Biology subjects

Chuang, S.-T.

Publications and source records attributed to Chuang, S.-T..

4 recordsLinked to original sources

bioRxiv2026

Effect of Immunosuppressive Drugs on Glucose-Stimulated Insulin Secretion: Concentration-Response Studies in Dynamic Perifusion Assays

Immunosuppressive drugs, which are required to maintain graft function in transplant recipients, are associated with many unavoidable side effects including posttransplant diabetes mellitus (PTDM) that involves both peripheral insulin resistance and impairment of insulin secretion. To characterize in detail the concentration-dependency of the effect of well-known immunosuppressive drugs on glucose-stimulated insulin secretion (GSIS), we performed dynamic perifusion studies with human pancreatic islets. The effect on the time-profile of GSIS has been assessed over a wide concentration range for several clinically relevant immunomodulatory therapies, including small-molecule drugs (cyclosporine, sirolimus, tacrolimus, prednisolone acetate, and loteprednol etabonate) and biologics (abatacept and anti-CD40L), plus a prospective {beta}-cell proliferation-inducing agent (harmine). While biologics showed no significant detrimental effects after one-day treatment even at relatively high concentrations (5 {micro}M), all small-molecule drugs inhibited insulin secretion in a concentration-dependent manner, although glucocorticoids showed a distinct response pattern. Calcineurin and mTOR inhibitors preserved GSIS within their therapeutic ranges but progressively distorted its time-profile at higher concentrations and completely suppressed secretion at the highest levels. Cyclosporine exhibited the least, only about 35-fold, separation between its therapeutic target (Ctarg) and half-maximal GSIS inhibitory (IC50) concentrations. Glucocorticoids did not alter the shape of the time-profile but inhibited overall insulin secretion even at therapeutic levels. Their inhibitory effect only increased slowly with concentration and did not follow a classic sigmoid pattern that has unity Hill slope. These findings establish quantitative benchmarks for immunosuppressant-induced {beta}-cell toxicity and provide a framework for optimizing immunosuppressive regimens to reduce the risk of PTDM.

pharmacology and toxicology↗

bioRxiv2025

Assessing the Rate-Dependence of the First Phase of Glucose-Stimulated Insulin Secretion: Dynamic Perifusion Studies with Isolated Human Pancreatic Islets

Insulin released in response to a stepwise increase in glucose (square wave) is biphasic with a transient first-phase peak of 5-10 min and a more sustained second phase. While it is usually assumed that the first phase is rate- and the second is concentration-dependent, there are no detailed investigations into the rate-sensitivity of the first phase. We performed dynamic perifusion studies with isolated human pancreatic islets in a system that allowed fully customizable glucose ramps and established the corresponding insulin secretion time-profiles with high (once-a-minute) time-resolution. We considered the first-phase release to be the excess amount of insulin in addition to what would be expected from the glucose concentration-dependent second-phase release and examined its dependence on the glucose gradient (rate of increase). The average first-phase insulin release rate calculated this way increased with the gradient and could be fitted well with a Hill-type sigmoid function having a half-maximal value around 1.25 mM/min (nHill=1.8, r2=0.96). This agrees well with our previously introduced glucose-insulin control system built on a general framework of a sigmoid proportional-integral-derivative ({sigma}PID) controller, a generalized PID controller more suitable for biological systems than classic linear ones as biological responses are always limited between zero and a possible maximum. Experimental results obtained here were used to slightly readjust the parameters of this local glucose concentration-based computational model resulting in predictions in good agreement with measured first- and second-phase insulin secretions (r2>0.90). Thus, glucose-stimulated insulin secretion (GSIS) of perifused human islets can be described well as the sum of a rate-sensitive first phase, which is a sigmoid function of the glucose gradient with half-maximal value around 1.25 mM/min, and a concentration-sensitive second phase, which is a sigmoid function of the glucose concentration with half-maximal value around 8 mM.

physiology↗

bioRxiv2024

A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort

BackgroundBiomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk MethodsTwelve candidate biomarkers, which were identified in the augmented data and selected based on their fold-change relative to healthy controls and cross-reference to proteomics data previously obtained in the expansive TEDDY and DAISY cohorts, were measured in the original samples by ELISA ResultsAll 12 biomarkers had established connections with lipid/lipoprotein metabolism, immune function, inflammation, and diabetes, but only 7 were found to be markedly changed in the high-risk subjects compared to the healthy controls: ApoC1 and PON1 were reduced while CETP, CD36, FGFR1, IGHM, PCSK9, SOD1, and VCAM1 were elevated ConclusionsResults further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.

biochemistry↗

bioRxiv2022

Methylene Blue Is a Nonspecific Protein-Protein Interaction Inhibitor with Potential for Repurposing as an Antiviral for COVID-19

We have previously identified methylene blue, a tricyclic phenothiazine dye approved for clinical use for the treatment of methemoglobinemia and used for other medical applications, as a small-molecule inhibitor of the protein-protein interaction (PPI) between the spike protein of the SARS-CoV-2 coronavirus and ACE2, the first critical step of the attachment and entry of this coronavirus responsible for the COVID-19 pandemic. Here, we show that methylene blue concentration-dependently inhibits this PPI for the spike protein of the original strain as well as for those of variants of concerns such as the D614G mutant and delta (B.1.617.2) with IC50 in the low micromolar range (1-5 M). Methylene blue also showed promiscuous activity and inhibited several other PPIs of viral proteins (e.g., HCoV-NL63 - ACE2, hepatitis C virus E - CD81) as well as others (e.g., IL-2 - IL-2R) with similar potency. This non-specificity notwithstanding, methylene blue inhibited the entry of pseudoviruses bearing the spike protein of SARS-CoV-2 in hACE2-expressing host cells both for the original strain and the delta variant. It also blocked SARS-CoV-2 (B.1.5) virus replication in Vero E6 cells with an IC50 in the low micromolar range (1.7 M) when assayed using quantitative PCR of the viral RNA. Thus, while it seems to be a promiscuous PPI inhibitor with low micromolar activity and it has a relatively narrow therapeutic index, methylene blue inhibits entry and replication of SARS-CoV-2, including several of its mutant variants, and has potential as a possible inexpensive, broad-spectrum, orally bioactive small-molecule antiviral for the prevention and treatment of COVID-19.

pharmacology and toxicology↗