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Record W4388140898 · doi:10.1128/msphere.00544-23

Single-cell quantitative bioimaging of <i>P. berghei</i> liver stage translation

2023· article· en· W4388140898 on OpenAlexfundno aff
James L. McLellan, William Sausman, Ashley B. Reers, Evelien M. Bunnik, Kirsten K. Hanson

Bibliographic record

VenuemSphere · 2023
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthUniversity of Cape TownMedicines for Malaria VentureYork University
KeywordsPlasmodium bergheiProteomeTranslation (biology)Plasmodium (life cycle)Plasmodium falciparumBiologyCell biologyParasite hostingComputational biologyObligateMalariaProtein biosynthesisBiochemistryImmunologyComputer scienceMessenger RNAGene

Abstract

fetched live from OpenAlex

ABSTRACT Plasmodium parasite resistance to existing antimalarial drugs poses a devastating threat to the lives of many who depend on their efficacy. New antimalarial drugs and novel drug targets are in critical need, along with novel assays to accelerate their identification. Given the essentiality of protein synthesis throughout the complex parasite lifecycle, translation inhibitors are a promising drug class, capable of targeting the disease-causing blood stage of infection, as well as the asymptomatic liver stage, a crucial target for prophylaxis. To identify compounds capable of inhibiting liver stage parasite translation, we developed an assay to visualize and quantify translation in the Plasmodium berghei- HepG2 infection model. After labeling infected monolayers with o-propargyl puromycin (OPP), a functionalized analog of puromycin permitting subsequent bioorthogonal addition of a fluorophore to each OPP-terminated nascent polypeptide, we use automated confocal feedback microscopy followed by batch image segmentation and feature extraction to visualize and quantify the nascent proteome in individual P. berghei liver stage parasites and host cells simultaneously. After validation, we demonstrate specific, concentration-dependent liver stage translation inhibition by both parasite-selective and pan-eukaryotic active compounds and further show that acute pre-treatment and competition modes of the OPP assay can distinguish between known direct translation inhibitors and other compounds which we identify as indirect translation inhibitors. Using this framework, we identify a Malaria Box compound, MMV019266, as a direct translation inhibitor in P. berghei liver stages and confirm this potential mode of action in Plasmodium falciparum asexual blood stages. IMPORTANCE Plasmodium parasites cause malaria in humans. New multistage active antimalarial drugs are needed, and a promising class of drugs targets the core cellular process of translation, which has many potential molecular targets. During the obligate liver stage, Plasmodium parasites grow in metabolically active hepatocytes, making it challenging to study core cellular processes common to both host cells and parasites, as the signal from the host typically overwhelms that of the parasite. Here, we present and validate a flexible assay to quantify Plasmodium liver stage translation using a technique to fluorescently label the newly synthesized proteins of both host and parasite followed by computational separation of their respective nascent proteomes in confocal image sets. We use the assay to determine whether a test set of known compounds are direct or indirect liver stage translation inhibitors and show that the assay can also predict the mode of action for novel antimalarial compounds.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.305
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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