Evaluation method of ordinary flatbed scanners for quantitative density analysis

α-Amanitin Restrains Cancer Relapse from Drug-Tolerant Cell Subpopulations via TAF15

Cancer relapse occurs with substantial frequency even after treatment with curative intent. Here we studied drug-tolerant colonies (DTCs), which are subpopulations of cancer cells that survive in the presence of drugs. Proteomic characterization of DTCs identified stemness- and epithelial-dominant subpopulations, but functional screening suggested that DTC formation was regulated at the transcriptional level independent from protein expression patterns. We consistently found that α-amanitin, an RNA polymerase II (RNAPII) inhibitor, effectively inhibited DTCs by suppressing TAF15 expression, which binds to RNA to modulate transcription and RNA processing. Sequential administration of α-amanitin and cisplatin extended overall survival in a cancer-relapse mouse model, namely peritonitis carcinomatosa. Therefore, post-treatment cancer relapse may occur through non-distinct subpopulations and may be effectively prevented by α-amanitin to disrupt transcriptional machinery, including TAF15.

Biomedical imaging and sensing using flatbed scanners

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600-700 cm(2)) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings.

Reverse-phase protein lysate microarray (RPA) for the experimental validation of quantitative protein network models

Theoretical models describing complex biological phenomena have been accumulating. However, most of these models have been created with hypothetical parameter determination without seeing actual cell reactions. The parameter determination requires high-dimensional data monitoring, particularly at the protein level. It has been a difficult task to develop the standard model system because of the lack of an appropriate validation technique. Reverse-phase protein lysate microarray (RPA) is one of the most potent technologies for high-dimensional proteomic monitoring. Therefore, proteomic monitoring by RPA may contribute substantially to develop theoretical protein network models based on experimental validation.

Reverse-phase protein lysate microarrays for cell signaling analysis

'Reverse-phase' protein lysate microarray (RPA) assays use micro-scale, cell lysate dot blots that are printed to a substrate, followed by quantitative immunochemical protein detection, known to be particularly effective across many samples. Large-scale sample collection is a labor-intensive and time-consuming process; the information yielded from RPA assays, however, provides unique opportunities to experimentally interpret theoretical protein networks quantitatively. When specific antibodies are used, RPA can generate 1,000 times more data points using 10,000 times less sample volume than an ordinary western blot, enabling researchers to monitor quantitative proteomic responses for various time-scale and input-dose gradients simultaneously. Hence, the RPA system can be an excellent method for experimental validation of theoretical protein network models. Besides the initial screening of primary antibodies, collection of several hundreds of sample lysates from 1- to 8-h periods can be completed in approximately 10 d; subsequent RPA printing and signal detection steps require an additional 2-3 d.

Quantitative protein network monitoring in response to DNA damage

Conventional molecular biology techniques have identified a large number of cell signaling pathways; however, the importance of these pathways often varies, depending on factors such as treatment type, dose, time after treatment, and cell type. Here, we describe a technique using "reverse-phase" protein lysate microarrays (RPAs) to acquire multiple dimensions of information on protein dynamics in response to DNA damage. Whole-cell lysates from three cellular stress treatments (IR, UV, and ADR) were collected at four doses per treatment, and each, in turn, at 10 time points, resulting in a single-slide RPA consisting of 10,240 features, including replicates. The dynamic molecular profile of 18 unique protein species was compared to phenotypic fate by FACS analysis for corresponding stress conditions. Our initial quantitative results in this new platform confirmed that (1) there is clear stress dose-response effect in p53 protein and (2) a comparison of the rates of increase of p21 and Cyclin D3/p53-Ser15 in response to DNA damage may be associated with the pattern of DNA content. This method, offering a quantitative time-course monitoring of protein expression levels, can provide an experimental reference for developing mathematical models of cell signaling dynamics. Although the present study focuses on the DNA damage-repair pathway, the technique is generally useful to the study of protein signaling.

Evaluation of two commercial systems for automated processing, reading, and interpretation of Lyme borreliosis Western blots

The diagnosis of Lyme borreliosis (LB) is commonly made by serologic testing with Western blot (WB) analysis serving as an important supplemental assay. Although specific, the interpretation of WBs for diagnosis of LB (i.e., Lyme WBs) is subjective, with considerable variability in results. In addition, the processing, reading, and interpretation of Lyme WBs are laborious and time-consuming procedures. With the need for rapid processing and more objective interpretation of Lyme WBs, we evaluated the performances of two automated interpretive systems, TrinBlot/BLOTrix (Trinity Biotech, Carlsbad, CA) and BeeBlot/ViraScan (Viramed Biotech AG, Munich, Germany), using 518 serum specimens submitted to our laboratory for Lyme WB analysis. The results of routine testing with visual interpretation were compared to those obtained by BLOTrix analysis of MarBlot immunoglobulin M (IgM) and IgG and by ViraScan analysis of ViraBlot and ViraStripe IgM and IgG assays. BLOTrix analysis demonstrated an agreement of 84.7% for IgM and 87.3% for IgG compared to visual reading and interpretation. ViraScan analysis of the ViraBlot assays demonstrated agreements of 85.7% for IgM and 94.2% for IgG, while ViraScan analysis of the ViraStripe IgM and IgG assays showed agreements of 87.1 and 93.1%, respectively. Testing by the automated systems yielded an average time savings of 64 min/run compared to processing, reading, and interpretation by our current procedure. Our findings demonstrated that automated processing and interpretive systems yield results comparable to those of visual interpretation, while reducing the subjectivity and time required for Lyme WB analysis.

Quantitative assessment of the p53-Mdm2 feedback loop using protein lysate microarrays

Mathematical simulations of the p53-Mdm2 feedback loop suggest that both proteins will exhibit impulsive expression characteristics in response to high cellular stress levels. However, little quantitative experimental evaluation has been done, particularly of the phosphorylated forms. To evaluate the mathematical models experimentally, we used lysate microarrays from an isogenic pair of gamma-ray-irradiated cell lysates from HCT116 (p53(+/+) and p53(-/-)). Both p53 and Mdm2 proteins showed expected pulses in the wild type, whereas no pulses were seen in the knockout. Based on experimental observations, we determined model parameters and generated an in silico "knockout," reflecting the experimental data, including phosphorylated proteins.

Profiling cancer stem cells using protein array technology

Since cancer cells and somatic stem cells share the biological characteristics of self-renewal and proliferation, it has been suggested that the principles of stem cell biology can be applied to improve our understanding of cancer biology. Recent studies have shown that the majority of cancers appear to originate from a small subset of cells that have the ability of self-renewal and to proliferate, namely 'cancer stem cells'. The isolation of cancer stem cells has been demonstrated using cell surface markers in haematopoietic and non-haematopoietic malignancies. Advances in protein array technologies have enabled the use of minuscule amounts of biological materials to profile these cells at the molecular level. Using a combination of protein arrays and cancer stem cell isolation techniques, a higher resolution molecular profiling can be performed, which might improve therapies targeting the cancer stem cells.