Transcript Investigating Seasonal Drug Resistance in Malaria

Investigating Drug Resistance
in Malaria
Anton E. Weisstein
Joyce V. Cadwallader
Margaret A.Waterman
Scientific Roots of this Problem Space
• Malaria can be seasonal, with precipitation playing a
key role. East Africa has significant wet and dry
seasons.
• Mosquito populations increase
during wet seasons.
• Chloroquine was the drug of choice, but resistance
developed. Resistance decreased as other drugs
were used.
• This suggests that resistance carries a cost to fitness
of Plasmodium falciparum
http://www.mara.org.za/images/picseas.gif
https://www.vectorbase.org/sites/default/files/ftp/an_gambiae.png
http://www.pharmaceutical-drug-manufacturers.com/gifs/Chloroquine.jpg
Background: Common Malaria
Drugs
Chloroquine (CQ):
• The most commonly used to prevent and treat before 1993
• inhibits the conversion of heme (toxic to malaria parasite) to
hemozoin thus allowing the toxicity to increase in the cell and lysis
to occur releasing sporozoites.
• In the late 1970’s resistance was detected. 1993 most countries
stop CQ as drug or primary drug
Sulfadoxine Pyrimethanime (SP):
• A combination of containing sulfonamide
antibacterial and the antiparasitic
pyrimethanime
http://www.traveldoctor.co.uk/images/chloroquine.gif
• Both inhibit folic acid synthesis and work synergistically to deprive
http://dailymed.nlm.nih.gov/dailymed/archives/image.cfm?archiveid=86578&type=img&name=fa
the parasite
of this needed nutrient.
nsidar-image01.jpg
Transdisciplinary Approach to PS
Objectives of Problem Space
Quantitative and scientific reasoning:
•
Modeling and simulation.
– The model allows students to test hypotheses by designing experiments and
manipulating variables to investigate selection under different climate conditions
– The frequency changes of the resistant allele (outcome of the model) will then be
interpreted by the students from graphic displays of the model simulation.
•
Critiquing the model in terms of its capabilities and limitations engages
students in both the scientific process and reasoning.
•
Use of data Students will use maps of climate data and incidence of
malaria and resistance in their hypothesis formation and interpretation of
data, as well as population risk data and bioinformatic data.
•
Communication literacy: students will use primary literature to find
parameters for hypothesis formation and testing with the model.
General Introduction to Malaria
• One of the scourges of humankind is the
disease Malaria. In 2010, the World Health
Organization estimated that 216 million
people were infected with malaria and
655,000 died.
• For understanding the basics of the malaria
parasite and disease, go to the Plasmodium
Problem Space or CDC Malaria site.
Introduction to the Malaria Resistance
Curriculum and Problem Space
1. Use Gapminder tool to show global
malaria prevalence as affected by
poverty.
•
•
Concept of correlation
Interpreting graphs, using data
2. Ask students to build a table of data
from a CQ resistance map and then
create a bubble graph of
•
malaria cases per 100000—reported versus
resistance prevalence
http://www.wwarn.org/resistance/explorer
Worldwide Antimalarial Resistance Network
3.
Provide some data on CQ resistance and loss of it in
Malawi. (from Kublin et al., 2003)
Year
4.
% pfcrt CQ resistance
1992
85
1993-4
50
2000
13
2001
0
Do a Know/Need to Know exercise
•
•
Self awareness of learning
Making a learning plan
Introduce Modeling Heme 1.1
Excel-based pop. genetics simulation,
customized to life cycle of P. falciparum
• 75-day rainy season;
290-day dry season
• Transmission & treatment
only during 1 life stage,
only in rainy season
• R allele = CQ-resistant,
S allele = susceptible
(haploid!)
• R also has a fitness cost
Parameters
• Relative fitness costs &
benefits of resistance
• % of population receiving
CQ before and after
changes in treatment
policy
Use published values OR
estimate by fitting model to published data
Design your own experiment
Communication Literacy
• Activity
– Describe the characteristics of primary literature
• Peer review (in a peer reviewed journal)
• Own work
– Ask students to find an article describing some
aspect of malarial resistance
• Submit to instructor before class since do not want all
to use the same article
• Students summarize the article in classroom
presentation.
