Python workflow for the selection and identification of marker peptides-proof-of-principle study with heated milk.

The analysis of almost holistic food profiles has developed considerably over the last years. This has also led to larger amounts of data and the ability to obtain more information about health-beneficial and adverse constituents in food than ever before. Especially in the field of proteomics, software is used for evaluation, and these do not provide specific approaches for unique monitoring questions. An additional and more comprehensive way of evaluation can be done with the programming language Python. It offers broad possibilities by a large ecosystem for mass spectrometric data analysis, but needs to be tailored for specific sets of features, the research questions behind. It also offers the applicability of various machine-learning approaches. The aim of the present study was to develop an algorithm for selecting and identifying potential marker peptides from mass spectrometric data. The workflow is divided into three steps: (I) feature engineering, (II) chemometric data analysis, and (III) feature identification. The first step is the transformation of the mass spectrometric data into a structure, which enables the application of existing data analysis packages in Python. The second step is the data analysis for selecting single features. These features are further processed in the third step, which is the feature identification. The data used exemplarily in this proof-of-principle approach was from a study on the influence of a heat treatment on the milk proteome/peptidome.

The Shelf Life of Milk-A Novel Concept for the Identification of Marker Peptides Using Multivariate Analysis.

The quality of food is influenced by several factors during production and storage. When using marker compounds, different steps in the production chain, as well as during storage, can be monitored. This might enable an optimum prediction of food's shelf life and avoid food waste. Especially, proteoforms and peptides thereof can serve as indicators for exogenous influences. The development of a proteomics-based workflow for detecting and identifying differences in the proteome is complex and time-consuming. The aim of the study was to develop a fast and universal workflow with ultra-high temperature (UHT) milk as a proteinaceous model food with expectable changes in protein/peptide composition. To find an optimum shelf life without sticking to a theoretically fixed best-before date, new evaluation and analytical methods are needed. Consequently, a modeling approach was used to monitor the shelf life of the milk after it was treated thermally and stored. The different peptide profiles determined with high-resolution mass spectrometry (HRMS) showed a significant difference depending on the preparation method of the samples. Potential marker peptides were determined using orthogonal projections to latent structures discriminant analysis (OPLSDA) and principal component analysis (PCA) following a typical proteomics protocol with tryptic hydrolysis. An additional Python-based algorithm enabled the identification of eight potential tryptic marker peptides (with mass spectrometric structural indications m/z 885.4843, m/z 639.3500, m/z 635.8622, m/z 634.3570, m/z 412.7191, m/z 623.2967, m/z 880.4767, and m/z 692.4041), indicating the effect of the heat treatment. The developed workflow is flexible and can be easily adapted to different research questions in the field of peptide analysis. In particular, the process of feature identification can be carried out with significantly less effort than with conventional methods.

Modular bioengineering of whole-cell catalysis for sialo-oligosaccharide production: coordinated co-expression of CMP-sialic acid synthetase and sialyltransferase.

BACKGROUND: In whole-cell bio-catalysis, the biosystems engineering paradigm shifts from the global reconfiguration of cellular metabolism as in fermentation to a more focused, and more easily modularized, optimization of comparably short cascade reactions. Human milk oligosaccharides (HMO) constitute an important field for the synthetic application of cascade bio-catalysis in resting or non-living cells. Here, we analyzed the central catalytic module for synthesis of HMO-type sialo-oligosaccharides, comprised of CMP-sialic acid synthetase (CSS) and sialyltransferase (SiaT), with the specific aim of coordinated enzyme co-expression in E. coli for reaction flux optimization in whole cell conversions producing 3'-sialyllactose (3SL). RESULTS: Difference in enzyme specific activity (CSS from Neisseria meningitidis: 36 U/mg; α2,3-SiaT from Pasteurella dagmatis: 5.7 U/mg) was compensated by differential protein co-expression from tailored plasmid constructs, giving balance between the individual activities at a high level of both (α2,3-SiaT: 9.4 × 102 U/g cell dry mass; CSS: 3.4 × 102 U/g cell dry mass). Finally, plasmid selection was guided by kinetic modeling of the coupled CSS-SiaT reactions in combination with comprehensive analytical tracking of the multistep conversion (lactose, N-acetyl neuraminic acid (Neu5Ac), cytidine 5'-triphosphate; each up to 100 mM). The half-life of SiaT in permeabilized cells (≤ 4 h) determined the efficiency of 3SL production at 37 °C. Reaction at 25 °C gave 3SL (40 ± 4 g/L) in ∼ 70% yield within 3 h, reaching a cell dry mass-specific productivity of ∼ 3 g/(g h) and avoiding intermediary CMP-Neu5Ac accumulation. CONCLUSIONS: Collectively, balanced co-expression of CSS and SiaT yields an efficient (high-flux) sialylation module to support flexible development of E. coli whole-cell catalysts for sialo-oligosaccharide production.

