Machine Learning-Assisted High-Throughput Identification and Quantification of Protein Biomarkers with Printed Heterochains.

Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of multi-material heterochains, which show improved sensitivity, throughput, and accuracy compared to standard ELISA kits. By controlling the material combination and the number of ligand nanoparticles (NPs), we observe robust near-field enhancement as well as both strong electromagnetic resonance in polymer-semiconductor heterochains. In particular, their optical signals show a linear response to the coordination number of the semiconductor NPs in a wide range. Accordingly, a visible nanophotonic biosensor is developed by functionalizing antibodies on central polymer chains that can identify target proteins attached to semiconductor NPs. This allows for the specific detection of multiple protein biomarkers from healthy people and pancreatic cancer patients in one step with an ultralow detection limit (1 pg/mL). Furthermore, rapid and high-throughput quantification of protein expression levels in diverse clinical samples such as buffer, urine, and serum is achieved by combining a neural network algorithm, with an average accuracy of 97.3%. This work demonstrates that the heterochain-based biosensor is an exemplary candidate for constructing next-generation diagnostic tools and suitable for many clinical settings.

Printed Divisional Optical Biochip for Multiplex Visualizable Exosome Analysis at Point-of-Care.

Rapid detection of various exosomes is of great significance in early diagnosis and postoperative monitoring of cancers. Here, a divisional optical biochip is reported for multiplex exosome analysis via combining the self-assembly of nanochains and precise surface patterning. Arising from resonance-induced near-field enhancement, the nanochains show distinct color changes after capturing target exosomes for direct visual detection. Then, a series of divisional nanochain-based biochips conjugated with several specific antibodies are fabricated through designed hydrophilic and hydrophobic patterns. Because of the significant wettability difference, one sample droplet is precisely self-splitting into several microdroplets enabling simultaneous identification of multiple target exosomes in 30 min with a sensitivity of 6 × 107 particles mL-1 , which is about two orders lower than enzyme-linked immunosorbent assay. Apart from the trace amount detection, excellent semiquantitative capability is demonstrated to distinguish clinical exosomes from glioblastoma patients and healthy people. This method is simple, versatile, and highly efficient that can be extended as a diagnostic tool for many diseases, promoting the development of liquid biopsy.

Molecular Recognition-Modulated Hetero-Assembly of Nanostructures for Visualizable and Portable Detection of Circulating miRNAs.

Biomolecular markers, particularly circulating microRNAs (miRNAs) play an important role in diagnosis, monitoring, and therapeutic intervention of cancers. However, existing detection strategies remain intricate, laborious, and far from being developed for point-of-care testing. Here, we report a portable colorimetric sensor that utilizes the hetero-assembly of nanostructures driven by base pairing and recognition for direct detection of miRNAs. Following hybridization, two sizes of nanoparticles modified with single-strand DNA can be robustly assembled into heterostructures with strong optical resonance, exhibiting distinct structure colors. Particularly, the large nanoparticles are first arranged into nanochains to enhance scattering signals of small nanoparticles, which allows for sensitive detection and quantification of miRNAs without the requirement of target extraction, amplification, and fluorescent labels. Furthermore, we demonstrate the high specificity and single-base selectivity of testing different miRNA samples, which shows great potential in the diagnosis, staging, and monitoring of cancers. These heterogeneous assembled nanostructures provide an opportunity to develop simple, fast, and convenient tools for miRNAs detection, which is suitable for many scenarios, especially in low-resource setting.

Efficacy of the monocarbonyl curcumin analog C66 in the reduction of diabetes-associated cardiovascular and kidney complications.

