Peak capacity optimisation for high resolution peptide profiling in complex mixtures by liquid chromatography coupled to time-of-flight mass spectrometry: Application to the Conus consors cone snail venom

Reversed-Phase Liquid Chromatography of Peptides for Bottom-Up Proteomics: A Tutorial

The performance of the current bottom-up liquid chromatography hyphenated with mass spectrometry (LC-MS) analyses has undoubtedly been fueled by spectacular progress in mass spectrometry. It is thus not surprising that the MS instrument attracts the most attention during LC-MS method development, whereas optimizing conditions for peptide separation using reversed-phase liquid chromatography (RPLC) remains somewhat in its shadow. Consequently, the wisdom of the fundaments of chromatography is slowly vanishing from some laboratories. However, the full potential of advanced MS instruments cannot be achieved without highly efficient RPLC. This is impossible to attain without understanding fundamental processes in the chromatographic system and the properties of peptides important for their chromatographic behavior. We wrote this tutorial intending to give practitioners an overview of critical aspects of peptide separation using RPLC to facilitate setting the LC parameters so that they can leverage the full capabilities of their MS instruments. After briefly introducing the gradient separation of peptides, we discuss their properties that affect the quality of LC-MS chromatograms the most. Next, we address the in-column and extra-column broadening. The last section is devoted to key parameters of LC-MS methods. We also extracted trends in practice from recent bottom-up proteomics studies and correlated them with the current knowledge on peptide RPLC separation.

Co-Culture Systems for the Production of Secondary Metabolites: Current and Future Prospects

Microorganisms are the great sources of Natural Products (NPs); these are imperative to their survival apart from conferring competitiveness amongst each other within their environmental niches. Primary and secondary metabolites are the two major classes of NPs that help in cell development, where antimicrobial activity is closely linked with secondary metabolites. To capitalize on the effects of secondary metabolites, co-culture methods have been often used to develop an artificial microbial community that promotes the action of these metabolites. Different analytical techniques will subsequently be employed based on the metabolite specificity and sensitivity to further enhance the metabolite induction. Liquid Chromatography-Mass Spectrometry (LC-MS) and Gas Chromatography (GC)-MS are commonly used for metabolite separation while Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS) have been used as tools to elucidate the structure of compounds. This review intends to discuss current systems in use for co-culture in addition to its advantages, with discourse into the investigation of specific techniques in use for the detailed study of secondary metabolites. Further advancements and focus on co-culture technologies are required to fully realize the massive potential in synthetic biological systems.

Sub-picomolar quantification of PTH 1-34 in plasma by UHPLC-MS/MS after subcutaneous injection of teriparatide and identification of PTH 1-33, its degradation product

Teriparatide (PTH 1-34, Forsteo^®) is a bioactive N-terminal fragment of the native endogenous parathyroid hormone (PTH 1-84) recommended for the treatment of osteoporosis in patients with high risk of fracture. Since PTH 1-34 may undergo proteolysis we have validated an ultra-high pressure liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method for unambiguously measuring intact PTH 1-34 with the same sensitivity as ELISA, at subpicomolar level (LLOQ at 0.4 pM). The full chromatographic run was achieved in 16.5 min. The method validation showed satisfactory intra- and inter-assay precision (CV < 13%) and excellent trueness (<5%), and almost no matrix effect (recoveries 78-92%). We found that after subcutaneous injection in two volunteers, PTH 1-34 half-life was shorter with UHPLC-MS/MS and that ELISA was overestimating PTH 1-34 late concentrations in both volunteers. Qualitative mass spectrometry was performed and led to the discovery of PTH 1-33, a fragment of PTH 1-34 with unknown function. This study emphasized the importance of switching from immunoassays to mass spectrometry when measuring bioactive peptides prompt to proteolysis into fragments that may exhibit altered bioactivity and duration of action.

