63 research outputs found
Identification and Quantification of Proteoforms by Mass Spectrometry
A proteoform is a defined form of a protein derived from a given gene with a specific amino acid sequence and localized post-translational modifications. In top-down proteomic analyses, proteoforms are identified and quantified through mass spectrometric analysis of intact proteins. Recent technological developments have enabled comprehensive proteoform analyses in complex samples, and an increasing number of laboratories are adopting top-down proteomic workflows. In this review, we outline some recent advances and discuss current challenges and future directions for the field
Quantitative Evidence for the Effects of Multiple Drivers on Continental-Scale Amphibian Declines
Since amphibian declines were first proposed as a global phenomenon over a quarter century ago, the conservation community has made little progress in halting or reversing these trends. The early search for a “smoking gun” was replaced with the expectation that declines are caused by multiple drivers. While field observations and experiments have identified factors leading to increased local extinction risk, evidence for effects of these drivers is lacking at large spatial scales. Here, we use observations of 389 time-series of 83 species and complexes from 61 study areas across North America to test the effects of 4 of the major hypothesized drivers of declines. While we find that local amphibian populations are being lost from metapopulations at an average rate of 3.79% per year, these declines are not related to any particular threat at the continental scale; likewise the effect of each stressor is variable at regional scales. This result - that exposure to threats varies spatially, and populations vary in their response - provides little generality in the development of conservation strategies. Greater emphasis on local solutions to this globally shared phenomenon is needed
Quantitative Evidence for the Effects of Multiple Drivers on Continental-Scale Amphibian Declines
Since amphibian declines were first proposed as a global phenomenon over a quarter century ago, the conservation community has made little progress in halting or reversing these trends. The early search for a “smoking gun” was replaced with the expectation that declines are caused by multiple drivers. While field observations and experiments have identified factors leading to increased local extinction risk, evidence for effects of these drivers is lacking at large spatial scales. Here, we use observations of 389 time-series of 83 species and complexes from 61 study areas across North America to test the effects of 4 of the major hypothesized drivers of declines. While we find that local amphibian populations are being lost from metapopulations at an average rate of 3.79% per year, these declines are not related to any particular threat at the continental scale; likewise the effect of each stressor is variable at regional scales. This result - that exposure to threats varies spatially, and populations vary in their response - provides little generality in the development of conservation strategies. Greater emphasis on local solutions to this globally shared phenomenon is needed
Bioinformatics Analysis of Top-Down Mass Spectrometry Data
Traditional bottom-up mass spectrometry-based proteomics relies on the use of an enzyme, often trypsin, to generate small peptides (typically < 25 amino acids long). In top-down proteomics, proteins remain intact and are directly measured within the mass spectrometer. This technique, while inherently simpler than bottom-up proteomics, generates data which must be processed and analyzed using software tools “purpose-built” for the job. In this chapter, we will show the analysis of proteins from deconvolution and deisotoping through analysis with ProSight Lite, a free, vendor agnostic tool for the analysis of top-down mass spectrometry data. We will illustrate with two examples of intact protein spectra and discuss the iterative use of the software to characterize proteoforms and to discover the sites of post-translational modifications
Bioinformatics Analysis of Top-Down Mass Spectrometry Data
Accompanying dataset to the protocol published in Methods in Molecular Biology. Click on the PURL link below in the "External Files" section to download the dataset.Traditional bottom-up mass spectrometry-based proteomics relies on the use of an enzyme, often trypsin, to generate small peptides (typically < 25 amino acids long). In top-down proteomics, proteins remain intact and are directly measured within the mass spectrometer. This technique, while inherently simpler than bottom-up proteomics, generates data which must be processed and analyzed using software tools “purpose-built” for the job. In this chapter, we will show the analysis of proteins from deconvolution and deisotoping through analysis with ProSight Lite, a free, vendor agnostic tool for the analysis of top-down mass spectrometry data. We will illustrate with two examples of intact protein spectra and discuss the iterative use of the software to characterize proteoforms and to discover the sites of post-translational modifications.NIH/NIGMS P41GM10856
