\label{sec:hooke:drivers}
\Hooke\ supports a number of different SMFS data formats, including
-Hemingway\citep{materassi09}, JPK's \citetalias{force-robot},
-Asylum's MFP3D\citep{mfp-3d}, Bruker's \citetalias{picoforce}, and
-my \unfoldprotein\ (\cref{sec:pyafm:unfold-protein}) formats.
+Hemingway\citep{materassi09}, JPK's \citetalias{force-robot}, Asylum's
+MFP3D\citep{mfp-3d}, Bruker's \citetalias{picoforce}, and my
+\unfoldprotein\ (\cref{sec:pyafm:unfold-protein}) formats. The
+drivers are responsible for loading curve data into a standardized
+format so that plugins can work with data from any source. Drivers
+have can determine if they are capable of reading a particular file,
+so if you need to analyze a directory full of curve files in a number
+of formats, you can just point Hooke at the directory and it will pick
+the appropriate driver for each curve.
+
+After loading and parsing the data, drivers return a list of scaled
+\emph{blocks} and a dictionary\footnote{
+ Python dictionaries are hash tables, which allow you to easily
+ access arbitrary data if you know the key under which it was stored.
+} of metadata. Each block corresponds to a different phase of the
+experiment; standard unfolding experiments have an approach block and
+a retraction block. The piezo position and cantilever deflection data
+in each block is scaled by the driver into meters, but further
+processing (e.g. the conversion of cantilever position to a chain
+tension in newtons) is carried out by plugins. The metadata
+dictionary includes standard keys for information that is required for
+the analysis (e.g.~the calibrated spring constant in N/m). If the
+driver can parse any additional metadata from the file, it adds it to
+the dictionary using non-standard keys. You can use this auxilliary
+metadata to perform subsequent analysis (e.g.~``give me all the curves
+that were recorded in \texttt{PBS + 0.5M CaCl2}'').
\subsection{Plugins for analysis}
\label{sec:hooke:plugins}
+Plugins are groups of related commands for processing curves. Curves
+can be stored in playlists, and there are builtin plugins for
+administrative tasks like managing curves (getting curve metadata,
+exporting blocks, \ldots) and playlists (moving to the next curve,
+globbing curves to the playlist, \ldots). There are also analysis
+plugins with commands for doing science. The \imint{python}|vclamp|
+plugin for velocity clamp analysis has commands for finding the
+surface contact point, scaling the cantilever deflection, removing the
+cantilever deflection from the total extension (\cref{fig:procedure}),
+and flattening polynomial drift in the non-contact region. The
+\imint{python}|flatfilt| plugin has commands for identifying peaks
+based on spikes in the deflection derivative and for filtering curves
+from a playlist that only have more than a minimum threshold of such
+peaks\citep{sandal08}. The \imint{python}|polymer_fit| plugin has
+commands for fitting polymer models to the loading peaks
+(\cref{sec:sawsim:tension}), which may have been identified using the
+\imint{python}|flatfilt| plugin or with any other peak-marking plugin.
+For other available plugins, see the \Hooke\ documentation.
+%
+\nomenclature{playlist}{Playlists are containers in \Hooke\ that hold
+ lists of unfolding curves along with some additional metadata.}
@string{DRBentley = "Bentley, D. R."}
@string{HJCBerendsen = "Berendsen, Herman J. C."}
@string{KBergSorensen = "Berg-S\orensen, K"}
+@string{EBergantino = "Bergantino, Elisabetta"}
@string{DBerk = "Berk, D."}
@string{FBerkemeier = "Berkemeier, Felix"}
@string{BBerne = "Berne, Bruce J."}
@string{TBruls = "Bruls, T."}
@string{VBrumfeld = "Brumfeld, Vlad"}
@string{JDBryngelson = "Bryngelson, J. D."}
+@string{LBubacco = "Bubacco, Luigi"}
@string{JBuckheit = "Buckheit, Jonathan B."}
@string{ABuguin = "Buguin, A."}
@string{ABulhassan = "Bulhassan, Ahmed"}
@string{WMajoros = "Majoros, W."}
@string{DEMakarov = "Makarov, Dmitrii E."}
@string{RMamdani = "Mamdani, Reneeta"}
+@string{SMammi = "Mammi, Stefano"}
@string{EMandello = "Mandello, Enrico"}
@string{GManderson = "Manderson, Gavin"}
@string{FMann = "Mann, F."}
@string{BMurphy = "Murphy, B."}
@string{SMurphy = "Murphy, S."}
@string{AMuruganujan = "Muruganujan, A."}
+@string{FMusiani = "Musiani, Francesco"}
@string{EWMyers = "Myers, E. W."}