Fast Determination of Phenolic Compounds in Rice Grains by Ultraperformance Liquid Chromatography Coupled to Photodiode Array Detection: Method Development and Validation

There are several phenolic compounds in rice grains providing benefits for human health. The concentration of phenolic compounds in rice is strongly affected by the polishing steps during rice production. A new sensitive ultraperformance liquid chromatography-ultraviolet-visible spectroscopy method with a photodiode array detection protocol has been developed and validated for the quantitation of phenolic compounds in rice grains. Several working variables and two different columns were evaluated. Finally, a less than 3 min analysis time was developed to achieve enough resolution for the simultaneous determination of the 20 most common phenolic compounds in rice. The analytical properties for the separation method produced an adequate sensitivity for all phenolic compounds in the regular range for phenolics in rice, 0.5-100 mg L^-1 ( R² > 0.997), with high precisions for both repeatability and intermediate precisions (coefficients of variation less than 0.4 and 2.5% for the retention time and area of the peaks, respectively).

Sensitive quantification of the somatostatin analog AP102 in plasma by ultra-high pressure liquid chromatography-tandem mass spectrometry and application to a pharmacokinetic study in rats

AP102 is a di-iodinated octapeptide somatostatin agonist (SSA) designed to treat acromegaly and neuroendocrine tumors. A sensitive and selective method was validated for the quantification of AP102 in plasma following the European Medicines Agency (EMA) and Food and Drug Administration (FDA) guidelines. Sample preparation was performed using solid-phase extraction microplates. Chromatographic separation was achieved on an ultra-high pressure liquid chromatography (UHPLC) C18 column in 6.0 minutes. The compounds were quantified using multiple reaction monitoring on a tandem quadrupole mass spectrometer with ¹³ C,¹⁵ N-labeled AP102 as internal standard. Calibration ranged from 50 to 10000 pg/mL. The lower limit of quantification (LLOQ) was measured at 20 pg/mL, and robust analytical performances were obtained with trueness at 99.2%-100.0%, intra-assay imprecision at 2.5%-4.4%, and inter-assay imprecision at 8.9%-9.7%. The accuracy profiles (total error) built on the 3 concentrations levels showed accuracy within the 70%-130% range. AP102 is remarkably stable since no proteolytic fragments were detected on plasma samples analyzed by Orbitrap-MS. Pharmacokinetic studies were conducted in rats, after single dose (1, 3, and 10 μg/kg, sc) and continuous subcutaneous administration (osmotic minipumps for 28 days, 3.0 or 10.0 μg/kg/h). AP102 showed a rapid absorption by the subcutaneous route (T_max : 15-30 minutes) and a fast elimination (t_1/2 : 33-86 minutes). The PK profile of AP102 exhibited a mean clearance of 1.67 L/h and a mean distribution volume at steady state of 7.16 L/kg, about 10-fold higher than those observed with other SSA or non- and mono-iodinated AP102. LogD_7.4 determination confirmed the lipophilic properties of AP102 that might influence its distribution in tissues.

Conventional-Flow Liquid Chromatography-Mass Spectrometry for Exploratory Bottom-Up Proteomic Analyses

Due to its sensitivity and productivity, bottom-up proteomics based on liquid chromatography-mass spectrometry (LC-MS) has become the core approach in the field. The de facto standard LC-MS platform for proteomics operates at sub-μL/min flow rates, and nanospray is required for efficiently introducing peptides into a mass spectrometer. Although this is almost a "dogma", this view is being reconsidered in light of developments in highly efficient chromatographic columns, and especially with the introduction of exceptionally sensitive MS instruments. Although conventional-flow LC-MS platforms have recently penetrated targeted proteomics successfully, their possibilities in discovery-oriented proteomics have not yet been thoroughly explored. Our objective was to determine what are the extra costs and what optimization and adjustments to a conventional-flow LC-MS system must be undertaken to identify a comparable number of proteins as can be identified on a nanoLC-MS system. We demonstrate that the amount of a complex tryptic digest needed for comparable proteome coverage can be roughly 5-fold greater, providing the column dimensions are properly chosen, extra-column peak dispersion is minimized, column temperature and flow rate are set to levels appropriate for peptide separation, and the composition of mobile phases is fine-tuned. Indeed, we identified 2 835 proteins from 2 μg of HeLa cells tryptic digest separated during a 60 min gradient at 68 μL/min on a 1.0 mm × 250 mm column held at 55 °C and using an aqua-acetonitrile mobile phases containing 0.1% formic acid, 0.4% acetic acid, and 3% dimethyl sulfoxide. Our results document that conventional-flow LC-MS is an attractive alternative for bottom-up exploratory proteomics.