Curcumin is a polyphenolic compound derived from turmeric that has potential beneficial properties for cardiovascular and renal diseases and is relatively safe and inexpensive. However, the application of curcumin is rather problematic due to its chemical instability and low bioavailability. The experimental results showed improved chemical stability and potent pharmacokinetics of one of its analogs - (2E,6E)-2,6-bis[(2-trifluoromethyl)benzylidene]cyclohexanone (C66). There are several advantages of C66, like its synthetic accessibility, structural simplicity, improved chemical stability (in vitro and in vivo), presence of two reactive electrophilic centers, and good electron-accepting capacity. Considering these characteristics, we reviewed the literature on the application of C66 in resolving diabetes-associated cardiovascular and renal complications in animal models. We also summarized the mechanisms by which C66 is preventing the release of pro-oxidative and pro-inflammatory molecules in the priming and in activation stage of cardiomyopathy, renal fibrosis, and diabetic nephropathy. The cardiovascular protective effect of C66 against diabetes-induced oxidative damage is Nrf2 mediated but mainly dependent on JNK2. In general, C66 causes inhibition of JNK2, which reduces cardiac inflammation, fibrosis, oxidative stress, and apoptosis in the settings of diabetic cardiomyopathy. C66 exerts a powerful antifibrotic effect by reducing inflammation-related factors (MCP-1, NF-κB, TNF-α, IL-1ß, COX-2, and CAV-1) and inducing the expression of anti-inflammatory factors (HO-1 and NEDD4), as well as targeting TGF-ß/SMADs, MAPK/ERK, and PPAR-γ pathways in animal models of diabetic nephropathy. Based on the available evidence, C66 is becoming a promising drug candidate for improving cardiovascular and renal health.

Observation of Magic Number Clusters from Thermal Dissociation Molecular Dynamics Simulations of Lithium Formate Ionic Clusters.

Molecular dynamics (MD) simulations are well positioned to elucidate the aspects of electrospray ionization (ESI) and high-energy collision dissociation (HCD), as well as give insight into processes that involve neutral species that cannot be observed experimentally in ESI, HCD, and collision-induced dissociation (CID). Here, we utilize temperature dissociation molecular dynamics (TDMD) to model the HCD/CID of lithium formate clusters carrying a single positive charge. These simulations successfully reproduce the experimental ESI HCD spectra of lithium formate solutions and also support the existence of magic number clusters (MNCs) that have been observed. The simulations also provide strong evidence that the main fragmentation channel of such clusters involves neutral (LiHCOO)2 dimers.

Characterizing the Tautomers of Protonated Aniline Using Differential Mobility Spectrometry and Mass Spectrometry.

The site of protonation for gas-phase aniline has been debated for many years, with many research groups contributing experimental and computational evidence for either the amino-protonated or the para-carbon-protonated tautomer as the gas-phase global minimum structure. Here, we employ differential mobility spectrometry (DMS) and mass spectrometry (MS) to separate and characterize the amino-protonated (N-protonated) and para-carbon-protonated ( p-protonated) tautomers of aniline. We demonstrate that upon electrospray ionization (ESI), aniline is protonated predominantly at the amino position. Similar analyses are conducted on another three isotopically labeled forms of aniline to confirm our structural assignments. We observe a significant reduction of the relative population of the p-protonated tautomer when a protic ESI solvent is employed (methanol/water) compared to when an aprotic solvent (acetonitrile) is employed. We also observe conversion of the p-protonated species into the N-protonated species upon clustering with protic solvent vapor post-DMS selection-a finding supported by previous experimental data acquired using DMS-MS.

Developments in FTICR-MS and Its Potential for Body Fluid Signatures.

Fourier transform mass spectrometry (FTMS) is the method of choice for measurements that require ultra-high resolution. The establishment of Fourier transform ion cyclotron resonance (FTICR) MS, the availability of biomolecular ionization techniques and the introduction of the Orbitrap™ mass spectrometer have widened the number of FTMS-applications enormously. One recent example involves clinical proteomics using FTICR-MS to discover and validate protein biomarker signatures in body fluids such as serum or plasma. These biological samples are highly complex in terms of the type and number of components, their concentration range, and the structural identity of each species, and thus require extensive sample cleanup and chromatographic separation procedures. Clearly, such an elaborate and multi-step sample preparation process hampers high-throughput analysis of large clinical cohorts. A final MS read-out at ultra-high resolution enables the analysis of a more complex sample and can thus simplify upfront fractionations. To this end, FTICR-MS offers superior ultra-high resolving power with accurate and precise mass-to-charge ratio (m/z) measurement of a high number of peptides and small proteins (up to 20 kDa) at isotopic resolution over a wide mass range, and furthermore includes a wide variety of fragmentation strategies to characterize protein sequence and structure, including post-translational modifications (PTMs). In our laboratory, we have successfully applied FTICR "next-generation" peptide profiles with the purpose of cancer disease classifications. Here we will review a number of developments and innovations in FTICR-MS that have resulted in robust and routine procedures aiming for ultra-high resolution signatures of clinical samples, exemplified with state-of-the-art examples for serum and saliva.

