The sound of silence: Predictive error responses to unexpected sound omission in adults.

The human auditory system excels at detecting patterns needed for processing speech and music. According to predictive coding, the brain predicts incoming sounds, compares predictions to sensory input and generates a prediction error whenever a mismatch between the prediction and sensory input occurs. Predictive coding can be indexed in electroencephalography (EEG) with the mismatch negativity (MMN) and P3a, two components of event-related potentials (ERP) that are elicited by infrequent deviant sounds (e.g., differing in pitch, duration and loudness) in a stream of frequent sounds. If these components reflect prediction error, they should also be elicited by omitting an expected sound, but few studies have examined this. We compared ERPs elicited by infrequent randomly occurring omissions (unexpected silences) in tone sequences presented at two tones per second to ERPs elicited by frequent, regularly occurring omissions (expected silences) within a sequence of tones presented at one tone per second. We found that unexpected silences elicited significant MMN and P3a, although the magnitude of these components was quite small and variable. These results provide evidence for hierarchical predictive coding, indicating that the brain predicts silences and sounds.

Aqueous Solutions of Peptides and Trialkylamines Lead to Unexpected Peptide Modification.

When trialkylamines are added to buffered solutions of peptides, unexpected adducts can be formed. These adducts correspond to Schiff base products. The source of the reaction is the unexpected presence of aldehydes in amines. The aldehydes can be detected in a few ways. Most importantly, they can lead to unanticipated results in proteomics experiments. Their undesirable effects can be minimized through the addition of other amines.

Use of Multiple Ion Fragmentation Methods to Identify Protein Cross-Links and Facilitate Comparison of Data Interpretation Algorithms.

Multiple ion fragmentation methods involving collision-induced dissociation (CID), higher-energy collisional dissociation (HCD) with regular and very high energy settings, and electron-transfer dissociation with supplementary HCD (EThcD) are implemented to improve the confidence of cross-link identifications. Three different S. cerevisiae proteasome samples cross-linked by diethyl suberthioimidate (DEST) or bis(sulfosuccinimidyl)suberate (BS3) are analyzed. Two approaches are introduced to combine interpretations from the above four methods. Working with cleavable cross-linkers such as DEST, the first approach searches for cross-link diagnostic ions and consistency among the best interpretations derived from all four MS2 spectra associated with each precursor ion. Better agreement leads to a more definitive identification. Compatible with both cleavable and noncleavable cross-linkers such as BS3, the second approach multiplies scoring metrics from a number of fragmentation experiments to derive an overall best match. This significantly increases the scoring gap between the target and decoy matches. The validity of cross-links fragmented by HCD alone and identified by Kojak, MeroX, pLink, and Xi was evaluated using multiple fragmentation data. Possible ways to improve the identification credibility are discussed. Data are available via ProteomeXchange with identifier PXD018310.

Capturing the Forest but Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics.

The brain is known to be active even when not performing any overt cognitive tasks, and often it engages in involuntary mind wandering. This resting state has been extensively characterized in terms of fMRI-derived brain networks. However, an alternate method has recently gained popularity: EEG microstate analysis. Proponents of microstates postulate that the brain discontinuously switches between four quasi-stable states defined by specific EEG scalp topologies at peaks in the global field potential (GFP). These microstates are thought to be "atoms of thought," involved with visual, auditory, salience, and attention processing. However, this method makes some major assumptions by excluding EEG data outside the GFP peaks and then clustering the EEG scalp topologies at the GFP peaks, assuming that only one microstate is active at any given time. This study explores the evidence surrounding these assumptions by studying the temporal dynamics of microstates and its clustering space using tools from dynamical systems analysis, fractal, and chaos theory to highlight the shortcomings in microstate analysis. The results show evidence of complex and chaotic EEG dynamics outside the GFP peaks, which is being missed by microstate analysis. Furthermore, the winner-takes-all approach of only one microstate being active at a time is found to be inadequate since the dynamic EEG scalp topology does not always resemble that of the assigned microstate, and there is competition among the different microstate classes. Finally, clustering space analysis shows that the four microstates do not cluster into four distinct and separable clusters. Taken collectively, these results show that the discontinuous description of EEG microstates is inadequate when looking at nonstationary short-scale EEG dynamics.

