Article

Single molecule transcription profiling with AFM.

Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA 90095, USA.
Nanotechnology (Impact Factor: 3.67). 05/2007; 18(4):44032. DOI: 10.1088/0957-4484/18/4/044032
Source: PubMed

ABSTRACT Established techniques for global gene expression profiling, such as microarrays, face fundamental sensitivity constraints. Due to greatly increasing interest in examining minute samples from micro-dissected tissues, including single cells, unorthodox approaches, including molecular nanotechnologies, are being explored in this application. Here, we examine the use of single molecule, ordered restriction mapping, combined with AFM, to measure gene transcription levels from very low abundance samples. We frame the problem mathematically, using coding theory, and present an analysis of the critical error sources that may serve as a guide to designing future studies. We follow with experiments detailing the construction of high density, single molecule, ordered restriction maps from plasmids and from cDNA molecules, using two different enzymes, a result not previously reported. We discuss these results in the context of our calculations.

Download full-text

Full-text

Available from: Bede Pittenger, Dec 18, 2013
1 Follower
 · 
100 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: There are many examples of problems in pattern analysis for which it is often possible to obtain systematic characterizations, if in addition a small number of useful features or parameters of the image are known a priori or can be estimated reasonably well. Often the relevant features of a particular pattern analysis problem are easy to enumerate, as when statistical structures of the patterns are well understood from the knowledge of the domain. We study a problem from molecular image analysis, where such a domain-dependent understanding may be lacking to some degree and the features must be inferred via machine-learning techniques. In this paper, we propose a rigorous, fully-automated technique for this problem. We are motivated by an application of atomic force microscopy (AFM) image processing needed to solve a central problem in molecular biology, aimed at obtaining the complete transcription profile of a single cell, a snapshot that shows which genes are being expressed and to what degree. Reed et al (Single molecule transcription profiling with AFM, Nanotechnology, 18:4, 2007) showed the transcription profiling problem reduces to making high-precision measurements of biomolecule backbone lengths, correct to within 20-25 bp (6-7.5 nm). Here we present an image processing and length estimation pipeline using AFM that comes close to achieving these measurement tolerances. In particular, we develop a biased length estimator on trained coefficients of a simple linear regression model, biweighted by a Beaton-Tukey function, whose feature universe is constrained by James-Stein shrinkage to avoid overfitting. In terms of extensibility and addressing the model selection problem, this formulation subsumes the models we studied.
    IEEE transactions on information technology in biomedicine: a publication of the IEEE Engineering in Medicine and Biology Society 06/2012; 16(6). DOI:10.1109/TITB.2012.2206819 · 2.07 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Nanotechnology has enabled the production of new materials and molecular-scale devices. Biotechnological advancements have allowed scientists to physical ly manipulate genetic pathways or engineering strains of proteins to possess novel functionalities. Informatics has served as the catalyst for organizing and understanding vast knowledge from a system point of view. The fusion of biotechnology, nanotechnology, and information science will culminate in system architectures that can rival those that have taken millions of years to come to fruition. With this comes the hope of achieving a fundamental comprehension of how to manipulate and control cells on die molecular level. It will also enable us to question just how much further we can push the envelope of human engineering.
    02/2008; 1(1):18-21. DOI:10.1109/MNANO.2007.912099
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We have used an atomic force microscope to examine a clinically derived sample of single-molecule gene transcripts, in the form of double-stranded cDNA, (c: complementary) obtained from human cardiac muscle without the use of polymerase chain reaction (PCR) amplification. We observed a log-normal distribution of transcript sizes, with most molecules being in the range of 0.4-7.0 kilobase pairs (kb) or 130-2300 nm in contour length, in accordance with the expected distribution of mRNA (m: messenger) sizes in mammalian cells. We observed novel branching structures not previously known to exist in cDNA, and which could have profound negative effects on traditional analysis of cDNA samples through cloning, PCR and DNA sequencing.
    Nanotechnology 09/2008; 19(38):384021. DOI:10.1088/0957-4484/19/38/384021 · 3.67 Impact Factor