Lithium formate ion clusters formation during electrospray ionization: Evidence of magic number clusters by mass spectrometry and ab initio calculations.

Small cationic and anionic clusters of lithium formate were generated by electrospray ionization and their fragmentations were studied by tandem mass spectrometry (collision-induced dissociation with N2). Singly as well as multiply charged clusters were formed in both positive and negative ion modes with the general formulae, (HCOOLi)nLi(+), (HCOOLi)nLim (m+), (HCOOLi)nHCOO(-), and (HCOOLi)n(HCOO)m (m-). Several magic number cluster (MNC) ions were observed in both the positive and negative ion modes although more predominant in the positive ion mode with (HCOOLi)3Li(+) being the most abundant and stable cluster ion. Fragmentations of singly charged positive clusters proceed first by the loss of a dimer unit ((HCOOLi)2) followed by the loss of monomer units (HCOOLi) although the former remains the dominant dissociation process. In the case of positive cluster ions, all fragmentations lead to the magic cluster (HCOOLi)3Li(+) as the most abundant fragment ion at higher collision energies which then fragments further to dimer and monomer ions at lower abundances. In the negative ion mode, however, singly charged clusters dissociated via sequential loss of monomer units. Multiply charged clusters in both positive and negative ion modes dissociated mainly via Coulomb repulsion. Quantum chemical calculations performed for smaller cluster ions showed that the trimer ion has a closed ring structure similar to the phenalenylium structure with three closed rings connected to the central lithium ion. Further additions of monomer units result in similar symmetric structures for hexamer and nonamer cluster ions. Thermochemical calculations show that trimer cluster ion is relatively more stable than neighboring cluster ions, supporting the experimental observation of a magic number cluster with enhanced stability.

Electron capture dissociation studies of the fragmentation patterns of doubly protonated and mixed protonated-sodiated peptoids.

The fragmentation patterns of a group of doubly protonated ([P + 2H](2+)) and mixed protonated-sodiated ([P + H + Na](2+)) peptide-mimicking oligomers, known as peptoids, have been studied using electron capturing dissociation (ECD) tandem mass spectrometry techniques. For all the peptoids studied, the primary backbone fragmentation occurred at the N-Cα bonds. The N-terminal fragment ions, the C-ions (protonated) and the C'-ions (sodiated) were observed universally for all the peptoids regardless of the types of charge carrier. The C-terminal ions varied depending on the type of charge carrier. The doubly protonated peptoids with at least one basic residue located at a position other than the N-terminus fragmented by producing the Z(•)-series of ions. In addition, most doubly protonated peptoids also produced the Y-series of ions with notable abundances. The mixed protonated-sodiated peptoids fragmented by yielding the Z(•)'-series of ions in addition to the C'-series. Chelation between the sodium cation and the amide groups of the peptoid chain might be an important factor that could stabilize both the N-terminal and the C-terminal fragment ions. Regardless of the types of the charge carrier, one notable fragmentation for all the peptoids was the elimination of a benzylic radical from the odd-electron positive ions of the protonated peptoids ([P + 2H](•+)) and the sodiated peptoids ([P + H + Na](•+)). The study showed potential utility of using the ECD technique for sequencing of peptoid libraries generated by combinatorial chemistry.

Chronic alcohol exposure disturbs lipid homeostasis at the adipose tissue-liver axis in mice: analysis of triacylglycerols using high-resolution mass spectrometry in combination with in vivo metabolite deuterium labeling.