Identification of N-terminal protein processing sites by chemical labeling mass spectrometry.

RATIONALE: Proteins undergo post-translational modifications and proteolytic processing that can affect their biological function. Processing often involves the loss of single residues. Cleavage of signal peptides from the N-terminus is commonly associated with translocation. Recent reports have suggested that other processing sites also exist. METHODS: The secreted proteins from S. aureus N315 were precipitated with trichloroacetic acid (TCA) and amidinated with S-methyl thioacetimidate (SMTA). Amidinated proteins were digested with trypsin and analyzed with a high-resolution orbitrap mass spectrometer. RESULTS: Sixteen examples of Staphylococcus aureus secretory proteins that lose an N-terminal signal peptide during their export were identified using this amidination approach. The N-termini of proteins with and without methionine were identified. Unanticipated protein cleavages due to sortase and an unknown protease were also uncovered. CONCLUSIONS: A simple N-terminal amidination based mass spectrometry approach is described that facilitates identification of the N-terminus of a mature protein and the discovery of unexpected processing sites.

Unusual fragmentation of derivatized cysteine-containing peptides.

RATIONALE: Modification of cysteines by aminoethylation results in side chains similar to those of lysine. Trypsin cleaves at this modified residue and this labeling method can facilitate the analysis of proteins, specifically antibodies. In this work, the ability to identify peptides containing aminoethylated cysteines is investigated through digestion, covalent labeling, and low-energy ion fragmentation. METHODS: A prototype antibody was reduced, aminoethylated, and digested with either Lys-N or Glu-C. The resulting peptides were amidinated with SMTA and analyzed by PSD in a MALDI-TOF/TOF mass spectrometer or by CID in an ESI ion trap/orbitrap mass spectrometer. RESULTS: PSD and CID fragmentation of peptides with an amidinated aminoethylated cysteine can produce an intense characteristic loss from this modified residue. A neutral loss of 118 Da or charged loss of 119 Da is observed when peptides have low charges. This fragment can form when the cysteine is located in any position in the peptide. The rationalization for this ion is that the amidino group can be initially neutral or protonated and initiates fragmentation. CONCLUSIONS: The combination of a dual-labeling technique and low-energy fragmentation produces an abundant diagnostic ion for the analysis of cysteine-containing peptides. These 118 and 119 Da losses are observed when protons are sequestered.

EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect.

fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ EEG. However, there has been no verification that these modalities provide converging information at the individual subject level. The present study examined simultaneous EEG and fMRI in healthy volunteers during six mental imagery tasks to determine whether one mental imagery task generates more robust activation across subjects; whether activation can be predicted from familiarity with the imagined activity; and whether EEG and fMRI converge upon the same conclusions about individual imagery performance. Mental arithmetic generated the most robust activation in the majority of subjects for both EEG and fMRI, and level of activation could not be predicted from familiarity, with either modality. We conclude that overall, EEG and fMRI agree regarding individual mental imagery performance.

Impact of Amidination on Peptide Fragmentation and Identification in Shotgun Proteomics.

Peptide amidination labeling using S-methyl thioacetimidate (SMTA) is investigated in an attempt to increase the number and types of peptides that can be detected in a bottom-up proteomics experiment. This derivatization method affects the basicity of lysine residues and is shown here to significantly impact the idiosyncracies of peptide fragmentation and peptide detectability. The unique and highly reproducible fragmentation properties of SMTA-labeled peptides, such as the strong propensity for forming b1 fragment ions, can be further exploited to modify the scoring of peptide-spectrum pairs and improve peptide identification. To this end, we have developed a supervised postprocessing algorithm to exploit these characteristics of peptides labeled by SMTA. Our experiments show that although the overall number of identifications are similar, the SMTA modification enabled the detection of 16-26% peptides not previously observed in comparable CID/HCD tandem mass spectrometry experiments without SMTA labeling.

