Evaluation of Analyte Transfer between Microfluidic Droplets by Mass Spectrometry.

Droplet microfluidics enables high-throughput experimentation and screening by encapsulating chemical and biochemical samples in aqueous droplets segmented by an immiscible fluid. In such experiments, it is critical that each droplet remains chemically distinct. A common approach is to use fluorinated oils with surfactants to stabilize droplets. However, some small molecules have been observed to transport between droplets under these conditions. Attempts to study and mitigate this effect have relied on evaluating crosstalk using fluorescent molecules, which inherently limits the analyte scope and conclusions drawn about the mechanism of the effect. In this work, transport of low molecular weight compounds between droplets was investigated using electrospray ionization mass spectrometry (ESI-MS) for measurement. The use of ESI-MS significantly expands the scope of analytes that can be tested. We tested 36 structurally diverse analytes that were found to exhibit crosstalk ranging from negligible to complete transfer using HFE 7500 as the carrier fluid and 008-fluorosurfactant as a surfactant. Using this data set, we developed a predictive tool showing that high log P and log D values correlate with high crosstalk, and high polar surface area and log S correlate with low crosstalk. We then investigated several carrier fluids, surfactants, and flow conditions. It was discovered that transport is strongly dependent on all of these factors and that experimental design and surfactant tailoring can reduce carryover. We present evidence for mixed crosstalk mechanisms including both micellar and oil partitioning transfer. By understanding the driving mechanisms, surfactant and oil compositions can be designed to better reduce chemical transport for screening workflows.

Recent advances in miniaturization of portable liquid chromatography with emphasis on detection.

Liquid chromatography is a prominent analytical technique in separation science and chemical analysis, applied across numerous fields of research and within industrial applications. Over the past few decades, there has been a growing interest in the miniaturization of this technique, which has been particularly enabled through new miniature and portable detection technologies for in-field, at-site, and point-of-need (collectively 'out-of-lab') analyses. Accordingly, significant advances have been made in recent years in the development of miniaturized liquid chromatography with photometric, electrochemical, and mass spectrometric detection, enabling the development of field-deployable and portable instruments for various applications. Herein, recent developments in the miniaturization of detection systems for inclusion within, and/or coupling with, portable liquid chromatographic systems, are reviewed in detail together with critical comments and expected future trends in this area.

Small-Footprint, Field-Deployable LC/MS System for On-Site Analysis of Per- and Polyfluoroalkyl Substances in Soil.

Per- and polyfluoroalkyl substances (PFASs) are emerging environmental pollutants of global concern. For rapid field site evaluation, there are very few sensitive, field-deployable analytical techniques. In this work, a portable lightweight capillary liquid chromatography (capLC) system was coupled with a small footprint portable mass spectrometer and configured for field-based applications. Further, an at-site ultrasound-assisted extraction (pUAE) methodology was developed and applied with a portable capLC/mass spectrometry (MS) system for on-site analysis of PFASs in real soil samples. The influential variables on the integration of capLC with MS and on the resolution and signal intensity of the capLC/MS setup were investigated. The important parameters affecting the efficiency of the pUAE method were also studied and optimized using the response surface methodology based on a central composite design. The mean recovery for 11 PFASs ranged between 70 and 110%, with relative standard deviations ranging from 3 to 12%. In-field method sensitivity for 12 PFASs ranged from 0.6 to 0.1 ng/g, with wide dynamic ranges (1-600 ng/g) and excellent linearities (R2 > 0.991). The in-field portable system was benchmarked against a commercial lab-based LC-tandem MS (MS/MS) system for the analysis of PFASs in real soil samples, with the results showing good agreement. When deployed to a field site, 12 PFASs were detected and identified in real soil samples at concentrations ranging from 8.1 ng/g (for perfluorooctanesulfonic acid) to 2935.0 ng/g (perfluorohexanesulfonic acid).

Miniature Multiwavelength Deep UV-LED-Based Absorption Detection System for Capillary LC.

A new miniature deep UV absorbance detector has been developed using low-cost and high-performance LEDs, which can be operated in both scanning (230 to 300 nm) and individual wavelength (240, 255, and 275 nm) detection modes. The detector is mostly composed of off-the-shelf components, such as LEDs, trifurcated fiber optic assembly, a capillary Z-type flow cell, and photodiodes. It has been characterized for use with a standard capillary LC system and was benchmarked against a standard variable wavelength capillary LC detector. The detector shows very low levels of stray light (<0.4%), utilization of up to 99.0% of the effective path length of the flow cell, a wide dynamic range (0.5 to 200 µg/mL for sulfamethazine, carbamazepine, and flavone), and low noise levels (at 300 µAU level). The detector was applied within a miniaturized LC system.

