Matrix effects demystified: Strategies for resolving challenges in analytical separations of complex samples

Matrix effects can significantly impede the accuracy, sensitivity, and reliability of separation techniques presenting a formidable challenge to the analytical process. It is crucial to address matrix effects to achieve accurate and precise measurements in complex matrices. The multifaceted nature of matrix effects which can be influenced by factors such as target analyte, sample preparation protocol, composition, and choice of instrument necessitates a pragmatic approach when analyzing complex matrices. This review aims to highlight common challenges associated with matrix effects throughout the entire analytical process with emphasis on gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, and sample preparation techniques. These techniques are susceptible to matrix effects that could lead to ion suppression/enhancement or impact the analyte signal at various stages of the analytical workflow. The assessment, quantification, and mitigation of matrix effects are necessary in developing any analytical method. Strategies can be implemented to reduce or eliminate the matrix effect by changing the type of ionization, improving extraction and clean-up methods, optimization of chromatography conditions, and corrective calibration methods. While development of an effective strategy to completely mitigate matrix effects remains elusive, an integrated approach that combines sample preparation, analytical extraction, and effective instrumental analysis remains the most promising avenue for identifying and resolving matrix effects.

Physical Pretreatments Applied in Three Commercial Kits for the Extraction of High-Quality DNA from Activated Sewage Sludge

Obtaining sufficient and high-quality genomic DNA from sludge samples is a fundamental issue of feasibility and comparability in genomic studies of microbial diversity. Commercial kits for soil are often used for the extraction of gDNA from sludge samples due to the lack of specific kits. However, the evaluation of the performance of commercial kits for sludge DNA extraction is scarce and optimization of these methods to obtain a high quantity and quality of DNA is necessary, especially for downstream genomic sequencing. Sequential batch reactors (SBRs) loaded with lignocellulosic biomass are used for the synthesis of renewable resources such as levulinic acid (LA), adipic acid (AA), and polyhydroxyalkanoates (PHAs), and the biochemical synthesis of these compounds is conducted through the inoculation of microbes present in the residual activated sludge (AS) obtained from a municipal wastewater treatment plant. To characterize these microbes, the extraction of DNA from residual sewage sludge was conducted with three different commercial kits: Nucleospin® Soil from Macherey-Nagel, DNEasy® PowerSoil® from Qiagen, and E.Z.N.A.® Plant DNA Kit from Omega BIO-TEK. Nevertheless, to obtain the highest load and quality of DNA for next-generation sequencing (NGS) analysis, different pretreatments and different combinations of these pretreatments were used. The pretreatments considered were an ultrasonic bath and a temperature of 80 °C, together and separately with different incubation time periods of 30, 60, and 90 min. The results obtained suggest a significant improvement in the efficiency and quality of DNA extraction with the three commercial extraction kits when used together with the ultrasonic bath and 80 °C for 60 min. Here, we were able to prove that physical pretreatments are a viable alternative to chemical lysis for DNA extraction from complex samples such as sludge.

A Review on Pretreatment and Analysis Methods of Polyether Antibiotics in Complex Samples

Polyether antibiotics (PAs) are the anti-coccidiosis drugs used for treating and preventing coccidiosis. Studies show the residues of these antibiotics in food cause adversities and threaten human health. PAs thus need robust, rugged, and accurate methods for their analysis. This review encompasses pretreatment and detection methods of PAs in diverse matrices since 2010. Both conventional and developed methods are part of the pretreatments, such as dispersive liquid-liquid microextraction, solid-phase extraction, solid-phase microextraction, solvent front position extraction, QuEChERS (Quick Easy Cheap Effective Rugged and Safe), supercritical fluid extraction, and others. The analysis methods involve liquid chromatography coupled with detectors, sensors, etc. The pros and cons of various techniques for PAs have been discussed and future tendencies are proposed.

One-pot synthesis of magnetic sulfonated covalent organic polymer for extraction of protoberberine alkaloids in herbs and human plasma

A novel magnetic sulfonated covalent organic polymer was prepared for magnetic solid-phase extraction of protoberberine alkaloids. The magnetic sulfonated covalent organic polymer was rapidly synthesized under mild conditions. The physicochemical properties of the prepared materials were characterized by Fourier-transform infrared spectrometry, transmission electron microscopy, and X-ray photoelectron spectroscopy. Several extraction parameters were systematically investigated, including desorption time, pH of sample solution, acetonitrile content, acetic acid content in the eluent, extraction time, and sample volume. By coupling magnetic solid-phase extraction and high-performance liquid chromatography, an efficient and sensitive method for the extraction and determination of protoberberine alkaloids in complex samples was developed. The proposed method showed great linearity (r > 0.9989), low limits of detection (0.2-0.3 ng/ml), and high precision (relative standard deviations ≤ 5.74%). The proposed method was further applied to the analysis of protoberberine alkaloids in Cortex phellodendri and human plasma samples. The recoveries were 91.50%-110.31% with relative standard deviations less than 6.63% in Cortex phellodendri and 96.12%-111.20% with relative standard deviations lower than 5.56% in plasma samples.

