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Investigation of the molecular basis of diseases with bioinformatics tools for students in different stages of training: problem space for cholera. Nancy Boury Anya Goodman Jose Monterrubio Srebrenka Robic Liz RyderArlin Toro

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Investigation of the molecular basis of diseases with bioinformatics tools for

students in different stages of training: problem space for cholera.

Nancy Boury Anya GoodmanJose Monterrubio Srebrenka Robic Liz Ryder Arlin Toro

Goal: Create a framework for engaging biology students in investigation of human disease in classrooms from freshman to senior level.

The problem space will include background

info/links/resources/data data from molecular to

population levels curriculum/lesson guides of

varying complexity

Intro Bio

GeneticsMol.bioCell BioMicrobiology

GenomicsIndep. studyCapstone

• target audience and required prior knowledge,

• learning objectives, • concepts covered, • student assignments/handouts, • required resources,• suggested activities,

implementation.

Lesson guides will include/specify

Learning objectives for all levels (different depth):

Students should be able to • 1. Use appropriate sources to find info

(Information literacy)1A use databases to find info.

• 2. Formulate questions and hypotheses from data exploration.

• 3. Draw conclusions supported by evidence.

Model problem space: cholera

Concepts:• Evolution, • Pathways, • Structure-function, • Information flow, • Systems

Why is clean water important?

• Cholera is a well-known hazard

• Cholera is a bacteria – Fecal Oral transmission– Cholera Toxin (A-B toxin)– Species Varability

• Serovars (different strains within each serovar)

Intro/intermediate level assignments for investigation:

1. Case study investigating cholera outbreak in Haiti after the earthquake – origin of outbreak – relief worker. Another example: Katrina

2. Some people are resistant to cholera– genetic basis of that?

http://www.cbsnews.com/8301-504763_162-20020850-10391704.html

Intro/intermediate level assignments for investigation:

3. Cholera toxin protein structure – understand how it causes disease, how this fold evolved, how it relates to other toxins.4. Explore the evolutionary relationship between the bacterium and phages encoding the toxins. molecule of the month

10.2210/rcsb_pdb/mom_2005_9

The 2010 Earthquake in Haiti

• Photos

• Destruction of Infrastructure

• Cholera Casualties – 534,647 cases resulting in 287,656

hospitalizations, and 7,091 deaths have been reported in Haiti as a result of the outbreak.

Katrina outbreak

Hurricane Katrina made landfall on August 29, 2005, with major impact on the U.S. Gulf Coast. During August 29–September 11, surveillance idetified 22 new cases of Vibrio illness with five deaths in persons who had resided in two state (Figure 1)

Cholera is a severe diarrheal illness caused by V. cholerae serogroups O1 or O139, which produce cholera toxin (i.e., toxigenic V. cholerae O1 or O139).

The most frequently reported post-hurricane Vibrio illnesses were V. vulnificus and V. parahaemolyticus wound infections. These cases represent an increase over the normal reported incidence of Vibrio wound infections in Gulf Coast states and are consistent with exposure after hurricane landfall.Illness likely resulted from infection of a wound or abrasion acquired before or during immersion in floodwaters.

http://www.cdc.gov/mmwr/preview/mmwrhtml/mm54d914a1.htm#fig1

Centers for Disease Control and Prevention (CDC).Vibrio illnesses after Hurricane Katrina--multiple states, August-September 2005. MMWR Morb Mortal Wkly Rep. 2005 Sep 23;54(37):928-31.

Center for Disease Control and Prevention (CDC).Two cases of toxigenic Vibrio cholerae O1 infection after Hurricanes Katrina and Rita--Louisiana, October 2005. MMWR Morb Mortal Wkly Rep. 2006 Jan 20;55(2):31-2.

