Complex Sample Mixtures Research Articles

Comprehensive reversed-phase×chiral two-dimensional liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry with post-first dimension flow splitting for untargeted enantioselective amino acid analysis.

This work describes a comprehensive achiral × chiral two-dimensional liquid chromatography separation for enantioselective amino acid analysis coupled to electrospray ionization-tandem mass spectrometry detection using data-independent acquisition. Flow splitting after the first and second dimension separation was utilized for volumetric flow reduction and for enabling a multi-detector approach (with ultraviolet, fluorescence, charged aerosol, and MS detection), respectively. Derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate provided a chromophore, a fluorophore, and an efficient mass tag for efficient ionization in positive electrospray ionization-mass spectrometry. Chiral columns often have limitations in terms of their chemoselectivity, which may be a problem when complex sample mixtures with structurally related compounds need to be separated. It can be alleviated by a reversed-phase×chiral two-dimensional-liquid chromatography setup, in which the first dimension provides the chemoselectivity and a chiral tandem column constituted of quinine-carbamate derived weak anion-exchanger and zwitterionic ion-exchanger in the second dimension separation of D- and L-amino acid enantiomers. The method was used to control the stereointegrity of the therapeutic peptide octreotide. After hydrolysis, all amino acid constituents were detected with the correct configuration and composition. Some options for flow splitting and integration of destructive detectors in the first dimension separation are outlined.

Comparative Analysis of Cell Mixtures Deconvolution and Gene Signatures Generated for Blood, Immune and Cancer Cells

In the last two decades, many detailed full transcriptomic studies on complex biological samples have been published and included in large gene expression repositories. These studies primarily provide a bulk expression signal for each sample, including multiple cell-types mixed within the global signal. The cellular heterogeneity in these mixtures does not allow the activity of specific genes in specific cell types to be identified. Therefore, inferring relative cellular composition is a very powerful tool to achieve a more accurate molecular profiling of complex biological samples. In recent decades, computational techniques have been developed to solve this problem by applying deconvolution methods, designed to decompose cell mixtures into their cellular components and calculate the relative proportions of these elements. Some of them only calculate the cell proportions (supervised methods), while other deconvolution algorithms can also identify the gene signatures specific for each cell type (unsupervised methods). In these work, five deconvolution methods (CIBERSORT, FARDEEP, DECONICA, LINSEED and ABIS) were implemented and used to analyze blood and immune cells, and also cancer cells, in complex mixture samples (using three bulk expression datasets). Our study provides three analytical tools (corrplots, cell-signature plots and bar-mixture plots) that allow a thorough comparative analysis of the cell mixture data. The work indicates that CIBERSORT is a robust method optimized for the identification of immune cell-types, but not as efficient in the identification of cancer cells. We also found that LINSEED is a very powerful unsupervised method that provides precise and specific gene signatures for each of the main immune cell types tested: neutrophils and monocytes (of the myeloid lineage), B-cells, NK cells and T-cells (of the lymphoid lineage), and also for cancer cells.

The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis

Resolving complex sample mixtures by liquid chromatography in a single run is challenging. The so-called mixed-mode liquid chromatography (MMLC) which combines several retention mechanisms within a single column, can provide resource-efficient separation of solutes of diverse nature. The Acclaim Mixed-Mode WCX-1 column, encompassing hydrophobic and weak cation exchange interactions, was employed for the analysis of small drug molecules. The stationary phase's interaction abilities were assessed by analysing molecules of different ionisation potentials. Mixed Quantitative Structure-Retention Relationship (QSRR) models were developed for revealing significant experimental parameters (EPs) and molecular features governing molecular retention. According to the plan of Face-Centred Central Composite Design, EPs (column temperature, acetonitrile content, pH and buffer concentration of aqueous mobile phase) variations were included in QSRR modelling. QSRRs were developed upon the whole data set (global model) and upon discrete parts, related to similarly ionized analytes (local models) by applying gradient boosted trees as a regression tool. Root mean squared errors of prediction for global and local QSRR models for cations, anions and neutrals were respectively 0.131; 0.105; 0.102 and 0.042 with the coefficient of determination 0.947; 0.872; 0.954 and 0.996, indicating satisfactory performances of all models, with slightly better accuracy of local ones. The research showed that influences of EPs were dependant on the molecule's ionisation potential. The molecular descriptors highlighted by models pointed out that electrostatic and hydrophobic interactions and hydrogen bonds participate in the retention process. The molecule's conformation significance was evaluated along with the topological relationship between the interaction centres, explicitly determined for each molecular species through local models. All models showed good molecular retention predictability thus showing potential for facilitating the method development.

