Biology subjects

Seki, T.

Publications and source records attributed to Seki, T..

22 records · Page 2Linked to original sources

bioRxiv2019

Water uptake analysis in Japanese mustard spinach: A numerical approach

We constructed an experimental system consisting of a syringe pump and water level feedback control to reveal the dynamics of water uptake in Japanese mustard spinach. We also analyzed differences in time-lapse images to quantify turgor movement in these plants. By performing harmonic analysis using the discrete Fourier transform on these dynamics, the frequency domain was obtained. These methods enabled the detailed visualization of plant dynamics. HighlightIn this study, the water uptake dynamics of Japanese mustard spinaches were measured in detail and image difference analysis was performed to investigate the plants turgor movements. Frequency domain analysis of the plant dynamics was carried out using a discrete Fourier transform.

plant biology↗

bioRxiv2019

Transcriptome stability profiling identifies novel and functional MIRNA targets in melanoma cells

RNA half-life is closely related to its cellular physiological function, so stability determinants may have regulatory functions. Micro(mi)RNAs have primarily been studied with respect to post-transcriptional mRNA regulation and target degradation. Here we study the impact of the tumor suppressive melanoma miRNA miR-211 on transcriptome stability and phenotype in the non-pigmented melanoma cell line, A375. Using 5-bromouridine IP chase (BRIC)-seq, transcriptome-wide RNA stability profiles revealed highly regulated genes and pathways important in this melanoma cell line. By combining BRIC-seq, RNA-seq and in silico predictions, we identified both existing and novel direct miR-211 targets. We validated DUSP3 as one such novel miR-211 target, which itself sustains colony formation and invasion in A375 cells via MAPK/PI3K signaling. miRNAs have the capacity to control RNA turnover as a gene expression mechanism, and RNA stability profiling is an excellent tool for interrogating functionally relevant gene regulatory pathways and miRNA targets when combined with other high-throughput and in silico approaches.

cancer biology↗

bioRxiv2019

Distinguishing Closely Related Pancreatic Cancer Subtypes In Vivo by 13C Glucose MRI without Hyperpolarization

Metabolic differences between patients and within the tumor itself can be an important determinant in cancer treatment outcome. However, methods for determining these differences non-invasively in vivo have been lacking. Using pancreatic ductal adenocarcinoma as a model, we demonstrate that tumor xenografts with a similar genetic background can be distinguished by their differing rates of metabolism, as detected by imaging of uniformly 13C labeled glucose tracers using a newly developed technique using tensor decomposition for noise suppression to bring the signal to a detectable level without hyperpolarization of the tracer. Using this method, cancer subtypes that appeared to exhibit similar metabolic profiles by other techniques that measured steady state metabolism can be distinguished.

cancer biology↗

bioRxiv2018

PET by MRI: Glucose Imaging by 13C-MRS without Dynamic Nuclear Polarization by Noise Suppression through Tensor Decomposition Rank Reduction

Metabolic reprogramming is one of the defining features of cancer and abnormal metabolism is associated with many other pathologies. Molecular imaging techniques capable of detecting such changes have become essential for cancer diagnosis, treatment planning, and surveillance. In particular, 18F-FDG (fluorodeoxyglucose) PET has emerged as an essential imaging modality for cancer because of its unique ability to detect a disturbed molecular pathway through measurements of glucose uptake. However, FDG-PET has limitations that restrict its usefulness in certain situations and the information gained is limited to glucose uptake only. 13C magnetic resonance spectroscopy theoretically has certain advantages over FDG-PET, but its inherent low sensitivity has restricted its use mostly to single voxel measurements. We show here a new method of imaging glucose metabolism in vivo that relies on a simple, but robust and efficient, post-processing procedure by the higher dimensional analog of singular value decomposition, tensor decomposition. Using this procedure, we achieve an order of magnitude increase in signal to noise in both dDNP and non-hyperpolarized non-localized experiments without sacrificing accuracy. In CSI experiments an approximately 30-fold increase was observed, enough that the glucose to lactate conversion indicative of the Warburg effect can be imaged without hyper-polarization with a time resolution of 12 s and an overall spatial resolution that compares favorably to 18F-FDG PET.

cancer biology↗