3D Printed Liquid Cooling Interface for a Deep-UV-LED-Based Flow-Through Absorbance Detector.

Ultraviolet (UV)-light-emitting diodes (LEDs) are now widely used in analytical absorbance-based detectors; as compared to conventional UV lamps, they offer lower cost, faster response time, and higher photon conversion efficiency. However, current generation deep-UV-LEDs produce excess heat when operated at normal operating currents, which affects output stability and reduces their overall performance and lifespan. Herein a 3D printed liquid cooling interface has been developed for a deep-UV-LED-based optical detector, for capillary format flow-through detection. The interface consists of a circular channel that is tightly wrapped around the LED to provide active liquid cooling. The design also facilitates easy plug-and-play assembly of the various essential components of the detector: specifically, a 255 nm UV-LED, a capillary Z-cell, and a broadband UV photodiode (PD). The unique liquid cooling interface improved the performance of the detector by reducing the LED temperature up to 22 °C, increasing the spectral output up to 34%, decreasing the required stabilization time by up to 6-fold, and reducing the baseline noise and limits of detection (LODs) by a factor of 2. The detector was successfully used within a capillary HPLC system and could offer a miniaturized, rapidly stabilized, highly sensitive, and low-cost alternative to conventional UV detectors.

Retention prediction using quantitative structure-retention relationships combined with the hydrophobic subtraction model in reversed-phase liquid chromatography.

The hydrophobic subtraction model (HSM) combined with quantitative structure-retention relationships (QSRR) methodology was utilized to predict retention times in reversed-phase liquid chromatography (RPLC). A selection of new analytes and new RPLC columns that had never been used in the QSRR modeling process were used to verify the proposed approach. This work is designed to facilitate early prediction of co-elution of analytes in pharmaceutical drug discovery applications where it is advantageous to predict whether impurities might be co-eluted with the active drug component. The QSRR models were constructed through partial least squares regression combined with a genetic algorithm (GA-PLS) which was employed as a feature selection method to choose the most informative molecular descriptors calculated using VolSurf+ software. The analyte hydrophobicity coefficient of the HSM was predicted for subsequent calculation of retention. Clustering approaches based on the local compound type and the local second dominant interaction were investigated to select the most appropriate training set of analytes from a larger database. Predicted retention times of five new compounds on five new RPLC C18 columns were compared with their measured retention times with percentage root-mean-square errors of 15.4 and 24.7 for the local compound type and local second dominant interaction clustering methods, respectively.

Recent advances in open tubular capillary liquid chromatography.

This review covers advances and applications of open tubular capillary liquid chromatography (OT-LC) over the period 2007-2018. Under the right conditions OT-LC columns have the potential to offer superior column efficiency, higher overall peak capacity, and higher column permeability compared to packed capillary and monolithic columns. However, such advantages are highly dependent upon column format and dimensions, and to date in liquid chromatography the advantages of open tubular format columns have been most widely discussed and applied in the field of proteomics. In this review we have focused on the wider variety of separation mechanisms and applications which can be achieved following the modification of the inner wall of the capillary with a thin-layer stationary phase. In particular the latest advances in stationary phase development and formation, together with new column formats and dimensions are reviewed. Detection options for OT-LC are also discussed and recent advances in this area highlighted. Finally, this review summarises existing applications of OT-LC and illustrates the future potential for this technique.

Membrane-Free Electrokinetic Device Integrated to Electrospray-Ionization Mass Spectrometry for the Simultaneous Removal of Sodium Dodecyl Sulfate and Enrichment of Peptides.

The removal of sodium dodecyl sulfate (SDS) in SDS-assisted proteomics with electrospray-ionization-mass-spectrometric (ESI-MS) analysis is an essential step in the analysis. Off-line state-of-the-art sample-preparation strategies can allow 100% removal of DS- and up to 100% peptide recoveries. These strategies, however, are typically laborious and require long analysis times and a complex experimental setup. Here, we developed a simple, membrane-free, electrokinetic, on-line, integrated SDS removal-ESI-MS device that was able to enhance ESI-MS signals of bradykinin and peptides from trypsin-digested bovine serum albumin (BSA) in samples that contained SDS micelles. The significant peptide-signal improvements were contributed by the complete removal of DS- and the enrichment of the peptides in the presence of an electric field. Enrichment was via micelle-to-solvent stacking, initially developed in capillary electrophoresis. Bradykinin percent recovery was 800%, and BSA peptide percent recovery was 87%. Enhancement factors in ESI-MS signals (after and before removal) for selected m/ z values of peptides from the BSA digest were 535-693.