A Pure Shift-Based Nuclear Magnetic Resonance Method for In-Phase Three-Dimensional Diffusion-Ordered Spectroscopy.

Diffusion-ordered nuclear magnetic resonance spectroscopy (DOSY) plays a vital role in mixture studies. However, its applications to complex mixture samples are generally limited by spectral congestion along the chemical shift domain caused by extensive J coupling networks and abundant compounds. Herein, we develop the in-phase multidimensional DOSY strategy for complex mixture analyses by simultaneously revealing molecular self-diffusion behaviors and multiplet structures with optimal spectral resolution. As a proof of concept, two pure shift-based three-dimensional (3D) DOSY protocols are proposed to record high-resolution 3D spectroscopic view with separated mixture components and their resolved multiplet coupling structures, thus suitable for analyzing complex mixtures that contain abundant compounds and complicated molecular structures, even under adverse magnetic field conditions. Therefore, this study shows a promising tool for component analyses and multiplet structure studies on practical mixture samples.

Kinetics in DMS: Modeling Clustering and Declustering Reactions.

Differential mobility spectrometry (DMS) uses high-frequency oscillating electrical fields to harness the differential mobility of ions for separating complex sample mixtures prior to detection. To increase the resolving power, a dynamic microsolvation environment is often created by introducing solvent vapors. Here, relatively large clusters are formed at low-field conditions which then evaporate to form smaller clusters at high-field conditions. The kinetics of these processes as the electrical field strength oscillates are not well studied. Here, we develop a computational framework to investigate how the different reactions (cluster association, cluster dissociation, and fast conformational changes) behave at different field strengths. We aim to better understand these processes, their effect on experimental outcomes, and whether DMS model accuracy is improved via incorporating their description. We find that cluster association and dissociation reactions for typical ion-solvent pairs are fast compared to the time scale of the varying separation fields usually used. However, low solvent concentration, small dipole moments, and strong ion-solvent binding can result in reaction rates small enough that a lag is observed in the ion's DMS response. This can yield differences of several volts in the compensation voltages required to correct ion trajectories for optimal transmission. We also find that the proposed kinetic approach yields generally better agreement with experiment than using a modified Boltzmann weighting scheme. Thus, this work provides insights into the chemical dynamics occurring within the DMS cell while also increasing the accuracy of dispersion plot predictions.

Differentiation and Quantitation of Coeluting Isomeric Amadori and Heyns Peptides Using Sugar-Specific Fragment Ion Ratios

d-glucose and d-fructose present in blood, tissues, and organs of all mammals can react with amino groups, leading to glucated (Amadori) and fructated (Heyns) products, i.e., proteins glycated at lysine residues. While typically present at low concentration in humans, metabolic diseases including diabetes elevate sugar levels, favoring glycation and consecutive reactions leading to advanced glycation end products (AGEs) linked to diabetic complications and cardiovascular diseases. Analytical methods able to differentiate and to individually quantify Amadori- and Heyns-modified proteins in complex sample mixtures, e.g., serum, are still very limited. Here, we show that the reported and supposedly specific neutral losses displayed in tandem mass spectra of Heyns peptides cannot be used for a reliable differentiation as they were also observed for Amadori peptides. However, the combination of several neutral loss signals in fragment ion ratios at both precursor and fragment ion signals allowed the differentiation and relative quantitation of coeluting isomeric Amadori and Heyns peptides at different concentrations and peptide ratios. This was also true for digested human plasma. Thus, the presented strategy allows the quantitation of Amadori and Heyns peptides in complex samples, especially by spiking isotope-labeled peptides. This will allow searching for glucated and fructated biomarkers in clinical samples.

