Anya Goodman

The Genomics Education Partnership: Successful Integration of Research into Laboratory Classes at a Diverse Group of Undergraduate Institutions

Genomics is not only essential for students to understand biology but also provides unprecedented opportunities for undergraduate research. The goal of the Genomics Education Partnership (GEP), a collaboration between a growing number of colleges and universities around the country and the Department of Biology and Genome Center of Washington University in St. Louis, is to provide such research opportunities. Using a versatile curriculum that has been adapted to many different class settings, GEP undergraduates undertake projects to bring draft-quality genomic sequence up to high quality and/or participate in the annotation of these sequences. GEP undergraduates have improved more than 2 million bases of draft genomic sequence from several species of Drosophila and have produced hundreds of gene models using evidence-based manual annotation. Students appreciate their ability to make a contribution to ongoing research, and report increased independence and a more active learning approach after participation in GEP projects. They show knowledge gains on pre- and postcourse quizzes about genes and genomes and in bioinformatic analysis. Participating faculty also report professional gains, increased access to genomics-related technology, and an overall positive experience. We have found that using a genomics research project as the core of a laboratory course is rewarding for both faculty and students.

Genomics Education Partnership

The Genomics Education Partnership offers an inclusive model for undergraduate research experiences, with students pooling their work to contribute to international databases.

A Course-Based Research Experience: How Benefits Change with Increased Investment in Instructional Time

While course-based research in genomics can generate both knowledge gains and a greater appreciation for how science is done, a significant investment of course time is required to enable students to show gains commensurate to a summer research experience. Nonetheless, this is a very cost-effective way to reach larger numbers of students.

A Central Support System Can Facilitate Implementation and Sustainability of a Classroom-Based Undergraduate Research Experience (CURE) in Genomics

There have been numerous calls to engage students in science as science is done. A survey of 90-plus faculty members explores barriers and incentives when developing a research-based genomics course. The results indicate that a central core supporting a national experiment can help overcome local obstacles.

Teaching bioinformatics in concert.

Can biology students without programming skills solve problems that require computational solutions? They can if they learn to cooperate effectively with computer science students. The goal of the in-concert teaching approach is to introduce biology students to computational thinking by engaging them in collaborative projects structured around the software development process. Our approach emphasizes development of interdisciplinary communication and collaboration skills for both life science and computer science students.

Pyroprinting: a rapid and flexible genotypic fingerprinting method for typing bacterial strains.

Bacterial strain typing is commonly employed in studies involving epidemiology, population ecology, and microbial source tracking to identify sources of fecal contamination. Methods for differentiating strains generally use either a collection of phenotypic traits or rely on some interrogation of the bacterial genotype. This report introduces pyroprinting, a novel genotypic strain typing method that is rapid, inexpensive, and discriminating compared to the most sensitive methods already in use. Pyroprinting relies on the simultaneous pyrosequencing of polymorphic multicopy loci, such as the intergenic transcribed spacer regions of rRNA operons in bacterial genomes. Data generated by sequencing combinations of variable templates are reproducible and intrinsically digitized. The theory and development of pyroprinting in Escherichia coli, including the selection of similarity thresholds to define matches between isolates, are presented. The pyroprint-based strain differentiation limits and phylogenetic relevance compared to other typing methods are also explored. Pyroprinting is unique in its simplicity and, paradoxically, in its intrinsic complexity. This new approach serves as an excellent alternative to more cumbersome or less phylogenetically relevant strain typing methods.

Short communication: Typing and tracking Bacillaceae in raw milk and milk powder using pyroprinting

