This study investigated the capability of electromembrane extraction (EME) as a general technique for peptides, by extracting complex pools of peptides comprising in total of 5953 different substances, varying in size from seven to 16 amino acids. Electromembrane extraction was conducted from a sample adjusted to pH 3.0 and utilized a liquid membrane consisting of 2-nitrophenyl octyl ether and carvacrol (1:1 w/w), containing 2% (w/w) di(2-ethylhexyl) phosphate. The acceptor phase was 50 mM phosphoric acid (pH 1.8), the extraction time was 45 min, and 10 V was used. High extraction efficiency, defined as a higher peptide signal in the acceptor than the sample after extraction, was achieved for 3706 different peptides. Extraction efficiencies were predominantly influenced by the hydrophobicity of the peptides and their net charge in the sample. Hydrophobic peptides were extracted with a net charge of +1, while hydrophilic peptides were extracted when the net charge was +2 or higher. A computational model based on machine learning was developed to predict the extractability of peptides based on peptide descriptors, including the grand average of hydropathy index and net charge at pH 3.0 (sample pH). This research shows that EME has general applicability for peptides and represents the first steps toward in silico prediction of extraction efficiency.

Laser micromachining can serve as a coarse machining step during sample preparation for high-resolution characterization methods leading to swift sample preparation. However, selecting the right laser parameters is crucial to minimize the heat-affected zone, which can potentially compromise the microstructure of the specimen. This study focuses on evaluating the size of heat-affected zone in laser annular milling, aiming to ascertain a minimal scan diameter that safeguards the inner region of micropillars against thermal damage. A computational model based on the finite element method was utilized to simulate the laser heating process. To validate the simulation results, a picosecond pulsed laser is then used to machine the micropillars of Al and Si. The laser-machined samples were subjected to surface and microstructural analysis using Scanning Electron Microscope (SEM) and Electron Backscatter Diffraction (EBSD) scans. The length of heat affected zone obtained from simulations was approximately 6 μm for silicon and 12 μm for aluminum. The diameter of micropillars formed with laser machining was 10 μm for silicon 26 μm for aluminum. The core of the pillars was preserved with less than one degree of microstructural misorientations making it suitable for further processing for preparing specimens for techniques like APT and TEM. For silicon micropillars, the preserved central region has a diameter of 6 μm and for aluminum its around 20-24 μm. Additionally, the study determines the minimum scan diameter that can be achieved using the given laser machining setup across a range of common materials.

Starches-rich and protein-rich cereal samples commonly need tedious sample preparation steps before instrumental analysis. This study developed a miniaturized centrifugal integrated cold-induced phase separation (CIPS) method for convenient sample preparation. A small-sized centrifuge tube (2 mL) and a low-temperature centrifuge, both of which are easily accessible, make up the basic components of the system. Unlike conventional sample preparation methods that need a step-by-step extraction, enrichment, purification, and centrifugation, this centrifugal integrated CIPS method can be performed by a one-step combination protocol under a low-temperature centrifuge. As a proof-of-concept study, satisfactory recoveries and enrichment factors were demonstrated for the extraction of fumonisins and ochratoxins from cereals. A sensitive and selective quantification method was yielded by combining LC-HRMS using tSIM acquisition mode, with good linearity (R2 > 0.998), accuracy (82.9-106.5%), and precision (<13.4%). This strategy is convenient, low-cost, repeatable, and easy to semi-automate, further expanding the extraction potential for other acidic mycotoxins.

Electron microscopy (EM) techniques play a vital role in virology research including phage discovery and their identification. The use of different staining protocols based on the concept of negative staining is one of the most important steps in the EM processing. This chapter will summarize the widely used EM protocols in phage research, their advantages, and limitations. Phage-based therapy, especially recently developed nanoparticle-phage conjugates, are expected to find clinical significance in the antimicrobial resistance (AMR) epidemic. EM techniques are important to characterize these conjugates and we will also discuss the methods here.

Sample preparation is essential for low-level compound determination. In the present work, supported liquid extraction (SLE) was used as sample preparation for the low-level determination of a new TLR7 agonist imiquimod compound, LFX453. Samples were extracted on ISOLUTE® SLE 96-well plates using tert-butyl-methyl ether followed by evaporation and dry residue reconstitution with 150 μl of a mixture of 0.1% formic acid in acetonitrile-water (50/50, v/v). Samples were eluted using a flow rate of 0.750 ml/min on a C18 column (50 × 2.1 mm, 2.7 μm) with a mobile phase consisting of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B). Tandem mass spectrometry was used to analyze the samples in positive mode. The method run time was 6.5 min, and the low limit of quantification was 1.00 pg/ml with 0.100 ml of minipig plasma. Intra-run and inter-run precision and accuracy were within the acceptance criteria at four concentration levels over a concentration ranging from 1.00 to 200 pg/ml. There was no matrix effect and recovery, three freeze-thaw cycles and incurred samples reanalysis were validated. The method was successfully applied for measuring LFX453 in minipig plasma after application on minipig skin.

Green Analytical Chemistry (GAC) metrics include a variety of criteria, such as the regent amounts and toxicity, energy consumption, generated waste, among others. The analytical greenness metric (AGREE) and its variant for sample preparation (AGREEprep) cover different aspects that contribute to the environmental sustainability of sample preparation. White Analytical Chemistry (WAC) considers not only environmental aspects but also analytical and practical aspects with a holistic vision based on a Red-Green-Blue color model. A case study is presented to assess the green and white profile of a method based on ultrasound-assisted extraction and determination of Mn and Fe in beef using microwave-induced plasma atomic emission spectroscopy (MP AES). The method was validated and resulted simple, fast without external heating using diluted acids. It was concluded that we should think in green sample preparation with the AGREEprep tool, as well as in white holistic assessments (WAC) as both constitute complementary tools.