The multifaceted roles of mass spectrometric analysis in nucleic acids drug discovery and development.

The deceptively simple concepts of mass determination and fragment analysis are the basis for the application of mass spectrometry (MS) to a boundless range of analytes, including fundamental components and polymeric forms of nucleic acids (NAs). This platform affords the intrinsic ability to observe first-hand the effects of NA-active drugs on the chemical structure, composition, and conformation of their targets, which might affect their ability to interact with cognate NAs, proteins, and other biomolecules present in a natural environment. The possibility of interfacing with high-performance separation techniques represents a multiplying factor that extends these capabilities to cover complex sample mixtures obtained from organisms that were exposed to NA-active drugs. This report provides a brief overview of these capabilities in the context of the analysis of the products of NA-drug activity and NA therapeutics. The selected examples offer proof-of-principle of the applicability of this platform to all phases of the journey undertaken by any successful NA drug from laboratory to bedside, and provide the rationale for its rapid expansion outside traditional laboratory settings in support to ever growing manufacturing operations.

How to read and Interpret GC/MS Spectra

Gas chromatography mass spectrometry (GC/MS) analysis is used as analytical tool for volatile and complex mixture samples. Its effectivity and sensitivity to detect the analyte components make it applicable in a wide range of purposes. This technique can be used to conduct quantitative as well as qualitative analysis. Unfortunately, very few, if there are, of publications dedicate the research to give an explanatory report using a step-by-step approach on how to read and interpret the analysis result. Thus, this study is aimed to fulfill the gap on bridging the spectra data output of GC/MS measurement into the light of easy way reading and interpreting its spectra. The research method used both library spectra matching and a priory spectra interpretation on chosen compound samples. The general guideline and application are discussed.

Separation of monomeric and dimeric phenolic compounds in lignosulphonate lignin on different stationary phases using ultrahigh-performance supercritical fluid chromatography

Lignin is a promising renewable resource and its valorization could help to reduce our dependency on fossil carbon resources. Especially the production of small molecular weight and economically valuable compounds, such as vanillin, are of interest. A good separation of the sample components is crucial for a confident identification of compounds in complex sample mixtures using for instance mass spectrometry. In this work, the resolving power and selectivity of five different stationary phases for ultrahigh-performance supercritical fluid chromatography were studied for the class separation of lignin monomers (LMs) and dimers (LDs). A separation of LMs and LDs will help to identify such compounds in complex technical lignin samples. It could be shown that stationary phases with both hydrogen-bonding acceptor and donator groups offer high overall resolving power, while π-π-interactions are advantageous for the separation of the two compound classes. An almost complete separation combined with an improved overall resolving power was achieved with the 1-aminoanthracene stationary phase, which offers both hydrogen-bonding interactions and π-π-interactions.

Application of the area correlation constraint in the MCR-ALS quantitative analysis of complex mixture samples

The application of the recently developed area correlation constraint in Multivariate CurveResolution–Alternating Least Squares (MCR-ALS) for the quantitative determination of analyte mixtures is shown. The feasibility of the proposed constraint is tested firstly for the calibration and quantitation of PAHs mixtures in their synthetic mixtures (validation samples) and in river water samples dissolved organic matter (DOM) using EEM fluorescent three-way data. In this case, MCR-ALS results obtained with the proposed area correlation constraint are comparable with the results obtained with methods based on the fulfillment of the trilinear model, like PARAFAC and MCR-ALS with the trilinearity constraint. Secondly, the possibility of applying this new area correlation constraint is extended to the analytical determination of lipid mixtures in synthetic and cell culture samples by LC-MS, where the trilinear model does not hold. The applicability of the proposed area correlation constraint is assessed, and it is proposed as a general tool for the quantitative determination of unknown mixtures of analytes in complex natural samples with severe profile overlapping and unknown composition, whatever the data structure is.