Contamination of fluid and processed milk products with endospore-forming bacteria, such as Bacillaceae, affect milk quality and longevity. Contaminants come from a variety of sources, including the dairy farm environment, transportation equipment, or milk processing machinery. Tracking the origin of bacterial contamination to allow specifically targeted remediation efforts depends on a reliable strain-typing method that is reproducible, fast, easy to use, and amenable to computerized analysis. Our objective was to adapt a recently developed genotype-based Escherichia coli strain-typing method, called pyroprinting, for use in a microbial source-tracking study to follow endospore-forming bacillus bacteria from raw milk to powdered milk. A collection of endospores was isolated from both raw milk and its finished powder, and, after germination, the vegetative cells were subject to the pyroprinting protocol. Briefly, a ribosomal DNA intergenic transcribed spacer present in multiple copies in Bacillaceae genomes was amplified by the PCR. This multicopy locus generated a mixed PCR product that was subsequently subject to pyrosequencing, a quantitative real-time sequencing method. Through a series of enzymatic reactions, each nucleotide incorporation event produces a photon of light that is quantified at each nucleotide dispensation. The pattern of light peaks generated from this mixed template reaction is called a pyroprint. Isolates with pyroprints that match with a Pearson correlation of 0.99 or greater are considered to be in the same group. The pyroprint also contains some sequence data useful for presumptive species-level identification. This method identified groups with isolates from raw milk only, from powdered milk only, or from both sources. This study confirms pyroprinting as a rapid, reproducible, automatically digitized tool that can be used to distinguish bacterial strains into taxonomically relevant groups and, thus, indicate probable origins of bacterial contamination in powdered milk.

Leveraging the k-Nearest Neighbors classification algorithm for Microbial Source Tracking using a bacterial DNA fingerprint library

Fecal contamination in bodies of water is an issue that cities must combat regularly. Often, city governments must restrict access to water sources until the contaminants dissipate. Sourcing the species of the fecal matter helps curb the issue in the future, giving city governments the ability to mitigate the effects before they occur again. Microbial Source Tracking (MST) aims to determine source host species of strains of microbiological lifeforms and library-based MST is one method that can assist in sourcing fecal matter. Recently, the Biology Department in conjunction with the Computer Science Department at California Polytechnic State University San Luis Obispo (Cal Poly) teamed up to build a database called the Cal Poly Library of Pyroprints (CPLOP). Students collect fecal samples, culture and pyrosequence the E. coli in the samples, and insert this data, called pyroprints, into CPLOP. Using two intergenic transcribed spacer regions of DNA, Cal Poly biologists perform studies on strain differentiation. We propose using k-Nearest Neighbors, a straightforward machine learning technique, to classify the host species of a given pyroprint, construct four algorithms to resolve the regions, and investigate classification accuracy.

Pyroprinting sensitivity analysis on the GPU

Microbial Source Tracking (MST) is a field in which microbial strains are identified and associated with a specific host source (e.g., human, canine, avian, etc). Identifying the hosts of microbial strains lies at the heart of many studies of bacterial contamination in the environment. Being able to determine which host species is responsible, e.g., for fecal contamination of a creek, allows the parties involved to develop specific measures for addressing the contamination. The paper presents an in-silico study to investigate the sensitivity of the pyroprinting method. Given a collection of possible DNA sequences that can be found in the sequenced ITS regions, we construct a collection of all possible theoretical combinations. Each such combination represents a theoretically possible strain of E. coli. We construct a pyroprint model of each strain, and then build a matrix of pairwise similarities between the pyroprints.

Microbial source tracking by molecular fingerprinting

To date, microbial source tracking (MST), i.e. determining the source of microbial contamination based on the specific strains observed in environment, is done using methods that are time-consuming, expensive and not always reliable. The biology department at Cal Poly, San Luis Obispo has developed a new method for MST called pyroprinting. Pyroprints are a result of pyrosequencing replicates of intergenic transcribed spacer (ITS) regions in a target bacterial genome. E. coli pyroprints can be used as DNA fngerprints of individual E. coli strains in identifying sources of fecal contamination and studying bacterial patterns in host animals. The MST method consists of two parts: the pyroprinting process and a database of sequenced pyroprints. The actual source tracking is achieved by comparing a newly obtained pyroprint to the pyroprints of known provenance from a database. In this paper, we describe the design and implementation of Cal Poly Library of Pyroprints (CPLOP). The CPLOP database provides storage and essential analysis of pyroprints for strain identification. Our current implementation contains pyroprints of bacterial isolates of E. coli, obtained by students and researchers from known hosts and from the environment. Users of CPLOP are able to organize pyroprints into groups, run analyses to find similarities between bacterial isolates, and cluster isolates into bacterial strains.