XLSearch: a Probabilistic Database Search Algorithm for Identifying Cross-Linked Peptides.

Chemical cross-linking combined with mass spectrometric analysis has become an important technique for probing protein three-dimensional structure and protein-protein interactions. A key step in this process is the accurate identification and validation of cross-linked peptides from tandem mass spectra. The identification of cross-linked peptides, however, presents challenges related to the expanded nature of the search space (all pairs of peptides in a sequence database) and the fact that some peptide-spectrum matches (PSMs) contain one correct and one incorrect peptide but often receive scores that are comparable to those in which both peptides are correctly identified. To address these problems and improve detection of cross-linked peptides, we propose a new database search algorithm, XLSearch, for identifying cross-linked peptides. Our approach is based on a data-driven scoring scheme that independently estimates the probability of correctly identifying each individual peptide in the cross-link given knowledge of the correct or incorrect identification of the other peptide. These conditional probabilities are subsequently used to estimate the joint posterior probability that both peptides are correctly identified. Using the data from two previous cross-link studies, we show the effectiveness of this scoring scheme, particularly in distinguishing between true identifications and those containing one incorrect peptide. We also provide evidence that XLSearch achieves more identifications than two alternative methods at the same false discovery rate (availability: https://github.com/COL-IU/XLSearch ).

Photosynthesis of a combinatorial peptide library in the gas phase.

A strategy for generating large numbers of peptides from a relatively small number of precursors based on photosynthetic combination in the gas phase is presented. In this approach, electrospray ionization is used to create a combination of proton-bound dimers from a specified set of peptides present in solution. The dimers are then accumulated and isolated in an ion trap mass spectrometer. Photoexcitation (at 157 nm) leads to water elimination and the formation of larger peptide sequences that are characterized by subsequent isolation and collision-induced dissociation. The method is illustrated by using a set of four enkephalin-related and acetylated peptides to generate 12 larger peptide sequences. The ability to synthesize, isolate, and characterize many amino acid sequences from only a few precursors provides a fast and efficient means of characterizing properties of such species (e.g., dissociation patterns and reactivities).

Ballistocardiogram correction in simultaneous EEG/ fMRI recordings: a comparison of average artifact subtraction and optimal basis set methods using two popular software tools.

Electroencephalography data recorded during functional magnetic resonance imaging acquisition are subject to large cardiac-related artifacts that must be corrected during postprocessing. This study compared two widely used ballistocardiogram (BCG) correction algorithms as implemented in two software programs. Reduction of BCG amplitude, correlation of corrected data with electrocardiogram traces, correlation of independent components with electrocardiogram traces, and event-related potential signal-to-noise ratio from each algorithm were compared. Both algorithms effectively reduced the BCG artifact, with a slight advantage of average artifact subtraction over the optimal basis set method (0.1-2.2%) when the quality of the correction was examined at the individual subject level. This study provides users of these software tools with an important, practical, and previously unavailable comparison of the performance of these two methods.

Dynamics of ribosomal protein S1 on a bacterial ribosome with cross-linking and mass spectrometry.

Ribosomal protein S1 has been shown to be a significant effector of prokaryotic translation. The protein is in fact capable of efficiently initiating translation, regardless of the presence of a Shine-Dalgarno sequence in mRNA. Structural insights into this process have remained elusive, as S1 is recalcitrant to traditional techniques of structural analysis, such as x-ray crystallography. Through the application of protein cross-linking and high resolution mass spectrometry, we have detailed the ribosomal binding site of S1 and have observed evidence of its dynamics. Our results support a previous hypothesis that S1 acts as the mRNA catching arm of the prokaryotic ribosome. We also demonstrate that in solution the major domains of the 30S subunit are remarkably flexible, capable of moving 30-50Å with respect to one another.

Non-Specific Signal Peptidase Processing of Extracellular Proteins in Staphylococcus aureus N315.