Metabolomics studies are becoming increasingly common for understanding how plant metabolism responds to changes in environmental conditions, genetic manipulations and treatments. Despite the recent advances in metabolomics workflow, the sample preparation process still limits the high-throughput analysis in large-scale studies. Here, we present a highly flexible robotic system that integrates liquid handling, sonication, centrifugation, solvent evaporation and sample transfer processed in 96-well plates to automatize the metabolite extraction from leaf samples. We transferred an established manual extraction protocol performed to a robotic system, and with this, we show the optimization steps required to improve reproducibility and obtain comparable results in terms of extraction efficiency and accuracy. We then tested the robotic system to analyze the metabolomes of wild-type and four transgenic silver birch (Betula pendula Roth) lines under unstressed conditions. Birch trees were engineered to overexpress the poplar (Populus × canescens) isoprene synthase and to emit various amounts of isoprene. By fitting the different isoprene emission capacities of the transgenic trees with their leaf metabolomes, we observed an isoprene-dependent upregulation of some flavonoids and other secondary metabolites as well as carbohydrates, amino acid and lipid metabolites. By contrast, the disaccharide sucrose was found to be strongly negatively correlated to isoprene emission. The presented study illustrates the power of integrating robotics to increase the sample throughput, reduce human errors and labor time, and to ensure a fully controlled, monitored and standardized sample preparation procedure. Due to its modular and flexible structure, the robotic system can be easily adapted to other extraction protocols for the analysis of various tissues or plant species to achieve high-throughput metabolomics in plant research.

Colorectal cancer (CRC) ranks as the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths. The current endoscopic-based or stool-based diagnostic techniques are either highly invasive or lack sufficient sensitivity. Thus, there is a need for less invasive and more sensitive screening approaches. We, therefore, conducted a study on 64 human serum samples representing three different groups (adenocarcinoma, adenoma, and control) using cutting-edge GC×GC-LR/HR-TOFMS (comprehensive two-dimensional gas chromatography coupled with low/high-resolution time-of-flight mass spectrometry). We analyzed samples with two different specifically tailored sample preparation approaches for lipidomics (fatty acids) (25 μL serum) and metabolomics (50 μL serum). In-depth chemometric screening with supervised and unsupervised approaches and metabolic pathway analysis were applied to both datasets. A lipidomics study revealed that specific PUFA (ω-3) molecules are inversely associated with increased odds of CRC, while some PUFA (ω-6) analytes show a positive correlation. The metabolomics approach revealed downregulation of amino acids (alanine, glutamate, methionine, threonine, tyrosine, and valine) and myo-inositol in CRC, while 3-hydroxybutyrate levels were increased. This unique study provides comprehensive insight into molecular-level changes associated with CRC and allows for a comparison of the efficiency of two different analytical approaches for CRC screening using same serum samples and single instrumentation.

Dendritic cells (DCs) are essential immune cells for defense against external pathogens. Upon activation, DCs undergo profound metabolic alterations whose precise nature remains poorly studied at a large scale and is thus far from being fully understood. The goal of the present work was to develop a reliable and accurate untargeted metabolomics workflow to get a deeper insight into the metabolism of DCs when exposed to an infectious agent (lipopolysaccharide, LPS, was used to mimic bacterial infection). As DCs transition rapidly from a non-adherent to an adherent state upon LPS exposure, one of the leading analytical challenges was to implement a single protocol suitable for getting comparable metabolomic snapshots of those two cellular states. Thus, a thoroughly optimized and robust sample preparation method consisting of a one-pot solvent-assisted method for the simultaneous cell lysis/metabolism quenching and metabolite extraction was first implemented to measure intracellular DC metabolites in an unbiased manner. We also placed special emphasis on metabolome coverage and annotation by using a combination of hydrophilic interaction liquid chromatography and reverse phase columns coupled to high-resolution mass spectrometry in conjunction with an in-house developed spectral database to identify metabolites at a high confidence level. Overall, we were able to characterize up to 171 unique meaningful metabolites in DCs. We then preliminarily compared the metabolic profiles of DCs derived from monocytes of 12 healthy donors upon in vitro LPS activation in a time-course experiment. Interestingly, the resulting data revealed differential and time-dependent activation of some particular metabolic pathways, the most impacted being nucleotides, nucleotide sugars, polyamines pathways, the TCA cycle, and to a lesser extent, the arginine pathway.

A major goal of structural biologists is to preserve samples as close to their living state as possible. High-pressure freezing (HPF) is a state-of-art technique that freezes the samples at high pressure (~2100 bar) and low temperature (-196 °C) within milliseconds. This ultrarapid fixation enables simultaneous immobilization of all cellular components and preserves the samples in a near-native state. This facilitates the study of dynamic processes in Golgi apparatus organization and membrane trafficking. The work in our laboratory shows that high-pressure freezing followed by freeze substitution (FS), the introduction of organic solvents at low temperature prior to plastic embedding, can better preserve the structure of Golgi apparatus and Golgi-associated vesicles. Here, we present a protocol for freezing monolayer cell cultures on sapphire disks followed by freeze substitution. We were able to use this protocol to successfully study Golgi organization and membrane trafficking in HeLa cells. The protocol gives decidedly better preservation of Golgi apparatus and associated vesicles than conventional chemically fixed preparation and as a plastic embedded preparation can be readily extended to 3D electron microscopy imaging through sequential block face-scanning electron microscopy. The 3D imaging of a multi-micron thick organelle such as the Golgi apparatus located near the cell nucleus is greatly facilitated relative to hydrated sample imaging techniques such as cryo-electron microscopy.