11 research outputs found
Transcriptomics and proteomics reveal two waves of translational repression during the maturation of malaria parasite sporozoites.
Plasmodium sporozoites are transmitted from infected mosquitoes to mammals, and must navigate the host skin and vasculature to infect the liver. This journey requires distinct proteomes. Here, we report the dynamic transcriptomes and proteomes of both oocyst sporozoites and salivary gland sporozoites in both rodent-infectious Plasmodium yoelii parasites and human-infectious Plasmodium falciparum parasites. The data robustly define mRNAs and proteins that are upregulated in oocyst sporozoites (UOS) or upregulated in infectious sporozoites (UIS) within the salivary glands, including many that are essential for sporozoite functions in the vector and host. Moreover, we find that malaria parasites use two overlapping, extensive, and independent programs of translational repression across sporozoite maturation to temporally regulate protein expression. Together with gene-specific validation experiments, these data indicate that two waves of translational repression are implemented and relieved at different times during sporozoite maturation, migration and infection, thus promoting their successful development and vector-to-host transition
Addendum: Transcriptomics and proteomics reveal two waves of translational repression during the maturation of malaria parasite sporozoites.
Origins of Replication Determine Plasmid Copy Number.
<p>The origins of replication used in the study are listed with their descriptions and part numbers in the Registry of Standard Biological Parts. The means and standard deviations of PCN values were determined by qPCR and yields of minipreps.</p
Results of Programmed Evolution.
<p>(A) The starting population with equal amounts of all 24 strains was spread on LB agar plates with the indicated antibiotic and a disk treated as indicated. (B) Top row: spots of cells on LB agar with ampicillin for all 24 starting strains (left) and examples of clones after Programmed Evolution (right). Middle row: Agarose gels with PCR products to determine PCN for all 24 strains (left) and examples after Programmed Evolution (right). The 750 bp band for the low copy origin and the 500 bp band for the high copy origin are indicated by arrows. Bottom row: Agarose gels with PCR products to chaperone genotype for all 24 strains (left) and examples after Programmed Evolution (right). (C) The graph shows relative frequency of each of the genotype before (top) and after (bottom) Programmed Evolution. The order of chaperone plasmids along the left to right horizontal axis is pG-Tf2, pTf16, pG-KJE8, pGro7, pKJE7, and no chaperone. The order of genotype combinations along the other horizontal axis from back to front is high strength promoter/RBS + high copy origin; high strength promoter/RBS + low copy origin; low strength promoter/RBS + high copy origin; and low strength promoter/RBS + low copy origin.</p
Starting Population for Programmed Evolution.
<p>(A) An ampicillin resistance plasmid carries variation in the strength of promoters and RBS elements as well as the low and high copy number origins of replication. (B) A chloramphenicol resistance plasmid carries chaperones DNA KJE, Trigger Factor, and Gro ESL chaperones individually and in two combinations (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118322#sec004" target="_blank">Methods</a> for details).</p
Relative Fitness of Genotypes as a Function of Theophylline Production.
<p>Theophylline production as measured by LC-MS analysis is listed for the three genotypes with the highest fitness and two genotypes with very low fitness.</p
Results of Programmed Evolution.
<p>The number and genotype of colonies analyzed after Programmed Evolution from three replicate plate experiments.</p
Biosensor and Fitness Modules.
<p>(A) The Biosensor Module contains a promoter, a riboswitch that binds to theophylline, and a GFP gene. (B) Cells with the indicated genotypes were incubated with caffeine or theophylline. Fluorescence of cells grown in theophylline or caffeine was divided by absorbance at 590 nm (relative fluorescence) to correct for variation in cell density. (C) Relative fluorescence as a function of time in cells with and without the biosensor grown in 2.5 mM theophylline. (D) The Fitness Module contains a promoter, a riboswitch that binds theophylline, and the tetracycline resistance gene (<i>tetA</i>). (E) Cell growth in media containing tetracycline and either theophylline or caffeine as indicated.</p
Programmed Evolution.
<p>The Combinatorics Module facilitates variation of elements controlling orthogonal metabolism. Genetic variation is illustrated by different colors of bacteria. The Fitness Module defines fitness as orthogonal metabolic output and cell growth, and imposes negative selection on bacteria with low metabolic output, shown by elimination of some of the colored bacteria. A Biosensor Module is used to measure the metabolic output of the population or individual cells. Programmed Evolution can be repeated for successive cycles.</p
Optimization of Metabolic Pathways.
<p>(A) Orthogonal metabolic output in a bacterial cell is depicted as a function (<i>f</i>) of the genetic circuit controlling metabolism and additional variables. (B) Two gene expression cassettes are drawn that encode enzymes controlling a metabolic pathway. Promoters, ribosome binding sites, and alleles for the two cassettes are chosen from a library of elements.</p