Staphylococcus aureus is one of the major community-acquired human pathogens, with growing multidrug-resistance, leading to a major threat of more prevalent infections to humans. A variety of virulence factors and toxic proteins are secreted during infection via the general secretory (Sec) pathway, which requires an N-terminal signal peptide to be cleaved from the N-terminus of the protein. This N-terminal signal peptide is recognized and processed by a type I signal peptidase (SPase). SPase-mediated signal peptide processing is the crucial step in the pathogenicity of S. aureus. In the present study, the SPase-mediated N-terminal protein processing and their cleavage specificity were evaluated using a combination of N-terminal amidination bottom-up and top-down proteomics-based mass spectrometry approaches. Secretory proteins were found to be cleaved by SPase, specifically and non-specifically, on both sides of the normal SPase cleavage site. The non-specific cleavages occur at the relatively smaller residues that are present next to the -1, +1, and +2 locations from the original SPase cleavage site to a lesser extent. Additional random cleavages at the middle and near the C-terminus of some protein sequences were also observed. This additional processing could be a part of some stress conditions and unknown signal peptidase mechanisms.

Tracking auditory mismatch negativity responses during full conscious state and coma.

The mismatch negativity (MMN) is considered the electrophysiological change-detection response of the brain, and therefore a valuable clinical tool for monitoring functional changes associated with return to consciousness after severe brain injury. Using an auditory multi-deviant oddball paradigm, we tracked auditory MMN responses in seventeen healthy controls over a 12-h period, and in three comatose patients assessed over 24 h at two time points. We investigated whether the MMN responses show fluctuations in detectability over time in full conscious awareness, or whether such fluctuations are rather a feature of coma. Three methods of analysis were utilized to determine whether the MMN and subsequent event-related potential (ERP) components could be identified: traditional visual analysis, permutation t-test, and Bayesian analysis. The results showed that the MMN responses elicited to the duration deviant-stimuli are elicited and reliably detected over the course of several hours in healthy controls, at both group and single-subject levels. Preliminary findings in three comatose patients provide further evidence that the MMN is often present in coma, varying within a single patient from easily detectable to undetectable at different times. This highlights the fact that regular and repeated assessments are extremely important when using MMN as a neurophysiological predictor of coma emergence.

Gray matter volume drives the brain age gap in schizophrenia: a SHAP study.

Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term ß = 1.71 [0.53; 3.23]; pcorr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.

In vitro and in vivo chemical labeling of ribosomal proteins: a quantitative comparison.

Thioimidates have emerged as reagents for probing the protein structure, folding, and interactions under physiological conditions. The same properties that give thioimidates biological relevance make these molecules ideal candidates for use in vivo. Through labeling of ribosomal proteins, we have quantified the in vivo and in vitro reactivity of two thioimidates: S-methylthioacetimidate (SMTA) and a novel, charge-carrying analogue, S-sulfethylthioacetimidate (SSETA). In vitro experiments demonstrate that both amidinating reagents can probe the protein structure. Under comparable in vivo conditions, SMTA is found to be membrane-permeable while SSETA is not. The use of mass spectrometry with permeant and impermeant thioimidates promises insights into the membrane topology and protein structure in the native environment.

Analyzing a Mixture of Disaccharides by IMS-VUVPD-MS.

Comparative analyses utilizing collision induced dissociation (CID) and vacuum ultraviolet photodissociation (VUVPD) for seven isobaric disaccharides have been performed in order to differentiate the linkage type and anomeric configuration of the isomers. Although an individual CID spectrum of a disaccharide ion provides information related to its structure, CID does not sufficiently differentiate mixture components due to the identical mass-to-charge values of most of the intense fragments. In contrast to the ambiguity of the CID analyses for the disaccharide mixture, VUVPD (157 nm) generates unique fragments for each disaccharide ion that are useful for distinguishing individual components from the mixture. When combined with a gas-phase ion mobility separation of the ions, the identification of each component from the mixture can be obtained.

Extracted Fragment Ion Mobility Distributions: A New Method for Complex Mixture Analysis.