Retention Index Prediction Using Quantitative Structure-Retention Relationships for Improving Structure Identification in Nontargeted Metabolomics.

Structure identification in nontargeted metabolomics based on liquid-chromatography coupled to mass spectrometry (LC-MS) remains a significant challenge. Quantitative structure-retention relationship (QSRR) modeling is a technique capable of accelerating the structure identification of metabolites by predicting their retention, allowing false positives to be eliminated during the interpretation of metabolomics data. In this work, 191 compounds were grouped according to molecular weight and a QSRR study was carried out on the 34 resulting groups to eliminate false positives. Partial least squares (PLS) regression combined with a Genetic algorithm (GA) was applied to construct the linear QSRR models based on a variety of VolSurf+ molecular descriptors. A novel dual-filtering approach, which combines Tanimoto similarity (TS) searching as the primary filter and retention index (RI) similarity clustering as the secondary filter, was utilized to select compounds in training sets to derive the QSRR models yielding R2 of 0.8512 and an average root mean square error in prediction (RMSEP) of 8.45%. With a retention index filter expressed as ±2 standard deviations (SD) of the error, representative compounds were predicted with >91% accuracy, and for 53% of the groups (18/34), at least one false positive compound could be eliminated. The proposed strategy can thus narrow down the number of false positives to be assessed in nontargeted metabolomics.

Recent developments in open tubular capillary electrochromatography from 2016 to 2017.

Interest in open-tubular capillary electrochromatography (OT-CEC) continues to thrive because of the inherent advantage of OT-CEC combining the high efficiency of capillary electrophoresis and the high selectivity of high performance liquid chromatography. For the period 2016 to 2017, novel materials have been developed as first-time stationary phases for OT-CEC and are grouped in this review as polymer-based materials, frameworks, nanoparticles, graphene-based materials, and biomaterials. Coating and fabrication methods mostly rely on covalent coating strategies while non-covalent immobilisation strategies like electrostatic assembly are notably still being employed. The concern of overcoming phase ratio challenges in OT-CEC coatings have also generated adoption of combined coating strategies including multi-layering, layer-by-layer self-assembly and methods adapted from nanofilm fabrications like epitaxial growth, liquid phase deposition, or nucleation of crystal growth. The emergence of non-conventional coating characterisation methods such as transmission electron microscopy, X-ray diffraction or X-ray photoelectron spectroscopy is also discussed.

Separation of superparamagnetic magnetite nanoparticles by capillary zone electrophoresis using non-complexing and complexing electrolyte anions and tetramethylammonium as dispersing additive.

Separations of bare superparamagnetic magnetite nanoparticles (BSPMNPs, approx. 11 nm diameter) was performed using non-complexing (nitrate) and complexing (chloride, citrate and phosphate) electrolyte ions with additions of tetramethylammonium hydroxide (TMAOH), which is commonly applied to control the synthesis of stable iron oxides. The use of TMAOH as a background electrolyte (BGE) additive for capillary electrophoresis (CE) separations provided for the first time electropherograms of BSPMNPs exhibiting symmetrical and highly reproducible peaks, free of spurious spikes characteristic of nanoparticle clusters. Consequently, accurate determination of the electrophoretic effective mobility of BSPMNPs was possible, yielding a value of -3.345E-08 m2 V-1 s-1 (relative standard deviation (RSD) of 0.500%). The obtained mobilities of BSPMNPs in the presence of various electrolyte ions show that the degree of complexation with the surface of BSPMNPs follows the order chloride < citrate < phosphate, correlating with the stabilities of Fe(III) complexes with the respective anions. Finally, bare and carboxylated iron oxide nanoparticles were successfully separated in only 10 min using 10 mM Tris-nitrate containing 20 mM of TMAOH as electrolyte. Our findings show that simple and rapid CE experiments are an excellent tool to characterise and monitor properties and interactions of iron oxide nanoparticles with other molecules for surface modification purposes.

Synthesis and characterization of MIL-101(Cr) intercalated by polyaniline composite, doped with silica nanoparticles and its evaluation as an efficient solid-phase extraction sorbent.