Peptidomic and transcriptomic profiling of four distinct spider venoms

Venom based research is exploited to find novel candidates for the development of innovative pharmacological tools, drug candidates and new ingredients for cosmetic and agrochemical industries. Moreover, venomics, as a well-established approach in systems biology, helps to elucidate the genetic mechanisms of the production of such a great molecular biodiversity. Today the advances made in the proteomics, transcriptomics and bioinformatics fields, favor venomics, allowing the in depth study of complex matrices and the elucidation even of minor compounds present in minute biological samples. The present study illustrates a rapid and efficient method developed for the elucidation of venom composition based on NextGen mRNA sequencing of venom glands and LC-MS/MS venom proteome profiling. The analysis of the comprehensive data obtained was focused on cysteine rich peptide toxins from four spider species originating from phylogenetically distant families for comparison purposes. The studied species were Heteropoda davidbowie (Sparassidae), Poecilotheria formosa (Theraphosidae), Viridasius fasciatus (Viridasiidae) and Latrodectus mactans (Theridiidae). This led to a high resolution profiling of 284 characterized cysteine rich peptides, 111 of which belong to the Inhibitor Cysteine Knot (ICK) structural motif. The analysis of H. davidbowie venom revealed a high richness in term of venom diversity: 95 peptide sequences were identified; out of these, 32 peptides presented the ICK structural motif and could be classified in six distinct families. The profiling of P. formosa venom highlighted the presence of 126 peptide sequences, with 52 ICK toxins belonging to three structural distinct families. V. fasciatus venom was shown to contain 49 peptide sequences, out of which 22 presented the ICK structural motif and were attributed to five families. The venom of L. mactans, until now studied for its large neurotoxins (Latrotoxins), revealed the presence of 14 cysteine rich peptides, out of which five were ICK toxins belonging to the CSTX superfamily. This in depth profiling of distinct ICK peptide families identified across the four spider species highlighted the high conservation of these neurotoxins among spider families.

Advances in venomics

The term “venomics” was coined to describe the global study of venom and venom glands, targeting comprehensive characterization of the whole toxin profile of a venomous animal by means of proteomics, transcriptomics, genomics and bioinformatics studies.

Retention time prediction for dereplication of natural products (CxHyOz) in LC-MS metabolite profiling

The detection and early identification of natural products (NPs) for dereplication purposes require efficient, high-resolution methods for the profiling of crude natural extracts. This task is difficult because of the high number of NPs in these complex biological matrices and because of their very high chemical diversity. Metabolite profiling using ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HR-MS) is very efficient for the separation of complex mixtures and provides molecular formula information as a first step in dereplication. This structural information alone or even combined with chemotaxonomic information is often not sufficient for unambiguous metabolite identification. In this study, a representative set of 260 NPs containing C, H, and O atoms only was analysed in generic UHPLC–HR-MS profiling conditions. Two easy to use quantitative structure retention relationship (QSRR) models were built based on the measured retention time and on eight simple physicochemical parameters calculated from the structures. First, an original approach using several partial least square (PLS) regressions according to the phytochemical classes provided satisfactory results with an easy calculation. Secondly, a unique artificial neural network (ANN) model provided similar results on the whole set of NPs but required dedicated software. The retention prediction methods described in this study were found to improve the level of confidence of the identification of given analytes among putative isomeric structures. Its applicability was verified for the dereplication of NPs in model plant extracts.

