Data-rich textbook figures promote core competencies: Comparison of two textbooks.

Many molecular biology and biochemistry instructors have altered their classroom behavior in favor of evidence-based, active learning instructional strategies. Overwhelming evidence confirms that lecture-only classrooms are detrimental to student learning outcomes, but we know less about the impact textbooks have on students outside the classroom. Two influential projects, the AP Biology redesign and Vision and Change, called for extensive restructuring of course content and hoped that textbooks would be restructured accordingly. This study evaluated all figures and tables from two introductory biology textbooks to quantify how well they implement recommendations from Vision and Change and AP Biology redesign. We documented significant differences among figures and tables when looking for experimental data, questions for students to answer, and quantitative interpretation. Using think-aloud interviews, we interrogated whether students engage differently with figures from the two textbooks. When figures provided take-home messages, students relied on written text rather than analyzing the graphical information for their understanding. Students frequently employed words from summaries within the figures to construct "inflated explanations" that mimicked comprehension.

Attempted use of PACE for riboswitch discovery generates three new translational theophylline riboswitch side products.

OBJECTIVE: The purpose of this project was to use an in vivo method to discover riboswitches that are activated by new ligands. We employed phage-assisted continuous evolution (PACE) to evolve new riboswitches in vivo. We started with one translational riboswitch and one transcriptional riboswitch, both of which were activated by theophylline. We used xanthine as the new target ligand during positive selection followed by negative selection using theophylline. The goal was to generate very large M13 phage populations that contained unknown mutations, some of which would result in new aptamer specificity. We discovered side products of three new theophylline translational riboswitches with different levels of protein production. RESULTS: We used next generation sequencing to identify M13 phage that carried riboswitch mutations. We cloned and characterized the most abundant riboswitch mutants and discovered three variants that produce different levels of translational output while retaining their theophylline specificity. Although we were unable to demonstrate evolution of new riboswitch ligand specificity using PACE, we recommend careful design of recombinant M13 phage to avoid evolution of "cheaters" that short circuit the intended selection pressure.

Programmed evolution for optimization of orthogonal metabolic output in bacteria.

Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields - evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation.

Implementing recommendations for introductory biology by writing a new textbook.

We redesigned the undergraduate introductory biology course by writing a new textbook (Integrating Concepts in Biology [ICB]) that follows first principles of learning. Our approach emphasizes primary data interpretation and the utility of mathematics in biology, while de-emphasizing memorization. This redesign divides biology into five big ideas (information, evolution, cells, emergent properties, homeostasis), addressing each at five levels of organization (molecules, cells, organisms, populations, ecological systems). We compared our course outcomes with two sections that used a traditional textbook and were taught by different instructors. On data interpretation assessments administered periodically during the semester, our students performed better than students in the traditional sections (p = 0.046) and exhibited greater improvement over the course of the semester (p = 0.015). On factual content assessments, our students performed similarly to students in the other sections (p = 0.737). Pre- and postsemester assessment of disciplinary perceptions and self-appraisal indicate that our students acquired a more accurate perception of biology as a discipline and may have developed a more realistic evaluation of their scientific abilities than did the control students (p < 0.05). We conclude that ICB improves critical thinking, metacognition, and disciplinary perceptions without compromising content knowledge in introductory biology.

Word selection affects perceptions of synthetic biology.

Members of the synthetic biology community have discussed the significance of word selection when describing synthetic biology to the general public. In particular, many leaders proposed the word "create" was laden with negative connotations. We found that word choice and framing does affect public perception of synthetic biology. In a controlled experiment, participants perceived synthetic biology more negatively when "create" was used to describe the field compared to "construct" (p = 0.008). Contrary to popular opinion among synthetic biologists, however, low religiosity individuals were more influenced negatively by the framing manipulation than high religiosity people. Our results suggest that synthetic biologists directly influence public perception of their field through avoidance of the word "create".

Solving a Hamiltonian Path Problem with a bacterial computer.

BACKGROUND: The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer. DNA computers have been developed that solve NP complete problems. Bacterial computers can be programmed by constructing genetic circuits to execute an algorithm that is responsive to the environment and whose result can be observed. Each bacterium can examine a solution to a mathematical problem and billions of them can explore billions of possible solutions. Bacterial computers can be automated, made responsive to selection, and reproduce themselves so that more processing capacity is applied to problems over time. RESULTS: We programmed bacteria with a genetic circuit that enables them to evaluate all possible paths in a directed graph in order to find a Hamiltonian path. We encoded a three node directed graph as DNA segments that were autonomously shuffled randomly inside bacteria by a Hin/hixC recombination system we previously adapted from Salmonella typhimurium for use in Escherichia coli. We represented nodes in the graph as linked halves of two different genes encoding red or green fluorescent proteins. Bacterial populations displayed phenotypes that reflected random ordering of edges in the graph. Individual bacterial clones that found a Hamiltonian path reported their success by fluorescing both red and green, resulting in yellow colonies. We used DNA sequencing to verify that the yellow phenotype resulted from genotypes that represented Hamiltonian path solutions, demonstrating that our bacterial computer functioned as expected. CONCLUSION: We successfully designed, constructed, and tested a bacterial computer capable of finding a Hamiltonian path in a three node directed graph. This proof-of-concept experiment demonstrates that bacterial computing is a new way to address NP-complete problems using the inherent advantages of genetic systems. The results of our experiments also validate synthetic biology as a valuable approach to biological engineering. We designed and constructed basic parts, devices, and systems using synthetic biology principles of standardization and abstraction.

