CAMDA 2004 Dissecting the Malaria Transcriptome Malaria - the - - PowerPoint PPT Presentation

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CAMDA 2004 Dissecting the Malaria Transcriptome Malaria - the - - PowerPoint PPT Presentation

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CAMDA 2004 Dissecting the Malaria Transcriptome Malaria - the disease More than 400 million affected every year 1 - 2.7 million annual deaths Most deaths are children under 5 A child dies every 20-40 seconds Transmitted by

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CAMDA 2004 Dissecting the Malaria Transcriptome

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Malaria - the disease

  • More than 400 million affected every year
  • 1 - 2.7 million annual deaths
  • Most deaths are children under 5
  • A child dies every 20-40 seconds
  • Transmitted by Anopheles mosquito
  • Large economic burden

in afflicted countries

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Why is malaria a problem?

  • Third world disease
  • Widespread drug resistance
  • Very few drugs available
  • No effective vaccine
  • Very few established drug targets
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  • ! " "#
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Centers for Disease Control (1997)

Distribution of Malaria and Chloroquine-Resistant P. falciparum

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Strategies against P. falciparum

Quinine Chloroquine Mefloquine Pyrimethamine Artemisinin

1. 2. 3.

Drugs Vaccines Mosquito Control

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Why is malaria research difficult?

  • Poor genetics, haploid
  • Low transfection efficiency
  • Very high A/T content (> 80%)
  • Difficult to express proteins
  • Difficult to scale up culturing
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Plasmodium

  • Malaria caused by parasites of the genus Plasmodium
  • Plasmodium are protists of the class Apicomplexa
  • Over 5,000 described Apicomplexa species
  • All Apicomplexa are parasites

4 infect humans:

  • P. ovale
  • P. malariae
  • P. vivax
  • P. falciparum
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  • P. falciparum Lifecycle Stages
  • D. Wirth
  • 1. Mosquito
  • 2. Liver
  • 3. Blood
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Intraerythrocytic Development

Merozoite Ring Trophozoite Schizont ~ 48 Hours

L.H. Bannister

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Aims of Project

1) To determine the transcriptional profile

  • f every gene throughout asexual red

blood cell development 2) Characterize which genes are being utilized during the asexual red blood cell stage 3) Use the dataset to identify putative candidates for further study as drug and/or vaccine candidates

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What are the Big Issues?

  • P. falciparum pathogenesis?
  • parasite/host interaction
  • Host immune evasion?
  • antigenic variation by P. falciparum
  • Regulation of developmental cycles?
  • factors for transcriptional control
  • Active metabolic pathways?
  • Role of the plastid?
  • Ability to respond to environment?
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Initial Goal

A comprehensive examination of the transcriptome of the intraerythrocytic lifecycle of P. falciparum

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Design Issues

  • Array production
  • Obtaining sufficient material (RNA)
  • Culture uniformity
  • Entire intraerythrocytic lifecycle

?

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The P. falciparum genome

!$%&

  • 14 linear chromosomes
  • 22.8Mbp, ~5,400 genes
  • 6kb linear mitochondrial genome
  • 3 proteins + rRNAs
  • 35kb circular plastid genome
  • ribosomal proteins + tRNAs, rRNAs
  • Overall A/T content: 80% - 90% non-coding

60% of ORFs UNKNOWN!

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Oligo Selection Flowchart

ArrayOligoSelector

http://arrrayoligosel.sourceforge.net

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  • P. falciparum Array

70-mer oligonucleotide elements predicted for 3D7 reference strain 70-mer oligonucleotide elements predicted for 3D7 reference strain

  • 4,488 ORFs
  • 990 ORFs with multiple oligos
  • 1,315 elements outside of ORFs
  • Now updated plus 1000 ORFs
  • 4,488 ORFs
  • 990 ORFs with multiple oligos
  • 1,315 elements outside of ORFs
  • Now updated plus 1000 ORFs
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DNA Microarray Hybridization

Reference Sample Experimental Sample

Cy3 Cy5 Ratio: Cy5/Cy3

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Culture Uniformity and RNA?

Traditional approach:

  • Grow up many flasks
  • Synchronize the parasites
  • Split back out into flasks

TOO SMALL-SCALE AND TOO MUCH VARIABILITY!

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5L Parasite Culture System

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Experimental Setup

48 hourly time points

Cy3-RNA reference pool Cy5-single time point

Large scale culture of highly synchronized parasites (HB3 strain)

total RNA labeling

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Uniformity and Synchronization

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Overview of the Data

  • Most ORFs characterized by a

single max and min

  • Large variation in the amplitude
  • f overall signal
  • Timing of expression significantly

varies throughout the IDC

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Reproducibility of the Data

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How can we determine which genes are highly regulated during the intraerythrocytic development of P. falciparum?

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The Fast Fourier Transform

“The Fourier transform, in essence, decomposes

  • r separates a waveform or function into

sinusoids of different frequency which sum to the

  • riginal waveform. “
  • Forrest Hoffman

Frequency domain Time domain hours

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Power spectrum example

This shows that a sine wave of frequency two can fit the above line.

