Development of a platform for activatable fluorescent substrates of glucose transporters (GLUTs).

We have developed a platform for activatable fluorescent substrates of glucose transporters (GLUTs). We firstly conjugated fluorescein to glucosamine via an amide or methylene linker at the C-2 position of d-glucosamine, but the resulting compounds, FLG1 and FLG2, showed no uptake into MIN6 cells. So, we changed the fluorophore moiety to a fluorescein analogue, 2-Me TokyoGreen, which is less negatively charged. TokyoGreen-conjugated glucosamines TGG1 and TGG2 were successfully taken up into cells via GLUT. We further derivatized TGG1 and TGG2, and among the synthesized compounds, 2-Me-4-OMe TGG showed weak fluorescence under the acidic conditions of the extracellular environment inside tumors and in gastric cancers, and strong fluorescence at the intracellular physiological pH, under the control of a photoinduced electron transfer (PeT) process. This fluorogenic platform should be useful for developing a range of activatable fluorescent substrates targeting GLUTs, as well as derivatives that would be fluorescently activated by various intracellular enzymes, such as esterases, ß-galactosidase and bioreductases.

A Collaborative Study on the Classification of Silicone Oil Droplets and Protein Particles Using Flow Imaging Method.

In this study, we conducted a collaborative study on the classification between silicone oil droplets and protein particles detected using the flow imaging (FI) method toward proposing a standardized classifier/model. We compared four approaches, including a classification filter composed of particle characteristic parameters, principal component analysis, decision tree, and convolutional neural network in the performance of the developed classifier/model. Finally, the points to be considered were summarized for measurement using the FI method, and for establishing the classifier/model using machine learning to differentiate silicone oil droplets and protein particles.

A transcription factor response element for gene expression during circadian night.

Mammalian circadian clocks consist of complex integrated feedback loops that cannot be elucidated without comprehensive measurement of system dynamics and determination of network structures. To dissect such a complicated system, we took a systems-biological approach based on genomic, molecular and cell biological techniques. We profiled suprachiasmatic nuclei and liver genome-wide expression patterns under light/dark cycles and constant darkness. We determined transcription start sites of human orthologues for newly identified cycling genes and then performed bioinformatical searches for relationships between time-of-day specific expression and transcription factor response elements around transcription start sites. Here we demonstrate the role of the Rev-ErbA/ROR response element in gene expression during circadian night, which is in phase with Bmal1 and in antiphase to Per2 oscillations. This role was verified using an in vitro validation system, in which cultured fibroblasts transiently transfected with clock-controlled reporter vectors exhibited robust circadian bioluminescence.