New Constructed EEM Spectra Combined with N-PLS Analysis Approach as an Effective Way to Determine Multiple Target Compounds in Complex Samples

Excitation-emission matrix (EEM) fluorescence spectroscopy has been applied to many fields. In this study, a simple method was proposed to obtain the new constructed three-dimensional (3D) EEM spectra based on the original EEM spectra. Then, the application of the N-PLS method to the new constructed 3D EEM spectra was proposed to quantify target compounds in two complex data sets. The quantitative models were established on external sample sets and validated using statistical parameters. For validation purposes, the obtained results were compared with those obtained by applying the N-PLS method to the original EEM spectra and applying the PLS method to the extracted maximum spectra in the concatenated mode. The comparison of the results demonstrated that, given the advantages of less useless information and a high calculating speed of the new constructed 3D EEM spectra, N-PLS on the new constructed 3D EEM spectra obtained better quantitative analysis results with a correlation coefficient of prediction above 0.9906 and recovery values in the range of 85.6-95.6%. Therefore, one can conclude that the N-PLS method combined with the new constructed 3D EEM spectra is expected to be broadened as an alternative strategy for the simultaneous determination of multiple target compounds.

Standard Sample Storage Conditions Have an Impact on Inferred Microbiome Composition and Antimicrobial Resistance Patterns

Storage of biological specimens is crucial in the life and medical sciences. Storage conditions for samples can be different for a number of reasons, and it is unclear what effect this can have on the inferred microbiome composition in metagenomics analyses. Here, we assess the effect of common storage temperatures (deep freezer, -80°C; freezer, -20°C; refrigerator, 5°C; room temperature, 22°C) and storage times (immediate sample processing, 0 h; next day, 16 h; over weekend, 64 h; longer term, 4, 8, and 12 months) as well as repeated sample freezing and thawing (2 to 4 freeze-thaw cycles). We examined two different pig feces and sewage samples, unspiked and spiked with a mock community, in triplicate, respectively, amounting to a total of 438 samples (777 Gbp; 5.1 billion reads). Storage conditions had a significant and systematic effect on the taxonomic and functional composition of microbiomes. Distinct microbial taxa and antimicrobial resistance classes were, in some situations, similarly affected across samples, while others were not, suggesting an impact of individual inherent sample characteristics. With an increasing number of freeze-thaw cycles, an increasing abundance of Firmicutes, Actinobacteria, and eukaryotic microorganisms was observed. We provide recommendations for sample storage and strongly suggest including more detailed information in the metadata together with the DNA sequencing data in public repositories to better facilitate meta-analyses and reproducibility of findings. IMPORTANCE Previous research has reported effects of DNA isolation, library preparation, and sequencing technology on metagenomics-based microbiome composition; however, the effect of biospecimen storage conditions has not been thoroughly assessed. We examined the effect of common sample storage conditions on metagenomics-based microbiome composition and found significant and, in part, systematic effects. Repeated freeze-thaw cycles could be used to improve the detection of microorganisms with more rigid cell walls, including parasites. We provide a data set that could also be used for benchmarking algorithms to identify and correct for unwanted batch effects. Overall, the findings suggest that all samples of a microbiome study should be stored in the same way. Furthermore, there is a need to mandate more detailed information about sample storage and processing be published together with DNA sequencing data at the International Nucleotide Sequence Database Collaboration (ENA/EBI, NCBI, DDBJ) or other repositories.

Standard Sample Storage Conditions Have an Impact on Inferred Microbiome Composition and Antimicrobial Resistance Patterns

Storage of biological specimens is crucial in the life and medical sciences. Storage conditions for samples can be different for a number of reasons, and it is unclear what effect this can have on the inferred microbiome composition in metagenomics analyses. Here, we assess the effect of common storage temperatures (deep freezer, -80°C; freezer, -20°C; refrigerator, 5°C; room temperature, 22°C) and storage times (immediate sample processing, 0 h; next day, 16 h; over weekend, 64 h; longer term, 4, 8, and 12 months) as well as repeated sample freezing and thawing (2 to 4 freeze-thaw cycles). We examined two different pig feces and sewage samples, unspiked and spiked with a mock community, in triplicate, respectively, amounting to a total of 438 samples (777 Gbp; 5.1 billion reads). Storage conditions had a significant and systematic effect on the taxonomic and functional composition of microbiomes. Distinct microbial taxa and antimicrobial resistance classes were, in some situations, similarly affected across samples, while others were not, suggesting an impact of individual inherent sample characteristics. With an increasing number of freeze-thaw cycles, an increasing abundance of Firmicutes, Actinobacteria, and eukaryotic microorganisms was observed. We provide recommendations for sample storage and strongly suggest including more detailed information in the metadata together with the DNA sequencing data in public repositories to better facilitate meta-analyses and reproducibility of findings. IMPORTANCE Previous research has reported effects of DNA isolation, library preparation, and sequencing technology on metagenomics-based microbiome composition; however, the effect of biospecimen storage conditions has not been thoroughly assessed. We examined the effect of common sample storage conditions on metagenomics-based microbiome composition and found significant and, in part, systematic effects. Repeated freeze-thaw cycles could be used to improve the detection of microorganisms with more rigid cell walls, including parasites. We provide a data set that could also be used for benchmarking algorithms to identify and correct for unwanted batch effects. Overall, the findings suggest that all samples of a microbiome study should be stored in the same way. Furthermore, there is a need to mandate more detailed information about sample storage and processing be published together with DNA sequencing data at the International Nucleotide Sequence Database Collaboration (ENA/EBI, NCBI, DDBJ) or other repositories.