Direct determination of glyphosate, aminomethylphosphonic acid and glufosinate in food samples with ion chromatography coupled to electrospray ionization tandem mass spectrometry.

A fast and reliable method for the direct determination of the herbicide glyphosate, its major degradation product aminomethylphosphonic acid (AMPA) and glufosinate is presented for a variety of food matrices. The Quick Polar Pesticides in food of Plant Origin method (QuPPe-PO-Method) was used for extraction without further preconcentration or clean-up steps involving e.g. solid phase extraction (SPE). The method makes use of a commercially available high performance liquid chromatograph coupled to a tandem mass spectrometer with electrospray ionization (LC-ESI-MS/MS) - as present in many laboratories - equipped with an ion chromatography (IC)-column using an MS-compatible eluent made of 0.8% formic acid in water. Due to the absence of time-consuming clean-up procedures, strong matrix effects (ME) of up to 91% for AMPA in grapefruit can be observed, when comparing its sensitivity to that obtained for solvent-based standards. The limits of detection (LODs) were determined for the sample matrices apple, mushrooms, grapefruit, linseed, red lentils and wheat and they were found to be in the range of 0.09 to 0.8, 0.04 to 1 and 0.2 to 2 µg/kg for glyphosate, AMPA and glufosinate, respectively. For the same matrices the validation was carried out according to SANTE guidelines for different commodity groups by spiking them up prior to extraction to concentrations ranging from 10 to 400 µg/kg for matrices with high water content and from 10 to 800 µg/kg for matrices with low water content. When using solvent-based calibration under the use of isotopically labelled internal standards (ILIS) the recoveries were found to range from 84% to 120% and the relative standard deviations (RSD) range between 1% and 19% for glyphosate, AMPA and glufosinate at all fortification levels for all matrices investigated. Accordingly, the method was successfully introduced in our laboratory with limits of quantification (LOQs) of 10 µg/kg for glyphosate, AMPA and glufosinate in samples from SANTE commodity groups 1, 2, 4a and 5. The reliability and robustness of the method are demonstrated by showing a recovery control chart obtained for glyphosate in randomly selected samples from different commodity groups. Therefore, the samples were spiked up with 10 µg/kg of glyphosate during routine analysis, whereby all recoveries were found to be in the range between 70 and 120%.

Shift of the reaction equilibrium at high pressure in the continuous synthesis of neuraminic acid.

The importance of a compound that helps fight against influenza is, in times of a pandemic, self-evident. In order to produce these compounds in vast quantities, many researchers consider continuous flow reactors in chemical industry as next stepping stone for large scale production. For these reasons, the synthesis of N-acetylneuraminic acid (Neu5Ac) in a continuous fixed-bed reactor by an immobilized epimerase and aldolase was investigated in detail. The immobilized enzymes showed high stability, with half-life times > 173 days under storage conditions (6 °C in buffer) and reusability over 50 recycling steps, and were characterized regarding the reaction kinetics (initial rate) and scalability (different lab scales) in a batch reactor. The reaction kinetics were studied in a continuous flow reactor. A high-pressure circular reactor (up to 130 MPa) was applied for the investigation of changes in the position of the reaction equilibrium. By this, equilibrium conversion, selectivity, and yield were increased from 57.9% to 63.9%, 81.9% to 84.7%, and 47.5% to 54.1%, respectively. This indicates a reduction in molar volume from N-acetyl-ᴅ-glucosamine (GlcNAc) and pyruvate (Pyr) to Neu5Ac. In particular, the circular reactor showed great potential to study reactions at high pressure while allowing for easy sampling. Additionally, an increase in affinity of pyruvate towards both tested enzymes was observed when high pressure was applied, as evidenced by a decrease of K I for the epimerase and K M for the aldolase from 108 to 42 mM and 91 to 37 mM, respectively.