@string{RMMyers = "Myers, R. M."}
@string{AMylonakis = "Mylonakis, Andreas"}
@string{MPlumbley = "Plumbley, Mark"}
@string{PLOS:ONE = "PLOS ONE"}
%string{PLOS:ONE = "Public Library of Science ONE"}
+@string{PLOS:BIO = "PLOS Biology"}
@string{DPlunkett = "Plunkett, David"}
@string{PPodsiadlo = "Podsiadlo, Paul"}
@string{ASPolitou = "Politou, A. S."}
@string{THEMath = "Technische Hogeschool Eindhoven, Nederland,
Onderafdeling der Wiskunde"}
@string{SJBTendler = "Tendler, S.~J.~B."}
+@string{ITessari = "Tessari, Isabella"}
@string{STeukolsky = "Teukolsky, S."}
@string{CJ = "The Computer Journal"}
@string{JBC = "The Journal of Biological Chemistry"}
@string{UIP:Urbana = "University of Illinois Press, Urbana"}
@string{UTMB = "University of Texas Medical Branch"}
@string{MUrbakh = "Urbakh, M."}
+@string{FValle = "Valle, Francesco"}
@string{KJVanVliet = "Van Vliet, Krystyn J."}
@string{PVandewalle = "Vandewalle, Patrick"}
@string{CVech = "Vech, C."}
pulling speed.},
}
+@article{ sandal08,
+ author = MSandal #" and "# FValle #" and "# ITessari #" and "#
+ SMammi #" and "# EBergantino #" and "# FMusiani #" and "#
+ MBrucale #" and "# LBubacco #" and "# BSamori,
+ title = {Conformational Equilibria in Monomeric $\alpha$-Synuclein
+ at the Single-Molecule Level},
+ year = 2008,
+ month = jan,
+ address = {Department of Biochemistry G. Moruzzi,
+ University of Bologna, Bologna, Italy.},
+ journal = PLOS:BIO,
+ volume = 6,
+ number = 1,
+ pages = {e6},
+ issn = {1545-7885},
+ doi = {10.1371/journal.pbio.0060006},
+ url = {http://www.ncbi.nlm.nih.gov/pubmed/18198943},
+ language = {eng},
+ keywords = {Buffers},
+ keywords = {Circular Dichroism},
+ keywords = {Copper},
+ keywords = {Entropy},
+ keywords = {Models, Molecular},
+ keywords = {Molecular Sequence Data},
+ keywords = {Mutation},
+ keywords = {Protein Structure, Secondary},
+ keywords = {Protein Structure, Tertiary},
+ keywords = {alpha-Synuclein},
+ abstract = {Human $\alpha$-Synuclein ($\alpha$Syn) is a natively
+ unfolded protein whose aggregation into amyloid fibrils is
+ involved in the pathology of Parkinson disease. A full
+ comprehension of the structure and dynamics of early intermediates
+ leading to the aggregated states is an unsolved problem of
+ essential importance to researchers attempting to decipher the
+ molecular mechanisms of $\alpha$Syn aggregation and formation of
+ fibrils. Traditional bulk techniques used so far to solve this
+ problem point to a direct correlation between $\alpha$Syn's unique
+ conformational properties and its propensity to aggregate, but
+ these techniques can only provide ensemble-averaged information
+ for monomers and oligomers alike. They therefore cannot
+ characterize the full complexity of the conformational equilibria
+ that trigger the aggregation process. We applied atomic force
+ microscopy-based single-molecule mechanical unfolding methodology
+ to study the conformational equilibrium of human wild-type and
+ mutant $\alpha$Syn. The conformational heterogeneity of monomeric
+ $\alpha$Syn was characterized at the single-molecule level. Three
+ main classes of conformations, including disordered and
+ ``$\beta$-like'' structures, were directly observed and quantified
+ without any interference from oligomeric soluble forms. The
+ relative abundance of the ``$\beta$-like'' structures
+ significantly increased in different conditions promoting the
+ aggregation of $\alpha$Syn: the presence of \Cu, the pathogenic
+ A30P mutation, and high ionic strength. This methodology can
+ explore the full conformational space of a protein at the
+ single-molecule level, detecting even poorly populated conformers
+ and measuring their distribution in a variety of biologically
+ important conditions. To the best of our knowledge, we present
+ for the first time evidence of a conformational equilibrium that
+ controls the population of a specific class of monomeric
+ $\alpha$Syn conformers, positively correlated with conditions
+ known to promote the formation of aggregates. A new tool is thus
+ made available to test directly the influence of mutations and
+ pharmacological strategies on the conformational equilibrium of
+ monomeric $\alpha$Syn.},
+}
+
@article{ sandal09,
author = MSandal #" and "# FBenedetti #" and "# MBrucale #" and "#
AGomezCasado #" and "# BSamori,
projects / thesis.git / commitdiff