Dynamic Cluster Analysis: An Unbiased Method for Identifying A + 2 Element Containing Compounds in Liquid Chromatographic High-Resolution Time-of-Flight Mass Spectrometric Data

ChloroDBPFinder: Machine Learning-Guided Recognition of Chlorinated Disinfection Byproducts from Nontargeted LC-HRMS Analysis

High-resolution mass spectrometry (HRMS) is a prominent analytical tool that characterizes chlorinated disinfection byproducts (Cl-DBPs) in an unbiased manner. Due to the diversity of chemicals, complex background signals, and the inherent analytical fluctuations of HRMS, conventional isotopic pattern (37Cl/35Cl), mass defect, and direct molecular formula (MF) prediction are insufficient for accurate recognition of the diverse Cl-DBPs in real environmental samples. This work proposes a novel strategy to recognize Cl-containing chemicals based on machine learning. Our hierarchical machine learning framework has two random forest-based models: the first layer is a binary classifier to recognize Cl-containing chemicals, and the second layer is a multiclass classifier to annotate the number of Cl present. This model was trained using ∼1.4 million distinctive MFs from PubChem. Evaluated on over 14,000 unique MFs from NIST20, this machine learning model achieved 93.3% accuracy in recognizing Cl-containing MFs (Cl-MFs) and 92.9% accuracy in annotating the number of Cl for Cl-MFs. Furthermore, the trained model was integrated into ChloroDBPFinder, a standalone R package for the streamlined processing of LC-HRMS data and annotating both known and unknown Cl-containing compounds. Tested on existing Cl-DBP data sets related to aspartame chlorination in tap water, our ChloroDBPFinder efficiently extracted 159 Cl-containing DBP features and tentatively annotated the structures of 10 Cl-DBPs via molecular networking. In another application of a chlorinated humic substance, ChloroDBPFinder extracted 79 high-quality Cl-DBPs and tentatively annotated six compounds. In summary, our proposed machine learning strategy and the developed ChloroDBPFinder provide an advanced solution to identifying Cl-containing compounds in nontargeted analysis of water samples. It is freely available on GitHub (https://github.com/HuanLab/ChloroDBPFinder).

Nontarget Insights into the Fate of Cl-/Br-Containing DOM in Leachate during Membrane Treatment

Halogenated organic compounds in wastewater are persistent and bioaccumulative contaminants of great concern, but few are known at the molecular level. Herein, we focus on nontarget screening of halogenated dissolved organic matter (DOM) in highly concentrated organic matrices of waste leachates and their concentrates. Solid-phase extraction (SPE) was optimized before capturing halogenated signatures via HaloSeeker 2.0 software on mining full-scan high-resolution mass spectrometry (HRMS) fingerprints. This study identified 438 Cl-/Br-containing DOM formulas in 21 leachates and membrane concentrates. Among them, 334 formulas were achieved via SPE with mixed-sorbent cartridges (mixed-SPE), surpassing the 164 formulas achieved through Bond Elut PPL cartridges (PPL-SPE). Herein, only four samples identified via PPL-SPE exhibited a resolution of >50% for extracted Cl-/Br-containing DOM by either SPE. The halogenated DOM constituted 6.87% of the total DOM mass features. Nevertheless, more abundant adsorbable organic halogens deciphered waste leachates and highly concentrated waste streams as reservoirs for halogenated contaminants. Remarkably, 75.7-98.1% of Cl-/Br-containing DOM in primary membrane concentrates remained stable through the secondary membrane treatment, indicating the persistence of these unknown contaminants even post-treatment.

Discovering New Natural Products Using Metabolomics-Based Approaches

The incessant search for new natural molecules with biological activities has forced researchers in the field of chemistry of natural products to seek different approaches for their prospection studies. In particular, researchers around the world are turning to approaches in metabolomics to avoid high rates of re-isolation of certain compounds, something recurrent in this branch of science. Thanks to the development of new technologies in the analytical instrumentation of spectroscopic and spectrometric techniques, as well as the advance in the computational processing modes of the results, metabolomics has been gaining more and more space in studies that involve the prospection of natural products. Thus, this chapter summarizes the precepts and good practices in the metabolomics of microbial natural products using mass spectrometry and nuclear magnetic resonance spectroscopy, and also summarizes several examples where this approach has been applied in the discovery of bioactive molecules.

Absolute quantitative analysis of intact and oxidized amino acids by LC-MS without prior derivatization