A new scattering correction method of different spectroscopic analysis for assessing complex mixtures

Physical properties such as particle size distribution and compactness have significant confounding effects on the spectral signals of complex mixtures, which multivariate linear calibration methods such as partial least-squares (PLS) cannot effectively model or correct. Therefore, these effects significantly deteriorate calibration models’ predictive abilities for spectral quantitative analysis of complex mixtures. Here, new scattering correction methods were proposed to estimate the additive and multiplicative parameters considering light scattering effects in each spectrum and hence mitigate the detrimental influence of additive and multiplicative effects on quantitative spectroscopic analysis of complex mixtures. Three different correction methods were proposed to estimate the addition coefficient based on two different underlying assumptions, namely, whether this coefficient is related to the wavelength. After addition coefficient elimination, the multiplicative parameter can be eliminated by a simple but very efficient spectral ratio method. Furthermore, linear models are built with key variables, and the predictive performance of these models is verified using the root-mean-square error of prediction datasets. The proposed methods were tested on one apple data set and two publicly available benchmark datasets (i.e., near-infrared spectral data of meat and powder mixture samples) and compared with some existing correction methods. The results showed that (1) additive effects of different types of samples can be eliminated by different methods and (2) these methods can appreciable improve quantitative spectroscopic analysis of complex mixture samples. This study indicates that accurate quantitative spectroscopic analysis of complex mixtures can be achieved through the combination of additive effect elimination and the spectral ratio method.

Highly selective ratiometric electrogenerated chemiluminescence assay of DNA methyltransferase activity via polyaniline and anti-fouling peptide modified electrode

In this work, an antifouling electrochemiluminescent (ECL) ratiometric biosensor is designed for the accurate, selective and sensitive detection of DNA methyltransferase (MTase) activity based on a dual-signaling strategy. Briefly, an ITO electrode is used to construct the anti-fouling interfaces with the modification of polyaniline (PANI), AuNPs and peptide. Hairpin DNA molecules containing the symmetric sequence of 5′-CATC-3′ are attached onto the modified ITO electrode and the ds-DNA can be cut off in the presence of Dam MTase and DpnI. The residual DNA and two hairpin DNA could lead to the extension of ds-DNA due to the Hybridization Chain Reaction (HCR). ECL signal is amplified significantly with the insertion of PTC-NH2 molecules into the dsDNA grooves. The ECLPTC-NH2/ECLAu@luminol is found in a logarithmic linear relation with the concentration of Dam MTase. Moreover, owing to the presence of antifouling peptide on the sensing interface, the ECL biosensor was capable of sensing MTase activity in complex biological media, such as FBS samples and human serum with significantly reduced nonspecific adsorption effect. Assaying Dam MTase in complex sample mixture containing 5% calf serum and 5% human serum further proved the feasibility of this ECL biosensor for early clinical diagnosis.

Fast online two-dimensional analysis of monoterpenes using multi-capillary column high-pressure photoionization time-of-flight mass spectrometry

One of the most abundant biological volatile organic compounds (BVOCs) in the atmosphere, monoterpene, is characterized by its short lifetime, low concentration, fast temporal and spatial variations, and wide variety of isomers. In this study, a multi-capillary column (MCC) was combined with high-pressure photoionization time-of-flight mass spectrometry (HPPI-TOF MS) and employed to develop an MCC-HPPI-TOF MS combination instrument as an online two-dimensional gas chromatography-mass spectrometry (GC-MS) method for the rapid qualitative and quantitative analysis of monoterpene isomers. As a result, six monoterpene isomers, α -pinene, β -pinene, α -terpinene, γ -terpinene, 3-carene, and limonene, were successfully isolated in 180 s with limits of detection (LODs) as low as 6 μg/m3 without sample pre-enrichment. This method was successfully applied to the rapid online analysis of monoterpenes released from the branches and leaves of Cedrus atlantica and Sabina chinensis, which shows the capability and potential application of the method for the online detection of complex sample mixtures in environmental monitoring, process analysis, and other fields.

