Mounting evidence points to the soluble oligomers of amyloid β (Aβ) peptide as important neurotoxic species in Alzheimer's disease, causing synaptic dysfunction and neuronal injury, and finally leading to neuronal death. The mechanism of the Aβ peptide self-assembly is still under debate. Here, Aβ1-40 peptide oligomers were studied using mass spectrometry combined with ion mobility spectrometry, which allowed separation of the signals of numerous oligomers and measurement of their collisional cross-section values (Ω). For several oligomers, at least two different species of different Ω values were detected, indicating the presence of at least two families of conformers: compact and extended. The obtained results are rationalized by a set of molecular models of Aβ1-40 oligomer structure that provided a very good correlation between the experimental and theoretical Ω values, both for the compact and the extended forms. Our results indicate that mass spectrometry detects oligomeric species that are on-pathway in the process of fibril formation or decay, but also alternative structures which may represent off-pathway evolution of oligomers.

The obligate intracellular developmental cycle of Chlamydia trachomatis presents significant challenges in defining its proteome. In this study we have applied quantitative proteomics to both the intracellular reticulate body (RB) and the extracellular elementary body (EB) from C. trachomatis. We used C. trachomatis L2 as a model chlamydial isolate for our study since it has a high infectivity:particle ratio and there is an excellent quality genome sequence. EBs and RBs (>99% pure) were quantified by chromosomal and plasmid copy number using PCR, from which the concentrations of chlamydial proteins per bacterial cell/genome were determined. RBs harvested at 15h post infection (PI) were purified by three successive rounds of gradient centrifugation. This is the earliest possible time to obtain purified RBs, free from host cell components in quantity, within the constraints of the technology. EBs were purified at 48h PI. We then used two-dimensional reverse phase UPLC to fractionate RB or EB peptides before mass spectroscopic analysis, providing absolute amount estimates of chlamydial proteins. The ability to express the data as molecules per cell gave ranking in both abundance and energy requirements for synthesis, allowing meaningful identification of rate-limiting components. The study assigned 562 proteins with high confidence and provided absolute estimates of protein concentration for 489 proteins. Interestingly, the data showed an increase in TTS capacity at 15h PI. Most of the enzymes involved in peptidoglycan biosynthesis were detected along with high levels of muramidase (in EBs) suggesting breakdown of peptidoglycan occurs in the non-dividing form of the microorganism. All the genome-encoded enzymes for glycolysis, pentose phosphate pathway and tricarboxylic acid cycle were identified and quantified; these data supported the observation that the EB is metabolically active. The availability of detailed, accurate quantitative proteomic data will be invaluable for investigations into gene regulation and function.

A new method for enhancing peptide ion identification in proteomics analyses using ion mobility data is presented. Ideally, direct comparisons of experimental drift times (tD) with a standard mobility database could be used to rank candidate peptide sequence assignments. Such a database would represent only a fraction of sequences in protein databases and significant difficulties associated with the verification of data for constituent peptide ions would exist. A method that employs intrinsic amino acid size parameters to obtain ion mobility predictions that can be used to rank candidate peptide ion assignments is proposed. Intrinsic amino acid size parameters have been determined for doubly-charged peptide ions from an annotated yeast proteome. Predictions of ion mobilities using the intrinsic size parameters are more accurate than those obtained from a polynomial fit to tD versus molecular weight data. More than a two-fold improvement in prediction accuracy has been observed for a group of arginine-terminated peptide ions twelve residues in length. The use of this predictive enhancement as a means to aid peptide ion identification is discussed and a simple peptide ion scoring scheme is presented.

Extracellular vesicles have created great interest as possible source of biomarkers for different biological processes and diseases. Although the biological function of these vesicles is not fully understood, it is clear that they participate in the removal of unnecessary cellular material and act as carriers of various macromolecules and signals between the cells. In this report, we analyzed the proteome of extracellular vesicles secreted by primary hepatocytes. We used one- and two-dimensional liquid chromatography combined with data-independent mass spectrometry. Employing label-free quantitative proteomics, we detected significant changes in vesicle protein expression levels in this in vitro model after exposure to well-known liver toxins (galactosamine and Escherichia coli-derived lipopolysaccharide). The results allowed us to identify candidate markers for liver injury. We validated a number of these markers in vivo, providing the basis for the development of novel methods to evaluate drug toxicity. This report strongly supports the application of proteomics in the study of extracellular vesicles released by well-controlled in vitro cellular systems. Analysis of such systems should help to identify specific markers for various biological processes and pathological conditions.

To accurately determine the quantitative change of peptides and proteins in complex proteomics samples requires knowledge of how well each ion has been measured. The precision of each ions' calculated area is predicated on how uniquely it occupies its own space in m/z and elution time. Given an initial assumption that prior to the addition of the "heavy" label, all other ion detections are unique, which is arguably untrue, an initial attempt at quantifying the pervasiveness of ion interference events in a representative binary SILAC experiment was made by comparing the centered m/z and retention time of the ion detections from the "light" variant to its "heavy" companion. Ion interference rates were determined for LC-MS data acquired at mass resolving powers of 20 and 40 K with and without ion mobility separation activated. An ion interference event was recorded, if present in the companion dataset was an ion within ± its Δ mass at half-height, ±15 s of its apex retention time and if utilized by ±1 drift bin. Data are presented illustrating a definitive decrease in the frequency of ion interference events with each additional increase in selectivity of the analytical workflow. Regardless of whether the quantitative experiment is a composite of labeled samples or label free, how well each ion is measured can be determined given knowledge of the instruments mass resolving power across the entire m/z scale and the ion detection algorithm reporting both the centered m/z and Δ mass at half-height for each detected ion. Given these measurements, an effective resolution can be calculated and compared with the expected instrument performance value providing a purity score for the calculated ions' area based on mass resolution. Similarly, chromatographic and drift purity scores can be calculated. In these instances, the error associated to an ions' calculated peak area is estimated by examining the variation in each measured width to that of their respective experimental median. Detail will be disclosed as to how a final ion purity score was established, providing a first measure of how accurately each ions' area was determined as well as how precise the calculated quantitative change between labeled or unlabelled pairs were determined. Presented is how common ion interference events are in quantitative proteomics LC-MS experiments and how ion purity filters can be utilized to overcome and address them, providing ultimately more accurate and precise quantification results across a wider dynamic range.