The precise characterization and quantification of oxidative protein damage is a significant challenge due to the low abundance, large variety, and heterogeneity of modifications. Mass spectrometry (MS)-based techniques at the peptide level (proteomics) provide a detailed but limited picture due to incomplete sequence coverage and imperfect enzymatic digestion. This is particularly problematic with oxidatively modified and cross-linked/aggregated proteins. There is a pressing need for methods that can quantify large numbers of modified amino acids, which are often present in low abundance compared to the high background of non-damaged amino acids, in a rapid and reliable fashion. We have developed a protocol using zwitterionic ion-exchange chromatography coupled with LC-MS to simultaneously quantify both parent amino acids and their respective oxidation products. Proteins are hydrolyzed with methanesulfonic acid in the presence of tryptamine and purified by strong cation exchange solid phase extraction. The method was validated for the common amino acids (excluding Gln, Asn, Cys) and the oxidation products 3-chlorotyrosine (3-ClTyr), 3-nitrotyrosine (3-NO₂Tyr), di-tyrosine, N^ε-(1-carboxymethyl)-l-lysine, o,o’-di-tyrosine, 3,4,-dihydroxyphenylalanine, hydroxy-tryptophan and kynurenine. Linear standard curves were observed over ~3 orders of magnitude dynamic range (2–1000 pmol for parent amino acids, 80 fmol–20 pmol for oxidation products) with limit-of-quantification values as low as 200 fmol (o,o’-di-tyrosine). The validated method was used to quantify Tyr and Trp loss, and formation of 3-NO₂Tyr on the isolated protein anastellin treated with peroxynitrous acid, and for 3-ClTyr formation (over a 2 orders of magnitude range) in cell lysates and complex protein mixtures treated with hypochlorous acid.

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Identification and quantification of oxidative protein damage is a major challenge.

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A versatile LC-MS assay is reported that involves hydrolysis to free amino acids.

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Quantification is possible for both parent amino acids and products in single runs.

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A dynamic range of 2-3 orders of magnitude is available for most analytes.

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Example of use with pure proteins, extracellular matrix and cell lysates are given.

Automated Isotopic Profile Deconvolution for High Resolution Mass Spectrometric Data (APGC-QToF) from Biological Matrices

An isotopic profile matching algorithm, the isotopic profile deconvoluted chromatogram (IPDC), was developed to screen for a wide variety of organic compounds in high-resolution mass spectrometry (HRMS) data acquired from instruments with resolution power as low as 22 000 fwhm. The algorithm initiates the screening process by generating a series of C/Br/Cl/S isotopic patterns consistent with the profiles of approximately 3 million molecular formulas for compounds with potentially persistent, bioaccumulative, and toxic (PBT) properties. To evaluate this algorithm, HRMS data were screened using these seed profiles to isolate relevant chlorinated and/or brominated compounds. Data reduction techniques included mass defect filtering and retention time prediction from estimated boiling points predicted using molecular formulas and reasonable elemental conformations. A machine learning classifier was also developed using spectrometric and chromatographic variables to minimize false positives. A scoring system was developed to rank candidate molecular formulas for an isotopic feature. The IPDC algorithm was applied to a Lake Michigan lake trout extract analyzed by atmospheric pressure gas chromatography-quadrupole time-of-flight (APGC-QToF) mass spectrometry in positive and negative modes. The IPDC algorithm detected isotopic features associated with legacy contaminants and a series of unknown halogenated features. The IPDC algorithm resolved 313 and 855 halogenated features in positive and negative modes, respectively, in Lake Michigan lake trout.

Identification of N,N',N″-triacetylfusarinine C as a key metabolite for root rot disease virulence in American ginseng

Background

It is estimated that 20–30% of ginseng crops in Canada are lost to root rot each harvest. This disease is commonly caused by fungal infection with Ilyonectria, previously known as Cylindrocarpon. Previous reports have linked the virulence of fungal disease to the production of siderophores, a class of small-molecule iron chelators. However, these siderophores have not been identified in Ilyonectria.

Methods

High-resolution LC–MS/MS was used to screen Ilyonectria and Cylindrocarpon strain extracts for secondary metabolite production. These strains were also tested for their ability to cause root rot in American ginseng and categorized as virulent or avirulent. The differences in detected metabolites between the virulent and avirulent strains were compared with a focus on siderophores.

Results

For the first time, a siderophore N,N′,N″-triacetylfusarinine C (TAFC) has been identified in Ilyonectria, and it appears to be linked to disease virulence. Siderophore production was suppressed as the concentration of iron increased, which is in agreement with previous reports.

Conclusion

The identification of the siderophore produced by Ilyonectria gives us further insight into the root rot disease that heavily affects ginseng crop yields. This research identifies a molecular pathway previously unknown for ginseng root rot and could lead to new disease treatment options.

Development of an Indirect Quantitation Method to Assess Ichthyotoxic B-Type Prymnesins from Prymnesium parvum

Harmful algal blooms of Prymnesium parvum have recurrently been associated with the killing of fish. The causative ichthyotoxic agents of this haptophyte are believed to be prymnesins, a group of supersized ladder-frame polyether compounds currently divided into three types. Here, the development of a quantitative method to assess the molar sum of prymnesins in water samples and in algal biomass is reported. The method is based on the derivatization of the primary amine group and subsequent fluorescence detection using external calibrants. The presence of prymnesins in the underivatized sample should be confirmed by liquid chromatography mass spectrometry. The method is currently only partly applicable to water samples due to the low amounts that are present. The growth and cellular toxin content of two B-type producing strains were monitored in batch cultures eventually limited by an elevated pH. The cellular toxin contents varied by a factor of ~2.5 throughout the growth cycle, with the highest amounts found in the exponential growth phase and the lowest in the stationary growth/death phases. The strain K-0081 contained ~5 times more toxin than K-0374. Further investigations showed that the majority of prymnesins were associated with the biomass (89% ± 7%). This study provides the basis for further investigations into the toxicity and production of prymnesins.