Extraction, Enrichment, and in situ Electrochemical Detection on Lab-on-a-Disc: Monitoring the Production of a Bacterial Secondary Metabolite.

Development of microsystems, which enable "sample-to-answer" detection from real samples, is often challenging. We present the first integration of supported liquid membrane extraction combined with electrochemical detection on a centrifugal fluidic platform. The developed lab-on-a-disc (LoD) system enabled the separation, enrichment, and subsequent electrochemical detection of the target analyte from a complex sample mixture. As a case study, we quantified the amount of a dietary supplement and pharmaceutical precursor, p-coumaric acid, from bacterial growth media at different time points during production. The assay, extraction, and detection, performed on the LoD device, proved to be a low cost and environmentally friendly approach, requiring only a few tens of microliters of organic solvent and enabled detection in a 3 μL volume. In addition, the data obtained from the centrifugal platform showed a good correlation with data obtained from the high performance liquid chromatography analysis.

Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins.

Quantitative proteomics has been extensively applied in the screening of differentially regulated proteins in various research areas for decades, but its sensitivity and accuracy have been a bottleneck for many applications. Every step in the proteomics workflow can potentially affect the quantification of low-abundance proteins, but a systematic evaluation of their effects has not been done yet. In this work, to improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multiparameter optimization was carried out using a complex 2-proteome artificial sample mixture for a series of steps from sample preparation to data analysis, including the desalting of peptides, peptide injection amount for LC-MS/MS, MS1 resolution, the length of LC-MS/MS gradient, AGC targets, ion accumulation time, MS2 resolution, precursor coisolation threshold, data analysis software, statistical calculation methods, and protein fold changes, and the best settings for each parameter were defined. The suitable cutoffs for detecting low-abundance proteins with at least 1.5-fold and 2-fold changes were identified for label-free and TMT methods, respectively. The use of optimized parameters will significantly improve the overall performance of quantitative proteomics in quantifying low-abundance proteins and thus promote its application in other research areas.

Methodical studies of the simultaneous determination of anions and cations by IC×CE-MS using arsenic species as model analytes.

The separation of the constituents of complex sample mixtures is a challenging task in analytical chemistry. Multidimensional separation systems are widely used to enhance the peak capacity. The comprehensive hyphenation of ion chromatography (IC) and capillary electrophoresis (CE) is promising because the two most important instrumental techniques in ion analysis are combined. In this report a new configuration for capillary anion chromatography is presented enabling the simultaneous IC×CE analysis of anions and cations using a switching valve. Electrospray ionization mass spectrometry (MS) was used for detection. A mixture of organic and inorganic arsenic species served as a model system. The coupling of anion chromatography to CE-MS was done via a modulator enabling periodical injections of the IC effluent into the CE. The injection parameters of the modulator were studied taking into account the complex transport situation. Graphical abstract ᅟ.

Portable combination of Fourier transform infrared spectroscopy and differential mobility spectrometry for advanced vapor phase analysis.

Designing mobile devices for the analysis of complex sample mixtures containing a variety of analytes at different concentrations across a large dynamic range remains a challenging task in many analytical scenarios. To meet this challenge, a compact hybrid analytical platform has been developed combining Fourier transform infrared spectroscopy based on substrate-integrated hollow waveguides (iHWG-FTIR) with gas chromatography coupled differential mobility spectrometry (GC-DMS). Due to the complementarity of these techniques regarding analyte type and concentration, their combination provides a promising tool for the detection of complex samples containing a broad range of molecules at different concentrations. To date, the combination of infrared spectroscopy and ion mobility techniques remains expensive and bound to a laboratory utilizing e.g. IMS as prefilter or IR as ionization source. In the present study, a cost-efficient and portable solution has been developed and characterized representing the first truly hyphenated IR-DMS system. As a model analyte mixture, 5 ppm isopropylmercaptan (IPM) in methane (CH4) were diluted, and the concentration-dependent DMS signal of IPM along with the concentration-dependent IR signal of CH4 were recorded for all three hybrid IR-DMS systems. While guiding the sample through the iHWG-FTIR or the GC-DMS first did not affect the obtained signals, optimizing the IR data acquisition parameters did benefit the analytical results.