Repetitive Synthesis of High-Molecular-Weight Hyaluronic Acid with Immobilized Enzyme Cascades.

Industrial hyaluronic acid (HA) production comprises either fermentation with Streptococcus strains or extraction from rooster combs. The hard-to-control product quality is an obstacle to these processes. Enzymatic syntheses of HA were developed to produce high-molecular-weight HA with low dispersity. To facilitate enzyme recovery and biocatalyst re-use, here the immobilization of cascade enzymes onto magnetic beads was used for the synthesis of uridine-5'-diphosphate-α-d-N-acetyl-glucosamine (UDP-GlcNAc), UDP-glucuronic acid (UDP-GlcA), and HA. The combination of six enzymes in the UDP-sugar cascades with integrated adenosine-5'-triphosphate-regeneration reached yields between 60 and 100 % for 5 repetitive batches, proving the productivity. Immobilized HA synthase from Pasteurella multocida produced HA in repetitive batches for three days. Combining all seven immobilized enzymes in a one-pot synthesis, HA production was demonstrated for three days with a HA concentration of up to 0.37 g L-1 , an average MW of 2.7-3.6 MDa, and a dispersity of 1.02-1.03.

Diving Deep into the Data: A Review of Deep Learning Approaches and Potential Applications in Foodomics.

Deep learning is a trending field in bioinformatics; so far, mostly known for image processing and speech recognition, but it also shows promising possibilities for data processing in food analysis, especially, foodomics. Thus, more and more deep learning approaches are used. This review presents an introduction into deep learning in the context of metabolomics and proteomics, focusing on the prediction of shelf-life, food authenticity, and food quality. Apart from the direct food-related applications, this review summarizes deep learning for peptide sequencing and its context to food analysis. The review's focus further lays on MS (mass spectrometry)-based approaches. As a result of the constant development and improvement of analytical devices, as well as more complex holistic research questions, especially with the diverse and complex matrix food, there is a need for more effective methods for data processing. Deep learning might offer meeting this need and gives prospect to deal with the vast amount and complexity of data.

Engineering analysis of multienzyme cascade reactions for 3'-sialyllactose synthesis.

Sialo-oligosaccharides are important products of emerging biotechnology for complex carbohydrates as nutritional ingredients. Cascade bio-catalysis is central to the development of sialo-oligosaccharide production systems, based on isolated enzymes or whole cells. Multienzyme transformations have been established for sialo-oligosaccharide synthesis from expedient substrates, but systematic engineering analysis for the optimization of such transformations is lacking. Here, we show a mathematical modeling-guided approach to 3'-sialyllactose (3SL) synthesis from N-acetyl- d-neuraminic acid (Neu5Ac) and lactose in the presence of cytidine 5'-triphosphate, via the reactions of cytidine 5'-monophosphate-Neu5Ac synthetase and α2,3-sialyltransferase. The Neu5Ac was synthesized in situ from N-acetyl- d-mannosamine using the reversible reaction with pyruvate by Neu5Ac lyase or the effectively irreversible reaction with phosphoenolpyruvate by Neu5Ac synthase. We show through comprehensive time-course study by experiment and modeling that, due to kinetic rather than thermodynamic advantages of the synthase reaction, the 3SL yield was increased (up to 75%; 10.4 g/L) and the initial productivity doubled (15 g/L/h), compared with synthesis based on the lyase reaction. We further show model-based optimization to minimize the total loading of protein (saving: up to 43%) while maintaining a suitable ratio of the individual enzyme activities to achieve 3SL target yield (61%-75%; 7-10 g/L) and overall productivity (3-5 g/L/h). Collectively, our results reveal the principal factors of enzyme cascade efficiency for 3SL synthesis and highlight the important role of engineering analysis to make multienzyme-catalyzed transformations fit for oligosaccharide production.

Development of a DNA-Based Detection Method for Cocos Nucifera Using TaqMan™ Real-Time PCR.

