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Kuo, Winston

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Kuo

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Kuo, Winston

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Now showing 1 - 5 of 5
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    Alternative Methods for Characterization of Extracellular Vesicles
    (Frontiers Research Foundation, 2012) Balaj, Leonora; Tigges, John; Toxavidis, Vasilis; Ivanov, Alexander R.; Skog, Johan; Momen-Heravi, Fatemeh; Alian, Sara; Ericsson, Maria; Distel, Robert; Kuo, Winston
    Extracellular vesicles (ECVs) are nano-sized vesicles released by all cells in vitro as well as in vivo. Their role has been implicated mainly in cell–cell communication, but also in disease biomarkers and more recently in gene delivery. They represent a snapshot of the cell status at the moment of release and carry bioreactive macromolecules such as nucleic acids, proteins, and lipids. A major limitation in this emerging new field is the availability/awareness of techniques to isolate and properly characterize ECVs. The lack of gold standards makes comparing different studies very difficult and may potentially hinder some ECVs-specific evidence. Characterization of ECVs has also recently seen many advances with the use of Nanoparticle Tracking Analysis, flow cytometry, cryo-electron microscopy instruments, and proteomic technologies. In this review, we discuss the latest developments in translational technologies involving characterization methods including the facts in their support and the challenges they face.
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    Impact of Biofluid Viscosity on Size and Sedimentation Efficiency of the Isolated Microvesicles
    (Frontiers Research Foundation, 2012) Momen-Heravi, Fatemeh; Balaj, Leonora; Alian, Sara; Trachtenberg, Alexander J.; Hochberg, Fred H; Skog, Johan; Kuo, Winston
    Microvesicles are nano-sized lipid vesicles released by all cells in vivo and in vitro. They are released physiologically under normal conditions but their rate of release is higher under pathological conditions such as tumors. Once released they end up in the systemic circulation and have been found and characterized in all biofluids such as plasma, serum, cerebrospinal fluid, breast milk, ascites, and urine. Microvesicles represent the status of the donor cell they are released from and they are currently under intense investigation as a potential source for disease biomarkers. Currently, the “gold standard” for isolating microvesicles is ultracentrifugation, although alternative techniques such as affinity purification have been explored. Viscosity is the resistance of a fluid to a deforming force by either shear or tensile stress. The different chemical and molecular compositions of biofluids have an effect on its viscosity and this could affect movements of the particles inside the fluid. In this manuscript we addressed the issue of whether viscosity has an effect on sedimentation efficiency of microvesicles using ultracentrifugation. We used different biofluids and spiked them with polystyrene beads and assessed their recovery using the Nanoparticle Tracking Analysis. We demonstrate that MVs recovery inversely correlates with viscosity and as a result, sample dilutions should be considered prior to ultracentrifugation when processing any biofluids.
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    MicroSAGE is Highly Representative and Reproducible but Reveals Major Differences in Gene Expression Among Samples Obtained from Similar Tissues
    (BioMed Central, 2003) Blackshaw, Seth; Kuo, Winston; Park, Peter; Tsujikawa, Motokazu; Gunnersen, Jenny M; Scott, Hamish S; Boon, Wee-Ming; Tan, Seong-Seng; Cepko, Constance
    Background: Serial analysis of gene expression using small amounts of starting material (microSAGE) has not yet been conclusively shown to be representative, reproducible or accurate. Results: We show that microSAGE is highly representative, reproducible and accurate, but that pronounced differences in gene expression are seen between tissue samples taken from different individuals. Conclusions: MicroSAGE is a reliable method of comprehensively profiling differences in gene expression among samples, but care should be taken in generalizing results obtained from libraries constructed from tissue obtained from different individuals and/or processed or stored differently.
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    Validation of Oligoarrays for Quantitative Exploration of the Transcriptome
    (BioMed Central, 2008) Nygaard, Vigdis; Holden, Marit; Trimarchi, Jeff; Ohno-Machado, Lucila; Frigessi, Arnoldo; Glad, Ingrid K; Wiel, Mark A van de; Hovig, Eivind; Lyng, Heidi; Liu, Fang; Kuo, Winston; Cepko, Constance
