40 research outputs found
Uncovering the Origins of Rare-Cell Phenomena
No full textRapid advances in technologies have enabled scientists to measure the molecular composition of individual cells with increasing detail and throughput. As these technologies have become widely adopted, they have exposed widespread molecular variability even among cells previously thought to be identical. However, despite the excitement over these discoveries, for many scientists a fundamental question remains: what forms of variability matter for differences in single-cell behavior? Here we describe the development and application of two methodologies for connecting the molecular profile of a cell (cell state) with its future behavior (cell fate), with particular applications for rare biological phenomena. Our first approach combines the experimental design of Luria and Delbrück’s classic “fluctuation analysis” with modern RNA sequencing techniques to identify groups of genes that are coordinately expressed in rare cells and whose expression persists through multiple cell divisions. Applied to multiple cancer models, we identify and validate several such gene expression programs and furthermore, demonstrate that the rare cell subpopulations marked by these programs are far more likely to survive drug treatments. Our second methodology searches for functional forms of single-cell variability from the opposite direction, starting with the unique behavior and effectively going back in time to isolate the cells from which it originated. Combining transcribed single-cell barcodes with high-sensitivity RNA FISH, this methodology is able to selectively recover cells as rare as 1:10,000 (from a population of millions) which can then be profiled using routine sequencing- or imaging-based assays. Using this approach in the context of therapy resistance in cancer, we uncover a variety of resistance outcomes that can be traced back, through weeks of selection and growth, to previously hidden axes of variability in the initial cell population before treatment. These findings begin to detail the complex mapping between rare-cell behaviors in cancer and the underlying molecular variability that enables these behaviors. Moreover, our work outlines a general strategy to uncover such mappings, with likely implication for all manner of phenomena in cancer and beyond
3' Azide labelling with TdT v1
No full textProtocol for add azide modified nucleotide to 3' end of unmodified DNA olgionucleotide using terminal transferase. Protocol adapted from Winz et al. 2015. </p
Design, construction and evaluation of the CSU optical fog detector
No full textJuly 2001.Also issued as Scott E. Emert's thesis (M.S.) -- Colorado State University, 2001.The goal of this project was to develop an inexpensive cloud/fog detector that could be used to automate sampling equipment at remote (unmanned) cloud/fog research sites. A secondary objective was to test the ability of this sensor to measure/track trends in fog/cloud liquid water content (LWC). This characteristic is important because LWC is a significant indicator of a cloud's ability to process aerosols and gases and changes in LWC often correspond to changes in fog/cloud solute concentration. The following actions were taken to help realize these objectives. An evaluation of the use of commercially available optical components for fog detection has been performed. The research reinforced the need to have an inexpensive cloud/fog detector that could be used to automate sampling equipment at remote (unmanned) cloud/fog research sites. No such instrument is currently available commercially. Requirements for components of the CSU Optical Fog Detector (OFD) were defined. Important factors included transmitter wavelength and modulation characteristics, detector sensitivity, and component stability/durability over a range of environmental conditions. Readily available commercial components were utilized to ensure the sensor could be built economically. Laboratory tests in a glove box filled with artificially generated fog proved that optical components purchased from Banner Engineering were capable of monitoring changes in fog liquid water content (L WC) when operated in a light attenuation mode. After an initial calibration, the signal from the CSU OFD was found to correlate strongly with LWC measured by a Gerber Scientific Particulate Volume Monitor (PVM-100). Theoretical calculations of attenuation of 880 run light passing through a population of fog drops were completed. The results indicated extinction decreases as the drops are shifted to larger sizes (with a fixed LWC and lognormal distribution breadth). Accordingly, the response of the CSU OFD is expected to vary with mean fog/cloud drop size. Numerous fog detector design configurations were tested and the current attenuation design of the CSU optical fog detector was deemed successful in that it provides, at a minimum, an inexpensive switch capable of automating remote fog sensing equipment. It also provides useful information concerning fog LWC. Two calibrated OFD's were compared to PVM LWC measurements during initial field tests of orographic clouds at Storm Peak Laboratory (SPL) in Steamboat Springs, Colorado. The combined results from both OFD's overall time periods yield a regression equation of LWCofd = 0.99 * LWCpvm with a correlation coefficient of 0.92. Tests performed in the absence of fog on top of our laboratory in Fort Collins provided a measure of OFD baseline noise. Analysis of the observed noise yielded a minimum detection limit of 4.4 mg m·3 for the OFD and a comparable value (5.6 mg m·3) for the PVM. The OFD was incorporated in several automated fog sampling systems deployed in California's San Joaquin Valley as part of the California Regional Particulate Air Quality Study (CRP AQS). The OFD performed well as a fog detector and provided some insight into fog LWC. LWC measurements by a PVM and a co-located OFD showed good correlation (R2 = 0.91) and only modest bias (LWCofd = 1.16 LWCpvm) during an extended radiation fog episode.Sponsored by the National Science Foundation ATM-9980540, and the San Joaquin Valleywide Air Pollution Study Agency
Abstract 2837: Single-cell heterogeneity with transcriptional memory confers resistance to cancer therapy
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Nat Biotechnol
No full textMolecular differences between individual cells can lead to dramatic differences in cell fate, such as death versus survival of cancer cells upon drug treatment. These originating differences remain largely hidden due to difficulties in determining precisely what variable molecular features lead to which cellular fates. Thus, we developed Rewind, a methodology that combines genetic barcoding with RNA fluorescence in situ hybridization to directly capture rare cells that give rise to cellular behaviors of interest. Applying Rewind to BRAF| melanoma, we trace drug-resistant cell fates back to single-cell gene expression differences in their drug-naive precursors (initial frequency of ~1:1,000-1:10,000 cells) and relative persistence of MAP kinase signaling soon after drug treatment. Within this rare subpopulation, we uncover a rich substructure in which molecular differences among several distinct subpopulations predict future differences in phenotypic behavior, such as proliferative capacity of distinct resistant clones after drug treatment. Our results reveal hidden, rare-cell variability that underlies a range of latent phenotypic outcomes upon drug exposure.T32 HL007439/HL/NHLBI NIH HHSUnited States/DP5 OD028144/OD/NIH HHSUnited States/R01 CA238237/CA/NCI NIH HHSUnited States/F30 CA236129/CA/NCI NIH HHSUnited States/T32 GM007170/GM/NIGMS NIH HHSUnited States/R01 CA232256/CA/NCI NIH HHSUnited States/F30 HD103378/HD/NICHD NIH HHSUnited States/P50 CA174523/CA/NCI NIH HHSUnited States/U01 CA227550/CA/NCI NIH HHSUnited States/F30 HG010822/HG/NHGRI NIH HHSUnited States/1350601/National Science Foundation (NSF)/DP5 OD028144/CD/ODCDC CDC HHSUnited States/T32 DK007780/DK/NIDDK NIH HHSUnited States/RM1 HG007743/HG/NHGRI NIH HHSUnited States/P30 CA016520/CA/NCI NIH HHSUnited States/U01 DK127405/DK/NIDDK NIH HHSUnited States/R01 GM137425/GM/NIGMS NIH HHSUnited States/U01 HL129998/HL/NHLBI NIH HHSUnited States/T32 HG000046/HG/NHGRI NIH HHSUnited States/2021-01-22T00:00:00Z33619394PMC82776661021
Gene regulation gravitates toward either addition or multiplication when combining the effects of two signals
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