• Use some of the data in article to develop a hypothesis
for Heme model later.
Sample Data Sources
• The malaria arena is rich with many forms
of data such as:
– Data on prevalence, resistance, risk, climate,
seasonality as numeric data or maps
– Models
– Genetic information, i.e., resistant genes
sequences that could be used in
bioinformatics problems similar to
Plasmodium Problem Space
Articles
Extension: Other Mapping Sites
• Use the maps to find out information:
– Incidence of malaria in Kenya
– Temperature and Precipitation in Kenya
– Resistance to Chloroquine in Kenya
• Use maps to generate hypotheses and
explanations.
Data sets
• http://www.mara.org.za/popatrisk.htm This
is populations at risk. Table exportable to
excel
Resistance Gene to CQ: Pfcrt 76T
•
>gi|18542431|gb|AF468006.1| Plasmodium falciparum isolate TM6 putative chloroquine
resistance transporter mRNA, complete
•
cdsATGAAATTCGCAAGTAAAAAAAATAATCAAAAAAATTCAAGCAAAAATGACGAGCGTTATAG
AGAATTAGATAATTTAGTACAAGAAGGAAATGGCTCACGTTTAGGTGGAGGTTCTTGTCTTGGT
AAATGTGCTCATGTGTTTAAACTTATTTTTAAAGAGATTAAGGATAATATTTTTATTTATATTTTAAG
TATTATTTATTTAAGTGTATGTGTAATTGAAACAATTTTTGCTAAAAGAACTTTAAACAAAATTGGT
AACTATAGTTTTGTAACATCCGAAACTCACAACTTTATTTGTATGATTATGTTCTTTATTGTTTATT
CCTTATTTGGAAATAAAAAGGGAAATTCAAAAGAACGACGCCGAAGCTTTAATTTACAATTTTTT
GCTATATCCATGTTAGATGCCTGTTCAGTCATTTTGGCCTTCATAGGTCTTACAAGAACTACTG
GAAATATCCAATCATTTGTTCTTCAATTAAGTATTCCTATTAATATGTTCTTCTGCTTTTTAATATTA
AGATATAGATATCACTTATACAATTATCTCGGAGCAGTTATTATTGTTGTAACAATAGCTCTTGTA
GAAATGAAATTATCTTTTGAAGCACAAGAAGAAAATTCTATCATATTTAATCTTGTCTTAATTAGT
TCCTTAATTCCTGTATGCTTTTCAAACATGACAAGGGAAATAGTTTTTAAAAAATATAAGATTGAC
ATTTTAAGATTAAATGCTATGGTATCCTTTTTCCAATTGTTCACTTCTTGTCTTATATTACCTGTAT
ACACCCTTCCATTTTTAAAAGAACTTCATTTACCATATAATGAAATATGGACAAATATAAAAAATG
GTTTCGCATGTTTATTCTTGGGAAGAAACACAGTCGTAGAGAATTGTGGTCTTGGTATGGCTAA
GTTATGTGATGATTGTGACGGAGCATGGAAAACCTTCGCATTGTTTTCCTTCTTTAGCATTTGT
GATAATTTAATAACCAGCTATATTATCGACAAATTTTCTACCATGACATATACTATTGTTAGTTGTA
TACAAGGTCCAGCAATAGCAATTGCTTATTACTTTAAATTCTTAGCCGGTGATGTTGTAATAGAA
CCAAGATTATTAGATTTCGTAACTTTGTTTGGCTACCTATTTGGTTCTATAATTTACCGTGTAGGA
AATATTATCTTAGAAAGAAAAAAAATGAGAAATGAAGAAAATGAAGATTCCGAAGGAGAATTAA
CCAACGTCGATTCAATTATTACACAATAA
You Know What To Do!!!!!
Bibliography (partial)
Bibliography of map resources