Bioinformatics Analysis of Top-Down Mass Spectrometry Data with ProSight Lite
Accompanying dataset to the protocol published in Methods in Molecular Biology. Click on the PURL link below in the "External Files" section to download the dataset.Traditional bottom-up mass spectrometry-based proteomics relies on the use of an enzyme, often trypsin, to generate small peptides (typically < 25 amino acids long). In top-down proteomics, proteins remain intact and are directly measured within the mass spectrometer. This technique, while inherently simpler than bottom-up proteomics, generates data which must be processed and analyzed using software tools “purpose-built” for the job. In this chapter, we will show the analysis of proteins from deconvolution and deisotoping through analysis with ProSight Lite, a free, vendor agnostic tool for the analysis of top-down mass spectrometry data. We will illustrate with two examples of intact protein spectra and discuss the iterative use of the software to characterize proteoforms and to discover the sites of post-translational modifications.NIH/NIGMS P41GM10856
Advancing Intact Protein Quantitation with Updated Deconvolution Routines
Analysis of intact proteins by mass spectrometry enables
direct
quantitation of the specific proteoforms present in a sample and is
an increasingly important tool for biopharmaceutical and academic
research. Interpreting and quantifying intact protein species from
mass spectra typically involves many challenges including mass deconvolution
and peak processing as well as determining optimal spectral averaging
parameters and matching masses to theoretical proteoforms. Each of
these steps can present informatic hurdles, as parameters often need
to be tailored specifically to the data sets. To reduce intact mass
deconvolution data analysis burdens, we built upon the widely used
“sliding window” mass deconvolution technique with several
additional concepts. First, we found that how spectra are averaged
and the overlap in spectral windows can be tuned to favor either sensitivity
or speed. A multiple window averaging approach was found to be the
most effective way to increase mass detection and yielded a >2-fold
increase in the number of masses detected. We also developed a targeted
feature-finding routine that boosted sensitivity by >2-fold, decreased
coefficient of variation across replicates by 50%, and increased the
quality of mass elution profiles through 3-fold more detected time
points. Lastly, we furthered existing approaches for annotating detected
masses with potential proteoforms through spectral fitting for possible
proteoform family modifications and network viewing. These proteoform
annotation approaches ultimately produced a more accurate way of finding
related, but previously unknown proteoforms from intact mass-only
data. Together, these quantitation workflow improvements advance the
information obtainable from intact protein mass spectrometry analyses
Autopilot: An Online Data Acquisition Control System for the Enhanced High-Throughput Characterization of Intact Proteins
The ability to study organisms by
direct analysis of their proteomes
without digestion via mass spectrometry has benefited greatly from
recent advances in separation techniques, instrumentation, and bioinformatics.
However, improvements to data acquisition logic have lagged in comparison.
Past workflows for Top Down Proteomics (TDPs) have focused on high
throughput at the expense of maximal protein coverage and characterization.
This mode of data acquisition has led to enormous overlap in the identification
of highly abundant proteins in subsequent LC-MS injections. Furthermore,
a wealth of data is left underutilized by analyzing each newly targeted
species as unique, rather than as part of a collection of fragmentation
events on a distinct proteoform. Here, we present a major advance
in software for acquisition of TDP data that incorporates a fully
automated workflow able to detect intact masses, guide fragmentation
to achieve maximal identification and characterization of intact protein
species, and perform database search online to yield real-time protein
identifications. On <i>Pseudomonas aeruginosa</i>, the software
combines fragmentation events of the same precursor with previously
obtained fragments to achieve improved characterization of the target
form by an average of 42 orders of magnitude in confidence. When HCD
fragmentation optimization was applied to intact proteins ions, there
was an 18.5 order of magnitude gain in confidence. These improved
metrics set the stage for increased proteome coverage and characterization
of higher order organisms in the future for sharply improved control
over MS instruments in a project- and lab-wide context
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