“power spectrum” sine p=2

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Real data example

Power in Two Main Frequency Components

% POWER =

(Signal to Noise) Total Power in All Frequency Components

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Data Power Spectra

74.4% 95.6% 53.1% % Power

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Distribution of % Power for

  • P. falciparum
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Distribution of % Power in Randomized Dataset

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Distribution of % Power for

  • S. cerevisiae cell cycle

(%) Power at Peak Frequencies

10 20 30 40 50 60 70 80 90 100

IDC Regulated

more less

300 200 100

Spellman, P.T. et. al., Mol. Biol. Cell 1998

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Fourier phase and timing

FFT phase

  • Related to when the maximal and minimal expression occurs.
  • Allowed us to order the profiles by the timing of expression.
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Overview Set of Most Regulated Genes

819 ORFs (24%) 2,714 ORFs (76%)

PLOT BY PHASE

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The Asexual Intraerythrocytic Developmental Cycle of Plasmodium falciparum

PHASEOGRAM

  • Continuum of expression
  • Similar function/phase
  • Just-in-time expression

“viral-like”

  • Once and only once
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Glycolysis - redundant genes

May be utilized in a different stage of development?

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Pyrimidine Synthesis dNTPs NTPs

“Just in time”

These two processes are transcriptionally uncoupled.

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Transcriptome Overview

  • Most genes are activated once and only once
  • The timing of expression is tightly correlated

with function (and trafficking)

  • Most genes in the genome are NOT

stage-specific

  • If the cascade is rigid, can it be perturbed?

Transcriptional Regulation?

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  • P. falciparum Chromosome II

Minimal coregulation within chromosomes

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Pearson Along Chromosomes

SERA Gene Family

14 total groups > 3 genes All functionally unrelated Transcription during the IDC is monocistronic.

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Apicoplast genome

Maréchal et al. Vol 6,5, 1 May 2001

  • 60 ORF RNA pol subunits,

rRNAs, tRNAs and 9 putative ORFs (one is ClpC homologue)

  • 41 represented on the array
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Comparative Genomic Hybridization

HB3 Strain used in this study vs. 3D7 Strain which was sequenced Variation in antigenic determinant genes: var, rifin, and stevor

100% loss in HB3 signal

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CGH between all chromosomes

Most differences in the highly antigenic telomere regions with some internal differences detected.

2 1 3 4 6 5 7 8 10 9 11 12 13 14

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Can we use the transcriptome to further gene predictions? Can we use the transcriptome to find anti-malarial targets?

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Apicoplast targeted ORFs

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Protease Drug Targets

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Putative Vaccine Targets

190 ORFs Unknown Function

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Erythrocyte Binding Antigen Transcriptionally-related genes

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Public availability of Data

malaria.ucsf.edu PlasmoDB.org

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  • How rigid is the IDC transcriptome?
  • Does it vary between strains of

falciparum?

  • Can P. falciparum sense and react to

external stimuli or is it hard coded? …. if so how?

New Directions

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Comparison of Three Strains

pyrimethamine sensitive pyrimethamine sensitive pyrimethamine resistant sulfadoxine resistant sulfadoxine resistant sulfadoxine sensitive chloroquine sensitive chloroquine resistant chloroquine sensitive Netherlands Indochina Honduras 3D7 Dd2 HB3

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Three Time courses

HB3: 48 timepoints Dd2: 50 timepoints 3D7: 53 timepoints

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What might change?

Genes may not be expressed in the other strains. Genes may change their timing of expression (phase). Genes may change their mode of regulation (constitutive). AMPLITUDE PHASE

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Overall program is preserved

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Sample Profiles

General Conclusions:

  • Most of the expression

profiles are similar.

  • Confirmation of initial

HB3 results.

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FFT % Power for 3 Strains

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Variable Expression Infrequent

Less than 1% of the expression profiles measured for these three strains differ significantly in their phase of expression.

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Interesting Case

  • For the Dd2 strain there is

NO DETECTABLE SIGNAL from

  • PFC0772.

3D7 HB3

Alternative Splicing?

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Data will be available at PlasmoDB.org soon!

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Perturbation Study No specific transcriptional response to an external stimulus has ever been detected in P. falciparum.

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> 350 genes

With so many similar profiles, how do we further dissect genes which are functionally related?

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6,000 genes

Expression Map of the Yeast Genome

Meiosis specific genes

100s of experiments

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Perturbation study

Chloroquine Glucose Depletion Serum Depletion Hypoxanthine 42 ° C Heat Shock MMS Run timecourse experiments so we can anchor the results in the transcriptome.

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Conclusions

  • Definitive first pass analysis of the transcriptome
  • See a cascade of gene expression which once

initiated continues until cycle terminates

  • Genes of similar function cluster together
  • aid in assignment of function to 60% unknown
  • Differences between strains will be important to

understanding drug resistance and provide leads for drug targets

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Bioinformatics + “wet lab”

  • Use all available data: PlasmoDB

Long-oligo microarray data Affymetrix data (Le Roch et al.)

  • other developmental stages

Other Plasmodium genomes EST data Proteomics data

  • More data on related strains and

environmental perturbations

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Acknowledgements

Joseph L. DeRisi malaria.ucsf.edu

The Rest of the Malaria Team...

  • Sandler Foundation
  • NIAID
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