A method of employing high-resolution mass spectrometry in combination with in vivo metabolite deuterium labeling was developed in this study to investigate the effects of alcohol exposure on lipid homeostasis at the white adipose tissue (WAT)-liver axis in a mouse model of alcoholic fatty liver. In order to differentiate the liver lipids synthesized from the fatty acids that were transported back from adipose tissue and the lipids synthesized from other sources of fatty acids, a two-stage mouse feeding experiment was performed to incorporate deuterium into metabolites. Hepatic lipids extracted from mouse liver, epididymal white adipose tissue (eWAT) and subcutaneous white adipose tissue (sWAT) were analyzed. It was found that 13 and 10 triacylglycerols (TGs) incorporated with a certain number of deuterium were significantly increased in alcohol induced fatty liver at two and four weeks of alcohol feeding periods, respectively. The concentration changes of these TGs ranged from 1.7 to 6.3-fold increase. A total of 14 deuterated TGs were significantly decreased in both eWAT and sWAT at the two and four weeks and the fold-change ranged from 0.19 to 0.77. The increase of deuterium incorporated TGs in alcohol-induced fatty liver and their decrease in both eWAT and sWAT indicate that alcohol exposure induces hepatic influx of fatty acids which are released from WATs. The results of time course analysis further indicate a mechanistic link between adipose fat loss and hepatic fat gain in alcoholic fatty liver.

Fragmentation of oxime and silyl oxime ether odd-electron positive ions by the McLafferty rearrangement: new insights on structural factors that promote α,ß fragmentation.

The McLafferty rearrangement is an extensively studied fragmentation reaction for the odd-electron positive ions from a diverse range of functional groups and molecules. Here, we present experimental and theoretical results of 12 model compounds that were synthesized and investigated by GC-TOF MS and density functional theory calculations. These compounds consisted of three main groups: carbonyls, oximes and silyl oxime ethers. In all electron ionization mass spectra, the fragment ions that could be attributed to the occurrence of a McLafferty rearrangement were observed. For t-butyldimethylsilyl oxime ethers with oxygen in a ß-position, the McLafferty rearrangement was accompanied by loss of the t-butyl radical. The various mass spectra showed that the McLafferty rearrangement is relatively enhanced compared with other primary fragmentation reactions by the following factors: oxime versus carbonyl, oxygen versus methylene at the ß-position and ketone versus aldehyde. Calculations predict that the stepwise mechanism is favored over the concerted mechanism for all but one compound. For carbonyl compounds, C-C bond breaking was the rate-determining step. However, for both the oximes and t-butyldimethylsilyl oxime ethers with oxygen at the ß-position, the hydrogen transfer step was rate limiting, whereas with a CH(2) group at the ß-position, the C-C bond breaking was again rate determining. n-Propoxy-acetaldehyde, bearing an oxygen atom at the ß-position, is the only case that was predicted to proceed through a concerted mechanism. The synthesized oximes exist as both the (E)- and (Z)-isomers, and these were separable by GC. In the mass spectra of the two isomers, fragment ions that were generated by the McLafferty rearrangement were observed. Finally, fragment ions corresponding to the McLafferty reverse charge rearrangement were observed for all compounds at varying relative ion intensities compared with the conventional McLafferty rearrangement.

MetSign: a computational platform for high-resolution mass spectrometry-based metabolomics.

Data analysis in metabolomics is currently a major challenge, particularly when large sample sets are analyzed. Herein, we present a novel computational platform entitled MetSign for high-resolution mass spectrometry-based metabolomics. By converting the instrument raw data into mzXML format as its input data, MetSign provides a suite of bioinformatics tools to perform raw data deconvolution, metabolite putative assignment, peak list alignment, normalization, statistical significance tests, unsupervised pattern recognition, and time course analysis. MetSign uses a modular design and an interactive visual data mining approach to enable efficient extraction of useful patterns from data sets. Analysis steps, designed as containers, are presented with a wizard for the user to follow analyses. Each analysis step might contain multiple analysis procedures and/or methods and serves as a pausing point where users can interact with the system to review the results, to shape the next steps, and to return to previous steps to repeat them with different methods or parameter settings. Analysis of metabolite extract of mouse liver with spiked-in acid standards shows that MetSign outperforms the existing publically available software packages. MetSign has also been successfully applied to investigate the regulation and time course trajectory of metabolites in hepatic liver.

iMatch: a retention index tool for analysis of gas chromatography-mass spectrometry data.

