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 Ryder ID: 914078
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Slide1
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
Slide2Goal: 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/datadata from molecular to population levelscurriculum/lesson guides of varying complexityIntro BioGenetics
Mol.bio
Cell Bio
Microbiology
GenomicsIndep. studyCapstone
Slide3target audience and required prior knowledge, learning objectives, concepts covered,
student assignments/handouts, required resources,suggested activities, implementation.Lesson guides will include/specify
Slide4Learning 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.
Slide5Model problem space: choleraConcepts:
Evolution,
Pathways,
Structure-function,
Information flow,
Systems
Slide6Why is clean water important?Cholera is a well-known hazardCholera is a bacteria
Fecal Oral transmissionCholera Toxin (A-B toxin)Species Varability Serovars (different strains within each serovar)
Slide7Intro/intermediate level assignments for investigation: 1. Case study investigating cholera outbreak in Haiti after the earthquake – origin of outbreak – relief worker.
Another example: Katrina2. Some people are resistant to cholera– genetic basis of that?http://www.cbsnews.com/8301-504763_162-20020850-10391704.html
Slide8Intro/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
Slide9The 2010 Earthquake in Haiti PhotosDestruction of InfrastructureCholera Casualties
534,647 cases resulting in 287,656 hospitalizations, and 7,091 deaths have been reported in Haiti as a result of the outbreak.
Slide10Katrina 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
.
Slide11Data, 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.htm3. Preoteopedia
cholera toxin link
http://
www.proteopedia.org/wiki/index.php/1xtc4. 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 Africa
http://wwwnc.cdc.gov/eid/article/17/11/11-0794_article.htm
Slide12Cholera Problem Space in an Upper level Bioinformatics classRevisit the Cholera Problem Space
Have students perform the alignment and phylogenetic tree generation from the paper from the Intro courseAsk students to find an experiment related to cholera in Expression ATLASHypothesize pathways that might be enriched for differentially expressed genesPerform the analysis and interpret dataPick an enriched pathway and explore it
Slide13Advanced courses: analysis of gene expression workflow
Disease(cholera)Differentially expressed genesClassify genes by function(Location, cell process, molecular function)
ID pathways
Involved/affected
by disease
AMIGO in
Gene Ontology
Reactome
ArrayExpress
Atlas
1. Explain mech. of disease on
the molecular and cellular levels
2. Propose
Experiments to test mechanisms
strategies for therapies
Slide14A promising experiment on cholera in Expression ATLAS
Slide15Nice, simple, one factor set upMouse dendritic cells
Cholera toxin, forskolin, control mediaIn mice – should have nice annotated pathwaysLooked at top 400 genes (p values 10-6 to 10-4)
Slide16Top 10 differentially expressed genes
Slide17Reactome databaseOver-representation analysis
Unfortunately, none of these pathways exactly leap out as being over-representedDrosophila and C. elegans experiments found very few genes that mapped to pathways
Slide18Model organism
Slide19Experiment compared gene expression in two fly mutants with different susceptibility to cholera
Slide20Slide21Heat Map
Slide22Sample expression data from ATLAS
http://www.ebi.ac.uk/gxa/experiment/E-GEOD-35439
Slide23Advanced courses: analysis of gene expression workflow
Disease(cholera)Differentially expressed genesClassify genes by function(Location, cell process, molecular function)
ID pathways
Involved/affected
by disease
AMIGO in
Gene Ontology
Reactome
ArrayExpress
Atlas
1. Explain mech. of disease on
the molecular and cellular levels
2. Propose
Experiments to test mechanisms
strategies for therapies
Slide24Disease
(cholera)Differentially expressed genesClassify genes by function(Location, cell process, molecular function)ID pathways Involved/affected by disease
Transcription
f
actors involved
AMIGO in
Gene Ontology
Reactome
Biomart
Sequence 2KB upstream of
Transcription start site
Meme
B
inding sites
for
Txn
factors
ArrayExpress
Atlas
Uniprot
Advanced courses: analysis of gene expression workflow
make simple models for regulatory networks and try to test their models with other
data
Slide25Assessment:
Learning Obj.:Students should be able to ConceptCommon 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
Slide26Learning Obj.:
Students should be able to ConceptCommon 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