So far, only a few cases of immunoglobulin E (IgE)-mediated coconut allergies have been described in the literature. Due to a growing consumption of coconut-containing foods in occidental countries, the number of coconut allergies may also increase. As there is no causative immunotherapy in clinical routine, appropriate food labelling is particularly important, also with regard to cross-contamination, to prevent serious health consequences. The purpose of this study was to develop a DNA-based detection method for coconut (Cocos nucifera). Initially, three sets of coconut-specific primers were designed and tested. A TaqMan™ probe was then developed to identify and quantify coconut by real-time PCR assay. With 27 other plant and animal species, the specificity of the primer/probe system was tested and cross reactivity was excluded. In a dilution series, a limit of detection of 1 pg/µL was determined. Thus, the developed real-time PCR assay is a suitable method to detect coconut in food.

Key Factors for A One-Pot Enzyme Cascade Synthesis of High Molecular Weight Hyaluronic Acid.

In the last decades, interest in medical or cosmetic applications of hyaluronic acid (HA) has increased. Size and dispersity are key characteristics of biological function. In contrast to extraction from animal tissue or bacterial fermentation, enzymatic in vitro synthesis is the choice to produce defined HA. Here we present a one-pot enzyme cascade with six enzymes for the synthesis of HA from the cheap monosaccharides glucuronic acid (GlcA) and N-acetylglucosamine (GlcNAc). The combination of two enzyme modules, providing the precursors UDP-GlcA and UDP-GlcNAc, respectively, with hyaluronan synthase from Pasteurella multocida (PmHAS), was optimized to meet the kinetic requirements of PmHAS for high HA productivity and molecular weight. The Mg2+ concentration and the pH value were found as key factors. The HA product can be tailored by different conditions: 25 mM Mg2+ and 2-[4-(2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid (HEPES)-NaOH pH 8 result into an HA product with high Mw HA (1.55 MDa) and low dispersity (1.05). Whereas with 15 mM Mg2+ and HEPES-NaOH pH 8.5, we reached the highest HA concentration (2.7 g/L) with a yield of 86.3%. Our comprehensive data set lays the basis for larger scale enzymatic HA synthesis.

Impacts of Fungicide Treatment and Conventional Fertilization Management on the Potato Metabolome (Solanum tuberosum L.) Evaluated with UPLC-IMS-QToF.

Two field trials were conducted to investigate the influence of fungicide and fertilization management on the potato tubers' metabolome (Solanum tuberosum L.). Thereby, fungicides and conventional fertilizers were varied in terms of quantities, number and date of applications, physical state, and product composition. Following a water-methanol-based extraction, samples were analyzed using an UPLC-IMS-QToF and multivariate data analysis. Fungicide application led to significant changes in the tubers' metabolome. Flavonoids were increasingly expressed as a natural response to impending fungal or viral infections in an untreated group, while the phytoalexin rishitinol was highly abundant in groups with fungicide application. In contrast to fungicides, the application of conventional fertilizers did not cause significant alterations in the tubers' compound composition. Consequently, the impact of fungicide application could be rated as more important than the fertilization-derived influence, which might be because of a gentler adaption to fertilization than to the acute stress of fungicide applications.

Polar Lipids in Starch-Rich Commodities to be Analyzed with LC-MS-Based Metabolomics-Optimization of Ionization Parameters and High-Throughput Extraction Protocols.

Metabolomics-based approaches are still receiving growing attention with regard to food authenticity testing. Such studies require enormous sample numbers with negligible experimental or analytical variations to obtain statistically reliable results. In this context, an extraction protocol in line with optimized ionization parameters was developed in consideration of potential starch-derived matrix effects focusing on the polar lipids of potatoes. Therefore, well-known extractions (Bligh and Dyer, Folch, Matyash, and a n-hexane-based procedure) were compared in a non-targeted and a targeted approach regarding the extractability of their lipids such as phosphatidylcholines, phosphatidylethanolamines, galacto- and glucocerebrosides, di- and triglycerides, and acylated steryl glucosides. The selected Folch method was also scrutinized in view of its ability to remove the matrix's starch and consequently improved by substituting trichlormethane with ethyl acetate as a "greener" Folch approach. Moreover, the challenge of starch-derived contamination and imminent ion suppression in the electrospray ionization source (ESI) was addressed by an optimization of ionization parameters varying desolvation settings, removing injection peaks, and increasing the angles and distances of the ESI-device. Long-term stability tests over five days were performed successfully with a combination of appropriate extraction and decreased desolvation settings during ionization. In conclusion, the present methodology provided the basis for on-going large-scale metabolomic studies with respect to the botanical origin of potatoes using UPLC-IMS-QToF (ultra-high performance liquid chromatography ion mobility spectroscopy quadrupole-time of flight mass spectrometer).

