorable substrate dockings in orientations not observed for the same substrate in the WT isoform. These results demonstrated that structural differences, namely an expanded substrate access channel and active site, confer greater capacity for unique compound docking positions suggesting a metabolic profile distinct from the wildtype form for these test compounds. ^

UNDERSTANDING NANOG'S ROLE IN CANCER BIOLOGY

Understanding Nanog’s Role in Cancer Biology Mark Daniel Badeaux Supervisory Professor Dean Tang, PhD The cancer stem cell model holds that tumor heterogeneity and population-level immortality are driven by a subset of cells within the tumor, termed cancer stem cells. Like embryonic or somatic stem cells, cancer stem cells are believed to possess self-renewal capacity and the ability to give rise to a multitude of varieties of daughter cell. Because of cancer’s implied connections to authentic stem cells, we screened a variety of prostate cancer cell lines and primary tumors in order to determine if any notable ‘stemness’ genes were expressed in malignant growths. We found a promising lead in Nanog, a central figure in maintaining embryonic stem cell pluripotency, and through a variety of experiments in which we diminished Nanog expression, found that it may play a significant role in prostate cancer development. We then created a transgenic mouse model in which we targeted Nanog expression to keratin 14-expressing in order to assess its potential contribution to tumorigenesis. We found a variety of developmental abnormalities and altered differentiation patterns in our model , but much to our chagrin we observed neither spontaneous tumor formation nor premalignant changes in these mice, but instead surprisingly found that high levels of Nanog expression inhibited tumor formation in a two-stage skin carcinogenesis model. We also noted a depletion of skin stem cell populations, which underlies the wound-healing defect our mice harbor as well. Gene expression analysis shows a reduction in c-Jun and Bmp5, two genes whose loss inhibits skin tumor development and reduces stem cell counts respectively. As we further explored Nanog’s activity in prostate cancer, it became apparent that the protein oftentimes was not expressed. Emboldened by the competing endogenous RNA (ceRNA) hypothesis, we identified the Nanog 3’UTR as a regulator of the tumor suppressive microRNA 128a (miR-128a), which includes known oncogenes such as Bmi1 among its authentic targets. Future work will necessarily involve discerning instances in which Nanog mRNA is the biologically relevant molecule, as well as identifying additional mRNA species which may serve solely as a molecular sink for miR-128a.

An innovative approach to impacting student academic achievement and attitudes: Pilot study of the HEADS UP Virtual Molecular Biology Lab

Objective. To evaluate the HEADS UP Virtual Molecular Biology Lab, a computer-based simulated laboratory designed to teach advanced high school biology students how to create a mouse model. ^ Design. A randomized clinical control design of forty-four students from two science magnet high schools in Mercedes, Texas was utilized to assess knowledge and skills of molecular laboratory procedures, attitudes towards science and computers as a learning tool, and usability of the program. ^ Measurements. Data was collected using five paper-and-pencil formatted questionnaires and an internal "lab notebook." ^ Results. The Virtual Lab was found to significantly increase student knowledge over time (p<0.005) and with each use (p<0.001) as well as positively increase attitudes towards computers (p<0.001) and skills (p<0.005). No significant differences were seen in science attitude scores.^ Conclusion. These results provide evidence that the HEADS UP Virtual Molecular Biology Lab is a potentially effective educational tool for high school molecular biology education.^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

Classification of cellular malignancy associated changes in cervical cancer

Cervical cancer is the leading cause of death and disease from malignant neoplasms among women in developing countries. Even though the Pap smear has significantly decreased the number of deaths from cervical cancer in the past years, it has its limitations. Researchers have developed an automated screening machine which can potentially detect abnormal cases that are overlooked by conventional screening. The goal of quantitative cytology is to classify the patient's tissue sample based on quantitative measurements of the individual cells. It is also much cheaper and potentially can take less time. One of the major challenges of collecting cells with a cytobrush is the possibility of not sampling any existing dysplastic cells on the cervix. Being able to correctly classify patients who have disease without the presence of dysplastic cells could improve the accuracy of quantitative cytology algorithms. Subtle morphologic changes in normal-appearing tissues adjacent to or distant from malignant tumors have been shown to exist, but a comparison of various statistical methods, including many recent advances in the statistical learning field, has not previously been done. The objective of this thesis is to use different classification methods applied to quantitative cytology data for the detection of malignancy associated changes (MACs). In this thesis, Elastic Net is the best algorithm. When we applied the Elastic Net algorithm to the test set, we combined the training set and validation set as "training" set and used 5-fold cross validation to choose the parameter for Elastic Net. It has a sensitivity of 47% at 80% specificity, an AUC 0.52, and a partial AUC 0.10 (95% CI 0.09-0.11).^