A method was developed to employ National Institute of Standards and Technology (NIST) 2008 retention index database information for molecular retention matching via constructing a set of empirical distribution functions (DFs) of the absolute retention index deviation to its mean value. The effects of different experimental parameters on the molecules' retention indices were first assessed. The column class, the column type, and the data type have significant effects on the retention index values acquired on capillary columns. However, the normal alkane retention index (I(norm)) with the ramp condition is similar to the linear retention index (I(T)), while the I(norm) with the isothermal condition is similar to the Kováts retention index (I). As for the I(norm) with the complex condition, these data should be treated as an additional group, because the mean I(norm) value of the polar column is significantly different from the I(T). Based on this analysis, nine DFs were generated from the grouped retention index data. The DF information was further implemented into a software program called iMatch. The performance of iMatch was evaluated using experimental data of a mixture of standards and metabolite extract of rat plasma with spiked-in standards. About 19% of the molecules identified by ChromaTOF were filtered out by iMatch from the identification list of electron ionization (EI) mass spectral matching, while all of the spiked-in standards were preserved. The analysis results demonstrate that using the retention index values, via constructing a set of DFs, can improve the spectral matching-based identifications by reducing a significant portion of false-positives.

A method of calculating the second dimension retention index in comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry.

A method was developed to calculate the second dimension retention index of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) data using n-alkanes as reference compounds. The retention times of the C(7)-C(31) alkanes acquired during 24 isothermal experiments cover the 0-6s retention time area in the second dimension retention time space, which makes it possible to calculate the retention indices of target compounds from the corresponding retention time values without the extension of the retention space of the reference compounds. An empirical function was proposed to show the relationship among the second dimension retention time, the temperature of the second dimension column, and the carbon number of the n-alkanes. The proposed function is able to extend the second dimension retention time beyond the reference n-alkanes by increasing the carbon number. The extension of carbon numbers in reference n-alkanes up to two more carbon atoms introduces <10 retention index units (iu) of deviation. The effectiveness of using the proposed method was demonstrated by analyzing a mixture of compound standards in temperature programmed experiments using 6 different initial column temperatures. The standard deviation of the calculated retention index values of the compound standards fluctuated from 1 to 12 iu with a mean standard deviation of 5 iu.

Unexpected linear ion trap collision-induced dissociation and Fourier transform ion cyclotron resonance infrared multi-photon dissociation fragmentation of a hydrated C-glycoside of 5-fluorouridine formed by the action of the pseudouridine synthases RluA and TruB.

As part of the investigation of the pseudouridine synthases, 5-fluorouridine in RNA was employed as a mechanistic probe. The hydrated, rearranged product of 5-fluorouridine was isolated as part of a dinucleotide and found to undergo unusual fragmentation during mass spectrometry, with the facile loss of HNCO from the product pyrimidine ring favored over phosphodiester bond rupture. Although the loss of HNCO from uridine and pseudouridine is well established, the pericyclic process leading to their fragmentation cannot operate with the saturated pyrimidine ring in the product of 5-fluorouridine. Based on the MS(n) results and calculations reported here, a new mechanism relying on the peculiar disposition of the functional groups of the product pyrimidine ring is proposed to account for the unusually facile fragmentation.

DISCO: distance and spectrum correlation optimization alignment for two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics.

A novel peak alignment algorithm using a distance and spectrum correlation optimization (DISCO) method has been developed for two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC/TOF-MS)-based metabolomics. This algorithm uses the output of the instrument control software, ChromaTOF, as its input data. It detects and merges multiple peak entries of the same metabolite into one peak entry in each input peak list. After a z-score transformation of metabolite retention times, DISCO selects landmark peaks from all samples based on both two-dimensional retention times and mass spectrum similarity of fragment ions measured by Pearson's correlation coefficient. A local linear fitting method is employed in the original two-dimensional retention time space to correct retention time shifts. A progressive retention time map searching method is used to align metabolite peaks in all samples together based on optimization of the Euclidean distance and mass spectrum similarity. The effectiveness of the DISCO algorithm is demonstrated using data sets acquired under different experiment conditions and a spiked-in experiment.

