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Characterization of a Novel HEK293 Cell Line (HEK293‐ENT1KO) to Assess the Role of Equilibrative Nucleoside Transporter Subtype‐2

2021· article· en· W3172531057 on OpenAlexaff
Nayiar Shahid, Christopher Chromwell, Basil P. Hubbard, James R. Hammond

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHEK 293 cellsNucleosideChemistryTransporterBiologyCell cultureGeneticsBiochemistryGene

Abstract

fetched live from OpenAlex

Background Equilibrative nucleoside transporters (ENT) mediate the transmembrane flux of endogenous nucleosides and nucleoside/nucleobase‐analog drugs that are used to treat breast, endometrial and uterine cancers (gemcitabine), lymphoma (cytarabine), as well as viral infections in pregnant women (ribavirin, abacavir). Of the two major ENT subtypes (ENT1, ENT2), ENT1 has been studied the most due to its relative predominance in most tissues, and the availability of the highly selective ENT1 inhibitor, nitrobenzylthioinosine (NBMPR). In contrast, there is much less information on how drugs interact with ENT2 or factors that affect ENT2 expression. This is mainly due to the fact that ENT2 is expressed at relatively lower levels concomitantly with ENT1, and no selective ENT2 inhibitor is available. Objectives To develop a model where ENT2 can be studied in isolation, we created a novel Human Embryonic Kidney (HEK293) cell mutant that lacks ENT1 (using CRISPR‐Cas9), leaving ENT2 as the only functional ENT in this system. We now report on the characterization of this HEK293‐ENT1KO model in terms of ENT2 expression, functional activity and the affinity of ENT2 for a range of known nucleoside/nucleobase compounds (endogenous and therapeutic analogs) in the absence of ENT1 interference. Potential compensatory changes in other genes associated with nucleoside metabolism were also assessed. Methods Transporter function was assessed through measurement of the initial rates of [ 3 H]2‐chloroadenosine uptake (2.5 ‐ 300 µM). K i values for inhibitors were defined using the IC 50 derived from concentration‐response curve analyses and the K m of [ 3 H]2‐chloroadenosine for ENT2 determined in this model. Data are expressed as mean ± SEM. The presence or absence of ENT1 was determined based on the binding of [ 3 H]NBMPR. Protein levels were assessed by immunoblotting using ENT‐specific antibodies, and changes in gene expression were examined by qPCR. Results HEK293‐ENT1KO cells had a similar level of ENT2 uptake (K m 104.7 µM ± 51.9, V max 1.6 pmol/µl/s ±0.4) as wild‐type (K m 105.3 µM ± 37.2, V max 1.4 pmol/µl/s ± 0.2). Neither [ 3 H]NBMPR binding sites nor ENT1 protein were observed in HEK293‐ENT1KO cells indicating the complete loss of ENT1. The relative expression of the gene encoding ENT1, SLC29A1, was negligible in the ENT1KO cells compared to the WT HEK293. ENT2 endogenously expressed in HEK293‐ENT1KO cells showed the expected affinities for known substrates such as adenine (2300 ± 750 µM), hypoxanthine (340 ± 54 µM), inosine (74.5 ± 29.9 µM), uridine (184.5 ± 33.7 µM), thymidine (42.4 ± 7.9 µM), guanosine (1500 ± 30 µM), gemcitabine (820 ± 79 µM), ribavirin (500 ± 140 µM) and abacavir (170 ± 18 µM). It also had the expected affinities for inhibitors such as NBMPR (2.9 ± 0.3 µM), dipyridamole (0.5 ± 0.1 µM), dilazep (2.6 ± 0.9 µM), and ticagrelor (11 ± 2.4 µM). Conclusion Our data suggest that removing ENT1 from HEK293 cells does not impact the expression, function or affinity of ENT2. This model can be used to advance our knowledge of pathways that regulate ENT2 expression and activity. It will also be a useful model for screening novel ENT2 inhibitors and substrates of potential therapeutic value.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.005

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 head0.244
Teacher spread0.225 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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