Metabolite induction via microorganism co-culture: a potential way to enhance chemical diversity for drug discovery

Microorganisms have a long track record as important sources of novel bioactive natural products, particularly in the field of drug discovery. While microbes have been shown to biosynthesize a wide array of molecules, recent advances in genome sequencing have revealed that such organisms have the potential to yield even more structurally diverse secondary metabolites. Thus, many microbial gene clusters may be silent under standard laboratory growth conditions. In the last ten years, several methods have been developed to aid in the activation of these cryptic biosynthetic pathways. In addition to the techniques that demand prior knowledge of the genome sequences of the studied microorganisms, several genome sequence-independent tools have been developed. One of these approaches is microorganism co-culture, involving the cultivation of two or more microorganisms in the same confined environment. Microorganism co-culture is inspired by the natural microbe communities that are omnipresent in nature. Within these communities, microbes interact through signaling or defense molecules. Such compounds, produced dynamically, are of potential interest as new leads for drug discovery. Microorganism co-culture can be achieved in either solid or liquid media and has recently been used increasingly extensively to study natural interactions and discover new bioactive metabolites. Because of the complexity of microbial extracts, advanced analytical methods (e.g., mass spectrometry methods and metabolomics) are key for the successful detection and identification of co-culture-induced metabolites. This review focuses on co-culture studies that aim to increase the diversity of metabolites obtained from microbes. The various strategies are summarized with a special emphasis on the multiple methods of performing co-culture experiments. The analytical approaches for studying these interaction phenomena are discussed, and the chemical diversity and biological activity observed among the induced metabolites are described.

On-line comprehensive two dimensional separations of charged compounds using reversed-phase high performance liquid chromatography and hydrophilic interaction chromatography. Part II: application to the separation of peptides

In this second paper of a two-part series, on-line RPLC×HILIC is compared to on-line RPLC×RPLC through the separation of peptides. Our choices regarding the conditions are discussed. Injection effects and overloading effects are evaluated in both configurations. It is shown that whereas large volumes can be injected in the second dimension in RPLC×RPLC under HT-UHPLC conditions (>20% of the column dead volume), even small injection volumes (8% of the column the dead volume) have a detrimental effect on peak shapes in RPLC×HILIC. Advantages and limits of the two 2D-systems are compared through the 2D-separation of a tryptic digest of three proteins. A ten-fold gain in analysis time along with a significant gain in peak capacity are obtained with both systems compared to the most efficient one-dimensional separation of peptides recently published.

Detection of metabolite induction in fungal co-cultures on solid media by high-throughput differential ultra-high pressure liquid chromatography-time-of-flight mass spectrometry fingerprinting

Access to new biological sources is a key element of natural product research. A particularly large number of biologically active molecules have been found to originate from microorganisms. Very recently, the use of fungal co-culture to activate the silent genes involved in metabolite biosynthesis was found to be a successful method for the induction of new compounds. However, the detection and identification of the induced metabolites in the confrontation zone where fungi interact remain very challenging. To tackle this issue, a high-throughput UHPLC-TOF-MS-based metabolomic approach has been developed for the screening of fungal co-cultures in solid media at the petri dish level. The metabolites that were overexpressed because of fungal interactions were highlighted by comparing the LC-MS data obtained from the co-cultures and their corresponding mono-cultures. This comparison was achieved by subjecting automatically generated peak lists to statistical treatments. This strategy has been applied to more than 600 co-culture experiments that mainly involved fungal strains from the Fusarium genera, although experiments were also completed with a selection of several other filamentous fungi. This strategy was found to provide satisfactory repeatability and was used to detect the biomarkers of fungal induction in a large panel of filamentous fungi. This study demonstrates that co-culture results in consistent induction of potentially new metabolites.