Evaluation of three automated genome annotations for Halorhabdus utahensis.

Genome annotations are accumulating rapidly and depend heavily on automated annotation systems. Many genome centers offer annotation systems but no one has compared their output in a systematic way to determine accuracy and inherent errors. Errors in the annotations are routinely deposited in databases such as NCBI and used to validate subsequent annotation errors. We submitted the genome sequence of halophilic archaeon Halorhabdus utahensis to be analyzed by three genome annotation services. We have examined the output from each service in a variety of ways in order to compare the methodology and effectiveness of the annotations, as well as to explore the genes, pathways, and physiology of the previously unannotated genome. The annotation services differ considerably in gene calls, features, and ease of use. We had to manually identify the origin of replication and the species-specific consensus ribosome-binding site. Additionally, we conducted laboratory experiments to test H. utahensis growth and enzyme activity. Current annotation practices need to improve in order to more accurately reflect a genome's biological potential. We make specific recommendations that could improve the quality of microbial annotation projects.

Engineering bacteria to solve the Burnt Pancake Problem.

BACKGROUND: We investigated the possibility of executing DNA-based computation in living cells by engineering Escherichia coli to address a classic mathematical puzzle called the Burnt Pancake Problem (BPP). The BPP is solved by sorting a stack of distinct objects (pancakes) into proper order and orientation using the minimum number of manipulations. Each manipulation reverses the order and orientation of one or more adjacent objects in the stack. We have designed a system that uses site-specific DNA recombination to mediate inversions of genetic elements that represent pancakes within plasmid DNA. RESULTS: Inversions (or "flips") of the DNA fragment pancakes are driven by the Salmonella typhimurium Hin/hix DNA recombinase system that we reconstituted as a collection of modular genetic elements for use in E. coli. Our system sorts DNA segments by inversions to produce different permutations of a promoter and a tetracycline resistance coding region; E. coli cells become antibiotic resistant when the segments are properly sorted. Hin recombinase can mediate all possible inversion operations on adjacent flippable DNA fragments. Mathematical modeling predicts that the system reaches equilibrium after very few flips, where equal numbers of permutations are randomly sorted and unsorted. Semiquantitative PCR analysis of in vivo flipping suggests that inversion products accumulate on a time scale of hours or days rather than minutes. CONCLUSION: The Hin/hix system is a proof-of-concept demonstration of in vivo computation with the potential to be scaled up to accommodate larger and more challenging problems. Hin/hix may provide a flexible new tool for manipulating transgenic DNA in vivo.

Microarray analysis of the in vivo sequence preferences of a minor groove binding drug.

BACKGROUND: Minor groove binding drugs (MGBDs) interact with DNA in a sequence-specific manner and can cause changes in gene expression at the level of transcription. They serve as valuable models for protein interactions with DNA and form an important class of antitumor, antiviral, antitrypanosomal and antibacterial drugs. There is a need to extend knowledge of the sequence requirements for MGBDs from in vitro DNA binding studies to living cells. RESULTS: Here we describe the use of microarray analysis to discover yeast genes that are affected by treatment with the MGBD berenil, thereby allowing the investigation of its sequence requirements for binding in vivo. A novel approach to sequence analysis allowed us to address hypotheses about genes that were directly or indirectly affected by drug binding. The results show that the sequence features of A/T richness and heteropolymeric character discovered by in vitro berenil binding studies are found upstream of genes hypothesized to be directly affected by berenil but not upstream of those hypothesized to be indirectly affected or those shown to be unaffected. CONCLUSION: The data support the conclusion that effects of berenil on gene expression in yeast cells can be explained by sequence patterns discovered by in vitro binding experiments. The results shed light on the sequence and structural rules by which berenil binds to DNA and affects the transcriptional regulation of genes and contribute generally to the development of MGBDs as tools for basic and applied research.

Genome Consortium for Active Teaching: meeting the goals of BIO2010.

The Genome Consortium for Active Teaching (GCAT) facilitates the use of modern genomics methods in undergraduate education. Initially focused on microarray technology, but with an eye toward diversification, GCAT is a community working to improve the education of tomorrow's life science professionals. GCAT participants have access to affordable microarrays, microarray scanners, free software for data analysis, and faculty workshops. Microarrays provided by GCAT have been used by 141 faculty on 134 campuses, including 21 faculty that serve large numbers of underrepresented minority students. An estimated 9480 undergraduates a year will have access to microarrays by 2009 as a direct result of GCAT faculty workshops. Gains for students include significantly improved comprehension of topics in functional genomics and increased interest in research. Faculty reported improved access to new technology and gains in understanding thanks to their involvement with GCAT. GCAT's network of supportive colleagues encourages faculty to explore genomics through student research and to learn a new and complex method with their undergraduates. GCAT is meeting important goals of BIO2010 by making research methods accessible to undergraduates, training faculty in genomics and bioinformatics, integrating mathematics into the biology curriculum, and increasing participation by underrepresented minority students.

DNA microarray wet lab simulation brings genomics into the high school curriculum.

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH indicators, which offer many ideal teaching characteristics. The simulation requires no specialized equipment, is very inexpensive, is very reliable, and takes very little preparation time. Student and teacher assessment data indicate the simulation is popular with both groups, and students show significant learning gains. We include many resources with this publication, including all prelab introductory materials (e.g., a paper microarray activity), the student handouts, teachers notes, and pre- and postassessment tools. We did not test the simulation on other student populations, but based on teacher feedback, the simulation also may fit well in community college and in introductory and nonmajors' college biology curricula.