Establishment of quantitative RNAi-based forward genetics in Entamoeba histolytica and identification of genes required for growth

Autor: Tammie S. Y. Tam, Hannah W. Miller, Rene L. Suleiman, Samuel S. Hunter, Wesley Huang, Maura C. Ruyechan, Akhila Bettadapur, Matthew L. Settles, Charles G. Barbieri, Katherine S. Ralston
Přispěvatelé: Singh, Upinder
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Mutant
Protozoan Proteins
Genome
Biochemistry
RNA interference
Amoebas
Cloning
Molecular

Biology (General)
Protozoans
Staining
biology
Entamoebiasis
Entamoeba histolytica
Eukaryota
High-Throughput Nucleotide Sequencing
Genomics
Specimen preparation and treatment
Nucleic acids
Infectious Diseases
Genetic interference
Medical Microbiology
Gene Knockdown Techniques
Protozoan
RNA Interference
Epigenetics
Biotechnology
Research Article
QH301-705.5
1.1 Normal biological development and functioning
Immunology
Computational biology
DNA construction
Transfection
Research and Analysis Methods
Microbiology
Deep sequencing
Vaccine Related
Entamoeba Histolytica
Underpinning research
Biodefense
Virology
Genetics
Animals
Molecular Biology Techniques
Gene
Molecular Biology
Gene Library
Prevention
Organisms
DAPI staining
Molecular
Biology and Life Sciences
DNA
DNA
Protozoan

RC581-607
biology.organism_classification
Forward genetics
Parasitic Protozoans
Emerging Infectious Diseases
Plasmid Construction
Nuclear staining
Mutation
RNA
Parasitology
Generic health relevance
Gene expression
Immunologic diseases. Allergy
Genome
Protozoan

Cloning
Genome-Wide Association Study
Zdroj: PLoS Pathogens, Vol 17, Iss 11, p e1010088 (2021)
PLoS Pathogens
PLoS pathogens, vol 17, iss 11
ISSN: 1553-7374
1553-7366
Popis: While Entamoeba histolytica remains a globally important pathogen, it is dramatically understudied. The tractability of E. histolytica has historically been limited, which is largely due to challenging features of its genome. To enable forward genetics, we constructed and validated the first genome-wide E. histolytica RNAi knockdown mutant library. This library allows for Illumina deep sequencing analysis for quantitative identification of mutants that are enriched or depleted after selection. We developed a novel analysis pipeline to precisely define and quantify gene fragments. We used the library to perform the first RNAi screen in E. histolytica and identified slow growth (SG) mutants. Among genes targeted in SG mutants, many had annotated functions consistent with roles in cellular growth or metabolic pathways. Some targeted genes were annotated as hypothetical or lacked annotated domains, supporting the power of forward genetics in uncovering functional information that cannot be gleaned from databases. While the localization of neither of the proteins targeted in SG1 nor SG2 mutants could be predicted by sequence analysis, we showed experimentally that SG1 localized to the cytoplasm and cell surface, while SG2 localized to the cytoplasm. Overexpression of SG1 led to increased growth, while expression of a truncation mutant did not lead to increased growth, and thus aided in defining functional domains in this protein. Finally, in addition to establishing forward genetics, we uncovered new details of the unusual E. histolytica RNAi pathway. These studies dramatically improve the tractability of E. histolytica and open up the possibility of applying genetics to improve understanding of this important pathogen.
Author summary Entamoeba histolytica is a globally important pathogen that is dramatically understudied. One of the major limitations of this organism is its challenging genome. RNAi is the state-of-the-art tool for genetic manipulation in E. histolytica, though the RNAi pathway has several noncanonical features. Here, we harnessed the RNAi pathway to enable RNAi-based forward genetics for the first time in this organism. We validated the RNAi library by performing the first E. histolytica RNAi screen and identified slow growth mutants. We showed that independently-generated mutants also exhibited slow growth phenotypes, and we characterized protein localization and domains for some of the identified slow growth genes. The RNAi library that we constructed enables modern, quantitative Illumina deep sequencing analysis to identify mutants that are enriched or depleted after selection. We developed a novel analysis pipeline to precisely define and quantify full-length gene fragments inferred from read mapping. Our approach differs from previous approaches for analysis of RNAi screens, and it better represents the actual DNA fragments and their quantities. This study dramatically improves the tractability of this important pathogen. Moreover, the strategies behind this RNAi library, and its analysis, are novel, and can be applied to other organisms.
Databáze: OpenAIRE