Characterization of the transport activity of SGLT2/MAP17, the renal low-affinity Na<sup>+</sup>-glucose cotransporter
Bibliographic record
Abstract
The cotransporter SGLT2 is responsible for 90% of renal glucose reabsorption, and we recently showed that MAP17 appears to work as a required β-subunit. We report in the present study a detailed functional characterization of human SGLT2 in coexpression with human MAP17 in Xenopus laevis oocytes. Addition of external glucose generates a large inward current in the presence of Na, confirming an electrogenic transport mechanism. At a membrane potential of −50 mV, SGLT2 affinity constants for glucose and Na are 3.4 ± 0.4 and 18 ± 6 mM, respectively. The change in the reversal potential of the cotransport current as a function of external glucose concentration clearly confirms a 1:1 Na-to-glucose transport stoichiometry. SGLT2 is selective for glucose and α-methylglucose but also transports, to a lesser extent, galactose and 3- O-methylglucose. SGLT2 can be inhibited in a competitive manner by phlorizin ( K i = 31 ± 4 nM) and by dapagliflozin ( K i = 0.75 ± 0.3 nM). Similarly to SGLT1, SGLT2 can be activated by Na, Li, and protons. Pre-steady-state currents for SGLT2 do exist but are small in amplitude and relatively fast (a time constant of ~2 ms). The leak current defined as the phlorizin-sensitive current in the absence of substrate was extremely small in the case of SGLT2. In summary, in comparison with SGLT1, SGLT2 has a lower affinity for glucose, a transport stoichiometry of 1:1, very small pre-steady-state and leak currents, a 10-fold higher affinity for phlorizin, and an affinity for dapagliflozin in the subnanomolar range.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".