Using size exclusion chromatography-RPLC and RPLC-CIEF as two-dimensional separation strategies for protein profiling.

Bottom-up proteomics (analyzing peptides that result from protein digestion) has demonstrated capability for broad proteome coverage and good throughput. However, due to incomplete sequence coverage, this approach is not ideally suited to the study of modified proteins. The modification complement of a protein can best be elucidated by analyzing the intact protein. 2-DE, typically coupled with the analysis of peptides that result from in-gel digestion, is the most frequently applied protein separation technique in MS-based proteomics. As an alternative, numerous column-based liquid phase techniques, which are generally more amenable to automation, are being investigated. In this work, the combination of size-exclusion chromatography (SEC) fractionation with RPLC-Fourier-transform ion cyclotron resonance (FTICR)-MS is compared with the combination of RPLC fractionation with CIEF-FTICR-MS for the analysis of the Shewanella oneidensis proteome. SEC-RPLC-FTICR-MS allowed the detection of 297 proteins, as opposed to 166 using RPLC-CIEF-FTICR-MS, indicating that approaches based on LC-MS provide better coverage. However, there were significant differences in the sets of proteins detected and both approaches provide a basis for accurately quantifying changes in protein and modified protein abundances.

Characterization of purified c-type heme-containing peptides and identification of c-type heme-attachment sites in Shewanella oneidenis cytochromes using mass spectrometry.

We describe methods for mass spectrometric identification of heme-containing peptides from c-type cytochromes that contain the CXXCH (X=any amino acid) sequence motif. The heme fragment ion yielded the most abundant MS/MS peak for standard heme-containing peptides with one amino acid difference for both 2+ and 3+ peptide charge states; both sequence and charge affect the extent of heme loss. Application to Shewanella oneidenis demonstrated the utility of this approach for identifying c-type heme-containing peptides from complex proteome samples.

Automatic gain control in mass spectrometry using a jet disrupter electrode in an electrodynamic ion funnel.

We report on the use of a jet disrupter electrode in an electrodynamic ion funnel as an electronic valve to regulate the intensity of the ion beam transmitted through the interface of a mass spectrometer in order to perform automatic gain control (AGC). The ion flux is determined by either directly detecting the ion current on the conductance limiting orifice of the ion funnel or using a short mass spectrometry acquisition. Based upon the ion flux intensity, the voltage of the jet disrupter is adjusted to alter the transmission efficiency of the ion funnel to provide a desired ion population to the mass analyzer. Ion beam regulation by an ion funnel is shown to provide control to within a few percent of a targeted ion intensity or abundance. The utility of ion funnel AGC was evaluated using a protein tryptic digest analyzed with liquid chromatography Fourier transform ion cyclotron resonance (LC-FTICR) mass spectrometry. The ion population in the ICR cell was accurately controlled to selected levels, which improved data quality and provided better mass measurement accuracy.

Targeted comparative proteomics by liquid chromatography-tandem Fourier ion cyclotron resonance mass spectrometry.

In proteomics, effective methods are needed for identifying the relatively limited subset of proteins displaying significant changes in abundance between two samples. One way to accomplish this task is to target for identification by MS/MS only the "interesting" proteins based on the abundance ratio of isotopically labeled pairs of peptides. We have developed the software and hardware tools for online LC-FTICR MS/MS studies in which a set of initially unidentified peptides from a proteome analysis can be selected for identification based on their distinctive changes in abundance following a "perturbation". We report here the validation of this method using a mixture of standard proteins combined in different ratios after isotopic labeling. We also demonstrate the application of this method to the identification of Shewanella oneidensis peptides/proteins exhibiting differential abundance in suboxic versus aerobic cell cultures.