A metal-organic framework/polyaniline composite was synthesized and doped with silica nanoparticles. The structure and morphology of the composite were characterized using Fourier transform infrared spectroscopy and scanning electron microscopy. It was packed inside a cartridge and evaluated for the solid-phase extraction of thymol and carvacrol, followed by gas chromatography with flame ionization detection measurement. The influence of the important experimental variables on the efficiency of the proposed method, including pH, ionic strength, volume of sample solution and type, and volume of eluent were studied and optimized. Under the optimal conditions, the relative standard deviations were found to be 3.8 and 9.8% for thymol and carvacrol, respectively, and the corresponding limits of detection were 0.1 and 1.0 ng/mL. The linear dynamic ranges for the calibration curves of the analytes were 10-10000 ng/mL, with determination coefficients (R2 ) > 0.993. The limits of quantifications were found to be 0.01 and 0.5 µg/mL, for thymol and carvacrol, respectively. The prepared nanocomposite sorbent was applied successfully to the extraction and determination of thymol and carvacrol in Lamiaceae plant extracts and a honey sample, with relative recoveries in the range of 90.28-122.0%.

Sample Clean-up Strategies for ESI Mass Spectrometry Applications in Bottom-up Proteomics: Trends from 2012 to 2016.

Bottom-up proteomics is a mass spectrometric (MS)-based approach for the characterization of peptides obtained from in-solution protein digestion. MS is favored over other methods for peptide and protein analysis because of its better sensitivity and high throughput. Inorganic ions and surfactants present in the sample or produced during tryptic digestion are detrimental in MS analysis and affect the proteome data, thus sample preparation for removal of these unwanted components has become essential. Here, we review 48 research papers on strategies for removal of salts and surfactants (in particular, SDS) prior to ESI-MS analysis in bottom-up proteomics from 2012 to 2016. The strategies were mostly based on SPE and membrane-based filter-aided sample preparation for salt and SDS removal, respectively. Some known limitations of SPE and filter-aided sample preparation procedures are that they can be time consuming, laborious, and require the use of organic solvents before a concentrated extract suitable for analysis is obtained. The development of faster analytical methods by reducing the sample preparation time and thereby, increasing sample throughput, and in a solvent-less and membrane-less operation, is a significant contribution to proteome research.

Electrokinetic Removal of Dodecyl Sulfate Micelles from Digested Protein Samples Prior to Electrospray-Ionization Mass Spectrometry.

In proteomics, dodecyl sulfate (DS-) as sodium salt is commonly used in protein solubilization prior to tryptic digestion, but the presence of the DS- hampers the electrospray ionization mass spectrometric (ESI-MS) analysis. The development of DS- depletion techniques is therefore important especially when dealing with small samples where there could be poor sensitivity due to sample loss or dilution during sample preparation. Here, we present a simple and fast electrokinetic removal method of DS- from small volumes of peptide and digested protein samples prior to ESI-MS. The selective removal was accomplished using an acidic extraction solution (ES) containing acetonitrile (ACN) inside a fused-silica capillary that was dipped into the sample. The use of acidic ES suppressed the electroosmotic flow; allowing the electrokinetic movement of DS- monomers and micelles into the capillary. The high amount of ACN present at the tip of the capillary served to collapse the micelles migrating into the capillary, thereby releasing the peptides that were bound to these micelles, facilitating peptide retention in the sample and efficient DS- removal. Increased % MS signal intensity (SI) restoration of the peptide was observed, while DS- removal was unaffected when the amount of ACN in the ES was increased. This is because of the micelle to solvent stacking mechanism (effective electrophoretic mobility reversal) working at high concentration of ACN for the improved recovery of the peptides. % MS SI restoration for the Z-Gly-Gly-Val and bradykinin peptides were 75-83% while % MS SI reduction of DS- was up to 99% under optimal conditions, that is, 40% ACN in the ES. Higher % peptide recoveries from digested protein samples were obtained using the proposed method compared to the conventional cold acetone precipitation method.

Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of Experiments.

A design-of-experiment (DoE) model was developed, able to describe the retention times of a mixture of pharmaceutical compounds in hydrophilic interaction liquid chromatography (HILIC) under all possible combinations of acetonitrile content, salt concentration, and mobile-phase pH with R2 > 0.95. Further, a quantitative structure-retention relationship (QSRR) model was developed to predict retention times for new analytes, based only on their chemical structures, with a root-mean-square error of prediction (RMSEP) as low as 0.81%. A compound classification based on the concept of similarity was applied prior to QSRR modeling. Finally, we utilized a combined QSRR-DoE approach to propose an optimal design space in a quality-by-design (QbD) workflow to facilitate the HILIC method development. The mathematical QSRR-DoE model was shown to be highly predictive when applied to an independent test set of unseen compounds in unseen conditions with a RMSEP value of 5.83%. The QSRR-DoE computed retention time of pharmaceutical test analytes and subsequently calculated separation selectivity was used to optimize the chromatographic conditions for efficient separation of targets. A Monte Carlo simulation was performed to evaluate the risk of uncertainty in the model's prediction, and to define the design space where the desired quality criterion was met. Experimental realization of peak selectivity between targets under the selected optimal working conditions confirmed the theoretical predictions. These results demonstrate how discovery of optimal conditions for the separation of new analytes can be accelerated by the use of appropriate theoretical tools.

