Real-time monitoring of DNA colonies growing in a polyacrylamide gel

Identifying RNA recombination events and non-covalent RNA-RNA interactions with the molecular colony technique

Molecular colonies (also known under names nanocolonies, polonies, RNA or DNA colonies, PCR colonies) form when nucleic acids are amplified in a porous solid or semi-solid medium, such as a gel, which contains a system for the exponential multiplication of RNA or DNA. As an individual colony comprises many copies of a single molecule (a molecular clone), the method can be used for the detection, enumeration, and analysis of individual DNA or RNA molecules, including the products of such rare events as RNA recombinations. Here we describe protocols for the detection of RNA molecules by growing colonies of RNA (in a gel containing Qβ replicase, the RNA-dependent RNA polymerase of phage Qβ) or cDNA (in a gel containing the components of PCR), and visualizing them by hybridization with fluorescent probes directly in the gel, including in real time, or by hybridization with fluorescent or radioactive probes followed by transfer to a nylon membrane.

Detecting overlapping instances in microscopy images using extremal region trees

In many microscopy applications the images may contain both regions of low and high cell densities corresponding to different tissues or colonies at different stages of growth. This poses a challenge to most previously developed automated cell detection and counting methods, which are designed to handle either the low-density scenario (through cell detection) or the high-density scenario (through density estimation or texture analysis). The objective of this work is to detect all the instances of an object of interest in microscopy images. The instances may be partially overlapping and clustered. To this end we introduce a tree-structured discrete graphical model that is used to select and label a set of non-overlapping regions in the image by a global optimization of a classification score. Each region is labeled with the number of instances it contains - for example regions can be selected that contain two or three object instances, by defining separate classes for tuples of objects in the detection process. We show that this formulation can be learned within the structured output SVM framework and that the inference in such a model can be accomplished using dynamic programming on a tree structured region graph. Furthermore, the learning only requires weak annotations - a dot on each instance. The candidate regions for the selection are obtained as extremal region of a surface computed from the microscopy image, and we show that the performance of the model can be improved by considering a proxy problem for learning the surface that allows better selection of the extremal regions. Furthermore, we consider a number of variations for the loss function used in the structured output learning. The model is applied and evaluated over six quite disparate data sets of images covering: fluorescence microscopy, weak-fluorescence molecular images, phase contrast microscopy and histopathology images, and is shown to exceed the state of the art in performance.

Quantitative analysis of genomic element interactions by molecular colony technique

Distant genomic elements were found to interact within the folded eukaryotic genome. However, the used experimental approach (chromosome conformation capture, 3C) enables neither determination of the percentage of cells in which the interactions occur nor demonstration of simultaneous interaction of >2 genomic elements. Each of the above can be done using in-gel replication of interacting DNA segments, the technique reported here. Chromatin fragments released from formaldehyde-cross-linked cells by sodium dodecyl sulfate extraction and sonication are distributed in a polyacrylamide gel layer followed by amplification of selected test regions directly in the gel by multiplex polymerase chain reaction. The fragments that have been cross-linked and separate fragments give rise to multi- and monocomponent molecular colonies, respectively, which can be distinguished and counted. Using in-gel replication of interacting DNA segments, we demonstrate that in the material from mouse erythroid cells, the majority of fragments containing the promoters of active β-globin genes and their remote enhancers do not form complexes stable enough to survive sodium dodecyl sulfate extraction and sonication. This indicates that either these elements do not interact directly in the majority of cells at a given time moment, or the formed DNA-protein complex cannot be stabilized by formaldehyde cross-linking.

In-gel technology for PCR genotyping and pathogen detection

This work describes the use of polyacrylamide gel and PCR reagents photopolymerized in a mold to create an array of semisolid posts that serve as reaction vessels for parallel PCR amplification of an externally added template. DNA amplification occurred in a cylindrical, self-standing 9 × 9 array of gel posts each less than 1 μL in volume. Photopolymerization of the gel with an intercalating dye added prior to polymerization permitted acquisition of real-time PCR data and melting curve analysis data without the need for any type of post-PCR staining procedures. PCR was equally efficient and reproducible when template DNA was polymerized within the gel or when exogenous template was added atop precast gel posts. PCR amplification occurred with template from purified DNA or from raw urine of patients with BK viruria. Multiple primer sets can be utilized per gel post array with no detectable cross contamination. As few as 34 BK virus templates were consistently detected by PCR in an individual gel post. Amplification of HPA1 and FGFR2 genes in human genomic DNA (gDNA) required as little as 2-5 ng of gDNA template/gel post. The device prototype includes a Peltier element for PCR thermal cycling and a CCD camera to capture fluorescence for product detection. Our technology is amenable to integration in point of care microdevices.

An Analysis of Quantitative PCR Reliability Through Replicates Using the C Method

There is considerable interest in quantitatively measuring nucleic acids from single cells to small populations. The most commonly employed laboratory method is the real-time polymerase chain reaction (PCR) analyzed with the crossing point or crossing threshold (C(t)) method. Utilizing a multiwell plate reader we have performed hundreds of replicate reactions at each of a set of initial conditions whose initial number of copies span a concentration range of ten orders of magnitude. The resultant C(t) value distributions are analyzed with standard and novel statistical techniques to assess the variability/reliability of the PCR process. Our analysis supports the following conclusions. Given sufficient replicates, the mean and/or median C(t) values are statistically distinguishable and can be rank ordered across ten orders of magnitude in initial template concentration. As expected, the variances in the C(t) distributions grow as the number of initial copies declines to 1. We demonstrate that these variances are large enough to confound quantitative classification of the initial condition at low template concentrations. The data indicate that a misclassification transition is centered around 3000 initial copies of template DNA and that the transition region correlates with independent data on the thermal wear of the TAQ polymerase enzyme. We provide data that indicate that an alternative endpoint detection strategy based on the theory of well mixing and plate filling statistics is accurate below the misclassification transition where the real time method becomes unreliable.