Metabolomics-Based Approach for the Discrimination of Potato Varieties ( Solanum tuberosum) using UPLC-IMS-QToF.

One hundred eighty-two authentic potato samples ( Solanum tuberosum) of known variety were collected from various German regions in 2016 and 2017. Samples were extracted with a liquid-liquid-extraction protocol that included isopropanol, methanol, and water in order to focus on lipophilic metabolites. The analysis of nonpolar extracts was performed using an UPLC-IMS-QToF-MS system; data sets obtained were evaluated via multivariate data analysis. A selection of 14 key metabolites with a significant difference in their abundance profiles was identified. This set of markers contained four hydroxylated glucocerebrosides, two phosphoinositols, one phosphocholine, and seven acylated sterol glucosides based on stigmasterol and ß-sitosterol, which primarily enable the varietal discrimination. Fragments and neutral losses commonly appearing within one class or subclass of lipids were summarized within a new database that included ion mobility data. The performance of the approach was verified with twenty-nine commercial potato samples.

Directed Evolution of Hyaluronic Acid Synthase from Pasteurella multocida towards High-Molecular-Weight Hyaluronic Acid.

Hyaluronic acid (HA), with diverse cosmetic and medical applications, is the natural glycosaminoglycan product of HA synthases. Although process and/or metabolic engineering are used for industrial HA production, the potential of protein engineering has barely been realised. Herein, knowledge-gaining directed evolution (KnowVolution) was employed to generate an HA synthase variant from Pasteurella multocida (pmHAS) with improved chain-length specificity and a twofold increase in mass-based turnover number. Seven improved pmHAS variants out of 1392 generated by error-prone PCR were identified; eight prospective positions were saturated and the most beneficial amino acid substitutions were recombined. After one round of KnowVolution, the longest HA polymer (<4.7 MDa), through an engineered pmHAS variant in a cell-free system, was synthesised. Computational studies showed that substitutions from the best variant (T40L, V59M and T104A) are distant from the glycosyltransferase sites and increase the flexibility of the N-terminal region of pmHAS. Taken together, these findings suggest that the N terminus may be involved in HA synthesis and demonstrate the potential of protein engineering towards improved HA synthase activity.

Identification and characterization of pesticide metabolites in Brassica species by liquid chromatography travelling wave ion mobility quadrupole time-of-flight mass spectrometry (UPLC-TWIMS-QTOF-MS).

A new mass spectrometric method for evaluating metabolite formation of the pesticides thiacloprid, azoxystrobin, and difenoconazole was developed for the Brassica species pak choi and broccoli. Both, distribution and transformation kinetics of the active compounds and their metabolites were analyzed by UPLC-TWIMS-QTOF-MS. Additionally, HR-MS analysis and structure elucidation tools such as diagnostic ions, isotopic matches, and collision cross sections were applied for metabolites identification. Following the application of two plant protection products (containing the above-mentioned active compounds) in a greenhouse study plant material was cryo-milled and extracted with water/methanol. The residual levels of active compounds were identified at certain timepoints during pre-harvest intervals and in the final products. Different phase I and phase II metabolites of the pesticides were identified in different plant organs such as leaves, stems, (broccoli) heads, and roots. Three individual degradation pathways and distribution profiles are suggested including eight thiacloprid, eleven azoxystrobin and three difenoconazole metabolites.

Ring-opening metathesis polymerization-derived, lectin-functionalized monolithic supports for affinity separation of glycoproteins.