Data, resources, links: 1. Cholera in Haiti : The Origin of the Haitian Cholera Outbreak Strain - NEJM article http://www.nejm.org/doi/pdf/10.1056/NEJMoa1012928

2. Notes from the Field: Identification of Vibrio cholerae Serogroup O1, Serotype Inaba, Biotype El Tor Strain — Haiti, March 2012 MMRW May 4, 2012 / 61(17);309-309

http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6117a4.htm

3. Preoteopedia cholera toxin link http://www.proteopedia.org/wiki/index.php/1xtc

4. Cholera toxin molecule of the month Link to “molecule of the month” on pdbhttp://www.rcsb.org/pdb/101/motm.do?momID=695. Vibrio cholera database at Broad Institute

http://www.broadinstitute.org/annotation/genome/vibrio_cholerae/MultiHome.html6. Comparative Genomics of Vibrio cholerae from Haiti, Asia, and Africahttp://wwwnc.cdc.gov/eid/article/17/11/11-0794_article.htm

Cholera Problem Space in an Upper level Bioinformatics class

• Revisit the Cholera Problem Space• Have students perform the alignment and

phylogenetic tree generation from the paper from the Intro course

• Ask students to find an experiment related to cholera in Expression ATLAS– Hypothesize pathways that might be enriched for

differentially expressed genes– Perform the analysis and interpret data– Pick an enriched pathway and explore it

Advanced courses: analysis of gene expression workflow

Disease(cholera)

Differentially expressed genes

Classify genes by function(Location, cell process, molecular function)

ID pathways Involved/affected by disease

AMIGO in Gene Ontology

Reactome

ArrayExpressAtlas

1. Explain mech. of disease on the molecular and cellular levels2. Propose •Experiments to test mechanisms•strategies for therapies

A promising experiment on cholera in Expression ATLAS

• Nice, simple, one factor set up– Mouse dendritic cells– Cholera toxin, forskolin, control media

• In mice – should have nice annotated pathways• Looked at top 400 genes (p values 10-6 to 10-4)

Top 10 differentially expressed genes

Reactome databaseOver-representation analysis

• Unfortunately, none of these pathways exactly leap out as being over-represented

• Drosophila and C. elegans experiments found very few genes that mapped to pathways

Model organism

Experiment compared gene expression in two fly mutants with different susceptibility to cholera

Heat Map

Sample expression data from ATLAS

http://www.ebi.ac.uk/gxa/experiment/E-GEOD-35439

Advanced courses: analysis of gene expression workflow

Disease(cholera)

Differentially expressed genes

Classify genes by function(Location, cell process, molecular function)

ID pathways Involved/affected by disease

AMIGO in Gene Ontology

Reactome

ArrayExpressAtlas

1. Explain mech. of disease on the molecular and cellular levels2. Propose •Experiments to test mechanisms•strategies for therapies

Disease(cholera)

Differentially expressed genes

Classify genes by function(Location, cell process, molecular function)

ID pathways Involved/affected by disease

Transcriptionfactors involved

AMIGO in Gene Ontology

ReactomeBiomart

Sequence 2KB upstream of Transcription start site

Meme

Binding sites for Txn factors

ArrayExpressAtlas

Uniprot

Advanced courses: analysis of gene expression workflow

make simple models for regulatory networks and try to test their models with other data

Assessment:Learning Obj.:Students should be able to

Concept Common misconception

Ideas for ways to assess

1. Use appropriate sources to find info (Information literacy)

1B. Peer reviewed source is more more trustworthy than non-peer reviewed.?1C. Expert source is more trustworthy than non-expert (as long as its a real expert with no conflict of interest e.g. Dr. X is selling pill Y that will make you live forever)

1B and 1C. If it is on the web, it must be true

give students X websites/sources and ask to evaluate most appropriate source of info for a given question.Alt: Pose a question, ask students to find info and report 3 credible sources and explain why these are credible

Learning Obj.:Students should be able to

Concept Common misconception

Ideas for ways to assess

1A. Use scientific databases to find info.

1A. Curated data is more trustworthy than automated data.

1A. if it is in the database, it is correct.

content specific questions: can student find X

2. Formulate questions and hypotheses.

Patterns in data can suggest relationships that can be tested.

3. Draw conclusions supported by evidence.

Credible statements in science must be supported by evidence.

correlation implies causation