    Background: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS) and serial analysis of gene expression (SAGE). By use of the TransCount method we calculated absolute transcript concentrations from spotted oligoarray intensities, enabling direct comparisons with tag counts obtained with MPSS and SAGE. The tag counts were converted to number of transcripts per cell by assuming that the sum of all transcripts in a single cell was 5·105. Our aim was to investigate whether the less resource demanding and more widespread oligoarray technique could provide data that were correlated to and had the same absolute scale as those obtained with MPSS and SAGE. Results: A number of 1,777 unique transcripts were detected in common for the three technologies and served as the basis for our analyses. The correlations involving the oligoarray data were not weaker than, but, similar to the correlation between the MPSS and SAGE data, both when the entire concentration range was considered and at high concentrations. The data sets were more strongly correlated at high transcript concentrations than at low concentrations. On an absolute scale, the number of transcripts per cell and gene was generally higher based on oligoarrays than on MPSS and SAGE, and ranged from 1.6 to 9,705 for the 1,777 overlapping genes. The MPSS data were on same scale as the SAGE data, ranging from 0.5 to 3,180 (MPSS) and 9 to1,268 (SAGE) transcripts per cell and gene. The sum of all transcripts per cell for these genes was 3.8·105 (oligoarrays), 1.1·105 (MPSS) and 7.6·104 (SAGE), whereas the corresponding sum for all detected transcripts was 1.1·106 (oligoarrays), 2.8·105 (MPSS) and 3.8·105 (SAGE). Conclusion: The oligoarrays and TransCount provide quantitative transcript concentrations that are correlated to MPSS and SAGE data, but, the absolute scale of the measurements differs across the technologies. The discrepancy questions whether the sum of all transcripts within a single cell might be higher than the number of 5·105 suggested in the literature and used to convert tag counts to transcripts per cell. If so, this may explain the apparent higher transcript detection efficiency of the oligoarrays, and has to be clarified before absolute transcript concentrations can be interchanged across the technologies. The ability to obtain transcript concentrations from oligoarrays opens up the possibility of efficient generation of universal transcript databases with low resource demands.
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    Peripheral Arterial Occlusive Disease: Global Gene Expression Analyses Suggest a Major Role for Immune and Inflammatory Responses
    (BioMed Central, 2008) Crawford, Keith; Jin, Jason Gang; Du, Yanzhi; Abzhanov, Arkhat; Zhou, Jianqin; Zhang, Ji; Jiang, Mier; Ohno-Machado, Lucila; Fu, Shijun; Zhao, Haiguang; Shi, Jiantao; Kuo, Winston
    Background Peripheral arterial disease (PAD), a major manifestation of atherosclerosis, is associated with significant cardiovascular morbidity, limb loss and death. However, mechanisms underlying the genesis and progression of the disease are far from clear. Genome-wide gene expression profiling of clinical samples may represent an effective approach to gain relevant information. Results After histological classification, a total of 30 femoral artery samples, including 11 intermediate lesions, 14 advanced lesions and 5 normal femoral arteries, were profiled using Affymetrix microarray platform. Following real-time RT-PCR validation, different algorithms of gene selection and clustering were applied to identify differentially expressed genes. Under a stringent cutoff, i.e., a false discovery rate (FDR) <0.5%, we found 366 genes were differentially regulated in intermediate lesions and 447 in advanced lesions. Of these, 116 genes were overlapped between intermediate and advanced lesions, including 68 up-regulated genes and 48 down-regulated ones. In these differentially regulated genes, immune/inflammatory genes were significantly up-regulated in different stages of PAD, (85/230 in intermediate lesions, 37/172 in advanced lesions). Through literature mining and pathway analysis using different databases such as Gene Ontology (GO), and the Kyoto Encyclopedia of Gene and Genomics (KEGG), genes involved in immune/inflammatory responses were significantly enriched in up-regulated genes at different stages of PAD(p < 0.05), revealing a significant correlation between immune/inflammatory responses and disease progression. Moreover, immune-related pathways such as Toll-like receptor signaling and natural killer cell mediated cytotoxicity were particularly enriched in intermediate and advanced lesions (P < 0.05), highlighting their pathogenic significance during disease progression. Conclusion Lines of evidence revealed in this study not only support previous hypotheses, primarily based on studies of animal models and other types of arterial disease, that inflammatory responses may influence the development of PAD, but also permit the recognition of a wide spectrum of immune/inflammatory genes that can serve as signatures for disease progression in PAD. Further studies of these signature molecules may eventually allow us to develop more sophisticated protocols for pharmaceutical interventions.