Lectin-functionalized monolithic columns were prepared within polyether ether ketone (PEEK) columns (150 × 4.6 mm id) via transition metal-catalyzed ring-opening metathesis polymerization of norborn-2-ene (NBE) and trimethylolpropane-tris(5-norbornene-2-carboxylate) (CL) using the first-generation Grubbs initiator RuCl2 (PCy3 )2 (CHPh) (1, Cy = cyclohexyl) in the presence of a macro- and microporogen, i.e. of 2-propanol and toluene. Postsynthesis functionalization was accomplished via in situ grafting of 2,5-dioxopyrrolidin-1-yl-bicyclo[2.2.1]hept-5-ene-2-carboxylate to the surface of the monoliths followed by reaction with α,ω-diamino-poly(ethyleneglycol). The pore structure of the poly(ethyleneglycol)- derivatized monoliths was investigated by electron microscopy and inverse-size exclusion chromatography, respectively. The amino-poly(ethyleneglycol) functionalized monolithic columns were then successfully used for the immobilization of lectin from Lens culinaris hemagglutinin. The thus prepared lectin-functionalized monoliths were applied to the affinity chromatography-based purification of glucose oxidase. The binding capacity of Lens culinaris hemagglutinin-immobilized monolithic column for glucose oxidase was found to be 2.2 mg/column.

Amino-functionalized monolithic spin-type columns for high-throughput lectin affinity chromatography of glycoproteins.

Hydrophilic poly(ethylene glycol)-based monoliths were synthesized in the spin-tip format for high-throughput applications via pulsed electron beam irradiation. Monoliths with a homogeneous porous structure and a total porosity of 69% were obtained. The cross-linked polymeric structure was further mechanically stabilized via the incorporation of silica nanoparticles. Amino-functionalization of the monoliths was accomplished by a straightforward, water-based, one-step approach that entailed the electron-beam irradiation-induced grafting of poly(allylamine). The amine functionalized spin columns showed very low unspecific protein adsorption and were successfully applied as adsorbents in lectin affinity chromatography for the purification of ovalbumin. The novel columns also outperformed a commercially available system.

Benefits of high resolution IC-ICP-MS for the routine analysis of inorganic and organic arsenic species in food products of marine and terrestrial origin.

A recently developed and validated method for simultaneous determination of 17 inorganic and organic arsenic compounds in marine biota has been successfully applied to routine analysis of different food products, including fish, shellfish, edible algae, rice, and other types of grain. During one year, approximately 250 food samples were analyzed, mostly fish and rice. Long-term stability and robustness of the system was observed and reproducible results for certified reference materials were ensured by means of control charts. The separation was performed by ion-pair chromatography on an anion-exchange column to separate anionic, neutral, and cationic arsenic species in one chromatographic run. Hyphenation to ICP-MS allowed element-specific and sensitive detection of the different arsenic species with a detection limit as low as 8 ng As L(-1 )in the sample extract, which is equivalent to 2 ng As g(-1) in the original sample. Special emphasis was laid on the analysis of marine algae and rice samples. These food types can contain elevated levels of the very toxic inorganic arsenic species (up to 90% in rice) and therefore are the focus of interest in the food industry. In marine algae, inorganic arsenic was mainly present as arsenate whereas in rice arsenite predominated.

Simultaneous separation of 17 inorganic and organic arsenic compounds in marine biota by means of high-performance liquid chromatography/inductively coupled plasma mass spectrometry.

A method using high-performance liquid chromatography/inductively coupled plasma mass spectrometry (HPLC/ICP-MS) has been developed to determine inorganic arsenic (arsenite, arsenate) along with organic arsenic compounds (monomethylarsonic acid, dimethylarsinic acid, arsenobetaine, arsenocholine, trimethylarsine oxide, tetramethylarsonium ion and several arsenosugars) in fish, mussel, oyster and marine algae samples. The species were extracted by means of a methanol/water mixture and a dispersion unit in 2 min, with extraction efficiencies ranging from 83 to 107% in the different organisms. Up to 17 different species were determined within 15 min on an anion-exchange column, using a nitric acid gradient and an ion-pairing reagent. As all species are shown in one chromatogram, a clear overview of arsenic distribution patterns in different marine organisms is given. Arsenobetaine is the major compound in marine animals whereas arsenosugars and arsenate are dominant in marine algae. The method was validated with CRM DORM-2 (dogfish muscle). Concentrations were within the certified limits and low detection limits of 8 ng g(-1) (arsenite) to 50 ng g(-1) (arsenate) were obtained.