A new method is presented for constructing ion mobility distributions of precursor ions based upon the extraction of drift time distributions that are monitored for selected fragment ions. The approach is demonstrated with a recently designed instrument that combines ion mobility spectrometry (IMS) with ion trap mass spectrometry (MS) and ion fragmentation, as shown in a recent publication [J. Am. Soc. Mass Spectrom. 22 (2011) 1477-1485]. Here, we illustrate the method by examining selected charge states of electrosprayed ubiquitin ions, an extract from diesel fuel, and a mixture of phosphorylated peptide isomers. For ubiquitin ions, extraction of all drift times over small mass-to-charge (m/z) ranges corresponding to unique fragments of a given charge state allows the determination of precursor ion mobility distributions. A second example of the utility of the approach includes the distinguishing of precursor ion mobility distributions for isobaric, basic components from commercially available diesel fuel. Extraction of data for a single fragment ion is sufficient to distinguish the precursor ion mobility distribution of cycloalkyl-pyridine derivatives from pyrindan derivatives. Finally, the method is applied for the analysis of phosphopeptide isomers (LFpTGHPESLER and LFTGHPEpSLER) in a mixture. The approach alleviates several analytical challenges that include separation and characterization of species having similar (or identical) m/z values within complex mixtures.

Comprehensive characterization of methicillin-resistant Staphylococcus aureus subsp. aureus COL secretome by two-dimensional liquid chromatography and mass spectrometry.

Two-dimensional LC combined with whole protein and peptide mass spectrometry is used to characterize proteins secreted by methicillin-resistant Staphylococcus aureus COL. Protein identifications were accomplished via off-line protein fractionation followed by digestion and subsequent peptide analysis by reverse phase LC-ESI-LTQ-FT-MS/MS. Peptide MS/MS analysis identified 127 proteins comprising 59 secreted proteins, seven cell wall-anchored proteins, four lipoproteins, four membrane proteins, and 53 cytoplasmic proteins. The identified secreted proteins included various virulence factors of known functions (cytotoxins, enterotoxins, proteases, lipolytic enzymes, peptidoglycan hydrolases, etc.). Accurate whole protein mass measurement (+/-1.5 Da) of the secreted proteins combined with peptide analysis enabled identification of signal peptide cleavage sites and various post-translational modifications. In addition, new observations were possible using the present approach. Although signal peptide cleavage is highly specific, signal peptide processing can occur at more than one site. Surprisingly, cleaved signal peptides and their fragments can be observed in the extracellular medium. The prediction accuracies of several signal peptide prediction programs were also evaluated.

Interpretation of anomalously long crosslinks in ribosome crosslinking reveals the ribosome interaction in stationary phase E. coli.

Crosslinking mass spectrometry (XL-MS) of bacterial ribosomes revealed the dynamic intra- and intermolecular interactions within the ribosome structure. It has been also extended to capture the interactions of ribosome binding proteins during translation. Generally, XL-MS often identified the crosslinks within a cross-linkable distance (<40 Å) using amine-reactive crosslinkers. The crosslinks larger than cross-linkable distance (>40 Å) are always difficult to interpret and remain unnoticed. Here, we focused on stationary phase bacterial ribosome crosslinking that yields ultra-long crosslinks in an E. coli cell lysate. We explain these ultra-long crosslinks with the combination of sucrose density gradient centrifugation, chemical crosslinking, high-resolution mass spectrometry, and electron microscopy analysis. Multiple ultra-long crosslinks were observed in E. coli ribosomes for example ribosomal protein L19 (K63, K94) crosslinks with L21 (K71, K81) at two locations that are about 100 Å apart. Structural mapping of such ultra-long crosslinks in 70S ribosomes suggested that these crosslinks are not potentially formed within one 70S particle and could be a result of dimer and trimer formation as evidenced by negative staining electron microscopy. Ribosome dimerization captured by chemical crosslinking reaction could be an indication of ribosome-ribosome interactions in the stationary phase.