In Silico Screening of Two-Dimensional Separation Selectivity for Ion Chromatography × Capillary Electrophoresis Separation of Low-Molecular-Mass Organic Acids.

A prerequisite for ordered two-dimensional (2D) separations and full utilization of the enhanced 2D peak capacity is selective exploitation of the sample attributes, described as sample dimensionality. In order to take sample dimensionality into account prior to optimization of a 2D separation, a new concept based on construction of 2D separation selectivity maps is proposed and demonstrated for ion chromatography × capillary electrophoresis (IC×CE) separation of low-molecular-mass organic acids as test analytes. For this purpose, 1D separation selectivity maps were constructed based on calculation of pairwise separation factors and identification of critical pairs for four IC stationary phases and 28 levels of background electrolyte pH in CE. The derived IC and CE maps were then superimposed and the effectiveness of the respective 2D separations assessed using an in silico approach, followed by testing examples of one successful and one unsuccessful 2D combination experimentally. The results confirmed the efficacy of the predictions, which require a minimal number of experiments compared to the traditional one-at-a-time approach. Following the same principles, the proposed framework can also be adapted for optimization of separation selectivity in various 2D combinations and for other applications.

Benchmarking of Computational Methods for Creation of Retention Models in Quantitative Structure-Retention Relationships Studies.

Quantitative structure-retention relationship (QSRR) models are powerful techniques for the prediction of retention times of analytes, where chromatographic retention parameters are correlated with molecular descriptors encoding chemical structures of analytes. Many QSRR models contain geometrical descriptors derived from the three-dimensional (3D) spatial coordinates of computationally predicted structures for the analytes. Therefore, it is sensible to calculate these structures correctly, as any error is likely to carry over to the resulting QSRR models. This study compares molecular modeling, semiempirical, and density functional methods (both B3LYP and M06) for structure optimization. Each of the calculations was performed in a vacuum, then repeated with solvent corrections for both acetonitrile and water. We also compared Natural Bond Orbital analysis with the Mulliken charge calculation method. The comparison of the examined computational methods for structure calculation shows that, possibly due to the error inherent in descriptor creation methods, a quick and inexpensive molecular modeling method of structure determination gives similar results to experiments where structures are optimized using an expensive and time-consuming level of computational theory. Also, for structures with low flexibility, vacuum or gas phase calculations are found to be as effective as those calculations with solvent corrections added.

Field-enhanced sample injection micelle-to-solvent stacking capillary zone electrophoresis-electrospray ionization mass spectrometry of antibiotics in seawater after solid-phase extraction.

The synergistic stacking approach of field-enhanced sample injection-micelle-to-solvent stacking was used for high sensitivity CZE-ESI-MS of eight penicillins and sulfonamides. Sensitivity enhancement factors (peak height) were 1629-3328 compared to typical injection, with LODs from 0.11 to 0.55 ng/mL. The analytical figures of merit were acceptable. SPE on a fortified seawater sample resulted in 50-fold enrichment with recoveries of 85-110%. The overall method LODs were 0.002-0.011 ng/mL.

Simultaneous electrophoretic concentration and separation of herbicides in beer prior to stacking capillary electrophoresis UV and liquid chromatography-mass spectrometry.

Simultaneous electrophoretic concentration and separation (SECS) was used as a simple and environmental friendly sample preparation strategy for herbicides in beer samples. An electric field was used to facilitate the separation and concentration of the analytes based on their charge from a 20 mL sample of diluted beer into two separate 20 µL aliquots of an acceptor electrolyte housed inside a micropipette. The anionic organophosphonate and cationic quaternary ammonium herbicides were concentrated in the anodic and cathodic pipette, respectively. Under optimized conditions, SECS was completed in 30 min at an applied voltage of 150 V, which provided analyte concentration factors of up to 90. After sample preparation, the SECS concentrate of cationic and anionic herbicides was analyzed by stacking CE with UV detection and also by LC-MS, respectively. The method detection limit for the diluted and undiluted sample was as low as 3 and 15 ng/mL, respectively. The method was linear over two orders of concentration with repeatability and intermediate precision of better than 5.8 and 7.0%RSD, respectively. Accuracy values were between 91.0-115.1%.