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      Functional Profiling of a Plasmodium Genome Reveals an Abundance of Essential Genes

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          Summary

          Malaria parasites have around 5,000 genes. Only a small proportion of these genes have homologs in well-studied model systems, and as a result the function of many is unclear. We performed the first genome-scale genetic screen in a malaria parasite.

          We used linear DNA vectors which integrate into the Plasmodium genome. We were able to create vectors to target around half of all Plasmodium berghei genes. Each vector integrates into the parasite genome in the place of its target gene. It carries a drug resistance marker that enables us to select only parasites in which a gene has been deleted. The vectors also carry a "genetic barcode" into the parasite genome. We can amplify all of the barcodes from a mixture of thousands of parasites and read them out using DNA sequencing. This allowed us to measure the growth of many different mutants in a mixed population of parasites. By doing so we could work out whether deleting a gene had a profound effect on parasite growth ("essential" gene), a more moderate effect ("slow" gene) or no evidence of a change in growth rate ("dipsensable gene").

           

          We unexpectedly found that most genes are important for parasite growth, even in a single stage of parasite growth - in the blood of an infected host. This is a higher proportion of essential genes than has been seen in any other organism screens and suggests that there may be more multi-stage drug targets encoded by the parasite than was previously supposed.

           

          All phenotypes are available on the PlasmoGEM site: http://plasmogem.sanger.ac.uk/phenotypes

          Summary

          The genomes of malaria parasites contain many genes of unknown function. To assist drug development through the identification of essential genes and pathways, we have measured competitive growth rates in mice of 2,578 barcoded Plasmodium berghei knockout mutants, representing >50% of the genome, and created a phenotype database. At a single stage of its complex life cycle, P. berghei requires two-thirds of genes for optimal growth, the highest proportion reported from any organism and a probable consequence of functional optimization necessitated by genomic reductions during the evolution of parasitism. In contrast, extreme functional redundancy has evolved among expanded gene families operating at the parasite-host interface. The level of genetic redundancy in a single-celled organism may thus reflect the degree of environmental variation it experiences. In the case of Plasmodium parasites, this helps rationalize both the relative successes of drugs and the greater difficulty of making an effective vaccine.

          Graphical Abstract

          Highlights

          • Two-thirds of Plasmodium berghei genes contribute to normal blood stage growth

          • The core genome of malaria parasites is highly optimized for rapid host colonization

          • Essential parasite genes and pathways are identified for drug target prioritization

          • Low functional redundancy reflects the constant environment encountered by a parasite

          Abstract

          An in vivo genetic screen in a mouse model of malaria reveals the essential genes and pathways required by Plasmodium parasite, with a surprising two-thirds of the genome being required for normal parasite growth in the blood.

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          Most cited references37

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          The genetic landscape of a cell.

          A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
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            Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

            Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. 1,2 Here we describe methods for large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short term culture. Analysis of 86,158 exonic SNPs that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome.
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              Count: evolutionary analysis of phylogenetic profiles with parsimony and likelihood.

              Count is a software package for the analysis of numerical profiles on a phylogeny. It is primarily designed to deal with profiles derived from the phyletic distribution of homologous gene families, but is suited to study any other integer-valued evolutionary characters. Count performs ancestral reconstruction, and infers family- and lineage-specific characteristics along the evolutionary tree. It implements popular methods employed in gene content analysis such as Dollo and Wagner parsimony, propensity for gene loss, as well as probabilistic methods involving a phylogenetic birth-and-death model. Count is available as a stand-alone Java application, as well as an application bundle for MacOS X, at the web site http://www.iro.umontreal.ca/ approximately csuros/gene_content/count.html. It can also be launched using Java Webstart from the same site. The software is distributed under a BSD-style license. Source code is available upon request from the author.
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                Author and article information

                Contributors
                Journal
                Cell
                Cell
                Cell
                Cell Press
                0092-8674
                1097-4172
                13 July 2017
                13 July 2017
                : 170
                : 2
                : 260-272.e8
                Affiliations
                [1 ]Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
                [2 ]Research School of Biology, Australian National University, Canberra, Australia
                [3 ]Drexel University College of Medicine, Philadelphia, PA, USA
                [4 ]School of Biosciences, University of Melbourne, Royal Parade, Parkville, Australia
                [5 ]DIMNP, CNRS, INSERM, University Montpellier, Montpellier, France
                Author notes
                []Corresponding author julian.rayner@ 123456sanger.ac.uk
                [∗∗ ]Corresponding author oliver.billker@ 123456sanger.ac.uk
                [6]

                These authors contributed equally

                [7]

                Lead Contact

                Article
                S0092-8674(17)30714-6
                10.1016/j.cell.2017.06.030
                5509546
                28708996
                3004a8d7-ec33-49dd-9493-950a15e53c4c
                © 2017 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 November 2016
                : 13 April 2017
                : 19 June 2017
                Categories
                Article

                Cell biology
                malaria,plasmodium,genetics,reverse genetic,knockout,screen,barcode,gene disruption,phenotypes
                Cell biology
                malaria, plasmodium, genetics, reverse genetic, knockout, screen, barcode, gene disruption, phenotypes

                Comments

                Malaria vaccine development collection topic 5) Identifying and developing the new generation of malaria vaccines - Unraveling host-parasite interactions.

                See https://www.scienceopen.com/collection/malariavaccine

                 

                An in vivo genetic screen in a mouse model of malaria reveals the essential genes and pathways required by Plasmodium  parasite, with a surprising two-thirds of the genome being required for normal parasite growth in the blood.

                2018-10-10 12:29 UTC
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