Christopher C Vanlang

Publications (5) View all

• Article: A mutate-and-map protocol for inferring base pairs in structured RNA

  Pablo Cordero, Wipapat Kladwang, Christopher C. VanLang, Rhiju Das
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  ABSTRACT: Chemical mapping is a widespread technique for structural analysis of nucleic acids in which a molecule's reactivity to different probes is quantified at single-nucleotide resolution and used to constrain structural modeling. This experimental framework has been extensively revisited in the past decade with new strategies for high-throughput read-outs, chemical modification, and rapid data analysis. Recently, we have coupled the technique to high-throughput mutagenesis. Point mutations of a base-paired nucleotide can lead to exposure of not only that nucleotide but also its interaction partner. Carrying out the mutation and mapping for the entire system gives an experimental approximation of the molecules contact map. Here, we give our in-house protocol for this mutate-and-map strategy, based on 96-well capillary electrophoresis, and we provide practical tips on interpreting the data to infer nucleic acid structure.
  01/2013;
• Article: Quantitative dimethyl sulfate mapping for automated RNA secondary structure inference.

  Pablo Cordero, Wipapat Kladwang, Christopher C Vanlang, Rhiju Das
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  ABSTRACT: For decades, dimethyl sulfate (DMS) mapping has informed manual modeling of RNA structure in vitro and in vivo. Here, we incorporate DMS data into automated secondary structure inference using an energy minimization framework developed for 2'-OH acylation (SHAPE) mapping. On six noncoding RNAs with crystallographic models, DMS-guided modeling achieves overall false negative and false discovery rates of 9.5% and 11.6%, respectively, comparable to or better than those of SHAPE-guided modeling, and bootstrapping provides straightforward confidence estimates. Integrating DMS-SHAPE data and including 1-cyclohexyl(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate (CMCT) reactivities provide small additional improvements. These results establish DMS mapping, an already routine technique, as a quantitative tool for unbiased RNA secondary structure modeling.
  Biochemistry 08/2012; 51(36):7037-9. · 3.42 Impact Factor
• Source

  Available from: Christopher C Vanlang

  Article: Understanding the errors of SHAPE-directed RNA structure modeling.

  Wipapat Kladwang, Christopher C VanLang, Pablo Cordero, Rhiju Das
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  ABSTRACT: Single-nucleotide-resolution chemical mapping for structured RNA is being rapidly advanced by new chemistries, faster readouts, and coupling to computational algorithms. Recent tests have shown that selective 2'-hydroxyl acylation by primer extension (SHAPE) can give near-zero error rates (0-2%) in modeling the helices of RNA secondary structure. Here, we benchmark the method using six molecules for which crystallographic data are available: tRNA(phe) and 5S rRNA from Escherichia coli, the P4-P6 domain of the Tetrahymena group I ribozyme, and ligand-bound domains from riboswitches for adenine, cyclic di-GMP, and glycine. SHAPE-directed modeling of these highly structured RNAs gave an overall false negative rate (FNR) of 17% and a false discovery rate (FDR) of 21%, with at least one helix prediction error in five of the six cases. Extensive variations of data processing, normalization, and modeling parameters did not significantly mitigate modeling errors. Only one varation, filtering out data collected with deoxyinosine triphosphate during primer extension, gave a modest improvement (FNR = 12%, and FDR = 14%). The residual structure modeling errors are explained by the insufficient information content of these RNAs' SHAPE data, as evaluated by a nonparametric bootstrapping analysis. Beyond these benchmark cases, bootstrapping suggests a low level of confidence (<50%) in the majority of helices in a previously proposed SHAPE-directed model for the HIV-1 RNA genome. Thus, SHAPE-directed RNA modeling is not always unambiguous, and helix-by-helix confidence estimates, as described herein, may be critical for interpreting results from this powerful methodology.
  Biochemistry 08/2011; 50(37):8049-56. · 3.42 Impact Factor
• Source

  Available from: arxiv.org

  Article: Two-dimensional chemical mapping for non-coding RNAs

  Wipapat Kladwang, Christopher C. VanLang, Pablo Cordero, Rhiju Das
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  ABSTRACT: Non-coding RNA molecules fold into precise base pairing patterns to carry out critical roles in genetic regulation and protein synthesis. We show here that coupling systematic mutagenesis with high-throughput SHAPE chemical mapping enables accurate base pair inference of domains from ribosomal RNA, ribozymes, and riboswitches. For a six-RNA benchmark that challenged prior chemical/computational methods, this mutate-and-map strategy gives secondary structures in agreement with crystallographic data (2 % error rates), including a blind test on a double-glycine riboswitch. Through modeling of partially ordered RNA states, the method enables the first test of an 'interdomain helix-swap' hypothesis for ligand-binding cooperativity in a glycine riboswitch. Finally, the mutate-and-map data report on tertiary contacts within non-coding RNAs; coupled with the Rosetta/FARFAR algorithm, these data give nucleotide-resolution three-dimensional models (5.7 {\AA} helix RMSD) of an adenine riboswitch. These results highlight the promise of a two-dimensional chemical strategy for inferring the secondary and tertiary structures that underlie non-coding RNA behavior.
  04/2011;
• Article: A two-dimensional mutate-and-map strategy for non-coding RNA structure.

  Wipapat Kladwang, Christopher C VanLang, Pablo Cordero, Rhiju Das
  [show abstract] [hide abstract]
  ABSTRACT: Non-coding RNAs fold into precise base-pairing patterns to carry out critical roles in genetic regulation and protein synthesis, but determining RNA structure remains difficult. Here, we show that coupling systematic mutagenesis with high-throughput chemical mapping enables accurate base-pair inference of domains from ribosomal RNA, ribozymes and riboswitches. For a six-RNA benchmark that has challenged previous chemical/computational methods, this 'mutate-and-map' strategy gives secondary structures that are in agreement with crystallography (helix error rates, 2%), including a blind test on a double-glycine riboswitch. Through modelling of partially ordered states, the method enables the first test of an interdomain helix-swap hypothesis for ligand-binding cooperativity in a glycine riboswitch. Finally, the data report on tertiary contacts within non-coding RNAs, and coupling to the Rosetta/FARFAR algorithm gives nucleotide-resolution three-dimensional models (helix root-mean-squared deviation, 5.7 Å) of an adenine riboswitch. These results establish a promising two-dimensional chemical strategy for inferring the secondary and tertiary structures that underlie non-coding RNA behaviour.
  Nature Chemistry 01/2011; 3(12):954-62. · 20.52 Impact Factor