Direct Competitive Enzyme-Linked Immunosorbent Assay (ELISA).

The competitive enzyme-linked immunosorbent assay (ELISA) (cELISA; also called an inhibition ELISA) is designed so that purified antigen competes with antigen in the test sample for binding to an antibody that has been immobilized in microtiter plate wells. The same concept works if the immobilized molecule is antigen and the competing molecules are purified labeled antibody versus antibody in a test sample. Direct cELISAs incorporate labeled antigen or antibody, whereas indirect assay configurations use reporter-labeled secondary antibodies. The cELISA is very useful for determining the concentration of small-molecule antigens in complex sample mixtures. In the direct cELISA, antigen-specific capture antibody is adsorbed onto the microtiter plate before incubation with either known standards or unknown test samples. Enzyme-linked antigen (i.e., labeled antigen) is also added, which can bind to the capture antibody only when the antibody's binding site is not occupied by either the antigen standard or antigen in the test samples. Unbound labeled and unlabeled antigens are washed away and substrate is added. The amount of antigen in the standard or the test sample determines the amount of reporter-labeled antigen bound to antibody, yielding a signal that is inversely proportional to antigen concentration within the sample. Thus, the higher the antigen concentration in the test sample, the less labeled antigen is bound to the capture antibody, and hence the weaker is the resultant signal.

Label-Free Discovery Array Platform for the Characterization of Glycan Binding Proteins and Glycoproteins.

The identification of carbohydrate-protein interactions is central to our understanding of the roles of cell-surface carbohydrates (the glycocalyx), fundamental for cell-recognition events. Therefore, there is a need for fast high-throughput biochemical tools to capture the complexity of these biological interactions. Here, we describe a rapid method for qualitative label-free detection of carbohydrate-protein interactions on arrays of simple synthetic glycans, more complex natural glycosaminoglycans (GAG), and lectins/carbohydrate binding proteins using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. The platform can unequivocally identify proteins that are captured from either purified or complex sample mixtures, including biofluids. Identification of proteins bound to the functionalized array is achieved by analyzing either the intact protein mass or, after on-chip proteolytic digestion, the peptide mass fingerprint and/or tandem mass spectrometry of selected peptides, which can yield highly diagnostic sequence information. The platform described here should be a valuable addition to the limited analytical toolbox that is currently available for glycomics.

Fast identification of microplastics in complex environmental samples by a thermal degradation method

In order to determine the relevance of microplastic particles in various environmental media, comprehensive investigations are needed. However, no analytical method exists for fast identification and quantification. At present, optical spectroscopy methods like IR and RAMAN imaging are used. Due to their time consuming procedures and uncertain extrapolation, reliable monitoring is difficult. For analyzing polymers Py-GC-MS is a standard method. However, due to a limited sample amount of about 0.5 mg it is not suited for analysis of complex sample mixtures like environmental samples. Therefore, we developed a new thermoanalytical method as a first step for identifying microplastics in environmental samples. A sample amount of about 20 mg, which assures the homogeneity of the sample, is subjected to complete thermal decomposition. The specific degradation products of the respective polymer are adsorbed on a solid-phase adsorber and subsequently analyzed by thermal desorption gas chromatography mass spectrometry. For certain identification, the specific degradation products for the respective polymer were selected first. Afterwards real environmental samples from the aquatic (three different rivers) and the terrestrial (bio gas plant) systems were screened for microplastics. Mainly polypropylene (PP), polyethylene (PE) and polystyrene (PS) were identified for the samples from the bio gas plant and PE and PS from the rivers. However, this was only the first step and quantification measurements will follow.