Project description:Colorectal cancer (CRC) is among the most preventable cancers when precancerous lesions are detected at an early stage. Current screening methods for CRC require bowel prep or stool-based testing that are inconvenient, resulting in low compliance. Stool based tests have limited sensitivity for the detection of precancerous lesions.
The CMx platform has been showed to be able to the detection of Circulating Tumor Cells (CTCs) in high sensitivity and specificity. In published studies, circulating Tumor Cells (CTCs) are captured and quantified in advanced-stages of colorectal cancer. In order to detect early and pre-cancer circulating tumor cells, we have developed an Automated Liquid Biopsy Platform that improves the detection of CTCs in early cancer stages. Therefore, this study goals are: 1) to establish a standard detection process utilizing the Automated Liquid Biopsy Platform. 2) Parallel comparison of laboratory manual operation and Automated Liquid Biopsy Platform. 3) Verify the feasibility of use of an Automated Liquid Biopsy Platform in the clinical setting.
Project description:Induced pluripotent stem cells (iPSCs) have become an essential tool for both modeling how causal genetic variants impact cellular function in disease, as well as being an emerging source of tissue for transplantation medicine. Unfortunately the preparation of somatic cells, their reprogramming and the subsequent verification of iPSC pluripotency are laborious, manual processes that limit the scale and level of reproducibility of this technology. Here we describe a modular, robotic platform for iPSC reprogramming that enables automated, high-throughput conversion of skin biopsies into iPSCs and differentiated cells with minimal manual intervention. Using this platform, we demonstrate that automated reprogramming and the pooled selection of pluripotent cells results in high quality, stable, iPSCs. These lines display less line-to-line variation than either manually produced lines or lines produced through automation followed by single colony-subcloning. The robotic platform we describe will enable the application of iPSCs to population-scale biomedical problems including the study of complex genetic diseases and the development of personalized medicines.
Project description:Analysis of human Caucasian colon adenocarcinoma cells (CaCo-2) using a novel selective comprehensive online nanoLCxCZE-MS platform to increase the number of detected proteoforms. The dataset also contains 1D nanoLC-MS and 1D CZE-MS reference measurements.
Project description:We developed a novel high-throughput and automated platform for MHC (major histocompatibility complex) peptides purification using AssayMAP with enhanced speed, sensitivity and reproducibility relative to prior studies.
Project description:Induced pluripotent stem cells (iPSCs) have become an essential tool for both modeling how causal genetic variants impact cellular function in disease, as well as being an emerging source of tissue for transplantation medicine. Unfortunately the preparation of somatic cells, their reprogramming and the subsequent verification of iPSC pluripotency are laborious, manual processes that limit the scale and level of reproducibility of this technology. Here we describe a modular, robotic platform for iPSC reprogramming that enables automated, high-throughput conversion of skin biopsies into iPSCs and differentiated cells with minimal manual intervention. Using this platform, we demonstrate that automated reprogramming and the pooled selection of pluripotent cells results in high quality, stable, iPSCs. These lines display less line-to-line variation than either manually produced lines or lines produced through automation followed by single colony-subcloning. The robotic platform we describe will enable the application of iPSCs to population-scale biomedical problems including the study of complex genetic diseases and the development of personalized medicines. Two independent human fibroblast lines were reprogrammed, using modified mRNA, into induced pluripotent stem cells (iPSCs). The genomic stability of several cell lines was evaluated using SNP arrays. Three iPSCs originating from one fibroblast line were tested at passages 8 and 20, with two of these derived as picked (clonal) lines and the third being a pooled population. Five iPSCs originating from a second fibroblast line were tested at passages 8 and 20, with three of these derives derived as picked (clonal) lines and two derived as pooled populations. The iPSCs were compared against the original parental fibroblasts.
Project description:The development of streamlined and high-throughput sample processing workflows is important for capitalizing on emerging advances and innovations in mass spectrometry-based applications. While the adaptation of new technologies and improved methodologies is fast paced, automation of upstream sample processing often lags. Here we have developed and implemented a semi-automated paramagnetic bead-based platform for isobaric tag sample preparation. We benchmarked the robot-assisted platform by comparing the protein abundance profiles of six common parental laboratory yeast strains in triplicate TMTpro16-plex experiments against an identical set of experiments in which the samples were manually processed. Both sets of experiments quantified similar numbers of proteins and peptides with good reproducibility. Using these data, we constructed an interactive website to explore the proteome profiles of six yeast strains. We also provide the community with open-source templates for automating routine proteomics workflows on an opentrons OT-2 liquid handler. The robot-assisted platform offers a versatile and affordable option for reproducible sample processing for a wide range of protein profiling applications.
Project description:Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and Data Independent Acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 of intraand inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.
Project description:Organ-on-a-chip systems combine microfluidics, cell biology, and tissue engineering to culture 3D organ-specific in vitro models that recapitulate the biology and physiology of their in vivo counterparts. Here, we have developed a multiplex platform that automates the culture of individual organoids in isolated microenvironments at user-defined media flow rates. Programmable workflows allow the use of multiple reagent reservoirs that may be applied to direct differentiation, study temporal variables, and grow cultures long term. Novel techniques in polydimethylsiloxane (PDMS) chip fabrication are described here that enable features on the upper and lower planes of a single PDMS substrate. RNA sequencing (RNA-seq) analysis of automated cerebral cortex organoid cultures shows benefits in reducing glycolytic and endoplasmic reticulum stress compared to conventional in vitro cell cultures.
Project description:We introduced a single-cell proteome microfluidic platform, integrating cell capture, lysis, protein reduction, alkylation and online digestion. The online enzymolysis facilitated the fast, efficient and all-in-one proteomic sample preparation, providing wide dynamic range and enhanced coverage of proteins.