HaloSeeker 1.0: A User-Friendly Software to Highlight Halogenated Chemicals in Nontargeted High-Resolution Mass Spectrometry Data Sets

In the present work, we address the issue of nontargeted screening of organohalogenated chemicals in complex matrixes. A global strategy aiming to seek halogenated signatures in full-scan high-resolution mass spectrometry (HRMS) fingerprints was developed. The resulting all-in-one user-friendly application, HaloSeeker 1.0, was developed to promote the accessibility of associated in-house bioinformatics tools to a large audience. The ergonomic web user interface avoids any interactions with the coding component while allowing interactions with the data, including peak detection (features), deconvolution, and comprehensive accompanying manual review for chemical formula assignment. HaloSeeker 1.0 was successfully applied to a marine sediment HRMS data set acquired on a liquid chromatography-heated electrospray ionization [LC-HESI(-)] Orbitrap instrument ( R = 140 000 at m/z 200). Among the 4532 detected features, 827 were paired and filtered in 165 polyhalogenated clusters. HaloSeeker was also compared to three similar tools and showed the best performances. HaloSeeker's ability to filter and investigate halogenated signals was demonstrated and illustrated by a potential homologue series with C₁₂H _xBr _yCl _zO₂ as a putative general formula.

Tremorgenic and neurotoxic paspaline-derived indole-diterpenes: biosynthetic diversity, threats and applications

Indole-diterpenes (IDTs) such as the aflatrems, janthitrems, lolitrems, paspalitrems, penitrems, shearinines, sulpinines, and terpendoles are biogenetically related but structurally varied tremorgenic and neurotoxic mycotoxins produced by fungi. All these metabolites derive from the biosynthetic intermediate paspaline, a frequently occurring IDT on its own right. In this comprehensive review, we highlight the similarities and differences of the IDT biosynthetic pathways that lead to the generation of the main paspaline-derived IDT subgroups. We survey the taxonomic distribution and the regulation of IDT production in various fungi and compare the organization of the known IDT biosynthetic gene clusters. A detailed assessment of the highly diverse biological activities of these mycotoxins leads us to emphasize the significant losses that paspaline-derived IDTs cause in agriculture, and compels us to warn about the various hazards they represent towards human and livestock health. Conversely, we also describe the potential utility of these versatile molecules as lead compounds for pharmaceutical drug discovery, and examine the prospects for their industrial scale manufacture in genetically manipulated IDT producers or domesticated host microorganisms in synthetic biological production systems.

A-, B- and C-type prymnesins are clade specific compounds and chemotaxonomic markers in Prymnesium parvum

Harmful blooms formed by planktonic microalgae (HABs) in both freshwater and coastal waters regularly lead to severe mortalities of fish and invertebrates causing substantial economic losses of marine products worldwide. The mixotrophic haptophyte Prymnesium parvum is one of the most important microalgae associated with fish kills. Here 26 strains of P. parvum with a wide geographical distribution were screened for the production of prymnesins, the suspected causative allelochemical toxins. All investigated strains produced prymnesins, indicating that the toxins play an important role for the organism. The prymnesins can be classified into three types based on the length of the carbon backbone of the compound and each algal strain produced only one of these types. Biogeographical mapping of the prymnesin distribution indicated a global distribution of each type. In addition, phylogenetic analyses based on internal transcribed spacer (ITS) sequences revealed monophyletic origin of all prymnesin types and clades could therefore be defined based on the toxic compound. It might be that evolution of new species within the P. parvum species complex is driven by changes in toxin type or that they are a result of it. Such a correlation between chemotype and phylotype has never been documented before for a harmful microalga. Chemotaxonomy and ITS-type classification may thus be used to further delimit the P. parvum species complex.

A Dereplication and Bioguided Discovery Approach to Reveal New Compounds from a Marine-Derived Fungus Stilbella fimetaria

A marine-derived Stilbella fimetaria fungal strain was screened for new bioactive compounds based on two different approaches: (i) bio-guided approach using cytotoxicity and antimicrobial bioassays; and (ii) dereplication based approach using liquid chromatography with both diode array detection and high resolution mass spectrometry. This led to the discovery of several bioactive compound families with different biosynthetic origins, including pimarane-type diterpenoids and hybrid polyketide-non ribosomal peptide derived compounds. Prefractionation before bioassay screening proved to be a great aid in the dereplication process, since separate fractions displaying different bioactivities allowed a quick tentative identification of known antimicrobial compounds and of potential new analogues. A new pimarane-type diterpene, myrocin F, was discovered in trace amounts and displayed cytotoxicity towards various cancer cell lines. Further media optimization led to increased production followed by the purification and bioactivity screening of several new and known pimarane-type diterpenoids. A known broad-spectrum antifungal compound, ilicicolin H, was purified along with two new analogues, hydroxyl-ilicicolin H and ilicicolin I, and their antifungal activity was evaluated.