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Record W4389793877 · doi:10.1101/2023.12.15.571799

Neoblast-like Stem Cells of <i>Fasciola hepatica</i>

2023· preprint· en· W4389793877 on OpenAlexfundno aff
Paul McCusker, Nathan Clarke, Erica Gardiner, Rebecca Armstrong, Erin McCammick, Paul McVeigh, Emily Robb, Duncan Wells, Madelyn Nowak-Roddy, Abdullah Albaqami, Angela Mousley, Jonathan A. Coulter, John Harrington, Nikki J. Marks, Aaron G. Maule

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilQueen's UniversityQueen's University Belfast
KeywordsBiologyFasciola hepaticaHepaticaStem cellFlatwormCell biologyStem cell markerPlanarianImmunologyRegeneration (biology)HelminthsZoology

Abstract

fetched live from OpenAlex

Abstract The common liver fluke ( Fasciola hepatica ) causes the disease fasciolosis, which results in considerable losses within the global agri-food industry. There is a shortfall in the drugs that are effective against both the adult and juvenile life stages within the mammalian host, such that new drug targets are needed. Over the last decade the stem cells of parasitic flatworms have emerged as reservoirs of putative novel targets due to their role in development and homeostasis, including at host-parasite interfaces. Here, we investigate and characterise the proliferating cells that underpin development in F. hepatica . We provide evidence that these cells are capable of self-renewal, differentiation, and are sensitive to ionising radiation - all attributes of neoblasts in other flatworms. Changes in cell proliferation were also noted during the early stages of in vitro juvenile growth/development (around four to seven days post excystment), which coincided with a marked reduction in the nuclear area of proliferating cells. Furthermore, we generated transcriptomes from worms following irradiation-based ablation of neoblasts, identifying 124 significantly downregulated transcripts, including known stem cell markers such as fgfrA and plk1 . Sixty-eight of these had homologues associated with neoblast-like cells in Schistosoma mansoni . Finally, RNA interference mediated knockdown of histone h2b (a marker of proliferating cells), ablated neoblast-like cells and impaired worm development in vitro . In summary, this work demonstrates that the proliferating cells of F. hepatica are equivalent to neoblasts of other flatworm species and demonstrate that they may serve as attractive targets for novel anthelmintics. Author Summary Liver fluke are parasitic worms that infect both livestock and humans worldwide, threatening food security and human health. Treatments against this disease-causing parasite are limited, and growing resistance to drugs is undermining the effectiveness of control strategies. Since drugs represent the only viable control option, it is crucial that new drugs are discovered through the identification and validation of new drug targets. Stem cells play important roles in the normal growth and repair processes of many organisms, but when these cells become dysregulated through mutation, they can drive the development of cancers. Stem cells of liver fluke may be attractive novel drug targets as disruption would affect worm survival and/or development within their host. In this research we describe the characteristics of liver fluke stem cells, such as their sensitivity to radiation and their ability to develop into new cell types (key stem cell features). We used radiation in combination with RNA sequencing to identify genes associated with the liver fluke stem cells. Finally, we used reverse genetics to reduce the expression of a gene associated with stem cells, which led to the loss of stem cells and reduced worm growth/development. These data provide evidence to support the exploitation of stem cells as a source of novel drug targets for liver fluke control.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

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