Immunoaffinity Extraction and Alternative Approaches for the Analysis of Toxins in Environmental, Food or Biological Matrices

The evolution of instrumentation in terms of separation and detection allowed a real improvement of the sensitivity and analysis time. However, the analysis of ultra-traces of toxins in complex samples requires often a step of purification and even preconcentration before their chromatographic analysis. Therefore, immunoaffinity sorbents based on specific antibodies thus providing a molecular recognition mechanism appear as powerful tools for the selective extraction of a target molecule and its structural analogs to obtain more reliable and sensitive quantitative analysis in environmental, food or biological matrices. This review focuses on immunosorbents that have proven their efficiency in selectively extracting various types of toxins of various sizes (from small mycotoxins to large proteins) and physicochemical properties. Immunosorbents are now commercially available, and their use has been validated for numerous applications. The wide variety of samples to be analyzed, as well as extraction conditions and their impact on extraction yields, is discussed. In addition, their potential for purification and thus suppression of matrix effects, responsible for quantification problems especially in mass spectrometry, is presented. Due to their similar properties, molecularly imprinted polymers and aptamer-based sorbents that appear to be an interesting alternative to antibodies are also briefly addressed by comparing their potential with that of immunosorbents.

The Utilization of Linear Polylysine Coupled with Mechanic Forces to Extract Microbial DNA from Different Matrices

Molecular approaches are powerful tools that are used for medical or environmental diagnoses. However, the main limitations of such a tools are that they extract low levels of DNA and they do not remove the inhibitors of polymerase chain reaction (PCR). Although the use of polycation to complex and purify DNA has been described in the literature, elution often requires a high ionic strength or pH levels not compatible with molecular analyses. In this paper, we described a new process that is based on the complexation of DNA with linear polylysine, followed by capturing the complex by a cation exchange resin. The originality of the process consisted of using mechanic force to elute DNA from the complex. The extraction method showed several advantages when compared to existing methods, such as being compatible with pH levels that range from 5 to 11, as well as high levels of DNA recovery and elimination of PCR inhibitors from complex samples. This method was successfully applied to different types of samples, such as environmental samples, beverage samples, and medical samples. Furthermore, it was proven to be a good solution for removing PCR inhibitors and assuring good DNA recovery yield.

A free-knot spline modeling framework for piecewise linear logistic regression in complex samples with body mass index and mortality as an example

This paper details the design, evaluation, and implementation of a framework for detecting and modeling nonlinearity between a binary outcome and a continuous predictor variable adjusted for covariates in complex samples. The framework provides familiar-looking parameterizations of output in terms of linear slope coefficients and odds ratios. Estimation methods focus on maximum likelihood optimization of piecewise linear free-knot splines formulated as B-splines. Correctly specifying the optimal number and positions of the knots improves the model, but is marked by computational intensity and numerical instability. Our inference methods utilize both parametric and nonparametric bootstrapping. Unlike other nonlinear modeling packages, this framework is designed to incorporate multistage survey sample designs common to nationally representative datasets. We illustrate the approach and evaluate its performance in specifying the correct number of knots under various conditions with an example using body mass index (BMI; kg/m²) and the complex multi-stage sampling design from the Third National Health and Nutrition Examination Survey to simulate binary mortality outcomes data having realistic nonlinear sample-weighted risk associations with BMI. BMI and mortality data provide a particularly apt example and area of application since BMI is commonly recorded in large health surveys with complex designs, often categorized for modeling, and nonlinearly related to mortality. When complex sample design considerations were ignored, our method was generally similar to or more accurate than two common model selection procedures, Schwarz's Bayesian Information Criterion (BIC) and Akaike's Information Criterion (AIC), in terms of correctly selecting the correct number of knots. Our approach provided accurate knot selections when complex sampling weights were incorporated, while AIC and BIC were not effective under these conditions.

Bacterial isolation by lectin-modified microengines

New template-based self-propelled gold/nickel/polyaniline/platinum (Au/Ni/PANI/Pt) microtubular engines, functionalized with the Concanavalin A (ConA) lectin bioreceptor, are shown to be extremely useful for the rapid, real-time isolation of Escherichia coli (E. coli) bacteria from fuel-enhanced environmental, food, and clinical samples. These multifunctional microtube engines combine the selective capture of E. coli with the uptake of polymeric drug-carrier particles to provide an attractive motion-based theranostics strategy. Triggered release of the captured bacteria is demonstrated by movement through a low-pH glycine-based dissociation solution. The smaller size of the new polymer-metal microengines offers convenient, direct, and label-free optical visualization of the captured bacteria and discrimination against nontarget cells.