Biomedical subjects

Tao Ju

Publications and source records attributed to Tao Ju.

6 recordsLinked to original sources

PubMed2026

Spatial Mapping of the Precancer-to-Cancer Transition in Breast and Prostate.

UNLABELLED: Breast and prostate cancers are both hormone-driven adenocarcinomas that undergo analogous invasion programs. Using lightsheet microscopy on intact tumors, we identified transitional junctions between precancerous and invasive regions. We then developed a multimodal serial-section workflow integrating volumetric reconstruction with spatial transcriptomics. Analysis of 319 spatial assays from 51 cases revealed gene expression features and novel structural insights defining the shift from precancer to invasive disease. In breast cancer, loss of MGP and PLAT was associated with invasive transition and promoted tumorigenesis in functional assays. In prostate cancer, GDF15, ALDH1A3, ANPEP, and FASN were upregulated along invasive progression, and their knockdown in PC-3 cells suppressed proliferation and migration. Enrichment of tumor-associated macrophages (SPP1+ and MS4A6A+) along non-triple-negative breast cancer breast cancer transitions highlights immune involvement as a potential driver of invasiveness. SIGNIFICANCE: Our method of defining precise spatial locations of invasive transition allows for the direct interrogation of transition drivers, presenting new therapeutic targets for the two most prevalent cancers and providing a framework for studying spatially defined mechanisms of tumor progression. See related commentary by Jing and Li, p. 1720.

Humans↗

PubMed2007

Identification of secondary structure elements in intermediate-resolution density maps.

An increasing number of structural studies of large macromolecular complexes, both in X-ray crystallography and cryo-electron microscopy, have resulted in intermediate-resolution (5-10 A) density maps. Despite being limited in resolution, significant structural and functional information may be extractable from these maps. To aid in the analysis and annotation of these complexes, we have developed SSEhunter, a tool for the quantitative detection of alpha helices and beta sheets. Based on density skeletonization, local geometry calculations, and a template-based search, SSEhunter has been tested and validated on a variety of simulated and authentic subnanometer-resolution density maps. The result is a robust, user-friendly approach that allows users to quickly visualize, assess, and annotate intermediate-resolution density maps. Beyond secondary structure element identification, the skeletonization algorithm in SSEhunter provides secondary structure topology, which is potentially useful in leading to structural models of individual molecular components directly from the density.

Computational Biology↗

PubMed2006

Probing 3'-ssDNA loop formation in E. coli RecBCD/RecBC-DNA complexes using non-natural DNA: a model for "Chi" recognition complexes.

The equilibrium binding of Escherichia coli RecBC and RecBCD helicases to duplex DNA ends containing varying lengths of polyethylene glycol (PEG) spacers within pre-formed 3'-single-stranded (ss) DNA ((dT)n) tails was studied. These studies were designed to test a previous proposal that the 3'-(dT)n tail can be looped out upon binding RecBC and RecBCD for 3'-ssDNA tails with n>or=6 nucleotides. Equilibrium binding of protein to unlabeled DNA substrates with ends containing PEG-substituted 3'-ssDNA tails was examined by competition with a Cy3-labeled reference DNA which undergoes a Cy3 fluorescence enhancement upon protein binding. We find that the binding affinities of both RecBC and RecBCD for a DNA end are unaffected upon substituting PEG for the ssDNA between the sixth and the final two nucleotides of the 3'-(dT)n tail. However, placing PEG at the end of the 3'-(dT)n tail increases the binding affinities to their maximum values (i.e. the same as binding constants for RecBC or RecBCD to a DNA end with only a 3'-(dT)6 tail). Equilibrium binding studies of a RecBC mutant containing a nuclease domain deletion, RecB(Deltanuc)C, suggest that looping of the 3'-tail (when n>or=6 nucleotides) occurs even in the absence of the RecB nuclease domain, although the nuclease domain stabilizes such loop formation. Computer modeling of the RecBCD-DNA complexes suggests that the loop in the 3'-ssDNA tail may form at the RecB/RecC interface. Based on these results we suggest a model for how a loop in the 3'-ssDNA tail might form upon encounter of a "Chi" recognition sequence during unwinding of DNA by the RecBCD helicase.

DNA, Single-Stranded↗

PubMed2006

3D volume reconstruction of a mouse brain from histological sections using warp filtering.

Sectioning tissues for optical microscopy often introduces upon the resulting sections distortions that make 3D reconstruction difficult. Here we present an automatic method for producing a smooth 3D volume from distorted 2D sections in the absence of any undistorted references. The method is based on pairwise elastic image warps between successive tissue sections, which can be computed by 2D image registration. Using a Gaussian filter, an average warp is computed for each section from the pairwise warps in a group of its neighboring sections. The average warps deform each section to match its neighboring sections, thus creating a smooth volume where corresponding features on successive sections lie close to each other. The proposed method can be used with any existing 2D image registration method for 3D reconstruction. In particular, we present a novel image warping algorithm based on dynamic programming that extends Dynamic Time Warping in 1D speech recognition to compute pairwise warps between high-resolution 2D images. The warping algorithm efficiently computes a restricted class of 2D local deformations that are characteristic between successive tissue sections. Finally, a validation framework is proposed and applied to evaluate the quality of reconstruction using both real sections and a synthetic volume.

Algorithms↗

PubMed2005

A digital atlas to characterize the mouse brain transcriptome.

Massive amounts of data are being generated in an effort to represent for the brain the expression of all genes at cellular resolution. Critical to exploiting this effort is the ability to place these data into a common frame of reference. Here we have developed a computational method for annotating gene expression patterns in the context of a digital atlas to facilitate custom user queries and comparisons of this type of data. This procedure has been applied to 200 genes in the postnatal mouse brain. As an illustration of utility, we identify candidate genes that may be related to Parkinson disease by using the expression of a dopamine transporter in the substantia nigra as a search query pattern. In addition, we discover that transcription factor Rorb is down-regulated in the barrelless mutant relative to control mice by quantitative comparison of expression patterns in layer IV somatosensory cortex. The semi-automated annotation method developed here is applicable to a broad spectrum of complex tissues and data modalities.

Anatomy, Artistic↗

PubMed2005

Hybrid segmentation framework for tissue images containing gene expression data.

Associating specific gene activity with functional locations in the brain results in a greater understanding of the role of the gene. To perform such an association for the over 20,000 genes in the mammalian genome, reliable automated methods that characterize the distribution of gene expression in relation to a standard anatomical model are required. In this work, we propose a new automatic method that results in the segmentation of gene expression images into distinct anatomical regions in which the expression can be quantified and compared with other images. Our method utilizes shape models from training images, texture differentiation at region boundaries, and features of anatomical landmarks, to deform a subdivision mesh-based atlas to fit gene expression images. The subdivision mesh provides a common coordinate system for internal brain data through which gene expression patterns can be compared across images. The automated large-scale annotation will help scientists interpret gene expression patterns at cellular resolution more efficiently.

Algorithms↗